othar
                                                                            101
CAN total dwelling
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                        150,892
                                                                          othar
                                                                            104
CAN Capped Total Dwelling
                                                                            421
                                                                         37,205
                                                                          2,766
                                                                            206
                                                                          1,952
                                                                          othar
                                                                            113
CAN Forestry and logging
                                                                            185
                                                                          2,210
                                                                         11,310
                                                                             45
                                                                          6,246
                                                                          othar
                                                                            211
CAN Oil and Gas Extraction
                                                                              0
                                                                             31
                                                                             60
                                                                             22
                                                                            925
                                                                          othar
                                                                            212
CAN Mining except oil and gas
                                                                              0
                                                                              0
                                                                          3,079
                                                                              0
                                                                              0
                                                                          othar
                                                                            221
CAN Total Mining
                                                                              0
                                                                              0
                                                                             43
                                                                              0
                                                                              0
                                                                          othar
                                                                            222
CAN Utilities
                                                                             34
                                                                          1,858
                                                                              0
                                                                            386
                                                                             22
                                                                          othar
                                                                            308
CAN Food manufacturing
                                                                              0
                                                                              0
                                                                         20,185
                                                                              0
                                                                         10,324
                                                                          othar
                                                                            321
CAN Wood product manufacturing
                                                                            874
                                                                          4,822
                                                                          1,646
                                                                            383
                                                                         16,606
                                                                          othar
                                                                            323
CAN Printing and related support activities
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                         11,770
                                                                          othar
                                                                            324
CAN Petroleum and coal products manufacturing
                                                                              0
                                                                          1,205
                                                                          1,542
                                                                            486
                                                                          9,304
                                                                          othar
                                                                            326
CAN Plastics and rubber products manufacturing
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                         23,283
                                                                          othar
                                                                            327
CAN Non-metallic mineral product manufacturing
                                                                              0
                                                                              0
                                                                          6,695
                                                                              0
                                                                              0
                                                                          othar
                                                                            331
CAN Primary Metal Manufacturing
                                                                              0
                                                                            158
                                                                          5,595
                                                                             30
                                                                             72
                                                                          othar
                                                                            350
CAN Water
                                                                              0
                                                                            120
                                                                              2
                                                                              0
                                                                              4
                                                                          othar
                                                                            412
CAN Petroleum product wholesaler-distributors
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                         45,257
                                                                          othar
                                                                            448
CAN clothing and clothing accessories stores
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                            149
                                                                          othar
                                                                            482
CAN Rail Transportation
                                                                              2
                                                                          4,980
                                                                            106
                                                                             12
                                                                            310
                                                                          othar
                                                                            562
CAN Waste management and remediation services
                                                                            271
                                                                          1,977
                                                                          2,710
                                                                          2,528
                                                                         13,138
                                                                          othar
                                                                            901
CAN Airport
                                                                              0
                                                                            109
                                                                             11
                                                                              0
                                                                             11
                                                                          othar
                                                                            921
CAN Commercial Fuel Combustion
                                                                            243
                                                                         23,628
                                                                          2,333
                                                                          2,821
                                                                          1,091
                                                                          othar
                                                                            923
CAN TOTAL INSTITUTIONAL AND GOVERNEMNT
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                         14,859
                                                                          othar
                                                                            924
CAN Primary Industry
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                         40,376
                                                                          othar
                                                                            925
CAN Manufacturing and Assembly
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                         71,198
                                                                          othar
                                                                            926
CAN Distribution and Retail (no petroleum)
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                          7,461
                                                                          othar
                                                                            927
CAN Commercial Services
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                         32,167
                                                                          othar
                                                                            932
CAN CANRAIL
                                                                             61
                                                                        132,985
                                                                          3,107
                                                                            485
                                                                          6,567
                                                                          othar
                                                                            946
CAN Construction and Mining
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                          4,359
                                                                          othar
                                                                            951
CAN Wood Consumption Percentage
                                                                          1,950
                                                                         21,662
                                                                        179,087
                                                                          3,095
                                                                        253,523
                                                                          othar
                                                                            990
CAN TOTFERT
                                                                             48
                                                                          4,456
                                                                              0
                                                                          9,881
                                                                            164
                                                                          othar
                                                                           1251
CAN OFFR_TOTFERT
                                                                             81
                                                                         77,166
                                                                          5,671
                                                                             58
                                                                          7,176
                                                                          othar
                                                                           1252
CAN OFFR_MINES
                                                                              1
                                                                          1,004
                                                                             70
                                                                              1
                                                                            138
                                                                          othar
                                                                           1253
CAN OFFR Other Construction not Urban
                                                                             66
                                                                         53,671
                                                                          6,096
                                                                             47
                                                                         12,159
                                                                          othar
                                                                           1254
CAN OFFR Commercial Services
                                                                             40
                                                                         17,791
                                                                          2,552
                                                                             34
                                                                         44,338
                                                                          othar
                                                                           1255
CAN OFFR Oil Sands Mines
                                                                             18
                                                                          9,491
                                                                            311
                                                                             10
                                                                          1,025
                                                                          othar
                                                                           1256
CAN OFFR Wood industries CANVEC
                                                                              9
                                                                          5,856
                                                                            476
                                                                              7
                                                                          1,318
                                                                          othar
                                                                           1257
CAN OFFR Unpaved Roads Rural
                                                                             32
                                                                         11,866
                                                                          1,169
                                                                             28
                                                                         49,975
                                                                          othar
                                                                           1258
CAN OFFR_Utilities
                                                                              8
                                                                          5,579
                                                                            349
                                                                              7
                                                                          1,087
                                                                          othar
                                                                           1259
CAN OFFR total dwelling
                                                                             16
                                                                          5,768
                                                                            773
                                                                             14
                                                                         15,653
                                                                          othar
                                                                           1260
CAN OFFR_water
                                                                             15
                                                                          4,356
                                                                            451
                                                                             29
                                                                         28,411
                                                                          othar
                                                                           1261
CAN OFFR_ALL_INDUST
                                                                              4
                                                                          5,770
                                                                            253
                                                                              3
                                                                          1,049
                                                                          othar
                                                                           1262
CAN OFFR Oil and Gas Extraction
                                                                              0
                                                                            368
                                                                             29
                                                                              0
                                                                            143
                                                                          othar
                                                                           1263
CAN OFFR_ALLROADS
                                                                              3
                                                                          2,418
                                                                            244
                                                                              2
                                                                            582
                                                                          othar
                                                                           1265
CAN OFFR_CANRAIL
                                                                              0
                                                                             85
                                                                              9
                                                                              0
                                                                             15
                                                                    onroad_
can
                                                                            200
CAN Urban Primary Road Miles
                                                                          1,619
                                                                         85,558
                                                                          2,851
                                                                            329
                                                                          8,396
                                                                    onroad_ can
                                                                            210
CAN Rural Primary Road Miles
                                                                            683
                                                                         51,307
                                                                          1,673
                                                                            139
                                                                          3,807
                                                                    onroad_ can
                                                                            220
CAN Urban Secondary Road Miles
                                                                          3,021
                                                                        136,582
                                                                          5,708
                                                                            690
                                                                         22,374
                                                                    onroad_ can
                                                                            230
CAN Rural Secondary Road Miles
                                                                          1,769
                                                                         96,911
                                                                          3,238
                                                                            374
                                                                         10,370
                                                                    onroad_ can
                                                                            240
CAN Total Road Miles
                                                                             43
                                                                         57,401
                                                                          1,355
                                                                             77
                                                                        103,658
                                                                    onroad_ mex
                                                                             11
MEX 2015 Population
                                                                              0
                                                                        281,317
                                                                          1,873
                                                                            533
                                                                        291,992
                                                                    onroad_
mex
                                                                             22
MEX Total Road Miles
                                                                         10,321
                                                                      1,208,461
                                                                         54,823
                                                                         25,855
                                                                        251,931
                                                                    onroad_
mex
                                                                             36
MEX Commercial plus Industrial Land
                                                                              0
                                                                          7,975
                                                                            142
                                                                             29
                                                                          9,192

 Preparation of Emissions for the CAMx model
 Development of CAMx Emissions for Standard CAMx Runs
To perform air quality modeling with the Comprehensive Air Quality Model with Extensions (CAMx model), the gridded hourly emissions output by the SMOKE model are output in the format needed by the CMAQ model, but must be converted to the format required by CAMx. For "regular" CAMx modeling (i.e., without two-way nesting), the CAMx conversion process consists of the following:

 Convert all emissions file formats from the I/O API NetCDF format used by CMAQ to the UAM format used by CAMx, including the merged, gridded low-level emissions files that include biogenics
 Shift hourly emissions files from the 25 hour format used by CMAQ to the averaged 24 hour format used by CAMx
 Rename and aggregate model species for CAMx
 Convert 3D wildland and agricultural fire emissions into CAMx point format
 Merge all inline point source emissions files together for each day, including layered fire emissions originally from SMOKE
 Add sea salt aerosol emissions to the converted, gridded low-level emissions files

Conversion of file formats from I/O API to UAM is performed using a program called "cmaq2uam". In the CAMx conversion process, all SMOKE outputs are passed through this step first. Unlike CMAQ, the CAMx model does not have an inline biogenics option, and so for the purposes of CAMx modeling, emissions from SMOKE must include biogenic emissions.

One difference between CMAQ-ready emissions files and CAMx-ready emissions files involves hourly temporalization. A daily emissions file for CMAQ includes data for 25 hours, where the first hour is 0:00 GMT of a given day, and the last hour is 0:00 GMT of the following day. For the CAMx model, a daily emissions file must only include data for 24 hours, not 25. Furthermore, to match the hourly configuration expected by CAMx, each set of consecutive hourly timesteps from CMAQ-ready emissions files must be averaged. For example, the first hour of a CAMx-ready emissions file will equal the average of the first two hours from the corresponding CMAQ-ready emissions file, and the last (24[th]) hour of a CAMx-ready emissions file will equal the average of the last two hours (24[th] and 25[th]) from the corresponding CMAQ-ready emissions file. This time conversion is incorporated into each step of the CAMx-ready emissions conversion process.

The CAMx model uses a slightly different version of the CB6 speciation mechanism than does the CMAQ model. SMOKE prepares emissions files for the CB6 mechanism used by the CMAQ model ("CB6-CMAQ"), and therefore, the emissions must be converted to the CB6 mechanism used by the CAMx model ("CB6-CAMx") during the CAMx conversion process. In addition to the mechanism differences, CMAQ and CAMx also occasionally use different species naming conventions. For CAMx modeling, we also create additional tracer species. A summary of the differences between CMAQ input species and CAMx input species for CB6 (VOC), AE6 (PM2.5), and other model species, is provided in Table 3-26. Each step of the CAMx-ready emissions conversion process includes conversion of CMAQ species to CAMx species using a species mapping table which includes the mappings in Table 3-26.

Table 3-26. Emission model species mappings for CMAQ and CAMx
Inventory Pollutant
CMAQ Model Species
CAMx Model Species
Cl2
CL2
CL2
HCl
HCL
HCL
CO
CO
CO
NOX
NO
NO

NO2
NO2

HONO
HONO
SO2
SO2
SO2

SULF
SULF
NH3
NH3
NH3

NH3_FERT
n/a (not used in CAMx)
VOC
ACET
ACET

ALD2
ALD2

ALDX
ALDX

BENZ
BENZ and BNZA (duplicate species)

CH4
CH4

ETH
ETH

ETHA
ETHA

ETHY
ETHY

ETOH
ETOH

FORM
FORM

IOLE
IOLE

ISOP
ISOP and ISP (duplicate species)

KET
KET

MEOH
MEOH

NAPH + XYLMN (sum)
XYL

NVOL
n/a (not used in CAMx)

OLE
OLE

PAR
PAR

PRPA
PRPA

SESQ
SQT

SOAALK
n/a (not used in CAMx)

TERP
TERP and TRP (duplicate species)

TOL
TOL and TOLA (duplicate species)

UNR + NR (sum)
NR
PM10
PMC
CPRM
PM2.5
PEC
PEC

PNO3
PNO3

POC
POC

PSO4
PSO4

PAL
PAL

PCA
PCA

PCL
PCL

PFE
PFE

PK
PK

PH2O
PH2O

PMG
PMG

PMN
PMN

PMOTHR
PMOTHR and FPRM (duplicate species)

PNA
NA

PNCOM
PNCOM

PNH4
PNH4

PSI
PSI

PTI
PTI

POC + PNCOM (sum)
POA[1]

PAL + PCA + PFE + PMG + PK + PMN + PSI + PTI (sum)
FCRS[1]
[1] The POA species, which is the sum of POC and PNCOM, is passed to the CAMx model in addition to individual species POC and PNCOM. The FCRS species, which is also a sum of multiple PM species, is passed to CAMx in addition to each of the individual component species.

One feature which is part of CMAQ and is not part of CAMx involves plume rise for fires. For CMAQ modeling, we process fire emissions through SMOKE as inline point sources, and plume rise for fires is calculated within CMAQ using parameters from the inline emissions files (heat flux, etc). This is similar to how non-fire point sources are handled, except that the fire parameters are used to calculate plume rise instead of traditional stack parameters. The CAMx model supports inline plume rise calculations using traditional stack parameters, but, does not support inline plume rise for fire sources. Therefore, for the purposes of CAMx modeling, we must have SMOKE calculate plume rise for fires using the Laypoint program. In this modeling platform, this must be done for the ptfire, ptfire_othna, and ptagfire sectors. To distinguish these layered fire emissions from inline fire emissions, layered fire emissions are processed with the sector names "ptfire3D", "ptfire_othna3D", and "ptagfire3D". When converting layered fire emissions files to CAMx format, stack parameters are added to the CAMx-ready fire emissions files to force the correct amount of fire emissions into each layer for each fire location.

CMAQ modeling uses one gridded low-level emissions file, plus multiple inline point source emissions files, per day. CAMx modeling also uses one gridded low-level emissions file per day - but instead of reading multiple inline point source emissions files at once, CAMx can only read a single point source file per day. Therefore, as part of the CAMx conversion process, all inline point source files are merged into a single "mrgpt" file per day. The mrgpt file includes the layered fire emissions described in the previous paragraph, in addition to all non-fire elevated point sources from the cmv_c3, othpt, ptegu, ptnonipm, and pt_oilgas sectors.

The remaining step in the CAMx emissions process is to generate sea salt aerosol emissions, which are distinct from ocean chlorine emissions. Sea salt emissions do not need to be included in CMAQ-ready emissions because they are calculated by the model, but, do need to be included in CAMx-ready emissions. After the merged low-level emissions are converted to CAMx format, sea salt emissions are generated using a program called "seasalt" and added to the low-level emissions. Sea salt emissions depend on meteorology, vary on a daily and hourly basis, and exist for model species PCL, NA, PSO4, and SS (i.e., sea salt).
 Development of CAMx Emissions for Source Apportionment CAMx Runs
The CAMx model supports source apportionment modeling for ozone and PM sources using techniques called Ozone Source Apportionment Technology (OSAT) and Particulate Matter Source Apportionment Technology (PSAT).  These source apportionment techniques allow emissions from different types of sources to be tracked through the CAMx model.  For the Revised CSAPR Update study, OSAT modeling was performed in CAMx for 2023 and 2028 using one-way nesting (i.e., the inner 12km grid takes boundary information from the outer 36km grid but the inner grid does not feed any concentration information back to the outer grid). The emissions developed specifically for OSAT modeling used the case names "2023fh1_ussa_16j" and "2028fh1_ussa_16j".

Source Apportionment modeling involves assigning tags to different categories of emissions. These tags can be applied by region (e.g., state), by emissions type (e.g., SCC or sector), or a combination of the two. For the Revised CSAPR Update study, emissions tagging was applied by state. All emissions from US states, except for biogenics, fires, and fugitive dust (afdust), were assigned a state-specific tag. Emissions from tribal lands were also assigned a separate tag, as well as offshore emissions. Other tags include a tag for biogenics and afdust; a tag for all fires, both inside and outside the US; and a tag for all anthropogenic emissions from Canada and Mexico. A full list of tags is provided in Table 3-27. State-level tags 2 through 51 exclude emissions from biogenics, fugitive dust, and fires, which are included in other tags.

Table 3-27. State tags for 2023fh1, 2028fh1 USSA modeling
                                      Tag
                           Emissions applied to tag
                                       1
       All biogenics (beis sector) and US fugitive dust (afdust sector)
                                       2
                                    Alabama
                                       3
                                    Arizona
                                       4
                                   Arkansas
                                       5
                                  California
                                       6
                                   Colorado
                                       7
                                 Connecticut
                                       8
                                   Delaware
                                       9
                             District of Columbia
                                      10
                                   Florida
                                      11
                                   Georgia
                                      12
                                    Idaho
                                      13
                                   Illinois
                                      14
                                   Indiana
                                      15
                                     Iowa
                                      16
                                    Kansas
                                      17
                                   Kentucky
                                      18
                                  Louisiana
                                      19
                                    Maine
                                      20
                                   Maryland
                                      21
                                Massachusetts
                                      22
                                   Michigan
                                      23
                                  Minnesota
                                      24
                                 Mississippi
                                      25
                                   Missouri
                                      26
                                   Montana
                                      27
                                   Nebraska
                                      28
                                    Nevada
                                      29
                                New Hampshire
                                      30
                                  New Jersey
                                      31
                                  New Mexico
                                      32
                                   New York
                                      33
                                North Carolina
                                      34
                                 North Dakota
                                      35
                                     Ohio
                                      36
                                   Oklahoma
                                      37
                                    Oregon
                                      38
                                 Pennsylvania
                                      39
                                 Rhode Island
                                      40
                                South Carolina
                                      41
                                 South Dakota
                                      42
                                   Tennessee
                                      43
                                     Texas
                                      44
                                     Utah
                                      45
                                    Vermont
                                      46
                                   Virginia
                                      47
                                  Washington
                                      48
                                 West Virginia
                                      49
                                   Wisconsin
                                      50
                                    Wyoming
                                      51
                                  Tribal Data
                                      52
                       Canada and Mexico (except fires)
                                      53
                                   Offshore
                                      54
           All fires from US, Canada, and Mexico, including ag fires

For OSAT and PSAT modeling, all emissions must be input to CAMx in the form of a point source (mrgpt) file, including low level sources that are found in gridded files for regular CAMx runs. In addition, for two-way nested modeling, all emissions must be input in a single mrgpt file, rather than separate mrgpt files for each of the two domains (36US3 and 12US2). Note that fire emissions require special consideration in two-way nested model runs and for PSAT and OSAT modeling.  That same consideration must be given to any sector in which emissions are being gridded by SMOKE.

There are two main approaches for tagging emissions for CAMx modeling. One approach is to tag emissions within SMOKE.  Here, SMOKE will output tagged point source files (SGINLN files), which can then be converted to CAMx point source format with the tags applied by SMOKE carried forward into the CAMx inputs. The second approach is to, if necessary, depending on the nature of the tags, split sectors into multiple components by tag so that each sector corresponds to a single tag. Then, the gridded and/or point source format SMOKE outputs from those split sectors are converted to CAMx point source format, and then merged into the full mrgpt file, with the tags applied at that last step.  In some situtations, a mix of the two approaches is appropriate.

For the Revised CSAPR Update study the first approach was used for most sectors, meaning tags were applied in SMOKE. The exceptions were sectors where the entire sector receives only one tag: afdust, beis, onroad_ca_adj, ptfire, ptagfire, ptfire_othna, and all Canada and Mexico sectors. Afdust emissions are not tagged by state because the current tagging methodology does not support applying transportable fraction and meteorological adjustments to tagged emissions.

Once the individual sector tagging is complete, the point source files for all of the sectors are merged together to create the mrgpt file which includes all emissions, with the desired tags and appropriate resolution throughout the domain for OSAT or PSAT modeling.
Development of 2023 and 2028 Emissions
The emission inventories for future years of 2023 and 2028 have been developed using projection methods that are specific to the type of emissions source. Future emissions are projected from the 2016 base case either by running models to estimate future year emissions from specific types of emission sources (e.g., EGUs, and onroad and nonroad mobile sources), or for other types of sources by adjusting the base year emissions according to the best estimate of changes expected to occur in the intervening years (e.g., non-EGU point and nonpoint sources). For some sectors, the same emissions are used in the base and future years, such as biogenic and fire. For the remaining sectors, rules and specific legal obligations that go into effect in the intervening years, along with changes in activity for the sector, are considered when possible. These sectors have been projected to 2023 and 2028 as summarized in Table 4-1.
Table 4-1.  Overview of projection methods for the 2023 and 2028 regional cases
                         Platform Sector: abbreviation
              Description of Projection Methods for 2023 and 2028
EGU units:
Ptegu
The Integrated Planning Model (IPM) was run to create the 2023 and 2028 emissions. IPM outputs from the January, 2020 version of the IPM platform were used (https://www.epa.gov/airmarkets/epas-power-sector-modeling-platform-v6-using-ipm-january-2020-reference-case). For 2023, the 2023 IPM output year was used and for 2028 the 2030 output year was used because the year 2028 maps to the 2030 output year. Emission inventory Flat Files for input to SMOKE were generated using post-processed IPM output data. Temporal allocation for future year emissions is discussed in the EGU-IPM specification sheet for the 2016v1 platform.
Point source oil and gas:
pt_oilgas
First, known closures were applied to the 2016 pt_oilgas sources. Production-related sources were then grown from 2016 to 2017 using historic production data. The production-related sources were then grown to 2023 and 2028 based on growth factors derived from the Annual Energy Outlook (AEO) 2019 data for oil, natural gas, or a combination thereof.  The grown emissions were then controlled to account for the impacts of relevant New Source Performance Standards (NSPS).
Remaining non-EGU point:
Ptnonipm
First, known closures were applied to the 2016 ptnonipm sources.  Closures were obtained from the Emission Inventory System (EIS) and also submitted by the states of Alabama, North Carolina, Ohio, Pennsylvania, and Virginia. Industrial sources were grown using factors derived from the AEO 2019. Rail yard emissions were grown using the same factors as line haul locomotives in the rail sector. Controls were then applied to account for relevant NSPS for reciprocating internal combustion engines (RICE), gas turbines, and process heaters. Reductions due to consent decrees that had not been fully implemented by 2016 were also applied, along with specific comments received by S/L/T agencies.
Airports
Starts with 2017 NEI. Airport emissions were grown using factors derived from the Terminal Area Forecast (TAF) (see https://www.faa.gov/data_research/aviation/taf/).
Agricultural:
Ag
Livestock were projected based on factors created from USDA National livestock inventory projections published in February 2018 (https://www.ers.usda.gov/webdocs/outlooks/87459/oce-2018-1.pdf?v=7587).  Fertilizer emissions were held constant at year 2016 levels.
Area fugitive dust:
afdust, afdust_ak
Paved road dust was grown to 2023 and 2028 levels based on the growth in VMT from 2016 to 2023 and 2028. The remainder of the sector including building construction, road construction, agricultural dust, and unpaved road dust was held constant, except in the MARAMA region where some factors were provided for categories other than paved roads.  The projected emissions are reduced during modeling according to a transport fraction (newly computed for the beta platform) and a meteorology-based (precipitation and snow/ice cover) zero-out as they are for the base year.
Category 1, 2 CMV:
cmv_c1c2
Category 1 and category 2 (C1C2) CMV emissions sources outside of California were projected to 2023 and 2028 based on factors from the Regulatory Impact Analysis (RIA) Control of Emissions of Air Pollution from Locomotive Engines and Marine Compression Ignition Engines Less than 30 Liters per Cylinder. California emissions were projected based on factors provided by the state.
Category 3 CMV:
cmv_c3
Category 3 (C3) CMV emissions were projected using a forthcoming EPA report on projected bunker fuel demand. The report projects bunker fuel consumption by region out to the year 2030. Bunker fuel usage was used as a surrogate for marine vessel activity. Factors based on the report were used for all pollutants except NOx. Growth factors for NOx emissions were handled separately to account for the phase in of Tier 3 vessel engines. The NOx growth rates from the EPA C3 Regulatory Impact Assessment (RIA) were refactored to use the new bunker fuel usage growth rates. The assumptions of changes in fleet composition and emissions rates from the C3 RIA were preserved and applied to the new bunker fuel demand growth rates for 2023 and 2028 to arrive at the final growth rates.
Locomotives:
rail
Passenger and freight were projected using separate factors. Freight emissions were computed for future years based on future year fuel use values for 2020, 2023, and 2028. Specifically, they were based on 2018 AEO freight rail energy use growth rate projections and emission factors, which are based on historic emissions trends that reflect the rate of market penetration of new locomotive engines.
Remaining nonpoint:
nonpt
Industrial emissions were grown according to factors derived from AEO2019. Portions of the nonpt sector were grown using factors based on expected growth in human population. Controls were applied to reflect relevant NSPS rules (i.e., reciprocating internal combustion engines (RICE), natural gas turbines, and process heaters).  Emissions were also reduced to account for fuel sulfur rules in the mid-Atlantic and northeast.
Nonpoint source oil and gas:
np_oilgas
Production-related sources were grown starting from an average of 2014 and 2016 production data. Emissions were initially projected to 2017 using historical data and then grown to 2023 and 2028 based on factors generatedfrom AEO2019. Based on the SCC, factors related to oil, gas, or combined growth were used. Coalbed methane SCCs were projected independently. Controls were then applied to account for NSPS for oil and gas and RICE.
Residential Wood Combustion:
rwc
RWC emissions were projected from 2016 to 2023 and 2028 based on growth and control assumptions compatible with EPA's 2011v6.3 platform, which accounts for growth, retirements, and NSPS, although implemented in the Mid-Atlantic Regional Air Management Association (MARAMA)'s growth tool.  RWC emissions in California, Oregon, and Washington were held constant.
Nonroad:
nonroad
Outside California, the MOVES2014b model was run to create nonroad emissions for 2023 and 2028 without any state inputs. The fuels used are specific to the future year, but the meteorological data represented the year 2016. For California, datasets provided by the California Air Resources Board (CARB) circa 2017 were used.
Onroad:
onroad, onroad_nonconus
Activity data were projected from 2016 to 2023 and 2028 based on factors derived from AEO2019. Where S/Ls provided activity data, those data were used. To create the emission factors, MOVES2014b was run for the years 2023 and 2028, with 2016 meteorological data and fuels, but with age distributions projected to represent future years, and the remaining inputs consistent with those used in 2014NEIv2.  The future year activity data and emission factors were then combined using SMOKE-MOVES to produce the 2023 and 2028 emissions. Section 4.3.2 describes the applicable rules that were considered when projecting onroad emissions.
Onroad California:
onroad_ca_adj
CARB-provided emissions were used for California, but they were gridded and temporalized using MOVES2014b-based data output from SMOKE-MOVES.  Volatile organic compound (VOC) HAP emissions derived from California-provided VOC emissions and MOVES-based speciation.
Other Area Fugitive dust sources not from the NEI:
othafdust
Othafdust emissions for future years were provided by ECCC. The emissions were extracted from a broader nonpoint source inventory. Adjustments to construction dust were made to make those more consistent with the 2016 and ECCC 2010 inventories. Mexico emissions are not included in this sector.
Other Point Fugitive dust sources not from the NEI:
othptdust
Wind erosion emissions were removed from the point fugitive dust inventory prior to regional haze modeling. Base year 2015 inventories with the rotated grid pattern removed were projected to 2023 and 2028 based on factors provided by ECCC. A transport fraction adjustment is applied to the projected inventories along with a meteorology-based (precipitation and snow/ice cover) zero-out.
Other point sources not from the NEI:
othpt
For agricultural sources that were originally developed on the rotated 10-km grid, the reallocated base year emissions were projected to 2023 and 2028 using projection factors based on data provided by ECCC and applied by province, pollutant, and ECCC sub-class code. Airports were also projected from 2016 using ECCC-based factors. For the remaining sources in this sector, ECCC provided future year inventories. For Mexico sources, inventories projected from Mexico's 2008 inventory to 2018, 2025, and 2030 were interpolated to the years 2023 and 2028.
Other non-NEI nonpoint and nonroad:
othar
Future year nonpoint inventories for many parts of this sector were provided by ECCC and were split into sectors to match those in the base year inventory. For Canadian nonroad sources, factors were provided from which the future year inventories could be derived.  For Mexico nonpoint and nonroad sources, inventories projected to 2018, 2025, and 2030 from their 2008 inventory were interpolated to 2023 and 2028.
Other non-NEI onroad sources:
onroad_can
For Canadian mobile onroad sources, future year inventories were derived from the base year 2015 inventory and data provided by ECCC. Projection factors were applied by province, sub-class code, and pollutant.
Other non-NEI onroad sources:
onroad_mex
Monthly year Mexico (municipio resolution) onroad mobile inventories were developed based runs of MOVES-Mexico for 2023 and 2028.

 EGU Point Source Projections (ptegu)
The original 2023fh and 2028fh EGU emissions inventories were developed from the output of the v6 platform using the May 2019 reference case run, while the 2023fh1 and 2028fh1 emissions are based on the January 2020 reference case run of the Integrated Planning Model (IPM). IPM is a linear programming model that accounts for variables and information such as energy demand, planned unit retirements, and planned rules to forecast unit-level energy production and configurations. The following specific rules and regulations are included in IPM v6 platform run from May 2019:

 The Cross-State Air Pollution Rule (CSAPR) Update, a federal regulatory measure to address transport of ozone and its precursors under the 1997 and 2008 National Ambient Air Quality Standards (NAAQS) for ozone.
 The Standards of Performance for Greenhouse Gas Emissions from New, Modified, and Reconstructed Stationary Sources: Electric Utility Generating Units.
 The Mercury and Air Toxics Rule (MATS), which was initially finalized in 2011 and later revised (https://www.epa.gov/mats/regulatory-actions-final-mercury-and-air-toxics-standards-mats-power-plants). MATS establishes National Emissions Standards for Hazardous Air Pollutants (NESHAP) for the "electric utility steam generating unit" source category.
 Current and existing state regulations.
 The final actions EPA has taken to implement the Regional Haze Regulations and Guidelines for Best Available Retrofit Technology (BART) Determinations Final Rule. This regulation requires states to submit revised State Implementation Plans (SIPs) that include (1) goals for improving visibility in Class I areas on the 20% worst days and allowing no degradation on the 20% best days and (2) assessments and plans for achieving BART emission targets for sources placed in operation between 1962 and 1977. Since 2010, EPA has approved SIPs or, in a very few cases, put in place regional haze Federal Implementation Plans for several states. The BART limits approved in these plans (as of summer 2017) that will be in place for EGUs are represented in the EPA Platform v6.
 Three non-air federal rules affecting EGUs: National Pollutant Discharge Elimination System-Final Regulations to Establish Requirements for Cooling Water Intake Structures at Existing Facilities and Amend Requirements at Phase I Facilities, Hazardous and Solid Waste Management System; Disposal of Coal Combustion Residuals From Electric Utilities; and the Effluent Limitation Guidelines and Standards for the Steam Electric Power Generating Point Source Category.

Some additional updates were made to IPM for the January 2020 case:

 Updated NEEDS to the December 2019 version.  This included more than 10 GW of retirements, 4 GW of which were coal plants, along with some unit-level rate changes in Utah, Nebraska, Kentucky, and New York.
 Updated (i.e., lowered) storage and renewal energy technology costs based on the National Renewable Energy Laboratory (NREL) Annual Technology Baseline 2019 mid case.
 Implemented offshore wind power mandates in Maryland, New Jersey, Connecticut, Massachusetts, and New York .
 Incorporated clean energy standards in California, New Mexico, Nevada, New York, and Washington.
 Implemented renewable portfolio standard updates in California, Washington D.C., Maryland, Maine, New Mexico, Nevada, New York, Ohio, and Washington.
 Reflected the Affordable Clean Energy (ACE) rule (June 19, 2019).
 Incorporated the 26 U.S. Code § 45Q. Credit for carbon oxide sequestration (https://www.energy.gov/sites/prod/files/2019/10/f67/Internal%20Revenue%20Code%20Tax%20Fact%20Sheet.pdf).

IPM is run for a set of years, including the 2023 and 2028 future years used in the 2016v1 platform. Further documentation of the IPM model and the v6 platform can be found on the CAMD website (https://www.epa.gov/airmarkets/documentation-epas-power-sector-modeling-platform-v6-january-2020-reference-case).

The EGU missions are calculated for the inventory using the output of the IPM model for the forecast year. Units that are identified to have a primary fuel of landfill gas, fossil waste, non-fossil waste, residual fuel oil, or distillate fuel oil may be missing emissions values for certain pollutants in the generated inventory flat file. Units with missing emissions values are gapfilled using projected base year values. The projections are calculated using the ratio of the future year seasonal generation in the IPM parsed file and the base year seasonal generation at each unit for each fuel type in the unit as derived from the 2016 EIA-923 tables. New controls identified at a unit in the IPM parsed file are accounted for with appropriate emissions reductions in the gapfill projection values. When base year unit-level generation data cannot be obtained no gapfill value is calculated for that unit. Additionally, some units, such as landfill gas, may not be assigned a valid SCC in the initial flat file. The SCCs for these units are updated based on the base year SCC for the unit-fuel type.

Combined cycle units produce some of their energy from process steam that turns a steam turbine. The IPM model assigns a fraction of the total combined cycle production to the steam turbine. When the emissions are calculated these steam units are assigned emissions values that come from the combustion portion of the process. In the base year NEI steam turbines are usually implicit to the total combined cycle unit. To achieve the proper plume rise for the total combined cycle emissions, the stack parameters for the steam turbine units are updated with the parameters from the combustion release point.

Large EGUs in the IPM-derived flat file inventory are associated with hourly CEMS data for NOX and SO2 emissions values in the base year. To maintain a temporal pattern consistent with the 2016 base year, the NOX and SO2 values in the hourly CEMS inventories are projected to match the total seasonal emissions values in the future years.

The EGU sector NOx emissions by state are listed in Table 4-2 for 2023 and 2028 regional cases. The designation "fh" here refers to the May 2019 IPM case and "fh1" refers to the January 2020 IPM case.
Table 4-2.  EGU sector NOx emissions by State for the 2023 and 2028 regional cases
State
                                    2016fh
                                    2023fh
                                    2023fh1
                                    2028fh
                                    2028fh1
Alabama
                                    28,596
                                     9,545
                                     9,954
                                    11,812
                                    12,376
Arizona
                                    18,786
                                    10,909
                                    11,175
                                     9,259
                                     9,011
Arkansas
                                    26,808
                                    11,579
                                    17,461
                                    15,318
                                    17,074
California
                                     6,908
                                     7,501
                                     5,808
                                     2,707
                                     1,719
Colorado
                                    30,152
                                    17,965
                                    16,561
                                    18,616
                                    15,448
Connecticut
                                     4,088
                                     4,359
                                     4,365
                                     4,249
                                     4,202
Delaware
                                     1,487
                                      367
                                      488
                                      407
                                      544
District of Columbia
                                      NA
                                       1
                                       1
                                       1
                                       1
Florida
                                    65,059
                                    32,327
                                    32,684
                                    33,282
                                    31,488
Georgia
                                    29,384
                                    14,292
                                    13,760
                                    15,950
                                    15,666
Idaho
                                     1,369
                                      469
                                      469
                                      949
                                      419
Illinois
                                    30,250
                                    31,189
                                    21,321
                                    32,474
                                    21,668
Indiana
                                    83,425
                                    44,029
                                    45,169
                                    44,971
                                    45,328
Iowa
                                    22,971
                                    23,069
                                    24,264
                                    22,976
                                    23,379
Kansas
                                    14,959
                                    15,669
                                    15,725
                                    15,684
                                    14,528
Kentucky
                                    57,342
                                    14,411
                                    14,316
                                    11,761
                                    14,495
Louisiana
                                    47,931
                                    17,223
                                    18,145
                                    16,179
                                    16,909
Maine
                                     4,935
                                     3,016
                                     3,005
                                     2,557
                                     2,945
Maryland
                                    10,448
                                     5,387
                                     5,436
                                     5,115
                                     5,599
Massachusetts
                                     8,121
                                     5,851
                                     5,819
                                     5,626
                                     5,683
Michigan
                                    37,149
                                    30,141
                                    28,344
                                    31,948
                                    32,895
Minnesota
                                    21,737
                                    15,565
                                    17,497
                                    15,364
                                    12,665
Mississippi
                                    16,414
                                     5,749
                                     5,604
                                     6,248
                                     6,135
Missouri
                                    57,647
                                    46,714
                                    48,809
                                    46,528
                                    45,433
Montana
                                    15,819
                                     9,186
                                     9,186
                                     9,193
                                     9,018
Nebraska
                                    20,734
                                    21,428
                                    21,451
                                    21,508
                                    21,468
Nevada
                                     3,949
                                     2,215
                                     2,368
                                     1,458
                                     1,531
New Hampshire
                                     2,158
                                      601
                                      590
                                      533
                                      529
New Jersey
                                     5,723
                                     5,771
                                     5,889
                                     6,135
                                     6,582
New Mexico
                                    20,222
                                     8,246
                                     9,332
                                     6,532
                                     6,542
New York
                                    13,770
                                    14,740
                                    14,552
                                    13,699
                                    13,707
North Carolina
                                    27,892
                                    30,088
                                    29,482
                                    21,685
                                    24,320
North Dakota
                                    38,400
                                    25,458
                                    25,772
                                    25,314
                                    24,151
Ohio
                                    55,581
                                    40,029
                                    45,211
                                    38,572
                                    43,345
Oklahoma
                                    25,084
                                    17,877
                                    17,396
                                    17,342
                                    16,375
Oregon
                                     4,067
                                     1,560
                                     1,827
                                     1,665
                                     1,791
Pennsylvania
                                    84,086
                                    33,301
                                    31,707
                                    31,326
                                    28,769
Rhode Island
                                      261
                                      769
                                      764
                                      739
                                      737
South Carolina
                                    13,734
                                    13,460
                                    13,474
                                    13,053
                                    13,048
South Dakota
                                     1,095
                                      692
                                      756
                                      832
                                      776
Tennessee
                                    18,752
                                     4,285
                                     5,896
                                     4,753
                                     5,958
Texas
                                    111,612
                                    81,051
                                    82,699
                                    80,579
                                    77,506
Tribal Data
                                    35,057
                                     6,897
                                     6,907
                                     6,902
                                     6,854
Utah
                                    27,450
                                    21,063
                                    14,455
                                    20,991
                                    13,986
Vermont
                                      302
                                      21
                                      21
                                      20
                                      20
Virginia
                                    26,387
                                    10,183
                                    10,050
                                    11,217
                                    11,899
Washington
                                     8,860
                                     1,760
                                     1,909
                                     1,809
                                     1,875
West Virginia
                                    50,984
                                    41,891
                                    41,992
                                    39,495
                                    39,601
Wisconsin
                                    16,148
                                    10,238
                                    10,467
                                    10,048
                                     9,293
Wyoming
                                    36,095
                                    15,216
                                    17,463
                                    13,300
                                    13,371

 Non-EGU Point and Nonpoint Sector Projections
To project all U.S. non-EGU stationary sources, facility/unit closures information and growth (PROJECTION) factors and/or controls were applied to certain categories within the afdust, ag, cmv, rail, nonpt, np_oilgas, ptnonipm, pt_oilgas and rwc platform sectors.  Some facility or sub-facility-level closure information was also applied to the point sources.  There are also a handful of situations where new inventories were generated for sources that did not exist in the 2014v2 NEI (e.g., biodiesel and cellulosic plants, yet-to-be constructed cement kilns).  This subsection provides details on the data and projection methods used for these sectors.

Because much of the projections and controls data are developed independently from how the EPA defines its emissions modeling sectors, this section is organized primarily by the type of projections data, with secondary consideration given to the emissions modeling sector (e.g., industrial source growth factors are applicable to four emissions modeling sectors).  The rest of this section is organized in the order that the EPA uses the Control Strategy Tool (CoST) in combination with other methods to produce future year inventories: 1) for point sources, apply plant (facility or sub-facility-level) closure information via CoST; 2) apply all PROJECTION packets via CoST (multiplicative factors that could cause increases or decreases); 3) apply all percent reduction-based CONTROL packets via CoST; and 4) append all other future-year inventories not generated via CoST.  This organization allows consolidation of the discussion of the emissions categories that are contained in multiple sectors, because the data and approaches used across the sectors are consistent and do not need to be repeated.  Sector names associated with the CoST packets are provided in parentheses.
 Background on the Control Strategy Tool (CoST)
CoST is used to apply most non-EGU projection/growth factors, controls and facility/unit/stack-level closures to the 2016-based emissions modeling inventories to create future year inventories for the following sectors:  afdust, ag, cmv, rail, nonpt, np_oilgas, ptnonipm, pt_oilgas and rwc.  Information about CoST and related data sets is available from https://www.epa.gov/economic-and-cost-analysis-air-pollution-regulations/cost-analysis-modelstools-air-pollution.

CoST allows the user to apply projection (growth) factors, controls and closures at various geographic and inventory key field resolutions.  Each of these CoST datasets, also called "packets" or "programs," provides the user with the ability to perform numerous quality assurance assessments as well as create SMOKE-ready future year inventories.  Future year inventories are created for each emissions modeling sector via a CoST "strategy" and each strategy includes all base year 2016 inventories and applicable CoST packets.  For reasons discussed later, some emissions modeling sectors require multiple CoST strategies to account for the compounding of control programs that impact the same type of sources.  There are also available linkages to existing and user-defined control measures databases and it is up to the user to determine how control strategies are developed and applied.  The EPA typically creates individual CoST packets that represent specific intended purposes (e.g., aircraft projections for airports are in a separate PROJECTION packet from residential wood combustion sales/appliance turnover-based projections).  CoST uses three packet types as described below:
 CLOSURE: Applied first in CoST.  This packet can be used to zero-out (close) point source emissions at resolutions as broad as a facility to as specific as a stack.  The EPA uses these types of packets for known post-2016 controls as well as information on closures provided by states on specific facilities, units or stacks.  This packet type is only used in the ptnonipm and pt_oilgas sectors.
 PROJECTION: This packet allows the user to increase or decrease emissions for virtually any geographic and/or inventory source level.  Projection factors are applied as multiplicative factors to the 2011 emissions inventories prior to the application of any possible subsequent CONTROLs.  A PROJECTION packet is necessary whenever emissions increase from 2011 and is also desirable when information is based more on activity assumptions rather than known control measures.  The EPA uses PROJECTION packet(s) in every non-EGU modeling sector.
 CONTROL: These packets are applied after any/all CLOSURE and PROJECTION packet entries.  The user has similar level of control as PROJECTION packets regarding specificity of geographic and/or inventory source level application.  Control factors are expressed as a percent reduction (0 to 100) and can be applied in addition to any pre-existing inventory control, or as a replacement control where inventory controls are first backed out prior to the application of a more-stringent replacement control.

All of these packets are stored as data sets within the Emissions Modeling Framework and use comma-delimited formats.  As mentioned above, CoST first applies any/all CLOSURE information for point sources, then applies PROJECTION packet information, followed by CONTROL packets.  A hierarchy is used by CoST to separately apply PROJECTION and CONTROL packets.  In short, in a separate process for PROJECTION and CONTROL packets, more specific information is applied in lieu of less-specific information in ANY other packets.  For example, a facility-level PROJECTION factor will be replaced by a unit-level, or facility and pollutant-level PROJECTION factor.  It is important to note that this hierarchy does not apply between packet types (e.g., CONTROL packet entries are applied irrespective of PROJECTION packet hierarchies).  A more specific example: a state/SCC-level PROJECTION factor will be applied before a stack/pollutant-level CONTROL factor that impacts the same inventory record.  However, an inventory source that is subject to a CLOSURE packet record is removed from consideration of subsequent PROJECTION and CONTROL packets.

The implication for this hierarchy and intra-packet independence is important to understand and quality assure when creating future year strategies.  For example, with consent decrees, settlements and state comments, the goal is typically to achieve a targeted reduction (from the 2011NEI) or a targeted future-year emissions value. Therefore, as encountered with this future year base case, consent decrees and state comments for specific cement kilns (expressed as CONTROL packet entries) needed to be applied instead of (not in addition to) the more general approach of the PROJECTION packet entries for cement manufacturing.  By processing CoST control strategies with PROJECTION and CONTROL packets separated by the type of broad measure/program, it is possible to show actual changes from the base year inventory to the future year inventory as a result of applying each packet.

Ultimately, CoST concatenates all PROJECTION packets into one PROJECTION dataset and uses a hierarchal matching approach to assign PROJECTION factors to the inventory.  For example, a packet entry with Ranking=1 will supersede all other potential inventory matches from other packets.  CoST then computes the projected emissions from all PROJECTION packet matches and then performs a similar routine for all CONTROL packets.  Therefore, when summarizing "emissions reduced" from CONTROL packets, it is important to note that these reductions are not relative to the 2011 inventory, but rather to the intermediate inventory after application of any/all PROJECTION packet matches (and CLOSURES).  A subset of the more than 70 hierarchy options is shown in Table 4-3, although the fields in the table are not necessarily named the same in CoST, but rather are similar to those in the SMOKE FF10 inventories.  For example, "REGION_CD" is the county-state-county FIPS code (e.g., Harris county Texas is 48201) and "STATE" would be the 2-digit state FIPS code with three trailing zeroes (e.g., Texas is 48000).
Table 4-3. Subset of CoST Packet Matching Hierarchy
Rank
Matching Hierarchy
Inventory Type
                                       1
REGION_CD, FACILITY_ID, UNIT_ID, REL_POINT_ID, PROCESS_ID, SCC, POLL
point
                                       2
REGION_CD, FACILITY_ID, UNIT_ID, REL_POINT_ID, PROCESS_ID, POLL
point
                                       3
REGION_CD, FACILITY_ID, UNIT_ID, REL_POINT_ID, POLL
point
                                       4
REGION_CD, FACILITY_ID, UNIT_ID, POLL
point
                                       5
REGION_CD, FACILITY_ID, SCC, POLL
point
                                       6
REGION_CD, FACILITY_ID, POLL
point
                                       7
REGION_CD, FACILITY_ID, UNIT_ID, REL_POINT_ID, PROCESS_ID, SCC
point
                                       8
REGION_CD, FACILITY_ID, UNIT_ID, REL_POINT_ID, PROCESS_ID
point
                                       9
REGION_CD, FACILITY_ID, UNIT_ID, REL_POINT_ID
point
                                      10
REGION_CD, FACILITY_ID, UNIT_ID
point
                                      11
REGION_CD, FACILITY_ID, SCC
point
                                      12
REGION_CD, FACILITY_ID
point
                                      13
REGION_CD, NAICS, SCC, POLL
point, nonpoint
                                      14
REGION_CD, NAICS, POLL
point, nonpoint
                                      15
STATE, NAICS, SCC, POLL
point, nonpoint
                                      16
STATE, NAICS, POLL
point, nonpoint
                                      17
NAICS, SCC, POLL
point, nonpoint
                                      18
NAICS, POLL
point, nonpoint
                                      19
REGION_CD, NAICS, SCC
point, nonpoint
                                      20
REGION_CD, NAICS
point, nonpoint
                                      21
STATE, NAICS, SCC
point, nonpoint
                                      22
STATE, NAICS
point, nonpoint
                                      23
NAICS, SCC
point, nonpoint
                                      24
NAICS
point, nonpoint
                                      25
REGION_CD, SCC, POLL
point, nonpoint
                                      26
STATE, SCC, POLL
point, nonpoint
                                      27
SCC, POLL
point, nonpoint
                                      28
REGION_CD, SCC
point, nonpoint
                                      29
STATE, SCC
point, nonpoint
                                      30
SCC
point, nonpoint
                                      31
REGION_CD, POLL
point, nonpoint
                                      32
REGION_CD
point, nonpoint
                                      33
STATE, POLL
point, nonpoint
                                      34
STATE
point, nonpoint
                                      35
POLL
point, nonpoint

The contents of the controls, local adjustments and closures for the future year base case are described in the following subsections.  Year-specific projection factors (PROJECTION packets) for the future year were used to create the future year base case, unless noted otherwise in the specific subsections.  The contents of a few of these projection packets (and control reductions) are provided in the following subsections where feasible.  However, most sectors used growth or control factors that varied geographically and their contents could not be provided in the following sections (e.g., facilities and units subject to the Boiler MACT reconsideration has thousands of records).  The remainder of Section 4.2 is divided into several subsections that are summarized in Table 4-4.  Note that future year inventories were used rather than projection or control packets for some sources.
Table 4-4. Summary of non-EGU stationary projections subsections
Subsection
Title
Sector(s)
Brief Description
4.2.2
CoST Plant CLOSURE packet
ptnonipm, pt_oilgas
All facility/unit/stack closures information, primarily from Emissions Inventory System (EIS), but also includes information from states and other organizations.
4.2.3
CoST PROJECTION packets
All
Introduces and summarizes national impacts of all CoST PROJECTION packets to the future year.
<IP_ADDRESS>
Fugitive dust growth
afdust
PROJECTION packet: county-level resolution, primarily based on VMT growth.
<IP_ADDRESS>
Livestock population growth
ag
PROJECTION packet: national, by-animal type resolution, based on animal population projections.
<IP_ADDRESS>
Category 1, 2, and 3 commercial marine vessels
cmv
PROJECTION packet: Category 1 & 2: CMV uses SCC/poll for all states except Calif.

<IP_ADDRESS>
Category 3 commercial marine vessels
cmv
PROJECTION packet: Category 3: region-level by-pollutant, based on cumulative growth and control impacts from rulemaking.
<IP_ADDRESS>
Oil and gas and industrial source growth
nonpt, np_oilgas, ptnonipm, pt_oilgas
Several PROJECTION packets: varying geographic resolutions from state, county, to oil/gas play-level and by-process/fuel-type applications.  Data derived from AEO2016 with several modifications.
<IP_ADDRESS>
Non-IPM Point Sources
ptnonipm
Several PROJECTION packets: specific projections from MARAMA region and states, EIA-based projection factors for industrial sources for non-MARAMA states.
<IP_ADDRESS>
Nonpoint sources
nonpt
Several PROJECTION packets: MARAMA states projection for Portable Fuel Containers and for all other nonpt sources. Non-MARAMA states projected with EIA-based factors for industrial sources. Evaporative Emissions from Finished Fuels projected using EIA-based factors. Human population used as growth for applicable sources.
<IP_ADDRESS>
Airport Sources
ptnonipm
PROJECTION packet: by-airport for all direct matches to FAA Terminal Area Forecast data, with state-level factors for non-matching NEI airports.
<IP_ADDRESS>
Residential wood combustion
rwc
PROJECTION packet: national with exceptions, based on appliance type sales growth estimates and retirement assumptions and impacts of recent NSPS.
4.2.4
CoST CONTROL packets
ptnonipm, nonpt, np_oilgas, pt_oilgas
Introduces and summarizes national impacts of all CoST CONTROL packets to the future year.
<IP_ADDRESS>
Oil and Gas NSPS
np_oil gas, pt_oilgas

<IP_ADDRESS>
RICE NSPS
ptnonipm, nonpt, np_oilgas, pt_oilgas
CONTROL packet: applies reductions for lean burn, rich burn, and combined engines for identified SCCs.
<IP_ADDRESS>
Fuel Sulfur Rules
ptnonipm, nonpt
CONTROL packet: updated by MARAMA, applies reductions to specific units in ten states.
<IP_ADDRESS>
Natural Gas Turbines NOx NSPS
ptnonipm
CONTROL packet: applies NOx emission reductions established by the NSPS.
<IP_ADDRESS>
Process Heaters NOx NSPS
ptnonipm
CONTROL packet: applies NOx emission limits established by the NSPS.
<IP_ADDRESS>
CISWI
ptnonipm
CONTROL packet: applies controls to specific CISWI units in 11 states.
<IP_ADDRESS>
Petroleum Refineries NSPS Subpart JA
ptnonipm
CONTROL packet: control efficiencies are applied to identified delayed coking and storage tank units.
<IP_ADDRESS>
State-Specific Controls
ptnonipm
CONTROL packets and comments submitted by individual states for rules that may only impact their state or corrections noted from previous review.

 CoST Plant CLOSURE Packet (ptnonipm, pt_oilgas)
Packet: CLOSURES_2016_beta_platform_04oct2019_v1

The CLOSURES packet contains facility, unit and stack-level closure information derived from an Emissions Inventory System (EIS) unit-level report from March 5, 2019, with closure status equal to "PS" (permanent shutdown; i.e., post-2016 permanent facility/unit shutdowns known in EIS as of the date of the report). In addition, comments on past modeling platforms received by states and other agencies specified additional closures, as well as some previously specified closures which should remain open, in the following states: Alabama, North Carolina, Ohio, Pennsylvania, and Virginia.  Ultimately, all data were updated to match the SMOKE FF10 inventory key fields, with all duplicates removed, and a single CoST packet was generated.  These changes impact sources in the ptnonipm and pt_oilgas sectors.  The cumulative reduction in emissions for ptnonipm are shown in Table 4-5.
Table 4-5. Reductions from all facility/unit/stack-level closures in 2016v1
                                   Pollutant
                                   ptnonipm
                                   pt_oilgas
CO
                                                                          1,010
                                                                            187
NH3
                                                                             59
                                                                              0
NOX
                                                                          1,373
                                                                            284
PM10
                                                                            447
                                                                              9
PM2.5
                                                                            358
                                                                              9
SO2
                                                                            727
                                                                            178
VOC
                                                                          2,211
                                                                            106

 CoST PROJECTION Packets (afdust, ag, cmv, rail, nonpt, np_oilgas, ptnonipm, pt_oilgas, rwc)
As previously discussed, for point inventories, after application of any/all CLOSURE packet information, the next step in running a CoST control strategy is the application of all CoST PROJECTION packets.  Regardless of inventory type (point or nonpoint), the PROJECTION packets applied prior to the CoST packets.  For several emissions modeling sectors (i.e., afdust, ag, cmv, rail and rwc), there is only one CoST PROJECTION packet. For all other sectors, there are several different sources of PROJECTIONS data and, therefore, there are multiple PROJECTION packets that are concatenated and quality-assured for duplicates and applicability to the inventories in the CoST strategy.  The PROJECTION (and CONTROL) packets were separated into a few "key" control program types to allow for quick summaries of these distinct control programs.  The remainder of this section is broken out by CoST packet, with the exception of discussion of the various packets used for oil and gas and industrial source projections; these packets are a mix of different sources of data that target similar sources.

MARAMA provided PROJECTION and CONTROL packets for years 2023 and 2028 for states including: Connecticut, Delaware, Maryland, Massachusetts, New Hampshire, New York, New Jersey, North Carolina, Pennsylvania, Rhode Island, Vermont, Virginia, West Virginia, Maine, and the District of Columbia.   MARAMA only provided pt_oilgas and np_oilgas packets for Rhode Island, Maryland and Massachusetts. For states not covered by the MARAMA packets, projection factors were developed using nationally available data and methods

 Fugitive dust growth (afdust)
Packets:
      Projection_2016_2023_afdust_version1_platform_MARAMA_04oct2019_v1 Projection_2016_2023_afdust_version1_platform_NJ_13sep2019_v0 Projection_2016_2023_afdust_version1_platform_national_04oct2019_v1 Projection_2016_2023_all_nonpoint_version1_platform_NC_04oct2019_v2 Projection_2016_2028_afdust_version1_platform_MARAMA_04oct2019_v1 Projection_2016_2028_afdust_version1_platform_NJ_13sep2019_v0 Projection_2016_2028_afdust_version1_platform_national_04oct2019_v1 Projection_2016_2028_all_nonpoint_version1_platform_NC_04oct2019_v2

MARAMA States
MARAMA submitted projection factors for their states to project 2016 afdust emissions to future years 2023 and 2028. These county-specific projection factors impacted paved roads (SCC<PHONE_NUMBER>), residential construction dust (SCC<PHONE_NUMBER>), industrial/commercial/institutional construction dust (SCC<PHONE_NUMBER>), road construction dust (SCC<PHONE_NUMBER>), dust from mining and quarrying (SCC<PHONE_NUMBER>), agricultural crop tilling dust (SCC<PHONE_NUMBER>), and agricultural dust kick-up from beef cattle hooves (SCC<PHONE_NUMBER>). Other afdust emissions, including unpaved road dust emissions, were held constant in future year projections. Note that North Carolina and New Jersey provided their own packets for this sector.

Non-MARAMA States
For paved roads (SCC<PHONE_NUMBER>), the 2016 afdust emissions were projected to future years 2023 and 2028 based on differences in county total VMT:
Future year afdust paved roads = 2016 afdust paved roads * (Future year county total VMT) / (2016 county total VMT)
The VMT projections are described in the onroad section.
All emissions other than paved roads are held constant in future year projections.  The impacts of the projections are shown in Table 4-6.
Table 4-6. Increase in total afdust PM2.5 emissions from projections in 2016v1
2016 Emissions
2023 Emissions
percent Increase 2023
2028 Emissions
percent Increase 2028
                                   2,530,625
                                   2,557,970
                                     1.09%
                                   2,570,714
                                     1.60%

 Livestock population growth (ag)
Packet:
      Projection_2016_2023_all_nonpoint_version1_platform_NC_04oct2019_v2
      Projection_2016_2028_all_nonpoint_version1_platform_NC_04oct2019_v2
      Projection_2017_2023_ag_version1_platform_11sep2019_v0
      Projection_2017_2023_ag_version1_platform_NJ_11sep2019_v0
      Projection_2017_2028_ag_version1_platform_11sep2019_v0
      Projection_2017_2028_ag_version1_platform_NJ_11sep2019_v0
The 2017NEI livestock emissions were projected to year 2023 and 2028 using projection factors created from USDA National livestock inventory projections published in March 2019 (https://www.ers.usda.gov/publications/pub-details/?pubid=92599) and are shown in Table 4-7. For emission projections to 2023, a ratio was created between animal inventory counts for 2023 and 2017 to create a projection factor. This process was completed for the animal categories of beef, dairy, broilers, layers, turkeys, and swine. The projection factor was then applied to the 2017NEI base emissions for the specific animal type to estimate 2023 NH3 and VOC emissions. For emission projections to 2028, the same projection method was used. New Jersey (NJ) provided NJ-specific projection factors that were used to grow livestock waste emissions from 2017 to 2023 and 2028. North Carolina (NC) provided NC-specific projection factors that used a 2016-based projection, therefore, NC's livestock waste emissions are projected from the 2016 back-casted base year emissions to 2023 and 2028.
Table 4-7. National projection factors for livestock: 2016 to 2023 and 2028
                                    Animal
                                     2023
                                     2028
beef
-0.02%
-2.87%
swine
+7.47%
+10.36%
broilers
+8.60%
+12.50%
turkeys
-0.03%
+1.57%
layers
+9.28%
+15.93%
dairy
+0.92%
+1.24%
 Category 1, Category 2 Commercial Marine Vessels (cmv_c1c2)
The cmv_c1c2 emissions outside of California were projected from 2016 to 2023 and 2028 using factors derived from the Regulatory Impact Analysis (RIA) Control of Emissions of Air Pollution from Locomotive Engines and Marine Compression Ignition Engines Less than 30 Liters per Cylinder (https://www.epa.gov/regulations-emissions-vehicles-and-engines/final-rule-control-emissions-air-pollution-locomotive). Table 4-8 lists the pollutant-specific projection factors to 2023, and 2028 that were used for cmv_c1c2 sources outside of California. California sources were projected to 2023 and 2028 using the factors in Table 4-9, which are based on data provided by CARB.

Table 4-8. National projection factors for cmv_c1c2
Pollutant
2016-to-2023
2016-to-2028
CO
-2.67%
-1.11%
NOX
-34.6%
-48.7%
PM10
-36.2%
-49.6%
PM2.5
-36.2%
-49.6%
SO2
-86.2%
-86.5%
VOC
-37.0%
-51.4%

Table 4-9. California projection factors for cmv_c1c2
Pollutant
2016-to-2023
2016-to-2028
CO
20.1%
25.3%
NOX
-29.3%
-17.7%
PM10
-29.9%
-33.5%
PM2.5
-29.9%
-33.5%
SO2
24.1%
48.7%
VOC
1.5%
1.9%

 Category 3 Commercial Marine Vessels (cmv_c3)
Growth rates for cmv_c3 emissions from 2016 to 2023 and 2028 were developed using a forthcoming EPA report on projected bunker fuel demand. The report projects bunker fuel consumption by region out to the year 2030. Bunker fuel usage was used as a surrogate for marine vessel activity. To estimate future year emissions of CO, CO2, hydrocarbons, PM10, and PM2.5, the bunker fuel growth rate from 2016 to 2023, and 2028 were directly applied to the estimated 2016 emissions.

Growth factors for NOx emissions were handled separately to account for the phase in of Tier 3 vessel engines. To estimate these emissions, the NOx growth rates from the EPA C3 Regulatory Impact Assessment (RIA) were refactored to use the new bunker fuel usage growth rates. The assumptions of changes in fleet composition and emissions rates from the C3 RIA were preserved and applied to the new bunker fuel demand growth rates for 2023, and 2028 to arrive at the final growth rates. The Category 3 marine diesel engines Clean Air Act and International Maritime Organization standards from April, 2010 (https://www.epa.gov/regulations-emissions-vehicles-and-engines/final-rule-control-emissions-new-marine-compression-0) were also considered for emission estimates.

The 2023 and 2028 projection factors are shown in Table 4-10. Some regions for which 2016 projection factors were available did not have 2023 or 2028 projection factors specific to that region, so factors from another region were used as follows:
 Alaska was projected using North Pacific factors.
 Hawaii was projected using South Pacific factors.
 Puerto Rico and Virgin Islands were projected using Gulf Coast factors.
 Emissions outside Federal Waters (FIPS 98) were projected using the factors given in Table 4-10 for the region "Other".
 California was projected using a separate set of state-wide projection factors based on CMV emissions data provided by the California Air Resources Board (CARB). These factors are shown in Table 4-11
Table 4-10. 2016-to-2023 and 2016-2028 CMV C3 projection factors outside of California
Region
                               2016-to-2023
NOX
                         2016-to-2023
other pollutants
                               2016-to-2028
NOX
                         2016-to-2028
other pollutants
US East Coast
                                    -6.05%
                                    27.71%
                                    -7.54%
                                    49.71%
US South Pacific
(ex. California)
                                    -24.79%
                                    20.89%
                                    -33.97%
                                    45.86%
US North Pacific
                                    -3.37%
                                    22.57%
                                    -4.07%
                                    41.31%
US Gulf
                                    -6.88%
                                    20.82%
                                    -12.40%
                                    36.41%
US Great Lakes
                                     8.71%
                                    14.55%
                                    19.80%
                                    28.29%
Other
                                    23.09%
                                    23.09%
                                    42.58%
                                    42.58%

 Non-Federal Waters
                                 2016-to-2023
                                 2016-to-2028
SO2
                                    -77.21%
                                    -73.60%
PM (main engines)
                                    -36.06%
                                    -25.93%
PM (aux. engines)
                                    -39.69%
                                    -30.14%
Other pollutants
                                    +23.09%
                                    +42.58%

Table 4-11. 2016-to-2023 and 2016-2028 CMV C3 projection factors for California
Pollutant
                                 2016-to-2023
                                 2016-to-2028
CO
                                     18.0%
                                     34.0%
Nox
                                     15.6%
                                     32.7%
PM10 / PM2.5
                                     20.5%
                                     38.1%
SO2
                                     18.3%
                                     33.2%
VOC
                                     24.2%
                                     46.1%
 Oil and Gas Sources (pt_oilgas, np_oilgas)
Future year projections for the 2016v1 platform were generated for point oil and gas sources for years 2023 and 2028.  These projections consisted of three components: (1) applying facility closures to the pt_oilgas sector using the CoST CLOSURE packet; (2) using historical and/or forecast activity data to generate future-year emissions before applicable control technologies are applied using the CoST PROJECTION packet; and (3) estimating impacts of applicable control technologies on future-year emissions using the CoST CONTROL packet. Applying the CLOSURE packet to the pt_oilgas sector resulted in small emissions changes to the national summary shown inTable 4-5.  Note the closures for years 2023 and 2028 are the same.

For pt_oilgas growth to 2023 and 2028, the oil and gas sources were separated into production-related and exploration-related sources by SCC. These sources were further subdivided by fuel-type by SCC into either OIL, natural gas (NGAS), BOTH oil-natural gas fuels possible, or coal-bed methane (CBM).  The next two subsections describe the growth component process.

For np_oilgas growth to 2023 and 2028, oil and gas sources were separated into production-related, transmission-related, and all other point sources by NAICS.  These sources are further subdivided by fuel-type by SCC into either OIL, natural gas (NGAS), or BOTH oil-natural gas fuels possible.

Production-related Sources (pt_oilgas, np_oilgas)

The growth factors for the production-related NAICS-SCC combinations were generated in a two-step process.   The first step used historical production data at the state-level to get state-level short-term trends or factors from 2016 to year 2017. In some cases, historical data for year 2018 were available for a state, in these cases a 2016 to 2018 factor was calculated. These historical data were acquired from EIA from the following links:

 Historical Natural Gas: http://www.eia.gov/dnav/ng/ng_sum_lsum_a_epg0_fgw_mmcf_a.htm
 Historical Crude Oil: http://www.eia.gov/dnav/pet/pet_crd_crpdn_adc_mbbl_a.htm
 Historical CBM: https://www.eia.gov/dnav/ng/ng_prod_coalbed_s1_a.htm

The second step involved using the Annual Energy Outlook (AEO) 2019 reference case for the Lower 48 forecast production tables to project from year 2017 to the years of 2023 and 2028.   Specifically, AEO 2019 Table 60 "Lower 48 Crude Oil Production and Wellhead Prices by Supply Region" and AEO 2019 Table 61 "Lower 48 Natural Gas Production and Supply Prices by Supply Region" were used in this projection process.  The AEO2019 forecast production is supplied for each EIA Oil and Gas Supply region shown in Figure 4-1.

Figure 4-1.  EIA Oil and Gas Supply Regions as of AEO2019

The result of this second step is a growth factor for each Supply Region from 2017 (or 2018) to 2023 and from 2017 (or 2018) to 2028. A Supply Region mapping to FIPS cross-walk was developed so the regional growth factors could be applied for each FIPS (for pt_oilgas) or to the county-level np_oilgas inventories. Note that portions of Texas are in three different Supply Regions and portions of New Mexico are in two different supply regions. The state-level historical factor (2016 to 2017 or 2018) was then multiplied by the Supply Region factor (2017 or 2018 to future years) to produce a state-level or FIPS-level factor to grow from 2016 to 2023 and from 2016 to 2028. This process was done using crude production forecast information to generate a factor to apply to oil-production related SCCs or NAICS-SCC combinations and it was also done using natural gas production forecast information to generate a factor to apply to natural gas-production related NAICS-SCC combinations. For the NAICS-SCC combinations that are designated "BOTH" the average of the oil-production and natural-gas production factors was calculated and applied to these specific combinations.

The state of Texas provided specific technical direction for growth of production-related point sources. Texas provided updated basin specific production for 2016 and 2017 to allow for a better calculation of the estimated growth for this one-year period. The AEO2019 was used as described above for the three AEO Oil and Gas Supply Regions that include Texas counties to grow from 2017 to 2023 and 2028 years. However, Texas only wanted these growth factors applied to sources in the Permian and Eagle Ford basins. The oil and gas production point sources in the other basins in Texas were not grown (i.e., 2016v1=2023=2028 emissions).

Transmission-related Sources (pt_oilgas)

Projection factors were generated using the same AEO2019 tables used for production sources.  The growth factors for transmission sources were developed solely using AEO 2019 data by Oil and Gas Supply Regions shown in Figure 4-1. Additionally, limits were put on these regional factors where the minimum factor was set to 1.0 and the maximum factor was set to 1.5. The states of Virginia and Pennsylvania provided source specific growth factors for natural gas transmission sources to be used in place of the AEO regional factors.

Exploration-related Sources (np_oilgas)
Due to Year 2016 being a low exploration activity year when compared to exploration activity in other recent years, Years 2014 through 2017 exploration activity data were averaged and the average activity input into EPA's Oil and Gas Tool to produce "averaged" emissions for exploration sources (Table 4-12). This four-year average (2014-2017) activity data were used because they were readily available for use with the 2016v1 platform. These averaged emissions were used for both the 2023 and 2028 future years in the 2016v1 emissions modeling platform. Colorado, Pennsylvania, California, and Oklahoma submitted inventories for use. Note CoST was not used for this step for exploration sources.

Table 4-12.  Year 2014-2017 high-level summary of national oil and gas exploration activity
                           Parameter (all US states)
                                   Year2014
                                   Year2015
                                   Year2016
                                   Year2017
                                4-year average
Total Well Completions
                                                                         40,306
                                                                         22,754
                                                                         15,605
                                                                         21,850
                                                                         25,129
Unconventional Well Completions
                                                                         20,896
                                                                         11,673
                                                                          7,610
                                                                         11,617
                                                                         12,949
Total Oil Spuds
                                                                         36,104
                                                                         17,240
                                                                          7,014
                                                                         14,322
                                                                         18,670
Total Natural Gas Spuds
                                                                          4,750
                                                                          3,168
                                                                          4,244
                                                                          4,025
                                                                          4,047
Total Coalbed Methane Spuds
                                                                            239
                                                                            130
                                                                            141
                                                                            222
                                                                            183
Total Spuds
                                                                         41,093
                                                                         20,538
                                                                         11,399
                                                                         18,569
                                                                         22,900
Total Feet Drilled
                                                                    327,832,580
                                                                    178,297,779
                                                                    106,468,774
                                                                    181,164,800
                                                                    198,440,983

 Non-EGU point sources (ptnonipm)
The 2023 and 2028 ptnonipm projections involved several growth and projection methods described here. The projection of all oil and gas sources is explained in the oil and gas specification sheet and will not be discussed in these methods.
2023 and 2028 Point Inventory - inside MARAMA region

2016-to-2023 and 2016-to-2028 projection packets for point sources were provided by MARAMA for the following states: CT, DE, DC, ME, MD, MA, NH, NJ, NY, NC, PA, RI, VT, VA, and WV.

The MARAMA projection packets were used throughout the MARAMA region, except in North Carolina, New Jersey, and Virginia. Those three states provided their own projection packets for the ptnonipm sector, and those projection packets were used instead of the MARAMA packets in those states. The Virginia growth factors for one facility were edited to incorporate emissions limits provided by MARAMA for that facility.

2023 and 2028 Point Inventory - outside MARAMA region

The Energy Information Administration's (EIA) AEO for year 2019 was used as a starting point for projecting industrial sources in this sector. SCC's were mapped to AEO categories and projection factors were created using a ratio between the base year and projection year estimates from each specific AEO category. Table 4-13 below details the 2019 AEO tables used to map SCCs to AEO categories for the projections of industrial sources. Depending on the category, a projection factor may be national or regional. The maximum projection factor was capped at 1.25 and the minimum projection factor was capped at 0.5. MARAMA states were not projected using this method, nor were aircraft and rail sources.
An SCC-NAICS projection was also developed using AEO2019. SCC/NAICS combinations with emissions >100tons/year for any CAP were mapped to AEO sector and fuel. Projection factors for this method were capped at a maximum of 2.5 and a minimum of 0.5.
Table 4-13. EIA's 2019 Annual Energy Outlook (AEO) tables used to project industrial sources
Table #
Table name
                                       2
Energy Consumption by Sector and Source
                                      25
Refining Industry Energy Consumption
                                      26
Food Industry Energy Consumption
                                      27
Paper Industry Energy Consumption
                                      28
Bulk Chemical Industry Energy Consumption
                                      29
Glass Industry Energy Consumption
                                      30
Cement Industry Energy Consumption
                                      31
Iron and Steel Industries Energy Consumption
                                      32
Aluminum Industry Energy Consumption
                                      33
Metal Based Durables Energy Consumption
                                      34
Other Manufacturing Sector Energy Consumption
                                      35
Nonmanufacturing Sector Energy Consumption
The state of Wisconsin provided source-specific growth factors for four facilities in the state. For those facilities, the growth factors provided by Wisconsin were used instead of those derived from the AEO.
 Nonpoint Sources (nonpt)

Inside MARAMA region

2016-to-2023 and 2016-to-2028 projection packets for all nonpoint sources were provided by MARAMA for the following states: CT, DE, DC, ME, MD, MA, NH, NJ, NY, NC, PA, RI, VT, VA, and WV. MARAMA provided one projection packet per year for portable fuel containers (PFCs), and a second projection packet per year for all other nonpt sources.

The MARAMA projection packets were used throughout the MARAMA region, except in North Carolina and New Jersey. Both NC and NJ provided separate projection packets for the nonpt sector, and those projection packets were used instead of the MARAMA packets in those two states. New Jersey did not provide projection factors for PFCs, and so NJ PFCs were projected using the MARAMA PFC growth packet.

Industrial Sources outside MARAMA region

The EIA's AEO for year 2019 was used as a starting point for projecting industrial sources in this sector. SCC's were mapped to AEO categories and projection factors were created using a ratio between the base year and projection year estimates from each specific AEO category. For the nonpoint sector, only 2018 AEO Table 2 was used to map SCCs to AEO categories for the projections of industrial sources. Depending on the category, a projection factor may be national or regional. The maximum projection factor was capped at a factor of 1.25 and the minimum projection factor was capped at 0.5. Aircraft and rail sources were not projected using this method. Sources within the MARAMA region were not projected with these factors, but with the MARAMA-provided growth factors.
Evaporative Emissions from Transport of Finished Fuels outside MARAMA region

Estimates on growth of evaporative emissions from transporting finished fuels are partially covered in the nonpoint and point oil and gas projection packets.  However, there are some processes with evaporative emissions from storing and transporting finished fuels which are not included in the nonpoint and point oil and gas projection packets, e.g., withdrawing fuel from tanks at bulk plants, filling tanks at service stations, etc., and those processes are included in nonpoint other.  The EIA's AEO for year 2018 was used as a starting point for projecting volumes of finished fuel that would be transported in future years, i.e., 2023 and 2028.  Then these volumes were used to calculate inventories associated with evaporative emissions in 2016, 2023, and 2028 using the upstream modules.  Those emission inventories were mapped to the appropriate SCCs and projection packets were generated from 2016 to 2023 and 2016 to 2028 using the upstream modules.  Sources within the MARAMA region were not projected with these factors, but with the MARAMA-provided growth factors.
Human Population Growth outside MARAMA region
For SCCs that are projected based on human population growth, population projection data were available from the Benefits Mapping and Analysis Program (BenMAP) model by county for several years, including 2017, 2023, and 2028.  These human population data were used to create modified county-specific projection factors. Note that 2017 is being used as the base year since 2016 human population is not available in this dataset. A newer human population dataset was assessed but it did not have trustworthy near-term (e.g., 2023/2028) projections, and was not used; for example, rural areas of NC were projected to have more growth than urban areas, which is the opposite of what one would expect. Growth factors were limited to a range of 0.9-1.35 for 2023 and 0.85-1.6 for 2028, but none of the factors fell outside that range. (The 1.35 and 1.6 caps are based on 5% annual growth.) Sources within the MARAMA region were not projected with these factors, but with the MARAMA-provided growth factors.
 Airport sources (airports)
Airports emissions were projected to 2023 and 2028 mostly using 2018 Terminal Area Forecast (TAF) data available from the Federal Aviation Administration (https://www.faa.gov/data_research/aviation/taf/). Projection factors were computed using the ratio of the itinerant (ITN) data between the base and projection year. For airports not matching a unit in the TAF data, state default growth factors by itinerant class (commercial, air taxi, and general) were created from the collection of airports unmatched. Emission growth for facilities is capped at 500% and the state default growth is capped at 200%. Military state default projection values were kept flat (i.e., equal to 1.0) to reflect uncertainly in the data regarding these sources.
 Residential Wood Combustion (rwc)
For states other than California, Oregon, and Washington, RWC emissions from 2016 were projected to 2023 and 2028 using projection factors derived using the MARAMA tool that is based on the projection methodology from EPA's 2011v6.3 platform.  Table 4-14 contains the factors to adjust the emissions from 2016 to 2023 and 2028. California, Oregon, and Washington RWC were held constant at NEI2014v2 levels for 2016, 2023, and 2028 due to the unique control programs those states have in place.
Table 4-14. Projection factors for RWC
SCC

SCC description
Pollutant*

                                 2016-to-2023
                                 2016-to-2028
2104008100
Fireplace: general

                                     7.19%
                                    12.36%
2104008210
Woodstove: fireplace inserts; non-EPA certified

                                    -13.92%
                                    -17.97%
2104008220
Woodstove: fireplace inserts; EPA certified; non-catalytic
PM10-PRI
                                     4.09%
                                     5.08%
2104008220
Woodstove: fireplace inserts; EPA certified; non-catalytic
PM25-PRI
                                     4.09%
                                     5.08%
2104008220
Woodstove: fireplace inserts; EPA certified; non-catalytic

                                     8.34%
                                    10.28%
2104008230
Woodstove: fireplace inserts; EPA certified; catalytic
PM10-PRI
                                     6.06%
                                     7.68%
2104008230
Woodstove: fireplace inserts; EPA certified; catalytic
PM25-PRI
                                     6.06%
                                     7.68%
2104008230
Woodstove: fireplace inserts; EPA certified; catalytic

                                    12.08%
                                    15.27%
2104008310
Woodstove: freestanding, non-EPA certified
CO
                                    -12.09%
                                    -15.72%
2104008310
Woodstove: freestanding, non-EPA certified
PM10-PRI
                                    -12.67%
                                    -16.52%
2104008310
Woodstove: freestanding, non-EPA certified
PM25-PRI
                                    -12.67%
                                    -16.52%
2104008310
Woodstove: freestanding, non-EPA certified
VOC
                                    -11.40%
                                    -14.84%
2104008310
Woodstove: freestanding, non-EPA certified

                                    -12.09%
                                    -15.72%
2104008320
Woodstove: freestanding, EPA certified, non-catalytic
PM10-PRI
                                     4.09%
                                     5.08%
2104008320
Woodstove: freestanding, EPA certified, non-catalytic
PM25-PRI
                                     4.09%
                                     5.08%
2104008320
Woodstove: freestanding, EPA certified, non-catalytic

                                     8.34%
                                    10.28%
2104008330
Woodstove: freestanding, EPA certified, catalytic
PM10-PRI
                                     6.07%
                                     7.69%
2104008330
Woodstove: freestanding, EPA certified, catalytic
PM25-PRI
                                     6.07%
                                     7.69%
2104008330
Woodstove: freestanding, EPA certified, catalytic

                                    12.08%
                                    15.27%
2104008400
Woodstove: pellet-fired, general (freestanding or FP insert)
PM10-PRI
                                    30.09%
                                    38.02%
2104008400
Woodstove: pellet-fired, general (freestanding or FP insert)
PM25-PRI
                                    30.09%
                                    38.02%
2104008400
Woodstove: pellet-fired, general (freestanding or FP insert)

                                    26.96%
                                    33.85%
2104008510
Furnace: Indoor, cordwood-fired, non-EPA certified
CO
                                    -64.93%
                                    -84.78%
2104008510
Furnace: Indoor, cordwood-fired, non-EPA certified
PM10-PRI
                                    -62.99%
                                    -82.89%
2104008510
Furnace: Indoor, cordwood-fired, non-EPA certified
PM25-PRI
                                    -62.99%
                                    -82.89%
2104008510
Furnace: Indoor, cordwood-fired, non-EPA certified
VOC
                                    -65.02%
                                    -84.89%
2104008510
Furnace: Indoor, cordwood-fired, non-EPA certified

                                    -64.93%
                                    -84.78%
2104008610
Hydronic heater: outdoor
PM10-PRI
                                     0.06%
                                    -0.40%
2104008610
Hydronic heater: outdoor
PM25-PRI
                                     0.06%
                                    -0.40%
2104008610
Hydronic heater: outdoor

                                    -0.73%
                                    -1.30%
2104008700
Outdoor wood burning device, NEC (fire-pits, chimineas, etc)

                                     7.19%
                                     9.25%
2104009000
Fire log total

                                     7.19%
                                     9.25%
  * If no pollutant is specified, facture is used for any pollutants that do not have a pollutant-specific factor
 CoST CONTROL Packets (nonpt, np_oilgas, ptnonipm, pt_oilgas)
The final step in the projection of emissions to a future year is the application of any control technologies or programs. For future-year New Source Performance Standards (NSPS) controls (e.g., oil and gas, Reciprocating Internal Combustion Engines (RICE), Natural Gas Turbines, and Process Heaters), we attempted to control only new sources/equipment using the following equation to account for growth and retirement of existing sources and the differences between the new and existing source emission rates.

Qn  =   Qo { [ (1 + Pf ) t  -  1 ] Fn + ( 1 - Ri ) t  Fe + [ 1 - ( 1 - Ri ) t ] Fn ] }
Eq. 4-1
where:
      Qn  =  emissions in projection year
      Qo  =  emissions in base year
      Pf  =  growth rate expressed as ratio (e.g., 1.5=50 percent cumulative growth)
      t  =  number of years between base and future years
      Fn  =  emission factor ratio for new sources
      Ri  =  retirement rate, expressed as whole number (e.g., 3.3 percent=0.033)
      Fe  =  emission factor ratio for existing sources
The first term in Eq. 4-1 represents new source growth and controls, the second term accounts for retirement and controls for existing sources, and the third term accounts for replacement source controls.   For computing the CoST % reductions (Control Efficiency), the simplified Eq. 4-2 was used for 2028 projections: