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TECHNICAL MEMORANDUM

To: Julie McDill, MARAMA

From: Gregory Stella, Alpine Geophysics, LLC

Edward Sabo, MACTEC Engineering and Consulting, Inc.

Date: 17 December 2010

Re: MARAMA Work Order #9; SMOKE Auxiliary File Review

INTRODUCTION

The purpose of this work order is to conduct a quality assurance (QA) review of the SMOKE 

speciation, spatial and temporal allocation files and to perform limited updates to those files to 

fill in data gaps or improve the profiles for certain categories. We obtained the latest versions of 

the SMOKE ancillary file data from CHIEF’s website1relevant to EPA’s 2005v4 modeling 

platform. These data included speciation, spatial and temporal allocation files as well as the 

cross-reference files necessary to correlate emissions inventory data to these profiles. We also 

used the final versions of the MANEVU+VA 2007 area, point, and nonroad emission 

inventories. The MANEVU+VA 2007 onroad inventory was not included in this evaluation. 

CHECKS TO MATCH SCCs USED IN THE MANEVU+VA 2007 INVENTORY WITH 

SMOKE ANCILLARY FILES 

We performed QA checks to ensure that all SCCs in the final MARAMA 2007 annual emissions 

inventories were cross referenced to this ancillary data and when a proper cross reference did not 

exist, we made recommendations on valid matches.

Speciation Profiles

We conducted a check of the annual emissions inventory data for 2007 area, nonroad, and point 

source inventories to ensure that appropriate matches were made to the SMOKE speciation 

profiles and cross-reference files available from EPA. The SMOKE files from the EPA 

distribution used in this comparison were:

 gsref_cmaq_cb05_soa_2005ck_05b_19mar2009.txt: Speciation cross-reference file using 

SPECIATE4.0 with some SPECIATE4.2 profiles

 gspro_cmaq_cb05_soa_2005ck_05b_19mar2009.txt: Speciation profiles for CMAQ 

version 4.7 CB05 with SOA chemical mechanism

For the majority of SCCs and almost all of the domain wide emission totals, SCC-profile 

matches were found in all cases. A small list of SCCs did not have appropriate matches within 

the EPA distributed tables. We have recommended speciation profile assignments based on the 

profiles used for similar SCCs. For example, SCCs 2275050011 (Aircraft/General 

 

1

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

ancillary_2005v4_smokeformat.zip, dated 05/25/2010

readme_2005v2cap_bafm_haps_anicllary_inputs.txt, dated 07/08/2010
 

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Aviation/Piston) and 2275050012 (Aircraft/General Aviation/Turbine) are subsets of the more 

general SCC 2275050000 (Aircraft/General Aviation, All Types). The SMOKE speciation 

profile for 2275050000 was used for both the Piston and Turbine SCCs. Exhibit 1 is attached 

and summarizes the SCC/pollutant code/speciation profile combinations that need to be added to 

the GSREF file. The second check made was to insure that each pollutant code/speciation 

profile in the GSREF file had a match in the GSPRO file. No problems were identified as the 

result of this check. 

Spatial Profiles

We conducted a check of the MANEVU+VA 2007 area and nonroad source inventories to 

ensure that all SCCs in the inventory had a spatial surrogate match in the SMOKE spatial crossreference file. Spatial allocation profiles are not used for point sources as the point source 

inventory has geographic coordinates for each stack. The point source coordinates were 

reviewed under Work Order 2 of this contract to check the reasonableness of each release point 

relative to county centroid and minimum/maximum coordinate associated with the FIPS code 

assigned to each stack.

The spatial allocation files from the EPA distribution used in this comparison were:

 amgref_us_can_mex_revised_11mar2010_v8.txt: Spatial cross-reference for sectors other 

than othar_hg

 srgdesc_36km_revised_17mar2009_v1.txt: Surrogate code descriptions (36 or 12 km) for 

all U.S. and non-U.S. sectors other than othar_hg 

For the majority of SCCs SCC-profile matches were found. However, a list of SCCs which 

appear to be unique to MARAMA did not have associations to the EPA spatial cross-reference 

file. We have recommended spatial profile assignments based on the profiles used for similar 

SCCs. For example, the was no spatial profile for SCC 2501090050 (Petrol & Petrol Product 

Storage /Marinas : Gasoline/ Stage 1: Total). We used profile 350 (water area) for this SCC 

since it is similar to SCC 2282005010 (Pleasure Craft /Gasoline 2-Stroke /Outboard). Exhibit 2

is attached and summarizes the SCC/spatial code combinations that need to be added to the 

AMGREF file. The second check made was to insure that each spatial allocation profile in the 

AMGREF file had a match in the SRGDESC file. No problems were identified as the result of 

this check. 

Temporal Profiles

We conducted a check of the 2007 area, nonroad and point source inventories to ensure that 

appropriate matches were made to the SMOKE temporal cross-reference files available from 

EPA. The files from the EPA distribution used in this comparison were:

 amptref_v3_3_revised_13mar2009_v1.txt: Temporal cross-reference to use for the 

"regulatory" (case name 2005ck_05b) simulation

 amptpro_2005_us_can_revised_10mar2009_v0.txt: 2005-specific temporal profiles used 

for "regulatory" (case name 2005ck_05b)
 

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Several SCCs are unique to the MANEVU+VA 2007 inventory and did not have associations to 

the EPA temporal cross-reference file. We used our engineering judgment to recommend profile 

assignments based on the profiles used for similar SCCs. Exhibit 3 is attached and summarizes 

the SCC/temporal code combinations that need to be added to the AMPTREF file.

AVAILABILITY OF IMPROVED PROFILES FOR KEY CATEGORIES

We reviewed and documented the SMOKE ancillary files used for EPA’s 2005v4 modeling 

platform for several key source categories. We also investigated whether new or improved data 

were available to improve the temporal or spatial allocation of emissions for each category. 

Temporal Profiles for Agricultural Ammonia Emissions

The temporal allocation profiles for agricultural emissions in the EPA SMOKE files vary by 

State. In particular, the monthly profiles for fertilizer application show a wide variation by State. 

For example, fertilizer application in the southern part of the region (i.e., Virginia) is allocated 

primarily to the months of March, April and May. In contrast, fertilizer application in the 

northern part of the region (i.e., Maine) is allocated primarily to the months of May and June. 

See Figure 1 for a graphical representation of the temporal profiles or an example SCC. The 

temporal profiles for ammonia emissions for livestock operations do not vary by State. See 

Figure 2 for a graphical representation of the temporal profiles or an example SCC.

We contacted Mark Janssen (LADCO) to determine if updated temporal profiles were available 

from planned work with the ammonia based process model. He referred us to the Eastern

Regional Technical Advisory Committee (ERTAC) process, but to date no new work has been 

published regarding these profiles. For this reason, we consider the agricultural ammonia 

temporal profiles currently distributed in the latest EPA modeling platform as the most recent 

available for MARAMA’s use.

Temporal Profiles for Residential Wood Combustion (RWC) Emissions

The temporal allocation profiles for RWC emissions vary by county. For example, RWC 

emissions in the southern part of the region (i.e., Brunswick County, Virginia) are primarily 

allocated to the winter months. In contrast, RWC emissions in the north (i.e., Addison County, 

Vermont) are allocated more smoothly throughout the Fall, Winter, and Spring months. See 

Figure 3 for a graphical representation of the temporal profiles or an example SCC.

The current RWC profiles from EPA’s modeling platform appear to be based on a 2004 report 

generated for MARAMA by E.H. Pechan and Associates, Inc.2 This report summarizes data 

collected during the 2002 emission inventory preparation process. Should MARAMA wish to 

replace these temporal profiles, we recommend an update to the monthly distribution profiles 

using National Climatic Data Center (NCDC) heating degree day distributions for calendar year 

20073. This would allow the emissions modeling to match the meteorological conditions of the 

chosen episodes (based on a 2007 calendar year meteorological data set).

 

2

http://marama.org/visibility/ResWoodCombustion/Final_report.pdf

3

http://www.cpc.noaa.gov/products/analysis_monitoring/cdus/degree_days/
 

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Figure 1 Temporal Profiles for Agricultural Fertilizer Application

Example SCC: 28-01-700-004 Miscellaneous Area Sources; Agriculture Production -

Crops; Fertilizer Application; Urea

Similar SCCs: All SCCs in 28-01-700-xxx series

Emission Summary: 28-01-700-xxx accounts for 32,688 tons of NH3 per year, about 13% of all 

NH3 from the point, area, and nonroad sectors.

Geographic Variability? Varies by State; examples below is for Pennsylvania and Virginia

 Maine Virginia
 

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Figure 2 Temporal Profiles for Agricultural Livestock Operations

Example SCC: 28-05-009-100 Miscellaneous Area Sources; Agriculture Production -

Livestock; Poultry production - broilers; Confinement

Similar SCCs: All SCCs in 28-05-xxx-xxx series

Emission Summary: 28-05-xxx-xxx accounts for 179, 248 tons of NH3 per year, about 70% of all 

NH3 from the point, area, and nonroad sectors.

Geographic Variability? National Default
 

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Figure 3 Temporal Profiles for Residential Wood Combustion

Example SCC: 21-04-008-000 Stationary Source Fuel Combustion; Residential; Wood; 

Total: Woodstoves and Fireplaces

Similar SCCs: 21-04-008-xxx includes all Res Wood Combustion SCCs

Emission Summary: 21-04-008-xxx accounts for 73, 227 tons of PM2.5 per year, about 18% of 

all PM2.5 and 162,914 tons of VOC, about 10% of all VOC from the point, 

area, and nonroad sectors.

Geographic Variability? Monthly profile varies by county – two examples below

 Addison County, Vermont Brunswick County, Virginia
 

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Temporal Profiles for NMIM Nonroad Sources

Discussions with MARAMA modeling staff confirmed that revised monthly temporal profile 

data were not necessary for NONROAD/NMIM generated source types. Because the emissions 

for these sources were generated on a monthly basis by MACTEC, the emissions are already

provided with monthly allocation based on NONROAD/NMIM input files. We also confirmed 

that the SMOKE day of week and hour of day profiles associated with NONROAD/NMIM 

sources are allocated to most recent NONROAD model profiles available with the model. 

Figure 4 provides an example of how using the results of monthly NMIM/NONROAD model 

runs provides improved monthly temporal allocation over the use of SMOKE defaults. The 

SMOKE default for pleasure craft (SCCs 22-82-xxx-xxx) is a flat profile, i.e., emissions occur 

uniformly throughout the year. Since we are using the NMIM/NONROAD monthly profiles 

instead for the 2007 inventory, a more realistic allocation is used which assigns most of the 

annual emissions from pleasure craft to the summer months. Another example (not shown 

graphically) is for snowmobiles (SCC 22-60-001-020) and snowblowers (SCC 22-60-004-035), 

where the NMIM/NONROAD monthly profile assigns nearly all of the annual emissions to the 

three month of December, January, and February. Thus, using the monthly NMIM/NONROAD 

model results provides a significant improvement in the seasonal allocation of nonroad 

emissions. 

Spatial and Temporal Profiles for Airports

Through communication with EPA staff, we determined that the landing and take-off (LTO) data 

used to allocate county level area source airport emissions to individual airports (using the 

ARTOPNT module of SMOKE) is based on airport specific information used in the development 

of EPA’s 2005 National Emission Inventory. These LTO data were obtained from airport 

specific LTO data and Bureau of Transportation Statistics (BTS) geographic information system 

(GIS) data.

The MANE-VU+VA 2007 airport inventory was developed at the county level. We conducted a 

quality assurance review of the SMOKE ARTOPNT file to verify that county level emissions 

were properly allocated to large commercial and military airports. Commercial aircraft account 

for about 75% of the region-wide airport NOx emissions, while military aircraft account for 

about 18% of the emissions. The remaining 7% of the region-wide airport NOx emissions result 

from general aviation, air taxi, and auxiliary power units. We did not QA the spatial allocation 

of these last three categories. 

We prepared a spreadsheet to show how county level commercial aircraft emissions will be 

allocated to specific locations using the SMOKE ARTOPNT file (see: “Commercial_spatial” tab 

of Airport_Spatial_Temporal_Allocation.xlsx). The top 20 counties account for 95% of the total 

commercial aircraft NOx emissions. We verified that there is just one large airport per top 20 

county, so that the county-level emissions are being allocated to the location of the large airport. 

The only exception is Queens County, NY, where LaGuardia and JFK airports are located. The 

SMOKE ARTOPNT file allocates 60% of the commercial emissions to LaGuardia and 40% of 

the emissions to JFK. EPA’s 2008 airport inventory has 160,043 commercial LTOs for 
 

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Figure 4 Temporal Profiles for Pleasure Craft

Example SCC: 22-82-005-010 Mobile Sources; Pleasure Craft; Gasoline 2-Stroke; 

Outboard

Similar SCCs: All SCCs in 22-85-xxx-xxx series (i.e., no variation by type of railroad)

Emission Summary: 22-85-xxx-xxx accounts for 153,771 tons of VOC per year, about 10% of all 

VOC from the point, area, and nonroad sectors.

Geographic Variability? SMOKE is National Default; NMIM/NONROAD is by region

 NONROAD/NMIM Monthly Profile

 SMOKE Default Monthly Profile (Used for 2007 MANE-VU+VA)
 

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LaGuardia and 211,922 LTOs for JFK, which suggests that 43% of the commercial emissions 

should be allocated to LaGuardia and 57% of the emissions allocated to JFK. We recommend 

that these factors be used in the SMOKE ARTOPNT file for commercial aircraft (SCC 22-75-

020-000). 

We also prepared a similar spreadsheet for military airport emissions and confirmed that the 

SMOKE ARTOPNT file reasonably allocates county-level emissions to the location of the 

military airport (see: “Military_spatial” tab of Airport_Spatial_Temporal_Allocation.xlsx). 

We also visually verified that the latitude and longitude of the top 20 commercial airports and 

top 10 military airports were reasonable using an internal MACTEC project locator mapping 

system. 

The SMOKE temporal profiles for commercial aircraft operations are shown in Figure 5. We 

investigated the availability of alternative data for the temporal profiles for commercial aircraft 

operations. The BTS Airline On-Time Performance Database contains information on monthly, 

day-of-week, and hour-of-day air travel (http://www.transtats.bts.gov/DataIndex.asp ). These 

data are reported by US certified air carriers that account for at least one percent of domestic 

scheduled passenger revenues. We used these data to develop alternative temporal profiles for 

commercial aircraft operations. 

Commercial aircraft uses monthly profile 246, which appears to be a bit odd. Monthly BTS 

flight data for 2007 is shown below and are plotted alongside the SMOKE profile in Figure 5. 

The BLS data show a peak in commercial air traffic during the summer months, with secondary

peaks in March and October. We recommend that the SMOKE monthly profile for commercial 

aircraft (SCC 22-75-020-000), ground support equipment, and Auxiliary power units (22-75-

070-000) be changed to use the 2007 BLS monthly profile shown below.

BTS 

Flights

BTS 

Fraction

SMOKE 

Fraction

Jan 621,559 0.08337 0.08283

Feb 565,604 0.07586 0.08283

Mar 639,209 0.08574 0.07685

Apr 614,648 0.08244 0.07685

May 631,609 0.08472 0.07685

Jun 629,280 0.08441 0.08683

Jul 648,560 0.08699 0.08683

Aug 653,279 0.08762 0.08683

Sep 600,187 0.08050 0.08683

Oct 629,992 0.08450 0.08683

Nov 605,149 0.08117 0.08683

Dec 616,382 0.08268 0.08283

Total 7,455,458 1.0000 1.00000

Commercial aircraft uses day-of-week profile 7, which is uniformly flat. Day-of-week BTS 

flight data for 2007 is shown below and are plotted alongside the SMOKE profile in Figure 5. 

The BLS data show a decline in the number of flights on Saturday, but otherwise a relatively flat 
 

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distribution for the rest of the week. We recommend that the SMOKE monthly profile for 

commercial aircraft (SCC 22-75-020-000), ground support equipment, and Auxiliary power units 

(22-75-070-000) be changed to use the 2007 BLS day-of-week profile shown below.

BTS 

Flights

BTS 

Fraction

SMOKE 

Fraction

Mon 1,112,919 0.1493 0.1430

Tue 1,078,562 0.1447 0.1430

Wed 1,088,858 0.1460 0.1430

Thu 1,097,738 0.1472 0.1430

Fri 1,102,261 0.1478 0.1430

Sat 933,953 0.1253 0.1430

Sun 1,041,167 0.1397 0.1430

Total 7,455,458 1.0000 1.0000

Commercial aircraft uses day-of-week profile 26. Hour-of-day BTS flight data for 2007 is 

shown below and are plotted alongside the SMOKE profile in Figure 5. The BLS data show 

very few flights during the overnight hours, with small peaks around 6am and 5pm. We 

recommend that the SMOKE monthly profile for commercial aircraft (SCC 22-75-020-000), 

ground support equipment, and Auxiliary power units (22-75-070-000) be changed to use the 

2007 BLS day-of-week profile shown below.

BTS 

Flights

BTS 

Fraction

SMOKE 

Fraction

hr0 10,426 0.00140 0.01980

hr1 10,426 0.00140 0.01860

hr2 10,426 0.00140 0.01820

hr3 10,426 0.00140 0.01870

hr4 10,426 0.00140 0.02100

hr5 10,426 0.00140 0.02500

hr6 523,279 0.07019 0.03110

hr7 512,002 0.06867 0.03880

hr8 510,575 0.06848 0.04670

hr9 486,566 0.06526 0.05279

hr10 467,553 0.06271 0.05709

hr11 494,120 0.06628 0.06039

hr12 461,344 0.06188 0.06199

hr13 486,189 0.06521 0.06309

hr14 459,359 0.06161 0.06349

hr15 451,652 0.06058 0.06239

hr16 482,371 0.06470 0.05939

hr17 501,153 0.06722 0.05479

hr18 437,944 0.05874 0.05309

hr19 437,305 0.05866 0.05089

hr20 297,934 0.03996 0.04250

hr21 250,926 0.03366 0.03270

hr22 91,519 0.01228 0.02570

hr23 41,111 0.00551 0.02180

7,455,458 1.00000 1.00000
 

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Figure 5 Temporal Profiles for Commercial Aircraft Operations

Example SCC: 22-75-020-000 Mobile Sources; Aircraft; Commercial Aircraft; Total: All 

Types

Similar SCCs: Most SCCs in 22-75-xxx-xxx series; General aviation 22-75-050-xxx has a 

flat monthly profile

Emission Summary: 22-75-xxx-xxx accounts for 25,462 tons of NOx per year, about 2% of all 

NOx from the point, area, and nonroad sectors.

Geographic Variability? National Default

 SMOKE Profile 246 BTS Data for 2007

 SMOKE Profile 7 BTS Data for 2007

 SMOKE Profile 26 BTS Data for 2007
 

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Spatial and Temporal Profiles for Residual Oil Commercial Marine Vessels (CMV C3)

The following inventory files are available:

 EPA NEI 2008. EPA provided a file (2008CountySCCSummary_100429.mdb) used for 

the NEI with county level emissions for both diesel (C1/C2) and residual oil (C3) 

engines. The two SCCs used for C3 engines are: below. 

 22-80-003-100 CMV/Residual (aka Class 3)/Port Emission 

 22-80-003-200 CMV/Residual (aka Class 3)/Underway Emissions 

EPA NEI Documentation4states that the inventory includes “port and interport emissions 

that occur within the area that extends 200 nautical miles (nm) from the official U.S. 

baseline.” However, it appears that the NEI only assigns emissions to counties to reflect 

State waters (3–10 nautical miles), not the entire 200 nm area. 

 MANE-VU+VA 2007 Inventory. States reviewed the EPA inventory and either 

accepted the EPA inventory or provided their own county-level estimates. In several 

cases, the State-supplied emissions differ dramatically from the 2008 NEI and the 

differences cannot be easily explained. 

 EPA Spatially Allocated C3 Emissions (June 2010). EPA provided a file with 2007 

emissions (ptinv_eca_imo_FINAL_c3_caps_2007_21JUN2010_orl.txt) for C3 vessels in 

SMOKE Point ORL format which represents shipping lanes as a series of point sources 

with specific latitude/longitude coordinates. For example, C3 emissions within 200 nm 

of Sussex County DE are represented by 107 point sources with a total of 3,853 tons of 

SO2 and 4,162 tons of NOx. The file has annual emissions (i.e., it is not temporally

allocated). The EPA point source inventory includes only a single SCC for the C3 

marine sources (22-80-003-000 C3 All Vessel types) instead of the two SCCs used in the 

MANE-VU+VA inventory (2280003100 – C3 Port, 2280003200 – C3 Underway). There 

are no Class 1/2 SCCs in this file. It appears that the emissions out to 200 nm were 

assigned to FIPS counties. 

 EPA Spatially Allocated C3 Emissions (October 2010). As part of the Transport Rule 

Final NODA5, EPA proposed to reduce the boundaries used to allocate C3 CMV 

emissions to States from 200 nautical miles to reflect State waters (3–12 nautical miles) 

based on Mineral Management Service State federal boundary data consistent with 

approaches used for the 2005 and 2008 National Emissions Inventories. For example, C3 

emissions within 3-12 nm of Sussex County DE are represented by 5 point sources with a 

total of 1,332 tons of SO2 and 248 tons of NOx. The total C3 emissions themselves are 

virtually unchanged from the 21JUN2010 file previously provided to MARAMA, but the 

county-level emissions change because EPA restricted state FIPS assignments to within 

3-12 nm of shore. Emissions beyond the 3-12 nm boundaries are assigned to generic 

FIPS county codes. EPA provided a 2005 file but has not generated other years yet

(ptinv_eca_imo_fixFIPS_US_caps_2005_19OCT2010_orl.txt). 

 

4

http://www.epa.gov/ttn/chief/net/cmv_report4.pdf

5

http://www.gpo.gov/fdsys/pkg/FR-2010-10-27/pdf/2010-27171.pdf
 

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NOx and SO2 emissions by county for the MANEV-VU+VA region contained in these four 

inventories are summarized in the attached spreadsheet (CMV_C3_Emission_Summary.xlsx).

Given the above data availability, the simplest option for spatially allocating MANE-VU+VA 

CMV C3 emissions may be to try to adjust the October 2010 EPA C3 point source ORL file and 

replace the EPA calculated emissions with the State-supplied emissions on a county-by-county

and SCC-by-SCC basis. Since the October 2010 EPA C3 point source ORL file extends only out 

to 3-12 nm (roughly the same distance as the State supplied emissions), the point source ORL 

file emissions could be adjusted by the ratio of the State-supplied county-level emissions to the 

ORL file county-level emissions, by SCC. There will be a few special cases that would have to 

be assessed, such as when the State supplied port emissions but the ORL file does not have port 

emissions, and vice versa, which would have to be worked out. We would only be altering the 

EPA C3 point source ORL file for emissions that occur within county boundaries; emissions for 

areas outside the county boundaries (i.e., from 3 to 200 nm) would remain unchanged. We 

would need EPA to generate a 2007 file for the areas outside of the county boundaries. 

Other options exist for spatially allocating the MANE-VU+VA C3 emissions, such as using the 

approach EPA employed using the above mentioned shape files and the methods identified in the 

EPA paper6. This likely will require much more effort than the approach described in the 

previous paragraph. 

The SMOKE temporal allocation for CMV Residual Port (SCC 22-80-003-100) and CMV 

Residual Underway (22-80-003-200) emissions are flat on a monthly, day of week and hour of 

day. However, the monthly profile for CMV/Residual/All Vessel Types (SCC 22-80-003-000) 

show a seasonal variation, as depicted in Figure 6. The monthly profile (#19531) used for SCC 

22-80-003-000 appears to be the same as that used by EPA in their C3 inventory. EPA explained 

the summer peak possibly being due to the setup for production for peak holiday season 

consumerism beginning in the fall. We recommend that monthly profile 19531 also be used for 

SCCs 22-80-003-100 (CMV/Residual/Port) and 22-80-003-200 (CMV/Residual/Underway) 

which are used in the MANE-VU+VA 2007 inventory.

Spatial and Temporal Profiles for C1/C2 Diesel Commercial Marine Vessels Activities

The section discusses the following two SCCs:

 22-80-002-100 CMV/Diesel (aka Class I/II)/Port Emissions 

 22-80-002-200 CMV/Diesel (aka Class I/II)/Underway Emissions 

(Category 1 and 2 vessels tend to be smaller ships that operate closer to shore, and along inland 

and intercoastal waterways.)

The SMOKE spatial allocation files for assigning county diesel CMV emissions to grid cells are 

as follows:

 22-80-002-100 CMV/Diesel/Port uses profile 800 (Marine Ports)

 22-80-002-200 CMV/Diesel/Underway uses profile 810 (Navigable Waterway Activity)

 

6

(http://www.epa.gov/ttn/chief/conference/ei17/session6/mason.pdf
 

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Figure 3 Temporal Profiles for CMV Residual (Class 3)

SCC = 22-80-003-000 Monthly Profile 19531

Mobile Sources; Marine Vessels, Commercial; Residual; Total, All Vessel Types

SCC = 22-80-003-100 Monthly Profile 262

Mobile Sources; Marine Vessels, Commercial; Residual; Port Emissions

SCC = 22-80-003-200 Profile Monthly Profile 262

Mobile Sources; Marine Vessels, Commercial; Residual; Underway Emissions
 

15

EPA has posted port and CMV shipping lane shape files on their ftp site7; port_032310.zip and 

shipping_lanes_111309.zip). In this EPA effort, spatial accuracy was greatly enhanced via the 

creation of GIS polygons representing port and waterway boundaries. GIS polygons allowed the 

estimation/allocation of emissions to defined port, waterway, and coastal areas, leading to 

improved spatial resolution compared to previous inventories. The shape files are documented in 

Documentation for the Commercial Marine Vessel Component of the National Emissions 

Inventory8as follows:

 For port emissions, GIS data or maps provided directly from the port were used. Next, 

maps or port descriptions from local port authorities, port districts, etc. were used in 

combination with existing GIS data to identify port boundaries. Finally, satellite imagery

from tools such as Google Earth and street layers from StreetMap USA were used to 

delineate port areas. Emphasis was placed on mapping the 117 ports with Category 3 

vessel activity using available shape files of the port area. Each polygon was identified by 

the port name and state and county FIPS in addition to a unique ShapeID. Smaller ports 

with Category 1 and 2 activities were mapped as small circles. 

 For underway emissions, a GIS polygon layer was created to more accurately represent 

the location of CMV-related activity and emissions. Inland waterway polygons were 

obtained from the Bureau of Transportation Statistics’ National Transportation Atlas 

Database hydro polygon layer (U.S. DOT, 2007). These polygons were further divided 

by county boundary and waterway ID. Coastal waters were drawn using Mineral 

Management Service state-federal boundary files and were also divided to indicate 

county boundaries. Federal waters were included as large area blocks outlined by the 

Exclusive Economic Zone (EEZ) boundary provided by EPA, which extends to 

approximately 200 nautical miles from the coastline. The final product is a polygon layer 

that includes all inland and coastal state waters and federal waters along with FIP, 

polygon area, and a unique ShapeID. 

EPA provided the shapefiles for input into the Spatial Surrogate Tool, which is stand-alone tool 

for generating spatial surrogates that are inputs to emission models such as SMOKE. This tool 

allows users to generate, merge or gapfill surrogate ratios for a user-specified grid, regardless of 

the type of operating system used and without needing third-party software.

Figure 7 shows the SMOKE temporal allocation for CMV Diesel Port emissions. The SMOKE 

profiles for CMV Diesel Underway is the same. Both are flat on a monthly, day of week, hour of 

day basis. We conducted a search of the Bureau of Transportation Statistics for information to 

develop improved temporal profiles for C1/C2 CMV, but could not locate any useful data. 

 

7

ftp://ftp.epa.gov/EmisInventory/2008_nei/mobile/rail_cmv_shapefiles

8

http://www.epa.gov/ttn/chief/net/cmv_report4.pdf 
 

16

Figure 7 Temporal Profiles for CMV Diesel (Class 1 and 2)

Example SCC: 22-80-002-100 Mobile Sources; Marine Vessels, Commercial; Diesel; Port 

emissions

Similar SCCs: 22-80-002-200 Mobile Sources; Marine Vessels, Commercial; Diesel; 

Underway emissions

Geographic Variability? National Default
 

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Spatial and Temporal Profiles for Railroads

The SMOKE spatial allocation files for assigning county level rail emissions to grid cells are as 

follows:

 22-85-002-006 Class I Ops uses profile 270 (Class I Railroad Miles)

 22-85-002-007 Class II/III Ops uses profile 280 (Class II/III Railroad Miles)

 22-85-002-008 AMTRAK uses profile 260 (Total Railroad Miles)

 22-85-002-009 Commuter Rail uses profile 260 (Total Railroad Miles)

 22-85-002-010 Rail Yards uses profile 260 (Total Railroad Miles)

New York State plotted the spatial distribution of gridding surrogates 260, 270 and 280 (see: 

map_railroad_gridding.PDF). The first three maps shows the total amount of this "feature" (total 

railroad miles for 260, class 1 railroad miles for 270, class II/III railroad miles for 280) for each

grid cell in our domain. Grid cells containing more than one county show the sum of this feature 

across all intersecting counties. This is for illustration only, for the actual gridding of countylevel emissions SMOKE will use the gridding ratios (i.e. the amount of a "feature" in a given 

grid cell in a county to the sum of this "feature" across all grid cells in the county). This is 

illustrated on pages 4-6 for Aroostook County, ME, a separate map would have to be generated 

for each county to QA the gridding ratios. Note that for this county, surrogates 260, 270 and 280 

all have the same weights. This may mean that the underlying shapefile did not distinguish 

between the different railroad classes in ME. This also seems to be the case for NH and VT. 

ERTAC did not investigate spatial profiles when preparing the rail inventory for line haul or 

passenger rail. However, ERTAC did estimate rail yard locomotives (SCC 22-85-002-010) 

emissions at specific yard locations. The specific ERTAC yard locations could be used rather 

than the entire track route mileage in a county to spatially allocate county level rail year 

emissions. However, there are several problems with this approach. First, only three States used 

the ERTAC rail yard emission estimates in the MANE-VU+VA 2007 inventory (NY, PA, VA). 

Four States (CT, DE, ME, RI) provided state-supplied rail yard emission estimates but do not 

have any specific rail yard locations in the ERTAC database. Three States (DC, MA, MD) 

provided state-supplied rail yard emission estimates and do have specific rail yard locations in 

the ERTAC database. Finally, three States (NH, NJ, VT) did not supply rail yard emissions for 

the MANE-VU+VA 2007 inventory and do not have specific rail yards in the ERTAC database. 

This information is summarized in Exhibit 4. Detailed summaries are contained in a spreadsheet 

(Railyards MANEVU ERTAC.xlsx)

Because of the types of data available varies by State, different spatial allocation schemes would 

be necessary for different States as shown in the following table. We do not think it is worth the 

time and effort to implement the three different approaches for spatially allocating rail yard 

emissions. Rail yard NOx emissions amount to 6,414 tons, only about 8% of all railroad 

equipment NOx emissions in the region, and only about 0.5% of all NOx emissions from point, 

area, and nonroad sources. Because of the small amount of emissions from rail yards, improving 

the spatial allocation would likely not have any significant impact on regional air quality model 

performance. 
 

18

Exhibit 4 - Data Availability for 2285002010 Yard Locomotives

State

Data Source for 

MANE-VU+VA

Inventory

Railyard 

Specific 

Emissions in 

ERTAC?

Option for Spatial Allocation 

CT State Supplied No Allocate county level emissions using 

SMOKE profile 260 (total railroad miles)

DE State Supplied No Allocate county level emissions using 

SMOKE profile 260 (total railroad miles)

DC State Supplied Yes

Apportion State-supplied county-level 

emissions to specific ERTAC railyards; 

Prepare Point ORL file using specific lat/lon 

and emissions for each ERTAC rail yard

Zero out emissions in Area ORL file

ME State Supplied No Allocate county level emissions using 

SMOKE profile 260 (total railroad miles)

MD State Supplied Yes

Apportion State-supplied county-level 

emissions to specific ERTAC railyards; 

Prepare Point ORL file using specific lat/lon 

and emissions for each ERTAC rail yard

Zero out emissions in Area ORL file

MA State Supplied Yes

Apportion State-supplied county-level 

emissions to specific ERTAC railyards; 

Prepare Point ORL file using specific lat/lon 

and emissions for each ERTAC rail yard

Zero out emissions in Area ORL file

NH n/a No None required

NJ n/a No None required

NY EPA ERTAC Yes

Prepare Point ORL file using specific lat/lon 

and emissions for each ERTAC rail yard

Zero out emissions in Area ORL file

PA EPA ERTAC Yes

Prepare Point ORL file using specific lat/lon 

and emissions for each ERTAC rail yard

Zero out emissions in Area ORL file

RI State Supplied No Allocate county level emissions using 

SMOKE profile 260 (total railroad miles)

VT n/a No None required

VA EPA ERTAC Yes

Prepare Point ORL file using specific lat/lon 

and emissions for each ERTAC rail yard

Zero out emissions in Area ORL file

EPA has posted rail line shape files on their ftp site9Since there is no documentation associated 

with these files, it is not clear how these shape files differ from the SMOKE ready gridded 

surrogate ratio files discussed above. EPA provided the shapefiles for input into the Spatial 

Surrogate Tool10, which is stand-alone tool for generating spatial surrogates that are inputs to 

emission models such as SMOKE. This tool allows users to generate, merge or gapfill surrogate 

ratios for a user-specified grid, regardless of the type of operating system used and without 

needing third-party software.

 

9

(ftp://ftp.epa.gov/EmisInventory/2008_nei/mobile/rail_cmv_shapefiles ). 

10 http://www.ie.unc.edu/cempd/projects/mims/spatial
 

19

Figure 8 shows the SMOKE temporal allocation profiles for Rail. The profiles are all flat –

monthly, day of week, hour of day. These profiles may be appropriate for Class I and Class II/III 

line haul locomotives, but it is reasonable to assume that AMTRAK and Commuter trains would 

have a different Weekday/Weekend and Hour-of-Day profile to reflect when most 

AMTRAK/commuter trains are operating in the NE corridor. ERTAC did not investigate 

temporal profiles when preparing the rail inventory. We conducted a search of the Bureau of 

Transportation Statistics for information to develop improved temporal profiles for rail, but 

could not locate any useful data. We recommend as a future research effort that MARAMA 

investigate the temporal profiles for AMTRAK/commuter trains, which are likely to vary for 

each commuter line.

Spatial and Temporal Profiles for Lightering Operations 

Two States – Delaware and New York - reported emissions from lightering operations. No other 

State has significant lightering operations and no other State reported emissions.

 Delaware included VOC emissions from lightering operations in the point source 

inventory using SCC 40600248. The Delaware lightering operation emitted 1,564 tons of 

VOC in 2007. The operation is geographically located at a specific latitude and longitude 

off of the coast of Sussex County. The SMOKE temporal profile for SCC 40600248 is 

shown in Figure 9. In the NIF EP table, Delaware reported a flat quarterly profile for this 

source, with activity occurring 24 hours per day, 7 days per week, 52 weeks per year.

 New York included VOC emissions from lightering operations in the CMV inventory

using SCC 22-80-002-000. The New York lightering operations emitted 938 tons of 

VOC in 2007 and occurred in Nassau, Queens, Richmond, and Suffolk counties. These 

county level emissions will be allocated to grid cells using SMOKE spatial profile 800 –

Marine Ports. The SMOKE temporal profile for SCC 22-80-002-000 is flat for all time 

periods – monthly, day of week, and hour of day. 

The spatial and temporal allocation profiles above appear to be reasonable, and we do not 

recommend any changes. 

GRAPHICAL REPRESENTATIONS OF SMOKE TEMPORAL PROFILES

We prepared an Excel workbook (amptref.xls) which allows MARAMA States to select and 

review the temporal profiles by SCC and for specific FIPS-SCC combinations from the SMOKE 

temporal profile cross-reference table. In this workbook, once the FIPS-SCC combination is 

selected, the associated temporal profile (and relative distribution values) for month of year, day

of week and hour of day are presented in tabular and graphical format. This will facilitate State 

review of the temporal allocation of emission for every SCC and FIPS-SCC combination. 

As shown in Figures 10-12, we examined the temporal profiles for three key VOC categories –

architectural coatings, consumer products, and portable fuel containers. The profiles appear to 

be reasonable. Since different States used different SCCs for consumer products, the monthly

profiles for consumer products vary by State. MARAMA states should review these monthly

profiles and either change the SCC used or adjust the SMOKE monthly temporal profiles for 

consistency.
 

20

Figure 8 Temporal Profiles for Railroad Equipment

Example SCC: 22-85-002-006 Mobile Sources; Railroad Equipment; Diesel; Line Haul 

Locomotives: Class I Operations

Similar SCCs: All SCCs in 22-85-xxx-xxx series (i.e., no variation by type of railroad)

Emission Summary: 22-85-xxx-xxx accounts for 81,546 tons of NOx per year, about 6% of all 

NOx from the point, area, and nonroad sectors.

Geographic Variability? National Default
 

21

Figure 9 Temporal Profiles for Delaware Lightering Operation

Example SCC: 4-06-002-48 Petroleum and Solvent Evaporation; Transportation and 

Marketing of Petroleum Products; Marine Vessels; Crude Oil: Loading 

Barges

Similar SCCs: None, the Delaware operation is the only source in the inventory that uses 

this SCC

Emission Summary: This source accounts for 1,564 tons of VOC in 2007

Geographic Variability? National Default
 

22

Figure 10 Temporal Profiles for Architectural Coatings

Example SCC: 24-01-001-000 Solvent Utilization; Surface Coating; Architectural Coatings; 

Total: All Solvent Types

Similar SCCs: 24-01-002-000 (solvent based AIM) and 24-01-003-000 (water-based AIM)

Emission Summary: These three SCCs account for 85,000 tons of VOC per year, about 5% of all 

VOC from the point, area, and nonroad sectors.

Geographic Variability? National Default
 

23

Figure 11 Temporal Profiles for Consumer Products

Example SCCs: 24-60-000-000 Consumer Products, all categories

24-60-xxx-000 Consumer Products; each category has a separate SCC

24-65-000-000 Consumer Products, all categories

Similar SCCs: Some States group all consumer products into a single SCC; other States 

itemize the 7 different types of products; the SMOKE monthly profiles vary 

depending on the SCC used 

Emission Summary: The three SCC groupings above account for 299,578 tons of VOC per year, 

about 19% of all VOC from the point, area, and nonroad sectors.

Geographic Variability? National Default

Monthly Profile for 24-60-000-000 (used by MA, NH, NJ)

Monthly Profile for 24-60-100-000, 24-60-200-000, etc.

(used by CT, DE, DC, ME, MD, PA, RI, VT, VA)

Monthly Profile for 24-65-000-000 (used by NY)
 

24

Day of Week Profile is the same for all Consumer Product SCCs

Hour of Day Profile is the same for all Consumer Product SCCs
 

25

Figure 12 Temporal Profiles for Portable Fuel Containers

Example SCC: 25-01-011-012 Residential Portable Gas Cans/Evaporation 

Similar SCCs: 25-01-011-xxx (Residential) and 25-01-012-xxx (commercial))

Emission Summary: These three SCCs account for 37,674 tons of VOC per year, about 2% of all 

VOC from the point, area, and nonroad sectors.

Geographic Variability? National Default
 

26

RECOMMENDATIONS

1. The GSREF file should be updated to include the missing SCC/pollutant code/speciation 

profile combinations identified in Exhibit 1.

2. The AMGREF file should be updated to include the missing SCC/spatial profile 

combinations identified in Exhibit 2.

3. The AMPTREF file should be updated to include the missing SCC/temporal profile 

combinations identified in Exhibit 3.

4. MARAMA should monitor the work of ERTAC and/or EPA in determining whether any 

improvements to temporal allocation of agricultural ammonia emissions have been made. 

5. MARAMA should further investigate whether to replace the current temporal profiles for 

residential fuel consumption (based on 2002 heating degree days) with profiles based on 

the heating degree day distributions for calendar year 2007. This would allow the 

emissions modeling to match the 2007 calendar year meteorological data set being used 

for air quality modeling.

6. The temporal profiles for commercial airport operations should be updated using the BTS 

Airline On-Time Performance Database, which contains 2007-specific information on 

monthly, day-of-week, and hour-of-day air travel. 

7. MARAMA should further investigate options for spatially allocating MANE-VU+VA 

CMV C3 emissions, perhaps by adjusting the October 2010 EPA C3 point source ORL 

file and replacing the EPA calculated emissions with the State-supplied emissions on a 

county-by-county and SCC-by-SCC basis. 

8. MARAMA should further investigate the temporal profiles for AMTRAK/commuter 

trains, which are likely to vary for each line.

9. Since different States used different SCCs for consumer products, the monthly profiles 

for consumer products vary by State. MARAMA states should review these monthly

profiles and either change the SCC used or adjust the SMOKE monthly temporal profiles 

for consistency.

ATTACHMENTS

Exhibit 1 Speciation Unmatched SCCs.xlsx

Exhibit 2 Spatial Unmatched SCCs.xlsx

Exhibit 3 Temporal Unmatched SCCs.xlsx

Airport_Spatial_Temporal_Allocation.xlsx

CMV_C3_Emission_Summary.xlsx

Railyards MANEVU ERTAC.xlsx

Map_railroad_gridding.PDF

amptref.xls