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## Technical Support Document (TSD) for the final Transport Rule Docket ID No. EPA - HQ - OAR - 200 9 - 0491



## Emissions Inventory TSD

U.S. Environmental Protection Agency Office of Air and Radiation June 201 1ii Deliberative

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## TA BLE OF CONTENTS ACRONYMS ................................ ................................ ................................ ................................ ............................... V LIST OF TABLES ................................ ................................ ................................ ................................ ................... VII LIST OF FIGURES ................................ ................................ ................................ ................................ ............... VIII LIST OF APPENDICES ................................ ................................ ................................ ................................ .......... IX 1 INTRODUCTION ................................ ................................ ................................ ................................ .............. 1 2 2005 EMISSION INVENT ORIES AND APPROACHES ................................ ................................ .............. 4 2.1 2005 NEI POINT SOURCES ( PTIPM AND PTNONIPM ) ................................ ................................ ......................... 10 2.1.1 IPM sector (ptipm) ................................ ................................ ................................ ............................... 11 2.1.2 Non -IPM sector (ptnonipm) ................................ ................................ ................................ ................. 13 2.2 2005 NONPOI

NT SOURCES (AFDUST , AG , NONPT) ................................ ................................ ............................ 15 2.2.1 Area fugitive dust sector (afdust) ................................ ................................ ................................ ......... 15 2.2.2 Agricultural ammonia sector (ag) ................................ ................................ ................................ ....... 16 2.2.3 Other nonpoint sources (nonpt) ................................ ................................ ................................ ........... 19 2.3 F IRES (AVEFIRE ) ................................ ................................ ................................ ................................ ............. 21 2.4 B IO GENIC SOURCES (BIOG) ................................ ................................ ................................ ............................. 22 2.5 2005 MOBILE SOURCES ( ON

_ NOADJ , ON

_MOVES

_RUNPM , ON

_MOVES

_ STARTPM , NONROAD , ALM

_ NO

_C 3, SECA

_C 3) ................................ ................................ ................................ ................................ ................................ . 22 2.5.1 Onroad gasoline exhaust cold -start mode PM (on_moves_startpm) ................................ ................... 25 2.5.2 Onroad gasoline exhaust running mode PM (on_moves_runpm) ................................ ........................ 27 2.5.3 Onroad mobile with no adjustments for daily temperature (on_noadj) ................................ ............... 28 2.5.4 Nonroad mobile sources: NMIM - based (nonroad) ................................ ................................ ............. 29 2.5.5 Nonroad mobile sources: locomotive and non - C3 commercial marine (alm_no_c3) ........................ 30 2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3) ................................ .............................. 32 2.6 E MI SSIONS FROM C ANADA , M EXICO AND OFFSHORE D RILLIN G PLATFORMS ( OTHPT , OTHAR , OTHON) .......... 35 2.7 SMOKE - READY NON - ANTHROPOGENIC INVENT ORIES FOR CHLORINE ................................ ........................... 37 3 EM ISSIONS MODELING S UMMARY ................................ ................................ ................................ ........ 38 3.1 KEY EMI SSIONS MODELIN G SETTINGS ................................ ................................ ................................ ............. 39 3.1.1 Spatial configuration ................................ ................................ ................................ ........................... 40 3.1.2 Chemical speciation configuration ................................ ................................ ................................ ...... 42 3.1.3 Temporal processing configuration ................................ ................................ ................................ ..... 50 3.2 E MI SSIONS MODELING AN CILLARY 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 ................................ ............................ 70 4.1 S TATIONARY SOURCE PRO JECTIONS : EGU SECTOR ( PTIPM ) ................................ ................................ .......... 76 4.2 S TATIONARY SOURCE PRO JECTIONS : NON - EGU SECTORS ( PTNONIPM , NONPT , AG , AFDUST) ......................... 77 4.2.1 Livestock emissions growth (ag, afdust) ................................ ................................ .............................. 77 4.2.2 Residential wood combustion growth (nonpt) ................................ ................................ ...................... 78 4.2.3 Gasoline Stage II growth and control (nonpt, ptnonipm) ................................ ................................ .... 79 4.2.4 Portable fuel container growth and control (nonpt) ................................ ................................ ............ 80 4.2.5 Aircraft growth (ptnonipm) ................................ ................................ ................................ .................. 81 4.2.6 Stationary source control programs, consent decrees & settlements, and plant closures (ptnonipm, nonpt) 82 4.2.7 Oil and gas projections in TX, OK, and non - California WRAP states (nonpt) ................................ .... 87 4.2.8 Future -

year VOC Speciation for gasoline - related sources (ptn onipm, nonpt) ................................ .... 88 4.3 M OBILE SOURCE PROJECT IONS ................................ ................................ ................................ ....................... 89 4. 3.1 Onroad mobile (on_noadj, on_moves_runpm, on_moves_startpm) ................................ .................... 89 4.3.2 Nonroad mobile (nonroad) ................................ ................................ ................................ .................. 91iv Deliberative

– Do Not Cite or Quote 4.3.3 Locomotives and Class 1 &2 commercial marine vessels (alm_no_c3) ................................ ............. 92 4.3.4 Class 3 commercial marine vessels (seca_c3) ................................ ................................ ..................... 93 4.3.5 Future -

year VOC Speciation (on_n oadj, nonroad) ................................ ................................ ............. 94 4.4 C ANADA , M EXICO , AND O FFSHORE SOURCES ( OTHAR , OTHON , AND OTHPT) ................................ ................. 95 5 SOURCE APPORTIONMENT ................................ ................................ ................................ ...................... 96 6 REMEDY CASE ................................ ................................ ................................ ................................ .............. 96 7 EM ISSION SUMMARIES ................................ ................................ ................................ ............................ 101 8 REFERENCES ................................ ................................ ................................ ................................ ............... 114v Deliberative

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## Ac rony ms 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 Cl Chlorine CMAQ Community Multiscale Air Quality CMV Commercial marine vessel CO Carbon monoxide EGU Electric generating units EPA Environmental Protection Agency EMFAC Emission Factor (California ’s on road mobile model) EEZ Exclusive Economic Zone FAA Federal Aviation Administration FCCS Fuel Characteristic Classification System FIPS Federal Information Processing Standards HAP Hazardous Air Pollutant HC l Hydrochloric acid H g Mercury HGNRVA Natural recycled, volcanic and anthropogenic Hg HMS Hazard Mapping System 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 OT AQ’s model for estimation of on road mobile emissions factors MOVES Motor Vehicle Emissions Simulator -- OTAQ’s model for estimation of onroad mobile

emissions

– replaces the use of the MOBILE model MSAT2 Mobile Source Air Toxics Rule NEEDS National Electric Energy Database System NEI National Emission Inventory NESHAP National Emission Standards for Hazardous Air Pollutants NH 3 Ammonia nm nautical mile NMIM National Mobile Inventory Model NOAA National Oceanic and Atmospheric Administration NODA Notice of Data Availability NONROAD OTAQ’s model for estimation of nonroad mobile emissions NO X Nitrogen oxides OAQPS The EPA’s Office of Air Quality Planning and Standardsvi Deliberative

– Do Not Cite or Quote 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 PM 2.5 Particulate matter less than or equal to 2.5 microns PM 10 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 SO 2 Sulfur dioxide SOA Secondary Organic Aerosol SPPD Sector Policies and Programs Division TAF Terminal Area Forecast TCEQ Texas Commission on Environmental Quality TSD Technical support document VOC Volatile organic compounds VMT Vehicle miles traveled WRAP Western Regional Air Partnershipvii Deliberative

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## List of T ables Table 1 - 1. List of cases run in support of the 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 signifi cant changes between v4 and v4.2 platforms by sector ................ 7 Table 2 - 3. 2005 Emissions by Sector: VOC, NO X , CO, SO 2 , NH 3 , PM 10 , PM 2.5 ........................ 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 platforms 1

... 23 Table 2 - 11. SCC s in the 2005 alm_no_c3 inventory compared to the 2002 platform alm sector 31 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 ... 36 Table 3 - 1. Key

emissions modeling steps b y sector. ................................ ................................ ... 39 Table 3 - 2. Descriptions of the 2005 -based platform grids ................................ .......................... 42 Table 3 - 3. Model species produced by SMOKE for CB05 with SOA for CMAQ4.7 and CAM X *

................................ ................................ ................................ ................................ ............... 43 Table 3 - 4. Integration status of benzene, acetaldehyde, formaldehyd e and methanol (BAFM) for each platform sector ................................ ................................ ................................ .............. 47 Table 3 - 5. Source - category specific criteria for integrating nonpt SCCs for categories comprising 8 0% 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 ................. 55 Table 3 - 9. Canadian Spatial Surrogates for 2005 - based platform Canadian Emissions (v4.2 unchanged from v4) ................................ ................................ ................................ .............. 56 Table 3 - 10. Differences between two profiles used for commercial marine residual oil ............ 59 Table 3 - 11. Differences between two profi les used for coal combustion ................................ .... 60 Table 3 - 12: PM 2.5 speciation profile updates assignments for the v4 platform ............................ 60 Table 3 - 13. Summary

of VOC speciation profile approach by sector for 2005 ........................... 61 Table 3 - 14. Summary

of spatial surrogates, temporal profiles, and speciation profiles used by gasoline vehicle types for the onroad parking area - related SCCs. ................................ ....... 65 Table 3 - 15. Summary

of spatial surrogates, temporal profiles, and speciation profiles used by diesel vehicle types for the onroad parking area- related SCCs fro m MOVES2010. ............ 67 Table 4 - 1. Control strategies and growth assumptions for creating the 2012 and 2014 base - case emissions inventories from the 2005 base case ................................ ................................ .... 73 Table 4 - 2. Growth factors from year 2005 to future years for Animal Operations ..................... 78 Table 4 - 3. Projection Factors for growing ye ar 2005 Residential Wood Combustion Sources .. 79 Table 4 - 4. Factors used to project 2005 base - case aircraft emissions to future years ................. 81 Table 4 - 5. Summary

of Non - EGU Emission Reductions Applied to the 2005 Inventory due to Unit and Plant Closures ................................ ................................ ................................ ........ 83viii Deliberative

– Do Not Cite or Quote Table 4 - 6. Future - ye ar ISI S -based cement industry annual reductions (tons/y r) for the non - EGU (ptnonipm) sector ................................ ................................ ................................ .................. 85 Table 4 - 7. State - level non - MACT Boiler Reductions from ICR Data Gathering ....................... 86 Table 4 - 8. National Impact of RICE Controls on 2012 and 2014 Non - EGU Projections ........... 87 Table 4 - 9. Impact of Fuel Sulfur Controls on 2014 Non - EGU Projections ................................ 87 Table 4 - 10. Oil and Gas NO X and SO 2 Emissions for 2005, 2012, and 2014 including additional reductions due to the RICE NESHAP ................................ ................................ .................. 88 Table 4 - 11 . Factors applied to year 2005 emissions to project locomotives and Class 1 and Class 2 Commercial Marine Vessel Emissions ................................ ................................ .............. 92 Table 4 - 12. NO X , SO 2 , and PM 2.5 Factors to Project Class 3 Commercial Marine Vessel emissions to 2012 and 2014 ................................ ................................ ................................ .. 94 Table 4 - 13. Future - ye ar Profiles for Mobile Source Related Sources ................................ ......... 95 Table 6 - 1. Transport Rule Status of States ................................ ................................ .................. 99 Table 7 - 1. State - level Total NO X Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C. ................................ ................................ ................................ ......... 102 Table 7 - 2. State - level Total SO 2 Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C. ................................ ................................ ................................ ......... 104 Table 7 - 3. State - level Electric Generating Unit Sector NO X Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C. ................................ ............................ 106 Table 7 - 4. State - level Electric Generating Unit Sector SO 2 Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C. ................................ ............................ 108 Table 7 - 5. Group 1 and Group 2 States NO X Total Emissions for each TR1 Modeling Case .. 110 Table 7 - 6. Group 1 and Group 2 States SO 2 Total Emissions for each TR1 Modeling Case .... 111 Table 7 - 7. Group 1 and Group 2 States NO X EGU Sector Emissions for each TR1 Modeling Case ................................ ................................ ................................ ................................ ..... 112 Table 7 - 8. Group 1 and Group 2 States SO 2 EGU Sector Emissions for each TR1 Modeling Case

................................ ................................ ................................ ................................ ............. 113 Table 7 - 9. 26 - State Total and Electric Generating Unit Sector Summer NO X Emissions for each TR1 Modeling Case ................................ ................................ ................................ ............ 113



## List of Figures Figure 2 - 1. MOVES exhaust temperature adjustment functions. ................................ ................ 26 Figure 3 - 1. Air quality

modeling domains ................................ ................................ .................... 41 Figure 3 - 2. Process of integrating BAFM with VOC for use in VOC Speciation ....................... 4 6 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 ...................... 64 Figure 4 - 1. MOVES exhaust temperature adjustment functions for 2005, 2012, and 2014 ........ 90 Figure 4 - 2. Tier 2 Fraction of Light Duty Vehicles ................................ ................................ ..... 95 Figure 6 - 1. States Covered by the Final Transport Rule ................................ ............................. 97 Figure 6 - 2. Group 1 and Group 2 States Covered by the Annual PM Component of the Final Transport Rule ................................ ................................ ................................ ...................... 99ix Deliberative

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## List of Ap pendic es Appendix A: Revisions to 2005 Inventories from Version 4 to Version 4.2 Appendix B: Ancillary

Input Data Differences between 2005 and Future - ye ar Scenarios Appendix C : SMOKE Input Inventory Data Files u sed for each TR1 Modeling Case Appendix D : Summary

of Future Base Case Transport Rule Non - EGU Control Programs, Closures and Projections1 

## 1 Introduction This technical support document (TSD) provides the details of emissions data processing done in support of the Environmental Protection Agency ’s (EPA) f inal r ulemaking effort for the Federal Transport Rule (hereafter referred to as Transport Rule). The Transport R ule 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 les s than 2.5 microns (PM 2.5 ), as well as the 1997 8 - hour ozone NAAQS. The emissions and modeling effort for Transport R ule consists of four ‘complete’ emissions cases : 2005 base case, 2012 base case, 2014 base case, and 2014 remedy ( i.e., “ c ontrol ”) 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 - ye ar 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 2 014 remedy case w ere 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 PM 2.5 and 8 - hour ozone c oncentrations 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 . Li st of cases run in support of the Transport Rule air quality modeling Case Name Internal EPA

Abbreviation Description 2005 base case 2005c s 2005 case created using average - ye ar fires data and an average ye ar temporal allocation approach for Electrical Generating Units (EGUs) ; use d for computing relative response factors with 2012 and 2014 scenarios 2012 base case 2012cs 2012 “baseline” scenario, representing the best estimate for the future ye ar without implementation of EGU remedy controls. 2014 base case 2014cs 2014 “baseline” scenario, representing the best estimate for the future ye ar without implementation of EGU remedy controls. 2014 Remedy case 2014cs_tr1remedy 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 (HCl ) 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). 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 p latform used for the Final Transport2 Rule , and focuses on the changes made since the 2005v4 platform . The 2 005v4 platform is documented at the emissions modeling clearinghouse website, http://www.epa.gov/ttn/chief/emch/ , under the section entitled “2005 - Based Modeling Platform” and the subsection entitled “CAP - 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 include s 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 receiv ed 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 mo deling clearinghouse website listed above. For simplicity, this TSD refers to the cumulative changes in both the 2005 v4.1 and 2005 v4.2 platforms, thus any comparisons made in this document will be against data in the 2005 v4 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 docke t and on the emissions modeling clearinghouse website specified above . The underl ying 2005 inventories used are most significantly defined by : 1) f

or 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) (http://www.epa.gov/otaq/models/moves/index.htm) . This document describes th e approach and data used to produce the emission inputs to the air quality model used in the 2005 v4. 2 platform for the 2005 and future ye ar scenarios. Emissions preparation for the 2005 v4. 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 (O 3 ), and particulate matter (PM) , and require hourl y and gridded emissions of chemical species from the following inventory pollutants: carbon monoxide (CO), nitrogen oxides (NO X), volatile organic compounds (VOC), sulfur dioxide (SO 2 ), ammonia (NH 3 ), particulate matter less than or equal to 10 microns (PM 10 ), and individual component species for particulate matter less than or equal to 2.5 microns (PM 2.5 ). Inaddition, the CMAQ Carbon Bond 05 ( CB05 ) chemical mechanism with chlorine chemistry, which is part of the “base” version of CMAQ, allows explicit treatment of BAFM and includes HAP emissions of HCl and C L2 . Inthe 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, onl y the CAMX model was used. The creation of emission inputs for the 2005v4. 2 platform included : ( 1 ) modif ying the emission inventories used for the 2005 v4 base case , (2 ) updating the emissions modeling ancillary files used by the emissions modeling tools, and ( 3 ) appl ying 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 s ys tem (http://www.smoke - model.org/index.cf m) . 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 “2005c s_05b” case).3 Unlike the version 4 platform (2005v4) , th e 2005v4.2 platform includes only a base case for 2005 and does not include a traditional model evaluation case. That is, the evaluation case in the 2005 v4 platform uses 2005 - specific fire emissions and 2005 hour- specific continuous emission monitoring (CEM) data for electric generating units (EGUs) whereas the 2005 base case in 2005v4.2 includes an “average ye ar” scenario for fires and a illustrative (rather than year- specific) temporal allocation approach for EGUs to allocate annual 2005 emissions to days and hours . This approach to temporal allocation 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 ye ar. 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 ye ar 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 - ye ar cases. The 2005v4.2 platform was developed using the concepts, tools and emissions modeling data from the EPA ’s 2005v4 platform , documented by : ftp://ftp.epa.gov/EmisInventory /2005v4/2005_emissions_tsd_07jul2010.pdf (main document) , ftp://ftp.epa.gov/EmisInventory /2005v4/2005_emissions_tsd_appendices_11may2010.pdf (appendices to the main document), and http://www.epa.gov/ttn/chief/emch/transport/tr_proposal_emissions_tsd.pdf (future ye ar). 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 Transpor t 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 website (http://www.epa.gov/ttn/chief/emch/index.html#2005 ). 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 201 2 (2012cs_05b) and 2014 (2014cs_05b) base case s. The 2012 Source Tagging scenarios are described in Section 5. The 2014 EGU Transport Rule Remedy (Control) case (2014cs_tr1remedy_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 3.4 

## 2 2005 E mission I nventories and A pproaches 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 (NE I), version 2, which includes emissions of CO, NO X , VOC, SO 2 , NH 3 , PM 10 , PM2.5 and hazardous air pollutants (HAPs). The HAPs we used from this inventory are mercury, chlorine (CL2), hydrogen chloride (HCl ) , benzene, acetaldehyde, formaldehyde, and methanol. We began with the same SMOKE - formatted inventory inputs as the 2005v4 platform (the EPA case name: 2005ck_05b) and made the changes described below . Documentation for the 2005 NEI can be found at: http://www.epa.gov/ttn/chief/net/2005inventory .html#documentation . For inventories outside of the United States, which include Canada and Mexico, we used the latest available base - ye ar inventories as discussed in Section 2.6 . The 2005 NEIincludes five sectors: nonpoint ( formerl y 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 NEIdata, 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 th e data is run through all of the SMOKE programs except the final merge (Mrggrid) independentl y from the other sectors. The final merge program then combines the sector- specific gridded, speciated and hourl y emissions together to create CMAQ - ready emission inputs . These inputs are then converted into emissions that can be used b y 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 u pdates to the 2005v4.2 platform as compared to th e 200 5 v4 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 , v ersion 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 evoluti onary 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 2005v4.5

Platform Sector : short name 2005 NEI

Sector Description and resolution of the data input to SMOKE Average- fire: avefire Not

applicable Average -year wildfire and prescribed fire emissions , unchanged from

the 2005v4 platform ; county and annual resolution. Agricultural: ag Nonpoint NH 3 emissions from NEI nonpoint livestock and fertilizer application, county and annual resolution. Unchanged from the 2005v4 platform. Area fugitive dust : afdust Nonpoint PM 10 and PM 2.5 from fugitive dust sources from the NEI nonpoint inventory after application of county- specific PM transportable fractions. Includes building construction, road construction, paved roads, unpaved roads, agricultural dust), county and annual resolution. 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 nonCalifornia WRAP oil and gas Phase II inventory , year 2005 Texas and O klahoma 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 th e 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 20 05v2 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 (http://www.epa.gov/otaq/oceanvessels.htm). Util ized 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: on_noadj Mobile:

onroad Three, monthly, county- level components:

1) California onroad, created using annual emissions for all pollutants, submitted by CARB for the 2005 v2 NEI. NH 3 (not submitted by CARB) from MOVES2010. 2) Onroad gasoline and diesel vehicle emissions from MOVES2010 not subject to temperature adjustments: exhaust CO, NO X , VOC, NH3, benzene, formaldehyde, acetaldehyde, 1,3 -butadiene, acrolein, naphthalene, brake and tirewear PM, and evaporative VOC, benzene, and naphthalene . 3) Onroad emissions for Hg from NMIM using MOBILE6.2, other than for California.6

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 MOVES 2010 -based onroad gasoline emissions

subject to temperature adjustments. Limited to exhaust mode only for PM species and naphthalene. California emissions not included. This sector is limited to cold start mode emissions that contain different temperatu re adjustment curves from running exhaust (see on_moves_runpm sector). Onroad running gasoline exhaust mode vehicle from MOVES subject to temperature adjustments: on_moves_runpm Mobile:

onroad Monthly, county - level draft MOVES 2010 -based onroad gasoline

emissions subject to temperature adjustments. Limited to exhaust mode only for PM spe cies 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: ot har 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 o nroa d 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 2005 v4 . 2 web site (see the end of Section 1 ) . The “readme” file provided indicates the particular zipped files associated with each platform sector. Before discussing the specific components of the 2005 v4. 2 emissions platform, we provide in Table 2 - 2 a summary of th e significant differences between the 200 5v4 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.7

Table 2 - 2 . Summary

of s ignificant changes between v4 and v4.2 p latform s by s ector 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 NO X , SO 2 or both using 2005 CEM data . Only replaced emissions if 2005 CEM data were confirmed to be for the entire year ( since some CEM s only run for the summer season) . A facility- level summary of these changes is provided in Appendix A, Table A - 1 of the 2005v4.1 TSD: http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf . 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. These sources are listed in Appendix A, Table A - 1 . 3) Deleted several units from the inventory that were found to be either double counts or closed. These sources 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 In formation Collection Request (ICR) . 2) Moved several stacks and units from the ptnonipm sector to the ptipm sector (Appendix A, Table A - 1 ) . 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. These sources are listed in Appendix A, Table A - 2 . 4) Revised emissions in several states from improved information obtained from Transport Rule comments. These sources are summarized in Appendix A , Table A - 2 . Remaining nonpoint sector: nonpt 1) Added : year 2005 oil and gas data f or Texas and Oklahoma provided by these s tates. 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 oi l 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. Details of these comments 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: alm_no_c3 Updated diesel fuel commercial marine vessel emissions in Delaware per Transport

Rule comments. Details of these comments are shown in Appendix A, Table A - 3 .8

Platform Sector Summary of Significant Inventory Differences from V4 to V4. 2 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) Proposal to the International Maritime Organization (EPA -420 -F - 10 - 041, August 2 010) . 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 . Details of these comments are shown in Appendix A, Table A - 3 . 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 b oundaries 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: on_noadj 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 NH 3 with MOVES2010 emissions for California b ecause California does not provide NH 3 in its onroad inventory . For the 2005v4 platform, w e used NH 3 from NMIM but since MOVES generates all criteria pollutants, we now use MOVES. Onroad cold- start gasoline exhaust mode vehicle from MOVES subject to temperature adjustments: on_moves_startpm For the 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, the se 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 2005 v4.2 , 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 2 005 base case are available at the 2005v4 web site (see the end of Section 1 ) under the link “Data Files” (see the “2005emis” directory). The inventories “readme” file indicates the particular zipped files associated with each platform sector .9 Table 2 -3 . 2005 Emissions by Sector: VOC, NO X , CO, SO 2 , NH 3 , PM 10 , PM 2.5 Sector short name 2005

VOC [ tons/yr] 2005

NOX [tons/yr] 2005 CO [tons/yr] 2005

SO2 [tons/yr] 2005

NH3 [tons/yr] 2005

PM10 [tons/yr] 2005

PM2_5 [tons/yr] V4. 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 alm_no_c3 67,690 same 1,92 2 , 723 1,924,925 270,007 same 153,068 154,016 773 same 59,3 42 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 n onpt 7,530,5 78 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_noadj 3,949,362 3,123,642 9,142,274 7,203,876 43,356,130 41,647,066 177,977 144,216 156,528 295,203 308,497 170,554 236,927 115,991 on_moves _runpm 54,071 46,430 49,789 42,753 on_moves_ startpm 22,729 23,607 20,929 21,738 ptipm 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 othar 1 1,281,095 same 734,587 same 3,789,362 same 95,086 same 546,034 same 1,666,188 same 432,402 same Canada othon 270,872 same 524,837 same 4,403,745 same 5,309 same 21,312 same 14,665 same 10,395 same 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 off shore othpt 51,240 same 82,581 same 89,812 same 1,961 same 0 same 839 same 837 same 1. Canada provided 2006 fires but we did not use them in the 2005 platform (for neither v4. 2 nor v4)10 Deliberative

– Do Not Cite or Quote 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 2005 v4. 2 platform emissions changed appreciabl y since the previousl y- documented 200 5v4 platform. 

### 2.1 2005 NEI p oint sources (ptipm and ptnonipm) Point sources are sources of emissions for which specific geographic coordinates (e.g., latitude/longitude) are specifi ed, 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 NE I 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 - IP M sector ( i.e., ptnonipm). This split facilitates the use of different SMOKE temporal processing and future - ye ar projection techniques for each of these sectors. The inventory pollutants processed through SMOKE for both ptipm and ptnonipm sectors were: CO, NO X , VOC, SO 2 , NH 3 , PM 10 , and PM 2.5 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. D ocumentation for the development of the 2005 point source NEI v2, is at: http://www.epa.gov/ttn/chief/net/2005inventory .html#documentation . A summary of this documentation describes these data as follows: 1. Electric generating unit (EGU) emissions are obtained from emissions/heat input from 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 b y the CEMS, the 2005 CEMS data were used. For CEMS units with pollutants not covered b y CEMS (e.g., VOC, PM 2.5 , HCl) unit - specific ratios of 2005 to 2002 heat input were applied to 2002 v3 NEI emissions to obtain 2005 estimates.11 Deliberative

– Do Not Cite or Quote 2. Non - EGU stationary

s ource development for the 2005 NEI focused on improving the following sectors: a. HAP data received from States and industry to support the MACT program, including the recent Risk and Technology Review rulemaking b. 2005 State, local, and tribal data submitted to the EPA under the C onsolidated 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 2005 v2 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 assigne d 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.  S tack parameters were defaulted for some point sources when modeling in SMOKE. SMOKE uses an ancill ary file, called the PSTK file that provides default stack parameters b y 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 2005 v4 web site (see the end of Section 1 ) .  We applied a transport fraction to all SC Cs 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 briefl y discussed in Table 2 - 2. One of these changes involved reassigning stacks, units and facilities from the ptnonipm sector to the ptipm sector becaus e it was determined that these sources were reflected in the future - ye ar IP M data. By moving these sources from ptnonipm to ptipm, we prevent their being double counted in future - ye ar 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) Th e ptipm sector contains emissions from EGUs in the 2005v2 NEI point inventory that we were able match to the units found in the NEEDS database . While we originall y used version 3.02 of NEED S to split out the ptipm sector for v4 of the platform, there were no changes to the mapping when we moved to NEEDs version 4.10 (http://www.epa.go v/airmarkets/progsregs/epa- ipm/index.html ). The IPM model provides future - ye ar 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 sourc es and future - ye ar EGU emissions for sources which are forecasted by IPM and (2) to avoid double counting in projecting point source emissions.12 Deliberative

– Do Not Cite or Quote The 2005v4 platform document provides additional details on how the 2005 NEI point source inventory was split into the ptipm and ptnonipm sectors. Creation of temporall y 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 dail y 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 - ye ar averages of 2004 - 2006 CEM data. These average annual - to - month factors were assigned to sources b y 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 dail y- 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 . Ptipmupdates from the 2005v4 platform used in creating the 2005v4 . 2 platform

 We started with the same ptipm/ptnonipm split as wa s 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 ORI S identifiers, we recomputed annual emissions for SO 2 , NO X or both using the CEMS data available at the EPA’s data and maps website. 2 Facility- level impacts of these changes are provided in Appendix A, Table A - 1 of the 2005v4.1 TSD: http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf .  Several sources in the 2005v4 ptnonipm inventory were found to be EGU emissions that were either found in the future - ye ar IPM inventories or deter mined to have closed between 2005 and the future years. If these emissions were retained in the ptnonipm sector, then future - ye ar projections would either double - count these EGU emissions, or incorrectly

not close these units; in both cases, future - ye ar E GU emissions were inflated in the 2005v4 platform. Therefore, we reassigned these known EGU emissions to the ptipm sector. Insituations where emissions were moved from ptnonipm to ptipm and these sources were not closed in the future (they were in the f

uture - ye ar IPM inventories), facility, and unit identifier codes were changed to match IPM codes, and more importantly, ORI S 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 - 1 .  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 ca ses, 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.wizard13 Deliberative

– Do Not Cite or Quote 

### 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 mine s . 4 Prior to input to SMOKE, we reduced the fugitive dust PM emissions to estimate the emissions that remain aloft by

applyingcounty- 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 b ecause 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 ty pes 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 primaril y Kansas and Minnesota, and petroleum product w orking losses . The modifications between the published 2005v2 NEI and the 2005 v4 ptnonipm inventory we used for modeling are summarized here: Ptnonipm changes from the original 2005v2 inventory for the v4 platform development  Removed duplic ate 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” c ounty 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.  Dropp ed 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 o f either NO X , VOC, SO 2 , or 5 tons/y r of PM 2.5 . 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.14 Deliberative

– Do Not Cite or Quote 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 - ye ar 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 s ignificant evolutionary

updates was incorporating the PM condensable portion of emissions to the Clarion Steel Plant in All egheny County Pennsylvania (PLANTID=4200300032), where by-product Coke Manufacturing, quenching PM condensable emissions were augmented, increasing total plant- level PM 2.5 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 2005v1 NEI but was mi ssing 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 2005v1 inventory . The list below includes only

the ethanol plants that were used in the previous modeling effort but were missing from the 2005v2 NEI . State/County FIPS code Plant Name CO (tons/yr ) NOX (tons/yr ) PM10 (tons/yr ) PM2.5 (tons/yr ) SO2 (tons/yr ) VOC (tons/yr ) 0 6065 Golden Cheese Company of CA 10 30 12 1 39 14 13205 Wind Gap Farms (Anheuser/Miller

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 5715 Deliberative

– Do Not Cite or Quote 35041 Abengoa Bioenergy Corporation 10 30 12 1 39 14 46005 Heartland Grain Fuels, LP 0 1 0 0 1 0 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 n onpoint sources (afdust, ag, nonpt) The 2005v2 NEI ty

pically 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 . W e 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 is available at: http://www.epa.gov/ttn/chief/net/2005inventory .html In the rest of this section, we describe in more detail each of the platform sectors into which we separated the 2005 nonpoint NEI , and the changes we made to these data. We will refer to the 2002 platform documentation for sectors that did not change. 

### 2.2.1 Area fugitive dust sector (afdust) The emissions for this sector are unchanged from the 2005v4 platform, and th e 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. Inprevious modeling , all days within the same month had the same emissions. The area- source fugitive dust (afdust) sector contains PM 10 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 transp ort 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, unpav ed 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., PM 10 and PM 2.5 ) that are considered “fugitive”. A complete list of all possible fugitive dust SCCs (including both 8 - digit point source SCCs and 10 - digit nonpoint SCCs) is provided at: http://www.epa.gov/ttn/chief/emch/dustfractions/tf_scc_list2002nei_v2.xls . However, not all of the SCCs in this file are present in the 2002 NEI. The SCCs included in the 2002 NEI that comprise the 2005 ( and 2002) platform afdust sector (which are a subset of the SCCs in the web link) are provided in Table 2 - 4 .16 Deliberative

– Do Not Cite or Quote Table 2 - 4 . SCCs in the afdust platform sector SCC SCC Description 2275085000 Mobile Sources;Aircraft;Unpaved Airstrips;Total 2294000000 Mobile Sources;Paved Roads;All Paved Roads;Total: Fugitives 2296000000 Mobile Sources;Unpaved Roads;All Unpaved Roads;Total: Fugitives 2296005000 Mobile Sources;Unpaved Roads;Public Unpaved Roads;Total: Fugitives 2296010000 Mobile Sources;Unpaved Roads;Industrial Unpaved Roads;Total: Fugitives 2311000000 Industrial Processes;Construction: SIC 15 - 17;All Processes;Total 2311010000 Industrial Processes;Construction: SIC 15 - 17;Residential;Total 2311010040 Industrial Processes;Construction: SIC 15 - 17;Residential;Ground Excavations 2311010070 Industrial Processes;Construction: SIC 15 - 17;Residential;Vehicle Traffic 2311020000 Industrial Processes;Construction: SIC 15 - 17;Industrial/Commercial/Institutional;Total 2311020040 Industrial Processes;Construction: SIC 15 - 17;Industrial/Commercial/Institutional;Ground

Excavations 2311030000 Industrial Processes;Construction: SIC 15 - 17;Road Construction;Total 2325000000 Industrial Processes;Mining and Quarrying: SIC 14;All Processes;Total 2801000000 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Total 2801000002 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Planting 2801000003 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Ti lling 2801000005 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Harvesting 2801000007 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Loading 2805000000 Miscellaneous Area Sources;Agriculture Production - Livestock;Agriculture - Livestock;Total 2805001000 Miscellaneous Area Sources;Agriculture Production - Livestock;Beef cattle - finishing

operations on feedlots (drylots);Dust Kicked -up by Hooves (use 28 - 05 - 020, - 001, - 002, or - 003 for Waste Our approach was to apply the transportable fractions by county such that all afdust SCCs in the same county receive the same factor. The approach used to calculate the county- specific transportable fractions is based on land use data and is described by : http://www.epa.gov/ttn/chief/emch/dustfractions/transportable_fraction_080305_rev.pdf As this paper mentions, a limitation of the transportable fraction approach is the lack of monthly variability, which would be expected due to seasonal changes in vegetative cover. Further, the variability

due to soil moisture, precipitation, and wind speeds is not accounted for b y the methodology . An electronic version of the county- level transport fractions can be found at: http://www.epa.gov/ttn/chief/emch/dustfractions/transportfractions052506rev.xls The 2002 platform documentation describes an error in which the transportable fraction application for PM 2.5 was not applied. This error was fixed for the 2005v4 . 2 platform, and 2005 PM 2.5 afdust emissions are therefore correctl y about 43% less than those in the 2002 platform. 

### 2.2.2 Ag ricultural a mmonia sector (ag) This sector is unchanged from the 2005v4 platform ; the documentation is repeated here for co mpleteness . The agricultural NH 3 “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 200517 Deliberative

– Do Not Cite or Quote platform. The rest of this section documentation is therefore very similar to that in the 2002 documentation. In building this sector we extracted livestock and fertilizer emissions based on the SCC. The livestock SCCs are listed in Table 2 - 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 28050180 00 Dairy cattle composite;Not Elsewhere Classified 2805019100 Dairy cattle - flush dairy;Confinement 2805019200 Dairy cattle - flush dairy;Manure handling and storage 2805019300 Dairy cattle - flush dairy;Land application of manure 2805020001 Cattle and Calves Waste Emissions;Milk Cows 2805020002 Cattle and Calves Waste Emissions;Beef Cows 2805020003 Cattle and Calves Waste Emissions;Heifers and Heifer Calves 2805020004 Cattle and Calves Waste Emissions;Steers, Steer Calves, Bulls, and Bull Calves 2805021100 Dairy cattle - scrape dairy;Confinement 2805021200 Dairy cattle - scrape dairy;Manure handling and storage 2805021300 Dairy cattle - scrape dairy;Land application of manure 2805022100 Dairy cattle - deep pit dairy;Confinement 2805022200 Dairy cattle - deep pit dairy;Manure handling and storage 2805022300 Dairy cattle - deep pit dairy;Land application of manure 2805023100 Dairy cattle - drylot/pasture dairy;Confinement 2805023200 Dairy cattle - drylot/pasture dairy;Manure handling and s torage 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;Turkeys18 Deliberative

– Do Not Cite or Quote SCC SCC Description* 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 2805040000 Sheep and Lambs Waste Emissions;Total 2805045000 Goats Waste Emissions;Not Elsewhere Classified 2805045002 Goats Waste Emissions;Angora Goats 2805045003 Goats Waste Emissions;Milk Goats 2805047100 Swine production - deep -pit house operations (unspecified animal age);Confinement 2805047300 Swine production - deep -pit house operations (unspecified animal age);Land application of manure 2805053100 Swine production - outdoor operations (unspecified animal age);Confinement * All SCC Descriptions begin “Miscellaneous Area Sources;Agriculture Production

– Livestock” The “ag” sector includes all of the NH 3 emissions from fertilizer from the NEI. However, the “ag” sector does not include all of the livestock ammonia emissions, as there are also significant NH 3 emissions from livestock in the point source inventory that we retained from the 2002 NEI . Note 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 NH 3 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 SCCs 5 :  30202001: Industrial Processes ; Food and Agriculture ; Beef Cattle Feedlots; Feedlots

General  30202101: Industrial Processes ; Food and Agriculture ; Eggs and Poultry Production; Manure Handling: Dry  30203099: Industrial Processes ; Food and Agriculture ; Dairy Products; Other Not Classified There are also livestock NH 3 emissions in the point source inventory with SCCs of 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 NH 3 point sources based on their facility name. The reason why we needed to identify livestock NH 3 in the ptnonipm sector was to properl y 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”.19 Deliberative

– Do Not Cite or Quote 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 p latform 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 ye ar 2005 Phase II oil and gas emissions.  Residential wood combustion (RWC) emissions were replaced with data for Oregon and New York. This update is consistent with the 2005 v2 NEI .  RWC VOC emissions were recalculated for all states except California to reflect an updated emissions factor for VOC from RWC sources. This update is consistent with the 2005 v2 NEI.  We uti lized 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 integration20 Deliberative

– Do Not Cite or Quote criteria (i.e., the “no - integrate” sources) so that BAFM would not be double counted with the BAFM generated via speciation of VOC. Updates from 2005v4 p latform used in creating the 2005v4 . 2 p latform

 We changed the integration status for pesticide emissions from using the “integrate” case to using the “no - integrate” case. The main reason is that there were significant benzene emissions from this category in the NEI that was considered incorrect. The NEI benzene came from solvent utilization data (Fredonia) for "other markets" for the year 1998. Since benzene no longer allowed in pesticides, we chose to eliminate the use of these HAP data and use a VOC speciation profile that did not include benzene emissions to be more consistent with the changed regulation s.  We replaced Delaware fuel combustion (all industrial, commercial, and residential) , residential wood combustion, and open burning with revised state estimates for NOX, SO2, 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) data set, version G . The impact of this inventory change i s s hown 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=2270 0 10010) . Because the nonroad emissions are significantl y 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 NH 3 3 NO X 42,854 4,70421 Deliberative

– Do Not Cite or Quote PM 10 3,036 275 PM 2. 5 2,945 267 SO 2 5,977 573 VOC 4,337 340 Oklahoma Oil and Gas Emissions The state of Oklahoma provided and emissions replacement for their 2005 oil and gas sector emissions. The se data added emissions for the SCCs shown in Ta ble 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 d escriptions start with the preface “Industrial Processes;Oil and Gas Production” In addition, this update removed emissions for SCC 2310000000, which is “ Industrial Processes;Oil and Gas Production: SIC 13;All Processes;Total: All Processes .” The resultant Oklahoma emissions are shown below in Table 2 - 9 . Note that Oklahoma instructed that PM 10 emissions were size PM 2.5 , and therefore no coarse PM (PMC) was generated and PM 10 is the same as PM2.5

Table 2 - 9 . Changes to Oklahoma oil and gas emissions Pollutant 2005 Oklahoma Oil and gas

emissions 2005, removed from nonpt (tons/yr) 2005 Oklahoma Oil and gas emissions , added to nonpt (tons/yr) CO 11,251 32,821 VOC 104,193 155,908 NO X 66,480 39,668 SO 2 0 1, 014 PM 10 = PM2.5 0 1,918 

### 2.3 Fires (avefire)22 Deliberative

– Do Not Cite or Quote The purpose of the avefire sector is to represent emissions for a ty pical ye ar’s fires for use in projection year inventories, since the location and degree of future - ye ar 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 b y changing the fires. Using an average of multiple years of data reduces the possibility that a single - ye ar's high or low fire activity would unduly affect future - year model -predicted concentrations. The avefire sector contains wildfire and prescribed burning emissions . It exclude s agricultural burning and other open burning sources , which are included in the nonpt sector. Generally, their ye ar- to - ye ar 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 - ye ar cases. Emissions are annu al 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 underl ying land use data and parameters are unchanged for the 2005 platform. The BE IS 3.14 model creates gridded, hourl y, model - species emissions from vegetation and soils. It estimates CO, VOC, and NO X emissions for the U.S., Mexico, and Canada. The BEIS3.14 model is described further in: http://www.cmascenter.org/conference/2008/slides/pouliot_tale_two_cmas08.ppt The inputs to BEI S include:  T emperature data at 2 meters which were obtained from the meteorological input files to the air quality

model ,  L and -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 m obile sources (on_noadj, on_moves_runpm, on_moves_startpm, nonroad, alm_no_c3, seca_c3) F or 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” . The23 Deliberative

– Do Not Cite or Quote on_moves_startpm and on_moves_runpm sectors are processed separatel y 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 previousl y mentioned, the aircraft emissions are in the non - EGU (ptnonipm) point 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 primaril y based on the publicly released 12/21/2009 version of the Motor Vehicle Emissions Simulator (MOVES2010) (http://www.epa.gov/otaq/models/moves/). MOVES was run with a s tate/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 2005 v2 NEI, were used. The major change s 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 ty pes 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 onl y exhaust mode PM 2.5 , VOC, NO X and CO) ; and (4 ) we used NH 3 from MOVES for California (as opposed to NH 3 from NMIM) since California - suppli ed emissions in the 2005v2 NEI do not include NH 3 . Itshould also be noted that the exhaust PM 2.5 from diesel vehicles, which had previously

come from NMIM but in v4. 2 come s 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 pollutant s, 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 2 005v4.2 platform. Table 2 - 10 . Data s ource s for onroad mobile sources in the 2005v4 and 2005v4 . 2 p latform s 1

Pollutants/vehicles/modes 2005v4 2005v4.2 PM 2.5 ; gasoline exhaust, partially speciated2 Draft MOVES MOVES2010 PM 2.5 ; diesel exhaust, partially speciated2 NMIM MOVES2010 PM 2.5 , brake and tirewear, unspeciated NMIM MOVES2010 VOC, Benzene (except refueling); gasoline Draft MOVES MOVES2010 VOC , Benzene (except refueling); diesel NMIM MOVES2010 CO, NO X , SO 2 , NH 3 , Acetaldehyde , Formaldehyd e ; gasoline Draft MOVES MOVES2010 CO, NO X , SO 2 , NH 3 , Acetaldehyde, Formaldehyd e; diesel NMIM MOVES2010 1 For California, 2005v4 and 2005v4.2 use draft MOVES and MOVES 2010 (respectively) only for NH 3 .24 Deliberative

– Do Not Cite or Quote 2 Exhaust mode PM 2.5 species from MOVES consist of: PEC, PSO 4 and the difference between PM 2.5 and PEC (named as “PM25OC”) . Procedures to produce the species needed are provided in Appendix D of the 2005v4.1 TSD: http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf . 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 e mi ssions. Brake wear and tire wear PM 2.5 emissions were not pre - speciated. Similar to the v4 platform , we used the MOVES data to create emissions by state and month (and SCC) and then allocated to counties based on 2005 NMIM -based county- level data. The reason for using the state resolution was due to (a) run time issues that made a county run for the entire nation infeasible in the timeframe required and (b) 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 onl y to allocate California submitted data to road types, to allocate the state - month - SCC MOVES data to counties, and for some of the nonroad mobile sources. NMIM relies on calculations from the MOBILE6 and NONROAD2005 models as described below, and in the NEI documentation. Inputs to NMIM are posted with the 2005 Emission Inventory . The direct link is: ftp://ftp.epa.gov/EmisInventory /2005_nei/mobile_sector/ncd/ncd20080522.zip . 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 20 05v2 NEI onroad and nonroad sectors is also posted with other 2005 NEIdocumentation; the direct link is: ftp://ftp.epa.gov/EmisInventory /2005_nei/mobile/2 005_mobile_nei_version_2_report.pdf 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 separatel y 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 PM 2.5 emissions for 7 counties was discovered. We corrected the se PM 2.5 emissions by using an earlier version of the 2005 submittal which California had provided values for the 7 counties .

6 Although OTAQ generated emissions using NMIM for California, these were not used in the 2005 NEI version 2, but rather were replaced by state - submitted emissions. Since California did not submit NH 3 , values from MOVES were used.25 Deliberative

– Do Not Cite or Quote The mobile sectors are compiled at a county and SCC resolution, with the exception of the seca_c3 sector that uses point source s to map the pre - gridded data to the modeling domain. Similar to v4, in v4. 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 Secti on 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 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_mo ves_startpm) This sector contains MOVES 2010 emissions for PM and naphthalene 7 for non - California onroad gasoline cold- start exhaust. These emissions (and the on_moves_runpm sector discussed in the next section) are processed separatel y 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 72oF. Because it was not feasible to run MOVES directl y for all of the gridded, hourl y temperatures needed for modeling, we created emissions of PM and naphthalene exhaust at 72oF and applied temperature adjustments after the emissions were spatiall y and temporall y allocated. The PM 2.5 (and naphthalene) adjustment factors were different for starting and running exhaust because these two processes respond differentl y to temperature as shown in Figure 2 - 1 which shows how these emissions incre ase with colder temperatures. The temperature adjustment factor in this figure is defined in terms of primary elemental carbon (PEC) as follows:

PEC = Adjustment Factor x PEC_72 Where: PEC = PEC at Temperature s below 72oF PEC_72 = PEC at 72oF or higher As seen in the figure, start exhaust emissions increase more than running exhaust emissions as temperatures decrease from 72oF. Figure 2 - 1 also shows that the actual adjustments are different for start exhaust and running exhaust emissions. The method for appl ying these adjustments was the same for both start and running exhaust sectors: They were applied to SMOKE gridded, hourl y intermediate files , based upon the gridded hourl y t emperature 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

7 Naphthalene is not used in the 2005v4 CAP - BAFM platform, but it is contained in the MOVES emissions.26 Deliberative

– Do Not Cite or Quote inputs for the on_moves_startpm and on_moves_runpm sectors will not be valid because they will not include the temperature adjustments. As a result, the post-processing for temperature adjustments included computing the emissions totals at state, county, and month resolution to use for summaries. Figure 2 - 1 . MOVES exhaust temperature adjustment functions.

The MOVES output data required pre -processing to develop county- level monthly ORLfiles 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 PM 2.5 , for which emissions from MOVES were partially speciated. T o 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 separatel y 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 s tate - 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 2005 v2 NEI). 0 10 20 30 40 50 60 70 80

-20 -10 1 11 21 31 41 51 61 71 Te mpe ra ture ( F)Adjustment Factor Run Exh aus t Sta rtExh aus t2 7 Deliberative

– Do Not Cite or Quote 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 road s 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. iii. We converted MOVES -based PM 2.5 species at 72 oF to SMOKE - ready PM species. The SMOKE - ready species are listed below and the speciation technique used to obtain the SMOKE - ready species is further discussed in Appendix D of the 2005v4.1 TSD : http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf .  NAPHTH_72: unchanged from MOVES -based file, subject to temperature adjustment below 72 oF .  PEC_72: unchanged from MOVES -based PM25EC, subject to temperature adjustment below 72 oF .  POC_72: modified MOVES -based PM25OC to remove metals, PNO3 (computed from MOVES -based PM25EC), NH 4 (computed from MOVES -based P M25SO4 and PNO3), and MOVES -based PM25SO4. Subject to temperature adjustment below 72 oF .  PSO 4 : unchanged from MOVES -based PM25SO4, not subject to temperature adjustment.  PNO 3 : computed from MOVES -based PM25EC, not subject to temperature adjustment.  OTHER: sum of computed metals (fraction of MOVES -based PM25EC) and NH 4 (computed from PNO3 and PSO4), not subject to temperature adjustment.  PMFINE_72: Computed from OTHER and fraction of POC_72. Subject to temperature adjustment below 72 oF .  PMC_72: Computed as fraction of sum of PMFINE_72, PEC_72, POC_72, PSO4, and PNO3. Subject to temperature adjustment below 72 oF . The total MOVES PM emissions are conserved during allocation from state s to counties, and from the generic total “start” SCCs to the two new parking SCCs that end in “350” and “370”. PEC and PSO 4 components of PM 2.5 emissions are also conserved as they are simply renamed from the MOVES specie s “PM25EC” and “PM25SO4” . However, as seen above, POC, PNO 3 , and PMFINE components involve multiplying the MOVES PM species by components of an onroad gasoline exhaust speciation profile described in Appendix D of the 2005v4.1 TSD . 

### 2.5.2 Onroad gasoline exhaust running mode PM (on_moves_runpm) This sector is identical to the on_moves_startpm sector discussed in S ection 2.5.1, but contains running exhaust emissions instead of cold- start exhaust emissions. The same pollutants are in this sector, and allocation from the MOVES state - level to county- level inventory is a simple match by SCC and month to NMIM state - county ratios. The only reason this sector is separated28 Deliberative

– Do Not Cite or Quote 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 ). 

### 2.5.3 Onroad mobile with n o adjustments for daily temperature (on_noadj) This sector consists of the bulk of the onroad mobile emissions , which are not covere d by the on_moves_startpm and on_moves_runpm sectors . These emissions did not receive any temperature adjustments in our processing . There are four sources of data that are pre -processed to create 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, NO X , CO, SO 2 , NH 3 , 1,3 -butadiene (106990), acetaldehyde (75070), acrolein (107028), benzene (71432), formaldehyde (50000) , and brake and tire wear PM 2.5 ; b. Diesel Exhaust: Partially- speciated PM 2.5 (that were full y speciated prior to input into SMOKE (via Appendix D of the 2005v4.1 TSD : http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf ), VOC, NO X , CO, SO 2 , NH 3 , 1,3 -butadiene (106990), acetaldehyde (75070), acrolein (107028), benzene (71432), formaldehyde (50000) , and brake and tire wear PM 2.5 . Because diesel exhaust PM does not require the same intermediate temperature adjustments as gasoline exhaust PM, diesel exhaust PM can therefore be processed with the remaining onroad mobile emissions . c. Evaporative: Non - refueling VOC, benzene, and naphthalene (91203 ) . For the 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 he avy 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 -processe d from state - level to county- level much like the on_moves_startpm and on_moves_runpm sectors already discussed. The preprocessing for the non - PM emissions did not require species calculations because the raw MOVES emissions translated directly to SMOKE inventory

species. 2. California onroad inventory : California 2005v2 NEI complete CAP/HAP onroad inventory . California monthly onroad emissions are year 2005 and are based on September 2007 California Air Resources Board (CARB) data from Chris Nguyen. NH 3 emissions are from MOVES2010 runs for California. We retained onl y those HAP s that are also estimated by

NMIM for onroad mobile sources; all other HAP s provided by California were dropped . The California onroad inventory does not use the SCCs for Heavy Duty Diesel Vehicles (HDDV) class 6 & 7 (2230073XXX) emissions. California does not specify

road ty pes, so we used NM IM -based California ratios to break out vehicle emissions to the match the more detailed NMIM level.29 Deliberative

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### 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 o mission of PM 2.5 from seven counties. Thus, except for seven counties in California, emissions from this sector did not 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 SIengine final rule, published May 200 9 (EPA, 200 8 ). 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 emi ssions for the 2005v2 NEI nonroad mobile CAP/HAP inventory, and similar to on_noadj, we removed California NMIM emissions that were submitted separatel y b y 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 NM IM nonroad emissions development: ftp://ftp.epa.gov/EmisInventory /2005_nei/mobile/2005_mobile_nei_version_2_report.pdf California nonroad California monthly

nonroad emissions are ye ar 2005 and are b ased on September 2007 California Air Resources Board (CARB) data from Chris Nguyen , other than for the PM 2.5 missing from 7 counties, which used the March 2007 version . In addition, NH 3 emissions are from NMIM runs for California because these were not included in the California NEI submittal . HAP emissions were estimated by appl ying HAP - to - CAP ratios computed from Calif ornia data provided in the 2005 v2 NEI submittal . We retained only those HAP s that are also estimated by NMIM for nonroad mobile sources ; all other HAP s 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, w e split the annual total California data into monthly, mode - specif ic nonroad emissions for California using the NM IM results. Details on this process are documented separatel y (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 ty pes based on ratios of evaporative - mode VOC. The factor o f 0.46 was computed by dividing the NMIM - derived California refueling for 2005 by the sum of portable fuel container emissions and NMIM - derived refueling for 2005.30 Deliberative

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### 2.5.5 Nonroad mob ile 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 . P oint- source airports were included in the non - EGU point sector (ptnonipm) through the 2005v2 NEI point source inventory . The C3 CMV emissions are in the seca _c3 sector. We note that the “a” in th e “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 p latform. The remaining emissions in the alm_no_c3 sector are ye ar 2002 emissions unchanged from the 2002 platform ; we repeat the 2005v4 documentation for completeness . The SCCs in the alm_no_c3 sector are listed in Table 2 - 11 .31 Deliberative

– Do Not Cite or Quote Table 2 - 11 . SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform alm sector SCC Action SCC Description 2275000000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: All Aircraft Types and Operations: Total 2275001000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: Military Aircraft: Total 2275020000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: Commercial Aircraft: Total: All Types 2275050000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: General Aviation: Total 2275060000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: Air Taxi: Total 2280002100 Retained from 2002 platform Mobile Sources;Marine Vessels, Commercial;Diesel;Port emissions 2280002200 Retained from 2002 platform Mobile Sources;Marine Vessels, Commercial;Diesel;Underway emissions 2280003100 Emissions removed and replaced by

seca_c3 inventories for 2005 platform Mobile Sources;Marine Vessels, Commercial;Residual;Port emissions 2280003200 Emissions removed and replaced by

seca_c3 inventories for 2005 platform Mobile Sources;Marine Vessels, Commercial;Residual;Underway emissions 2280004000 Retained from 2002 platform Mobile Sources;Marine Vessels, Commercial;Gasoline;Total, All Vessel Types 2285002006 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations 2285002007 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations 2285002008 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) 2285002009 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines 2285002010 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Yard Locomotives The documentation of the 2002 NEI for the category 1 and 2 (C1/C2) commercial marine and locomotive emissions is available at: http://www.epa.gov/ttn/chief/net/2002inventory .html#documentation For modeling purposes, the following additional change s were made to the NEI data for the 2005 v4 platform:

 For the 2005 v4 platform, we removed C3 CMV SCCs (residual fuel) and aircraft SCCs .32 Deliberative

– Do Not Cite or Quote  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 anal ys is of VOC and VOC HAPs indicates the source is not integrated. Although our CAP - HAP integrati on 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 - IM O ) 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 recentl y , were allowed to meet relativel y 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 - ye ar goals for red

uction of NO X , SO 2 , and PM C3 emissions can be found at: http://www.epa.gov/oms/regs/nonroad/marine/ci/420f09015.htm The resulting coordinated strategy, including emission standards under the Clean Air Act for new marine diesel engines with per- cylinder displacement at or above 30 liters , and the establishment of Emission Control Areas is at: http://www.epa.gov/oms/oceanvessels.htm . The raw ECA inventory

started as a set of ASCII raster datasets at approximately 4 - km resolution that we converted to SMOKE point - source ORL input format as described in http://www.epa.gov/ttn/chief/conference/ei17/session6/mason.pdf . In summary, this paper describes how the ASCII raster dataset was converted to latitude longitude, mapped to state/county FIPS codes that extend up to 200 nautical miles (nm) from the coast, assigned stack parameters, and how the monthly ASCII raster dataset emissions were used to create monthl y temporal profiles. Counties in 2005v4 were assigned as extending up to 200nm from the coast because of this was th e 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.33 Deliberative

– Do Not Cite or Quote The base ye ar ECA inventory is 2002 and consists of these CAPs: PM 10 , CO, CO 2 , NH 3 , NO X , SO X ( assumed to be SO 2 ), and Hydrocarbons ( assumed to be VOC). 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 onl y 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 Acetaldehyd e = VOC * 2.286E - 04 Formaldehyd e = VOC * 1.5672E - 03 We converted the emissions to SMOKE point sou rce 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 simpl y 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 w ith 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 . Table 2 - 12 . Adjustment f actors to update the 2005 seca_c3 sector emissions for the v4. 2

p latform. 2005 Adjustments Relative to 200234 Deliberative

– Do Not Cite or Quote Region NO X PM 10 PM 2.5 VOC (HC ) CO SO2 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 u p 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. Itis 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 2005 v4 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 emission s (2280003100 and 2280003200). The net impact of all the 2005v4.2 changes to U.S. total NO X , SO 2 , and PM2.5 seca_c3 emissions are shown in Table 2 - 13 . Again, with the exceptions of NO X , PM 2.5 , and most notably, SO 2 in Delaware, approximately 99% of these differences are solel y 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. Table 2 - 13 . Contiguous U.S. C3 CMV emissions in the 2005 v4 and 2005v4.2 platforms

Pollutant 2005v4 2005v4.2 NO X 642,0 00 130,000 PM 2.5 49,000 11,000 SO 2 417,000 97,00035 Deliberative

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### 2.6 Emissions from Canada, Mexico and offshore d rilling 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 platform s 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” emissi ons 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 - ye ar emissions, as we were advised by Canada that the improvement in the 2006 inventory over the 2000 inventory

w as 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 cov ers 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 nonp oint (nonpt) inventory; these emissions are also absent from our U.S. inventory . vii. Quebec PM 2.5 emissions (2,000 tons/y r) were removed for one SCC (2305070000) for Industrial Processes, Mineral Processes, Gy psum, 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.36 Deliberative

– Do Not Cite or Quote 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 Mex ico we continued to use emissions for 1999 (Eastern Research Group Inc., 2006) which were developed as part of a partnership between Mexico's Secretariat of the Environment and Natural Resources (Secretaría de Medio Ambiente y Recursos Naturales - SEMARNAT) and National Institute of Ecology (Instituto Nacional de Ecología- IN E), 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 Mex ico. 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 b y 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 s ectors changes from the 2002 platform Sector Components Changes from 200 2 platform othpt Mexico, 1999, point None

Canada, 2006, point Uses emissions from 2006 National Pollutant Release Inventory

(NPRI), 3 components: 1) upstream oil and gas sector emissions for all CAPs except VOC; 2) VOC sources pre - speciated to CB05 speciation except for benzene; 3) Remaining point source emissions. Offshore, 2005, point Uses emissions from 2005 v2 point inventory othar Mexico, 1999, nonpoint None

Mexico, 1999, nonroad None Canada, 2006, nonpoint Uses 2006 Canadian aircraft (landing and take - offs only), agricultural NH 3 , fugitive dust, and remaining nonpoint inventories. Canada, 2006, nonroad Uses 2006 Canadian nonroad mobile, non - C3 marine, and locomotives inventories. othon Mexico, 1999, onroad None

Canada, 2006, onroad Uses 2006 Canadian onroad inventory . Emissions are given at vehicle type resolution only (i.e., does not include road types) .37 Deliberative

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### 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 . S ee ftp://ftp.epa.gov/EmisInventory /2002v3CAPHAP/documentation for details.38 Deliberative

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## 3 Emissions M odeling S ummary Both the CMAQ and CAMX model s require hourly emissions of specific gas and particle species for the horizontal and vertical grid cells contained within the modeled region (i.e., modeling domain). T o provide emissions in the form and format required b y 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 b y the air quality model . As seen in Section 2 , the temporal resolution of the emissions inventories input to SMOKE for the 200 5 platform varies across sectors, and may be hourly, monthl y, or annual total emissions . The spatial resolution, which also can be dif ferent 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 200 5 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 emi ssions 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 u pdated the ancillary files to handle additional MOVES SCCs related to parking area emissions and to make some changes to the temporal and spatial approaches that were originall y assigned to parking area SCCs .  W e change d speciation prof iles for headspace vapor (V OC) .  W e changed the PM 2.5 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.  W e use d an updated county- to - cell spatial surrogate for U.S. oil and gas emissio ns .  W e change d 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) residential39 Deliberative

– Do Not Cite or Quote natural gas combustion and commercial propane and kerosene combustion from uniform monthly to a profile that varies for the nonpt sector . We also utilized the feature in SMOKE (updated in version 2.5) to create combination speciatio n 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 s ource -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 b y CAMX using a FORTRAN convertor 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 b y CAMX . Emissions totals by specie for the entire model domain are output as reports that are then compared to reports generated b y 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 Section 3.2.1.2 ). 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 hourl y 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 q uality 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 2005 v4. 2 p latform s , 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 s ector. The seca_c3 s ector is the only sector with only “in - line” emission s , meaning that all of the entire emissions occur in aloft layers and there are no emissions in the two - dimensional , layer- 1 files created b y SMOKE.

Table 3 - 1 . Key

emissions modeling steps by sector . Platform sector Spatial Speciation Inventory resolution Plume rise p tipm P oint Yes daily & hourl y in - line40 Deliberative

– Do Not Cite or Quote Platform sector Spatial Speciation Inventory resolution Plume rise p tnonipm P oint Yes annual in - line o thpt P oint Yes annual in - line nonroad surrogates &

area - to -point Yes monthly o thar S urrogates Yes annual seca_c3 P oint Yes annual in - line alm _no_c3 surrogates &

area - to -point Yes annual on_noadj S urrogates Yes monthly on_noadj S urrogates Yes monthly on_moves_startpm S urrogates Yes monthly on_moves_runpm S urrogates Yes monthly o thon surrogates Yes annual nonpt surrogates &

area - to -point Yes annual ag surrogates Yes annual afdust surrogates Yes annual b iog pre - gridded landuse in BEIS 3.14 hourly avefire surrogates Yes annual In addition to the above settings, we used the PELVCONFIG file , which can be optionally used to group sources so that they would be treated as a single stack by SMOKE when computing plume rise. For the 2005 v4. 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 S patial configuration For the 200 5 v4.2 platform in support of the Transport Rule , we ran SMOKE followed by CAMX for the 36 - km CONtinental United S tates “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.41 Deliberative

– Do Not Cite or Quote Figure 3 - 1 . Air quality modeling domain s

All three grids use a Lambert- Conformal projection, with Alpha = 33 o , Beta = 45 o and Gamma =

- 97 o , with a center of X = - 97 o and Y = 40 o . Table 3 - 2 describes the grids for the three domains. 36km Domain Boundary

12km East Domain Boundary 12km West Domain Boundary42 Deliberative

– Do Not Cite or Quote Table 3 - 2 . Descriptions of the 200 5 -based platform grids Common Name Grid

Cell Size Description

(see Figure 3 - 1) Grid name Parameters listed in SMOKE grid description (GRIDDESC) file: p rojection name , xorig, yorig, xcell, ycell, ncols, nrows, nthik US 36 km or CONUS - 36 36 km Entire conterminous US plus some of Mexico/Canada US36KM_148X1

12 ‘LAM_40N97W', - 2736.D3, - 2088.D3,

36.D3, 36.D3, 148, 112, 1 Big East 12 km 12 km Goes west to Colorado, covers some Mexico/Canada EUS12_279X240 ‘LAM_40N97W', - 1008.D3 , - 1620.D3, 12.D3, 12.D3, 279, 240, 1 West 12 km 12 km Goes east to Oklahoma, covers some of Mexico/Canada US12_213X192 'LAM_40N97W', - 2412.D3 , - 972.D3, 12.D3, 12.D3, 213, 192, 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 b y 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 200 5 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 i s implemented in CAMX 5.2 . The specific version s of CMAQ and CAMx used in applications of this platform include secondary organic a erosol (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 s esquiterpene s ( SESQ ) . It should be noted that the BENZENE model species is not part of CB05 in that the concentrations of BENZENE do not provide any feedback into the chemical reactions (i.e., it is not “inside” the chemical mechanism) . Rather , benzene is used as a reactive tracer and as such is impacted by the CB05 chemistry . BENZENE, along with several reactive CBO5 species (such as TOL and XYL) plays a role in SOA formation.43 Deliberative

– Do Not Cite or Quote Table 3 -3 . Model species produced b y SMOKE for CB0 5 with SOA for CMAQ4.7 and CAMX * Inventory Pollutant Model Species Model species description CL2 CL2 Atomic gas -phase chlorine HCl HCL Hydrogen Chloride (hydrochloric acid) gas CO CO Carbon monoxide NO X NO Nitrogen oxide

NO2 Nitrogen dioxide HONO Nitrous acid SO 2 SO2 Sulfur dioxide

SULF Sulfuric acid vapor NH 3 NH3 Ammonia VOC ALD2 Acetaldehyd e

ALDX Propionaldehyde and higher aldehydes BENZENE Benzene (not part of CB05) ETH Ethene ETHA Ethane ETOH Ethanol FORM Formaldehyd e IO LE Internal olefin carbon bond (R- C=C - R) ISOP Isoprene MEOH Methanol OLE Terminal olefin carbon bond (R- C=C) PAR Paraffin carbon bond TOL Toluene and other monoalkyl aromatics XYL Xylene and other polyalkyl aromatics Various additional VOC species from the biogenics model which do not map to the above model species SESQ S esquiterpene s

TERP Terpenes

PM 10 PMC Coarse PM > 2.5 microns and  10 microns PM 2.5 PEC Particulate elemental carbon  2.5 microns

PNO3 Particulate nitrate  2.5 microns POC Particulate organic carbon (carbon onl y)  2.5

microns PSO4 Particulate Sulfate  2.5 microns PMFINE Other particulate matter  2.5 microns Sea- salt species (non

–anthropogenic emissions) PCL Particulate chloride

PNA Particulate sodium *T he same species names are used for the CAM X model with exceptions as follows: 1. CL2 is not used in CAM X 2 . CAM X particulate sodium is NA (in CMAQ it is PNA) 3 . CAM X uses different names for species that are both in CBO5 and SOA for the following: TOLA=TOL,44 Deliberative

– Do Not Cite or Quote XYLA=XYL, ISP=ISOP, TRP=TERP. They are duplicate species in CAM X that are used in the SOA chemistry. CMAQ uses the same names in CB05 and SOA for these species. 4 . CAM X uses a different name for sesquiterpenes: CMAQ SESQ = CAM X SQT 5 . CAM X uses particulate species uses different names for organic carbon, coarse particulate matter and other particulate mass as follows: CMAQ POC = CAM X POA, CMAQ PMC = CAM X C PRM , and CMAQ PMFINE= CAM X FPRM The approach for speciating PM 2.5 emissions in v4.2 is the same as v4 except that in addition to the on_moves_startpm and on_moves_runpm sectors, exhaust PM from diesel is provided to SMOKE as speciated emissions. Thus, the only PM species requiring speciation in SMOKE from the onroad sector are the brake and tirewear PM2.5. Canada point sources have an SCC of 3999999999 and all use the Speciation profile ‘92037’ which is the “Industry Manufacturing Avge profile.” While this had not changed between v4 and v4.2 , 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 PM 2.5 . One other difference in PM 2.5 speciation is that we used a new profile (‘92200’) called “ simplified profi le - 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. F or some sources, HAP emissions are used in the speciation process to allow integration of VOC and HAP emissions in the NEI. This has the 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. F or some mobile sources, “combination” profiles are specified by county and month and emission mode (e.g. , exhaust, evaporative). SMOKE computes the resultant profile using the fraction of each specific profile assigned b y county, month and emission mode. A new feature and new profile file in SMOKE (the GSPRO_COMBO file ) allowed the use o f this approach for the 2005v4 platform, and its use continues here . The VOC speciation data files are different because we added another part of the nonpt sector to exclude from HAP VOC integration : 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 evaporativ e gasoline processes (portable fuel containers and any evaporation of gasoline associated with gasoline storage and distribution sources). The below subsections provide a further description of the HAP/CAP integration and use of combination profiles. Section 3.2.2 provides the details about the data files used to accomplish these speciation processing steps.45 Deliberative

– Do Not Cite or Quote 3.1.2.1 The c ombination of HAP BA FM (benzene, acetaldehyde, forma ldehyde and methanol) and VOC for VOC s peciation The VOC speciation approach for the 2005 v4.2 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 i s, 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 no t double count emissions and uses the BAFM directly in the speciation process. We believe that generall y, 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 integration 8 ). 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 proce ss is illustrated in Figure 3 - 2 . Note that we did not need to remove B AFM from no - integrate sources in a sector where all sources are no - integrate because this is accomplished by through use of a SMOKE ancillary “I NVTABLE” 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.46 Deliberative

– Do Not Cite or Quote Figure 3 - 2 . Proce ss of integrating BAFM with VOC for use in VOC Speciation

Emi ssi onsr eady fo r SMOKE

list of “no - integrate” sources (N HAPEXCLUDE) Compute NONHAP VOC= VOC – (B + F + A+M) emi ssi onsfo r each integ ra te so ur ce Retain VOC emissions f or e ac h no - int egra te so ur ce Assign sp eci at ion pr of ile code to each emission so ur ce Compute: NONHAP TO G emissi onsfro m NONHAP VOC fo r each int egra te so ur ce Compute: TO G emissi onsfro m V OC fo r each no - integrate so ur ce TO G and NONHAPT OG speciation factors (GS PRO) Spe ciation Cross Ref erence File ( GS REF ) SMOKE

Compute moles of each CBO5 model s pecies. Use N ONHAP TO G p ro files applied to NO NHAPTOG emi ssi onsa nd B, F, A , M emi ssi ons fo r integr ate so urces. Use TOG profilesa pplie d to TOG f or no - int egra te so ur ces Speciated Emi ssi onsfo r VOC sp eci es VOC -to -TO G factors NONHAPVOC - to - NONHA PTOG factors (GSCNV) Step 2: Run SMOKE47 Deliberative

– Do Not Cite or Quote 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, formaldehyd e and methanol (BAFM) for each platform sector PlatformSector Approach for Integrating NEI emissions of Benzene (B), Acetaldehyde (A),

Form aldehyde (F) and Methanol (M) ptipm No integration because emissions of BAFM are relatively small for this sector ptnonipm No integration because emissions of BAFM are relatively small for this sector and it is not

expected that criteria for integration would be met by a significant number of sources avefire No integration ag N/A

– sector contains no VOC afdust N/A

– sector contains no VOC nonpt Partial integration ; details provided below table nonroad For other than California: Partial integration

– did not integrate CNG or LPG sources (SCC

beginning with 2268 or 2267 ) because NMIM computed only VOC and not any HAPs for these SCCs. For California: Full integration alm _no_c3 Partial integration; details provided below table seca_c3 Full integration onroad Full integration b iog N/A

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

– not the NEI othar No integration

– not the NEI othon No integration

– not the NEI For the nonpt sector, we used the following integration criteria to determine the sources to integrate (Step 1) : 1. Any source for which B AFM emissions were from the 1996 NEI were not integrated ( data source code contains a “96” ). 2. Any source for which the sum of B AF M is greater than the VOC was not integrated , since this clearl y 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 th e category per the criteria specified in the first c olumn in Table 3 - 5 . For most of these source categories, we allow sources to be integrated if they had the minimum combination of B AF M specified in the first column. For a few source categories, we designated all sources as “no - integrate” . The one change we made from Table 3 - 5 for the v4. 2 platform is highlighted : we change d pesticides application to “no integrate.” 4. For source categories not covered in Table 3 - 5 (i.e., that do no t comprise the top 80% of VOC emissions ) , then as long as the source has emissions of one of the BFAM pollutants , then it can be integrated.48 Deliberative

– Do Not Cite or Quote Table 3 - 5 . Source - category specific criteria for integrating nonpt SCCs for categories comprising 80% of the nonpoint VOC emissions mi ni mum HAP (s) needed SCC Tier 3 SCC Tier 3 Description C omments BFA 2104008000 Stationary Source Fuel Combustion;Residential;Wood B 2501060000 Storage and Transport;Petroleum and Petroleum Product Storage;Gasoline Service Stations BM 2440000000 Solvent Utilization;Miscellaneous Industrial;All Processes Speciation profile: 3144 has no benzene but most records have it and they're from the EPA (and Calif) FAM 2401001000 Solvent Utilization;Surface Coating;Architectural Coatings B 2310001000 Industrial Processes;Oil and Gas Production: SIC 13;All Processes : On - shore M 2460000000 Solvent Utilization;Miscellaneous Non - industrial: Consumer and Commercial;All Processes B 2501011000 Storage and Transport;Petroleum and Petroleum Product Storage;Residential Portable Gas Cans M 2425000000 Solvent Utilization;Graphic Arts;All Processes M 2465000000 Solvent Utilization;Miscellaneous Non - industrial: Consumer;All Products/Processes 3144 is profile, and it does have methanol (but no BFA). BFA 2801500000 Miscellaneous Area Sources;Agriculture Production

- Crops;Agricultural Field Burning - whole field set on fire 8746 is speciation profile and has BFA M 2440020000 Solvent Utilization;Miscellaneous Industrial;Adhesive (Industrial) Application 3142 is speciation profile which has methanol (.32%) and 0 form (and no acetald, benz) B 2501050000 Storage and Transport;Petroleum and Petroleum Product Storage;Bulk Terminals: All Evaporative Losses B 2310000000 Industrial Processes;Oil and Gas Production: SIC 13;All Processes M 2465400000 Solvent Utilization;Miscellaneous Non - industrial: Consumer;Automotive Aftermarket Products 8520 is speciation profile which doesn't have benz but does have methanol. OR is only state with benzene which is negligible No integrate (change from v4 platform) 2461850000 Solvent Utilization;Miscellaneous Non - industrial: Commercial;Pesticide Application: Agricultural P rofile has no benzene. Inventory b enzene came from solvent utilization data (Fredonia) for "other markets" for the year 1998. S ince benzene no longer allowed in pesticides , use of a no -benzene profile would give more accurate results. Note that this is a change from 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 F ormaldehyde 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 o f these HAP. Only M innesota has a tiny amount. no integrate 2401005000 Solvent Utilization;Surface Coating;Auto Refinishing: SIC 7532 Only NY has b enz ene . Spec . profile is 2402 and has none of these HAP. D ocumentation for NEI does not estimate this HAP. use Integrate 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.49 Deliberative

– Do Not Cite or Quote mi ni mum HAP (s) needed SCC Tier 3 SCC Tier 3 Description C omments case 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 prof ile 3139 has only M no integrate 2401020000 Solvent Utilization;Surface Coating;Wood Furniture: SIC 25 profile 2405 has no HAP B 2505040000 Storage and Transport;Petroleum and Petroleum Product Transport;Pipeline any 1 HAP 2610030000 Waste Disposal, Treatment, and Recovery;Open Burning;Residential profile 0121 is old and has only hexane. any 1 HAP 2610000000 Waste Disposal, Treatment, and Recovery;Open Burning;All Categories profile 0121 is old and has only hexane. FAM 2401003000 Solvent Utilization;Surface Coating;Architectural Coatings - Water-based profile 3140 has FAM M 2460100000 Solvent Utilization;Miscellaneous Non - industrial: Consumer and Commercial;All Personal Care Products profile (3247, nonlegacy based on CARB 1997 survey) has no M or B. However, F reedonia was used for M. M 2465200000 Solvent Utilization;Miscellaneous Non - industrial: Consumer;Household Products M 2415300000 Solvent Utilization;Degreasing;All Industries: Cold Cleaning profile 8745 (non legacy but composite made up of a bunch of E - rated profiles )has M, B. any 1 HAP 2401040000 Solvent Utilization;Surface Coating;Metal Cans: SIC 341 profile 2408 has none. - no HAPs in NEI so this SCC will not have any integrated sources any 1 HAP 2401050000 Solvent Utilization;Surface Coating;Miscellaneous Finished Metals: SIC 34 - (341 + 3498) SPEC PROFILE 3127 has none - no HAPs in NEI so this SCC will not have any integrated sources any 1 HAP 2401200000 Solvent Utilization;Surface Coating;Other Special Purpose Coatings profile 3138 has methanol. Not legacy. 0.11% aerosol coatings.

B 2461800000 Solvent Utilization;Miscellaneous Non - industrial: Commercial;Pesticide Application: All Processes 3001 is speciation profile (not leg acy) "D" rating 2004. Calif. Testing for speciation profile from 2000. Has NO benzene! Benzene came from solvent utilization data (Fredonia) for "other markets" for the year 1998. M 2460800000 Solvent Utilization;Miscellaneous Non - industrial: Consumer and Commercial;All FIFRA Related Products 3145 has M only and just a 0.01%50 Deliberative

– Do Not Cite or Quote For the alm_no_c3 sector , the integration criteria were (1) that the source had to have at least one of the 4 HAPs and (2) that the sum of BAFM could not exceed the VOC emissions. The criteria for this sector were less complex than the nonpt sector because it has much fewer sourc e categories. We used the SMOKE feature to compute speciation profiles from mixtures of other profiles in user- specified proportions. The combinations 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 b y modeling ye ar ( 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 ty pe) and M_TYPE (m erge type) settings and (b) the ancillary data files described in Section 3.2.3 . The one change made from the v4 to the v4. 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. Inthe 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 process es .51 Deliberative

– Do Not Cite or Quote Table 3 - 6 . Temporal s ettings u sed for the platform s ectors in SMOKE , v4.2 platform Platform sector short name (see Table 2 - 1) Inventory

resolution Monthly

profiles used? Daily

temporal approach 1,2 Merge

processing approach 1,3 Process

Holidays as separate days? p tipm daily & hourly all all yes ptnonipm annual yes mwdss all yes o thpt annual yes mwdss all nonroad monthly mwdss mwdss yes o thar annual yes mwdss mwdss alm_no_c3 annual yes mwdss mwdss seca_c3 annual yes mwdss mwdss on_noadj monthly week week yes on_moves_startpm monthly week week yes on_moves_runpm monthly week week yes o thon annual yes week week nonpt annual yes mwdss mwdss yes ag annual yes aveday aveday afdust annual yes week week yes b iog 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 mo nth, which means emissions have day - of - week variation, but not week - to - week variation within the mo nth 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 mo nth. 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 . T he values given are the values of the L_TYPE setting. 3 Merge processing approach refers to the days used to represent other days in the month for the merge step. If not “all”, then the SMOKE merge step just run for 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, 200 5 , which is intended to mitigate the effects of initial condition concentrations. The same procedures were used for all grids, but with different ramp -up periods for each grid:

 36 km: 10 days (Dec 22 - Dec 31)  12 km (East): 3 days (Dec 29 - Dec 31) 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 emissions52 Deliberative

– Do Not Cite or Quote (representative days) for D ecember 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 200 5 v4. 2 platform . The ancillary data files , particularl y the cross - reference files, provide the specific inventory resolution at which spatial , speciation, and temporal factors are applied. For the 200 5 v4. 2 platform , we generally applied spatial factors b y country/SCC, speciation factors by pollutant/SCC or (for combination profiles) state/county FIPS code and month , and temporal factors b y some combination of country, state, county, SCC, and pollutant. For the v4. 2 platform, w e 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, temp oral and speciation profiles to parking area emissions for additional vehicle ty

pes (new data from MOVES 2010) and updated previous assignments for some vehicle typ es (summarized in Table 3 - 14 and Table 3 - 15 5 ). 3. We updated the headspace VOC speciation profile we used for refueling. 4. We used a new profile for speciating PM 2.5 from C3 marine emissions. 

### 3.2.1 Spatial a llocation d ata 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 surrogate s and a SMOKE area- to -point data file . For the U.S. and Mexico, we used the same spatial surrogates as were used for the 2002 v3 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 web site s listed at the end of Section 1. The oil and natural gas surrogate files are posted at the 2005v4 .1 website. The following list of seven files provides descriptions of each of their content s and intended uses for the v4.2 platform.  36km_surg_2002v3mpCAP_smokeformat.zip : U.S. and Mexican surrogate files for 36 - km spatial resolution ( Canadian data contained in this zip file was not used for the 2005 -based platform). This data can be found on the 2002v3 website under “Data Files” at: ftp://ftp.epa.gov/EmisInventory /2002v3CAP/anci llary

_smoke/ .  12km_surg_2002v3mpCAP_smokeformat.zip : U.S. and Mexican surrogate files for surrogate files for 12 km spatial resolution (Canadian data contained in this zip file was not used for the 2005 -based platform). This data can be found on the 2002v3 website under “Data Files” at: ftp://ftp.epa.gov/EmisInventory /2002v3CAP/ancillary

_smoke/ .  new36km_surg_200 5v4_smokeformat.zip : Canadian surrogate files for 36 - km spatial resolution for Canadian surrogates . This data can be found on the 2005v4 website under “2005 Emissions Data Files” at: ftp://ftp.epa.gov/EmisInventory /2005v4/ancillary

_smoke/ .53 Deliberative

– Do Not Cite or Quote  new 12km_surg_200 5 v4_smokeformat.zip : Canadian surrogate files for 12 - km spatial resolution for Canadian surrogates . This data can be found on the 2005v4 website under “2005 Emissions Data Files” at: ftp://ftp.epa.gov/EmisInventory /2005v4/ancillary

_smoke/ .  new_oilgas_surg_2005v4_1_smokeformat.zip : Oil and gas surrogate files for 36 - km spatial resolution and 12 - km spatial resolution for the new oil and gas surrogate (US) . This data can be found on the 2005v4.1 website under “2005 Emissions Data Files” at: ftp://ftp.epa.gov/EmisInventory /2005v4.1/ancillary

_smoke/ .  ancillary_200 5v4_2_smokeformat.zip : spatial related data included are the grid description (GRIDDESC), surrogate description (SRGDESC), surrogate cross reference file (AGREF), and area- to -point (ARTOPNT) file. This data is provided on the 2005v4.2 website under “2005 Emissions Data Files” at: ftp://ftp.epa.gov/EmisInventory /2005v4.2/ancillary

_smoke/ . The U.S., Mexican , and Canadian 12 - km surrogates cover the entire CONUS domain, though they are used directl y as inputs for the two separate Eastern and Western Domains shown in Figure 3 - 1 . The SMOKE model windowed the Eastern and Western grids while it created these emissions. The remainder of this sub section provides further detail on the origin of the data used for the spatial surrogates and the area- to -point data. 3.2.1.1 Surrogates for U.S. e missions There are 6 7 spatial surrogates available for spatially allocating U.S. county- level emissions to the 36 - km and 12 - km grid cells used b y 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 p latform . Code Surrogate Description Code Surrogate Description N/A Area - to -point approach (see 3. 3 .1.2) 515 Commercial plus Institutional Land 100 Population 520 Commercial plus Industrial plus Institutional 110 Housing 525 Golf Courses + Institutional + Industrial + Commercial 120 Urban Population 527 Single Family Residential 130 Rural Population 530 Residential - High Density 137 Housing Change 535 Residential + Commercial + Industrial + Institutional + Government 140 Housing Change and Population 540 Retail Trade 150 Residential Heating - Natural Gas 545 Personal Repair 160 Residential Heating - Wood 550 Retail Trade plus Personal Repair 165 0.5 Residential Heating - Wood plus 0.5 Low Intensity Residential 555 Professional/Technical plus General Government 170 Residential Heating - Distillate Oil 560 Hospital 180 Residential Heating - Coal 565 Medical Office/Clinic54 Deliberative

– Do Not Cite or Quote Code Surrogate Description Code Surrogate Description 190 Residential Heating - LP Gas 570 Heavy and High Tech Industrial 200 Urban Primary Road Miles 575 Light and High Tech Industrial 210 Rural Primary Road Miles 580 Food, Drug, Chemical Industrial 220 Urban Secondary Road Miles 585 Metals and Minerals Industrial 230 Rural Secondary Road Miles 590 Heavy Industrial 240 Total Road Miles 595 Light Industrial 250 Urban Primary plus Rural Primary 596 Industrial plus Institutional plus Hospitals 255 0.75 Total Roadway Miles plus 0.25 Population 600 Gas Stations 260 Total Railroad Miles 650 Refineries and Tank Farms 270 Class 1 Railroad Miles 675 Refineries and Tank Farms and Gas Stations 280 Class 2 and 3 Railroad Miles 680 Oil & Gas Wells, IHS Energy, Inc. and USGS 300 Lo w Intensity Residential 700 Airport Areas 310 Total Agriculture 710 Airport Points 312 Orchards/Vineyards 720 Military Airports 320 Forest Land 800 Marine Ports 330 Strip Mines/Quarries 807 Navigable Waterway Miles 340 Land 810 Navigable Waterway Activity 350 Water 850 Golf Courses 400 Rural Land Area 860 Mines 500 Commercial Land 870 Wastewater Treatment Facilities 505 Industrial Land 880 Drycleaners 510 Commercial plus Industrial 890 Commercial Timber We did not use all of the available surrogates to spatially allocate sources in the v4 . 2 p latf orm; 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 2002 v3 platform documentation and is not repeated here. The tool and u pdated documentation for it is available at http://www.ie.unc.edu/cempd/projects/mims/spatial/ and http://www.cmascenter.org/help/documentation.cfm?MODEL=spatial_allocator&VERSION=3. 6&temp_id=99999 . This same tool was used for the new 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 thi s surrogate is a grid of one - quarter square mile cells containing an attribute to indicate whether the we lls within the cell are predominantl y 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. More information can be obtained from http://pubs.usgs.gov/dds/dds 069/dds - 069 - q/text/layer.htm and55 Deliberative

– Do Not Cite or Quote http://certmapper.cr.usgs.gov/rooms/uti lities/layer_info.jsp?docId={A90AF432 - 612F - 41F9 - A315 - 7329FD933FB3}&type=download&docURL=http://certmapper.cr.usgs.gov/data/noga00/natl/sp atial/doc/uscells05g.htm The spatial cross - reference file was also updated to assign onroad off - network (parking area) emissions from the MOVES 2010 model , new to the 2005 v4 platform, were allocated as shown in Table 3 - 8 . Table 3 - 8 . Surrogate assignments to new mobile categories in the 2005 v4 platform

SCC & Description Surrogate 2201001350 Light Duty Gas Vehicles - parking areas rural 2201002350 Light Duty Gas Trucks 1&2 - parking areas rural 2201004350 Light Duty Gas Trucks 3&4 - parking areas rural Rural population (same as rural local roads), code= 130 2201001370 Light Duty Gas Vehicles - parking areas urban 2201002370 Light Duty Gas Trucks 1&2 - parking areas urban 2201004370 Light Duty Gas Trucks 3&4 - parking areas urban Urban population (same as urban local roads), code =120 2201070350 Heavy Duty Gasoline Vehicles 2B through 8B & Buses

(HDGV) - parking areas rural 2201070370 Heavy Duty Gasoline Vehicles 2B through 8B & Buses

(HDGV) - parking areas urban Commercial plus Industrial plus Institutional , code = 520 3.2.1.2 Al location m ethod for a irport - related s ource s in the U.S. There are numerous airport- related emission sources in the 200 5 NEI, such as aircraft, airport ground support equipment , and jet refueling. Unlike the 2002 v3 platform in which most of these emissions were contained in sectors with county- level resolution

– alm (aircraft), nonroad (airport ground support) and nonpt (jet refueling), the 2005 platform includes the aircraft emissions as point sources . As shown in Table 2 - 1 , aircraft emissions are part of the ptnonipm sector, since the 2005v2 inventory included them as point sources. Thus , for the 2005 platform , we use d the SMOKE “area- to -point” approach for only airport ground support equipment (nonroad sector), and jet refueling (nonpt sector). The approach is described in detail in the 2002 platform documentation : http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol1_02 - 28 - 08.pdf . We used nearl y the same ARTOPNT file to implement the area- to -point approach as was used for the C AP and HAP - 2002 - Based platform . This was slightl y 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.56 Deliberative

– Do Not Cite or Quote 3.2.1.3 Surrogates for Canada and Mexico e mission i nventories We used an updated set of surrogates for Canad a to spatially allocate the 2006 Canadian emissions for the 200 5 v4 platform . The updated set completely replaced the 2002 v3 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 T ool (previous ly referenced) . Per Environment Canada, the surrogates are based on 2001 Canadian census data . We changed the cross references that Canada originall y provided as follows: all assignments to surrogate '978' (manufacturing industries) were changed to '906' (manufacturing services ) , and all assignments to '985' (construction and mining) and ‘9 8 4’ (construction industries) were changed to '907' (construction services) because the surrogate fractions in 984, 978 and 985 did not sum to 1 . We also changed codes for surrogates other than population that did not 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 Sp atial 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 Upstream O il and G as (UOG) CA_904_NOFILL.txt dow nstream_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 wa ste 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.txt57 Deliberative

– Do Not Cite or Quote Surrogate description Filename of 2005

Platform Surrogate Surrogate description Filename of 2005

Platform Surrogate Intersection of UTILITIES and DWELLING CA_924_NOFILL.txt dow nstream petroleum industries CA_975_FILL.txt Intersection of CONSTRUCTION and DWELLING CA_925_NOFILL.txt Electric utilities CA_976_FILL.txt Intersection of PUBADMIN and DWELLING CA_926_NOFILL.txt grain industries CA_977_FILL.txt Commercial Marine Vessels CA_928_NOFILL.txt manufacturing industries 1 CA_978_FILL.txt HIGHJET CA_929_NOFILL.txt mining industries CA_979_FILL.txt LOWMEDJET CA_930_NOFILL.txt smelting industries CA_981_FILL.txt OTHERJET CA_931_NOFILL.txt wa ste management CA_982_NOFILL.txt CANRAIL CA_932_NOFILL.txt construction industries 1 CA_984_NOFILL.txt LDGV CA_934_NOFILL.txt construction and mining 1 CA_985_NOFILL.txt PAVED ROADS CA_941_NOFILL.txt TO TALBEEF 2 CA_986_NOFILL.txt 2 UNPAVED ROADS CA_942_NOFILL.txt TO TALPOUL 2 CA_987_NOFILL.txt2 Oil Sands CA_950_NOFILL.txt TO TALSWIN 2 CA_988_NOFILL.txt2 TO TALFERT 2 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 platform s . 

### 3.2.2 Chemical speciation ancillary files The following data file s , provided at the 200 5v4 .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 c apital letters in parentheses:

 ancillary_200 5 v4

_2_smokeformat.zip: inventory table (INVTABLE), NONHAPVOC emissions calculation exclusions file (NHAPEXCLUDE), speciation cross reference s (GSREF), speciation VOC - to - TOG conversion factors (GSCNV) , speciation profiles (GSPRO) , and combined, monthly speciation profiles (GSPRO_COMBO) .  ancillary_2005v4

_2_futureyear_sm okeformat.zip: speciation - related files associated with the future - ye ar speciation changes. The following subsections explain these SMOKE input files. 3.2.2.1 INVA BLE and NHA PEXCLUDE 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 p latform.58 Deliberative

– Do Not Cite or Quote We prepared two different I NVTABLE files to use with different sectors of the platform. For sectors in which we chose no integration across the entire sector (see Table 3 - 5 ), we created a “no HAP use” INVTABLE that set the “KEEP” flag to “N” for BAFM pollutants . Thus, any BAFM pollutants in the inventory input into SMOKE would be dropped. This approach both av oids 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 (b y setting the “VOC or TOG component” field to “V” for all four HAP pollutants. We also prepared sector - specific NHAP EXCLUDE files that provide the specific sources that are excluded from integration (see Table 3 - 5 ). 3.2.2.2 GSPRO, GSPRO_ COMBO , GSREF and GSCNV For VOC speciation, we generated the following SMOKE - ready profiles for the CB05 ch emical mechanism using the Speciation Tool (Ey th, 200 6 ) :  TOG - to - model species (used only for no - integrate sources)  NONHAPTOG - to - model species (used onl y 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, respectivel y. These profiles were used onl y for the integrate sources. Note that we process the integrate and no - integrate sources using the same GSREF and GSPRO files. Thus, to avoid double counting of these HAP species, we removed BAFM pollutants for all no - integrate sources in the inventory . If the entire sector was no - integrate, then we were able to remove these in SMOKE (by

using “N” in the INVTABLE) but if a sector was partiall y 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 N ONHAPVOC - to NONHAPTOG conversion factors . The TOG and PM 2.5 speciation factors that are the basis of the chemical speciation approach were developed from the SPECIATE4. 2 database (http://www.epa.gov/ttn/chief/software/speciate/index.html ) which is 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 i s a collaboration involving the EPA ’s ORD , OTAQ, and the EPA ’s Office of Air Quality Planning and Standards (OAQPS) , and59 Deliberative

– Do Not Cite or Quote Environment Canada (EPA, 2006 a). The SPE CIATE database contains speciation profiles for TOG, speciated into individual chemical compounds, VOC - to - TOG conversion factors associated with the TOG profiles, and speciation profiles for PM 2.5 . The database also contains the PM 2.5 speciated into both individual chemical compounds (e.g., zinc, potassium, manganese, lead), and into the “simplified” PM 2.5 components used in the air quality model. These simplified components are:

 PSO4 : primary

particulate sulfate  PNO3: primary

particulate nitrate  PEC : primary

particulate elemental carbon  POC: primary

particulate organic carbon  PMFINE: other primary particulate, less than 2.5 micrograms in diameter As discussed earlier, for the v4. 2 platform we updated the PM 2.5 profile used for category 3 marine vessels burning residual oil to use the profile: Marine Vessel - Main Engine - Heavy Fuel Oil which will be published in SPECIATE4.3. This profile was compiled from data published in Emission Measurements from a Crude O il 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 Ty pes 228 0003010 Mobile Sources;Marine Vessels, Commerci al;Residual;Ocean - going Vessels 2280003100 Mobile Sources;Marine Vessels, Commercial;Residual;Port emissions 2280003200 Mobile Sources;Marine Vessels, Commercial;Residual;Underway emissions The difference between the two profiles is provided in Table 3 - 10 , and shows that the new profile produces much more organic carbon and less elemental carbon, sulfate, and other PM 2 .5 . Table 3 - 10 . Differences between two profiles used for c ommercial m arine residual o il P ollutant S pecies Split fa ctors new c3 profile 92 200 used for v4. 2 S plit factors residual oil combustion 92072 , used fo r v4 PM2_5 PEC 0.0 05 0.01 PM2_5 PMFINE 0. 5022 0. 54 PM2_5 PNO3 0 0 PM2_5 POC 0. 1125 0. 01 PM2_5 PSO4 0. 3803 0. 44 We also updated the bituminous coal profile, 92095, which we had previously used for only

a single nonpoint SCC (2101002000) with the sub - bituminous profile 92084, which was used for all other coal combustion SCCs. We replaced profile 92095 with 92084 for consistency . Table 3 - 11 shows the differences are shown below , though these are quite small and represent only a minor change to the SMOKE results :60 Deliberative

– Do Not Cite or Quote Table 3 - 11 . Differences between two profiles used for coal combustion P ollutant S pecies Split fa ctors sub bituminous 92084 S plit factors bituminous 920 9 5 PM2_5 PEC 0.0188 0.01696 PM2_5 PMFINE 0.8266 0.827928 PM2_5 PNO3 0.0016 0.00208 PM2_5 POC 0.0263 0.026307 PM2_5 PSO4 0.1267 0.126725 We made other updates to profile assignments for the SCCs shown in Table 3 - 12 below as compared to the 2002 platform . These updates were kept for the v4. 2 platform .

Table 3 - 12 : PM 2.5 speciation profile updates assignments for the v4 platform SCC New

Profile Code Pollutant Profile Name 39900501 92025 PM2_5 Distillate Oil Combustion Source Type: Distillate Oil Combustion 49090021 92025 PM2_5 Distillate Oil Combustion Source Type: Distillate Oil Combustion 30890002 92072 PM2_5 Residential Oil Combustion Source Type: Residential Oil Combustion 10100912 92091 PM2_5 Wood Fired Boiler Source Type: Wood/Bark Combustion 10102018 92057 PM2_5 PM/SO2 controlled lignite combustion: Waste Coal Combustion 50410563 92082 PM2_5 Solid Waste Combustion Source Type: Solid Waste Combustion 10100692 92048 PM2_5 Natural Gas Combustion Source Type: Natural Gas Combustion 50100511 92086 PM2_5 Tire Burning Source Type: Tire Burning 50100512 92082 PM2_5 Solid Waste Combustion: Solid Waste Combustion 2810040000 92035 PM2_5 HDDV Source Type: Aircraft Engines Key changes to the TOG profiles for the v4. 2 platform from the 2005v4 platform are as follows:  Used new headspace profiles for E0 (no ethanol gasoline) and E10 (10% ethano l 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 - ye ar 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 - 15 5 for diesel vehicles. Table 3 - 13 provides a summary of the 2005 sp eciation approach for mobile and other fuel related sources. It shows the updated profiles that form the 2005 combinations. The headspace61 Deliberative

– Do Not Cite or Quote profile , 87 62 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 b y s ector for 2005 Inventory type and mode VOC speciation approach for fuels VOC

Profile Codes 2005

sectors Mobile onroad and nonroad Exhaust E0 and E10 combinations (excludes Tier 2) 8750 8751 on_noadj

nonroad Mobile onroad and nonroad Evaporative E0 and E10 combinations 8753 8754 on_noadj

nonroad Mobile nonroad Refueling Stationary (no mode assigned to VOC) : P ortable Fuel Containers, bulk plant - to pump, refinery- to -bulk terminal E0 87 62 Nonroad nonpt In future ye ars, 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 - ye ar scenarios will be discussed in more detail in the documentation of future - year emissions development for the rule or application of interest . Insummary, we utilized additional profiles in the combinations that is appropriate . The profiles we added were Tier 2 profiles for E0 and E10 and an E10 headspace profile. Speciation profiles for use with BEIS are not included in SPECIATE. The 2005 platform uses BEIS3.14 , which includes a new species (SESQ) that was not in BEIS3.13 (the version used for the 2002 platform). Thus we added this species (it is mapped to the model species SESQT) to the set of profiles that we had been using in the 2002 platform . The profile c ode associated with BEIS3.1 4 profiles for use with CB05 uses the same as in the 2002 platform : “B10C5.” 

### 3.2.3 Temporal allocation ancillary files The emissions modeling step for temporal allocation creates the 200 5 hourly emission inputs for the air quality

mode l 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, weekl y, and diurnal temporal profiles and associated cross references used to create the 200 5 hourl y emissions inputs for the air quality model were generall y based on the temp oral allocation data used for the 200 2 v3 platform . For the v4 and v4. 2 platforms, w e added new profile assignments for SCCs in the 2005 inventory that were not in the 200 2 inventory, and we updated the profiles used for ptipm sources without CEM data to represent the year 2005 .62 Deliberative

– Do Not Cite or Quote The following data file, provided at the 2005v4 web site (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, an d 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 discuss es the development of the new temporal profiles or profile assignments used in the 2005 v4 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 hourl y profile (code 26) that put emissions in every hour, but weighted towards the day light hours. Diurnal Profiles for Electric Generating Units (ptipm) We updated the state - specific and pollutant- specific diurnal profiles for use in allocating the dayspecific emissions for non - CEM sources in the ptipm sector. We used the 2005 CEM data to create state - specific, day- to - hour factors, averaged over the whol e ye ar and all units in each state. We calculated the diurnal factors using CEM SO 2 and NO X emissions and heat input. We computed SO 2 and NO X - specific factors from the CEM data for these pollutants. All other pollutants used factors created from the hourl y heat input data. We assigned the resulting profiles b y 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 (c ode 262 and 7 respectivel y) 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/ins titutional construction, road construction, mining and quarrying, and agricultural production (planting, tilling, harvesting, and loading).63 Deliberative

– Do Not Cite or Quote Diurnal weekday

and weekend temporal profiles were changed from a simple bell curve profile (code 26) for all categ ories in v4 to a more dy namic 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, day

time 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 respectivel y) 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 pl atform v4.2. Onroad Parking Area Profiles The SCCs and descriptions, along with the assignments chosen are shown in Table 3 - 14 (ga soline vehicles) and Table 3 - 15 5 (diesel vehicles) . Figure 3 - 3 and Figure 3 - 4 show the diurnal profiles referred to in the table s . Figure 3 -3 . Diurnal Profiles based on road type (use local for “start”) and whether the road is urban v ersus rural Weekday Di urnal

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0 2 4 6 8 10 12 14 16 18 20 22 Hourof Day Rural Local: code = 2006 Ur ban Local: code = 2012 We eken d Diurnal (same code s)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

0 2 4 6 8 10 12 14 16 18 20 2264 Deliberative

– Do Not Cite or Quote Figure 3 - 4 . Diurnal temporal profile for HDDV 2B through 8B at Parking areas

0 100 200 300 400 500 600 700

hr0 hr1 hr2 hr3 hr4 hr5 hr6 hr 7 hr8 hr 9 hr10 hr11 hr12 hr13 hr14 hr15 hr 16 hr17 hr 18 hr19 hr 20 hr21 hr 22 hr23 We eken d and We ek day diurnal pr of ile s used forH DDV (exc ept school/transi t buses) At ur ban and ru ral parki ngare as (i .e., idlin g emi ssi ons) prof ile co de = 300065 Deliberative

– Do Not Cite or Quote Table 3 - 14 . Summary

of spatial surrogates , t emporal profiles , and speciation profiles used b y gasoline vehicle type s for the onroad p arking area- related SCCs. GASOLINE VEHICLE TYPES SCC&Description Surrogate Temporal Profile: Monthly Variation Temporal Profile:

Day of Week Variation Temporal Profile: Diurnal variation Speciation Profile 2201001350 Light Duty Gas Vehicles - parking areas rural 2201020350 Light Duty Gas Trucks 1&2 - parking areas rural 2201040350 Light Duty Gas Trucks 3&4 - parking areas rural 2201080370 Motorcycles (MC) - parking areas rural Rural

Population (same as rural local roads) 130 Not

applicable

– inventory contains monthly emissions RURAL LD values are:

Mon

–Fri 12.1% 1 2.1% 12.1% 12.1% 18.3% Sat/Sun: 15.3% 18.3% Weekly_code (for SMOKE) =20021 Use same as profile as rural local roads (Rdtype=210) . Code = 2006 (see Figure 3 - 3 , reddish curve) Use same speciation profiles as what is used for LD GAS

vehicles on the other roadway types. * i.e.: EVP__VOC: COMBO of 8753 (Gasoline Vehicle - Evaporative emission - Reformulated gasoline) & 8754 (Gasoline Vehicle - Evaporative emission - E10 ethanol gasoline) Note that these are the combinations used in 2005. In some cases , future - year profiles may also include 8755 (Gasoline Vehicle - Evaporative emission - E85) EXH__VOC: COMBO of 8750&8751 These combinations are used in 2005. In some cases , future - year profiles may also include combinations of 8752 (E85) , 8756 (tier 2 exhaust, E0), 8757 (tier 2 exhaust, E10) EXH__PM2.5 not needed because OTAQ supplies pre speciated emissions BRK_PM2.5 and TIR_PM2.5 use same as other roadways (92009 and 92087, respectively) 2201001370 Light Duty Gas Vehicles - parking areas urban 2201020370 Light Duty Gas Trucks 1&2 - parking areas urban 2201040370 Light Duty Gas Trucks 3&4 - parking areas urban 2201080370 Urban

Population (same as urban local roads) 120 Not

applicable

– inventory contains monthly emissions URBAN LD values are:

Mon - Fri 14.8% 14.8% 14.8% 14.8% 16.0% Sat Sun 13.4% and 11.6% Weekly_code (for SMOKE) =20031 Use same as profile as urban local roads . (Rdtype=330) . Code = 2012 (see Figure 3 - 3 , yellow curve) Same as above66 Deliberative

– Do Not Cite or Quote GASOLINE VEHICLE TYPES SCC&Description Surrogate Temporal Profile: Monthly Variation Temporal Profile:

Day of Week Variation Temporal Profile: Diurnal variation Speciation Profile Motorcycles (MC) - parking areas rural 2201070350 Heavy Duty Gasoline Vehicles 2B 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 above67 Deliberative

– Do Not Cite or Quote Table 3 - 15 . Summary

of spatial surrogates , temporal profiles , and speciation profiles used b y diesel vehicle type s for the onroad

p arking area- related SCCs from MOVES2010 .

DIESEL VEHICLE TYPES SCC&Description Surrogate Temporal Profile: Monthly Variation Temporal Profile:

Day of Week Variation Temporal Profile: Diurnal variation Speciation Profile 2230001350 Light Duty Diesel Vehicles (LDDV) - parking areas rural 2230060350 Light Duty Diesel Trucks 1 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 above68 Deliberative

– Do Not Cite or Quote

DIESEL VEHICLE TYPES SCC&Description Surrogate Temporal Profile: Monthly Variation Temporal Profile:

Day of Week Variation Temporal Profile: Diurnal variation Speciation Profile 2230071350 Heavy Duty Diesel Vehicles (HDDV) Class 2B parking areas rural 2230072350 Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5 - parking areas rural 2230073350 Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7 - parking areas rural 2230074350 Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B parking areas rural Rural primary roads code=210 Rationale: most idling will occur at truckstops Not

applicable

– inventory contains monthly 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 2230074370 Heavy Duty Diesel Vehic les (HDDV) Class 8A & 8B parking areas urban URBAN primary roads code=200 Rationale: most idling will occur at truckstops Not

applicable

– inventory contains monthly emissions URBAN LD values are:

Mon - Fri 14.8% 14.8% 14.8% 14.8% 16.0% Sat Sun 13.4% and 11.6% Weekly_code (for SMOKE) =20031 Construct new profile CODE=3000 which is low at daytime and high at night - time (11pm to 2am) See Figure 3 - 4 Same as above69 Deliberative

– Do Not Cite or Quote

DIESEL VEHICLE TYPES SCC&Description Surrogate Temporal Profile: Monthly Variation Temporal Profile:

Day of Week Variation Temporal Profile: Diurnal variation Speciation Profile 2230075350 Heavy Duty Diesel Buses (School & Transit) - parking areas rural Rural Population (same as rural local roads) 130 Not

applicable

– inventory contains monthly emissions USE URBAN LD values:

Mon - Fri 14.8% 14.8% 14.8% 14.8% 16.0% Sat Sun 13.4% and 11.6% Weekly_code (for SMOKE) =20031 Rationale: these vehicles follow profile of LD vehicles better than HD; day of week variation should more closely follow urban (higher weekday than weekend) Use same as profile as rural local roads (Rdtype=210) . Code = 2006 (see Figure 3 - 3 , reddish curve) Rationale: choose same diurnal profile for all vehicles (except HDDV 2B to 8B) for all rural parking areas (which is the profile used for rural local roads) Same as above

2230075370 Heavy Duty Diesel Buses (School & Transit) - parking areas urban URBAN Population (same as ur ban 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 above70 Deliberative

– Do Not Cite or Quote 

## 4 De velopment of 2012 and 2014 Base - Case Emissions This section describes the methods we used for developing the 2012 and 2014 future - ye ar 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, respectivel y. The ancillary input data in the future - ye ar 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. Appendix B provides a table of differences between these ancillary input data between the 2005 base case and these future - year scenarios. 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 De cember 1, 2010 . For mobile sources (on_noadj, on_moves_runpm, and on_moves_startpm 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 PM 2.5 NAAQS annual standard, 2006 PM NAAQS (24 - hour) standard, and the 1997 ozone NAAQS are generall y 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 e stimates from IPM, version 4.10.  N on - IP M 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 proje cted 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 liv estock estimates based on expected changes in animal population from 2005 Department of Agriculture data ; no growth or control for NH 3 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.71 Deliberative

– Do Not Cite or Quote  Remaining Nonpoint sector (nonpt): Projection factors that implement Transport Rule Proposal comments and reflect emis sion 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 (MSAT 2) 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 nonCalifornia 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 - ye ar equipment population estimates and control programs to the ye ars 2012 and 201 5 and using national level inputs . Year 2014 emissions were created by interpolating 2012 and 2015 emissions. F inal controls from the final locomotive - marine and small spark ignition OTAQ rules are included . California- specific data provided by the state of California, except NH 3 used 2012 and 201 4 (interpolated) NMIM. Year - specific speciation was applied to some portions of this sector and is discussed in Section 4. 3 . 5 .  L ocomotive, 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): B ase - ye ar 200 5 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 NO X and SO 2 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 201 2 and NMIM 2015 emissions estimates . Temperature impacts at the monthly average resolution. California- specific data provided by the state of California , except NH 3 which was obtained from MOVES2010 . VOC speciation uses different future - ye ar 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 on_moves_startpm and on_moves_runpm sectors .  Onroad PM gasoline running mode sector (on_moves_startpm): Running mode MOVES2010 ye ar 2012 and 2014 future - year state - month estimates for PM and naphthalene, apportioned to the county level using NM IM201 2 and NMIM 201 5 state - county ratios matched to vehicle and road typ es. Use future - ye ar 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 - ye ar 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 - ye ar temperature adjustment file for adjusting the 72 ° F emissions (f or elemental and organic carbon) to ambient temperatures based on grid cell hourly temperature s (lower temperatures result in increased emissions).  Other nonroad/nonpoint (othar): No growth or control.  Other onroad sector (othon): No growth or control.72 Deliberative

– Do Not Cite or Quote  Other nonroad/nonpoint (othar): No growth or control.  Other p oint (othpt): No growth or control.  Biogenic: 2005 emissions used for all future - ye ar 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 2005 v4.2 base - case inventories. All Mexico, Canada, and offshore oil emissions are unchanged in all future case s 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 pollutants column; however, we did not include Hg in our v4.2 modeling. Note that a few controls are not fully promulgated b y 2012 but are b y 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 reflecte d in the 2012 base c ase but is reflected in the 2014 base and control cases. A list of control, closures, projection packets (datasets) we used to create Transport Rule 2012 and 2014 future ye ar base - case scenario inventories from the 2005 base case is provided in Appendix D, Table D - 1. Additional summaries of these various control programs that were too large to include in this section are also provided in Appendix D. The remainder of this section is organized either by source sector or b y 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 containe d 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 categorie s are provided in parentheses.73 Deliberative

– Do Not Cite or Quote 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 ( g rouped by a ffected p ollutants or s tandard and approach u sed to app ly to the i nventory) Pollutants a ffected Approach/

Reference Non - EGU Point (pt nonipm sector) p rojection approaches carried f orward from the Proposed Transport Rule MACT rules, national, VOC: national applied by SCC, MACT Boat Manufacturing (promulgated in year 2013, thus not reflected in the 2012 base case) 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- Gasoli ne) Refractory Products Manufacturing Sites Remediation VOC EPA, 2007 a

Consent decrees on c om

panies (based on information from the Office of Enforcement and Compliance Assurance

– OECA) apportioned to plants owned/operated by the c om panies VOC, CO, NOx, PM, SO 2 1 DOJ 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, SO 2 3 Hazardous Waste Combustion PM 4 Municipal Waste Combustor Reductions

– plant level PM 5 Hospital/Medical/Infectious Waste Incinerator Regulations NO X , PM, SO 2 EPA, 2005 b 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 & SO 2 : Lime Manufacturing PM, SO 2 7 MACT rules, plant - level, PM: Taconite Ore PM 8 Additional p rojections u sed i n the final T ransport Rule modeling for non - EGU point sources (ptnonipm sector) NESHAP: Portland Cement ( 09/09/10)

– plant level 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 Hg, NO X , SO2, PM, HCl 13 ; EPA , 201074 Deliberative

– Do Not Cite or Quote closures . (promulgated in year 2013, thus only known closures and new units through year 2009 were included for year 2012

– ISIS - based future -

year projections included only for 2014 ) New York o zone SIP c ontrols VOC, NO X , HAP VOC 14 Additional p lant 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. NO X , SO 2 , HCl Section 4 .2.6 Reciprocating Internal Combustion Engines (RICE) NESHAP: ( SO2 controls for RICE are not effective until after 2012, but are applied in 2014 ) NO X , CO, PM , SO 2 15 Replaced 2005 with 2008 emissions for Corn Products International, Cook C ounty, 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 (ILE PA) All 1 6 State fuel sulfur content rules for fuel oil

–effective only in Maine and New York in 2014 SO 2 1 7 Nonpoint ( nonpt sector) p rojection approaches carried f orward from the Proposed Transport Rule Municipal Waste Landfills: projection factor of 0.25 applied All EPA, 2007 a Livestock Emissions Growth from year 2002 to year 201 2 and 2014 NH3, PM 9 Residential Wood Combustion Grow th and Change - outs from year 2005 to year 201 2 and 2014 All 10 Gasoline Stage II growth and control from year 2005 to year 201 2 and 2014 VOC 11 Portable Fuel Container Mobile Source Air Toxics Rule 2 ( MSAT2 ) inventory grow th and control from year 2005 to year 2012 and 201 4 VOC 12 Additional p rojections used i n the final T ransport Rule modeling for Nonpoint sources (nonpt sector) RICE NESHAP: (

SO2 controls for RICE are not effective until after 2012, but are applied in 2014

) NO X , CO, VOC, PM , SO 2 15 Use Phase II WRAP 2005 Oil and Gas, but apply year 2012 - and year 2014 - specif i c RICE controls to these emissions VOC, SO 2 , NO X , CO Section 3.2.7 Use 2008 Oklahoma and Texas Oil and Gas, and apply year 2012 - and year 2014 - specif i c RICE controls to these emissions . VOC, SO 2 , NO X , CO, PM Section 3.2.7 New York , Connecticut, and Virginia ozone SIP controls VOC 1 4, 1 8 State fuel sulfur content rules for fuel oil

–effective only in Maine and New York in 2014 SO 2 1 7 APPROACHES/REFERENCES - Stationary Sources : 1. Appendix B in the Proposed Toxics Rule TSD: http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf 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 - H azardous W aste 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, 2007 a 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. SO 2 percent reduction are computed by 6 , 147/30,783 = 20 % and PM 10 and PM 2.5 reductions are computed by 3 , 786/13 , 588 = 28% 8. Same approach as used in the 2006 Clean Air Interstate Rule (CAIR) , which estimate d 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 from75 Deliberative

– Do Not Cite or Quote CAIR : http://www.envinfo.com/caain/June04updates/tiop_fr2.pdf 9. Except for dairy cows and turkeys (no growth), based o n animal population growth estimates from the US D epartment of Agriculture (USDA) and the Food and Agriculture Policy and Research Institute. See Section 3.2.1. 10. Grow th and Decline in woodstove types based on industry trade group data, See S ection . 11. VOC emission ratios of year 20 16 (linear interpolation between 2015 and 2020) - specific from year 2005 from the National Mobile Inventory Model (NMIM ) results for onroad refueling including activity grow th 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 20 16 (linear interpolation between 2015 and 2020) from year 2002 from MSAT2 rule (EPA, 2007 b ) 13. Data files for the cement sector provided by Elineth Torres, the EPA - SPPD, fro m the analysis done for the Cement NES HAP: 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 5496 9 - 55066 14. New York NO X and VOC reductions obtained from Appendix J in NY Department of Environmental Conservation Im plementation Plan for Ozone (February 2008): http://www.dec.ny.gov/docs/air_pdf/NYMASIP7final.pdf . See Section 3.2.6. 15. Appendix F in the Proposed Toxics Rule TSD: http://www.epa.gov/ttn/chief/emch/toxics/propo sed_toxics_rule_appendices.pdf 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: http://www.ilta.org/LegislativeandRegulatory/MVNRLM/NEUSASulfur%20Rules_09.2010.pdf , http://www.mainelegislature.org/legis/bills/bills_124th/billpdfs/SP062701.pdf , http://switchboard.nrdc.org/blogs/rkassel/governor_paterson_signs_ne w_la.html , http://green.blogs.nytimes.com/2010/07/20/new- york- mandates - cleaner -heating - oil/ 18. VOC reductions in Connecticut and Virginia obtained from Transport Rule comments. Onroad mobile and n onroad m obile c ontrols (list includes all key mobile control strategies but is not exhaustive) a 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): “Pentathalon Rule” : 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 20 12 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 Emiss ions 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. all 7, 3 ; EPA, 200976 Deliberative

– Do Not Cite or Quote 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 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 P roposed T ransport R ule. APPROACHES/REFERENCES – Mobile Sources 1. http://epa.gov/otaq/hwy.htm 2. Only for states submitting these inputs: http://www.epa.gov/otaq/lev - nlev.htm 3. http://www.epa.gov/nonroad - diesel/2004fr.htm 4. http://www.epa.gov/cleanschoolbus/ 5. http://www.epa.gov/otaq/marinesi.htm 6. Federal Aviation Administration (FAA) Terminal Area Forecast (TAF) System, December 20 08 : http://www.apo.data.faa.gov/main/taf.asp 7. http://www.epa.gov/otaq/oceanvessels.htm 

### 4.1 Stationary s ource projections: EGU sector (ptipm) The future - year data for the ptipm sector used in the air quality modeling were created b y version 4.10 (v4.10) of the Integrated Planning Model (IPM) (http://www.epa.gov/airmarkt/progsregs/epa ipm/index.html ). The IPM is a multiregional, dy namic, deterministic linear programming model of the U.S. electric power sector. V ersion 4.1 0 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 (NODA) 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 SO 2 or NO X 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 efficienc y parameters . Updates to IPM 4.10 (with respect to the version release d in the IP M 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 - ye ar EGU emissions inventory used for this rule can be found in the incremental documentation of the IP M v.4.1 0 platform , available at http://www.epa.gov/airmarkets/progsregs/epa- ipm/BaseCasev410.html . Note that the Transport Rule future ye ar base case s 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 . IP M results were generated for 2012 and 2015. The IPM 2015 results are vali d for representing 2014, 2015, and 2016. As explained in the Transport Rule IP M TSD, additional steps were taken to ensure that the results were valid for use in a 2014, 2015 ( or 2016 ) model run.77 Deliberative

– Do Not Cite or Quote Directl y emitted PM emissions (i.e., PM 2.5 and PM 10 ) 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 s ource 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 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 - IP M 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 th e 2005, v4.2 platform. More details on the rationale for this approach can be found in Appendix D of the Regulatory Impact Assessment f

or the PM NAAQS rule (EPA, 2006b ). The starting point was the emission projections done for the 2005v4 platform for the P roposed Transport Rule. The 2012 and 2014 projection factors developed for the Transport Rule Proposal (see http://www.epa.gov/ttn/chief/emch/index.html#transport) were updated for these 2012 and 2014 baseline projections. Several additional National Emission Standards for Hazardous Air Pollutants (NESHAP s ) were promulgated since emission projections were done for the Proposed Transport Rule, and these were included for the 2012 and 2014 base case s . 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 201 2 and 2014 were used for creating the 2012 and 2014 base case s 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 Error! Reference source not found. Error! Reference source not found. ) . 

### 4.2.1 Livestock emissions growth (ag, afdust) Growth in ammoni a (NH 3 ) and dust (PM 10 and PM 2.5 ) 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 NH 3 in the ptnonipm sector of roughl y 1 , 160 tons in 2012 and 1,390 tons in 2014 (primarily in Kansas and Minnesota for which the NH 3 were reported at specific farms in the point source inventory) , and for PM 2.5 the ptnonipm sector underestimate s 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 fro m the 2005 base - case emissions to 201 2 and 2014 for animal categories applied to the ag and afdust sectors for livestock- related SCCs. For example, year 201 4 beef emissions are 1. 7 % larger than the 2005 base - case emissions. Except for dairy cows and turkey

production,78 Deliberative

– Do Not Cite or Quote 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 as sumed that there would be no growth in emissions. This assumption was based on an anal ys is 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 directl y related to animal population but also nitrogen excretion. With the cow numbers going 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: http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol2_Appendices_01 - 15 - 08.pdf . 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 typ es of wood stoves. As newer, cleaner woodstov es 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 pro gram (http://www.epa.gov/ burnwise ). Details of this approach can be found in Section 2.3.3 of the PM NAAQS Regulatory Impact Anal ys is (EPA, 2006 b ). The spe cific 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%/year79 Deliberative

– Do Not Cite or Quote For the general woodstoves and fireplaces category (SCC 2104008000) we computed a we ighted 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 PM 2.5 . 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 2002 v3 NEI. This approach results in an overall decrease of 1.056% per ye ar for this source category . Table 4 - 3 presents the projection factors used to project the 2005 base case (2002 emissions) for residential wood combustion. Table 4 -3 . Projection Factors for growing ye ar 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 - catal ytic Woodstoves: Non - EPA certified 2104008003 Fireplaces: Insert; EPA certified; non - catal ytic 1.20 1.24 2104008004 Fireplaces: Insert; EPA certified; catal ytic 2104008030 Cataly

tic Woodstoves: General 2104008050 Non - catal ytic Woodstoves: EPA certified 2104008052 Non - catal ytic Woodstoves: Low Emitting 2104008053 Non - catal ytic 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 onl y 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 Contro ls)  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 Classified80 Deliberative

– Do Not Cite or Quote 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–ye ar 201 2 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. We computed VOC, benzene and naphthalene projection factors at a county- specifi c, annual resolution as shown below ; note that naphthalene, while provided by MOVES2010, is not used in th e Transport Rule : PF_VOC [state , future year] = V OC_RFL [ state , future year] /VOC_RFL [ state , 2005] , PF_BENZENE [ state , future year] = B ENZENE_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, specificall y, 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 Section 3.1.2.1 , 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 - ye ar and base - ye ar 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 ef fort. 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 - ye ar VOC emissions from Portable Fuel Containers (PFCs) from inventories developed and modeled for the EPA ’s MSAT 2 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: Permeation  25010110 12 Residential Portable Fuel Containers: Evaporation  2501011013 Residential Portable Fuel Containers: Spillage During Transport  2501011014 Residential Portable Fuel Containers: Refilling at the Pump: Vapor Displacement  2501011015 Residential Portable Fuel Containers: Refilling at the Pump: Spillage  2501012011 Commercial Portable Fuel Containers: Permeation  2501012012 Commercial Portable Fuel Containers: Evaporation81 Deliberative

– Do Not Cite or Quote  2501012013 Commercial Portable Fuel Containers: Spillage During Transport  2501012014 Commercial Portable Fuel Containers: Refilling at the Pump: Vapor Displacement  2501012015 Commercial Portable Fuel Containers: Refilling at the Pump: Spillage Additional information on the PFC inventories is available in Section 2.2.3 of the documentatio n for the 2002 Platform (http://www.epa.gov/ttn/chief/emch/index.html#2002 ). The future - year emissions reflect projected increases in fuel consumption, state programs to reduce PFC emi ssions, standards promulgated in the MSAT 2 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 line arl y interpolated ye ar 201 0 and year 2015 inventories. Benzene and other VOC HAP future - ye ar PFC emissions were also included in the interpolation. Benzene 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 Ai rcraft 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 air

port, or aircraft landings whereb y 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) S ys tem: http://www.apo.data.faa.gov/main/taf.asp (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 b y summing the airport - specific (U.S. airports only) ITN operations to national totals by year and b y aircraft operation, for each of the four available operation ty pes: commercial, general, air taxi, military . We computed growth factors for e ach operation ty pe b y dividing future - ye ar ITN b y 2005 - ye ar 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 are documented in: http://www.faa.gov/data_research/aviation/aerospace_forecasts/2009 - 2025/media/2009%20Forecast%20Doc.pdf 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 . F actors 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 1.06682 Deliberative

– Do Not Cite or Quote SCC SCC Description Projection Factor 2012 2014 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). None of our aircraft emission projections account for any control programs. We considered the NO X standard adopted b y the International Civil Aviation Organization’s (ICAO) Committee on Aviation Environmental Protection (CAEP) in February 2004, which is expected to reduce NO X 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 - ye ar emissions projections. 

### 4.2.6 Station ary s ource control programs, consent decrees & settlements, and plant closures (ptnonipm, nonpt) We applied emissions reduction factors to the 200 5 emissions for particular sources in the ptnonipm and nonpt sectors to reflect the impact of stationary- sourc e 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 2 01 2 and 2014 base cases. Detailed summaries of the impacts of the control programs are provided in Appendix D. Controls from the NO X 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 b y the NOx SIP call. The future - ye ar base controls consist of the following:

 We di d 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 rul es, 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 - ye ar 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 ye ars) were also included where information indicated that the plant was actually closed after the 2005 base ye ar 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, pl ants projected to close in the83 Deliberative

– Do Not Cite or Quote 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 th e 2005 Inventory due to Unit and Plant Closures State CO

(tons) NH 3 (tons) NO X

(tons) PM 10

(tons) PM 2.5

(tons) SO 2

(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 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 Il linois 10,175 0 11,605 1,996 1,267 23,830 716 Indiana 1,058 0 4,794 486 207 8,468 157 Io wa 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 78384 Deliberative

– Do Not Cite or Quote State CO

(tons) NH 3 (tons) NO X

(tons) PM 10

(tons) PM 2.5

(tons) SO 2

(tons) VOC (tons) 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: http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf . 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.  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 appl y 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. SO 2 RICE cobenefit controls are not applied in 2012.  M ost 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 NO X and VOC sources based on NY State Department of Environmental Conservation February 2008 guidance. These reductions are found in Appendix J in : http://www.dec.ny .gov/docs/air_pdf/NYMASIP 7final.pdf . See Section 3.2.6. 4.2.6.1 2014 base - c ase reductions from the Portland Cement NESHA P As indicated in Table 4 - 1 , the Industrial Sectors Integrated Solutions (I SI S) 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 emissions85 Deliberative

– Do Not Cite or Quote were developed in support for the Portland Cement NESHAPs and the NSPS for the Portland cement manufacturing industry . The I SI S model produced a Portland Cement NESHAP policy case of multi -pollutant emissions for individual cement kilns (emission inventory units) th at were relevant for ye ars 2013 through 2017. These IS IS -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 ISI S -based policy case predictions of emissions reductions and activity growth were only include d in the 2014 base case and not in the 2012 base case . The I SI S 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 PM 2.5 nonattainment areas. The I SI S 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 IS IS -based cement industry reductions in the future - ye ar emissions that represent 2014 , and the impact that these re ductions have on total stationary non - EGU point source (ptnonipm) emissions. Table 4 - 6 . Future - ye ar ISI S -based cement industry annual reductions (tons/y r) for the non - EGU (ptnonipm) sector Pollutant Cement Industry

emissions in 2005 Decrease in cement

industry emissions in 201 4 vs 2005 % decrease in

ptnonipm from cement reduction NO X 193,000 56,740 2.4% PM 2.5 14,400 7,840 1.8% SO 2 128,400 106,000 5.0% VOC 6,900 5,570 0.4% HC l 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_results 2 .mdb ” (EPA - HQ - OAR- 2002 - 0058 - 0788) which is posted under the Technical Information for the Boiler MACT major source rule (http://www.epa.gov/ttn/atw/boiler/boilerpg.html ) . We extracted all controls that were installed after 2005, determined a percent reduction, and verified with source owners that these controls were activel y 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 .86 Deliberative

– Do Not Cite or Quote Table 4 - 7 . State - level non - MACT Boiler Reductions from ICR Data Gathering State Pollutant Pre - controlled Emissions (tons) Controlled

Emissions (tons) Reductions

(tons) Percent

Reduction % Michigan NO X 907 544 363 40 North Carolina SO 2 652 65 587 90 Virginia SO 2 3379 338 3041 90 Washington SO 2 639 383 256 40 North Carolina HC l 31 3 28 90 4.2.6.3 RICE NESHA P 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, specificall y, CO, NO X , VOC, PM, and SO 2 . In 2014 and beyond, compliance dates have passed for all three rules ; thus all three rules are included in the emissions projection. In 2012 onl y the earliest rule’s compliance date has passed so only one rule is included. The rules can be found at http://www.epa.gov/ttn/atw/rice/ricepg.html and are listed below:  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 engine s, different facility typ es (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 onl y 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: http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf . Impacts of the RICE contro ls 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 .87 Deliberative

– Do Not Cite or Quote 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 SO2 0 23,368 VOC 1,069 15,934 4.2.6.4 Fuel s ulfur r ules 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 30 th 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: http://www.ilta.org/LegislativeandRegulatory /MVNRLM/NEUSASulfur%20Rules_09.2010.pdf . The f uel 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 SO 2 emissions by 99.5% for 2014 projections (and no reduction for 2012). These New York sulfur content reductions are further discussed here: http://switchboard.nrdc.org/blogs/rkassel/governor_paterson_signs_new_la.html . The Maine fuel sulfur rule effective January 1, 2014 reduces sulf

ur to 500ppm, resulting in an 83.33% reduction from 3000 ppm . These Maine sulfur content reductions are discussed here: http://www.mainelegislature.org/legis/bill s/bills_124th/billpdfs/SP062701.pdf . 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 SO2 is shown in Table 4 - 9 .

Table 4 - 9 . Impact of Fuel Sulfur Controls on 2014 Non - EGU Projections

State SO 2 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 emis sions from Texas and Oklahoma. For Texas oil and gas production, we used 2012 and 2014 estimates from the Texas Commissio n of Environmental Quality

(TCEQ) and used them as described in : http://www.tceq.state.tx.us/assets/public/implementation/air/am/contracts/reports/ei/5820783985FY0901 - 20090715 - ergi - Drilling_Rig_EI.pdf .88 Deliberative

– Do Not Cite or Quote 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 ina ppropriate 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, w e applied CO, NO X , and VOC emissions reductions from the Stationary

Reciprocating Internal Combustion Engine (RICE) NESHAP, which we assumed has some applicability

to this industry

(see Appendix F in the Proposed Toxics Rule TSD: http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf ) . SO 2 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 SO2 emissions including RI CE reductions for Oklahoma and the WRAP states. Table 4 - 10 . Oil and Gas NO X and SO 2 Emissions for 2005, 201 2, and 2014 including additional reductions due to the RICE NESHAP NOX (tons) SO2 (tons) State 2005 2012 201 4 2005 2012 201 4 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 ,8 34 2,888 1,479 

### 4.2.8 Future -ye ar 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 - ye ar VOC speciation for certain gasoline - related emission sources. Such sources include g asoline 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 . F or the 201 2 and 2014 profiles , we used co mbinations of E0 and ten percent ethanol (E10) fuel profiles. The fuel ty

pe 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 fuel89 Deliberative

– Do Not Cite or Quote 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 nonro ad mobile emissions were created for 201 2 and 2014 using a combination of the NMIM and MOVES2010 models. Future - ye ar 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 ty pes, fuel sulfur content, and evaporative emissions s tandards. 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 primaril y based on the 2010 version of the Motor Vehicle Emissions Simulator (MOVES2010)

– the same version as was used for 2005. The same MOVES -based PM 2.5 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 PM 2.5 temperature adjustments are fairly insensitive to the countyspecific inputs, which is why this is only

a minor limitation. California onroad (on_noadj) Like ye ar 2005 emissions, future - ye ar California NH 3 emissions are from MOVES runs for California , disaggregated to the county level using NMIM . For all other pollutants, w e did not use MOVES to generate future - ye ar onroad emissions for California, because the 200 5 base ye ar emissions were provided b y CARB’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 201 2 and 2014 emissions. This approach involved computing projection factors from a consistent set of future an d 2005 - ye ar data provided b y C ARB based on the EMFAC2007 model. For 2012 emissions, w e generated projection factors b y dividing the EMFAC2007 -based emissions for 201 2 (linearl y 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 PM 2.5 (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).90 Deliberative

– Do Not Cite or Quote 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 ty pes, and pollutants. Vehicle Miles Travelled (VMT ) were projected using growth rates from the Department of Energy ’s AEO2009. 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. 201 4 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 replac e 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 (on_moves_startpm and on_moves_runpm) MOVES -based cold start and running mode emissions consist of gasoline exhaust speciated PM and naphthalene. These pre - temperature - adjusted emis sions at 72 ° F are projected to years 2012 and 2014 from ye ar 2005 inventori es using the 201 2 - and 2014 - specific run s of MOVES2010. VMT were projected using growth rates from the AEO2009. As with the on_noadj sector, the 201 2 and 2014 MOVES2010 data were created at the state - month level, and the 201 2 and 201 5 NMIM results were used to disaggregate th e 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 b y under 4% for temperatures down to 0  F. Note that running exhaust temperature adj ustment factors are the same for all years. Also, these running mode exhaust mode emissions are considerabl y larger than cold start mode emissions. Figure 4 - 1 . MOVES exhaust temperature adjustment functions for 2005, 2012, and 2014

0 10 20 30 40 50 60 70 80

-20 -10 0 10 20 30 40 50 60 70

Te mp erat ure ( F)Adjustment Factor Run Exha ust: Al l Ye ars Start E xha ust: 2005 &2012 Start E xha ust: 20149 1 Deliberative

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### 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 b y NMIM) were created using a consistent NMIM -based approach as was used for 2005, but projected for 201 2 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, ye ar 2014 NM IMemissions were created by interpolating year 2012 and year 2015 NM IMinventories. These future - ye ar 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 ye ar differentl y due to engine turnover . The national regulations incorporated in the modeling are those promulgated prior to December 200 9 , 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: (http://www.epa.gov/otaq/regs/nonroad/420f08004.htm)  OTAQ’s Small Engine Spark Ignition (“Bond”) Rule: (http://www.epa.gov/otaq/equip - ld.htm) 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 datab a se NCD20070912, and NONROAD model version NONROAD2008a (see http://www.epa.gov/otaq/nonrdmdl.htm#model ) was used to create NM IMinventories for 2012 and 2015. California nonroad emissions Similar to onroad mobile, NMIM was not used to generate future - ye ar nonroad emissions for California, other than for NH 3 . We u sed NMIM for California future nonroad NH 3 emissions because CARB did not provide these data for any nonroad vehicle typ es. 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 ye ar 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 201 2 nonroad CAP emissions were computed by linearl y interpolating ye ar 2009 and 20 14 inventories. And 201 2 HAP emissions were also computed using the same 2005 -based CAP - HAP ratios used to create 201 4 HAP emi ssions.92 Deliberative

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### 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 ye ars. These national summaries were used to create national by-pollutant, by- SCC projection factors; these factors include final loco motive - 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 SCC 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 NH 3 1.094 1.114 2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions NO X 0.851 0.792 2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions PM 10 0.875 0.762 2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions PM 2.5 0.890 0.775 2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions SO 2 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 NH 3 1.223 1.26 2 2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations NO X 0.732 0.711 2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations PM 10 0.768 0.696 2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations PM 2.5 0.778 0.705 2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations SO 2 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 NH 3 1.223 1.262 2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations NO X 0.339 0.350 2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations PM 10 0.283 0.286 2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations PM 2.5 0.286 0.288 2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations SO 2 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) NH 3 1.223 1.262 2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) NO X 0.667 0.598 2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) PM 10 0.660 0.576 2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) PM 2.5 0.662 0.578 2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) SO 2 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 NH 3 1.223 1.262 2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines NO X 0.658 0.590 2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines PM 10 0.650 0.568 2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines PM 2.5 0.651 0.568 2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines SO 2 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 NH 3 1.223 1.262 2285002010 Railroad Equipment;Diesel;Yard Locomotives NO X 1.133 1.127 2285002010 Railroad Equipment;Diesel;Yard Locomotives PM 10 0.942 0.919 2285002010 Railroad Equipment;Diesel;Yard Locomotives PM 2.5 0.962 0.938 2285002010 Railroad Equipment;Diesel;Yard Locomotives SO 2 0.183 0.005 2285002010 Railroad Equipment;Diesel;Yard Locomotives VOC 1.548 1.52693 Deliberative

– Do Not Cite or Quote 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, 20 09 ). This rule lowered diesel sulfur content and tightened emission standards for existing and new locomotives and marine diesel emissions to lower future - ye ar PM, SO 2 , and NO X , and is documented at: http://www.epa.gov/otaq/reg s/nonroad/420f08004.htm . Voluntary retrofits under the National Clean Diesel Campaign (http://www.epa.gov/otaq/diesel/index.htm) 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, acro le in, benzene, and formaldehyde. Class 1 and 2 CMV gasoline emissions (SCC = 2280004000) were not changed for future - ye ar processing. C1/C2 diesel emissions (SCC = 2280002100 and 2280002200) were projected based on the Final L ocomotive 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 - ye ar NO X , SO 2 , 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 SO 2 Emissions Control Area- International Marine Organization (ECA - IM O ) 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 ye ars 201 2 and 2014 for the future base case s . Both future base case s include ECA IMO controls. An overview of the ECA - IMO project and future - ye ar goals for reduction of NO X , SO 2 , and PM C3 emissions can be found at: http://www.epa.gov/oms/regs/nonroad/marine/ci/420f09015.htm The resulting coordinated strategy, including emission standards under the Clean Air Act for new marine diesel engines with per- cylinder displacement at or above 30 liters , and the establishment of Emission Control Areas is at: http://www.epa.gov/oms/oceanvessels.htm These projection factors vary depending on geographic region and pollutant; where VOC HAPs are assigned the same growth rates as VOC . The projection factors u sed to create the 201 2 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 suppo rt document: http://www.epa.gov/oms/regs/nonroad/marine/ci/420r09007 - chap2.pdf . 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 b y roughl y the upper Florida Keys just southwest of Miami. Delaware provided updated future - ye ar NO X , SO 2 , 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 .94 Deliberative

– Do Not Cite or Quote 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 . NO X , SO 2 , and PM 2.5 Factors to Project C lass 3 Commercial Marine Vessel emissions to 201 2 and 2014 NO X SO 2 PM 2.5 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 -ye ar 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 ye ars. The same future - ye ar 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 spe ciation 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 ye ars in terms of different metrics. For previous modeling applications, we based the fraction on the population of vehi cles. However, since these vehicle s 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 201 2 case described here . The fraction of T ier 2 emissions used here for 201 2 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.95 Deliberative

– Do Not Cite or Quote Table 4 - 13 . Future - ye ar 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 : Compos ite 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 AEO2007 projections of E0 and E10 fuel  Tier 2 and pre - Tier 2 combinations are based on the 201 2 contribution of Tier 2 exhaust emissions Figure 4 - 2 . Tier 2 Fraction of Light Duty Vehicles



### 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 ye ar 1999, offshore oil is based on year 2005, and Canada i s based on year 2006. For both Mexico and Canada, their responsible agencies did not provide future - ye ar emissions that were consistent with the base year emissions. 0.0 0.2 0.4 0.6 0.8 1.0 1.2

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 2030Fraction of Light Duty Vehicles

Cal endar Year Exhaust TH C Vehicle Miles T raveled Population96 Deliberative

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## 5 Source Ap portionment 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 s tates on projected downwind nonattainment and maintenance receptors for both PM 2.5 and 8 - hour ozone. T o 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 wi ldfire emissions for all ozone and PM 2.5 precursors. Separate tagging runs were done for ozone and PM 2.5 precursors. Biogenic and wildfire emissions were not tagged b y 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 anal yz ed using source apportionment for ozone and for PM 2.5 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, Penns ylvania, 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 onl y 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 Re medyCase The 2014 Remedy C ase for the Transport Rule represent s the implementation of SO 2 , annual NO X , and ozone - season NO X emission reductions to address upwind state emissions that contribute significantly to nonattainment in, or interfere with maintenance b y downwind states with respect to the existing ozone and PM 2.5 NAAQS standards in the eastern U.S. The final Transport Rule requires SO 2 and/or NO X 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 SO 2 and NO X 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 NO X and SO 2 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 s tates covered b y the annual SO 2 and NO X reduction requirements for the annual and/or 24 - hour PM 2.5 standard s 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 SO 2 reductions starting in 2014 ( sections VI and VII of the preamble to the final Transport Rule discuss the SO 2 groups in detail). All states covered for the annual and/or 24 - hour PM 2.5 standards are in one annual NO X tier with uniform stringency beginning in 2012. Table 6 - 1 shows the97 Deliberative

– Do Not Cite or Quote groups in which each state is included, including whether the state is included in the Eastern modeling domain. Section 7 provides annual SO 2 and NO X summaries for the se selected groups/tiers of states. The 20 states required to make ozone - season NO X 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 NO X 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 inc lusion 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 ye llow in Figure 6 - 1 . Section 7 provides ozone - season NO X emissions summaries for the states required in the final Transport Rule to make ozone - season NO X reductions and the six additional states addressed in th e 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 b y the Transport Rule . The emissions, cost, air quality, and benefits analyses done for the Transport Rule are from a modeling scenario that requires annual SO 2 and NO x reductions in the 23 states covered for the PM 2.5 standards, and ozone season NO X 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.)98 Deliberative

– Do Not Cite or Quote99 Deliberative

– Do Not Cite or Quote Figure 6 - 2 . Group 1 and Group 2 States Covered by the Annual PM Component of the Final Transport Rule

Table 6 - 1 . Transport Rule Status of States

State State EPA Region Covered for

PM 2.5 – Group 1 SO 2 Covered for

PM 2.5 – Group 2 SO 2 Covered for Ozone in Transport Rule Covered for

Ozone in Supplemental Proposal Total

State Coverage In

Eastern Domain Western

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 0100 Deliberative

– Do Not Cite or Quote State State EPA Region Covered for

PM 2.5 – Group 1 SO 2 Covered for

PM 2.5 – Group 2 SO 2 Covered for Ozone in Transport Rule Covered for

Ozone in Supplemental Proposal Total

State Coverage In

Eastern Domain Western

State IDAHO ID 10 0 0 0 0 0 0 1 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 MI 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 0 1 NEBRASKA NE 7 0 1 0 0 1 1 0 NEVADA NV 9 0 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 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 0 1 PENNSYLVANIA PA 3 1 0 1 0 1 1 0 RHODE ISLAND RI 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 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 0 1 WEST VIRGINIA WV 3 1 0 1 0 1 1 0101 Deliberative

– Do Not Cite or Quote State State EPA Region Covered for

PM 2.5 – Group 1 SO 2 Covered for

PM 2.5 – Group 2 SO 2 Covered for Ozone in Transport Rule Covered for

Ozone in Supplemental Proposal Total

State Coverage In

Eastern Domain Western

State WISCONSIN WI 5 1 0 0 1 1 1 0 WYOMING WY 8 0 0 0 0 0 0 1 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 NO X and SO 2 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 c ontrol 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) NO X and SO 2 emissions (respectively) b y 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 NO X and SO 2 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 rem edy 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, N evada, 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 onl y (ptipm) NO X and SO 2 emissions (respectivel y) 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 NO X for the states that the Transport Rule covers for ozone. See Figure 6 - 2 for a map of these states. Emissions are provi ded 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.102 Deliberative

– Do Not Cite or Quote Additional information and pollutants are provided in the accompanying workbook: TransportRuleFinalEmissionsSummaries.xls103 Deliberative

– Do Not Cite or Quote Table 7 - 1 . State - level Total NO X 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%104 Deliberative

– Do Not Cite or Quote State 2005 Base 2012 Base 2014 Base 2014 Remedy 2012 Base minus 2005 Base 2014 Base minus 2012 Base 2014 Remedy minus 2014 Base New Hampshire 73,325 50,415 47,637 47,482 - 22,910 - 31.2% - 2,778 - 5.5% - 156 - 0.3% 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%105 Deliberative

– Do Not Cite or Quote Table 7 - 2 . State - level Total SO 2 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%106 Deliberative

– Do Not Cite or Quote State 2005 Base 2012 Base 2014 Base 2014 Remedy 2012 Base minus 2005 Base 2014 Base minus 2012 Base 2014 Remedy minus 2014 Base Nevada 73,018 29,694 30,112 30,112 - 43,325 - 59.3% 418 1.4% 0 0.0% 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%107 Deliberative

– Do Not Cite or Quote Table 7 -3 . State - level Electric Generating Unit Sector NO X 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 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%108 Deliberative

– Do Not Cite or Quote State 2005 Base 2012 Base 2014 Base 2014 Remedy 2012 Base minus 2005 Base 2014 Base minus 2012 Base 2014 Remedy minus 2014 Base Nebraska 52,426 44,496 45,047 28,211 - 7,930 - 15.1% 551 1.2% - 16,836 - 37.4% 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%109 Deliberative

– Do Not Cite or Quote Table 7 - 4 . State - level Electric Generating Unit Sector SO 2 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 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%110 Deliberative

– Do Not Cite or Quote State 2005 Base 2012 Base 2014 Base 2014 Remedy 2012 Base minus 2005 Base 2014 Base minus 2012 Base 2014 Remedy minus 2014 Base Nebraska 74,955 71,904 73,073 71,339 - 3,050 - 4.1% 1,169 1.6% - 1,734 - 2.4% 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%111 Deliberative

– Do Not Cite or Quote Table 7 - 5 . Group 1 and Group 2 States NO X Total Emissions for each TR1 Modeling C ase

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 NO X 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 NO X 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 NO X 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 NO X 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 NO X 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 NO X 21,152,309 14,973,199 13,924,510 13,725,678 - 1,247,521 - 8.3% - 198,832 - 1.4%112 Deliberative

– Do Not Cite or Quote Table 7 - 6 . Group 1 and Group 2 States SO 2 Total Emissions for each TR1 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 SO2 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 SO2 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 SO2 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 SO2 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 SO2 Emissions for All Western States 808,533 567,085 566,435 594,818 27,733 4.9% 28,383 5.0% Total SO2 14,354,370 10,928,889 10,078,786 6,275,795 -4,653,094 -42.6% - 3,802,991 - 37.7%113 Deliberative

– Do Not Cite or Quote Table 7 - 7 . Group 1 and Group 2 States NO X EGU Sector Emissions for each TR1 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 NO X 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 NO X Emissions for States in Group 2 700,110 444,377 425,686 372,355 - 72,022 - 16.2% - 53,331 - 12.5% Annual EGU NO X 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 NO X 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 NO X Emissions for All Western States 504,861 369,180 371,244 371,680 2,500 0.7% 435 0.1% Total EGU NO X 3,729,161 2,084,689 2,089,422 1,890,590 - 194,099 - 9.3% - 198,832 - 9.5%114 Deliberative

– Do Not Cite or Quote Table 7 - 8 . Group 1 and Group 2 States SO 2 EGU Sector Emissions for each TR1 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 SO2 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 SO2 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 SO2 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 SO2 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 SO2 Emissions for All Western States 361,613 224,026 247,039 275,422 51,397 22.9% 28,383 11.5% EGU SO2 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 NO X Emissions for each TR1 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 Summer EGU NO x 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 NO x 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%115 Deliberative

– Do Not Cite or Quote 

## 8 References Eastern Research Group, Mexico National Emissions Inventory, 1999: Final, prepared for Secratariat of the Environment and Natural Resources and the National Institute of Ecology, Mexico, October 11, 2006. Available at: http://www.epa.gov/ttn/chief/net/mexico/1999_mexico_nei_final_report.pdf EPA, 2005 a . EPA’s National Inventory Model (NMIM), A Consolidated Emissions Modeling System for MOBILE6 and NONROAD , U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Assessment and Standards Division. Ann Arbor, MI 48105, EPA420 - R- 05 - 024 , December 2005 . Available at http://www.epa.gov/otaq/models/nmim/420r05024.pdf . EPA, 2005 b . Clean Air Interstate Rule Emissions Inventory Technical Support Document, U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, March 005. Available at http://www.epa.gov/cair/pdfs/finaltech01.pdf . EPA 2006 a. SPECIATE 4.0, Speciation Database Development Document , Final Report, U.S. Environmental Protection Agency, Office of Research and Development , National Risk Management Research Laboratory, Research Triangle Park, NC 27711 , EPA 600 - R- 06 - 161 , February 2006. Available at http://www.epa.gov/ttn/chief/software/speciate/speciate4/documentation/speciatedoc_1206.pdf . EPA, 2006b . Regulatory Impact Anal ys es, 2006 National Ambient Air Quality Standards for Particle Pollution. U.S. Environmental Protection Agency , Office of Air Quality Planning and Standards, October, 2006. Docket # EPA - HQ - OAR- 2001 - 0017, # EPAHQ - OAR- 2006 - 0834. Available at http://www.epa.gov/ttn/ecas/ria.html . EPA, 2007 a . Guidance for Estimating VOC and NOx Emission Changes from MACT Rules, U.S. Environmental Protection Agency Office of Air Quality

Planning and Standards, Air Quality Policy Division, Research Triangle Park, NC 27711, EPA - 457/B - 07 - 001, May 2007. Available at http://www.epa.gov/ttn/naaqs/ozone/o3imp8hr/documents/guidance/200705_epa457_b - 07 - 001_emission_changes_mact_rules.pdf . EPA. 2007 b . National Scale Modeling for the Final Mobile Source Air Toxics Rule, Office of Air Quality Planning and Standards, Emissions Analysis and Monitoring Division, Research Triangle Park, NC 27711, EPA 454/R- 07 - 002, February 2007. Available at http://www.epa.gov/otaq/regs/toxics/454r07002.pdf EPA, 2008. Re gulatory

Impact Anal ys is: Control of Emissions from Marine SIand Small SIEngines, Vessels, and Equipment. U.S. Environmental Protection Agency Office of Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI 48105, EPA420 - R- 08 - 014, September, 2008. Available at: http://www.epa.gov/otaq/regs/nonroad/marinesi - equipld/420r08014.pdf EPA, 2009. Regulatory

Impact Anal ys is: Control of Emissions of Air Pollution from Locomotive Engines and Marine Compression Ignition Engines Less than 30 Liters Per C yl inder. U.S. Environmental Protection Agency

Office of Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI 48105, EPA420 - R- 08 - 001a, May 2009. Available at: http://www.epa.gov/otaq/regs/nonroad/420r08001a.pdf EPA, 2010. Technical Support Document: The Ind ustrial Sectors Integrated Solutions (I SI S) Model and the Analysis for the National Emission Standards for Hazardous Air Pollutants and New Source Performance Standards for the Portland Cement Manufacturing Industry, U.S. Environmental116 Deliberative

– Do Not Cite or Quote Protection Agency, S ectors Policies and Program Division and Air Pollution Prevention and Control Division, Research Triangle Park, NC 27711, August 2010. Ey th , A ., L. Ran, R. Partheepan, G. Yarwood, M. Jimenez, S. Rao. (2006) . “New Tools to Generate Spatial Surrogate and Sp eciation Profile Inputs to SMOKE . ” International Emission Inventory Conference, New Orleans , LA. Available at http://www.epa.gov/ttn/chief/conference/ei15/session9/ey th.pdf . Pouliot , G ., H. Simon, P. Bhave, D. Tong, D. Mobley, T. Pace, and T. Pierce . (2010) “Assessing the Anthropogenic Fugitive Dust Emission Inventory and Temporal Allocation Using an Updated Speciation of Particulate Matter.” International Emission Inventory Conference, San Antonio , TX. Available at http://www.epa.gov/ttn/chief/conference/ei19/session9/pouliot.pdf . Strum, M., D. Mintz, L . Driver, C. Harvey, H. Michaels, R. Mason. (2007) “ Estimating the Monthly Variation in California's Nonroad Equipment Emissions for the 2002 Emissions and Air Quality Modeling Platform . ” International Emission Inventory Conference, Raleigh, NC . Available at http://www.epa.gov/ttn/chief/conference/ei16/session4/strum.pdf . Yarwood, G., S. Rao, M. Yocke, and G. Whitten, 2005: Updates to the Carbon Bond Chemical Mechanism: CB05. Final Report to the US EPA, RT - 0400675. Avail able at http://www.camx.com/publ/pdfs/CB05_Final_Report_120805.pdf .