RFS2 Emissions Inventory for Air
Quality Modeling Technical Support
Document
United States
Environmental Protection
Agency
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RFS2 Emissions Inventory for Air
Quality Modeling Technical Support
Document
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
SER&
United States
Environmental Protection
Agency
EPA-420-R-10-005
January 2010
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TABLE OF CONTENTS
ACRONYMS Hi
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 Parti: Proj ecting 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 RFSI Point sources 22
5.2 2022 RF SI Nonpoint sources 22
5.3 2022 RF SI 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
11
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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
EO 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
in
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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 vl 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
IV
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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 scenario representing the original reformulated
fuel standard (RFS1) mandated ethanol volume (6.7
billion gallons)
2022 RFSI case
2022ci tox rfsl
2022 RF SI headspace
profile sensitivity case
2022ci tox rfslv2 sensl
Revised RFS1 case with adjusted nonroad exhaust
speciation and headspace vapor for fuel with zero
percent ethanol (EO) 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
1
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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
IPM sector: ptipm
Non-IPM sector:
ptnonipm
Point source fire
sector: ptfire
Average-fire sector:
avefire
Agricultural sector:
ag
Area fugitive dust
sector: afdust
Remaining nonpoint
sector: nonpt
Nonroad sector:
nonroad
2005 NEI
Sector
Point
Point
Fires
N/A
Nonpoint
Nonpoint
Nonpoint
Mobile:
Nonroad
Description
NEI EGU processes at facilities mapped to the IPM model using
the National Electric Energy Database System (NEEDS) database.
All NEI point source records not matched to the ptipm sector.
Point source fire inventory - contains wildfires and prescribed
burning. Used only for the 2005 model performance case.
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.
NH3 emissions from NEI nonpoint livestock and fertilizer
application.
PM10 and PM2 5 from fugitive dust sources from the NEI nonpoint
inventory.
All nonpoint sources not otherwise included in other emissions
modeling sectors.
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.
Contains HAP
emissions?
Yes
Yes
Yes
Yes
No
No
Yes
Yes
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Platform Sector
Aircraft,
locomotive, marine:
aim no c3
C3 commercial
marine: seca c3
Onroad, except
gasoline PM:
on noadj
Onroad starting
exhaust PM:
on moves startpm
Onroad running
exhaust PM
on moves runpm
Biogenic: biog
Other point sources
not from the NEI:
othpt
Other nonpoint and
nonroad not from
the NEI: othar
Other onroad
sources not from the
NEI: othon
Other point
mercury: othpt hg
Other nonpoint
mercury: othar hg
2005 NEI
Sector
Mobile:
Nonroad
Mobile:
nonroad
Mobile:
onroad+
Mobile:
onroad+
Mobile:
onroad+
N/A
N/A
N/A
N/A
N/A
N/A
Description
Aircraft, locomotive, commercial marine except for c3
commercial marine vessels
C3 commercial marine vessels
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.
MOVES-based onroad mobile start exhaust PM and naphthalene
data. More details provided in the 2005 v4 platform
documentation.
MOVES-based onroad mobile running exhaust PM and
naphthalene data. More details provided in the 2005 v4 platform
documentation.
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.
Point sources from Canada's 2000 inventory, Mexico's 1999
inventory, and off-shore point sources from the 2001 platform
Canada and Mexico nonpoint and nonroad mobile inventories
Canada and Mexico onroad mobile inventories
Canada point Hg
Canada nonpoint Hg
Contains HAP
emissions?
Yes
Yes
Yes
Yes,
naphthalene
only
Yes,
naphthalene
only
No
No
No
No
Yes, Hg only
Yes, Hg only
Some data used for footnoted sectors are not contained in the 2005 NEI vl 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.
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Table 3: Comparison of model species in 2005 v4 platform and RFS2 platform
Description
Carbon Monoxide
Nitrogen Oxide
Nitrogen Dioxide
Nitrous acid
Ammonia
Sulfur dioxide
Sulfuric acid vapor
PM2 5 Elemental carbon
PM25 Organic carbon
PM2 5 primary nitrate
PM2 5 primary sulfate
PM25 other
PM Coarse (PM10-PM2 5)
Acetaldehyde
Higher aldehydes
Ethene
Ethane
Ethanol
Formaldehyde
Internal olefin carbon bond
Isoprene
Methanol
Nonreactive VOC
Nonvolatile (from VOC mass)
Terminal olefin carbon bond
Parrafin carbon bond
Toluene and other monoalkyl
aromatics
Unknown VOC
Unreactive VOC
Xylene and other polyalkyl
aromatics
Sequiterpenes
Terpene
Benzene
Chlorine
Hydrochloric acid
Divalent gaseous mercury
Elemental mercury
Paniculate mercury
Naphthalene from the HAP
inventory
Acrolein from the HAP
inventory
Acetaldehyde from the HAP
inventory
1,3 Butadiene from the HAP
inventory
2005 v4
platform
species
CO
NO
NO2
HONO
NH3
S02
SULF
PEC
POC
PNO3
PSO4
PMFINE
PMC
ALD2
ALDX
ETH
ETHA
ETOH
FORM
IOLE
ISOP
MEOH
NR
NVOL
OLE
PAR
TOL
UNK
UNR
XYL
SESQ
TERP
BENZENE
CL2
HCL
HGIIGAS
HGNRVA
PHGI
RFS2 platform
Species in CMAQ
MPlite
CO
NO
NO2
HONO
NH3
S02
SULF
PEC
POC
PNO3
PSO4
PMFINE
PMC
ALD2
ALDX
ETH
ETHA
ETOH
FORM
IOLE
ISOP
MEOH
NR
NVOL
OLE
PAR
TOL
UNK
UNR
XYL
SESQ
TERP
BENZENE
CL2
HCL
HGIIGAS
HGNRVA
PHGI
NAPHTHALENE
ACROLEIN
ALD2_PRIMARY
BUTADIENE13
Additional RFS2
platform HAP
Species*
ACRYLONITRILE
BR2 C2 12
CARBONTET
CHCL3
CL_ETHE
CL2 C2 12
CL2 ME
CL3_ETHE
CL4_ETHANE1122
CL4 ETHE
DICHLOROBENZE
NE
DICHLOROPROPE
NE
ETOX
HEXAMETHY_DIIS
HYDRAZINE
MAL_ANHYDRIDE
PROPDICHLORIDE
QUINOLINE
TOL_DIIS
TRIETHYLAMINE
DIESEL PEC
DIESEL POC
DIESEL PMFINE
DIESEL_PNO3
DIESEL_PMC
DIESEL PSO4
BERYLLIUM_C
BERYLLIUM F
CADMIUM_C
CADMIUM_F
CHROMHEX_C
CHROMHEX F
CHROMTRI C
CHROMTRI_F
LEAD_C
LEAD F
MANGANESE C
MANGANESE F
NICKEL_C
NICKEL_F
Description
Acrylonitrile
1,2 Dibromoethane
Carbontet
Chloroform
Vinyl Chloride
1,2 Dichloroethane
Methylene Chloride
Trichloroethylene
1,1,2,2 Tetrachloroethane
Perchloroethylene
Dichlorobenzene
Dichloropropene
Ethylene Oxide
Hexamethylene 1,6-
Diisocyanate
Hydrazine
Maleic Anhydride
Propdichloride
Quinoline
2,4-Toluene Diisocyanate
Triethylamine
Diesel PM2 5 elemental carbon
Diesel PM2 5 organic carbon
Diesel PM2 5 primary nitrate
Diesel PM2 5 primary sulfate
Diesel PM2 5 other
Diesel coarse PM
Coarse Beryllium
Fine Beryllium
Coarse Cadmium
Fine Cadmium
Coarse Hexavalent Chromium
Fine Hexavalent Chromium
Coarse Trivalent Chromium
Fine Trivalent Chromium
Coarse Lead
Fine Lead
Coarse Manganese
Fine Manganese
Coarse Nickel
Fine Nickel
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Description
Methane from the HAP
inventory
Formaldehyde from the HAP
inventory
M-isomer of Xylene from the
HAP inventory
O-isomer of Xylene from the
HAP inventory
P-isomer of Xylene from the
HAP inventory
Toluene from the HAP
inventory
2005 v4 RFS2 platform
platform Species in CMAQ
species MP lite
CH4
FORM_PRIMARY
MXYL
OXYL
PXYL
TOLU
Additional RFS2
platform HAP
Species* Description
* 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
Spatial cross references
Temporal cross-
references
Temporal profiles
Speciation cross-
references and
Speciation profiles
Inventory tables
NonHAP exclusions
data
Difference between 2005 v4 platform and RFS2 platform
The 2005 v4 platform data are updated to support the newer (2006) Canadian
inventories that were not available in time for RFS2 modeling.
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.
The 2005 v4 platform dataset adds additional profiles from Environment
Canada to support processing of the 2006 Canadian inventory.
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.
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.
The 2005 v4 platform data has been updated with new oil and gas SCCs not
used for the RFS2 platform.
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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 HC1 emissions for missing ptipm sector HC1 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 ethanol-
heavy 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 l/(453.6 x
2000) x 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
vl 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
vl 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 vl
5) A dataset with HAP emissions from the all other nonEGU sources from the 2005 NEI vl
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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/chi ef/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.
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Table 5: Emissions from ethanol plants added to 2005 vl point inventory (tons/year)
County Name
Swift Co
Chippewa Co
Dodge Co
Sibley Co
Dawson Co
Stevens Co
Wichita Co
Sedgwick Co
Roosevelt Co
Linn Co
Clinton Co
Platte Co
Lyon Co
Peoria Co
Pembina Co
Tazewell Co
Monroe Co
Des Moines Co
Washington Co
Christian Co
Codington Co
Kossuth Co
Riverside Co
Cerro Gordo
Co
Hardin Co
Brown Co
Beadle Co
Pierce Co
Kearney Co
Stearns Co
Crawford Co
State Name
Minnesota
Minnesota
Minnesota
Minnesota
Nebraska
Minnesota
Kansas
Kansas
New Mexico
Iowa
Iowa
Nebraska
Minnesota
Illinois
North
Dakota
Illinois
Wisconsin
Iowa
Nebraska
Kentucky
South
Dakota
Iowa
California
Iowa
Iowa
South
Dakota
South
Dakota
Nebraska
Nebraska
Minnesota
Illinois
St/Co
FIPS
27151
27023
27039
27143
31047
27149
20203
20173
35041
19113
19045
31141
27083
17143
38067
17179
55081
19057
31177
21047
46029
19109
06065
19033
19083
46013
46005
31139
31099
27145
17033
PLANT
Chippewa Valley Ethanol Co LLLP (*)
Granite Falls WWTP (+)
Al-Corn Clean Fuel (+)
Heartland Corn Products (+)
Cornhusker Energy Lexington (CEL)
Diversified Energy Company (DENCO),
LLC
ESE Alcohol Inc.
Abengoa Bioenergy Corporation
Abengoa Bioenergy Corporation
Archer Daniels Midland (ADM)
Archer Daniels Midland (ADM)
Archer Daniels Midland (ADM)
Archer Daniels Midland (ADM)
Archer Daniels Midland (ADM)
Archer Daniels Midland (ADM)
Aventine Renewable Energy, Inc. (formerl
Badger State Ethanol, LLC
Big River Resources, LLC
Cargill (was PGLA-1CO)
Commonwealth Agri-Energy, LLC
Glacial Lakes Energy, LLC (OLE)
Global Ethanol
Golden Cheese Company of CA
Golden Grain Energy LLC
Hawkeye Renewables, LLC
Heartland Grain Fuels, LP
Heartland Grain Fuels, LP
HuskerAg,LLC
KAAPA Ethanol, LLC
Land O' Lakes / Melrose Dairy Proteins
Lincolnland Agri-Energy
CO
29.7
0.0
28.5
51.4
10.5
52.4
3.1
52.4
62.8
964.7
733.2
366.6
154.4
439.8
52.4
385.9
108.9
108.9
328.0
41.9
104.7
209.4
10.5
146.6
115.2
20.9
29.3
54.5
125.7
5.4
58.6
NOX
40.4
0.0
45.0
62.9
30.3
151.6
9.1
151.6
181.9
1,338.4
1,017.2
508.6
214.1
1,273.1
151.6
535.4
315.3
315.3
455.1
121.3
303.1
606.3
30.3
424.4
333.4
60.6
84.9
157.6
363.8
15.8
169.8
voc
155.1
0.7
207.6
378.3
14.3
71.6
4.3
71.6
86.0
418.1
317.7
158.9
66.9
601.9
71.6
167.2
149.0
149.0
142.1
57.3
143.3
286.6
14.3
200.6
157.6
28.7
40.1
74.5
172.0
7.5
80.2
SO2
0.6
0.0
0.5
0.4
38.6
192.9
11.6
192.9
231.5
1,266.3
962.4
481.2
202.6
1,620.4
192.9
506.5
401.2
401.2
430.5
154.3
385.8
771.6
38.6
540.1
424.4
77.2
108.0
200.6
463.0
20.1
216.0
PM25
19.7
0.0
0.0
36.7
1.1
6.5
0.4
5.5
6.6
546.7
415.5
207.8
87.5
365.5
43.5
218.7
13.4
13.4
185.9
5.2
12.9
25.8
1.3
15.3
14.2
2.2
3.1
5.7
15.5
0.7
7.2
PM10
28.4
0.0
24.0
61.6
12.1
60.6
3.6
60.6
72.8
1,248.9
949.2
474.6
199.8
509.3
60.6
499.6
126.1
126.1
424.6
48.5
121.3
242.5
12.1
169.8
133.4
24.3
34.0
63.1
145.5
6.3
67.9
ACROLEIN
0.0001
0.0000
0.0618
0.0000
0.0557
0.2783
0.0166
0.2783
0.3339
2.7827
2.1148
1.0574
0.4452
2.3375
0.2783
1.1131
0.5788
0.5788
0.9458
0.2226
0.5567
1.1131
0.0557
0.7793
0.6122
0.1113
0.1558
0.2894
0.6678
0.0290
0.3119
-------
County Name
Cherokee Co
Jefferson Co
Tazewell Co
Lincoln Co
Hamilton Co
Roberts Co
Delaware Co
Ida Co
Finney Co
Sioux Co
Red Willow Co
Loudon Co
Hitchcock Co
Winnebago Co
Gove Co
Mitchell Co
State Name
Iowa
Colorado
Illinois
Nebraska
Nebraska
South
Dakota
Iowa
Iowa
Kansas
Iowa
Nebraska
Tennessee
Nebraska
Wisconsin
Kansas
Georgia
St/Co
FIPS
19035
08059
17179
31111
31081
46109
19055
19093
20055
19167
31145
47105
31087
55139
20063
13205
PLANT
Little Sioux Corn Processors
Merrick & Company (Coors Brewery)
MGP Ingredients, Inc.
Midwest Renewable Energy, LLC (MRE)
Nebraska Energy
North Country Ethanol (NCE)
Permeate Refining
Quad-County Corn Processors
Reeve Agri-Energy
Siouxland Energy & Livestock Coop
(SELC)
SW Energy, LLC.
Tate & Lyle
Trenton Agri-Products, LLC. (TAP)
Utica Energy, LLC
Western Plains Energy, LLC
Wind Gap Farms (Anheuser/Miller
Brewery)
Total
CO
184.3
4.2
188.5
41.9
104.7
52.4
3.1
56.5
25.1
46.1
0.2
254.7
83.8
108.9
62.8
0.8
6,074.3
NOX
533.5
12.1
545.6
121.3
303.1
151.6
9.1
163.7
72.8
133.4
0.6
353.3
242.5
315.3
181.9
2.4
12,610.4
voc
252.2
5.7
257.9
57.3
143.3
71.6
4.3
77.4
34.4
63.1
0.3
110.4
114.6
149.0
86.0
1.1
5,923.2
S02
679.0
15.4
694.4
154.3
385.8
192.9
11.6
208.3
92.6
169.8
0.8
334.3
308.6
401.2
231.5
3.1
14,417.5
PM25
19.3
0.5
23.2
5.2
10.9
6.5
0.4
7.0
3.1
4.8
0.0
144.3
10.3
11.4
6.6
0.1
2,537.1
PM10
213.4
4.9
218.3
48.5
121.3
60.6
3.6
65.5
29.1
53.4
0.2
329.7
97.0
126.1
72.8
1.0
7,456.6
ACROLEIN
0.9795
0.0223
1.0020
0.2226
0.5565
0.2783
0.0166
0.3005
0.1336
0.2449
0.0011
0.7346
0.4452
0.5788
0.3339
0.0045
24.0
(*) Data taken from the 2002 NEI
(+) Data taken from the 2005 NEI
data by 0.65.
rather than provided by OTAQ for 2005. Units conversion not performed on this facility and no adjustment of the emissions by 0.65.
vl, rather than provided by OTAQ for 2005. Units conversion not performance on these facilities and no adjustments of the emissions
-------
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.s 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
10
-------
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-to-
pump (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 future-
year 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 EO 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
Mobile
Exhaust
Mobile
Evaporative
VOC
speciation
approach
for fuels
Tier 1 EO and
E10
combinations
Tier 1 and
Tier 2 EO and
E10
combinations
Tier2E10
and E85
combinations
Tier 1 E10
EOandElO
combinations
EOorElO
(by county)
EOorElO or
combinations
E10andE85
combinations
E10
VOC
Profile
Codes
8750
8751
8750
8751
8756
8767
8752
8757
8751
8753
8754
8753
8754
8753
8754
8754
8755
8754
2005
cases
on noadj
nonroad
on_noadj
nonroad
2022
AEO
on noadj
nonroad
on noadj
nonroad
2022
RFS1
on noadj
nonroad
on_noadj
nonroad
2022
RFS1
sensitivity
nonroad
on noadj
on_noadj
nonroad
2022
RFS2
on_noadj
nonroad
on noadj
nonroad
2022
RFS2
sensitivity
on noadj
nonroad
on_noadj
nonroad
11
-------
Inventory
type and
mode
Other
sources:
nonroad
refueling,
PFCs,
btp,
rbt
voc
speciation
approach
for fuels
EO
EOandElO
combination
EO (revised)
andElO
combinations
EO (revised)
E10andE85
combinations
E10
VOC
Profile
Codes
8737
8736
8737
8736
873 7B
8737B
8736
8755
8736
2005
cases
All listed
2022
AEO
All
listed+
2022
RFS1
All listed
2022
RFS1
sensitivity
All listed
2022
RFS2
rbt
PFCs
btp
nonroad
2022
RFS2
sensitivity
btp
rbt
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
8750 Tierl EO
8751 Tierl E10
8752 E85
8756 Tier2 EO
8757 Tier2E10
Evaporative
8753 EO
8754 E10
8755 E85
Refueling
8736 E10 headspace vapor
8737 EO headspace vapor
873 7B EO headspace vapor
with reduced olefms.
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
12
-------
denote the run is EPA30Draft_BC_421. 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 uncertainly 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 vl 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
13
-------
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 OTAQ-
provided 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 =
NMEVI Emis2022 * 1.0306 /NMIM Emis20o5 (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 (TAP) 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 refinery-
to-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 EO 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 PMi0, to ensure SMOKE could properly calculate PMC as PMi0-PM2.5
14
-------
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:
15
-------
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. Cl 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_ClC2_2022RFS2cases.xls. We applied HAP factors to VOC to obtain 1,3-butadiene,
acetaldehyde, acrolein, benzene, and formaldehyde, and applied factors to PMio 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
16
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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 aim 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 TAP data. This is same approach and FAA TAP 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 ECA-
IMO 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
Acetaldehyde
Benzene
Formaldehyde
Benz[a]Anthracene
Benzo[a]Pyrene
Benzo[b]Fluoranthene
Benzo[k]Fluoranthene
Chrysene
lndeno[1 ,2,3-c,d]Pyrene
Acenaphthene
Acenaphthylene
Anthracene
Benzo[g,h,i,]Perylene
Apply to
VOC
VOC
VOC
PM2_5
PM2_5
PM2_5
PM2_5
PM2_5
PM2_5
PM2_5
PM2_5
PM2_5
PM2_5
Pollutant Code
75070
71432
50000
56553
50328
205992
207089
218019
193395
83329
208968
120127
191242
Factor
0.0002286
9.795E-06
0.0015672
5.674E-07
1.844E-07
1 .56E-07
1 .56E-07
9.929E-08
1.418E-08
3.404E-07
5.248E-07
5.248E-07
1.277E-07
17
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Pollutant
Fluoranthene
Fluorene
Naphthalene
Phenanthrene
Pyrene
Beryllium
Cadmium
Chromium VI
Chromium III
Lead
Manganese
Nickel
Selenium
Apply to
PM2_5
PM2_5
PM2_5
PM2_5
PM2_5
PM10
PM10
PM10
PM10
PM10
PM10
PM10
PM10
Pollutant Code
206440
86737
91203
85018
129000
7440417
7440439
18540299
16065831
7439921
7439965
7440020
7782492
Factor
3.12E-07
6.95E-07
1.987E-05
7.943E-07
5.532E-07
5.459E-07
7.642E-06
2.948E-06
1.343E-05
3.002E-05
5.732E-05
0.0016377
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 NMEVI monthly emissions was also provided for gasoline
equipment that was used to replace gasoline equipment emissions in the reference set. All NMEVI data are
based on AEO2007 fuels and NMEVI 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
18
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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,
NMTM-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.
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• 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
NMEVI runs.
MOVES-based, monthly state-level emissions were first allocated to county based emissions using county-
SCC specific state to county ratios that we created from the 2022 AEO NMIM run. California MOVES-
based 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
20
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for California (same data as were used in 2020v3). We estimated HAP emissions by applying HAP-
to-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 NMTM-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 (Rfs2ref2022orVcl laeo) 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=l 1; hence the "Vcl 1" designation. (These have been referred to
previously as "8b trucks," but Vcl 1 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
"Veil" emissions replaced the reference case emissions for AEO; similar "Vcl 1" 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 NMTM-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 NMEVI 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.
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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
1 1/17/2008 in the Excel® dataset "Corn_EtOH_Plant_Inv_2022-rfsl.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 RF SI -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
1 1/17/2008: "Corn_EtOH_Plant_Inv_2022-rfsl .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_RFSl.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
1 1/25/2008: "Biodsl_Plant_Inv_2022-rfsl-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_rfsl.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.
22
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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 Cl 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_ClC2_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_rfsl.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
RFSl-specific NMIM data from case "Rfs2ref2022orVcl Irfsl", 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=l 1 (these have been referred to previously ad "8b trucks," but Vcl 1
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 rfs2ref2022orVcl Irfsl 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 RFSl-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.
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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 EO headspace vapor VOC speciation profile 8737 profile with profile
8737B. This second change affects all categories that use this EO 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
EO 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 EO, some got E10, some got both EO 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 EO, Tier 1 E10, or a mixture of EO 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
8750 (Tier 1 EO) and 8756 (Tier 2 EO)
OR
8751 (Tier 1 E10) and 8757 (Tier2E10)
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
RFS1 Sensitivity
exhaust VOC speciation for
nonroad mobile
8750 (Tier 1 EO)
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_Rfs2Aqm2022RfslNR.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 EO headspace vapor VOC speciation
profile 8737 profile with profile 8737B. This affects all categories that use this EO 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 EO to E10 that was not consistent with what one would expect as a result of increased ethanol use. In
these cases, the EO 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 EO 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.
24
-------
Table 10: SCCs affected by revised headspace profile in the 2022 RFS1 headspace profile sensitivity case.
sec
40600233
40600235
40600241
40688805
404002"
404004"
406001"
406003"
406004"
406006"
406007"
2501011*"
2501012*"
2501055"*
2501060*"
2505030*"
2660000*"
40400240
40400249
40400260
40600231
40600232
40600234
40600236
40600237
40600238
40600239
40600240
40600298
40600299
40688803
403001"
403002"
403003"
40301 0"
403011"
40301 2"
404001"
406005"
2501050*"
2505000*"
2505020*"
2505040*"
Sector
ptnonipm
nonpt
ptnonipm
nonpt
Description
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-to-
bulk section
below)
Refinery to bulk
terminal
SCC TieM
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Storage and Transport
Storage and Transport
Storage and Transport
Storage and Transport
Storage and Transport
Waste Disposal, Treatment, & Recov
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Petroleum and Solvent Evaporation
Storage and Transport
Storage and Transport
Storage and Transport
Storage and Transport
SCC Tier2
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Petroleum Liquids Storage (non-Refinery)
Petroleum Liquids Storage (non-Refinery)
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Petroleum and Petroleum Product Storage
Petroleum and Petroleum Product Storage
Petroleum and Petroleum Product Storage
Petroleum and Petroleum Product Storage
Petroleum and Petroleum Product Transport
Leaking Underground Storage Tanks
Petroleum Liquids Storage (non-Refinery)
Petroleum Liquids Storage (non-Refinery)
Petroleum Liquids Storage (non-Refinery)
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and arketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Transportation and Marketing of Petroleum Products
Petroleum Product Storage at Refineries
Petroleum Product Storage at Refineries
Petroleum Product Storage at Refineries
Petroleum Product Storage at Refineries
Petroleum Product Storage at Refineries
Petroleum Product Storage at Refineries
Petroleum Liquids Storage (non-Refinery)
Transportation and Marketing of Petroleum Products
Petroleum and Petroleum Product Storage
Petroleum and Petroleum Product Transport
Petroleum and Petroleum Product Transport
Petroleum and Petroleum Product Transport
SCC TierS
Marine Vessels
Marine Vessels
Marine Vessels
Fugitive Emissions
Bulk Plants
Petroleum Products - Underground Tanks
Tank Cars and Trucks
Gasoline Retail Operations - Stage I
Filling Vehicle Gas Tanks - Stage II
Consumer (Corporate) Fleet Refueling - Stage II
Consumer (Corporate) Fleet Refueling - Stage I
Residential Portable Gas Cans
Commercial Portable Gas Cans
Bulk Plants: All Evaporative Losses
Gasoline Service Stations
Truck
Leaking Underground Storage Tanks
Bulk Plants
Bulk Plants
Bulk Plants
Marine Vessels
Marine Vessels
Marine Vessels
Marine Vessels
Marine Vessels
Marine Vessels
Marine Vessels
Marine Vessels
Marine Vessels
Marine Vessels
Fugitive Emissions
Fixed Roof Tanks (Varying Sizes)
Floating Roof Tanks (Varying Sizes)
Variable Vapor Space
Bulk Terminals
Pipeline Petroleum Transpt - General - All Products
Bulk Terminals: All Evaporative Losses
All Transport Types
Marine Vessel
Pipeline
-------
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_Refmery_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 refinery-
to-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 EO 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.
26
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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_tox-
cmp.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 EO 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 Cl 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_ClC2_2022RFS2cases.xls". OAQPS
27
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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 "Rfs2ref2022orVcl leisa", 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=l 1 (these have been referred to previously ad "8b trucks,"
but Vcl 1 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 rfs2ref2022orVcl leisa 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.
28
-------
Given the timing of this sensitivity run, it did not include the revised EO 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.
29
-------
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
EO - Refinery to Bulk Terminal
EO - 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-l 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 EO, E10 and E85 using national fuel volumes for the scenarios. The
national fuel volumes are given in Table A-l. 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.
30
-------
Table A-l. EO, E10 and E85 fuel volumes for RFS2 scenarios in 2022 (billions of gallons).
Scenario
RFS1 AEO RFS2
EO
E10
E85
77.95
67
0
16.03
131
0.1097
0
124.6
29.3
Application of Speciation Profiles
The most straightforward approach for speciating emissions is to apply the following speciation profiles:
EO - Profile 8737: Composite profile - Non-oxygenated gasoline headspace vapor (except 8734 non-
oxygenated 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 Profile-
Ethanol blended gasoline)
E85 - Profile for light-duty gasoline evaporative emissions (attached).
The EO profile would be applied to all SCCs representing refinery to bulk terminal emissions. For the
remaining SCCs, EO, E10 and E85 profiles are be weighted by national fuel sales volumes to come up with
composite profiles for each control scenario.
-------
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: Working 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 Te minals, Gasoline RVP 7: Standing Loss - External Floating Roof w/ Secondary Seal Refinery to Bulk Terminal
40400148 BulkTe minals, Gasoline RVP 13/10/7: Withdrawal Loss - External Floating Roof (Primary/Secondary SRefinery to Bulk Terminal
40400150 Bulk Te minals, Miscellaneous Losses/Leaks: Loading Racks Refinery to Bulk Terminal
40400151 Bulk Te minals, Valves, Flanges, and Pumps Refinery to Bulk Terminal
40400152 Bulk Te minals, Vapor Collection Losses Refinery to Bulk Terminal
40400153 Bulk Terminals, VaporControl 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
32
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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:
EO
E10
E85
Total
RFS1
billions
of gallons
77.95
67
0
144.95
RFS2-
fraction
0.5378
0.4622
AEO
billions
of gallons
16.03
131
0.1097
147.14
AEO-
fraction
0.1089
0.8903
0.0007
RFS2
billions of
gallons
0
124.6
29.3
153.9
RFS2-
fraction
0.0000
0.8096
0.1904
EO - Profile 8737: Composite profile - Non-oxygenated gasoline headspace vapor (except 8734 non-
oxygenated 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 Profile-
Ethanol 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
33
-------
Steps taken to represent the approaches above in the modeling cases:
• Copy gsref file that is used for future year VOC to the following name: "gsref_rfs2_voc_2022"
• Change "bulk terminal to pump" sees in the gsref file to xref to "combo"
• Change all "refinery to bulk terminal SCCs" to the EO 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 (EO 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. AEOCase:
gspro_combo_aeo_stationary all counties/months use the following:
0.1089 x Profile 8737 + 0.8903 x Profile 8736 + 0.0007 x Profile 8755
2. gspro_combo_rfsl_stationary all counties/months use the following
0.5378 x Profile 8737 + 0.4622 x Profile 8736
3. gspro_combo_eisa_stationary: all counties/months use the following
0.8096 x Profile 8736 + 0.1904 x 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.
34
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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 has been provided, this is intended to
mean 12 separate files with the 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.
35
-------
Table C-l: List of inventory data associated with RFS2 modeling cases.
Case
2005 All
Sector
ptipm
ptnonipm
nonpt
afdust
ag
aim no c3
nonroad
seca_c3
on_noadj
on moves startpm
on moves runpm
ptfire
SMOKE input files
Annual: ptinv_ptipm cap2005nei 26aug2008 v2 orl.txt
ptinv_ptipm_hap2005agtox_vl_noBAFM_28aug2008_vO_orl.txt
Daily: ptday_ptipm caphap noncem 2005ag ida.txt
Hourly: HOUR UNIT 2005 *.txt
ptinv_ptnonipm xportfrac 2005cap remainder 24nov2008 vO orl.txt
ptinv_ptnonipm_2005caphap_3ethanol_plants_delete_for_all2022_19nov2008_vO_orl.txt
ptinv_ptnonipm 2005caphap chippewa delete for 2022EISA 19nov2008 vO orl.txt
ptinv_ptnonipm 2005hap noBAFM remainder 24nov2008 vO orl.txt
ptinv ptnonipm caphap ethanol plant additions 2005 17dec2008 vl orl.txt
arinv nonpt_pf4 cap nopfc 08sep2008 vO orl.txt
arinv nonpt_pf4 hap nopfc Ilsep2008 vO orl.txt
arinv_pfc 2002 caphap 27dec2007 vO orl.txt
arinv nonpt caphap ethanol plant additions 2005 17dec2008 vO orl.txt
arinv afdust 2002ad xportfrac 26sep2007 vO orl.txt
arinv ag cap2002nei 06nov2006 vO orl.txt
arinv_alm_no_c3_cap2002v3_30jul2008_vl_orl.txt
arinv aim no c3 hap2002v4 12sep2008 vO orl.txt
arinv nonroad caps 2005v2 revised 08sep2008 vO orl.txt
arinv nonroad haps 2005v2 revised 05sep2008 vO orl.txt
arinv nonroad calif caphap 2005v2 02apr2008 vO orl.txt
ptinv_seca_c3_caps2005pf4_31jul2008_vO_orl.txt
ptinv_seca_c3_haps_east2005pf4_31jul2008_vO_orl.txt
ptinv_seca_c3_haps_central2005pf4_31jul2008_vO_orl.txt
ptinv seca c3 haps west2005pf4 31jul2008 vO orl.txt
ptinv_seca_c3_haps_NonUS_east2005pf4_09sep2008_vO_orl.txt
ptinv_seca_c3_haps_NonUS_central2005pf4_09sep2008_vO_orl.txt
ptinv seca c3 haps NonUS west2005pf4 09sep2008 vO orl.txt
mbinv onroad capshaps 2005v2 nmim not2moves 08sep2008 vO orl.txt
mbinv on noadj moves 14NOV08 14nov2008 vO orl.txt
mbinv onroad calif caphap 2005v2 02apr2008 vO orl.txt
mbinv onroad moves startpm 20oct2008 vO orl.txt
mbinv onroad moves runpm 20oct2008 vO orl.txt
Master: ptinv_ptfire_2005rfs2_l 8nov2008_vl_orl.txt
Daily: ptday ptfire *2005rfs2 * v0.orl.txt
-------
Case
2005 "ci"
case
2022 - All
Sector
othar
othar hg
othon
othpt
othpt hg
ptipm
avefire
ptipm
avefire
afdust
othar
SMOKE input files
arinv nonroad mexico inter! or 1999 21dec2006 vO ida.txt
arinv nonroad mexico border 1999 21dec2006 vO ida.txt
arinv nonroad Canada 2000 inventory Ilfeb2008 v2 ida.txt
arinv nonpoint Canada2000 21dec2006 vO ida.txt
arinv nonpt mexico interior 1999 21dec2006 vO ida.txt
arinv nonpt mexico border 1999 21dec2006 vO ida.txt
arinv area Canada hg 2000 noduplicates 23jul2008 vO ida.txt
mbinv onroad Canada2000 07nov2006 vO ida.txt
mbinv onroad mexico border 1999 21dec2006 vO ida.txt
mbinv onroad mexico interior 1999 21dec2006 vO ida.txt
Canadian point sources from the 2002 platform are proprietary
ptinv mexico border99 03mar2008 vl ida.txt
ptinv mexico interior99 05feb2007 vO ida.txt
ptinv offshore point from 2001 platform 07nov2006 vO ida.txt
Canadian point sources from the 2002 platform are proprietary
Annual: Same as 2005ai tox 05b
Daily: ptday_ptipm caphap noncem 2005ag ida.txt
ptday ptipm caphap cem 2005ci ida.txt
arinv avefire 2002ce 21dec2007 vO ida.txt
arinv avefire 2002 hap 18nov2008 vO orl.txt
Annual/seasonal: ptinv egu summer 2020_pf31capsHgHCl 19feb2008 vO orl.txt
ptinv_egu_winter_2020_pf3 1 capsHgHCM 9feb2008_vO_orl .txt
ptinv_ptipm hap2005agtox vl noBAFM noHgHCL 07jan2009 v2 orl.txt
Daily: ptday _ptipm caphap noncem 2022ci 31mar ida.txt
ptday _ptipm caphap noncem 2022ci apr ida.txt
ptday _ptipm_caphap_cem_2022ci_3 1 mar_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
Same as data in base case (2005ci tox 05b)
arinv afdust 2020ce 02b BASE 07apr2008 vO orl.txt
arinv nonroad mexico interior 1999 21dec2006 vO ida.txt
arinv nonroad mexico border 1999 21dec2006 vO ida.txt
-------
oo
Case
2022
AEO
Sector
othon
othpt
othar_hg and
othpt hg
ptnonipm
nonpt
ag
on_noadj
on moves startpm
on moves runpm
seca_c3
SMOKE input files
arinv 2020nr canada_province 17apr2008 vl ida.txt
arinv 2020as canada_province 05oct2007 vO ida.txt
arinv nonpt mexico inter! or 1999 21dec2006 vO ida.txt
arinv nonpt mexico border 1999 21dec2006 vO ida.txt
mbinv 2020ms canada_province 05jun2007 vO ida.txt
mbinv onroad mexico border 1999 21dec2006 vO ida.txt
mbinv onroad mexico interior 1999 21dec2006 vO ida.txt
Canadian point sources from the 2002 platform are proprietary
ptinv mexico border99 03mar2008 vl ida.txt
ptinv mexico interior99 05feb2007 vO ida.txt
ptinv offshore point from 2001 platform 07nov2006 vO ida.txt
Same as 2005
ptinv_ptnonipm_2022ci_tox_aeo_05b_AEO_06j an2009_vO_orl .txt
ptinv_ptnonipm_caphap_ethanol_plant_additions_2022AEO_05jan2009_vl_orl.txt
ptinv ptnonipm 2005caphap chippewa delete for 2022EISA 19nov2008 vO orl.txt
arinv_nonpt_2022ci_tox_aeo_05b_AEO_29dec2008_vO_orl.txt
arinv_pfc_caphap2020_02apr2008_vO_orl.txt
arinv_nonpt_caphap_biodiesel_plant_additions_2022AEO_18dec2008_vO_orl.txt
arinv_nonpt_caphap_ethanol_plant_additions_2022AEO_15dec2008_vO_orl.txt
arinv nonpt voc ethanol transfer additions 2022AEO 15dec2008 vO orl.txt
arinv ag 2020ce 02b BASE 08apr2008 vO orl.txt
mbinv_on_noadj _MO VES_2022rf s_aeo__2 1 J AN2009_2 1 j an2009_vO_orl . txt
mbinv on noadj rfs2 aeo caphap2022 12jan2009 vO orl.txt
mbinv onroad calif caphap 2020v31 17apr2008 vO orl.txt
mbinv onroad moves startpm 2022rfs aeo 18dec2008 vO orl.txt
mbinv onroad moves runpm 2022rfs aeo 18dec2008 vO orl.txt
ptinv_eca_c3_caps2022BASE_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_NonUS_central2022BASE_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_NonUS_east2022BASE_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_NonUS_west2022BASE_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_central2022BASE_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_east2022BASE_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_west2022BASE_10dec2008_vO_orl.txt
-------
VQ
Case
2022
RFS1 and
RFS1
sensitivity
2022
RFS2
Sector
nonroad
aim no c3
ptnonipm
nonpt
ag
on_noadj
on moves startpm
on moves runpm
seca c3
nonroad
aim no c3
ptnonipm
nonpt
ag
SMOKE input files
arinv nonroad rfs2 aeo caphap2022 09jan2009 vO orl.txt
arinv nonroad calif caphap 1m 2020v31 17apr2008 vO orl.txt
arinv_alm_no_c3_LOCOMOTIVES_Classl_rfs2_aeo_caphap2022_14dec2008_vO_orl.txt
arinv aim no c3 C1C2 rfs2 aeo caphap2022 14dec2008 vO orl.txt
arinv aim no c3 AIRCRAFT nonClassl LOCO rfs2 aeo caphap2022 14dec2008 vO orl.txt
ptinv_ptnonipm_2022ci_tox_rfs 1 _05b_RF S 1 _22j an2009_vO_orl .txt
ptinv_ptnonipm_caphap_ethanol_plant_additions_2022RFSl_26jan2009_vl_orl.txt
ptinv ptnonipm 2005caphap chippewa delete for 2022EISA 19nov2008 vO orl.txt
arinv_nonpt_2022ci_tox_rf s 1 _05b_RF S 1 _22j an2009_vO_orl .txt
arinv_pfc_rfs2_rfsl_caphap2020_15jan2009_vO_orl.txt
arinv_nonpt_caphap_biodiesel_plant_additions_2022RFSl_18dec2008_vO_orl.txt
arinv nonpt caphap ethanol_plant additions 2022RFS1 15dec2008 vO orl.txt
arinv nonpt voc ethanol transfer additions 2022RFS1 15dec2008 vO orl.txt
Same as 2022 AEO
mbinv_on_noadj_MOVES_2022rfs_RFSl_apr_09FEB2009_10feb2009_vO_orl.txt
mbinv on noadj rfs2 rfsl caphap2022 apr 12jan2009 vO orl.txt
mbinv onroad calif caphap 2020v31 apr 17apr2008 vO orl.txt
mbinv onroad moves startpm 2022rfs RFS1 09FEB2009 10feb2009 vO orl.txt
mbinv onroad moves runpm 2022rfs RFS1 09FEB2009 10feb2009 vO orl.txt
Same as 2022 AEO
arinv nonroad rfs2 rfsl caphap2022 09jan2009 vO orl.txt
arinv nonroad calif caphap 1m 2020v31 17apr2008 vO orl.txt
arinv_alm_no_c3_AIRCRAFT_nonClassl_LOCO_rfs2_all_RFS2_scenarios_
caphap2022_14dec2008_vO_orl.txt
arinv_alm_no_c3_C 1 C2_rfs2_rfs I_caphap2022_14j an2009_vO_orl.txt
arinv aim no c3 LOCOMOTIVES Class 1 rfs2 rfsl caphap2022 14jan2009 vO
ptinv_ptnonipm 2022ci tox eisa 05b EISA 23jan2009 vO orl.txt
ptinv ptnonipm caphap ethanol plant additions 2022EISA 27jan2009 v2 orl.txt
arinv_nonpt_2022ci_tox_eisa_05b_EISA_26jan2009_vO_orl.txt
arinv_nonpt_caphap_biodiesel_plant_additions_2022EISA_18dec2008_vO_orl.txt
arinv nonpt caphap ethanol_plant additions 2022EISA 15dec2008 vO orl.txt
arinv nonpt voc ethanol transfer additions 2022EISA 15dec2008 vO orl.txt
arinv_pfc_rfs2_eisa_caphap2020_15jan2009_vO_orl.txt
arinv nonpt caphap cellolosic_plant additions 2022eisa 21OCT2009 orl.txt
arinv ag 2022ci tox eisa 05b EISA 27jan2009 vO orl.txt
-------
Case
2022
RFS2,
Sensitivity
Sector
afdust
on noadj
on moves startpm
on moves runpm
seca c3
nonroad
nonpt
SMOKE input files
arinv afdust 2022ci tox eisa 05b EISA 27jan2009 vO orl.txt
mbinv_on_noadj_MOVES_2022rfs_EISA__26FEB2009_26feb2009_vO_orl.txt
mbinv on noadj rfs2 eisa caphap2022 14jan2009 vO orl.txt
mbinv onroad calif caphap 2020v31 17apr2008 vO orl.txt
mbinv onroad moves startpm 2022rfs EISA 26FEB2009 26feb2009 vO orl.txt
mbinv onroad moves runpm 2022rfs EISA 26FEB2009 26feb2009 vO orl.txt
ptinv_eca_c3_caps2022EISA_10dec2008_vO_orl.txt
ptinv eca c3 haps east2022EISA 10dec2008 vO orl.txt
ptinv eca c3 haps centra!2022EISA 10dec2008 vO orl.txt
ptinv_eca_c3_haps_west2022EISA_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_NonUS_east2022EISA_10dec2008_vO_orl.txt
ptinv_eca_c3_haps_NonUS_central2022EISA_10dec2008_vO_orl.txt
ptinv eca c3 haps NonUS west2022EISA 10dec2008 vO orl.txt
arinv nonroad rfs2 eisa caphap2022 09jan2009 vO orl.txt
arinv nonroad calif caphap 1m 2020v31 17apr2008 vO orl.txt
Same as 2022 RFS2 case, but did not include dataset:
arinv nonpt caphap biodiesel_plant additions 2022EISA 18dec2008 vO orl.txt
-------
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: __.txt, where is
the last date of change for that version and will have a unique value for the combination of Dataset Name
and Version number.
41
-------
Table D-l: Detailed list of ancillary data differences between RFS2 2005 and 2005 v4 platform
Description
Area-source spatial
cross-reference
Onroad spatial
cross-reference
Area and onroad
temporal profiles
Area temporal
cross-reference
Onroad temporal
cross-reference
Grid descriptions
Inventory table
Inventory table
Non-HAP
Exclusions for nonpt
sector
Elevated
configuration file for
seca c3 sector
Speciation profiles
for INTEGRATE
HAPS
Speciation profiles
for TOG
Speciation profiles
static
Speciation profiles
speciated VOC
Environment
Variable
AGREF
MGREF
ATPRO,
MTPRO,
PTPRO
ATREF,
PTREF
MTREF
GRIDDESC
INVTABLE
INVTABLE
NHAP
EXCLUDE
PELV
CONFIG
GSPRO
GSPRO
GSPRO
GSPRO
Sectors
All sectors
All sectors
All sectors
All sectors
All sectors
All sectors
All sectors
avefire,
ptnonipm,
ptipm
nonpt
seca_c3
All sectors
All sectors
All sectors
othpt
2005 v4 platform
Dataset
amgref_us_can_mex_revised
amgref_us_can_mex_revised
amptpro_2005_us_can_revised
amptref_v3_3_revised
amptref_v3_3_revised
griddescjambertonly
invtable_hapcapintegate_cb05s
oa_nomp
invtable_hapcapnohapuse_cb05
soa_nomp
nhapexclude_nonpt_pf4
pelvconfig_seca_c3
gspro integratehaps cb05 tx p
f4
gspro tog cb05 soa pf4 pretie
r2
gspro_static_cmaq
gspro_speciated_voc
Vsn
5
7
0
1
0
24
4
4
3
0
1
1
9
0
2005 RFS2 platform
Dataset
amgref_us_can_allmex3
amgref_us_can_allmex3
amptpro_2005_us_can
amptref_v3_3
amptref_v3_3
griddescjambertonly
invtable_hapcap_cb05soa
n/a
nhapexclude_nonpt_pf4
n/a
gspro integratehaps cb05 tx p
f4
gspro_tog_nohapuse_cb05_tx_
pf4_pretier2
gspro_static_cmaq
n/a
Vsn
5
5
1
5
5
13
6
0
0
1
7
Comment and Impact
For v4 platform, revised for new Canadian inventory and
spatial surrogates
For v4 platform, revised for new Canadian inventory and
spatial surrogates
For v4 platform, revised for new Canadian inventory and
temporal profiles
For v4 platform, added SCCs needed for 2005 v2 point
inventory and for WRAP oil and gas inventory
For v4 platform, added SCCs needed for 2005 v2 point
inventory (but not for WRAP oil and gas inventory).
Superceeded by v1 of the same dataset.
An older file used for RFS2 with fewer grids defined.
RFS2 used a full toxics approach for processing the
emissions and 2005 v4 platform used an approach without
most toxics. Impacts only the species included in the air
quality modeling.
Approach for implementing "no HAP use" approach for
these sectors was different in RFS2, but the result was the
same.
v1 file contains updates for ethanol 8-digit SCCs with not
HAPs associated with the VOC. v3 includes WRAP oil and
gas SCCs since these do not have HAP VOCs either. v1
needed for future year RFS2 and v3 needed for the v4
platform.
v4 platform used inline point sources, and so PELVCONFIG
file needed only in v4 platform.
For v4 platform: Added benzene-to-benzene record: move
this record from the "other HAP VOC" gspro since it is used
in SOA
Excluded ald2_primary and form_primary from v4 platform
since not needed
For the v4 platform, this dataset modified to remove
biogenic profiles to put them into a separate dataset.
For the v4 platform, this speciation profile dataset passes
through the pre-speciated VOC point source species
provided by Environment Canada 2006 data.
Impact?
Yes
Yes
Yes
Yes
Yes
No
No
No
Yes
Yes
No
No
No
Yes
-------
Description
Speciation profiles
Canada PM
Speciagtino profiles
for biogenic
emissions
Speciation profiles
Other VOC HAP
Speciation profiles
CHROMIUM
Speciation profiles
DIESEL PM
Speciation profiles
METALS
Speciation xref for
PM2.5 diesel SCCs
but do not produce
diesel
Speciation xref for
non-diesel PM2.5
Speciation xref for
VOC, not year-
specific
Speciation xref for
NONHAPVOC, not
year-specific
Speciation xref for
VOC, year-specific
Speciation xref for
NONHAPVOC,
year-specific
Environment
Variable
GSPRO
GSPRO
GSPRO
GSPRO
GSPRO
GSPRO
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
Sectors
othpt
biog
All sectors
All sectors
All sectors
All sectors
All sectors
All sectors
All sectors
All sectors
All sectors
All sectors
2005 v4 platform
Dataset
gspro_pm25_canada_2006_poi
nt
gspro_biogenics
n/a
n/a
n/a
n/a
gsref_no_dieselpm
gsref_pm25_pf4_nondiesel
gsref_voc_general
gsref_nonhapvoc_general_upda
te
gsref_voc_2005
gsref_nonhapvoc_2005
Vsn
0
0
1
8
19
3
2
1
2005 RFS2 platform
Dataset
n/a
n/a
gspro_other_hapvoc
gspro_chromium
gspro_dieselpm
gspro_hapmetals
n/a
gsref_pm25_pf4_nondiesel
gsref_voc_general
gsref_nonhapvoc_general
gsref_voc_2002
gsref_nonhapvoc_2002
Vsn
4
0
1
0
1
9
0
2
1
Comment and Impact
For the v4 platform, this speciation profile dataset provides
the Canadia-specific PM2.5 speciation profile recommended
by Environment Canada for point sources (1 % POC, 2%
PEC, 12% PS04, 85% PMFINE)
For the v4 platform, this dataset contains the biogenic VOC
speciation profiles previously included in gspro_static_cmaq
v7 for the RFS2 effort
For RFS2, this dataset has the HAP VOC species that get
passed through from inventory to the multipollutant inputs
created for RFS2.
Chromium speciation profiles needed only for multi-
polltutant approach used in RFS2
DIESEL_PM speciation profiles needed only for multi-
pollutant approach used in RFS2.
HAP metal pass-through profiles needed only for multi-
pollutant approach used in RFS2.
Since the v4 platform did not create the DIESEL_PM
species needed for the multipollutant version of CMAQ, the
data set used for the v4 platform contains the SCC cross-
references for diesel SCCs without the DIESEL_PM
species. The RFS2 platform cross-references to the
DIESEL_PM prof lies.
For the v4 platform, this dataset includes updates for 2005
v2 point sources as well as WRAP oil and gas inventory.
Note that future years of RFS2 used more current version
than "v1 " of this dataset, and the v8 dataset could be used
for replicating RFS2 runs.
For v4 platform, includes updates for 2005 v2 point
inventory, WRAP oil and gas SCCs, changes to gasoline
distribution SCCs.
Matches differences between "voc" files
The v4 platform includes gasoline distribution SCCs
deemed not to be year specific (refinery to bulk terminal)
and updates for 2006 Canadian point sources.
Matches differences between "voc" files
Impact?
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
-------
Description
Speciation xref
static NOX -
MONO for mobile
sources
Speciation xref for
Canada PM
Speciation xref
DIESEL PM,
alm_no_c3
Speciation xref NO
DIESEL PM, othar
Speciation xref HAP
chromium nonroad
sectors
Speciation xref HAP
chromium on_noadj
sector
Speciation xref HAP
chromium stationary
sectors
Speciation xref HAP
metals nonroad
sectors
Speciation xref HAP
metals stationary
sector
Speciation xref HAP
metals nonroad
sectors
Speciation xref HAP
metals on_noadj
sector
Environment
Variable
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
GSREF
Sectors
All sectors
All sectors
othpt
alm_no_c3
nonroad
on_noadj
othar
alm_no_c3
nonroad
seca_c3
on_noadj
nonpt
ptipm
ptnonipm
alm_no_c3
nonroad
seca_c3
nonpt
ptipm
ptnonipm
nonroad
on_noadj
2005 v4 platform
Dataset
gsref_static_nox_hono_pf4
gsref_static_integratehap_emv4
gsref_pm25_canada_2006_poi n
t
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
Vsn
3
2
2
2005 RFS2 platform
Dataset
gsref_static_nox_hono_pf4
n/a
n/a
gsref_dieselpm
gsref_no_dieselpm
gsref_chromium_nonroad
gsref_chromium_onroad
gsref_chromium_stationary
gsref_metals_nonroad
gsref_metals_stationary
gsref_metals_nonroad
gsref_metals_onroad
Vsn
2
0
0
1
1
0
0
1
0
0
Comment and Impact
The v4 platform dataset adds four Canadian SCCs that are
needed for processing the 2006 Canadian inventory.
For the v4 platform, this speciation cross-reference dataset
passes through the pre-speciated VOC point source
species provided by Environment Canada 2006 data.
For the v4 platform, this speciation cross-reference dataset
assigns the single Canadia-specific PM2.5 speciation profile
recommended by Environment Canada for all point
sources.
Enables creation of diesel PM species
Prevents creation of diesel PM species in Canada
Enables creation of chromium species
Enables creation of chromium species
Enables creation of chromium species
Enables creation of HAP metal species
Enables creation of HAP metal species
Enables creation of HAP metal species
Enables creation of HAP metal species
Impact?
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
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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-l: 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)
Non-EGU Point Controls
NOX SIP Call (Phase II):
Cement Manufacturing
Large Boiler/Turbine Units
Large 1C Engines
DOJ Settlements: plant SCC controls
Alcoa, TX
MOTIVA, DE
Refinery Consent Decrees: plant/SCC controls
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
Industrial Boiler/Process Heater plant/SCC controls for PM
Large Municipal Waste Combustors (LMWC)
Small Municipal Waste Combustors (SMWC)
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
Pollutants
Affected
NOx
NOx, SO2
NOx, PM, SO2
all
PM
PM, Hg, and
metals
PM, Hg, metals,
NOx, SO2
VOC
Approach or
Reference:
1
2
3
4
5
6
6
EPA, 2007f
45
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Control Strategies
(Grouped by Affected Pollutants or Standard and Approach Used to
Apply to the Inventory)
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/llld)
Hospital/Medical/Infectious Waste Incinerator Regulations
MACT rules, national, PM:
Portland Cement Manufacturing
Secondary Aluminum
MACT rules, plant-level, VOC:
Auto Plants
MACT rules, plant-level, PM & SO2:
Lime Manufacturing
MACT rules, plant-level, PM:
Taconite Ore
Stationary Area Assumptions
Municipal Waste Landfills: project factor of 0.25 applied,
Livestock Emissions Growth to year 2020
Residential Wood Combustion Growth and Changeouts to year 2020
Gasoline Stage II growth and control to 2022 AEO
Portable Fuel Container growth and control to year 2020
ECU Point Controls
CAIR/CAMR/CAVR
IPM Model 3.0
Onroad Mobile and Nonroad Mobile Controls (list includes all key
mobile control strategies but is not exhaustive)
Pollutants
Affected
NOx, PM, SO2
PM
VOC
PM, SO2
PM
VOC
NH3
all
VOC
VOC
NOx, SO2, PM
Approach or
Reference:
EPA, 2005
7
8
9
10
EPA, 2007f
11
12
13
14
15
National Onroad Rules:
Tier 2 Rule
2007 Onroad Heavy-Duty Rule all
Final Mobile Source Air Toxics Rule (MSAT2)
Renewable Fuel Standard
Local Onroad Programs:
National Low Emission Vehicle Program (NLEV) VOC 16
Ozone Transport Commission (OTC) LEV Program
46
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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 all 17,18,19
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
Aircraft, Locomotives, and Commercial Marine Assumptions | |
Aircraft:
Itinerant (ITN) operations at airports to year 2022 a11 20
Locomotives:
Energy Information Administration (ElA) fuel consumption projections for
freight rail ^ EPA, 2007e, 21,
Clean Air Nonroad Diesel Final Rule - Tier 4 18
Locomotive Emissions Final Rulemaking, December 17, 1997
Control of Emissions of Air Pollution from Locomotives and Marine
Commercial Marine:
EIA fuel consumption projections for diesel-fueled vessels
OTAQ EGA C3 Base 2022 inventory for residual-fueled vessels ~, /Fp *
Clean Air Nonroad Diesel Final Rule - Tier 4 all 9007^1
Emissions Standards for Commercial Marine Diesel Engines, December 29,
1999
Tier 1 Marine Diesel Engines, February 28, 2003
AEO-specific inventory adjustments
Nonpt and ptnonipm:
Gasoline distribution by SCC: bulk-plant-to-pump (btp) and refinery-to- vnr FPA ^c\^c\
i 11 j. • i / j.1 \ V V_/l^- \—ii£\. Z\) \.\j
bulk terminal (rtb) processes ,,
Ethanol plant additions
ptnonipm:
Refinery adjustments by state and SCC all EPA, 2010
Ethanol plant additions all
nonpt:
Ethanol transfer additions VOC EPA, 2010
Biodiesel Plant additions all
Cl and C2 Commercial Marine:
Complete OTAQ inventory replacement with AEO adjustments to year 2022 a11 EPA' 2010
Class 1 Locomotives:
Complete OTAQ inventory replacement with AEO adjustments to year 2022 a11 EPA' 2010
ECA C3:
Complete OTAQ inventory replacement with AEO adjustments for year all EPA, 2010
2022
Nonroad (not including California): EPA, 2010
AEO-specific gasoline equipment &
Onroad (not including California): EPA, 2010
MOVES AEO-specific emissions for onroad gasoline all
AEO-specific Class 8a and 8B truck emissions for 816 counties determined all
to have enhanced truck traffic from ethanol distribution
APPROACHES:
1. Used Emission Budget Inventories report (EPA, 1999) for list of SCCs for application of controls, and for
percent reductions (except 1C Engines). Used Federal Register on Response to Court decisions (Federal
47
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Register, 2004) for 1C 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/summarv2006.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
48
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