RFS2 Emissions Inventory for Air 

Quality Modeling Technical Support 

Document
EPA-420-R-10-005

January 2010

Assessment and Standards Division

Office of Transportation and Air Quality

and

Emissions Inventory and Analysis Group

Office of Air Quality Planning and Standards

U.S. Environmental Protection Agency

RFS2 Emissions Inventory for Air 

Quality Modeling Technical Support 

Document
ii

TABLE OF CONTENTS 

ACRONYMS ...................................................................................................................................................iii

LIST OF TABLES...........................................................................................................................................iv

LIST OF APPENDICES.................................................................................................................................iv

1 Introduction .............................................................................................................................................. 1

2 2005 Emission inventories and their preparation ................................................................................. 2

2.1 Custom configuration for emissions modeling for RFS2...................................................................3 

2.2 Point sources.......................................................................................................................................6 

2.3 2005 Nonpoint sources.....................................................................................................................10 

2.4 2005 Mobile sources.........................................................................................................................10 

3 VOC speciation changes that represent fuel changes ......................................................................... 10

4 2022 AEO Case ....................................................................................................................................... 12

4.1 2022 AEO Point sources ..................................................................................................................12 

4.1.1 Part 1: Projecting 2005 to 2022 AEO for ptnonipm................................................................13 

4.1.2 Part 2: Additional OTAQ-supplied emissions data for ptnonipm............................................14 

4.2 2022 AEO Nonpoint sources............................................................................................................15 

4.2.1 Part 1: Projecting 2005 to 2022 AEO for nonpt .......................................................................15 

4.2.2 Part 2: Additional OTAQ-supplied emissions data for nonpt ..................................................15 

4.3 Mobile sources..................................................................................................................................16 

4.3.1 US Aircraft, locomotive, and non-c3 commercial marine (alm_no_c3) ..................................16 

4.3.2 Canada and Mexico onroad mobile sources (othon) ................................................................17 

4.3.3 C3 commercial marine sources from all waters (seca_c3).......................................................17 

4.3.4 US nonroad mobile sources (nonroad) .....................................................................................18 

4.3.5 Onroad mobile sources (on_moves_runpm, on_moves_startpm, and on_noadj) ....................19 

5 2022 RFS1 Case ...................................................................................................................................... 21

5.1 2022 RFS1 Point sources..................................................................................................................22 

5.2 2022 RFS1 Nonpoint sources...........................................................................................................22 

5.3 2022 RFS1 Mobile sources ..............................................................................................................23 

6 2022 RFS1 headspace profile sensitivity case ...................................................................................... 24

7 2022 RFS2 Case ...................................................................................................................................... 26

7.1 2022 RFS2 Point sources..................................................................................................................26 

7.2 2022 RFS2 Nonpoint sources...........................................................................................................26 

7.3 2022 RFS2 Mobile sources ..............................................................................................................27 

8 2022 RFS2 nonroad speciation sensitivity case.................................................................................... 28
iii

ACRONYMS 

AEO Annual Energy Outlook

BEIS Biogenic Emission Inventory System 

btp Bulk plant-to-pump 

CAMD EPA’s Clean Air Markets Division 

CAP Criteria Air Pollutant 

CARB California Air Resources Board 

CEM Continuous Emissions Monitoring 

CMAQ Community Multiscale Air Quality 

DOE Department of Energy

E0 0% Ethanol gasoline 

E10 10% Ethanol gasoline

E85 85% Ethanol gasoline

EISA Energy Independence and Security Act of 2007 

EGU Electric Generating Utility 

FAA Federal Aviation Administration 

FIPS Federal Information Processing Standard 

HAP Hazardous Air Pollutant 

HDGV Heavy-duty Gasoline Vehicles 

IPM Integrated Planning Model 

LDGT1 Light-duty Gasoline Trucks, 0-6000 pounds gross vehicle weight 

LDGT2 Light-duty Gasoline Trucks, 6000-8500 pounds gross vehicle weight 

LDGV Light-duty Gasoline Vehicles 

MOBILE6 Mobile Source Emission Factor Model, version 6 

MOVES Motor Vehicle Emissions Simulator 

NEEDS National Electric Energy Database System

NEI National Emission Inventory 

NMIM National Mobile Inventory Model

OAQPS EPA’s Office of Air Quality Planning and Standards 

ORL One Record per Line (a SMOKE input format) 

ORNL Oak Ridge National Laboratory 

MP Multipollutant 

PFC Portable Fuel Container 

rtb Refinery-to-bulk terminal 

RFS1 Renewable Fuel Standard program 

RFS2 Revised annual renewable fuel standard

SMOKE Sparse Matrix Operator Kernel Emissions

SCC Source Category Code

TAF Terminal Area Forecast 

VOC Volatile Organic Compound 

WRAP Western Regional Air Partnership
iv

LIST OF TABLES 

Table 1: List of cases run in support of RFS2 air quality modeling 

Table 2: Sectors Used in Emissions Modeling for the RFS2 Platform 

Table 3: Comparison of model species in 2005 v4 platform and RFS2 platform

Table 4: Description of differences in ancillary data between the RFS2 2005 case and the 2005 v4 platform

Table 5: Emissions from ethanol plants added to 2005 v1 point inventory (tons/year) 

Table 6: Summary of VOC speciation profile approaches by sector across cases 

Table 7: Explanation of VOC profile codes listed in Table 6. 

Table 8: HAP emission ratios for generation of HAP emissions from criteria emissions for C3 commercial 

marine vessels. 

Table 9: Comparison of exhaust speciation profiles used for RFS1 headspace profile 

sensitivity case 

Table 10: SCCs affected by revised headspace profile in the 2022 RFS1 headspace profile 

sensitivity case 

LIST OF APPENDICES 

APPENDIX A: Approach for Allocating Emission Reductions and Speciating Emissions from 

Finished Fuel Transport and Distribution 

APPENDIX B: Implementation Of Speciation Profile Update For Future Year “Bulk Terminal To Pump” 

SCCs 

APPENDIX C: Inventory Data Files Used for Each RFS2 Modeling Case – SMOKE Input Inventory 

Datasets 

APPENDIX D: Ancillary Data Files Used for RFS2 2005 Case Compared to 2005 v4 Platform Data Files 

APPENDIX E: Growth and Control Assumptions and Affected Pollutants for the 2022 AEO Case 
1

1 Introduction 

This document provides the details of emissions data processing done in support of the revised annual 

renewable fuel standard (RFS2) air quality modeling. The modeling effort had five cases and two of these 

cases had additional sensitivities performed to evaluate the impact of improved approaches, for a total of 7 

different emissions cases. Table 1 provides of list of the emissions cases created for this modeling effort. 

Table 1: List of cases run in support of RFS2 air quality modeling 

Case Name 

Internal EPA 

Abbreviation Description 

2005 model evaluation 2005ai_tox 2005 case done with year-specific data for fires and 

hourly electric generating utilities (EGUs), to use for 

model performance evaluation 

2005 basecase 2005ci_tox 2005 case done with average year fires data and 

average year temporal allocation approach, to use for 

computing relative response factors with 2022 

scenarios 

2022 AEO case 2022ci_tox_aeo 2022 scenario representing Annual Energy Outlook 

(AEO) 2007 projected ethanol volume (13.2 billion 

gallons) 

2022 RFS1 case 2022ci_tox_rfs1 2022 scenario representing the original reformulated 

fuel standard (RFS1) mandated ethanol volume (6.7 

billion gallons)

2022 RFS1 headspace 

profile sensitivity case 

2022ci_tox_rfs1v2_sens1 Revised RFS1 case with adjusted nonroad exhaust 

speciation and headspace vapor for fuel with zero 

percent ethanol (E0) speciation profile 

2022 RFS2 case 2022ci_tox_eisa_rr 2022 scenario representing proposed ethanol volume 

of 34 billion gallons to meet RFS2 renewable fuel 

requirement 

2022 RFS2 nonroad 

speciation sensitivity 

case 

2022ci_tox_eisa2 Revised RFS2 case with volatile organic compound 

(VOC) speciation profiles all nonroad and Portable 

Fuel Container (PFC) emissions changed to 100% fuel 

with 10% ethanol (E10). Also does not include 

cellulosic ethanol plant emissions. 

The data used in the 2005 emissions cases are often the same as those described in the 2005-based, v4 

platform document (http://www.epa.gov/ttn/chief/emch/index.html#2005). The RFS2 cases use some 

different emissions data than the official v4 platform for two reasons: (1) the 2005 RFS2 modeling 

performed from December 2008 through March of 2009 was completed prior to the completion of the 2005 

v4 platform and (2) the RFS2 modeling used data intended only for the rule development and not for general 

use. All of the documentation provided here describes what was done differently and specifically for the 

RFS2 effort in contrast to what is used in the v4 platform. 

In RFS2, the same emission inventories were used for both the 2005 model performance case and the 2005 

base case, with the exception of the fires data and EGU temporal allocation approach. These differences are 

documented with the v4 platform documentation as well and use the same approaches previously 

documented with OAQPS’s 2002-based v3 platform (http://www.epa.gov/ttn/chief/emch/index.html#2002). 

In addition, the same biogenic emissions data as the v4 platform was used not only in the 2005 cases for 
2

RFS2, but also in all future-year cases run for RFS2. For RFS2, the only significant data changes between 

the 2005 and future-year cases are emission inventories and speciation approaches. 

For this effort, we have created and provided state, county, and source category code (SCC) summaries for 

external review for the nonpoint and mobile sectors. For point sources, we have posted the actual inventory 

datasets that we used for emissions modeling. The data have been provided to the EPA docket for this rule. 

In addition, the data can be found associated with the “RFS2 2005 and 2022 emissions data” link on the 

CHIEF website at http://www.epa.gov/ttn/chief/emch/index.html#2005. 

In the remainder of this document, we provide a description of the approaches taken for the emissions in 

support of air quality modeling for RFS2. In Section 2, we describe the ancillary data and 2005 inventory 

differences from the v4 platform. In Section 3, we describe the speciation differences among each of the 

cases run for RFS2. In Section 4, we describe the 2022AEO case as compared to the 2005 base case, and in 

Sections 5 through 8, we describe each of the additional future-year cases in comparison to a previously 

described future-year case. 

2 2005 Emission inventories and their preparation 

The 2005 emissions modeling approach for RFS2 used much of the same data and approaches as the v4 

platform. In this section, we identify the differences between the data used for RFS2 and that used for the 

2005 v4 platform. Section 2.1 provides ancillary data differences that impact multiple sectors and Sections 

2.2 through 2.4 provides differences for the point, area, and mobile sectors. 

Table 2 below lists the platform sectors used for the RFS2 modeling platform. It also indicates which 

platform sectors include HAP emissions and the associated sectors from the National Emission Inventory 

(NEI). Subsequent sections refer to these platform sectors for identifying the emissions differences between 

the v4 platform and the RFS2 platform. 

Table 2: Sectors Used in Emissions Modeling for the RFS2 Platform 

Platform Sector 

2005 NEI 

Sector Description 

Contains HAP 

emissions? 

IPM sector: ptipm Point NEI EGU processes at facilities mapped to the IPM model using 

the National Electric Energy Database System (NEEDS) database. 

Yes 

Non-IPM sector: 

ptnonipm

Point All NEI point source records not matched to the ptipm sector. Yes 

Point source fire 

sector: ptfire 

Fires Point source fire inventory - contains wildfires and prescribed 

burning. Used only for the 2005 model performance case. 

Yes 

Average-fire sector: 

avefire 

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

the 2001 Platform avefire sector, county and annual resolution. 

Used for the 2005 base year and the future base model runs, but 

not for the model evaluation case.

Yes 

Agricultural sector: 

ag

Nonpoint NH3 emissions from NEI nonpoint livestock and fertilizer 

application. 

No 

Area fugitive dust 

sector: afdust

Nonpoint PM10 and PM2.5 from fugitive dust sources from the NEI nonpoint 

inventory. 

No 

Remaining nonpoint 

sector: nonpt

Nonpoint All nonpoint sources not otherwise included in other emissions 

modeling sectors. 

Yes 

Nonroad sector: 

nonroad

Mobile: 

Nonroad 

Nonroad emissions from National Mobile Inventory Model 

(NMIM) using NONROAD2005, other than for California, in 

which emissions submitted by the California Air Resources Board 

(CARB) were used. CARB data used for HAPs are annual, other 

data are monthly. 

Yes 
3

Platform Sector 

2005 NEI 

Sector Description 

Contains HAP 

emissions? 

Aircraft, 

locomotive, marine: 

alm_no_c3 

Mobile: 

Nonroad 

Aircraft, locomotive, commercial marine except for c3 

commercial marine vessels

Yes 

C3 commercial 

marine: seca_c3 

Mobile: 

nonroad 

C3 commercial marine vessels Yes 

Onroad, except 

gasoline PM: 

on_noadj

Mobile: 

onroad+ 

A combination of onroad mobile sources from MOBILE6, 

MOVES, and 2005 NEI v2 data from California. MOVES-based 

data used only for onroad gasoline CO, NOx, VOC, some VOC 

HAPs, Exhaust PM2.5, and Exhaust PM10. More details 

provided in the 2005 v4 platform documentation.

Yes 

Onroad starting 

exhaust PM: 

on_moves_startpm

Mobile: 

onroad+ 

MOVES-based onroad mobile start exhaust PM and naphthalene 

data. More details provided in the 2005 v4 platform 

documentation. 

Yes, 

naphthalene 

only 

Onroad running 

exhaust PM 

on_moves_runpm

Mobile: 

onroad+

MOVES-based onroad mobile running exhaust PM and 

naphthalene data. More details provided in the 2005 v4 platform 

documentation. 

Yes, 

naphthalene 

only 

Biogenic: biog N/A Hour-specific emissions generated from the Biogenic Emission 

Inventory System (BEIS), version 3.13 model (includes emissions 

in Canada and Mexico) run with the Sparse Matrix Operator 

Kernel Emissions (SMOKE) modeling system. 

No 

Other point sources 

not from the NEI: 

othpt

N/A Point sources from Canada’s 2000 inventory, Mexico’s 1999 

inventory, and off-shore point sources from the 2001 platform 

No 

Other nonpoint and 

nonroad not from 

the NEI: othar

N/A Canada and Mexico nonpoint and nonroad mobile inventories No 

Other onroad 

sources not from the 

NEI: othon

N/A Canada and Mexico onroad mobile inventories No 

Other point 

mercury: othpt_hg

N/A Canada point Hg Yes, Hg only 

Other nonpoint 

mercury: othar_hg

N/A Canada nonpoint Hg Yes, Hg only 

+ Some data used for footnoted sectors are not contained in the 2005 NEI v1 or v2. 

As with the 2005 v4 platform, we processed all emissions data with a custom version of the Sparse Matrix 

Operator Kernel Emissions (SMOKE) modeling system, version 2.5. Users seeking to replicate modeling 

done for this effort can use version 2.6 of SMOKE. More details about SMOKE including user 

documentation are available at its website (http://www.smoke-model.org). 

2.1 Custom configuration for emissions modeling for RFS2 

Unlike the 2005 v4 platform, the configuration for RFS2 modeling included additional hazardous air 

pollutants (HAPs) and used slightly older ancillary data. Both of these differences are described in this 

section. 

Table 3 lists the additional HAP pollutants processed for the RFS2 platform, which were not included in the 

2005 v4 platform. However, since using the full multipollutant HAP version of the Community Multiscale 

Air Quality (CMAQ) model would have taken longer than the time available for our project, we used a “lite” 

version of the multipollutant CMAQ that required emissions only for the species flagged in the third column 

of Table 3. Additional model species that will appear in model-ready data files are listed in the right two 

columns of the table, but we did not run these additional HAPs through CMAQ for this effort. 
4

Table 3: Comparison of model species in 2005 v4 platform and RFS2 platform 

Description 

2005 v4 

platform 

species 

RFS2 platform 

Species in CMAQ 

MP lite 

Additional RFS2 

platform HAP 

Species* Description 

Carbon Monoxide CO CO ACRYLONITRILE Acrylonitrile 

Nitrogen Oxide NO NO BR2_C2_12 1,2 Dibromoethane 

Nitrogen Dioxide NO2 NO2 CARBONTET Carbontet 

Nitrous acid HONO HONO CHCL3 Chloroform 

Ammonia NH3 NH3 CL_ETHE Vinyl Chloride 

Sulfur dioxide SO2 SO2 CL2_C2_12 1,2 Dichloroethane 

Sulfuric acid vapor SULF SULF CL2_ME Methylene Chloride 

PM2.5 Elemental carbon PEC PEC CL3_ETHE Trichloroethylene 

PM2.5 Organic carbon POC POC CL4_ETHANE1122 1,1,2,2 Tetrachloroethane 

PM2.5 primary nitrate PNO3 PNO3 CL4_ETHE Perchloroethylene 

PM2.5 primary sulfate 

PSO4 PSO4 DICHLOROBENZE

NE 

Dichlorobenzene 

PM2.5 other 

PMFINE PMFINE DICHLOROPROPE

NE 

Dichloropropene 

PM Coarse (PM10 – PM2.5) PMC PMC ETOX Ethylene Oxide 

Acetaldehyde 

ALD2 ALD2 HEXAMETHY_DIIS Hexamethylene 1,6-

Diisocyanate 

Higher aldehydes ALDX ALDX HYDRAZINE Hydrazine 

Ethene ETH ETH MAL_ANHYDRIDE Maleic Anhydride 

Ethane ETHA ETHA PROPDICHLORIDE Propdichloride 

Ethanol ETOH ETOH QUINOLINE Quinoline 

Formaldehyde FORM FORM TOL_DIIS 2,4-Toluene Diisocyanate 

Internal olefin carbon bond IOLE IOLE TRIETHYLAMINE Triethylamine 

Isoprene ISOP ISOP DIESEL_PEC Diesel PM2.5 elemental carbon 

Methanol MEOH MEOH DIESEL_POC Diesel PM2.5 organic carbon 

Nonreactive VOC NR NR DIESEL_PMFINE Diesel PM2.5 primary nitrate 

Nonvolatile (from VOC mass) NVOL NVOL DIESEL_PNO3 Diesel PM2.5 primary sulfate 

Terminal olefin carbon bond OLE OLE DIESEL_PMC Diesel PM2.5 other 

Parrafin carbon bond PAR PAR DIESEL_PSO4 Diesel coarse PM 

Toluene and other monoalkyl 

aromatics 

TOL TOL BERYLLIUM_C Coarse Beryllium 

Unknown VOC UNK UNK BERYLLIUM_F Fine Beryllium 

Unreactive VOC UNR UNR CADMIUM_C Coarse Cadmium 

Xylene and other polyalkyl 

aromatics 

XYL XYL CADMIUM_F Fine Cadmium 

Sequiterpenes SESQ SESQ CHROMHEX_C Coarse Hexavalent Chromium 

Terpene TERP TERP CHROMHEX_F Fine Hexavalent Chromium 

Benzene BENZENE BENZENE CHROMTRI_C Coarse Trivalent Chromium 

Chlorine CL2 CL2 CHROMTRI_F Fine Trivalent Chromium 

Hydrochloric acid HCL HCL LEAD_C Coarse Lead 

Divalent gaseous mercury HGIIGAS HGIIGAS LEAD_F Fine Lead 

Elemental mercury HGNRVA HGNRVA MANGANESE_C Coarse Manganese 

Particulate mercury PHGI PHGI MANGANESE_F Fine Manganese 

Naphthalene from the HAP 

inventory 

NAPHTHALENE NICKEL_C Coarse Nickel 

Acrolein from the HAP 

inventory 

ACROLEIN NICKEL_F Fine Nickel 

Acetaldehyde from the HAP 

inventory 

ALD2_PRIMARY 

1,3 Butadiene from the HAP 

inventory 

BUTADIENE13 
5

Description 

2005 v4 

platform 

species 

RFS2 platform 

Species in CMAQ 

MP lite 

Additional RFS2 

platform HAP 

Species* Description 

Methane from the HAP 

inventory 

CH4 

Formaldehyde from the HAP 

inventory 

FORM_PRIMARY

M-isomer of Xylene from the 

HAP inventory 

MXYL 

O-isomer of Xylene from the 

HAP inventory 

OXYL 

P-isomer of Xylene from the 

HAP inventory 

PXYL 

Toluene from the HAP 

inventory 

TOLU 

* These species are created by the emissions configuration, but were not modeled. 

In addition to the species changes, the RFS2 platform had a few additional custom aspects in the 2005 cases. 

Table 4 lists the datasets used by the RFS2 platform that are different from the v4 platform, including a 

description of the impact of the differences. These differences stem from the 2005 v4 platform having been 

done after the RFS2 platform, resulting in newer inventory data used for the v4 platform. These inventory 

differences are described more in later sections of this document. In addition, Appendix D provides a more 

detailed comparison of the ancillary datasets for the 2005 v4 platform versus the RFS2 platform. 

Another consideration is the speciation across the RFS2 future-year cases as compared to 2005. Section 3 

provides a detailed account of these differences. Otherwise, the future-year ancillary data were largely the 

same as those in 2005, with no substantial differences. Are ancillary data files can be found at the 2005-

based platform website (http://www.epa.gov/ttn/chief/emch/index.html#2005). 

Table 4: Description of differences in ancillary data between the RFS2 2005 case and the 2005 v4 platform. 

Ancillary Data Type Difference between 2005 v4 platform and RFS2 platform 

Spatial cross references The 2005 v4 platform data are updated to support the newer (2006) Canadian 

inventories that were not available in time for RFS2 modeling. 

Temporal crossreferences The 2005 v4 platform data are updated to support the 2006 Canadian data, 

additional source category codes (SCCs) found in the 2005 v2 NEI point 

inventory, and a revised oil and gas inventory. 

Temporal profiles The 2005 v4 platform dataset adds additional profiles from Environment 

Canada to support processing of the 2006 Canadian inventory. 

Speciation crossreferences and 

Speciation profiles 

The RFS2 data files are configured to support the multi-pollutant (MP) version 

of CMAQ, whereas the 2005 v4 platform data file is configured to support only 

the non-MP version. Therefore, the RFS2 data files include profiles for 

additional HAP species, including HAP VOCs, HAP metals, chromium, and 

diesel PM. The 2005 v4 platform data files include profiles for passing through 

the pre-speciated VOCs for the 2006 Canadian inventory. 

Inventory tables The RFS2 data file is configured to support the MP version of CMAQ, whereas 

the 2005 v4 platform data file is configured to support only the non-MP 

version. 

NonHAP exclusions 

data 

The 2005 v4 platform data has been updated with new oil and gas SCCs not 

used for the RFS2 platform. 
6

2.2 Point sources 

The 2005 emissions from the U.S. point source sectors (ptipm and ptnonipm) used for RFS2 differ from the 

v4 platform primarily because the emissions are based on the 2005 NEI version 1, rather than the 2005 NEI 

version 2. The original emissions were created from the NEI database on June 10, 2008. These emissions 

were further modified, further changing the 2005 NEI version 1, as follows: 

1) Inventory split into ptipm and ptnonipm sectors using the IPM indicator of the SMOKE-ready datasets 

2) Applied fugitive dust transport fractions to the appropriate SCCs (see 

http://www.epa.gov/ttn/chief/emch/dustfractions)

3) Further analyzed HCl emissions for missing ptipm sector HCl sources and moved emissions originally 

labeled as ptnonipm to correctly be placed with their associated criteria air pollutants (CAP) emissions 

in the ptipm sector 

4) Removed emissions of benzene, acetaldehyde, formaldehyde, methanol, to support the “no hap use” 

approach for the ptipm and ptnonipm sectors 

5) Added an additional 47 ethanol plants based on direction from staff at the Office of Transportation and 

Air Quality (OTAQ). Unless otherwise note in Table 5 (a list of ethanol facilities and their emissions), 

we adjusted the original VOC emissions provided by a factor of 0.65 (a reduction) to offset the ethanolheavy speciation profile (99.6% ethanol) that we had available for speciation of ethanol plants. This 

prevented the overstating of ethanol emissions. In addition, we multiplied all emissions by 1/(453.6 

2000)  1,000,000 = 1.1023113109 (converting from grams/yr per million gallons to tons/yr) at the 

direction of OTAQ to correct the units of the emissions (from grams per million gallon per year to 

tons/year). These changes resulted in roughly a 10.23% increase in the emissions values initially 

provided by OTAQ. The list of these facilities and their emissions is available in Table 5. 

6) Removed facilities that closed between 2002 and 2005, since much of the ptnonipm portion of the 2005 

v1 NEI was carried forward from the 2002 v3 NEI. This change was also made in creating the v4 

platform. The list of removed sources is available in the Excel® file 

“Closures_applied_to_2002v3_point_for_2005af.xls” provided with the 2005 v4 platform 

documentation. 

7) Removed Minnesota airport ground support equipment (SCCs 2265008005 and 2270008005), to prevent 

double counting with the nonroad sector. 

8) Other minor adjustments: 

o Removed exclamation marks, asterisks, and embedded double quotes in facility names, and 

other key text fields, changed “PM25” and “PM25-PRI” to “PM2_5”, and changed the 

state/county Federal Information Processing Standard (FIPS) code field for tribal records from 

00000 to 88TTT, where TTT is the tribal code. 

o Removed two SCC=201002 records because this is an invalid SCC; both records had zero 

emissions 

To implement the inventory processing, we split the 2005 ptnonipm CAP and HAP inventories into five 

separate datasets to facilitate replacement and projection for the 2022 scenarios. These datasets are: 

1) A dataset with one ethanol plant (Chippewa) CAP and HAP emissions for which the emissions are 

held at 2005 values for the AEO and RFS1 cases and changed in the RFS2 case 

2) A dataset with three ethanol plants’ CAP and HAP emissions that are replaced in all 2022 scenarios 

3) A dataset with CAP and HAP emissions for 43 additional ethanol plants not available in the 2005 

v1 NEI, which also have different emissions n all 2022 scenarios. 

4) A dataset with CAP emissions from the all other nonEGU sources from the 2005 NEI v1 

5) A dataset with HAP emissions from the all other nonEGU sources from the 2005 NEI v1 
7

In addition to differences in the U.S. point sources, further differences exist from the v4 platform for the 

Canadian point emissions. The Mexico point emissions are identical to those documented for the 2002 v3 

platform and the 2005 v4 platform. The RFS2 modeling inventories included year 2000 Canadian emissions 

from the 2002 v3 platform and did not include the updated 2006 Canadian emissions, because these 

emissions were not available in time to support the development of the model-ready emissions. There was 

no Canadian mercury emissions data, and so these are the same as the 2002 v3 platform. The offshore 

sources were different from what was used in the 2005 v4 platform because they were not updated with the 

new offshore inventory available in the 2005 v2 NEI. For more information on the Canadian and Mexican 

emissions used for this effort, please refer to the 2002 v3 platform documentation at 

http://www.epa.gov/ttn/chief/emch/index.html#2002.

In addition, we processed emissions for RFS2 using the 3-d emissions option for all point source sectors 

rather than the “inline” point source option that we used for the 2005 v4 platform. This approach has 

essentially no effect on the modeling results. Using the inline approach makes the CMAQ emissions data 

files smaller, but that option was not available in time for use on this effort. 
Table 5: Emissions from ethanol plants added to 2005 v1 point inventory (tons/year)

County Name State Name 

St/Co FIPS PLANT CO NOX VOC SO2 P

Swift Co Minnesota 27151 Chippewa Valley Ethanol Co LLLP (*) 29.7 40.4 155.1 0.6 Chippewa Co Minnesota 27023 Granite Falls WWTP (+) 0.0 0.0 0.7 0.0 Dodge Co Minnesota 27039 Al-Corn Clean Fuel (+) 28.5 45.0 207.6 0.5 Sibley Co Minnesota 27143 Heartland Corn Products (+) 51.4 62.9 378.3 0.4 Dawson Co Nebraska 31047 Cornhusker Energy Lexington (CEL) 10.5 30.3 14.3 38.6 Stevens Co Minnesota 27149 Diversified Energy Company (DENCO), 

LLC 

52.4 151.6 71.6 192.9 

Wichita Co Kansas 20203 ESE Alcohol Inc. 3.1 9.1 4.3 11.6 Sedgwick Co Kansas 20173 Abengoa Bioenergy Corporation 52.4 151.6 71.6 192.9 Roosevelt Co New Mexico 35041 Abengoa Bioenergy Corporation 62.8 181.9 86.0 231.5 Linn Co Iowa 19113 Archer Daniels Midland (ADM) 964.7 1,338.4 418.1 1,266.3 5Clinton Co Iowa 19045 Archer Daniels Midland (ADM) 733.2 1,017.2 317.7 962.4 4Platte Co Nebraska 31141 Archer Daniels Midland (ADM) 366.6 508.6 158.9 481.2 2Lyon Co Minnesota 27083 Archer Daniels Midland (ADM) 154.4 214.1 66.9 202.6 Peoria Co Illinois 17143 Archer Daniels Midland (ADM) 439.8 1,273.1 601.9 1,620.4 3Pembina Co North 

Dakota 

38067 Archer Daniels Midland (ADM) 52.4 151.6 71.6 192.9 

Tazewell Co Illinois 17179 Aventine Renewable Energy, Inc. (formerl 385.9 535.4 167.2 506.5 2Monroe Co Wisconsin 55081 Badger State Ethanol, LLC 108.9 315.3 149.0 401.2 Des Moines Co Iowa 19057 Big River Resources, LLC 108.9 315.3 149.0 401.2 Washington Co Nebraska 31177 Cargill (was PGLA-1CO) 328.0 455.1 142.1 430.5 1Christian Co Kentucky 21047 Commonwealth Agri-Energy, LLC 41.9 121.3 57.3 154.3 Codington Co South 

Dakota 

46029 Glacial Lakes Energy, LLC (GLE) 104.7 303.1 143.3 385.8 

Kossuth Co Iowa 19109 Global Ethanol 209.4 606.3 286.6 771.6 Riverside Co California 06065 Golden Cheese Company of CA 10.5 30.3 14.3 38.6 Cerro Gordo Co 

Iowa 19033 Golden Grain Energy LLC 146.6 424.4 200.6 540.1 

Hardin Co Iowa 19083 Hawkeye Renewables, LLC 115.2 333.4 157.6 424.4 Brown Co South 

Dakota 

46013 Heartland Grain Fuels, LP 20.9 60.6 28.7 77.2 

Beadle Co South 

Dakota 

46005 Heartland Grain Fuels, LP 29.3 84.9 40.1 108.0 

Pierce Co Nebraska 31139 Husker Ag, LLC 54.5 157.6 74.5 200.6 Kearney Co Nebraska 31099 KAAPA Ethanol, LLC 125.7 363.8 172.0 463.0 Stearns Co Minnesota 27145 Land O' Lakes / Melrose Dairy Proteins 5.4 15.8 7.5 20.1 Crawford Co Illinois 17033 Lincolnland Agri-Energy 58.6 169.8 80.2 216.0 

8
9

County Name State Name 

St/Co FIPS PLANT CO NOX VOC SO2 P

Cherokee Co Iowa 19035 Little Sioux Corn Processors 184.3 533.5 252.2 679.0 Jefferson Co Colorado 08059 Merrick & Company (Coors Brewery) 4.2 12.1 5.7 15.4 Tazewell Co Illinois 17179 MGP Ingredients, Inc. 188.5 545.6 257.9 694.4 Lincoln Co Nebraska 31111 Midwest Renewable Energy, LLC (MRE) 41.9 121.3 57.3 154.3 Hamilton Co Nebraska 31081 Nebraska Energy 104.7 303.1 143.3 385.8 Roberts Co South 

Dakota 

46109 North Country Ethanol (NCE) 52.4 151.6 71.6 192.9 

Delaware Co Iowa 19055 Permeate Refining 3.1 9.1 4.3 11.6 Ida Co Iowa 19093 Quad-County Corn Processors 56.5 163.7 77.4 208.3 Finney Co Kansas 20055 Reeve Agri-Energy 25.1 72.8 34.4 92.6 Sioux Co Iowa 19167 Siouxland Energy & Livestock Coop 

(SELC) 

46.1 133.4 63.1 169.8 

Red Willow Co Nebraska 31145 SW Energy, LLC. 0.2 0.6 0.3 0.8 Loudon Co Tennessee 47105 Tate & Lyle 254.7 353.3 110.4 334.3 1Hitchcock Co Nebraska 31087 Trenton Agri-Products, LLC. (TAP) 83.8 242.5 114.6 308.6 Winnebago Co Wisconsin 55139 Utica Energy, LLC 108.9 315.3 149.0 401.2 Gove Co Kansas 20063 Western Plains Energy, LLC 62.8 181.9 86.0 231.5 Mitchell Co Georgia 13205 Wind Gap Farms (Anheuser/Miller 

Brewery) 

0.8 2.4 1.1 3.1 

Total 6,074.3 12,610.4 5,923.2 14,417.5 2,5

(*) Data taken from the 2002 NEI rather than provided by OTAQ for 2005. Units conversion not performed on this facility and no adjustme(+) Data taken from the 2005 NEI v1, rather than provided by OTAQ for 2005. Units conversion not performance on these facilities and no 

data by 0.65. 
10

2.3 2005 Nonpoint sources 

The emissions from the agricultural ammonia (ag) and nonpoint fugitive dust (afdust) sectors are the same as 

the v4 platform, documented elsewhere. For the “other” nonpoint (nonpt) sector, the only difference from 

the v4 platform is that these emissions do not include the oil and gas extraction emissions (SCCs matching 

23100XXXXX) provided by the Western Regional Air Partnership (WRAP) for the western states. These 

updated oil and gas extraction emissions were provided after the modeling platform development for RFS2. 

For the Canadian and Mexican nonpoint sector (othar), we used the same inventories as the 2002 v3 

platform, and did not yet have the updated 2006 Canadian inventory used in the v4 platform. 

The 2005ci_tox_05b case uses the average fires (avefire) sector rather than the point source fires (ptfire) 

sector. The avefire emissions are the same as those in the 2005ci_tox_05b case mentioned above, with the 

exception that we added 1-3-butadiene, acrolein, and xylenes, and toluene using ratios to PM2.5 available in 

the Excel® file “Wildfire HAP ratios to PM2.5 08oct2008.xls” compiled by Madeleine Strum on 10/8/2008. 

The factors in this Excel® file also were used to create emissions for benzene, acetaldehyde, and 

formaldehyde in the 2005 v4 platform and were unchanged for RFS2. References for these data are provided 

in the spreadsheet. 

2.4 2005 Mobile sources 

Mobile sources include three US onroad sectors (on_noadj, on_moves_startpm, on_moves_runpm) and two 

US nonroad sectors (nonroad and alm_no_c3). In addition, it includes Canadian and Mexican emissions in a 

separate onroad sector (othon) and nonroad/nonpoint sector (othar). 

For onroad mobile, the on_noadj sector is the same as the v4 platform, with the exception of keeping 

additional pollutants as described in Section 2.1. The on_moves_startpm and on_moves_runpm emissions 

inventory data are also the same as the v4 platform, with the only additional pollutant for these sectors being 

naphthalene. In addition for the Motor Vehicle Emission Simulator (MOVES) sectors, the temperature 

adjustment calculations applied to PM2.5 species were also applied to naphthalene, but the methods we used 

were the same as the v4 platform. 

The nonroad emissions inventory data are the same as the v4 platform, with additional HAPs being kept for 

RFS2 as well. The alm_no_c3 emission sector does use different data from that of the v4 platform. 

Specifically, the aircraft emissions remain in this sector and are older data from that of the v4 platform. In 

the v4 platform, the aircraft emissions had been revised and included in the ptnonipm sector as part of the 

2005 NEI v2. The airport emissions used in RFS2 were from the 2002 NEI, version 3, acquired March 27, 

2007 and used in the Office of Air Quality Planning and Standards’ (OAQPS’s) 2002 v3.1 platform. 

Additionally, the othon sector for RFS2 differs from the v4 platform because we used the older Canadian 

data. The data we used reflect 2000 emissions and are the same data used in the v3 and v3.1 2002-based 

platforms. The 2005 v4 platform uses 2006 Canadian inventory data, not available at the time that we 

performed RFS2 modeling. 

3 VOC speciation changes that represent fuel changes 

A significant detail that changes for each of the RFS2 modelingcases is the VOC speciation profiles used to 

split total VOC emissions into the various VOC model species needed for CMAQ. In this section, we 
11

summarize the various speciation profile information used in configuring the various cases, and we include 

Table 6 to provide a summary of the VOC speciation approach for each of the future-year cases. 

The approaches taken in the 2005 cases below are the same as the 2005 v4 platform, but are included here 

for completeness. The approaches used for each of the future year cases are customized for those cases, and 

they include the impact of fuel changes for each of the future-year cases on emissions from the on_noadj 

sector, the nonroad sector, and parts of the nonpt and ptnonipm sectors. The speciation changes from fuels in 

the nonpt sector include changes for portable fuel containers (PFCs) and some parts of the bulk-plant-topump (btp) and refinery-to-bulk terminal (rbt) emissions. The speciation changes from fuels in the ptnonipm 

sector include the remainder of the emissions for the btp and rbt emissions. Appendices A and B provide 

additional details on the origin of the speciation changes based on fuel assumptions among the three futureyear cases. 

In Table 6 below, the VOC speciation approach gives a general indication of the approached used, but the 

details of the implementation are found in the ancillary data provided and in Appendices A and B. Although 

a sector might take the same general approach between two cases, differences may exist in the details of the 

approach. For example, the nonroad sector uses combinations of E0 and E10 Tier 1 profiles in the 2005 and 

2022 RFS1 sensitivity cases, but different fractions of these two profiles were used for each case. 

Table 6: Summary of VOC speciation profile approaches by sector across cases 

Inventory 

type and 

mode 

VOC 

speciation 

approach 

for fuels 

VOC 

Profile 

Codes 

2005 

cases 

2022 

AEO 

2022 

RFS1 

2022 

RFS1 

sensitivity 

2022 

RFS2 

2022 

RFS2 

sensitivity

Tier 1 E0 and 

E10 

combinations 

8750 

8751 

on_noadj

nonroad nonroad 

Tier 1 and 

Tier 2 E0 and 

E10 

combinations 

8750 

8751 

8756 

8767 

on_noadj

nonroad 

on_noadj

nonroad on_noadj 

Tier 2 E10 

and E85 

combinations 

8752 

8757 

on_noadj

nonroad on_noadj 

Mobile 

Exhaust 

Tier 1 E10 8751 nonroad 

E0 and E10 

combinations 

8753 

8754 

on_noadj

nonroad 

E0 or E10 

(by county) 

8753 

8754 

on_noadj

nonroad 

E0 or E10 or 

combinations 

8753 

8754 

on_noadj

nonroad 

on_noadj 

nonroad 

E10 and E85 

combinations 

8754 

8755 

on_noadj

nonroad on_noadj 

Mobile 

Evaporative 

E10 8754 nonroad 
12

Inventory 

type and 

mode 

VOC 

speciation 

approach 

for fuels 

VOC 

Profile 

Codes 

2005 

cases 

2022 

AEO 

2022 

RFS1 

2022 

RFS1 

sensitivity 

2022 

RFS2 

2022 

RFS2 

sensitivity

E0 8737 All listed

E0 and E10 

combination 

8736 

8737 

All 

listed+ All listed

E0 (revised) 

and E10 

combinations 

8736 

8737B All listed 

E0 (revised) 8737B rbt 

E10 and E85 

combinations 

8736 

8755 

PFCs 

btp 

nonroad 

btp 

rbt 

Other 

sources:

nonroad 

refueling, 

PFCs, 

btp, 

rbt 

E10 8736 PFCs 

nonroad + A negligible fraction of E85 evaporative emissions (profile 8755, fraction 0.00075) was assumed in this combination. 

Table 7 provides the purpose of the VOC speciation profile codes used in the table: 

Table 7: Explanation of VOC profile codes listed in Table 6. 

Exhaust Evaporative Refueling 

8750 Tier1 E0 

8751 Tier1 E10 

8752 E85 

8756 Tier2 E0 

8757 Tier2 E10 

8753 E0 

8754 E10 

8755 E85 

8736 E10 headspace vapor

8737 E0 headspace vapor 

8737B E0 headspace vapor 

 with reduced olefins. 

Appendix D summarizes the data file names used for all of the data files that are updated from the v4 

platform. All ancillary data files are available on the 2005-based platform website previously referenced. 

4 2022 AEO Case 

The 2022 AEO case is intended to represent the emissions associated with use of the most likely volume of 

ethanol in the absence of the RFS2 rule and Energy Independence and Security Act of 2007 (EISA) 

renewable fuel requirements. For this case, the ethanol volume was projected for 2022 using the Department 

of Energy, Energy Information Administration in the 2007 Annual Energy Outlook (AEO) report. That 

year’s AEO projections were used because Department of Energy (DOE) started accounting for EISA in 

their 2008 AEO projections. A list of inventory datasets used for this and all cases is provided in Appendix 

A. A list of all growth and control assumptions for this Case is provided in Appendix E. Other Sections 

describe the projection differences amoung the 2022 AEO, RFS1, and RFS2 cases. 

4.1 2022 AEO Point sources 

The point sources for the 2022 AEO case included US EGU point sources (ptipm), US nonEGU point 

sources (ptnonipm) and sources from Mexico, Canada, and the Gulf of Mexico (othpt and othpt_hg). The 

US EGU point sources for all 2022 cases use an Integrated Planning Model (IPM) run for criteria pollutants, 

HCl, and mercury in 2020. We used 2020 because it was the year closest to the 2022 modeling year 

supported by the IPM model. The code number used by EPA’s Clean Air Markets Division (CAMD) to 
13

denote the run is EPA30Draft_BC_42l. While these emissions are different from those used in the v4 

platform, they are consistent with the 2020 emissions used in the v3 platform. OAQPS post-processed these 

data in the same way as described in the 2005 v4 platform documentation for the “base case” to create daily 

emissions that include temporal allocation information from three years of Continuous Emissions Monitoring 

(CEM) data. The temporal allocation approach is the same as for the RFS2 2005 base case 

(2005ci_tox_05b), to eliminate artificial differences in temporal allocation between the base and future years. 

In addition to the IPM emissions, we held the remaining HAPs at the same values used in the 2005 cases, 

except mercury was removed from the original 2005 dataset (i.e., no future-year mercury data are included in 

the RFS2 platform). 

For the Mexican and offshore point source emissions, we held the data constant with the 2005 base case. 

This means that the Mexican emissions were based on year 1999, since Mexico has not provided emissions 

projections to date. We used 2020 emissions projections for Canadian emissions, provided by Environment 

Canada, which are consistent with the 2000 base year. The Canadian data are the same as those used for the 

2002-based v3 platform. The data used for RFS2 future years are different from our v4 platform, which was 

not available for this work and which used 2006 Canadian emissions provided by Environment Canada. 

For the US nonEGU emissions (sector ptnonipm) there were two main pieces for the 2022 AEO ptnonipm 

inventories: data projected from 2005 values and data that were replaced by OTAQ-generated data in 2022. 

Referring to the five parts listed in Section 2.2, datasets (4) and (5) were projected from 2005 to 2022 values, 

datasets (2) and (3) were replaced, and dataset (1) was unchanged. 

4.1.1 Part 1: Projecting 2005 to 2022 AEO for ptnonipm 

We applied both control and growth factors to a subset of the 2005 ptnonipm to create 2022 AEO. We 

started with 2020 projection factors from the 2002 v3.1 platform for most of the RFS2 year 2022 projections. 

Given the uncertainty of emissions projections and the lack of any additional controls coming into effect 

between 2020 and 2022, we decided that using 2020 as the year for our non-EGU point and nonpoint 

projections would be sufficient. This approach matched the ptipm approach since IPM results were available 

for 2020 and not 2022. Furthermore, we did not have to adjust the factors for a 2005-base year in most 

cases, because most of the 2005 v1 nonEGU point emissions data were populated with 2002 emissions 

values. 

The 2002 v3.1 platform growth and control factors had been revised from the 2002v3.0 platform projection 

factors that are documented in the 2002 v3 emissions modeling platform documentation (see 

http://www.epa.gov/ttn/chief/emch/index.html#2002). These updates included Hazardous Waste 

Incineration adjustments and Small and Large Municipal Waste Combustor closures and adjustments. The 

following describes how we further modified the 2002v3.1 projection factors for the 2022 AEO case. 

We used SMOKE with a “control” packet to apply control factors that implement known emissions 

reductions from point and nonpoint sources for national rules. For RFS2, the control packet was revised 

from the 2002 v3.1 factors to give key VOC HAPs the same control factors as those for VOC. The VOC 

HAPs (and CAS numbers) of interest for this effort were: 1,3-butadiene (CAS=106990), acrolein 

(CAS=107028), formaldehyde (CAS=50000), methanol (CAS=67561), benzene (CAS=71432), acetaldehyde 

(CAS=75070), and naphthalene (CAS=91203). The “control” packet (data file) header lists all the various 

components and the SAS® programs used to create it. 

We also used SMOKE with a “projection” packet to apply growth adjustments, some control adjustments, 

and plant closures. For RFS2, the projection packet for ptnonipm consisted of several components. First, we 

modified the data from the 2002v3.1 platform packet to remove entries for which we had new factors for this 
14

effort, such as onroad refueling and aircraft. In addition, we added the same list of VOC HAPs to the 

projection factors as we had added to the control packet for the VOC-specific entries already present (e.g., 

landfills in nonpt sector). Next, we added the AEO-specific projection factors from several OTAQ sources, 

as follows: 

1. Onroad refueling: We retained the same list of refueling ptnonipm and nonpt state/county FIPS 

codes and SCCs from the 2002 v3 emissions modeling platform. For California, we used the 2005v2 

California and NMIM data and 2022 NMIM reference case VOC and VOC-HAP refueling emissions 

to obtain annual adjustment ratios by pollutant and county. Next, we applied an additional OTAQprovided ethanol adjustment factor of 1.0306 to each ratio for each of the RFS2 scenarios, provided 

by David Brzezinski on 12/12/2008. The final formula for the projection factors was Factor 2022 = 

NMIM Emis2022 * 1.0306 /NMIM Emis2005 (note: we applied different ethanol adjustment factors to 

the RFS1 and RFS2 cases. These factors were applied to the refueling SCCs from the 2005 base case. 

2. Year 2022 aircraft Federal Aviation Administration (FAA) takeoff and landing data from the 

Terminal Area Forecast (TAF) data: This activity data replaces the 2020 factors for all RFS2 2022 

scenarios. 

3. We applied adjustments to refinery emissions by state and SCC, using the same factor for all 

pollutants to represent activity adjustments (note: different adjustments were made to the RFS2 case, 

and no adjustments were made to the RFS1 case). The state-level adjustments and the list of SCCs 

affected were provided by Rich Cook on 11/25/2008 in Excel® workbook 

“RFS2_Refinery_Adjust.xls”. 

4. For gasoline distribution SCCs (both ptnonipm and nonpt SCCs), we additionally applied VOC and 

VOC HAP adjustments to SCCs representing emissions from bulk-plant-to-pump (btp) and refineryto-bulk terminal (rtb) processes. These SCC-level adjustments impact VOC and VOC HAPs in both 

the ptnonipm and nonpt sectors. The adjustments were provided by Craig Harvey on 12/16/2008 in 

the Excel® workbook “2005ai_tox_SCC_50state_CAPHAP-20081216.xls”. (Note: these adjustments 

were not applied to RFS1 and different adjustments were applied to RFS2, based on assumed changes 

in the ratios of E0 to E10 and E85). 

We applied the control and projection factors to the ptnonipm 2005 inventory described in Section 2.2, 

resulting in a “2022” ptnonipm inventory. To this inventory, we added additional OTAQ-supplied inventory 

data as described in Step 2 below. The configuration of the processing was designed specifically to prevent 

inadvertent double counting of emissions. 

4.1.2 Part 2: Additional OTAQ-supplied emissions data for ptnonipm 

In addition to the data preparation described above, we added the following data supplied by OTAQ: 

1. Ethanol plant additions: These emissions data completely replace all of the ethanol plants listed in 

Table 5 except the first one. OTAQ provided the emissions, stack parameters, locations and the same 

SCC assignments were made as described for 2005: PM2.5 (30299999) and VOC and all other 

pollutants (30125010). The original VOC emissions were supplied by Rich Cook in Excel® and 

OAQPS further adjusted the data to correct for units conversions and to adjust VOC downward to 

account for too much ethanol in the speciation profile. These were the same adjustments made to the 

2005 data and are described in Section 2.2. Further, we changed the original data to use the same 

Stack IDs for both PM2.5 and PM10, to ensure SMOKE could properly calculate PMC as PM10-PM2.5
15

after matching emissions sources. Lastly, we removed the benzene, formaldehyde, acetaldehyde, and 

methanol inventory emissions from these sources because they are “no integrate” sources for VOC 

HAPs (we do not use the VOC HAPs to augment speciation information for this sector), and so these 

model species were to be calculated from VOC speciation. 

2. In addition, we retained the Chippewa plant from 2005 (the emissions at this plant were only changed 

for the RFS2 case). 

4.2 2022 AEO Nonpoint sources 

The nonpoint sources are sources aggregated to the county (or Canadian Province) and process level and 

included US fugitive dust sources (afdust sector), US agricultural NH3 (ag sector), US average fires (avefire 

sector), other US nonpoint sources (nonpt sector), and emissions for Canada and Mexico (othar and 

othar_hg). Of these, the nonpt sector contained the most detailed changes for the RFS2 modeling, as 

explained further below. 

The emissions used for this case for the afdust and ag sectors are the same as those used in 2020 in the 2002-

based v3 platform, previously referenced. Additionally, the avefire emissions are the same as those in the 

2005ci_tox_05b case mentioned above, and were intentionally held constant between the 2005 base case and 

the 2022 AEO case and all other 2022 cases. 

The emissions for Canada and Mexico were the same as the 2002 v3 platform referenced earlier, with one 

minor exception: we modified the Canada nonroad sources to remove C3 commercial marine SCC 

(2280003010), which was just one record in British Columbia and which prevented double-counting with the 

seca_c3 sector. This means that the RFS2 platform differs from the v4 platform in that older estimates of 

2020 emissions were used for nonpoint sources in Canada, rather than 2006 estimates retained between the 

base and future years in the v4 platform. This sector includes both nonroad mobile and nonpoint sources. 

The nonpt sector is comprised of several different pieces. Like the ptnonipm sector, the nonpt sector 

required two steps to compile the 2022 AEO inventories: data projected from 2005 values and data that are 

replaced by OTAQ-generated data in 2022. 

4.2.1 Part 1: Projecting 2005 to 2022 AEO for nonpt 

The same steps taken and described for the ptnonipm sector (Section 4.1.1) were also taken for the nonpt 

sector. In fact, all of the information that we added to the SMOKE projection and control packets has already 

been described in that section and the parts that also applied to the nonpt sector have already been identified 

in that section. 

In addition to the documentation provided previously for ptnonipm, the 2020 projection factors for 

Residential Wood Combustion SCCs in this nonpt sector were not updated for 2022 because the difference 

would have been very small and these emissions are highly uncertain. 

The refueling and gasoline distribution projection approaches described in the point source section also apply 

to the nonpoint sector, since those approaches affect SCCs in both sectors. 

4.2.2 Part 2: Additional OTAQ-supplied emissions data for nonpt 

In addition to the nonpt emissions projected from 2005 to 2022, several additional OTAQ-provided emission 

inventories were created to complete the emissions needed for the 2022 AEO nonpt sector: 
16

1. Ethanol plant additions: These are conceptually the same as the ptnonipm plant additions but are for 

plants with unknown coordinates, and are therefore aggregated to the county-SCC level. SCC 

assignments determine spatial allocation using spatial surrogate ancillary data. The nonpoint ethanol 

plants were created from an Excel® spreadsheet provided by Craig Harvey on 11/17/2008: 

Corn_EtOH_Plant_Inv_2022-aeo.xls. The same VOC adjustments and SCC assignments detailed for 

ptnonipm were made here as well. 

2. Ethanol transfer additions: These new VOC emissions account for vapor loss during transport and 

loading by truck and rail are assigned three SCCs (30205031, 30205052, and 30205053). Ethanol 

transfer emissions were provided for AEO on 12/11/2008 by Craig Harvey in an Excel® workbook 

called “EtOH_transport_vapor_AEO.xls”. 

3. Biodiesel plant additions: These new emissions are assigned SCC 2102006001 and also contain an 

units correction (grams/year to tons/year) of 1.102311309E-06, applied by OAQPS after receiving 

the data from OTAQ. These data were created from an Excel® spreadsheet provided by Craig Harvey 

on 11/21/2008: Biodsl_Plant_Inv_2022-aeo-prelim.xls. We selected the SCC 2102006001 

(Stationary Source Fuel Combustion;Industrial;Natural Gas;All Boiler Types) to represent these 

sources in consultation with Ron Ryan. The VOC was not adjusted by 65% like it was for ethanol 

and cellulosic plants. OAQPS converted emissions from grams to tons. 

4. Portable Fuel Containers: These MSAT-based emissions were provided by OTAQ for the year 2020 

for the 2002v3 platform and are unchanged for the 2022 AEO case. We applied adjustment factors 

(provided by OTAQ) to the RFS1 and RFS2 cases. 

4.3 Mobile sources 

The mobile sources included many different approaches, depending on the modeling sector. Each of these is 

described in a separate subsection below. 

4.3.1 US Aircraft, locomotive, and non-c3 commercial marine (alm_no_c3) 

This sector has traditionally been projected from a base year (e.g., 2005) to a future year (e.g., 2022); 

however, so many elements of these data were developed specifically for RFS2 that we created a new 

program to combine all the pieces (ALM_no_C3_create_2022.sas), which includes some leftover projection 

steps normally done in SMOKE. This program creates three inventories in SMOKE’s One Record per Line 

(ORL) nonroad format: 

1. C1 and C2 CMV: Class 1 and class 2 Commercial Marine Vehicle SCCs (2280002100, 2280002200, 

and 2280004000) complete inventory created by OTAQ for each of the 2022 RFS2 scenarios. For 

this case, data were provided by Penny Carey on 12/10/2008 in Excel® file: 

CMV_C1C2_2022RFS2cases.xls. We applied HAP factors to VOC to obtain 1,3-butadiene, 

acetaldehyde, acrolein, benzene, and formaldehyde, and applied factors to PM10 to compute 

naphthalene. The remaining HAPs -metals and other non-VOC HAPs not already provided- are held 

at base year levels (the 2002 emissions estimates used in the 2005 basecase). 

2. Class 1 Locomotives: This group includes the class 1 locomotives SCC (2285002006), though a very 

small amount of the class 2 and 3 emissions were also captured by this SCC. Emissions data were 

provided by OTAQ (Craig Harvey) 11/17/2008 in the data file: 

Class_I_II_III_locomotives_alm_2020ce_cty_scc_aeo.xls. These data included CAP emissions as 

well as HAP emissions for 1,3-butadiene, acetaldehyde, acrolein, benzene, formaldehyde, and 
17

naphthalene. Tribal data (SMOKE region code=88206) from the 2005 NEI were retained. The 

remaining HAPs -metals and other non-VOC HAPs not provided- are held at base year levels (the 

2002 emissions estimates used in the 2005 basecase). 

3. Remaining alm_no_c3 emissions: These emissions are the leftover alm_no_c3 emissions after 

removing the data provided and computed in (1) and (2) above. These emissions are limited to 

aircraft and non-class 1 locomotives. For aircraft, all CAPs and VOC HAPs are projected to year 

2022 using FAA TAF data. This is same approach and FAA TAF output as used for year 2020 

projections in 2002v3 and 2002v3.1-based platforms, except we used 2022 activity data instead of 

2020. Metals and non-VOC HAP aircraft emissions were held at base year levels (2002 emissions 

estimates used for 2005). We projected the other component of this file, non-class 1 locomotive 

emissions (SCCs=228500200##, where # = 07, 08, 09, and 10) using the final Locomotive-Marine 

Rule projection factors for year 2020 for CAPs and VOC HAPs. Non-VOC HAPs are also held at 

2005 base year levels. For California, we applied locomotive/marine controls to diesel pleasure craft 

SCCs (2282020005, 2282020010) to project from 2005 to 2022. 

4.3.2 Canada and Mexico onroad mobile sources (othon) 

The data in this sector are the same as 2020 data released in 2002-based v3 platform, previously referenced. 

These are different from 2005 v4 platform because the 2006 Canadian data were not available for use in this 

project. 

4.3.3 C3 commercial marine sources from all waters (seca_c3) 

The seca_c3 sector emissions data were provided by OTAQ in an ASCII raster format used since the ECAIMO project began in 2005. (S)ECA C3 year 2022 reference (AEO and RFS1) and control (RFS2) 

inventories were provided by OTAQ (Penny Carey) 11/20/2008: 2022base_redo.zip and 2022rfs2.zip. 

Penny Carey also provided factors to compute HAP emission (based on emissions ratios) on 2/28/2008, 

which OAQPS applied to either VOC or PM2.5 to obtain HAP emissions values. Table 8 below shows these 

factors and whether they were applied to VOC or PM2.5. As with the 2005 case, this sector uses CAP-HAP 

VOC integration. The “base” dataset is used for both AEO and RFS1 cases and different data are used for 

the RFS2 case. 

Table 8: HAP emission ratios for generation of HAP emissions from criteria 

emissions for C3 commercial marine vessels. 

Pollutant Apply to Pollutant Code Factor 

Acetaldehyde VOC 75070 0.0002286 

Benzene VOC 71432 9.795E-06 

Formaldehyde VOC 50000 0.0015672 

Benz[a]Anthracene PM2_5 56553 5.674E-07 

Benzo[a]Pyrene PM2_5 50328 1.844E-07 

Benzo[b]Fluoranthene PM2_5 205992 1.56E-07 

Benzo[k]Fluoranthene PM2_5 207089 1.56E-07 

Chrysene PM2_5 218019 9.929E-08 

Indeno[1,2,3-c,d]Pyrene PM2_5 193395 1.418E-08 

Acenaphthene PM2_5 83329 3.404E-07 

Acenaphthylene PM2_5 208968 5.248E-07 

Anthracene PM2_5 120127 5.248E-07 

Benzo[g,h,i,]Perylene PM2_5 191242 1.277E-07 
18

Pollutant Apply to Pollutant Code Factor 

Fluoranthene PM2_5 206440 3.12E-07 

Fluorene PM2_5 86737 6.95E-07 

Naphthalene PM2_5 91203 1.987E-05 

Phenanthrene PM2_5 85018 7.943E-07 

Pyrene PM2_5 129000 5.532E-07 

Beryllium PM10 7440417 5.459E-07 

Cadmium PM10 7440439 7.642E-06 

Chromium VI PM10 18540299 2.948E-06 

Chromium III PM10 16065831 1.343E-05 

Lead PM10 7439921 3.002E-05 

Manganese PM10 7439965 5.732E-05 

Nickel PM10 7440020 0.0016377 

Selenium PM10 7782492 1.337E-05 

OAQPS converted emissions to SMOKE point source ORL format allowing for emissions to be allocated to 

modeling layers above the surface layer. OAQPS corrected emissions for one state/county FIPS code fix in 

Rhode Island. All non-US emissions (i.e., in waters considered outside of US territory) are simply assigned 

a dummy state/county FIPS code=98001. Due the huge size of these data, the CAP emissions are in one 

ORL file and the HAP emissions are split into 6 separate ORL files. The emissions spatial extent includes 

waters off of the coasts of the US, Canada, and Mexico, as well as emissions in major waterways and the 

Great Lakes. The SMOKE-ready data have also been cropped from the original data provided by OTAQ to 

cover only the 36km CMAQ domain, which is the largest domain used for this effort. 

4.3.4 US nonroad mobile sources (nonroad) 

All states except California:

OTAQ provided a reference set (NMIM case “Rfs2Ref2022Nr”) of NMIM emissions to be used for all 2022 

RFS2 scenarios. This reference set of monthly emissions includes all 50 states plus DC and all CAPs and 

HAPs of interest. An AEO-specific set of NMIM monthly emissions was also provided for gasoline 

equipment that was used to replace gasoline equipment emissions in the reference set. All NMIM data are 

based on AEO2007 fuels and NMIM county database NCD20080727. We also reassigned NMIM 

evaporative and refueling xylene (compound XYL or CAS=EVP__1330207, RFL__1330207) into MXYL 

(CAS=EVP__108383, RFL__108383) and OXYL (CAS=EVP__95476, RFL__95476) using a 68% and 32% 

ratio to both evaporative and refueling XYL, respectively. We also split NMIM exhaust xylene 

(CAS=EXH__1330207) into MXYL (CAS=EXH__108383) and OXYL (CAS=EXH__95476) using a 74% 

and 26% ratio to XYL, respectively. We converted emissions from monthly totals to monthly average-day 

values based the on number of days in each month. CO2 and all of California emissions were removed prior 

to creating SMOKE ORL files. 

California nonroad:

California monthly nonroad emissions are year 2020 and are based on March 2007 California Air Resources 

Board (CARB) data (Martin Johnson: mjohnson@arb.ca.gov). NH3 emissions are from NMIM runs for 

California (same data as were used in 2020 from the 2002 v3 platform). We allocated refueling emissions to 

the gasoline equipment types based on evaporative mode VOC emissions from the v3 platform 2020 NMIM 

data, and the refueling emissions were computed by multiplying SCC 2505000120 emissions by 0.61, to 

adjust to remove double counting with Portable Fuel Container inventory for California. We estimated HAP 

emissions by applying HAP-to-CAP ratios computed from the California data provided for the 2005 NEI v2, 

collected by EPA (Laurel Driver) 12/2007. This was done because the CARB submittal from March 2007 
19

did not include estimates for HAPs. We retained only those HAPs that are also estimated by NMIM for 

nonroad mobile sources; all other HAPs were dropped. 

4.3.5 Onroad mobile sources (on_moves_runpm, on_moves_startpm, and 

on_noadj) 

As in 2005, the on_moves_runpm and on_moves_startpm sectors include emissions from onroad gasoline 

sources for PM and naphthalene, which need temperature adjustment factors. The temperature adjustment 

factors were specific to 2022 (different from those used in 2005) and we used the same adjustment factors in 

all of the 2022 cases. The temperature adjustments have the limitation that they were based on the use of 

MOVES default inputs rather than county-specific inputs, because a county-specific database for input to 

MOVES was not available at the time this approach was needed. Further, the version of MOVES used for 

all runs was a preliminary version and has since changed. 

Also like 2005, the on_noadj sector includes non-PM MOVES data for gasoline vehicles for some pollutants, 

NMIM-based data for motorcycles, diesel vehicles, and the remaining pollutants for onroad gasoline, as well 

as all California onroad mobile emissions. The detailed approaches described here are the same as those for 

2005 (except for the NMIM and MOVES data used), but are included here for convenience. 

on_moves_startpm and on_moves_runpm

For the on_moves_runpm and on_moves_startpm sectors, the same preprocessing as was done in 2005 was 

done here, but using the 2022 AEO NMIM runs to create the monthly county-to-state ratios by state and SCC 

and using the 2022 PM adjustment factors. The MOVES data used in this project were unique for each of 

the three main 2022 cases (AEO, RFS1, and RFS2), except for the adjustment factors that were the same for 

each case. 

OTAQ supplied three input files containing state-level MOVES-based onroad gasoline emissions by month 

for the following pollutants: 

1. Exhaust: VOC, NOX, CO, 1,3-butadiene (106990), acetaldehyde (75070), acrolein (107028), 

benzene (71432), and formaldehyde (50000); 

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

3. MOVES-speciated PM at 72 degrees: Naphthalene, and what MOVES labels as the OC, EC, and 

SO4 components of PM2.5 –PM25OC, PM25EC, and PM25SO4 respectively. Emissions are 

computed at 72F and we used SAS® and existing technical direction to convert the MOVES-based 

PM2.5 species into the following SMOKE-ready pollutants: 

 NAPHTH_72: unchanged from MOVES-based file, subject to temperature adjustment below 

72F. 

 PEC_72: unchanged from MOVES-based PM25EC, subject to temperature adjustment below 

72F. 

 POC_72: modified MOVES-based PM25OC to remove metals, PNO3 (computed from 

MOVES-based PM25EC), NH4 (computed from MOVES-based PM25SO4 and PNO3), and 

MOVES-based PM25SO4. Subject to temperature adjustment below 72 degrees F. 

 PSO4: unchanged from MOVES-based PM25SO4, not subject to temperature adjustment. 

 PNO3: computed from MOVES-based PM25EC, not subject to temperature adjustment. 

 OTHER: sum of computed metals (fraction of MOVES-based PM25EC) and NH4 (computed 

from PNO3 and PSO4), not subject to temperature adjustment. 
20

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

adjustment below 72 degrees F. 

 PMC_72: Computed as fraction of sum of PMFINE_72, PEC_72, POC_72, PSO4, and 

PNO3. Subject to temperature adjustment below 72 degrees F. 

MOVES gasoline emissions were used for light-duty gasoline vehicles (LGDV), light-duty gasoline trucks 0-

6000 pounds gross vehicle weight (LDGT1), light-duty gasoline trucks 6000-8500 pounds gross vehicle 

weight (LDGT2), and heavy-duty gasoline trucks (HDGV). Motorcycle emissions were not available from 

MOVES at the time of this project and so emissions from that vehicle class came from the case-specific 

NMIM runs. 

MOVES-based, monthly state-level emissions were first allocated to county based emissions using countySCC specific state to county ratios that we created from the 2022 AEO NMIM run. California MOVESbased emissions are discarded; they do not replace the existing California inventories (discussed in on_noadj 

sector). MOVES data were provided by OTAQ (Harvey Michaels) on 01/16/2009. 

In each MOVES file, “start” emissions are represented by SCCs with the SCC characters 8-9 equal to “00”: 

2201001000 (LDGV), 2201020000 (LDGT1), 2201040000 (LDGT2), and 2201070000 (HDGV). These 

start emissions are assigned to urban and rural SCCs based on the county-level ratio of NMIM emissions 

from urban versus local roads. For example, LDGV start emissions (2201001000) were split into urban 

(2201001370) and rural (2201001350) based on the ratio of LDGV emissions from urban (2201001330) and 

rural (2201001210) local roads. 

Finally, the set of emissions are broken into 3 sets: 

1. on_moves_startpm: monthly MOVES-based “start” PM emissions subject to temperature 

adjustments, and PM species not subject to temperature adjustments (e.g., PNO3 and PSO4). These 

are limited to 8 SCCs (urban/rural and 4 vehicle types) for the following pollutants: PEC_72, 

POC_72, PNO3, PSO4, OTHER, PMFINE_72, PMC_72, NAPHTH_72. 

2. on_moves_runpm: monthly MOVES-based “running” PM emissions subject to a different set of 

temperature adjustments compared to “start” emissions; similar to the on_moves_startpm sector, this 

sector includes all PM species, not just those subject to temperature adjustments. The same 

pollutants are provided as on_moves_startpm. 

3. on_noadj MOVES-based emissions: The remaining monthly non-PM MOVES-based emissions that 

are also not subject to temperature adjustments -see inputs (1) and (2) above. These emissions are 

modeled in the on_noadj sector discussed below and include both start and running emissions for 

non-PM pollutants. 

on_noadj

The on_noadj sector contains all US onroad mobile emissions not replaced by MOVES. There are four 

sources of data that are pre-processed to create three sets of monthly inventories for this sector. 

1. MOVES-based non-PM: These are the monthly non-PM, non-naphthalene MOVES-based emissions 

discussed in item #3 in “Outputs” in the on_moves_runpm and on_moves_startpm sector discussion. 

In short, these are non-California, select pollutants exhaust and evaporative (non-refueling) onroad 

gasoline LDGV, LDGT1, LDGT2, and HDGV emissions. 

2. California onroad inventory: California year 2020 complete CAP/HAP onroad inventory. California 

monthly onroad emissions are year 2020 and are based on March 2007 California Air Resources 

Board (CARB) data (Martin Johnson: mjohnson@arb.ca.gov). NH3 emissions are from NMIM runs 
21

for California (same data as were used in 2020v3). We estimated HAP emissions by applying HAPto-CAP ratios computed from California 2005 NEI submittal provided by EPA (Laurel Driver) 

12/2007. This was done because the CARB submittal from March 2007 did not include estimates for 

HAPs. We retained only those HAPs that were also estimated by NMIM for nonroad mobile sources; 

all other HAPs were dropped. 

3. Remaining onroad NMIM-based onroad inventory: The remainder of the non-California onroad 

inventory not replaced by MOVES. This includes monthly emissions for all onroad diesel, all 

motorcycles, all refueling, and onroad LDGV, LDGT1, LDGT2, and HDGV emissions for pollutants 

not covered by MOVES (e.g., SO2, NH3). All NMIM onroad data are based on AEO2007 fuels and 

NMIM county database NCD20080727. 

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

remainder of the on_noadj sector (#3 above). 

OTAQ (Harvey Michaels) provided a reference set (Rfs2Ref2022Or) 12/12/2008 of NMIM emissions to be 

used for all 2022 RFS2 scenarios. This reference set of monthly emissions includes all 50 states plus DC and 

all CAPs and HAPs of interest. An AEO-specific (Rfs2ref2022orVc11aeo) set of NMIM monthly emissions 

was also provided 12/15/2008 by OTAQ (Harvey Michaels) for 816 counties that Oak Ridge National 

Laboratory (ORNL) determined would have enhanced truck traffic for the distribution of ethanol in 2022. 

The only trucks affected are part5vclass=11; hence the “Vc11” designation. (These have been referred to 

previously as “8b trucks,” but Vc11 is more accurate, since it refers to both 8a and 8b.) The adjustments 

were determined by annual VMT in the affected counties. We assumed that trucks made a return trip. The 

adjustments often average a fraction of a percent, but the largest on a county basis is about 6%. These 

“Vc11” emissions replaced the reference case emissions for AEO; similar “Vc11” emissions are also 

substituted for the RFS2 and RFS1 cases.

Similar to nonroad pre-processing, we also reassigned NMIM evaporative and refueling xylene (compound 

XYL or CAS=EVP__1330207, RFL__1330207) into MXYL (CAS=EVP__108383, RFL__108383) and 

OXYL (CAS=EVP__95476, RFL__95476) using a 68% and32% ratio to both evaporative and refueling 

XYL, respectively. We also split NMIM exhaust xylene (CAS=EXH__1330207) into MXYL 

(CAS=EXH__108383) and OXYL (CAS=EXH__95476) using a 74% and 26% ratio to XYL, respectively. 

Emissions were converted from monthly to average-day based the on number of days in each month. CO2

and all of California emissions were removed prior to creating the NMIM-only parts of the final inventory 

files. 

We also removed refueling emissions from the raw NMIM data prior to creating the SMOKE inputs, since 

these emissions were included in the nonpt and ptnonipm sectors. The NMIM refueling data were used with 

existing 2005 refueling emissions to create projection ratios for ptnonipm and nonpt refueling, as previously 

described in Section 4.1.1. 

5 2022 RFS1 Case 

The 2022 RFS1 reference case was intended to represent the emissions associated with only the volume of 

ethanol required by the RFS1 rule. RFS1 required 7.5 billion gallons of renewable fuel in 2012 and later, 

and 6.7 billion gallons of that was considered to be ethanol. A list of inventory datasets used for this and all 

cases is provided in Appendix A. 
22

5.1 2022 RFS1 Point sources 

The point sources for the 2022 RFS1 Case include the same emissions as the 2022 AEO Case for the 

following sectors: US EGU point source (ptipm), sources from Mexico, Canada, and the Gulf of Mexico 

(othpt and othpt_hg). 

For the nonEGU point sources (ptnonipm), some of the data are replaced for the 2022 RFS1 case. These 

differences from the 2022 AEO case are: 

 46 ethanol plants were revised from the 2002 AEO case with new emissions values. Only the 

Chippewa ethanol plant is unchanged in this case. These data were provided by Craig Harvey on 

11/17/2008 in the Excel® dataset “Corn_EtOH_Plant_Inv_2022-rfs1.xls”. 

 Onroad refueling: We used the same overall projection approach for onroad refueling as was used in 

the 2022 AEO case for the ptnonipm and nonpt sectors. Instead of using the 2022 AEO NMIM run, 

we used the RFS1-specific NMIM run for the 2022 refueling ratio calculation, with an additional 

ethanol adjustment factor of 1.0153, provided by David Brzezinski on 12/12/2008. The final formula 

for the projection factors was Factor 2022 = Emis2022 * 1.0153 /Emis2005. We applied these 

factors to the refueling SCCs from the 2005 base case. 

Note that we did not adjust emissions from refineries, bulk-plant-to-pump (btp), or refinery-to-bulk terminal 

(rtb) processes (these adjustments were applied in the AEO and RFS2 cases). Lastly, VOC speciation profile 

changes affected this sector, as described in Section 3. 

5.2 2022 RFS1 Nonpoint sources 

The nonpoint sources for the 2022 RFS1 Case include the same emissions as the 2022 AEO Case for the 

following sectors: US fugitive dust sources (afdust sector), US agricultural NH3 (ag sector), the US average 

fires (avefire sector), and the nonpoint emissions for Canada and Mexico (othar and othar_hg). 

The 2022 RFS1 Case emissions for the “other nonpoint” sector (nonpt) emissions differed from the 2022 

AEO case in the following ways: 

 Revised the ethanol plant emissions. OAQPS converted these data to SMOKE input format using the 

same approaches as in the 2022 AEO case from an Excel® workbook provided by Craig Harvey 

11/17/2008: “Corn_EtOH_Plant_Inv_2022-rfs1.xls”. 

 Revised the ethanol transfer emissions. OAQPS converted these data to SMOKE input format using 

the same approaches as in the 2022 AEO case from an Excel® workbook provided by Craig Harvey 

on 12/15/2008: “EtOH_transport_vapor_RFS1.xls”. 

 Revised biodiesel plant emissions. OAQPS converted these data to SMOKE input format using the 

same approaches as in the 2022 AEO case from an Excel® workbook provided by Craig Harvey on 

11/25/2008: “Biodsl_Plant_Inv_2022-rfs1-prelim.xls”. 

 Created revised PFC emissions by applying adjustment factors by county and pollutant, based on an 

Excel® spreadsheet provided by Ari Kahan on 1/14/2009: “aeo_to_rfs1.xls”. These adjustments 

reduced PFC emissions as compared to the AEO case. 

 As previously mentioned for the point sources, we changed refueling emissions projections, which 

also affected the nonpt sector. 
23

The gasoline distribution adjustments that affected AEO and RFS2 were not relevant to this Case. Lastly, 

VOC speciation profile changes affected this sector, as described in Section 3. 

5.3 2022 RFS1 Mobile sources 

Compared to the 2022 AEO case, the mobile source emissions included changes in all of the mobile source 

sectors except for the C3 commercial marine (seca_c3) and the Canada and Mexico emissions (othon). 

For the aircraft, locomotive, and non-C3 commercial marine (alm_no_c3) emissions, the “remaining 

alm_no_c3 emissions” (item 3 in Section 4.3.1) were unchanged from the 2022 AEO case, but the C1 and C2 

commercial marine emissions and the locomotive class 1 emissions both changed. Otherwise, the processing 

for this sector was the same as for 2005 and 2022 AEO. For the C1/C2 Commercial Marine (SCCs 

2280002100, 2280002200, and 2280004000), OAQPS prepared the SMOKE-ready inventory from an 

Excel® worksheet provided by Penny Carey on 12/10/2008: “CMV_C1C2_2022RFS2cases.xls”. OAQPS 

applied factors also provided by Penny Carey on 12/11/2008 to compute Benzene, Acetaldeyde, 

Formaldehyde, Acrolein, 1,3-butadiene, and naphthalene. 

For the locomotive class 1 emissions, OAQPS create the SMOKE-ready inventory from an Excel®

worksheet provided by Craig Harvey on 11/17/2008: 

“Class_I_II_III_locomotives_alm_2020ce_cty_scc_rfs1.xls”. This CAP-only dataset was updated by Craig 

on 12/10/2008 to include HAP emissions of the key HAPs for RFS2. 

For the nonroad sector, OAQPS made adjustments to the 2022 AEO inventory to create the RFS1 inventory. 

California emissions were not changed, but emissions in all other states were updated. OAQPS used data 

provided by OTAQ for gasoline equipment SCCs to replace those emissions from the reference case 

“Rfs2Ref2022Nr” mentioned in Section 4.3.4. The RFS1 case “Rfs2AqmRFS12022Nr” replaced the 

gasoline equipment SCCs: 2260*, 2265*, 2282005010, 2282005015, 2282010005, and 2285004015. 

Otherwise the steps taken were the same as described for the 2022 AEO case. 

For the US onroad mobile sectors, revised NMIM data were provided by Harvey Michaels in late September 

2008. OAQPS adjusted the reference case emissions “Rfs2Ref2022Or” (mentioned in Section 4.3.5) using 

RFS1-specific NMIM data from case “Rfs2ref2022orVc11rfs1”, which contains adjusted inventories for 497 

counties that ORNL determined would have enhanced truck traffic for the distribution of ethanol in 2022. 

The only trucks affected are part5vclass=11 (these have been referred to previously ad “8b trucks,” but Vc11 

is more accurate, since it refers to both 8a and 8b). The adjustments were determined by annual VMT in the 

affected counties. We assumed that trucks made a return trip. All county-SCC, pollutant-code, emissiontype, month combinations in rfs2ref2022orVc11rfs1 replaced those combinations from the Rfs2Ref2022Or 

NMIM run. These changes affected the emissions in the on_noadj sector directly, and were also used in the 

MOVES emissions allocation step described next.

In addition to the changes in the on_noadj sector, the monthly onroad gasoline emissions were changed using 

a MOVES run specifically for the RFS1 scenario. We allocated the state-SCC MOVES data to county-SCC 

using ratios developed from the RFS1-specific NMIM county-SCC data. Other than the different data used 

for creating the monthly county-SCC SMOKE-ready inventories, we used the same processing steps as 

described for 2005 and the 2022 AEO cases. 

Lastly, VOC speciation profile changes affected this sector, as described in Section 3.
24

6 2022 RFS1 headspace profile sensitivity case 

This case made two updates: (1) revised VOC speciation for the nonroad sector from the 2022 RFS1 

reference case and (2) replaced the E0 headspace vapor VOC speciation profile 8737 profile with profile 

8737B. This second change affects all categories that use this E0 headspace vapor profile. 

In the RFS1 Reference case, the nonroad sector used the same VOC speciation profiles as onroad mobile for 

the exhaust mode. Specifically for exhaust, the RFS1 Reference case used combinations of Tier 1 and Tier 2 

E0 profiles, combinations of Tier 1 and Tier2 E10 profiles, or combinations of all four profiles, depending on 

the county. In other words, some counties got E0, some got E10, some got both E0 and E10, and the mix of 

Tier 1 and Tier2 onroad vehicles was considered in creating composite profiles. 

Since nonroad mobile is not affected by Tier 2 standards, the improved approach that we implemented in this 

case used only Tier 1 E0, Tier 1 E10, or a mixture of E0 and E10, depending on the county. Table 9 below 

shows the different exhaust speciation profiles used for each case: 

Table 9: Comparison of exhaust speciation profiles used for RFS1 headspace profile sensitivity case 

RFS1 Reference 

exhaust VOC speciation codes for 

nonroad mobile 

RFS1 Sensitivity 

exhaust VOC speciation for 

nonroad mobile 

8750 (Tier 1 E0) and 8756 (Tier 2 E0)

OR 

8751 (Tier 1 E10) and 8757 (Tier 2 E10)

OR 

(8750 and 8756 and 8751 and 8757) 

Depending on the county, 

using fractions of Tier 1 and Tier 2 and 

fractions of E10 penetration 

8750 (Tier 1 E0) 

OR 

8751 (Tier 1 E10) 

OR 

8750 and 8751 

Depending on the county, 

using fractions of E10 penetration 

The improved exhaust speciation information was provided by Harvey Michaels on 6/11/2009 in Excel® file 

“Gspro_Combo_Rfs2Aqm2022Rfs1NR.zip”. OAQPS further post-processed these data to reduce the size 

and reformatted into SMOKE-ready format. 

In addition to the exhaust speciation changes, we also replaced the E0 headspace vapor VOC speciation 

profile 8737 profile with profile 8737B. This affects all categories that use this E0 headspace vapor profile. 

This headspace profile part of the sensitivity analysis was done because EPA staff noted that the headspace 

profiles used in the RFS1 and AEO reference case scenarios exhibited a reduction in alkene levels going 

from E0 to E10 that was not consistent with what one would expect as a result of increased ethanol use. In 

these cases, the E0 gasoline headspace profile has 13% of the VOC as alkenes and the E10 profile has an 

alkene content of 4%. To address this inconsistency, EPA adjusted the E0 headspace profile 8737, assuming 

the emissions have an alkene content of 4%, consistent with the percent alkene content of the E10 headspace 

profile. This adjusted profile was designated 8737B. Development of the adjusted profile is described in 

EPA Report No. EPA-420-D-10-001, “Hydrocarbon Composition of Gasoline Vapor Emissions from 

Enclosed Fuel Tanks,” which is included in the docket for this rule. 

This sensitivity affected emissions in the nonroad, nonpt, and ptnonipm sectors. Table 10 below shows the 

affected SCCs with their descriptions (the first 3 levels of the SCC descriptions). For the SCCs categorized 

as “Bulk plant to pump”, the VOC emissions used a combination profile that consistent of 53.78% profile 

8737B and 46.22% profile 8736 (E10 headspace vapor). The SCCs categorized as “Refinery to bulk 

terminal” used the 8737B profile directly. 
25

Table 10: SCCs affected by revised headspace profile in the 2022 RFS1 headspace profile sensitivity case. 

SCC Sector Description SCC Tier1 SCC Tier2 SCC Tier3 40600233 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600235 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600241 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40688805 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Fugitive Em404002** Petroleum and Solvent Evaporation Petroleum Liquids Storage (non-Refinery) Bulk Plants 404004** Petroleum and Solvent Evaporation Petroleum Liquids Storage (non-Refinery) Petroleum 406001** Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Tank Cars 406003** Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Gasoline R406004** Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Filling Vehi406006** Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Consumer 406007** 

ptnonipm 

Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Consumer 

2501011*** Storage and Transport Petroleum and Petroleum Product Storage Residential 2501012*** Storage and Transport Petroleum and Petroleum Product Storage Commercia2501055*** Storage and Transport Petroleum and Petroleum Product Storage Bulk Plants2501060*** Storage and Transport Petroleum and Petroleum Product Storage Gasoline S2505030*** Storage and Transport Petroleum and Petroleum Product Transport Truck 2660000*** 

nonpt 

Bulk plant to 

pump 

(note: for SCCs 

starting with 

404002, all 

SCCs included 

as bulk plant to 

pump except 

for the 3 SCCs 

starting with 

404002 listed in 

the refinery-tobulk section 

below) 

Waste Disposal, Treatment, & Recov Leaking Underground Storage Tanks Leaking Un

40400240 Petroleum and Solvent Evaporation Petroleum Liquids Storage (non-Refinery) Bulk Plants 40400249 Petroleum and Solvent Evaporation Petroleum Liquids Storage (non-Refinery) Bulk Plants 40400260 Petroleum and Solvent Evaporation Petroleum Liquids Storage (non-Refinery) Bulk Plants 40600231 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600232 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600234 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600236 Petroleum and Solvent Evaporation Transportation and arketing of Petroleum Products Marine Ves40600237 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600238 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600239 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600240 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600298 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40600299 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Marine Ves40688803 Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Fugitive Em403001** Petroleum and Solvent Evaporation Petroleum Product Storage at Refineries 403002** Petroleum and Solvent Evaporation Petroleum Product Storage at Refineries 403003** Petroleum and Solvent Evaporation Petroleum Product Storage at Refineries 403010** Petroleum and Solvent Evaporation Petroleum Product Storage at Refineries Fixed Roof 403011** Petroleum and Solvent Evaporation Petroleum Product Storage at Refineries Floating Ro403012** Petroleum and Solvent Evaporation Petroleum Product Storage at Refineries Variable Va404001** Petroleum and Solvent Evaporation Petroleum Liquids Storage (non-Refinery) Bulk Termi406005** 

ptnonipm 

Petroleum and Solvent Evaporation Transportation and Marketing of Petroleum Products Pipeline Pe

2501050*** Storage and Transport Petroleum and Petroleum Product Storage Bulk Termi2505000*** Storage and Transport Petroleum and Petroleum Product Transport All Transpo2505020*** Storage and Transport Petroleum and Petroleum Product Transport Marine Ves2505040*** 

nonpt 

Refinery to bulk 

terminal 

Storage and Transport Petroleum and Petroleum Product Transport Pipeline 
26

7 2022 RFS2 Case 

This case represented the emissions associated with EPA’s best estimate at the time of proposal of the 

renewable fuel volumes that would be used to meet the EISA requirements. This included 34.14 billion 

gallons of ethanol and 0.81 billion gallons of biodiesel. A list of inventory datasets used for this and all cases 

is provided in Appendix A. 

7.1 2022 RFS2 Point sources 

The point sources for the 2022 RFS2 Case include the same emissions as the 2022 AEO Case for the 

following sectors: US EGU point source (ptipm) and sources from Mexico, Canada, and the Gulf of Mexico 

(othpt and othpt_hg). 

For the nonEGU point sources (ptnonipm), some of the data is replaced for the 2022 RFS2 case. These 

differences from the 2022 AEO case are: 

 47 ethanol plants revised from the 2002 AEO case with new emissions values. The only additional 

plant changed in this case that was not changed in the RFS1 Case was the Chippewa ethanol plant 

These data were provided by Craig Harvey on 11/17/2008: in the Excel® dataset 

“Corn_EtOH_Plant_Inv_2022-eisa-fix.xls”. 

 We applied adjustments to refinery emissions by state and SCC, using the same factor for all 

pollutants to represent activity adjustments (note: different adjustments were made to the AEO case, 

and no adjustments were made to the RFS1 case). The state-level adjustments and the list of SCCs 

affected were provided by Rich Cook on 11/25/2008 in Excel® workbook 

“RFS2_Refinery_Adjust.xls”. 

 Onroad refueling: We used the same overall projection approach for onroad refueling as was used in 

the 2022 AEO case for the ptnonipm and nonpt sectors. Instead of using the 2022 AEO NMIM run, 

we used the RFS2-specific NMIM run for the 2022 refueling ratio calculation, with an additional 

ethanol adjustment factor of 1.0153, provided by David Brzezinski on 12/12/2008. The final formula 

for the projection factors was Factor 2022 = Emis2022 * 1.0780 /Emis2005. These factors were 

applied to the refueling SCCs from the 2005 base case. 

 For gasoline distribution SCCs (both ptnonipm and nonpt SCCs), we additionally applied VOC and 

VOC HAP adjustments to SCCs representing emissions from bulk-plant-to-pump (btp) and refineryto-bulk terminal (rtb) processes. These SCC-level adjustments only impact VOC and VOC HAPs in 

both the ptnonipm and nonpt sectors. The adjustments were provided by Craig Harvey on 

12/16/2008 in the Excel® workbook “2005ai_tox_SCC_50state_CAPHAP-20081216.xls”. (Note: 

these adjustments were not applied to RFS1 and different adjustments were applied to AEO, based on 

assumed changes in the ratios of E0 to E10 and E85) 

 Upstream ag-related adjustments described below for the “ag” and “afdust” sectors also affected 

some ptnonipm SCCs. 

Lastly, VOC speciation profile changes affected this sector, as described in Section 3. Emissions were 

otherwise the same as the 2022 AEO case. 

7.2 2022 RFS2 Nonpoint sources 

The nonpoint sources for the 2022 RFS2 Case include the same emissions as the 2022 AEO Case for the 

following sectors: the US average fires (avefire sector), and the nonpoint emissions for Canada and Mexico 

(othar and othar_hg). Changes were made to the ag, afdust, and nonpt sectors. 
27

For the ag and afdust sectors, we adjusted emissions by SCC or SCC-pollutant combinations based on data 

provided by Craig Harvey on 11/7/2008 in Excel® workbook“otaq_upstream_2020cc_2020ce_2005ag_toxcmp.xls”. These adjustments were different for the following different groups of SCCs: “Fertilizer 

Application”, “Pesticide Application”, “Fertilizer Production, mixing/blending”, “Pesticide Production”, “Ag 

Tilling/loading dust”, “Ag Burning”, “Livestock dust”, and “Livestock waste”. 

The emissions for the “other nonpoint” emissions (nonpt) changed for the 2022 RFS2 Case in the following 

ways: 

 Upstream ag-related adjustments just described for the “ag” and “afdust” sectors also affected some 

nonpt SCCs. 

 Revised the ethanol plant emissions. OAQPS converted these data to SMOKE input format using the 

same approaches as in the 2022 AEO case from an Excel® workbook provided by Craig Harvey 

11/17/2008: “Corn_EtOH_Plant_Inv_2022-eisa-fix.xls”. 

 Revised the ethanol transfer emissions. OAQPS converted these data to SMOKE input format using 

the same approaches as in the 2022 AEO case from an Excel® workbook provided by Craig Harvey 

on 12/15/2008: “EtOH_transport_vapor_EISA.xls”. 

 Revised biodiesel plant emissions. OAQPS converted these data to SMOKE input format using the 

same approaches as in the 2022 AEO case from an Excel® workbook provided by Craig Harvey on 

11/25/2008: “Biodsl_Plant_Inv_2022-eisa-prelim.xls”. 

 Added cellulosic ethanol plants. OAQPS converted emissions estimates for cellulosic ethanol plants 

to run in SMOKE, based on an Excel® file provided by Craig Harvey on 10/21/2009: 

“Cellulosic_Plant_Inv_2022-eisa-fixC-RevCell.xls”. 

 Created revised portable fuel container (PFC) emissions by applying adjustment factors by county 

and pollutant, based on an Excel® spreadsheet provided by Ari Kahan on 1/14/2009: 

“aeo_to_eisa.xls”. These adjustments reduced PFC emissions as compared to the AEO case. 

 As previously mentioned for the point sources in Section 7.1, we changed refueling emissions 

projections, which also affected the nonpt sector. 

 As previously mentioned for point sources in Section 7.1, we adjusted the gasoline distribution 

emissions, which also affected the nonpt sector. 

 Speciation changes also affected this case for the nonpt and ptnonipm sectors as noted in Section 3 by 

using the 8737B profile for E0 fuels for refinery to bulk (rtb) emissions sources. 

Lastly, VOC speciation profile changes affected this sector, as described in Section 3. 

7.3 2022 RFS2 Mobile sources 

Compared to the 2022 AEO case, the mobile source emissions included changes in all of the mobile source 

sectors except for the Canada and Mexico emissions (othon). 

For the aircraft, locomotive, and non-C3 commercial marine (alm_no_c3) emissions, the “remaining 

alm_no_c3 emissions” (item 3 in Section 4.3.1) were unchanged from the 2022 AEO case, but the C1 and C2 

commercial marine emissions and the locomotive class I emissions both changed. Otherwise, the processing 

for this sector was the same as for 2005 and 2022 AEO. For the C1/C2 Commercial Marine (SCCs 

2280002100, 2280002200, and 2280004000), OAQPS prepared the SMOKE-ready inventory from an 

Excel® worksheet provided by Penny Carey on 12/10/2008: “CMV_C1C2_2022RFS2cases.xls”. OAQPS 
28

applied factors also provided by Penny Carey on 12/11/2008 to compute benzene, acetaldehyde, 

formaldehyde, acrolein, 1,3-butadiene, and naphthalene. Although the process was the same, these 

emissions differed from those in the AEO and RFS1 cases. 

For the locomotive class I emissions, OAQPS create the SMOKE-ready inventory from an Excel® worksheet 

provided by Craig Harvey on 11/17/2008: “Class_I_II_III_locomotives_alm_2020ce_cty_scc_eisa.xls”. 

This CAP-only dataset was updated by Craig on 12/10/2008 to include HAP emissions of the key HAPs for 

RFS2. 

For the C3 commercial marine sources, new inventory data were provided in the same pre-gridded formats as 

for 2005 and 2022 AEO by Penny Carey on 11/20/2008: “2022base_redo.zip and 2022rfs2.zip”. OAQPS 

pre-processed these data using the same approaches described previously to create SMOKE-ready point 

source inventories (with each “point” representing a grid cell). Otherwise, the processing for this sector was 

the same as 2005 and 2022 AEO. 

For the US nonroad sector, OAQPS made adjustments to the 2022 AEO inventory to create the RFS2 

inventory. California emissions were not changed, but emissions in all other states were updated. OAQPS 

used data provided by OTAQ for gasoline equipment SCCs to replace those emissions from the reference 

case “Rfs2Ref2022Nr” mentioned in section 4.3.4. The RFS2 case “Rfs2AqmE102022Nr” replaced the 

gasoline equipment SCCs: 2260*, 2265*, 2282005010, 2282005015, 2282010005, and 2285004015. 

Otherwise the steps taken were the same as described for the 2022 AEO case. 

For the US onroad mobile sectors, revised NMIM data were provided by Harvey Michaels in late September 

2008. OAQPS adjusted the reference case emissions “Rfs2Ref2022Or” (mentioned in Section 4.3.5) using 

RFS2-specific NMIM data from case “Rfs2ref2022orVc11eisa”, which contains adjusted inventories for 

1023 counties that ORNL determined would have enhanced truck traffic for the distribution of ethanol in 

2022. The only trucks affected are part5vclass=11 (these have been referred to previously ad “8b trucks,” 

but Vc11 is more accurate, since it refers to both 8a and 8b). The adjustments were determined by annual 

VMT in the affected counties. We assumed that trucks made a return trip. All county-SCC, pollutant-code, 

emission-type, month combinations in rfs2ref2022orVc11eisa replaced those combinations in 

Rfs2Ref2022Or. These changes affected the emissions in the on_noadj sector directly, and were also used in 

the MOVES emissions allocation step described next.

In addition to the changes in the on_noadj sector, the monthly onroad gasoline emissions were changed using 

a MOVES run specifically for the RFS2 scenario. We allocated the state-SCC MOVES data to county-SCC 

using ratios developed from the RFS2-specific NMIM county-SCC data. Other than the different data used 

for creating the monthly county-SCC SMOKE-ready inventories, we used the same processing steps as 

described for 2005 and the 2022 AEO cases. 

Lastly, VOC speciation profile changes affected this sector, as described in Section 3.

8 2022 RFS2 nonroad speciation sensitivity case 

The purpose of this case was to test the impact of improving the nonroad speciation approach from the 

approach used in the 2022 RFS2 case. In the 2022 RFS2 case, the same mixtures of fuels as onroad were 

assumed for the nonroad exhaust and evaporative VOC emissions, and for refueling VOC speciation we 

assumed a mixture of 81% E10 (profile 8736) and 19% E85 (profile 8755). For this sensitivity, we revised 

our approach to assume 100% E10 fuel usage for nonroad mobile, which meant profile 8751 for exhaust 

VOC, profile 8754 for evaporative VOC, and profile 8736 for refueling VOC. Thus, this sensitivity was able 

to help quantify the modest magnitude of the impact of the original VOC speciation assumptions. 
29

Given the timing of this sensitivity run, it did not include the revised E0 headspace vapor VOC speciation 

profile 8737B, but rather used the original 8737 profile that was also used in the 2022 RFS1 and 2022 AEO 

cases. 

In addition, this sensitivity did not include the cellulosic ethanol plant emissions that were included in the 

2022 RFS2 case, because we ran this sensitivity prior to adding those emissions to the RFS2 case. Since this 

run was compared primarily to the RFS1 case for the purposes of the nonroad mobile speciation impacts, this 

sensitivity was still useful for our analysis. Comparison of this case with the RFS2 case will be confounded 

in areas that have significant emissions from cellulosic ethanol emissions sources. 
30

APPENDIX A 

Approach for Allocating Emission Reductions and Speciating Emissions from 

Finished Fuel Transport and Distribution 

Allocation of Emission Reductions

1) Emission Reductions were estimated for RFS2 at the National-scale as follows for each scenario by 

OTAQ using a spreadsheet tool. References for this spreadsheet tool are: 

 EPA Docket number EPA-HQ-OAR-2005-0161-0537; Renewable Fuels Standard (RFS) 2 

Production/Distribution Emission Impacts Calculation Spreadsheet - AEO Reference Case 

 EPA Docket number EPA-HQ-OAR-2005-0161-0538; RFS2 Production/distribution Emission 

Impacts Calculation Spreadsheet - RFS1 Mandate reference case 

E0 – Refinery to Bulk Terminal 

E0 – Bulk Terminal to Pump 

E10 – Bulk Terminal to Pump 

E85 – Bulk Terminal to Pump 

2) Definitions: 

Refinery to Bulk Terminal = Emissions associated with pipelines and bulk terminals 

Bulk Terminal to Pump = Emissions associated with bulk plants, tank trucks in transit, service station 

unloading, and gasoline service stations, underground tank: breathing and emptying 

3) Assignment of reduction estimates to SCCs: 

There are over 90 SCCs associated with finished fuel transport and distribution. In order to assign reductions 

to SCCs, each SCC must be identified as “refinery to bulk terminal” and “bulk terminal to pump.” Table 

A-1 provides this mapping. 

4) Allocation of emissions to fuel streams: 

In order to calculate percent reduction estimates to apply to each fuel transport and distribution SCC in the 

NEI, emission reductions for each scenario in the categories in Step 1 must be applied to total emissions in 

the platform for those categories. That means total emissions from the platform must first be allocated to 

“refinery to bulk terminal” and “bulk terminal to pump” using the allocation in Step 3. Then “bulk terminal 

to pump” emissions must be assigned to E0, E10 and E85 using national fuel volumes for the scenarios. The 

national fuel volumes are given in Table A-1. Due to the complexity with determining differences in 

volumes for each fuel type across geographic areas for different SCCs, we will not account for local 

differences. Once the national emissions in the platform are allocated, and emission reductions from the 

spreadsheet tool can be used to calculate percent change estimates, and these percent change estimates 

applied to each SCC. 
31

Table A-1. E0, E10 and E85 fuel volumes for RFS2 scenarios in 2022 (billions of gallons). 

Scenario 

RFS1 AEO RFS2 

E0 77.95 16.03 0 

E10 67 131 124.6 

E85 0 0.1097 29.3 

Application of Speciation Profiles

The most straightforward approach for speciating emissions is to apply the following speciation profiles: 

E0 – Profile 8737: Composite profile - Non-oxygenated gasoline headspace vapor (except 8734 nonoxygenated gasoline composite profile for splash filling). For an RFS1 sensitivity case and for the RFS2 

case, profile 8737B was used instead. See EPA document number EPA-420-D-10-001 “Hydrocarbon 

Composition of Gasoline Vapor Emissions from Enclosed Fuel Tanks” for more information about this 

profile. 

E10 -- 8736: Composite profile - ethanol blended gasoline headspace vapor (except 8733 Composite ProfileEthanol blended gasoline) 

E85 – Profile for light-duty gasoline evaporative emissions (attached). 

The E0 profile would be applied to all SCCs representing refinery to bulk terminal emissions. For the 

remaining SCCs, E0, E10 and E85 profiles are be weighted by national fuel sales volumes to come up with 

composite profiles for each control scenario.
32

Table A-2. Mapping of Fuel Distribution SCCs to “Refinery to Bulk Terminal” and “Bulk Terminal to 

 Pump” Categories. 

Assignment

NONPOINT

GASOLINE DISTRIBUTION: STAGE I 

SCCs: 2501050120 (Bulk Terminals) Refinery to Bulk Terminal

2501055120 (Bulk Plants) Bulk Terminal to Pump

2505030120 (Tank Trucks in Transit) Bulk Terminal to Pump

2505040120 (Pipelines) Refinery to Bulk Terminal

2501060051 (Gasoline Service Station Unloading: Submerged Fill) Bulk Terminal to Pump

2501060052 (Gasoline Service Station Unloading: Splash Fill) Bulk Terminal to Pump

2501060053 (Gasoline Service Station Unloading: Balanced Submerged Fill) Bulk Terminal to Pump

2501060201 (Gasoline Service Stations, Underground Tank: Breathing and Emptying) Bulk Terminal to Pump

GASOLINE DISTRIBUTION: STAGE II

SCC: 2501060100 (Gasoline Service Stations, Stage 2: Total) Bulk Terminal to Pump

POINT

40400103 Bulk Terminals, Gasoline Reid vapor pressure (RVP) 7: Breathing Loss (67000 Bbl. Capacity) - Fixed R Refinery to Bulk Terminal

40400104 Bulk Terminals, Gasoline RVP 13: Breathing Loss (250000 Bbl Capacity)-Fixed Roof Tank Refinery to Bulk Terminal

40400105 Bulk Terminals, Gasoline RVP 10: Breathing Loss (250000 Bbl Capacity)-Fixed Roof Tank Refinery to Bulk Terminal

40400106 Bulk Terminals, Gasoline RVP 7: Breathing Loss (250000 Bbl Capacity) - Fixed Roof Tank Refinery to Bulk Terminal

40400107 Bulk Terminals, Gasoline RVP 13: Working Loss (Diam. Independent) - Fixed Roof Tank Refinery to Bulk Terminal

40400108 Bulk Terminals, Gasoline RVP 10: Working Loss (Diam. Independent) - Fixed Roof Tank Refinery to Bulk Terminal

40400109 Bulk Terminals, Gasoline RVP 7: W orking Loss (Diam. Independent) - Fixed Roof Tank Refinery to Bulk Terminal

40400110 Bulk Terminals, Gasoline RVP 13: Standing Loss (67000 Bbl Capacity)-Float. Roof Tank Refinery to Bulk Terminal

40400111 Bulk Terminals, Gasoline RVP 10: Standing Loss (67000 Bbl Capacity)-Float. Roof Tank Refinery to Bulk Terminal

40400112 Bulk Terminals, Gasoline RVP 7: Standing Loss (67000 Bbl Capacity)- Floating Roof Tank Refinery to Bulk Terminal

40400113 Bulk Terminals, Gasoline RVP 13: Standing Loss (250000 Bbl Capacity) - Floating Roof Tank Refinery to Bulk Terminal

40400114 Bulk Terminals, Gasoline RVP 10: Standing Loss (250000 Bbl Capacity) - Floating Roof Tank Refinery to Bulk Terminal

40400115 Bulk Terminals, Gasoline RVP 7: Standing Loss (250000 Bbl Capacity) - Floating Roof Tank Refinery to Bulk Terminal

40400116 Bulk Terminals, Gasoline RVP 13/10/7: Withdrawal Loss (67000 Bbl Capacity) - Floating Roof Tank Refinery to Bulk Terminal

40400117 Bulk Terminals, Gasoline RVP 13/10/7: Withdrawal Loss (250000 Bbl Capacity) - Floating Roof Tank Refinery to Bulk Terminal

40400118 Bulk Terminals, Gasoline RVP 13: Filling Loss (10500 Bbl Capacity) - Variable Vapor Space Refinery to Bulk Terminal

40400119 Bulk Terminals, Gasoline RVP 10: Filling Loss (10500 Bbl Capacity) - Variable Vapor Space Refinery to Bulk Terminal

40400120 Bulk Terminals, Gasoline RVP 7: Filling Loss (10500 Bbl Capacity) - Variable Vapor Space Refinery to Bulk Terminal

40400131 Bulk Terminals, Gasoline RVP 13: Standing Loss - External Floating Roof w/ Primary Seal Refinery to Bulk Terminal

40400132 Bulk Terminals, Gasoline RVP 10: Standing Loss - External Floating Roof w/ Primary Seal Refinery to Bulk Terminal

40400133 Bulk Terminals, Gasoline RVP 7: Standing Loss - External Floating Roof w/ Primary Seal Refinery to Bulk Terminal

40400141 Bulk Terminals, Gasoline RVP 13: Standing Loss - External Floating Roof w/ Secondary Seal Refinery to Bulk Terminal

40400142 Bulk Terminals, Gasoline RVP 10: Standing Loss - External Floating Roof w/ Secondary Seal Refinery to Bulk Terminal

40400143 Bulk Terminals, Gasoline RVP 7: Standing Loss - External Floating Roof w/ Secondary Seal Refinery to Bulk Terminal

40400148 Bulk Terminals, Gasoline RVP 13/10/7: Withdrawal Loss - External Floating Roof (Primary/Secondary SRefinery to Bulk Terminal

40400150 Bulk Terminals, Miscellaneous Losses/Leaks: Loading Racks Refinery to Bulk Terminal

40400151 Bulk Terminals, Valves, Flanges, and Pumps Refinery to Bulk Terminal

40400152 Bulk Terminals, Vapor Collection Losses Refinery to Bulk Terminal

40400153 Bulk Terminals, Vapor Control Unit Losses Refinery to Bulk Terminal

40400161 Bulk Terminals, Gasoline RVP 13: Standing Loss - Internal Floating Roof w/ Primary Seal Refinery to Bulk Terminal

40400162 Bulk Terminals, Gasoline RVP 10: Standing Loss - Internal Floating Roof w/ Primary Seal Refinery to Bulk Terminal

40400163 Bulk Terminals, Gasoline RVP 7: Standing Loss - Internal Floating Roof w/ Primary Seal Refinery to Bulk Terminal

40400171 Bulk Terminals, Gasoline RVP 13: Standing Loss - Internal Floating Roof w/ Secondary Seal Refinery to Bulk Terminal

40400172 Bulk Terminals, Gasoline RVP 10: Standing Loss - Internal Floating Roof w/ Secondary Seal Refinery to Bulk Terminal

40400173 Bulk Terminals, Gasoline RVP 7: Standing Loss - Internal Floating Roof w/ Secondary Seal Refinery to Bulk Terminal

40400178 Bulk Terminals, Gasoline RVP 13/10/7: Withdrawal Loss - Internal Float Roof (Primary/Secondary Seal)Refinery to Bulk Terminal

SCC SCC Description

40400201 Bulk Plants, Gasoline RVP 13: Breathing Loss (67000 Bbl Capacity) - Fixed Roof Tank Bulk Terminal to Pump

40400202 Bulk Plants, Gasoline RVP 10: Breathing Loss (67000 Bbl Capacity) - Fixed Roof Tank Bulk Terminal to Pump

40400203 Bulk Plants, Gasoline RVP 7: Breathing Loss (67000 Bbl. Capacity) - Fixed Roof Tank Bulk Terminal to Pump

40400204 Bulk Plants, Gasoline RVP 13: Working Loss (67000 Bbl. Capacity) - Fixed Roof Tank Bulk Terminal to Pump

40400205 Bulk Plants, Gasoline RVP 10: Working Loss (67000 Bbl. Capacity) - Fixed Roof Tank Bulk Terminal to Pump

40400206 Bulk Plants, Gasoline RVP 7: Working Loss (67000 Bbl. Capacity) - Fixed Roof Tank Bulk Terminal to Pump

40400207 Bulk Plants, Gasoline RVP 13: Standing Loss (67000 Bbl Cap.) - Floating Roof Tank Bulk Terminal to Pump

40400208 Bulk Plants, Gasoline RVP 10: Standing Loss (67000 Bbl Cap.) - Floating Roof Tank Bulk Terminal to Pump

40400209 Bulk Plants, Gasoline RVP 7: Standing Loss (67000 Bbl Cap.) - Floating Roof Tank Bulk Terminal to Pump

40400210 Bulk Plants, Gasoline RVP 13/10/7: Withdrawal Loss (67000 Bbl Cap.) - Floating Roof Tank Bulk Terminal to Pump

40400211 Bulk Plants, Gasoline RVP 13: Filling Loss (10500 Bbl Cap.) - Variable Vapor Space Bulk Terminal to Pump

40400212 Bulk Plants, Gasoline RVP 10: Filling Loss (10500 Bbl Cap.) - Variable Vapor Space Bulk Terminal to Pump

40400213 Bulk Plants, Gasoline RVP 7: Filling Loss (10500 Bbl Cap.) - Variable Vapor Space Bulk Terminal to Pump

40400231 Bulk Plants, Gasoline RVP 13: Standing Loss - External Floating Roof w/ Primary Seal Bulk Terminal to Pump

40400232 Bulk Plants, Gasoline RVP 10: Standing Loss - External Floating Roof w/ Primary Seal Bulk Terminal to Pump

40400233 Bulk Plants, Gasoline RVP 7: Standing Loss - External Floating Roof w/ Primary Seal Bulk Terminal to Pump

40400241 Bulk Plants, Gasoline RVP 13: Standing Loss - External Floating Roof w/ Secondary Seal Bulk Terminal to Pump

40400242 Bulk Plants, Gasoline RVP 10: Standing Loss - External Floating Roof w/ Secondary Seal Bulk Terminal to Pump

40400243 Bulk Plants, Gasoline RVP 7: Standing Loss - External Floating Roof w/ Secondary Seal Bulk Terminal to Pump
33

APPENDIX B 

IMPLEMENTATION of SPECIATION PROFILE UPDATE FOR 

FUTURE YEAR “bulk terminal to pump” SCCs 

Speciation approach is provided in: Rich Cook’s writeup (email sent 11/18/2008, file called “Transport AQ 

Inv.doc”) along with the profiles to use via the “GSPRO_COMBO” approach and the fuels data needed to 

compute the linear weights to use for each profile for each future year scenario. It should be noted that the 

bulk terminal to pump SCCs are in both the nonpt and ptnonipm modeling sectors. 

See below table for how the weights are computed from the fuels data. 

All state/county FIPS codes and all months use the same speciation profile combinations based on the table 

from Rich Cook’s writeup (email sent 11/18/2008, file called “Transport AQ Inv.doc”), as follows: 

 RFS1 

billions 

of gallons 

RFS2- 

fraction 

AEO 

billions 

of gallons

AEOfraction 

RFS2 

billions of 

gallons 

RFS2- 

fraction 

E0 77.95 0.5378 16.03 0.1089 0 0.0000 

E10 67 0.4622 131 0.8903 124.6 0.8096 

E85 0 0.1097 0.0007 29.3 0.1904 

Total 144.95 147.14 153.9 

E0 – Profile 8737: Composite profile - Non-oxygenated gasoline headspace vapor (except 8734 nonoxygenated gasoline composite profile for splash filling): use only headspace vapor because VOC emissions 

from SCCs assigned to headspace vapor in the nonpoint inventory are three times higher than the emissions 

from SCCs assigned to gasoline spillage (=933,818/295,259)

E10 -- 8736: Composite profile - ethanol blended gasoline headspace vapor (except 8733 Composite ProfileEthanol blended gasoline): use only headspace vapor since approximating that more emissions assigned to 

headspace than spillage (as discussed above) 

E85 – Profile for light-duty gasoline evaporative emissions: use pre-tier2 since it is the only evaporative E85 

profile available: 8755 
34

Steps taken to represent the approaches above in the modeling cases: 

Step 1: 

 Copy gsref file that is used for future year VOC to the following name: “gsref_rfs2_voc_2022” 

 Change “bulk terminal to pump” sccs in the gsref file to xref to “combo” 

 Change all “refinery to bulk terminal SCCs” to the E0 profile. This is profile 8737 (they are probably 

currently 8736). If there are any 8733 (don’t think there are any), then they should be changed to 

8734 (E0 profile for spillage) 

 Import to Emissions Modeling Framework (data system we use to manage modeling cases) 

 List of “bulk terminal to pump” and refinery to bulk terminal SCCs” provided in Appendix A. 

Step 2: Make 3 new GSPRO_COMBO files 

1. AEO Case: 

gspro_combo_aeo_stationary all counties/months use the following: 

0.1089  Profile 8737 + 0.8903  Profile 8736 + 0.0007  Profile 8755 

2. gspro_combo_rfs1_stationary all counties/months use the following 

0.5378  Profile 8737 + 0.4622  Profile 8736 

3. gspro_combo_eisa_stationary: all counties/months use the following 

0.8096  Profile 8736 + 0.1904  Profile 8755 

Note: even though some stationary source SCCs use gasoline profile spillage, the ratio of nonpoint 

VOC emissions from SCCs assigned to the headspace speciation –to- SCCs assigned to spillage 

speciation is 3 ( 933818/295259) so we will use only headspace for E10. There are no point source 

SCCs assigned to spillage, so headspace is applicable to all point source sector SCCs. 

Step 3: Assign the appropriate gspro_combo stationary datasets to ptnonipm and nonpt sectors in the future 

year cases. No need (and not possible) to concatenate with GSPRO combo from other sectors. 
35

APPENDIX C 

Inventory Data Files Used for Each RFS2 Modeling Case – SMOKE Input Inventory Datasets 

In any of the following dataset names where the placeholder <mon> has been provided, this is intended to 

mean 12 separate files with the <mon> placeholder replaced with either jan, feb, mar, apr, may, jun, jul, aug, 

sep, oct, nov, or dec, each associated with a particular month of the year. 
36

Table C-1: List of inventory data associated with RFS2 modeling cases. 

Case Sector SMOKE input files 

ptipm Annual: ptinv_ptipm_cap2005nei_26aug2008_v2_orl.txt 

 ptinv_ptipm_hap2005agtox_v1_noBAFM_28aug2008_v0_orl.txt Daily: ptday_ptipm_caphap_noncem_2005ag_<mon>_ida.txt Hourly: HOUR_UNIT_2005_*.txt 

ptnonipm ptinv_ptnonipm_xportfrac_2005cap_remainder_24nov2008_v0_orl.txt 

ptinv_ptnonipm_2005caphap_3ethanol_plants_delete_for_all2022_19nov2008_ptinv_ptnonipm_2005caphap_chippewa_delete_for_2022EISA_19nov2008_v0_ptinv_ptnonipm_2005hap_noBAFM_remainder_24nov2008_v0_orl.txt ptinv_ptnonipm_caphap_ethanol_plant_additions_2005_17dec2008_v1_orl.txt 

nonpt arinv_nonpt_pf4_cap_nopfc_08sep2008_v0_orl.txt 

arinv_nonpt_pf4_hap_nopfc_11sep2008_v0_orl.txt arinv_pfc_2002_caphap_27dec2007_v0_orl.txt arinv_nonpt_caphap_ethanol_plant_additions_2005_17dec2008_v0_orl.txt 

afdust arinv_afdust_2002ad_xportfrac_26sep2007_v0_orl.txt ag arinv_ag_cap2002nei_06nov2006_v0_orl.txt alm_no_c3 arinv_alm_no_c3_cap2002v3_30jul2008_v1_orl.txt 

arinv_alm_no_c3_hap2002v4_12sep2008_v0_orl.txt 

nonroad arinv_nonroad_caps_2005v2_<mon>_revised_08sep2008_v0_orl.txt 

arinv_nonroad_haps_2005v2_<mon>_revised_05sep2008_v0_orl.txt 

arinv_nonroad_calif_caphap_2005v2_<mon>_02apr2008_v0_orl.txt 

seca_c3 ptinv_seca_c3_caps2005pf4_31jul2008_v0_orl.txt 

ptinv_seca_c3_haps_east2005pf4_31jul2008_v0_orl.txt ptinv_seca_c3_haps_central2005pf4_31jul2008_v0_orl.txt 

ptinv_seca_c3_haps_west2005pf4_31jul2008_v0_orl.txt ptinv_seca_c3_haps_NonUS_east2005pf4_09sep2008_v0_orl.txt ptinv_seca_c3_haps_NonUS_central2005pf4_09sep2008_v0_orl.txt ptinv_seca_c3_haps_NonUS_west2005pf4_09sep2008_v0_orl.txt 

on_noadj mbinv_onroad_capshaps_2005v2_nmim_not2moves_<mon>_08sep2008_v0_or

mbinv_on_noadj_moves_<mon>_14NOV08_14nov2008_v0_orl.txt mbinv_onroad_calif_caphap_2005v2_<mon>_02apr2008_v0_orl.txt 

on_moves_startpm mbinv_onroad_moves_startpm_<mon>_20oct2008_v0_orl.txt on_moves_runpm mbinv_onroad_moves_runpm_<mon>_20oct2008_v0_orl.txt 

2005 All 

ptfire Master: ptinv_ptfire_2005rfs2_18nov2008_v1_orl.txt 

Daily: ptday_ptfire_<mon>_*2005rfs2_*_v0.orl.txt 
37

Case Sector SMOKE input files 

othar arinv_nonroad_mexico_interior1999_21dec2006_v0_ida.txt 

arinv_nonroad_mexico_border1999_21dec2006_v0_ida.txt arinv_nonroad_Canada_2000_inventory_11feb2008_v2_ida.txt arinv_nonpoint_Canada2000_21dec2006_v0_ida.txt arinv_nonpt_mexico_interior1999_21dec2006_v0_ida.txt arinv_nonpt_mexico_border1999_21dec2006_v0_ida.txt 

othar_hg arinv_area_canada_hg_2000_noduplicates_23jul2008_v0_ida.txt othon mbinv_onroad_Canada2000_07nov2006_v0_ida.txt 

mbinv_onroad_mexico_border1999_21dec2006_v0_ida.txt mbinv_onroad_mexico_interior1999_21dec2006_v0_ida.txt

othpt Canadian point sources from the 2002 platform are proprietary 

ptinv_mexico_border99_03mar2008_v1_ida.txt ptinv_mexico_interior99_05feb2007_v0_ida.txt ptinv_offshore_point_from_2001_platform_07nov2006_v0_ida.txt 

othpt_hg Canadian point sources from the 2002 platform are proprietary ptipm Annual: Same as 2005ai_tox_05b 

Daily: ptday_ptipm_caphap_noncem_2005ag_<mon>_ida.txt  ptday_ptipm_caphap_cem_2005ci_<mon>_ida.txt 

2005 “ci” case 

avefire arinv_avefire_2002ce_21dec2007_v0_ida.txt 

arinv_avefire_2002_hap_18nov2008_v0_orl.txt 

ptipm Annual/seasonal: ptinv_egu_summer_2020_pf31capsHgHCl_19feb2008_v0_or

 ptinv_egu_winter_2020_pf31capsHgHCl_19feb2008_v0_orl.t ptinv_ptipm_hap2005agtox_v1_noBAFM_noHgHCL_07jan2Daily: ptday_ptipm_caphap_noncem_2022ci_31mar_ida.txt  ptday_ptipm_caphap_noncem_2022ci_apr_ida.txt  ptday_ptipm_caphap_cem_2022ci_31mar_ida.txt  ptday_ptipm_caphap_cem_2022ci_apr_ida.txt  ptday_ptipm_hap_cem_2005ci_31mar_ida.txt  ptday_ptipm_hap_cem_2005ci_apr_ida.txt  ptday_ptipm_hap_noncem_2005ag_31mar_ida.txt  ptday_ptipm_hap_noncem_2005ag_apr_ida.txt 

avefire Same as data in base case (2005ci_tox_05b) afdust arinv_afdust_2020ce_02b_BASE_07apr2008_v0_orl.txt 

2022 – All 

othar arinv_nonroad_mexico_interior1999_21dec2006_v0_ida.txt 

arinv_nonroad_mexico_border1999_21dec2006_v0_ida.txt 
38

Case Sector SMOKE input files 

arinv_2020nr_canada_province_17apr2008_v1_ida.txt arinv_2020as_canada_province_05oct2007_v0_ida.txt arinv_nonpt_mexico_interior1999_21dec2006_v0_ida.txt arinv_nonpt_mexico_border1999_21dec2006_v0_ida.txt 

othon mbinv_2020ms_canada_province_05jun2007_v0_ida.txt 

mbinv_onroad_mexico_border1999_21dec2006_v0_ida.txt mbinv_onroad_mexico_interior1999_21dec2006_v0_ida.txt 

othpt Canadian point sources from the 2002 platform are proprietary 

ptinv_mexico_border99_03mar2008_v1_ida.txt ptinv_mexico_interior99_05feb2007_v0_ida.txt ptinv_offshore_point_from_2001_platform_07nov2006_v0_ida.txt 

othar_hg and othpt_hg 

Same as 2005 

ptnonipm ptinv_ptnonipm_2022ci_tox_aeo_05b_AEO_06jan2009_v0_orl.txt 

ptinv_ptnonipm_caphap_ethanol_plant_additions_2022AEO_05jan2009_v1_orptinv_ptnonipm_2005caphap_chippewa_delete_for_2022EISA_19nov2008_v0_

nonpt arinv_nonpt_2022ci_tox_aeo_05b_AEO_29dec2008_v0_orl.txt 

arinv_pfc_caphap2020_02apr2008_v0_orl.txt arinv_nonpt_caphap_biodiesel_plant_additions_2022AEO_18dec2008_v0_orl.t

arinv_nonpt_caphap_ethanol_plant_additions_2022AEO_15dec2008_v0_orl.txt arinv_nonpt_voc_ethanol_transfer_additions_2022AEO_15dec2008_v0_orl.txt 

ag arinv_ag_2020ce_02b_BASE_08apr2008_v0_orl.txt on_noadj mbinv_on_noadj_MOVES_2022rfs_aeo_<mon>_21JAN2009_21jan2009_v0_o

mbinv_on_noadj_rfs2_aeo_caphap2022_<mon>_12jan2009_v0_orl.txt mbinv_onroad_calif_caphap_2020v31_<mon>_17apr2008_v0_orl.txt 

on_moves_startpm mbinv_onroad_moves_startpm_2022rfs_aeo_<mon>_18dec2008_v0_orl.txt on_moves_runpm mbinv_onroad_moves_runpm_2022rfs_aeo_<mon>_18dec2008_v0_orl.txt 

2022 AEO 

seca_c3 ptinv_eca_c3_caps2022BASE_10dec2008_v0_orl.txt 

ptinv_eca_c3_haps_NonUS_central2022BASE_10dec2008_v0_orl.txt ptinv_eca_c3_haps_NonUS_east2022BASE_10dec2008_v0_orl.txt ptinv_eca_c3_haps_NonUS_west2022BASE_10dec2008_v0_orl.txt ptinv_eca_c3_haps_central2022BASE_10dec2008_v0_orl.txt ptinv_eca_c3_haps_east2022BASE_10dec2008_v0_orl.txt ptinv_eca_c3_haps_west2022BASE_10dec2008_v0_orl.txt 
39

Case Sector SMOKE input files 

nonroad arinv_nonroad_rfs2_aeo_caphap2022_<mon>_09jan2009_v0_orl.txt 

arinv_nonroad_calif_caphap_lm_2020v31_<mon>_17apr2008_v0_orl.txt 

alm_no_c3 arinv_alm_no_c3_LOCOMOTIVES_Class1_rfs2_aeo_caphap2022_14dec2008

arinv_alm_no_c3_C1C2_rfs2_aeo_caphap2022_14dec2008_v0_orl.txt 

arinv_alm_no_c3_AIRCRAFT_nonClass1_LOCO_rfs2_aeo_caphap2022_14de

ptnonipm ptinv_ptnonipm_2022ci_tox_rfs1_05b_RFS1_22jan2009_v0_orl.txt 

ptinv_ptnonipm_caphap_ethanol_plant_additions_2022RFS1_26jan2009_v1_orptinv_ptnonipm_2005caphap_chippewa_delete_for_2022EISA_19nov2008_v0_

nonpt arinv_nonpt_2022ci_tox_rfs1_05b_RFS1_22jan2009_v0_orl.txt 

arinv_pfc_rfs2_rfs1_caphap2020_15jan2009_v0_orl.txt arinv_nonpt_caphap_biodiesel_plant_additions_2022RFS1_18dec2008_v0_orl.

arinv_nonpt_caphap_ethanol_plant_additions_2022RFS1_15dec2008_v0_orl.txarinv_nonpt_voc_ethanol_transfer_additions_2022RFS1_15dec2008_v0_orl.txt 

ag Same as 2022 AEO on_noadj mbinv_on_noadj_MOVES_2022rfs_RFS1_apr_09FEB2009_10feb2009_v0_orl

mbinv_on_noadj_rfs2_rfs1_caphap2022_apr_12jan2009_v0_orl.txt mbinv_onroad_calif_caphap_2020v31_apr_17apr2008_v0_orl.txt 

on_moves_startpm mbinv_onroad_moves_startpm_2022rfs_RFS1_<mon>_09FEB2009_10feb2009on_moves_runpm mbinv_onroad_moves_runpm_2022rfs_RFS1_<mon>_09FEB2009_10feb2009seca_c3 Same as 2022 AEO nonroad arinv_nonroad_rfs2_rfs1_caphap2022_<mon>_09jan2009_v0_orl.txt 

arinv_nonroad_calif_caphap_lm_2020v31_<mon>_17apr2008_v0_orl.txt 

2022 RFS1 and RFS1 sensitivity 

alm_no_c3 arinv_alm_no_c3_AIRCRAFT_nonClass1_LOCO_rfs2_all_RFS2_scenarios_ 

caphap2022_14dec2008_v0_orl.txt 

arinv_alm_no_c3_C1C2_rfs2_rfs1_caphap2022_14jan2009_v0_orl.txt arinv_alm_no_c3_LOCOMOTIVES_Class1_rfs2_rfs1_caphap2022_14jan2009

ptnonipm ptinv_ptnonipm_2022ci_tox_eisa_05b_EISA_23jan2009_v0_orl.txt 

ptinv_ptnonipm_caphap_ethanol_plant_additions_2022EISA_27jan2009_v2_or

nonpt arinv_nonpt_2022ci_tox_eisa_05b_EISA_26jan2009_v0_orl.txt 

arinv_nonpt_caphap_biodiesel_plant_additions_2022EISA_18dec2008_v0_orl.

arinv_nonpt_caphap_ethanol_plant_additions_2022EISA_15dec2008_v0_orl.txarinv_nonpt_voc_ethanol_transfer_additions_2022EISA_15dec2008_v0_orl.txt arinv_pfc_rfs2_eisa_caphap2020_15jan2009_v0_orl.txt arinv_nonpt_caphap_cellolosic_plant_additions_2022eisa_21OCT2009_orl.txt 

2022 RFS2 

ag arinv_ag_2022ci_tox_eisa_05b_EISA_27jan2009_v0_orl.txt 
40

Case Sector SMOKE input files 

afdust arinv_afdust_2022ci_tox_eisa_05b_EISA_27jan2009_v0_orl.txt on_noadj mbinv_on_noadj_MOVES_2022rfs_EISA_<mon>_26FEB2009_26feb2009_v0

mbinv_on_noadj_rfs2_eisa_caphap2022_<mon>_14jan2009_v0_orl.txt mbinv_onroad_calif_caphap_2020v31_<mon>_17apr2008_v0_orl.txt 

on_moves_startpm mbinv_onroad_moves_startpm_2022rfs_EISA_<mon>_26FEB2009_26feb2009on_moves_runpm mbinv_onroad_moves_runpm_2022rfs_EISA_<mon>_26FEB2009_26feb2009_seca_c3 ptinv_eca_c3_caps2022EISA_10dec2008_v0_orl.txt 

ptinv_eca_c3_haps_east2022EISA_10dec2008_v0_orl.txt ptinv_eca_c3_haps_central2022EISA_10dec2008_v0_orl.txt ptinv_eca_c3_haps_west2022EISA_10dec2008_v0_orl.txt ptinv_eca_c3_haps_NonUS_east2022EISA_10dec2008_v0_orl.txt ptinv_eca_c3_haps_NonUS_central2022EISA_10dec2008_v0_orl.txt ptinv_eca_c3_haps_NonUS_west2022EISA_10dec2008_v0_orl.txt 

nonroad arinv_nonroad_rfs2_eisa_caphap2022_<mon>_09jan2009_v0_orl.txt 

arinv_nonroad_calif_caphap_lm_2020v31_<mon>_17apr2008_v0_orl.txt 

2022 RFS2, Sensitivity 

nonpt Same as 2022 RFS2 case, but did not include dataset: 

arinv_nonpt_caphap_biodiesel_plant_additions_2022EISA_18dec2008_v0_orl.
41

APPENDIX D 

Ancillary Data Files Used for RFS2 2005 Case Compared to 2005 v4 Platform Data Files 

 

To match the Datasets and Versions listed in this table to actual data files, combine the Dataset name and the 

version number in the following pattern: <Dataset Name>_<Date>_<Version number>.txt, where <Date> is 

the last date of change for that version and will have a unique value for the combination of Dataset Name 

and Version number. 
42

Table D-1: Detailed list of ancillary data differences between RFS2 2005 and 2005 v4 platform 

2005 v4 platform 2005 RFS2 platform 

Description

Environment Variable Sectors Dataset Vsn Dataset Vsn Comment and Impact 

Area-source spatial cross-reference AGREF All sectors amgref_us_can_mex_revised 5 amgref_us_can_allmex3 5 For v4 platform, revised for n

spatial surrogates 

Onroad spatial cross-reference MGREF All sectors amgref_us_can_mex_revised 7 amgref_us_can_allmex3 5 For v4 platform, revised for n

spatial surrogates 

Area and onroad temporal profiles 

ATPRO, MTPRO, PTPRO 

All sectors amptpro_2005_us_can_revised 0 amptpro_2005_us_can 1 For v4 platform, revised for n

temporal profiles 

Area temporal cross-reference 

ATREF, PTREF All sectors amptref_v3_3_revised 1 amptref_v3_3 5 For v4 platform, added SCC

inventory and for WRAP oil a

Onroad temporal cross-reference MTREF All sectors amptref_v3_3_revised 0 amptref_v3_3 5 

For v4 platform, added SCCinventory (but not for WRAP Superceeded by v1 of the sa

Grid descriptions GRIDDESC All sectors griddesc_lambertonly 24 griddesc_lambertonly 13 An older file used for RFS2 wInventory table INVTABLE All sectors invtable_hapcapintegate_cb05s oa_nomp 4 invtable_hapcap_cb05soa 6 

RFS2 used a full toxics appremissions and 2005 v4 platfmost toxics. Impacts only thquality modeling. 

Inventory table INVTABLE 

avefire, ptnonipm, ptipm 

invtable_hapcapnohapuse_cb05soa_nomp 

4 n/a 

Approach for implementing "these sectors was different isame. 

Non-HAP Exclusions for nonpt sector 

NHAP EXCLUDE nonpt nhapexclude_nonpt_pf4 3 nhapexclude_nonpt_pf4 0 

v1 file contains updates for eHAPs associated with the Vgas SCCs since these do noneeded for future year RFS2 platform. 

Elevated configuration file for seca_c3 sector 

PELV CONFIG seca_c3 pelvconfig_seca_c3 0 n/a v4 platform used inline point 

file needed only in v4 platfor

Speciation profiles for INTEGRATE HAPS 

GSPRO All sectors gspro_integratehaps_cb05_tx_p f4 1 gspro_integratehaps_cb05_tx_p f4 0 For v4 platform: Added benz

this record from the "other Hin SOA 

Speciation profiles for TOG GSPRO All sectors gspro_tog_cb05_soa_pf4_pretie r2 1 gspro_tog_nohapuse_cb05_tx_ pf4_pretier2 1 Excluded ald2_primary and 

since not needed 

Speciation profiles static GSPRO All sectors gspro_static_cmaq 9 gspro_static_cmaq 7 For the v4 platform, this data

biogenic profiles to put them 

Speciation profiles speciated VOC GSPRO othpt gspro_speciated_voc 0 n/a 

For the v4 platform, this spethrough the pre-speciated Vprovided by Environment Ca
43

2005 v4 platform 2005 RFS2 platform 

Description

Environment Variable Sectors Dataset Vsn Dataset Vsn Comment and Impact 

Speciation profiles Canada PM GSPRO othpt gspro_pm25_canada_2006_poi nt 0 n/a 

For the v4 platform, this spethe Canadia-specific PM2.5 s

by Environment Canada for PEC, 12% PSO4, 85% PMF

Speciagtino profiles for biogenic emissions 

GSPRO biog gspro_biogenics 0 n/a 

For the v4 platform, this dataspeciation profiles previously 

v7 for the RFS2 effort 

Speciation profiles Other VOC HAP GSPRO All sectors n/a gspro_other_hapvoc 4 

For RFS2, this dataset has tpassed through from inventocreated for RFS2. 

Speciation profiles CHROMIUM GSPRO All sectors n/a gspro_chromium 0 Chromium speciation profile

polltutant approach used in 

Speciation profiles DIESEL PM GSPRO All sectors n/a gspro_dieselpm 1 DIESEL_PM speciation prof

pollutant approach used in R

Speciation profiles METALS GSPRO All sectors n/a gspro_hapmetals 0 HAP metal pass-through pro

pollutant approach used in R

Speciation xref for PM2.5 diesel SCCs but do not produce diesel 

GSREF All sectors gsref_no_dieselpm 1 n/a 

Since the v4 platform did nospecies needed for the multdata set used for the v4 platreferences for diesel SCCs wspecies. The RFS2 platform DIESEL_PM profiles. 

Speciation xref for non-diesel PM2.5 GSREF All sectors gsref_pm25_pf4_nondiesel 8 gsref_pm25_pf4_nondiesel 1 

For the v4 platform, this datav2 point sources as well as WNote that future years of RFthan "v1" of this dataset, and for replicating RFS2 runs. 

Speciation xref for VOC, not yearspecific GSREF All sectors gsref_voc_general 19 gsref_voc_general 9 

For v4 platform, includes upinventory, WRAP oil and gas distribution SCCs. 

Speciation xref for NONHAPVOC, not year-specific 

GSREF All sectors gsref_nonhapvoc_general_upda te 3 gsref_nonhapvoc_general 0 Matches differences betwee

Speciation xref for VOC, year-specific GSREF All sectors gsref_voc_2005 2 gsref_voc_2002 2 

The v4 platform includes gasdeemed not to be year specand updates for 2006 Canad

Speciation xref for NONHAPVOC, year-specific 

GSREF All sectors gsref_nonhapvoc_2005 1 gsref_nonhapvoc_2002 1 Matches differences betwee
44

2005 v4 platform 2005 RFS2 platform 

Description

Environment Variable Sectors Dataset Vsn Dataset Vsn Comment and Impact 

Speciation xref static NOX -- HONO for mobile sources 

GSREF All sectors gsref_static_nox_hono_pf4 3 gsref_static_nox_hono_pf4 2 The v4 platform dataset add

needed for processing the 2

GSREF All sectors gsref_static_integratehap_emv4 2 n/a 

For the v4 platform, this spepasses through the pre-specspecies provided by Environ

Speciation xref for Canada PM GSREF othpt gsref_pm25_canada_2006_poin t 2 n/a 

For the v4 platform, this speassigns the single Canadia-s

recommended by Environmesources. 

Speciation xref DIESEL PM, alm_no_c3 

GSREF 

alm_no_c3 

nonroad on_noadj n/a 

gsref_dieselpm 0 Enables creation of diesel P

Speciation xref NO DIESEL PM, othar GSREF othar n/a gsref_no_dieselpm 0 Prevents creation of diesel PSpeciation xref HAP chromium nonroad sectors 

GSREF 

alm_no_c3 

nonroad seca_c3 

n/a

gsref_chromium_nonroad 1 Enables creation of chromiu

Speciation xref HAP chromium on_noadj sector 

GSREF on_noadj 

n/a

gsref_chromium_onroad 1 Enables creation of chromiu

Speciation xref HAP chromium stationary

sectors 

GSREF 

nonpt ptipm ptnonipm 

n/a

gsref_chromium_stationary 0 Enables creation of chromiu

Speciation xref HAP metals nonroad sectors 

GSREF 

alm_no_c3 nonroad seca_c3 

n/a

gsref_metals_nonroad 0 Enables creation of HAP me

Speciation xref HAP metals stationary sector 

GSREF 

nonpt ptipm ptnonipm 

n/a

gsref_metals_stationary 1 Enables creation of HAP me

Speciation xref HAP metals nonroad sectors 

GSREF nonroad 

n/a

gsref_metals_nonroad 0 Enables creation of HAP me

Speciation xref HAP metals on_noadj sector 

GSREF on_noadj 

n/a

gsref_metals_onroad 0 Enables creation of HAP me
45

APPENDIX E 

Growth and Control Assumptions and Affected Pollutants for the 2022 AEO Case 

For nonEGU point and stationary area sources, the “2005” inventory data used 2002 emissions. As a result, 

we used our 2002-based approaches for these sectors to project to 2022. Many of these controls have 

effective dates between 2002 and 2005, and therefore would not be applied to a true 2005 inventory value. 

Table E-1: Control Strategies and Projection Assumptions in the 2022 RFS2 AEO Emissions 

Inventories. 

Control Strategies 

(Grouped by Affected Pollutants or Standard and Approach Used to 

Apply to the Inventory) 

Pollutants 

Affected 

Approach or 

Reference: 

Non-EGU Point Controls 

NOX SIP Call (Phase II): 

Cement Manufacturing 

Large Boiler/Turbine Units 

Large IC Engines

NOx 1 

DOJ Settlements: plant SCC controls 

Alcoa, TX 

MOTIVA, DE

NOx, SO2 2 

Refinery Consent Decrees: plant/SCC controls NOx, PM, SO2 3 

Closures, pre-2007: plant control of 100% 

Auto plants 

Pulp and Paper 

Large Municipal Waste Combustors 

Small Municipal Waste Combustors 

Plants closed in preparation for 2005 inventory

all 4 

Industrial Boiler/Process Heater plant/SCC controls for PM PM 5 

Large Municipal Waste Combustors (LMWC) 

PM, Hg, and 

metals 6 

Small Municipal Waste Combustors (SMWC) 

PM, Hg, metals, 

NOx, SO2 6 

MACT rules, national, VOC: national applied by SCC, MACT 

Boat Manufacturing 

Polymers and Resins III (Phenolic Resins) 

Polymers and Resins IV (Phenolic Resins) 

Wood Building Products Surface Coating 

Generic MACT II: Spandex Production, Ethylene manufacture 

Large Appliances 

Miscellaneous Organic NESHAP (MON): Alkyd Resins, Chelating Agents, 

Explosives, Phthalate Plasicizers, Polyester Resins, Polymerized Vinylidene 

Chloride 

Manufacturing Nutritional Yeast 

Oil and Natural Gas 

Petroleum Refineries -Catalytic Cracking, Catalytic Reforming, & Sulfur 

Plant Units 

Pesticide Active Ingredient Production 

Publicly Owned Treatment Works 

Reinforced Plastics 

Rubber Tire Manufacturing 

Asphalt Processing & Roofing 

Combustion Sources at Kraft, Soda, and Sulfite Paper Mills 

Fabric Printing, Coating and Dyeing 

Iron & Steel Foundries 

Metal: Can, Coil 

Metal Furniture 

VOC EPA, 2007f 
46

Control Strategies 

(Grouped by Affected Pollutants or Standard and Approach Used to 

Apply to the Inventory) 

Pollutants 

Affected 

Approach or 

Reference: 

Miscellaneous Metal Parts & Products 

Municipal Solid Waste Landfills 

Paper and Other Web 

Plastic Parts 

Plywood and Composite Wood Products 

Wet Formed Fiberglass Production 

Wood Building Products Surface Coating 

Carbon Black Production 

Cellulose Products Manufacturing 

Cyanide Chemical Manufacturing 

Friction Products Manufacturing 

Leather Finishing Operations 

Miscellaneous Coating Manufacturing 

Organic Liquids Distribution (Non-Gasoline) 

Refractory Products Manufacturing 

Sites Remediation

Solid Waste Rules (Section 129d/111d) 

Hospital/Medical/Infectious Waste Incinerator Regulations NOx, PM, SO2 EPA, 2005 

MACT rules, national, PM: 

Portland Cement Manufacturing 

Secondary Aluminum 

PM 7 

MACT rules, plant-level, VOC: 

Auto Plants VOC 8 

MACT rules, plant-level, PM & SO2: 

Lime Manufacturing PM, SO2 9 

MACT rules, plant-level, PM: 

Taconite Ore PM 10 

Stationary Area Assumptions 

Municipal Waste Landfills: project factor of 0.25 applied, VOC EPA, 2007f 

Livestock Emissions Growth to year 2020 NH3 11 

Residential Wood Combustion Growth and Changeouts to year 2020 all 12 

Gasoline Stage II growth and control to 2022 AEO VOC 13 

Portable Fuel Container growth and control to year 2020 VOC 14 

EGU Point Controls 

CAIR/CAMR/CAVR 

IPM Model 3.0 NOx, SO2, PM 15 

Onroad Mobile and Nonroad Mobile Controls (list includes all key 

mobile control strategies but is not exhaustive) 

National Onroad Rules: 

Tier 2 Rule 

2007 Onroad Heavy-Duty Rule 

Final Mobile Source Air Toxics Rule (MSAT2) 

Renewable Fuel Standard

all 

Local Onroad Programs: 

National Low Emission Vehicle Program (NLEV) 

Ozone Transport Commission (OTC) LEV Program 

VOC 16 
47

Control Strategies 

(Grouped by Affected Pollutants or Standard and Approach Used to 

Apply to the Inventory) 

Pollutants 

Affected 

Approach or 

Reference: 

National Nonroad Controls: 

Clean Air Nonroad Diesel Final Rule – Tier 4 

Control of Emissions from Nonroad Large-Spark Ignition Engines and 

Recreational Engines (Marine and Land Based): “Pentathalon Rule” 

Clean Bus USA Program 

Control of Emissions of Air Pollution from Locomotives and Marine 

Compression-Ignition Engines Less than 30 Liters per Cylinder 

Exhaust emission standards for marine spark-ignition engines and small 

land-based nonroad engines 

all 17, 18, 19 

Aircraft, Locomotives, and Commercial Marine Assumptions 

Aircraft: 

Itinerant (ITN) operations at airports to year 2022 all 20 

Locomotives: 

Energy Information Administration (EIA) fuel consumption projections for 

freight rail 

Clean Air Nonroad Diesel Final Rule – Tier 4 

Locomotive Emissions Final Rulemaking, December 17, 1997 

Control of Emissions of Air Pollution from Locomotives and Marine

all EPA, 2007e, 21, 

18 

Commercial Marine: 

EIA fuel consumption projections for diesel-fueled vessels 

OTAQ ECA C3 Base 2022 inventory for residual-fueled vessels 

Clean Air Nonroad Diesel Final Rule – Tier 4 

Emissions Standards for Commercial Marine Diesel Engines, December 29, 

1999 

Tier 1 Marine Diesel Engines, February 28, 2003 

all 21, (EPA, 

2007e) 

AEO-specific inventory adjustments 

Nonpt and ptnonipm: 

Gasoline distribution by SCC: bulk-plant-to-pump (btp) and refinery-tobulk terminal (rtb) processes 

Ethanol plant additions 

VOC 

all 

EPA, 2010 

ptnonipm: 

Refinery adjustments by state and SCC 

Ethanol plant additions 

all 

all 

EPA, 2010 

nonpt: 

Ethanol transfer additions 

Biodiesel Plant additions 

VOC 

all 

EPA, 2010

C1 and C2 Commercial Marine: 

Complete OTAQ inventory replacement with AEO adjustments to year 2022 all EPA, 2010 

Class 1 Locomotives: 

Complete OTAQ inventory replacement with AEO adjustments to year 2022 all EPA, 2010 

ECA C3: 

Complete OTAQ inventory replacement with AEO adjustments for year 

2022 

all EPA, 2010 

Nonroad (not including California): 

AEO-specific gasoline equipment all EPA, 2010 

Onroad (not including California): 

MOVES AEO-specific emissions for onroad gasoline 

AEO-specific Class 8a and 8B truck emissions for 816 counties determined 

to have enhanced truck traffic from ethanol distribution 

all 

all 

EPA, 2010 

APPROACHES: 

1. Used Emission Budget Inventories report (EPA, 1999) for list of SCCs for application of controls, and for 

percent reductions (except IC Engines). Used Federal Register on Response to Court decisions (Federal 
48

Register, 2004) for IC Engine percent reductions and geographic applicability 

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 Brenda Shine, EPA, OAQPS 

4. Closures obtained from EPA sector leads; most verified using the world wide web. 

5. Used data list of plants provided by project lead from 2001-based platform; required mapping the 2001 plants 

to 2002 NEI plants due to plant id changes across inventory years 

6. Used data provided by Walt Stevenson, EPA, OAQPS 

7. Same as used in CAIR, except added SCCs appeared to be covered by the rule: both reductions based on 

preamble to final rule. (Portland Cement used a weighted average across two processes ) 

8. Percent reductions recommended and plants to apply to reduction to were based on recommendations by rule 

lead engineer, and are consistent with the reference: EPA, 2007e 

9. Percent reductions recommended are determined from the existing plant estimated baselines and estimated 

reductions as shown in the Federal Register Notice for the rule. SO2 % reduction will therefore be 

6147/30,783 = 20% and PM10 and PM2.5 reductions will both be 3786/13588 = 28% 

10. Same approach used in CAIR: FR notice estimates reductions of "PM emissions by 10,538 tpy, a reduction of 

about 62%." Used same list of plants as were identified based on tonnage and SCC from CAIR. 

11. Except for dairy cows and turkeys (no growth), based in animal population growth estimates from USDA and 

Food and Agriculture Policy and Research Institute. 

12. Expected benefits of woodstoves change-out program: http://www.epa.gov/woodstoves/index.html

13. VOC emission ratios of year 2022 AEO-specific from year 2005 from the National Mobile Inventory Model 

(NMIM) results for onroad refueling including activity growth from VMT, Stage II control programs at 

gasoline stations, and phase in of newer vehicles with onboard Stage II vehicle controls. 

14. VOC and benzene emissions for year 2020 from year 2002 from MSAT rule (EPA, 2007c, EPA, 2007d) 

15. http://www.epa.gov/airmarkets/progsregs/epa-ipm/docs/summary2006.pdf

16. Only for states submitting these inputs: http://www.epa.gov/otaq/lev-nlev.htm

17. http://www.epa.gov/nonroad-diesel/2004fr.htm

18. http://www.epa.gov/cleanschoolbus/

19. http://www.epa.gov/otaq/marinesi.htm

20. Federal Aviation Administration (FAA) Terminal Area Forecast (TAF) System, December 2007: 

http://www.apo.data.faa.gov/main/taf.asp

21. http://www.epa.gov/nonroad-diesel/2004fr.htm