1

**TECHNICAL MEMORANDUM** To: Julie McDill , MARAMA From: Gregory

Stella, Alpine Geophy sics, LL C Edward Sabo, MACTEC Engineering and Consulting, Inc. Date: 17 December 2010 Re: MARAMA Work Order #9; SMOKE Auxiliary File Revie w **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 website 1 relevant 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 i nventory 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 2**  **007 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 majorit y 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 appropriat e matches within the EPA distributed tables . W e have recommend ed 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 re adme_2005v2cap_bafm_haps_anicllary_inputs.txt, dated 07/08/20102

Aviation/Piston) and 2275050012 (Aircraft/General Aviation/Turbine ) are subsets of the more general SCC 2275050000 (Aircraft/General Aviation, All Ty pes). 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 pro file 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. **Spatia l**  **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 cross reference 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 count y centroid and minimum/maxi mum 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 cr oss - reference for sectors other than othar_hg  s rgdesc_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 majorit y 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 /Mari nas : 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 add ed 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)3

S everal 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. Ex hibit 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 i nvestigated 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 th e EPA SMOKE files vary b y 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 o f March, April and May . In contrast, fertilizer application in the northern part of the region (i.e., Maine) is allocated primarily to the month s of May

and June. See Figure 1 for a graphical representation of the temporal profiles or an example SCC . Th e 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. W e contacted Mark Janssen (LADCO) to determine if updated temporal profiles w ere 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 th e agricultural ammonia temporal profiles currently distributed in the latest EPA modeling platform a s the most recent available for MARAMA’s use. **Temporal Profiles for Residential Wood Combustion (RWC)**  **Emissions** The temporal allocation profiles for RWC e missions vary by count y. For example, RWC emissions in the southern part of the region (i.e., Brunswick County , Virginia) are primaril y 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 u sing National Climatic Data Center (NCDC) heating degree day distributions for calendar y ear 2007 3 . This would allow the emissions modeling to match the meteorological conditions of the chosen episodes (based on a 2007 calendar ye ar meteorological data set). 2 http://marama.org/visibility/ResWoodCombustion/Final_report.pdf 3 http://www.cpc.noaa.gov/products/analysis_monitoring/cdus/degree_days/4 **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:** 2 8 - 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; example s below is for Penns yl vania and Virginia

**Maine Virginia** 5 **Figure 2**  **Temporal Profiles for Agricultural Livestock Operations**  **Example SCC:** 28 - 05 - 009 - 100 Miscellaneous Area Sources; Agricu lture 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 sec tors. **Geographic Variability?** National Default6 **Figure 3**  **Temporal Profiles for Residential Wood Combustion**  **Example SCC:** 21 - 04 - 008 - 000 Stationary Source Fuel Comb ustion; Residential; Wo od;

Total: Wo odstoves and Fireplaces **Similar SCCs:** 21 - 04 - 008 - xxx includes all Res Wo od 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, abo ut 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**7

**Temporal Profiles for NMIM Nonroad Sources** Discussions with MARAMA modeling staff confirmed that revised monthly temporal profile data were not necessary

for NONROAD/NM IM generated source ty pes. 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 NON ROAD/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 NM IM /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 y ear. Since we are using the NM IM/NONROAD monthly profiles instead for the 2007 inventory , a more realistic allocation i s used which assigns most of the annual emissions from pleasure craft to the summer months. Another example (not shown graphicall y) is for snowmobiles (SCC 22 - 60 - 001 - 020) and snowblowers (SCC 22 - 60 - 004 - 035), where the NMIM/NONROAD monthly profile assigns nearl y 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**  **Profil es for**  **Airports** Through communication with EPA staff, we determined that the landing and take - off (LTO) data used to allocate count y level area source airport emissions to individual airports (using the ARTOPNT module of SMOKE) is based on airport specifi c information used in the development of EPA’s 2005 National Emission Inventory . These L TO data were obtained from airport specific LTO data and Bureau of Transportation Statistics (BTS) geographic information sy stem (GI S) data. The MANE - VU+VA 2007 airpo rt inventory was developed at the count y level. We conducted a quality assurance review of the SMOKE ARTOPNT file to verify that county

level emissions were properl y allocated to large commercial and military airports. Commercial aircraft account for abo ut 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 th e spatial allocation of these last three categories. We prepared a spreadsheet to show how count y 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 for8 **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) **Emiss ion 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)9

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 reasonabl y allocates county - level emissions to the location of the military airport (see: “Mili tary

_spatial” tab of Airport_Spatial_Temporal_Allocation.xlsx). We also visually

verified that the latitude and longitude of the top 20 commer c ial airports and top 10 military

airports were reasonable using an internal MACTEC project locator mapping sy st em. 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 c ontains information on monthly , day - of - week, and hour - of

- day air travel ( http://www.transtats.bts.gov/DataIndex.asp ). These data are reported b y US certified air carriers that account for at leas t 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 d ata 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 SM**  **OKE**

**Fraction** Jan 621,559 0.08337 0.08283 Fe b 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 relativel y flat10

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 Fligh**  **ts BTS** 

**Fraction SM**  **OKE**

**Fraction** Mon 1,112,919 0.1493 0.1430 Tue 1,078,562 0.1447 0.1430 We d 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 BL S day - of

- week profile shown below. **BTS Fl**  **ights BTS** 

**Fraction SM**  **OKE**

**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 482,37 1 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**11 **Figure 5**  **Temporal Profiles for Commercial Aircraft Operations**  **Example SCC:** 22 - 75 - 020 - 000 Mobile Sources; Aircraft; Commercial Aircraft; Total: All

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

flat monthly p rofile **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** 12

**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 ( 2008County SCCSummary _100429.mdb ) used for the NEI with count y 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 Emis sions EPA NEI Documentation4 states that the inventory include s “ 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 onl y 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 provide d their own county - level estimates . In several cases, the Stat e - 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 ORLformat 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 b y 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 ty pes) instead of the two S CCs used in the MANE - VU+VA inventory ( 2280003100

– C3 Port , 2280003200

– C3 Underway). There are no Class 1/2 SCCs in this file . Itappears that the emissions out to 200 nm were assigned to FIPS counties .  **EPA Spatially Allocated C3 Emissions (October 2**  **010)** . As part of the Transport Rule Final NODA 5 , EPA propose d to reduce the boundaries used to allocate C3 CMV emissions to States from 200 nautical miles to reflect State waters (3

– 1 2 nautical miles) based on Mineral Management Service State federal boun dary 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 tot al 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 boundari es are assigned to generic FIPS county

codes. EPA provided a 2005 file but has not generated other years y et (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.pdf13

NOx and SO2 emissions by count y for the MANEV - VU+VA region contained in these four invent ories 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 f ile and replace the EPA calculated emissions with the State - supplied emissions on a count y - 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 emi ssions), the point source ORL file emissions could be adjusted by the ratio of the State - supplied count y - level emissions to the ORLfile 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 ORLfile 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 count y boundaries; emissions for areas outside the count y 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 u sing the approach EPA employ ed using the above mentioned shape files and the methods identified in the EPA paper 6 . This likely

will require much more effort than the approach described in the previous paragraph. The SMOKE temporal allocation for CMV Re sidual 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 Ty pes (SCC 22 - 80 - 003 - 000) show a seasonal variation, as depict ed 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 beg inning 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/I I)/Port Emissions  22 - 80 - 002 - 200 CMV/Diesel (aka Class I/I I)/Underway Emissions ( Category 1 and 2 vessels tend to be smaller ship s 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 - 0 02 - 200 CMV/Diesel/Underway uses profile 810 (Navigable Waterway Activity)

6 ( http://www.epa.gov/ttn/chief/conference/ei17/session6/mason.pdf14 **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 Ty pes

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; Re sidual; Underway Emissions15

EPA has posted port and CMV shipping lane shape files on their ftp site 7 ; port_032310.zip and shipping_lanes_111309.zip). Inthis 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 Inventory 8 as follows:  For port emissions, GIS data or maps provided directl y from the port were used. Next, maps or port descriptions from local port auth orities, port districts, etc. were used in combination with existing GI S data to identify port boundaries. Finally , satellite imagery from tools such as Google Earth and street lay ers from StreetMap USA were used to delineate port areas. Emphasis was pla ced on mapping the 117 ports with Category 3 vessel activity

using available shape files of the port area. Each pol ygon was identified b y the port name and state and county FIPS in addition to a unique ShapeID. Smaller ports with Category

1 and 2 activiti es were mapped as small circles.  For underway

emissions, a GIS polygon lay er was created to more accurately represent the location of CMV - related activity and emissions. In land waterway pol ygons were obtained from the Bureau of Transportation Statistics ’ National Transportation Atlas Database h ydro pol ygon layer (U.S. DOT, 2007). These pol ygons were further divided by count y boundary

and waterway

I D. Coastal waters were drawn using Mineral Management Service state - federal boundary files and were also d ivided 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 p olygon lay er 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 s urrogates 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 ty pe of operating s ys tem 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.pdf16 **Figure 7**  **Temporal Profiles for CMV Diesel (Class 1 and 2)**  **Example SCC:** 22 - 80 - 002 - 100 Mobile Sources; Marine Vessels, Commercial; Diesel; Port

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

Underway emissions **Geographic Variability?** National Default17

**Spatial and Tempo**  **ral 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 IRailroad Miles)  22 - 85 - 002 - 007 Class II/III Ops uses profile 280 (Clas s 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 di stribution 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 county level emissions SMOKE will use the gridding ratios ( i.e. the amount of a "feature" in a given grid cell in a count y 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 count y to QA the gridding ratios. Note that for this county , surrogates 260, 270 and 280 all have the same weights . T his may mean that the underl yi ng shapefile did n o t 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 count y l evel rail ye ar emissions. However, there are several problems with this approach. First, only three States used the ERTAC rail y ard emission estimates in the MANE - VU+VA 2007 inventory (NY, PA, VA). Four States (CT, DE, ME, RI ) provided state - supplied rail y ard emission estimates but do not have an y specific rail yard locations in the ERTAC database. Three States (DC, MA, MD) provided state - supplied rail y ard emission estimates and do have specific rail yard locations in the ERTAC database. Finally , three States (NH, NJ, VT) did not supply rail y ard 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 ( Raily ards MANEVU ERTAC .xlsx ) Because of the ty

pes of data available varies by State, different spatial allocation schemes would be necessary

for different States a s shown in the following table. We do not think it is worth the time and effort to implement the three different approaches for spatiall y al locating rail y ard emissions. Rail y ard NOx emissions amount to 6,414 tons, only about 8% of all railroad equipment NOx emissions in the region, and onl y about 0.5% of all NOx emissions from point, area, and nonroad sources. Because of the small amount of emissions from rail y ards, improving the spatial allocation would likely not have any

significant impact on regio nal air quality model performance.18 **Exhibit 4 -**  **Data A**

**vailability for 2285002010**  **Yard Locomotives State**  **Data Source for**

**MA NE**  **- VU+VA**  **Inventory Railyard** 

**Specific Emissions in**  **ERT AC?**  **Option for Spatial A llocation**  CT State Supplied No Allocate county level em issions 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 em issions to specific ERTAC railyard s; 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 Apporti on State - supplied county - level em issions 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 em i ssions 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 s pecific 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 Allo cate 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 site 9 Since there is no documentation associated with these files, it is not clear how these shape files differ from the SMOKE read y gridded surrogate ratio files discussed above. EPA provided the shapefiles for input into the Spatial Surrogate Tool 10 , 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 ty pe of operating s ys tem used and without needing third - part y software.

9 ( ftp://ftp.epa.gov/EmisInventory/2008_nei/mobile/rail_cmv_s hapefiles ). 10 http://www.ie.unc.edu/cempd/projects/mims/spatial19

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 Iand Cla ss 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 inve stigate 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 an y useful data. We recommend as a future r esearch 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 fro m 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 oper ation emitted 1,564 tons of VOC in 2007. The operation is geographicall y 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 repo rted a flat quarterl y profile for this source, with activity

occurring 24 hours per day , 7 day s per week, 52 weeks per y ear.  New York included VOC emissions from lightering operations in the CMV inventory using SCC 22 - 80 - 002 - 000. The New York lightering o perations 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 - 8 0 - 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 an y changes. **GRAPHICAL REPRESENTATIONS OF SMOKE TEMPORAL PROFILES**  We p repared 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 combinati on 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 ev ery 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) **E mission 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 Default21 **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 Default22 **Figure 10**  **Temporal Profiles for Architectural Coatings**  **Example SCC:** 24 - 01 - 001 - 000 Solvent Utilization; Surface Coating; Architectural Coatings;

Total: All Solvent T yp es **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 Default23 **Figure 11**  **Temporal Profiles for Consumer Products**  **Example SCC s**  **:** 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, a ll categories **Similar SCCs:** Som e States group all consumer products into a single SCC; other States

item iz e the 7 different types of products; the SMOKE monthly profiles var y depending on the SCC used **Emission Summary:** The three SCC groupings above acco unt 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 -**  **1 00**  **- 000, 24**  **- 60**  **- 200**  **- 000,**  **etc. (used by CT, DE, DC, ME, MD, PA, RI, VT, VA)** 

**Monthly Profile for 24 -**  **6 5**  **- 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 Default26

**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 update d to include the missing SCC/sp atial 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 de termining whether an y 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 day s) with profiles based on the heating degree day

distributions for calendar year 2007. This would allow the emissions modeling to match the 2007 calendar ye ar meteorological data set being used for air qualit y modeling. 6. The temporal profiles for commerc ial 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 - count y 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 pr ofiles 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_Tempo ral_Allocation.xlsx CMV_C3_Emission_Summary .xlsx Raily ards MANEVU ERTAC.xlsx M ap_railroad_gridding.PDF amptref.xls