# Appendix A

2008 Base Year Annual Carbon Monoxide (CO) Emissions Inventory For St. Louis County and St. Louis City

Missouri Department of Natural Resources Division of Environmental Quality Air Pollution Control Program Jefferson City, Missouri

Adoption March 27, 2014

Project Number: 1971-CO-5

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### Page 3 

## Table of Contents

TABLE OF CONTENTS 2

LIST OF APPENDICES 5

LIST OF TABLES 6

1.0 INTRODUCTION 7

1.1 P URPOSE 

### 7

1.2 I NVENTORY 

### C OVERAGE 

### 7

1.2.1 G EOGRAPHY 

### 7

1.2.2 E MISSION 

### Y EAR 

### 7

1.2.3 P OLLUTANTS 

### 7

1.3 C ONTENTS OF 

### R EPORT 

### 7

1.4 A UTOMATED 

### S YSTEMS 

### U SED 

### 8

1.5 I NVENTORY 

### E XCLUSIONS 

### 8

1.6 G UIDANCE AND 

### R EFERENCE 

### D OCUMENTS 

### 8

1.7 L IST OF 

### C ONTACTS 

### 9

2.0 EMISSIONS SUMMARY 9

2.1 S UMMARY BY 

### C OUNTY AND 

### C ATEGORY 

### 9

3.0 INVENTORY DOCUMENTATION 10

3.1 P OINT 

### S OURCE 

### E MISSIONS 

### 10

3.1.1 P ROCEDURES AND 

### M ETHODOLOGIES 

### 10

3.1.2 E MISSION 

### I NVENTORY 

### Q UESTIONNAIRE 

### (EIQ) 10

3.1.3 L IST OF 

### F ACILITIES AND 

### E MISSIONS 

### 13

3.2 N ONPOINT 

### S OURCE 

### E MISSIONS 

### 22

3.2.1 P ROCEDURES AND 

### M ETHODOLOGIES 

### 22

3.2.2 L IST OF 

### S OURCE 

### C ATEGORIES AND 

### E MISSIONS 

### 22

3.2.3 S OURCE 

### C ATEGORY 

### D OCUMENTATION 

### 40

3.2.3.1 Fossil Fuel Combustion – Residential – Coal Combustion 40

3.2.3.2 Fossil Fuel Combustion – Residential – Distillate Oil 44

3.2.3.3 Fossil Fuel Combustion – Residential - Kerosene 46

3.2.3.4 Fossil Fuel Combustion – Residential – Natural Gas 49 3.2.3.5 Commercial Cooking 52 3.2.3.6 Open Burning – Land Clearing Debris 53 3.2.3.7 Open Burning – Residential Household Waste 58 3.2.3.8 Open Burning – Yard Waste – Leaf and Brush Species 61

3.2.3.9 Fuel Combustion – Industria l and Commercial/Institutional (ICI) 64 3.2.3.10 Fossil Fuel Combustion – Residential – Liquefied Petroleum Gas (LPG) 66

3.2.3.11 Fuel Combustion – Residential- Wood 68

3.2.4 N ONPOINT 

### S OURCE 

### E MISSION 

### S UMMARY 

### 68

### Page 4 3.3 M OBILE 

### S OURCE 

### E MISSIONS 

### 69

3.3.1 N ONROAD 

### M OBILE 

### S OURCES 

### 69 3.3.1.1 Procedures and Methodologies 69 3.3.1.2 List of Source Categories and Emissions 69 3.3.1.3 Source Category Documentation 70 3.3.1.4 Nonroad Source Emission Summary 70

3.3.2 O NROAD 

### M OBILE 

### S OURCES 

### 70

3.3.2.1 Mobile Model Choice 70 3.3.2.2 Mobile Model Inputs 71 3.3.2.3 On Road Source Emissions Summary 84

4.0 QUALITY ASSURANCE/QUALITY CONTROL 84

4.1 P OINT 

### S OURCE 

### QA/QC AND 

### R ESULTS 

### 84

4.2 N ONPOINT 

### S OURCE 

### QA/QC 86

4.3 M OBILE 

### S OURCE 

### QA/QC 87

4.3.1 N ONROAD 

### S OURCE 

### QA/QC 87

4.3.2 O NROAD 

### S OURCE 

### QA/QC 87

### Page 5 LIST OF APPENDICES

Appendix A-1: List of Statewide Point Source Emissions by Facility

Appendix A-2: List of On Road Emi ssions by SCC for St. Louis County and St. Louis City

Appendix A-3: Nonroad 2008 Category Documentation

Appendix A-4: List of St. Louis County and St. Louis City Nonroad Emissions by

SCC

Appendix A-5: Nonpoint Industrial and Commercial/Institutional (ICI) Fuel

Combustion Documentation

Appendix A-6: Inspection/Maintenance I nput Table Development Protocol for

MOVES for Counties in the St. L ouis Ozone Nonattainment Area

### Page 6 LIST OF TABLES

Table 1 Total 2008 CO Emissions for St. Louis City and St. Louis County (tons per year) _____________ 9 Table 2 List of EIQ Forms _____________________________________________________________ 10 Table 3 St. Louis County and City 2008 Point Sources by NAICS _______________________________ 13 Table 4 St. Louis County and City 2008 Point Source CO Emission s by Facility (tons per year) _______ 16

Table 5 Statewide Point Source Emissions by Category (t ons per year) __________________________ 19

Table 6 Statewide Point Emissions by County (tons per year) __________________________________ 20 Table 7 Nonpoint 2008 Emission Records for St. Louis County and City (tons per year) _____________ 23 Table 8 Nonpoint Category O verview of Met hodology _______________________________________ 27 Table 9 Nonpoint CO Emissions for St. Louis City and St. Louis County (tons per year) _____________ 68 Table 10 St. Louis County and City 2008 Nonroad Em issions (excluding Marine and Rail Emissions) __ 70 Table 11 St. Louis County and City 2008 Marine and Rail Emissi ons ____________________________ 70 Table 12 St. Louis County and City Total 2008 Nonroad Mobile Source Emi ssions _________________ 70

Table 13 2008 Vehicle Mile s Traveled by County ___________________________________________ 72 Table 14 Missouri Regist ration Distribution _______________________________________________ 74

Table 15 2008 Source Type Population ___________________________________________________ 75 Table 16 2008 Annual VMT by HPMS Vehicle Type, County, and Year __________________________ 75 Table 17 Age Distributio n by Source Type _________________________________________________ 76 Table 18 Inspection and Main tenance Data for 2 008 ________________________________________ 77

Table 19 Fuel Form ulation for 2008 _____________________________________________________ 78 Table 20 2008 Fuel Supply _____________________________________________________________ 79 Table 21 Average Monthly Temperatures by Hour of the Day for St. Louis County in Fahrenheit ______ 80 Table 22 Average Monthly Percent Relative Humidity by Hour of the Day for St. Louis County _______ 81 Table 23 Average Monthly Temperatures by Hour of the Day for St. Louis City in Fahrenheit ________ 82 Table 24 Average Monthly Percent Relative Humidity by Hour of the Day for St. Louis City __________ 83 Table 25 On Road Mobile CO Emissions for St. Louis City and St. Louis County (tons per year) ______ 84

### Page 7 1.0 Introduction

1.1 Purpose

This document meets the nonattainment plan pr ovisions under the Clean Air Act Section 172 (c)(3):

“Such plan provisions shall include a comprehensive, accurate, current inventory of

actual emissions from all sources of the relevant pollutant or pollutants in such area, including such periodic revisions as the Administrator may determine necessary to assure
that the requirements of this part are met.”

Missouri’s limited maintenance pl an for the 8-hour CO National Ambient Air Quality Standard (NAAQS) requires a base year em issions inventory for 2008. The inventory is comprehensive in its inclusion of multiple source categories (point , nonpoint or area, and mobile sources), it is accurate based on the quality assurance steps outl ined in Section 4, contains current 2008 actual emissions for CO, and can be updated through the triennial National Emissions Inventory (NEI).

Emissions are documented for both the statewide i nventory and the St. Louis Nonclassifiable CO

Maintenance Area.

1.2 Inventory Coverage

1.2.1 Geography

The inventory covers St. Louis County and the City of St. Louis. Several summaries of

statewide Missouri totals are also included for reference. There are no inventory components provided by local or tr ibal agencies.

1.2.2 Emission Year

Emission year 2008 is the base year.

1.2.3 Pollutants

The only pollutant covered in the inve ntory is the criteria pollutant CO.

1.3 Contents of Report

This report documents the 2008 inventory in detail, from its creation, quality assurance, and final summaries. It also details the qualifications a nd limitations of the inventory. The document is arranged by purpose, emission summaries, docume ntation, quality assurance, and detailed appendices with lengthy emissions data tabl es and EPA provided category documentation.

### Page 8 1.4 Automated Systems Used

The 2008 emission inventory is maintained across multiple computing systems. Point source inventories are compiled from facility-supplied info rmation in the Missouri Emissions Inventory System (MoEIS) database. Point sources are a llowed to submit their i nventory data via the MoEIS web interface or on hardcopy paper form s which are data entered to the electronic system. Nonpoint emissions ar e calculated using Microsoft® Excel spreadsheet and Access

database tools. Mobile emissions are estimated using EPA’s Motor Vehicle Emissions Simulator (MOVES), and the National Mobile Inventor y Model (NMIM) which incorporates the

NONROAD2008 model.

1.5 Inventory Exclusions

This 2008 inventory does not include biogenic or geogenic emissions. The inventory does not include the nonpoint categories fo r wildfire, prescribed, or ag ricultural burning, agricultural tilling, plus others described in section 3.2.2. This inventory does not include hazardous air pollutant (HAP) inventories as they are not relevant pollutants for the Carbon Monoxide Maintenance plan. The HAP inventory is doc umented in Missouri’s 2008 National Emissions Inventory Documentation and is available on EPA’s NEI page at http://www.epa.gov/ttn/chie f/net/2008inventory.html . Point emissions data is summarized at the facility level in this document , though facility operational data and emission process data is

collected and submitted to the NEI.

1.6 Guidance and Reference Documents

This document is completed with the following references:

 Emissions Inventory Guidance for Implemen tation of Ozone and Particulate matter National Ambient Air Quality Standard s (NAAQS) and Regional Haze Regulations (August 2005, EPA-454/R-05-001, http://www.epa.gov/ttnchie1 /eidocs/eiguid/index.html )

 Emission Inventory Improvement Plan (EIIP) (July 1997, http://www.epa.gov/ttn/chief/eiip/index.html )

 2008 National Emissions Inventory Data version 1.5 and documentation (May 2011, http://www.epa.gov/ttn/chie f/net/2008inventory.html )

 Air Emission Reporting Rule (Dec 2008, http://www.epa.gov/ttn/chief/aerr/ )

 AP-42, Compilation of Air Po llutant Emission Factors ( http://www.epa.gov/ttn/chief/ap42/index.html )

 MOVES Technical Guidance, Policy Memos, etc at ( http://www.epa.gov/otaq/models/moves/index.htm )

 National Mobile Inventory Model (NMIM) ( http://www.epa.gov/oms/nmim.htm )

### Page 9 1.7 List of Contacts

The emission inventory is compiled by Stacy A llen, Environmental Spec ialist IV and Emission Inventory/Data Management Unit Chief with th e Missouri Department of Natural Resources. Specific contacts for other porti ons of the inventory are:

Point and Nonpoint Emissions: Stacy Allen, stacy.allen@dnr.mo.gov Mobile (Onroad and Nonroad) Emissions: Nathan O’Neil, nathan.o’neil@dnr.mo.gov

2.0 Emissions Summary

2.1 Summary by County and Category

Table 1 Total 2008 CO Emissions for St. Louis City and St. Louis County



### Area Source Category 2008 CO Emissions (tons/year)

St. Louis County Point Sources 4,995.09



### St. Louis County Area Sources 8,752.71



### St. Louis County On Road Mobile Sources 132,855.83



### St. Louis County Off Road Mobile Sources 76,069.44



### St. Louis County subtotal 222,673.07



### St. Louis City Point Sources 1,319.83



### St. Louis City Area Sources 3,086.57



### St. Louis City On Road Mobile Sources 34,576.81



### St. Louis City Off Road Mobile Sources 15,573.38



### St. Louis City subtotal 54,556.59



### Total (St. Louis City and County) Point Sources 6,314.92



### Total (St. Louis City and County) Area Sources 11,839.28



### Total (St. Louis City and Count y) On Road Mobile Sources 167,432.64



### Total (St. Louis City and Count y) Off Road Mobile Sources 91,642.82



### Total (St. Louis City and County) Total 277,229.66

### Page 10 3.0 Inventory Documentation

3.1 Point Source Emissions

3.1.1 Procedures and Methodologies

The point source inventory is based on info rmation collected on Emissions Inventory Questionnaires (EIQs). Facilities with a construction or opera ting permit from the Air Pollution Control Program are required to submit an EIQ on an annual basis per 10 CSR 10-6.110. The EIQ details the amount of air pollution emitted and other operational data for the previous calendar year.

2008 point sources include those with Part 70 and Intermediate operating permits. The EIQ

solicitation was mailed to facilities in January 2009. The due date for 2008 reporting was June 1, 2009, and all point source reports were receive d and included in this document summary.

3.1.2 Emission Inventory Questionnaire (EIQ)

All point source emissions data for the State of Missouri is contained in a database called the Missouri Emissions Inventory System (MoEIS). Emission reports may be submitted either directly via the MoEIS web interface, a user-frien dly, online portal linked directly to the MoEIS database, or they may be submitted on the hardcopy EIQ forms. Hardcopy EIQ submittals are then data entered into the MoEIS database by EI unit staff members. As a result, the MoEIS database is updated yearly with the most curren t emissions data for the State of Missouri.

Hardcopy EIQ forms are described in Table 2. All hardcopy forms have an electronic counterpart in the MoEIS web interface system. In general, forms beginning with number one (1) provide general information about a facility, forms beginni ng with a two (2) provide the detailed annual emission calculations, incl uding activity or thr oughput, emission factors, emissions, and operational characteristics. More information on EIQ forms and instructions and

MoEIS is available at http://www.dnr.mo.gov/env/apcp/moeis/emissionsreporting.htm

Table 2 List of EIQ Forms



### F ORM 

### N AME 

### F ORM 

### D ESCRIPTION 

### F ORM


### N UMBER



### F ORM 

### 1.0

G ENERAL 

### P LANT



### I NFORMATION 

### G ENERAL PLANT INFORMATION



### , PLANT



### - WIDE EMISSIONS

TOTALS



### , SIGNATURE SECTION CERTIFYING SUBMITTED

INFORMATION IS ACCURATE AND COMPLETE 

### 780-1431

F ORM 

### 1.1 P ROCESS



### F LOW 

### D IAGRAM 

### D IAGRAM IDENTIFYING AND LINKING ALL EMISSION

UNITS



### , PROCESSES



### , AIR POLLUTION CONTROL DEVICES



### , AND EMISSION RELEASE POINTS FOR A FACILITY



### . S UBMIT

ONLY IF THERE HAVE BEEN CHANGES



### . 780-1619

### Page 11 F ORM 

### N AME 

### F ORM 

### D ESCRIPTION 

### F ORM


### N UMBER



### F ORM 

### 1.2

S UMMARY OF



### E MISSION 

### U NITS

AND 

### R ELATED



### P ROCESSES 

### L IST OF ALL EMISSION UNITS AND ASSOCIATED PROCESSES

AND THE STATUS OF EACH 

### ( ACTIVE



### , INSIGNIFICANT



### , DISMANTLED 

### ) 780-1620

F ORM 

### 2.0

E MISSION 

### U NIT


### I NFORMATION 

### M AIN EMISSIONS REPORTING FORM 

### ; SEPARATE 

### F ORM 

### 2.0

REQUIRED FOR EACH PROCESS FOR WHICH EMISSIONS ARE

BEING REPORTED 

### ( I



### . E



### ., F ORM 

### 2.0 NOT REQUIRED FOR

EMISSIONS BELOW REPORTING THRESHOLDS 

### ) 780-1621

F ORM 

### 2.0C

C ONTROL 

### D EVICE



### I NFORMATION 

### C ONTROL DEVICE INFORMATION WHEN THERE IS A

CONTROL DEVICE OPERATIVE AT AN EMISSION UNIT 

### ;

SEPARATE 

### F ORM 

### 2.0C REQUIRED FOR EACH CONTROL

DEVICE 

### 780-1434

F ORM 

### 2.0K

C HARCOAL 

### K ILN



### I NFORMATION 

### D ETAILS THE OPERATIONS AND CHARACTERISTICS OF

CHARCOAL KILNS 

### 780-1530

F ORM 

### 2.0L

L ANDFILL



### I NFORMATION 

### F ORM FOR REPORTING EMISSIONS FROM LANDFILLS 

### 780-1583

F ORM 

### 2.0P

P ORTABLE



### E QUIPMENT



### I NFORMATION 

### D ETAILS THE LOCATIONS AND OPERATIONS FOR

PORTABLE EQUIPMENT OPERATIONS INCLUDING

QUARRIES



### , ASPHALT PLANTS



### , AND CONCRETE BATCH

PLANTS 

### 780-1433

F ORM 

### 2.0S

S TACK 

### /V ENT



### I NFORMATION 

### S TACK INFORMATION FOR EMISSION UNITS WHERE

EMISSIONS FROM A PROCESS ENTER THE AMBIENT AIR

THROUGH ONE OR MORE STACKS 

### / VENTS 

### 780-1435

F ORM 

### 2.0Z O ZONE


### S EASON



### I NFORMATION



### F ORM 

### C ALCULATION OF OZONE SEASON DAY EMISSIONS OF 

### VOC, NO
X 

### , OR 

### CO; REQUIRED FROM FACILITIES LOCATED

IN 

### S T



### . L OUIS



### , S T



### . C HARLES



### , F RANKLIN AND 

### J EFFERSON 

### C OUNTIES AND 

### S T



### . L OUIS 

### C ITY WITH 

### 10 TONS OR MORE OF 

### VOC, NO
X OR 

### CO ANNUAL EMISSIONS



### . 780-1452

F ORM 

### 2.1 F UEL


### C OMBUSTION


### W ORKSHEET 

### I NFORMATION RELATED TO COMBUSTION EQUIPMENT



### , FUEL USAGE



### , AND THE CALCULATIONS ASSOCIATED WITH

COMBUSTION PROCESSES 

### 780-1436

F ORM 

### 2.2

I NCINERATOR


### W ORKSHEET 

### I NFORMATION RELATED TO THE INCINERATOR



### , WASTE

MATERIAL 

### ( S 

### ) INCINERATED



### , AND THE ANNUAL WASTE

MATERIAL THROUGHPUT 

### 780-1438

F ORM 

### 2.3 VOC

P ROCESS 

### M ASS



### B ALANCE


### W ORKSHEET 

### C ALCULATES A 

### VOC MASS BALANCE EMISSION FACTOR 

### 780-1440

### Page 12 F ORM 

### N AME 

### F ORM 

### D ESCRIPTION 

### F ORM


### N UMBER



### F ORM 

### 2.4

V OLATILE


### O RGANIC 

### L IQUID



### L OADING


### W ORKSHEET 

### C ALCULATES AN EMISSION FACTOR FOR PETROLEUM

LIQUID LOADING INTO TANK TRUCKS



### , RAIL CARS



### , AND

BARGES BASED ON 

### AP-42 780-1625

F ORM 

### 2.5L

G ENERAL 

### L IQUID


### S TORAGE 

### T ANK



### I NFORMATION 

### I NFORMATION ABOUT STORAGE TANKS 

### 780-1444

F ORM 

### 2.7 H AUL



### R OAD 

### F UGITIVE



### E MISSIONS


### W ORKSHEET 

### C ALCULATES AN EMISSION FACTOR FOR UNPAVED HAUL

ROADS BASED ON 

### AP-42 FORMULA 

### 780-1445

F ORM 

### 2.8

S TORAGE 

### P ILE


### W ORKSHEET 

### C ALCULATES EMISSION FACTORS FOR ACTIVITY AND

WIND EROSION FROM STORAGE PILES BASED ON 

### AP-42

FORMULAS 

### 780-1446

F ORM 

### 2.9 S TACK



### T EST 

### /C ONTINUOUS



### E MISSION



### M ONITORING


### W ORKSHEET 

### D OCUMENTATION FOR EMISSION FACTORS DERIVED FROM

STACK TESTS OR 

### CEM DEVICES 

### 780-1447

F ORM 

### 2.T

H AZARDOUS 

### A IR



### P OLLUTANT


### W ORKSHEET 

### I NFORMATION ON 

### HAP CHEMICALS EMITTED AT THE

PROCESS LEVEL 

### ; SEPARATES INDIVIDUAL 

### HAP S FROM

THOSE INCLUDED IN 

### VOC/PM EMISSIONS 

### 780-1448

F ORM 

### 3.0

E MISSION 

### F EE


### C ALCULATION 

### S UMMARY TABLE SHOWING EMISSIONS FROM ALL

PROCESSES 

### 780-1509

F ORM 

### 3.0CK

E MISSION 

### F EE


### C ALCULATION FOR


### C HARCOAL 

### K ILNS 

### S UMMARY TABLE SHOWING EMISSIONS FROM CHARCOAL

KILN OPERATIONS 

### 780-1508

D RY 

### C LEANER



### – N ON



### CHLORINATED

AND 

### P ETROLEUM



### B ASED 

### S OLVENTS 

### E MISSIONS CALCULATIONS FOR DRY CLEANERS USING

NON



### - CHLORINATED SOLVENT AND WITH COMBINED

DRYER CAPACITY OF 

### 84 POUNDS OR MORE 

### 780-1954

F ORM 

### 4.0

F INANCIAL 

### C OST



### E STIMATE 

### E STIMATE THE COST OF COMPLYING WITH AIR POLLUTION

REGULATION 

### 780-1622



### Point source EIQ data received via hard copy fo rms is data entered to the MoEIS emissions database by emission inventory st aff. During this step, process- level emissions and operational information are checked for consistency between the hardcopy forms and database calculations, and inconsistencies are flagged for review . Problems include, but are not limited to: Incorrect Source Classification Codes (SCCs) Emission unit numbering changes

### Page 13 Calculation errors Missing or incomplete records Transposition errors If no errors are found during data entry, and th e emissions reported on the hardcopy full EIQ match what is calculated by the MoEIS database, th en the emission report is considered complete

and data entered.

EIQs with inconsistencies are moved from emission inventory data entry staff to a member of the

technical review team. The tec hnical review team will address the problems encountered during data entry by identifying the specific issue(s) and possible causes and co ntacting the facility to resolve those issues. Other issues may also be addressed during the review, including the appropriate use of emission esti mation methods, documentation of source data, and consistency with permit emission calculations. Supplemental EIQ information may be collected by staff via telephone or email contact with th e facility in question. Informati on collected in this manner will be recorded on the EIQ for refere nce, tracking and QA a uditing. If the facility is requested to submit follow up verification or additional informa tion in writing, a statement pertaining to this request will also be recorded on the EIQ. The info rmation recorded will include the date of the call or contact, staff person’s name, contact pe rson’s name, and written documentation of the

call.

After the submission deadline of June 1 has passed, a list of unsubmitted EIQs is generated and sent to the compliance and enfor cement section of the Air Pollu tion Control Program. With all emissions data contained in the MoEIS database, further quality assurance steps are completed as

described in Section 4.

3.1.3 List of Facili ties and Emissions

There are 139 facilities in the point source inve ntory for the Missouri co unties of the St. Louis nonattainment area. Their primary economic activity described by their North American Industry Classification System (NAI CS) code is listed in Table 3 for St. Louis City and St. Louis County. The emissions of each facility in tons per year are listed in Table 4.

Table 3 St. Louis County and Ci ty 2008 Point Sources by NAICS

Primary Economic Activity Description St. Louis County St. Louis City Adhesive Manufacturing 1 1 Administration of Air and Water Resource and Solid Waste Management Programs 1 Air-Conditioning and Warm Air Heating E quipment and Commercial and Industrial Refrigeration Equipment Manufacturing Aircraft Manufacturing 1 All Other Basic Organic Chemical Manufacturing 1

All Other Miscellaneous Textile Product Mills 1 All Other Rubber Product Manufacturing 1 Asphalt Paving Mixture and Block Manufacturing 6 1 Automobile Manufacturing 2 Biological Product (except Diagnostic) Manufacturing 1

Breweries 1 Carburetor, Piston, Piston Ring, and Valve Manufacturing 1

### Page 14 Primary Economic Activity Description St. Louis County St. Louis City Cement Manufacturing Coated and Laminated Packaging Paper Manufacturing 1 Coffee and Tea Manufacturing 1 Colleges, Universities, and Professional Schools 1 1 Commercial and Industrial Machinery and Equipment (except Automotive and Electronic) Repair and Maintenance 1 Commercial and Institutional Building Construction 1

Commercial Bakeries 1 Commercial Flexographic Printing 1 Commercial Lithographic Printing 2 2 Crushed and Broken Limestone Mining and Quarrying 3 Dry Pasta Manufacturing 1 Electronic Coil, Transformer, and Other Inductor Manufacturing Electroplating, Plating, Polishing, Anodizing, and Coloring Fabric Coating Mills Fabricated Structural Metal Manufacturing Farm Supplies Merchant Wholesalers 1
Flour Milling 2 Folding Paperboard Box Manufacturing

Fossil Fuel Electric Power Generation 1 1 General Medical and Surgical Hospitals 5 3 General Warehousing and Storage 1 Glass Container Manufacturing Glass Product Manufacturing Made of Purchased Glass 1

Grain and Field Bean Merchant Wholesalers 1 Heating Equipment (except Warm Air Furnaces) Manufacturing 1 Industrial Sand Mining 1 Industrial Valve Manufacturing Inorganic Dye and Pigment Manufacturing 1 1 Institutional Furniture Manufacturing 1 Iron and Steel Pipe and Tube Manufacturing from Purchased Steel Laminated Aluminum Foil Manufacturing for Flexible Packaging Uses 1 Leather and Hide Tanning and Finishing 1 Machine Tool (Metal Cutting Types) Manufacturing 1 Manifold Business Forms Printing 1 Metal Can Manufacturing Metal Coating, Engraving (except Jewelry and Silverware), and Allied Services to

Manufacturers 2 Motor Vehicle Body Manufacturing Motor Vehicle Seating and Interior Trim Manufacturing National Security 1

Natural Gas Distribution 1 Natural Gas Liquid Extraction 2
Newspaper Publishers 1 1 Offices of Physicians (except Mental Health Specialists) 1 Other Aircraft Parts and Auxiliary Equipment Manufacturing 1 Other Metal Container Manufacturing 1

### Page 15 Primary Economic Activity Description St. Louis County St. Louis City Other Metal Valve and Pipe Fitting Manufacturing 1 Paint and Coating Manufacturing 3 Pesticide and Other Agricultural Chemical Manufacturing 1 Petrochemical Manufacturing 1 2

Petroleum Bulk Stations and Terminals 1 Pharmaceutical Preparation Manufacturing 3 Plastics Material and Resin Manufacturing 1 Polystyrene Foam Product Manufacturing 1 Primary Smelting and Refining of Nonferrous Metal (except Copper and Aluminum) Railroad Rolling Stock Manufacturing Research and Development in the Physical, Engineering, and Life Sciences 1 Rubber and Plastics Hoses and Belting Manufacturing 1 Secondary Smelting and Alloying of Aluminum 1 Semiconductor and Related Device Manufacturing Sewage Treatment Facilities 3 Ship Building and Repairing Sign Manufacturing Soap and Other Detergent Manufacturing 2

Solid Waste Landfill 4 Spice and Extract Manufacturing 1 Steel Foundries (except Investment)

Steel Investment Foundries Toy and Hobby Goods and Supplies Merchant Wholesalers 1 Truck Trailer Manufacturing 1 Unlaminated Plastics Profile Shape Manufacturing

Wired Telecommunications Carriers 1

Total Number of Facilities 52 49

### Page 16 Table 4 St. Louis County and City 2008 Point S ource CO Emissions by Facility (tons per year)

Area Site ID Facility Name CO

Emissions

St. Louis County 0002 Chrysler Assembly Plant 1-Fenton 21.86

St. Louis County 0010 Amerenue-Meramec Plant 3,811.99

St. Louis County 0017 Fred Weber Inc-North Stone

St. Louis County 0019 Fred Weber Inc-South Stone

St. Louis County 0020 Monsanto World Headquarters-Lindbergh Blvd 10.33

St. Louis County 0021 U S Silica Company-Pacific 3.51

St. Louis County 0025 Dana Corporation-Perfect Circ le Division 0.87

St. Louis County 0032 Pharmacia-Chesterfield Village 14.82

St. Louis County 0035 Rockwood Pigments Na Inc-E Hoffmeister 8.27

St. Louis County 0042 Washington University-Millbrook Blvd 18.42

St. Louis County 0057 St Louis Post-Dispatch-Dunlap Ind Dr 0.16

St. Louis County 0064 Sunnen Products Company-Maplewood 1.01

St. Louis County 0065 St Louis Airport Authority-Lambert International Blvd 9.38

St. Louis County 0111 Simpson Construction Materials Llc-West Lake Quarry & Material Co 15.71

St. Louis County 0141 Energy Petroleum Company-Kienlen

St. Louis County 0208 Printpack Inc-Hazelwood Plant 3.45

St. Louis County 0217 Metropolitan St Louis Sewer District-Lemay Waste Water Treatment Plant 321.07

St. Louis County 0226 Nesco Container Corp-Fenton 1.07

St. Louis County 0230 McDonnell Douglas Corp /Boeing Co mpany-Lindbergh Plant 20.96

St. Louis County 0231 Chrysler Corp-North Plant 65.23

St. Louis County 0238 St Louis Lithographing Company-Heege Avenue

St. Louis County 0242 Multiplex Display Fixture-Fenton 0.49

St. Louis County 0275 Bussen Quarries Inc-Bussen Road

St. Louis County 0276 Ruprecht Quarry-Paule Rd

St. Louis County 0281 BFI Missouri Pass Landfill-Maryland Heights 30.58

St. Louis County 0282 Color Art Inc-Crestwood 1.01

St. Louis County 0308 Fred Weber Inc Sanitary Landfill-St Louis County 130.13

St. Louis County 0310 Onyx Oak Ridge Landfill Inc-(West County) 44.89

St. Louis County 0312 Bridgeton Landfill Authority-Bridgeton 244.28

St. Louis County 0315 Flex-O-Lite Inc-Fenton -

St. Louis County 0317 Pro-Tect Mfg Inc-Ferguson Ave

St. Louis County 0318 St Marys Health Center-Richmond Heights 6.74

St. Louis County 0327 Camie-Campbell Inc-Watson Industrial Park

St. Louis County 1012 Belt Service Corp-Earth City 0.47

St. Louis County 1015 Kv Pharmaceutical Company-Br entwood -

St. Louis County 1029 Depaul Health Center-Bridgeton 6.05

St. Louis County 1047 Kv Pharmaceutical Company- Schuetz Rd 1.22

St. Louis County 1052 Veterans Admin Medical Center-Jefferson Barracks Drive -

St. Louis County 1097 Reichhold Chemicals Inc-Valley Park 4.40

St. Louis County 1101 St Luke'S Hospital-Woods Mill Road 5.24

### Page 17 Area Site ID Facility Name CO

Emissions

St. Louis County 1156 St Joseph Hospital-Kirkwood 2.99

St. Louis County 1192 Pan-Glo St Louis-Trenton Avenue

St. Louis County 1204 Whitmire Microgen Research Laboratory-Kirkwood

St. Louis County 1205 Metropolitan St Louis Sewer District-Mo River Wasterwater Treatment Plant 7.10

St. Louis County 1210 Metropolitan St Louis Sewer District-Coldwat er Creek Sewage Treatment Plant 50.69

St. Louis County 1226 Simpson Construction Material s Llc-Valley Park 20.28

St. Louis County 1248 Fred Weber Inc-South Asphalt 24.49

St. Louis County 1249 Fred Weber Inc-North Asphalt H & B 37.15

St. Louis County 1250 Fred Weber Inc-North Asphalt B & G 37.42

St. Louis County 1489 Gkn Aeros pace Services Inc-Berkeley 11.36

St. Louis County 1520 F & S Real Eastate Inc-St Louis

St. Louis County 1538 KV PHARMACEUTICAL-BRIDGETON -

St. Louis County Total 4,995.09

St. Louis City 0003 Anheuser-Busch Inc-St Louis 145.98

St. Louis City 0017 Mallinckrodt Inc 77.49

St. Louis City 0027 Precoat Metals 5.10

St. Louis City 0031 ADM Gromark River Systems-St Louis 0.00

St. Louis City 0038 Trigen-St Louis Energy Corp-Ashley Street Station 46.27

St. Louis City 0040 Washington Univ Medical Sc hool-Boiler Plant 28.23

St. Louis City 0047 Fred Weber Inc-Asphalt Plant 9.56

St. Louis City 0053 Metropolitan St Louis Sewer District-Bissel Plant 552.29

St. Louis City 0057 Procter & Gamble-Procter & Gamble 9.89

St. Louis City 0063 Dial Corp-Dial Corp 8.39

St. Louis City 0066 Elementis Specialties Inc 6.78

St. Louis City 0070 Astaris Llc-Carondelet Plant 27.07

St. Louis City 0096 P D George Co (The) 3.73

St. Louis City 0097 U S Paint Div Of Grow Group-U S Paint Div Of Grow Group

St. Louis City 0118 Alumax Foils Inc-Alcoa Foil Produc ts/Alumax Foils Inc 14.02

St. Louis City 0159 ADM/TPC Milling Co-Pillsbury Company -

St. Louis City 0161 Poly One Corporation-St Louis

St. Louis City 0162 Marquette Tool & Die

St. Louis City 0175 St Louis Metallizing-St Louis 0.08

St. Louis City 0179 Italgrani Elevator 3.22

St. Louis City 0200 St Alexius Hospital-St Louis 0.33

St. Louis City 0204 Bjc Health System-Pavillion 1.51

St. Louis City 0269 Sensient Colors Inc-Baldwin Plant 2.41

St. Louis City 0391 Hermann Oak Leather Co -

St. Louis City 0468 Lange-Stegmann Co 0.00

St. Louis City 0697 Sigma - Aldrich Co 3.14

St. Louis City 0808 Chemisphere Corporation-Chemisphere

St. Louis City 0809 PQ Corporation (The)-St Louis 9.65

### Page 18 Area Site ID Facility Name CO

Emissions

St. Louis City 0938 Interstate Brands Corp-Interstate Brands Corp 1.27

St. Louis City 1055 Goodwin Printing Co -St Louis

St. Louis City 1077 Mid-West Industrial Chemical -

St. Louis City 1093 Brenntag Mid-South Inc 0.00

St. Louis City 1123 U S Ringbinder Corp-Loose Leaf Metals

St. Louis City 1280 St Louis Post Dispatch 0.44

St. Louis City 1370 National Geospatial-Intelli gence Agency 1.38

St. Louis City 1396 Sigma - Aldrich Co-Sigma Chem ical Company 4.92

St. Louis City 1407 Southern Metal Processing 2.17

St. Louis City 1423 Ashland Distribut ion Company-St Louis Plant

St. Louis City 1460 Allied Health Care Products -

St. Louis City 1505 Energy Center (The)-St Louis Univ H ealth Sciences Center 9.43

St. Louis City 1519 Permacel St Louis Inc-Permac el St Louis Inc 2.30

St. Louis City 1556 Connector Castings 0.00

St. Louis City 1642 J S Alberici Construction -

St. Louis City 2300 Superior Solvent & Chemical-St Louis

St. Louis City 2378 Laclede Tower Associates Ll c-Laclede Gas Building 320.75

St. Louis City 2433 New World Pasta- Marceau Facility-New World Pasta 4.59

St. Louis City 2545 Southwestern Bell Telephone Company 6.68

St. Louis City 2711 St Louis University-Facilities Svcs 9.70

St. Louis City 2833 WASHINGTON UNIVERSITY-HILLTOP CAMPUS 1.06

St. Louis City Total 1,319.83

St. Louis County and St. Louis City Combined 6,314.92

### Page 19 Table 5 Statewide Point Source Emissi ons by Category (tons per year)



### Category Description Number of

Facilities CO

Emissions

Fossil Fuel Electric Power Generation 76 22,142 Primary Smelting and Refining of N onferrous Metal (except Copper and Aluminum) 2 23
Cement Manufacturing 6 11,122
Steam and Air-Conditioning Supply 3 94
Petrochemical Manufacturing 2 121
Primary Aluminum Production 1 24,771
Pesticide and Other Agricultural Chemical Manufacturing 5 173
Lime Manufacturing 2 11,843
Pipeline Transportation of Natural Gas 10 1,350
Sewage Treatment Facilities 4 931
Nitrogenous Fertilizer Manufacturing 1

Breweries 1 146 Secondary Smelting, Refining, and Allo ying of Nonferrous Metal (except Copper and Aluminum) 1 13,391
Lead Ore and Zinc Ore Mining 2 0
Medicinal and Botanical Manufacturing 2 3

Automobile Manufacturing 2 159
Soybean Processing 4 34
Motor Vehicle Body Manufacturing 9 16

All Other Categories 435 5,959

Statewide Total 568 92,278

### Page 20 Table 6 Statewide Point Emissions by County (tons per year)

State County FIPS Code County Name CO Emissions

29001 Adair 0.05

29003 Andrew 8.66

29007 Audrain 237.83

29009 Barry 31.17

29011 Barton 125.64

29013 Bates 1.58

29017 Bollinger 161.20

29019 Boone 1,143.44

29021 Buchanan 220.11

29023 Butler 220.70

29025 Caldwell

29027 Callaway 51.94

29029 Camden 1.61

29031 Cape Girardeau 8,724.64

29033 Carroll 4.10

29037 Cass 109.64

29039 Cedar 8.20

29041 Chariton

29047 Clay 105.47

29049 Clinton -

29051 Cole 112.87

29053 Cooper 75.60

29055 Crawford

29061 Daviess 1.34

29063 DeKalb 3.86

29065 Dent 38.34

29069 Dunklin 32.55

29071 Franklin 2,496.24

29073 Gasconade 1.58

29075 Gentry -

29077 Greene 1,828.54

29079 Grundy 3.69

29081 Harrison 19.60

29083 Henry 519.94

29087 Holt 7.54

29091 Howell 1,034.81

29093 Iron 13,390.58

29095 Jackson 4,257.40

29097 Jasper 980.35

29099 Jefferson 1,683.83

29101 Johnson 81.04

29105 Laclede 38.55

29107 Lafayette 7.84

29109 Lawrence 21.75

29111 Lewis

29113 Lincoln 6.22

29115 Linn 0.04

29117 Livingston 1.38

### Page 21 State County FIPS Code County Name CO Emissions

29119 McDonald 52.65

29121 Macon 120.37

29123 Madison 194.01

29125 Maries 22.89

29127 Marion 150.36

29131 Miller 0.05

29133 Mississippi 0.92

29137 Monroe 0.04

29139 Montgomery 82.34

29143 New Madrid 25,872.19

29145 Newton 43.28

29147 Nodaway 380.16

29151 Osage 78.95

29155 Pemiscot 4.25

29157 Perry 5.39

29159 Pettis 418.53

29161 Phelps 23.80

29163 Pike 1,792.34

29165 Platte 652.80

29167 Polk -

29169 Pulaski 9.45

29171 Putnam 0.01

29173 Ralls 84.78

29175 Randolph 4,493.43

29179 Reynolds -

29183 St. Charles 900.69

29186 Ste. Genevieve 11,853.64

29187 St. Francois 45.81

29189 St. Louis 4,995.08

29195 Saline 114.08

29201 Scott 375.52

29203 Shannon 19.55

29205 Shelby 82.31

29207 Stoddard 118.32

29209 Stone

29213 Taney 29.80

29215 Texas 17.62

29217 Vernon 31.19

29219 Warren 6.68

29221 Washington 4.55

29225 Webster 0.31

29229 Wright 39.63

29510 St. Louis city 1,319.86

Missouri Total 92,239.10

### Page 22 3.2 Nonpoint Source Emissions

3.2.1 Procedures and Methodologies

The nonpoint (also known as area) source categorie s with published methods of estimation are too numerous to calculate county-level inventor ies given current resources. The EPA, in conjunction with the Eastern Region Technical Advisory Committee (ERTAC), will complete inventory documentation and calculation for most nonpoint source categories using national defaults. Several categories are then improved with state-level information or with point-source

subtraction.

Missouri prepared inventories for 18 categories th at required point source subtraction or statespecific data. These categories are listed in the Missouri Category Summary section below. Documentation of the calculation methodology a nd data sources is included in Table . Categories that did not require po int source subtraction that were calculated by EPA are listed in the EPA Category Summary section.

3.2.2 List of Source Categories and Emissions

Table 8 includes a list of all area source categories and the 2008 emissions from each category for St. Louis City and St. Louis County.

.Page 23Table 7 Nonpoint 2008 Emission Records forSt. Louis County and City (tons per year)AreaSCCSCC Level OneSCC Level TwoSCC Level ThreeSCC Level Four2008 COEmissionsSt. Louis County 2102001000Stationary SourceFuel CombustionAnthracite Coal Industrial Total: All Boiler Types-St. Louis County 2102002000Stationary SourceFuel CombustionBituminous/Subbituminous CoalIndustrial Total: All Boiler Types302.17St. Louis County 2102004000Stationary SourceFuel CombustionDistillate Oil Industrial Total: Boilers and IC Engines1.44St. Louis County 2102005000Stationary SourceFuel CombustionResidual Oil Industrial Total: All Boiler Types0.41St. Louis County 2102006000Stationary SourceFuel CombustionNatural Gas Industrial Total: Boilers and IC Engines4.14St. Louis County 2102007000Stationary SourceFuel CombustionLiquified Petroleum Gas(LPG)Industrial Total: All Boiler Types-St. Louis County 2102008000Stationary SourceFuel CombustionWood Industrial Total: All Boiler Types213.58St. Louis County 2102011000Stationary SourceFuel CombustionKerosene Industrial Total: All Boiler Types-St. Louis County 2103001000Stationary SourceFuel CombustionAnthracite Coal Commercial/Institutional Total: All Boiler Types-St. Louis County 2103002000Stationary SourceFuel CombustionBituminous/Subbituminous CoalCommercial/Institutional Total: All Boiler Types2.10St. Louis County 2103004000Stationary SourceFuel CombustionDistillate Oil Commercial/Institutional Total: Boilers and IC Engines0.02St. Louis County 2103005000Stationary SourceFuel CombustionResidual Oil Commercial/Institutional Total: All Boiler Types-St. Louis County 2103006000Stationary SourceFuel CombustionNatural Gas Commercial/Institutional Total: Boilers and IC Engines11.07St. Louis County 2103007000Stationary SourceFuel CombustionLiquified Petroleum Gas(LPG)Commercial/Institutional Total: All Combustor Types0.71St. Louis County 2103008000Stationary SourceFuel CombustionWood Commercial/Institutional Total: All Boiler Types2.15St. Louis County 2103011000Stationary SourceFuel CombustionKerosene Commercial/Institutional Total: All Combustor Types0.01St. Louis County 2104002000Stationary SourceFuel CombustionBituminous/Subbituminous CoalResidential Total: All Combustor Types76.40St. Louis County 2104004000Stationary SourceFuel CombustionDistillate Oil Residential Total: All Combustor Types1.06St. Louis County 2104006000Stationary SourceFuel CombustionNatural Gas Residential Total: All Combustor Types504.76St. Louis County 2104007000Stationary SourceFuel CombustionLiquified Petroleum Gas(LPG)Residential Total: All Combustor Types4.50Page 24AreaSCCSCC Level OneSCC Level TwoSCC Level ThreeSCC Level Four2008 COEmissionsSt. Louis County 2104008100Stationary SourceFuel CombustionWood Residential Fireplace: general1,367.95St. Louis County 2104008210Stationary SourceFuel CombustionWood Residential Woodstove: fireplace inserts; non-EPA certified2,146.20St. Louis County 2104008220Stationary SourceFuel CombustionWood Residential Woodstove: fireplace inserts; EPA certified; non-catalytic375.81St. Louis County 2104008230Stationary SourceFuel CombustionWood Residential Woodstove: fireplace inserts; EPA certified; catalytic92.70St. Louis County 2104008310Stationary SourceFuel CombustionWood Residential Woodstove: freestanding, non-EPA certified1,758.77St. Louis County 2104008320Stationary SourceFuel CombustionWood Residential Woodstove: freestanding, EPA certified, non-catalytic344.06St. Louis County 2104008330Stationary SourceFuel CombustionWood Residential Woodstove: freestanding, EPA certified, catalytic84.99St. Louis County 2104008400Stationary SourceFuel CombustionWood Residential Woodstove: pellet-fired, general (freestanding or FP insert)39.08St. Louis County 2104008510Stationary SourceFuel CombustionWood Residential Furnace: Indoor, cordwood-fired, non-EPA certified413.58St. Louis County 2104008610Stationary SourceFuel CombustionWood Residential Hydronic heater: outdoor761.67St. Louis County 2104009000Stationary SourceFuel CombustionFirelog Residential Total: All Combustor Types147.52St. Louis County 2104011000Stationary SourceFuel CombustionKerosene Residential Total: All Heater Types0.56St. Louis County 2302002100Industrial ProcessesCommercial Cooking -CharbroilingFood and Kindred Products:SIC 20Conveyorized Charbroiling22.69St. Louis County 2302002200Industrial ProcessesCommercial Cooking -CharbroilingFood and Kindred Products:SIC 20Under-fired Charbroiling64.38St. Louis County 2302003000Industrial ProcessesCommercial Cooking -FryingFood and Kindred Products:SIC 20Deep Fat Fying-St. Louis County 2302003100Industrial ProcessesCommercial Cooking -FryingFood and Kindred Products:SIC 20Flat Griddle Frying8.22St. Louis County 2302003200Industrial ProcessesCommercial Cooking -FryingFood and Kindred Products:SIC 20Clamshell Griddle Frying-St. Louis County Total8,752.71St. Louis City 2102001000Stationary SourceFuel CombustionAnthracite Coal Industrial Total: All Boiler Types-St. Louis City 2102002000Stationary SourceFuel CombustionBituminous/Subbituminous CoalIndustrial Total: All Boiler Types180.54Page 25AreaSCCSCC Level OneSCC Level TwoSCC Level ThreeSCC Level Four2008 COEmissionsSt. Louis City 2102004000Stationary SourceFuel CombustionDistillate Oil Industrial Total: Boilers and IC Engines0.86St. Louis City 2102005000Stationary SourceFuel CombustionResidual Oil Industrial Total: All Boiler Types0.25St. Louis City 2102006000Stationary SourceFuel CombustionNatural Gas Industrial Total: Boilers and IC Engines2.04St. Louis City 2102007000Stationary SourceFuel CombustionLiquified Petroleum Gas(LPG)Industrial Total: All Boiler Types-St. Louis City 2102008000Stationary SourceFuel CombustionWood Industrial Total: All Boiler Types138.74St. Louis City 2102011000Stationary SourceFuel CombustionKerosene Industrial Total: All Boiler Types-St. Louis City 2103001000Stationary SourceFuel CombustionAnthracite Coal Commercial/Institutional Total: All Boiler Types-St. Louis City 2103002000Stationary SourceFuel CombustionBituminous/Subbituminous CoalCommercial/Institutional Total: All Boiler Types2.08St. Louis City 2103004000Stationary SourceFuel CombustionDistillate Oil Commercial/Institutional Total: Boilers and IC Engines0.02St. Louis City 2103005000Stationary SourceFuel CombustionResidual Oil Commercial/Institutional Total: All Boiler Types-St. Louis City 2103006000Stationary SourceFuel CombustionNatural Gas Commercial/Institutional Total: Boilers and IC Engines7.86St. Louis City 2103007000Stationary SourceFuel CombustionLiquified Petroleum Gas(LPG)Commercial/Institutional Total: All Combustor Types0.61St. Louis City 2103008000Stationary SourceFuel CombustionWood Commercial/Institutional Total: All Boiler Types2.21St. Louis City 2103011000Stationary SourceFuel CombustionKerosene Commercial/Institutional Total: All Combustor Types0.01St. Louis City 2104002000Stationary SourceFuel CombustionBituminous/Subbituminous CoalResidential Total: All Combustor Types67.06St. Louis City 2104004000Stationary SourceFuel CombustionDistillate Oil Residential Total: All Combustor Types0.85St. Louis City 2104006000Stationary SourceFuel CombustionNatural Gas Residential Total: All Combustor Types178.48St. Louis City 2104007000Stationary SourceFuel CombustionLiquified Petroleum Gas(LPG)Residential Total: All Combustor Types2.32St. Louis City 2104008100Stationary SourceFuel CombustionWood Residential Fireplace: general440.92St. Louis City 2104008210Stationary SourceFuel CombustionWood Residential Woodstove: fireplace inserts; non-EPA certified641.76Page 26AreaSCCSCC Level OneSCC Level TwoSCC Level ThreeSCC Level Four2008 COEmissionsSt. Louis City 2104008220Stationary SourceFuel CombustionWood Residential Woodstove: fireplace inserts; EPA certified; non-catalytic137.55St. Louis City 2104008230Stationary SourceFuel CombustionWood Residential Woodstove: fireplace inserts; EPA certified; catalytic35.48St. Louis City 2104008310Stationary SourceFuel CombustionWood Residential Woodstove: freestanding, non-EPA certified595.41St. Louis City 2104008320Stationary SourceFuel CombustionWood Residential Woodstove: freestanding, EPA certified, non-catalytic116.06St. Louis City 2104008330Stationary SourceFuel CombustionWood Residential Woodstove: freestanding, EPA certified, catalytic29.04St. Louis City 2104008400Stationary SourceFuel CombustionWood Residential Woodstove: pellet-fired, general (freestanding or FP insert)14.17St. Louis City 2104008510Stationary SourceFuel CombustionWood Residential Furnace: Indoor, cordwood-fired, non-EPA certified141.36St. Louis City 2104008610Stationary SourceFuel CombustionWood Residential Hydronic heater: outdoor260.87St. Louis City 2104009000Stationary SourceFuel CombustionFirelog Residential Total: All Combustor Types53.50St. Louis City 2104011000Stationary SourceFuel CombustionKerosene Residential Total: All Heater Types0.45St. Louis City 2302002100Industrial ProcessesCommercial Cooking -CharbroilingFood and Kindred Products:SIC 20Conveyorized Charbroiling8.11St. Louis City 2302002200Industrial ProcessesCommercial Cooking -CharbroilingFood and Kindred Products:SIC 20Under-fired Charbroiling25.78St. Louis City 2302003000Industrial ProcessesCommercial Cooking -FryingFood and Kindred Products:SIC 20Deep Fat Fying-St. Louis City 2302003100Industrial ProcessesCommercial Cooking -FryingFood and Kindred Products:SIC 20Flat Griddle Frying2.16St. Louis City 2302003200Industrial ProcessesCommercial Cooking -FryingFood and Kindred Products:SIC 20Clamshell Griddle Frying-St. Louis City Total3,086.57St. Louis Nonclassifiable Maintenance Area Total11,839.28Page 27Table 8 Nonpoint Category Overview of MethodologySCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear21030*and21020*IndustrialandCommercialInstitutionalFuelCombustion16CAPYesEPA/CENRAPTemplateincludingenergyintensitypersectorNAICSHuntley200962006EIA'sSEDS120062401005000AutomobileRefinishing1VOCand5HAPSNoEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401015000WoodandFlatStock(FactoryFinishedWood)1VOCand6HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401020000WoodFurniture1VOConlyYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401025000MetalFurniture1VOCand6HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns22006Page 28SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2401030000PaperFilmFoil1VOCand6HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401040000MetalCans1VOCand6HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401045000MetalCoilOnly1VOCand6HAPsNoEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401050000MetalSheetStripandCoil1VOCand6HAPsYesEPATemplate‐emissionsbasedonemployment,HAPsnotincludedintemplatewerecreatedbyMODNRSolventDocumentation4Employmentfrom2006CountyBusinessPatterns22006Page 29SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2401055000MachineryandEquipment1VOCand6HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401060000Appliances1VOCand6HAPsNoEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401065000Electronicandotherspecialcoatings1VOCand6HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401070000MotorVehicles1VOCand6HAPsYesEPATemplate‐emissionsbasedonemployment,HAPsnotincludedintemplatewerecreatedbyMODNRSolventDocumentation4Employmentfrom2006CountyBusinessPatterns22006Page 30SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2401075000Aircraft1VOCand6HAPsYesEPATemplate‐emissionsbasedonemployment,HAPsnotincludedintemplatewerecreatedbyMODNRSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401085000Railroads1VOCand6HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062401080000MarineCoatings1VOCand6HAPsYesEPATemplate‐emissionsbasedonemployment,HAPsnotincludedintemplatewerecreatedbyMODNRSolventDocumentation4Employmentfrom2006CountyBusinessPatterns22006Page 31SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2401090000MiscManufacturing1VOCand6HAPsYesEPATemplate‐emissionsbasedonemployment,HAPsnotincludedintemplatewerecreatedbyMODNRSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062415000000Degreasing1VOCand1HAPYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062420000000DryCleaning1VOConlyNoEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns220062425000000GraphicArts1VOCand5HAPsYesEPATemplate‐emissionsbasedonemploymentSolventDocumentation4Employmentfrom2006CountyBusinessPatterns22006Page 32SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2401001000ArchitecturalCoatings1VOCand5HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082401008000TrafficPaints1VOCand4HAPsNoTemplate‐emissionsbasedon2006highwaymilesSolventDocumentation42006FHWAHPMS520062401100000IndustrialMaintenanceCoatings1VOCand6HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082401200000OtherSpecialPurposeCoatings1VOCand6HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082460100000PersonalCareProducts1VOCand2HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus32008Page 33SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2460200000CleaningProducts:household1VOCand2HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082460400000AutomotiveAftermarket1VOCand2HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082460500000CoatingsandRelatedProducts1VOCand2HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082460600000AdhesivesandSealants1VOCand2HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082460800000FIFRARegulatedProducts1VOCand2HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus32008Page 34SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2460900000MiscProducts1VOCand2HAPsNoTemplate‐populationbasedemissionsSolventDocumentation4PopulationfromUSCensus320082501050120BulkTerminal1VOCand8HAPsYesEPATemplate‐pointsourceemissionssubtractedbyNAICSandcountyNoemissionfactor,scaledup1998VOCemissionfromMACTanalysis8Scaled1998emissionsby2008DOE720082501055120BulkPlants1VOCand8HAPsYesEPATemplate‐pointsourceemissionssubtractedbyNAICSandcountyFromGasdistributionMACTstandards89%oftotalgasolineconsumptionfrom2008EIAPetroleumNavigator1020082505040120PetroleumPipeline1VOCand8HAPsNoEPATemplateNoemissionfactor,scaledup1998VOCemissionfromMACTanalysis8Scaled1998emissionsby2008DOE720082501060201GasolineStage1UndergroundStorageTanks1VOCand8HAPsNoEPATemplateEIIP200192008NMIMcounty‐levelonroadandnonroadestimates2008Page 35SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2505030120GasolineStage1TrucksinTransit1VOCand8HAPsNoEPATemplateEIIP200192008NMIMcounty‐levelonroadandnonroadestimates2008250106005*GasolineServiceStationLoading(submerg,splash,andbalancedfill)3VOCand8HAPsNoEPATemplateAP‐42Section5.2112008NMIMcounty‐levelonroadandnonroadestimates20082501060100GasolineDistribution:StageII1VOCand8HAPsNoEPATemplateAP‐42Section5.2112008NMIMcounty‐levelonroadandnonroadestimates200821040*ResidentialFuelCombustion(multiplefueltypes)16CAPsNoEPATemplatesandResidentialWoodCombustionTool25AP‐42EIA120062280002*MobileSources‐MarineVessels‐portandunderwayemissions2CAPNo2002estimatesadjustedfor2008activityEPA'sOfficeofTransportationandAirQuality(OTAQ)CAP,SEPAHAPspeciation13Regionalgrowthfactorforvesselactivity2002grownto2008Page 36SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2294000000and2296000000PavedandUnpavedRoads2PM10FIL/PRI,PM25FIL/PRINoAP‐42EquationwithstateorregionalconstantsAP‐42Section13.2.22007FHWAHighwayStatistics142007230200*CommericalCooking5CAPandHAPNoTemplate‐populationbasedemissions2002emissionsdividedbypopulationtocreatepercaptiafactorsPopulationfromUSCensus3200823110*ConstructionDust(residential,industrial/commercial,roadway)3PM10PRI,PM25PRINoResidentialactivitybycountyused,allocatenationalroadwaybyemploymentEPAdocumentationConstructionfromCensus15andhighwayconstructionFHWA142006forroadway,2008forresidentialandnon‐residentialconstruction,246102*Asphalt(cutbackandemulsified)2CAPandHAPNoNationalusageallocatedtocountybypavedroadVMTEIIP200117AsphaltInstitute’s2008AsphaltUsageSurvey20082501011*ResidentialPortableFuelContainer5VOCAndHAPNoLinearfitbetween2002and2010emissionestimatesEPA18NonroadactivityfromNMIM2002grownto2010withalinearfitto2008Page 37SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear2501012*CommercialPortableFuelContainer5VOCandHAPNoLinearfitbetween2002and2010emissionestimatesEPA18NonroadactivityfromNMIM2002grownto2010withalinearfitto20082501080*AviationPetroleumProductuse(Stage1and2)2VOCandHAPNoNationaluseallocatedbyregionsand2008landingandtake‐offactivityFourEPAdocumentsEIAPetroleumAnnualSupply,200819200826100*WasteDisposal‐OpenBurning4VOCandHAPNoPercapitaemissionsincludingcontrolsEPAdocumentation,EFbasedon2007reportEPAReport20andconstructionactivitySCC23110*20082630020000WasteDisposalPublicTreatment1VOCandNH3NoCalculatenationalemissions,allocatetocountiesbypopulationEPA23,24reportsEPAReport222004and2010figuresinterpolatedto20082801700*FertilizerApplication14NH3NoActivityusedinCMUAmmoniaModelCMUAmmoniaModel2002and2007activityfromtheFertilizerInstitute21grownto2008grown2008figurePage 38SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear28050*AnimalHusbandry(byanimalandmanuresystem)42NH3NoCMUAmmoniaModelCMUAmmoniaModel2007CensusofAgriculture1220071EIASEDS‐EnergyInformationAdministration‐StateEnergyDataSystemhttp://www.eia.doe.gov/emeu/states/_seds.html2EmploymentUSCensusBureauCountyBusinessPatternshttp://www.census.gov/epcd/cbp/download/06_data/index.html3PopulationfromUSCensushttp://factfinder.census.gov4SolventDocumentation,Table2andTable35FHWAHPMS‐FederalHighwayAdministrationHighwayPerformanceMonitoringSystemhttp://www.fhwa.dot.gov/policy/ohpi/hpms/index.cfm6Huntley,Roy2009,CriteriaPollutantEmissionFactorsforICICombustionAreaSourceCategories7DOE‐DepartmentofEnergyEnergyInformationAdministrationPetroleumSupplyAnnual2008,Volume1,Table28"GasolineDistributionIndustry(Stage1)‐BackgroundInformationforProposedStandards,"EPA‐453/R94‐002a,OAQPS,Jan1994and"GasolineDistributionIndustry(Stage1)‐BackgroundInformationforPromulgatedStandards,"EPA‐453/R94‐002b,OAQPS,Nov19949EIIP,EmissionInventoryImprovementProgram"VolumeIII:Chapter11,GasolineMarketing(StageIandStageII),RevisedFinal",Jan200110EIAEnergyInformationAdministrationPetroleumNavigator‐ProductSuppliedfromhttp://tonto.eia.doe.gov/dnav/pet/pet_cons_psup_dc_nus_mbblpd_a.htm11AP‐42Section5.2"TransportationandMarketingofPetroleumLiquids"122007CensusofAgriculture,USDepartmentofAgriculture,http://www.agcensus.usda.gov/13SEPA‐SwedishEnvironmentalProtectionAgencyreport2004‐02‐02http://westcoastcollaborative.org/files/sector‐marine/SMED%20Methodology%20for%20Calculating%20Emissions%20from%20Ships.pdf14FederalHighwayAdministration2007HighwayStatisticshttp://www.fhwa.dot.gov/policyinformation/statistics/2007/.15AnnualValueofConstructionhttp://www.census.gov/const/www/ototpage.html16AsphaltInstitute2008Surveyhttp://www.asphaltinstitute.org/.17EIIP,EmissionInventoryImprovementProgramVolumeIII–AreaSources,Chapter17,“AsphaltPaving,”2001Page 39SCCCategoryNameNumberofSCCsPollutantsIncludedPointSourceSubtractionCategorySubmittedbyMissouri‐CalculationMethodCategorySubmittedbyEPA‐CalculationMethodEmissionFactorSourceActivityforCategoryActivityBaseYear18EPADocumentEstimatingEmissionsfromPortableFuelContainers(PFCs)http://www.epa.gov/otaq/regs/toxics/420r07001.pdf19EIA2008PetroleumAnnualSupply,http://www.eia.doe.gov/oil_gas/petroleum/data_publications/petroleum_supply_annual/psa_volume1/psa_volume1.html20EPAMunicipalSolidWasteintheUnitedStates:2007FactsandFigures,EPA530‐R‐08‐010,http://www.epa.gov/epawaste/nonhaz/municipal/pubs/msw07‐rpt.pdf21AssnofAmericanPlantFoodControlOfficialswithTheFertilizerInstitute,CommercialFertilizers2002andCommercialFertilizers2007,http://www.aapfco.org/aapfcopubs.html22BiosolidsGeneration,Use,andDisposalintheUnitedStates,TableA‐8EPA530‐R‐99‐009,September199923EPAEIIPEmissionInventoryImprovementProgram,April2004,EstimatingAmmoniaEmissionsfromAnthropogenicNonagriculturalSources–DraftFinalReport24VOCEmissionsfromWastewaterTreatmentPlants:Characterization,Control,andCompliance,LewisPublishers,2003,p.26125ResidentialWoodCombustionTool,http://www.epa.gov/ttn/chief/net/2008inventory.html

### Page 40 3.2.3 Source Category Documentation

The following documentation covers nonpoint categorie s that were prepared with guidance from

EPA and CENRAP. The documentation files incl ude methodologies to be applied nationally, and include Missouri-specifi c updates and information.

3.2.3.1 Fossil Fuel Combustion – Residential – Coal Combustion

a. Source Category Description

Residential Coal Combustion is coal that is burned to heat residential housing.

The general approach to calcula ting emissions for these two SCCs is to take State Coal Consumption from the EIA and allocate it to th e county level using met hods described below. County-level coal consumption is multiplied by the emission factors to calculate emissions.

For this source category, the following SCCs were assigned:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2104001000 Stationary Source
Fuel Combustion Residential Anthracite Coal All Boiler Types

2104002000 Stationary Source
Fuel Combustion Residential Bituminous/
Subbituminous Coal All Boiler Types



### b. Activity Data

The mass of coal consumed by residential co mbustion in the U.S. was used to estimate emissions. Coal consumption by energy use se ctor is presented in State Energy Data 2006 Consumption tables published by the En ergy Information Administration (EIA). 1 

### Year 2006 consumption data were used as a surrogate fo r 2008 emissions because year 2006 data were the latest data available when this inventory was prepared.

EIA data do not distinguish betw een anthracite and bituminous coal consumption estimates. The

EIA table “Domestic Distribution of U.S. Coal by Destination State, Consumer, Origin and Method of Transportation,” provide s state-level residen tial coal distribution data for 2006 that

was used to estimate anthracite and bituminous coal consumption. The amount of anthracite

distributed to each state and the total coal deliv ered to each state were used to estimate the proportion of anthracite and bituminous coal consumption. 2 

### The 2006 ratio of anthracite (and bituminous) coal consumption to total coal cons umption was used to distribute the EIA’s total residential sector coal consump tion data by coal type. Table 1 presents the 2006 anthracite and

bituminous coal ratios for each state.

State-level coal consumption was allocated to each county using the US Census Bureau’s 2000 Census Detailed Housing Information. 3 

### These data include the number of housing units using a specific type of fuel for reside ntial heating. Stat e coal consumption was allocated to each county using the ratio of the number of houses burning coal in each count y to the total number of houses burning coal in the State.

### Page 41 c. Control Factors

No controls were assumed for this category

d. Emission Factors

CO emissions were calculated by multiplying the total coal consumed in each county per year by

an emission factor. The emi ssion factor is from AP-42. 5 

### Table 2 presents the CO emission

factors for residential anthra cite coal combustion (SCC 2104001000) and residential bituminous coal combustion (SCC 2104002000).

e. Sample Calculations

Annual emissions are calculated for each c ounty using emission factors and activity as:

E x,p 

### = FC

x 

### × (1 - CE x,p 

### ) × EF x,p



### where:

E x,p 

### = annual emissions for fuel type x and pollutant p (ton/year),

FC

x 

### = annual fuel consumption for fuel type x,

CE x,p 

### = control efficiency for fuel type x and pollutant p, and

EF x,p 

### = emission factor for fuel type x and pollutant p.

County level fuel consumpti on is calculated using:

FC

x 

### = A State 

### x Ratio Anth, Bit 

### x Ratio County houses



### where:

A State 

### = total tons of coal reported by the EIA,

Ratio Anth, Bit 

### = ratio reported in Table 1, and

Ratio County houses 

### = county allocation ratio based on number of houses burning coal.

Example: Using Allegheny County, PA as an example:

The State of Pennsylvania had a reported use of 49,935 tons of coal in the residential sector in

2006.

Statewide Anthracite coal use is calculated using the ratio of Anth racite to Bituminous in Table 1 for PA: 80.64%. Allegheny County, PA had 183 houses out of the state to tal of 67,986 that use coal as the primary heating fuel. This equates to a share of 0.27% of the co al used for residential heating in the state.

The emission factor for PM 2.5 

### -PRI (See Table 4) is 0.6 × stat e-specific % ash content + 0.08 lbs/ton× state-specific % ash c ontent. The ash cont ent is 13.38%, (See Table 2) so the emission

factor is 9.09 lbs/ton.

### Page 42 FC Allegheny, anth 

### = 49,935 × 0.8064 × 0.0027 = 109 tons anthracite coal

Emis Allegheny, anth, PM2.5-PRI 

### = 109 tons Coal × 9.09 lbs PM 2.5 

### -PRI per ton coal

= 990 lbs PM 2.5 

### -PRI

f. References

1. U.S. Department of Energy, Energy Inform ation Administration (EIA). State Energy Data 2006 Consumption. Washington, DC 2008. Internet Address: http://www.eia.doe.gov/emeu/states/se p_use/total/csv/use_a ll_phy.csv accessed

November 2008.

2. EIA, 2008. U.S. Department of Energy, En ergy Information Administration, “Domestic Distribution of U.S. Coal by Destination State, Consumer, Origin and Method of Transportation”, 2006. Available from: http://www.eia.doe.gov/cneaf/coal/page/coald istrib/coal_distribu tions.html, accessed

December 2008.

3. U.S. Census Bureau. "Table H40. House Heating Fuel Type", Census 2000: Summary

File 3. Internet address: http://factfinder.census.gov/servlet/Data setMainPageServlet?_program=DEC&_submenu Id=&_lang=en&_ts=, accessed July 2009.

4. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Final Summary of the Development and Results of a Methodology for Calculating Area Source

Emissions from Residential Fuel Combus tion. Prepared by Pacific Environmental Services, Inc. Research Triangle Park, NC . September 2002. Internet address: http://www.epa.gov/ttn/chief/eiip /techreport/volume03/draft1999_ residfuel_inven_apr2003.zip accessed November 2004.

5. U.S. Environmental Protection Agency. Co mpilation of Air Pollutant Emission Factors, 5th Edition, AP-42, Volume I: Stationary Point and Area Sources. Research Triangle Park, North Carolina. 1996.

6. U.S. Environmental Protection Agency. Emission Inventory Improvement Program. Estimating Ammonia Emissions from Anthr opogenic Sources, Draft Final Report. Prepared by E.H. Pechan and Associates, Inc. Research Triangle Park, NC. April 2004.

### Page 43 Table 1. 2006 Anthracite and Bi tuminous Coal Distribution for the
Residential and Commercial Sectors

State Ratio of

Bituminous Ratio of

Anthracite State Ratio of

Bituminous Ratio of

Anthracite

Alabama 1.0000 0.0000 Montana 1.0000 0.0000

Alaska 1.0000 0.0000 Nebraska 1.0000 0.0000

Arizona 0.8140 0.1860 Nevada 1.0000 0.0000

Arkansas 0.8140 0.1860 New Hampshire 0.0000 1.0000
California 1.0000 0.0000 New Jersey 0.0000 1.0000

Colorado 0.9962 0.0038 New Mexico 1.0000 0.0000

Connecticut 0.0000 1.0000 New York 0.6000 0.4000

Delaware 0.8140 0.1860 North

Carolina 1.0000 0.0000

Dist.

Columbia 1.0000 0.0000 North Dakota 1.0000 0.0000

Florida 0.8140 0.1860 Ohio 0.8727 0.1273
Georgia 1.0000 0.0000 Oklahoma 0.9167 0.0833
Hawaii 1.0000 0.0000 Oregon 1.0000 0.0000
Idaho 0.9792 0.0208 Pennsylvania 0.1936 0.8064

Illinois 0.9981 0.0019 Rhode Island 0.0000 1.0000

Indiana 0.9474 0.0526 South

Carolina 0.9972 0.0028

Iowa 0.9992 0.0008 South Dakota 1.0000 0.0000

Kansas 1.0000 0.0000 Tennessee 0.9939 0.0061
Kentucky 0.9981 0.0019 Texas 0.8140 0.1860

Louisiana 1.0000 0.0000 Utah 1.0000 0.0000

Maine 0.0000 1.0000 Vermont 0.0000 1.0000
Maryland 0.9286 0.0714 Virginia 0.9630 0.0370
Massachusetts 0.5000 0.5000 Washington 1.0000 0.0000
Michigan 0.6667 0.3333 West Virginia 0.9048 0.0952

Minnesota 0.9973 0.0027 Wisconsin 0.9914 0.0086
Mississippi 1.0000 0.0000 Wyoming 1.0000 0.0000

Missouri 1.0000 0.0000



### Table 2. CO Emission Factor for Resi dential Anthracite Coal Combustion (SCC 2104001000) and Residential Bituminous Coal Combustion (SCC 2104002000): Not Adjusted for Point Source Fuel Consumption

SCC Pollutant

Code Pollutant Code Description Factor

Numeric

Value Factor

Unit

Numerator Factor Unit

Denominator

2104001000 CO CARBON MONOXIDE 275 LB TON

2104002000 CO CARBON MONOXIDE 275 LB TON

### Page 44 3.2.3.2 Fossil Fuel Combustion – Residential – Distillate Oil

a. Source Category Description

Residential Distillate Oil Combus tion is oil that is burned in residential housing

The general approach to calcula ting emissions for this SCC is to take State Distillate Oil Consumption from the EIA and allocate it out to the county level using methods described below. County-level oil consumption is mu ltiplied by the emission factors to calculate

emissions.

For this source category, the following SCCs were assigned:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2104004000 Stationary Source
Fuel Combustion Residential Distillate Oil Total Boilers and IC Engines



### b. Activity Data

The state-level volume of distillate oil consumed by residential combustion in the U.S. was used to estimate emissions. Distillate oil consump tion by energy use sector is presented in State Energy Data 2006 Consumption tables published by the Energy Information Administration (EIA). 1 

### Year 2006 consumption data were used as a surrogate for 2008 emissions because year

2006 data were the latest data availabl e when this invent ory was prepared.

State-level distillate oil consumption was alloca ted to each county using the US Census Bureau’s 2000 Census Detailed Housing Information. 2 

### These data include the number of housing units using a specific type of fuel for residential hea ting. State distillate oil consumption was allocated to each county using the ratio of the number of h ouses burning distillate oil in each county to the total number of houses burning di stillate oil in the State.

c. Control Factors

No control measures are assumed for this category.

d. Emission Factors

The CO emission factor for di stillate oil is from AP-42. 3 

### For all counties in the United States, the distillate oil consumed by commercial/institu tional combustion is assumed to be No. 2 fuel oil with a heating valu e of 140,000 Btu per gallon.

e. Sample Calculations

Emissions are calculated for each county using emission factors and activity as:

E x,p 

### = FC

x 

### × EF x,p

### Page 45 where:

E x,p 

### = annual emissions for fuel type x and pollutant p

FC

x 

### = annual fuel consumption for fuel type x

EF x,p 

### = emission factor for fuel type x and pollutant p

And FC

x 

### = A State 

### x (H county 

### / H State 

### )

where :

A State 

### = State activity data from EIA

H County 

### = number of houses in the county using dist illate oil as the primary heating fuel

H State 

### = number of houses in the state using di stillate oil as the primary heating fuel

Example: Using Allegheny County, PA as an example:

The State of Pennsylvania had a reported use of 16,902 thousand barrels of distillate oil in the

residential sector in 2006. Allegheny County, PA had 8,123 houses out of the state total of 1,217,155 that use distillate oil as the primary heati ng fuel. This equates to a share of 0.67% of the distillate oil used for residential heating in the state. From Table 5, the emission factor for CO is 5 lb/thousand gallons. Because the em ission factor is in lbs/thousand gallons, a conversion factor of 42 gall ons per barrel is applied.

A Alegheny 

### = 16,902 thousand barrels × 8,123 houses / 1,217,155 houses) × 42 gal / barrel = 4,737.6 thousand gallons

Emis Alegheny, CO 

### = = 4,737.6 thousand gallons × 5 lb CO/ thousand gallons = 23,688 lbs CO or 11.8 tons CO

f. References

1. U.S. Department of Energy, Energy Inform ation Administration (EIA). State Energy Data 2006 Consumption. Washington, DC 2008. Internet Address: http://www.eia.doe.gov/emeu/states/se p_use/total/csv/use_a ll_phy.csv, accessed

November 2008.

2. U.S. Census Bureau. "Table H40. House Heating Fuel Type", Census 2000: Summary

File 3. Internet address: http://factfinder.census.gov/servlet/Data setMainPageServlet?_program=DEC&_submenu Id=&_lang=en&_ts=, accessed July 2009.

3. U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission Factors, 5th Edition, AP-42, Volume I: Stationary Point and Area Sources. Research Triangle Park, North Carolina. 1996.

### Page 46 4. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Final Summary of the Development and Results of a Methodology for Calculating

Area Source Emissions from Residential Fuel Combustion. Prepared by Pacific Environmental Services, Inc. Research Triangle Park, NC. September 2002. Internet address: http://www.epa.gov/ttn /chief/eiip/techrepo rt/volume03/draft1999_ residfuel_inven_apr2003.zip accessed November 2004.

5. U.S. Environmental Protection Agency, Office of Air Quality Planning and

Standards. “Documentation of Emissi ons Estimation methods for Year 2000 and 2001 Mobile Source and Nonpoint Source Diox in Inventories.” Prepared by E.H. Pechan & Associates, Inc., Durham, NC. May 2003.

6. U.S. Environmental Protection Agenc y, Emission Factors and Inventory Group.

“Documentation for the 1999 Base Year Nonpoint Area Source National Emission Inventory for Hazardous Air Pollutants.” Pr epared by Eastern Research Group, Inc. Morrisville, NC. September 2002.

7. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Final Summary of the Development and Results of a Methodology for Calculating

Area Source Emissions from Residential Fuel Combustion. Prepared by Pacific Environmental Services, Inc. Research Triangle Park, NC. September 2002. Internet address: http://www.epa.gov/ttn /chief/eiip/techrepo rt/volume03/draft1999_ residfuel_inven_apr2003.zip accessed November 2004.

8. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Estimating Ammonia Emissions from Anthropoge nic Sources, Draft Report. Prepared by E.H. Pechan and Associates, Inc. Research Triangle Park, NC. September 2003.

Table 1. National Emission Factors for Residential Distillate Oil Combustion

Code Pollutant Emission

Factor Emission Factor

Numerator Emission Factor

Denominator

CO Carbon Monoxide 5 LB E3GAL

3.2.3.3 Fossil Fuel Combustion – Residential - Kerosene

a. Source Category Description

Residential Kerosene Combustion is kerosene that is burned in residential housing. Common uses of energy associated with this sector include space heating, water heating, cooking, and running a wide variety of other equipment.

### Page 47 The general approach to calcu lating emissions for this SCC is to take State Kerosene Consumption from the EIA and allocate it to th e county level using met hods described below. County-level kerosene consumption is multiplied by the emission factors to calculate emissions.

For this source category, the following SCC was assigned:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2104011000 Stationary Source
Fuel Combustion Residential Kerosene Tota l: All Combustor Types



### b. Activity Data

The volume of kerosene consumed by residentia l combustion in the U.S. was used to estimate emissions. Kerosene consumption by energy use sector is presented in State Energy Data 2006 Consumption tables published by the En ergy Information Administration (EIA). 1 

### Year 2006 consumption data were used as a surrogate fo r 2008 emissions because year 2006 data were the latest data available when this inventory was prepared.

State-level kerosene consumption was allocated to each county using the US Census Bureau’s 2000 Census Detailed Housing Information. 2 

### These data include the number of housing units using a specific type of fuel for residential he ating. State kerosene cons umption was allocated to each county using the ratio of the number of hou ses burning kerosene in each county to the total number of houses burning kerosene in the State.

c. Control Factors

No control measures are assumed for this category.

d. Emission Factors

Emission factors for distill ate oil were used for kerosene, but the distillate oil emission factors were multiplied by a factor of 135/140 to convert them for this use. This factor is based on the

ratio of the heat content of ke rosene (135,000 Btu/gallon) to the heat content of distillate oil (140,000 Btu/gallon). 3 

### The CO emission factor is from AP-42. 4



### e. Sample Calculations

Emissions are calculated for each county using emission factors and activity as:

E x,p 

### = FC

x 

### × EF x,p



### where:

E x,p 

### = annual emissions for fuel type x and pollutant p,

FC

x 

### = annual fuel consumption for fuel type x,

EF x,p 

### = emission factor for fuel type x and pollutant p,

And FC

x 

### = A State 

### x (H county 

### / H State 

### )

### Page 48 where :

A State 

### = State activity data from EIA

H County 

### = number of houses in the county using kerosene as the primary heating fuel

H State 

### = number of houses in the state using kerosene as the primary heating fuel

Example: Using Allegheny County, PA as an example:

The State of Pennsylvania had a reported use of 1,419.7 thousand barrels of kerosene in the

residential sector in 2006. Allegheny County, PA had 8,123 houses out of the state total of 1,217,155 that used kerosene as the primary heating fuel. This equates to a share of 0.67% of the kerosene used for residential heating in the st ate. From Table 1, CO Emission factor is 202.5

lb/thousand barrels.

E CO 

### = 1,419.7 thousand barrels × ( 8,123 houses / 1,217,155 houses)

× 202.5 lb/thousand barrels = 1,918.6 lbs CO or 0.96 tons CO

f. References

1. U.S. Department of Energy, Energy Inform ation Administration (EIA). State Energy Data 2006 Consumption. Washington, DC 2008. Internet address: http://www.eia.doe.gov/emeu/states/sep_use/to tal/csv/use_all_phy.csv, accessed November

2008.

2. U.S. Census Bureau. "Table H40. House Heating Fuel Type", Census 2000: Summary

File 3. Internet address: http://factfinder.census.gov/servlet/DatasetM ainPageServlet?_program=DEC&_submenuId=&_l ang=en&_ts=, accessed July 2009.

3. U.S. Environmental Protection Agency. Co mpilation of Air Pollutant Emission Factors, 5th Edition, AP-42, Volume I: Stationary Poin t and Area Sources. Rese arch Triangle Park,

North Carolina. 1996.

4. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Final Summary of the Development and Results of a Methodology for Calculating Area Source Emissions from Residential Fuel Combustion. Prep ared by Pacific Environm ental Services, Inc. Research Triangle Park, NC. Sept ember 2002. Internet address: http://www.epa.gov/ttn/chief/eiip/techreport/v olume03/draft1999_ residfuel_inven_apr2003.zip

accessed November 2004.

5. U.S. Environmental Protection Agency, Offi ce of Air Quality Planning and Standards.

“Documentation of Emissions Estimation methods for Year 2000 and 2001 Mobile Source and Nonpoint Source Dioxin Inventorie s.” Prepared by E.H. Pechan & Associates, Inc., Durham, NC. May 2003.

### Page 49 6. U.S. Environmental Protection Agenc y, Emission Factors and Inventory Group. “Documentation for the 1999 Base Year Nonpoint Area Source National Emission Inventory for Hazardous Air Pollutants.” Prepared by Easter n Research Group, Inc. Morrisville, NC. September 2002.

7. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Final Summary of the Development and Results of a Methodology for Calculating Area Source Emissions from Residential Fuel Combustion. Prep ared by Pacific Environm ental Services, Inc. Research Triangle Park, NC. Sept ember 2002. Internet address: http://www.epa.gov/ttn/chief/eiip/techreport/v olume03/draft1999_ residfuel_inven_apr2003.zip,

accessed November 2004.

Table 1. National Emission Factors for Residential Kerosene Combustion

Pollutant

Code Pollutant Code Description Factor

Numeric

Value Factor

Unit

Numerator Factor Unit

Denominator

CO CARBON MONOXIDE 202.5 LB E3BBL



### 3.2.3.4 Fossil Fuel Combustion – Residential – Natural Gas

a. Source Category Description

Residential Natural Gas Combustion is natural gas th at is burned to heat residential housing as well as in grills, hot water heaters, and dryers.

The general approach to calcula ting emissions for this SCC is to take State Natural Gas Consumption from the EIA and allocate it to the county level using the methods described below. County level natural gas consumption is multiplied by the emission factors to calculate

emissions.

For this source category, the following SCC was assigned:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2104006000 Stationary Source
Fuel Combustion Residential Natural Gas Total: Boilers and IC Engines



### b. Activity Data

The state-level volume of natural gas consumed by residential combustion in the United States was used to estimate emissions. Natural gas consumption by energy use sector was obtained from the State Energy Data 2006 Consumption tables published by the EIA. 1 

### Year 2006

### Page 50 consumption data were used as a surrogate for 2 008 emissions because these data were the latest data available when this inventory was prepared.

State-level natural gas consumption was allocate d to each county using the US Census Bureau’s 2000 Census Detailed Housing Information. 2 

### These data include the number of housing units using a specific type of fuel for residential he ating. State natural gas c onsumption was allocated to each county using the ratio of the number of houses burning natural gas in each county to the total number of houses burning na tural gas in the State.

c. Control Factors

No control measures are assumed for this category.

d. Emission Factors

The CO emission factor for natural gas is from AP-42. 3 

### According to AP-42 (maximum value provided) 2 

### , natural gas has a heat content of 1,050 million BTU per million cubic feet. This value was required to convert those emission factors originally given in units “pounds per million Btu” to units “pounds per million cubic feet .” Some emission factors were revised based on recommendations by an ERTAC advisory pa nel composed of state and EPA personnel.

County-level CO emissions were calculated by multiplying the total natural gas consumed in each county per year by an emission factor. Ta ble 1 provides a summary of the CO emissions

factor for residential co mbustion of natural gas.

e. Sample Calculations

Emissions are calculated for each county using emission factors and activity as:

E x,p 

### = FC

x 

### × EF x,p



### where:

E x,p 

### = annual emissions for fuel type x and pollutant p,

FC

x 

### = annual fuel consumption for fuel type x,

EF x,p 

### = emission factor for fuel type x and pollutant p,

And FC

x 

### = A State 

### x (H county 

### / H State 

### )

where :

A State 

### = State activity data from EIA

H County 

### = number of houses in the county using na tural gas as the primary heating fuel

H State 

### = number of houses in the state using natural gas as the primary heating fuel

Example: Using Allegheny County, PA as an example:

### Page 51 The State of Pennsylvania had a reported use of 205,812 million cubic feet of natural gas in the

residential sector in 2006. Allegheny County, PA had 474,292 houses out of the state total of 2,452,941 that use natural gas as the primary heating fuel. This equa tes to a share of 19.34% of the natural gas used for residential heating in th e state. From Table 1, CO emission factor is 40

lb/million ft 3



### .

E CO 

### = 205,812 million ft 3 

### × (474,292 houses / 2,452,941 houses) × 40 lb CO/ million ft 3



### = 1,591,803 lb CO or 795.9 ton CO

f. References

1. U.S. Department of Energy, Energy Inform ation Administration (EIA). State Energy Data 2006 Consumption. Washington, DC 2008. Internet address: http://www.eia.doe.gov/emeu/states/sep_use/to tal/csv/use_all_phy.csv, accessed November

2008.

2. U.S. Census Bureau. "Table H40. House Heating Fuel Type", Census 2000: Summary

File 3. Internet address: http://factfinder.census.gov/servlet/DatasetM ainPageServlet?_program=DEC&_submenuId=&_l ang=en&_ts=, accessed July 2009.

3. U.S. Environmental Protection Agency. Co mpilation of Air Pollutant Emission Factors, 5th Edition, AP-42, Volume I: Stationary Poin t and Area Sources. Rese arch Triangle Park,

North Carolina. 1996.

4. U.S. Environmental Protection Agency. Emission Inventory Improvement Program. Estimating Ammonia Emissions from Anthropogenic Sources, Draft Final Report. Prepared by E.H. Pechan and Associates, Inc. Research Triangle Park, NC. April 2004.

5. U.S. Environmental Protection Agenc y, Emission Factors and Inventory Group. “Documentation for the 1999 Base Year Nonpoint Area Source National Emission Inventory for Hazardous Air Pollutants.” Prepared by Easter n Research Group, Inc. Morrisville, NC. September 2002.

6. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Final Summary of the Development and Results of a Methodology for Calculating Area Source Emissions from Residential Fuel Combustion. Prep ared by Pacific Environmental Services, Inc. Research Triangle Park, NC. Sept ember 2002. Internet address: http://www.epa.gov/ttn/chief/eiip/techreport/v olume03/draft1999_ residfuel_inven_apr2003.zip,

accessed November 2004.

### Page 52 Table 1. National Criteria Pollutant and HAP Emission Factors for Residential
Natural Gas Combustion

Pollutant

Code Pollutant Code Description Factor

Numeric

Value Factor Unit

Numerator Factor Unit

Denominator

CO CARBON MONOXIDE 40 LB E6FT3



### 3.2.3.5 Commercial Cooking

a. Source Category Description Commercial Cooking emissions are for 5 source categories based on equipment type. Emissions estimates are for all types of meat cooked in a pa rticular piece of equipment. Deep fat frying of

french fries was also included.

For this source category, the following SCCs were assigned:

Source

Classification Code SCC Level One SCC Level Two SCC Level Three SCC Level Four

2302002100 Industrial

Processes Food and Kindred

Products: SIC 20 Commercial Cooking ‐ Charbroiling Conveyorized
Charbroiling

2302002200 Industrial

Processes Food and Kindred

Products: SIC 20 Commercial Cooking ‐ Charbroiling Under

‐ fired
Charbroiling

2302003000 Industrial

Processes Food and Kindred

Products: SIC 20 Commercial Cooking ‐ Frying Deep Fat Frying

2302003100 Industrial

Processes Food and Kindred

Products: SIC 20 Commercial Cooking ‐ Frying Flat Griddle Frying

2302003200 Industrial

Processes Food and Kindred

Products: SIC 20 Commercial Cooking ‐ Frying Clamshell Griddle
Frying



### b. Activity Data

Activity data was collected from the US Census Bureau’s county level population estimates for July 1, 2008. 1



### c. Control Factors

No controls were assumed for this category.

d. Emission Factors

Emission factors were developed and reviewed by an ERTAC advisory panel composed of state and EPA personnel (Contact: R oy Huntley, huntley.roy@epa.gov). They were created by taking 2002 emissions in the NEI and dividing by the 2002 population to develo p per capita emission

factors. These emission factors are listed in Table 1.

### Page 53 e. Sample Calculations

Emissions are calculated for each county using emission factors and activity as:

E x,p 

### = A

x 

### × EF x,p



### where:

E x,p 

### = annual emissions for category x and pollutant p;

A

x 

### = population data associ ated with category x;

EF x,p 

### = emission factor for cat egory x and pollutant p.

Example: Using conveyorized charbr oiling in Allegheny County, PA as an example:

According to the US Census Bur eau, population on July 1, 2008 is 1,215,103 The emission factor for VOC is 0.01205 lb/person

E VOC 

### = 1,215,103 people × 0.01205 lb VOC/ person

= 14,650 lb VOC or 7.3 ton VOC

f. References

1. DOC, 2008: U.S. Department of Co mmerce, Bureau of the Census, 2008 Population Estimates Program GCT-T1: Population Estimates , Washington, DC.

Table 1: Commercial Cooking Emissi on Factors Developed by ERTAC

SCC SCC description Pollutant

Code Factor

Numeric

Value Factor Unit

Numerator Factor Unit

Denominator

2302002100 Conveyorized Charbroiling CO 4.245E

‐ 02 LB EACH

2302002200 Under

‐ fired Charbroiling CO 1.350E

‐ 01 LB EACH

2302003000 Deep Fat Flying CO 0.000E+00 LB EACH

2302003100 Flat Griddle Frying CO 1.269E

‐ 02 LB EACH

2302003200 Clamshell Griddle Frying CO 0.000E+00 LB EACH



### 3.2.3.6 Open Burning – Land Clearing Debris

a. Source Category Description

Open burning of land clearing debris is the purposeful bur ning of debris, such as trees, shrubs, and brush, from the clearing of land for the cons truction of new buildings and highways. CO emission estimates from open burning of land clea ring debris are a functi on of the amount of material or fuel subject to burning per year.

### Page 54 For this source category, the following SCC was assigned:

SCC SCC Level 1 SCC Level 2 SCC Level 3 SCC Level 4 2610000500 Waste Disposal, Treatment, and Recovery Open Burning All Categories Land Clearing Debris (use 28-10-005-000 for Logging Debris Burning) 

### b. Activity Data

The amount of material burned was estimated using the county-level to tal number of acres disturbed by residential, non-residential, and road construc tion. County-level weighted loading factors were applied to the total number of construction acres to conve rt acres to tons of available

fuel.

Acres Disturbed from Residential Construction

The US Census Bureau has 2008 data for Housing Starts - New Priv ately Owned Housing Units
Started 1 

### which provides regional level housing starts ba sed on the groupings of 1 unit, 2-4 units,
5 or more units. A consultation with the Ce nsus Bureau in 2002 gave a breakdown of approximately 1/3 of the housing starts being for 2 unit structures, and 2/3 being for 3 and 4 unit structures. The 2-4 unit category was divided into 2-units, and 3- 4 units based on this ratio. To determine the number of structures for each gr ouping, the 1 unit category was divided by 1, the 2 unit category was divided by 2, and the 3-4 unit ca tegory was divided by 3.5. The 5 or more unit category may be made up of more than one structure. New Privately Owned Housing Units Authorized Unadjusted Units 2 

### gives a conversion factor to dete rmine the ratio of structures to
units in the 5 or more unit ca tegory. For example if a county has one 40 unit apartment building,

the ratio would be 40/1. If there are 5 different 8 unit buildings in the same project, the ratio

would be 40/5. Structures started by category are then calculated at a regional level. The table Annual Housing Units Authorized by Building Permit 3 

### has 2007 data at the county level to allocate regional housing starts to the county level. This results in county level housing starts by number of units. The following surface area s were assumed disturbed for each unit type:

Table 1: Surface Acres Disturbed per Unit Type

1-Unit 1/4 acre/structure

2-Unit 1/3 acre/structure

A p artment 1/2 acre/structure

The 3-4 unit and 5 or more unit categories were c onsidered to be apartments. Multiplication of housing starts to surface acres disturbed results in total number of acres disturbed for each unit
category.

Acres Disturbed from Non- Residential Construction

Annual Value of Construction Put in Place in the U.S 4 

### has the 2008 National Value of Nonresidential construction. The national value of non-residential construction put in place (in millions of dollars) was alloca ted to counties using county-le vel non-residential construction (NAICS Code 2362) employm ent data obtained from County Business Patterns 5 

### (CBP) . Because some counties employment data was withheld du e to privacy concerns, the following procedure was adopted:

### Page 55 1. State totals for the known county level employ ees were subtracted from the number of employees reported in the state level version of CBP. This results in the total number of withheld employees in the state.

2. A starting guess of the midpoint of the range code was used (so for instance in the 1-19 employees range, a guess of 10 employees w ould be used) and a state total of the withheld counties was computed.

3. A ratio of guessed employees (Step 2) to with held employees (Step 1) was then used to adjust the county level guesses up or down so the state total of adjusted guesses should match state total of withheld employees (Step 1)

In 1999 a figure of 2 acres/$10 6 

### was developed. The Bur eau of Labor Statistics Producer Price

Index 6 

### lists costs of the constr uction industry from 1999-2007.

2007 acres per $10 6 

### = 1999 acres per $10 6 

### x (1999 PPI / 2007 PPI) = 2 acres/$10 6 

### (132.9 / 204.3) = 1.301 acres per $10 6



### Acres Disturbed by Road Construction

The Federal Highway Administration has Highway Statistics, Secti on IV - Highway Finance, Table SF-12A, State Highway Agency Capital Outlay 7 

### for 2006 which outlines spending by state in several different categories. For this SCC, the following columns are used: New Construction, Relocation, Added Capacity, Major Widening, a nd Minor Widening. These columns are also differentiated according to the following six classifications:

1. Interstate, urban 2. Interstate, rural 3. Other arterial, urban 4. Other arterial, rural 5. Collectors, urban 6. Collectors, rural

The state expenditure data are then converted to new miles of road constructed using $/mile

conversions obtained from the North Carolina Department of Transportation (NCDOT) in 2000. A conversion of $4 million/mile was applied to th e interstate expenditures. For expenditures on other arterial and collectors, a conversion factor of $1.9 million/mile was applied, which corresponds to all other projects.

The new miles of road constructed are used to estimate the acreage disturbed due to road

construction. The total area disturbed in each state was calculated by converting the new miles

of road constructed to acres usi ng an acres disturbed/mile conversi on factor for each road type as given in Table 2 below:

### Page 56 Table 2: Spending per Mile and Acres Disturbed per Mile by Highway Type

Road T yp e Thousand Dollars per
mile Acres Disturbed per
mile

Urban Areas, Interstate 4000 15.2

Rural Areas, Interstate 4000 15.2

Urban Areas, Other Arterials 1900 15.2

Rural Areas, Other Arterials 1900 12.7

Urban Areas, Collectors 1900 9.8

Rural Areas, Collectors 1900 7.9

Residential building starts are used to allocate the state-level acres dist urbed by road construction to the county. 3 

### A ratio of the number of building starts in each count y to the total number of building starts in each state was applied to the state-level acres disturbed to estimate the total number of acres disturbed by road construction in each county.

Converting Acres Disturbed to Tons of Land Clearing Debris Burned

Version 2 of the Biogenic Emissions Land cove r Database (BELD2) within EPA’s Biogenic Emission Inventory System (BEIS) was used to identify the acres of hardwoods, softwoods, and grasses in each county. Table 3 presents the average fuel load ing factors by vegetation type. The average loading factors for slash hardwood a nd slash softwood were ad justed by a factor of

1.5 to account for the mass of tree that is below the soil surface that would be subject to burning

once the land is cleared. 8 

### Weighted average county-level loading factors were calculated by multiplying the average loading factors by the percent contribution of each type of vegetation

class to the total land area for each county.

Table 3. Fuel Loading Fa ctors by Vegetation Type

Vegetation Type Unadjusted Average Fuel Loading Factor (Ton/acre) Adjusted Average Fuel Loading

Factor (Ton/acre)

Hardwood 66 99

Softwood 38 57

Grass 4.5 Not Applicable

The total acres disturbed by all construction type s was calculated by summing the acres disturbed from residential, non-residentia l, and road construction. The c ounty-level total acres disturbed were then multiplied by the weighted average load ing factor to derive tons of land clearing
debris in 2008.
c. Controls

### Page 57 Controls for land clearing debris burning are generally in the form of a ban on open burning of waste in a given municipality or county. Countie s that were more than 80% urban were assumed not to practice any open burning. Therefore, CO emissions from open burning of land clearing

debris are zero in these counties. In addition, the State of Co lorado implemented a state-wide ban on open burning. Emissions from open burni ng of land clearing debris in all Colorado

counties were assumed to be zero.

d. Emission Factors

Emission factors are reported in Table 4 below. The emission f actor for CO was developed by the U.S. Environmental Protection Agency (EPA ) in consultation with the Eastern Regional Technical Advisory Committee and ba sed primarily on the AP-42 report. 9,10



### e. Emissions

County-level CO emissions (in lb/year) were calculated by multiplying the total mass of land clearing debris burned per ye ar by an emission factor.

f. Example Calculations

VOC emissions in Autauga County, Alabama from open burning of land clearing debris:

Rural fraction of Autauga County populat ion = 0.448, so no emission controls

Acres disturbed by residential, non-residential, and road construction in Autauga County

= 434.26 Weighted average fuel loading fact or for Autauga County = 65.48 tons/acre

Mass of land clearing debris burned = 434.26 acres * 65.48 tons/acre = 28,437 tons

VOC emission factor = 11.6 lbs/ton

Factor to convert from lbs to tons = 1/2000

VOC emissions = tons of land clearing debris burned * VOC emission factor

VOC emissions from land clearing debris burning = 28,437 tons * 11.6 lbs/ton *
1 ton/2000 lbs

VOC emissions from land clearing debris bu rning in Autauga County in 2008 = 165 tons

g. References

1. U.S. Census Bureau, “New Privately Owned Housing Units Started for 2008 ( Not seasonally adjusted),” available at http://www.census.gov/const/startsua.pdf

2. U.S. Census Bureau, “Table 2au. New Pr ivately Owned Housing Units Authorized Unadjusted Units for Regions, Divisions, and States, Annual 2007” available at http://www.census.gov/const/C40/Table2/tb2u2007.txt

### Page 58 3. Annual Housing Units Authorized by Build ing Permits CO2007A, purchased from US Department of Census

4. U.S. Census Bureau, “Annual Value of C onstruction Put in Place,” available at http://www.census.gov/const/www/ototpage.html

5. U.S. Census Bureau, “County Busi ness Patterns,” available at http://www.census.gov/econ/cbp/index.html

6. Bureau of Labor Statistics, Producer Pr ice Index, Table BMNR, available at http://www.bls.gov/data/

7. Federal Highway Administration, 2 006 Highway Spending, available at http://www.fhwa.dot.gov/polic y/ohim/hs06/xls/sf12a.xls

8. Ward, D.E., C.C. Hardy, D.V. Sandberg, and T.E. Reinhardt. “Mitigation of Prescribed Fire Atmospheric Pollution through Increased Utilization of Hardwoods, Piled Residues, and Long-Needled Conifers.” Final Report. USDA Forest Service, Pacific Northwest Research Station, Fire and Air Resource Management. 1989.

9. Huntley, Roy, U.S. Environmental Protec tion Agency, “state_comparison ERTAC SS_version7_3 Oct 20 2009 [electro nic file],” November 5, 2009.

10. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Compilation of Air Pollutant Emission Factors, AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources, Section 2.5 Open Burning . Research Triangle Park,

NC. October 1992.

11. U.S. Environmental Protection Agency, “E valuation of Emissions from the Open Burning of Household Waste in Barre ls, EPA-600/R-97-134a,” Control Technology

Center. November 1997.

12. Gullet, B.K. and T. Abderrahmne, “PCDD/F Em issions from Forest Fire Simulations,” Atmospheric Environment , Vol. 37, No. 6, pp. 803-813. February 2003.

3.2.3.7 Open Burning – Residential Household Waste

a. Source Category Description

Open burning of residential municipal solid wa ste (MSW) is the purposeful burning of MSW in
outdoor areas. Criteria ai r pollutant (CAP) and hazardous air po llutant (HAP) emission estimates for MSW burning are a function of the amount of waste burned per year.

For this source category, the following SCC was assigned:

SCC SCC Level 1 SCC Level 2 SCC Level 3 SCC Level 4 2610030000 Waste Disposal, Treatment, and Recovery Open Burning Residential Household Waste (use 26-10-000-xxx for Yard Wastes)

### Page 59 b. Activity Data

The amount of household MSW burned was es timated using data from EPA’s report Municipal
Solid Waste in the United States: 2007 Facts and Figures

. 1 

### The report presents the total mass of waste generated in the United States by type of waste for the calendar year 2007. This information was used to calculate a daily estimat e of the per capita household waste subject to burning, 3.40 lbs/person/day. Non-combustible waste, such as glass and metals, was not considered to be waste subject to burning. Burning of yard waste is included in SCC 2610000100 and SCC 2610000400; therefore, it is not pa rt of residential MSW. Approximately 25 to 32 percent of all waste that is s ubject to open burning is actually burned. 2 

### A median value of 28 percent is assumed to be burned in all counties in the United States.

Since open burning is generally not practiced in urban areas, onl y the rural population of each county was assumed to practice open burning. The ratio of urban to rural population was
obtained from 2000 U.S. Census data. 3 

### This ratio was then multiplied by the 2008 U.S. Census Bureau estimate of the population in each county to obtain the county-level rural population for

2008. 4 

### The county-level rural population was then multiplied by the per capita household waste subject to burning to determine the amount of rural household MSW generated in each county in

2008.

c. Controls

Controls for residential MSW burning are generally in the fo rm of a ban on open burning of waste in a given municipality or county. Countie s that were more than 80% urban were assumed not to practice any open burning. Therefore, criteria pollutant a nd HAP emissions from residential municipal solid waste burning are zero in these counties. In addition, the State of Colorado implemented a state-wide ban on ope n burning. Emissions from open burning of

residential waste in all Colorado co unties were assumed to be zero.

d. Emission Factors

Emission factors are reported in Table 1 below. Emission factor s for CAPs were developed by the U.S. Environmental Protection Agency (EPA ) in consultation with the Eastern Regional Technical Advisory Committee and ba sed primarily on the AP-42 report. 5, 6 

### Emission factors for HAPs are from an EPA Control Technology Center report and emission factors for 17 dioxin congeners were obtained from an EPA dioxin report. 7,8



### e. Emissions

County-level CO emissions were calculated by multiplying the total amount of residential municipal solid waste burned per year by an emission factor.

f. Example Calculations

VOC emissions in Autauga County, Alabama from open burning of residential MSW:

Population of Autauga County in 2008 = 50,364 Rural fraction of Autauga County population = 0.448 Per capita MSW waste genera ted (lb/person/day) = 3.40

### Page 60 Fraction of rural populati on that burns MSW = 0.28 Number of days in a year = 365
Factor to convert from lbs to tons = 1/2000

2008 MSW burning activity in Autauga County = 50,364 * 0.448 * 3.40 * 0.28 * 365 *

1/2000

2008 leaf burning activity in Autauga County = 3,921 tons

VOC emissions = tons of leaves burned * VOC emission factor

VOC emission factor = 8.56 lb/ton

VOC emissions from leaf burning in Auta uga County in 2008 = 3,921 tons * 8.56 lbs/ton

* 1 ton/2000 lbs

VOC emissions from leaf burning in Autauga County in 2008 = 16.78 tons

g. References

1. U.S. Environmental Protection Agency, Municipal Solid Waste in the United States: 2007 Facts and Figures , EPA530-R-08-010, Office of So lid Waste and Emergency Response. November 2008. Available at http://www.epa.gov/epawaste/nonhaz/municipal/pubs/msw07-rpt.pdf

2. U.S. Environmental Protection Agency, Regi on V. “Emission Characteristics of Burn Barrels.” Prepared by Two Rivers Regional Council of Public Officials and Patrick Engineering, Inc. June 1994.

3. U.S. Census Bureau, Decennial Censuses, 2000 Census: SF1, Table P2

4. U.S. Census Bureau. Annual Estimates of the Resident Population for the United States, Regions, States, and Puerto Rico: Apr il 1, 2000 to July 1, 2008 (NST-EST2008-01). Available at http://www.census.gov/ popest/states/NST-ann-est.html

5. Huntley, Roy, U.S. Environmental Protec tion Agency, “state_comparison ERTAC SS_version7_3 Oct 20 2009 [electro nic file],” November 5, 2009.

6. United States Environmental Protection Ag ency, Office of Air Quality Planning and

Standards. Compilation of Air Pollutant Emission Factors, AP-42, Fifth Edition, Volume I: Stationary Point and Area Source s, Section 2.5 Open Burning . Research Triangle Park, NC. October 1992.

7. U.S. Environmental Protection Agency, C ontrol Technology Center. “Evaluation of Emissions from the Open Burning of House hold Waste in Barrels.” EPA-600/R-97-134a.
November 1997.

8. United States Environmental Protection Agen cy, Office of Research and Development. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzeno-p-Dioxin

### Page 61 (TCCD) and Related Compounds. Part I: Estimating Exposure to Dioxin-Like Compounds. Volume 2: Sources of Diox in-Like Compounds in the United States

. EPA/600/P-00/001Ab. Washington D.C. March 2001.

Table 1. Emission Factors for Open Burning of Residential MSW (2610030000)

Pollutant Pollutant Code Emission Factor (lb/ton) Emission Factor
Reference

CO CO 8.50E+01 Reference 5

Table 2. Emission Factors for Open Burning of Land Clearing Debris (SCC 2610000500)

Pollutant Pollutant Code Emission Factor (lb/ton) Emission

Factor
Reference

CO CO 1.69E+02 Reference 9



### 3.2.3.8 Open Burning – Yard Waste – Leaf and Brush Species

a. Source Category Description

Open burning of yard waste is the purposeful bur ning of leaf and brush sp ecies in outdoor areas.
CO emission estimates for leaf and brush waste burning are a function of the amount of waste burned per year.

For this source category, the following SCCs were assigned:

SCC SCC Level 1 SCC Level 2 SCC Level 3 SCC Level 4 2610000100 Waste Disposal, Treatment, and Recover y Open Burning All Categories Yard Waste

– Leaf Species Unspecifie d 2610000400 Waste Disposal, Treatment, and Recover y Open Burning All Categories Yard Waste

– Brush Species Unspecifie d



### b. Activity Data

The amount of leaf and brush waste burned was estimated using data from EPA’s report Municipal Solid Waste in the Un ited States: 2007 Facts and Figures. 1 

### The report presents the total mass of waste generated in the United States by type of waste, including yard waste, for the calendar year 2007. This information was used to calculate a daily estim ate of the per capita yard waste, 0.59 lbs/person/day. Of the total amount of yard waste generated, the yard waste composition was assumed to be 25 percent leav es, 25 percent brush, and 50 percent grass by weight. 2



### Open burning of grass clippings is not typical ly practiced by homeowners, and as such only estimates for leaf burning and br ush burning were developed. Appr oximately 25 to 32 percent of all waste that is subject to open burning is actually burned. 2 

### A median value of 28 percent is

assumed to be burned in all c ounties in the United States.

### Page 62 The per capita estimate was then multiplied by the 2008 population in each county that is expected to burn waste. Since open burning is generally not pract iced in urban areas, only the rural population of each county was assumed to practice open burning. The ratio of urban to rural population was obtained from 2000 U.S. Census data. 3 

### This ratio was then multiplied by the 2008 U.S. Census Bureau estimate of the pop ulation in each count y to obtain the countylevel rural population for 2008. 4



### The percentage of forested acres from Version 2 of BELD2 within BEIS wa s used to adjust for variations in vegetation. The pe rcentage of forested acres per county (including rural forest and urban forest) was then determined. To better ac count for the native vegetation that would likely be occurring in the residential yards of farmi ng States, agricultural la nd acreage was subtracted before calculating the percentage of forested acres. Table 1 presents the ranges that were used to make adjustments to the amount of yard waste th at is assumed to be generated per county. All municipios in Puerto Rico and counties in the U.S. Virgin Is lands, Hawaii, and Alaska were assumed to have greater than 50 percent forested acres.

Table 1. Adjustment for Percentage of Forested Acres

Percent Forested Acres per County Adjustment for
Yard Waste Generated

< 10% 0% generated

>= 10%, and < 50% 50% generated

>= 50% 100% generated



### c. Controls

Controls for yard waste burning are generally in the form of a ban on open burning of waste in a given municipality or county. Counties that were more than 80% urban were assumed not to practice any open burning. Therefore, CO emissi ons from residential municipal solid waste burning are zero in these counties. In addition, the State of Colo rado implemented a state-wide ban on open burning. Emissions from open burning of residential waste in all Colorado counties
were assumed to be zero.

d. Emission Factors

Emission factors are specific to yard waste type and are repor ted in Tables 2 and 3 below. Emission factors for CAPs were developed by th e U.S. Environmental Protection Agency (EPA)

in consultation with the Eastern Re gional Technical Advisory Committee. 5 

### Emission factors for

HAPs are from AP-42 and an EPA Control Technology Center report. 6, 7



### e. Emissions

County-level CO emissions were calculated by multiplying the tota l amount of yard waste (either leaf or brush) burned per year by an emission fact or. Emissions for leaves and residential brush were calculated separately, since emission factor s vary by yard waste type. Tons of debris burned were converted to kilograms (kg) by multiplying by 907.18474.

### Page 63 f. Example Calculations

VOC emissions in Autauga County, Alabam a from open burning of leaf waste:

Population of Autauga County in 2008 = 50,364 Rural fraction of Autauga County population = 0.448 Per capita waste yard waste ge nerated (lb/person/day) = 0.59

Leaf fraction of waste = 0.25 Fraction of rural population th at burns yard waste = 0.28 Adjustment factor based on % forested acres = 1 Number of days in a year = 365
Factor to convert from lbs to tons = 1/2000

2008 leaf burning activity in Autauga County = 50,364 * 0.448 * 0.59 * 0.25 * 0.28 * 1 *

365 * 1/2000

2008 leaf burning activity in Autauga County = 170.11 tons

VOC emissions = tons of leaves burned * VOC emission factor

VOC emission factor = 28 lb/ton

VOC emissions from leaf burning in Auta uga County in 2008 = 170.11 tons * 28 lbs/ton

* 1 ton/2000 lbs

VOC emissions from leaf burning in Autauga County in 2008 = 2.38 tons

g. References

1. U.S. Environmental Protection Agency, Municipal Solid Waste in the United States: 2007 Facts and Figures , EPA530-R-08-010, Office of Solid Waste and Emergency Response. November 2008. Available at http://www.ep a.gov/epawaste/nonhaz/municipal/pubs/msw07- rpt.pdf

2. Two Rivers Regional Council of Public Offici als and Patrick Engineering, Inc. “Emission Characteristics of Burn Barrels,” prepared for the U.S. Environmental Protection Agency, Region V. June 1994.

3. U.S. Census Bureau, Decennial Censuses, 2000 Census: SF1, Table P2

4. U.S. Census Bureau. Annual Estimates of the Resident Population for the United States, Regions, States, and Puerto Rico: Apr il 1, 2000 to July 1, 2008 (NST-EST2008-01). Available at http://www.census.gov/popest/states/NST-ann-est.html

5. Huntley, Roy, U.S. Environmental Protec tion Agency, “state_comparison ERTAC SS_version7_3 Oct 20 2009 [electro nic file],” November 5, 2009.

6. U.S. Environmental Protection Agency, Comp ilation of Air Pollutant Emission Factors, AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources, Section 2.5 Open Burning,, Tables 2.5-5 and 2.5-6. October 1992.

### Page 64 7. U.S. Environmental Protection Agency, Evaluation of Emissions from the Open Burning of
Household Waste in Barrels , EPA-600/R-97-134a, Control Technology Center. November

1997.

8. Gullet, B.K. and T. Abderrahmne, “PCDD/F Emissions from Forest Fire Simulations,” Atmospheric Environment , Vol. 37, No. 6, pp. 803-813. February 2003.

Table 2. Emission Factors for Open Burning of Leaf Species (SCC 2610000100)

Pollutant Pollutant Code Emission Factor (lb/ton) Emission

Factor
Reference

CO CO 112 Reference 5

Table 3. Emission Factors for Open Burning of Brush Species (SCC 2610000400)

Pollutant Pollutant Code Emission Factor (lb/ton) Emission

Factor
Reference

CO CO 140 Reference 5



### 3.2.3.9 Fuel Combustion – Industrial a nd Commercial/Institutional (ICI)

The Central States Regional Planning Associatio n (CENRAP) contracted w ith Pechan to provide an updated methodology to calculate ICI fuel combustion emissions for 2002, and make the methodology updatable for future inventory projects. Appendix A-5 is documentation of the ICI methodology and describes how it is app lied to a revised 2002 inventory.

Statewide emissions are calculated using the fuel activity and emission factors, then statewide point source emission contributi ons are subtracted, and finally the emissions are allocated to counties. The Energy Information Administration’ s (EIA’s) State Energy Data System (SEDS) provides total energy consumption by sector, but th e values have to be adjusted by energy not used for combustion and nonroad equipment use. EIA’s 2002 Manufacturing Energy Consumption Survey (MECS) was used to get regional sect oral energy consumption that is not

used for combustion. A run of the NONROAD model for 2006 provided the diesel and LPG quantity to subtract for commer cial sector nonroad equipment. Emission factors from Roy Huntley of the EPA, the Emission Inventory im provement Plan (EIIP), and AP-42 cover the various fuel types for criteria pollutants. Emissions from coal combustion require the use of Missouri-specific coal sulfur content from th e Energy Information Administration Quarterly Coal Report. Statewide point source emissi on contributions are subtracted by compiling the sector’s CO emissions by Source Classification Code (SCC), which is fuel specific, backcalculating using AP-42 emission factors to a fuel throughput, and subtracting that fuel throughput from the statewide total. Before allocating the remaining nonpoint emissions to Missouri counties, an ener gy-intensity adjustment is done to account for the variation of energy

### Page 65 used per employee for each industrial manufacturing NAICS code. County Business Patterns (CBP) published annually by the US Census Bur eau outlines employment by NAICS codes and the energy-intensity per employee by NAICS code derived from EIA’s 2002 Annual Energy

Outlook. Emissions are then allocated to indi vidual counties based on commercial/institutional employment by county and based on energy intens ity and employment for the industrial sector.

Appendix A-5 outlines the activity data used, em ission factors, and the calculation template spreadsheets for the categories below.

SCC SCC Description

2102001000 Stationary Source Fuel Combustion; Industr ial; Anthracite Coal; Total: All Boiler Types

2102002000 Stationary Source Fuel Combustion; Industrial; Bituminous/Subbituminous Coal; Total: All Boiler Types

2102004000 Stationary Source Fuel Combustion; Industria l; Distillate Oil; Total: Boilers and IC Engines

2102005000 Stationary Source Fuel Combustion; Industr ial; Residual Oil; Total: All Boiler Types

2102006000 Stationary Source Fuel Combustion; Industria l; Natural Gas; Total: Boilers and IC Engines

2102007000 Stationary Source Fuel Combustion; Industr ial; Liquid Petroleum Gas; Total: All Boiler Types

2102008000 Stationary Source Fuel Combustion; Industrial; Wood; Tota l: All Boiler Types

2102011000 Stationary Source Fuel Combustion; I ndustrial; Kerosene; Total: All Boiler Types

2103001000 Stationary Source Fuel Combustion; Comme rcial/Institutional; Anthracite Coal; Total: All Boiler Types

2103002000 Stationary Source Fuel Combustion; Commercial/Institutional; Bituminous/Subbituminous Coal; Total: All Boiler Types

2103004000 Stationary Source Fuel Combustion; Commercia l/Institutional; Distillate Oil; Total: Boilers and IC Engines

2103005000 Stationary Source Fuel Combustion; Commercial/Institutional; Residual Oil; Total: All Boiler Types

2103006000 Stationary Source Fuel Combustion; Commercial/Institutional; Natural Gas; Total: Boilers and IC Engines

2103007000 Stationary Source Fuel Combustion; Commercial/Institutional; Liquid Petroleum Gas; Total: All Combustor Types

2103008000 Stationary Source Fuel Combustion; Comme rcial/Institutional; Wood; Total: All Boiler Types

2103011000 Stationary Source Fuel Combustion; Commercial/Institutional; Kerosene; Total: All Combustor Types

### Page 66 3.2.3.10 Fossil Fuel Combustion – Residentia l – Liquefied Petroleum Gas (LPG)

a. Source Category Description

Residential LPG Combustion is liquefied propane gas that is burned in residential housing. Common uses of energy associated with this sector include space heating, water heating, and cooking.

The general approach to calcula ting emissions for this SCC is to take State LPG Consumption from the EIA and allocate it to the county leve l using methods described below. County level LPG consumption is multiplied by the emi ssion factors to calculate emissions.

For this source category, the following SCC was assigned:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2104007000 Stationary Source
Fuel Combustion Residential Liquefied
Petroleum Gas (LPG) Total: All Combustion Types



### b. Activity Data

Residential liquefied petroleum gas (LPG) co mbustion emissions were calculated using the

volume of LPG consumed in the United States. State-level LPG consumption by sector is available from the Energy In formation Administration (EIA). 1 

### Year 2006 consumption data were used as a surrogate for 2008 emissions because these were th e latest data available when this inventory was prepared.

State-level LPG consumption was allocated to each county using the US Census Bureau’s 2000 Census Detailed Housing Information. 2 

### These data include the number of housing units using a specific type of fuel for reside ntial heating. State LPG consump tion was allocated to each county using the ratio of the number of houses burni ng LPG in each county to the total number of houses burning LPG in the State.

c. Control Factors

No control measures are assumed for this category.

d. Emission Factors

Pollutant emission factors for residential LPG ar e based on the residential natural gas emission

factors. 3,4,5 

### For all counties in the United States, the natural ga s consumed by residential combustion is assumed to have a heating value of 1,020 Btu per cubic foot and a sulfur content of 2,000 grains per million cubic feet. 3 

### Those natural gas emission factors originally presented in the units “pounds per million cubic feet” were converted to energy-based units using the 1,020

Btu/cubic foot conversion factor . Once all the natural gas emi ssion factors were converted to energy-based units, the natural ga s emission factors were conver ted to LPG emission factors by

### Page 67 multiplying by 96,750 Btu/gallon. Some emi ssion factors were revised based on recommendations by an ERTAC advisory pane l composed of state and EPA personnel.

e. Sample Calculations

Emissions are calculated for each county using emission factors and activity as:

E x,p 

### = FC

x 

### × EF x,p



### where:

E x,p 

### = annual emissions for fuel type x and pollutant p,

FC

x 

### = annual fuel consumption for fuel type x,

EF x,p 

### = emission factor for fuel type x and pollutant p,

And FC

x 

### = A State 

### x (H county 

### / H State 

### )

where :

A State 

### = State activity data from EIA

H County 

### = number of houses in the county usi ng LPG as the primary heating fuel

H State 

### = number of houses in the state us ing LPG as the primary heating fuel.

Example: Using Allegheny County, PA as an example:

The State of Pennsylvania had a reported use of 4,743 thousand barrels of LPG in the residential sector in 2006. Allegheny County, PA had 4,317 hous es out of the state total of 145,254 that use LPG as the primary heating fuel. This equates to a share of 2.97% of the LPG used for residential heating in the state. From Table 1, CO emission factor is 1 59.6 lb/thousand barrels.

E CO 

### = 4,743 thousand barrels × (4,317 houses / 145,254 houses)

× 159.6 lb/thousand barrels

= 22,498 lb CO or 11.25 tons CO

f. References

1. U.S. Department of Energy, Energy Inform ation Administration (EIA). State Energy Data 2006 Consumption. Washington, DC 2008. Internet address: http://www.eia.doe.gov/emeu/states/sep_use/to tal/csv/use_all_phy.csv, accessed November

2008.

2. U.S. Census Bureau. "Table H40. House Heating Fuel Type", Census 2000: Summary

File 3. Internet address: http://factfinder.census.gov/servlet/DatasetM ainPageServlet?_program=DEC&_submenuId=&_l ang=en&_ts=, accessed July 2009.

### Page 68 3. U.S. Environmental Protection Agency. Co mpilation of Air Pollutant Emission Factors, 5th Edition, AP-42, Volume I: Stationary Poin t and Area Sources. Rese arch Triangle Park,

North Carolina. 1996.

4. U.S. Environmental Protection Agenc y, Emission Factors and Inventory Group. “Documentation for the 1999 Base Year Nonpoint Area Source National Emission Inventory for Hazardous Air Pollutants.” Prepared by Easter n Research Group, Inc. Morrisville, NC. September 2002.

5. U.S. Environmental Protection Agency. Emission Factor and Inventory Group. Final Summary of the Development and Results of a Methodology for Calculating Area Source Emissions from Residential Fuel Combustion. Prep ared by Pacific Environmental Services, Inc. Research Triangle Park, NC. Sept ember 2002. Internet address: http://www.epa.gov/ttn/chief/eiip/techreport/v olume03/draft1999_ residfuel_inven_apr2003.zip accessed, November 2004.

Table 1. National CO Emission Fact or for Residential LPG Combustion

Pollutant

Code Pollutant Code Description Factor Numeric

Value Factor Unit

Numerator Factor Unit

Denominator

CO CO 159.6 LB E3BBL



### 3.2.3.11 Fuel Combustion – Residential- Wood

EPA created the Residential Wood Combustion t ool to assist states with compiling the 2005 NEI, and has updated the tool with new SCCs to reflect new equipment (certified/ non-certified inserts, outdoor hydronic heaters, wood pellet stoves), revised equipment population based on regional surveys and American Housing Survey (US Census) data, and wood use ratios.

The tool is a Microsoft Access database with data input tables fo r appliance types and population, fuel inputs, burn temporal profiles, and emission factors. Missouri had no statespecific updates to input files, so the EPA defaults for Missouri were used to calculate emissions. A specific query is run that performs the calcul ation and outputs the emission table for the state

or counties of interest.

3.2.4 Nonpoint Source Emission Summary

Table 9 Nonpoint CO Emissions for St. Louis City and St. Louis County (tons per year) 

### County Name CO Emissions St. Louis County 8,752.71
St. Louis City 3,086.57
Totals 11,839.27

### Page 69 3.3 Mobile Source Emissions

3.3.1 Nonroad Mobile Sources

Nonroad categories include recreational marine and land-based vehicles, farm and construction machinery, industrial, commercial, logging, and lawn and garden equipment, and railway maintenance equipment. These types of equipment are powered by compression-ignition engines which are typically diesel -fueled, as well as spark-igniti on (gasoline-fueled) engines. Compressed natural gas (CNG) and liquefied pe troleum gas (LPG) engines may also power certain types of nonroad equipment.

3.3.1.1 Procedures and Methodologies

For nonroad gasoline, diesel, LPG and CNG sour ces, EPA’s National Mobile Inventory Model (NMIM), incorporating the NONROAD2008 model, was used to calculate nonroad emissions. The annual CO emissions data generated by EPA for the 2008 off-road mobile source emissions for the St. Louis City and St. Loui s County are summar ized in Table .

For aircraft, EPA ran the Federal Aviation Ad ministration (FAA) Emissions and Dispersion Modeling System (EDMS) using Bureau of Tr ansportation Statistics (BTS) T-100 Landing and Takeoff (LTO) and Terminal Area Forecast (TAF) data. The state of Missouri did not provide alternate emissions or input data, so EPA calculations were accepted.

For commercial marine vehicles, EPA’s Offi ce of Transportation and Air Quality (OTAQ) provided emission estimates based on grown 2002 emissions and 2008 Locomotive and Marine federal rule making. Again, EPA em ission estimates were accepted.

For locomotives, the Eastern Regional Techni cal Advisory Committee (ERTAC Rail) provided

emission estimates based on fuel use data from the American Associatio n of Railroads (AAR), Surface Transportation Board (STB) Annual Repor ts, and railroad provided fleet and activity information. These estimates were accepted by Missouri.

EPA generates emissions data for commercial marine and locomotive sources using a method similar to the way emissions are generated for non-point sources. Therefore, 2008 NEI data for commercial marine and locomotive emissions, whic h are listed as nonpoint emissions in the NEI data, need to be added to the nonroad mobile source category. See Section 3.3.1.4 for emission

totals.

3.3.1.2 List of Source Categories and Emissions

The list of source categories and emissions in St. Louis City and St. Louis County is provided in Appendix A-4. EPA’s NONROAD 2008a model wa s used to generate the nonroad emission summary listed in table 10.

### Page 70 3.3.1.3 Source Category Documentation

EPA’s NONROAD 2008a model was used to genera te the nonroad emission summary listed in table 10; this does not include emissions from locomotive and marine engines. The methodology for calculating locomotive and marine engines ca n be found in Appendix A-3. The emissions for these two source categories are list ed in Table 11, and the total annual nonroad CO emissions for St. Louis City and St. Louis C ounty are listed in Table 12.

3.3.1.4 Nonroad Source Emission Summary

Table 10 St. Louis County and City 2008 Nonroad Emissions (excl uding Marine,Rail,andAir Emissions)



### Area CO Emissions (tons/year) St. Louis County 75,892.69
St. Louis City 14,001.59
Totals 89,894.28

Table 11 St. Louis County and City 2008 Marine, Rail, and Air Emissions



### Area CO Emissions (tons/year) St. Louis County 1,548.15
St. Louis City 1,581.52
Totals 3,129.67

Table 12 St. Louis County a nd City Total 2008 Nonroad Mobile Source Emissions



### Area CO Emissions (tons/year) St. Louis County 77,440.84
St. Louis City 15,583.11
Totals 93,023.95



### 3.3.2 Onroad Mobile Sources

Onroad emission sources are also known as highw ay sources. They include vehicles used on roads for transportation of passengers or frei ght. The emissions from internal combustion engines in these vehicles are included in this category.

3.3.2.1 Mobile Model Choice

EPA released the Mobile Vehicle Emissi on System (MOVES) in December of 2010, and MOVES is now the official model to use for mobile emissions modeling. MOVES was chosen

because it is the official model for future inventories and to en sure that grown emissions and budgets will be calculated consistently. 2008 mob ile emissions were initially created using Mobile6.2 via NMIM for the St. Louis nonattainment area for the purpose of submitting state

wide emissions data for EPA’s 2008 National Emissions Inventory (NEI). The NMIM NCD input data was updated with Misso uri specific information. Local VMT data, vehicle registration

### Page 71 distributions, and meteorology data from th e updated NCD were converted to MOVES formatting using EPA provided conversion workbooks.

MOVES is a completely redesigned model, not ju st an updated version of the previous Mobile model. The way MOVES calculates emissions ha s changed to reflect EPA’s more current understanding of the emissions pr oduced by vehicles and the vari ous factors that affect the

emissions.

3.3.2.2 Mobile Model Inputs

Local VMT data was gathered from East-West Gatewa y at the county level. Th is data is listed in

Table 13.

The road type distribution in th e baseyearvmt table from the NC D was used to distribute the county level VMT to road type. EPA’s VMT converter workbook was then used to produce MOVES input tables.

An age distribution for light dut y vehicles was created from a list of Vehicle Identification Numbers (VINs) contained in ve hicle registration records from the Missouri Department of

Revenue. The VINs were decoded into model year and MOBILE6 vehicle classes by ESP Data Solutions, Inc, a private contract or. A specific registration distri bution was created for the five county Missouri portion of the St. Louis Nona ttainment area. This data updated the BaseYearVMT Table and the CountyYear Table. The vehicle distribution was converted to MOVES age distribution table using EPA’s VMT converter workbook. The re gistration data was

also used to create the MOVE S vehicle population input tables. Vehicle counts were converted

from Mobile 6.2 vehicle classes to MOVES source types using the s ource type fractions from the Source Type Pop Fractions table in EPA’s VMT converter workbook. The vehicle distribution is

listed in Table 14.

St. Louis City and St. Louis County both partic ipate in the Gateway Vehicle Inspection Program (GVIP). For counties subject to Emission In spection/Maintenance (I /M) Programs, MOVES allows for an I/M input table to be created. An I/M input table was created to describe the GVIP for St. Louis City and St. Louis County. Develo pment of the table was in accordance with EPA technical guidance on appropriate input assumptions and sources of data for the use of MOVES 2010 in State Implementation Plans ( http://www.epa.gov/otaq/models/moves/420b10023.pdf ). Documentation for the development protocol fo r the I/M input table can be found in Appendix

A-6.

MOVES base data was used for all other inputs, af ter reviewing the data to ensure accuracy. The base fuel supply tables in MOVES were used for the runs, as they alread y took into account the reformulated gasoline used in the St. Louis nona ttainment area. A separate input database was created for each county, using county specific da ta where possible. The MOVES input tables, other than default EPA templates, ar e included in Table 15 through Table .

### Page 72 Table 13 2008 Vehicle M iles Traveled by County

County

FIPS County_Name VMT* in

Million Miles County

FIPS County_Name VMT* in Million

Miles

1 Adair County 159.4784 121 Macon County 242.8909

3 Andrew County 319.5966 123 Madison County 138.1476

5 Atchison County 196.4741 125 Maries County 122.7927

7 Audrain County 240.2153 127 Marion County 354.5883

9 Barry County 356.2431 129 Mercer County 52.8821

11 Barton County 228.2903 131 Miller County 348.3599

13 Bates County 276.5227 133 Mississippi County 241.8438

15 Benton County 213.8250 135 Moniteau County 141.0637

17 Bollinger County 117.7653 137 Monroe County 91.6368

19 Boone County 1,484.7484 139 Montgomery County 381.1052

21 Buchanan County 751.9344 141 Morgan County 221.8110

23 Butler County 488.9247 143 New Madrid County 483.9027

25 Caldwell County 154.1807 145 Newton County 791.7511

27 Callaway County 913.0340 147 Nodaway County 188.0544

29 Camden County 491.0100 149 Oregon County 151.1144

31 Cape Girardeau
County 722.6664 151 Osage County 176.1925

33 Carroll County 96.9629 153 Ozark County 115.5051

35 Carter County 122.2928 155 Pemiscot County 491.2463

37 Cass County 947.9729 157 Perry County 299.3293

39 Cedar County 113.8193 159 Pettis County 406.5007

41 Chariton County 85.0137 161 Phelps County 711.2055

43 Christian County 721.9733 163 Pike County 276.9507

45 Clark County 139.0347 165 Platte County 1,363.4685

47 Clay County 2,256.7113 167 Polk County 355.0242

49 Clinton County 320.3453 169 Pulaski County 537.7921

51 Cole County 618.3292 171 Putnam County 52.0246

53 Cooper County 479.2263 173 Ralls County 202.9427

55 Crawford County 491.5010 175 Randolph County 289.3356

57 Dade County 77.8041 177 Ray County 190.6346

59 Dallas County 193.3356 179 Reynolds County 88.8169

61 Daviess County 267.3748 181 Ripley County 110.1861

63 DeKalb County 199.1815 183 St. Charles County 2,727.9563

65 Dent County 149.0151 185 St. Clair County 182.8044

67 Douglas County 127.5733 186 Ste. Genevieve County 398.6384

69 Dunklin County 317.1931 187 St. Francois County 548.1491

71 Franklin County 1,636.7261 189 St. Louis County 11,925.1835

73 Gasconade County 156.4525 195 Saline County 463.6895

75 Gentry County 58.3613 197 Schuyler County 62.0992

77 Greene County 2,404.9309 199 Scotland County 51.6444

79 Grundy County 80.0101 201 Scott County 471.9991

81 Harrison County 274.5483 203 Shannon County 119.4785

83 Henry County 310.2750 205 Shelby County 99.2628

85 Hickory County 97.5059 207 Stoddard County 363.2309

87 Holt County 259.7343 209 Stone County 312.0035

89 Howard County 99.7101 211 Sullivan County 65.6205

91 Howell County 470.7985 213 Taney County 642.9550

### Page 73 County

FIPS County_Name VMT* in

Million Miles County

FIPS County_Name VMT* in Million

Miles

93 Iron County 126.2972 215 Texas County 322.3266

95 Jackson County 6,713.6034 217 Vernon County 345.9822

97 Jasper County 1,067.1157 219 Warren County 524.8759

99 Jefferson County 1,884.7099 221 Washington County 220.3597

101 Johnson County 499.5025 223 Wayne County 183.2741

103 Knox County 57.7446 225 Webster County 662.7641

105 Laclede County 652.5356 227 Worth County 18.6762

107 Lafayette County 692.2315 229 Wright County 278.1377

109 Lawrence County 656.1909 510 St. Louis City 3,450.4882

111 Lewis County 166.5792

113 Lincoln County 495.2502 *From MoDOT except for Cass, Clay, Jackson, and Platte (MARC) and Franklin, Jefferson, St. Charles, St. Louis, and St.

Louis City (East

‐ West Gateway) 115 Linn County 153.6966

117 Livingston County 170.1267

119 McDonald County 330.7242

### Page 74 Table 14 Missouri Registration Distribution

Vehicle

Class Vehicle Model Year Popul ation Percentage Per Vehicle Classification

2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996

LDV 0.0248 0.0564 0.0666 0.0649 0.0653 0.0632 0. 0633 0.0679 0.0675 0.0652 0.0604 0.0501 0.0488

LDT1 0.0130 0.0345 0.0103 0.0666 0.0759 0.0255 0.0713 0.0780 0.0859 0.0487 0.0474 0.0398 0.0379

LDT2 0.0179 0.0593 0.0700 0.0750 0.0840 0.0759 0.0728 0.0808 0.0671 0.0640 0.0563 0.0522 0.0427

LDT3 0.0161 0.0734 0.0630 0.0760 0.0785 0.0842 0.0838 0.0728 0.0624 0.0539 0.0561 0.0365 0.0328

LDT4 0.0153 0.0843 0.1358 0.0771 0.0953 0.1119 0.0736 0.0461 0.0564 0.0549 0.0715 0.0395 0.0342

HDV2b 0.0078 0.0468 0.0483 0.0729 0.0660 0.0808 0.0871 0.0713 0.0773 0.0671 0.0642 0.0310 0.0519

HDV3 0.0066 0.0628 0.0602 0.0961 0.0876 0.0681 0. 0715 0.0613 0.0774 0.0669 0.0734 0.0272 0.0331

HDV4 0.0040 0.0200 0.0638 0.0404 0.0338 0.0366 0.0385 0.0413 0.0653 0.0781 0.0821 0.0383 0.0630

HDV5 0.0187 0.1207 0.0664 0.0804 0.0535 0.0639 0. 0560 0.0450 0.0578 0.0951 0.0899 0.0465 0.0572

HDV6 0.0311 0.0355 0.1005 0.0865 0.0529 0.0268 0.0212 0.0199 0.0840 0.0765 0.0685 0.0572 0.0591

HDV7 0.0182 0.0324 0.1250 0.1080 0.1033 0.0772 0. 0847 0.0669 0.0285 0.0427 0.0285 0.0253 0.0281

HDV8a 0.0136 0.0110 0.0524 0.0497 0.0565 0.0513 0.0420 0.0301 0.0426 0.0791 0.0570 0.0386 0.0354

HDV8b 0.0189 0.0726 0.2263 0.0348 0.0639 0.0957 0. 0899 0.0552 0.0522 0.1363 0.0697 0.0305 0.0203

HDBS 0.0343 0.0556 0.0925 0.0556 0.1004 0.0587 0.0623 0.0351 0.0489 0.0657 0.0669 0.0678 0.0426

HDBT 0.0060 0.0045 0.0132 0.0144 0.0138 0.0291 0. 0378 0.0258 0.0249 0.0390 0.0351 0.0309 0.0351

MC 0.0190 0.0646 0.1035 0.1096 0.1172 0.0874 0.0922 0.0713 0.0610 0.0435 0.0360 0.0255 0.0208

1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984

LDV 0.0390 0.0420 0.0313 0.0274 0.0213 0.0184 0.0138 0.0121 0.0083 0.0065 0.0049 0.0106

LDT1 0.0443 0.0211 0.0168 0.0210 0.0189 0.0193 0.0184 0.0363 0.0582 0.0433 0.0250 0.0426

LDT2 0.0292 0.0287 0.0266 0.0215 0.0157 0.0149 0.0096 0.0096 0.0076 0.0054 0.0042 0.0090

LDT3 0.0322 0.0423 0.0338 0.0207 0.0181 0.0106 0.0112 0.0104 0.0070 0.0067 0.0058 0.0117

LDT4 0.0201 0.0158 0.0145 0.0101 0.0074 0.0055 0.0052 0.0063 0.0074 0.0045 0.0014 0.0059

HDV2b 0.0350 0.0393 0.0244 0.0196 0.0151 0.0122 0.0124 0.0154 0.0097 0.0062 0.0102 0.0280

HDV3 0.0266 0.0340 0.0223 0.0165 0.0122 0.0126 0.0134 0.0118 0.0126 0.0096 0.0098 0.0264

HDV4 0.0504 0.0723 0.0647 0.0308 0.0247 0.0243 0.0238 0.0270 0.0198 0.0121 0.0128 0.0321

HDV5 0.0517 0.0217 0.0147 0.0083 0.0067 0.0110 0.0113 0.0125 0.0080 0.0012 0.0000 0.0018

HDV6 0.0557 0.0389 0.0134 0.0152 0.0093 0.0162 0.0292 0.0196 0.0184 0.0240 0.0062 0.0342

HDV7 0.0253 0.0321 0.0174 0.0202 0.0158 0.0166 0.0139 0.0226 0.0162 0.0178 0.0103 0.0230

HDV8a 0.0333 0.0786 0.0447 0.0381 0.0239 0.0228 0.0291 0.0360 0.0277 0.0261 0.0163 0.0641

HDV8b 0.0087 0.0015 0.0015 0.0029 0.0044 0.0044 0.0029 0.0044 0.0000 0.0000 0.0015 0.0015

HDBS 0.0489 0.0327 0.0185 0.0146 0.0106 0.0095 0.0114 0.0173 0.0024 0.0035 0.0032 0.0410

HDBT 0.0830 0.0836 0.0492 0.0441 0.0267 0.0399 0.0609 0.0333 0.0558 0.0540 0.0351 0.1248

MC 0.0189 0.0171 0.0122 0.0119 0.0073 0.0063 0.0063 0.0064 0.0054 0.0068 0.0097 0.0401Page 75Table 15 2008 Source Type PopulationSource Type Population by CountyYearIDSourceTypeNameSourceTypeIDSt Louis CountySt Louis City2008 Motorcycle 11 19,243 31042008 Passenger Car 21 527,148 125,7762008 Passenger Truck31 303,295.72 59,405.612008 Light Commercial Truck 32 97,845.28 20,194.392008 Refuse Truck 41 93.5 69.52008 Single Unit Short-haul Truck 42 280.5 208.52008 Single Unit Long-haul Truck 43 2,709.24 6612008 Motor Home 51 50.14 16.252008 School Bus 52 3,623.55 1,249.22008 Transit Bus 53 270.27 92.62008 Intercity Bus 54 378.69 143.452008 Combination Short-haul Truck 61 791.19 247.52008 Combination Long-haul Truck 62 544.92 160Table 16 2008 Annual VMT by HPMSVehicle Type, County, and YearHPMSBaseYearVMT by CountyHPMSVtypeIDHPMSVtypeNameYearIDSt. LouisSt. Louis City10 Motorcycles 2008 91,989,970 26,665,06320 Passenger Cars 2008 5,115,865,231 1,477,495,62130 Other 2 axle-4 tire vehicles 2008 5,875,722,138 1,702,465,53340 Buses 2008 35,928,481 10,469,86250 Single Unit Trucks 2008 207,228,073 59,856,11960 Combination Trucks 2008 598,448,609 173,536,046Page 76Table 17 Age Distribution by Source TypeSource Type IDAgeID1121313241424351525354616200.019 0.0248 0.016038 0.015215 0.006 0.006 0.03372 0.019407 0.022549 0.022677 0.024421 0.018826 0.01783410.0646 0.0564 0.059034 0.058508 0.0045 0.0045 0.054157 0.048521 0.039325 0.03937 0.032671 0.049995 0.05261320.1035 0.0666 0.063189 0.062229 0.0132 0.0132 0.092687 0.158149 0.129508 0.130555 0.106219 0.16227 0.16983530.1096 0.0649 0.073971 0.073529 0.0144 0.0144 0.057163 0.057986 0.082002 0.084645 0.091592 0.052692 0.0440340.1172 0.0653 0.081725 0.079405 0.0138 0.0138 0.098055 0.068814 0.07432 0.076743 0.07138 0.066656 0.06347950.0874 0.0632 0.072225 0.07206 0.0291 0.0291 0.05743 0.075516 0.060754 0.062113 0.04642 0.077218 0.08058460.0922 0.0633 0.075227 0.075017 0.0378 0.0378 0.060728 0.071294 0.059753 0.061551 0.046468 0.072242 0.07439270.0713 0.0679 0.075731 0.074101 0.0258 0.0258 0.034794 0.048222 0.045101 0.04668 0.038418 0.04791 0.04777580.061 0.0675 0.069095 0.069315 0.0249 0.0249 0.049567 0.050551 0.053801 0.053336 0.05744 0.050259 0.04962290.0435 0.0652 0.059343 0.060606 0.039 0.039 0.065329 0.101607 0.075238 0.074281 0.059218 0.106403 0.114631100.036 0.0604 0.056546 0.058019 0.0351 0.0351 0.065952 0.060365 0.052757 0.052173 0.04901 0.061907 0.064481110.0255 0.0501 0.045379 0.044021 0.0309 0.0309 0.066337 0.035034 0.038694 0.038608 0.041544 0.03448 0.033479120.0208 0.0488 0.040069 0.041299 0.0351 0.0351 0.042714 0.030037 0.038252 0.038379 0.043733 0.028628 0.026173130.0189 0.039 0.031719 0.032547 0.083 0.083 0.048635 0.022609 0.033622 0.033505 0.041779 0.020871 0.017769140.0171 0.042 0.029341 0.030746 0.0836 0.0836 0.033323 0.026945 0.032499 0.031744 0.038573 0.026434 0.025331150.0122 0.0313 0.025132 0.025766 0.0492 0.0492 0.018302 0.014853 0.01522 0.015277 0.015313 0.014766 0.014626160.0119 0.0274 0.020261 0.020238 0.0441 0.0441 0.01489 0.014543 0.016624 0.016485 0.018482 0.014281 0.013778170.0073 0.0213 0.01591 0.015912 0.0267 0.0267 0.010657 0.011093 0.012019 0.01218 0.012215 0.010861 0.010491180.0063 0.0184 0.014002 0.013972 0.0399 0.0399 0.009968 0.011696 0.014667 0.014636 0.016859 0.011229 0.010394190.0063 0.0138 0.011117 0.011398 0.0609 0.0609 0.012691 0.012448 0.018417 0.017168 0.026192 0.012123 0.011221200.0064 0.0121 0.014109 0.014268 0.0333 0.0333 0.018084 0.014903 0.019136 0.018141 0.024946 0.014734 0.014172210.0054 0.0083 0.015761 0.015219 0.0558 0.0558 0.00363 0.01022 0.014831 0.014247 0.019752 0.009773 0.008829220.0068 0.0065 0.011686 0.011205 0.054 0.054 0.00501 0.010636 0.017272 0.016478 0.024234 0.009966 0.008574230.0097 0.0049 0.00791 0.008124 0.0351 0.0351 0.003627 0.006385 0.007661 0.00744 0.00919 0.006293 0.006072240.013837 0.003694 0.00582 0.006825 0.022815 0.022815 0.003017 0.003218 0.003631 0.003569 0.004095 0.003185 0.003108250.019738 0.002785 0.004029 0.004856 0.01483 0.01483 0.002668 0.001864 0.001955 0.001889 0.002204 0.001885 0.001903260.006525 0.002099 0.002201 0.002308 0.009639 0.009639 0.002379 0.001137 0.001109 0.001082 0.001162 0.001156 0.001183270 0.001582 0.001069 0.001073 0.006266 0.006266 0.00214 0.00071 0.000645 0.000647 0.000595 0.000721 0.000739280 0.00044 0.000253 0.000245 0.004073 0.004073 0.001953 0.000417 0.000378 0.000362 0.000398 0.000432 0.000454290 0 0.000147 0.000139 0.002647 0.002647 0.001784 0.00024 0.000223 0.000197 0.000282 0.000256 0.000278300 0 0.001957 0.001836 0.064531 0.064531 0.028609 0.010581 0.018036 0.013841 0.035194 0.011546 0.012147Page 77Table 18 Inspection and Maintenance Data for 2008PolProcessIDstateIDyearIDSourcetypeIDFuelTypeIDIMProgramIDInspectFreqTestStandardsIDBegModelYearIDEndModelYearIDUseIMynComplianceFactor101292008211111119711995N93.121012920082111025119962006Y97.94101292008311111119711995N93.121012920083111025119962006Y92.06101292008321111119711995N93.121012920083211025119962006Y86.18102292008211111119711995N93.121022920082111025119962006Y97.94102292008311111119711995N93.121022920083111025119962006Y92.06102292008321111119711995N93.121022920083211025119962006Y86.18112292008211714119711995N93.12112292008211824319962006Y97.94112292008311714119711995N93.12112292008311824319962006Y92.06112292008321714119711995N93.12112292008321824319962006Y86.18113292008211714119711995N93.12113292008211824319962006Y97.94113292008311714119711995N93.12113292008311824319962006Y92.06113292008321714119711995N93.12113292008321824319962006Y86.18201292008211111119711995N93.122012920082111025119962006Y97.94201292008311111119711995N93.122012920083111025119962006Y92.06201292008321111119711995N93.12Page 78PolProcessIDstateIDyearIDSourcetypeIDFuelTypeIDIMProgramIDInspectFreqTestStandardsIDBegModelYearIDEndModelYearIDUseIMynComplianceFactor2012920083211025119962006Y86.18202292008211111119711995N93.122022920082111025119962006Y97.94202292008311111119711995N93.122022920083111025119962006Y92.06202292008321111119711995N93.122022920083211025119962006Y86.183012920082111025119962006Y97.943012920083111025119962006Y92.063012920083211025119962006Y86.183022920082111025119962006Y97.943022920083111025119962006Y92.063022920083211025119962006Y86.18Table 19 Fuel Formulation for 2008FuelFormulationIDFuelSubtypeIDFuelSubtypeDescRVPSulfurLevelETOHVolumeMTBEVolumeETBEVolumeTAMEVolumeAromaticContentOlefinContent2302 12 Gasohol (E10) 11.2917 43.0622 10 0 0 0 20.2606 8.391542303 12 Gasohol (E10) 8.75115 46.6452 10 0 0 0 18.9623 8.143452304 12 Gasohol (E10) 6.84571 49.3325 10 0 0 0 17.9886 7.957392305 12 Gasohol (E10) 13.1972 40.375 10 0 0 0 21.2343 8.5775920043 20 Conventional Diesel 0 43 0 0 0 0 0 0FuelFormulationIDFuelSubtypeIDfuelSubtypeDescBenzeneContente200e300biodieselEsterVolumecetaneIndexPAHContent2302 12 Gasohol (E10) 0.848747 56.4983 84.16 0 0 02303 12 Gasohol (E10) 0.763743 53.3414 85.1429 0 0 02304 12 Gasohol (E10) 0.69999 50.9738 85.88 0 0 02305 12 Gasohol (E10) 0.9125 58.8659 83.4229 0 0 020043 20 Conventional Diesel 0 0 0 0 0 0Page 79Table 20 2008 Fuel SupplyFuelYearIDMonth GroupIDFuel FormulationIDMarket ShareMarket ShareCV2008 1 2305 1 0.52008 1 20043 1 0.52008 2 20043 1 0.52008 2 2302 1 0.52008 3 2302 1 0.52008 3 20043 1 0.52008 4 20043 1 0.52008 4 2303 1 0.52008 5 2303 1 0.52008 5 20043 1 0.52008 6 20043 1 0.52008 6 2304 1 0.52008 7 2304 1 0.52008 7 20043 1 0.52008 8 20043 1 0.52008 8 2304 1 0.52008 9 2304 1 0.52008 9 20043 1 0.52008 10 20043 1 0.52008 10 2303 1 0.52008 11 2302 1 0.52008 11 20043 1 0.52008 12 20043 1 0.52008 12 2302 1 0.5Page 80Table 21 Average Monthly Temperatures by Hour ofthe Day for St. Louis County in FahrenheitMonthIDHourID123456789101112125.5 28.1 39 48.2 56.2 70.2 71.8 68.8 62.4 50.7 38.8 24.4224.5 26.6 37.3 46.2 55 69.1 70.6 68.1 62.5 49.8 38.6 24.6323.6 25.2 36.1 45.1 53.8 68 69.9 67.2 61.6 49.1 37.8 23.9422.7 24.5 35.1 44.3 52.8 67 69.6 66.5 60.9 48.4 37 23.2521.9 23.9 34.2 43.6 52.1 66.1 68.9 65.9 60.4 47.6 36.3 22.5621.4 23.4 33.1 43.3 51.6 65.6 68.4 65.3 59.9 47.1 35.6 22.5721.2 23.1 32.6 43.3 53.2 67.7 69.7 65.8 59.8 46.6 35 22.5821.2 22.7 32.9 45.7 56.5 70.9 72.5 69.4 61.9 47.9 34.9 22922.5 24.1 36.4 48.9 59.4 73.9 75.7 72.8 65.2 52.2 37.8 23.91026.6 26.7 39.8 51.8 62.5 76.8 78.5 76.6 68.7 56.7 41.5 27.21130.8 29.5 43.3 54.6 65.2 79.3 81 79.5 72.2 60.7 45.1 31.11234.9 32.5 46.7 56.8 67.1 81.6 83.1 81.4 74.8 63.9 48.4 35.11338.2 35 49.4 59.3 68.4 83.1 84.8 83 76.8 65.8 50.9 38.71441 37.1 51.3 61 69.4 84 86.2 84.1 78.3 67.2 52.8 40.81542.5 38.5 52.7 62.4 70.8 84.8 87.2 84.8 79 67.9 54 421642.5 39 53 63.2 71.6 85 87.3 84.9 79 68.1 54.1 42.51741.6 38.6 53 63.1 71.9 84.9 86.8 84.6 78.4 67 52.8 40.81838.1 37.2 51.7 62.4 70.9 84 85.9 83.2 76.3 64.2 49.5 371934.2 34.6 49.1 60.1 69.3 82.5 83.9 80.5 72.3 59.9 46.6 34.42031.8 32.9 46.3 56.8 65.6 79.5 80.7 76.8 68.5 57.1 44.8 32.32130.1 31.6 44.4 54.4 62.5 76 77.4 73.9 66.6 55.5 43.4 30.62229.2 30.8 42.6 52.8 60.2 73.9 75.8 72.1 65.2 54.1 42.2 28.42327.9 29.5 41.7 51 58.4 72.4 74.4 70.8 64.1 52.9 41.1 272426.8 28.8 40 49.6 57.2 71.2 73 69.8 63.1 51.7 39.9 25.3Page 81Table 22 Average Monthly Percent Relative Humidityby Hour of the Day for St. Louis CountyMonthIDHourID123456789101112167.3 75.9 71.8 70 75.9 75.8 82.3 85 87.4 75.9 68.9 70.2268.1 77.1 72.2 72.6 76 78.1 83.3 85.8 87.7 77.6 70.3 71.8369.5 78.3 73.3 74.2 77.4 80 84.2 86.7 88.6 79.1 71.7 72.9470.3 78.5 74.4 74.7 78.5 81.3 84.7 87 89.5 79.6 72.5 73.8571.5 78.5 75.9 75.6 79.3 82.4 85.9 87.9 89.8 81.1 73.6 75.7672 78.8 77.7 76.1 80.5 83.3 86.2 88.4 90.1 82 75.4 76.4771.7 79.1 78 76.4 79.4 81.1 84.7 88.2 90.1 82.9 76.3 76.7871.4 78.4 78.6 72.5 75 75.6 79.8 83.2 88.6 82.4 76.6 76.6970.3 77.2 74.8 67.9 71 70 73.4 76.3 83.3 76.7 74.1 75.21066 74.2 69.9 63.7 65 64.7 67.9 68.6 76.2 67.6 68.2 72.71161.4 70.5 64.6 60.2 60 60 63.2 62.8 69.1 59.4 62.3 68.91256.7 67.1 59.6 57.8 57.5 55.2 59.2 58.4 63.5 53.1 57.5 661352.8 64.6 56 54.9 56.4 52.3 56.3 55.8 59.6 49.5 53.4 63.21449.8 62 53.9 53.1 55.1 51.3 54.2 53.9 57 47.2 50.4 61.21547.8 59.9 52.4 51.3 53.5 49.5 52.5 52.9 55.5 45.9 48.4 59.91646.8 59 52.7 49.9 52.7 48.6 52.5 52.9 55.3 45.5 47.5 59.21747.2 59.7 52.9 49.6 51.4 48.6 53.2 53.9 56.8 46.6 48.8 60.51850.6 61.2 54.8 50.5 51.4 49.7 54.7 56.4 61.5 51.4 53.2 64.11955.1 65.1 58.5 54 53.5 52.4 58.9 62 70.6 59.1 57.2 66.52058.2 68.2 62.5 58.2 59 57.9 65.8 69.8 78.6 65.1 60 67.92160.2 70.4 65.3 61.4 64.5 64.3 72.3 76.1 82.2 68.2 62.1 68.32261.9 72.1 67.7 63.6 69.2 69 75.5 80 84.2 70.4 64 68.62363.7 73.8 69.3 66.6 72.5 71.6 77.7 82.2 85.3 72.5 65.7 692465.2 75 71.1 68.3 74.6 74.3 80.1 83.9 86.5 74.6 67.4 69.7Page 82Table 23 Average Monthly Temperatures by Hour ofthe Day for St. LouisCity in FahrenheitMonthIDHourID123456789101112125.9 28.9 40.2 48.1 56 70.1 72.4 69.2 62.7 51.5 39.4 25.9225 27.5 38.4 46.2 54.9 69.1 71.2 68.5 62.9 50.7 39.2 25.9324 26.3 37.4 45.3 53.8 68 70.6 67.7 62.2 49.9 38.3 25422.9 25.4 36.3 44.3 52.9 67 70.1 67 61.5 49.4 37.8 24.6522.4 24.9 35.6 43.7 52.2 66.2 69.6 66.3 61 48.6 37.1 23.9621.7 24.4 34.5 43.4 51.8 65.6 69.1 65.9 60.6 47.9 36.4 23.9721.5 23.8 33.9 43.7 53.6 67.9 70.6 66.5 60.5 47.5 35.8 23.9821.3 23.5 34.2 46 57 71.2 73.5 70.2 62.6 48.8 35.8 23.2922.8 24.9 37.7 49.2 59.8 74.4 76.5 73.7 66 53.3 38.7 25.21027 27.5 41 52.1 62.9 77.4 79.2 77.5 69.5 57.8 42.5 28.41131 30.3 44.3 54.8 65.6 79.9 81.6 80.3 72.9 61.8 45.9 321235 33 47.4 57 67.7 82.1 83.6 82.3 75.4 64.8 49.3 35.91338.1 35.5 50.1 59.3 68.7 83.8 85.2 83.7 77.3 66.8 51.7 39.31441.1 37.4 51.8 61 69.7 84.5 86.7 84.9 78.7 68.1 53.5 41.51542.7 38.8 53.3 62.4 71.1 85.3 87.6 85.5 79.4 68.8 54.6 42.91642.5 39.3 53.6 63.2 71.7 85.4 87.8 85.5 79.5 68.8 54.6 42.91741.6 39.1 53.4 62.9 72 85.4 87.5 85.3 78.7 67.9 53.3 41.51838.1 37.7 52.2 62.1 71.2 84.4 86.4 83.8 76.8 65.1 50 37.71934.3 35.1 49.5 60.1 69.4 82.9 84.5 81.2 72.5 60.7 47.2 352032.1 33.4 47 56.7 65.8 79.8 81.4 77.2 68.5 57.8 45.2 33.42130.4 32.2 45 54.5 62.5 76 77.9 74.3 66.8 56.2 43.8 31.62229.5 31.3 43.5 52.8 60.2 73.6 76.2 72.3 65.5 54.9 42.7 29.82328.3 30.1 42.6 51 58.3 72.2 74.8 71.2 64.3 53.6 41.6 28.42427.2 29.6 41.1 49.5 57.1 71 73.6 70.3 63.4 52.4 40.6 26.8Page 83Table 24 Average Monthly Percent Relative Humidity by Hour of the Day for St. Louis CityMonthIDHourID123456789101112168 76.6 72.6 71.4 77 76.6 83.4 85.9 87.7 76.9 69.3 69.8269 78.1 73.2 73.8 76.9 78.7 84.2 86.5 87.7 78 71 71.3369.8 79 74 74.8 78 80.8 85.4 87 88 79.7 72.1 72.7470.9 79 75.2 75.9 79.1 81.9 85.6 87.6 88.9 80.3 72.3 73.6572.1 78.9 76.3 76.5 79.9 82.7 86.5 88.5 89.5 81.5 73.4 75.2672.4 79.2 78.4 77.4 80.5 83.9 86.8 88.5 89.8 82.7 75.2 75.8772.7 79.5 79 77.1 79.4 81.7 85.1 88.2 89.5 83.3 76.3 76.2872.3 79.1 79.4 73.4 75.1 75.9 80.1 83.3 88.3 83.1 76.3 76.4970.9 77.9 75.6 68.3 71 70 74 76.4 83 77 73.6 751066.7 74.9 70.6 64.2 64.8 64.5 68.4 68.9 75.7 67.4 68 72.51161.9 71.5 65.5 60.7 60.1 59.6 63.7 63.1 68.9 59.1 62.4 691257.4 68.3 60.7 58.5 57.1 55.3 59.7 58.7 63.6 52.8 57.2 66.11353.7 65.5 57 55.7 56.4 52 57.1 56.3 59.7 48.9 53.8 63.11450.6 63.3 55.1 53.7 55.1 51.2 54.6 54.2 57 46.4 50.7 61.11548.4 61.4 53.4 51.7 53.7 49.5 53.1 53.5 55.5 45.5 48.5 59.51647.8 60.3 53.4 50.4 52.9 48.9 52.7 53.5 55.1 45.3 47.8 59.11748 60.7 53.8 50.2 51.8 48.9 53.4 54.2 56.8 46.4 48.9 60.11851.2 62.1 55.8 51.4 51.4 49.9 55.2 57.1 61.6 51.3 53.3 63.61955.9 66 59.7 54.8 53.9 52.4 59.2 62.6 71.1 59.4 57.3 66.22058.7 69.2 63.6 59.6 59.7 58.2 66.3 71.1 79.7 65.7 60.6 67.52160.8 71.1 66.4 62.1 65.5 65 73.6 77.5 83.4 68.8 62.6 68.42262.5 73.1 68.7 64.8 70 70.2 76.8 81.4 84.8 71 64.5 68.72364.3 74.8 70.2 67.7 73.6 72.8 79.1 83.1 86.2 73.1 66.3 68.92466.1 75.7 71.8 69.4 75.7 75.3 81 84.8 87.1 75.5 67.8 69.6

### Page 84 3.3.2.3 On Road Source Emissions Summary

The MOVES model runs were set up selecti ng all available gasoline and diesel fuel vehicle type combinations, all months, days , hours, and all road types. The emissions were post-aggregated to the year level using MOVES.

A list of on road mobile emissions by count y and SCC is included in Appendix A-2.

Table 25 summarizes the 2008 annual on-road emissions by county as calculated using

MOVES 2010A for St. Louis C ity and St. Louis County.

Table 25 On Road Mobile 2008 CO Emissi ons for St. Louis City and St. Louis County 

### County Name CO Emissions (tons/year) St. Louis County 132,855.83
St. Louis City 34,576.81
Totals 167,432.64



### 4.0 Quality Assurance/Quality Control

4.1 Point Source QA/QC and Results

Prioritization

The EI Unit prioritizes review of those facilities that ha ve the largest bulk emissions, specifically facilities with a Part 70 or Inte rmediate operating permit. While every data element collected helps to characterize the emission estimate, in evaluating the data, those fields most directly tied to the emissions calculation ar e given the highest priority. The MoEIS database system itself was quality assured to provide smooth data transfer from the state inventory to the NEI.

Methods

The EI Unit’s general QA procedures utilize any and all of the techniques outlined in the EPA’s Emission Inventory Improvement Pr ogram (EIIP) Technical Report Series Volume 6: Quality Assurance Procedures. The unit groups these techniques into two basic categories: Phase I, or Bottom-Up QA procedures, and Phas e II, or Top-Down QA procedures. Top-Down Procedures analyze groups of emissions data that share a common trait and look for outliers, in keep ing with the ‘Reality Check’ technique. Bottom-Up Procedures evaluate individual EI Qs that are believed to be erroneous, whether due to a top-down analysis, erro rs found when entering the EIQ into the database, or inconsistencies br ought to the attention of the EI Unit by a third party. These bottom-up procedures utilize the ‘Peer Review ’, the ‘Sample Calculations’, or the ‘Independent Audit’ t echniques. Note that any of th ese techniques could be found in

### Page 85 either category; they have simply been men tioned in reference to the category in which they are most often found.

Quality checks are completed using computerized checks in the MoEIS automated system, exploiting its utility in ensuring that the necessary data is reported, and in providing an acceptable numeric ra nge for certain fields. It streamlines the process of ensuring that all data fields required for the EPA’s EIS system are present, are compatible with, and meet the needs of the EPA system. For example, emission release point records that were missing fields were corrected with the input of emission modelers and facility

staff. Outdated Source Classification Codes (SCC), units of measure, and control device codes were removed, and required data fields for stack emission release points were

added.

Phase I reviews address individual EIQs to reconcile discrepancies with emission data. Phase I reviews are generally done only on hardcopy submitted EIQs, but may also be done based on priority. Examples of EIQ issues that were encountered include throughputs and emission factors with incons istent units of m easure, emission unit

identifiers that are different from previous EIQs, and MoEI S-calculated emissions that differ from the emissions on the hardcopy forms. Technical staff conducting these reviews worked with the companies to make corrections to their EIQs and place written documentation of all changes in the hardc opy EIQ files stored in the fileroom. In addition, all changes made to EIQs are tracked in an elec tronic log file.

Phase II reviews take a top-dow n look at the emissions data. This phase involves running Access queries to identify potential issues to investigate further. The Phase II QA queries included ensuring condensable particulate emissions were reported, ensuring correct application of sulfur/ash cont ent in emission factors, and reviewing emission trends by facility and industry type to identify any anomalies. In a ddition, point source data from other databases incorporated by the EPA into the EIS, such as the Toxics Release Inventory (TRI) and the Clean Air Market s Division (CAMD), will be reviewed and compared to MoEIS data. Prioritization of the largest sources, largest changes, and largest anomalies is a top consideration, as is realizing a meaningful emission difference

within a reasonable amount of time. Any changes made to EIQs during the Phase II QA process will be done with input from the co mpanies, and written documentation of all changes will be placed in the EIQ files stored in the fileroom and in electronic files.

Results

Interannual Variability - Facilities that reported over 20 tons of chargeable emissions were examined to find sources with large in terannual variability. A list of 20 facilities was generated where plantwide chargeable emissions changed by more than 20%, and

each of these facilities were contacted to ve rify the source of the increase or decrease. Four facilities reported an emission change due to emission factor or control device changes, and the other 16 f acilities reported throughput chan ges were the cause of the emission differences. Since the cause of the emission variability has been documented, there is no cause for changes to the emissions report for these twenty facilities.

### Page 86 Local Agency QA – Four facilities in St. Louis City were selected for a detailed audit

based on their level of emissions and variati on from past year reporting. At the four facilities, over 20 emission units were audited to confirm throughput, appropriate emission factor use, appropriate control efficiency application, permitted equipment limits, and number of pollutants. Six emi ssion units were found to be incorrectly reported in the 2008 emission report, with one f acility having overreported almost 10 tons

of PM 10 

### , and another underreported 40 tons facil ity-wide. Phase 1 quality assurance steps were used on 14 facilities in Springfield, 7 facilities in St. Louis County, and twenty facilities in Kansas City. Throughputs, emissi on factors, incorrect calculations, and HAP reporting were reviewed for these sites.

Stack Parameters – In preparation for point source data submission to the NEI, the required data elements for stack emission rel ease points were queried to ensure the data

submittal could occur without errors. Of the over 2,600 stack release points associated with point source emission reports that ar e submitted to the 2008 NEI, almost 50% required quality assurance before they could be submitted. Three main quality assurance steps were taken to correct the stack data: missing data elements were filled in as possible, data elements that were out of range were quality assured, and previously submitted NEI data elements were compared to current Missouri emission report data to identify discrepancies. Filling in missi ng data elements took the most time because it required review of modeling file s, contact with local agency staff, or contact with the facility. Out of range data elements we re a much smaller portion of the quality assurance, but these were also corrected via modeling files and contac t with the facility. Discrepancies between the EIS and 2008 Missour i EIQ data were reconciled by accepting

the Missouri data instead of EIS data.

4.2 Nonpoint Source QA/QC

EI Unit staff has documented the following information for each nonpoint source category: source of data fo r activity, emission factors, allocation methodologies, nonpoint source SCCs covered, pollutants covered, and po int source subtraction in Table . Much of the documentation for EPA categories appears at the NEI website: http://www.epa.gov/ttn/chie f/net/2008inventory.html

Emission inventory staff participated in the ERTAC workgroup that developed many of the updated emission factors and methodologi es used for 2008 emission estimates, and the resulting emission factors were checked against those used in EPA templates for accuracy. All nonpoint source categories in the 2008 NEI will be reviewed, including those for which EPA is developing emissions estimates. The emission estimates were compared to the 2005 NEI to identify outlying or missing categories.

Quality checks of the EPA excel worksheets showed that three worksheets had incorrect emission factors when compared to the ERTA C summary emission factor page, and these were corrected before emissions were submitted. Several categories had spreadsheet

### Page 87 templates that omitted HAP calculations, and these were amended prior to completing the categories. Spot checks were also done on th e calculation pages to ensure formulas were followed, and no problems were found.

Quality assurance of the data included ch ecks against 2002 NEI data submissions, and completeness checks for the number of coun ties, number of pollutants, order of magnitude, and correct units of measure. Th e priority data checks showed no errors, but there are a few source categories included in the 2002 NEI that were not included in the 2008 NEI due to time constraints (see section 3.2).

4.3 Mobile Source QA/QC

4.3.1 Nonroad Source QA/QC

Quality control and quality assurance were conducted throughout the nonroad modeling process. Data collected from various data sources were verified and correctly entered or

transcribed into the model. In some instan ces, input values, i.e., temperatures and fuel values were double and/or trip le checked for accuracy to insure they corresponded to Missouri DNR data. In addition, a spot-che cking of the modeling results, including rerunning the model for those results in question, was performed to ensure reliability.

4.3.2 Onroad Source QA/QC

The data used for the modeling was origin ally collected for cr eating the 2008 NEI. Missouri DNR has conducted extensive quality assurance on the model inputs and the inputs have been reviewed by EPA. The i nputs were converted to MOVES formatting using EPA conversion tools. The MOVES c onverted data was double and/or triple checked to ensure accuracy. In addition, a spot-checking of the modeling results, including rerunning the model for those results in ques tion, was performed to ensure reliability.

### 1 of 16 

# Appendix A

‐ 1

List of Statewide Point Source CO Emissions by Facility

### 2 of 16 This page left intentionally blank.

### 3 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Amerenue-Kirksville Combustion Turbine 29001 0006 221112 0.05

Keller Construction Company-Keller Construction Company 29003 P011 324121 8.66

Archer Daniels Midland Co-Mexico Plant 29007 0002 311222 19.79

Harbison-Walker Refractories-Vandalia Plant 29007 0003 327124 20.69

Amerenue-Mexico Combustion Turbine 29007 0012 221112 0.11

Martinsburg Farmers Elevator-Martinsburg 29007 0033 42451

Teva Pharmaceuticals Usa Inc-Mexico 29007 0040 325412 0.51

VANDALIA POWER PLANT-VANDALIA 29007 0041 221112 0.08

Cerro Copper Casting Company-Cerro Copper Casting Company 29007 0047 331525 144.61

Mexico Plastic Company-Mexico 29007 0051 326111 0.07
Audrain Generating Station 29007 0053 221112 10.66

POET BIOREFINING-LADDONIA PLANT 29007 0054 325193 41.29

Efco Corporation-Efco Corporation 29009 0003 332321 4.34

Hydro Aluminum Wells-Monett 29009 0005 331421 14.26

SCHREIBER FOODS INC-SC HREIBER FOODS INC - MONETT 29009 0021 311513 10.99

Fasco Industries Inc-Cassville Plant 29009 0037 335312 1.23

Justin Boot Company-Cassville (Plant 414) 29009 0052 316213 0.14

ARCHITECTURAL SYSTEMS INC-MONETT 29009 0062 332321

GEORGE'S INC-POULTRY FEED MILL 29009 0066 311119 0.21

Lamar City Electrical Generation-Lamar 29011 0031 221112 0.20

BFI Waste Systems Of North Americ a Inc-Lamar Landfill & Prairie View Reg Waste 29011 0039 562212 125.44

Butler Municipal Power Plant-Butler 29013 0029 221112 0.08

CONTINENTAL COAL INC-COTTONWOOD CREEK MINE 29013 0036 212111 1.50

Natural Gas Pipeline Company-Marble Hill Plant 29017 0019 48621 161.20

Columbia Municipal Power Plant-Columbia 29019 0002 221112 137.00

University Of Missouri - Columbia-Pow er Plant 29019 0004 221112 681.51
Magellan Pipeline Company Llc-Columbia Station 29019 0005 48691 9.25

A B Chance Co-Allen Street Complex 29019 0039 335313 5.05

Christian Health Systems-Boone Hospital Cent er 29019 0045 62211 1.70
University Of Missouri - Columbia-Main Campus Sources 29019 0047 62211 -

Torque Traction Integration Technologies-Columbia 29019 0066 336211 0.35

Panhandle Eastern Pipeline-Centralia Compressor Station 29019 0077 48621 232.05

Columbia Sanitary Landfill-Columbia Sanitary Landfill 29019 0091 562212 76.16

Ameren Energy Generating Company-Columbia Energy Center 29019 0105 221112 0.37

Aquila Inc-Lake Road Plant 29021 0004 221112 165.26
Life Line Foods-St Joseph 29021 0016 311211 22.39

Albaugh Inc-Albaugh Inc 29021 0037 32532
Omnium Llc-St Joseph 29021 0045 32532 -

Weyerhaeuser-St Joseph 29021 0046 322211 4.25

Bartlett Grain Company Lp-St Joseph 29021 0056 42451
Ag Processing Inc-St Joseph - Lower Lake Road 29021 0060 311222 1.53
Heartland Regional Medical Center East-St Joseph 29021 0063 62211 4.25

### 4 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)
Silgan Containers Corp-Silgan Containers 29021 0064 332431 5.42

Altec Industries Inc-Altec Industries Inc 29021 0078 33312 1.95
Varco-Pruden Buildings-St Joseph 29021 0095 332311 -

St Joseph Landfill-St Joseph Landfill 29021 0105 562212 15.08

AG PROCESSING-ST. JOSEPH BIODIESEL 29021 0118 325199

Williamsville Materials-Poplar Bluff 29023 0003 212321

Pace Construction Co-Poplar Bluff Plant 29023 0021 324121 0.07
John J Pershing Va Medical Center-Poplar Bluff 29023 0027 62211 1.23

Gates Rubber Company-Poplar Bluff Division 29023 0032 32622 3.51
Briggs & Stratton Corp-Poplar Bluff 29023 0038 333618 30.85
Centerpoint Energy-Poplar Bluff Compressor Station 29023 0042 48621 130.90

Poplar Bluff Municipal Utilities-Generating Plant 29023 0050 221112 3.61

Butler County Sanitary Landfill-Allied Waste I ndustries 29023 0058 562212 50.51

Nordyne-Poplar Bluff 29023 0062 333415 0.01

Consumers Oil And Supply Company-Braymer Plant 29025 0008 42451

Harbison-Walker Refractories-Harbison-Walker Refr actories 29027 0001 327124 5.08

Fulton Power Plant-Fulton 29027 0007 221112 1.29

A P Green Industries Inc-Fulton Plant 29027 0010 327124 31.57

ABB Inc-Jefferson City Plant 29027 0019 335311 4.16
Fulton State Hospital-Fulton 29027 0021 62221 5.51

Amerenue-Callaway Nuclear Power Plant 29027 0026 221113 4.34
Modine Manufacturing Co-Modine Manufacturing Co 29029 0009 333415 1.61

Delta Asphalt Inc-Cape Girardeau 29031 0002 324121 37.21

Martin Marietta Materials-Appleton Quarry #368 29031 0008 212312 -

Southeast Missouri State Univer sity-Facilities Management 29031 0010 61131 33.90

Ceramo Co Inc-Jackson 29031 0012 327112 3.48

Lone Star Industries Inc-Cape Girardeau 29031 0021 32731 8,359.89

Procter & Gamble Paper Products Co-Neely'S Landing 29031 0053 322291 266.04
St Francis Medical Center-Cape Girardeau 29031 0058 62211 4.24

Jackson Municipal Utilities-Jack son Municipal Utilities 29031 0061 221112 0.12
Biokyowa Inc-Nash Road Site 29031 0064 325411 19.76

Nordenia U S A Inc-Neely'S Landing 29031 0072 31213 -
Consolidated Grain And Barge Co-Cape Girardeau 29031 0081 42451

Sinclair Oil Corp-Carrollton Station 29033 0001 48691 3.18

Agriservices Of Brunswick Ll c-Brunswick West 29033 0013 42451 -
Carrollton Municipal Utilities 29033 0022 221112 0.71

Ray-Carroll County Grain Growers Inc-Carrollton Facility 29033 0023 42451 0.20

SHOW ME ETHANOL LLC-CARROLLTON 29033 0036 325193 -

Martin Marietta-Greenwood Quarry #527 29037 0001 212312

Martin Marietta-Peculiar Quarry #528 29037 0002 212312

Aquila Inc-Ralph Green Generating Plant 29037 0003 221112 0.53

Southern Star Central Gas Pipeline-Peculiar Compress or Station 29037 0048 48621 6.58

Aries Power Plant-Pleasant Hill 29037 0056 221112 46.47

### 5 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

KCP&L GMO-SOUTH HARPER PEAKING FACILITY 29037 0063 221112 56.06
Dairiconcepts-El Dorado Springs 29039 0003 311514 8.20

Salisbury Station Platte Pipe Line Co-Salisbury 29041 0013 42472

National Starch & Chemical Co-National Starch & Chemical Co 29047 0002 311221 28.73
Archer Daniels Midland Co-ADM Milling Co 29047 0009 311211 0.59

Cook Composites And Polymers Co-North Kansas City 29047 0012 325510 5.19

Ford Motor Co-Kansas City Assembly Plant 29047 0019 336111 57.08
Bartlett Grain Company-Birmingham 29047 0025 42451

Cargill Inc-Chouteau Elevator 29047 0027 42451

Henry Wurst Inc-North Kansas City 29047 0032 323110 0.07
Midland Lithography Co-North Kansas City 29047 0033 323110 -

Davis Paint Co-Davis Paint Co 29047 0040 32551 -

Jesco Resources Inc-Jesco Resources Inc 29047 0052 324191 0.15

Hallmark Cards Inc-Distribution Center 29047 0059 323110 1.62

Tnemec Company Inc-Tnemec Company Inc 29047 0075 32551
Campbell Earl Mfg Co-Campbell Earl Mfg Co 29047 0079 32551
Independence Power And Light-Missouri City Stat ion 29047 0096 221112 8.85

Banta Publications-Kansa s City 29047 0122 336211 1.50

Sericol Inc-Sericol Inc 29047 0141 32591 0.07

Vertex Plastics Inc-Kearney 29047 0175 326191
Water Supply Division-Kansas City 29047 2227 22131 1.62
United Cooperative Inc-Plattsburg Elevator 29049 0016 42472 -

Amerenue-Moreau Combustion Turbine 29051 0008 221112 0.13

Unilever Hpc Usa-Jefferson City Plant 29051 0009 325611 3.21

Von Hoffman Press Inc-Jefferson City 29051 0028 323117
Modine Manufacturing Company-Jefferson City 29051 0032 336211 2.06

Johnson Controls Hoover Auto-Johnson Controls Hoover Auto 29051 0037 32614 -

Phillips Pipeline Company-Jefferson City Terminal 29051 0042 42471 32.25

Command Web Offset Missouri Inc-Jefferson City 29051 0043 323110 4.51

Amerenue-Fairgrounds Combustion Turbine 29051 0049 221112 0.25

Jefferson City Landfill-Laidlaw Waste Systems 29051 0058 562212 70.46

W R Meadows Inc-Boonville 29053 0003 321219 70.39

Caterpillar Inc-Caterpillar Inc 29053 0019 326291 1.80

Nordyne Inc-Boonville Plant 29053 0021 333414 0.74
Missouri Dept Of Corrections-Boonville Correction al Center 29053 0027 92214 2.67

Paramount Metalizing Co-Sullivan 29055 0043 32622
Landmark Mfg Corp-Landmark Mfg Corp 29061 0010 332313 1.34
Magellan Pipeline Company Llc-Osborn Station 29063 0009 48691 3.86

United Cooperative Inc-Osborn Elevator 29063 0013 42451
Royal Oak Enterprises Inc-Salem Briquet Plant 29065 0038 325191 38.34

White Oak Gin Company Inc-White Oak Gin Company Inc 29069 0010 115111 1.02

Graves Kennett Gin-Kennett 29069 0014 115111 0.13

Farmers Union Gin-Farmers Union Gin 29069 0018 115111

### 6 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Four Way Gin Company-Four Way Gin Company 29069 0027 115111

Cardwell Cooperative Inc-Cardwell Cooperative Inc 29069 0029 115111

Stokes Mayberry Gin Company-Stokes Mayberry Gin Company 29069 0032 115111 -
Kennett Generating Plant 29069 0063 221112 0.97

Campbell Municipal Power Plant 29069 0064 221112 0.20

Associated Electric Cooperative Inc-St Francis Power Plant 29069 0066 221112 30.23

Amerenue-Labadie Plant 29071 0003 221112 2,494.33
Canam Steel Corp-Canam Steel Corp 29071 0014 332312 0.14

Steelweld Equipment Co-St Clair 29071 0020 336211 0.17

Jefferson Smurfit Corp-Pacific 29071 0031 322212 -

Meramec Industries Inc-Ramsey St Plant 29071 0068 326121 0.06

Bull Moose Tube Company-Bull Moose Tube Company 29071 0087 33121 0.32

Sullivan Precision Metal Finishing In c-Sullivan Precision Metal Finishing

Inc 29071 0131 332813 -
Sporlan Valve Company-Plant #2 - West Main 29071 0132 332911
Integram - St Louis Seating-Pacific 29071 0144 33636 0.48

Aerofil Technology Inc-Aerofil Technology Inc 29071 0151 311942 0.39

Magnet Llc-Washington 29071 0153 33995

Marble Decor Inc-Marble Decor Inc 29071 0154 326121 -

Plaze Incorporated-Plaze Incorporated 29071 0157 311942 0.35
GDX Automotive - Danny Scott Drive-New Haven 29071 0173 31332
Sporlan Valve Company-Plant #3 - Lange Drive 29071 0178 332919

RR Donnelley-Owensville 29073 0008 323110 1.58
Carlisle Power Transmission Products Inc-Springfield 29077 0004 326220 5.97

James River Power Plant 29077 0005 221112 1,195.87
Bristol Manufacturing Corp-Bristol Manufacturing Corp 29077 0008 311513 0.91

Aarons Automotive Products Inc-Westgate Ave Facility 29077 0010 336211 192.96
Interstate Brands Corporation-Butternut Bread 29077 0011 311812 0.75

Clariant Life Science Molecules-Clariant Life Science Molecules 29077 0017 325411 1.79

Sweetheart Cup-Sweetheart Cup 29077 0021 322215 2.11

Kraft Foods North America Inc-Kraft Foods North America Inc 29077 0026 311513 9.33
St John'S Regional Health Center-Springfield 29077 0028 62211 16.38
Dairy Farmers Of America Inc-Springfield 29077 0036 311514 7.82

Southwest Power Plant 29077 0039 221112 154.05

Southwest Mo State Univ-Physical Plant 29077 0047 61131 6.15
3M Company-Springfield ITSD/TMD 29077 0051 32552 6.00
General Electric-Springfield 29077 0056 335312 0.84

Magellan Pipeline Company Llc-Springfield Terminal 29077 0116 48691 17.94
City Utilities Of Springfield-Main Avenue Gas Tu rbine 29077 0145 221112 0.02
Springfield Sanitary Landfill-Willard 29077 0161 562212 90.80

City Utilities Of Springfield-Fulbright Treatment Plant 29077 0163 92613 0.09
N L McCartney Dist Generation 29077 0164 221112 21.29

CITY UTILITIES OF SPRINGFIELD MISSOURI-NOBLE HILL LANDFILL
RENEW ENGY CTR 29077 0170 221119 97.45

### 7 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Trinity Industries Inc-Trinity Industries Inc 29077 0200 48711 -
Superior Solvents & Chemicals-Superior Solvents & Chemicals 29077 0228 42469

Modine Manufacturing Company-Trenton 29079 0004 336211 3.32

Trenton Municipal Utilities-Trenton Peaking Pl ant 29079 0027 221112 0.37
Magellan Pipeline Company Llc-Ridgeway Station 29081 0010 48691 19.60

Montrose Generating Station 29083 0001 221112 517.37

Tracker Marine-Clinton Plant 29083 0031 336612 2.03
Schreiber Foods Inc-Packaging Converting Plant 29083 0033 322221 0.54

Exide Technologies-Canon Hollow 29087 0001 331314 3.47
Golden Triangle Energy-Craig 29087 0016 32511 4.07
Smith Flooring Company-Mountain View 29091 0005 321918 30.17

Systems & Electronics Inc-West Plains 29091 0011 336212 0.15

Garnett Wood Products-Charcoal Plant 29091 0038 325191 982.05

Bruce Hardwood Floors-Bruce Hardwood Floors 29091 0046 321113 22.44
West Plains City Power Station 29091 0068 221112 0.01

Doe Run Company-Buick Mill 29093 0005 212231 -

Doe Run Company-Glover Smelter 29093 0008 331419 0.01

Doe Run Company-Buick Smelter 29093 0009 331419 13,390.57
Bp Products North America Inc-Sugar Creek Terminal 29095 0002 32411 1.07

U S Dept Of Energy-Kansas City Plant (Alliedsignal) 29095 0005 33422 1.07

Bayer Cropscience-Kansas City 29095 0011 32532 25.81
Clay & Bailey Mfg Co-Clay & Bailey Mfg Co 29095 0012 331511 0.05

Folgers Coffee Co-Folgers Coffee Co 29095 0017 31192 331.48
Trigen Energy Corporation-Grand Avenue St ation 29095 0021 221112 34.41

Hawthorn Station 29095 0022 221112 2,406.55

Kansas City Power & Light Co-Northeast Station 29095 0023 221112 0.09

Wolcott & Lincoln Jackson Llc-Kansas City 29095 0026 42451

Lafarge North America Inc-Independence Plant 29095 0030 32731 639.59
Aquila Inc-Sibley Generating Station 29095 0031 221112 370.96

Vance Brothers Inc-Vance Brothers Inc 29095 0037 324121 18.54

Blue River Treatment Plant-Blue River Treatment Plant 29095 0039 562211 28.33
Alliant Llc-Lake City Army Ammunition Plant 29095 0046 332992 26.59
Blue Valley Station 29095 0050 221112 53.07

Koch Materials Company-Koch Materials Company 29095 0064 324121 0.40

Independence Regional Health Center-Independenc e 29095 0066 62211 0.98
Peterson Mfg Co-Grandview 29095 0075 336321 0.51
Barber & Sons Aggregates-Barber & Sons Aggregates 29095 0076 212312 10.24

Hallmark Cards-Hallmark Cards 29095 0114 323110 3.07
Aquila Inc-Greenwood Energy Center 29095 0139 221112 14.18
Ball Metal Beverage Container Co -Kansas City 29095 0175 332431 6.72

Unilever Bestfoods North America-Unilever Bestfoods North America 29095 0178 311421 8.74

Aero Transportation Products Inc-Independence Plant 29095 0191 336211
Independence Power And Light-Sub Station I 29095 0222 221112 0.07

### 8 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)
Independence Power And Light-Sub Station H 29095 0223 221112 0.55
Independence Power And Light-Sub Station J 29095 0224 221112 0.03

Tiffany Marble Inc-Lee'S Summit 29095 0244 326121 -
Courtney Ridge Landfill Llc-Courtney Ridge Landfill Llc 29095 0267 562212 129.38

Lee'S Summit Sanitary Landfill-Lee'S Summit Sanitary Landfill 29095 0272 562212 37.96

Rumble Recycling And Disposal-S anitary Landfill Rumble 1 & 2 29095 0273 562212 22.83

LAFARGE NORTH AMERICA INC-COURTN EY RIDGE QUARRY 29095 0321 212312
Cargill Inc-Kansas City 29095 2001 311222 1.82

Crown Center Redevelopment Corporation-Kansas City 29095 2007 72111 9.65

Research Medical Center-Research Medical Center 29095 2054 62211 2.40

Cook Brothers Insulation Inc-Cook Brothers Insulation Inc 29095 2058 32614 -

Baptist Medical Center-Baptist Medical Center 29095 2087 62211 0.88

Allied Waste Industries Sanitary Landfil-Kansas City Landfill 29095 2101 562212 66.75

Truman Medical Center - East-Truman Medical Center - East 29095 2154 62211 0.04

International Paper Company-Inter national Paper Company 29095 2177 322211 2.62

New Surface Llc-East 12th 29095 2224 327991 0.00

SUN CHEMICAL-KANSAS CITY 29095 2431 325910

Empire District Electric Co-Asbury Plant 29097 0001 221112 195.75
Dyno Nobel Inc-Carthage Plant 29097 0007 32592 5.49
ADM Milling Company-Carthage Flour Mill 29097 0011 311211 0.07

Tamko Roofing Products Inc-High St Plant 29097 0013 324122 8.14
St John'S Regional Medical Center-St John'S Regional Medical Center 29097 0021 62211 4.24
Justin Boot Company-Carthage (P lant 417) 29097 0058 316219

Empire District Electric Co-E mpire Energy Center 29097 0062 221112 6.01
Modine Manufacturing Company-Joplin 29097 0065 332313 0.43
Magellan Pipeline Company-Carthage Terminal 29097 0079 48691 2.36

Able Manufacturing & Assembly L L C -Schifferdecker 29097 0089 336211

Tamko Roofing Products Inc-Rangeline Plant 29097 0094 324122 88.27
Able Manufacturing Corporation- 7th Street 29097 0095 326121

Empire District Electric Co-State Line Facility 29097 0104 221112 650.53
Carthage Water & Electric 29097 0110 221112 3.79
Eagle-Picher Technologies Llc-Federal Systems 29097 0117 335911 0.18

Pechiney Plastic Packaging Inc-Joplin Plant 29097 0132 323112 2.08
ICI Explosives Environmental Co-Joplin 29097 0138 562211 0.35
Leggett & Platt-Wire Mill - Carthage Central Ave 29097 0143 331222 12.67

DYNAMIC FINISHES - JOPLIN 29097 0154 333131

Rc Cement Company Inc-River Cement Co - Selma Plant 29099 0002 32731 302.96

Doe Run Company-Herculaneum Smelter 29099 0003 331419 23.25

Union Pacific Railroad Co-Desoto Car Shop 29099 0011 336510 1.27

Trautman Quarry-Pevely 29099 0012 212312

Dow Chemical Company The-Riverside Plant 29099 0014 325211 1.11

Amerenue-Rush Island Plant 29099 0016 221112 1,333.35
Metal Container Corporation-Arnold 29099 0044 332431 9.43

### 9 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)
Engineered Coil Company-D B A Marlo Coil 29099 0052 336611 0.02

Saint-Gobain Containers Llc-Pevely 29099 0068 327213 8.30

Bussen Quarries Inc-Antire Quarry 29099 0103 212312

Carondelet Corporation-Carondelet Corporat ion 29099 0111 331513 4.14

Aero Metal Finishing-Aero Metal Finishing 29099 0114 332813
Central Missouri State University-Physical Plant 29101 0002 61131 5.60
Stahl Specialty Co-Kingsville Plant 29101 0003 331524 10.16

Whiteman Air Force Base-Whiteman 29101 0009 92811 15.54

Hawker Energy Products Inc-Warrensburg 29101 0023 335912 2.72
Show-Me Regional Landfill-Show-Me Regional Landfill 29101 0046 562212 46.45

Holden Power Plant 29101 0051 221112 0.57

Master Marble Inc-Holden 29101 0054 326121 -
Independent Stave Co Inc-Lebanon Plant 29105 0001 321920 37.88

Lowe Boats-Omc Aluminum Boat Group 29105 0006 336612 0.16

Detroit Tool & Engineering-Lebanon 29105 0013 332212
Marathon Electric Mfg Corp-Lebanon Plant 29105 0033 335312 0.28

G3 Boats-Lebanon 29105 0038 336612

Tracker Marine-Lebanon Plant 29105 0046 336612 0.23

S & K Industries Inc-S & K Industries Inc B #1 29107 0004 337122 2.00

Wincup-Higginsville Plant 29107 0010 325211 5.40

S & K Industries Inc-S & K Industries Inc B #2 29107 0029 321912

Higginsville Municipal Power Facility 29107 0038 221112 0.43
Bartlett Grain Company Lp-Waverly 29107 0050 42451 0.00

NEW SURFACE-ODESSA 29107 0063 326121 0.01
Razorback Pipeline Company-Transmontaigne Product Services Inc 29109 0002 49311 0.30

Bcp Ingredients-Verona Plant 29109 0004 325411 1.61

Mo Rehabilitation Center-Mo Rehabilitation Center 29109 0008 62211 1.06

ConocoPhillips Co-Mount Vernon Products Terminal 29109 0036 42471 18.78
E F Marsh Engineering Company-Mt Vernon 29109 0051 333922

AYERS OIL CO-CANTON 29111 0019 424710
Old Monroe Elevator & Supplies-Old Monroe 29113 0003 311119 0.04

Toyota Motor Corporate Services-Bodine Aluminum Inc 29113 0029 331524 4.70

Farmers Elevator & Supply Co-Hawk Point 29113 0042 42491 0.02

Most Inc-Troy 29113 0046 331314 1.46
Walsworth Publishing Company-Marceline 29115 0001 323110 0.04

Chillicothe Municipal Utilities 29117 0002 221112 0.22

Donaldson Co Inc-Donaldson Co Inc 29117 0012 336211 1.16

Simmons Foods Inc-Southwest City 29119 0017 311615 52.65

Superior Maple Hill Landfill-Macon 29121 0027 562212 41.59

Northeast Missouri Grain Llc-Macon 29121 0028 32511 66.39

MACON MUNICIPAL UTILITIES-NEMO GENERATING STATION 29121 0033 221112 12.02

MACON MUNICIPAL UTILITIES-KELLOGG AVE 2912 1 0035 221112 0.25

MACON MUNICIPAL UTILITIES-NOLL DRIVE 29121 0036 221112 0.12

### 10 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)
Centerpoint Energy-Twelve Mile Compressor Station 29123 0018 48621 194.01

Versa-Tech Inc-Fredericktown 29123 0022 32614 -
Kingsford Manufacturing Co-Briquetting Plant 29125 0001 325191 22.89
BASF Agri Chemicals-Hannibal Plant 29127 0001 32532 147.32
Magellan Pipeline Company Llc-Palmyra Station 29127 0002 48691 3.04

Fasco Industries Inc-Eldon Plant 29131 0032 335312 0.05
Gates Rubber Company-Gates Rubber Company 29133 0014 32622 0.92
Consolidated Grain And Barge Co-Dorena Facility 29133 0016 49313 -

Monroe City Power Plant-Monroe City 29137 0028 221112 0.04
Christy Minerals Co-High Hill 29139 0008 212324 82.34

Associated Electric Cooperative Inc-New Madrid Power Plant 29143 0004 221112 1,100.66

Noranda Aluminum Inc-Noranda Aluminum Inc 29143 0008 331312 24,770.83

Mahan Gin Co-Mahan Gin Co 29143 0012 115111 0.02
Portageville Farmers Gin Inc-Portageville Farmers Gin Inc 29143 0013 115111

Plastene Supply Company-Div Siegel-Robert Inc 29143 0015 326121 0.65

Mccord Gin Company-Gideon 29143 0023 115111 -
Cargill Inc-New Madrid 29143 0027 325314

A C Riley Cotton Company-New Madrid Gin 29143 0046 115111

Bootheel Cotton Company Inc-Matthews 29143 0047 115111 -

Bunge North America Inc-Linda Elevator 29143 0062 42451 0.03
La-Z-Boy Chair Company-La-Z-Boy Midwest 29145 0005 337121 0.81
Fag Bearings Corporation-Joplin 29145 0007 332991 22.08

Premier Turbines-Neosho Plant 29145 0044 336412 12.45
Southern Star Central Gas Pipeline-Saginaw Compress or Station 29145 0049 48621 7.95

Northwest Missouri State University-Maryv ille 29147 0005 61131 57.07
Eveready Battery Co Inc-Maryville Plant 29147 0008 335912 1.90

Kawasaki Motors Mfg Corp-Kawasaki Motors Mfg Corp 29147 0023 333618 84.25

Anr Pipeline Company-Maitland Compressor Station 29147 0024 486210 236.82
Consumers Oil Co Inc-Maryville Plant 29147 0027 42451

Nodaway Plant 29147 0032 221112 0.12
Central Electric Power Cooperative-Chamois Plant 29151 0002 221112 78.38

Quaker Window Products Company-Quaker Window Products Company 29151 0050 332321 0.56

L Berry Gin Company-L Berry Gin Company 29155 0021 115111 0.10

Still Gin & Grain Inc-Steele 29155 0024 115111 -

Trinity Marine Products Inc-Caruthersville - Plant #75 29155 0030 336611 0.50

Loxcreen Company Inc-Hayti 29155 0045 331316 3.53

Trinity Marine Products Inc-Caruthersville Plant #73 29155 0049 326121 0.12

Bunge North America Inc-Caruthersville Plant 29155 0063 42451 -

Tg Missouri-Perryville 29157 0019 336211 2.67

Falcon Foam-Falcon Foam 29157 0020 326121 2.28
H & G Marine Service Inc-Perryville 29157 0022 332439

Tnt Plastics Inc-Perryville 29157 0027 326113 -
Martin Marietta Materials-Carolina Asphalt Company 29157 0032 324121 0.44

### 11 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Martin Marietta Materials Inc-Perryville Quarry #366 29157 P023 212312
Lafarge North America Inc -Sedalia Quarry & Asphalt 29159 0002 212312 9.15

Pittsburgh-Corning Corp-Pittsburgh-Corning Corp 29159 0009 327993 22.34

Waterloo Industries Inc-Waterloo Industries Inc 29159 0012 332117 5.99
Alcan Cable-Div Of Alcan Products Corporation 29159 0022 331319 2.26

Hayes Lemmerz International Inc-Sedalia 29159 0027 336211 4.96
Tyson Foods Inc-Sedalia Processing Plant 29159 0037 311615 32.29

Gardner Denver Inc-Sedalia Plant 29159 0039 333912 -

Missouri Pressed Metals Inc-Sedalia 29159 0041 332117 0.00

Panhandle Eastern Pipe Line Co-Houstoni a 29159 0047 48621 341.54
Edwards Fiberglass Inc-Sedalia 29159 0056 326191

WEST CENTRAL CONCRETE LLC-SNOW RD 29159 0058 327320 -

EDWARDS FRP REPAIR-WING ATE 29159 0059 325211
University Of Mo - Rolla-Rolla Power Plant 29161 0006 61131 23.79

Manchester Packaging Company-Manchester Packaging Company 29161 0039 326121 0.01

Rolla Municipal Utilities-Multiple Peaking Plants 29161 0054 221112 0.01
Holcim (Us) Inc-Clarksville 29163 0001 32731 1,734.85

Aqualon Div Of Hercules Inc-Missouri Chemical Works 29163 0002 32511 54.23

Wayne B Smith Inc-Wayne B Smith Inc 29163 0008 212312 0.03

Bunge North America Inc-Louisiana Plant 29163 0025 49313 0.11

Dyno Nobel Inc-Lomo Plant 29163 0031 325311
Eagle Ridge Landfill-Bowling Green 29163 0040 562212 0.94
Amerenue-Peno Creek Energy Center 29163 0047 221112 2.18

American Airlines-Mci Maintenance And Engineering Base 29165 0005 336411 -
Kansas City Power & Light Co-Iatan Generating Station 29165 0007 221112 628.83
Package Service Co Llc-Package Service Co Llc 29165 0021 323112 -

Woodbridge Corporation-Kansas City Foam Div 29165 0028 32614 1.21

KCI Airport - KCMO Aviation Dept 29165 2404 488111 3.20

Harley Davidson Motor Company-Kansas City Plant 29165 2415 336991 6.42

FACILITY OPERATION SERVICES LLC-NW 112TH 29165 2424 221330 13.15

Tracker Marine-Bolivar Plant 29167 0028 336612 -

Manscen And Fort Leonard Wood-Manscen And Fort Leonard Wood 29169 0004 928110 9.45

Associated Electric Cooperative Inc-Unionville Power Station 29171 0015 221112 0.01

Continental Cement Company Inc-Ilasco Plant 29173 0001 32731 84.78

ENNIS PAINT INC-SAVERT ON 29173 0021 325510

Buckhorn Rubber Products Inc-Buckhorn Rubber Company Inc 29173 0037 32622 - Associated Electric Cooperative In c-Thomas Hill Energy Center-Power

Division 29175 0001 221112 4,486.18
Amerenue-Moberly Combustion Turbine 29175 0010 221112 0.13

OFFICE OF ADMINISTRATION FMDC-MOBERLY CORRECTIONAL
CENTER 29175 0034 922140 6.92

Wilson Trailer Sales Inc-Moberly 29175 0061 336212 0.21

Doe Run Company-Bunker (Fletcher Mine) 29179 0006 212231 -

Amerenue-Sioux Plant 29183 0001 221112 765.30

### 12 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Fred Weber Inc-O'Fallon Asphalt Plant 29183 0004 324121 15.54

Fred Weber Inc-O'Fallon Stone Plant 29183 0007 212312

McDonnell Douglas Corp-Boeing Company 29183 0010 334413 2.15

St Joseph Health Center-St Joseph Health Center 29183 0019 62211 3.18

Memc Electronic Materials Inc-St Peters Plant 29183 0027 334416 10.07

General Motors-Wentzville Center 29183 0076 336111 101.51
O Fallon Casting Llc-O Fallon 29183 0077 331512 1.55

Woodbridge Corporation-St Peters 29183 0129 32614 -

Superior Home Products Inc-Superior Home Products Inc 29183 0131 326121 -
True Manufacturing Co-O'Fallon 29183 0184 333415 1.39

Mississippi Lime Company-Mississippi Lime Co 29186 0001 32741 11,815.05

Biltbest Windows Corp-Ste Genevieve 29186 0003 321911 0.49

Tower Rock Stone Co-Ste Genevieve 29186 0022 212312

Centerpoint Energy-Ste Genevieve Compressor Station 29186 0024 48621 9.73

Chemical Lime Company-Ste Genevieve 29186 0035 32741 28.37

Lead Belt Materials Co Inc-Park Hills 29187 0001 212312 4.30

Vessell Mineral Products-Vessell Mineral Products 29187 0002 327124 32.06

Flat River Glass Co-Park Hills 29187 0017 327211 4.76
Playpower Lt Farmington Inc-Iron Mountain Forge Corp 29187 0041 337121 2.67

S-R Products-Farmington 29187 0048 336991 0.21

Base Rock Minerals Inc-Bonne Terre Plant 29187 0072 212312 1.70

FARMINGTON LIGHT & POWER-FARMINGTON 29187 0075 221112 0.10

Chrysler Assembly Plant 1-Fenton 29189 0002 336111 21.86

Amerenue-Meramec Plant 29189 0010 221112 3,811.99

Fred Weber Inc-North Stone 29189 0017 324121

Fred Weber Inc-South Stone 29189 0019 324121

Monsanto World Headquarters-Lindbergh Blvd 29189 0020 54171 10.33
U S Silica Company-Pacific 29189 0021 212322 3.51

Dana Corporation-Perfect Circle Division 29189 0025 336311 0.87
Pharmacia-Chesterfield Village 29189 0032 32511 14.82

Rockwood Pigments Na Inc-E Hoffmeister 29189 0035 325131 8.27

Washington University-Millbrook Blvd 29189 0042 61131 18.42
St Louis Post-Dispatch-Dunlap Ind Dr 29189 0057 51111 0.16

Sunnen Products Company-Maplewood 29189 0064 333512 1.01

St Louis Airport Authority-Lambert International Blvd 29189 0065 336212 9.38

Simpson Construction Materials Llc-West Lake Quarry & Material Co 29189 0111 212312 15.71
Energy Petroleum Company-Kienlen 29189 0141 42471

Printpack Inc-Hazelwood Plant 29189 0208 322221 3.45

Metropolitan St Louis Sewer Distri ct-Lemay Waste Water Treatment

Plant 29189 0217 22132 321.07
Nesco Container Corp-Fenton 29189 0226 332439 1.07
McDonnell Douglas Corp /Boeing Company-Lindbergh Plant 29189 0230 336411 20.96

Chrysler Corp-North Plant 29189 0231 336111 65.23

### 13 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)
St Louis Lithographing Company-Heege Avenue 29189 0238 323110

Multiplex Display Fixture-Fenton 29189 0242 337127 0.49

Bussen Quarries Inc-Bussen Road 29189 0275 212312

Ruprecht Quarry-Paule Rd 29189 0276 212312

BFI Missouri Pass Landfill-Maryland Heights 29189 0281 562212 30.58

Color Art Inc-Crestwood 29189 0282 323110 1.01

Fred Weber Inc Sanitary Landfill-St Louis County 29189 0308 562212 130.13
Onyx Oak Ridge Landfill Inc-(West County) 29189 0310 562212 44.89

Bridgeton Landfill Authority-Bridgeton 29189 0312 562212 244.28

Flex-O-Lite Inc-Fenton 29189 0315 327215 -

Pro-Tect Mfg Inc-Ferguson Ave 29189 0317 32614
St Marys Health Center-Richmond Heights 29189 0318 62211 6.74

Camie-Campbell Inc-Watson Industrial Park 29189 0327 325520

Belt Service Corp-Earth City 29189 1012 326220 0.47

Kv Pharmaceutical Company-Brentwood 29189 1015 325412 -
Depaul Health Center-Bridgeton 29189 1029 62211 6.05

Kv Pharmaceutical Company-Schuetz Rd 29189 1047 325412 1.22

Veterans Admin Medical Center-Jefferson Barracks Drive 29189 1052 62211 -

Reichhold Chemicals Inc-Valley Park 29189 1097 325211 4.40

St Luke'S Hospital-Woods Mill Road 29189 1101 62211 5.24

St Joseph Hospital-Kirkwood 29189 1156 62211 2.99

Pan-Glo St Louis-Trenton Avenue 29189 1192 811310

Whitmire Microgen Research Laboratory-Kirkwood 29189 1204 32532

Metropolitan St Louis Sewer Distri ct-Mo River Wasterwater Treatment

Plant 29189 1205 22132 7.10

Metropolitan St Louis Sewer District-Coldwater Creek Sewage

Treatment Plant 29189 1210 22132 50.69
Simpson Construction Materials Llc-Valley Park 29189 1226 324121 20.28

Fred Weber Inc-South Asphalt 29189 1248 324121 24.49

Fred Weber Inc-North Asphalt H & B 29189 1249 324121 37.15

Fred Weber Inc-North Asphalt B & G 29189 1250 324121 37.42

Gkn Aerospace Services Inc-Berkeley 29189 1489 336413 11.36

F & S Real Eastate Inc-St Louis 29189 1520 323112

KV PHARMACEUTICAL-BRIDGETON 29189 1538 325412 -
Conagra Foods-Marshall Plant 29195 0004 311412 4.08

Marshall Municipal Utilities 29195 0010 221112 45.49

MID-MISSOURI ENERGY INC-MALTA BEND 29195 0046 325193 64.50

Tetra Pak Materials-Sikeston 29201 0003 32213 -

Sikeston Power Station-Sikeston Power Station 29201 0017 221112 287.95

TEPPCO-Cape Girardeau Term inal 29201 0018 48691

Havco Wood Products Inc-Havco Wood Products Inc 29201 0021 321113 57.98
Crowder Gin Company Inc-Sikeston 29201 0073 115111 0.03

Texas Eastern Transmission Corporation-Oran Facility 29201 0099 48621 29.32

### 14 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Manac Trailers Usa Inc-Oran 29201 0102 333294 0.01

CONSTRUCTION TRAILER SPECIALISTS INC-SIKESTON 29201 0110 336212

CONSOLIDATED GRAIN AND BARGE CO-CONSOLIDATED GRAIN
AND BARGE CO 29201 8001 424510 0.23

Missouri Hardwood Flooring Co-Missouri Hardwood Flooring Co 29203 0005 321113 19.55

Cerro Copper Tube Company-Cerro Copper Tube Company 29205 0010 331421 82.30

Shelbina Power Plant 29205 0011 221112 0.01

Ames True Temper Inc-Bernie North Plant 29207 0007 321999 6.92

J P Ross Cotton Co Inc-J P Ross Cotton Co Inc 29207 0008 115111 0.05

Nestle Purina Petcare Company-Bloomfield 29207 0014 212324 43.19

Stoddard County Cotton Co-Bernie 29207 0018 115111 0.23

W W Wood Products-Dudley 29207 0019 321113 0.64
Lemons Sanitary Landfill-Lemons Sanitary Landf ill 29207 0062 562212 67.28

Essex Power Plant 29207 0064 221112 0.01
Table Rock Asphalt Constr Co Inc-Quarry #3 & Concrete Plant 29209 0007 212312

Horner Charcoal Co Inc-Horner Charcoal Co Inc 29213 0002 325191 0.86

Table Rock Asphalt Constr Co Inc-Hwy 248 Quarry 29213 0003 212312 1.03

Royal Oak Enterprises-Royal Oak Enterprises 29213 0007 325191 26.06
College Of The Ozarks-Branson 29213 0048 61131 1.85

Dairy Farmers Of America Inc-Cabool 29215 0026 311514 7.69

Woodpro Cabinetry Inc-Cabool 29215 0060 33711 9.92

3M Company-Nevada - Commercial Graphics 29217 0004 326121 20.58

Aquila Inc-Nevada Gas Turbine 29217 0034 221112 0.01

PRAIRIE PRIDE INC-EVE 29217 0043 311222 10.61

Holland Usa-Warrenton Facility 29219 0013 332117 0.00

Warrenton Copper Llc-Warrenton 29219 0028 331314 6.59
Greif Inc-Wright City 29219 0036 322214 0.09

Cascades Plastics Inc-Warrenton 29219 0038 32614

Red Wing Shoe Company Inc-Potosi 29221 0008 316214

Buckman Laboratories Inc-Cadet 29221 0018 311942 2.45

Purcell Tire-Purcell Tire 29221 0022 443112 2.10

IESI CORPORATION-TIMBER RIDGE LANDFILL 29221 0031 562212

Steel Processors-Steel Processors 29225 0026 336212 0.31

Hutchens Industries-Mansfield Steel Div 29229 0001 336212 0.29

Black Oak Recycling & Disposal Facility-Div Waste Corporation Of

America 29229 0022 562212 39.35

Anheuser-Busch Inc-St Louis 29510 0003 312120 145.98

Mallinckrodt Inc -Mallinckrodt Inc 29510 0017 32511 77.49

Precoat Metals-Precoat Metals 29510 0027 332812 5.10
ADM Gromark River Systems-St Louis 29510 0031 311211 0.00

Trigen-St Louis Energy Corp-Ashley Street Station 29510 0038 221112 46.27
Washington Univ Medical School-Boiler Plant 29510 0040 62211 28.23

Fred Weber Inc-Asphalt Plant 29510 0047 324121 9.56

Metropolitan St Louis Sewer District-Bissel Plant 29510 0053 92411 552.29

### 15 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Procter & Gamble-Procter & Gamble 29510 0057 325611 9.89

Dial Corp-Dial Corp 29510 0063 325611 8.39

Elementis Specialties Inc-Elementis Specialties Inc 29510 0066 325131 6.78

Astaris Llc-Carondelet Plant 29510 0070 211112 27.07
P D George Co (The)-P D George Co (The) 29510 0096 32551 3.73

U S Paint Div Of Grow Group-U S Paint Div Of Grow Group 29510 0097 32551

Alumax Foils Inc-Alcoa Foil Products/Alumax Foils Inc 29510 0118 322225 14.02
ADM/TPC Milling Co-Pillsbury Company 29510 0159 311211 -

Poly One Corporation-St Louis 29510 0161 32551

Marquette Tool & Die-Marquette Tool & Die 29510 0162 314999
St Louis Metallizing-St Louis 29510 0175 332812 0.08

Italgrani Elevator-Italgrani Elevator 29510 0179 42451 3.22
St Alexius Hospital-St Louis 29510 0200 62211 0.33

Bjc Health System-Pavillion 29510 0204 62211 1.51

Sensient Colors Inc-Baldwin Plant 29510 0269 31192 2.41

Hermann Oak Leather Co-Hermann Oak Leather Co 29510 0391 31611 -
Lange-Stegmann Co-Lange-Stegmann Co 29510 0468 42491 0.00

Sigma - Aldrich Co-Sigma - Aldrich Co 29510 0697 325199 3.14

Chemisphere Corporation-Chemisphere 29510 0808 32511

PQ Corporation (The)-St Louis 29510 0809 211112 9.65

Interstate Brands Corp-Interstate Brands Corp 29510 0938 311812 1.27
Goodwin Printing Co -St Louis 29510 1055 323110

Mid-West Industrial Chemical-Mid-West Industrial Chemical 29510 1077 32552 -

Brenntag Mid-South Inc-Brenntag Mid-South Inc 29510 1093 42392 0.00
U S Ringbinder Corp-Loose Leaf Metals 29510 1123 323116

St Louis Post Dispatch-St Louis Post Dispatch 29510 1280 51111 0.44

National Geospatial-Intelligence Agen cy-National Geospatial-Intelligence Agency 29510 1370 92811 1.38
Sigma - Aldrich Co-Sigma Chemical Company 29510 1396 325414 4.92
Southern Metal Processing-Southern Metal Proces sing 29510 1407 333414 2.17
Ashland Distribution Company-St Louis Plant 29510 1423 311942

Allied Health Care Products-Allied Health Care Products 29510 1460 332919 -
Energy Center (The)-St Louis Univ Health Scienc es Center 29510 1505 621111 9.43

Permacel St Louis Inc-Permacel St Louis Inc 29510 1519 326299 2.30

Connector Castings-Connector Castings 29510 1556 331314 0.00

J S Alberici Construction-J S Al berici Construction 29510 1642 236220 -

Superior Solvent & Chemical-St Louis 29510 2300 49311

Laclede Tower Associates Llc-Laclede Gas Building 29510 2378 22121 320.75

New World Pasta- Marceau Facility-New World Pasta 29510 2433 311823 4.59

Southwestern Bell Telephone Company-Southwestern Bell Telephone Company 29510 2545 517110 6.68

St Louis University-Facilities Svcs 2951 0 2711 323110 9.70

WASHINGTON UNIVERSITY-HILLTOP CAMPUS 29510 2833 611310 1.06

### 16 of 16 Facility Name State County
FIPS Code Facility

ID NAICS CO

Emissions (tons/year)

Statewide Total 92,239.10

### 1 of 17 

# Appendix A

‐ 2

List of On-Road Mobile Source Em issions by SCC for St. Louis Count y and St. Louis City (tons/year)

### 2 of 17 This page intentionally left blank.

### 3 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 220100100X Off-Network Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 23,231.78

St. Louis County 220100111X Rural Interstate Li ght Duty Gasoline Vehicles (LDGV) Exhaust 

### 42.35

St. Louis County 220100113X Rural Principal

Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 92.46

St. Louis County 220100115X Rural Minor Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 43.77

St. Louis County 220100117X Rural Major Collector Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 84.79

St. Louis County 220100119X Rural Minor Collector Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis County 220100121X Rural Local Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 56.87

St. Louis County 220100123X Urban Interstate Li ght Duty Gasoline Vehicles (LDGV) Exhaust 

### 8,912.00

St. Louis County 220100125X Urban Freeway/Expressway Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 1,981.59

St. Louis County 220100127X Urban Principal

Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 3,686.99

St. Louis County 220100129X Urban Minor Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 2,437.24

St. Louis County 220100131X Urban Collector Li ght Duty Gasoline Vehicles (LDGV) Exhaust 

### 1,299.25

St. Louis County 220100133X Urban Local Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 4,799.43

St. Louis County 220102000X Off-Network Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 18,311.11

St. Louis County 220102011X Rural Interstate Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 49.09

St. Louis County 220102013X Rural Principal

Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 111.16

St. Louis County 220102015X Rural Minor Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 52.62

St. Louis County 220102017X Rural Major Collector Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 101.94

St. Louis County 220102019X Rural Minor Collector Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

St. Louis County 220102021X Rural Local Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 68.37

St. Louis County 220102023X Urban Interstate Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 11,379.00

### 4 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 220102025X Urban Freeway/Expressway Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 2,530.13

St. Louis County 220102027X Urban Principal

Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 4,433.25

St. Louis County 220102029X Urban Minor Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 2,930.54

St. Louis County 220102031X Urban Collector Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 1,562.22

St. Louis County 220102033X Urban Local Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 5,770.85

St. Louis County 220104000X Off-Network Li ght Duty Gasoline Trucks 3 and 4 Exhaust 

### 9,432.99

St. Louis County 220104011X Rural Interstate Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 25.29

St. Louis County 220104013X Rural Principal

Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 57.27

St. Louis County 220104015X Rural Minor Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 27.11

St. Louis County 220104017X Rural Major Collector Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 52.51

St. Louis County 220104019X Rural Minor Collector Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis County 220104021X Rural Local Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 35.22

St. Louis County 220104023X Urban Interstate Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 5,861.91

St. Louis County 220104025X Urban Freeway/Expressway Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 1,303.40

St. Louis County 220104027X Urban Principal

Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 2,283.79

St. Louis County 220104029X Urban Minor Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 1,509.67

St. Louis County 220104031X Urban Collector Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 804.78

St. Louis County 220104033X Urban Local Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 2,972.86

St. Louis County 220107000X Off-Network Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 2,637.96

St. Louis County 220107011X Rural Interstate Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 7.63

St. Louis County 220107013X Rural Principal

Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 18.99

St. Louis County 220107015X Rural Minor Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 8.99

### 5 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 220107017X Rural Major Collector Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 17.41

St. Louis County 220107019X Rural Minor Collector Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis County 220107021X Rural Local Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 11.68

St. Louis County 220107023X Urban Interstate Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 1,918.39

St. Louis County 220107025X Urban Freeway/Expressway Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 426.56

St. Louis County 220107027X Urban Principal

Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 777.97

St. Louis County 220107029X Urban Minor Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 514.26

St. Louis County 220107031X Urban Collector Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 274.14

St. Louis County 220107033X Urban Local Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 1,012.70

St. Louis County 220108000X Off-Network Motorcycles (MC) Exhaust 

### 83.09

St. Louis County 220108011X Rural Interstate Motorcycles (MC) Exhaust 

### 2.21

St. Louis County 220108013X Rural Principal

Arterial Motorcycles (MC) Exhaust 

### 7.69

St. Louis County 220108015X Rural Minor Arterial Motorcycles (MC) Exhaust 

### 3.64

St. Louis County 220108017X Rural Major Collector Motorcycles (MC) Exhaust 

### 7.05

St. Louis County 220108019X Rural Minor Collector Motorcycles (MC) Exhaust



### ‐

St. Louis County 220108021X Rural Local Motorcycles (MC) Exhaust 

### 4.73

St. Louis County 220108023X Urban Interstate Motorcycles (MC) Exhaust 

### 771.73

St. Louis County 220108025X Urban Freeway/Expressway Motorcycles (MC) Exhaust 

### 171.60

St. Louis County 220108027X Urban Principal

Arterial Motorcycles (MC) Exhaust 

### 298.99

St. Louis County 220108029X Urban Minor Arterial Motorcycles (MC) Exhaust 

### 197.64

St. Louis County 220108031X Urban Collector Motorcycles (MC) Exhaust 

### 105.36

St. Louis County 220108033X Urban Local Motorcycles (MC) Exhaust 

### 389.20

### 6 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 223000100X Off-Network Light Duty Diesel Vehicles (LDDV) Exhaust 

### 3.01

St. Louis County 223000111X Rural Interstate Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.00

St. Louis County 223000113X Rural Principal

Arterial Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.02

St. Louis County 223000115X Rural Minor Arterial Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.01

St. Louis County 223000117X Rural Major Collector Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.02

St. Louis County 223000119X Rural Minor Collector Light Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis County 223000121X Rural Local Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.01

St. Louis County 223000123X Urban Interstate Li ght Duty Diesel Vehicles (LDDV) Exhaust 

### 1.34

St. Louis County 223000125X Urban Freeway/Expressway Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.30

St. Louis County 223000127X Urban Principal

Arterial Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.80

St. Louis County 223000129X Urban Minor Arterial Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.53

St. Louis County 223000131X Urban Collector Li ght Duty Diesel Vehicles (LDDV) Exhaust 

### 0.28

St. Louis County 223000133X Urban Local Light Duty Diesel Vehicles (LDDV) Exhaust 

### 1.04

St. Louis County 223006000X Off-Network Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 13.15

St. Louis County 223006011X Rural Interstate Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 0.18

St. Louis County 223006013X Rural Principal

Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 0.86

St. Louis County 223006015X Rural Minor Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 0.41

St. Louis County 223006017X Rural Major Collector Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 0.79

St. Louis County 223006019X Rural Minor Collector Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

St. Louis County 223006021X Rural Local Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 0.53

St. Louis County 223006023X Urban Interstate Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 77.82

St. Louis County 223006025X Urban Freeway/Expressway Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 17.30

### 7 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 223006027X Urban Principal

Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 44.94

St. Louis County 223006029X Urban Minor Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 29.71

St. Louis County 223006031X Urban Collector Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 15.84

St. Louis County 223006033X Urban Local Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 58.50

St. Louis County 223007100X Off-Network Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 5.71

St. Louis County 223007111X Rural Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 0.08

St. Louis County 223007113X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 0.38

St. Louis County 223007115X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 0.18

St. Louis County 223007117X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 0.35

St. Louis County 223007119X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis County 223007121X Rural Local Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 0.23

St. Louis County 223007123X Urban Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 34.32

St. Louis County 223007125X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 7.63

St. Louis County 223007127X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 19.82

St. Louis County 223007129X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 13.10

St. Louis County 223007131X Urban Collector Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 6.98

St. Louis County 223007133X Urban Local Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 25.80

St. Louis County 223007200X Off-Network Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 30.70

St. Louis County 223007211X Rural Interstate Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 0.43

St. Louis County 223007213X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 2.07

St. Louis County 223007215X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 0.98

St. Louis County 223007217X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 1.90

### 8 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 223007219X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

St. Louis County 223007221X Rural Local Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 1.27

St. Louis County 223007223X Urban Interstate Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 186.81

St. Louis County 223007225X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 41.54

St. Louis County 223007227X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 107.92

St. Louis County 223007229X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 71.34

St. Louis County 223007231X Urban Collector Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 38.03

St. Louis County 223007233X Urban Local Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 140.48

St. Louis County 223007300X Off-Network Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 46.26

St. Louis County 223007311X Rural Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 0.59

St. Louis County 223007313X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 2.60

St. Louis County 223007315X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 1.23

St. Louis County 223007317X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 2.38

St. Louis County 223007319X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis County 223007321X Rural Local Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 1.60

St. Louis County 223007323X Urban Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 217.78

St. Louis County 223007325X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 48.42

St. Louis County 223007327X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 116.12

St. Louis County 223007329X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 76.76

St. Louis County 223007331X Urban Collector Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 40.92

St. Louis County 223007333X Urban Local Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 151.15

St. Louis County 223007400X Off-Network Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 472.81

### 9 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 223007411X Rural Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 2.31

St. Louis County 223007413X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 9.68

St. Louis County 223007415X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 4.58

St. Louis County 223007417X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 8.87

St. Louis County 223007419X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis County 223007421X Rural Local Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 5.95

St. Louis County 223007423X Urban Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 826.54

St. Louis County 223007425X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 183.78

St. Louis County 223007427X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 431.19

St. Louis County 223007429X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 285.03

St. Louis County 223007431X Urban Collector Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 151.94

St. Louis County 223007433X Urban Local Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 561.28

St. Louis County 223007500X Off-Network Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 32.97

St. Louis County 223007511X Rural Interstate Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 0.19

St. Louis County 223007513X Rural Principal

Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 0.63

St. Louis County 223007515X Rural Minor Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 0.30

St. Louis County 223007517X Rural Major Collector Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 0.58

St. Louis County 223007519X Rural Minor Collector Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

St. Louis County 223007521X Rural Local Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 0.39

St. Louis County 223007523X Urban Interstate Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 69.03

St. Louis County 223007525X Urban Freeway/Expressway Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 15.35

St. Louis County 223007527X Urban Principal

Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 22.90

### 10 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis County 223007529X Urban Minor Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 15.14

St. Louis County 223007531X Urban Collector Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 8.07

St. Louis County 223007533X Urban Local Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 29.81

St. Louis County Total 132,855.83

St. Louis City 220100100X Off-Network Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 5,479.03

St. Louis City 220100111X Rural Interstate Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis City 220100113X Rural Principal

Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis City 220100115X Rural Minor Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis City 220100117X Rural Major Collector Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis City 220100119X Rural Minor Collector Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis City 220100121X Rural Local Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis City 220100123X Urban Interstate Li ght Duty Gasoline Vehicles (LDGV) Exhaust 

### 2,813.60

St. Louis City 220100125X Urban Freeway/Expressway Light Duty Gasoline Vehicles (LDGV) Exhaust



### ‐

St. Louis City 220100127X Urban Principal

Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 1,206.30

St. Louis City 220100129X Urban Minor Arterial Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 797.84

St. Louis City 220100131X Urban Collector Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 425.96

St. Louis City 220100133X Urban Local Light Duty Gasoline Vehicles (LDGV) Exhaust 

### 1,570.28

St. Louis City 220102000X Off-Network Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 3,609.69

St. Louis City 220102011X Rural Interstate Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

St. Louis City 220102013X Rural Principal

Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

St. Louis City 220102015X Rural Minor Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

St. Louis City 220102017X Rural Major Collector Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

### 11 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis City 220102019X Rural Minor Collector Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

St. Louis City 220102021X Rural Local Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

St. Louis City 220102023X Urban Interstate Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 3,617.21

St. Louis City 220102025X Urban Freeway/Expressway Light Duty Gasoline Trucks 1 & 2 Exhaust



### ‐

St. Louis City 220102027X Urban Principal

Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 1,448.26

St. Louis City 220102029X Urban Minor Arterial Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 957.87

St. Louis City 220102031X Urban Collector Li ght Duty Gasoline Trucks 1 & 2 Exhaust 

### 511.40

St. Louis City 220102033X Urban Local Light Duty Gasoline Trucks 1 & 2 Exhaust 

### 1,885.26

St. Louis City 220104000X Off-Network Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 1,859.54

St. Louis City 220104011X Rural Interstate Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis City 220104013X Rural Principal

Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis City 220104015X Rural Minor Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis City 220104017X Rural Major Collector Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis City 220104019X Rural Minor Collector Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis City 220104021X Rural Local Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis City 220104023X Urban Interstate Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 1,863.41

St. Louis City 220104025X Urban Freeway/Expressway Light Duty Gasoline Trucks 3 and 4 Exhaust



### ‐

St. Louis City 220104027X Urban Principal

Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 746.08

St. Louis City 220104029X Urban Minor Arterial Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 493.45

St. Louis City 220104031X Urban Collector Li ght Duty Gasoline Trucks 3 and 4 Exhaust 

### 263.45

St. Louis City 220104033X Urban Local Light Duty Gasoline Trucks 3 and 4 Exhaust 

### 971.19

St. Louis City 220107000X Off-Network Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 582.21

### 12 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis City 220107011X Rural Interstate Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis City 220107013X Rural Principal

Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis City 220107015X Rural Minor Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis City 220107017X Rural Major Collector Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis City 220107019X Rural Minor Collector Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis City 220107021X Rural Local Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis City 220107023X Urban Interstate Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 606.29

St. Louis City 220107025X Urban Freeway/Expressway Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust



### ‐

St. Louis City 220107027X Urban Principal

Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 254.42

St. Louis City 220107029X Urban Minor Arterial Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 168.27

St. Louis City 220107031X Urban Collector Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 89.84

St. Louis City 220107033X Urban Local Heavy Duty Gasoline Vehicles 2B thru
8B and Gasoline Buses Exhaust 

### 331.19

St. Louis City 220108000X Off-Network Motorcycles (MC) Exhaust 

### 13.15

St. Louis City 220108011X Rural Interstate Motorcycles (MC) Exhaust



### ‐

St. Louis City 220108013X Rural Principal

Arterial Motorcycles (MC) Exhaust



### ‐

St. Louis City 220108015X Rural Minor Arterial Motorcycles (MC) Exhaust



### ‐

St. Louis City 220108017X Rural Major Collector Motorcycles (MC) Exhaust



### ‐

St. Louis City 220108019X Rural Minor Collector Motorcycles (MC) Exhaust



### ‐

St. Louis City 220108021X Rural Local Motorcycles (MC) Exhaust



### ‐

St. Louis City 220108023X Urban Interstate Motorcycles (MC) Exhaust 

### 242.33

St. Louis City 220108025X Urban Freeway/Expressway Motorcycles (MC) Exhaust



### ‐

St. Louis City 220108027X Urban Principal

Arterial Motorcycles (MC) Exhaust 

### 97.39

### 13 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis City 220108029X Urban Minor Arterial Motorcycles (MC) Exhaust 

### 64.41

St. Louis City 220108031X Urban Collector Motorcycles (MC) Exhaust 

### 34.39

St. Louis City 220108033X Urban Local Motorcycles (MC) Exhaust 

### 126.78

St. Louis City 223000100X Off-Network Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.71

St. Louis City 223000111X Rural Interstate Li ght Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis City 223000113X Rural Principal

Arterial Light Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis City 223000115X Rural Minor Arterial Light Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis City 223000117X Rural Major Collector Light Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis City 223000119X Rural Minor Collector Light Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis City 223000121X Rural Local Light Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis City 223000123X Urban Interstate Li ght Duty Diesel Vehicles (LDDV) Exhaust 

### 0.42

St. Louis City 223000125X Urban Freeway/Expressway Light Duty Diesel Vehicles (LDDV) Exhaust



### ‐

St. Louis City 223000127X Urban Principal

Arterial Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.26

St. Louis City 223000129X Urban Minor Arterial Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.17

St. Louis City 223000131X Urban Collector Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.09

St. Louis City 223000133X Urban Local Light Duty Diesel Vehicles (LDDV) Exhaust 

### 0.34

St. Louis City 223006000X Off-Network Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 2.65

St. Louis City 223006011X Rural Interstate Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

St. Louis City 223006013X Rural Principal

Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

St. Louis City 223006015X Rural Minor Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

St. Louis City 223006017X Rural Major Collector Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

St. Louis City 223006019X Rural Minor Collector Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

### 14 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis City 223006021X Rural Local Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

St. Louis City 223006023X Urban Interstate Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 25.39

St. Louis City 223006025X Urban Freeway/Expressway Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust



### ‐

St. Louis City 223006027X Urban Principal

Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 15.06

St. Louis City 223006029X Urban Minor Arterial Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 9.96

St. Louis City 223006031X Urban Collector Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 5.32

St. Louis City 223006033X Urban Local Light Duty Diesel Trucks 1 thru 4 (LDDT) Exhaust 

### 19.61

St. Louis City 223007100X Off-Network Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 1.15

St. Louis City 223007111X Rural Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis City 223007113X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis City 223007115X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis City 223007117X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis City 223007119X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis City 223007121X Rural Local Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis City 223007123X Urban Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 11.19

St. Louis City 223007125X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust



### ‐

St. Louis City 223007127X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 6.63

St. Louis City 223007129X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 4.39

St. Louis City 223007131X Urban Collector Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 2.34

St. Louis City 223007133X Urban Local Heavy Duty Diesel Vehicles (HDDV)
Class 2B Exhaust 

### 8.64

St. Louis City 223007200X Off-Network Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 6.19

St. Louis City 223007211X Rural Interstate Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

### 15 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis City 223007213X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

St. Louis City 223007215X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

St. Louis City 223007217X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

St. Louis City 223007219X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

St. Louis City 223007221X Rural Local Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

St. Louis City 223007223X Urban Interstate Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 61.09

St. Louis City 223007225X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust



### ‐

St. Louis City 223007227X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 36.26

St. Louis City 223007229X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 23.98

St. Louis City 223007231X Urban Collector Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 12.80

St. Louis City 223007233X Urban Local Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, and 5 Exhaust 

### 47.20

St. Louis City 223007300X Off-Network Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 14.50

St. Louis City 223007311X Rural Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis City 223007313X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis City 223007315X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis City 223007317X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis City 223007319X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis City 223007321X Rural Local Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis City 223007323X Urban Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 69.65

St. Louis City 223007325X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust



### ‐

St. Louis City 223007327X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 38.13

St. Louis City 223007329X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 25.22

### 16 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis City 223007331X Urban Collector Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 13.47

St. Louis City 223007333X Urban Local Heavy Duty Diesel Vehicles (HDDV)
Class 6 and 7 Exhaust 

### 49.64

St. Louis City 223007400X Off-Network Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 136.61

St. Louis City 223007411X Rural Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis City 223007413X Rural Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis City 223007415X Rural Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis City 223007417X Rural Major Collector Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis City 223007419X Rural Minor Collector Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis City 223007421X Rural Local Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis City 223007423X Urban Interstate Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 263.29

St. Louis City 223007425X Urban Freeway/Expressway Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust



### ‐

St. Louis City 223007427X Urban Principal

Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 139.88

St. Louis City 223007429X Urban Minor Arterial Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 92.51

St. Louis City 223007431X Urban Collector Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 49.39

St. Louis City 223007433X Urban Local Heavy Duty Diesel Vehicles (HDDV)
Class 8A and 8B Exhaust 

### 182.08

St. Louis City 223007500X Off-Network Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 9.88

St. Louis City 223007511X Rural Interstate Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

St. Louis City 223007513X Rural Principal

Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

St. Louis City 223007515X Rural Minor Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

St. Louis City 223007517X Rural Major Collector Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

St. Louis City 223007519X Rural Minor Collector Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

St. Louis City 223007521X Rural Local Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

### 17 of 17 Area SCC SCC Road Type SCC Vehicle Type SCC

Process

Type CO

Emissions (tons/year)

St. Louis City 223007523X Urban Interstate Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 28.04

St. Louis City 223007525X Urban Freeway/Expressway Heavy Duty Diesel Buses (School and Transit) Exhaust



### ‐

St. Louis City 223007527X Urban Principal

Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 9.69

St. Louis City 223007529X Urban Minor Arterial Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 6.41

St. Louis City 223007531X Urban Collector Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 3.42

St. Louis City 223007533X Urban Local Heavy Duty Diesel Buses (School and Transit) Exhaust 

### 12.61

St. Louis City Total 

### 34,576.81

Combined Total For St. Louis County and St. Louis City 

### 167,432.64

## Appendix A-3

Nonroad 2008 Inventory Documentation for the Emissi ons Inventory Methodology for Commercial Marine Vessels, Locomotives, and Aircraf ts

 Documentation of the Commercial Marine Vessel Compo nent of the National Emissions Inventory Methodology

 Documentation of the Locomotive Component of the Na tional Emissions Inventory Methodology

 Documentation of the Aircraft Component of the Nati onal Emissions Inventory Methodology

### ERG No.: 0245.02.302.001

Contract No.: EP-D-07-097



## Documentation for the Commerci al Marine Vessel Component of the National Emissions Inventory

Methodology

Prepared by:

Eastern Research Group

1600 Perimeter Park Drive Morrisville, North Carolina 27560

Under Contract to:

E.H. Pechan & Associates, Inc. 3622 Lyckan Parkway

Suite 2002 Durham, North Carolina 27707

For Submittal to:

Laurel Driver Emissions, Monitoring and Analysis Division U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27711

March 30, 2010

### TABLE OF CONTENTS

Section Page No.

1.0 INTRODUCTION ........................................................................................................... 1-1

1.1 What is the Nationa l Emission Inventory? .......................................................... 1-1

1.2 Why Did the EPA Create the NEI?...................................................................... 1-1

1.3 How is the EPA Going to Use This Version of the NEI? ....................................1-1

1.4 Report Organization ............................................................................................. 1-2

2.0 DEVELOPMENT OF THE COMMERCIAL MARINE VESSEL COMPONENT FOR

THE NEI .......................................................................................................................... 2-1

2.1 How Does This CMV Study Fit into the NEI? .................................................... 2-1

2.2 What are Commercial Marine Vessels? ............................................................. 2-10

2.3 What Pollutants are Included in the National Emission Estimates for CMVs? .2-11

2.4 How Were the CMV Emissions Estimated? ...................................................... 2-11

2.5 How Were Emissions Allocated? ...................................................................... 2-14

2.6 How Were Port Emissions Allocated? ............................................................... 2-14

2.7 How Were Underway Emissions Allocated? ..................................................... 2-15

2.7.1 Category 1 and 2 Underway .................................................................. 2-15

2.7.2 Category 3 Reduced Speed Zones (RSZ) .............................................. 2-15

2.7.3 Category 3 Approach ............................................................................. 2-15

2.7.4 Category 3 Interport ............................................................................... 2-16

2.8 QA/QC ............................................................................................................... 2-16

2.9 What are the Results? ......................................................................................... 2-17

2.10 Commercial Marine Vessel References ............................................................. 2-19

Appendix A – 2008 Category 3 Commercial Marine Vessel Inventory Methodology

Appendix B – 2008 Commercial Marine Vessel HAP Speciation Profiles

i

### LIST OF TABLES AND FIGURES

Tables Page No.

Table 2-2. Commercial Marine Vessel Pollutant List ............................................................... 2-12

Table 2-3. Commercial Marine Vessel Criteria and Greenhouse Gas Emission Estimates 2008 (TPY)......................................................................................................................... ....2-17

Table 2-4. Commercial Marine Vessel HAP Emission Estimates 2008 (TPY) ........................ 2-18

Figures Page No.

Figure 2-1. General Approach Used to Develop Marine Vessel Component of the 2008 National

Emission Inve ntory........................................................................................................2-13

ii

## 1.0 INTRODUCTION

1.1 What is the National Emission Inventory?

The National Emission Inventory (NEI) is a comprehensive inve ntory covering all anthropogenic sources of criteria pollutants and hazardous air pollutants (HAPs) for all areas of the United States. The NEI was created by the U.S. Environmental Protection Agency’s Emission Inventory and Analysis Group (EIAG) in Research Triangle Park, North Carolina. The NEI will be used to support air quality modeli ng and other activities. To this end, the EPA established a goal to compile comprehensive emissi ons data in the NEI for criteria and HAPs for mobile, point, and nonpoint sources. This report presents an overview of how emission estimates for the commercial marine vessel (CMV) component of the 2008 NEI was compiled.

1.2 Why Did the EPA Create the NEI?

The Clean Air Act (CAA), as amended in 1990, includes mandates for the EPA related to criteria and hazardous air polluta nts. The CAA defines criteria pollutants as being one of the following air pollutants:

• Carbon monoxide (CO);

• Sulfur oxides (SO

x 

### );

• Nitrogen oxides (NO

x 

### );

• Ozone; and

• Particulate matter (PM).

Where emission factors and activ ity data permit, ammonia (NH 3 

### ) estimates are also included as an important precursor to PM. Hazar dous air pollutants are also delineated in the
CAA, see http://www.epa.gov/ttn/atw/188polls.html for a complete list of regulated pollutants and their chemical abstract service [CAS] numbers.

The CAA requires the EPA to identify emi ssion sources of these pollutants, quantify emissions, develop regulations for the identified source categories, and assess the public health and environmental impacts after th e regulations are put into effect . The NEI is a tool that EPA

can use to meet the CAA mandates. In this re port, criteria and HAP emission estimates are

discussed for CMV sources.

1.3 How is the EPA Going to Use This Version of the NEI?

It is anticipated that the emission inventory developed from this effort will have multiple end uses. The data have been formatted according to protocols established for the EPA’s NEI submittals. The common data structure on which the NEI platform is based will allow the NEI emission data to be transferred to multiple end-users for a variety of purposes.

1-1

### The criteria and HAP emission estimates devel oped for the NEI will be used to evaluate air pollution trends, air quality modeling an alysis and impacts of potential regulations.

1.4 Report Organization

Following this introduction, Section 2.0 provi des information on how the national CMV, emission estimates were developed. This invent ory effort was coordinated by the EPA’s Office of Transportation and Air Quality (OTAQ) and EIAG.

The appendix were created to provide technical details on how the national emissions were developed and how state and local inventory data (when provided) we re incorporated into the national estimates. Appendix A provides a co py of the report documenting how the 2002 data were adjusted to reflect marine vessel activity and emissions for 2008.

1-2

## 2.0 DEVELOPMENT OF THE COMM ERCIAL MARINE VESSEL

COMPONENT FOR THE NEI

2.1 How Does This CMV Study Fit into the NEI?

The NEI was developed to include all point, nonp oint (sometimes referenced as “area”), and mobile sources. The approaches used in the point and nonpoint s ource categories are documented in other reports. Table 1 summarizes the approaches used to estimate emissions from all nonroad sources included in the NEI pr ogram. Those source categories and years that are included in this report are noted in bold.

The scope of this inventory component of the NEI was to compile criteria and HAP emissions data for CMVs operating in United St ates waters and federal waters extending 200

nautical miles from the United States’ coastline. In this effort, national emission estimates were often developed and allocated to counties base d on available Geographic Information System (GIS) data. The methodologies used to estimate emissions and the procedures used to spatially allocate them to the county-level are discussed in this report.

Table 2-1. Methods Used to Develop Annual Emission Estimates for

Nonroad Mobile Sources (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method* NONROAD Categories

N onroad Gasoline, Diesel, LPG,

CNG 2002 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### , NH 3 

### , & HAPs Emission estimates for NONROAD model engines were developed using EPA’s National Mobile Inventory Model (NMIM), which incorporates NONROAD2004. Where states provided alternate nonroa d inputs, these data replaced EPA default inputs. State-supplied emissions data also replaced default EPA

emission estimates.

2-1

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method*

1999 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory, developed using EPA’s October 2001 draft NONROAD model; and 2) an updated 1999 national inventory, based on

EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily countyto-national ratios were then developed for application to updated national estimates per

season estimated from the Lockdown C model. Replaced State-submitted data for California for all NONROAD model categories; Pennsylvania for recreational marine and aircraft ground support equipment, and Texas for select equipment categories.
1996, 1997, 1998, 2000

& 2001 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory, developed using EPA’s October 2001 draft NONROAD model; and 2) updated year-specific national and California inventories, based on EPA’s draft Lockdown C

N ONROAD model (dated May 2002). Using the 1996 county-level emission estimates, seasonal and daily county -to-national ratios and California county-to-state ratios were then developed for application to updated national estimates per season estimated from the

Lockdown C model. Calif ornia results replace the diesel equipment emissions generated from prior application of c ounty-to-national ratios.

2-2

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method*

N onroad Gasoline, Diesel, LPG,

and CNG (Continued) 1991-1995 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### , NH 3 

### Using 1990 and 1996 county-level emissions inventories, estimated emissions using linear interpolation of national emissions between 1990 and 1996. From these emissions, calculated the average annual growth rate for each pollutant/SCC combination for each year, and then applied the growth factors to 1990 county-level emissions to estimate 1991-1995

emissions.

1990 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory, developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1990 national inventory, based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-level emission estimates, seasonal and daily county-to-national ratios were then developed for application to updated national estimates per season estimated

from the Lockdown C model.
1986, 1988,

& 1989 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### , NH 3 

### Using 1985 and 1990 county-level emissions inventories, estimated emissions using linear interpolation of national emissions between 1985 and 1990. From these emissions, calculated the average annual growth rate for each pollutant/SCC combination for each year, and then applied the growth factors to 1985 county-level emissions to estimate 1986-1989

emissions.

1987 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated national emissions for 1987 by running 4

seasonal NONROAD model runs to estimate annual criteria pollutant emissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.

2-3

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method*

N onroad Gasoline, Diesel, LPG,

and CNG (Continued) 1985 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory, developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1985 national inventory, based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-level emission estimates, seasonal and daily county-to-national ratios were then developed for application to updated national estimates per season estimated

from the Lockdown C model.
1970, 1975, 1978, &

1980 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated national emissions for all years by running 4

seasonal NONROAD model runs to estimate annual criteria pollutant emissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.
1996, 1997, 1998, 1999, 2000, &

2001 NH 3 

### Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying by NH 3 

### emission factors, and distributing to countie s using 1996 inventory,

based on October 2001 draft NONROAD. NH 3 

### emissions for California were also recalculated using updated diesel fuel consumption values generated for Californi a-specific runs, and assuming the 1996 county-level distribution.

1985 & 1990 NH 3 

### Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying by NH 3 

### emission factors, and distributing to countie s using 1996 inventory,

based on October 2001 draft NONROAD.

1987 NH 3 

### Obtaining 1987 national fuel consumption

estimates from Lockdown C NONROAD model and multiplying by NH 3 

### emission factors.

2-4

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method*

N onroad Gasoline, Diesel, LPG,

and CNG (Continued) 1970, 1975, 1978, &

1980 NH 3 

### Obtaining national fuel consumption estimates

from the Lockdown C NONROAD model and multiplying by NH 3 

### emission factors.

1990, 1996,

& 1999 HAPs Speciation profiles applied to county VOC and

PM estimates. Metal HAPs were calculated using fuel and activity-bas ed emission factors. Some state data were provided and replaced national estimates. (2003)

A ircra ft

Commercial

Aircraft 2008 Criteria and HAPs Federal Av iation Administration (FAA) Emissions and Dispersion and Modeling Syste m(EDMS) - Version 5.1.was run using BTS T100 LTO data. (2009)

2002 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion and Modeling Syste m (EDMS) was run for criteria pollutants, VOC and PM emissions were speciated into HAP components. (2004)
1990, 1996, 1999, 2000,

2001 VOC, NO

x 

### , CO,

SO

x 

### Input landing and take-off (LTO) data into FAA EDMS. National emissions were assigned to airports based on airport specific LTO data and BTS GIS data. State data replaced national estimates. (2003)

1970-1998 VOC, NO

x 

### , CO,

SO

x 

### Estimated emissions for interim years using linear interpolation between available base years. (2003)
1990, 1996,

1999 HAPs Speciation profiles were applied to VOC estimates to get national HAP estimates. State data replaced national estimates. (2003)

General Aviation, Air

Taxis 2008 Criteria and HAPs Used FAA LTO data from TAF and OTAQ provided activity data for smaller airports

derived from FAA 5010 master plans. EPA approved generic emission factors for criteria estimates. Speciation prof iles were applied to VOC and PM estimates to get national HAP estimates. (2009)

2-5

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method*

General Aviation, Air

Taxis (Continued) 1978, 1987, 1990, 1996, 1999, 2000, 2001, &

2002 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Used FAA LTO data and EPA approved

emission factors for criteria estimates. Speciation profiles were applied to VOC estimates to get national HAP estimates. State data replaced national estimates. (2004)

1970-1998 VOC, NO

x 

### , CO,

SO

x 

### , PM 10 

### , PM 2.5 

### Estimated emissions for interim years using linear interpolation between available base years. (2003)
1990, 1996, 1999, &

2002 HAPs Used FAA LTO data and EPA approved

emission factors for criteria estimates. Speciation profiles were applied to VOC estimates to develop national HAP estimates. (2004)
1990, 1996, 1999, &

2002 Pb Used Department of Energy (DOE) aviation gasoline usage data with lead concentration of aviation gasoline. (2004)

1996 NH 3 

### Applied NH 3 

### emissions factors to 1996 national j et fuel and aviation gasoline consumption

estimates. Military

Aircraft 1978, 1987, 1990, 1996, 1999, 2000, 2001, 2002,

2008 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Used FAA LTO data as reported in TAF and EPA approved emission factors for criteria estimates. Representative HAP profiles were not readily available, therefore HAP estimates were not developed. (2009)

1970-1998 VOC, NO

x 

### , CO,

SO X 

### , PM 10 

### , PM 2.5 

### Estimated emissions for interim years using linear interpolation between available base years. (2003) Auxiliary

Power Units 2008 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Federal Aviation Administration (FAA) Emissions and Dispersion and Modeling Syste m(EDMS) - Version 5.1.was run using BTS T100 LTO data. (2009)

1985-2001 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Grew 1996 emissions to each year using LTO operations data from the FAA. Estimation methods prior to 1996 reported in EPA, 1998.

2-6

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method* Unpaved Airstrips 1 

### 1985-2001 PM 10 

### , PM 2.5 

### Grew 1996 emissions to each year using SIC 45- Air Transportation growth f actors, consistent with

the current draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998.

Aircraft Refueling 1 

### 1985-2001 VOC Grew 1996 emissions to each year using SIC 45- Air Transportation growth f actors, consistent with

the current draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998. Commercial Marine Vessel (CMV)

All CMV Categories 2008 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### 2002 estimates were adjusted by OTAQ to reflect 2008 activity leve ls., note that the SCCs for this category have changed such that the Diesel category refers to smaller vessels (Cate g or y 1 and 2) usin g distillate fuels and the Residual category refers to larger (Category 3) vessel using a blend of residual fuels (2009)

2008 HAPs OTAQ’s 2008 estima tes were speciated into HAP components using SEPA profiles

2002 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### 2001 Estimates carried over. Used state data when provided. (2004)

HAPs 1999 Estimates carried over. Used state data when provided. (2004)

CMV Diesel 1978, 1987, 1990, 1996, 1999, 2000,

& 2001 VOC, NO

x 

### , CO,

SO

x 

### , PM 10 

### , &

PM 2.5 

### Used criteria emission estimates in the background document for marine diesel regulations for 2000. Adjusted 2000 criteria

emission estimates for other used based on fuel usage. Emissions were disaggregated into port traffic and underway activities. Port emissions were assigned to specific ports based on amount of cargo handled. Underway emissions were allocated based on Army Corp of Engineering waterway data. State data replaced national estimates. (2003)

1970-1998 VOC, NO

x 

### , CO,

SO

x 

### , PM 10 

### , PM 2.5 

### Estimated emissions for interim years using linear interpolation between ava ilable base years. (2003)
1990, 1996,

1999 HAPs VOC and PM emission estimates were speciated into HAP components. State data replaced national estimates. (2003)

2-7

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method*

1996 NH 3 

### Applied NH 3 

### emissions factors to 1996 distillate

and residual fuel oil esti mates (i.e., as reported in EIA, 1996).

1990-1995 NH 3 

### Estimation methods reported in EPA, 1998.

CMV Steam

Powered 1978, 1987, 1990, 1996, 1999, 2000,

& 2001 VOC, NO

x 

### , CO,

SO

x 

### , PM 10 

### , &

PM 2.5 

### Calculated criteria emi ssions based on EPA SIP guidance. Emissions were disaggregated into port traffic and under way activities. Port emissions were assigned to specific ports based on amount of cargo handled. Underway emissions were allocated based on Army Corp of Engineering waterway data. State data replaced national estimates. (2003)

1970-1998 VOC, NO

x 

### , CO,

SO

x 

### , PM 10 

### , PM 2.5 

### Estimated emissions for interim years using linear interpolation between ava ilable base years. (2003)
1990, 1996,

& 1999 HAPs VOC and PM emission estimates were speciated into HAP components. State data replaced national estimates. (2003) Military Marine 1997-2001 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Applied EGAS growth factors to 1996 emissions estimates for this category.
CMV Coal, 2



### CMV, Steam

p owered, CMV

Gasoline 2 

### 1997-1998 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Applied EGAS growth factors to 1996 emissions estimates for this category.

CM Coal, CMV, Steam powered, CMV Gasoline, Military Marine 1991-1995 VOC, NO

x 

### , CO,

SO 2 

### , PM 10 

### , PM 2.5 

### Estimation methods reported in EPA, 1998.

L ocomotives

Class I, Class II,
Commuter, Passenger, and

Yard

Locomotives 1978, 1987, 1990, 1996, 1999, 2000, 2000, &

2002 VOC, NO

x 

### , CO,

PM 10 

### , PM 2.5 

### Criteria pollutants were estimated by using

locomotive fuel use data from DOE EIA and available emission factors. County-level estimates were obtained by scaling the national estimates

with the rail GIS data from DOT. State data replaced national estimates. (2004)

2-8

### Table 2-1. Methods Used to Develop Annual Emission Estimates for Nonroad Mobile Sources (Continued) (Categories included in this repo rt are noted in bold print)

Category Base Year Pollutant(s) Estimation Method*
Class I, Class
II, Commuter, Passenger, and

Yard

Locomotives (Continued) 1978, 1987, 1990, 1996, 1999, 2000, 2001, &

2002 SO 2 

### SO

x 

### emissions were calculated by using

locomotive fuel use and fuel sulfur concentration data from EIA. County-level estimates were obtained by scaling the national estimates with the county level rail activity data

from DOT. State da ta replaced national estimates. (2004)

1970-1998 VOC, NO

x 

### , CO,

SO

x 

### , PM 10 

### , PM 2.5 

### Estimated emissions for interim years using linear interpolation between available base years. (2003)
1990, 1996, 1999, &

2002 HAPs HAP emissions were calculated by applying speciation profiles to VOC and PM estimates. County-level estimates were obtained by scaling the national estimates with the county level rail activity from DOT. State data replaced national estimates. (2004)

1997-1998 N H 3 

### Grew 1996 base year emissions using EGAS growth indicators.

1996 N H 3 

### Applied NH 3 

### emissions factors to diesel consumption estimates for 1996.

1990-1995 N H 3 

### Estimation methods reported in EPA, 1998.

Notes:

* Dates included at the end of Estimation Method re present the year that the section was revised. 1 Emission estimates for unpaved airstrip s and aircraft refueling are included in the area source NEI, since they represent non-engine emissions. 2 National Emission estimates for CMV Coal and CMV Gasoline were not developed though states and local agencies may have submitted estimates for these source categories. EPA, 1998. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, EmissionFactors and Inventory Group, National Air Pollutant Emission Trends, Procedures Document, 1900–1996, EPA454/R-98-008. May 1998



### .

2-9

### The target inventory area includes every state in the United States and every county within a state. There are no boundary limitations pertaining to traditional criteria pollutant nonattainment areas or to designate d urban areas. The pollutants inve ntoried included all criteria pollutants (except for the other nonroad source category which addressed only HAPs in this report) and the 188 HAPs identified in Section 112(b) of the CAA. Some state or local agencies provided emissions information on more HAPs th an those delineated in the CAA, only the federally regulated HAPs are included in the NEI.

In addition to numerous specific chem ical compounds, the list of 188 HAPs includes several compound groups [e.g., individual metals and their compounds, polycyclic organic matter (POM)]; the NEI includes emission esti mates for the individual compounds wherever possible. Many of the uses of the NEI depend up on data (e.g., toxicity) for individual compounds within these groups rather than aggregat ed data on each group as a whole.

The intent in presenting the following em ission inventory approach is to provide sufficient and transparent documentation such th at states and local agencies can use these approaches, in conjunction with th eir specific local activity data to develop more accurate and comparable emission estimates in future submittals.

2.2 What are Commercial Marine Vessels?

The CMV source category includes all boats and ships used either directly or indirectly in the conduct of commerce or military activity. Thes e vessels range from 20-foot charter boats to large tankers which can exceed 1,000 feet in leng th (EPA, 1989). In spite of the broad range of vessels represented by this cate gory, a number of common characte ristics allow for the use of simple emission estimation methods. The majority of vessels in this category are powered by diesel engines that are either fuel ed with distillate or residual fu el oil blends. For the purpose of this inventory it is assumed that Category 3 vesse ls primarily use residual blends while Category 1 and 2 vessels typically used distillate fuels.

The Category 3 (C3) inventory develope d by OTAQ includes vessels which use C3 engines for propulsion. C3 engine s are defined as having displacement above 30 liters per cylinder (U.S. EPA, 2003). The resulting invent ory includes emissions from both propulsion and auxiliary engines used on these vessels, as we ll as those on gas and steam turbine vessels. Geographically, the inventories in clude port and interport emissions that occur within the area that extends 200 nautical miles (nm) from the offi cial U.S. baseline, whic h is roughly equivalent to the border of the U.S. Exclusive Economic Zone (EEZ).

Category 1 and 2 vessels tend to be smaller ship s that operate closer to shore, and along inland and intercoastal waterway s. Naval vessels are not include d in this inventory, though Coast Guard vessels are included as Category 1 and 2 vessels.

The CMV source category does not include recreational marine vessels, which are generally less than 100 feet in length, most being less than 30 feet, and powered by either inboard or outboard engines (EPA, 1989). Emi ssions from recreational marine vessels are included in the nonroad source category.

2-10

### 2.3 What Pollutants are Include d in the National Emission Estimates for CMVs?

The E PA’s Office of Transportation and Air Quality ( 

### OTAQ) provided estimates for all criteria pollutants including volatile or ganic compounds (VOC), nitrogen oxides (NO

x 

### ), carbon monoxide (CO), sulfur oxides (SO

x 

### ), particulate matter less than 10 microns (PM 10 

### ), particulate matter less than 2.5 microns (PM 2.5 

### ) and carbon dioxide (CO 2 

### ). Criteria emissions were provided for Category 1 and 2 vessels (C arey, 2009b); Category 3 port, redu ced speed zone, and cruising activities (Carey, 2009a and Care y, 2009c); and Category 3 inter port activities (Carey, 2009d).

The VOC and PM estimates were specia ted into hazardous air pollutants (HAP) components based on available data sources. Th e Swedish Environmental Protection Agency (SEPA) document Methodology for Calculating Emissions from Ships: 1. Update of emission factors served as the primary source of HAP em ission factors which were converted into speciation profiles (Cooper a nd Gustafsson, 2004). Ammonia em ission factors were also obtained from the SEPA, but as these factors require activity da ta, and such data were not available for Category 3 vessels op erating in Federal waters, ammoni a was estimated as a ratio of

PM 10 

### using the SEPA emission factors. Similar ratios were developed for Category 1 and 2 vessels, assuming that this fleet primarily operates on marine diesel fuel with 80.5 percent of the fleet equipped with medium speed engines a nd the remaining 19.5 percent were high speed engines. This pr ovided a weighted NH 3 

### emission factor of 4.61E-03 g/kw-hr for operations atsea and in-port. The PM 10 

### factors vary for at-sea (0.2 g/kw-hr) and in-port (0.4 g/kw-hr), so our

NH 3 

### / PM 10 

### ratios were different for at-sea (2.31E-02) and in-port (1.15E-02).

While the SEPA document was used as the primary speciation source, other resources were investigated for potential inclusion in this effort. Recent BTEX data from Moldanova et al. were examined, but it included inconsistent benzene factors, some over 20% of hydrocarbon (HC) factors, were much higher th an others found in recent pub lications and, as a result, were not included (Cook, 2009). CE-CERT me tals data was also reviewed as it pertained to slow speed residual fuel engines (Cook, 2009). The CE-C ERT emission factors were in line with the Swedish factors for nickel and lead, but they were an order of magnitude different for chromium, cadmium, and selenium. As a result, the Swedish factors were retained over the CE-CERT data based on the larger study sample size, while CE-CERT’s manganese emission factors were

added as these factors were not incl uded in the Swedish study (Cook, 2009).

The complete pollutant list fo r CMVs is shown in Table 2-2.

2.4 How Were the CMV Emissions Estimated?

As noted above, the CMV criteria and CO 2 

### emission estimates were provided for this inventory by OTAQ. Category 3 co mmercial marine inventories we re developed for a base year of 2002 then projected to 2008 appl ying regional adjustment factor s to account for growth. In addition, NO X 

### adjustment factors were applied to account for implementation of the NO X 

### Tier 1 standard. Details about adjust ments and growth factors ca n be found in the Category 3 documentation (Appendix A). For Category 1 and 2 marine diesel engines, the emission

estimates were consistent with the 2008 Locomotive and Marine federal rule making (Carey, 2009b).

2-11

### Table 2-2. Commercial Marine Vessel Pollutant List

2,2,4 Trimethylpentane Carbon Monoxide * 

### Naphthalene Acenaphthene Chromium(VI) Nickel Acenaphthylene Chromium (III) Nitrogen Oxides *



### Acetaldehyde Chrysene PAH, total

Acrolein Cobalt Phenanthrene

Ammonia Dibenzo[a,h]Anthracene Phosphorus

Anthracene Dioxins/Furans PM10 Primary *



### Arsenic Ethyl benzene PM2.5 Primary +


### Benz(a)anthracene Fluoranthene Polychlorinated Biphenyls

Benzene Fluorene Propionaldehyde Benzo(a)pyrene Formaldehyde Pyrene Benzo(b)fluoranthene Hexachlorobenzene Selenium Benzo(g,h,i)perylene Hexane Styrene Benzo(k)fluoranthene Indeno( 1,2,3-cd)pyrene Sulfur Dioxide *



### Beryllium Lead Toluene

Cadmium Manganese VOCs *



### Carbon Dioxide * 

### Mercury Xylene

* Provided by OTAQ

+ PM 2.5 was provided by OTAQ for all vessels and modes except for Category 3 Interport, where it was calculated

using OTAQ guidance.



### OTAQ’s emissions were then allocated to individual GIS polygons using appropriate methods that varied by operating mode (i.e., hotelling, maneuvering, reduced speed zone, and underway). HAP emissions were estimated by a pplying speciation profiles to each polygon’s VOC and PM estimates. Figure 2-1 provides an overview of the appr oach used to estimate and spatially allocate CMV emissions.

Speciation profiles were applied to the VOC, PM 10 

### , and PM 2.5 

### emission estimates to

calculate the associated HAP emi ssions using the following equation.

VOC-PM 10/2.5 

### * speciation profile i 

### = HAP emission estimate:

Where:

HAP emission estimate = HAP Emission estimate (tons/year) for pollutant:

VOC-PM 10/2.5 

### = VOC or PM emission estimate (tons/year) Speciation Profile i 

### = VOC or PM speciation fraction for

HAP i

2-12

### Criteria Estimates for All Marine Diesel Engines

Criteria/HAP Annual Emission Estimates

Vessels Equipped with Category 1 and 2

Propulsion Engine

Ports Inland Waterways
and Coast Vessel Equipped with Category 3 Propulsion Engine

Ports Reduced Speed

Zone Approach Underway Criteria Estimates for All Marine

Distillate and Residual Fueled Engines

HAP Speciation Profiles

Criteria/HAP Annual Emission Estimates

Vessels Equipped with Category 1 and 2

Propulsion Engine

Ports Inland Waterways
and Coast Vessel Equipped with Category 3 Propulsion Engine

Ports Reduced Speed

Zone Approach Underway



### Figure 2-1. General Approach Used to Deve lop Marine Vessel Component of the 2008 National Emission Inventory

2-13

### For Category I diesel-powered vessels, the speciation profiles were based on high-speed diesel vehicle (HSDV) factors obtain ed from information in the SEPA’s Methodology for Calculating Emissions from Ships : 1. Update of emission factors (Cooper and Gustafsson, 2004). For Category 2 diesel-powered vessels, the speciation profiles were developed from mediumspeed diesel vehicles (MSDV). Since emissions a nd activity data were provided as a combined value for all Category 1 and 2 vessels, the Cate gory 1 and Category 2 emission factors were averaged to obtain a single emission factor for all diesel vessels. All port activities for Category 1 and 2 vessels were assumed to be maneuvering.

For Category 3 vessels, speciation prof iles were developed using data from Methodology for Calculating Emissions from Shi ps: 1. Update of emission factors and assuming 80.5% of Category 3 vessels were equipped with slow-spe ed engines and 19.5% of vessels were equipped with medium speed engines based on vessel census data reported in the International Maritime Organization’s (IMO) recent gr eenhouse gas (GHG) study (IMO 2009). Separate speciation profiles were created for Category 3 vessels fo r underway, maneuvering, a nd hotelling activities. Chromium emissions were split into hexavalent and trivalent chromium based on an assumption that 34% of total chromium was hexavalent and the remaining 66% was trivalent.

2.5 How Were Emissions Allocated?

Previous emissions allo cations were based on wate rway length and port county assignment. In this effort, spatial accuracy was greatly enhanced vi a the creation of GIS polygons representing port and waterway boundaries. GIS polygons allowed the

estimation/allocation of emissions to defined port, waterway, a nd coastal areas, leading to improved spatial resolution compared to 2002’s county-level emissions. Methodologies for both port and underway emissions are described in detail in the sections that follow.

2.6 How Were Port Emissions Allocated?

Port boundaries were developed using a variety of resources to identify the most accurate port boundaries. First, GIS data or maps provided directly from the port were used. Next, maps or port descriptions from local port authorities, po rt districts, etc. were used in combination with existing GIS data to identify port boundaries. Fi nally, satellite imagery from tools such as Google Earth and street layers fr om 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. The Port of Huntington was de veloped differently give n its large extent and limited available map data. The state of West Virg inia provided a revised file of US Army Corps of Engineers port terminals reported to be part of the Port of Huntington-Tristate area. A 200 meter buffer of the water features near these po rt terminals was created to identify port area.

In all cases, polygons were created on land, bordering waterways and coastal areas, and were split by county boundary. Each polygon wa s identified by the port name and state and county FIPS in addition to a unique ShapeID. Sm aller ports with Catego ry 1 and 2 activities were mapped as small circles. Note that no Category 3 emissions were mapped to small circles. The final shapefile contained 159 ports and 196 polygons.

OTAQ provided Category 1 and 2 criteria em issions and activity as a single national number. These emissions and activity were allocat ed to ports based on total commodity tonnage

2-14

### data obtained from the U.S. Army Corps of Engineers (USACE) Princi pal Ports file for 2007 (U.S. ACE, 2009). Emissions were then assigned to polygons within a port based on port area.

OTAQ developed port-level emissions for 117 of the largest U.S. ports with Category 3 activity. Activity in megawatt hours (MWh) and resulting criteria and CO 2 

### emissions were provided by port for maneuvering and hotelling modes. Emissions were then assigned to polygons within a port based on port area. HAP em issions were then speciated from VOC and PM estimates for each polygon using the methodology described in Section 3.0.

2.7 How Were Underway Emissions Allocated?

For this inventory, 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’ Na tional Transportation A tlas Database hydro polygon layer (U.S. DOT, 2007). These polygons were fu rther divided by county boundary and waterway ID. Coastal waters were drawn using Mineral Ma nagement Service state-federal boundary files

and were also divided to indica te county boundaries. Federal wate rs were included as large area blocks outlined by the Exclusive Economic Z one (EEZ) boundary provided by EPA, which extends to approximately 200 nautical miles fr om the coastline. The final product is a polygon layer that includes all inland a nd coastal state waters and federal waters along with FIP, polygon area, and a unique ShapeID. Underway emissions were allocated differently by vessel category and mode, as outlined below.

2.7.1 Category 1 and 2 Underway

OTAQ provided Category 1 and 2 criteria em issions and activity as a single national number. These emissions and activity were allocat ed to underway polygons in state waters based on total commodity movements (in tons) data ob tained from USACE (U.S. ACE, 2001). These data were waterway-specific, so waterways th at crossed into multiple FIPs had emissions assigned by waterway length in each polygon. HAP emissions were then speciated from VOC and PM estimates using the methodology described in Section 3.0 for each polygon.

2.7.2 Category 3 Reduced Speed Zones (RSZ)

OTAQ provided polyline shapef iles indicating locati on of RSZ activities along with portspecific RSZ emissions and activity. These polylines were intersected with existing shipping lane polygons, and emissions were allocated to polygo ns based on the approach segment length on a per-port basis. HAP emissions were then speci ated from VOC and PM estimates using the methodology described in Section 3.0 for each polygon.

2.7.3 Category 3 Approach

OTAQ provided polyline shap efiles indicating loca tion of cruising activities along with port-specific cruising emi ssions and activity. These polylines we re intersected with our existing polygons, and emissions were allocated to polygo ns based on the approach segment length on a per-port basis. HAP emissions were then speci ated from VOC and PM estimates using the methodology described in Section 3.0 for each polygon.

2-15

### 2.7.4 Category 3 Interport

OTAQ provided 4km grids for interport-only emissions for CO, CO 2 

### , HC, NO

x 

### , SO

x 

### , and

PM 10 

### . These grids were provided in a customized projection which, without a custom geographic transformation, could not be converted to matc h the polygon layer’s projection. Furthermore, the emission estimates provided by OTAQ were deve loped using EEZs which were in the GCS Arc Sphere projection. Per OTAQ’s direction, the inte rport polygons were converted from North American Equidistant Conic to GCS Arc Sphere by using the data frame projections tool as the a transformation method. This approach was recomme nded by OTAQ in order to mirror previous methodology and provide emission estimates consis tent with the recent Category 3 Commercial Marine Inventory. Zonal statisti cs tools were used to sum the gridded emissions within each underway polygon

. HAP emissions were then speciated fr om VOC and PM estimates using the methodology described in Section 3.0 for each polygon.

2.8 QA/QC

Given the significant methodological changes ov er previous inventory efforts, several quality checks were implemented to ensure that these data were developed and allocated in a clear and reproducible manner. So me of the quality checks impl emented include the following:

GIS shapefiles

• Topology was created and validated through se veral rounds or revisions to remove gaps or overlapping features both within and between polygon layers.

• Boundaries derived from Google Earth imag ery were validated against Street Map network, port-provided map images, USAC E ports points, and other online mapping resources to improve boundary accuracy.

• All final shapefiles and polygon characteristic s (such as area, etc.) were managed and evaluated in a single projection to ensure quality area and distance measurements, consistent results across CMV activity type s, and maximum accuracy across the study area. The only exception to this was in the case of the interport criteria emissions, as

described in Section 4.2.4.

Emissions allocations and estimations

• Emission factors were compiled from a va riety of sources, and emission factor development methodologies evaluated to identify the most accurate emission factor for use in this inventory effort.

• National emission sums were checked both be fore and after allocation to ensure no emissions were dropped or grown.

• HAP speciation profiles were checked for accuracy, and speciated emissions were checked on both the polygon and nati onal level to ensure accuracy.

• All unit conversions were double-checked for errors.

• Emission sums were evaluated across act ivity types (i.e., hotelling, maneuvering, cruising, reduced speed zones, and interpor t) to ensure they consistently mirror activity levels.

• Port and underway emissions were examined across SCCs to ensure consistency with activity levels and vessel populations.

2-16

### • 2008 pollutants and emissions were checked against the 2005 inventory to identify any missing pollutants or major changes compared to previous inventories. Discrepancies were investigated a nd revisions were made as needed.

2.9 What are the Results?

Table 2-3 summarizes the emission estimates for CMVs for criteria pollutants. Table 2-4

summarizes the emission estimates for individua l HAPs. Note that for the purposes of this inventory vessels equipped with category 1 a nd 2 propulsion engines are assumed to operate on Distillate diesel, while vessels equipped with Category 3 propulsion engine s are assumed to used a residual blend. Both tables provide data for all states; these 2008 estimat es do not include state

submitted data.

Table 2-3. Commercial Marine Vessel Criteria and Greenhouse Gas Emission Estimates 2008 (TPY)

Pollutant Diesel

Port Diesel Underway Diesel

Total Residual

Port Residual Underway Residual

Total CMV

Total

CO 113,452 37,817 151,269 5,871 68,588 74,459 225,728

CO 2 39,221,848 13,073,950 52,295,798 3,703,169 30,986,332 34,689,501 86,985,299

NH 3 210 140 350 64 323 387 737

NO X 588,844 196,281 785,125 70,044 813,908 883,952 1,669,077

PM10-

PRI 20,954 6,985 27,939 6,730 67,702 74,432 102,371

PM25-

PRI 20,325 6,775 27,100 6,081 62,318 68,399 95,499

SO 2 34,803 11,601 46,404 52,512 522,327 574,839 621,243

VOC 12,752 4,251 17,003 2,412 28,711 31,123 48,126



### * Note that for the purposes of this inventory vessels equipped with category 1 and 2 propulsion engines are assumed to operate on Distillate diesel, while vessels equi pped with Category 3 propulsion engines are assumed to

used a residual blend.



### 2-17

### Table 2-4. Commercial Marine Vessel HAP Emission Estimates 2008 (TPY)

Pollutant Diesel

Port Residual

Port Diesel Underway Residual Underway

2,2,4-Trimethylpentane 3.825675 NA 1.062688 NA Acenaphthene 0.36585 0.002068 0.101625 0.021188 Acenaphthylene 0.564019 0.003193 0.156672 0.032717 Acetaldehyde 710.6 0.552315 197.388896 6.574751

Acrolein 33.47466 NA 9.298516 NA

Anthracene 0.564019 0.003193 0.156672 0.032717

Arsenic 0.366686 2.358644 0.209535 11.836005
Benz[a]Anthracene 0.60975 0.003448 0.169375 0.035334

Benzene 194.5738 0.023636 54.048288 0.281365 Benzo[a]Pyrene 0.052384 0.011793 0.034923 0.059180
Benzo[b]Fluoranthene 0.104768 0.023586 0.069845 0.118360 Benzo[g,h,i,]Perylene 0.137194 0.000778 0.038109 0.007977
Benzo[k]Fluoranthene 0.052384 0.011793 0.034923 0.059180 Beryllium NA 0.003674 NA 0.036965

Cadmium 0.059298 0.057506 0.035970 1.530064 Chromium (VI) 0.178105 1.224973 0.118737 4.419583

Chromium III 0.345733 2.377888 0.230489 8.579191 Chrysene 0.106706 0.000604 0.029641 0.006188

Cobalt NA 1.717108 NA 10.426100 Dioxins/Furans as 2,3,7,8-TCDD TEQs 1.57E-06 1.18E-06 0.000001 0.000006 Ethyl Benzene 19.12838 NA 5.313438 NA

Fluoranthene 0.335363 0.001897 0.093156 0.019443

Fluorene 0.746944 0.004227 0.207484 0.043311 Formaldehyde 1430.802 3.786611 397.445137 45.075801

Hexachlorobenzene 0.000419 9.43E-05 0.000279 0.000473

Hexane 52.60303 NA 14.611954 NA Indeno[1,2,3-c,d]Pyrene 0.104768 0.023586 0.069845 0.118360

Lead 1.571513 0.354705 1.047675 1.773791 Manganese 0.032059 0.385606 0.008905 3.879322 Mercury 0.000524 0.008218 0.000349 0.035508 Naphthalene 21.35649 0.121021 5.932360 1.240126

Nickel 10.47675 90.68502 6.984500 398.764466
PAH, total 26.5488 0.154501 7.496895 1.584859

Phenanthrene 0.85365 0.004829 0.237125 0.049480 Phosphorus 26.71489 NA 387.932155 Polychlorinated Biphenyls 0.005238 0.001179 0.003492 0.005918 Propionaldehyde 58.34154 NA 16.205985 NA Pyrene 0.594506 0.003363 0.165141 0.034462

Selenium 0.000593 0.053465 0.000360 0.235603 Styrene 20.08479 NA 5.579110 NA

Toluene 30.6054 NA 8.501500 NA Xylenes (Mixed Isomers) 45.9081 NA 12.752250 NA



### * Note that for the purposes of this inventory vessels equipped with category 1 and 2 propulsion engines are assumed to operate on Distillate diesel, while vessels equi pped with Category 3 propulsion engines are assumed to

used a residual blend. NA – Not Applicable.



### 2-18

### 2.10 Commercial Marine Vessel References

Carey, Penny. Document entitled 2008 Deep Sea Summary Baseline , to Laurel Driver, U.S. EPA Office of Air Quality Planning and Standards (O AQPS). U.S. EPA Office of Mobile Sources (OMS). Ann Arbor, MI. February 5, 2009.

Carey, Penny. Memorandum entitled 2008 Emissions, Activity, and Fu el Consumption for CMV Diesel (i.e., Category 1, Category 2, and CMV < 37kW) , to Laurel Driver, U.S. EPA Office of Air Quality Planning and Standa rds (OAQPS). U.S. EPA Office of Mobile Sources (OMS). Ann Arbor, MI. September 16, 2009.

Carey, Penny. Document entitled 2008 Great Lakes Summary Baseline , to Laurel Driver, U.S. EPA Office of Air Quality Pla nning and Standards (OAQPS). U. S. EPA Office of Mobile Sources (OMS). Ann Arbor, MI. February 5, 2009.

Carey, Penny. Memorandum entitled 2008 OGV inventories and shapefiles , to Laurel Driver, U.S. EPA Office of Air Quality Planning and St andards (OAQPS). U.S. EPA Office of Mobile Sources (OMS). Ann Arbor, MI. February 5, 2009.

Cook, Rich. Memorandum entitled Marine EFs , to Laurel Driver and Penney Carrey, U.S. EPA Office of Air Quality Planning and Standards (O AQPS). U.S. EPA Office of Mobile Sources. Ann Arbor, MI. September 18, 2009.

Cooper, D. and Gustafsson, T. Methodology for Calc ulating Emissions from Ships: 1. Update of emission factors. Swedish Methodology for Environmental Data, Report No. 2004-02-02.

International Maritime Organization (IMO), Updated Study on Greenhouse Gas Emissions from Ships: Final Report Covering Phase 1 and Phase 2 , 9 April 2009.

U.S. Army Corps of Engineers. U.S. Army Corps of Engineers (U SACE) Principal Ports file for

2007. U.S. Army Corps of Engineers, Navigation Data Center, Waterborne Commerce Statistics.

Available at: http://www.iwr.usace.army.mil/ndc/db/pport/dbf/pport07.xls

. September 10, 2009

.

U.S. Army Corps of Engineers. Waterway Network Link Commodity Data . Water Resources Support Center, Fort Belvoir, VA. Downloaded from the following Internet site: http://www.iwr.usace.army.mil/ndc/db/watern et/tons/dbf/linktons07.xls. January 22, 2001.

U.S. Department of Transportation, Bu reau of Transportation Statistics. National Transportation
Atlas Database, 2007. Available at https://www.bts.gov/pdc/user/products/src/products.xml?p=2559&c=-1.

U.S. Environmental Protection Agency. Development of 2008CY Category 3 Commercial Marine Inventory . Office of Transportation and Air Quality, Ann Arbor, MI. 2009.

U.S. Environmental Protection Agency

. 

### Final Regulatory Support Document: Control of Emissions from New Marine Comp ression-Ignition Engines at or above 30 Liters per Cylinder. January 2003, EPA420-R-03-004

.



### 2-19

### U.S. Environmental Protection Agency. Procedures for Emission Inventory Preparation, Volume

IV: Mobile Sources . Office of Air Quality Planning and St andards. Research Triangle Park, NC.

1989.

2-20

## Appendix A 2008 Category 3 Commercial Marine Vessel Inventory Methodology

Citation: U.S. Environmental Protection Agency. Development of 2008CY Category 3 Commercial Marine Inventory . Office of Transportation and Air Quality, Ann Arbor, MI. 2009.

## Development of 2008CY Category 3 Commercial Marine Inventory

The Category 3 (C3) inventory includes vesse ls which use C3 engines for propulsion. C3 engines are defined as having di splacement above 30 liters per cy linder. The resulting inventory includes emissions from both propulsion and auxilia ry engines used on these vessels, as well as those on gas and steam turbine vessels.

Geographically, the inventories include port a nd interport emissions that occur within the area that extends 200 nautical miles (nm) from the official U.S. baseline, which is roughly equivalent to the border of the U.S. Exclusive Economic Zone (EEZ). The U.S. region was clipped to the boundaries of th e U.S. EEZ in areas where the 200nm boundary extended beyond

the EEZ.

Category 3 commercial marine inventories were developed for a base year of 2002. [1] These were then projected to 2008. Regional adju stment factors were applied to account for growth. In addition, NO X 

### adjustment factors were applied to account for implementation of the

NO X 

### Tier 1 standard. The methodology for each type of adjustment is described below.

Growth Factors by Geographic Region

The emissions inventory is calculated for nine geographic regions: Alaska East, Alaska West, East Coast, Gulf Coast, Hawaii East, Hawa ii West, North Pacific, South Pacific, and the Great Lakes. Average annual growth rates from 2002-2020 were calculated for five regions: East Coast, Gulf Coast, North Pacific, South Pacific, and the Great Lakes. The Alaska regions were assigned the growth factor for the North Pacifi c region, while the Hawaii regions were assigned the growth factor for the South Pacific region. Each regional growth rate was then compounded over the inventory projection time period for 2008 (i.e., 6 years). The av erage annual growth rates and resulting multiplicative growth factors for each emission inventory region is presented

in Table 1 below.

Table 1. Regional Emission Inventory Growth Factors for 2008

Emission Inventory Region 2002-2020 Average

Annualized Growth Rate (%) Multiplicative Growth

Factor for 2008

Relative to 2002
Alaska East (AE) 3.3 1.2151 Alaska West (AW) 3.3 1.2151
East Coast (EC) 4.5 1.3023 Gulf Coast (GC) 2.9 1.1871 Hawaii East (HE) 5.0 1.3401 Hawaii West (HW) 5.0 1.3401 North Pacific (NP) 3.3 1.2151 South Pacific (SP) 5.0 1.3401 Great Lakes (GL) 1.7 1.1064

A-1

### NO

x 

### Adjustment Factors

The 2008 calendar year baseline inventory incl udes pre-control (Tier 0) engines and those subject to the NO X 

### Tier 1 standard that became effective in 2000. The NO X 

### emission factors (EFs) by tier and engine/ship type are given in Table 2.

Table 2. NO X 

### Emission Factors by Tier

NO X 

### EF (g/kW-hr) Engine/Ship Type Tier 0 Tier 1

Main Slow-Speed Diesel (SSD) 18.1 16.1

Medium-Speed Diesel (MSD) 14 12.5 Steam Turbine (ST) 2.1 n/a

Gas Turbine 6.1 n/a Auxiliary Passenger Ship 14.6 13.0 Other Ships 14.5 12.9

The NO X 

### EFs by tier were then used with age di stributions to generate calendar year NO X 

### EFs by engine/ship type for 2008. For 2002, Tier 0 EFs were used for simplicity. These calendar year NO X 

### EFs are provided in Table 3. Since the age di stributions are different for vessels in the Great Lakes, NO X 

### EFs were determined separately for the Great Lakes.

Table 3. NO X 

### Emission Factors by Calendar Year

CY NO X 

### EF (g/kW-hr)

2008 Engine/Ship Type 2002 DSP a 

### GL b



### Main Slow-Speed Diesel (SSD) 18.1 17.07 17.50 Medium-Speed Diesel (MSD) 14 13.01 13.74 Steam Turbine (ST) 2.1 2.1 2.1

Gas Turbine 6.1 6.1 n/a Auxiliary Passenger Ship 14.6 13.76 14.32 Other Ships 14.5 13.60 14.16

a 

### DSP = Deep sea ports and areas other than the Great Lakes

b 

### GL = Great Lakes

A-2

### Emission adjustment factors for NO X 

### were then calculated. Ad justment factors are ratios of the 2008 calendar year EFs to the 2002 calenda r year EFs. The adjustment factors by engine/ship type are provided in Table 4.

Table 4. NO X 

### EF Adjustment Factors for 2008CY

2008 NO X 

### Adj (unitless) Engine/Ship Type DSP a 

### GL b



### Main Slow-Speed Diesel (SSD) 0.9433 0.9670 Medium-Speed Diesel (MSD) 0.9293 0.9815 Steam Turbine (ST) 1.0000 1.0000

Gas Turbine 1.0000 n/a Auxiliary Passenger Ship 0.9403 0.9784 Other Ships 0.9403 0.9784

Methodology for Development of 2008CY Port Inventories

For the non-California ports, 2002 emissions for each port are summed by engine/ship type. Propulsion and auxiliary emissions are summed separately, since the EF adjustment factors differ. The appropriate regional gr owth factor, as provided in Tabl e 1, is then applied, along with

the NO X 

### EF adjustment factors by engine/ship ty pe in Table 4 to calculate the 2008 port

inventories.

For the California ports, 2002 emissions for each port are summed by ship type. Propulsion and auxiliary emissions are summed separately, since the EF adjustment factors differ. The EF adjustment factors by engine/ship type in Table 4 are consolidated by ship type, using the CARB assumption that engines on all ships except passe nger ships are 95 percent slow speed diesel (SSD) engines and 5 percent me dium speed diesel engines (MSD) based upon a 2005 CARB survey. All passenger ships were assumed to be MSD engines. Steam turbines (ST) and gas turbines (GT) are not included in the CARB inventory. The NO X 

### EF adjustment factors by ship type are then applie d, along with ship-specific grow th factors used by CARB, to calculate the 2008 California port in ventories. The ship-specific growth factors for 2008 relative to 2002 are provided in Table 5 below.

A-3

### Table 5. Growth Factors by Ship Type for California Ports

Calendar Year Ship Type 2002 2008

Auto 1.0000 1.1525

Bulk 1.0000 0.7412

Container 1.0000 1.4023

General 1.0000 0.9071 Passenger 1.0000 1.9823

Reefer 1.0000 1.0112

RoRo 1.0000 1.1525

Tanker 1.0000 1.3005

Methodology for Development of 2008CY Interport Inventories

The interport portion of the inventory is not segregated by engine or ship type. As a result, regional NO X 

### EF adjustment factors were devel oped based on the assumed mix of main (propulsion) engine types in each region. The mix of main engine types by region was developed using the ship call and power data and is presented in Table 6. Main engines are considered a good surrogate for interport emissions, since the majority of emissions while underway are due to the main engines. The NO X 

### EF adjustment factors by main engine type in Table 4 were used together with the mix of main engine types by region in Table 6 to develop the regional adjustment factors. The resulting NO X 

### EF regional adjustment fact ors are provided in Table 7.

These NO X 

### EF regional adjustment factor s, together with the regiona l growth factors in Table 1, were applied to calculate th e 2008 interport inventories.

Table 6. Installed Power by Main Engine Type

2008 Installed Power (%) Region MSD SSD GT ST
Alaska East (AE) 19.1% 18.4% 0.3% 62.2% Alaska West (AW) 19.1% 18.4% 0.3% 62.2%
East Coast (EC) 25.6% 72.5% 0.9% 1.0% Gulf Coast (GC) 13.7% 85.5% 0.0% 0.8% Hawaii East (HE) 66.2% 18.5% 7.4% 8.0% Hawaii West (HW) 66.2% 18.5% 7.4% 8.0% North Pacific (NP) 5.1% 83.5% 1.6% 9.7% South Pacific (SP) 17.8% 82.2% 0.0% 0.0% Great Lakes (GL) 47.9% 43.7% 0.0% 8.4%

A-4

### Table 7. NO X 

### EF Regional Adjustment Factors

Region 2002 2008
Alaska East (AE) 1.0000 0.9761 Alaska West (AW) 1.0000 0.9761
East Coast (EC) 1.0000 0.9408 Gulf Coast (GC) 1.0000 0.9419 Hawaii East (HE) 1.0000 0.9428 Hawaii West (HW) 1.0000 0.9428 North Pacific (NP) 1.0000 0.9490 South Pacific (SP) 1.0000 0.9408 Great Lakes (GL) 1.0000 0.9767

The resulting 2008 Category 3 emission inventor ies are shown in Table 8 for each of the nine geographic regions and the nation.

Table 8. 2008 Regional and National Emissi ons from Category 3 Vessel Main and Auxiliary Engines

Metric Tonnes
Region NO X PM 10 PM 2.5 a HC CO SO 2 CO 2 Alaska East (AE) 21,590 1,749 1,609 733 1,730 13,032 807,159
Alaska West (AW) 71,901 5,755 5,294 2,441 5,750 42,694 2,631,081
East Coast (EC) 271,707 23,021 21,180 9,573 22,665 190,767 10,696,360
Gulf Coast (GC) 195,240 16,839 15,492 6,903 16,990 125,728 7,604,870
Hawaii East (HE) 28,837 2,403 2,211 1,013 2,390 17,843 1,108,047
Hawaii West (HW) 40,573 3,381 3,110 1,426 3,362 25,105 1,559,016
North Pacific (NP) 30,248 2,647 2,435 1,153 2,568 18,790 1,216,723
South Pacific (SP) 132,669 10,982 10,103 4,692 11,368 81,896 5,145,632
Great Lakes (GL) 16,395 1,318 1,212 557 1,312 9,797 605,001

Total Metric Tonnes 809,160 68,094 62,646 28,492 68,136 525,651 31,373,889

Total Short Tons b 891,946 75,061 69,056 31,407 75,107 579,431 34,583,792

a Estimated from PM 10 using a multiplicative adjustment factor of 0.92



### .

Reference (for 2002 inventory development) 1) U.S. Environmental Protection Agency, “Dra ft Regulatory Impact Analysis: Control of Emissions of Air Pollution from Category 3 Marine Diesel Engines,” Office of Transportation and Air Qua lity, EPA-420-D-09-002, June 2009.

A-5

## Appendix B

2008 Commercial Marine Vessel Hazardou s Air Pollutant Speciation Profiles

### Table 1. Category 1 and 2 Hazardous Air Pollutant Speciation Profile for Port Activities

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

540841 2,2,4-trimethylpentane VOC 3.00E-04

83329 Acenaphthene PM 2.5 

### 1.80E-05

208968 Acenaphthylene PM 2.5 

### 2.78E-05

75070 Acetaldehyde VOC 5.57E-02

107028 Acrolein VOC 2.63E-03

NH3 Ammonia PM 10 

### 1.15E-02

120127 Anthracene PM 2.5 

### 2.78E-05

7440382 Arsenic PM 10 

### 1.75E-05

56553 Benz[a]Anthracene PM 2.5 

### 3.00E-05

71432 Benzene VOC 1.53E-02

50328 Benzo[a]Pyrene PM 10 

### 2.50E-06

205992 Benzo[b]Fluoranthene PM 10 

### 5.00E-06

191242 Benzo[g,h,I,]Perylene PM 2.5 

### 6.75E-06

207089 Benzo[k]Fluoranthene PM 10 

### 2.50E-06

7440439 Cadmium PM 10 

### 2.83E-06

16065831 Chromium III PM 10 

### 1.65E-05

18540299 Chromium VI PM 10 

### 8.50E-06

218019 Chrysene PM 2.5 

### 5.25E-06

600 Dioxin PM 10 

### 2.50E-09

100414 Ethylbenzene VOC 1.50E-03

206440 Fluoranthene PM 2.5 

### 1.65E-05

86737 Fluorene PM 2.5 

### 3.68E-05

50000 Formaldehyde VOC 1.12E-01

118741 Hexachlorobenzene PM 10 

### 2.00E-08

193395 Indeno[1,2,3-c,d]Pyrene PM 10 

### 5.00E-06

439921 Lead PM 10 

### 7.50E-05

7439965 Manganese PM 10 

### 1.53E-06

7439976 Mercury PM 10 

### 2.50E-08

91203 Naphthalene PM 2.5 

### 1.05E-03

110543 n-Hexane VOC 4.13E-03

7440020 Nickel PM 10 

### 5.00E-04

1336363 Polychlorinated Biphenyls PM 10 

### 2.50E-07

85018 Phenanthrene PM 2.5 

### 4.20E-05

123386 Propionaldehyde VOC 4.58E-03

129000 Pyrene PM 2.5 

### 2.93E-05

7782492 Selenium PM 10 

### 2.83E-08

100425 Styrene VOC 1.58E-03

108883 Toluene VOC 2.40E-03

B-1

### Table 2. Category 1 and 2 Hazardous Air Pollutant Speciation Profile for Underway Activities

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

1330207 Xylene VOC 3.60E-03

540841 2,2,4-trimethylpentane VOC 2.50E-04

83329 Acenaphthene PM 2.5 

### 1.50E-05

208968 Acenaphthylene PM 2.5 

### 2.31E-05

75070 Acetaldehyde VOC 4.64E-02

107028 Acrolein VOC 2.19E-03

NH3 Ammonia PM 10 

### 2.31E-02

120127 Anthracene PM 2.5 

### 2.31E-05

7440382 Arsenic PM 10 

### 3.00E-05

56553 Benz[a]Anthracene PM 2.5 

### 2.50E-05

71432 Benzene VOC 1.27E-02

50328 Benzo[a]Pyrene PM 10 

### 5.00E-06

205992 Benzo[b]Fluoranthene PM 10 

### 1.00E-05

191242 Benzo[g,h,I,]Perylene PM 2.5 

### 5.63E-06

207089 Benzo[k]Fluoranthene PM 10 

### 5.00E-06

7440439 Cadmium PM 10 

### 5.15E-06

16065831 Chromium III PM 10 

### 3.30E-05

18540299 Chromium VI PM 10 

### 1.70E-05

218019 Chrysene PM 2.5 

### 4.38E-06

600 Dioxin PM 10 

### 5.00E-09

100414 Ethylbenzene VOC 1.25E-03

206440 Fluoranthene PM 2.5 

### 1.38E-05

86737 Fluorene PM 2.5 

### 3.06E-05

50000 Formaldehyde VOC 9.35E-02

118741 Hexachlorobenzene PM 10 

### 4.00E-08

193395 Indeno[1,2,3-c,d]Pyrene PM 10 

### 1.00E-05

7439921 Lead PM 10 

### 1.50E-04

7439965 Manganese PM 10 

### 1.28E-06

7439976 Mercury PM 10 

### 5.00E-08

91203 Naphthalene PM 2.5 

### 8.76E-04

110543 n-Hexane VOC 3.44E-03

7440020 Nickel PM 10 

### 1.00E-03

1336363 Polychlorinated Biphenyls PM 10 

### 5.00E-07

B-2

### Table 2. Category 1 and 2 Hazardous Air Pollutant Speciation Profile for Underway Activities (Continued)

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

85018 Phenanthrene PM 2.5 

### 3.50E-05

123386 Propionaldehyde VOC 3.81E-03

129000 Pyrene PM 2.5 

### 2.44E-05

7782492 Selenium PM 10 

### 5.15E-08

100425 Styrene VOC 1.31E-03

108883 Toluene VOC 2.00E-03

1330207 Xylene VOC 3.00E-03

Table 3. Category 3 Hazardous Air Pollutant Speciation Profile for Hotelling Activities

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

83329 Acenaphthene PM 2.5 

### 3.40E-07

208968 Acenaphthylene PM 2.5 

### 5.25E-07

75070 Acetaldehyde VOC 2.29E-04

NH3 Ammonia PM 10 

### 1.08E-02

120127 Anthracene PM 2.5 

### 5.25E-07

7440382 Arsenic PM 10 

### 4.00E-04

56553 Benz[a]Anthracene PM 2.5 

### 5.67E-07

71432 Benzene VOC 9.80E-06

50328 Benzo[a]Pyrene PM 10 

### 2.00E-06

205992 Benzo[b]Fluoranthene PM 10 

### 4.00E-06

191242 Benzo[g,h,I,]Perylene PM 2.5 

### 1.28E-07

207089 Benzo[k]Fluoranthene PM 10 

### 2.00E-06

7440417 Beryllium PM 10 

### 5.46E-07

7440439 Cadmium PM 10 

### 5.90E-06

16065831 Chromium III PM 10 

### 3.96E-04

18540299 Chromium VI PM 10 

### 2.04E-04

218019 Chrysene PM 2.5 

### 9.93E-08

7440484 Cobalt PM 10 

### 2.92E-04

53703 Dibenzo[a,h]Anthracene PM 2.5 

### 0.00E+00

600 Dioxin PM 10 

### 2.00E-09

B-3

### Table 3. Category 3 Hazardous Air Pollutant Speciation Profile for Hotelling Activities (Continued)

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

206440 Fluoranthene PM 2.5 

### 3.12E-07

86737 Fluorene PM 2.5 

### 6.95E-07

50000 Formaldehyde VOC 1.57E-03

118741 Hexachlorobenzene PM 10 

### 1.60E-08

193395 Indeno[1,2,3-c,d]Pyrene PM 10 

### 4.00E-06

7439921 Lead PM 10 

### 6.00E-05

7439965 Manganese PM 10 

### 5.73E-05

7439976 Mercury PM 10 

### 1.40E-06

91203 Naphthalene PM 2.5 

### 1.99E-05

7440020 Nickel PM 10 

### 1.54E-02

1336363 Polychlorinated Biphenyls PM 10 

### 2.00E-07

85018 Phenanthrene PM 2.5 

### 7.94E-07

7723140 Phosphorous PM 10 

### 4.38E-03

130498292 POM as 16-PAH PM 2.5 

### 2.49E-05

130498292 POM as 7-PAH PM 10 

### 4.50E-07

129000 Pyrene PM 2.5 

### 5.53E-07

7782492 Selenium PM 10 

### 9.08E-06

Table 4. Category 3 Hazardous Air Pollutant Speciation Profile for Maneuvering Activities

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

83329 Acenaphthene PM 2.5 

### 3.40E-07

208968 Acenaphthylene PM 2.5 

### 5.25E-07

75070 Acetaldehyde VOC 2.29E-04

NH3 Ammonia PM 10 

### 2.38E-03

120127 Anthracene PM 2.5 

### 5.25E-07

7440382 Arsenic PM 10 

### 8.74E-05

56553 Benz[a]Anthracene PM 2.5 

### 5.67E-07

71432 Benzene VOC 9.80E-06

50328 Benzo[a]Pyrene PM 10 

### 4.37E-07

205992 Benzo[b]Fluoranthene PM 10 

### 8.74E-07

B-4

### Table 4. Category 3 Hazardous Air Pollutant Speciation Profile for Maneuvering Activities (Continued)

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

191242 Benzo[g,h,I,]Perylene PM 2.5 

### 1.28E-07

207089 Benzo[k]Fluoranthene PM 10 

### 4.37E-07

7440417 Beryllium PM 10 

### 5.46E-07

7440439 Cadmium PM 10 

### 2.26E-05

16065831 Chromium III PM 10 

### 1.27E-04

18540299 Chromium VI PM 10 

### 6.53E-05

218019 Chrysene PM 2.5 

### 9.93E-08

7440484 Cobalt PM 10 

### 5.94E-05

53703 Dibenzo[a,h]Anthracene PM 2.5 

### 0.00E+00

600 Dioxin PM 10 

### 4.37E-10

206440 Fluoranthene PM 2.5 

### 3.12E-07

86737 Fluorene PM 2.5 

### 6.95E-07

50000 Formaldehyde VOC 1.57E-03

118741 Hexachlorobenzene PM 10 

### 3.50E-09

193395 Indeno[1,2,3-c,d]Pyrene PM 10 

### 8.74E-07

7439921 Lead PM 10 

### 1.40E-05

7439965 Manganese PM 10 

### 5.73E-05

7439976 Mercury PM 10 

### 2.71E-07

91203 Naphthalene PM 2.5 

### 1.99E-05

7440020 Nickel PM 10 

### 3.25E-03

1336363 Polychlorinated Biphenyls PM 10 

### 4.37E-08

85018 Phenanthrene PM 2.5 

### 7.94E-07

7723140 Phosphorous PM 10 

### 1.79E-03

130498292 POM as 16-PAH PM 2.5 

### 2.49E-05

130498292 POM as 7-PAH PM 10 

### 4.90E-07

129000 Pyrene PM 2.5 

### 5.53E-07

7782492 Selenium PM 10 

### 1.91E-06

Table 5. Category 3 Hazardous Air Pollutant Speciation Profile for Underway Activities

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

83329 Acenaphthene PM 2.5 

### 3.40E-07

208968 Acenaphthylene PM 2.5 

### 5.25E-07

B-5

### Table 5. Category 3 Hazardous Air Pollutant Speciation Profile for Underway Activities (Continued)

Pollutant

Code Pollutant Speciation

Basis 2008

Emission

Factor

75070 Acetaldehyde VOC 2.29E-04

NH3 Ammonia PM 10 

### 4.77E-03

120127 Anthracene PM 2.5 

### 5.25E-07

7440382 Arsenic PM 10 

### 1.75E-04

56553 Benz[a]Anthracene PM 2.5 

### 5.67E-07

71432 Benzene VOC 9.80E-06

50328 Benzo[a]Pyrene PM 10 

### 8.74E-07

205992 Benzo[b]Fluoranthene PM 10 

### 1.75E-06

191242 Benzo[g,h,I,]Perylene PM 2.5 

### 1.28E-07

207089 Benzo[k]Fluoranthene PM 10 

### 8.74E-07

7440417 Beryllium PM 10 

### 5.46E-07

7440439 Cadmium PM 10 

### 2.26E-05

7440473 Chromium PM 10 

### 1.92E-04

16065831 Chromium III PM 10 

### 1.27E-04

18540299 Chromium VI PM 10 

### 6.53E-05

218019 Chrysene PM 2.5 

### 9.93E-08

7440484 Cobalt PM 10 

### 1.54E-04

53703 Dibenzo[a,h]Anthracene PM 2.5 

### 0.00E+00

600 Dioxin PM 10 

### 8.74E-10

206440 Fluoranthene PM 2.5 

### 3.12E-07

86737 Fluorene PM 2.5 

### 6.95E-07

50000 Formaldehyde VOC 1.57E-03

118741 Hexachlorobenzene PM 10 

### 6.99E-09

193395 Indeno[1,2,3-c,d]Pyrene PM 10 

### 1.75E-06

7439921 Lead PM 10 

### 2.62E-05

7439965 Manganese PM 10 

### 5.73E-05

7439976 Mercury PM 10 

### 5.24E-07

91203 Naphthalene PM 2.5 

### 1.99E-05

7440020 Nickel PM 10 

### 5.89E-03

1336363 Polychlorinated Biphenyls PM 10 

### 8.74E-08

85018 Phenanthrene PM 2.5 

### 7.94E-07

7723140 Phosphorus PM 10 

### 5.73E-03

130498292 POM as 16-PAH PM 2.5 

### 2.49E-05

130498292 POM as 7-PAH PM 10 

### 4.90E-07

129000 Pyrene PM 2.5 

### 5.53E-07

7782492 Selenium PM 10 

### 3.48E-06

B-6

### ERG No.: 0245.03.402.001

Contract No.: EP-D-07-097



## Documentation for Locomotive Compon ent of the National Emissions

Inventory Methodology

Prepared by:

Eastern Research Group

1600 Perimeter Park Drive Morrisville, North Carolina 27560

Under Contract to: E.H. Pechan & Associates, Inc. 3622 Lyckan Parkway

Suite 2002 Durham, North Carolina 27707

For Submittal to:

Laurel Driver Emissions, Monitoring and Analysis Division U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27711

May 3, 2011

### i TABLE OF CONTENTS

Section Page No.

1.0 INTRODUCTION ........................................................................................................... 1-1

1.1 What are Locomotive Sources? ........................................................................... 1-1

2.0 DEVELOPMENT OF THE LOCOMOTIVE COMPONENT FOR THE NEI .............. 2-1

2.1 What Pollutants are Included in the National Emission Estimates for

Locomotives? ....................................................................................................... 2-1

3.0 HOW WERE LOCOMOTIVE EM ISSIONS ESTIMATED? ........................................ 3-1

3.1 Line Haul Criteria Emissions Estimates .............................................................. 3-1

3.2 Rail Yard Criteria Emissions Estimates ............................................................... 3-1

3.3 Hazardous Air Pollutant Emissions Estimates ..................................................... 3-2

4.0 HOW WERE COUNTY LINE HAUL EMISSIONS REALLOCATED TO

INDIVIDUAL RAIL SEGMENTS? ................................................................................ 4-1

4.1 Class I Line Haul Emi ssions Allocation .............................................................. 4-1

4.2 Class II/III Line Haul Em issions Allocation ........................................................ 4-2

4.3 Rail Yard Emissions Allocation........................................................................... 4-3

4.4 State Provided Data .............................................................................................. 4-3

4.5 What are the Results?........................................................................................... 4-3

5.0 REFERENCES ................................................................................................................ 5-1

Appendix A – ERTAC Class I Line Haul Documentation

Appendix B – ERTAC Class II/III Line Haul Documentation

Appendix C – ERTAC Rail Yard Documentation

### ii LIST OF TABLES AND FIGURES

Tables Page No.

Table 2-1. Locomotive Pollutant List .......................................................................................... 2-1 Table 2-2. Methods Used to Develop A nnual Emission Estimates for Nonroad

Mobile Sources ................................................................................................................ ............ 2-2 Table 3-1. Hazardous Air Pollutant Speciation Profile for 2008 Locomotive

Emission Es timation ........................................................................................................... ......... 3-2 Table 4-1. Line Haul Segment Activity (MGTM/Mi) Categories ............................................... 4-1

### 1-1 

## 1.0 INTRODUCTION

1.1 What are Locomotive Sources?

The locomotive source category includes railro ad locomotives powered by diesel-electric engines. A diesel-electric locomo tive uses 2-stroke or 4-stroke di esel engines and an alternator or a generator to produce the electricity require d to power its traction motors. The locomotive source category does not include locomotives powered by electricity or steam. Emissions associated with the operation of electric locomotiv es would be included in the point source utility

emission estimate. It is believed that the numbe r of wood or coal driven steam locomotives is currently very small; therefore, these types of locomotives are not included in this inventory.

The locomotive source category is further divi ded up into three cate gories: Class I line haul, Class II/III line haul, and Class I yard. The national rail estimates were developed by the Eastern Regional Technical Advisory Committee he reafter referenced as ERTAC Rail. This group is comprised of eastern stat es’ regulatory agencies in collabo ration with the rail industry. ERTAC Rail developed emissions estimates base d on fuel data obtained from the American Association of Railroads for each subcategory. California locomotive emission estimates were handled separately from the rest of the Unite d States because of th eir use of low sulfur

locomotive diesel fuels.

### 2-1 

## 2.0 DEVELOPMENT OF THE LOCOMO TIVE COMPONENT FOR THE

NEI

2.1 What Pollutants are Included in the Nation al Emission Estimates for Locomotives?

All of the criteria pollutants, VOC, CO, NO

x 

### , SO

x 

### , PM, and PM 2.5 

### , are included in the locomotive component of the NEI. OTAQ identified the HAPs for which data were available to develop inventory estimates (Scarbro, 2001). Th e hazardous air pollutants (HAPs), listed below,

were identified based on available test data and accepted emission estimation procedures. Emission estimation methods have changed over the history of the NEI, as outlined briefly in

Table 2-2 for nonroad sources.

Table 2-1. Locomotive Pollutant List

1,3-Butadiene Beryllium Napthalene

2,2,4-Trimethylpentane Cadmium n-Hexane

Acenaphthene Chromium (Hexavalent) Nickel

Acenaphthylene Chromium (Trivalent) Phenanthrene

Acetaldehyde Chrysene PAH Propionaldehyde

Acrolein Dibenz(a,h) anthracene Pyrene

Anthracene Ethyl Benzene Styrene

Arsenic Fluoranthene Toluene

Benzene Fluorene Xylene

Benzo(a)anthracene Formaldehyde

Benzo[a]pyrene Indeno(1,2,3-cd) pyrene

Benzo[b]fluoranthene Lead

Benzo[g,h,i,]perylene Manganese

Benzo[k]fluoranthene Mercury2-2Table 2-2. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*NONROAD CategoriesNonroad Gasoline,Diesel, LPG,CNG2008 VOC, NOx, CO, SO2,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines weredeveloped using EPA’s National Mobile InventoryModel (NMIM), which incorporates NONROAD2008.Where states providedalternate NMIM nonroadinputs, these data replaced EPA default inputs.2005 VOC, NOx, CO, SO2, ,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines were developed using EPA’s NMIM, which incorporatesNONROAD2005. Where States providedalternate nonroad inputs, these data replaced EPA default inputs.2002 VOC, NOx, CO, SO2,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines were developed using EPA’s NMIM, which incorporatesNONROAD2004. Where states provided alternate nonroad inputs, these data replaced EPA default inputs.State-supplied emissions data also replaced default EPA emission estimates.1999 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROADmodel; and 2) an updated 1999 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated fromthe Lockdown C model. Replaced State-submitted datafor California for all NONROAD model categories; Pennsylvania for recreational marine and aircraft groundsupport equipment, and Texas forselect equipment categories.1996, 1997,1998, 2000 &2001VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated year-specific national andCalifornia inventories, based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the1996 county-level emission estimates, seasonal and daily county-to-national ratios and California county-tostate ratios were then developed for application to updated national estimates per season estimated from theLockdown C model. California results replace the diesel equipment emissions generated from priorapplication of county-to-national ratios.2-3Table 2-2. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Nonroad Gasoline,Diesel, LPG, andCNG(Continued)1991-1995 VOC, NOx, CO, SO2,PM10, PM2.5, NH3Using 1990 and 1996 county-level emissions inventories, estimated emissions using linear interpolation ofnational emissions between 1990 and 1996. From these emissions, calculated the average annual growth ratefor each pollutant/SCC combination for each year, and thenapplied the growth factors to 1990 county-levelemissions to estimate 1991-1995 emissions.1990 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1990 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated from the Lockdown C model.1986, 1988, &1989VOC, NOx, CO, SO2,PM10, PM2.5, NH3Using 1985 and 1990 county-level emissions inventories, estimated emissions using linear interpolation ofnational emissions between 1985 and 1990. From these emissions, calculated the average annual growth ratefor each pollutant/SCC combination for each year, and thenapplied the growth factors to 1985 county-levelemissions to estimate 1986-1989 emissions.1987 VOC, NOx, CO, SO2,PM10, PM2.5Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated nationalemissions for 1987 by running 4 seasonal NONROAD model runs to estimate annual criteria pollutantemissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.1985 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1985 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated from the Lockdown C model.1970, 1975,1978, & 1980VOC, NOx, CO, SO2,PM10, PM2.5Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated nationalemissions for all years by running 4 seasonal NONROAD model runs to estimate annual criteria pollutantemissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.2-4Table 2-2. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Nonroad Gasoline,Diesel, LPG, andCNG(Continued)1996, 1997,1998, 1999,2000, & 2001NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying byNH3emission factors, and distributing to counties using 1996 inventory, based on October 2001 draftNONROAD. NH3emissions for California were also recalculated using updated diesel fuel consumptionvalues generated for California-specific runs, and assuming the 1996 county-level distribution.1985 & 1990 NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying byNH3emission factors, and distributing to counties using 1996 inventory, based on October 2001 draftNONROAD.1987 NH3Obtaining 1987 national fuel consumption estimates from Lockdown C NONROAD model and multiplyingby NH3emission factors.1970, 1975,1978, & 1980NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model and multiplying byNH3emission factors.1990, 1996, &1999HAPs Speciation profiles applied to county VOC and PM estimates. Metal HAPs were calculated using fuel andactivity-based emission factors. Some state data were provided and replacednational estimates. (2003)AircraftCommercial Aircraft 2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System (EDMS) - Version5.1.was run using BTS T-100 LTO data. (2009)2002 and 2005 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion and Modeling System (EDMS) was runfor criteria pollutants, VOC and PM emissions were speciated into HAP components. (2004)1990, 1996,1999, 2000,2001VOC, NOx, CO, SOxInput landing and take-off (LTO) data into FAA EDMS. National emissions were assigned to airports basedon airport specific LTO data and BTS GIS data.State data replaced national estimates. (2003)1970-1998 VOC, NOx, CO, SOxEstimated emissions for interim years using linearinterpolation between available base years. (2003)1990, 1996,1999HAPs Speciation profiles were applied to VOC estimates to get national HAP estimates. State data replacednational estimates. (2003)General Aviation,Air Taxis2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System (EDMS) - Version5.1.was run using BTS T-100 LTO for aircraft identified as Air taxis. (2010)Used FAA LTO data from TAF and OTAQ provided activity data for smaller airports derived from FAA5010 master plans. EPA approved generic emission factors for criteria estimates. Speciation profiles wereapplied to VOC and PM estimates to get national HAP estimates. (2010)2-5Table 2-2. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*General Aviation,Air Taxis(Continued)2005 VOC, NOx, CO, SO2,PM10, PM2.52002 emissions for approximately 4,000 largest airports were calculated via EDMS and SIP guidance andincluded in the 2005 NEI as point sources. Only airports in FAA’s T100 and TAF databases were included.State point source submittals were incorporated.1978, 1987,1990, 1996,1999, 2000,2001, & 2002VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data and EPA approved emission factors for criteria estimates. Speciation profiles wereapplied to VOC estimates to get national HAP estimates. State data replaced national estimates. (2004)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999, & 2002HAPs Used FAA LTO data and EPA approved emission factors for criteria estimates. Speciation profiles wereapplied to VOC estimates to develop national HAP estimates. (2004)1990, 1996,1999, & 2002Pb Used Department of Energy (DOE) aviation gasoline usage data with lead concentration of aviation gasoline.(2004)1996 NH3Applied NH3emissions factors to 1996 national jet fuel and aviation gasoline consumption estimates.Military Aircraft2008 VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data as reported in TAF and EPA approved emission factors for criteria estimates.Representative HAP profiles were not readily available,therefore HAP estimates were not developed. (2010)2005 VOC, NOx, CO, SO2,PM10, PM2.52002 emissions were included in the 2005 NEI as point sources similar to other TAF reported data.1978, 1987,1990, 1996,1999, 2000,2001, 2002,2008VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data as reported in TAF and EPA approved emission factors for criteria estimates.Representative HAP profiles were not readily available, therefore HAP estimates were not developed.1970-1998 VOC, NOx, CO, SOX,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)Auxiliary PowerUnits and GroundSupport Equipment2008 VOC, NOx, CO, SO2,PM10, PM2.5, HAPsFederal Aviation Administration (FAA) Emissions and Dispersion and Modeling System (EDMS) - Version5.1.was run using BTS T-100 LTO data. (2009)2002 and 2005 VOC, NOx, CO, SO2,PM10, PM2.5, HAPsComputed via NONROAD2005 model runs1985-2001 VOC, NOx, CO, SO2,PM10, PM2.5Grew 1996 emissions to each year using LTO operations data from the FAA. Estimation methods prior to1996 reported in EPA, 1998.2-6Table 2-2. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Unpaved Airstrips11985-2001 PM10, PM2.5Grew 1996 emissions to each year using SIC 45-Air Transportation growth factors, consistent with thecurrent draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998.Aircraft Refueling11985-2001 VOC Grew 1996 emissions to each year using SIC 45-Air Transportation growth factors, consistent with thecurrent draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998.Commercial Marine Vessel (CMV)All CMV Categories 2008 VOC, NOx, CO, SO2,PM10, PM2.5OTAQ provided CAP emission estimates for all CMV categories. Note that the SCCs for this category havechanged such that the Diesel category refers to smaller vessels (Category 1 and 2) using distillate fuels andthe Residual category refers to larger (Category 3) vessels using a blend of residual fuels. Emissions wereallocated to segments using GIS shapefiles and adjusted based on limited state data (2010)2008 HAPs OTAQ’s 2008 estimates were speciated into HAP components using SEPA profiles (2009)CMV Diesel 2002 and2005VOC, NOx, CO, SO2,PM10, PM2.52001 Estimates carried over. Usedstate data when provided. (2004)HAPs 1999 Estimates carried over. Used state data when provided. (2004)1978, 1987,1990, 1996,1999, 2000, &2001VOC, NOx, CO, SOx,PM10, & PM2.5Used criteria emission estimates in the background document for marine diesel regulations for 2000.Adjusted 2000 criteria emission estimates for other used based on fuel usage. Emissions were disaggregatedinto port traffic and underway activities. Port emissions were assignedto specific ports based on amount ofcargo handled. Underway emissions were allocated based on Army Corp of Engineering waterway data.State data replaced national estimates. (2003)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999HAPs VOC and PM emission estimateswere speciated into HAP components. State data replaced nationalestimates. (2003)1996 NH3Applied NH3emissions factors to 1996 distillate and residualfuel oil estimates (i.e., as reported in EIA,1996).1990-1995 NH3Estimation methods reported in EPA, 1998.2-7Table 2-2. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*CMV SteamPowered2005 VOC, NOx, CO, SOx,PM10, & PM2.5,HAPs2002 estimates grown to 2005 (2008).2002 VOC, NOx, CO, SOx,PM10, & PM2.5,HAPs2002 based estimates were developed for port and underway category 3 (C3) vessels as part of a rulemakingeffort. Emissions were developed separately for near port and underway emissions. For near portemissions, inventories for 2002 were developed for 89 deep water and 28 Great Lake ports in the U.S. TheWaterway Network Ship Traffic, Energy, and Environmental Model (STEEM) was used to provideemissions from ships traveling in shipping lanes between and near individual ports (2008)1978, 1987,1990, 1996,1999, 2000, &2001VOC, NOx, CO, SOx,PM10, & PM2.5Calculated criteria emissions based on EPA SIP guidance. Emissions were disaggregated into port trafficand under way activities. Port emissions were assignedto specific ports based onamount of cargo handled.Underway emissions were allocated based on Army Corpof Engineering waterway data. State data replacednational estimates. (2003)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996, &1999HAPs VOC and PM emission estimateswere speciated into HAP components. State data replaced nationalestimates. (2003)Military Marine 1997-2001 VOC, NOx, CO, SO2,PM10, PM2.5Applied EGAS growth factors to 1996emissions estimates for this category.CMV Coal,2CMV,Steam powered,CMV Gasoline21997-1998 VOC, NOx, CO, SO2,PM10, PM2.5Applied EGAS growth factors to 1996emissions estimates for this category.CM Coal, CMV,Steam powered,CMV Gasoline,Military Marine1991-1995 VOC, NOx, CO, SO2,PM10, PM2.5Estimation methods reported in EPA, 1998.LocomotivesClass I, II, III andYard operations2008 VOC, NOx, CO, PM10,PM2.5,SOx& HAPsCriteria emission estimates were provided to EPA byERTAC. These data were assigned to individualrailway segments using DOT shapefiles and guidance from ERTAC. HAP emissions were calculatedby applying speciation profiles toVOC and PM estimates. (2010)2-8Table 2-2. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Class I, Class II,Commuter,Passenger, and YardLocomotives1978, 1987,1990, 1996,1999, 2000,2000, 2002, &2005VOC, NOx, CO, PM10,PM2.5Criteria pollutants were estimated by using locomotive fuel use data from DOE EIA and available emissionfactors. County-level estimates were obtained by scaling the national estimates with the rail GIS data fromDOT. State data replaced national estimates. (2004)1978, 1987,1990, 1996,1999, 2000,2001, 2002, &2005SO2SOxemissions were calculated by using locomotive fuel use and fuel sulfur concentration data from EIA.County-level estimates were obtained by scaling the national estimates with the county level rail activitydata from DOT. State data replaced national estimates. (2004)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999, & 2002HAPs HAP emissions were calculated byapplying speciation profiles to VOCand PM estimates. County-levelestimates were obtained by scaling the national estimates with the county level rail activity from DOT.State data replaced national estimates. (2004)1997-1998 NH3Grew 1996 base year emissions using EGAS growth indicators.1996 NH3Applied NH3emissions factors to diesel consumption estimates for 1996.1990-1995 NH3Estimation methods reported in EPA, 1998.Notes:*Dates included at the end of Estimation Method represent the year that the section was revised.1 Emission estimates for unpaved airstrips and aircraft refueling are included in the area source NEI, since they represent non-engine emissions.2 National Emission estimates for CMV Coal and CMV Gasoline were not developed though states and local agencies may have submitted estimates for these sourcecategories.EPA, 1998. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Emission Factors and Inventory Group, National Air PollutantEmission Trends, Procedures Document, 1900–1996, EPA-454/R-98-008. May 1998.

### 3-1 

## 3.0 HOW WERE LOCOMOTIVE EMISSIONS ESTIMATED?

ERTAC Rail used confidential railroad-provided data to generate railroad-specific criteria emission estimates for line haul and rail ya rds at the rail segment and rail yard level, respectively. Appendices A-C provide more detail on how emissions were developed and includes critical data used in calculating these esti mates. This section of the report describes the emission estimating methods used in general term s as well as the approach for reallocating the emissions to protect confidenti al data. The data and documentation provided with respect to ERTAC Rail’s emission estimates pertain to the ve rsion that was incorporated into the NEI and

does not reflect recent revisions.

3.1 Line Haul Criteria Emissions Estimates

Criteria pollutant emissions were estimate d by applying emission factors to the total amount of distillate fuel oil used by line ha ul locomotives. Fuel usage was obtained from publically available Class I Railroad Annual Repor ts (Form R-1). The R-1 reports are submitted to the Surface Transportation Board annually and include financial and op erations data to be used in monitoring rail industry health and id entifying changes that may affect national transportation policy. Additionally, each railroad provided fleet mix information that allowed ERTAC Rail to calculate railroad-specific emissi on factors. Weighted Emission Factors (EF) per pollutant for each gallon of fuel used (gm/gal or lbs/gal) were calculated for each Class I

railroad fleet based on its fracti on of line haul locomotives at each regulated Tier level. EPA

emission factors were used for PM 2.5 

### , SO 2 

### , and NH 3



### .

The weighted emission factors were then appl ied to the link-specific fuel consumption to obtain emissions for each rail segment. Given th e confidentiality of the activity data, emissions for criteria pollutants were provided to EPA by ERTAC Rail by county for Class I line haul. Class II/III rail was provided by railroad company and county. Appendices A and B provide

more detail on the Class I and Class II/III lin e haul emission development, respectively.

3.2 Rail Yard Criteria Emissions Estimates

Rail yard locations were identified using a database from the Federal Railroad Administration. Criteria pollutant emissions were estimated by applying emission factors to the total amount of distillate fuel used by locomotiv es. Each railroad provided fleet mix information that allowed ERTAC to calculate railroad-speci fic emission factors. The company-specific, system wide fleet mix was used to calculate we ighted average emissions factors for switchers operated by each Class I railroad. EP A emission factors were used for PM 2.5 

### , SO 2 

### , and NH 3



### .

R-1 report-derived fuel use was allocated to rail yards using an approximation of line haul activity data within the ya rd; see Appendix C for more deta ils. These fuel consumption values were further revised by di rect input from the Class I ra ilroads. The weighted emission factors were then applied to the yard-specifi c fuel consumption to obtain emissions for each yard. Since the rail yard inventory was based on publically-available data, the final criteria emission estimates were provided per rail yard.

### 3-2 3.3 Hazardous Air Pollutant Emissions Estimates

HAP emissions were estimated by applying speciation profiles to the VOC or PM estimates. The speciation profiles were derived from Evaluation of Factors that Affect Diesel Exhaust Toxicity (Truex and Norbeck, 1998), and data provided by OTAQ (Scarbro, 2001 and 2002). It should be noted that si nce California uses low sulfur di esel fuel and emission factors specific for California railroad fuel s were available, calculations of the state’s emissions were done separately from the other states. The HAP speci ation profile used in th is effort is shown in Table 3-1. HAP estimates were calculated at the ya rd and link level, after the criteria emissions

had been allocated.

Table 3-1. Hazardous Air Pollutant Speciat ion Profile for 2008 Lo comotive Emission

Estimation

Pollutant Name California All Other

States Speciation

Base
1,3 Butadiene 0.0000615 0.0047735 PM 10 

### 2-2-4 Trimethylpentane 0.0022425 0.0022425 VOC Acenaphthene 0.0000080 0.0000306 PM 10 

### Acenaphthylene 0.0002182 0.0004275 PM 10 

### Acetaldehyde 0.0004492 0.0276274 PM 10 

### Acrolein 0.0000855 0.0045943 PM 10 

### Anthracene 0.0000535 0.0001009 PM 10 

### Arsenic 0.0000004 0.0000004 PM 10 

### Benzene 0.0000517 0.0038020 PM 10 

### Benzo(a)anthracene 0.0000121 0.0000160 PM 10 

### Benzo(a)pyrene 0.0000044 0.0000027 PM 10 

### Benzo(b)fluoranthene 0.0000044 0.0000064 PM 10 

### Benzo(ghi)perylene 0.0000044 0.0000031 PM 10 

### Benzo(k)fluoranthene 0.0000044 0.0000052 PM 10 

### Beryllium 0.0000280 0.0000280 PM 10 

### Cadium 0.0000280 0.0000280 PM 10 

### Chromium (III) 0.0000001 0.0000040 PM 10 

### Chromium (VI) 0.0000000 0.0000021 PM 10 

### Chrysene 0.0000092 0.0000119 PM 10 

### Dibenz(a,h)anthracene 0.0000000 0.0000000 PM 10 

### Ethylbenzene 0.0020000 0.0020000 VOC

Fluoranthene 0.0000601 0.0000746 PM 10 

### Fluorene 0.0000619 0.0001407 PM 10 

### Formaldehyde 0.0009451 0.0636582 PM 10 

### Indeno(1,2,3-cd)pyrene 0.0000033 0.0000027 PM 10 

### Lead 0.0000840 0.0000840 PM 10 

### Manganese 0.0000020 0.0000020 PM 10 

### Mercury 0.0000280 0.0000280 PM 10 

### Napthalene 0.0018505 0.0025756 PM 10 

### n-Hexane 0.0055000 0.0055000 VOC

### 3-3 Table 3-1. Hazardous Air Pollutant Speciat ion Profile for 2008 Lo comotive Emission Estimation (Cont.)

Pollutant Name California All Other

States Speciation

Base

Nickel 0.0000066 0.0000066 PM 10 

### Phenanthrene 0.0002822 0.0005671 PM 10 

### Propionaldehyde 0.0061000 0.0061000 VOC Pyrene 0.0000771 0.0001054 PM 10 

### Styrene 0.0021000 0.0021000 VOC

Toluene 0.0032000 0.0032000 VOC Xylene 0.0048000 0.0048000 VOC

### 4-1 

## 4.0 HOW WERE COUNTY LINE H AUL EMISSIONS REALLOCATED

TO INDIVIDUAL RAIL SEGMENTS?

4.1 Class I Line Haul Emissions Allocation

Class I line haul emissions were allocated to rail segments based on segment-specific railroad traffic data (ton mile s) obtained from the Department of Transportation (BTS, 2009). This dataset categorizes the segments’ level of activity into ranges of MGTM and is populated by FRA. Emissions were divided between all main line segments using these activity ranges as a proxy to allocate more emissions to segments with higher activity.

Since the activity data were provided as ra nges, a single “allocation value”, typically the midpoint of the range, was selected for use in the emissions allocation. The exception to this was the “0” activity category, which by definitio n had “unknown” activity. As a result, most mainline segments with the “0” activity cat egory were not included in the emissions calculation/allocation. However, there was a sma ll subset of segments that did have known activity values in the confidential data set but were labe led as “unknown” in the publically available data set. Those segment IDs were provided by ERTAC Rail for inclusion in the emission allocation; however, the activity of thes e segments was averaged to protect confidential data. Table 4-1 lists the activity categories along with their ranges in MGTM/mi and the allocation value used in the emissions spatial allocation.

Table 4-1. Line Haul Segment Activity (MGTM/Mi) Categories

Category Range

Minimum Range

Maximum Allocation

Value Used

0* 0.0003 0.09 0.01233

1 0.1 4.9 2.5

2 5 9.9 7.45

3 10 19.9 14.95

4 20 39.9 29.95

5 40 59.9 49.95

6 60 99.9 79.95

7 100 1000000 100

* The “0” category has “unknown” activity in the publically available segment data. As a result, this table lists the minimum, maximum, and average of the confidential activity data greater than zero that were categorized as “unknown” in the public data.



### The county emission sums were reallocated to the segments by multiplying the county emissions by the segment’s allocation value divide d by the sum of the allocation values for all links within the county.

### 4-2 

# ∑

= 

### ∗ = N

C LC L

iC iL 

### A A E E

1



### Where:

E iL 

### = Emissions of pollutant i per link L (tons/year).

E iC 

### = Emissions of pollutant i per county C (tons/year).

A L 

### = Allocation value for link L per activity category from public BTS dataset

A LC 

### = Sum of allocation values for all li nks in county C from public BTS dataset

Note that rail line data for Puerto Rico, U.S. Virgin Islands, and Hawaii data were not included in ERTAC Rail’s shapefile and were developed separately; however, since these areas have exclusively Class II/III railroads presen t, these efforts are discussed in the following

section.

4.2 Class II/III Line Haul Emissions Allocation

ERTAC Rail created a shapefile of Class II/III mainline rail segments from their FRAprovided proprietary shapefile as described in Appendix B fo r the contiguous 48 states and

Alaska. Raw rail line data for Puerto Rico were obtained from USGS (Scanlon and Briere, 2000), and rail line data for Hawaii was obtained fr om ESRI’s Digital Chart of the World (ESRI 2010). The U.S. Virgin Islands have no rail lines. Because Class II/III rail roads are less likely to use rail segments that are heavily traveled by Cl ass I railroads, the activity-based approach used for Class I lines was not appropriate . Instead, Class II/III line ha ul emissions were allocated to rail segments using segment length as a proxy.

The county emission sums were reallocated to the segments by multiplying the county emissions by the segment’s length divided by the sum of the length for all links within the

county.



# ∑

= 

### ∗ = N

C LC L

iC iL 

### l l E E

1



### Where:

E iL 

### = Emissions of pollutant i per link L (tons/year).

E iC 

### = Emissions of pollutant i per county C (tons/year).

l L



### = Allocation value for link L per activity category from public BTS dataset

l LC



### = Sum of allocation values for all li nks in county C from public BTS dataset

Since ERTAC Rail used proprietary data to develop the shapefile, some segment IDs

were not found in the EIS data set. These segments were manually identified, and their emissions were allocated to the nearest segment within the EIS data set.

### 4-3 4.3 Rail Yard Emissions Allocation

Rail yard emissions were deve loped based on yard name and ownership properties. As a result, unique yards needed to be identified and emissions summed. Unfortunately, the yard data lacked detail necessary for confident duplicate checks and yard matching such as address, detailed yard name, etc. As a result, a GIS wa s used to find the centroid of the yards based on the latest public BTS rail network, using the yard name and FIPS. The list of unique yards was further examined against ERTAC’s data and wi thin Google Earth to identify any yards that required further revision. A crosswalk of origin al ERTAC data to new, consolidated yard IDs facilitated the summing of activit y and emissions. 753 unique yards were identified nationwide. This underestimate of the total number of yards is most likely due to using line-haul-focused data to identify locations and develop rail yard emissions.

Once the unique yards were identified and crit eria emissions were summed at the yard, the PM and VOC-based HAP speciation profile was applied to estimate HAP emissions at each yard.

4.4 State Provided Data

In this version of NEI, stat e and local agencies were inv ited to provide locomotive data that replaced the estimates based on national fuel consumption. However, only a small rail yard dataset was received from Kentucky. Their rail yard list was compared with the ERTAC/ERG yard list, and 2 yards were found in both sets. These yards were merged so as to avoid duplication in activity or emissions.

4.5 What are the Results?

Table 3 summarizes the 2008 locomotive mobile source emission estimates.

Table 3. 2008 Locomotive Emissions Data

2008 Locomotive Criteria Emissions

Pollutant Name Class I

Line Haul Class II/III

Line Haul Rail Yard TOTAL

CO 110,969 5,055 9,152 125,176

NH 3 

### 347 16 27 390

NO X 

### 754,433 51,342 73,741 879,516

PM 10 

### -PRI 25,477 1,264 2,086 28,827

PM 25 

### -PRI 23,439 1,163 2,024 26,626

SO 2 

### 7,836 357 619 8,811

VOC 37,941 1,896 4,824 44,661

2008 Locomotive Hazardous Air Pollutant Emissions

Pollutant Name Class I Line

Haul Class II/III

Line Haul Rail Yard TOTAL

1,3 Butadiene 116.7941 5.7969 9.3296 131.9206
2-2-4 Trimethylpentane 85.0832 4.2511 10.8178 100.1521 Acenaphthene 0.7569 0.0376 0.0609 0.8554

### 4-4 Table 3. 2008 Locomotive Emissions Data (Cont.)

2008 Locomotive Hazardous Air Pollutant Emissions

Pollutant Name Class I Line

Haul Class II/III

Line Haul Rail Yard TOTAL

Acenaphthylene 10.6772 0.5298 0.8639 12.0709 Acetaldehyde 676.0572 33.5552 54.0089 763.6213

Acrolein 112.4351 5.5806 8.9828 126.9985

Anthracene 2.5231 0.1252 0.2042 2.8525

Arsenic 0.0091 0.0005 0.0007 0.0103

Benzene 93.0272 4.6173 7.4312 105.0757
Benzo(a)anthracene 0.40 47 0.0201 0.0329 0.4577

Benzo(a)pyrene 0.0717 0.0036 0.0059 0.0812

Benzo(b)fluoranthene 0.1607 0.0079 0.0131 0.1817

Benzo(ghi)perylene 0.0798 0.0040 0.0066 0.0904
Benzo(k)fluoranthene 0.1312 0.0065 0.0107 0.1484 Beryllium 0.7138 0.03 54 0.0584 0.8076

Cadium 0.7138 0.0354 0.0584 0.8076

Chromium (III) 0.0985 0.0049 0.0079 0.1113
Chromium (VI) 0.0508 0.0025 0.0041 0.0574 Chrysene 0.2998 0.0149 0.0244 0.3391 Ethylbenzene 75.8814 3.7914 9.6479 89.3207

Fluoranthene 1.8868 0.0936 0.1538 2.1342

Fluorene 3.5039 0.1739 0.2830 3.9608

Formaldehyde 1,557.66 77.3124 124.4335 1759.4059 Indeno(1,2,3-cd)pyrene 0.0684 0.0034 0.0056 0.0774

Lead 2.1413 0.1062 0.1753 2.4228 Manganese 0.0520 0.0026 0.0043 0.0589

Mercury 0.7138 0.0354 0.0584 0.8076

Napthalene 64.8766 3.2187 5.2765 73.3718

n-Hexane 208.6739 10.4263 26.5317 245.6319

Nickel 0.1669 0.00983 0.0137 0.19043

Phenanthrene 14.1555 0.7024 1.1450 16.0029

Propionaldehyde 231.4383 11.5637 29.4261 272.4281

Pyrene 2.6566 0.1318 0.2161 3.0045

Styrene 79.6755 3.9809 10.1303 93.7867

Toluene 121.4103 6.0662 15.4366 142.9131

Xylene 182.1154 9.0993 23.1549 214.3696

### 5-1 

## 5.0 REFERENCES

Bureau of Transportation Statistics, 2009. Na tional Transportation Atlas Databases - National Rail Network 1:2,000,000. Washington, DC, Publisher: Bureau of Transportation Statistics.

Energy Information Administration Form EI A-821, “Annual Fuel Oil and Kerosene Sales Report” for 1999. Table 23: Adjust ed Sales for Transportation Use: Distillate Fuel Oil Residual Fuel Oil, 1999, U.S.

ESRI, Digital Chart of the Wo rld Hawaii Rail line dataset http://data.geocomm.com/catalog/US/61094/group103.html July 27, 2010

Fritz, Steve, Diesel Fuel Effects on Locomotive Exhaust Emissions , California Air Resource Board. SwRI 08.02062, October 2000.

Porter, Fred L., U.S. Environmental Protection Agency, Emission Standards Division. Note to Anne Pope, U.S. EPA/Emissions, Monitoring an d Analysis Division. Comments on combustion

source information in the Baseline Emission Inventory of HAP Emissions from MACT Sources - Interim final Report (September, 18, 1998. November 13, 1998)

Scanlon, Kathryn and Peter R. Briere, U.S. Ge ological Survey Open-File Report 00-006. Puerto Rico Marine Sediments, Terrestrial and Seaf loor Imagery, and Tectonic Interpretations, 2000. http://pubs.usgs.gov/of/2000/of00-006/htm/index.htm

Scarbro, Carl, E-mail entitled A Few Questions on the Rail Emissions

- Reply , to Richard Billings, and Roger Chang, Eastern Research Group, Inc., United States Environmental Protection Agency Office of Trans port and Air Quality. July 19, 2001

Scarbro, Carl, E-mail entitled Chromium in Loco’s

- Reply , to Richard Billings , Eastern Research Group, Inc., United States Environmental Protec tion Agency Office of Transport and Air Quality. June 1, 2001

Scarbro, Carl, E-mail entitled Better Railroad Numbers This Wi ll Disaggregate Class I Work , to Roger Chang, Eastern Research Group, Inc., Unit ed States Environmental Protection Agency Office of Transport and Air Quality. May 8, 2001

Scarbro, Carl, E-mail entitled CMV SO

x 

### corrections - Reply , to Richard Billings, Eastern Research Group, Inc., United States Environmenta l Protection Agency Office of Transport and Air Quality. May 28, 2002

Scarbro, Carl, E-mail entitled 2, 2, 4-trimethylpentane , to Richard Billings, Eastern Research Group, Inc., United States Environmental Protec tion Agency Office of Transport and Air Quality. June 1, 2001

Scarbro, Carl, E-mail entitled 2, 2, 4-trimethylpentane , to Roger Chang, Eastern Research Group, Inc., United States Environmental Protection Ag ency Office of Transport and Air Quality. March 26, 2002

### 5-2 Truex, Timothy J. and Joseph M. Norbeck. Evaluation of Factors that Affect Diesel Exhaust Toxicity . University of California-Riverside, Center for Environmental Research and Technology. Riverside, CA. March 16, 1998.

U.S. Environmental Protection Agency Form APR420-F-97-051, Emission Factors for

Locomotives , for 1996 Table 9: Fleet Average Emission Factors for All Locomotives (Projected 1999), December 1997

U.S. Environmental Protection Agency, Locomotive Emission Standards Regulatory Support

Document , page 109 April 1998.

U.S. Environmental Protection Agency, Procedures for Emission Inve ntory Preparation, Volume

IV: Mobile Sources. 1992.

U.S. Environmental Protection Agency. Procedures for Emission Inventory Preparation,

Volume IV: Mobile Sources . Office of Air Quality Planning and Standards. Research Triangle Park, NC. 1989.

## Appendix A

ERTAC Class I Line Haul Documentation

### A-1 

# DRAFT

ERTAC Rail Emissions Inventory

Part 1: Class I Line-Haul Locomotives

Michelle Bergin, GA Environm ental Protection Division

Matthew Harrell, IL Environmental Protection Agency Mark Janssen, Lake Michigan Air Directors Consortium

Acknowledgments: Robert Fronczak, Associati on of American Railroads Raquel Wright, Federal Railroad Administration Julie McDill, Mid-Atlantic Regi onal Air Management Association Patrick Davis, Mid-Atlantic Regi onal Air Management Association Laurel Driver, US EPA, Office of Air Quality Planning and Support Byeong Kim, GA Environmen tal Protection Division

Introduction

Air protection agencies from twenty-seven st ates, coordinated thr ough the Eastern Regional Technical Advisory Committee (ERTAC) and headed by the Lake Michigan Air Directors Consortium (LADCO), identified a n eed to better quantify and char acterize rail-related emissions inventories. Traditional locomotives largely ut ilize diesel engines, resu lting in emissions of

NO

x 

### , diesel PM, hydrocarbons, greenhouse gases, a nd other pollutants. These emissions are sometimes concentrated in areas exceeding Na tional Ambient Air Quality Standards. No

cohesive nationwide railroad emission estimat es based on local operations are known to have been made previously. Inventory development methods for locomotive emissions estimates vary from state to state and, in general, lack the spa tial or temporal resoluti on needed to support air quality modeling and planning 1-5



### .

The ERTAC Rail Subcommittee (ERTAC Rail) was es tablished with active representatives from twelve member states, thr ee regional planning offices, and the US EPA. The subcommittee’s goals are to (1) standardize agencies’ invent ory development methods through a collaborative effort, (2) improve the quality of data received and the resulting emission inventories, and (3)

reduce the administrative burden on railro ad companies of providing data.

With support from the Rail industry and assi stance from the ERTAC Rail Data Workgroup (Appendix A), ERTAC Rail has deve loped 3 inventories of locomotive emissions (Table 1); from Class I line-haul, Shortline and Regional Railr oads (Class II and III operations), and Class I railyard switchers. Because of the difficulty in ob taining data and differences in states’ needs for inventory years, sources from both 2007 and 2008 were utilized (Appendix B.) Due to the variability and uncertainty in much of the data, the results are considered applicable for either

2007 or 2008.

### A-2 The Surface Transportation Board (STB) define s Class I Railroads as having had minimum carrier operating revenues of $401.4 million (USD ) in 2008. There are 8 Class I Railroads operating in the United States (Table 2), about 12 Regional Railroads (Class II), and approximately 530 Class III Railroads (Shortlines). While categorized as a Class I Railroad,

Amtrak was excluded from these inventories beca use of significant differences in equipment and operation characteristics. Line-h aul locomotives travel long distances (e.g. between cities) while switcher locomotives largely operate in railyards , splitting and joining rail cars with varying destinations. Passenger and Commuter Rail (inc luding Amtrak), industrial locomotives, and associated non-locomotive equipment are not included in thes e inventories.

This paper documents the data sources and met hodologies used for calculating the Class I linehaul emissions inventory. Class I line-haul ac tivities are the largest source of rail-related emissions, with estimates of Class I line-haul fuel consumption totals to be from 74 to 84% of all

rail sources combined 4, 5 

### . For this reason, characterizing Clas s I line-haul emissions were a focal point of ERTAC Rail’s inventory development e fforts. Information on ERTAC Rail, Railroad participation, the Rail industry, and effects of rail on air quality ar e available elsewhere 6



### .

Table 1. Summary of ERTAC Rail Inventories: U.S. Locomotive Emissions and Fuel Use

for either 2007 or 2008*.

Fuel Use** (gal/yr) Emissions (tons/yr)

NO

x 

### PM 2.5 

### HC SO 2 

### CO NH 3

### Class I*** linehaul 3,770,914,002 754,443 23,439 37,941 7,836 110,969 347

Class I switcher 300,492,223 73,741 2,024 4,824 619 9,152 27
Class II and III 157,800,000 51,367 1,163 1,897 357 5,058 16 *See Appendix B for a description of the year and source of data utilized for each inventory. **Locomotive grade diesel ***Excluding Amtrak and incl uding work train fuel use

Table 2. Class I Railroads, Reported Locomotive Fuel Use, and Railroad Fuel Consumption Index (RFCI) 7



### .

Class I Railroads* R-1 Reported Locomotive Fuel Use (gal/yr) RFCI (ton-miles/gal) Line-Haul (2007)** Switcher (2008)
BNSF 1,393,874,954 52,497,057 883.14
Canadian National 93,830,751 12,290,022 1190.79
Canadian Pacific*** 50,320,233 4,594,067 1096.28
CSX 514,687,186 53,717,674 963.81 Kansas City Southern 69,787,071 1,816,759 785.89
Norfolk Southern 463,267,278 32,317,375 865.75
Union Pacific 1,185,146,529 143,470,336 974.64 Total 3,770,914,002 300,492,223 929.47

### A-3 * Excluding Amtrak

** Includes work trains

*** CP’s line-haul fuel use valu es include 2008 data (rather than 2007) for their Delaware and Hudson subsidiary.

Method

Earlier efforts to characterize line-haul railroa d emissions relied on hi ghly aggregated activity data (Figure 1), and generally apportioned annual system-wide fuel use equally across all route miles of track operated by a Class I railroad. Howe ver, the majority of freight tonnage carried by Class I railroads is concentrated on a dispropo rtionately small number of route miles. In addition, emissions calculations were previously based on an estimate of annual nationwideaverage locomotive fleet mix to creat e one set of emissions factors.

For this inventory, the Class I Railroads a llowed ERTAC Rail access under a confidentiality agreement to a link-level (single lengths of track) line-haul GIS layer activity dataset managed by the Federal Railroad Administration 9 

### . Each railroad also provide d fleet mix information that allowed ERTAC Rail to calculate weighted emi ssion factors based on the fraction of their linehaul fleet meeting each Tier leve l category. The use of this data, largely following a line-haul inventory methodology recomm ended by Sierra Research 2, 3 

### , resulted in a link-level line-haul locomotive emission inventory using railroad-speci fic emission factors. This segment-level inventory is nationwide, aggregat ed to state and county level file s, and will be released as gridded emissions files for use in photochemical and dispersion modeling. Link-level emissions may be provided for special study requests pending approval of any Class I railroads operating in the study domain. The calculations are describe d below as a two-part process, calculating railroad-specific factors and emissions per rail link.

Figure 1. US Railroad Traffic Density in 2006. 8 

### MGT is million gross tons.

### A-4 1. Calculate Railroad-Specific Factors.

The EPA provides annual default Emission Fact ors for locomotives based on characteristic operating cycles (‘duty cycles’) and the estimated nationwide fleet mixes for both switcher and line-haul locomotives. However, fl eet mixes vary from railroad to ra ilroad and, as can be seen in Figure 2, Class I railroad activity is highly regionalized in nature and subject to issues of local terrain such as operation on plai ns vs. mountainous areas, which can have a significant impact on fuel consumption and emissions.

Figure 2. Class I Railroad Terri tories in the United States 10



### .

As an alternative approach to using a single nationwide set of emission factors, ERTAC Rail requested each Class I company to provide a de scription of their line-haul fleet mix based on Tier rating, which each company provided under a conf identiality agreement. An engine’s Tier level is based on the year the engine was built an d determines allowable emission limits (Table 3).

### A-5 Table 3. EPA line-haul locomoti ve Emission Factors by Tier, 1997 standards (grams/gal).

Note that the new standards released in 2008 did not apply to fleets in the year 2008. 11



### PM 10 

### HC NO

x 

### CO Uncontrolled (pre-1973) 6.656 9.984 270.4 26.624 Tier 0 (1973-2001) 6.656 9.984 178.88 26.624 Tier 1 (2002-2004) 6.656 9.776 139.36 26.624 Tier 2 (2005 + ) 3.744 5.408 102.96 26.624

Based on values in EPA Technical Highlights: Emission Factors for Locomotives, EPA Office of Transportation and Air Quality, EPA-420-F-09-025, April 2009.



### Weighted Emission Factors (EF) pe r pollutant for each gallon of fu el used (gm/gal or lbs/gal)

were calculated for each Class I railroad fleet ba sed on its fraction of line-haul locomotives at each regulated Tier level (Eqn 1; Table 3).



# ∑

= 

### = 4

1 

### ) * (

T TRR iT iRR 

### f EF EF 

### Equation 1

EF iRR 

### = Weighted Emission Factor for polluta nt i for Class I railroad RR (gm/gal).

EF iT



### = Emission Factor for pollutant i for loco motives in Tier T (gm/gal) (Table 3).

There were 4 Tiers of loco motives in the 2008 fleets. f

TRR 

### = Fraction of railroad RR fleet in Tier T.

While engine emissions are variab le within Tier categories, this approach likely provides better regional estimates than uniform ly applying the nationwide aver age emission factors. This approach likely provides conser vative emission estimates as locomotive engines are certified to

meet or exceed the emissions standard for each Tier, although emission levels may increase after

certification.

Other emission factors are not engine specific. For locomotives, PM 2.5 

### is assumed to be 97% of

PM 10 11 

### , and emission factors applied for SO 2 

### and NH 3 

### are 1.88 g/gal 11 

### and 83.3 mg/gal 12


### respectively. Greenhouse gases are estimated using emission factors shown in Table 4.

Table 4. EPA greenhouse gas emission factors for locomotive diesel fuel (grams/gal). 13



### CO 2 

### N 2 

### O CH 4 

### Locomotive diesel 1.015E4 0.26 0.80

A Railroad Fuel Consumption Index (RFCI) was al so calculated for each Class I railroad using their system-wide line-haul fuel consumption (F C) and gross ton-mile (GTM) data reported in their annual R-1 reports submitted to the Surface Transportation Board 7 

### (Eqn 2). This value represents the average number of GTM produced pe r gallon of diesel fuel used over their system in a year, and varies between railroad carrier s depending on factors such as fleet mix, system

### A-6 terrain, speeds, loading/weight of cargo, train type (e.g., intermodal, unit, and manifest), and operating practices. (Table 2).

RR

RR

RR 

### FC GTM RFCI = 

### Equation 2

RFCI RR 

### = Railroad Fuel Consumption Index (gro ss ton-miles/gal) per Class I railroad (RR). GTM RR 

### = Gross Ton-Miles (GTM), annual syst em-wide gross ton miles of freight transported per RR. (R-1 Report Schedule 755, Line 104)

FC RR 

### = Annual system-wide fuel consumpti on by line-haul and work trains per RR (gal) (R-1 Report Schedule 750, Lines 1 and 6).

2. Calculate Emissions per Link.

Emissions of pollutant i per link L ( E iL 

### ) are then calculated by multiplying the gallons of diesel fuel consumed by each Class I railroad on the li nk by that railroad’s weighted Emission Factor for the pollutant, and summed over all railroads operating on the li nk (Eqn 3). This approach splits the activity on each link (rep resented by MGT) evenly betw een all railroads operating on the link. Note that the weighted Emission F actors are converted to tons/gal for these calculations, and that variables with units in t ons may represent tons of freight hauled (MGT, RFCI) or tons of pollutants (EF, E).



# ∑

= 

### ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

= N

RR iRR

RR L L

iL 

### EF RFCI l

N MGT

E

1 6



### * * 10 *

Equation 3

E iL 

### = Emissions of pollutant i per link L (tons/year).

N

= Number of Class I ra ilroads operating on link L.

MGT L



### = Millions of Gross Tons hauled per link per year from the FRA database (10 6 

### tons/yr) 9



### . l L



### = Link length from the FRA database (miles).

EF iRR 

### = Weighted Emission Factor for pollutant i per railroad RR (Eqn 1; tons/gal).

RFCI RR 

### = Railroad Fuel Consumption Inde x per railroad RR (Eqn 2; gross ton-miles/gal).

Note that approximately 36% of Cl ass I route miles in the United States are shared by more than one Class I carrier, a fraction that drops to 26% when neglecting track only shared between one Class I freight railroad and Amtr ak. Accurately apportioning the specific fractions of tonnage (MGT) per carrier per link was considered, but after comparing likely worst-case areas, the difficultly of merging carrier-specific MGT with the aggregated FRA MGT dataset was considered too great consideri ng the potential gain in accuracy. Where warranted, MGT data may be apportioned more accurately in the future.

### A-7 Limitations, Conclusions, and Future Work



### Rail-related emissions can be important compone nts of emissions inventories used to support effective air quality management pr actices, at local, state, regional, and national levels. This linehaul inventory, as well as the companion Class I railyard invent ory and Class II/III inventory, greatly improve our estimates of rail-related emissions. However, a systematic study of variability and uncertainty in line-haul locomotive emissions and activity, by fleets, locations, and through time, would give valuable informa tion for identifying how to best improve this inventory as well provide an i ndication of how representative the inventory may be. An uncertainty study on the data used for this inventory, including th e R-1 reported fuel use and the confidential link-level tonnage data, would also help in evaluating th e quality of this inventory.

Localized studies should also examine how sh ared tracks are apportioned between multiple

carriers.

Early ERTAC Rail discussions conc luded that link-level tonnage was the most important data to obtain, while other variables such as track grade and track speed could not be addressed at this time. ERTAC Rail calculated railroad-specific fleet-averaged emission factors rather than applying the estimated national average; however, it is recognized that em issions from individual engines are highly variable even within Tier categories depend ing on variables such as the specific locomotive model, operation cycle, and conditions of operation. Future evaluation of emission variability within Tiers and between cert ain types of operation and locations would also

be valuable.

Emissions inventory preparation guidance from the U.S. EPA describes locomotive activity as relatively constant thro ughout the year (e.g. no daily, weekly , or seasonal variability); however, actual activity levels do vary s easonally and annual averagin g may dilute or exaggerate concentrations during pollution episodes. ERTA C Rail and the Class I railroad community had some discussions addressing if incorporating more specific fl eet mix or monthly or seasonal variation may be worthwhile, and these t opics should be looked into further.

Finally, it is important to reiterate that the link-level MGT data maintained by the FRA is proprietary and can only be released to agen cies/groups outside the FRA with the express permission of each Class I railroad. It is possi ble that one or more Class I railroads could withhold permission for access, but data for specia lized studies may be provided if requested. This database can also be improved by better dis tinguishing between haulag e and trackage rights, and by apportioning tonnage hauled on links to specific carriers.

We would like to thank the Class I Railroads a nd their representatives for their assistance and support in the developmen t of this inventory.

References



### 1. Eastern Research Group (ERG) for E.H. Pechan & Associates, Inc., “Documentation for Aircraft, Commercial Marine Vessel, Loco motive, and Other Nonroad Components of the National Emissions Inventory, Volume I – Methodology”; EPA Contract No.: 68-D02-063. Prepared for the US EPA Emissions, Monitoring and Analys is Division, Sept.

### A-8 30, 2005. ftp://ftp.epa.gov/EmisInventory/2002final nei/documentation/mobile/2002nei_mobile_no nroad_methods.pdf . Related documents at ftp://ftp.epa.gov/EmisInventory/2002final nei/documentation/mobile/2002nei_mobile_no nroad_train.pdf

2. Sierra Research, Inc., “Revised Inventor y Guidance For Locomotive Emissions”; Report No. SR2004-06-01. Prepared for Southeas tern States Air Resource Managers (SESARM), June 2004. http://www.metro4-se sarm.org/pubs/railroad/FinalGuidance.pdf

3. Sierra Research, Inc., “Research Project: Development of Railroad Emission Inventory Methodologies”; Report No. SR 2004-06-02. Prepared for Southeastern States Air Resource Managers (SESARM), June 2004. http://www.metro4- sesarm.org/pubs/railroad/ FinalMethodologies.pdf

4. Environ, “Draft LADCO 2005 Locomotive Emissi ons”. Prepared for Lake Michigan Air Director Consortium, Feb 2007. http://www.ladco.org/reports/technical_ support_document/references/ladco_2005_locom otive_emissions.021406.pdf

5. Southern Research Institute, “NYSERDA Clean Diesel Technol ogy: Non-Road Field Demonstration Program, Development of the 2002 Locomotive Survey for New York State”; Agreement Number 8958. Prepared for the New York State En ergy Research And Development Authority ( NYSERDA), Feb. 09, 2007. http://www.nyserda.org/pub lications/LocomotiveSurve yReportwithAppendices.pdf

6. M. Bergin; M. Harrell; J. McD ill; M. Janssen; L. Driver; R. Fronczak; R. Nath,; and D. Seep. "ERTAC Rail: A Collaborative Effort in Building a Railroad-Related Emissions Inventory Between Eastern States Air Protect ion Agencies and Participation with the Railroad Industry," 18th Annual International Emissi on Inventory Conference. Baltimore, MD. April 14 - 17, 2009. Pa per and presentation available at: http://www.epa.gov/ttn/chief/c onference/ei18/session6/bergin.pdf

7. Surface Transportation Board R-1 Reports, available at: http://www.stb.dot.gov/stb /industry/econ_reports.html

.
8. US DOT Bureau of Transportation Statis tics’ 2008 National Transportation Atlas

Database.

9. Confidential database was provided with assi stance from Raquel Wright of the Federal Railroad Administration. Similar public data providing ranges of tonnage hauled rather than link-level tonnage is available from the Bureau of Transportation Statistics in the NTAD 2009 shapefile data (data is representative for the year 2007): http://www.bts.gov/publications/nationa l_transportation_a tlas_database/2009

.
10. Freight Railroads in the Un ited States 2008. Association of American Railroads.

Available at: http://www.aar.org/~/media /AAR/InCongress_RailroadsSt ates/2008unitedstates.ashx

.

11. EPA Technical Highlights: Emission Factors for Locomotives, EPA Office of Transportation and Air Quality , EPA-420-F-09-025, April 2009. http://www.epa.gov/otaq/regs/nonroad/locomotv/420f09025.pdf

### A-9 12. Estimating Ammonia Emissions From Anthr opogenic Nonagricultural Sources - Draft Final Report by E.H. Pechan & Assoc. Ap ril 2004. Prepared for EPA/STAPPAALAPCO Emission Inventory Improveme nt Program. Supported by personal communication (5/6/2010) with Craig Harvey, US EPA, OTAQ, and Robert Wooten, NC

DENR. http://www.epa.gov/ttnchie1/ eiip/techreport/volume0 3/eiip_areasourcesnh3.pdf

13. U.S. Environmental Protection Agency. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005, EPA 430-R-07-002, Annex 3.2, (April 2007), web site: http://www.epa.gov/climatechange/emissions/usinventoryreport.html

.



### Appendix A: ERTAC Rail Data Workgroup

REPRESENTATIVE ORGANIZATION



### Matt Harrell IL EPA Michelle Bergin (Co-Ch air) and Byeong Kim GA EPD Mark Janssen (Co-Chair) LADCO

Julie McDill and Patrick Davis MARAMA Laurel Driver US EPA OAQPS

Robert Fronczak AAR

Steven Sullivan ASLRRA

Rick Nath CSX David Seep and Lyle Staley BNSF Ken Roberge CPR

Carl Akins and Peter Conlon KCS

Erika Akkerman CN

M. John Germer UP

Brent Mason and Richard Russell NS

Joanne Maxwell Amtrak

### A-10 Appendix B: Source and Year of Data Utilized for Each Inventory

Data Year Source

Class I Line-Haul



### Annual Line-Haul Fuel Use

and Gross Ton-Miles 2007 STB R-1 Reports (CP data for D&H is for 2008.)

Line-haul fleet mix for

emission factors 2008 Each Class I railroad

Link-level tonnage 2007 FRA confidential database

Class I Railyards (Switcher Locomotives)



### Annual Switcher Fuel Use 2008 R-1 Reports

Switcher fleet mix for

emission factors 2008 Each Class I railroad

Link-level tonnage or Density Code (for activity estimate) 2007 FRA confidential database

Class II and III Locomotives



### Annual Total Fuel Use 2008 ASLRRA Annual Report (2008)

Track length and railroad 2008 ASLRRA Annual Report (2008)

Estimated fleet mix for

emission factors Discussions with ASLRRA and Class II and III representatives.

## Appendix B

ERTAC Class II/III Line Haul Documentation

### B-1 

# DRAFT

ERTAC – Class 2/3 Shapefile Documentation

13 Jul 2009

Introduction



### This document outlines the methods and procedures used to compile a shapefile representing the links in the FRA 1:100,000 railro ad dataset that are owned or operated by Class II and III railroad companies. It is important to note that there is a consider able amount of overlap

between the Class II’s and III’s and the Class I a nd passenger railroads. Class II’s and III’s can operate on Class I or passenger rail links a nd vice versa. Although the final shapefile specifically represents Class II and III links , there are many Class I and passenger railroads represented as well.

Procedure



### 1. Started with all proprietary FRA links where “NET = ‘M’ and “STCNTYFIPS” <> ‘ ‘
(this definition query selects all active mainline links located within the United

States).

2. Ran 12 queries, one for each ownership and trac kage rights field, to select all links
not associated with a Class I freight rail road or Amtrak and not containing a null
value (e.g., "RROWNER1" <> 'AMTK' AND "RROWNER1" <> 'BNSF' AND

"RROWNER1" <> 'CN' AND "RROWNER1" <> 'CPRS' AND "RROWNER1" <>

'CSXT' AND "RROWNER1" <> 'KCS ' AND "RROWNER1" <> 'NS' AND

"RROWNER1" <> 'UP' AND "RROWNER1" <> ' '). The first query was setup as a
new selection. Each of the 11 subsequent que ries were setup to add records to initial

set of records. 26,261 links were sel ected and exported to a new shapefile.

3. Due to the multitude of railroad codes us ed to represent commuter rail operations
across the country, additional processing was re quired to remove any links that were
not operated by a Class II or III freight railr oad. Each commuter railroad was queried
out of the new shapefile and the links analy zed to eliminate all links where no Class II
or III operations were occurring. Th e following commuter rail operations were
evaluated: NJT (New Jersey Transit), MN CW (Metro-North Commuter Railroad), LI
(Long Island Railroad), CDOT (Connecticut DOT), MBTA (Massachusetts Bay
Transportation Authority), SEPA (Sout heastern Pennsylvania Transportation
Authority), MARC (Maryla nd Area Rail Commuter), VRE (Virginia Railway
Express), MTRA (Northeastern Illinois Regional Commuter Railroad), CSS
(Northern Indiana Commuter Transportation District), DART (Dallas Area Rapid
Transit), SCRA (Southern California Regiona l Rail Authority – including also SCAX,
LACM, LAPT, and LATC), TCRA (Sout h Florida Regional Transportation
Authority), PJPB (Caltrain), and AC E (Altamont Commuter Express).

### B-2 Approximately 1581 links were identified with no Class II or III operations and were
deleted from the Class 2/3 shapefile.

4. The remaining Class II and III links were then compared to the regional maps
contained in the July-August issue of The Official Railway Guide to assess the
completeness of the Class 2/3 shapefile. Six specific edits were made to the shapefile
to correct the most glaring errors: 1) BMLP links deleted (Black Mesa & Lake
Powell, an electric coal hauling railway in Arizona); 2) DSNG links deleted (Durango

& Silverton steam tourist railroad in Colo rado; 3) CIC haulage rights links on CN
from Chicago to Omaha deleted; 4) DMIR links deleted (Duluth, Missabe & Iron
Range, now owned and operated by CN in Minnesota; 5) EVWR’s ex-CSXT links

coded from Evansville, IN to Okawville, IL (Evansville Western Railroad); 6) INRD

ex-CP links coded from Ch icago, IL to Louisville , IN (Indiana Rail Road).

5. During the course of reviewing the FRA dataset, 555 “active” links were found to
have no ownership or trackage rights codes. 1005 links have no codes listed in the 3
ownership fields. In most cases these li nks are very short a nd scattered across the
country. Only the links re presenting the EVWR and INRD spanned large distances
and were fixed. The other problem links we re deemed to be insi gnificant. A listing of
these links will be provided b ack to the FRA to assist with their coding in 1:100K
railway shapefile.

## Appendix C

ERTAC Rail Yard Documentation

### C-1 

# DRAFT

ERTAC Rail Emissions Inventory Part 2: Class I Railyard Switcher Locomotives

Michelle Bergin, GA Environm ental Protection Division

Matthew Harrell, IL Environmental Protection Agency Mark Janssen, Lake Michigan Air Directors Consortium

Acknowledgments: Robert Fronczak, Asso ciation of American Railroads Laurel Driver, US EPA, Office of Air Quality Planning and Support Byeong Kim, GA Environmen tal Protection Division

Introduction



### Air protection agencies from twenty-seven st ates, coordinated thr ough the Eastern Regional Technical Advisory Committee (ERTAC) and headed by the Lake Michigan Air Directors Consortium (LADCO), identified a need to better quantify and characterize rail-related emissions inventories. Traditional locomotives largely ut ilize diesel engines, resulting in emissions of

NO

x 

### , diesel PM, hydrocarbons, gree nhouse gases, and other polluta nts. These emissions are sometimes concentrated in areas exceeding Na tional Ambient Air Quality Standards. No

cohesive nationwide railroad emission estimates are known to have been made previously. Inventory development methods for locomotive emissi ons estimates vary from state to state and, in general, lack the spatial or temporal reso lution needed to support air quality modeling and planning 1-5



### .

The ERTAC Rail Subcommittee (ERTAC Rail) was established with active representatives from twelve member states, thr ee regional planning offices, and the US EPA. The subcommittee’s goals are to (1) standardize agencies’ invent ory development methods through a collaborative effort, (2) improve the quality of data received and th e resulting emission inventories, and (3)

reduce the administrative burden on railroad companies of provi ding data. With support from the Rail industry and assist ance from the ERTAC Rail Data Workgroup (Appendix), ERTAC Rail has developed 3 inventories of locomotive em issions; from Class I line-haul, Shortline and Regional Railroads, and Class I railyard sw itchers, for the year 2008 (Table 1).

The Surface Transportation Board (STB) define s Class I Railroads as having had minimum carrier operating revenues of $401.4 million (U SD) in 2008. There are 8 Class I Railroads operating in the United States (Table 2), about 12 Regional Railroads (Class II), and approximately 530 Class III Railroads (Shortlines). While categorized as a Class I Railroad,

Amtrak was excluded from these inventories beca use of significant differences in equipment and operation characteristics. Line-h aul locomotives travel long distan ces (e.g. between cities) while switcher locomotives largely operate in railyards , splitting and joining rail cars with varying destinations. Passenger and Comm uter Rail (including Amtrak), industrial locomotives, and associated non-locomotive equipment are not included in these inventories.

### C-2 Table 1. Summary of ERTAC Ra il Inventories: U.S. Locomotiv e Emissions and Fuel Use for

either 2007 or 2008*.

Fuel Use** (gal/yr) Emissions (tons/yr)

NO

x 

### PM 2.5 

### HC SO 2 

### CO NH 3

### Class I*** linehaul 3,770,914,002 754,443 23,439 37,941 7,836 110,969 347

Class I switcher 300,492,223 73,741 2,024 4,824 619 9,152 27
Class II and III 157,800,000 51,367 1,163 1,897 357 5,058 16 *See Appendix B for a description of the year an d source of data utilized for each inventory. **Locomotive grade diesel ***Excluding Amtrak and incl uding work train fuel use

Table 2. Class I Railroads and Reported Locomotive Fuel Use 7



### .

Class I Railroads* R-1 Reported Locomotive Fuel Use (gal/yr)

Line-Haul (2007)** Switcher (2008)
BNSF 1,393,874,954 52,497,057
Canadian National 93,830,751 12,290,022
Canadian Pacific*** 50,320,233 4,594,067
CSX 514,687,186 53,717,674 Kansas City Southern 69,787,071 1,816,759
Norfolk Southern 463,267,278 32,317,375
Union Pacific 1,185,146,529 143,470,336 Total 3,770,914,002 300,492,223 

### * Excluding Amtrak

** Includes work trains

*** CP’s line-haul fuel use values in clude 2008 data (rather than 2007) for their Delaware and Hudson subsidiary.

This paper documents the data sources and methodologies used for calculating the Class I switcher (“Railyard”) inventory. Information on ERTAC Rail, Railroad participation, the Rail industry, and effects of rail on ai r quality are available elsewhere 6



### .

Method



### Switcher locomotives are expected to be the single largest source of air emissions in railyards. Therefore, as a starting point for a comprehensive railyard inventory, a Cl ass I switcher emission inventory was developed. It is assumed that estimates for yards of interest, associated equipment and activity, and smaller railroad s could be refined later.

While ERTAC Rail represents states east of the Mississippi River, the railroad companies specified they wanted this effort to result in a consistent nationwide inventory. ERTAC Rail agreed to calculate emissions for all states wh en the data was available and when additional

### C-3 significant effort was not required. Because both the dataset of railyards and switcher fuel use was nationwide in scope, the resulting initial railyard inventory is a nationwide, ‘top-down’ derivation. However, railroad companies may have different levels and quality of data available, and may have interpreted some data requests diffe rently. Also, states are requested to update yards they have detailed information on when possi ble, and a few states (i.e. California) have unique railroad operations and equipment. Therefore, data for some areas will be more accurate than for others, and locally-derived inventories may be more accurate.

This documentation describes development of the initial top-down inventor y, which consisted of

three main activities: 1. Locate Class I Railyards

2. Select/Calculate Emission Factors 3. Estimate Locomotive Activity 4. Improve Estimates

1. Locate Class I Railyards.



### Identification and correct plac ement of railyards was an im portant first step, requiring a comprehensive electronic dataset. A confiden tial database was obtained from the Federal Railroad Administration (FRA) with permission from the Class I Railroads (FRA database). A similar public database compiled by the Bureau of Transportation Statistic s is also available 7



### . Data from this source will not match the confiden tial data exactly, but will be very similar. The FRA database has rail links (track lengths) individually identified as parts of specific railyards. While there may be discrepancie s in how each railroad defined railyard links, this dataset appears to identify most Class I railyards in th e U.S., and shows a high density of yards in the eastern states (Figure 1). The database give s length, up to 3 owners and 3 operators, and a Federal Density Code (explained below) for each railyard link.

Figure 1. Class I Railyards in the Un ited States and estim ates of Annual NOx emissions from switcher locomotives (tons/yr in 2008).

### C-4 2. Select/Calculate Emission Factors.



### The EPA provides annual default emission factors based on charac teristic operating cycles (‘duty cycles’) and the estimated nationwide fleet mix for both switcher and lin e-haul locomotives. However, switcher fleet mix is not uniform from company to company and, as can be seen in Figure 2, Class I railroad activity is highly regional.

As an alternative approach, ERTAC Rail requested each Class I rail company to provide a description of their switcher fleet mix based on Tier rating, which each company provided under a confidentiality agreement. An engine’s Tier determines allowable emission limits based on the year the engine was built (Table 3). While engine emissions are variable within Tier categories, this estimate likely provides a better regional estimate than the nationwide average. The company-specific systemwide fl eet mix was used to calculate weighted average emissions factors for switchers operated by each Class I railroad.

Figure 2. Class I Railroad Territories in the United States.

Table 3. EPA switcher locomotive emission f actors by Tier, 1997 standards (grams/gal).

PM 10 

### HC NO

x 

### CO 

### Uncontrolled (pre-1973) 6.688 15.352 264.48 27.816 Tier 0 (1973-2001) 6.688 15.352 191.52 27.816 Tier 1 (2002-2004) 6.536 15.352 150.48 27.816 Tier 2 (2005 + ) 2.888 7.752 110.96 27.816
Listed years apply to the year the engine was built. Table based on values from 8 . Note that the new standards released in 2008 did not apply to existing fleets in the year 2008.

### C-5 For locomotives, PM 2.5 

### is assumed to be 97% of PM 10 8 

### , and emission factors for SO 2 

### and NH 3 

### are 1.88 g/gal and 83.3 mg/gal re spectively (add cites). Gree nhouse gases are also estimated using emission factors shown in Table 4.

Table 4. EPA greenhouse gas emission factors for locomotive diesel fuel (grams/gal).

CO 2 

### N 2 

### O CH 4 

### Locomotive diesel 1.015E4 0.26 0.80
Source: U.S. Environmental Protection Agency. In ventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005, EPA 430-R-07-002, Annex 3.2, (April 2007), web site: http://www.epa.gov/climatechange/emissions/usinventoryreport.html



### These emission factors are based on a characteristic duty cycl e for switchers which assumes operation over 24-hour per day 365 days per year. An evaluation of the effect of variability in railyards and switching duties on emissions would be useful for future inventories.

3. Estimate Locomotive Activity.



### Class I railroads report total annual switcher locomotive fuel use to the STB, which is reported in publicly available ‘R-1’ reports (Table 2). Ther e may be inconsistencies between railroads in how fuel use is estimated to be apportioned be tween line-haul and switcher locomotive use, and possibly in the total locomotive fuel use, so th ese values may be adjusted in the future. However, the use of these values provides a starting point for estimating total U.S. Class I locomotive-related emissions segregated by Class I carrier. The R-1 report was used by ERTAC

for both the line-haul and switcher locomotive emissions inventories.

The next step for inventory development is to allocate switcher fuel us e to each railyard. Two methods were applied, one that relies on public ly available line-haul activity (the ‘Dencode’ method), and the other using conf idential line-haul activ ity (the ‘MGT’ method.) At this time, Norfolk Southern and Kansas City Southern ha ve provided input for us e of the MGT method and the Dencode method is applied fo r the other five railroads.

The Dencode Method – Publicly available data



### Each link in both the publicly available BTS data base and the confidential FRA database has a ‘Federal Density Code’ (Dencode ) ranging from 1 to 7 assigned based on the cumulative annual freight tonnage hauled on the link (track). Total Switcher Fuel Use in each railyard Y (SFU Y 

### ) is

estimated as follows:

First the Switcher Activity Indicator per yard (SAI Y 

### ) is estimated by multiplying the average

dencode of the links identified as part of the same railyard by th e sum of the length of the links for that railyard (Eqn 1).

SAI Y 

### = 

### ) * ( nY

nY 

### FDC l 

# ∑ Equation 1

SAI Y 

### = Switcher Activity I ndicator in Railyard Y

### C-6 n Y 

### = number of links identified as part of railyard Y

l nY 

### = length of link n in miles

FDC

n 

### = Federal Density Code (1 to 7) of link n

Next, this value is then weighted (SAI Y 

### ’) based on an ownership factor (OF) set between 0 and 1. The OF depends on the number of owners listed fo r each railyard: if ther e is one owner the OF is set to 1, if there ar e two owners the primary owner is set to 0.8 and the secondary is 0.2, and if there are 3 owners the primary is 0.6, the s econdary is 0.2, and th e tertiary is 0.1.

SAI Y 

### ’ = OF Y 

### * SAI Y 

### Equation 2

Next, the SAI Y 

### ’ of all railyards belonging to a Class I railroad (RR) were summed, and the

fraction of the railroads total SAI associated with each railyar d was multiplied by the railroads

total annual switcher fuel us e reported in the R-1 (TFU RR 

### ), resulting in the total Switcher Fuel Use for each railyard Y (Eqn 2).

SFU Y 

### = RR

RR Y Y 

### TFU SAI SAI
*

' ' 

# ∑ Equation 3

SFU Y 

### = Switcher Fuel Use at railyard Y

Finally, the SFU Y 

### is multiplied by the emission factors described in the previous section to

obtain annual switcher em issions at each railyard.

The MGT Method – Confidential data



### Two railroads, Norfolk Southern and Kansas Ci ty Southern, provided confidential link-level tonnage information and weighti ng factors to correct skewed es timates to improve estimated switcher activity at important yards. Other railro ads may also allow the use of this technique for

their inventories in the future.

The MGT Method also uses the FRA database fo r railyard identification and link lengths. However, rather than using the average dencode per link, confidential annual gross tonnage (MGT) hauled per link in the railyard was used to calculate the railyard switcher activity (SAI Y 

### ). This is calculated by replacing FDC

n 

### in Equation 2 with link-specific tonnage MGT

n 

### (Equation 4).

SAI Y 

### = 

### ) * ( nY

nY 

### MGT l 

# ∑ Equation 4

SAI Y 

### = Switcher Activity I ndicator in Railyard Y

n Y 

### = number of links identified as part of railyard Y

### C-7 l nY 

### = length of link n in miles

MGT nY 

### = million gross tons on link n

This method provides a more refined comparis on between railyards th an the use of the 7- category dencodes; however, is more susceptibl e to errors for yards where tonnage is not correlated to switching activ ity. For example, a yard with la rge coal trains pulling through used for crews to change over would be assigned an overly high le vel of emissions for switching activity. To account for this, a discretionary Sw itching Activity Factor (SAF) was introduced to allow railroads to roughly weight yards with clear ly higher or lower levels of switchi ng activity

than what results from the mathema tical allocation. Therefore, SAI Y 

### is weighted based on both the ownership factor (OF) as well as the SAF (E quation 5). For example, a yard used for crew changes and not switching may have an SAF of 0, while a yard at a major interchange between cities may have an SAF of 3.

SAI Y 

### ’ = OF Y 

### *SAF Y 

### * SAI Y 

### Equation 5

Again, the SAI Y 

### ’ of all railyards belonging to a Class I railroad (RR) are summed, and the

fraction of the railroads total SAI associated with each railyar d was multiplied by the railroads

total annual switcher fuel us e reported in the R-1 (TFU RR 

### ), resulting in the total Switcher Fuel Use for each railyard Y (Eqn 6).

SFU Y 

### = RR

RR Y Y 

### TFU SAI SAI
*

' ' 

# ∑ Equation 6

While the SAF allows estimates of yard-specfic emissions to be adjusted, the total level of emissions for each railroad, which is based on systemwide fuel use and systemwide emission factors, remains unchanged. The MGT method SFU Y 

### is also later multiplied by the emission factors described in the previous section to obtain annual switcher emissions at each railyard.

4. Improve estimates.



### In addition to the Switching Activity Factor desc ribed above, direct inpu t was also used to improve emission estimates for important railyards . Each Class I railroad provided an estimate of annual average switcher fuel use (generally much lower than the EPA default of 82,490 gal/yr) as well as the name, location, and number of operating switchers for railyards with 8 or more switchers operating in ozone or PM2.5 nonattainment areas. This data was used to

overwrite the dencode or MGT derived em issions estimates for those railyards.

The difference in estimated fuel use for those railyards was re-allocated (added or removed) between the remaining railyards belonging to that Cl ass I railroad. It is important to note that there are some discrepancies in how this data was reported for the la rge railyards by each railroad. For example, some railroads reported all switchers located at a railyard while others reported ‘full time equivalent’ switchers, meani ng the number of switchers normalized to a full working cycle (24-hours per day year-round.) This process should be stan dardized for future inventory versions.

### C-8 States also have the option of updating specifi c railyard emissions estimates. Because this inventory is derived ‘top-down’, local studies and familiarity with specific railyards is expected to provide better estimates, which ca n be used to adjust this invent ory. Care must be taken to ensure the other railyard estimates are adjusted to account for increases or decreases in estimated fuel use per yard.

Limitations, Conclusions, and Future Work



### What this ERTAC Rail railyard inventory does well is provide a comprehensive overview of where railyards are, who owns them, and gives a geographical allocation of switcher emissions bounded by what is reported as nationwide switche r fuel usage by the Class I railroads. These sources can be important for air quality manage ment in nonattainment areas, as well as in regional analysis and for future transportation planning. This invent ory will be useful for regional and some local modeling, helps identify wh ere railyards need to be better characterized, and provides a strong foundation for future deve lopment of a meaningf ul nationwide Class I switcher emissions inventory.

There are important uncertainties associated with estimates from th is method, including, but not limited to, the use of tonnage hauled as an indi cator of the amount of sw itching activity, and, for a few of the railroads, how the amount of switche r fuel use was determined to be reported in the R-1. The R-1 reported values ar e currently under examination.

There is also likely significant va riability in actual switching duty -cycles and, potentially, in the number of switchers operating at some railyards at different times of the year. ‘Road-switching’,

or the use of what are consider ed switching locomotives to m ove between nearby yards, should

be addressed in either this or the ERTAC line-haul inventory.

It must be noted that freight-related rail activity is not always routin e and no annual emissions inventory will ever be able to capture the innate variability of the source. However, as other large emission sources are reduced, and if rail activ ity increases as expected, it is important to

include our best estimates of these sources in ai r quality analysis. In the future, on-line data loggers and other tracking technol ogies, combined with ambient studies and detailed modeling, will hopefully provide more insight to the emissi ons of locomotives and other railyard sources.

References



### 1. E.H. Pechan & Associates, Inc., “Doc umentation for Aircraft, Commercial Marine Vessel, Locomotive, and Other Nonroad Components of the National Emissions Inventory, Volume I – Methodology”; EPA Cont ract No.: 68-D-02-063. Prepared for the US EPA Emissions, Mon itoring and Analysis Di vision, Sept. 30, 2005. ftp://ftp.epa.gov/EmisInventory/2002final nei/documentation/mobile/2002nei_mobile_no nroad_methods.pdf . Related documents at ftp://ftp.epa.gov/EmisInventory/2002final nei/documentation/mobile/2002nei_mobile_no nroad_train.pdf

### C-9 2. Sierra Research, Inc., “Revised Inventor y Guidance For Locomotive Emissions”; Report No. SR2004-06-01. Prepared for Southeas tern States Air Resource Managers (SESARM), June 2004. http://www.metro4-se sarm.org/pubs/railroad/FinalGuidance.pdf

3. Sierra Research, Inc., “Research Project: Development of Railroad Emission Inventory Methodologies”; Report No. SR 2004-06-02. Prepared for Southeastern States Air Resource Managers (SESARM), June 2004. http://www.metro4- sesarm.org/pubs/railroad/ FinalMethodologies.pdf

14. Environ, “Draft LADCO 2005 Locomotive Emissi ons”. Prepared for Lake Michigan Air Director Consortium, Feb 2007. http://www.ladco.org/reports/technical_ support_document/references/ladco_2005_locom otive_emissions.021406.pdf

15. Southern Research Institute, “NYSERDA Clean Diesel Technol ogy: Non-Road Field Demonstration Program, Development of the 2002 Locomotive Survey for New York State”; Agreement Number 8958. Prepared for the New York State En ergy Research And Development Authority ( NYSERDA), Feb. 09, 2007. http://www.nyserda.org/pub lications/LocomotiveSurve yReportwithAppendices.pdf

16. M. Bergin; M. Harrell; J. McD ill; M. Janssen; L. Driver; R. Fronczak; R. Nath,; and D. Seep. "ERTAC Rail: A Collaborative Effort in Building a Railroad-Related Emissions Inventory Between Eastern States Air Protect ion Agencies and Participation with the Railroad Industry," 18th Annual International Emissi on Inventory Conference. Baltimore, MD. April 14 - 17, 2009. Pa per and presentation available at: http://www.epa.gov/ttn/chief/c onference/ei18/session6/bergin.pdf

17. Confidential database was provided with assi stance from Raquel Wright of the Federal Railroad Administration. Similar public data is available from the Bureau of Transportation Statistics, in the NTAD 2009 shap efile data (data is representative for the year 2007): http://www.bts.gov/publications/nationa l_transportation_a tlas_database/2009

.
18. EPA Technical Highlights: Emission Factors for Locomotives, EPA Office of Transportation and Air Quality , EPA-420-F-09-025, April 2009. http://www.epa.gov/otaq/regs/nonroad/locomotv/420f09025.pdf

Appendix: ERTAC Rail Data Workgroup

REPRESENTATIVE ORGANIZATION



### Matt Harrell IL EPA Michelle Bergin (Co-Ch air) and Byeong Kim GA EPD Mark Janssen (Co-Chair) LADCO

Julie McDill and Patrick Davis MARAMA Laurel Driver US EPA OAQPS

Robert Fronczak AAR

Steven Sullivan ASLRRA

Rick Nath CSX

### C-10 David Seep and Lyle Staley BNSF Ken Roberge CPR

Carl Akins and Peter Conlon KCS

Erika Akkerman CN

M. John Germer UP

Brent Mason and Richard Russell NS

Joanne Maxwell Amtrak

### ERG No.: 0245.03.402.001

Contract No.: EP-D-07-097



## Documentation for Aircraft Compone nt of the National Emissions

Inventory Methodology

Prepared by:

Eastern Research Group

1600 Perimeter Park Drive Morrisville, North Carolina 27560

Under Contract to: E.H. Pechan & Associates, Inc. 3622 Lyckan Parkway

Suite 2002 Durham, North Carolina 27707

For Submittal to:

Laurel Driver Emissions, Monitoring and Analysis Division U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27711

January 27, 2011

### i TABLE OF CONTENTS

Section Page No.

1.0 INTRODUCTION ........................................................................................................... 1-1

1.1 What is the National Em ission Inventory? .......................................................... 1-1

1.2 Why Did the EPA Create the NEI? ...................................................................... 1-1

1.3 How is the EPA Going to Use This Version of the NEI? .................................... 1-1

1.4 Report Organization ............................................................................................. 1-2

2.0 DEVELOPMENT OF THE AIRCRAFT COMPONENT FOR THE NEI ..................... 2-1

2.1 How does this aircraft study fit into the NEI? ..................................................... 2-1

2.2 What are Aircraft Sources? ................................................................................ 2-11

2.3 What Pollutants are Included in th e National Emission Estimates for

Aircraft? ............................................................................................................. 2-11

2.4 How Were the Aircraft Emissions Estimated? .................................................. 2-12

2.5 How Were Emissions Allocated? ...................................................................... 2-17

2.6 QA/QC ............................................................................................................... 2-17

2.7 What are the Results?......................................................................................... 2-17

2.8 Aircraft References ............................................................................................ 2-20

Appendix A – Generic Airc raft Emission Factors

Appendix B – Calculating Piston- Engine Aircraft Airport Inve ntories for Lead for the 2008 National Emissions Inventory

### ii LIST OF TABLES AND FIGURES

Tables Page No.

Table 2-1a. Methods Used to Develop Emission Estimates for Onroad Vehicle Sources .......... 2-2 Table 2-1b. Methods Used to Develop A nnual Emission Estimates for Nonroad

Mobile Sources ................................................................................................................ ............ 2-4

Table 2-2. Aircraft Pollutant List ............................................................................................ ... 2-12

Table 2-3. National-Scale GSE Engine Distribution ................................................................. 2-14

Table 2-4. Aircraft Criteria Emissi on Estimates 2008 (tons per year) ...................................... 2-18

Table 2-5. Aircraft HAP Emission Es timates 2008 (tons per year) ........................................... 2-18

Figures Page No.

Figure 2-1. Procedures for Estimating Emissi ons from Commercial Air Carriers .................... 2-14 Figure 2-2. Procedures for Estimating Emissions from Commercial Ai r Taxis and General

Aviation....................................................................................................................... ............... 2-15

### 1-1 

## 1.0 INTRODUCTION

1.1 What is the National Emission Inventory?

The National Emission Inventory (NEI) is a comprehensive i nventory covering all anthropogenic sources of criteria pollutants and hazardous air pollutants (HAPs) for all areas of the United States. The NEI was created by the U.S. Environmental Protection Agency’s Emission Inventory and Analysis Group (EIAG) in Research Triangle Park, North Carolina. The NEI will be used to support air quality modeli ng and other activities. To this end, the EPA established a goal to compile comprehensive emissi ons data in the NEI for criteria and HAPs for mobile, point, and nonpoint sources. This report presents an overview of how emission estimates for the aircraft component of the NEI were compiled.

1.2 Why Did the EPA Create the NEI?

The Clean Air Act (CAA), as amended in 1990, includes mandates for the EPA related to criteria and hazardous air polluta nts. The CAA defines criteria pollutants as being one of the following air pollutants:

 Carbon monoxide (CO);

 Sulfur oxides (SO

x 

### );

 Nitrogen oxides (NO

x 

### );

 Ozone; and

 Particulate matter (PM).

Hazardous air pollutants are also delineated in the CAA, see http://www.epa.gov/ttn/atw/188polls.html for a complete list of re gulated pollutants and their chemical abstract service [CAS] numbers.

The CAA requires the EPA to identify emi ssion sources of these pollutants, quantify emissions, develop regulations for the identified source categories, and assess the public health and environmental impacts after th e regulations are put into effect . The NEI is a tool that EPA

can use to meet the CAA mandates. In this re port, criteria and HAP emission estimates are

discussed for aircraft sources.

1.3 How is the EPA Going to Use This Version of the NEI?

It is anticipated that the emission inventory developed from this effort will have multiple end uses. The data have been formatted according to protocols established for the EPA’s NEI

submittals. The common data structure on which th e NEI platform is based will allow the NEI emission data to be transferred to multiple end-users for a variety of purposes.

### 1-2 The criteria and HAP emission estimates devel oped for the NEI will be used to evaluate air pollution trends, air quality modeling anal ysis, and impacts of potential regulations.

1.4 Report Organization

Following this introduction, Section 2.0 provide s information on how the national aircraft emission estimates were develope d. This inventory effort was c oordinated by the EPA’s Office of Transportation and Air Quality (OTAQ) and EIAG. The appendixes were created to provide the supporting references from OTAQ.

### 2-1 

## 2.0 DEVELOPMENT OF THE AIRC RAFT COMPONENT FOR THE

NEI

2.1 How does this aircraft study fit into the NEI?

The NEI was developed to include all point, nonpoint (sometimes referenced as “area”), and mobile sources. The approaches used in the point and nonpoint s ource categories are documented in other reports. Table 2-1 summarizes the approaches used to estimate emissions from all nonroad sources included in the NEI pr ogram. Those source categories and years that are included in this report are noted in bold.

The scope of this inventory component of the NEI was to compile criteria and HAP emissions data for aircraft operating in United Stat es air space. In this effort, national emission estimates were often developed as point sources for each airport. The methodologies used to estimate emissions are discussed in this report.

The target inventory area includes every st ate in the United States and every county within a state, including Wash ington, DC, Puerto Rico, and US Virgin Islands. There are no boundary limitations pertaining to traditional cr iteria pollutant nonattainment areas or to designated urban areas. The pollutants inventorie d included all criteria pollutants (and the

188 HAPs identified in Sec tion 112(b) of the CAA).

In addition to numerous specific chem ical compounds, the list of 188 HAPs includes several compound groups [e.g., individual metals and their compounds, polycyclic organic matter (POM)]; the NEI includes emission esti mates for the individual compounds wherever possible. Many of the uses of the NEI depend up on data (e.g., toxicity) for individual compounds within these groups rather than aggreg ated data on each group as a whole.

The intent in presenting the following em ission inventory approach is to provide sufficient and transparent documentation such th at states and local agencies can use these approaches, in conjunction with th eir specific local activity data to develop more accurate and comparable emission estimates in future submittals.

This documentation is not meant to provide an exhaustive analysis on the derivation of all the inputs. For example, an emission factor used for a national estimate may be given in the appendix, but the source test data that were evaluated to obtain th is factor may not be presented or discussed. The goal of the documentation provid ed is to show in a brief and concise manner how a given estimate was derived.2-2Table 2-1a. Methods Used to Develop Emission Estimates for Onroad Vehicle Sources(Years addressed in this report are noted in bold print)Base Year(s)Pollutant(s)Geographic AreaEmission Estimation Method2008 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed using EPA’s National MobileInventory Model (NMIM), which uses MOBILE6 (specifically,M6203ChcOxFixNMIM.exe) to calculateonroad emission factors. Where Statesprovided alternate onroad MOBILE6 inputsor VMT, these data replaced EPA defaultinputs. Default VMT is based on FHWA 2008 data and 2008 Census populationestimates.2005 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed using EPA’s NMIM,which usesMOBILE6 to calculate onroad emission factors. Where Statesprovided alternateonroad MOBILE6 inputs or VMT, these data replaced EPA default inputs. DefaultVMT is based on FHWA 2005 data and 2005 Census population estimates.2002 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed using EPA’s NMIM,which usesMOBILE6 to calculate onroad emission factors. Where Statesprovided alternateonroad MOBILE6 inputs or VMT, these data replaced EPA default inputs. Californiasupplied emissions data which replaced defaultEPA emission estimates for this state.Default VMT is based on FHWA 2002 data and population data from 2000 Census.2001VOC, NOx, CO, SO2, PM10,PM2.5California Emissions and VMT provided by California at county/vehicle type level; Stateprovided emissions expanded to county/SCC level by EPA.2001NH3California Calculated at State/county/SCC level by month using MOBILE6 emission factors withState-provided VMT data.2001All CriteriaAL; CO; ME; MA; MS; OR; UT; VA;WV; Maricopa County, AZ; HamiltonCounty, TNState-provided VMT grown to 2001; emissions calculated by EPA using MOBILE6emission factors.2001All CriteriaRest of US Calculated at State/county/SCC level by month using MOBILE6 and FHWA-basedVMT.1999All CriteriaAL; ME; MA; MS; UT; VA; WV;Maricopa County, AZ; HamiltonCounty, TNCalculated at State/county/SCC level by month using MOBILE6; State-providedVMT data used.1999VOC, NOx, CO, SO2, PM10,PM2.5California Emissions and VMT provided by California at county/vehicle type level; Stateprovided emissions expanded to county/SCC level by EPA.1999NH3California Calculated at State/county/SCC level by month using MOBILE6 emission factors withState-provided VMT data.1999PM10ExhaustColorado PM10emissions and VMT provided by State.2-3Table 2-1a. Methods Used to Develop Emission Estimates for Onroad Vehicle Sources(Years addressed in this report are noted in bold print)Base Year(s)Pollutant(s)Geographic AreaEmission Estimation Method1999VOC, NOx, CO, SO2, PM10brake and tire wear, PM2.5,NH3Colorado Calculated at State/county/SCC level by month using MOBILE6; State-providedVMT data used.1999All CriteriaOregon Emissions and VMT provided by Oregon at county/vehicle type level; State-providedemissions expanded to county/SCC level by EPA.1999All CriteriaRest of US, Puerto Rico, and USVirgin IslandsCalculated at State/county/SCC level by month using MOBILE6 and FHWA-basedVMT.1999HAPsCalifornia HAP emissions and VMT provided by California at county/vehicle type level;emissions allocated to SCC level by EPA.1999HAPsRest of US, Puerto Rico, and USVirgin IslandsMOBILE6 emission factors calculated at State/county/SCC level by season; applied toFHWA-based VMT.1997-1998All CriteriaUS 2-step linear interpolation at State/count/SCC level based on 1996 and 1999State/count/SCC level data.1990, 1996HAPsUS MOBILE6 emission factors calculated at State/county/SCC level by season; applied toFederal Highway Administration (FHWA)-based vehicle miles traveled (VMT).1991-1995All CriteriaUS Linear interpolation at State/count/SCC level based on 1990 and 1996State/count/SCC level data.1988-1989All CriteriaUS Linear interpolation at State/count/SCC level based on 1987 and 1990State/count/SCC level data.1979-1986All CriteriaUS Linear interpolation at State/count/SCC level based on 1978 and 1987State/count/SCC level data.1978, 1987,1990, 1996,2000All CriteriaUS Calculated at State/county/source classification code (SCC) level by month usingMOBILE6, no State data incorporated.1970, 1975All CriteriaUS Linear extrapolation at national vehicle type level based on 1978 and 1987 nationaldata.2-4Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*NONROAD CategoriesNonroad Gasoline,Diesel, LPG,CNG2008 VOC, NOx, CO, SO2,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines weredeveloped using EPA’s National Mobile InventoryModel (NMIM), which incorporates NONROAD2008.Where states providedalternate NMIM nonroadinputs, these data replaced EPA default inputs.2005 VOC, NOx, CO, SO2, ,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines were developed using EPA’s NMIM, which incorporatesNONROAD2005. Where States providedalternate nonroad inputs, these data replaced EPA default inputs.2002 VOC, NOx, CO, SO2,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines were developed using EPA’s NMIM, which incorporatesNONROAD2004. Where states provided alternate nonroad inputs, these data replaced EPA default inputs.State-supplied emissions data also replaced default EPA emission estimates.1999 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROADmodel; and 2) an updated 1999 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated fromthe Lockdown C model. Replaced State-submitted datafor California for all NONROAD model categories; Pennsylvania for recreational marine and aircraft groundsupport equipment, and Texas forselect equipment categories.1996, 1997,1998, 2000 &2001VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated year-specific national andCalifornia inventories, based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the1996 county-level emission estimates, seasonal and daily county-to-national ratios and California county-tostate ratios were then developed for application to updated national estimates per season estimated from theLockdown C model. California results replace the diesel equipment emissions generated from priorapplication of county-to-national ratios.2-5Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Nonroad Gasoline,Diesel, LPG, andCNG(Continued)1991-1995 VOC, NOx, CO, SO2,PM10, PM2.5, NH3Using 1990 and 1996 county-level emissions inventories, estimated emissions using linear interpolation ofnational emissions between 1990 and 1996. From these emissions, calculated the average annual growth ratefor each pollutant/SCC combination for each year, and thenapplied the growth factors to 1990 county-levelemissions to estimate 1991-1995 emissions.1990 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1990 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated from the Lockdown C model.1986, 1988, &1989VOC, NOx, CO, SO2,PM10, PM2.5, NH3Using 1985 and 1990 county-level emissions inventories, estimated emissions using linear interpolation ofnational emissions between 1985 and 1990. From these emissions, calculated the average annual growth ratefor each pollutant/SCC combination for each year, and thenapplied the growth factors to 1985 county-levelemissions to estimate 1986-1989 emissions.1987 VOC, NOx, CO, SO2,PM10, PM2.5Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated nationalemissions for 1987 by running 4 seasonal NONROAD model runs to estimate annual criteria pollutantemissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.1985 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1985 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated from the Lockdown C model.1970, 1975,1978, & 1980VOC, NOx, CO, SO2,PM10, PM2.5Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated nationalemissions for all years by running 4 seasonal NONROAD model runs to estimate annual criteria pollutantemissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.2-6Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Nonroad Gasoline,Diesel, LPG, andCNG(Continued)1996, 1997,1998, 1999,2000, & 2001NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying byNH3emission factors, and distributing to counties using 1996 inventory, based on October 2001 draftNONROAD. NH3emissions for California were also recalculated using updated diesel fuel consumptionvalues generated for California-specific runs, and assuming the 1996 county-level distribution.1985 & 1990 NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying byNH3emission factors, and distributing to counties using 1996 inventory, based on October 2001 draftNONROAD.1987 NH3Obtaining 1987 national fuel consumption estimates from Lockdown C NONROAD model and multiplyingby NH3emission factors.1970, 1975,1978, & 1980NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model and multiplying byNH3emission factors.1990, 1996, &1999HAPs Speciation profiles applied to county VOC and PM estimates. Metal HAPs were calculated using fuel andactivity-based emission factors. Some state data were provided and replacednational estimates. (2003)AircraftCommercialAircraft2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System (EDMS) - Version5.1.was run using BTS T-100 LTO data. (2009)2002 and 2005 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion and Modeling System (EDMS) was runfor criteria pollutants, VOC and PM emissions were speciated into HAP components. (2004)1990, 1996,1999, 2000,2001VOC, NOx, CO, SOxInput landing and take-off (LTO) data into FAA EDMS. National emissions were assigned to airports basedon airport specific LTO data and BTS GIS data.State data replaced national estimates. (2003)1970-1998 VOC, NOx, CO, SOxEstimated emissions for interim years using linearinterpolation between available base years. (2003)1990, 1996,1999HAPs Speciation profiles were applied to VOC estimates to get national HAP estimates. State data replacednational estimates. (2003)General Aviation,Air Taxis2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System (EDMS) - Version5.1.was run using BTS T-100 LTO for aircraft identified as Air taxis. (2010)Used FAA LTO data from TAF and OTAQ provided activity data for smaller airports derived fromFAA 5010 master plans. EPA approved generic emission factors for criteria estimates. Speciationprofiles were applied to VOC and PM estimates to get national HAP estimates. (2010)2-7Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*General Aviation,Air Taxis(Continued)2005 VOC, NOx, CO, SO2,PM10, PM2.52002 emissions for approximately 4,000 largest airports were calculated via EDMS and SIP guidance andincluded in the 2005 NEI as point sources. Only airports in FAA’s T100 and TAF databases were included.State point source submittals were incorporated.1978, 1987,1990, 1996,1999, 2000,2001, & 2002VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data and EPA approved emission factors for criteria estimates. Speciation profiles wereapplied to VOC estimates to get national HAP estimates. State data replaced national estimates. (2004)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999, & 2002HAPs Used FAA LTO data and EPA approved emission factors for criteria estimates. Speciation profiles wereapplied to VOC estimates to develop national HAP estimates. (2004)1990, 1996,1999, & 2002Pb Used Department of Energy (DOE) aviation gasoline usage data with lead concentration of aviation gasoline.(2004)1996 NH3Applied NH3emissions factors to 1996 national jet fuel and aviation gasoline consumption estimates.Military Aircraft2008 VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data as reported in TAF and EPAapproved emission factors for criteria estimates.Representative HAP profiles were not readily available, therefore HAP estimates were not developed.(2010)2005 VOC, NOx, CO, SO2,PM10, PM2.52002 emissions were included in the 2005 NEI as point sources similar to other TAF reported data.1978, 1987,1990, 1996,1999, 2000,2001, 2002,2008VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data as reported in TAF and EPA approved emission factors for criteria estimates.Representative HAP profiles were not readily available, therefore HAP estimates were not developed.1970-1998 VOC, NOx, CO, SOX,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)Auxiliary PowerUnits and GroundSupportEquipment2008 VOC, NOx, CO, SO2,PM10, PM2.5, HAPsFederal Aviation Administration (FAA) Emissions and Dispersion and Modeling System (EDMS) -Version 5.1.was run using BTS T-100 LTO data. (2009)2002 and 2005 VOC, NOx, CO, SO2,PM10, PM2.5, HAPsComputed via NONROAD2005 model runs.1985-2001 VOC, NOx, CO, SO2,PM10, PM2.5Grew 1996 emissions to each year using LTO operations data from the FAA. Estimation methods prior to1996 reported in EPA, 1998.2-8Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Unpaved Airstrips11985-2001 PM10, PM2.5Grew 1996 emissions to each year using SIC 45-Air Transportation growth factors, consistent with thecurrent draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998.Aircraft Refueling11985-2001 VOC Grew 1996 emissions to each year using SIC 45-Air Transportation growth factors, consistent with thecurrent draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998.Commercial Marine Vessel (CMV)All CMV Categories 2008 VOC, NOx, CO, SO2,PM10, PM2.5OTAQ provided CAP emission estimates for all CMV categories. Note that the SCCs for this category havechanged such that the Diesel category refers to smaller vessels (Category 1 and 2) using distillate fuels andthe Residual category refers to larger (Category 3) vessels using a blend of residual fuels. Emissions wereallocated to segments using GIS shapefiles and adjusted based on limited state data (2010)2008 HAPs OTAQ’s 2008 estimates were speciated into HAP components using SEPA profiles (2009)CMV Diesel 2002 and2005VOC, NOx, CO, SO2,PM10, PM2.52001 Estimates carried over. Usedstate data when provided. (2004)HAPs 1999 Estimates carried over. Used state data when provided. (2004)1978, 1987,1990, 1996,1999, 2000, &2001VOC, NOx, CO, SOx,PM10, & PM2.5Used criteria emission estimates in the background document for marine diesel regulations for 2000.Adjusted 2000 criteria emission estimates for other used based on fuel usage. Emissions were disaggregatedinto port traffic and underway activities. Port emissions were assignedto specific ports based on amount ofcargo handled. Underway emissions were allocated based on Army Corp of Engineering waterway data.State data replaced national estimates. (2003)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999HAPs VOC and PM emission estimateswere speciated into HAP components. State data replaced nationalestimates. (2003)1996 NH3Applied NH3emissions factors to 1996 distillate and residualfuel oil estimates (i.e., as reported in EIA,1996).1990-1995 NH3Estimation methods reported in EPA, 1998.2-9Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*CMV SteamPowered2005 VOC, NOx, CO, SOx,PM10, & PM2.5,HAPs2002 estimates grown to 2005 (2008).2002 VOC, NOx, CO, SOx,PM10, & PM2.5,HAPs2002 based estimates were developed for port and underway category 3 (C3) vessels aspart of a rulemakingeffort. Emissions were developed separately for near port and underway emissions. For near port emissions,inventories for 2002 were developed for 89 deep water and 28 Great Lake ports in the U.S. The WaterwayNetwork Ship Traffic, Energy, and EnvironmentalModel (STEEM) was used to provide emissions fromships traveling in shipping lanes between and near individual ports (2008)1978, 1987,1990, 1996,1999, 2000, &2001VOC, NOx, CO, SOx,PM10, & PM2.5Calculated criteria emissions based on EPA SIP guidance. Emissions were disaggregated into port trafficand under way activities. Port emissions were assignedto specific ports based onamount of cargo handled.Underway emissions were allocated based on Army Corpof Engineering waterway data. State data replacednational estimates. (2003)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996, &1999HAPs VOC and PM emission estimateswere speciated into HAP components. State data replaced nationalestimates. (2003)Military Marine 1997-2001 VOC, NOx, CO, SO2,PM10, PM2.5Applied EGAS growth factors to 1996emissions estimates for this category.CMV Coal,2CMV,Steam powered,CMV Gasoline21997-1998 VOC, NOx, CO, SO2,PM10, PM2.5Applied EGAS growth factors to 1996emissions estimates for this category.CM Coal, CMV,Steam powered,CMV Gasoline,Military Marine1991-1995 VOC, NOx, CO, SO2,PM10, PM2.5Estimation methods reported in EPA, 1998.LocomotivesClass I, II, III andYard operations2008 VOC, NOx, CO, PM10,PM2.5,SOx& HAPsCriteria emission estimates were provided to EPA by ERTAC. These data were assigned to individualrailway segments using DOT shapefiles and guidance from ERTAC. HAP emissions were calculated byapplying speciation profiles to VOC and PM estimates. (2010)2-10Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Class I, Class II,Commuter,Passenger, and YardLocomotives1978, 1987,1990, 1996,1999, 2000,2000, 2002, &2005VOC, NOx, CO, PM10,PM2.5Criteria pollutants were estimated by using locomotive fuel use data from DOE EIA and available emissionfactors. County-level estimates wereobtained by scaling the national estimates with the rail GIS data fromDOT. State data replaced national estimates. (2004)1978, 1987,1990, 1996,1999, 2000,2001, 2002, &2005SO2SOxemissions were calculated by using locomotive fuel use and fuel sulfur concentration data from EIA.County-level estimates were obtained by scaling the national estimates with the county level rail activitydata from DOT. State data replaced national estimates. (2004)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999, & 2002HAPs HAP emissions were calculatedby applying speciation profiles toVOC and PM estimates. County-levelestimates were obtained by scaling the national estimates with the county level rail activity from DOT. Statedata replaced national estimates. (2004)1997-1998 NH3Grew 1996 base year emissions using EGAS growth indicators.1996 NH3Applied NH3emissions factors to diesel consumption estimates for 1996.1990-1995 NH3Estimation methods reported in EPA, 1998.Notes:*Dates included at the end of Estimation Method represent the year that the section was revised.1 Emission estimates for unpaved airstrips and aircraft refueling are included in the area source NEI, since they represent non-engine emissions.2 National Emission estimates for CMV Coal and CMV Gasoline were not developed though states and local agencies may have submitted estimates for thesesource categories.EPA, 1998. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Emission Factors and Inventory Group, National AirPollutant Emission Trends, Procedures Document, 1900–1996, EPA-454/R-98-008. May 1998.

### 2-11 2.2 What are Aircraft Sources?

The aircraft source category includes all ai rcraft types used for public, private, and military purposes. This includes four types of ai rcraft (EPA, 1992): 1) Commercial; 2) Air Taxis; 3) General Aviation; and 4) Military.

Commercial aircraft include those used fo r transporting passengers, freight, or both.

Commercial aircraft tend to be larger aircraft powered with jet engines. Air Taxis (AT) carry passengers, freight, or both, but us ually are smaller aircraft and operate on a more limited basis

than the commercial carriers. General Aviation (GA) includes most other aircraft used for recreational flying and personal tr ansportation. Aircraft that su pport business travel, usually on an unscheduled basis, are included in the category of general aviation.

The national AT and GA fleet includes both je t and piston-powered aircraft. Most of the AT and GA fleet are made up of piston powered airc raft, though smaller business jets can also be found in these categories. According to a 2008 Federal Aviation Administration GA and AT Activity Survey, 66% of all GA and AT activit y are powered by piston- powered aircraft and 34% are jet (or turbine) driven. EPA has used th is estimate as a national-scale default value in recently published studies investigating lead em issions from aviation sources (EPA, 2008). The piston powered aircraft tend to have higher VOC, PM, and CO emissions and lower NO X 

### emissions than larger jet-powered aircraft (EPA, 1992). Military ai rcraft cover a wide range of aircraft types such as training aircraft, fighter jets, helicopters, and jet- and a small number of piston powered planes of varying sizes.

It should be noted that this inventory effort also include s criteria and Hazardous Air Pollutants (HAP) emission estimates for aircraft Auxiliary Power Units (APU) and aircraft Ground Support Equipment (GSE) typical ly found at airports, such as aircraft refueling vehicles, baggage handling vehicles, and equipment, ai rcraft towing vehicles, and passenger buses.

2.3 What Pollutants are Included in the Nati onal Emission Estimates for Aircraft?

Emissions estimates were developed for all cr iteria pollutants includ ing volatile organic compounds (VOC), nitrogen oxides (NO

x 

### ), carbon monoxide (CO), sulfur oxides (SO

x 

### ), particulate matter less than 10 microns (PM 10 

### ), particulate matter less than 2.5 microns (PM 2.5 

### ) and hazardous air pollutants (HAP) (Cook, 1997; Cook, 1998; EPA/FAA, 2009). The HAPs that are included in the national aircraft inventory ar e shown in Table 2-2 and are based on available test data and accepted emission estimation procedures.

### 2-12 Table 2-2. Aircraft Pollutant List

1,3-Butadiene Carbon Dioxide Naphthalene

1-Methylnaphthalene* Carbon Monoxide Nitrogen Oxides

2,2,4-Trimethylpentane Chrysene* O-xylene*

2-Methylnaphthalene* Cumene* Phenanthrene*

Acenaphthene* Dibenzo[a,h]Anthracene* Phenol

Acenaphthylene* Ethyl Benzene PM 10 

### Primary

Acetaldehyde Fluoranthene* PM 2.5 

### Primary

Acrolein Fluorene* Propionaldehyde

Anthracene* Formaldehyde Pyrene*

Benz[a]Anthracene* Hexane* Styrene

Benzene Indeno[1,2,3-c,d]Pyrene* Sulfur Dioxide

Benzo[a]Pyrene* Lead Toluene

Benzo[b]Fluoranthene* Methane* VOCs

Benzo[g,h,i,]Perylene* Methanol* Xylene

Benzo[k]Fluoranthene* M-xylene*

* Added to 2008 Inventory



### 2.4 How Were the Aircraft Emissions Estimated?

EPA has developed guidance for inventorying aircraft emissions associated with an aircraft’s landing and takeoff (LTO) cycle. The cycle begins when the aircraft approaches the airport on its descent from cruisi ng altitude, lands, taxis to th e gate, and idles during passenger deplaning. It continues as the aircraft idles du ring passenger boarding, taxis back out onto the runway for subsequent takeoff, and ascent (climb out) to cruising altitude. Thus, the five specific operating modes in an LTO are (EPA, 1992): 1) A pproach; 2) Taxi/idle-in; 3) Taxi/idle-out; 4) Takeoff; and 5) Climbout.

The LTO cycle provides a basis for calculati ng aircraft emissions. During each mode of operation, an aircraft engine operates at a fairly standard power setting for a given aircraft category. Emissions for one complete cycle ar e calculated using emission factors for each operating mode for each specific aircraft engine combined with the typical period of time the aircraft is in the operating mode.

On March 20, 2009, the EPA posted preliminar y LTO data intended to be will use to calculate emissions for review prio r to developing the aircraft i nventory. State and local agencies were encouraged to review the materials posted at ftp://ftp.epa.gov/Emis Inventory/2008_nei/ and provide comments on any necessary corrections to:

### 2-13  Airport names and locations for approximate ly 20,000 airports to be included in the Emission Inventory System (EIS) facility inventory;

 Landing and Takeoff (LTO) information that will be used to estimate emissions for each airport;

 Aircraft/engine combinations to link to F AA LTO data including default assumptions and AircraftEngineCodeTypes for EIS submittals; and

 Lead estimates and lead estimation methodology.

This preliminary review by state, local, and trib al groups provided information that EPA used to improve EPA’s work. EPA received comments fro m four states (i.e., Minnesota Pollution Control Agency - Environmental Analysis and Ou tcomes Division; New Jersey Department of Environmental Protection; Bureau of Air Management, Connecticut Department of Environmental Protection; and Wisconsin Departme nt of Natural Resources (specifically related to Volk Field Air National Guard Base (VOK) in Juneau County Wittman Regional Airport (OSH)) and three local agencies (i.e., Mecklenburg County No rth Carolina; Ventura County

California Air Pollution Control District (Specifically related to Oxnard (OXR), Camarillo (CMA) and Santa Paula (SZP); and - Regiona l Air Pollution Control Agency (Dayton and Montgomery County Ohio)).

Criteria emission estimates are presented here for four different aircraft types: commercial air carrier, air taxis, general avia tion, and military. HAP emission estimates were developed for all aircraft types.

Emissions for commercial air carriers for whic h detailed aircraft-s pecific activity data were available, were calculated differently than the other three aircraft categories (See Figure 2- 1). Criteria and HAP emissions were estimated fo r commercial aircraft by applying aircraft make and model (e.g., Boeing 747-200 series) sp ecific LTO activity data from FAA’s Form 41, Schedules T100 and T100(f) Air Carrier Data to the FAA’s Emissions and Dispersion Modeling System (EDMS), Version 5.1 (DOT, 2008). It should be noted that due to the reporting requirements of T-100, only commercial activities are included in the dataset, and therefore does not include activity data for non- air carrier applications such as general aviation and military.

This distinction lead to a revisi on to EPA’s original aircraft cro sswalk table, also known as the aircraft engine type code, used to match airc raft to EDMS aircraft and to account for double counting between the T-100 data and the TAF data. In the revised crosswal k, aircraft that were previously considered general aviation and military based on aircraft model were changed to air

taxi and commercial air car rier aircraft types base d on the definition of air taxis (i.e., any aircraft

that was not considered an air taxi was classified as an air carrier airc raft). The FAA reviewed the cross walk tables and made additional changes that moved some of the larger air taxis to the commercial air carrier category and some of the smaller commercial air carriers to the air taxi category. The revised crosswalk tabl e is provided in an electronic f ile as supporting data for this study.

### 2-14 Emissions were calculated for each airport individually using airport specific mixing height. The national-scale defau lt values for taxi in and out are seven and nineteen minutes, respectfully. It should be noted that EDMS inco rporates the latest ai rcraft engine emission

factors from the International Civil Aviation Or ganization Engine Exhaust Emissions Data Bank. The EDMS output includes organic HAPs, but not metals.

Figure 2-1. Procedures for Estimating Emissions from Commercial Air Carriers

Emissions for GSE and APU associated with commercial air carriers and air taxis for

which T-100 data were available were estimate d by EDMS, using the assumptions and defaults incorporated in the model. This is significant change from previous NEI year’s emissions where

GSE estimates came from the NONROAD model and APUs were not included in EPA’s estimates. With EDMS, GSE that are assigned to an aircraft are given times (minutes per arrival, minutes per departure) based upon the type of servi ce. For example, a fuel truck servicing a large

commercial aircraft will have a different operating time than the same fuel truck servicing a

commuter aircraft. All EDMS defaults for GSE durat ion and type (e.g., fuel truck, cabin service truck, baggage belt loader) were used. GSE emission factors used by EDMS are derived from

EPA’s NONROAD2005 model and are based on the fo llowing variables: fuel, brake horsepower and load factor. GSE engines burn gasoline, dies el, compressed natural gas (CNG), and liquefied petroleum gas (LPG). EPA has used a national-scal e value to characterize engines type. The GSE engine distribution is shown below in Table 2- 3. Like GSE, APU emissions are the product of operating time. The purpose of an aircraft APU is to provide power to start the main engines and run the heating, cooling, and ventilation sy stems prior to starting the main engines.

Table 2-3. National-Scale GSE Engine Distribution

GSE Engines Type Percent of

Total

Gasoline Fired, 4-Stroke 16.9

Liquefied Petroleum Gas (LPG) Fired 1.65

Compressed Natural Gas (CNG) Fired 1.25

Diesel Fired 80.2

Emissions of criteria pollutants for air taxis, general aviation, and military aircraft were calculated by combining aircraft operations data from FAA’s Terminal Area Forecasts (TAF)

and 5010 Forms. To avoid double counting between the T-100 data set and the TAF/5010 data,

### 2-15 LTOs by airport and aircraft type were summed in the T-100 data and compared with data in the

TAF/5010 data. If the TAF/5010 LTO estimates were larger than the T-100 estimates for a specified aircraft type then th e T-100 values were subtracted from the TAF/5010 values. If the T-100 values were larger than the TAF values, then the TAF values were set to zero. A data set of adjusted TAF/5010 LTOs were provided to OTAQ where additional adjustments were made

to address older data in the TAF and 5010 datasets and to incorporate ot her insights provided by

FAA reviewers.

The TAF/5010 LTO data were dividing into jet and piston powered fractions based on the national observation that 66 percent of all general aviati on and air taxi activities are associated with piston powered aircraft and the remaini ng 34 percent of general aviation and air taxi activities are associated with je t powered aircraft. The adjusted and split TAF/5010 activity data were applied to emission factors as appropriate (See Fi gure 2-2). It should be noted that EDMS calculates organic HAP emissions in the model (metal HAPs are currently not included in the EDMS output). HAP emission estimates for air taxi s, general aviation, and military aircraft were estimated by applying specia tion profiles to VOC or PM 10 

### emissions estimates. The following equation was used (emission factor are included as Appendix A).

E ixj 

### = LTO i 

### × FR pro-i 

### × EF ij



### Where:

E ixj 

### = Emission estimate for aircraft t ype i equipped with engine type x and pollutant j (lbs/year)

LTO i 

### = Annual count of LTO cycl es for aircraft type i

FR

x 

### = Fraction of LTOs equipped with engine type x

EF ij 

### = Generic emission factor for airc raft type i equipped with engine type x and pollutant j (lbs/LTO) i = Aircraft type (i.e., air ta xi, general aviation, and military) x = Engine type (i.e., jet or turboprop, and piston engine) j = Criteria pollutant j

Figure 2-2. Procedures for Estimating Em issions from Commercial Air Taxis and

General Aviation Split into: Jet-Propelled and

Piston-Driven

Aircraft FAA LTO Data

for Air Taxis

and General

Aviation

(5010 and TAF) Apply Criteria and

HAP Pollutant

Emission Factors Apportion

Emissions Based on Airport Activity

for Air Taxis and

General Aviation Split into: Jet-Propelled and

Piston-Driven

Aircraft FAA LTO Data

for Air Taxis

and General

Aviation

(5010 and TAF) Apply Criteria and

HAP Pollutant

Emission Factors Apportion

Emissions Based on Airport Activity

for Air Taxis and

General Aviation

### 2-16 Lead emission estimates were handled differe ntly. Lead emissions are associated with leaded aviation fuel used in piston driven ai rcraft associated with general aviation. Lead emissions per LTO are calculate d using the following equation:

Pb(tons) = (piston-engine LTO) ( 7.34 g Pb/LTO) (0.95) / 907,180 (g/ton)

Where the lead content of aviation gasoline is assumed to be 0.56 grams per liter or 2.12 grams per gallon.

In flight lead emissions were calculate ba sed on national aviation gasoline consumption and similar assumptions noted above about lead fu el content and retention rates. Lead emissions associated with airport LTO activities were s ubtracted from the national fuel based lead emissions to approximate in flight lead emissi ons which were allocated to individual counties

and noted with the code 777.

For additional details on EPA lead emissi on calculation procedures see Calculating Piston-Engine Aircraft Airport Inventories for Lead for the 2008 National Emissions Inventory (included in Appendix B).

HAP Emission Estimates

As noted earlier, EDMS calculate s organic HAP emissions for ai rcraft activity reported in the T-100 dataset. Representative HAP speciation profiles were used to estimate the individual chemical species for each aircraft type includ ed in the TAF/5010 dataset. Profiles are used to split (or speciate) organic gases, hydrocarbons, a nd particulate matter emissions estimates into more individual HAP compounds using the following equation:

E ixj 

### = LTO ix 

### × SP ixj



### Where:

E ixj 

### = Emission estimate for aircraft t ype i equipped with engine type x and pollutant j (tons/year)

LTO ix 

### = Annual count of LTO cycles for ai rcraft type i a nd engine type x

SP ixj 

### = Generic speciation profiles for ai rcraft type i equipped with engine type x and pollutant j (tons/LTO) i = Aircraft type (i.e., air ta xi, general aviation, and military) x = Engine type (i.e., jet or turboprop, and piston engine) j = Pollutant j

Appendix A contains the HAP profiles converted to emissions factors used for this 2008 inventory. In this version of the NEI aircraft em issions inventory the foll owing corrections to the

HAP emission estimates were made:

 Acenpthylene was removed from this inventory for SCC 2275050012.

### 2-17  To avoid double counting tota l xylene emissions were removed if speciated xylene

factors were also available.

2.5 How Were Emissions Allocated?

For the 2008 inventory, emissions were indi vidually estimated for each airport. A GIS database obtained from the Bureau of Transporta tion Statistics (BTS) contai ned airport level data with latitude and longitude coordinates.

2.6 QA/QC

Given the significant methodological changes ov er previous inventory efforts, several quality checks were implemented to ensure that these data were developed and allocated in a clear and reproducible manner. So me of the quality checks impl emented include the following:

Emissions allocations and estimations

 All original data importations and transc riptions into the da tabase were doublechecked for errors.

 All calculation methods and approaches we re evaluated for t echnical soundness.

 All unit conversions and equations used to generate results were double-checked for

errors.

 All sources of original data are referenced in the spreadsheet.

 Emission factors were compiled from a va riety of sources. Each emission factor development methodologies were evaluated to identify the most accurate emission factor for use in this inventory effort.

 Emission sums were evaluate d across activity types (e.g., Ai rcraft, APU, and GSE) to ensure they consistently mirror LTO activity levels.

 2008 pollutants and emissions were checked against the 2005 inventory to identify any missing pollutants or major changes compared to previous inventories. Discrepancies were investigated a nd revisions were made as needed.

 The validity of SCC codes, FIP county code s, and pollutant codes were confirmed.

 The validity of Airport and plane id entification codes were confirmed.

2.7 What are the Results?

Table 2-4 summarizes the emission estimates for Aircraft, ground support equipment and APUs for criteria pollutants. Table 2-5 summari zes the emission estimates for individual HAPs. Both tables aggregate the data for all states, in cluding the District of Columbia. Note that the

2008 estimates do not include state submitted emissions data.2-18Table 2-4. Aircraft Criteria Emission Estimates 2008 (tons per year)Pollutant2008Military(2275001000)Commercial(2275020000)GA, Piston(2275050011)GA, Turbine(2275050012)AT, Piston(2275060011)AT, Turbine(2275060012)GSE, Gas(2265008005)GSE, LPG(2267008005)GSE, CNG(2268008005)GSE, Diesel(2270008005)APU(2275070000)CO33,161.20 75,463.61 192,510.69 56,532.07 19,116.38 10,180.90 18,005.13 1,768.69 1,398.67 85,607.61 4,072.84NOX284.92 102,561.46 1,041.55 1,911.11 465.64 2,274.10 1,927.90 189.38 149.76 9,166.44 2,841.72PM10-PRI709.12 1,782.43 3,792.85 1,397.21 242.12 797.03 55.87 5.49 4.34 265.62 457.11PM2.5-PRI92.60 1,776.37 493.07 181.64 44.81 103.65 53.63 5.27 4.17 254.97 457.11SO227.32 10,179.67 160.24 434.33 53.76 439.43 53.21 5.23 4.13 252.99 443.04VOC1,652.02 13,608.67 2,399.79 3,223.93 310.48 2,610.94 615.80 60.49 47.84 2,927.89 313.72Table 2-5. Aircraft HAP EmissionEstimates 2008 (tons per year)Pollutant2008Military(2275001000)Commercial(2275020000)GA, Piston(2275050011)GA, Turbine(2275050012)AT, Piston(2275060011)AT, Turbine(2275060012)GSE, Gas(2265008005)GSE, LPG(2267008005)GSE, CNG(2268008005)GSE, Diesel(2270008005)APU(2275070000)1,3-Butadiene0.87 184.14 29.75 61.04 5.01 44.44 5.321-Methylnaphthalene0.13 26.96 8.94 0.23 6.20 0.782,2,4-Trimethylpentane0.69 1.09 1.55 0.03 0.51 8.95 0.88 0.69 42.542-methylnaphthalene0.11 22.48 7.45 0.20 5.17 0.65Acenaphthene0.36 0.17Acenaphthylene2.03 0.93Acetaldehyde2.21 466.29 18.82 154.57 11.97 113.00 2.43 0.24 0.19 11.57 13.47Acrolein0.02 37.70 1.82 88.61 0.04 32.72Anthracene0.42 6.16E-04 0.19 3.52E-04Benz[a]Anthracene6.09E-04 0.05 9.33E-05 0.02 5.32E-05Benzene0.87 183.48 122.97 60.82 7.58 44.59 10.44 1.03 0.81 49.62 5.30Benzo[a]Pyrene4.52E-04 0.05 5.11E-05 0.02 2.91E-05Benzo[b]Fluoranthene8.89E-04 0.06 0.03Benzo[g,h,i,]Perylene8.11E-06 0.13 8.47E-06 0.06 4.83E-06Benzo[k]Fluoranthene8.89E-04 0.06 0.03Chrysene6.17E-04 0.05 8.69E-05 0.02 4.96E-052-19Table 2-5. Aircraft HAP Emission Estimates 2008 (tons per year) (Continued)Pollutant2008Military(2275001000)Commercial(2275020000)GA, Piston(2275050011)GA, Turbine(2275050012)AT, Piston(2275060011)AT, Turbine(2275060012)GSE, Gas(2265008005)GSE, LPG(2267008005)GSE, CNG(2268008005)GSE, Diesel(2270008005)APU(2275070000)Cumene2.68E-05 0.05 0.11 0.04Ethyl Benzene1.55E-03 2.68 44.63 6.30 1.05 2.32Fluoranthene1.17E-03 0.45 1.29E-03 0.21 7.35E-04Fluorene0.74 0.34Formaldehyde6.36 1,343.45 81.67 445.41 38.06 327.87 7.20 0.71 0.56 34.23 38.82Hexane21.25 0.50Indeno[1,2,3-c,d]Pyrene0.00 0.04 0.02Lead **245.48 8.97Methane0.01 18.96 14.79 14.61 1.44 1.14 69.47Methanol0.02 27.78 65.31 24.11m-Xylene0.14 26.44 0.36 1.58E-04 0.88 3.66 11.09 1.09 0.86 52.74 0.89Naphthalene0.28 54.17 21.11 20.42 5.05 13.86 1.71O-xylene0.08 15.56 2.03 9.30E-05 1.40 2.19 5.43 0.53 0.42 25.80 0.52Phenanthrene0.01 1.25 0.01 0.58 3.27E-03Phenol0.01 11.17 26.27 9.70Propionaldehyde0.38 79.35 1.82 26.30 2.29 19.45 1.48 0.15 0.11 7.04 2.29Pyrene1.42E-03 0.61 1.58E-03 0.28 8.99E-04Styrene0.16 33.73 10.32 11.18 1.18 8.25 0.97Toluene0.33 70.07 315.76 23.23 8.87 16.77 17.77 1.75 1.38 84.50 2.02Xylenes (MixedIsomers)4.85 177.92 19.04 4.18 6.21**The lead estimated provided above represent emissions at individual airports, for 2008, there is an additional 296 tons of leademitted associated with thecombustion of leaded aviation gasoline during in flight operations which is not attributed to airports.

### 2-20 2.8 Aircraft References

Cook, Rich. Memorandum entitled Guidance on Mobile Source Emi ssion Estimates in the 1996 National Toxics Inventory , to Laurel Driver and Anne Pope, U.S. EPA Office of Air Quality Planning and Standards. U.S. EPA Office of Mobile Source s. Ann Arbor, MI. June 9, 1998.

Cook, Rich. Memorandum entitled Source Identification and Base Year 1990 Emission Inventory Guidance for Mobile Source HAPs on th e OAQPS List of 40 Priority HAPs , to Laurel Driver and Anne Pope, U.S. EPA Office of Air Quality Pl anning and Standards ( OAQPS). U.S. EPA Office of Mobile Sources. Ann Arbor, MI. June 11, 1997.

Billings, Richard and Roger Chang, Eastern Research Group, Inc. Memorandum entitled Revised HAP Speciation Profiles for Commercial Aircra ft, to Laurel Driver and Rich Cook, U.S. Environmental Protection Agency. October 25, 2004.

Federal Aviation Administration. General Avia tion and Part 135 Activity Survey - Calendar Year 2008. Downloaded from the following Internet site: http://www.faa.gov/data_res earch/aviation_data_statist ics/general_aviation/.

Federal Aviation Administration. Emissions and Dispersion Modeling System (EDMS), Version 5.1 released September 2008. Downloaded from the following Internet site: http://www.faa.gov/about/office_org/headqua rters_offices/aep/models/edms_model/.

U.S. Department of Transportation. Emissions and Dispersion M odeling System, Version 5.1. Federal Aviation Administration. September 2008. Do wnloaded from the following Internet site: http://www.faa.gov/about/office_org/headqua rters_offices/aep/models/edms_model/.

U.S. Department of Transportation. Terminal Area Forecast System . Federal Aviation Administration, Aviation Policy and Plans. Down loaded from the following Internet Site: http//www.apo.data.faa.gov/.

U.S. Department of Transportation. T-100 Segmen t (All Carriers). Bureau of Transportation Statistics. Downloaded from the following Internet site: http ://transtats.bts.gov/.

U.S. Environmental Protection Agency and Federal Aviation Administration. Recommended Best Practice for Quantifying Speciat ed Organic Gas Emissions from Aircraft Equipped with Turbofan, Turbojet, and Turboprop Engines - Version 1.0 . EPA-420-R-09-901. Assessment and Standards Division, Office of Transportation a nd Air Quality, U.S. Environmental Protection Agency in collaboration with the AEE-300 - Em issions Division, Office of Environment and Energy, Federal Aviation Administration. May 2009.

U.S. Environmental Protection Agency. Lead Emissions from the Use of Leaded Aviation

Gasoline in the United States - Technical Support Document . EPA-420-R-08-020. Assessment and Standards Division, Office of Trans portation and Air Quality. October 2008.

U.S. Environmental Protection Agency. Calculating Aviation Gasoline Lead Emissions in the Draft 2008 NEI . Assessment and Standards Division, Offi ce of Transportation and Air Quality.

December 2009.

### 2-21 U.S. Environmental Protection Agency. Procedures for Emission Inve ntory Preparation, Volume

IV: Mobile Sources . EPA-450/4-81-026d (Revised). Office of Air and Radiation. Research Triangle Park, NC, and Ann Arbor, MI. 1992.

## Appendix A

Generic Aircraft Emission Factors/ Speciation Profiles

### A-1 Commercial Aircraft Emission Factors

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

THC 2.680E-03

VOC 2.934E-03

TOG 3.276E-03

NO

x 

### 9.288E-03

CO 1.119E-02

SO

x 

### 8.910E-04

PM 10 

### 5.385E-04

PM 2.5 

### 5.256E-04 Acetaldehyde 75070 CAA 1.400E-04

Acetone 67641 1.025E-05 Acetylene 74862 1.290E-04

Acrolein 107028 CAA 8.023E-05 Benzaldehyde 100527 IRIS 1.540E-05

Benzene 71432 CAA 5.507E-05 Benzo(a)anthracene 56553 1.297E-09 Benzo(a)pyrene 50328 9.621E-10 Benzo(b)fluoranthene 205992 1.892E-09 Benzo(ghi)perylene 191242 1.726E-11 Benzo(k)fluoranthene 207089 1.892E-09 1,3-Butadiene 101314 CAA 5.527E-05

1-Butene 101389 5.746E-05 Butyraldehyde 123728 3.899E-06

C14-Alkane No CAS 6.094E-06

C15-Alkane No CAS 5.799E-06

C16 Branched Alkane No CAS 4.783E-06

C18-Alkane No CAS 6.552E-08

C4-Benzene + C3-Aroald No CAS 2.149E-05

C5-Benzene+C4-Aroald No CAS 1.061E-05 Chrysene 218019 1.313E-09

Cis-2-Butene 514181 6.880E-06

Cis-2-Pentene 627203 9.042E-06 Crotonaldehyde 4170303 3.384E-05

1-Decene 872059 6.061E-06 Dibenzo(ah)anthracene 53703 2.551E-09 Dimethylnapthalenes 28804888 2.949E-06

Ethane 74840 1.707E-05 Ethylbenzene 100414 CAA 5.701E-06 Ethylene 74851 5.065E-04

Fluoranthene 206440 2.492E-09

### A-2 Commercial Aircraft Emission Factors

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO) Formaldehyde 50000 CAA 4.033E-04 Glyoxal 107222 5.950E-05 Heptene 25339564 1.435E-05

Hexadecane 544763 1.605E-06

1-Hexene 592416 2.411E-05 Indeno(1,2,3-cd)pyrene 193395 2.050E-09 Isopropylbenzene 98828 CAA 9.829E-08 Isovaleraldehyde 514863 1.048E-06

Methacrolein 78853 1.405E-05

Methanol 67561 CAA 5.913E-05 Methyl Glyoxal 78988 4.924E-05 1-Methyl Naphthalene 14120 8.092E-06 2-Methyl Naphthalene 91576 IRIS 6.749E-06 3-Methyl-1-Butene 563451 3.669E-06 4-Methyl-1-Pentene 131372 4.259E-07 2-Methyl-1-Butene 563462 4.587E-06 2-Methyl-2-Butene 513359 6.061E-06 2-Methylpentane 107835 1.337E-05 2-Methyl-1-Pentene 763291 1.114E-06 M-Ethyltoluene 620144 5.045E-06 M-Tolualdehyde 620235 9.108E-06 Naphthalene (gas phase) 91203 CAA 6.084E-06 Naphthalene (solid phase) 91203 CAA 1.260E-06 Napthalene 91203 CAA 1.772E-05

N-Decane 124185 1.048E-05

N-Dodecane 112403 1.514E-05 N-Heptadecane 629787 2.949E-07 N-Heptane 142825 2.097E-06

N-Nonane 111842 2.031E-06

N-Octane 111659 2.031E-06

1-Nonene 124118 8.059E-06

N-Pentadecane 629629 5.668E-06

N-Pentane 109660 6.487E-06 N-Propylbenzene 103651 1.736E-06

N-Tetradecane 629594 1.363E-05

N-Tridecane 629505 1.753E-05

N-Undecane 1120214 1.455E-05

Octene 111660 9.042E-06 O-Ethyltoluene 611143 2.130E-06

### A-3 Commercial Aircraft Emission Factors

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO) O-Tolualdehyde 529204 7.535E-06

1-Pentene 109671 2.542E-05 P-Ethyltoluene 622968 2.097E-06

Phenanthrene 85018 1.112E-08

Phenol 108952 CAA 2.378E-05 Propane 74986 2.555E-06 Propionaldehyde 123386 CAA 2.382E-05 Propylene 115071 1.485E-04 P-Tolualdehyde 104870 1.573E-06 Pyrene 121400 3.028E-09 Styrene 100425 CAA 1.012E-05

Toluene 108883 CAA 2.103E-05

Trans-2-Hexene 4050457 9.829E-07

Trans-2-Pentene 646048 1.176E-05 1,2,3-Trimethylbenzene 526738 3.473E-06 1,2,4-Trimethylbenzene 95636 1.147E-05 1,3,5-Trimethylbenzene 108678 1.769E-06 2,2,4-Trimethylpentane 540841 CAA 1.466E-06 Valeraldehyde 110623 8.027E-06 Xylene 1330207 CAA 1.032E-05

### A-4 Air Taxi Emission Factors - Jet

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

THC 4.37E-04

VOC 5.03E-04

TOG 5.06E-04

NO

x 

### 3.88E-04

CO 1.81E-03

SO

x 

### 8.12E-05

PM 10 

### 3.017E-04

PM 2.5 

### 3.922E-05 Acetaldehyde 75070 CAA 2.160E-05

Acetone 67641 1.583E-06 Acetylene 74862 1.992E-05

Acrolein 107028 CAA 1.238E-05

Anthracene 120127 1.331E-10 Benzaldehyde 100527 IRIS 2.377E-06

Benzene 71432 CAA 8.500E-06 Benzo(a)anthracene 56553 2.014E-11 Benzo(a)pyrene 50328 1.103E-11 Benzo(ghi)perylene 191242 1.829E-12 1,3-Butadiene 101314 CAA 8.531E-06

1-Butene 101389 8.869E-06 Butyraldehyde 123728 6.017E-07

C14-Alkane No CAS 9.405E-07

C15-Alkane No CAS 8.950E-07

C16 Branched Alkane No CAS 7.383E-07

C18-Alkane No CAS 1.011E-08

C4-Benzene + C3-Aroald No CAS 3.317E-06

C5-Benzene+C4-Aroald No CAS 1.638E-06 Chrysene 218019 1.876E-11

Cis-2-Butene 514181 1.062E-06

Cis-2-Pentene 627203 1.396E-06 Crotonaldehyde 4170303 5.224E-06

1-Decene 872059 9.355E-07 Dimethylnapthalenes 28804888 4.551E-07

Ethane 74840 2.635E-06 Ethylbenzene 100414 CAA 8.799E-07 Ethylene 74851 7.818E-05

Fluoranthene 206440 2.784E-10 Formaldehyde 50000 CAA 6.225E-05 Glyoxal 107222 9.183E-06

### A-5 Air Taxi Emission Factors - Jet

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO) Heptene 25339564 2.215E-06

Hexadecane 544763 2.478E-07

1-Hexene 592416 3.722E-06 Isopropylbenzene 98828 CAA 1.517E-08 Isovaleraldehyde 514863 1.618E-07

Methacrolein 78853 2.169E-06

Methanol 67561 CAA 9.127E-06 Methyl Glyoxal 78988 7.600E-06 1-Methyl Naphthalene 14120 1.249E-06 2-Methyl Naphthalene 91576 IRIS 1.042E-06 3-Methyl-1-Butene 563451 5.663E-07 4-Methyl-1-Pentene 131372 6.574E-08 2-Methyl-1-Butene 563462 7.079E-07 2-Methyl-2-Butene 513359 9.355E-07 2-Methylpentane 107835 2.063E-06 2-Methyl-1-Pentene 763291 1.719E-07 M-Ethyltoluene 620144 7.787E-07 M-Tolualdehyde 620235 1.406E-06 Napthalene 91203 CAA 2.736E-06

N-Decane 124185 1.618E-06

N-Dodecane 112403 2.336E-06 N-Heptadecane 629787 4.551E-08 N-Heptane 142825 3.236E-07

N-Nonane 111842 3.135E-07

N-Octane 111659 3.135E-07

1-Nonene 124118 1.244E-06

N-Pentadecane 629629 8.748E-07

N-Pentane 109660 1.001E-06 N-Propylbenzene 103651 2.680E-07

N-Tetradecane 629594 2.104E-06

N-Tridecane 629505 2.705E-06

N-Undecane 1120214 2.245E-06

Octene 111660 1.396E-06 O-Ethyltoluene 611143 3.287E-07 O-Tolualdehyde 529204 1.163E-06

1-Pentene 109671 3.924E-06 P-Ethyltoluene 622968 3.236E-07

Phenanthrene 85018 1.238E-09

Phenol 108952 CAA 3.671E-06

### A-6 Air Taxi Emission Factors - Jet

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO) Propane 74986 3.944E-07 Propionaldehyde 123386 CAA 3.676E-06 Propylene 115071 2.293E-05 P-Tolualdehyde 104870 2.427E-07 Pyrene 121400 3.401E-10 Styrene 100425 CAA 1.563E-06

Toluene 108883 CAA 3.246E-06

Trans-2-Hexene 4050457 1.517E-07

Trans-2-Pentene 646048 1.815E-06 1,2,3-Trimethylbenzene 526738 5.360E-07 1,2,4-Trimethylbenzene 95636 1.770E-06 1,3,5-Trimethylbenzene 108678 2.731E-07 2,2,4-Trimethylpentane 540841 CAA 1.915E-07 Valeraldehyde 110623 1.239E-06 Xylene 1330207 CAA 2.352E-06

### A-7 Air Taxi Emission Factors - Piston

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

THC 7.750E-05

VOC 8.484E-05

TOG 9.474E-05

NO

x 

### 7.900E-05

CO 1.407E-02

SO

x 

### 7.500E-06

PM 10 

### 3.015E-04

PM 2.5 

### 3.920E-05 Acenaphthene 83329 2.201E-07 Acenaphthylene 208968 1.242E-06 Acetaldehyde 75070 CAA 5.874E-07

Acrolein 107028 CAA 5.684E-08

Anthracene 120127 2.563E-07

Benzene 71432 CAA 3.837E-06 Benzo(a)anthracene 56553 3.015E-08 Benzo(a)pyrene 50328 3.015E-08 Benzo(b)fluoranthene 205992 3.618E-08 Benzo(ghi)perylene 191242 7.839E-08 Benzo(k)fluoranthene 207089 3.618E-08 1,3-Butadiene 101314 CAA 9.285E-07 Chrysene 218019 3.015E-08 Ethylbenzene 100414 CAA 1.393E-06

Fluoranthene 206440 2.744E-07

Fluorene 86737 4.553E-07 Formaldehyde 50000 CAA 2.548E-06 Indeno(1,2,3-cd)pyrene 193395 2.412E-08 M-Xylene and P-Xylene 108383 CAA 2.201E-07 Naphthalene (gas phase) 91203 CAA 4.327E-07 Naphthalene (solid phase) 91203 CAA 4.432E-06

N-Hexane 110543 6.632E-07 O-Xylene 95476 CAA 1.242E-06

Phenanthrene 85018 7.658E-07 Propionaldehyde 123386 CAA 5.684E-08 Pyrene 121400 3.739E-07 Styrene 100425 CAA 3.221E-07

Toluene 108883 CAA 9.853E-06 2,2,4-Trimethylpentane 540841 CAA 3.394E-08

### A-8 General Aviation Emission Factors - Jet

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

THC 3.00E-04

VOC 2.73E-04

TOG 3.06E-04

NO

x 

### 1.62E-04

CO 4.79E-03

SO

x 

### 3.68E-05

PM 10 

### 1.184E-04

PM 2.5 

### 1.539E-05 Acetaldehyde 75070 CAA 1.309E-05

Acetone 67641 9.593E-07 Acetylene 74862 1.207E-05

Acrolein 107028 CAA 7.506E-06

Anthracene 120127 5.221E-11 Benzaldehyde 100527 IRIS 1.440E-06

Benzene 71432 CAA 5.152E-06 Benzo(a)anthracene 56553 7.903E-12 Benzo(a)pyrene 50328 4.327E-12 Benzo(ghi)perylene 191242 7.178E-13 1,3-Butadiene 101314 CAA 5.170E-06

1-Butene 101389 5.376E-06 Butyraldehyde 123728 3.647E-07

C14-Alkane No CAS 5.700E-07

C15-Alkane No CAS 5.425E-07

C16 Branched Alkane No CAS 4.475E-07

C18-Alkane No CAS 6.130E-09

C4-Benzene + C3-Aroald No CAS 2.010E-06

C5-Benzene+C4-Aroald No CAS 9.930E-07 Chrysene 218019 7.359E-12

Cis-2-Butene 514181 6.436E-07

Cis-2-Pentene 627203 8.459E-07 Crotonaldehyde 4170303 3.166E-06

1-Decene 872059 5.670E-07 Dimethylnapthalenes 28804888 2.758E-07

Ethane 74840 1.597E-06 Ethylbenzene 100414 CAA 5.333E-07 Ethylene 74851 4.738E-05

Fluoranthene 206440 1.092E-10 Formaldehyde 50000 CAA 3.773E-05 Glyoxal 107222 5.566E-06

### A-9 General Aviation Emission Factors - Jet

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO) Heptene 25339564 1.342E-06

Hexadecane 544763 1.502E-07

1-Hexene 592416 2.256E-06 Isopropylbenzene 98828 CAA 9.194E-09 Isovaleraldehyde 514863 9.807E-08

Methacrolein 78853 1.315E-06

Methanol 67561 CAA 5.532E-06 Methyl Glyoxal 78988 4.606E-06 1-Methyl Naphthalene 14120 7.570E-07 2-Methyl Naphthalene 91576 IRIS 6.313E-07 3-Methyl-1-Butene 563451 3.433E-07 4-Methyl-1-Pentene 131372 3.984E-08 2-Methyl-1-Butene 563462 4.291E-07 2-Methyl-2-Butene 513359 5.670E-07 2-Methylpentane 107835 1.250E-06 2-Methyl-1-Pentene 763291 1.042E-07 M-Ethyltoluene 620144 4.720E-07 M-Tolualdehyde 620235 8.520E-07 Naphthalene (gas phase) 91203 CAA 1.674E-06 Naphthalene (solid phase) 91203 CAA 5.571E-08 Napthalene 91203 CAA 1.658E-06

N-Decane 124185 9.807E-07

N-Dodecane 112403 1.416E-06 N-Heptadecane 629787 2.758E-08 N-Heptane 142825 1.961E-07

N-Nonane 111842 1.900E-07

N-Octane 111659 1.900E-07

1-Nonene 124118 7.539E-07

N-Pentadecane 629629 5.302E-07

N-Pentane 109660 6.068E-07 N-Propylbenzene 103651 1.624E-07

N-Tetradecane 629594 1.275E-06

N-Tridecane 629505 1.640E-06

N-Undecane 1120214 1.361E-06

Octene 111660 8.459E-07 O-Ethyltoluene 611143 1.992E-07 O-Tolualdehyde 529204 7.049E-07

1-Pentene 109671 2.378E-06 P-Ethyltoluene 622968 1.961E-07

Phenanthrene 85018 4.858E-10

### A-10 General Aviation Emission Factors - Jet

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

Phenol 108952 CAA 2.225E-06 Propane 74986 2.391E-07 Propionaldehyde 123386 CAA 2.228E-06 Propylene 115071 1.390E-05 P-Tolualdehyde 104870 1.471E-07 Pyrene 121400 1.334E-10 Styrene 100425 CAA 9.470E-07

Toluene 108883 CAA 1.968E-06

Trans-2-Hexene 4050457 9.194E-08

Trans-2-Pentene 646048 1.100E-06 1,2,3-Trimethylbenzene 526738 3.249E-07 1,2,4-Trimethylbenzene 95636 1.073E-06 1,3,5-Trimethylbenzene 108678 1.655E-07 2,2,4-Trimethylpentane 540841 CAA 1.313E-07 Valeraldehyde 110623 7.509E-07 Xylene 1330207 CAA 1.612E-06

### A-11 General Aviation Emissi on Factors - Piston

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

THC 7.750E-05

VOC 7.524E-05

TOG 8.537E-05

NO

x 

### 3.250E-05

CO 6.007E-03

SO

x 

### 5.000E-06

PM 10 

### 1.184E-04

PM 2.5 

### 1.539E-05 Acenaphthene 83329 1.123E-08 Acenaphthylene 208968 6.339E-08 Acetaldehyde 75070 CAA 5.874E-07

Acrolein 107028 CAA 5.684E-08

Anthracene 120127 1.308E-08

Benzene 71432 CAA 3.837E-06 Benzo(a)anthracene 56553 1.539E-09 Benzo(a)pyrene 50328 1.539E-09 Benzo(b)fluoranthene 205992 1.846E-09 Benzo(ghi)perylene 191242 4.000E-09 Benzo(k)fluoranthene 207089 1.846E-09 1,3-Butadiene 101314 CAA 9.285E-07 Chrysene 218019 1.539E-09 Ethylbenzene 100414 CAA 1.393E-06

Fluoranthene 206440 1.400E-08

Fluorene 86737 2.323E-08 Formaldehyde 50000 CAA 2.548E-06 Indeno(1,2,3-cd)pyrene 193395 1.231E-09 M-Xylene and P-Xylene 108383 CAA 1.123E-08 Naphthalene (gas phase) 91203 CAA 4.327E-07 Naphthalene (solid phase) 91203 CAA 2.262E-07

N-Hexane 110543 6.632E-07 O-Xylene 95476 CAA 6.339E-08

Phenanthrene 85018 3.908E-08 Propionaldehyde 123386 CAA 5.684E-08 Pyrene 121400 1.908E-08 Styrene 100425 CAA 3.221E-07

Toluene 108883 CAA 9.853E-06 2,2,4-Trimethylpentane 540841 CAA 3.394E-08

### A-12 Military Emission Factor

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

THC 6.170E-04

VOC 6.815E-04

TOG 7.597E-04

NO

x 

### 7.900E-05

CO 1.407E-02

SO

x 

### 7.500E-06

PM 10 

### 3.017E-04

PM 2.5 

### 3.922E-05 Acetaldehyde 75070 CAA 3.245E-05

Acetone 67641 2.378E-06 Acetylene 74862 2.993E-05

Acrolein 107028 CAA 1.861E-05 Benzaldehyde 100527 IRIS 3.571E-06

Benzene 71432 CAA 1.277E-05 1,3-Butadiene 101314 CAA 1.282E-05

1-Butene 101389 1.333E-05 Butyraldehyde 123728 9.041E-07

C14-Alkane No CAS 1.413E-06

C15-Alkane No CAS 1.345E-06

C16 Branched Alkane No CAS 1.109E-06

C18-Alkane No CAS 1.519E-08

C4-Benzene + C3-Aroald No CAS 4.984E-06

C5-Benzene+C4-Aroald No CAS 2.461E-06

Cis-2-Butene 514181 1.595E-06

Cis-2-Pentene 627203 2.097E-06 Crotonaldehyde 4170303 7.848E-06

1-Decene 872059 1.405E-06 Dimethylnapthalenes 28804888 6.837E-07

Ethane 74840 3.958E-06 Ethylbenzene 100414 CAA 1.322E-06 Ethylene 74851 1.175E-04 Formaldehyde 50000 CAA 9.352E-05 Glyoxal 107222 1.380E-05 Heptene 25339564 3.328E-06

Hexadecane 544763 3.723E-07

1-Hexene 592416 5.591E-06 Isopropylbenzene 98828 CAA 2.279E-08 Isovaleraldehyde 514863 2.431E-07

Methacrolein 78853 3.259E-06

### A-13 Military Emission Factor

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO)

Methanol 67561 CAA 1.371E-05 Methyl Glyoxal 78988 1.142E-05 1-Methyl Naphthalene 14120 1.876E-06 2-Methyl Naphthalene 91576 IRIS 1.565E-06 3-Methyl-1-Butene 563451 8.509E-07 4-Methyl-1-Pentene 131372 9.876E-08 2-Methyl-1-Butene 563462 1.064E-06 2-Methyl-2-Butene 513359 1.405E-06 2-Methylpentane 107835 3.100E-06 2-Methyl-1-Pentene 763291 2.583E-07 M-Ethyltoluene 620144 1.170E-06 M-Tolualdehyde 620235 2.112E-06 Napthalene 91203 CAA 4.110E-06

N-Decane 124185 2.431E-06

N-Dodecane 112403 3.510E-06 N-Heptadecane 629787 6.837E-08 N-Heptane 142825 4.862E-07

N-Nonane 111842 4.710E-07

N-Octane 111659 4.710E-07

1-Nonene 124118 1.869E-06

N-Pentadecane 629629 1.314E-06

N-Pentane 109660 1.504E-06 N-Propylbenzene 103651 4.026E-07

N-Tetradecane 629594 3.160E-06

N-Tridecane 629505 4.064E-06

N-Undecane 1120214 3.373E-06

Octene 111660 2.097E-06 O-Ethyltoluene 611143 4.938E-07 O-Tolualdehyde 529204 1.747E-06

1-Pentene 109671 5.895E-06 P-Ethyltoluene 622968 4.862E-07

Phenol 108952 CAA 5.515E-06 Propane 74986 5.926E-07 Propionaldehyde 123386 CAA 5.523E-06 Propylene 115071 3.445E-05 P-Tolualdehyde 104870 3.647E-07 Styrene 100425 CAA 2.348E-06

Toluene 108883 CAA 4.877E-06

Trans-2-Hexene 4050457 2.279E-07

Trans-2-Pentene 646048 2.727E-06

### A-14 Military Emission Factor

Pollutant CAS No. CAA

"187"

or IRIS

HAP? Emission

Factors (tons/LTO) 1,2,3-Trimethylbenzene 526738 8.053E-07 1,2,4-Trimethylbenzene 95636 2.659E-06 1,3,5-Trimethylbenzene 108678 4.102E-07 Valeraldehyde 110623 1.861E-06

## Appendix B

Calculating Piston-Engine Aircraft Ai rport Inventories for Lead for the 2008 National Emissions Inventory

### B-1 Calculating Piston-Engine Aircraft Airport Inventories for Lead for the 2008 National Emissions Inventory

December 2010

Section 1. Introduction

The main purpose of this doc ument is to describe the methods the Environmental Protection Agency (EPA) used to calculate airport lead (Pb) inventories for the 2008 National Emissions Inventory (NEI). 1 

### These methods focus on the development of approaches to estimate piston-e ngine aircraft activity at airports in the U.S. since the activity of this fleet is reported to the Fe deral Aviation Administra tion (FAA) as general aviation (GA) or air taxi (AT) activity – categ ories that also include jet-engine aircraft activity. The methods described here reflect improvements to th e methods used in developing the airport-specific pi ston-engine aircraft inventori es in the 2002 NEI and the

2005 NEI.

Background information regarding the use of leaded aviation gasoline (avgas) in piston-engine powered aircraft is available in other documents. 2,3 

### Briefly, most pistonengine aircraft ope rations fall into the ca tegories of either GA or AT. Aircraft used in

GA and AT activities include a diverse set of aircraft types and en gine models and are

used in a wide vari ety of applications. 4 

### Lead emissions associated with GA and AT

aircraft stem from the use of one hundred octane low lead (100LL) avgas. The lead is

added to the fuel in the form of tetraethyl lead (T EL). This lead additive helps boost fuel octane, prevent engine knock, and prevent valve seat recession and subsequent loss of compression for engines wit hout hardened valves. Today, 100LL is the most commonly available type of aviation gasoline in the United States. 5 

### Lead is not added to jet fuel that is used in commercial aircraft, most militar y aircraft, or other tu rbine-engine powered

aircraft. Lead emissions from the use of leaded avgas comprised 45% of the national inventory for emissions of lead in 2002. 6

1 In this document ‘2008 NEI’ refers to 200 8 NEI version 1 (January 2011), available at http://www.epa.gov/ttn/chief/net/2008inventory.html

2 EPA (2007) Review of the National Ambient Air Qu ality Standards for Lead: Policy Assessment of Scientific and Technical Information. OAQPS Staff Paper. EPA-452/R-07-013 November 2007. pp 2-8 and

2-9.

3 FAA William J. Hughes Technical Center http://www.tc.faa.gov /act4/insidethefenc e/2006/0609_06_AvFuels.htm

4 Commercial aircraft include those used for scheduled service transporting passen gers, freight, or both. Air taxis fly scheduled and for-hire service carrying passengers, frei ght or both, but they usually are smaller aircraft than those operated by commercial air carrier s. General aviation includes most other aircraft (fixed and rotary wing) used for personal transportation, business, instructional flying, and aerial application.

5 ChevronTexaco (2005) Aviation Fu els Technical Re view. FTR-3. http://www.chevronglobalaviation.co m/docs/aviation_tech_review.pdf

6 U.S. Environmental Protection Agency (2008) EPA’ s Report on the Environment EPA/600/R-07/045F.

Available at: http://www.epa.gov/roe

### B-2 This document is or ganized into eight sections. Se ction 2 describes the data we

use to calculate the national inventory for the amount of lead re leased to the air from the combustion of leaded avgas. S ection 3 describes the landing and takeoff data we use to calculate airport-specific i nventories for lead. Section 4 describes how we estimate landing and takeoff data for the airport facilities that do not report it to the FAA. Section 5 describes the estimate of landing and takeoff activity occurring at heliports in the

U.S. Section 6 describes the me thods used to calculate the ai rport-specific inventories for

lead. Section 7 describes data that would be needed to improve the estimates of airportspecific inventories for lead and Section 8 desc ribes the estimates of the amount of lead emitted in-flight that are in the 2008 NEI.

In this document, units of tons (i.e., U.S. short tons) are used when discussing the national and airport-specific lead inventory in order to be consistent with the manner in which the NEI reports inventorie s for lead and other pollutants. The unit of grams is used in describing the concentration of lead in avgas and in describing emission factors. Conversion factors are provided for clarity.

Section 2. Calculating the National Avgas Lead Inventory



### Because lead is a persistent pollutant and accumulates in th e environment, we include all lead emissions from piston-engi ne aircraft in the NEI – emissions occurring during the landing and take-off cycle at airports as well as emissions occurring at

altitude. 7 

### To calculate the national avgas lead inventory, we use information provided by the U.S. Department of Tr ansportation’s (DOT’s) Federa l Aviation Administration (FAA) regarding the volume of leaded avgas consumed in the U.S. in 2008. 8 

### The U.S. Department of Energy’s (DOE’s) Energy In formation Administration (EIA) provides information regarding the volume of leaded avgas produced in a given year. EPA has historically used the DOE EIA avgas fuel volume produced to calculate national lead inventories from the consumption of leaded avgas. However, since EPA uses DOT airport activity and aircraft data, we are us ing the DOT fuel volume data in the 2008 NEI to calculate the national lead inventory in order to use a consistent data source. In this document, when we refer to avgas fuel volume data it is data supplied by DOT, except

where noted.

As demonstrated in the equation below, to calculate the annual emission of lead from the consumption of leaded avgas, we multiply the volume of avgas used by the

concentration of lead in the a vgas, minus the small amount of lead that is retained in the engine, engine oil and/or exhaust system. Th e volume of avgas used in the U.S. in 2008

7 U.S. EPA, 2006. Air Quality: Criteria for Lead: 2006; EPA/600/R-5/144aF; U.S. Government Printing Office, Washington, DC, October, 2006.

8 U.S. Department of Tr ansportation Federal Aviation Administration Aviation Policy and Plans. FAA Aerospace Forecast Fiscal Years 2010-2030. p.99. Available at: http://www.faa.gov/data_research/a viation/aerospace_forecasts/2010- 2030/media/2010%20Forecast%20Doc.pdf This documen t provides historical data for 2000-2008 as well

as forecast data.

### B-3 was 248,100,000 gallons. 9 

### The concentration of lead in avgas ([Pb] in the equation below) can be one of four levels (ranging fro m 0.14 to 1.12 grams of lead per liter) as specified by the American Society for Tes ting and Materials (ASTM). By far the most common avgas supplied is “100 Low L ead” or 100LL. 10,11 

### The maximum lead concentration specified by AS TM for 100LL is 0.56 grams pe r liter or 2. 12 grams per gallon. 12 

### A fraction of lead is retained in the engine, engine oil and/or exhaust system which we currently estimate at 5%. 13



### For the 2008 NEI, the national estimate of lead emissions from the consumption of avgas was 551 tons (see equation below).

(248,100,000 gal)(2 .12 g Pb/gal)(0.95)

= 

### 551 tons Pb 907,180 g/ton

As described above, DOE’s EIA also provides estimates of the annual volume of leaded avgas produced in a given year. For 2008, the volum e of avgas produced in the U.S. was 5,603 thousand ba rrels or 235,326,000 gallons. 14 

### Consumption of this volume of avgas equates to a national lead emission s estimate for this source of 522 short tons.

Section 3. Landing and Takeoff Data Sources and Uses



### Airport-specific inventories require in formation regarding landing and takeoff (LTO) activity by aircraft type. 15 

### According to FAA records, there are approximately 20,000 airport facilities in the U.S., the vast majority of which are expected to have activity by piston-engine aircraft that operate on leaded avgas. Of these facilities, EPA’s NEI has in the past, reported emissions of lead (and other criteria pollutants and

9 U.S. Department of Transporta tion Federal Aviation Administration Aviation Policy and Plans. FAA Aerospace Forecast Fiscal Years 2010-2030. p.99. Available at: http://www.faa.gov/data_research/a viation/aerospace_forecasts/2010- 2030/media/2010%20Forecast%20Doc.pdf This documen t provides historical data for 2000-2008 as well

as forecast data.

10

ChevronTexaco (2005) Aviation Fuels Technical Review. FTR-3.

11 The 2008 General Aviation Sta tistical Databook & Industry Ou tlook report by General Aviation

Manufactures Associ ation (GAMA) found that over 90% of avgas is 100LL.

12

ASTM International (2005) Annu al Book of ASTM Standards S ection 5: Petroleum Products, Lubricants, and Fossil Fuels Volume 05.01 Petrol eum Products and Lubricants (I): D 56 – D 3230.

13 The information used to develop this estimate is from the following references : (a) Todd L. Petersen, Petersen Aviation, Inc, Aviation Oil Lead Content Analysis , Report # EPA 1-2008, January 2, 2008, available at William J. Hughes Technical Center Technical Reference and Research Library at http://actlibrary.tc.fa a.gov/ and (b) E-mail from Theo Rindlisbach er of Switzerland Federal Office of Civil Aviation to Bryan Manning of U.S. EPA, regard ing lead retained in engine, September 28, 2007.

14

DOE Energy Information Administration. Fuel production volume data obtained from http://tonto.eia.doe.gov/dnav/pet/hist/mgaupus1A.htm accessed November 2006.

15 An aircraft operation is defined as any landing or takeoff event, therefore, to calculate LTOs, operations are divided by two. Most data sour ces from FAA report aircraft activity in numbers of operations which, for the purposes of calculating lead emissions using the method described in th is document, need to be

converted to LTO events.

### B-4 hazardous air pollutants) at 3,410 airports. 16 

### While the 3,410 airport facilities are among

the most active in the U.S ., they comprise on ly a small fraction of the total airport facilities where leaded avgas is used.

FAA’s Office of Air Traffic provides a co mplete listing of operational airport facilities in the National Airspace System Resources (NASR) data base. The electronic NASR data report, referred to here as the 50 10 airport data report, can be generated from

the NASR database and is available for download from the FAA website. 17 

### This report is updated every 56 days. EPA ob tains airport information (i ncluding operations) for a

subset of the facilities in the NASR databa se from FAA’s Terminal Area Forecast (TAF) database that is prepared by FAA’s Office of Aviation Policy and Plans. 18 

### The TAF database currently includes information for ai rports in FAA’s National Plan of Integrated Airport Systems (NPIAS), whic h identifies airports that are significant to national air transportation. Approximately 500 of the airports that are in the TAF database have

either an FAA air traffic control tower or an FAA contract tower where controllers count operations. The operations data from the cont rol towers is reported to The Operations Network (OPSNET) 19 

### which is publically available in the Air Traffic Activity System (ATADS) database. 20 

### The operations data for the towered airports that is reported in OPSNET and ATADS is then reported to the TAF database. The operations data for the airports in the TAF database that do not ha ve control towers represent estimates. 21 

### The operations supplied in the 5010 airport data report for facilities not repo rted in the TAF may be self-reported by airport operators through da ta collection accomplished by airport inspectors who work for the State Aviation Agency, or operations data can be obtained through other means. 22



### The 5010 airport data report supplies the date that the associated operations data

represents. 23 

### Because airports that are not in the TAF database submit data voluntarily to FAA for the 5010 data report, many of the air ports have operations data that represent data for years earlier than 2008. Nationally, GA and AT pist on-engine operations have

decreased in recent years, 24 

### therefore EPA did not use operations data from years prior to 2008 as it is reported. Instead , EPA multiplied the older GA and AT piston- engine data (Section 6 describes the method EPA used to calculate the number of piston-engine

16

These 3,410 facilities are the facilit ies for which the FAA’s Terminal Area Forecast (TAF) database provides information regarding aircraft activity. Th e TAF database is prepared by FAA’s Office of Aviation Policy and Plans and includes information for th e airports in FAA’s Nati onal Plan of Integrated Airport Systems (NPIAS). One of the goals of the NPIAS is to identify airports that are significant to national air transportation.

17 http://www.faa.gov/airports_airtraffic/ai rports/airport_safety/airportdata_5010/

18 http://aspm.faa.gov/main/taf.asp

19 http://aspm.faa.gov/opsnet/sys/

20 http://aspm.faa.gov/opsnet/sys/Airport.asp

21 FAA’s Terminal Area Forecast Summary (Fis cal Years 2009 – 2030), Appendix A (page 28) http://www.faa.gov/data_r esearch/aviation/taf_reports/media/ TAF%20Summary%20Report%20FY%2020 09%20-%202030.pdf

22

In the absence of updated information from States, local authorities or Tribes, we are using the LTO data provided in the FAA database.

23 The 12-month ending date on which annual operations data in the report is based.

24 http://www.faa.gov/data_r esearch/aviation_data_stat istics/general_aviation/

### B-5 operations from total GA and AT activity data) by sc aling factors that we re calculated by dividing the 2008 national amount of avgas pr oduced by the national amount of avgas produced in the year the ope rations data represents. 25 

### A table with the scaling factors is provided in Appendix A. The national volu me of avgas produced data comes from the DOE, EIA website and is av ailable for 1981 – 2009. 26 

### For operations data older than 1981, EPA divided the 2008 national amount of avgas produced by the average of the national amount of avgas produced from 19 81 – 1989. Jet engines do not use avgas, therefore EPA did not apply scaling factors to the turbine operations for data from years prior to 2008.

EPA also obtains operations data from the T-100 segment data from the Bureau of Transportation Statistics (BTS). The aircraft in the T-100 data are ma tched to aircraft in the FAA’s Emission and Dispersion Modeling System (EDMS) using the crosswalk table developed for earlier versions of the NEI. Generally the T-100 data covers commercial air carrier operations, but some AT activitie s are included in the data set that would

double count with th e TAF data at the sa me airport. To correct for possible double counting, first the AT LTOs included in the T-100 data were compiled using the aircraft type data included in the ai rcraft make/models crosswalk. 27 

### The resulting aggregated LTOs were compared with the reported TAF LTOs for airports where there were overlaps. The T-100 AT LTOs were then subt racted from the TAF AT data to ensure
that double counting was minimized. Note that if the T-100 AT value was larger than the TAF value, the TAF value was set to zero to eliminate the possibility of negative LTOs in

the dataset.

The 2008 draft NEI was developed using the January 15, 2009 version of the 5010 airport data report. In that version of th e report there were 19,925 airport facilities

in the U.S. that had submitt ed data to the F AA. Among these 19,9 25 facilities, 99 facilities were not relevant for the purposes of estimating lead emissions because they were either listed as closed (85) or they were balloonports (14). 28 

### Therefore, lead

inventories were needed for 19,826 facilities. In the Janua ry 15, 2009 version of the 5010 airport data report th ere were 5,654 airport facilities for which operations data were provided (many of which are facilities in FAA’s TAF database). 29 

### There were 14,172 facilities in the 5010 airport data report for which there were no operations data. 30 

### As a

25 The FAA General Aviation and Air Taxi (Part 135) Activity Surveys (source ofnational level pistonengine operations data) are only av ailable annually, starti ng in 1999. Because ther e are airports with operations data older than 1999, EPA used avgas product supplied data as a surrogate for piston-engine operations to estimate the change in piston-engine activity over the last three decades.

26 http://tonto.eia.doe.gov/dnav/pet/hist /LeafHandler.ashx?n=PET&s=mgaupus1&f=A. DOT recently changed the way they estimate fuel consumption data, so while EPA used DOT data to determine the 2008 national avgas lead inventory, for the purpose of calculating these scali ng factors EPA used DOE’s data in

order to have historical fuel data that is calculated in a consistent manner.

27 The T-100 data does not specify that the operations data is ai r taxi in nature; however, in discussions with FAA, EPA determined that these flig hts are air taxi in nature and has assigned them in the 2008 NEI as

such.

28 Balloon craft do not use avgas

29

Either Commuter, GA I tinerant, GA Local, or Air Taxi operations data, as these operations can be performed by piston- engine aircraft.

30

No Commuter, GA Itinerant, GA Local, or Air Taxi operations data.

### B-6 part of the review process fo r the draft 2008 NEI, EPA receiv ed updated airport data from

states and also looked at more recent versions of the 5010 airport data report to update the status of airports, so the number of airports for which EPA estimated activity is slightly lower in the 2008 NEI than in the draft 2008 NEI. The following section of this

document describes the method EPA used to estimate operations for the 14,132 airport facilities in the 2008 NEI that do not have reported activity data.

As described in Section 1, most piston-engine aircraft fall into the categories of either GA or AT. Some GA and AT activity is conducted by turboprop and turbojet aircraft which do not used leaded avgas. There are no national databases that provide airport-specific LTO activity da ta for piston-engine aircraft separately from turbojet and turboprop aircraft. The databases described above report total GA and AT activity conducted by both piston-engine and jet-engine aircraft. Part (a) in Section 6 describes how we estimate piston-engine LTOs at airports in the 2008 NEI.

Section 4. Estimating LTOs at the 14,132 Airport Facilities with No LTO Data

FAA has used regression mo dels to estimate operations at facilities where operations data are not available. 31,32 

### In this work and othe r work, FAA identified characteristics of small towered airports fo r which there were statistically significant relationships with operati ons at these airports. 33 

### Regression models based on the airport

characteristics were then used to estimate general aviation operations for a set of nontowered airports. The airport characteristics identified by FAA and used to estimate general aviation operations at small airports include: the nu mber of aircraft based at a facility (termed ‘based aircraft ’), population in the vi cinity of the airpor t, airport regional prominence, per capita income, region, and th e presence of certificated flight schools.

In the 2000 report titled ‘Model for Estimating Genera l Aviation Operations at Non-towered Airports,’ a model of GA annual activity was developed using information from small towered airports to explain GA activ ity at towered and non-towered airports. The model explained GA activity at the towered airports well (R 2 

### of 0.75) but produced higher estimates than state-supp lied estimates for non-towered airports. 34



### The relevant data available in the 5010 airport data report for the purposes of estimating airport operations include: facility type (airport, balloonport, seaplane base, gliderport, heliport, stolport, 35 

### ultralight); number of GA aircraft based at each airport by

31 Federal Aviation Administration, Office of Aviation Policy and Plans, Statistics and Forecast Branch. July 2001. Model for Estimating General Aviation Op erations at Non-towered Airports Using Towered

and Non-towered Ai rport Data. Prepared by GRA, Inc.

32

Mark Hoekstra, “Model for Estimating General Avia tion Operations at Non-Towered Airports” prepared for FAA Office of Aviation Policy and Plans, April 2000.

33 GRA, Inc. “Review of TAF Methods,” Final Report, prepared for FAA Office of Aviation Policy and Plans under Work Order 45, Contract No. DTFA01-93-C-00066, February 25, 1998.

34

The mean absolute difference between the model operations estimate and the state operations estimate was 16,940 operations.

35 Stolport is an airport designed with STOL (Short Take-Off and Landing) opera tions in mind, normally having a short single runway.

### B-7 type (glider, helicopter, jet engine, military, multi-engine, single engine, ultralight); operations data (air taxi , commercial, commuter, GA iti nerant, GA local, military) 36 

### ; and operations date (12-month ending date on which annual operations data is based). Census data was also merged with the 5010 ai rport data report to give population data for each airport’s county.

Using the FAA work referenced above, we explored relationships among the airport data variables that best predicted ai rcraft activity (LTOs). We found that based aircraft was a highly significan t and positive regressor to LTOs. Table 1 shows that for facilities that did not have LTO data in the January 15, 2009 version of the 5010 airport data report, 7,856 had based airc raft data while 6,316 did not have based aircraft data. 37, 38 

### Therefore, as described below, LTO estimat es were derived usi ng different methods depending on data availability.

Table 1: Contingency ta ble describing the number s of airport facilities that have or do

not have LTO data and/or based aircraft data for airport faci lities in the Ja nuary 15, 2009 version of the 5010 airport data report



## HAVE LTO DATA

YES NO

YES 4,872 7,856 12,728

NO 782 6,316 7,098

5,654 14,172 19,826

36

As explained in footnote 15, an aircraft operation is defined as a ny landing or takeoff event, therefore, to calculate LTOs, operations are divided by two. The 5 010 airport data report fr om FAA reports aircraft activity in numbers of operations which, for the purposes of calcula ting Pb emissions using the method described in the TSD, are converted to LTO events.

37 As described in Section 3, the number of facilities with no LTO data changed slightly from the draft 2008 NEI to the 2008 NEI. In the 2008 NEI, of the facilities that did not have reported activity data, 7,837 facilities reported based aircraft data and 6,295 did not report based aircraft data.

38

These numbers include data for the following types of facilities: ai rports, balloonports, seaplane bases, gliderports, heliports, stol ports, and ultralights. 

## HAVE
BASED

AIRCRAFT

DATA

### B-8 (a) Estimating LTOs at Facilities with Ba sed Aircraft Data, but No LTO Data:

There are 6,414 facilities in the 2008 NE I (not including heliports) for which the 5010 airport data report supplies the number of based aircraft 39 

### but not activity data to which the regression equation (based aircra ft vs. LTOs) could be applied. Using the 4,872 airports for which both LTO and aircra ft data is known, th e initial relationship

found between based aircraft and LTOs was:

Equation 1:

LTOs = 2494 + 208*aircraft R 2 

### = 0.55

The FAA models found population to be another significant regressor. We used the population of the county in which the airport is located as the population variable. Adding county population to the model gave the following relationship:

Equation 2:

LTOs = 2204 + 194*aircraft + 0.0038*county population R 2 

### = 0.56

EPA received numerous comments to th e docket on its Advance Notice of Proposed Rulemaking on Lead Emissions from Piston-Engine Aircraft Using Leaded

Aviation Gasoline 40 

### indicating that aviation in Alaska is differ ent than it is in the continental U.S. Commenters pointed out that in Alaska, 82% of communities are not accessible by road and rely on air transpor t for life sustaining goods and services. 41



### Commenters also noted that Alaskans travel by air eight times more often per capita than

those in the continental U.S. For those reas ons, we added a dummy variable in equation 3 to identify whether or not an airport is located in Alas ka. Because the relationship between based aircraft and LTOs is likely di fferent for Alaskan airports than it is for airports that aren’t in Alaska, we also added an interaction term to equation 3 (interaction of an airport being in Alaska and its sum of based aircraft).

Equation 3:

LTOs = 1937 + 205*aircraft + 0.00 38*county population + 566*Alaska – 108*(AlaskaXaircraft)

R 2 

### = 0.58

After analyzing the data and plot for th e data underlying equation 3, we found many airport facilities identified as commerci al airports for which based aircraft was extremely low (i.e., less than 10), yet LTO s were quite high (i.e., anywhere from 100,000

39

Based aircraft for this purpose was limited to single- and multi-engine ai rcraft, helicopters, and ultralights since these aircraft types can use leaded avgas.

40

U.S. Environmental Protection Agency (2010) A dvance Notice of Proposed Rulemaking on Lead Emissions From Piston-Engine Ai rcraft Using Leaded Aviation Ga soline. 75 FR 22440 (April 28, 2010).

41 Comments to the docket on EPA’s Advance Noti ce of Proposed Rulemaking on Lead Emissions from Piston-Engine Airc raft Using Leaded Aviation Gasoline from the Alaska Air Carriers Association (dated 18 June 2010; comment number OAR-2007-0294-0323.1) an d Alaska Governor Parnell (dated 25 August 2010; comment number OAR-2007-0294-0403.1).

### B-9 to more than 200,000 LTOs/year). 42 

### These facilities were re moved from the regression analysis. Additionally, for reasons describe d below, heliports were also removed from the regression. The resu lting relationship was:

Equation 4: LTOs = 1293 + 203*aircraft + 0.0019*county population - 473*Alaska –

144*(AlaskaXa ircraft) R 2 

### = 0.65

When equation 4 was applied to the 6,414 airport facil ities that report based

aircraft data but not LTO ac tivity, the resulting sum of LTO s was almost 15 million.

EPA estimates that the number of LTOs at the airports that do not report activity data should approximate the number of LTOs from th e bottom of the distribution of the set of airports that report ac tivity data to the 5010 airport data report but th at are not in the TAF database. The average number of LTOs per year from airpor ts in the bottom 30% of the set of airports that report activi ty data to the 5010 airport da ta report but th at are not in the TAF database is ~63 LTOs/year. Multiply ing 63 by the number of airports that do not report activity data equals 549,050 LTOs. 43 

### Therefore, EPA us ed equation 4 to generate the distribution of LTOs at the individu al airports that report based aircraft data but not activity data and then applied a scali ng factor of 0.0356 to those LTOs to obtain the LTOs that are reported in the 2008 NEI. 44 

### The sum of the LTOs from this set of airports plus the sum of the LTOs at the airports that do not report either based aircraft or activity data (described below in section (b) ) sum to 549,050 LTOs. These LTOs are all assigned to the GA, piston-engine category since they are assigned to smaller general aviation airports that are assu med to have little to no air taxi or jet aircraft activity.

Equation 4 and the scaling factor were used to estimate LTO activity for the 2008 NEI at airport facilitie s that report based aircraft da ta but not activity data.

(b) Estimating LTOs at Facilities with Neith er Based-Aircraft Data nor LTO Data:

There are 2,260 facilities (not including heliports) for which the 5010 airport data report supplies neither the numb er of based aircraft nor acti vity data. In the absence of

data to establish a relationshi p to airport activity , we assign a defaul t value of LTOs to the GA, piston-engine category for each of these facilities.

42 From FAA’s website, “Addresses for Comme rcial Service Airports”, available at: http://www.faa.gov/airports _airtraffic/airports/planni ng_capacity/passenger_allcar go_stats/addresses/media
/commercial_service_ai rports_addresses.xls

43 This rounded number is calculated by multiplying 63 .298 LTOs/year by 8,674, which is the number of airports that don’t report activity data (6,414 don’ t report activity data and 2,260 facilities don’t report activity or based aircraft data).

44

The scaling factor was calc ulated by dividing 528,710 LTOs by 14,862,767 LTOS; the 528,710 LTOs are equal to 549,050 LTOs minus 20,340 LTOs (20,340 LTOs represent the sum of LTOs assigned to the 2,260 facilities that don’t report either activity data or base d aircraft data - the derivation of LTO estimates for

these facilities is described in Section 4 (b) ). The 14,862,767 LTOs are the sum of LTOs that result from applying equation 4 to the 6,414 facilities wi th based aircraft data but no activity data.

### B-10 The default value was determined by evaluating GA LTOs that are reported at the set of 2,471 facilities th at report activity data to the 5010 airport data report but that are not in the TAF set of airports. The average number of LTOs reported to the bottom ten percent of these facilities (when sorted by to tal GA LTOs) was 9. These facilities are assumed to most closely approximate the set of 2,260 facilities that do not report any based aircraft or LTO data; therefore, we assigned 9 LTO s to the GA, piston-engine category for these airport facilities for pur poses of developing inventory estimates.

Section 5. Calculating LTOs at Heliports:

There were 5,559 heliport facilities in the January 15, 2009 FAA 5010 data report that were operational. Of thos e, only 92 (or 2%) reported LTO data, and of those, only 31 reported both based aircra ft and LTO data. Because of the limited information regarding activity at heliports, some munici palities have hired contractors to survey activity in their local area. 45, 46



### The summary statistics for LTO data provided at the 92 operational heliports is presented in Table 2. These facilities report a wide range in activity from 3 LTOs/year to more than 18,000 LTOs/year. Some facilities clearly have significant helicopter traffic (i.e., thousands of LTOs/year) which is supported by the contractor su mmaries of heliport activity in the Washington Metropolitan area. Th e little data available to us suggests that the median helicopter activity is less than 200 LTOs/year. In the absence of more

information on which to base estimates of LTO activity, we assigned 141 LTOs (the median of the reported heliport LTOs) to the GA category at all of the heliports which do not report LTO data. The piston-engine fracti on developed in Section 6 is applied to the 141 LTOs resulting in 51 LT Os assigned to the GA, piston-engine category and 90 assigned to the GA, turbine-engine category. Th is is an area of significant uncertainty in the inventory and one for which EPA is seeking information from local agencies.

Table 2: Heliport LTO Data for those Reporting LTO Da ta in the Janua ry 15, 2009 Version of the 5010 Airport Data Report
18,250 Maximum LTOs

3 Minimum LTOs 1,123 Average LTOs

141 Median LTOs

50 Mode LTOs

45 Executive Summary: Region al Helicopter System Plan, Metropo litan Washington Area, prepared by Edwards and Kelcey for the Metropolitan Washington Counc il of Governments, 2005.

46

Alaska Aviation Emission Inventory, prepared by Sierra Research, Inc. for Western Regional Air Partnership, 2005.

### B-11 Section 6. Methodology for Estimating Airport

­ Specific Lead Emissions



### In 2008, EPA developed a method to calcula te lead emissions at airports where piston-engine powered aircraft operate. 47 

### This method brings le ad inventories into alignment with the manner in which other cr iteria pollutants emitte d by aircraft are

calculated. This method is described here wi th changes that were made from previous methods (i.e., the method us ed to develop the 2002 invent ory) and applied in developing airport lead inventories for the 2008 NEI. In this section we first present the equation used to calculate lead emitted during the LTO cycle then we de scribe each of the components of th e input data: we describe how we calculate piston-engine LTOs from data available in FAA databases, we describe the derivation of the em ission factor for the amount of lead emitted during the LTO cycle, and we describe the estimate of the amount of lead retained in the engi ne and oil that we do not include in the amount of lead

released to the air.

Historically, where aircraft specific activ ity data are available (such as T-100), aircraft gaseous and particulate matter (PM) emissions have been calculated through the

FAA’s EDMS. 48 

### This modeling system was designed to develop emission inventories for the purpose of assessing potential air quali ty impacts of airport operations and proposed airport development pr ojects. However, EDMS has a limited number of pistonengine aircraft in its aircraft data and is cu rrently not set up to ca lculate metal emissions and thus, it is not a readily available tool fo r determining airport lead inventories related to aircraft operations. In developing this approach to determine pi ston-engine aircraft lead emissions, EPA relied upon the ba sic methodology employed in EDMS. This requires as input the ac tivity of piston-eng ine aircraft at a facility , fuel consumption rates by these aircraft during the various mode s of the LTO cycle and time in each mode (taxi/idle-out, takeoff, climb-ou t, approach, and taxi/idle-in), the concentration of lead in

the fuel and the retention of lead in the engine and oil. The equation used to calculate airport-specific lead emissions during the LTO cycle is below, follow ed by a description of each of the input parameters.

LTO Pb (tons) = (pisto n-engine LTO)(avgas Pb g/LTO)(1-Pb retention) 907,180 g/ton

(a) Calculating Piston-engine LTO:

Piston-engine LTOs are used to calculate emissions of le ad that are assigned to the airport facility where the aircraft operations occur. An aircraft operation is defined as any landing or takeoff event, ther efore, to calculate LTOs, ope rations are divided by two. Most data sources from FAA report aircraft activity in numbers of operations which, for the purposes of calculating lead emissions, need to be converted to LTO events. We

47

U.S. EPA (2008) Lead Emissions from the Use of Leaded Aviation Gasolin e in the United States, Technical Support Document. EPA420-R-08-020. Available at: www.epa.gov/otaq/aviation.htm.

48 EDMS available from http://www.faa.gov/ about/office_org/headquarters_o ffices/aep/models/edms_model/

### B-12 describe here the method used to estimate th e fraction of GA and AT LTOs at an airport that are conducted by piston-engine aircraft. These frac tions are calculated separately (one fraction for GA and one for AT). Th ese fractions are multiplied by total LTOs reported separately for GA and AT and then summed to arrive at the total LTOs conducted by piston-engine aircraft at an airport.

One use of the 2008 NEI is to identify s ources of lead, including airports, that have inventories of 0.50 tons per year or m ore for the purposes of identifying locations where lead monitoring may be required to evaluate compliance with the National Ambient Air Quality Standard for Lead. To calculate the most airport-specific inventories for airports that ma y potentially exceed this inve ntory threshold, we used a more airport-specific surrogat e for this subset of airports than the remainder of the airports where we applied national default averages described below.

We used the fraction of based aircraft at an airport that are single- or multi-engine

to calculate the number of GA LTOs at an airport that were conducted by piston-engine aircraft. The data regarding th e population of based aircraft at an airport is available for a subset of airports in the FAA 5010 master records data report described in Section 3. For example, if an airport reports 150 single-engine aircraft, 20 multi-engine aircraft and a

total of 180 aircraft based at that facility, then th e fraction of based aircraft we would use as a surrogate for piston-engine aircraft is 94% ((150+20)/1 80). We then multiply the total GA LTOs for that facility by 0.94 to calculate piston-engine LTOs.

We evaluated this surrogat e by comparing the results of using it with pistonengine aircraft operations reported for airpor ts that supply this information in master plans, airport layout plans, noise abatement studies and/or land use compatibility plans. We could rarely find data fro m the same year for comparison purposes; however, for the majority of airports, based aircraft and actu al observed piston-engine aircraft activity agreed within ten percent. 49



### For the majority of airports in the 2008 NE I we used national average fractions of GA and AT LTOs conducted by piston-engine aircraft that were derived using FAA’s

General Aviation and Part 135 50 

### Activity Surveys – CY 2008 (GAATA). 51 

### Table 2.4 in the 2008 GAATA Survey re ports that approxim ately sixty-si x percent (66%) of all GA and AT LTOs are from piston-engine aircraft which use avgas, a nd about thirty-four

49 Documents used to evaluate the use of based aircraft in clude the following:
Airport Master Plan Update Prescott Municipal Ai rport (Ernest A Love Field) (2009) Available at: www.cityof prescott .net/_d/amp_tablecontents.pdf Gillespie field Airport Layout Plan Upda te Narrative Report (2005) Available at: www.co.sandiego.ca.us/dpw/ airport s/powerpoints/pdalp.pdf Land Use Compatibility Pl an for the Grand Forks Internatio nal Airport (2006) Available at: www.gfk airport .com/authority/pdf/ land

_ use .pdf McClellan-Palomar Land Use Compatibility Plan (Amended March 4, 2010) Available at:

www.ci.oceanside.ca.us/.../ McClellan

- Palomar _ALUCP_03-4-10_amendment.pdf

50

On-demand (air taxi) and commuter operations not cove red by Part 121

51 The FAA GAATA is a database collected from surveys of pilots flying aircraft used for general aviation and air taxi activity. For more informa tion on the 2008 GAATA, see Appendix A at http://www.faa.gov/data_rese arch/aviation_data_statistic s/general_aviation/CY2008/

### B-13 percent (34%) are turboprop and turbojet powered which use jet fuel, such as Jet A. The

LTO data in Table 2.4 in the 2008 GAATA Survey does not distinguish LTOs as GA or AT, and thus does not allow us derive separate piston activity fractions for GA and AT.

We are using the number of hours flown by piston versus turboprop or turbojet aircraft (reported in Table 1.4 in the 2008 GAATA Survey) to allow us to make separate estimates of the fraction of GA activity conduc ted by piston aircraft and the fraction of AT activity conducted by piston aircraft. We ch ose to use the fraction of hours flown by piston-engine aircraft as a surrogate to calculate the fraction of LTOs flown by piston aircraft since the overall (i.e., for GA and AT combined) piston percent of hours flown (66.4%) is very close to the percent of LTOs that are piston (65.7%). Table 1.4 of the 2008 GAATA presents the total hours flow n by aircraft type an d separates GA from AT. Seventy-three percent (73%) of all GA hours fl own are by piston-engine aircraft while twenty-eight percent (28%) of all GA hours flown are by turboprop and turbojet powered

aircraft. 52 

### Twenty-three percent (23% ) of all AT hours flow n are by piston-engine aircraft while seventy-seven percent (77%) of all AT hours flown are by turboprop and turbojet powered aircraft. Approximately 5,000 of the total 20,000 airport facilities in the U.S. are heliports at which only helicopters (rotocraft) operate. Therefore, EPA also calculated the percent of rotocraft hours flown that are conduc ted by piston-engine aircraft. Thirty-six percent (36%) of all GA rotocraft hours flown are by piston-engine rotocraft while sixty-four percent (64%) of al l GA rotocraft hours flown are by turboprop and turbojet powered rotocraft. Two percent (2%) of all AT rotocraft hours flown are by piston-engine rotocraft while ninety-eight pe rcent (98%) of all AT rotocraft hours flown are by turboprop and turbojet po wered rotocraft. Table 3 iden tifies the piston and turbine

fractions that were used in th e absence of airport-specific information to calculate pistonengine operations at airports and heliports in the 2008 NEI.

Table 3: Piston and Turb ine Activity Fractions used in the 2008 NEI 

## Airports Heliports

GA AT GA AT

Piston

Powered 72.5% 23.1% 36.1% 2%

Turbine

Powered 27.5% 76.9% 63.9% 98%

52

Numbers in the text may not add to 100% due to r ounding; the percentages in Table 3 are the values we

used to calculate the 2008 NEI.

### B-14 (b) Calculating the Piston-engine Aircraft Emission Factor: Grams of Lead Emitted per

LTO:

Piston-engine aircraft can have either one or two engines. EDMS version 5.0.2 contains information on the amount of avga s used per LTO for so me single and twinengine aircraft. The proportion of piston-engineLTOs conducted by single- versus twinengine aircraft was taken from the FAA’s GAATA Survey for 2008 (90% of LTOs are conducted by aircraft having one engine and 10% of LTOs by aircraft having two engines). 53 

### Since twin-engine aircraft have higher fuel consump tion rates than those with single engines, a weighted-average LTO fuel usage rate was calculated to apply to the population of piston-engine aircraft as a w hole. For the single-engine aircraft, the average amount of fuel consumed per LTO was determined from the six types of single piston-engine aircra ft within EDMS. 54 

### This was calculated by averaging the singleengine EDMS outputs for fuel consumed per LTO using the EDMS scenario property of ICAO/USEPA Default - Times in Mode (TIM), with a 16 minute taxi-in/taxi-out time according to EPA’s Procedures for Emission Inventory Preparation, Volume IV: Mobile

Sources , 1992. 55 

### This gives a value of 16.96 pounds of fuel per LTO (lbs/LTO). The average single-engine fuel consumption rate was divided by the average density of 100LL avgas, 6 pounds per gall on (lbs/gal), producing an average fuel usage rate for single-engine piston aircraft of 2.83 gallon s per LTO (gal/LTO). This same calculation was performed for the two twin-engine pist on aircraft within EDMS, producing an average LTO fuel usage rate for twin-e ngine piston aircraft of 9.12 gal/LTO.

Using these single- and twin-engine piston aircraft fuel consumption rates, a weighted average fuel usage rate per LTO wa s computed by multiplying the average fuel usage rate for single-engine aircraft (2.83 gal/LTO) by the fleet percentage of singleengine aircraft LTOs (90%). Next, the twin-engi ne piston aircraft average fuel usage rate (9.12 gal/LTO) was mu ltiplied by the fleet percentage of twin-engine aircraft LTOs (10%). By summing the results of the single - and twin-engine aircra ft usage rates, the overall weighted-average fuel usage rate per LTO of 3.46 gal/LTO was obtained.

To calculate the emission factor, the concen tration of lead in fuel is multiplied by the fuel consumption per LTO. The maximum lead concentr ation specified by ASTM for 100LL is 0.56 grams per liter or 2.12 grams pe r gallon. This amount of lead is normally added to assure that the required lean and rich mixture knock values are achieved. Multiplying this lead concentr ation in avgas by the weighted average fuel usage rate produces an overall average valu e of 7.34 grams oflead per LTO (g Pb/LTO) for pistonengines: 3.46 gal/LTO x 2.12 g Pb/gal = 7.34 g Pb/LTO.

53 The LTOs from the categories of 1-e ngine fixed wing pi ston, piston rotocraft, experimental total, and light sport were summed to determine the total nu mber of single-engine piston aircraft LTOs.

54

EPA understands that EDMS 5.0.2 ha s a limited list of pi ston-engines, but these are currently the best

data available.

55 U.S. EPA, Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources , EPA-450/4- 81026d (Revised), 1992.

### B-15 (c) Retention of Lead in Engine and Oil (1-Pb Retention):

Data collected from aircraft piston-engines operating on leaded avgas suggests

that about 5% of the lead fr om the fuel is retained in the engine and engine oil. 56 

### Thus

the emitted fraction is 0.95. This information is used in calculating airport-specific lead

inventories and will be used to develop future natio nal estimates of lead emitted from the consumption of leaded avgas.

Applying these parameters in the equation above yields the following equation:

Pb(tons) = (piston-engine LTO) (7.34 g Pb/LTO) (0.95) 907,180 g/ton

which simplifies to:

Pb(tons) = (piston-engine LTO) (7.7 X 10 -6 

### )

Where piston-engine LTO 57 

### = (GA LTO x 0.725) + (AT LTO x 0.231)

(d) Estimating Lead Emissions from Piston-Engine Helicopters:

The emission factor for helicopters (g Pb/LTO) was determined in the same manner as described above for piston-engine fixed-wing aircraft. The concentration of lead in avgas (2.12 g/gal) was multiplied by the weighted aver age fuel usage rate for four types of Robinson helicopter engines. 58 

### This produced an overall average emission factor of 6.60 grams of lead per LTO (g Pb/ LTO) for piston-engine powered helicopters.

There are no national databases that prov ide heliport-specifi c LTO activity data for piston-engine powered helicopters se parately from turbine-engine powered helicopters. The 2008 FAA GA and Part 135 Activity (GAATA) Survey reports that approximately 36% of all GA he licopter hours flown are by pi ston-engine aircraft which use avgas, and about 64% are by turbine-engine powered which use jet fuel (which does

56 The information used to develop this estimate is from the following references : (a) Todd L. Petersen, Petersen Aviation, Inc, Aviation Oil Lead Content Analysis , Report # EPA 1-2008, January 2, 2008, available at William J. Hughes Technical Center Technical Reference and Research Library at http://actlibrary.tc.fa a.gov/ and (b) E-mail from Theo Rindlisbacher of Switzerland Federal Office of Civil Aviation to Bryan Manning of U.S. EPA, regardin g lead retained in engine, September 28, 2007.

57 This equation for piston-engine LTOs only applie s to non-heliport facilities. See the text immediately below for equations for calculating piston-engi ne LTOs and Pb emis sions at heliports.

58 This was done using the followi ng 4 engine types in EDMS 5.1: Robinson R22 IO-320-D1AD; Robinson R22 IO-360-B; Robinson R22 O- 320; Robinson R22 TSIO-360C. The fuel consumption rates were: Robinson R22 IO-320-D1AD – 5.546 g Pb/LTO; Robinson R22 IO-360-B – 5.973 g Pb/LTO; Robinson R22 O-320 – 6.276 g Pb/LTO; Robinson R22 TSIO-360C – 8.604 g Pb/LTO.

### B-16 not contain lead). 59 

### The 2008 FAA GAATA Su rvey reports that approximately 2% of all AT helicopter hours flown are by piston-engin e aircraft which use avgas, and about 98% are by turbine-engine powered rotocraft. We expect the fraction of helicopter activity conducted by piston -engines to vary by heliport with some facilities havi ng no pistonengine powered helicopter activity and some hosting mainly or only piston-engine powered helicopters. However, in the abse nce of heliport-specifi c data, the national

default estimates of 36% fo r GA and 2% for AT from th e GAATA Survey were used. Therefore, to calculate piston-engine airc raft LTO as input for this equation, the helicopter GA LTOs were mul tiplied by 0.36 and he licopter AT LTOs were multiplied by

0.02.

Lead emitted at the heliport facility wa s calculated for the 2008 NEI using either the LTO data provided in FAA databases or the es timate LTO activity in the following equation (i.e., 141 LTOs):

Pb(tons) = (piston-engine helic opter LTO) (6.60 g Pb/LTO) (0.95)

907,180 g/ton

which simplifies to:

Pb(tons) = (piston-engine helicopter LTO) (6.9 X 10 -6 

### )

Where piston-engine helicopter LTO = (Helicopter GA LTO x 0.36) + (Helicopter AT LTO x 0.02)

Section 7. Improving Airport

­ specific Lead Emissions Estimates

There are refinements to the methods described here that would improve airportspecific inventories, most of which involve acquiring airport- and aircraft-specific input

data. The following information describes data inputs that could be used to generate airport lead inventories tailored to specific airports or otherwise improve the estimates using currently available data . State and local authorities might have, or be able to collect, better information for so me of these key data inputs.

State and local agencies might have acce ss to airport-specific data that would improve the national estimates of lead emissions per LTO . These improvements largely involve replacing national average or default values with airport-specific data on the activity of piston-engine aircraft. Three key data inputs are:

59 The FAA GAATA is a database collected from surveys of pilots flying aircraft used for general aviation and air taxi activity. For more information on the GAATA, see Appendix A at http://www.faa.gov/data_statistics/avia tion_data_statistics/general_aviation/

### B-17 1) Airport-specific LTO activity for piston-powered aircraft, including the fraction of piston-engine activity c onducted by single- versus twin-engine aircraft. Some airport facilities collect this informati on and states may use these data to calculate airport-specific lead inventories. The activity data should be current and updated on a regular schedule so that the data represents the inventory year as closely as possible. 2) The time spent in each mode of the LTO cycle. EPA uses the EDMS scenario property of ICAO/USEPA Defa ult - Times in Mode, wi th a 16 mi nute taxiin/taxi-out time according to EPA’s Procedures for Emission Inventory Preparation, Volume IV: Mobile Source s, 1992. While some local authorities

have confirmed that these are the relevant times in mode at thei r airports for piston aircraft, the applicability of these times in mode will vary by airport. EPA has learned that one of the important factors in piston aircraft operation that is currently not included in the time in mode or emissions estimates is the time and fuel consumption during the pre-flight run-u p checks conducted by piston-engine aircraft prior to takeoff. 3) Other data inputs for the airport-specif ic lead inventory calculation for which

states or local authoritie s may provide airport-specific information include the concentration of lead in the avgas supplied at an airport, and the fraction of lead

in fuel that is retained in the engine and oil, and aircraft-specific fuel consumption rates by the piston-engine ai rcraft in specific modes of operation.

The accuracy of the based aircraft data on which equation 4 is modeled can be improved. FAA recogniz es the need to improve the inte grity of the 5010 data report based-aircraft counts for all of the GA airports and reliever airports in the NPIAS and is currently in the process of improving the data collection and submission methods to accomplish this task. 60



### Section 8. Lead emitted in flight (i.e., outside the LTO cycle):



### Lead emissions, especially those at al titude, undergo dispersion and eventually deposit to surfaces, and lead deposited to soil and water can remain available for uptake by plants, animals and humans for long periods of time. Because lead is a persistent pollutant, we are including all lead emissions – at airports and in-flight – in the NEI. 61



### For inventory purposes, lead emitted outside the LTO cycl e occurs during aircraft cruise mode and portions of the climb-out and approach modes above the mixing height (typically 3,000 ft 62 

### ). This part of an aircraft operation emits lead at various altitudes as well as close to and away from airports. B ecause the precise area of lead emission and deposition is not known for these flights, EP A is using a simplistic approach to allocate

60 National Based Aircraft Inventory Program: http://www.basedaircraft.com/pub lic/FrequentlyAsk edQuestions.aspx, accessed 2/17/2009

61 U.S. EPA, 2006. Air Quality: Criteria for Lead: 2006; EPA/600/R-5/144aF; U.S. Government Printing Office, Washington, DC, October, 2006.

62

According to EPA’s Procedurees for Emission Inventory Preparation, Volume IV: Mobile Sources, 1992

.

### B-18 these emissions for the purposes of the 2008 NEI. A brief explanation of the nature of GA flights is provided here for context regarding emissions of lead in-flight.

FAA categorizes GA flights as either lo cal area or itinerant operations and this distinction plays a role in the area over which lead is emitted. Local operations are those activities performed by aircraft operating in the local traffic pa ttern or within sight of the airport, aircraft executing simulated instrumen t approaches or low passes at the airport, and/or aircraft operating to or from the ai rport in a designated practice area located

within a 20-mile radius of th e airport. Local operations are common for GA aircraft. This includes applications such as recreational, proficiency and instructional flying as well as many common general aerial support task s. Emissions during lo cal flying are more likely to influence air and soil co ncentrations of lead in the vi cinity of the airport because they occur near the airport, often at altitudes below the mixing height.

Itinerant operations are all operations othe r than those described above as local operations. An itinerant aircraft operation us ually is one in which the aircraft departs from one airport and lands at a different air port. Depending on air ti me and distance, an itinerant flight is much more likely to i nvolve departing the local flying area of the originating airport and climbing to altitude s above the mixing heig ht. It is reasonable then, to generally expect that lead emi tted outside the LTO cy cle during itinerant operations, in contrast with lo cal operations, will be more wi dely dispersed and at greater distances from the airport.

The portion of the national avgas lead emitted in flight (i.e., outside the LTO cycle) is calculated by subtracting the sum of airport facility lead inventories from the national avgas lead inventory. Even th ough FAA collects and reports information regarding the fraction of GA operations that are local and itinerant, there is no practical method to assign in-flight lead emissions to small geographic areas such as airports or

census tracts. And similar data is not availabl e for AT operations, a portion of which are conducted by piston-engine aircraft. Sinc e the average duration of a piston-engine aircraft flight is approximately an hour, an itinerant flight can traverse county lines. Therefore, given the current data available, the best approach is to assign the out-of-LTO cycle lead to the state where the flight originated.

In the 2008 NEI EPA allocated lead emissions that are calculated as being outside the LTO cycle to states based on the state-specific fraction ofnational GA and AT pistonengine LTO activity. The state-specific fr actions were calculate d by multiplying the percent of GA and AT piston-eng ine LTO activity in each state by 296 tons, which is the amount of lead we currently estimate is emitted outside of the LTO cycle nationwide. Table 4 presents the total GA and AT piston- engine LTOs by state, the state-specific faction of national GA and AT piston-engine LTO activity, and the out-of-LTO lead emissions assigned to each state.

### B-19 Table 4: Out-of-LTO Lead Emissions by State

STATE Total GA
and AT

Piston

LTOs Percent of

National GA

and AT Piston LTOs (by state) Out of LTO

Pb emissions (tons)

A K 660,133 2.0% 5.86
AL 671,026 2.0% 5.96
AR 638,875 1.9% 5.68
AZ 1,430,302 4.3% 12.71
CA 3,881,357 11.6% 34.48
CO 780,426 2.3% 6.93
CT 226,807 0.7% 2.01
DC 28,833 0.1% 0.26
DE 84,617 0.3% 0.75
FL 2,751,015 8.3% 24.44
GA 750,876 2.3% 6.67
HI 138,432 0.4% 1.23
IA 281,961 0.8% 2.50
ID 430,812 1.3% 3.83
IL 920,908 2.8% 8.18
IN 566,583 1.7% 5.03
KS 459,720 1.4% 4.08
KY 280,378 0.8% 2.49
LA 622,011 1.9% 5.53
MA 714,159 2.1% 6.34
MD 436,861 1.3% 3.88
ME 228,302 0.7% 2.03
MI 880,818 2.6% 7.82
MN 647,876 1.9% 5.76
MO 389,551 1.2% 3.46
MS 461,383 1.4% 4.10
MT 270,311 0.8% 2.40
NC 743,004 2.2% 6.60
ND 214,139 0.6% 1.90
NE 221,681 0.7% 1.97
NH 173,355 0.5% 1.54
NJ 466,961 1.4% 4.15
NM 309,657 0.9% 2.75
NV 298,712 0.9% 2.65
NY 999,738 3.0% 8.88
OH 1,180,583 3.5% 10.49
OK 575,402 1.7% 5.11
OR 596,730 1.8% 5.30
PA 954,839 2.9% 8.48

### B-20 PR 80,728 0.2% 0.72
RI 45,348 0.1% 0.40
SC 506,650 1.5% 4.50
SD 228,198 0.7% 2.03
TN 535,913 1.6% 4.76
TX 2,422,722 7.3% 21.52
UT 299,471 0.9% 2.66
VA 502,559 1.5% 4.46
VI 25,763 0.1% 0.23
VT 88,318 0.3% 0.78
WA 1,189,142 3.6% 10.56
WI 778,320 2.3% 6.91
WV 143,393 0.4% 1.27
WY 106,190 0.3% 0.94

For additional information or if you have ques tions regarding the methods described in this document, please contact Meredith Pedde (pedde.meredith@epa.gov) or Marion Hoyer (hoyer.marion@epa.gov ).

### B-21 Supplemental Table 1

Table A-1: Scaling factors

Year U.S. Product Supplied

of Aviation Gasoline (Thousand Barrels) 63 

### Ratio of

2008 to

Year X

Before
1981 64 

### 0.57

1981 11,147 0.50

1982 9,307 0.60

1983 9,444 0.59

1984 8,692 0.64

1985 9,969 0.56

1986 11,673 0.48

1987 9,041 0.62

1988 9,705 0.58

1989 9,427 0.59

1990 8,910 0.63

1991 8,265 0.68

1992 8,133 0.69

1993 7,606 0.74

1994 7,555 0.74

1995 7,841 0.71

1996 7,400 0.76

1997 7,864 0.71

1998 7,032 0.80

1999 7,760 0.72

2000 7,188 0.78

2001 6,921 0.81

2002 6,682 0.84

2003 5,987 0.94

2004 6,189 0.91

2005 7,006 0.80

2006 6,626 0.85

2007 6,258 0.90

2008 5,603 1.00

63 Data from the Energy Information Administration’ s (EIA’s) table, “U.S. Pr oduct Supplied of Aviation Gasoline (Thousand Barrels).” Available at: http://tonto.eia.doe .gov/dnav/pet/hist/LeafHandler .ashx?n=PET&s=mgaupus1&f=A Accessed August 25, 2010.

64

EIA does not have data for volumes of avgas produ ct supplied for years earlie r than 1981. To calculate the scaling factor to use for activity data from years before 1981, we used the r atio of 2008 avgas volume product supplied to the average avgas volume supplied from 1981 to 1989.

### 1 of 11 

# Appendix A

‐ 4

List of St. Louis County and St. Louis City Nonroad Emissions by SCC

### 2 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis County 2260001010 201.59
St. Louis County 2260001020 -
St. Louis County 2260001030 280.60
St. Louis County 2260001060 45.48
St. Louis County 2260002006 75.73
St. Louis County 2260002009 2.77
St. Louis County 2260002021 3.34
St. Louis County 2260002027 0.03
St. Louis County 2260002039 192.25
St. Louis County 2260002054 0.68
St. Louis County 2260003030 1.12
St. Louis County 2260003040 0.09
St. Louis County 2260004015 11.16
St. Louis County 2260004016 110.40
St. Louis County 2260004020 146.27
St. Louis County 2260004021 2,070.88
St. Louis County 2260004025 191.31
St. Louis County 2260004026 1,139.14
St. Louis County 2260004030 128.59
St. Louis County 2260004031 1,279.60
St. Louis County 2260004035 147.00
St. Louis County 2260004036 747.30
St. Louis County 2260004071 0.46
St. Louis County 2260005035 0.07
St. Louis County 2260006005 29.35
St. Louis County 2260006010 193.41
St. Louis County 2260006015 0.08
St. Louis County 2260006035 1.28
St. Louis County 2260007005 7.68
St. Louis County 2265001010 85.85
St. Louis County 2265001030 885.66
St. Louis County 2265001050 942.36
St. Louis County 2265001060 55.59
St. Louis County 2265002003 43.36
St. Louis County 2265002006 0.38
St. Louis County 2265002009 105.79
St. Louis County 2265002015 76.49
St. Louis County 2265002021 185.89
St. Louis County 2265002024 68.91
St. Louis County 2265002027 3.51
St. Louis County 2265002030 130.92
St. Louis County 2265002033 56.94
St. Louis County 2265002039 299.14
St. Louis County 2265002042 194.85
St. Louis County 2265002045 7.18

### 3 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis County 2265002054 19.22
St. Louis County 2265002057 9.27
St. Louis County 2265002060 19.45
St. Louis County 2265002066 100.33
St. Louis County 2265002072 53.81
St. Louis County 2265002078 29.74
St. Louis County 2265002081 8.90
St. Louis County 2265003010 118.36
St. Louis County 2265003020 253.53
St. Louis County 2265003030 77.92
St. Louis County 2265003040 188.58
St. Louis County 2265003050 8.50
St. Louis County 2265003060 4.43
St. Louis County 2265003070 13.89
St. Louis County 2265004010 3,203.78
St. Louis County 2265004011 4,790.28
St. Louis County 2265004015 269.26
St. Louis County 2265004016 2,783.47
St. Louis County 2265004025 17.54
St. Louis County 2265004026 106.24
St. Louis County 2265004030 33.52
St. Louis County 2265004031 3,522.30
St. Louis County 2265004035 384.09
St. Louis County 2265004036 1,952.52
St. Louis County 2265004040 522.88
St. Louis County 2265004041 448.08
St. Louis County 2265004046 639.08
St. Louis County 2265004051 323.11
St. Louis County 2265004055 6,970.00
St. Louis County 2265004056 6,088.28
St. Louis County 2265004066 762.57
St. Louis County 2265004071 19,082.16
St. Louis County 2265004075 304.00
St. Louis County 2265004076 821.05
St. Louis County 2265005010 0.25
St. Louis County 2265005015 0.54
St. Louis County 2265005020 0.00
St. Louis County 2265005025 0.36
St. Louis County 2265005030 0.24
St. Louis County 2265005035 2.48
St. Louis County 2265005040 7.00
St. Louis County 2265005045 0.57
St. Louis County 2265005055 1.08
St. Louis County 2265005060 0.68
St. Louis County 2265006005 9,140.97

### 4 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis County 2265006010 1,856.31
St. Louis County 2265006015 809.73
St. Louis County 2265006025 2,066.08
St. Louis County 2265006030 3,894.54
St. Louis County 2265006035 158.28
St. Louis County 2265007010 15.73
St. Louis County 2265007015 0.13
St. Louis County 2265008005 76.64
St. Louis County 2265010010 33.50
St. Louis County 2267001060 0.56
St. Louis County 2267002003 1.67
St. Louis County 2267002015 2.52
St. Louis County 2267002021 0.48
St. Louis County 2267002024 0.28
St. Louis County 2267002030 5.19
St. Louis County 2267002033 1.92
St. Louis County 2267002039 3.86
St. Louis County 2267002045 1.97
St. Louis County 2267002054 0.33
St. Louis County 2267002057 3.43
St. Louis County 2267002060 8.06
St. Louis County 2267002066 0.82
St. Louis County 2267002072 7.20
St. Louis County 2267002081 2.99
St. Louis County 2267003010 39.88
St. Louis County 2267003020 3,400.08
St. Louis County 2267003030 22.91
St. Louis County 2267003040 7.49
St. Louis County 2267003050 2.14
St. Louis County 2267003070 12.77
St. Louis County 2267004066 63.21
St. Louis County 2267005055 0.00
St. Louis County 2267005060 0.00
St. Louis County 2267006005 130.87
St. Louis County 2267006010 29.26
St. Louis County 2267006015 34.31
St. Louis County 2267006025 61.57
St. Louis County 2267006030 0.84
St. Louis County 2267006035 0.51
St. Louis County 2267008005 20.76
St. Louis County 2268002081 0.12
St. Louis County 2268003020 242.20
St. Louis County 2268003030 0.26
St. Louis County 2268003040 0.18
St. Louis County 2268003060 0.43

### 5 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis County 2268003070 0.94
St. Louis County 2268005055 0.00
St. Louis County 2268005060 0.03
St. Louis County 2268006005 39.53
St. Louis County 2268006010 1.96
St. Louis County 2268006015 2.65
St. Louis County 2268006020 18.62
St. Louis County 2268006035 -
St. Louis County 2268010010 2.04
St. Louis County 2270001060 1.62
St. Louis County 2270002003 14.60
St. Louis County 2270002006 0.05
St. Louis County 2270002009 0.78
St. Louis County 2270002015 43.32
St. Louis County 2270002018 39.51
St. Louis County 2270002021 2.77
St. Louis County 2270002024 2.21
St. Louis County 2270002027 5.68
St. Louis County 2270002030 27.41
St. Louis County 2270002033 17.40
St. Louis County 2270002036 119.52
St. Louis County 2270002039 2.07
St. Louis County 2270002042 0.87
St. Louis County 2270002045 21.91
St. Louis County 2270002048 26.57
St. Louis County 2270002051 99.30
St. Louis County 2270002054 5.27
St. Louis County 2270002057 69.69
St. Louis County 2270002060 166.51
St. Louis County 2270002066 252.07
St. Louis County 2270002069 140.57
St. Louis County 2270002072 219.31
St. Louis County 2270002075 20.22
St. Louis County 2270002078 0.66
St. Louis County 2270002081 20.70
St. Louis County 2270003010 10.87
St. Louis County 2270003020 67.13
St. Louis County 2270003030 15.90
St. Louis County 2270003040 17.36
St. Louis County 2270003050 1.88
St. Louis County 2270003060 68.10
St. Louis County 2270003070 24.84
St. Louis County 2270004031 0.01
St. Louis County 2270004036 1.36
St. Louis County 2270004046 49.81

### 6 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis County 2270004056 10.48
St. Louis County 2270004066 57.34
St. Louis County 2270004071 4.94
St. Louis County 2270004076 0.20
St. Louis County 2270005010 0.00
St. Louis County 2270005015 12.01
St. Louis County 2270005020 0.90
St. Louis County 2270005025 0.01
St. Louis County 2270005030 0.00
St. Louis County 2270005035 0.09
St. Louis County 2270005040 0.00
St. Louis County 2270005045 0.10
St. Louis County 2270005055 0.25
St. Louis County 2270005060 0.12
St. Louis County 2270006005 91.88
St. Louis County 2270006010 21.71
St. Louis County 2270006015 47.20
St. Louis County 2270006020 -
St. Louis County 2270006025 72.41
St. Louis County 2270006030 2.74
St. Louis County 2270006035 2.06
St. Louis County 2270007010 -
St. Louis County 2270007015 1.56
St. Louis County 2270008005 85.78
St. Louis County 2270009010 -
St. Louis County 2270010010 0.95
St. Louis County 2282005010 562.87
St. Louis County 2282005015 241.18
St. Louis County 2282010005 386.17
St. Louis County 2282020005 3.66
St. Louis County 2282020010 0.04
St. Louis County 2285002015 2.33
St. Louis County 2285004015 4.47
St. Louis County 2285006015 0.03
St. Louis County Total 89,513.99
St. Louis City 2260001010 -
St. Louis City 2260001020 -
St. Louis City 2260001030 -
St. Louis City 2260001060 -
St. Louis City 2260002006 -
St. Louis City 2260002009 -
St. Louis City 2260002021 -
St. Louis City 2260002027 -
St. Louis City 2260002039 -
St. Louis City 2260002054 -

### 7 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis City 2260003030 0.50
St. Louis City 2260003040 0.04
St. Louis City 2260004015 4.55
St. Louis City 2260004016 5.92
St. Louis City 2260004020 59.63
St. Louis City 2260004021 111.05
St. Louis City 2260004025 78.00
St. Louis City 2260004026 61.08
St. Louis City 2260004030 52.43
St. Louis City 2260004031 68.62
St. Louis City 2260004035 59.93
St. Louis City 2260004036 40.07
St. Louis City 2260004071 0.02
St. Louis City 2260005035 -
St. Louis City 2260006005 10.22
St. Louis City 2260006010 67.33
St. Louis City 2260006015 0.03
St. Louis City 2260006035 0.45
St. Louis City 2260007005 -
St. Louis City 2265001010 -
St. Louis City 2265001030 -
St. Louis City 2265001050 118.00
St. Louis City 2265001060 -
St. Louis City 2265002003 -
St. Louis City 2265002006 -
St. Louis City 2265002009 -
St. Louis City 2265002015 -
St. Louis City 2265002021 -
St. Louis City 2265002024 -
St. Louis City 2265002027 -
St. Louis City 2265002030 -
St. Louis City 2265002033 -
St. Louis City 2265002039 -
St. Louis City 2265002042 -
St. Louis City 2265002045 -
St. Louis City 2265002054 -
St. Louis City 2265002057 -
St. Louis City 2265002060 -
St. Louis City 2265002066 -
St. Louis City 2265002072 -
St. Louis City 2265002078 -
St. Louis City 2265002081 -
St. Louis City 2265003010 52.70
St. Louis City 2265003020 112.89
St. Louis City 2265003030 34.70

### 8 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis City 2265003040 83.97
St. Louis City 2265003050 3.79
St. Louis City 2265003060 1.52
St. Louis City 2265003070 6.18
St. Louis City 2265004010 1,308.59
St. Louis City 2265004011 257.34
St. Louis City 2265004015 109.98
St. Louis City 2265004016 149.53
St. Louis City 2265004025 7.17
St. Louis City 2265004026 5.71
St. Louis City 2265004030 13.69
St. Louis City 2265004031 189.22
St. Louis City 2265004035 156.74
St. Louis City 2265004036 104.80
St. Louis City 2265004040 213.57
St. Louis City 2265004041 24.07
St. Louis City 2265004046 34.33
St. Louis City 2265004051 17.36
St. Louis City 2265004055 2,846.91
St. Louis City 2265004056 327.07
St. Louis City 2265004066 40.97
St. Louis City 2265004071 1,025.13
St. Louis City 2265004075 124.17
St. Louis City 2265004076 44.11
St. Louis City 2265005010 -
St. Louis City 2265005015 -
St. Louis City 2265005020 -
St. Louis City 2265005025 -
St. Louis City 2265005030 -
St. Louis City 2265005035 -
St. Louis City 2265005040 -
St. Louis City 2265005045 -
St. Louis City 2265005055 -
St. Louis City 2265005060 -
St. Louis City 2265006005 3,186.44
St. Louis City 2265006010 647.09
St. Louis City 2265006015 282.26
St. Louis City 2265006025 720.21
St. Louis City 2265006030 1,357.59
St. Louis City 2265006035 55.18
St. Louis City 2265007010 -
St. Louis City 2265007015 -
St. Louis City 2265008005 -
St. Louis City 2265010010 -
St. Louis City 2267001060 -

### 9 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis City 2267002003 -
St. Louis City 2267002015 -
St. Louis City 2267002021 -
St. Louis City 2267002024 -
St. Louis City 2267002030 -
St. Louis City 2267002033 -
St. Louis City 2267002039 -
St. Louis City 2267002045 -
St. Louis City 2267002054 -
St. Louis City 2267002057 -
St. Louis City 2267002060 -
St. Louis City 2267002066 -
St. Louis City 2267002072 -
St. Louis City 2267002081 -
St. Louis City 2267003010 17.73
St. Louis City 2267003020 1,511.71
St. Louis City 2267003030 10.19
St. Louis City 2267003040 3.33
St. Louis City 2267003050 0.95
St. Louis City 2267003070 5.68
St. Louis City 2267004066 3.39
St. Louis City 2267005055 -
St. Louis City 2267005060 -
St. Louis City 2267006005 45.56
St. Louis City 2267006010 10.19
St. Louis City 2267006015 11.94
St. Louis City 2267006025 21.43
St. Louis City 2267006030 0.29
St. Louis City 2267006035 0.18
St. Louis City 2267008005 -
St. Louis City 2268002081 -
St. Louis City 2268003020 107.69
St. Louis City 2268003030 0.12
St. Louis City 2268003040 0.08
St. Louis City 2268003060 0.15
St. Louis City 2268003070 0.42
St. Louis City 2268005055 -
St. Louis City 2268005060 -
St. Louis City 2268006005 13.76
St. Louis City 2268006010 0.68
St. Louis City 2268006015 0.92
St. Louis City 2268006020 6.48
St. Louis City 2268006035 -
St. Louis City 2268010010 -
St. Louis City 2270001060 -

### 10 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis City 2270002003 -
St. Louis City 2270002006 -
St. Louis City 2270002009 -
St. Louis City 2270002015 -
St. Louis City 2270002018 -
St. Louis City 2270002021 -
St. Louis City 2270002024 -
St. Louis City 2270002027 -
St. Louis City 2270002030 -
St. Louis City 2270002033 -
St. Louis City 2270002036 -
St. Louis City 2270002039 -
St. Louis City 2270002042 -
St. Louis City 2270002045 -
St. Louis City 2270002048 -
St. Louis City 2270002051 -
St. Louis City 2270002054 -
St. Louis City 2270002057 -
St. Louis City 2270002060 -
St. Louis City 2270002066 -
St. Louis City 2270002069 -
St. Louis City 2270002072 -
St. Louis City 2270002075 -
St. Louis City 2270002078 -
St. Louis City 2270002081 -
St. Louis City 2270003010 4.83
St. Louis City 2270003020 29.84
St. Louis City 2270003030 7.07
St. Louis City 2270003040 7.72
St. Louis City 2270003050 0.83
St. Louis City 2270003060 23.30
St. Louis City 2270003070 11.05
St. Louis City 2270004031 0.00
St. Louis City 2270004036 0.07
St. Louis City 2270004046 2.67
St. Louis City 2270004056 0.56
St. Louis City 2270004066 3.07
St. Louis City 2270004071 0.26
St. Louis City 2270004076 0.01
St. Louis City 2270005010 -
St. Louis City 2270005015 -
St. Louis City 2270005020 -
St. Louis City 2270005025 -
St. Louis City 2270005030 -
St. Louis City 2270005035 -

### 11 of 11 Area SCC 2008 CO Emissions (tons/year)
St. Louis City 2270005040 -
St. Louis City 2270005045 -
St. Louis City 2270005055 -
St. Louis City 2270005060 -
St. Louis City 2270006005 31.98
St. Louis City 2270006010 7.56
St. Louis City 2270006015 16.43
St. Louis City 2270006020 -
St. Louis City 2270006025 25.21
St. Louis City 2270006030 0.95
St. Louis City 2270006035 0.72
St. Louis City 2270007010 -
St. Louis City 2270007015 -
St. Louis City 2270008005 -
St. Louis City 2270009010 -
St. Louis City 2270010010 -
St. Louis City 2282005010 151.01
St. Louis City 2282005015 64.71
St. Louis City 2282010005 103.83
St. Louis City 2282020005 0.98
St. Louis City 2282020010 0.01
St. Louis City 2285002015 2.12
St. Louis City 2285004015 4.07
St. Louis City 2285006015 0.03
St. Louis City Total 16,556.63 Combined Total for St. Louis County and St. Louis City 106,070.62

### 1 of 53 

# Appendix A-5

Nonpoint Industrial and Commercial/Inst itutional (ICI) Fuel Combustion Category

Documentation

### 2 of 53 

# A REA 

# C OMBUSTION 

# S OURCE 

# E MISSIONS 

# I NVENTORY



# I MPROVEMENT 

# M ETHODOLOGY



# T ECHNICAL 

# M EMORANDUM

Contract No. 07-0901-RPO-036

March 20, 2009

Prepared for:

Kathy Pendleton Texas Commission on Environmental Quality

MC-164

P.O. Box 13087 Austin, TX 78711-3087

Annette Sharp Central Regional Air Planning Association 10005 S. Pennsylvania, Suite C Oklahoma City, OK 73159

Prepared by:

E.H. Pechan & Associates, Inc. 3622 Lyckan Parkway, Suite 2005 Durham, NC 27707

### ii of 53 

### CONTENTS Page

A. INTRODUCTION 

### ....................................................................................................................... 1

B. METHODOLOGY 

### ....................................................................................................................... 1

1. Total ICI Energy Consumption 

### ............................................................................................... 3

2. Non-Fuel Energy Consumption 

### .............................................................................................. 3

3. Nonroad Source Energy Consumption 

### .................................................................................... 4

4. Point Source Energy Consumption 

### ....................................................................................... 11

5. Emission Factors 

### ................................................................................................................. 23

6. Coal Sulfur Content 

### ............................................................................................................. 25

7. County Allocation Data 

### ....................................................................................................... 26

8. Temporal Allocation Data 

### .................................................................................................... 32

C. CALCULATION TEMPLATES 

### ................................................................................................. 34

D. REFERENCES 

### .......................................................................................................................... 35

ATTACHMENT: PRELIMINARY SUMMARY OF 2002 POINT SOURCE ANNUAL

THROUGHPUT DATA 

### ................................................................................................................... 37

TABLES

Table 1. ICI Combustion Area Source Classification Codes 

### ................................................................. 2
Table 2. Industrial Sector Energy Consumption from Non-Fuel Uses 

### ................................................... 4

Table 3. Nonroad Sector Subtraction SCCs 

### ........................................................................................ 5

Table 4. Industrial Fuel Combustion Crosswalk for Point Source Subtractions 

### .................................... 12

Table 5. Commercial/Institutional Fuel Com bustion Crosswalk for Point Source Subtractions 

### ............. 20
Table 6. Criteria Pollutant Emission Factors for ICI Combustion Area Source Categories 

### ................... 24

Table 7. Carbon Dioxide Emission Factors for Indu strial and Commercial/Institutional Coal Combustion
(lb/MMBtu)



### .............................................................................................................................. ...... 25 Table 8. Additional Greenhouse Gas Emission Factors for ICI Combustion Area Source Categories
(lb/MMBtu)



### .............................................................................................................................. ...... 25
Table 9. Comparison of County Allocation Approaches for Missouri 

### ................................................. 30

Table 10. EPA Default Commercial Fuel Combustion Sector Allocation 

### ............................................ 33

### 1 of 53 

## A. INTRODUCTION

The objective of this project is to estimate area source emissions from Industrial and Commercial/Institutional (ICI) fu el combustion for the CENRAP region, which encompasses the

States and tribal areas of Ar kansas, Iowa, Kansas, Louisiana, Minnesota, Missouri, Nebraska, Oklahoma, and Texas. This project will result in the development of a set of revised 2002 ICI

area source emission inventorie s for sulfur dioxide (SO 2 

### ), nitrogen oxides (NO

x 

### ), non-methane volatile organic compounds (VOCs), particulate matter (specifically, PM 10 

### and primary/direct

PM 2.5 

### ), ammonia (NH 3 

### ), carbon dioxide (CO 2 

### ), methane (CH 4 

### ), and nitrous oxide (N 2 

### O). The emission inventories will be developed at the co unty level and will provide emissions for the following time periods: annual; monthly; and average weekly, weekda y, and weekend day

emissions for each month.

This technical memorandum is one of two components for documenting the methodology that E.H. Pechan & Associates, Inc. (Pechan) will follow in preparing CENRAP’s 2002 ICI area source emissions inventory. The sec ond component is a set of Microsoft ® 

### Excel workbook templates that Pechan will use to implement th e methodology described in this document. This memorandum is organized into four secti ons: this section (In troduction), Section B (Methodology) , which describe s the emission estimation met hodology, Section C (Calculation Templates), which summarizes the content of the calculation templates, and Section D (References), which identifies the information sources that were consulted in preparing this

document.



## B. METHODOLOGY

This section documents the emission inventor y development methodology that Pechan will use to prepare an ICI combustion area source emission inventory for the CENRAP States. Table 1 identifies the source classification codes (S CCs) for which Pechan plans to prepare ICI

combustion area source emission estimates. It is important to note that some of these SCCs may not ultimately appear in each CE NRAP State’s inventory. If it is determined that all of an individual State’s consumption of a particular fuel is already acc ounted for in the State’s nonroad and/or point source inventory, then the SCC for that fuel will not be included in the area source inventory for that State.

The key data inputs in the emi ssions estimation methodology are:

1. Total Industrial and total Commercial/Insti tutional energy consumption by fuel type and CENRAP State for the year 2002;

2. Industrial energy consumption us ed for non-fuel purposes by fu el type and State in 2002;

3. ICI distillate fuel and liquefied petroleu m gas (LPG) consumption for nonroad sources by State in year 2002;

4. ICI energy consumption by fuel type for poi nt sources by CENRAP State in year 2002;

5. Emission factors relating emission rates to vol ume of energy consumed by fuel type for the ICI sectors;

6. Sulfur content of coal consumed in the ICI sectors by State in year 2002;2 of 53Table 1. ICI Combustion Area Source Classification CodesSCC DESCRIPTION2102001000 Stationary Source Fuel Combustion; Industrial; Anthracite Coal; Total: All Boiler Types2102002000 Stationary Source Fuel Combustion; Industrial; Bituminous/Subbituminous Coal; Total: All Boiler Types2102004000 Stationary Source Fuel Combustion; Industrial; Distillate Oil; Total: Boilers and IC Engines2102005000 Stationary Source Fuel Combustion; Industrial; Residual Oil; Total: All Boiler Types2102006000 Stationary Source Fuel Combustion; Industrial; Natural Gas; Total: Boilers and IC Engines2102007000 Stationary Source Fuel Combustion; Industrial; Liquid Petroleum Gas; Total: All Boiler Types2102008000 Stationary Source Fuel Combustion;Industrial; Wood; Total: All Boiler Types2102011000 Stationary Source Fuel Combustion; Industrial; Kerosene; Total: All Boiler Types2103001000 Stationary Source Fuel Combustion; Commercial/Institutional; Anthracite Coal; Total: All Boiler Types2103002000 Stationary Source Fuel Combustion; Commercial/Institutional; Bituminous/Subbituminous Coal; Total: All Boiler Types2103004000 Stationary Source Fuel Combustion; Commercial/Institutional; Distillate Oil; Total: Boilers and IC Engines2103005000 Stationary Source Fuel Combustion; Commercial/Institutional; Residual Oil; Total: All Boiler Types2103006000 Stationary Source Fuel Combustion; Commercial/Institutional; Natural Gas; Total: Boilers and IC Engines2103007000 Stationary Source Fuel Combustion; Commercial/Institutional; Liquid Petroleum Gas; Total: All Combustor Types2103008000 Stationary Source Fuel Combustion; Commercial/Institutional; Wood; Total: All Boiler Types2103011000 Stationary Source Fuel Combustion; Commercial/Institutional; Kerosene; Total: All Combustor Types

### 3 of 53 

### 7. County-level employment in the ICI sectors by Stat e for the year 2002; and

8. Temporal allocation data for estimating th e proportion of annua l fuel combusted by month, as well as data for estimating the volum e of fuel combusted in each month for the following time-frames: average week, aver age week day; and average weekend day.

The following sections describe the methodology/data source(s) for developing each of these data inputs. The following identifies the planned source(s) of information for each of these data elements. In selecting the information sources fo r each of these data elements, Pechan evaluated the representativeness and level of confidence criteria id entified in the Quality Assurance Project Plan (QAPP) for this project. For example, inform ation sources that provide data specific to the source category/geography/inventor y period were selected over t hose that are less specific.

1. Total ICI Energy Consumption

For total Industrial and total Commercial/Inst itutional energy consumption by fuel type/State,

Pechan will use the same source that EPA uses in developing ICI combustion emission estimates for the National Emissions Inventory (NEI) – the Energy Information Administration (EIA)’s State Energy Data System (SEDS) (EIA, 2009a). The SEDS reports total energy consumption estimates by sector, State, fuel type, and year. To facilitate use with the criteria pollutant and GHG emission factors, Pechan will compile the SE DS energy consumption data in both sets of units provided by the SEDS: physical un its and British thermal units (Btus).

2. Non-Fuel Energy Consumption

Some Industrial sector energy is consumed for non- fuel purposes. For example, natural gas is used as a feedstock in chemical manufacturing plants and to make n itrogenous fertilizer, and LPG is used to create intermediate products that are made into plastics. To estimate the volume

of fuel that is associated w ith ICI combustion, it is necessary to subtract the volume of fuel consumption for non-energy uses from the volume of total fuel consumption. The EPA’s State Inventory Tool (SIT) provides national defaults re presenting the percenta ge of total Industrial fuel consumption from non-energy uses. 1 

### These default values have an additional limitation beyond their lack of geographic detail - they repr esent the EIA’s definition of the Industrial sector, which includes fuel use th at is accounted for in other i nventory source categories. In particular, the EIA Industrial se ctor includes fuel consumption from Farm, Mining, Construction,

and Commercial sectors that is accounted for in the nonroad inventory. Because of these limitations, Pechan plans to use regional non-fu el use percentages computed from energy consumption data from the EIA’s 2002 Manufacturing Energy Consumption Survey (MECS) for all fuel types except coal (E IA, 2007). There are two reas ons why MECS provides a more representative data set for use in this study: (1) MECS provides da ta specific to the regions of interest; and (2) MECS focuses solely on the Manuf acturing sector. The la tter characteristic is particularly important for fuel types whic h consume significant amounts of non-Manufacturing sector energy that is already included elsewhere (e.g., distillate fuel used by the Construction sector, which is included in the nonroad inventor y). The MECS non-fuel consumption data treat

1 Although the SIT also develops CO 2 emission estimates associated with n on-fuel energy use, such estimates are not developed here because they are not associated with industrial fuel combustion.

### 4 of 53 

### coal that is used to produce coke as a feedstock. However, ava ilable data indicate that none of the CENRAP States produce coke (Pechan, 2006) . In addition, the 2002 MECS data treat “synthetic coal” that is ultimately combusted as regular coal, as a non-fuel (feedstock) use. Because of these data limitations, Pechan contac ted EIA for assistance in obtaining a reasonable estimate of the percentage of non-coking coal that is used for non-fuel purposes (treating “synthetic coal” as a fuel use). Based on the EIA’s estimate that 5-10 percent of 2002 non-coke coal was used for non-fuel purposes, Pechan pl ans to assume that 7 percent of CENRAP

Industrial sector coal co nsumption is for non-fuel purposes (Lorenz, 2009).

Table 2 presents the available non -fuel use percentages by type of energy. It was not possible to develop percentages by region fo r each fuel type because some regional MECS data are withheld. For this study, Pechan plans to use th e most geographic-specific data reported in Table 2. States are encouraged to provide available State-specific estimates to replace the defaults

below.

Table 2. Industrial Sector Energy Consumption from Non-Fuel Uses

Energy Type 2002 MECS % Energy Consumption from Non-Fuel Use

Midwest South Midwest+South National

Residual not available not available 25% 17%

Distillate not available not available 9% 7%

Natural Gas 6% 15% 12% 10%

LPG/NGL 88% 98% 97% 97%

Coal not available not available not available 7%

Sources: EIA, 2007 and Lorenz, 2009. Midwest region includes Iowa, Kansas, Minnesota, Missouri, and Nebraska. South region includes Arkansas, Louisiana, Oklahoma, and Texas.



### 3. Nonroad Source Energy Consumption

To avoid double-counting with the nonroad inventory, it is necessary to subtract 2002 year diesel and LPG consumption estimates for Industrial, Farm, Logging, Mining, and Construction sector nonroad equipment. For the Commercial sector SE DS data, it is necessary to subtract 2002 year diesel and LPG consumption for Commercial sector nonroad equipment. Pechan plans to run the

NONROAD model for 2002 for the CENRAP States to obtain State-le vel diesel and LPG consumption estimates to perform these subtract ions. Table 3 identifies the SCCs for which Pechan will compile NONROAD fuel consumption estimates.5 of 53Table 3. Nonroad Sector Subtraction SCCsSCCDescription_2Description_3Description_4Industrial Sector-Distillate2270000000 Off-highway Vehicle Diesel Compression Ignition Equipment except Rail and Marine Total2270001000 Off-highway Vehicle Diesel Recreational Equipment Total2270001010 Off-highway Vehicle Diesel Recreational Equipment Motorcycles: Off-road2270001020 Off-highway Vehicle Diesel Recreational Equipment Snowmobiles2270001030 Off-highway Vehicle Diesel Recreational Equipment All Terrain Vehicles2270001040 Off-highway Vehicle Diesel Recreational Equipment Minibikes2270001050 Off-highway Vehicle Diesel Recreational Equipment Golf Carts2270001060 Off-highway Vehicle Diesel Recreational Equipment Specialty Vehicles/Carts2270002000 Off-highwayVehicle DieselConstruction and Mining Equipment Total2270002003 Off-highwayVehicle DieselConstruction and Mining EquipmentPavers2270002006 Off-highway Vehicle Diesel Construction and MiningEquipment Tampers/Rammers2270002009 Off-highway Vehicle Diesel Construction and MiningEquipment Plate Compactors2270002012 Off-highway Vehicle Diesel Construction and MiningEquipment Concrete Pavers2270002015 Off-highwayVehicle DieselConstruction and Mining Equipment Rollers2270002018 Off-highway Vehicle Diesel Construction and Mining Equipment Scrapers2270002021 Off-highway Vehicle Diesel Construction and MiningEquipment Paving Equipment2270002024 Off-highway Vehicle Diesel Construction and Mining Equipment Surfacing Equipment2270002027 Off-highwayVehicle DieselConstruction and Mining Equipment SignalBoards/Light Plants2270002030 Off-highwayVehicle DieselConstruction and Mining Equipment Trenchers2270002033 Off-highway Vehicle Diesel Construction and MiningEquipment Bore/Drill Rigs2270002036 Off-highwayVehicle Diesel Construction and Mining Equipment Excavators2270002039 Off-highway Vehicle Diesel Construction and Mining EquipmentConcrete/Industrial Saws2270002042 Off-highway Vehicle Diesel Construction and Mining EquipmentCement and Mortar Mixers2270002045 Off-highwayVehicle DieselConstruction and Mining EquipmentCranes2270002048 Off-highway Vehicle Diesel Construction and Mining Equipment Graders6 of 53SCCDescription_2Description_3Description_42270002051 Off-highway Vehicle Diesel Construction and Mining Equipment Off-Highway Trucks2270002054 Off-highwayVehicle DieselConstruction and Mining Equipment Crushing/Processing Equipment2270002057 Off-highwayVehicle Diesel Construction andMining Equipment Rough Terrain Forklifts2270002060 Off-highway Vehicle Diesel Construction and Mining EquipmentRubber Tired Loaders2270002063 Off-highwayVehicle DieselConstruction and Mining Equipment Rubber Tire Tractor/Dozers2270002066 Off-highway Vehicle Diesel Construction and Mining EquipmentTractors/Loaders/Backhoes2270002069 Off-highwayVehicle Diesel Construction andMining Equipment Crawler Tractor/Dozers2270002072 Off-highway Vehicle Diesel Construction and Mining Equipment Skid Steer Loaders2270002075 Off-highway Vehicle Diesel Construction and Mining Equipment Off-Highway Tractors2270002078 Off-highway Vehicle Diesel Construction and Mining Equipment Dumpers/Tenders2270002081 Off-highwayVehicle DieselConstruction and Mining Equipment Other Construction Equipment2270003000 Off-highway Vehicle Diesel Industrial Equipment Total2270003010 Off-highway Vehicle Diesel Industrial Equipment Aerial Lifts2270003020 Off-highway Vehicle Diesel Industrial Equipment Forklifts2270003030 Off-highway Vehicle Diesel Industrial EquipmentSweepers/Scrubbers2270003040 Off-highway Vehicle Diesel Industrial Equipment Other General Industrial Equipment2270003050 Off-highway Vehicle Diesel Industrial Equipment Other Material Handling Equipment2270003060 Off-highway Vehicle Diesel Industrial Equipment AC/Refrigeration2270003070 Off-highway Vehicle Diesel Industrial Equipment Terminal Tractors2270005000 Off-highway Vehicle Diesel Agricultural Equipment Total2270005010 Off-highwayVehicle Diesel Agricultural Equipment 2-Wheel Tractors2270005015 Off-highway Vehicle Diesel Agricultural Equipment Agricultural Tractors2270005020 Off-highway Vehicle Diesel Agricultural Equipment Combines2270005025 Off-highway Vehicle Diesel AgriculturalEquipment Balers2270005030 Off-highway Vehicle Diesel Agricultural Equipment Agricultural Mowers2270005035 Off-highway Vehicle Diesel Agricultural Equipment Sprayers2270005040 Off-highway Vehicle Diesel Agricultural Equipment Tillers > 6 HP2270005045 Off-highway Vehicle Diesel Agricultural Equipment Swathers2270005050 Off-highwayVehicle Diesel Agricultural Equipment Hydro-power Units7 of 53SCCDescription_2Description_3Description_42270005055 Off-highway Vehicle DieselAgricultural Equipment Other Agricultural Equipment2270005060 Off-highwayVehicle DieselAgricultural Equipment Irrigation Sets2270007000 Off-highwayVehicle DieselLogging Equipment Total2270007005 Off-highwayVehicle DieselLogging Equipment Chain Saws > 6 HP2270007010 Off-highway Vehicle Diesel Logging Equipment Shredders > 6HP2270007015 Off-highway Vehicle Diesel LoggingEquipment Forest Eqp– Fellers/Bunch/Skidder2270007020 Off-highway Vehicle DieselLogging Equipment Fellers/Bunchers ** (see 22-70-007-015)2270009000 Off-highway Vehicle Diesel Underground Mining Equipment All2270009010 Off-highway Vehicle Diesel Underground Mining Equipment Other Underground Mining Equipment2270010000 Off-highwayVehicle DieselIndustrial Equipment All2270010010 Off-highway Vehicle Diesel Industrial Equipment OtherOil Field EquipmentIndustrial Sector-LPG2267002000 LPG Construction and Mining Equipment All2267002003 LPGConstruction and Mining Equipment Pavers2267002006LPGConstruction and Mining Equipment Tampers/Rammers2267002009LPGConstruction and Mining Equipment Plate Compactors2267002015LPGConstruction and Mining Equipment Rollers2267002018LPGConstruction and Mining Equipment Scrapers2267002021LPGConstruction and Mining Equipment Paving Equipment2267002024LPGConstruction and Mining Equipment Surfacing Equipment2267002027LPGConstruction and Mining Equipment Signal Boards/Light Plants2267002030LPGConstruction and Mining Equipment Trenchers2267002033LPGConstruction and Mining Equipment Bore/Drill Rigs2267002036LPGConstruction and Mining Equipment Excavators2267002039LPGConstruction and Mining Equipment Concrete/Industrial Saws2267002042LPGConstruction and Mining Equipment Cement and Mortar Mixers2267002045LPGConstruction and Mining Equipment Cranes2267002048LPGConstruction and Mining Equipment Graders2267002051LPGConstruction and Mining Equipment Off-highway Trucks8 of 53SCCDescription_2Description_3Description_42267002054 LPGConstruction and Mining Equipment Crushing/Processing Equipment2267002057 LPGConstruction and Mining Equipment Rough Terrain Forklifts2267002060 LPGConstruction and Mining Equipment Rubber Tire Loaders2267002063 LPGConstruction and Mining Equipment Rubber Tire Tractors/Dozers2267002066 LPGConstruction and Mining Equipment Tractors/Loaders/Backhoes2267002069 LPGConstruction and Mining Equipment Crawler Tractor/Dozers2267002072 LPGConstruction and Mining Equipment Skid Steer Loaders2267002075LPGConstruction and Mining Equipment Off-Highway Tractors2267002078LPGConstruction and Mining Equipment Dumpers/Tenders2267002081LPGConstruction and Mining Equipment Other Construction Equipment2267003000LPGIndustrial Equipment All2267003010LPGIndustrial Equipment Aerial Lifts2267003020LPGIndustrial Equipment Forklifts2267003030LPGIndustrial Equipment Sweepers/Scrubbers2267003040LPGIndustrial Equipment Other General Industrial Equipment2267003050LPGIndustrial Equipment Other Material Handling Equipment2267003060LPGIndustrial Equipment AC\Refrigeration2267003070LPGIndustrial Equipment Terminal Tractors2267005000LPGAgricultural Equipment All2267005010LPGAgricultural Equipment 2-Wheel Tractors2267005015LPGAgricultural Equipment Agricultural Tractors2267005020LPGAgricultural Equipment Combines2267005025LPGAgricultural Equipment Balers2267005030LPGAgricultural Equipment Agricultural Mowers2267005035LPGAgricultural Equipment Sprayers2267005040LPGAgricultural Equipment Tillers >6 HP2267005045LPGAgricultural Equipment Swathers2267005050LPGAgricultural Equipment Hydro-power Units2267005055 LPGAgricultural Equipment Other Agricultural Equipment9 of 53SCCDescription_2Description_3Description_42267005060 LPGAgricultural Equipment Irrigation Sets2267007000 LPGLogging Equipment All2267007005 LPGLogging Equipment Chain Saws > 6 HP2267007010 LPGLogging Equipment Shredders > 6 HP2267007015 LPGLogging Equipment Forest Eqp – Feller/Bunch/Skidder2267009000 LPGUnderground Mining Equipment All2267009010 LPGUnderground Mining Equipment Other Underground Mining Equipment2267010000 LPGIndustrial Equipment All2267010010 LPGIndustrial Equipment OtherOil Field EquipmentCommercial Sector-Distillate2270004000 Off-highway Vehicle Diesel Lawn and Garden Equipment All2270004011 Off-highway Vehicle Diesel Lawnand Garden Equipment Lawn Mowers (Commercial)2270004016 Off-highway Vehicle Diesel Lawn and Garden Equipment Rotary Tillers < 6HP (Commercial)2270004021 Off-highway Vehicle Diesel Lawn and Garden Equipment Chain Saws < 6 HP (Commercial)2270004026 Off-highway Vehicle Diesel Lawn and GardenEquipment Trimmers/Edgers/Brush Cutters (Commercial)2270004031 Off-highway Vehicle Diesel Lawn and Garden Equipment Leafblowers/Vacuums (Commercial)2270004036 Off-highway Vehicle Diesel Lawn and Garden Equipment Snowblowers (Commercial)2270004041 Off-highway Vehicle Diesel Lawn and Garden Equipment Rear EngineRiding Mowers (Commercial)2270004046 Off-highway Vehicle Diesel Lawnand Garden Equipment FrontMowers (Commercial)2270004051 Off-highway Vehicle Diesel Lawn and Garden Equipment Shredders < 6 HP (Commercial)2270004056 Off-highway Vehicle Diesel Lawn and GardenEquipment Lawn and Garden Tractors (Commercial)2270004061 Off-highway Vehicle Diesel Lawnand Garden Equipment Wood Splitters (Commercial)2270004066 Off-highway Vehicle Diesel Lawn and Garden Equipment Chippers/Stump Grinders (Commercial)2270004070 Off-highway Vehicle Diesel Lawnand Garden Equipment Commercial Turf Equipment ** (use 22-70-004-71)2270004071 Off-highway Vehicle Diesel Lawn and Garden Equipment Turf Equipment (Commercial)2270004076 Off-highway Vehicle Diesel Lawn and Garden Equipment Other Lawn and Garden Equipment (Commercial)2270006000 Off-highway Vehicle Diesel Commercial Equipment Total2270006005 Off-highway Vehicle Diesel Commercial Equipment Generator Sets2270006010 Off-highway Vehicle Diesel Commercial Equipment Pumps10 of 53SCCDescription_2Description_3Description_42270006015 Off-highway Vehicle Diesel Commercial Equipment Air Compressors2270006020 Off-highway Vehicle Diesel Commercial Equipment Gas Compressors2270006025 Off-highway Vehicle Diesel Commercial Equipment Welders2270006030 Off-highwayVehicle DieselCommercial Equipment Pressure Washers2270008000 Off-highway Vehicle Diesel Airport Ground Support Equipment Total2270008005 Off-highway Vehicle Diesel Airport Ground Support Equipment Airport Ground Support Equipment2270008010 Off-highway Vehicle Diesel Airport Ground Support Equipment Terminal TractorsCommercial Sector-LPG22670004011 LPG Lawn and Garden Equipment Lawn Mowers (Commercial)22670004016LPGLawn and Garden EquipmentRotary Tillers < 6 HP (Commercial)22670004021LPGLawn and Garden EquipmentChain Saws < 6 HP (Commercial)22670004026LPGLawn and Garden EquipmentTrimmers/Edgers/Brush Cutters (Commercial)22670004031LPGLawn and Garden EquipmentLeafblowers/Vacuums (Commercial)22670004036LPGLawn and Garden EquipmentSnowblowers (Commercial)22670004041LPGLawn and Garden EquipmentRear Engine Riding Mowers (Commercial)22670004046LPGLawn and Garden EquipmentFront Mowers (Commercial)22670004051LPGLawn and Garden EquipmentShredders < 6 HP (Commercial)22670004056LPGLawn and Garden EquipmentLawn and Garden Tractors (Commercial)22670004061LPGLawn and Garden EquipmentWood Splitters (Commercial)22670004066LPGLawn and Garden EquipmentChippers/Stump Grinders (Commercial)22670004071LPGLawn and Garden EquipmentTurf Equipment (Commercial)22670004076LPGLawn and Garden EquipmentOther Lawn and Garden Equipment (Commercial)22670006000 LPGCommercial Equipment All22670006005LPGCommercial EquipmentGenerator Sets22670006010LPGCommercial EquipmentPumps22670006015LPGCommercial EquipmentAir Compressors22670006020LPGCommercial EquipmentGas Compressors22670006025LPGCommercial EquipmentWelders22670006030LPGCommercial EquipmentPressure Washers

### 11 of 53 

### 4. Point Source Energy Consumption

To ensure that energy consumption is not double- counted in the point source inventory, it will also be necessary to subtract po int source inventory fuel use from the fuel consumption estimates developed from the aforementioned data sources. To assist in the point source subtractions, Pechan has developed two crosswalks: one be tween each Industrial fuel combustion area SCC and associated point SCCs (Table 4), and an analogous crosswalk for Commercial/Institutional fuel combustion (Table 5). Pechan requests CE NRAP comments on the point SCCs included in

these crosswalks.

In addition, a summary analysis was performed on the throughput data re ported in the 2002 point source inventory compiled for CENRAP (Pech an/CEP, 2005). The Attachment to this memorandum provides a summary of the 2002 annua l point source throughput data associated with the ICI area source categories (reflecting use of the Table 4 a nd 5 crosswalks). As indicated by this summary, there appear to be numerous pot ential reporting errors in the CENRAP point source inventory throughput information. Th ese errors include throughput reported using inappropriate units (e.g., reporting natural gas throughput in tons a nd distillate fuel throughput in million cubic feet), and throughput reported using an inappropriate material code (e.g., reporting a distillate fuel combustion category’s throughpu t as water). There ar e also records with emissions that report throughput as zero and throughput data repor ted without any unit identifiers. Pechan requests guidance from CE NRAP States as to revisions to the throughput information to ensure the validity of the data that are used in the point source subtractions. For States/source categories with suspect values for which revisions are not available, Pechan will estimate throughput by dividing point source em issions by the carbon monoxide (CO) emission

factors listed in the next section. The CO-based approach will also be used for all States that do not report any throughput data for ICI point source fuel combusti on categories (i.e., Louisiana and Texas).

To ensure that the methodology results in accurate estimates of point source throughput, Pechan will supply States with the SEDS energy consum ption estimates by fuel type and the point source energy consumption by fuel type comput ed using the throughput or CO emissions-based approach. Pechan will wait for State approval of these estimates before final use in the point source subtraction procedure.12 of 53Table 4. Industrial Fuel Combustion Crosswalk for Point Source SubtractionsPoint SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC2102001000 & 2102002000 – Industrial; Anthracite Coal; Total: All Boiler Types and Bituminous/Subbituminous Coal; Total: All Boiler Types10200101 External Combustion Boilers Industrial Anthracite Coal Pulverized Coal10200104 External Combustion Boilers Industrial Anthracite Coal Traveling Grate (Overfeed) Stoker10200107 External Combustion Boilers Industrial Anthracite Coal Hand-fired10200117 External Combustion Boilers Industrial Anthracite Coal Fluidized Bed Boiler Burning Anthracite-Culm Fuel39000189 Industrial Processes In-process Fuel Use Anthracite Coal General39000199 Industrial Processes In-process Fuel Use Anthracite Coal General10200201 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Pulverized Coal: Wet Bottom10200202 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Pulverized Coal: Dry Bottom10200203 External Combustion Boilers IndustrialBituminous/SubbituminousCoal Cyclone Furnace10200204 External Combustion Boilers IndustrialBituminous/Subbituminous Coal Spreader Stoker10200205 External Combustion Boilers IndustrialBituminous/Subbituminous Coal Overfeed Stoker10200206 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Underfeed Stoker10200210 External Combustion Boilers Industrial Bituminous/Subbituminous CoalOverfeed Stoker **10200212 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Pulverized Coal: Dry Bottom (Tangential)10200213 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Wet Slurry10200217 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Atmospheric Fluidized Bed Combustion: BubblingBed (Bituminous Coal)10200218 External Combustion Boilers Industrial Bituminous/Subbituminous CoalAtmospheric Fluidized Bed Combustion: CirculatingBed (Bitum. Coal)10200219 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Cogeneration (Bituminous Coal)10200221 External Combustion Boilers Industrial Bituminous/Subbituminous CoalPulverized Coal: Wet Bottom (Subbituminous Coal)10200222 External Combustion Boilers Industrial Bituminous/Subbituminous CoalPulverized Coal: Dry Bottom (Subbituminous Coal)10200223 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Cyclone Furnace (Subbituminous Coal)10200224 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Spreader Stoker (Subbituminous Coal)10200225 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Traveling Grate (Overfeed) Stoker (SubbituminousCoal)10200226 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Pulverized Coal: Dry Bottom Tangential(Subbituminous Coal)10200229 External Combustion Boilers Industrial Bituminous/Subbituminous Coal Cogeneration (Subbituminous Coal)10500102 External Combustion Boilers Space Heaters Industrial Coal **39000201 Industrial Processes In-process Fuel Use Bituminous Coal Cement Kiln/Dryer (Bituminous Coal)39000203 Industrial Processes In-process Fuel Use Bituminous Coal Lime Kiln (Bituminous)39000288 Industrial Processes In-process FuelUse Bituminous CoalGeneral (Subbituminous)39000289 Industrial Processes In-process FuelUse Bituminous CoalGeneral (Bituminous)39000299 Industrial Processes In-process FuelUse Bituminous CoalGeneral (Bituminous)50390002 Waste Disposal Solid Waste Disposal -Industrial Auxiliary Fuel/No Emissions Coal13 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC2102004000 – Industrial; Distillate Oil;Total: Boilers and IC Engines10200501 External Combustion Boilers Industrial Distillate OilGrades 1 and 2 Oil10200502 External Combustion Boilers Industrial Distillate Oil 10-100 Million Btu/hr **10200503 External Combustion Boilers Industrial Distillate Oil < 10 Million Btu/hr **10200504 External Combustion Boilers Industrial DistillateOil Grade 4 Oil10200505 External Combustion Boilers Industrial Distillate Oil Cogeneration10201403 External Combustion Boilers Industrial CO BoilerDistillate Oil10500105 External Combustion Boilers Space Heaters Industrial Distillate Oil20200101 Internal Combustion Engines Industrial Distillate Oil(Diesel) Turbine20200102 Internal Combustion Engines IndustrialDistillate Oil (Diesel) Reciprocating20200103 Internal Combustion Engines Industrial Distillate Oil (Diesel) Turbine: Cogeneration20200104 Internal Combustion Engines Industrial Distillate Oil (Diesel) Reciprocating: Cogeneration20200105 Internal Combustion Engines Industrial DistillateOil (Diesel) Reciprocating: Crankcase Blowby20200106 Internal Combustion Engines Industrial Distillate Oil (Diesel) Reciprocating: Evaporative Losses (Fuel Storageand Delivery System)20200107 Internal Combustion Engines Industrial Distillate Oil (Diesel)Reciprocating: Exhaust20200108 Internal Combustion Engines Industrial Distillate Oil (Diesel) Turbine: Evaporative Losses (Fuel Storage andDelivery System)20200109 Internal Combustion Engines IndustrialDistillate Oil (Diesel) Turbine: Exhaust20200401 Internal Combustion Engines Industrial Large Bore Engine Diesel20200405 Internal Combustion Engines Industrial Large Bore Engine Crankcase Blowby20200406 Internal Combustion Engines Industrial Large BoreEngine Evaporative Losses (Fuel Storage and DeliverySystem)20200407 Internal Combustion EnginesIndustrial Large Bore Engine Exhaust27000320 Internal Combustion Engines Off-highway Diesel Engines Industrial Equipment Industrial Fork Lift: Diesel30190001 Industrial Processes Chemical Manufacturing Fuel Fired Equipment Distillate Oil (No. 2): Process Heaters30190011 Industrial Processes Chemical Manufacturing Fuel Fired Equipment Distillate Oil (No. 2): Incinerators30190021 Industrial Processes ChemicalManufacturing Fuel Fired EquipmentDistillate Oil (No. 2): Flares30290001 Industrial Processes Food and Agriculture Fuel FiredEquipment Distillate Oil(No. 2): Process Heaters30390001 Industrial Processes Primary Metal Production Fuel Fired Equipment Distillate Oil(No. 2): Process Heaters30390011 Industrial Processes Primary Metal Production Fuel Fired Equipment DistillateOil (No. 2): Incinerators30390021 Industrial Processes Primary Metal Production FuelFired Equipment Distillate Oil (No. 2): Flares30400406 Industrial Processes Secondary Metal Production Lead Pot Furnace Heater: Distillate Oil30490001 Industrial Processes Secondary MetalProduction Fuel Fired Equipment Distillate Oil (No. 2): Process Heaters30490011 Industrial Processes Secondary Metal Production Fuel Fired Equipment DistillateOil (No. 2): Incinerators30490021 Industrial Processes Secondary Metal Production FuelFired Equipment Distillate Oil (No. 2): Flares30490031 Industrial Processes Secondary Metal Production FuelFired Equipment Distillate Oil (No. 2): Furnaces30500208 Industrial Processes MineralProducts Asphalt Concrete Asphalt Heater: Distillate Oil30505022 Industrial Processes MineralProducts Asphalt Processing (Blowing)Asphalt Heater: Distillate Oil30590001 Industrial Processes Mineral Products Fuel Fired Equipment Distillate Oil (No. 2): Process Heaters30590011 Industrial Processes Mineral Products Fuel Fired Equipment Distillate Oil (No. 2): Incinerators30590021 Industrial Processes MineralProducts Fuel Fired Equipment Distillate Oil (No. 2): Flares14 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC30600901 Industrial Processes PetroleumIndustry Flares Distillate Oil30609901 Industrial Processes Petroleum Industry Incinerators Distillate Oil (No. 2)30790001 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment DistillateOil (No. 2): Process Heaters30790011 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment Distillate Oil (No. 2): Incinerators30790021 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment Distillate Oil (No. 2): Flares30890001 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment DistillateOil (No. 2): Process Heaters30890011 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Distillate Oil (No. 2): Incinerators30890021 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Distillate Oil (No. 2): Flares30990001 Industrial Processes Fabricated Metal Products Fuel Fired Equipment Distillate Oil (No. 2): Process Heaters30990011 Industrial Processes Fabricated Metal Products FuelFired Equipment DistillateOil (No. 2): Incinerators31000401 Industrial Processes Oil and Gas ProductionProcess Heaters Distillate Oil (No. 2)31000411 Industrial Processes Oil and Gas Production ProcessHeaters Distillate Oil (No. 2): Steam Generators31390001 Industrial Processes Electrical EquipmentProcess Heaters Distillate Oil (No. 2)39000501 Industrial Processes In-process FuelUse Distillate Oil Asphalt Dryer **39000502 Industrial Processes In-process FuelUse Distillate Oil Cement Kiln/Dryer39000503 Industrial Processes In-process Fuel Use Distillate Oil Lime Kiln39000589 Industrial Processes In-processFuel Use Distillate Oil General39000598 Industrial Processes In-process Fuel Use Distillate Oil Grade 4 Oil: General39000599 Industrial Processes In-processFuel Use Distillate Oil General39900501 Industrial ProcessesMiscellaneous ManufacturingIndustriesProcess Heater/Furnace Distillate Oil39990001 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesDistillate Oil (No.2): Process Heaters39990011 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesDistillate Oil (No. 2): Incinerators39990021 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesDistillate Oil (No. 2 Oil): Flares40201002 Petroleum and SolventEvaporationSurface Coating Operations Coating Oven Heater Distillate Oil40290011 Petroleum and SolventEvaporationSurface Coating Operations FuelFired Equipment DistillateOil: Incinerator/Afterburner49090011 Petroleum and SolventEvaporationOrganic Solvent Evaporation Fuel Fired Equipment Distillate Oil (No. 2): Incinerators49090021 Petroleum and SolventEvaporationOrganic Solvent Evaporation Fuel Fired Equipment Distillate Oil (No. 2): Flares50390005 Waste Disposal Solid Waste Disposal - Industrial Auxiliary Fuel/No Emissions Distillate Oil2102005000 – Industrial; Residual Oil; Total: All Boiler Types10200401 External Combustion Boilers Industrial Residual Oil Grade 6 Oil15 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC10200402 External Combustion Boilers Industrial Residual Oil 10-100 Million Btu/hr **10200403 External Combustion Boilers Industrial Residual Oil < 10 Million Btu/hr **10200404 External Combustion Boilers Industrial Residual Oil Grade 5 Oil10200405 External Combustion BoilersIndustrial Residual Oil Cogeneration10201404 External Combustion BoilersIndustrial CO Boiler Residual Oil20200501 Internal Combustion Engines Industrial Residual/Crude Oil Reciprocating20200505 Internal Combustion Engines Industrial Residual/Crude Oil Reciprocating: Crankcase Blowby20200506 Internal Combustion Engines Industrial Residual/Crude Oil Reciprocating: Evaporative Losses (Fuel Storageand Delivery System)20200507 Internal Combustion Engines Industrial Residual/Crude Oil Reciprocating: Exhaust30190002 Industrial Processes Chemical Manufacturing FuelFired Equipment Residual Oil: Process Heaters30190012 Industrial Processes Chemical Manufacturing Fuel Fired Equipment Residual Oil: Incinerators30190022 Industrial Processes Chemical ManufacturingFuel Fired EquipmentResidual Oil: Flares30290002 Industrial Processes Food and Agriculture FuelFired Equipment Residual Oil: Process Heaters30390002 Industrial Processes Primary Metal Production FuelFired Equipment Residual Oil: Process Heaters30390012 Industrial Processes Primary Metal Production Fuel Fired Equipment Residual Oil: Incinerators30390022 Industrial Processes Primary Metal ProductionFuel Fired EquipmentResidual Oil: Flares30490002 Industrial Processes Secondary Metal Production FuelFired Equipment Residual Oil: Process Heaters30490012 Industrial Processes Secondary Metal Production Fuel Fired Equipment Residual Oil: Incinerators30490022 Industrial Processes Secondary Metal ProductionFuel Fired EquipmentResidual Oil: Flares30490032 Industrial Processes Secondary Metal ProductionFuel Fired Equipment Residual Oil: Furnaces30500207 Industrial Processes Mineral Products Asphalt Concrete Asphalt Heater: Residual Oil30505021 Industrial Processes MineralProducts Asphalt Processing (Blowing) Asphalt Heater: Residual Oil30590002 Industrial Processes Mineral Products FuelFired Equipment Residual Oil: Process Heaters30590012 Industrial Processes Mineral Products FuelFired Equipment Residual Oil: Incinerators30600111 Industrial Processes Petroleum Industry Process Heaters Oil-fired (No. 6 Oil) > 100 Million Btu Capacity30600902 Industrial Processes PetroleumIndustry Flares Residual Oil30609902 Industrial Processes PetroleumIndustry Incinerators Residual Oil30790002 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment Residual Oil: Process Heaters30790012 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment Residual Oil: Incinerators30790022 Industrial Processes Pulp and Paper and WoodProductsFuel Fired EquipmentResidual Oil: Flares30890002 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Residual Oil: Process Heaters30890012 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Residual Oil: Incinerators30890022 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired EquipmentResidual Oil: Flares30990002 Industrial Processes Fabricated Metal Products Fuel Fired Equipment Residual Oil: Process Heaters30990012 Industrial Processes Fabricated Metal ProductsFuel Fired Equipment Residual Oil: Incinerators31000402 Industrial Processes Oil and Gas Production Process Heaters Residual Oil16 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC31000412 Industrial Processes Oil and Gas Production Process Heaters Residual Oil: Steam Generators31390002 Industrial Processes Electrical Equipment Process Heaters Residual Oil39000402 Industrial Processes In-process FuelUse Residual Oil Cement Kiln/Dryer39000403 Industrial Processes In-processFuel Use Residual Oil Lime Kiln39000489 Industrial Processes In-process Fuel Use Residual Oil General39000499 Industrial Processes In-process Fuel Use Residual Oil General39990002 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesResidual Oil: Process Heaters39990012 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesResidual Oil: Incinerators39990022 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesResidual Oil: Flares40201003 Petroleum and SolventEvaporationSurface Coating Operations Coating Oven Heater Residual Oil40290012 Petroleum and SolventEvaporationSurface Coating Operations Fuel Fired Equipment Residual Oil: Incinerator/Afterburner49090012 Petroleum and SolventEvaporationOrganic Solvent Evaporation Fuel FiredEquipment Residual Oil: Incinerators49090022 Petroleum and SolventEvaporationOrganic Solvent Evaporation Fuel Fired Equipment Residual Oil: Flares2102006000 – Industrial; Natural Gas; Total: Boilers and IC Engines10200601 External Combustion Boilers Industrial Natural Gas > 100 Million Btu/hr10200602 External Combustion Boilers Industrial Natural Gas 10-100 Million Btu/hr10200603 External Combustion Boilers Industrial Natural Gas < 10 Million Btu/hr10200604 External Combustion Boilers Industrial Natural Gas Cogeneration10201401 External Combustion BoilersIndustrial CO Boiler Natural Gas10500106 External Combustion Boilers Space Heaters Industrial Natural Gas20200201 Internal Combustion Engines Industrial Natural Gas Turbine20200202 Internal Combustion Engines Industrial Natural Gas Reciprocating20200203 Internal Combustion Engines Industrial Natural Gas Turbine: Cogeneration20200204 Internal Combustion Engines Industrial Natural Gas Reciprocating: Cogeneration20200205 Internal Combustion Engines Industrial Natural Gas Reciprocating: Crankcase Blowby20200206 Internal Combustion Engines Industrial NaturalGas Reciprocating: Evaporative Losses (Fuel DeliverySystem)20200207 Internal Combustion Engines Industrial Natural Gas Reciprocating: Exhaust20200208 Internal Combustion Engines Industrial Natural Gas Turbine: Evaporative Losses (Fuel Delivery System)20200209 Internal Combustion Engines Industrial Natural Gas Turbine: Exhaust20200252 Internal Combustion Engines Industrial Natural Gas 2-cycle Lean Burn20200253 Internal Combustion Engines Industrial Natural Gas 4-cycle Rich Burn20200254 Internal Combustion Engines Industrial Natural Gas 4-cycle Lean Burn20200255 Internal Combustion Engines Industrial Natural Gas 2-cycle Clean Burn20200256 Internal Combustion Engines Industrial Natural Gas 4-cycle Clean Burn30190003 Industrial Processes Chemical Manufacturing FuelFired Equipment Natural Gas: Process Heaters17 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC30190013 Industrial Processes Chemical Manufacturing Fuel Fired Equipment Natural Gas: Incinerators30190023 Industrial Processes Chemical ManufacturingFuel Fired Equipment Natural Gas: Flares30290003 Industrial Processes Food and Agriculture FuelFired Equipment Natural Gas: Process Heaters30291001 Industrial Processes Food and Agriculture FuelFired Equipment Broiling Food: Natural Gas30390003 Industrial Processes Primary Metal Production FuelFired Equipment Natural Gas: Process Heaters30390013 Industrial Processes Primary Metal Production Fuel Fired Equipment Natural Gas: Incinerators30390023 Industrial Processes Primary Metal ProductionFuel Fired Equipment Natural Gas: Flares30400407 Industrial Processes Secondary Metal Production Lead Pot Furnace Heater: Natural Gas30490003 Industrial Processes Secondary Metal Production FuelFired Equipment Natural Gas: Process Heaters30490013 Industrial Processes Secondary Metal Production Fuel Fired Equipment Natural Gas: Incinerators30490023 Industrial Processes Secondary Metal ProductionFuel Fired Equipment Natural Gas: Flares30490033 Industrial Processes Secondary Metal ProductionFuel Fired Equipment Natural Gas: Furnaces30500206 Industrial Processes Mineral Products Asphalt Concrete Asphalt Heater: Natural Gas30505020 Industrial Processes MineralProducts Asphalt Processing (Blowing) Asphalt Heater: Natural Gas30590003 Industrial Processes Mineral Products FuelFired Equipment Natural Gas: Process Heaters30590013 Industrial Processes Mineral Products FuelFired Equipment Natural Gas: Incinerators30590023 Industrial Processes Mineral Products Fuel Fired Equipment Natural Gas: Flares30790003 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment Natural Gas: Process Heaters30790013 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment Natural Gas: Incinerators30790023 Industrial Processes Pulp and Paper and WoodProductsFuel Fired Equipment Natural Gas: Flares30890003 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Natural Gas: Process Heaters30890013 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Natural Gas: Incinerators30890023 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Natural Gas: Flares30990003 Industrial Processes Fabricated Metal Products Fuel Fired Equipment Natural Gas: Process Heaters30990013 Industrial Processes Fabricated Metal ProductsFuel Fired Equipment Natural Gas: Incinerators30990023 Industrial Processes Fabricated Metal ProductsFuel Fired Equipment Natural Gas: Flares31000404 Industrial Processes Oil and Gas Production Process Heaters Natural Gas31000414 Industrial Processes Oil and Gas Production Process Heaters Natural Gas: Steam Generators31390003 Industrial Processes Electrical Equipment Process Heaters Natural Gas39000602 Industrial Processes In-process Fuel Use Natural Gas Cement Kiln/Dryer39000603 Industrial Processes In-process Fuel Use Natural Gas Lime Kiln39000605 Industrial Processes In-process Fuel Use Natural Gas Metal Melting **39000689 Industrial Processes In-process Fuel Use Natural Gas General39000699 Industrial Processes In-process Fuel Use Natural Gas General39900601 Industrial ProcessesMiscellaneous ManufacturingIndustriesProcess Heater/Furnace Natural Gas39990003 Industrial Processes MiscellaneousManufacturing Miscellaneous Manufacturing Natural Gas: Process Heaters18 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESCIndustries Industries39990013 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesNatural Gas: Incinerators39990023 Industrial ProcessesMiscellaneous ManufacturingIndustriesMiscellaneous ManufacturingIndustriesNatural Gas: Flares40201001 Petroleum and SolventEvaporationSurface Coating Operations Coating Oven Heater Natural Gas40290013 Petroleum and SolventEvaporationSurface Coating Operations Fuel Fired Equipment Natural Gas: Incinerator/Afterburner40290023 Petroleum and SolventEvaporationSurface Coating Operations Fuel Fired Equipment Natural Gas: Flares49090013 Petroleum and SolventEvaporationOrganic Solvent Evaporation Fuel FiredEquipment Natural Gas: Incinerators49090023 Petroleum and SolventEvaporationOrganic Solvent Evaporation Fuel Fired Equipment Natural Gas: Flares50390006 Waste Disposal Solid Waste Disposal - Industrial Auxiliary Fuel/No Emissions Natural Gas2102007000 – Industrial; Liquified Petroleum Gas (LPG); Total: All Boiler Types10201001 External Combustion Boilers Industrial Liquified Petroleum Gas (LPG) Butane10201002 External Combustion Boilers Industrial Liquified Petroleum Gas (LPG) Propane10201003 External Combustion Boilers Industrial Liquified Petroleum Gas (LPG) Butane/Propane Mixture: Specify Percent Butane inComments10500110 External Combustion Boilers Space Heaters Industrial Liquified Petroleum Gas (LPG)20201001 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Propane: Reciprocating20201002 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Butane: Reciprocating20201005 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Reciprocating: Crankcase Blowby20201006 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Reciprocating: Evaporative Losses (Fuel Storageand Delivery System)20201007 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Reciprocating: Exhaust20201008 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Turbine: Evaporative Losses (Fuel Storage andDelivery System)20201009 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Turbine: Exhaust20201011 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Turbine20201012 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Reciprocating Engine20201013 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Turbine: Cogeneration20201014 Internal Combustion Engines Industrial Liquified Petroleum Gas (LPG) Reciprocating Engine: Cogeneration27300320 Internal Combustion Engines Off-highway LPG-fueled Engines Industrial EquipmentIndustrial Fork Lift: Liquified Petroleum Gas (LPG)30290005 Industrial Processes Food and Agriculture Fuel Fired Equipment Liquified Petroleum Gas (LPG): Process Heaters30490035 Industrial Processes Secondary Metal Production Fuel Fired Equipment Propane: Furnaces30500209 Industrial Processes Mineral ProductsAsphalt Concrete Asphalt Heater: LPG30505023 Industrial Processes MineralProducts Asphalt Processing (Blowing) Asphalt Heater: LP Gas30590005 Industrial Processes Mineral ProductsFuel Fired Equipment Liquified Petroleum Gas (LPG): Process Heaters30600107 Industrial Processes PetroleumIndustry Process Heaters LPG-fired30600905 Industrial Processes Petroleum Industry Flares Liquified Petroleum Gas19 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC30609905 Industrial Processes Petroleum Industry Incinerators Liquified Petroleum Gas30890004 Industrial Processes Rubber and MiscellaneousPlastics ProductsFuel Fired Equipment Liquified Petroleum Gas (LPG): Process Heaters31000406 Industrial Processes Oil and Gas Production Process Heaters Propane/Butane39001089 Industrial Processes In-process FuelUse Liquified Petroleum Gas General39001099 Industrial Processes In-process FuelUse Liquified Petroleum Gas General39901001 Industrial ProcessesMiscellaneous ManufacturingIndustriesProcess Heater/Furnace LPG40201004 Petroleum and SolventEvaporationSurface Coating Operations Coating OvenHeater Liquified Petroleum Gas (LPG)50390010 Waste Disposal Solid Waste Disposal - Industrial Auxiliary Fuel/No Emissions Liquified Petroleum Gas (LPG)2102008000 – Industrial; Wood; Total: All Boiler Types10200902 External Combustion Boilers Industrial Wood/Bark Waste Wood/Bark-fired Boiler10200903 External Combustion Boilers Industrial Wood/BarkWaste Wood-fired Boiler - Wet Wood (>=20% moisture)10200905 External Combustion Boilers Industrial Wood/BarkWaste Wood/Bark-fired Boiler (< 50,000 Lb Steam) **10200906 External Combustion Boilers Industrial Wood/BarkWaste Wood-fired Boiler (< 50,000 Lb Steam) **10200907 External Combustion Boilers Industrial Wood/Bark Waste Wood Cogeneration10200908 External Combustion Boilers Industrial Wood/BarkWaste Wood-fired Boiler - Dry Wood (<20% moisture)10200910 External Combustion Boilers Industrial Wood/Bark Waste Fuel cell/Dutch oven boilers **10200911 External Combustion Boilers Industrial Wood/Bark Waste Stoker boilers **10200912 External Combustion Boilers Industrial Wood/Bark Waste Fluidized bed combustion boiler39000989 Industrial Processes In-process Fuel Use Wood General39000999 Industrial Processes In-process Fuel Use Wood General: Wood2102011000 – Industrial; Kerosene; Total: All Boiler Types20200901 Internal Combustion Engines Industrial Kerosene/Naphtha (Jet Fuel) Turbine20200902 Internal Combustion Engines IndustrialKerosene/Naphtha (Jet Fuel) Reciprocating20200905 Internal Combustion Engines Industrial Kerosene/Naphtha (Jet Fuel) Reciprocating: Crankcase Blowby20200906 Internal Combustion Engines Industrial Kerosene/Naphtha (Jet Fuel) Reciprocating: Evaporative Losses (Fuel Storageand Delivery System)20200907 Internal Combustion Engines Industrial Kerosene/Naphtha (Jet Fuel)Reciprocating: Exhaust20200908 Internal Combustion Engines Industrial Kerosene/Naphtha (Jet Fuel) Turbine: Evaporative Losses (Fuel Storage andDelivery System)20200909 Internal Combustion Engines Industrial Kerosene/Naphtha (Jet Fuel) Turbine: Exhaust20 of 53Table 5. Commercial/Institutional Fuel Combustion Crosswalk for Point Source SubtractionsPoint SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC2103001000 & 2103002000 --Commercial/Institutional; Anthracite Coal; Total: All Boiler Types and Bituminous/Subbituminous Coal; Total: All Boiler Types10300101 External Combustion Boilers Commercial/Institutional Anthracite Coal Pulverized Coal10300102 External Combustion Boilers Commercial/InstitutionalAnthracite Coal Traveling Grate (Overfeed) Stoker10300103 External Combustion Boilers Commercial/Institutional Anthracite Coal Hand-fired10300203 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Cyclone Furnace (Bituminous Coal)10300205 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Pulverized Coal: Wet Bottom (Bituminous Coal)10300206 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Pulverized Coal: Dry Bottom (Bituminous Coal)10300207 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Overfeed Stoker (Bituminous Coal)10300208 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal UnderfeedStoker (Bituminous Coal)10300209 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal SpreaderStoker (Bituminous Coal)10300211 External Combustion Boilers Commercial/Institutional Bituminous/SubbituminousCoal Overfeed Stoker **10300214 External Combustion Boilers Commercial/InstitutionalBituminous/Subbituminous Coal Hand-fired (Bituminous Coal)10300216 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous CoalPulverized Coal: Dry Bottom (Tangential)(Bituminous Coal)10300217 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous CoalAtmospheric Fluidized Bed Combustion: BubblingBed (Bituminous Coal)10300218 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous CoalAtmospheric Fluidized BedCombustion: CirculatingBed (Bitum. Coal)10300221 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Pulverized Coal: Wet Bottom (Subbituminous Coal)10300222 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Pulverized Coal: Dry Bottom (Subbituminous Coal)10300223 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Cyclone Furnace (Subbituminous Coal)10300224 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous Coal Spreader Stoker (Subbituminous Coal)10300225 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous CoalTraveling Grate (Overfeed) Stoker (SubbituminousCoal)10300226 External Combustion Boilers Commercial/Institutional Bituminous/Subbituminous CoalPulverized Coal: Dry Bottom Tangential(Subbituminous Coal)10500202 External Combustion Boilers Space Heaters Commercial/Institutional Coal **50190002 Waste DisposalSolid Waste Disposal -Government Auxiliary Fuel/No Emissions Coal50290002 Waste DisposalSolid Waste Disposal -Commercial/Institutional Auxiliary Fuel/No Emissions Coal2103004000 -- Commercial/Institutional; Distillate Oil; Total: Boilers and IC Engines10300501 External Combustion Boilers Commercial/Institutional Distillate Oil Grades 1 and 2 Oil10300502 External Combustion Boilers Commercial/Institutional Distillate Oil 10-100 Million Btu/hr **10300503 External Combustion Boilers Commercial/Institutional Distillate Oil < 10 Million Btu/hr **10300504 External Combustion Boilers Commercial/Institutional Distillate Oil Grade 4 Oil10500205 External Combustion Boilers Space Heaters Commercial/Institutional Distillate Oil20300101 Internal Combustion Engines Commercial/Institutional Distillate Oil(Diesel) Reciprocating20300102 Internal Combustion Engines Commercial/Institutional DistillateOil (Diesel) Turbine21 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC20300105 Internal Combustion Engines Commercial/Institutional Distillate Oil (Diesel) Reciprocating: Crankcase Blowby20300106 Internal Combustion Engines Commercial/Institutional Distillate Oil (Diesel)Reciprocating: Evaporative Losses (Fuel Storageand Delivery System)20300107 Internal Combustion Engines Commercial/Institutional Distillate Oil (Diesel) Reciprocating: Exhaust20300108 Internal Combustion Engines Commercial/Institutional Distillate Oil (Diesel)Turbine: Evaporative Losses (Fuel Storage andDelivery System)20300109 Internal Combustion Engines Commercial/Institutional Distillate Oil (Diesel) Turbine: Exhaust50190005 Waste DisposalSolid Waste Disposal -Government Auxiliary Fuel/No Emissions Distillate Oil50290005 Waste DisposalSolid Waste Disposal -Commercial/Institutional Auxiliary Fuel/No Emissions Distillate Oil2103005000 -- Commercial/Institutional; Residual Oil; Total: All Boiler Types10300401 External Combustion Boilers Commercial/Institutional Residual Oil Grade 6 Oil10300402 External Combustion Boilers Commercial/Institutional Residual Oil 10-100 Million Btu/hr **10300403 External Combustion Boilers Commercial/Institutional Residual Oil < 10 Million Btu/hr **10300404 External Combustion Boilers Commercial/Institutional Residual Oil Grade 5 Oil2103006000 -- Commercial/Institutional; Natural Gas; Total: Boilers and IC Engines10300601 External Combustion Boilers Commercial/Institutional Natural Gas > 100 Million Btu/hr10300602 External Combustion Boilers Commercial/Institutional Natural Gas 10-100 Million Btu/hr10300603 External Combustion Boilers Commercial/Institutional Natural Gas < 10 Million Btu/hr10500206 External Combustion Boilers Space Heaters Commercial/Institutional Natural Gas20300201 Internal Combustion Engines Commercial/Institutional Natural Gas Reciprocating20300202 Internal Combustion Engines Commercial/Institutional Natural Gas Turbine20300203 Internal Combustion Engines Commercial/Institutional Natural Gas Turbine: Cogeneration20300204 Internal Combustion Engines Commercial/Institutional Natural Gas Cogeneration20300205 Internal Combustion Engines Commercial/Institutional Natural Gas Reciprocating: Crankcase Blowby20300206 Internal Combustion Engines Commercial/Institutional Natural GasReciprocating: Evaporative Losses (Fuel DeliverySystem)20300207 Internal Combustion Engines Commercial/Institutional Natural Gas Reciprocating: Exhaust20300208 Internal Combustion Engines Commercial/Institutional Natural Gas Turbine: Evaporative Losses (Fuel Delivery System)20300209 Internal Combustion EnginesCommercial/Institutional Natural Gas Turbine: Exhaust50190006 Waste DisposalSolid Waste Disposal -Government Auxiliary Fuel/No Emissions Natural Gas50290006 Waste DisposalSolid Waste Disposal -Commercial/Institutional Auxiliary Fuel/No Emissions Natural Gas2103007000 -- Commercial/Institutional; Liquid Petroleum Gas; Total: All Combustor Types10301001 External Combustion Boilers Commercial/Institutional Liquified Petroleum Gas (LPG) Butane10301002 External Combustion Boilers Commercial/Institutional Liquified Petroleum Gas (LPG) Propane10301003 External Combustion Boilers Commercial/Institutional Liquified Petroleum Gas (LPG)Butane/Propane Mixture: Specify Percent Butane inComments10500210 External Combustion Boilers Space Heaters Commercial/Institutional Liquified Petroleum Gas (LPG)20301001 Internal Combustion Engines Commercial/Institutional Liquified Petroleum Gas(LPG) Propane: Reciprocating20301002 Internal Combustion Engines Commercial/Institutional Liquified PetroleumGas (LPG) Butane: Reciprocating22 of 53Point SCCSCC1 DESCSCC3 DESCSCC6 DESCSCC8 DESC20301005 Internal Combustion Engines Commercial/Institutional Liquified Petroleum Gas (LPG) Reciprocating: Crankcase Blowby20301006 Internal Combustion Engines Commercial/Institutional Liquified Petroleum Gas (LPG)Reciprocating: Evaporative Losses (Fuel Storageand Delivery System)20301007 Internal Combustion Engines Commercial/Institutional Liquified PetroleumGas (LPG) Reciprocating: Exhaust50190010 Waste DisposalSolid Waste Disposal -Government Auxiliary Fuel/No Emissions Liquified Petroleum Gas (LPG)50290010 Waste DisposalSolid Waste Disposal -Commercial/Institutional Auxiliary Fuel/No Emissions Liquified Petroleum Gas (LPG)2103008000 -- Commercial/Institutional; Wood; Total: All Boiler Types10300902 External Combustion Boilers Commercial/Institutional Wood/Bark Waste Wood/Bark-fired Boiler10300903 External Combustion Boilers Commercial/Institutional Wood/Bark Waste Wood-fired Boiler - Wet Wood (>=20% moisture)10300908 External Combustion Boilers Commercial/Institutional Wood/Bark Waste Wood-fired Boiler - Dry Wood (<20% moisture)10300910 External Combustion Boilers Commercial/Institutional Wood/Bark Waste Fuel cell/Dutch oven boilers **10300911 External Combustion Boilers Commercial/Institutional Wood/Bark Waste Stoker boilers **10300912 External Combustion Boilers Commercial/Institutional Wood/Bark Waste Fluidized bed combustion boilers10500209 External Combustion Boilers SpaceHeaters Commercial/Institutional Wood2103011000 -- Commercial/Institutional; Kerosene; Total: All Combustor Types20300901 Internal Combustion Engines Commercial/Institutional Kerosene/Naphtha (Jet Fuel) Turbine: JP-420300908 Internal Combustion Engines Commercial/Institutional Kerosene/Naphtha (Jet Fuel)Turbine: Evaporative Losses (Fuel Storage andDelivery System)20300909 Internal Combustion Engines Commercial/Institutional Kerosene/Naphtha (Jet Fuel) Turbine: Exhaust50100603 Waste DisposalSolid Waste Disposal -Government Fire Fighting Structure: Kerosene

### 23 of 53 

### 5. Emission Factors

Table 6 presents the criteria pollutant emission fact ors that will be applied to fuel consumption

estimates to calculate ICI combustion area source emissions. Except as noted below, all criteria air pollutant emission factors were from an EPA database of emission factors that will be used in preparing the 2008 nonpoint source NEI (Huntley, 2009). 2 

### Wood combustion emission factors were compiled from AP-42 (EPA, 2003). Because there are no NH 3 

### emission factors for ICI fuel

combustion available in the 2008 NEI emission factor database, AP-42, or EPA’s WebFIRE, Pechan will use emission factors reported in an NH 3 

### emissions Emission Inventory Improvement Program (EIIP) guidance document (Pechan, 2004). Pechan compared the 2008 NEI emission

factors with those used to deve lop the last area source NEI (2002) , as well as those listed by the Eastern Regional Technical Advisory Committ ee (ERTAC) for potential use by States in developing their area source inve ntories (ERTAC, 2009). With a few notable exceptions, the

2008 NEI emission factors are the same as those used for the 2002 NEI. 3 

### The PM emission factors for natural gas and LPG combustion are the major exceptions. Because the 2002 emission factors were deemed too high because of artifact formation in the test method (method 202) during stack testing, EPA deve loped a set of SCC-specific adjust ment factors to apply to the

2002 NEI to better reflect PM emissions from these fuels. 4 

### In preparation for the 2008 NEI, EPA developed revised natural gas and LPG PM em ission factors by applying these adjustment

factors to the 2002 NE I emission factors.

Pechan does not plan to use the ERTAC emissi on factors that differ from the 2008 NEI factors

because of the lack of documentation as to the source of the ERTAC factors. For PM emissions from ICI bituminous coal combustion, ERTAC sp ecifically notes that their proposed emission

factors reflect combustion in an uncontrolled over feed stoker. The EPA PM emission factors for these categories, which were obtained from AP-42 , reflect coal-fired boi lers with controls (specifically, multiple cyclones with or without fly ash reinjection) . Because an analysis of an

EPA boiler database indicates that most small coal -fired boilers have PM controls (with cyclones as the most common type of control), EPA’s PM emission factors will be used in preparing the CENRAP emission inventory (ERG, 2002).

For greenhouse gases (GHGs), Pechan will us e the emission factors from EPA’s State Greenhouse Gas Inventory Tool, which incorpor ates the EIIP’s GHG emissions inventory guidelines for States (EPA, 2009). Tabl e 7 displays the State-specific CO 2 

### emission factors for each ICI combustion area source category, and Table 8 presents the N 2 

### O and CH 4 

### emission factors by source category. Because SIT assumes that CO 2 

### emissions from U.S. biomass

combustion need not be inventor ied, the SIT does not provide CO 2 

### emission factors for ICI wood

combustion. 5 

### Therefore, Pechan will use the wood combustion CO 2 

### emission factors reported in

AP-42 (EPA, 2003).

2 All criteria pollutant emission fact ors were rounded to two decimal places.

3 The 2002 NEI documentation provides citations to the AP-42 source for each emissi on factor (Pechan, 2006).

4 These factors reduce PM emissi ons by more than 90 percent.

5 As stated in the EIIP fossil fuel combustion CO 2 emissions guidance: “...biomass fuels are generally grown on a

sustainable basis. ... In cases where biomass fuels are not grown sustainably, GHG emissi ons are captured as a land use change.”24 of 53Table 6. Criteria Pollutant Emission Factors for ICI Combustion Area Source CategoriesSCC DescriptionEmissionFactor Units VOC NOxCO SO2PM2.5-FIL PM10-FIL PM-CON NH32102001000 Industrial Anthracite Coal lb/ton 0.39 0.6 39 * S% 0.48 * A% 1.1 * A% 0.08 0.032102002000 Industrial Bitum/Subbitum Coal lb/ton 0.05 11 5 38 * S% 1.4 12 1.04 0.032102004000 Industrial Distillate Oil lb/1000 gal 0.2 20 5 142 * S% 0.25 1 1.3 0.82102005000 Industrial Residual Oil lb/1000 gal 0.28 55 5 157 * S%4.67 * (1.12 *S% + 0.37)7.17 * (1.12 *S% + 0.37)1.5 0.82102006000 Industrial Natural Gas lb/MMcf5.5 100 84 0.6 0.110.13 0.32 3.22102007000 Industrial LPG1lb/1000 bbl 20.09 365.32 306.87 2.19 0.39 0.47 1.18 1.792102008000 Industrial Wood2lb/MMBtu 0.017 0.22 0.6 0.0250.43 0.5 0.017 0.08632102011000 Industrial Kerosene lb/1000 gal 0.1919.29 4.82 142 * S% 0.24 0.96 1.25 0.7712103001000 Comm/Inst Anthracite Coal lb/ton 0.3 9 0.6 39 * S% 0.48 * A% 1.1 * A% 0.08 0.032103002000 Comm/Inst Bitum/Subbitum Coal lb/ton 0.05 11 5 38 * S% 1.4 12 1.04 0.032103004000 Comm/Inst Distillate Oil lb/1000 gal 0.34 20 5 142 * S% 0.83 1.08 1.3 0.82103005000 Comm/Inst Residual Oil lb/1000 gal 1.13 55 5 157 * S%1.92 * (1.12 *S% + 0.37)5.17 * (1.12 *S% + 0.37)1.5 0.82103006000 Comm/Inst NaturalGas lb/MMcf 5.5 100 84 0.6 0.11 0.13 0.32 0.492103007000 Comm/Inst LPG lb/1000 bbl 20.09365.32 306.87 2.19 0.390.47 1.18 1.792103008000 Comm/Inst Wood1lb/MMBtu 0.017 0.22 0.60.025 0.43 0.5 0.017 0.08632103011000 Comm/Inst Kerosene lb/1000 gal 0.3319.29 4.82 142 * S%0.8 1.04 1.25 0.771Source: Unless otherwise noted, 2008nonpoint source NEI (Huntley, 2009).Notes:1Emission factors from Commercial/Institutional LPG.2Emission factors fromAP-42, Section 1.6 (Wood Residue Combustion in Boilers).3Emission factor from Pechan, 2004; reported in lb/tons.In addition to above, PM2.5-PRI and PM10-PRI will be computed asthe sum of condensable PM emissions and PM25-FIL/PM10-FIL emissions.lb = tongal = gallonMMcf = million cubic feetMMBtu = million British thermal unitsbbl = barrelsS = sulfur contentA = ash content

### 25 of 53 

### Table 7. Carbon Dioxide Emi ssion Factors for Industrial and Commercial/Institutional Coal Combustion (lb/MMBtu)

State Industrial CO 2 Commercial/Institutional CO 2 Arkansas 205.70 227.41

Iowa 207.72 204.42

Kansas 203.02 204.89

Louisiana 204.78 227.41

Minnesota 209.70 208.27

Missouri 203.98 204.53

Nebraska 209.66 212.70

Oklahoma 205.99 205.92

Texas 210.39 206.25

Source: EPA State Greenhouse Gas Inventory Tool (EPA, 2009).



### Table 8. Additional Greenhouse Gas Em ission Factors for ICI Combustion Area Source Categories (lb/MMBtu)

SCC Description CO 2 CH 4 N 2 O

2102001000 Industrial Anthracite Coal see above 0.02210 0.00331

2102002000 Industrial Bitum/Subbitum Coal see above 0.02210 0.00331

2102004000 Industrial Distillate Oil 161.11 0.00663 0.00133

2102005000 Industrial Residual Oil 173.54 0.00663 0.00133

2102006000 Industrial Natural Gas 116.86 0.00209 0.00021

2103007000 Industrial LPG 137.32 0.00663 0.00133

2102008000 Industrial Wood 1 195 0.06280 0.00837

2102011000 Industrial Kerosene 159.28 0.00663 0.00133

2103001000 Comm/Inst Anthracite Coal see above 0.02210 0.00331

2103002000 Comm/Inst Bitum/Subbitum Coal see above 0.02210 0.00331

2103004000 Comm/Inst Distillate Oil 161.11 0.02210 0.00133

2103005000 Comm/Inst Residual Oil 173.54 0.02210 0.00133

2103006000 Comm/Inst Natural Gas 116.86 0.01047 0.00021

2103007000 Comm/Inst LPG 139.00 0.02210 0.00133

2103008000 Comm/Inst Wood 1 195 0.62802 0.00837

2103011000 Comm/Inst Kerosene 159.28 0.02210 0.00133
Source: Unless otherwise noted, EPA State Gr eenhouse Gas Inventory Tool (EPA, 2009).

1 CO 2 emission factors from AP-42 , Section 1.6 - Wood Residue Combustion in Boilers.



### 6. Coal Sulfur Content

Under a forthcoming task (Task 4) , Pechan will evaluate the reliab ility of various data sources for coal sulfur content before identifying the source(s) that will be used to estimate emissions in this project. Pechan will re view potential coal sulfur cont ent data sources, including:

### 26 of 53 

### (1) information reported in the poin t source inventories of each State; 6 

### (2) the USGS’ U.S. Coal Quality Database (this is the ICI coal sulfur content source used in the 2002 NEI); (3) plant-level data from the Federal Energy Regulat ory Commission’s (FERC) Form 423; 7 

### and (4) State-level data reported in EIA’s “Monthly Report of Cost and Quality of Fuels for Electric Plants.” Pechan will evaluate these and any other identified alternative data sources for use in this project to ensure that the data are as representative as possible with respect to consuming sector, geography, and time-frame. Any data sets that ar e deemed equally representative will next be evaluated with respect to level of confidence (i.e., a data source for which estimated coal content is based on more data points than other data so urces will be deemed to have higher confidence, and therefore, the preferred data source). Pechan will prepare a memorandum identifying the

coal content data sources that were reviewed a nd a priority ranking of pr eferred sources based on an evaluation of the aforementioned criteria. The memorandum will identify the preferred approach for characterizing the sulfur content of coal consumption for each ICI area source combustion source category, which will be incorpor ated into the Excel calculation templates.

7. County Allocation Data

After computing State-level emissions using th e data described above, the project requires allocating these emissions to i ndividual counties. There are two allocation approaches that CENRAP is evaluating for this step. The first, which has been used in past inventory efforts including the 2002 NEI, is based on each county’ s proportion of total State employment for the energy-consuming sectors for each source categor y. The second is based on estimates of total energy consumption for each sector. For both appr oaches, the initial step is to identify the

economic sectors associated with Industrial fuel combustion, and the economic sectors

associated with Commercial/I nstitutional fuel combustion.

Commercial/Institutional

For area source Commercial/Institutional fuel combustion, the 2002 NEI used employment data

in North American Industrial Classificati on System (NAICS) code s 42, 44-45, 51-54, 56, 61-62, 71-72, and 81 to allocate EIA State Commercial sector energy consump tion data to counties. 8


### These NAICS codes suggest that fuel combustion emissions for the following sectors are covered elsewhere in the NEI: Agriculture , Forestry, Fishing and Hunting; Mining; Construction; Manufacturing; Transportation an d Warehousing; Manageme nt of Companies and Enterprises; and Public Admini stration. Meanwhile the EIIP area source method abstracts for Commercial/Institutional fuel combustion categori es identify Standard Industrial Classification (SIC) codes 50-99 as representing the Commercial/Ins titutional sector. These SIC codes indicate that the following is the comprehe nsive list of non-Commercial sect ors: Agriculture, Forestry, Fishing and Hunting; Mining; Constructio n; Manufacturing; and Transportation, Communications, Electric, Gas, and Sanitary Services.

6 Iowa has stated that they did not report coal sulfur content information in their 2002 point source inventory.

7 Note that these data include Commercial and Industri al combined heat and power producers whose total fossilfueled nameplate generating capacity is 50 or more megawatts.

8 These NAICS codes are also listed in ERTAC’s ar ea source methodology worksheet (ERTAC, 2009).

### 27 of 53 

### Documentation for the SEDS is not entirely cl ear on the NAICS codes associated with the Commercial sector, defining the Co mmercial sector as “an energy-c onsuming sector that consists of service-providing facilities and equipment of: businesses; Federal, State, and local governments; and other private and public organizations, such as re ligious, social, or fraternal groups. The Commercial sector includes instituti onal living quarters. It also includes sewage treatment facilities.” In an attempt to furthe r clarify the NAICS codes associated with this sector, Pechan performed additional research into the original data sources that are used to create

the SEDS.

Because data for the SEDS originates with data collected from EIA fuel sector-specific surveys of energy suppliers, 9 

### Pechan reviewed these survey forms/in structions for further details on what

SEDS considers Commercial sector use of each fuel. This review found that the surveys/guidance do not always pr ovide further clarity. In add ition, the EIA has admitted that energy suppliers may use their own account cl assifications as well as EIA guidance in determining whether a particular account belongs in the Residential, Commercial, Industrial, or Transportation sector. The only source of NAICS-c ode based EIA definitions of the Commercial energy sector is a “rough crosswalk” between Commercial building types and NAICS codes developed for EIA’s Commercial Building Energy Consumption Survey (CBECS). With the exception of NAICS code 814 (Private Househol ds), this crosswalk links all NAICS codes

between 42 and 92 with Commerci al building energy consumption, suggesting that both the EIIP guidance and NEI definitions of the Commercial fuel combustion source category are missing some sectors, while also including one sector that should not be included (Private Households). In lieu of additional information, data for the CBECS-identified NAICS codes (42 though 92 with exception of 814) will be us ed to allocate SEDS energy c onsumption data to individual

counties.

Industrial

Although there are no EIIP guidance documents fo r area source Industrial fuel combustion, the 2002 NEI used the Manufacturing sector NAICS codes (31-33) to represent this category. Unlike the Commercial sector, the SEDS documen tation provides a clear listing of the NAICS codes associated with SEDS Industrial energy consumption data: “the industrial sector encompasses the following types of activity: Manufacturing (NAICS c odes 31–33); Agriculture, Forestry, Fishing and Hunting (NAICS code 11); Mining, including Oil and Gas Extraction (NAICS code 21); and Construction (NAICS code 23) .” As noted earlier, this indicates that a portion of Industrial sector consumption is al ready accounted for in ot her emission inventory sectors. It is expected that non-Manufacturing sector Industrial fuel consumption will largely be eliminated via the nonroad subtractions described earlier. Therefore, Pechan will not expand the list of NAICS codes used to represent the area source Industrial fuel combustion category beyond the Manufacturing sector NAICS codes (31-33).

Standard Employment-Based Approach

9 For natural gas, for example – EIA-176 “Annual Report of Natural and Supplemental Gas Supply and Disposition.”

### 28 of 53 

### In keeping with EIIP guidance and past EPA practic e, employment data can be used to allocate

State-level emission estimates to counties. Each year the Census Bureau releases County

Business Patterns (CBP), a county level data set of em ployment by NAICS code (Census, 2009). The CBP county-level employment estimates for 2002 can be compiled for the appropriate

NAICS codes noted above. Due to concerns wi th releasing confidentia l business information, the CBP withholds values for a given county/NAICS code if it would be possible to identify

individual businesses from these values. In such cases, the CBP reports a letter code, representing a particular employ ment size range. To estimate da ta for withheld counties/NAICS codes, Pechan used the following procedure.

1. County-level employment for counties with repo rted values are tota led by State for the applicable NAICS code.

2. Value from step 1 is subtracted from the State employment value for the NAICS code.

3. Each of the withheld countie s is assigned an initial empl oyment estimate reflecting the midpoint of the CBP range code (e.g., code A, which reflects 1-19 employees, is assigned an estimate of 10 employees).

4. The initial employment estimates from step 3 are then summed to the State level.

5. The value from step 2 is divided by the value from step 4 to yi eld an adjustment factor to apply to the initial employment estimates to yield employment values that will sum to the State employment total for the applicable NAICS code.

6. The final county-level employment values are estimated by multiplying the initial employment estimates from step 3 by the step 5 adjustment factors.

Example: NAICS 31-33 (Manufacturing)

fipsstate fipscty naics empflag emp

23 001 31---- 6,774
23 003 31---- 3,124

23 005 31---- 10,333

23 007 31---- 1,786

23 009 31---- 1,954

23 011 31---- 2,535

23 013 31---- 1,418

23 015 31---- F 0

23 017 31---- 2,888

23 019 31---- 4,522

23 021 31---- 948

23 023 31---- I 0

23 025 31---- 4,322
23 027 31---- 1,434

23 029 31---- 1,014

23 031 31---- 9,749



### 1. The total of employees not incl uding counties 015 and 023 is 52,801.

2. The State-level CBP reports 59,322 employees in NAICS 31----the difference is 6,521.

3. County 015 is given a midpoint of 1,750 (sin ce range code F is 1,000-2,499) and County 023 is given a midpoint of 17,500.

### 29 of 53 

### 4. State total for these two counties is 19,250.

5. 6,521/19,250 = 0.33875.

6. The final employment estimate for c ounty 015 is 1,750 * 0.33875 = 593. The county 023 final employment estimate is computed as 17,500 * 0.33875 = 5,928.

Energy Intensity-Adjusted Approach

Employment-based county allocation methods lead to overrepresentation of energy consumption in counties with sectors that have high employ ment but low energy intensities (measured on a Btu per employee basis), and vice-versa. Th erefore, Pechan recommended that CENRAP consider utilizing energy use per employee valu es by NAICS code to refine the employmentbased county allocation approach. Because Stat e/NAICS code-level energy use data are not available, this approach reli es on 2002 national energy consum ption data by NAICS code as reported by EIA in Annual Energy Outlook (EIA, 2005). Energy intens ity values are computed by dividing these Btu-based ener gy consumption estimates by 2002 national employment data by NAICS code. The resulting intensity values are then multiplied by county/NAICS code-level employment estimates to estimate total count y energy consumption by NAICS code. These values are then summed for the appropriate Industrial and Commercial/Institutional fuel combustion NAICS codes. The resulting county-level total I ndustrial and total Commercial/Institutional energy consumption estimat es can then be used to apportion State-level

Industrial fuel combustion emissions and State- level Commercial/Institutional fuel combustion emissions to each county.

Table 9 displays a comparison of the county-leve l allocation percentages computed for Missouri

from the two methods. This table is sorted in descending order based on each county’s Industrial fuel combustion employment-based allocation percen tage. The cells shaded in green indicate that the energy intensity-adjusted approach reflect s a greater than 50 percent higher allocation of activity/emissions to the given c ounty versus the employment-based approach. Similarly, cells

shaded in tan indicate that the energy-based approach reflects an allocation that is more than 50 percent lower than that resulting from the empl oyment-based approach. Th e table shows that the

Industrial sector allocations di ffer more substantially between the two methods in Missouri. Focusing on the Industrial sector allocation percentages for Jackson county, for example, overall Manufacturing sector employment is approximately 10 percent of the Missour i total. However, a much higher percentage of Miss ouri total Industrial s ector energy consumption is estimated for this county (~17 percent). A closer look at the underlying data indicates that this county has a relatively high proportion of total State employmen t in the Chemicals and Paper industries that are the third and fifth highest energy-intensive manufacturing sector industries. Pechan will provide the information in Table 9 for all CENRAP States when it submits the Task 3 State-level fuel consumption estimates, which are due by April 17.

### 30 of 53 

### Table 9. Comparison of County Allocation Approaches for Missouri

County Industrial Commercial/Institutional
Employment Energy Ratio Employment Energy Ratio

St. Louis 17.3% 14.9% 0.9 25.2% 21.8% 0.9

Jackson 10.3% 16.5% 1.6 16.2% 15.2% 0.9
City of St. Louis 8.3% 8.9% 1.1 11.9% 11.4% 1.0

Greene 5.2% 4.5% 0.9 6.0% 6.1% 1.0

St. Charles 4.6% 2.3% 0.5 4.0% 4.1% 1.0
Clay 4.6% 3.4% 0.7 3.3% 3.6% 1.1
Jasper 3.4% 2.5% 0.7 2.0% 2.0% 1.0

Franklin 3.2% 2.5% 0.8 1.0% 1.1% 1.1

Buchanan 2.3% 5.1% 2.2 1.5% 1.5% 1.0
Barry 2.0% 1.3% 0.6 0.4% 0.4% 1.0

Boone 1.7% 0.7% 0.4 2.8% 2.7% 0.9

Pettis 1.6% 1.6% 1.0 0.6% 0.7% 1.2
Cape Girardeau 1.6% 5.5% 3.4 1.6% 1.5% 1.0

Laclede 1.6% 0.4% 0.3 0.3% 0.4% 1.1

Jefferson 1.4% 2.4% 1.7 1.5% 1.8% 1.2

Newton 1.4% 1.2% 0.9 0.5% 0.6% 1.2

Howell 1.2% 0.3% 0.3 0.5% 0.6% 1.2

Cole 1.1% 0.5% 0.4 1.6% 1.5% 0.9

Butler 1.1% 0.4% 0.4 0.6% 0.6% 1.1
Perry 0.9% 0.5% 0.5 0.2% 0.2% 1.0

McDonald 0.9% 0.7% 0.7 0.1% 0.1% 1.3

Marion 0.8% 1.5% 1.8 0.4% 0.5% 1.1

St. Francois 0.8% 1.0% 1.3 0.7% 0.8% 1.0

New Madrid 0.8% 1.7% 2.1 0.1% 0.2% 1.6

Scott 0.8% 0.5% 0.6 0.6% 0.7% 1.1

Stoddard 0.8% 0.4% 0. 5 0.3% 0.4% 1.3

Christian 0.7% 0.3% 0.4 0.4% 0.5% 1.2
Nodaway 0.6% 0.6% 1.0 0.3% 0.3% 1.1

Platte 0.6% 0.3% 0.5 1.8% 1.6% 0.9

Audrain 0.6% 0.3% 0.5 0.3% 0.3% 1.1
Phelps 0.6% 0.3% 0.4 0.6% 0.7% 1.3

Linn 0.6% 0.2% 0.4 0.1% 0.2% 1.1
Henry 0.5% 0.3% 0.5 0.2% 0.3% 1.3

Johnson 0.5% 0.3% 0.5 0.4% 0.5% 1.3

Crawford 0.5% 0.2% 0.4 0.2% 0.2% 1.3

Warren 0.5% 0.5% 0.9 0.2% 0.2% 1.1

Ste. Genevieve 0.5% 0.4% 0.8 0.1% 0.2% 1.2

Sullivan 0.5% 0.6% 1.2 0.0% 0.1% 1.4

Barton 0.5% 0.3% 0.6 0.1% 0.2% 1.4

Cass 0.5% 0.5% 1. 1 0.7% 0.8% 1.2

Gasconade 0.5% 0.2% 0.5 0.1% 0.2% 1.3

Saline 0.5% 0.4% 0.8 0.3% 0.3% 1.2

### 31 of 53 County Industrial Commercial/Institutional
Employment Energy Ratio Employment Energy Ratio

Lawrence 0.5% 0.2% 0.5 0.2% 0.4% 1.5
Randolph 0.5% 0.2% 0.5 0.3% 0.4% 1.1
Grundy 0.4% 0.3% 0.7 0.1% 0.2% 1.5

Adair 0.4% 0.2% 0.6 0.3% 0.4% 1.1

Lincoln 0.3% 0.1% 0.4 0.3% 0.4% 1.3

Vernon 0.3% 0.2% 0.4 0.2% 0.3% 1.4

Camden 0.3% 0.1% 0.4 0.6% 0.6% 1.1

Dunklin 0.3% 0.3% 0.8 0.3% 0.4% 1.2
Lafayette 0.3% 0.3% 0.9 0.3% 0.4% 1.2
Osage 0.3% 0.1% 0.4 0.1% 0.1% 1.4

Texas 0.3% 0.2% 0.5 0.2% 0.2% 1.5

Monroe 0.3% 0.1% 0.4 0.1% 0.1% 1.9

Miller 0.3% 0.1% 0.2 0.2% 0.3% 1.2

Webster 0.3% 0.6% 2.2 0.2% 0.2% 1.3

Moniteau 0.3% 0.2% 0.8 0.1% 0.1% 1.3
Callaway 0.3% 0.1% 0.4 0.4% 0.5% 1.2

Pemiscot 0.3% 0.3% 1.2 0.2% 0.2% 1.3

Polk 0.3% 0.1% 0.4 0.3% 0.4% 1.3

Dent 0.2% 0.6% 2.6 0.1% 0.2% 1.2
Livingston 0.2% 0.2% 0.9 0.2% 0.2% 1.2
Washington 0.2% 0.3% 1.3 0.1% 0.2% 1.6
Montgomery 0.2% 0.2% 0.9 0.1% 0.1% 1.4

Pike 0.2% 2.3% 10.5 0.2% 0.2% 1.4
Ripley 0.2% 0.1% 0.6 0.1% 0.1% 1.4
Wright 0.2% 0.1% 0.3 0.1% 0.2% 1.3
Morgan 0.2% 0.1% 0.3 0.1% 0.1% 1.3
Douglas 0.2% 0.1% 0.3 0.1% 0.1% 1.6
Ray 0.2% 0.4% 2.3 0.1% 0.2% 1.4
Cooper 0.2% 0.1% 0.5 0.2% 0.2% 1.3
Taney 0.2% 0.3% 1.5 0.9% 0.9% 1.0

Shannon 0.2% 0.1% 0.5 0.0% 0.0% 1.4

Macon 0.2% 0.3% 1.8 0.1% 0.2% 1.9

Ralls 0.2% 1.6% 10.4 0.1% 0.1% 1.6

Madison 0.2% 0.1% 0.6 0.1% 0.1% 1.3
Wayne 0.1% 0.1% 0.6 0.1% 0.1% 1.3

Dallas 0.1% 0.1% 0.8 0.1% 0.1% 1.0

Carroll 0.1% 0.1% 0.4 0.1% 0.1% 1.4

Bates 0.1% 0.1% 1.3 0.1% 0.2% 1.4

Lewis 0.1% 0.1% 0.5 0.1% 0.1% 1.5
Shelby 0.1% 0.1% 0.7 0.0% 0.1% 2.0

Benton 0.1% 0.1% 1.2 0.1% 0.1% 1.4
Reynolds 0.1% 0. 1% 0.8 0.0% 0.1% 1.6
Oregon 0.1% 0.1% 0.8 0.1% 0.1% 1.4

Iron 0.1% 0.0% 0.4 0.1% 0.1% 1.4

### 32 of 53 County Industrial Commercial/Institutional
Employment Energy Ratio Employment Energy Ratio
Mississippi 0.1% 0.0% 0.3 0.1% 0.1% 1.2
Gentry 0.1% 0.0% 0.3 0.1% 0.1% 1.3

Howard 0.1% 0.2% 2.1 0.1% 0.1% 1.4

Stone 0.1% 0.0% 0.3 0.2% 0.2% 1.2

Carter 0.1% 0.2% 2.7 0.0% 0.0% 1.4

Dade 0.1% 0.0% 0.5 0.1% 0.1% 1.6

Clinton 0.1% 0.0% 0.5 0.2% 0.2% 1.1

Pulaski 0.1% 0.0% 0.2 0.3% 0.4% 1.2

Cedar 0.1% 0.0% 0.5 0.1% 0.1% 1.4

Maries 0.1% 0.5% 8.7 0.1% 0.1% 1.4

Ozark 0.1% 0.0% 0.6 0.0% 0.1% 1.7

Daviess 0.0% 0.0% 0.2 0.0% 0.1% 1.6
Bollinger 0.0% 0.1% 2.3 0.1% 0.1% 1.5

Scotland 0.0% 0.0% 0.5 0.0% 0.1% 2.5

Holt 0.0% 0.2% 4.8 0.0% 0.1% 1.7

Clark 0.0% 0.0% 0.4 0.0% 0.1% 1.8

DeKalb 0.0% 0.2% 4.6 0.1% 0.1% 1.3

Putnam 0.0% 0.0% 1.7 0.0% 0.1% 2.0

Harrison 0.0% 0.0% 0.5 0.1% 0.1% 1.4

Chariton 0.0% 0.0% 0.5 0.1% 0.1% 1.5

Andrew 0.0% 0.0% 0.5 0.1% 0.1% 1.7

Atchison 0.0% 0.0% 0.5 0.1% 0.1% 1.3

Knox 0.0% 0.0% 0.5 0.0% 0.1% 1.8
Hickory 0.0% 0.0% 0.4 0.0% 0.1% 1.7

Worth 0.0% 0.0% 0.4 0.0% 0.0% 2.0

Caldwell 0.0% 0.0% 0.4 0.0% 0.1% 2.1

St. Clair 0.0% 0.0% 0.3 0.1% 0.1% 1.5

Mercer 0.0% 0.0% 0.5 0.0% 0.0% 1.5
Schuyler 0.0% 0.0% 0.2 0.0% 0.0% 2.1



### 8. Temporal Allocation Data

The EPA provides national default temporal allocation data via th e “temporal allocation” section of their Emissions Modeling Clearinghouse (EMCH). For all Industrial sect or fuel types, the EPA default is for an equal distribution of a nnual activity across months. For the Commercial sector, the EPA default is for an equal distribu tion of annual activity ac ross months for LPG and kerosene, but the EPA default distribution for all other fuel types is as displayed in Table 10.

### 33 of 53 

### Table 10. EPA Default Commercial Fuel Combustion Sector Allocation

Month % Allocation
January 11.7
February 11.7

March 8.3
April 8.3
May 8.3

June 5
July 5
August 5 September 8.3

October 8.3

November 8.3

December 11.7
Note: Excludes LPG and kerosene (equal distribution assumed throughout year).



### Pechan researched the availability of more representative (sector, geographic, and/or timespecific) energy consumption data than that us ed to develop the EMCH’s temporal allocation factors. The following summari zes the available information:

 Natural Gas – State-level volume delivered data are available by month and sector (Industrial versus Commercial) for 2002;

 Coal – national consumption data are availabl e by month and sector (Industrial versus Commercial) for 2002; and

 Petroleum products (i.e., dist illate, residual, LPG, kero sene) – regional level product supplied data are available by month for 2002.

Pechan was unable to identify a source reporting sub-annual c onsumption estimates for wood.

Pechan plans to use EIA’s Stat e-level natural gas deliveries da ta for 2002 to allocate the annual SEDS data to each month (EIA, 2009b). Given the limitations of the available coal and petroleum product data, and the lack of data for wood, Pechan plans to apply EPA’s monthly default profiles to allocate annual activity/emissi ons for these fuel types. Because Pechan was unable to identify any source of sub-monthly estimates of ICI energy consumption, the EPA default allocation profiles will be used to develop average weekday, average weekend day, and average weekly emission estimates for each month.

### 34 of 53 

## C. CALCULATION TEMPLATES

This section summarizes the draft templates th at Pechan has produced to develop the ICI

combustion area source emission estimates for CENRAP. CENRAP should not review the actual data in these draft templates at this ti me because some entries are currently missing or represent “dummy” placeholder values. Pechan will provide completed templates for CENRAP review by April 17 as required under Task 5.

Template 1 – Adjust SEDS Fuel Consumption – this workbook, which reflects the discussion in sections B.1 through B.4, performs the following tasks:

 Computes Industrial sector State-level non-fuel energy c onsumption estimates by fuel type by applying MECS-based non-fuel percenta ges to the SEDS tota l Industrial sector energy consumption estimates;

 Subtracts Industrial and Commer cial sector State-level dist illate and LPG consumption estimates from a (forthcoming) NONROAD model run for 2002.

 Converts the result of the steps above from their original units to the emission factor units;

 Performs the point source subtractions usi ng 2002 CENRAP point s ource inventory data

and the ICI area source combustion S CC to point source SCC crosswalk;

Template 2 – Apply Emission Factors – this workbook accompanies the discussion in Sections B.5 and B.6 of criteria pollutant and GHG emission factors and associated coal sulfur content assumptions. Reflecting the fact that some emissi on factors differ by type of coal, this template also estimates the proportion of Industrial and Commercial/Institutional coal that is anthracite

versus bituminous/subbituminous in each State. This template will ultimately report the

estimated sulfur content of co al consumed in each State.

Template 3 – County Allocations – this workbook, which reflec ts the Section B.7 discussion, contains the data used to compute both sets of county allocation data (i.e., the county employment data and the total county energy c onsumption data). This template currently develops actual allocation data for Missouri counties. Ultimately, this template will only include county data for the allocation method that CENRAP chooses to implement in this project. This template also calculates county-level emissions from the Template 2 State-level emission

estimates.

Template 4 – Temporal Allocation – this workbook, which reflects the discussion in Section B.8, provides the data that will be used to allocate annual county emissions to monthly, average weekly, average weekday, and average weekend da y time periods. It will ultimately perform the necessary calculations to estim ate emissions in each period.

### 35 of 53 

## D. REFERENCES

Census, 2009: U.S. Census Bureau, County Business Patterns , accessed from http://www.census.gov/epcd/cbp/index.html , U.S. Department of Commerce, March

2009.

EIA, 2009a: Energy Information Administrati on, “State Energy Data System (SEDS): Consumption, Price, and Expenditure Estimat es,” U.S. Department of Energy, accessed

from http://www.eia.doe.gov/emeu/states/_seds.html , March 2009.

EIA, 2009b: Energy Information Administrati on, “Natural Gas Navigator – Natural Gas Consumption by End Use,” U.S. Department of Energy, accessed from http://tonto.eia.doe.gov/dnav/ ng/ng_cons_sum_dcu_nus_m.htm , March 2009.

EIA, 2007: Energy Information Administrati on, “2002 Energy Consumption by Manufacturers

 Data Tables,” 2002 Manufacturing Energy Consumption Survey , U.S. Department of Energy, accessed from http://www.eia.doe.gov/emeu/mecs/mecs2002/data02/shelltables.html , issued January 2007.

EIA, 2005: Energy Information Administration, Annual Energy Outlook 2005 with Projections

to 2025 , U.S. Department of Energy, accessed from http://www.eia.doe.gov/oiaf/ archive/aeo05/index.html , issued January 2005.

EPA, 2009: U.S. Environmental Protecti on Agency, “Emission Inventory Improvement Program, Technical Report Series Volume 8, Estimating Greenhouse Gas Emissions,”

accessed from http://www.epa.gov/ttn/chief/eiip /techreport/volume08/index.html

, March 2009.

EPA, 2003: U.S. Environmental Protection Agency, AP 42, Compilation of Air Pollutant Emission Factors, Fifth Edition , “Volume I, Chapter 1: External Combustion Sources, Section 1.6-Wood Residue in Combustion Boilers,” accessed from http://www.epa.gov/ttn/chief/ap42/ch01/final/c01s06.pdf , September 2003.

ERG, Inc., 2002: Eastern Research Group, “Dev elopment of Model Units for the Industrial/

Commercial/Institutional Boilers and Proce ss Heaters National Emission Standards for Hazardous Air Pollutants,” prepared for U.S. Environmental Protection Agency, Office of Air Quality Planning a nd Standards, October 2002.

ERTAC, 2009: Eastern Regiona l Technical Advisory Committee, “Area Source Comparability, Comparability Spreadsheet with Week 1 Modifications,” accessed from http://www.ertac.us/ , March 2009.

Huntley, 2009: Huntley, Roy, U.S. Envir onmental Protection Agency, “SCCs & emission

factors to be used in 2008 NE I to Bollman March 13 2009.mdb [ electronic file ],” March 13, 2009.

### 36 of 53 

### Lorenz, 2009: Lorenz, Thomas, Energy Info rmation Administration, personal communication with Andy Bollman, E.H. Pechan & Associates, Inc., March 19, 2009.

Pechan/CEP, 2005: E.H. Pechan & Associates , Inc. and Carolina Environmental Program, “Consolidation of Emissions Inventories (Sched ule 9; Work Item 3), Final,” prepared for the Central Regional Air Pla nning Association, April 28, 2005.

Pechan, 2006: E.H. Pechan & Associates, In c., “Documentation for the Final 2002 Nonpoint Sector (Feb 06 version) Na tional Emission Inventory for Criteria and Hazardous Air Pollutants,” prepared for U.S. Environmenta l Protection Agency, Office of Air Quality Planning and Standards, July 2006.

Pechan, 2004: E.H. Pechan & Associates, Inc. “Estimating Ammonia Emissions from Anthropogenic Nonagricultural Sources - Draf t Final Report,” prepared for the Emission Inventory Improvement Program, April 2004.

### 37 of 53 

## ATTACHMENT: PRELIMINARY SUMMARY OF

2002 POINT SOURCE ANNUA L THROUGHPUT DATA

The following table reports 2002 annual point sour ce throughput data asso ciated with the ICI area source categories. The table is sorted in descending order by CENRAP State and area SCC. Cells that are shaded in light blue indicate potentially suspect entries.38 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102001000 Industrial Anthracite Coal ARKANSAS 1,167,890 TON 640 Anthracite2102002000 Industrial Bituminous/Subbituminous CoalARKANSAS 3,153,027 TON 663 Bituminous Coal2102004000 Industrial Distillate Oil ARKANSAS 8,255,280 E3GAL 44 Diesel2102004000 Industrial Distillate Oil ARKANSAS0E3GAL 57 Distillate Oil (Diesel)2102004000 Industrial Distillate Oil ARKANSASE3GAL 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil ARKANSAS 2,136,217E3GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil ARKANSAS 6,408,642 E3GAL 825 Distillate Oil (No. 4)2102005000 Industrial Residual Oil ARKANSAS 224,941 E3GAL 279 Residual Oil2102005000 Industrial Residual Oil ARKANSAS 13,587,658 E3GAL 923 Residual Oil (No. 6)2102005000 Industrial Residual Oil ARKANSASE3GAL 924 Residual/Crude Oil2102006000 Industrial Natural Gas ARKANSAS 184,838,095 E6FT3 209 Natural Gas2102006000 Industrial Natural Gas ARKANSAS2102007000 Industrial Liquified Petroleum Gas (LPG) ARKANSASE3GAL 178 Liquified Petroleum Gas (LPG)2102008000 Industrial Wood ARKANSAS 56,092,213 TON 15 Wood2102008000 Industrial Wood ARKANSAS 21,798,710 TON 943 Wood/Bark2103004000 Commercial/Institutional Distillate Oil ARKANSASE3GAL 57 Distillate Oil (Diesel)2103006000 Commercial/Institutional Natural Gas ARKANSAS 23,912,086 E6FT3 209 Natural Gas2103008000 Commercial/Institutional Wood ARKANSAS 7,655,765 TON 15 Wood2102001000 Industrial Anthracite Coal IOWA24E3GAL255Propane2102001000 Industrial Anthracite Coal IOWA 98,368 TON645Ash2102002000 Industrial Bituminous/Subbituminous Coal IOWA 30,950,000 LB561Sludge2102002000 Industrial Bituminous/Subbituminous CoalIOWA 87,110 TON 323 Subbituminous Coal2102002000 Industrial Bituminous/SubbituminousCoal IOWA 3,741,706 TON 717 Coal2102004000 Industrial Distillate OilIOWA 1,039 E3GAL 44 Diesel2102004000 Industrial Distillate Oil IOWA0E3GAL 56 Distillate Oil2102004000 Industrial DistillateOil IOWA 926 E3GAL 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil IOWA 2 E3GAL255Propane2102004000 Industrial DistillateOil IOWA 42 E3GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil IOWA0E3LB 44 Diesel2102004000 Industrial Distillate OilIOWA 5,599 E6BTU 44 Diesel2102004000 Industrial Distillate Oil IOWA0E6BTU 56 Distillate Oil2102004000 Industrial Distillate Oil IOWA0E6BTU209Natural Gas2102004000 Industrial DistillateOil IOWA 42 E6BTU 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil IOWA90E6FT3209Natural Gas39 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102004000 Industrial DistillateOil IOWA 8 E6GAL 58 Distillate Oil (No. 2)2102004000 Industrial DistillateOil IOWA 2 E6GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil IOWA341,800,000FT3209Natural Gas2102004000 Industrial Distillate Oil IOWA 4,758 GAL5Water2102004000 Industrial Distillate Oil IOWA 35,967 GAL 44 Diesel2102004000 Industrial Distillate OilIOWA 613 GAL 56 Distillate Oil2102004000 Industrial DistillateOil IOWA 459 GAL 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil IOWA 330 GAL209Natural Gas2102004000 Industrial Distillate Oil IOWA 10,262 GAL255Propane2102004000 Industrial DistillateOil IOWA 339 GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial DistillateOil IOWA 14,123 HP-HR 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil IOWA2,681HR 44 Diesel2102004000 Industrial Distillate Oil IOWA29HR209Natural Gas2102004000 Industrial Distillate Oil IOWA138HR 268 Raw Material2102004000 Industrial Distillate Oil IOWA0KL 44 Diesel2102004000 Industrial Distillate Oil IOWA0TON 44 Diesel2102004000 Industrial Distillate Oil IOWA0TON 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil IOWA1,628TON 268 Raw Material2102004000 Industrial Distillate Oil IOWA2102005000 Industrial Residual Oil IOWA 14 E3GAL44Diesel2102005000 Industrial Residual Oil IOWA0E3GAL 923 Residual Oil (No. 6)2102005000 Industrial Residual Oil IOWA 438 E3GAL2102005000 Industrial Residual Oil IOWA 0 GAL127Gasoline2102005000 Industrial Residual Oil IOWA 978,215 GAL 279 Residual Oil2102005000 Industrial Residual Oil IOWA 6,000 GAL823Distillate Oil (No. 1 & 2)2102005000 Industrial Residual Oil IOWA 188,565 GAL 923 Residual Oil (No. 6)2102005000 Industrial Residual Oil IOWA2102006000 Industrial Natural Gas IOWA 6,690 E3FT3 209 Natural Gas2102006000 Industrial Natural Gas IOWA11E3GAL 58 Distillate Oil (No. 2)2102006000 Industrial Natural Gas IOWA 18,353,512 E6BTU 209 Natural Gas2102006000 Industrial Natural Gas IOWA 248,378 E6BTU 268 Raw Material2102006000 Industrial Natural Gas IOWA 69,899 E6FT3127Gasoline2102006000 Industrial Natural Gas IOWA 2,851,074 E6FT3 209 Natural Gas2102006000 Industrial Natural Gas IOWA0E6FT3225Paint2102006000 Industrial Natural Gas IOWA 21 E6FT3 268 Raw Material40 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102006000 Industrial Natural Gas IOWA 119 E6FT3315Starch2102006000 Industrial Natural Gas IOWA0E6LB 268 Raw Material2102006000 Industrial Natural Gas IOWA0E6LB281Resin2102006000 Industrial Natural Gas IOWA 1,818,653,437 FT3 209 Natural Gas2102006000 Industrial Natural Gas IOWA 1,335,666,448 FT3S 209 Natural Gas2102006000 Industrial Natural Gas IOWA1,320GAL 189 Material2102006000 Industrial Natural Gas IOWA73,408GAL225Paint2102006000 Industrial Natural Gas IOWA46GAL255Propane2102006000 Industrial Natural Gas IOWA0GAL 268 Raw Material2102006000 Industrial Natural Gas IOWA4GAL952Solvents: All2102006000 Industrial Natural Gas IOWA0GAL973ABS Polymer2102006000 Industrial Natural Gas IOWA30,621HR516Metal2102006000 Industrial Natural Gas IOWA7,000LB 189 Material2102006000 Industrial Natural Gas IOWA0LB225Paint2102006000 Industrial Natural Gas IOWA13,848LB 268 Raw Material2102006000 Industrial Natural Gas IOWA0LB281Resin2102006000 Industrial Natural Gas IOWA317LB516Metal2102006000 Industrial Natural Gas IOWA344,238TON 209 Natural Gas2102006000 Industrial Natural Gas IOWA14TON225Paint2102006000 Industrial Natural Gas IOWA40,230TON 268 Raw Material2102006000 Industrial Natural Gas IOWA0TON289Sand2102006000 Industrial Natural Gas IOWA54TON303Soil2102006000 Industrial Natural Gas IOWA162TON315Starch2102006000 Industrial Natural Gas IOWA0TON561Sludge2102006000 Industrial Natural Gas IOWA0TON580Sulfur Dioxide2102006000 Industrial Natural Gas IOWA 209 Natural Gas2102006000 Industrial Natural Gas IOWA2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA0E3GAL 178 Liquified Petroleum Gas (LPG)2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA0E3GAL 255 Propane2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA 2,977 E6BTU209Natural Gas2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA0E6BTU 255 Propane2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA0E6FT3209Natural Gas2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA0E6LB 268 Raw Material2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA3E6LB281Resin2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA 7,399 GAL 255 Propane41 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102007000 Industrial Liquified Petroleum Gas (LPG) IOWA2102008000 Industrial Wood IOWA13,154HR 124 Fuel2102008000 Industrial Wood IOWA 6,497 TON 268 Raw Material2102008000 Industrial Wood IOWA0TON-YR717Coal2102011000 Industrial Kerosene IOWA0E3GAL 162 Kerosene2102011000 Industrial Kerosene IOWA 13,717 TON 189 Material2103002000 Commercial/Institutional Bituminous/Subbituminous Coal IOWA 142,485 TON 717 Coal2103004000 Commercial/Institutional Distillate Oil IOWA 26 E3GAL 44 Diesel2103004000 Commercial/InstitutionalDistillate Oil IOWA0E3GAL 56 Distillate Oil2103004000 Commercial/InstitutionalDistillate Oil IOWA0E3GAL 58 Distillate Oil (No. 2)2103004000 Commercial/Institutional DistillateOil IOWA 18 E3GAL 268 Raw Material2103004000 Commercial/Institutional Distillate Oil IOWA 162 E3GAL 823 Distillate Oil (No. 1 & 2)2103004000 Commercial/Institutional Distillate Oil IOWA 1,033 GAL 44 Diesel2103004000 Commercial/Institutional Distillate OilIOWA 34,758 GAL 58 Distillate Oil (No. 2)2103004000 Commercial/InstitutionalDistillate Oil IOWA0TON 44 Diesel2103004000 Commercial/Institutional Distillate Oil IOWA2103005000 Commercial/Institutional Residual Oil IOWA 1 E3GAL 58 Distillate Oil (No. 2)2103005000 Commercial/Institutional Residual Oil IOWA 21 E3GAL2103005000 Commercial/Institutional ResidualOil IOWA 332,184 GAL 279 Residual Oil2103005000 Commercial/Institutional Residual OilIOWA 4,340 GAL 923 Residual Oil (No. 6)2103006000 Commercial/Institutional Natural Gas IOWA 51,606 BTU 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA 719,333 E3FT3 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA1E3GAL58Distillate Oil (No. 2)2103006000 Commercial/Institutional Natural Gas IOWA6E3GAL 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA0E6BTU 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA 28 E6FT3127Gasoline2103006000 Commercial/Institutional Natural Gas IOWA 28 E6FT3 189 Material2103006000 Commercial/Institutional Natural Gas IOWA 465,334 E6FT3 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA 16 E6FT3 268 Raw Material2103006000 Commercial/Institutional Natural Gas IOWA0E6GAL823Distillate Oil (No. 1 & 2)2103006000 Commercial/Institutional Natural Gas IOWA 8,169,622 FT3 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA576GAL58Distillate Oil (No. 2)2103006000 Commercial/Institutional Natural Gas IOWA0GAL 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA831GAL255Propane2103006000 Commercial/Institutional Natural Gas IOWA24HR44Diesel42 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2103006000 Commercial/Institutional Natural Gas IOWA13,632TON 209 Natural Gas2103006000 Commercial/Institutional Natural Gas IOWA0TON225Paint2103006000 Commercial/Institutional Natural Gas IOWA16,178TON724Coke2103006000 Commercial/Institutional Natural Gas IOWA2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) IOWA0E3GAL 178 Liquified Petroleum Gas (LPG)2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) IOWA0E3GAL 255 Propane2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) IOWA0E3GAL 268 Raw Material2103007000 Commercial/Institutional LiquifiedPetroleum Gas (LPG) IOWA 15 E6FT3209Natural Gas2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) IOWA0E6GAL 268 Raw Material2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) IOWA 88,575 GAL 255 Propane2103008000 Commercial/Institutional Wood IOWA 7,142 TON 15 Wood2102004000 Industrial Distillate Oil KANSAS 1,148 E3GAL 44 Diesel2102004000 Industrial Distillate Oil KANSAS 92,275 E3GAL 56 Distillate Oil2102004000 Industrial Distillate Oil KANSAS 83 E3GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil KANSAS 2,437 E3HP-HR 945 Work2102004000 Industrial Distillate Oil KANSAS 22,979 E6BTU 44 Diesel2102004000 Industrial Distillate Oil KANSAS 488E6BTU 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil KANSAS 1,082,040 HP-HR 945 Work2102004000 Industrial Distillate Oil KANSAS233HR209Natural Gas2102004000 Industrial Distillate Oil KANSAS 716 HR 945 Work2102004000 Industrial Distillate Oil KANSAS10,248,064KW-HR 828 Electricity2102004000 Industrial Distillate Oil KANSAS02102005000 Industrial Residual Oil KANSAS 380 E3GAL 922 Residual Oil (No. 5)2102005000 Industrial Residual Oil KANSAS 3,402 E3GAL 923 Residual Oil (No. 6)2102005000 Industrial Residual Oil KANSAS 48E6BTU 923 Residual Oil (No. 6)2102006000 Industrial Natural Gas KANSAS 287 E3FT3 209 Natural Gas2102006000 Industrial Natural Gas KANSAS19E3GAL 189 Material2102006000 Industrial Natural Gas KANSAS 2,594,753 E3HP-HR 945 Work2102006000 Industrial Natural Gas KANSAS 17,010,214 E6BTU 209 Natural Gas2102006000 Industrial Natural Gas KANSAS 282,631 E6FT3 209 Natural Gas2102006000 Industrial Natural Gas KANSAS39EACH 189 Material2102006000 Industrial Natural Gas KANSAS 288,425,458 HP-HR 945 Work2102006000 Industrial Natural Gas KANSAS100HR127Gasoline2102006000 Industrial Natural Gas KANSAS856,039HR 209 Natural Gas2102006000 Industrial Natural Gas KANSAS100,217HR 945 Work43 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102006000 Industrial Natural Gas KANSAS269LB 209 Natural Gas2102006000 Industrial Natural Gas KANSAS10,000LB635Ammonia2102006000 Industrial Natural Gas KANSAS7TON 209 Natural Gas2102006000 Industrial Natural Gas KANSAS25TON305Solvent2102006000 Industrial Natural Gas KANSAS02102007000 Industrial Liquified Petroleum Gas (LPG)KANSAS 5 E3GAL 178 Liquified Petroleum Gas (LPG)2102007000 Industrial Liquified Petroleum Gas (LPG)KANSAS 54 E3GAL 178 Liquified Petroleum Gas (LPG)2102007000 Industrial Liquified Petroleum Gas (LPG) KANSAS0E3GAL 189 Material2102007000 Industrial Liquified Petroleum Gas (LPG) KANSAS 99 E3GAL 255 Propane2103004000 Commercial/Institutional Distillate Oil KANSAS 22 E3GAL 44 Diesel2103004000 Commercial/Institutional Distillate OilKANSAS 29 E3GAL 823 Distillate Oil (No. 1 & 2)2103004000 Commercial/Institutional Distillate Oil KANSAS02103006000 Commercial/Institutional Natural Gas KANSAS 3,150 E6FT3 209 Natural Gas2103006000 Commercial/Institutional Natural Gas KANSAS0EACH 189 Material2103006000 Commercial/Institutional Natural Gas KANSAS107,768HR 209 Natural Gas2103006000 Commercial/Institutional Natural Gas KANSAS7,200HR 945 Work2103006000 Commercial/Institutional Natural Gas KANSAS02102002000 Industrial Bituminous/Subbituminous Coal LOUISIANA2102004000 Industrial DistillateOil LOUISIANA2102005000 Industrial Residual Oil LOUISIANA2102006000 Industrial Natural Gas LOUISIANA2102007000 Industrial Liquified Petroleum Gas (LPG) LOUISIANA2102008000 Industrial Wood LOUISIANA2103004000 Commercial/Institutional Distillate Oil LOUISIANA2103005000 Commercial/Institutional Residual Oil LOUISIANA2103006000 Commercial/Institutional Natural Gas LOUISIANA2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) LOUISIANA2102002000 Industrial Bituminous/Subbituminous Coal MINNESOTA 6,138,274 E6BTU 142 Heat2102002000 Industrial Bituminous/Subbituminous Coal MINNESOTA10,584HR 830 Equipment2102002000 Industrial Bituminous/Subbituminous Coal MINNESOTA 582,249TON 323 Subbituminous Coal2102002000 Industrial Bituminous/Subbituminous Coal MINNESOTA 81,870 TON 663 Bituminous Coal2102004000 Industrial Distillate OilMINNESOTA 232 E3GAL 44 Diesel2102004000 Industrial Distillate Oil MINNESOTA4,003 E3GAL 57 Distillate Oil (Diesel)2102004000 Industrial Distillate Oil MINNESOTA 1,071 E3GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil MINNESOTA535 E3GAL 825 Distillate Oil (No. 4)44 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102004000 Industrial Distillate Oil MINNESOTA 586 E6BTU 142 Heat2102004000 Industrial Distillate Oil MINNESOTA1,353,017 GAL 57 Distillate Oil (Diesel)2102004000 Industrial Distillate Oil MINNESOTA 342,565 GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil MINNESOTA2102005000 Industrial Residual Oil MINNESOTA 362 E3GAL 279 Residual Oil2102005000 Industrial Residual Oil MINNESOTA 370 E3GAL 922 Residual Oil (No. 5)2102005000 Industrial Residual Oil MINNESOTA 21,526 E3GAL 923 Residual Oil (No. 6)2102005000 Industrial Residual Oil MINNESOTA 34,637 E6BTU 142 Heat2102006000 Industrial Natural Gas MINNESOTA 6,400,498 E6BTU 142 Heat2102006000 Industrial Natural Gas MINNESOTA 39,046 E6FT3 209 Natural Gas2102006000 Industrial Natural Gas MINNESOTA 7,395,200 FT3 209 Natural Gas2102006000 Industrial Natural Gas MINNESOTA19,936,121,225GAL 209 Natural Gas2102006000 Industrial Natural Gas MINNESOTA155,328HR 830 Equipment2102007000 Industrial Liquified Petroleum Gas (LPG) MINNESOTA 94,000 BTU 142 Heat2102007000 Industrial Liquified Petroleum Gas(LPG) MINNESOTA 1,212 E3GAL 255 Propane2102007000 Industrial Liquified Petroleum Gas (LPG) MINNESOTA 209 E3GAL 675 Butane2102007000 Industrial Liquified Petroleum Gas (LPG) MINNESOTA 274 E6BTU 142 Heat2102007000 Industrial Liquified Petroleum Gas(LPG) MINNESOTA 266,584 GAL 255 Propane2102007000 Industrial Liquified Petroleum Gas (LPG) MINNESOTA626HR 830 Equipment2102008000 Industrial Wood MINNESOTA 4,675,962 E6BTU 142 Heat2102008000 Industrial Wood MINNESOTA16,467HR 830 Equipment2102008000 Industrial Wood MINNESOTA 120,057 TON 15 Wood2102008000 Industrial Wood MINNESOTA 89,216 TON 943 Wood/Bark2102011000 Industrial Kerosene MINNESOTA 12 E3GAL 159 Jet Fuel2103001000 Commercial/Institutional Anthracite Coal MINNESOTA2103002000 Commercial/InstitutionalBituminous/Subbituminous Coal MINNESOTA 2,648 E6BTU 142 Heat2103002000 Commercial/Institutional Bituminous/Subbituminous Coal MINNESOTA184,324 TON 323 Subbituminous Coal2103002000 Commercial/Institutional Bituminous/Subbituminous Coal MINNESOTA51,658 TON 663 Bituminous Coal2103004000 Commercial/Institutional Distillate Oil MINNESOTA 1,197 E3GAL 57 Distillate Oil (Diesel)2103004000 Commercial/Institutional Distillate Oil MINNESOTA 1,334 E3GAL 823 Distillate Oil (No. 1 & 2)2103004000 Commercial/Institutional Distillate Oil MINNESOTA 29 E3GAL 825 Distillate Oil (No. 4)2103005000 Commercial/Institutional Residual Oil MINNESOTA 1,695 E3GAL 922 Residual Oil (No. 5)2103005000 Commercial/Institutional Residual Oil MINNESOTA 3,303 E3GAL 923 Residual Oil (No. 6)2103006000 Commercial/Institutional Natural Gas MINNESOTA 8,623,850 E6BTU 142 Heat2103006000 Commercial/Institutional Natural Gas MINNESOTA 19,921 E6FT3 209 Natural Gas45 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2103006000 Commercial/Institutional Natural Gas MINNESOTA174,979HR 830 Equipment2103006000 Commercial/Institutional Natural Gas MINNESOTA2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) MINNESOTA 3,033 E3GAL 255 Propane2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) MINNESOTA 4,614 E6BTU 142 Heat2103008000 Commercial/Institutional Wood MINNESOTA 1,096 TON 15 Wood2103008000 Commercial/Institutional WoodMINNESOTA 246,551 TON 943 Wood/Bark2102002000 Industrial Bituminous/Subbituminous Coal MISSOURI 20,843 TON174Lime2102002000 Industrial Bituminous/Subbituminous Coal MISSOURI0TON 189 Material2102002000 Industrial Bituminous/Subbituminous CoalMISSOURI 271,022 TON 663 Bituminous Coal2102002000 Industrial Bituminous/Subbituminous Coal MISSOURI2102004000 Industrial Distillate Oil MISSOURI0E2LB 253 Product2102004000 Industrial Distillate OilMISSOURI 77,335 E3GAL 44 Diesel2102004000 Industrial Distillate Oil MISSOURI 1,146 E3GAL 56 Distillate Oil2102004000 Industrial Distillate Oil MISSOURI 3,922 E3GAL 57 Distillate Oil (Diesel)2102004000 Industrial Distillate Oil MISSOURI 1,462,931 E3GAL 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil MISSOURI0E3GAL352Toluene2102004000 Industrial Distillate Oil MISSOURI 641E3GAL 823 Distillate Oil (No. 1 & 2)2102004000 Industrial Distillate Oil MISSOURI0E3GAL 825 Distillate Oil (No. 4)2102004000 Industrial Distillate Oil MISSOURI0E3GAL 868 Liquid2102004000 Industrial Distillate Oil MISSOURI0E3GAL 908 Petroleum Distillate2102004000 Industrial Distillate Oil MISSOURI 27E3GAL-YR 58 Distillate Oil (No. 2)2102004000 Industrial Distillate Oil MISSOURI0E3GAL-YR127Gasoline2102004000 Industrial Distillate OilMISSOURI 10 E3GAL-YR 192 Methanol2102004000 Industrial Distillate Oil MISSOURI20E6FT3209Natural Gas2102004000 Industrial DistillateOil MISSOURI 1 E6GAL4Wastewater2102004000 Industrial Distillate Oil MISSOURI0EACH 364 Unit2102004000 Industrial Distillate Oil MISSOURI235MILE368Vehicle2102004000 Industrial Distillate Oil MISSOURI24TON133Grain2102004000 Industrial Distillate Oil MISSOURI0TON174Lime2102004000 Industrial Distillate Oil MISSOURI1,462,933TON 189 Material2102004000 Industrial Distillate Oil MISSOURI1TON 189 Material2102004000 Industrial Distillate Oil MISSOURI13TON 253 Product2102004000 Industrial Distillate Oil MISSOURI226TON 268 Raw Material2102004000 Industrial Distillate Oil MISSOURI0TON311Soybean Meal2102004000 Industrial Distillate Oil MISSOURI5TON849Hot Mix Asphalt46 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102004000 Industrial Distillate Oil MISSOURI2102005000 Industrial Residual Oil MISSOURI 345 E3GAL 279 Residual Oil2102005000 Industrial Residual Oil MISSOURI9 E3GAL 922 Residual Oil (No. 5)2102005000 Industrial Residual Oil MISSOURI 1,512 E3GAL 923 Residual Oil (No. 6)2102005000 Industrial Residual Oil MISSOURI2 E3GAL 924 Residual/Crude Oil2102005000 Industrial Residual Oil MISSOURI30TON174Lime2102005000 Industrial Residual Oil MISSOURI0TON 189 Material2102005000 Industrial Residual Oil MISSOURI0TON849Hot Mix Asphalt2102005000 Industrial Residual Oil MISSOURI2102006000 Industrial Natural Gas MISSOURI84ACRE-YR320Storage Area2102006000 Industrial Natural Gas MISSOURI0BALE740Cotton2102006000 Industrial Natural Gas MISSOURI25E2LB 253 Product2102006000 Industrial Natural Gas MISSOURI16E3EACH654Batteries2102006000 Industrial Natural Gas MISSOURI0E3FT3 189 Material2102006000 Industrial Natural Gas MISSOURI15E3GAL44Diesel2102006000 Industrial Natural Gas MISSOURI63E3GAL56Distillate Oil2102006000 Industrial Natural Gas MISSOURI233E3GAL 57 Distillate Oil (Diesel)2102006000 Industrial Natural Gas MISSOURI56E3GAL 58 Distillate Oil (No. 2)2102006000 Industrial Natural Gas MISSOURI21E3GAL178Liquified Petroleum Gas (LPG)2102006000 Industrial Natural Gas MISSOURI24E3GAL 189 Material2102006000 Industrial Natural Gas MISSOURI133E3GAL255Propane2102006000 Industrial Natural Gas MISSOURI123E3GAL823Distillate Oil (No. 1 & 2)2102006000 Industrial Natural Gas MISSOURI0E3GAL-YR 58 Distillate Oil (No. 2)2102006000 Industrial Natural Gas MISSOURI79E3GAL-YR127Gasoline2102006000 Industrial Natural Gas MISSOURI2E3GAL-YR374Crude Oil2102006000 Industrial Natural Gas MISSOURI11E3GAL-YR865Jet Kerosene2102006000 Industrial Natural Gas MISSOURI190E3GAL-YR868Liquid2102006000 Industrial Natural Gas MISSOURI5,202E3GAL-YR908Petroleum Distillate2102006000 Industrial Natural Gas MISSOURI 254,692 E6FT3 209 Natural Gas2102006000 Industrial Natural Gas MISSOURI0EACH 364 Unit2102006000 Industrial Natural Gas MISSOURI206EACH368Vehicle2102006000 Industrial Natural Gas MISSOURI97EACH712Circuit Boards2102006000 Industrial Natural Gas MISSOURI 26 GAL151Ink2102006000 Industrial Natural Gas MISSOURI 12 GAL 189 Material2102006000 Industrial Natural Gas MISSOURI 9 GAL305Solvent47 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102006000 Industrial Natural Gas MISSOURI 375 GAL720Coating2102006000 Industrial Natural Gas MISSOURI5MILE368Vehicle2102006000 Industrial Natural Gas MISSOURI32TON93Ethylene Oxide2102006000 Industrial Natural Gas MISSOURI59TON133Grain2102006000 Industrial Natural Gas MISSOURI153TON174Lime2102006000 Industrial Natural Gas MISSOURI1,780TON 189 Material2102006000 Industrial Natural Gas MISSOURI456TON 189 Material2102006000 Industrial Natural Gas MISSOURI15TON224P2O52102006000 Industrial Natural Gas MISSOURI121TON 253 Product2102006000 Industrial Natural Gas MISSOURI73TON 268 Raw Material2102006000 Industrial Natural Gas MISSOURI2TON289Sand2102006000 Industrial Natural Gas MISSOURI293TON305Solvent2102006000 Industrial Natural Gas MISSOURI348TON306Solvent in Coating2102006000 Industrial Natural Gas MISSOURI65TON311Soybean Meal2102006000 Industrial Natural Gas MISSOURI0TON315Starch2102006000 Industrial Natural Gas MISSOURI6TON516Metal2102006000 Industrial Natural Gas MISSOURI116TON516Metal2102006000 Industrial Natural Gas MISSOURI0TON673Brick2102006000 Industrial Natural Gas MISSOURI1TON699Charge2102006000 Industrial Natural Gas MISSOURI13TON723Coating Mix2102006000 Industrial Natural Gas MISSOURI2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI 4,610 E3GAL 178 Liquified Petroleum Gas (LPG)2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI 12,560 E3GAL 255 Propane2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI 9 E3GAL-YR374Crude Oil2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI 122 E3GAL-YR908Petroleum Distillate2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI2E3LB77Electrode2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI 9 GAL305Solvent2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI 39 GAL 720 Coating2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI186MILE368Vehicle2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI0TON15Wood2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI0TON133Grain2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI37TON 189 Material2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI29TON 268 Raw Material2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI10TON291Sawdust2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI0TON306Solvent in Coating48 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI0TON 723 Coating Mix2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI0TON849Hot Mix Asphalt2102007000 Industrial Liquified Petroleum Gas (LPG) MISSOURI2102008000 Industrial Wood MISSOURI13,640MILE368Vehicle2102008000 Industrial Wood MISSOURI 435,597 TON 15 Wood2102008000 Industrial Wood MISSOURI 366 TON 18 Wood Waste2102008000 Industrial Wood MISSOURI 133,848 TON 943 Wood/Bark2102011000 Industrial Kerosene MISSOURI 115 E3GAL 159 Jet Fuel2102011000 Industrial Kerosene MISSOURI0GAL305Solvent2102011000 Industrial Kerosene MISSOURI0MILE368Vehicle2102011000 Industrial Kerosene MISSOURI2103002000 Commercial/Institutional Bituminous/Subbituminous Coal MISSOURI20,339 TON 663 Bituminous Coal2103002000 Commercial/Institutional Bituminous/Subbituminous Coal MISSOURI2103004000 Commercial/InstitutionalDistillate Oil MISSOURI0E3GAL 44 Diesel2103004000 Commercial/Institutional DistillateOil MISSOURI 423 E3GAL56 Distillate Oil2103004000 Commercial/Institutional Distillate Oil MISSOURI 1,295 E3GAL 57 Distillate Oil (Diesel)2103004000 Commercial/Institutional Distillate Oil MISSOURI 8 E3GAL127Gasoline2103004000 Commercial/Institutional Distillate Oil MISSOURI 26,744 E3GAL 823 Distillate Oil (No. 1 & 2)2103004000 Commercial/Institutional Distillate OilMISSOURI 6 E3GAL 825 Distillate Oil (No. 4)2103004000 Commercial/InstitutionalDistillate Oil MISSOURI12E6FT3 209 Natural Gas2103004000 Commercial/InstitutionalDistillate Oil MISSOURI0MILE368Vehicle2103004000 Commercial/InstitutionalDistillate Oil MISSOURI1TON180Logs2103004000 Commercial/InstitutionalDistillate Oil MISSOURI0TON 253 Product2103004000 Commercial/InstitutionalDistillate Oil MISSOURI1TON291Sawdust2103004000 Commercial/InstitutionalDistillate Oil MISSOURI0TON306Solvent in Coating2103004000 Commercial/Institutional Distillate Oil MISSOURI2103005000 Commercial/Institutional ResidualOil MISSOURI 719 E3GAL 279 Residual Oil2103005000 Commercial/Institutional Residual OilMISSOURI 11 E3GAL 922 Residual Oil (No. 5)2103005000 Commercial/Institutional Residual OilMISSOURI 32 E3GAL 923 Residual Oil (No. 6)2103005000 Commercial/Institutional Residual Oil MISSOURI 4 E3GAL-YR58Distillate Oil (No. 2)2103005000 Commercial/Institutional Residual Oil MISSOURI2E6FT3209Natural Gas2103005000 Commercial/Institutional Residual Oil MISSOURI2103006000 Commercial/Institutional Natural Gas MISSOURI8ACRE-YR 320 Storage Area2103006000 Commercial/Institutional Natural Gas MISSOURI125E3GAL57Distillate Oil (Diesel)2103006000 Commercial/Institutional Natural Gas MISSOURI60E3GAL58Distillate Oil (No. 2)49 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2103006000 Commercial/Institutional Natural Gas MISSOURI1E3GAL127Gasoline2103006000 Commercial/Institutional Natural Gas MISSOURI1E3GAL305Solvent2103006000 Commercial/Institutional Natural Gas MISSOURI282E3GAL-YR58Distillate Oil (No. 2)2103006000 Commercial/Institutional Natural Gas MISSOURI69E3GAL-YR127Gasoline2103006000 Commercial/Institutional Natural Gas MISSOURI 40,033 E6FT3 209 Natural Gas2103006000 Commercial/Institutional Natural Gas MISSOURI62GAL 189 Material2103006000 Commercial/Institutional Natural Gas MISSOURI141GAL720Coating2103006000 Commercial/Institutional Natural Gas MISSOURI95MILE368Vehicle2103006000 Commercial/Institutional Natural Gas MISSOURI30TON65Dried Sludge2103006000 Commercial/Institutional Natural Gas MISSOURI5TON129Glaze2103006000 Commercial/Institutional Natural Gas MISSOURI29TON133Grain2103006000 Commercial/Institutional Natural Gas MISSOURI17TON151Ink2103006000 Commercial/Institutional Natural Gas MISSOURI0TON180Logs2103006000 Commercial/Institutional Natural Gas MISSOURI41TON 189 Material2103006000 Commercial/Institutional Natural Gas MISSOURI6TON224P2O52103006000 Commercial/Institutional Natural Gas MISSOURI16TON 253 Product2103006000 Commercial/Institutional Natural Gas MISSOURI355TON306Solvent in Coating2103006000 Commercial/Institutional Natural Gas MISSOURI39TON308Solvent in Ink2103006000 Commercial/Institutional Natural Gas MISSOURI8TON874Medical Waste2103006000 Commercial/Institutional Natural Gas MISSOURI2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) MISSOURI 25 E3GAL 178 Liquified Petroleum Gas (LPG)2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) MISSOURI 24,781 E3GAL 255 Propane2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) MISSOURI9E6FT3209Natural Gas2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) MISSOURI1TON 253 Product2103007000 Commercial/Institutional LiquifiedPetroleum Gas (LPG) MISSOURI2103008000 Commercial/Institutional Wood MISSOURI 25,448 TON 15 Wood2103008000 Commercial/Institutional Wood MISSOURI 128 TON 943 Wood/Bark2102002000 Industrial Bituminous/Subbituminous Coal NEBRASKA 45,820 TON2102004000 Industrial Distillate Oil NEBRASKA 137,269 E3GAL2102004000 Industrial Distillate Oil NEBRASKA2102005000 Industrial Residual Oil NEBRASKA 268 E3GAL2102006000 Industrial Natural Gas NEBRASKA 319,058 E3FT32102006000 Industrial Natural Gas NEBRASKA 7,733,748 E6FT32102006000 Industrial Natural Gas NEBRASKA232MASS1Waste Material2102006000 Industrial Natural Gas NEBRASKA50 of 53Area_SCCSCC_2Area SCC_3StateNameThroughputThroughputUnitsMaterialCodeMaterial2102007000 Industrial Liquified Petroleum Gas (LPG) NEBRASKA 48 E3GAL2102008000 Industrial Wood NEBRASKA 1,141 TON2103004000 Commercial/Institutional Distillate Oil NEBRASKA0E3GAL2103006000 Commercial/Institutional Natural Gas NEBRASKA 168,142 E6FT32103006000 Commercial/Institutional Natural Gas NEBRASKA22MASS1Waste Material2103006000 Commercial/Institutional Natural Gas NEBRASKA2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) NEBRASKA 4,866 E3GAL2103008000 Commercial/Institutional Wood NEBRASKA 9,398 TON2102001000 Industrial Anthracite Coal OKLAHOMA6452102002000 Industrial Bituminous/Subbituminous Coal OKLAHOMA2,181,4922102004000 Industrial Distillate Oil OKLAHOMA25,0212102005000 Industrial Residual Oil OKLAHOMA1,4632102006000 Industrial Natural Gas OKLAHOMA10,908,5132102007000 Industrial Liquified Petroleum Gas (LPG) OKLAHOMA02102008000 Industrial Wood OKLAHOMA114,6192103004000 Commercial/Institutional Distillate Oil OKLAHOMA212103006000 Commercial/Institutional Natural Gas OKLAHOMA228,8992102002000 Industrial Bituminous/Subbituminous Coal TEXAS2102004000 Industrial Distillate Oil TEXAS2102005000 Industrial Residual Oil TEXAS2102006000 Industrial Natural Gas TEXAS2102007000 Industrial Liquified Petroleum Gas (LPG) TEXAS2102008000 Industrial Wood TEXAS2102011000 Industrial Kerosene TEXAS2103004000 Commercial/Institutional Distillate Oil TEXAS2103006000 Commercial/Institutional Natural Gas TEXAS2103007000 Commercial/Institutional Liquified Petroleum Gas (LPG) TEXAS2103008000 Commercial/Institutional Wood TEXAS2103011000 Commercial/Institutional Kerosene TEXAS

# Appendix A-6

Inspection/Maintenance Input Table Developmen t Protocol for MOVES for Counties in the

St. Louis Ozone Nonattainment Area

EPA has technical guidance on appropriate input a ssumptions and sources of data for the use of MOVES 2010 in State Implementation Plan ( http://www.epa.gov/otaq/models/moves/420b10023.pdf ). Section 3.10 of this guidance document explains the appropriate assumptions a nd methods to be used when developing the I/M input table for MOVES 2010. This guidance has b een followed in the development of I/M input

Tables 2 – 6 at the end of this document. This document outlines the approach used to develop each parameter of these I/M input tables in MO VES. The goal in developing these I/M input tables is to accurately reflect the actual I/M program being implemented in the St. Louis

nonattainment area.

Pollutant Process ID

To begin development of the I/M input table, the default data for the I/M input table for St. Louis County was exported from the MOVES county data base manager. The default data included four different I/M test types. However, the actual St. Louis area only had two different test types (On-board diagnostics) OBD tests for the exhaust and evaporative systems. In the default I/M input table, these were the onl y two types of tests that were “turned on” along with the appropriate pollutant process IDs that would be impacted by each test. Therefore, the pollutant process IDs that were included in the default table for the two OB D tests were the same pollutant process IDs used in the I/M input table for the St. Louis nonattainment area. The other two tests included in the default data along with their asso ciated pollutant process IDs were still included in the I/M input table, bu t they were “turned off”.

Source Type ID

The St. Louis I/M program includes passenger cars a nd also trucks with a gross vehicle weight rating of 8,500 lbs. or less. Therefore, the three source type IDs included in the I/M input table for the St. Louis nonattainment area are passenge r cars, passenger trucks, and light commercial trucks (IDs = 21, 31, and 32).

Fuel Type ID

The St. Louis I/M program is applicable to bo th gasoline and diesel vehicles; however, MOVES only calculates an I/M benefit for gasoline vehicles. Therefore, the fuel type ID for gasoline was the only uel type ID used in the I/M input table for the St. Louis nonattainment area.

Inspection Frequency

### The St. Louis I/M program requires that emission be tested ever y two years, so the inspection frequency ID that represents biennial tests (ID = 2) was used in the I/M input table for the OBD tests applicable to the St . Louis nonattainment area.

Test Standards

The St. Louis I/M program is a centralized progr am with OBD tests for exhaust and evaporative systems on the vehicles. Therefore, the test standard IDs for exhaust OBD check and the evaporative system OBD check (IDs = 43 and 51) we re used in the I/M input table for the St.

Louis nonattainment area.

I/M Program ID This is an arbitrary number developed by the M OVES user to define a unique test given for vehicles within a range of model years. Therefore, I/M program IDs were arbitrarily assigned to the various unique tests within the St. Louis I/M program.

Beginning and Ending Model Years The St. Louis I/M program applies to gasoline vehicles with a m odel year of 1996 or later and it also applies to diesel vehicles with a model year of 1997 or later. Since the emissions inspection is required biennially, the endi ng model year would always be tw o years less than the emissions inventory year that is being developed. Ther efore, for the tests for gasoline vehicles, the beginning model year is 1996 and the ending model year is two years earlie r than the year for which MOVES is being run, and th e for diesel vehicles the be ginning model year is 1997 and the ending model year is two years earlier th an the year for which MOVES is being run.

Compliance Factor According to page 39 of the MOVES guidance doc ument the compliance factor is calculated with the following equation:

Compliance Factor = percent compliance rate x (100 – percent waiver rate) x regulatory class coverage adjustment.

Therefore, in order to calculate the compliance f actor for each source type included in the I/M program, the compliance rate, waiver rate, and regula tory class coverage adjustment needed to be determined. These three values were determined by the processes described below and then the compliance factors for each source type were calculated with the equation written above.

Compliance Rate The compliance rate was calculate d with the following equation:

Compliance Rate = Number of vehicles that we re tested over a two year period (2008 – 2009) / Population of vehicles that is theoretically subject to I/M during the same period.

### In order to determine the compliance rate, as it compares to the source type population by model year, the population of vehicles th at is theoretically subject to I/M first needed to be determined.

In May 2009, the Missouri Department of Reve nue (DOR) Vehicle Registration database was queried and a VIN decoder was us ed to separate the vehicle counts into Mobile 6.2 vehicle classes by model year. In the St. Louis nonattainm ent area, the Mobile 6 .2 vehicle classes that are subject to I/M include 1996 a nd newer light duty gasoline vehi cles, light duty gasoline trucks Class 1, light duty gasoline trucks Class 2, light du ty gasoline trucks Cla ss 3, light duty gasoline trucks Class 4, as well as 1997 and newer light duty diesel vehicles, light dut y diesel trucks Class 1, light duty diesel trucks Cla ss 2, light duty diesel trucks Clas s 3, and light duty diesel trucks

Class 4. Table 1 below shows the total combined population of these 10 vehicle classes within the appropriate model years by county in the St. Louis nonattainment area according the May

2009 DOR data.

Table 1. Vehicles Theoretically Subject to the I/M Program in the St. Louis Nonattainment Area

1996 and later 1997 and later County Light Duty Gas (1996 and newer) Light Duty Diesel (1997 and newer)
Franklin 73,300 328
Jefferson 150,998 484
St Charles 238,672 589 St Louis City 144,871 345 St Louis County 756,978 1,653

Total 1,364,819 3,399
Total Count 1,368,218



### The Air Program also queried the I/M report genera tor to determine the total number of vehicles,

which had their emissions tested at least once from January 1, 2008 through December 31, 2009. The query also included the tota l number of vehicles that receiv ed waivers during the same time period. Table 2 below, was genera ted with data from this query.

Table 2. Initially Tested Vehicles that R eceived a Waiver in the St. Louis I/M Program from January 1, 2008 through December 31, 2009

### Using the data from Tables 1 and 2 above the comp liance rate is calculated for the St. Louis I/M Program with the following equation:

Compliance Rate: (1,344,747 / 1,368,218) x 100% = 98.28%

Waiver Rate The waiver rate is the percentage of vehicles th at fail an initial I/M test and do not pass a retest, but do receive a certificate of compliance. Th e waiver rate was determined by dividing the

number of vehicles that received waiver s from January 1, 2008 through December 31, 2009 by

the total number of vehicles that were test ed at least once during the same time period. Therefore, the waiver rate was calculated fo r the St. Louis I/M Progr am with the following equation:

Waiver Rate: (4,761 / 1,344,747) X 100% = 0.35%

Regulatory Class Coverage Adjustment The regulatory class coverage adjustment is an adjustment that accoun ts for the fraction of vehicles within a source type th at are covered by the I/M program. Since the I/M program in St. Louis exempts vehicles with a gross vehicl e weight rating above 8,500 lbs., the compliance factor needs to reflect the percen tage of vehicles in the source types subject to I/M that are exempt because of their GVWR. Table A.3 in the Appendix of the MOVES Technical Guidance Document was used to develop adjustments to the compliance factor to account for this discrepancy. The adjustments are percentages of vehicle miles traveled by the various regulatory weight classes within a source type. The corre sponding adjustment factors used for the three source categories are as follow: Passenger cars: 100% Passenger Trucks: 94% Light Commercial Trucks: 88%

### Calculating the Compliance Factor Based on the calculations listed above the compliance factor for each source category impacted by the I/M program in St. Louis is listed below.

Passenger cars: 98.28% x ( 100% - 0.35%) x 100% = 97.94% Passenger Trucks: 98.28% x (100% - 0.35%) x 94% = 92.06% Light Commercial Trucks: 98.28% x (100% - 0.35%) x 88% = 86.18%