# Appendix B

Base Year 2002 Emissions Inventory
and Documentation

# 2002 BASE YEAR EMISSIONS INVENTORY

FOR THE 

# W ASHINGTON 

# DC-MD-VA
P M2.5 

# N ONATTAINMENT 

# A REA

Prepared by:

District of Columbia Depa rtment of the Environment Maryland Department of the Environment, Virginia Department of Environmental Quality,
and Metropolitan Washington Council of Governments

on behalf of the Metropolitan Washington Air Quality CommitteeTABLE OF CONTENTS

1.0 INTRODUCTION ...........................................................................................................B- 1 1.1 Overview and Background ..........................................................................................B-2 1.2 PM2.5 Nonattainment Geographic Area......................................................................B-3 1.3 Temporal Resolution....................................................................................................B-3 1.4 Quality Assurance Policy and Objectives....................................................................B-4
1.5 Plan Information Sources.............................................................................................B-4 1.6 Summary of the Base Year Emissions Inventory ........................................................B-4
1.7 Document Contents......................................................................................................B-5

2.0 POINT SOURCES...........................................................................................................B- 6
2.1 Introduction.............................................................................................................. ....B-7 2.2 Compilation and Documentation of Point Source Emissions......................................B-7 2.3 Quasi-Point Source (Andrews Air Force Base)...........................................................B-7 2.4 Point Source Summary – Base Y ear 2002 Sip Emission Inventory ..........................B-11

3.0 AREA AND NONROAD SOURCES...........................................................................B-12 3.1 Introduction and Scope ..............................................................................................B-13 3.2 Methodology and Approach ......................................................................................B-13 3.2.1 Source and Category Identification ......................................................................B-14 3.2.2 Emission Estimation Approach.............................................................................B-14 3.3 Summary of Emission Results for Area Sources Categories......................................B-14 3.4 Discussion of Area Source Categories........................................................................B-15
3.4.1 Gasoline and Diesel Distribution..........................................................................B-15 3.4.1.1 Tank Truck Unloading (Stage I)........................................................................B-15 3.4.1.2 Vehicle Fueling (Stage I I) and Underground Tank Breathing...........................B-18
3.4.1.3 Losses from Gasoline Tank Trucks in Transit...................................................B-20 3.4.1.4 Aircraft Refueling ..............................................................................................B-22 3.4.1.5 Petroleum Vessel Loading and Unloading Losses.............................................B-24 3.4.2 Stationary Source Solvent Evaporation ................................................................B-26 3.4.2.1 Dry Cleaning......................................................................................................B-26 3.4.2.2 Surface Cleaning................................................................................................B-27 3.4.2.3 Surface Coating..................................................................................................B-2 9 3.4.2.4 Graphic Arts.......................................................................................................B -32 3.4.2.5 Asphalt Paving...................................................................................................B-34 3.4.2.6 Pesticide Application .........................................................................................B-36
3.4.2.7 Commercial/Consumer Solvent Use..................................................................B-38 3.4.2.8 Synthetic Organic Chemical Storage Tanks ......................................................B-40 3.4.2.9 Barge, Tank, Tank Truck, Rail Car and Drum Cleaning...................................B-40
3.4.2.10 Industrial Adhesives and Sealants ...................................................................B-42
3.4.2.11 Portable Fuel Containers..................................................................................B-44 3.4.3 Bioprocess Sources ...............................................................................................B-50
3.4.3.1 Bakeries..............................................................................................................B-50
3.4.3.2 Breweries ...........................................................................................................B-52
3.4.3.3 Wineries ............................................................................................................ .B-543.4.3.4 Distilleries........................................................................................................ ..B-56 3.4.4 Waste Management Practices ...............................................................................B-57 3.4.4.1 Publicly Owned Wastewater Treatment Works (POTWs) ................................B-57
3.4.4.2 Industrial Wastewater Treatment.......................................................................B-59 3.4.4.3 Hazardous Waste Treatment, Storage, and Disposal Facilities (TSDFs) ..........B-60 3.4.4.4 Municipal Solid Waste Landfills .......................................................................B-61 3.4.4.5 Solid Waste Burning..........................................................................................B-62
3.4.4.5.1 On-Site Incineration........................................................................................B-62 3.4.4.5.2 Open Burning..................................................................................................B-64 3.4.5 Small Stationary Source – Re sidential/Commercial/Industrial Fuel Combustion.B-66 3.4.5.1 Fuel Oil Consumption........................................................................................B-66 3.4.5.2 Coal Consumption .............................................................................................B-69 3.4.5.3 Natural Gas and Liquefied Pe troleum Gas (LPG) Consumption.......................B-71 3.4.5.4 Other Fuels Consumption (Residential Wood Burning)....................................B-74
3.4.5.5 Small Electric Utility Boilers.............................................................................B-77
3.4.6 Other Area Sources...............................................................................................B-78 3.4.6.1 Slash/Prescribed Burning and Forest Fires........................................................B-78 3.4.6.2 Agricultural Burning..........................................................................................B-81
3.4.6.3 Structure Fires....................................................................................................B -82
3.4.6.4 Orchard Heaters .................................................................................................B-84 3.4.6.5 Leaking Underground Storage Tanks ................................................................B-85 3.4.6.6 Oil Spills .......................................................................................................... ..B-87 3.4.6.7 Commercial Cooking.........................................................................................B-89 3.4.6.8 Composting........................................................................................................B-91
3.4.6.9 Motor Vehicle Fires ...........................................................................................B-92
3.4.6.10 Construction.....................................................................................................B-93 3.4.6.11 Mining and Quarying.......................................................................................B-94 3.4.6.12 Crop Tilling......................................................................................................B -95 3.4.6.13 Livestock, Beef Cattle, Feedlo ts, Dust Kicked-up by Hooves ........................B-96 3.4.6.14 Fugitive Emissions – Paved and Unpaved Roads............................................B-97 3.4.7 Non-Road Engines and Vehicles ..........................................................................B-98
3.4.7.1 Commercial Aviation.........................................................................................B-98
3.4.7.2 General Aviation and Air Taxi ..........................................................................B-99 3.4.7.3 Military Aviation .............................................................................................B-101
3.4.7.4 Railroad Locomotives......................................................................................B-103 3.4.7.5 Aircraft Auxiliary Power Units........................................................................B-105
3.4.7.6 Commercial Marine Vessels............................................................................B-106
3.4.8 EPA Non-Road Source Estimates.......................................................................B-107 3.4.8.1 Description.......................................................................................................B-107
3.4.8.2 Method And Data Sources...............................................................................B-107
3.4.8.3 Results............................................................................................................. .B-110

4.0 ONROAD MOBILE SOURCES ................................................................................B-111
4.1 Introduction.............................................................................................................. B-111 4.2 Summary of On-Road Mobile Source Emissions....................................................B-1125.0 QUALITY ASSURANCE PROCEDURES...............................................................B-114
District of Columbia 5.0 Quality Assurance Procedures .................................................................................B-115 5.1 Reality Check/Peer Review Check ..........................................................................B-115 5.2 Sample Calculations.................................................................................................B-116 5.3 Sensitivity Analysis .................................................................................................B-116 5.4 Standard Range Checks ...........................................................................................B-117
5.5 Corrective Action Plan.............................................................................................B-117 Maryland 5.0 Quality Assurance Procedures ................................................................................. B-118 5.1 Reality Check/Peer Review Check ..........................................................................B-118 5.2 Sample Calculations.................................................................................................B-119 5.3 Sensitivity Analysis .................................................................................................B-119 5.4 Standard Range Checks ...........................................................................................B-120
5.5 Corrective Action Plan.............................................................................................B-120 5.6 Quality Assurance Final Report...............................................................................B-120 Virginia 5.0 Quality Assurance Procedures ................................................................................. B-121 5.1 Reality Check/Peer Review Check ..........................................................................B-121 5.2 Sample Calculations.................................................................................................B-122 5.3 Sensitivity Analysis .................................................................................................B-122 5.4 Standard Range Checks ...........................................................................................B-123
5.5 Corrective Action Plan.............................................................................................B-123

List of Attachments

A1. BY 2002 Point Source Emissions Summary
A2. BY 2002 Point Source Emissions Files – NIF3.0 Format (Available on a CD on request)
B1. Technical Memorandum on Co mmercial Cooking Emissions
B2. Technical Memorandum on Composting Emissions B3. BY 2002 Emissions Inventory Document for Maryland B4. Airport Emissions (Metropolitan Washington Airports Authority) B5. Portable Fuel Container Calculation Methodology for Virginia B6. BY 2002 PM2.5, PM10, and SO2 Emissions Calculation Methodology for Virginia C1. BY 2002 Area and Nonroad Source Emissions Summary C2. BY 2002 Area & Non-Nonroad Model Emissions Files – NIF3.0 Format (Available on a CD on request)
C3. BY 2002 Nonroad Model Emissions Files - NI F3.0 Format (Available on a CD on request)
D1. BY 2002 Onroad Mobile Source Emi ssions Inventory and Documentation D2. BY 2002 Onroad Mobile Model Input & Ou tput Files (Available on a CD on request)
D3. BY 2002 Onroad Mobile Source Emissions - NIF3.0 Format (Available on a CD on requestB-1 

# Chapter 1

IntroductionB-2 1.0 INTRODUCTION

1.1 Overview and Background

This document contains a de tailed explanation of the 2002 base year SIP emissions inventory for stationary, area, nonroad and mobile anthr opogenic sources and biogenic sources for nitrogen dioxide (NOx), vol atile organic compound (VOC), PM2.5, PM10, sulfur dioxide (SO2), and ammonia (NH3) emissions for the Washington, DC-VA-MD PM2.5 nonattainment region.

The federal Clean Air Act (CAA), 42 U.S.C.A § 7401 et seq , as amended by the Clean Air Act Amendments of 1990, P.L. 101-549, (referred to hereafter as the Act) requires all
areas of the nation to attain and maintain compliance with the federal ambient air quality
standards. These federal standards are desi gned to protect the public health and welfare from these six criteria pollutants. These sta ndards are referred to as the National Ambient Air Quality Standards (NAAQS).

The base year 2002 emissions inventor y covers the Washington, DC-MD-VA PM2.5 nonattainment area. The goal of a base year inventory is to pr ovide guidance on the development of a reliable inventory, the qual ity of emissions data collected and provide for acceptable documentation and reporting of this information.

The inventory document includes emissions from point sources, mobile sources, biogenic emissions, non-road mobile sources, and ar ea sources. The Metropo litan Washington Council of Government (MWCOG) prepared the nonroad and onroad portions of the inventory. Air quality staff of the District Department of the Environment (DDOE), Maryland Department of the Environment (MDE), and Virginia Department of Environmental Quality (VDEQ) herein refe rred to as “State Air Agencies”, in collaboration with MWCOG, developed the point and area source emissions estimates.

MWCOG used the Non-Road Mobile Emissions Model, NONROAD2005, for developing all nonroad emissions except, commercial marine vessels, aircraft, and locomotives, which are developed separa tely. MWCOG developed the 2002 onroad mobile inventory using MOBILE6.2 mode l and a Travel Demand Model (TDM).

The applications for emissions inventory data include use of the data in annual trends reports, State Implementation Plans (SIPs) , compliance demonstrations, emissions trading, emissions fees programs, and in mode ling activities designed to evaluate ambient air concentrations encountered by the gene ral public. For the SIP program, the air emission inventory is a fundamental building block in developing an air quality control and maintenance strategy. Section 172, Part C, of the Clean Air Act (CAA) as amended in 1990, which addresses SIP requirements, states that “. . . plan provisions shall include a comprehensive, accurate, current inventory of actual emissions from all sources or the relevant pollutants or pollutants in such ar ea . . .”. Regulatory agencies and industrial facilities rely on emission inventories on an ongoing basis as indicators of air quality changes and for setting permit requirements.B-3 The end use of emission inventories require s that they be of the highest quality obtainable. They are the foundati on of air quality decisions. I nventory quality is critical to defining realistic regulations and a ttainment strategies. Deficiencies and inconsistencies in existing compilation pro cesses accentuate the need for developing and implementing more uniform and systematic a pproaches to collecti ng and reporting data. One of the primary goals of the Base Year is to improve the quality of inventory data
collection so that it is a reliable source of information for sound decision-making.

1.2 PM2.5 Nonattainment Geographic Area

On January, 2005, EPA designated the followi ng jurisdictions in Washington, DC-MDVA region as nonattainment areas for the PM2.5 standard.

• District of Columbia

• Charles County, Maryland

• Frederick County, Maryland

• Montgomery County, Maryland

• Prince George's County, Maryland

• Arlington County, Virginia

• Alexandria City, Virginia

• Fairfax County, Virginia (inc ludes independent Fairfax and Falls Church cities)

• Loudoun County, Virginia

• Prince William County, Virginia (include s independent Manassas and Manassas Park cities)

1.3 Temporal Resolution

Another step of inventory development is th e temporal allocation of emissions. Because air quality modeling attempts to represent the actual physical and chemical processes as they occur over a specific duration of time, it is important that the temporal allocation of emissions be as accurate as possible. Temporal allocation can be thought of as an accounting of emissions variation over time. The simplest temporal allocation is for a steady-state emissions source that continually releases emissions at the same rate all the time. Under actual conditions, however, steady- state emission sources are quite rare. Instead, under actual conditions, emissions s ources may operate only in the winter not operate on Sundays, or their activity may peak during certain hours of the day.

The planning period for the PM2.5 emissions inventory covers the entire year. For the purpose of submitting the base year 2002 SIP inventory to EPA, annual emissions are estimated for VOC, NOx, PM2.5, PM10, SO2, and NH3.B-4 1.4 Quality Assurance Policy and Objectives

In order to provide data of sufficient quality for mainte nance planning needs, quality assurance (QA) and quality c ontrol (QC) procedures are im plemented as part of the inventory process. The procedures addr ess data quality objectives of accuracy, completeness, comparability and representativeness. A brief discussion of the data quality objectives is given below.

Data quality objectives of accuracy, comple teness, comparability, and representativeness
are addressed to ensure an i nventory of high quality. The ta rget goals for each objective
are listed below.

Accuracy: All estimates must be calculated and documented using acceptable methods. Individual source requirements and availability of data and resources will affect the
estimation method selection.

Completeness: Completeness is addressed by ensu ring that all applicable source categories are included in the inventory, and that all information required to estimate emissions is present. Applicable source categories are listed in Appendix A.

Comparability: Data will be compared to the most recent base year inventories: 1990 for VOC, NOx, and CO. Any discre pancies (data outliers) gr eater than 20% involving sources that made up greater than 5% of the 1990 inventories will be corrected or justified.

Representativeness: Actual 2002 annual emissions will be calculated for the base year inventory. Local data will be used in inventory calcul ations wherever possible.

1.5 Plan Information Sources This plan draws upon inventory, quality assura nce, and emissions projections guidance available from state and federal agencies and partnerships. The effort will also draw upon experience gained with the 1990 base y ear SIP and 1996/1999/2002 periodic emission inventory reviews.

A primary source of emissions inventory data is the 2002 Consolidated Emissions Reporting Rule (CERR) submittal recently subm itted to the U.S. EPA by MDE, VDEQ,
and DDOE. Another source of information is EPA’s National Emissions Inventory (NEI). Virginia area and a few nonroad source emissions were acquired from VISTAS (Visibility Improvement – State and Tr ibal Association of the Southeast).

1.6 Summary of the Base Year Emissions Inventory

A summary of annual emissi ons of PM2.5, PM10, VOC, NOx, SO2, and NH3 in tons per year for Washington, DC-MD-VA nonattainment region is shown in Table 1-1. For summaries relating to the individual sections of the inventory, such as point sources, referB-5 to the beginning of the respective section. Th ere also may be slight differences between the executive summary table and the section tables due to rounding.

Table 1-1 2002 Base Year SIP Emission Inventories
Annual Emissions Washington, DC-VA-MD Nonattainment Area

Source Category PM2.5 (TPY) NOx (TPY) SO2 (TPY) VOC (TPY) NH3 (TPY) PM10 (TPY)

Point 4,169.55 6,1342.56 204,651.84 1,901.86 36.46 6,387.42

Area 13,666.87 13,954.02 12,335.56 72,377.39 3,670.14 52,611.59

Non-road 2,618.31 2,6722.11 2,833.10 30,492.27 0.00 2,748.53

On-road 1,724.70 97,575.31 3,539.98 43,903.91 4,245.62 2,472.19
Anthropogenic Subtotal 22,179.44 199,594.00 223,360.49 148,675.43 7,952.22 64,219.72

1.7 Document Contents

Chapter 2 Presents the methodology for determining 2002 annual emissions from point sources.

Chapter 3 Presents the methodology for determining 2002 annual emissions from
area and non-road sources.

Chapter 4 Presents the methodology for de termining 2002 annual em issions from onroad mobile sources.

Chapter 5 Presents the QA/QC plan for Washington, DC-MD-VA PM2.5 attainment region 2002 annual emissions.

Detailed point, area, nonroad, and onroad m obile emissions tables are presented in Attachments A1, C1, and D1 of this document.

# Chapter 2

Point Sources

B-62.0 POINT SOURCES

2.1 Introduction

This section documents the development of the Washington, DC-MD-VA nonattainment area stationary point source emissions inventory a nd serves to characterize the point source component of the emissions inventory by de scribing the 2002 annual emissions estimation techniques. The point source invent ory consists of actual emissions for the entire period in the year 2002, and includes sources in the geographic area of the Washington DC-MD-VA
nonattainment area.

The Virginia Department of Environmental Qu ality, Maryland Department of Environment and the District of Columbia Depa rtment of Health are the responsible state air agencies for developing emission inventories and maintaining the data. MWCOG compiled annual emissions data provided by the state agencies for inclusion in this periodic emissions inventories document.

2.2 Compilation and Documentatio n of Point Source Emissions

District Department of the Environment (DDOE), the Maryland Department of the Environment (MDE), and the Virginia Department of Envir onmental Quality (VDEQ) maintain substantial databases of both small and large air emission sources . The list of point s ources in this inventory was developed by applying the appropriate thresholds to the emission levels in the database to differentiate between point and ar ea stationary sources. Sources with emission levels greater than the threshold or sources previously included in Periodic Emissions Inventory submittals are by definition point sources while sources with emi ssions levels less than the thresholds are by
definition area sources.

Full documentation on point sources and emissions in individual states are maintained by DDOE, MDE, and VDEQ.

Appendix A provides a detailed description of the total poi nt source emissions for the Washington region. Detailed point source emissions are being provided sepa rately in electronic format (NIF3.0) as Appendix A2 of this document.

2.3 Quasi-Point Source (A ndrews Air Force Base)

The Maryland Department of the Environment has identified Andrews Air Force Base as a point
source due to its size and/or function. This estab lishment contains a wide variety of air emission sources, including traditional point sources, on-road mobile sources, off-road mobile sources and area sources. For this particular establishment, the emissions are tota led under a single point source and summary documents include this “quasi-point” source as a point source.

Andrews Air Force Base (ICAO code KADW) is a United States Air Force base near Washington, DC and the home base of the U. S. presidential aircraft, Air Force One.

B-7Emission Source Categories MDE staff reviewed emission estimates prepar ed for Andrews Air Force Base by a private
contractor. These emission estimates included data for the following source categories:

• Mobile Onroad Source Emissions LDGV, LDGT12, LDGT34, HDGV / Buses, MC, LDDV, LDDT, HDDBT, HDDV, HDDBS, Heavy Duty Trucks , Light Duty Vehicles

• Mobile Nonroad Source Emissions Nonroad Mobile – Recreational, Construction, Industrial, Lawn and Garden, Agricultural, Gas-Fired Non-road vehicle-4-stroke gaso line engine, Gas-Fired Non-road vehicle-2- stroke gasoline engine, Aircraft - All Airc raft Types and Operations, Emissions from military aviation aircraft landing and take off, Emissions from commercial aviation aircraft landing and takeoff, Diesel Generators, Off-highway Vehicle Gasoline, 2-Stroke Total without APUs, Off-highway Vehicle Ga soline, 4-Stroke Total without APUs, Offhighway Vehicle Gasoline, 4-Stroke APU em issions, Off-highway Vehicle Diesel APU emissions, Aircraft Ground Equipment - All Gasoline Engines and all JP-8 Engines

• Point Source Emissions

o MDE staff also reviewed and includ ed emission estimates from emission certification reports prepared by Andrew s Air Force Base and submitted on an annual basis to MDE’s Compliance and Enforcement Program. These emission estimates include major sources.

Emission Estimation Methodologies Methodologies varied by source category. A brie f synopsis of the methodologies is presented
below.

Mobile On-Road Source Emissions The Andrews AFB on-road vehicle inventory consists of a mix of light- and heavy-duty gasoline-, diesel-, and natura l gas-powered government-, a nd privately owned vehicles (POVs). POVs include vehicles owned by both daily employees and weekend personnel. The inventory contains the vehicle type, m odel year, number of vehicles, and annual onbase mileage. To distinguish leased Gene ral Services Administration (GSA) governmentowned vehicles (GOVs) from the regular fleet, vehicle tag numbers are provided in cases where they are known.

On the basis of inventory data provided by vehicle maintenance personnel, governmentowned vehicles (GOVs) were grouped into eight vehicle categories according to vehicle type, gross vehicle weight (GVW), and fuel type. The 2002 mileage for each vehicle was provided by vehicle maintenance personnel, as were estimates of on-base mileage or a percentage of the total miles per vehi cle that were driven on the base.

Emissions were calculated only for the estimated miles and hours of on-base vehicle and equipment operation. Miles traveled off the base were not included in the emission calculations. The Fifth Edition of AP-42, Volu me II includes the emission factors for NOx,

B-8CO, and VOC, which were calculated us ing EPA’s MOBILE 5 model for gasoline and diesel operated vehicles. AP -42 has not been updated with NOx, CO, and VOC emission
factors from the latest version of EPA’ s MOBILE 6.2.03 model, rel eased in October 2002. Therefore, the emission factors for on-road vehicles were obtained by running the
MOBILE 6.2.03 model. The MOBI LE model DOHs not address compressed natural gas vehicles, so emission factors for these vehi cles have been obtained from 40CFR86.1708- 99, 40CFR88.105-94, and 40CFR88.104.94.

Emission estimates for privately owned vehi cles (POVs) are based on traffic studies supplied by base personnel (89th AW Civ il Engineering, July 2004). Andrews AFB has approximately 61, 738 vehicles traveling on base each workday. This number assumes a working schedule of employees of 40 hours per week. In addition, 25% of the daily personnel are assumed to be on the base on the weekends.

The emission factors were used in the follo wing equation to estimate annual emissions:

E = V * F * C

Where:
E = Annual emissions of particular polluta nt from each vehicle category (lb/yr)
V = Vehicle miles traveled on-base per ye ar for each vehicle category (mi/yr)
F = Average model year emission factor in the applicable vehicle category (g/mi)
C = Conversion factor (2.205 

### x 10 lb/g)

Mobile Nonroad Mobile Source Emissions The Andrews AFB non-road vehicle inventory consists of various equipment including forklifts, loaders, riding lawn care equipm ent, and towing equipment. The inventory contains the equipment name, model year, hor sepower rating, number of vehicles, fuel type, engine cycle type, a nd operating hours for CY 2002. The inventory specifies whether the operating hours are a total operating time fo r CY 2002 for the number of units listed or an operating time for each unit.

Criteria pollutant and HAP emission factors were obtained from Air Emissions Inventory Guidance Document for Mobile Sources at Ai r Force Installations, United States Air Force Institute for Environment, Safety & Occupational Health Risk Analysis (IERA), January 2002

, which includes the emission fact ors used in EPA’s NONROAD 2002a
model.

The Andrews AFB aircraft operati ons inventory consists of info rmation related to landings and takeoffs (LTOs), touch and go’s (T&Gs), low approaches (LAs), and trim and power checks (T&PCs). Calendar year 2002 was used for the calculations of the baseline emissions inventory because 2002 is the baselin e year selected by the MDE for use in the revision of its SIP. The inventory contains the aircraft type a nd manufacturer, engine model and manufacturer, the number of LTOs, T&Gs, LAs, and T&PCs. The calendar year 2002 inventory was generated using informati on compiled from the Aerial Port Squadron,

B-9B-10 the Andrews AFB Federal Aviation Admini stration (FAA) Liason, and Allan Holtzm an, Andrews AFB Air Quality Program Manager. This inventory will also be submitted to MDE for incorporation into EDMS (version 4.4).

Activity An activity level of 7 days a week with no seasonal adjustm ent factor was used.

Emission Factors Emission factors were derived from the ED MS Airport Em ission Model, Version 4.4; EPA's NON-ROAD 2002 model; and EPA's MOBILE 6.02.03 model.2.4 POINT SOURCE SUMMARY – BASE YEAR2002 SIP EMISSION INVENTORYPoint Source Emissions – Base Year 2002 Annual Emissions Inventory (Tons Per Year)Metropolitan Washington NAA1

Pollutant C County

harles o airfax o o illiam anassas istrict Of

Fredrck County Montgomer y County Prince George's County Arlington C unty Alexandria City F County Fairfax City L udoun C unty Prince W County M City D Columbia MD Total VA Total NAA TotalPM2.5-Direct2397.62665.5345.73388.42220.4219.25303.222.82126.533497.31545.714169.55NOx18979.261992.538573.2316284.4133.886315.352234.0977.285494.3640.691317.4645829.4314195.6761342.56SO271397.886734.0934038.8852613.215.9516144.95132.6426.6821078.2311.792467.55164784.0637400.23204651.84VOC117.32299.04129.64566.1610.0347.36245.3589.41114.66193.801.3287.761112.16701.941901.86NH322.333.000.0011.1325.330.0036.46PM103786.77841.9149.22530.3312.73501.8151.9219.71398.9112.55181.565208.23997.636387.421 There is no PM2.5, NOx, SO2, VOC, NH3, and PM10 emissions for the Virginia Independent Cities ofFalls Church and Manassas Park.Point source inventory of Prince George'scounty includes quasi- point source inventoryfrom Andrews AFB (Refer to Appendix A -Maryland Point Source Emissions).B-11

# Chapter 3

Area and Nonroad Sources

B-123.0 AREA AND NONROAD SOURCES

3.1 Introduction and Scope

This document contains a de tailed explanation of how th e base year 2002 emissions inventory for area and nonroad sources of PM2.5-Primary (also known as PM2.5-Direct), sulfur dioxide, nitrogen oxides, volatile organic compounds, ammonia, and PM10- Primary (also known as PM10-Direct) was devel oped. The area source inventories for the entire year in 2002 were prepared by the state air agencies. Th e MWCOG staff compiled the states’ data for including in this SI P inventory document. Detailed area and nonNonroad model source emissions are being pr ovided separately in electronic format (NIF3.0) as Attachment C2 of this document. Unless mentioned otherwise, “Staff” in this section is referred specifically to the staff at State Air Agencies of Maryland, Virginia,
and the District of Columbia.

Area sources include stationary sources not included in the states' point source inventories, as well as "qua si" stationary sources such as facilities, operations or processes (except for Andrews Air Force Base in Maryland) whose activities produce
emissions and non-road vehicles such as air port activities, lawn a nd garden equipment, construction equipment and recreational boating.

All questions or comments regarding the contents of this document should be directed to the respective state/district air ag ency in the metropolitan area.

3.2 Methodology and Approach

The inventory is broken down by pollutant source, and each source is broken down into the following parts:

• Description - explains what the source is and why it is relevant to the inventory.

• Methods and data sources - provides all data sources and a narrative on exactly how the emissions were computed.

• Factors - provides all the necessary i nputs for a computation, excluding the surrogate activity data, which is provided in the appendices.

• Equation - enables the user to reprodu ce the estimates once all the necessary parameters are obtained.

• Summary of jurisdictional estimates - pr ovides a summary table listing emissions estimates for the source by county and pollutant.

Jurisdictional estimates are provided for a ll six pollutants, where appropriate.

Tables at the end of area source methods sec tion list the activity, control, and emission factors applied by the staff in compiling emissions estimates. In an effort to reduce clutter, data is presented in columns, with the indicated value prevailing down the length
of the column until another value is encountered.

B-13B-14 3.2.1 Source and Category Identification

All of the area source categories contai ned in the EPA Procedures document 1 , herein
referred to as “Procedures” were evaluated for emission estimates for the Washington,
DC-MD-VA PM2.5 nonattainment area. Where sources were not estimated to produce emissions, the estimate is equal to zero.

3.2.2 Emission Estimation Approach

Area source estimates were generally calcula ted using the recommended guidance in the EPA Procedures document. Exceptions to the recommended approaches , and selection of the approach, are detailed in the individua l source category discussions. While VOC and NOx emissions for Virginia and the District of Columbia were prepared by their respective state air agencies, PM2.5, PM10, SO 2, and NH3 emissions were prepared by the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) and the Mid-Atlantic/Northeast Visibility Union (MANE-VU). VISTAS and MANE-VU were responsible for performing modeling a nd planning studies for regional haze and visibility issues for southeastern and mid-A tlantic and northeastern states respectively.
MWCOG staff collected all area and non-nonr oad model from VISTAS and the DDOE provided these emissions based on MANE- VU data. MWCOW staff later on revised VISTAS emissions for a few source categorie s for Virginia to include most updated emissions. While details on methodologi es to calculate PM2.5, PM10, and SO2 emissions for Virginia for different source ca tegories are being provided in a separate attachment (Attachment B6), the same can be found for the District of Columbia in the
document titled “ Technical Support Document For 2002 MANE-VU SIP Modeling Inventories, Version 3, November 20, 2006; Prepared for the Mid-Atlantic/Northeast Visibility Union (MANE-VU) by E.H. Pechan & Associates, Inc.” available from the web-site of the Mid-Atlantic Region al Air Management Association, Inc (http://www.marama.org). Ma ryland has provided detailed documentation of emission estimation methods, emission factors, and da ta sources for its area and nonroad source VOC, NOx, PM2.5, PM10, SO2, and NH3 emis sions in the following report:

2002 Base Year State Implementation Plan Emissions Inventory and Methodologies for PM2.5 and Precursors; Prepared for U.S. Environm ental Protection Agency by Maryland Department of the Environment.

Individuals are referred to th is report for further detail s on Maryland’s area and nonnonroad model source inventory methods, which has been provided as Attachment B3 of this document for a quick reference.

3.3 Summary of Emission Results for Area Sources categories

A detailed breakout of pollutant type by sour ce category and jurisdic tion can be found in
Attachment C1 of this document.

1 Procedures for the Preparation of Emission Inventories for Carbon monoxide and Precursors of Ozone – Vol. I: General Guidance for Stationary Sources (EPA-450/4-91-016), May 1991.3.4 Discussion of Area Source Categories

3.4.1 Gasoline and Diesel Distribution

3.4.1.1 Tank Truck Unloading (Stage I)

Most gasoline dispensing outlets emit less th an 10 tons VOC per year and therefore are generally inventoried using area source me thods. One of the sources of such VOC emissions at gasoline dispensing outlets is th e vapor lost during tank truck unloading into underground storage tanks. The amount of va por lost is depende nt upon the filling method used for the storage tank in question.

Method and Data Sources:

Staff followed the procedures and methods set forth in the Emission Inventory Improvement Program (EIIP).

Data for fuel sales were obtained from st ate fuel sale data (gallons) and were apportioned to each county in the nonattainme nt area. In Virginia, apportionment by county was done by using county retail fuel sales, obtained from 1997 Census of Retail
Trade , as a percentage of states retail fuel sales. These percentages were applied to
statewide fuel sales data to obtain the county estimates.

After apportionment by county/city, the data were further broken down according to filling methods: submerged, balanced submerged, and splash. Since "balanced submerged" is the only controlled filli ng method, it was the only method for which control efficiency, rule pe netration and rule effectiv eness were calculated.

Emissions factors taken from AP-42, Table 4.4-7, were adjusted based upon a regional measured gasoline RVP of 6.8 psi and a study temperature of 82 degrees F. A 365 days/year (30.42 days/month) activity period was used based on the recommendation of DC-MD-VA air management staff. See the document entitled “1990 Base Year Emissions Inventory for St ationary Anthropogenic, Bi ogenic Sources, and Highway vehicle Emissions of Ozone Precursors in the Washington, DC-MD-VA Metropolitan
Statistical Nonattainment Area”

, prepared for The District of Columbia, Maryland, and Virginia by the Metropolitan Washington C ouncil of Governments dated September 22,
1993 , herein referred to as “1990 Inventor y Document” for a deta iled explanation of
these calculations in Attachme nt A beginning on Page 3-5.

B-15Factors:

Filling
Method Filling Method Apportionment (Nonattainment area) Filling Losses (lbs/kgal)

DC VA
Balanced Submerged 100% 100% 6.0

Emission Controls Rule Penetration Control Efficiency Rule Effectiveness Stage I Vapor Recovery (Balanced Submerged only)
-- District 100% 95% 80% -- Virginia 100% 90% 70%
Unit Conversion Factor 0.0005 tons/lb Activity Days per Period 30.42 days/month

Equation: SFS x (CRS/SRS) x [(FM1 x EF1) + {[1 - (CP x CE x RE)] x (FM2 x EF2)} + (FM3 x EF3)] x CF / AD = E
SFS State Fuel Sales CRS County Service Station Retail Sales
SRS State Service Station Retail Sales
CP Control Penetration CE Control Efficiency
RE Rule Effectiveness FM1 Submerged Filling Me thod Apportionment Factor FM2 Balanced Submerged Filli ng Method Apportionment Factor FM3 Splash Filling Method Apportionment Factor EF1 Submerged Filling Emissions Factor EF2 Balanced Submerged Filling Emissions Factor EF3 Splash Filling Emissions Factor
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

B-16Summary of Jurisdictional Esti mates, Tank Truck Unloading:

Jurisdiction VOC (TPY)
District of Columbia 75.34 Charles County 27.24 Frederick County 46.42 Montgomery County 170.86 Prince George’s County 143.78 Arlington County 77.80 Alexandria City 54.77 Fairfax County 372.30 Fairfax City 28.76 Falls Church City 13.75 Loudoun County 71.16 Prince William County 132.71 Manassas City 29.22 Manassas Park City 0.00 Region Total 1244.11

B-173.4.1.2 Vehicle Fueling (Stage II) and Underground Tank Breathing

VOC emissions from gasoline dispensing out lets are typically less than 10 tons per year, and therefore are inve ntoried with area sources. Much of the VOC emissions at a gasoline dispensing outlet come from vehi cle fueling and underground tank breathing. Vehicle fueling displaces vapors from the ve hicle's tank into the atmosphere, and also results in drip and spit-back spillage. Tank breathing results when ga soline is drawn out of the tanks (and into the pump lines), and air moves into the tank, evaporating gasoline and emitting vapors in the process.

Method and Data Sources:

Staff followed the methods detailed in EIIP . The emissions from vehicle fueling (stage II) and underground tank breat hing were calculated separately.

Data for fuel sales were obtained from st ate fuel sale data (gallons) and were apportioned to each county in the nonattainme nt area. In Virginia, apportionment by county was done by using county retail fuel sales, obtained from 1997 Census of Retail
Trade , as a percentage of states retail fuel sales. These percentages were applied to
statewide fuel sales data to obtain the county estimates.

State regulations were consulted for data on tank breathing, refueling vapor displacement and refueling spillage, and information on cont rol efficiency, rule penetration and rule effectiveness. Staff used a 30.42-day (365/12) activity month. Emissions factors were taken from AP-42 for underground tank breathi ng, Table 4.4-7, and were adjusted based upon a measured regional gasoline RVP of 6.8 psi and a study temperature of 82 degrees
F. Emission factors used in the estimati on of emissions from vehicle fueling was determined by running MOBILE6.2. These factors were multiplied by gallons of gasoline by county for the District and Virginia and summed for the region.

Factors:

Emissions Underground Tank Breathing 0.8 lbs VOC/kgal – DC 0.717 lbs VOC/kgal - VA 1.0 lbs VOC/kgal - MD

Emission Controls Rule Penetration Control Efficiency Rule Effectiveness Stage II Vapor Recovery
-- District 100% 90% 80% -- Virginia 100% 70% 80%
Unit Conversion Factor 0.0005 tons/lb Activity Days per Period 30.42 days/month

B-18Equation:

District of Columbia

SFS x (CRS/SRS) x (EF1 + [EF2 x (1 - (RP x CE x RE))]) x CF / AD = E

All Other Jurisdictions

SFS x (CRS/SRS) x (EF1 + EF2) x CF / AD = E

SFS State Fuel Sales CRS County Service Station Retail Sales
SRS State Service Station Retail Sales EF1 Underground Tank Breathing Emissions Factor EF2 Uncontrolled Refueling Displacement Emissions Factor
RP Rule Penetration CE Control Efficiency
RE Rule Effectiveness
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

Summary of Jurisdictional Estimates For Vehicle Fueling (Stage II) and Underground Tank Breathing:

Jurisdiction VOC (TPY)
District of Columbia 315.27 Charles County 62.84 Frederick County 143.81 Montgomery County 383.04 Prince George’s County 457.31 Arlington County 122.56 Alexandria City 73.89 Fairfax County 707.65 Fairfax City 15.54 Falls Church City 7.43 Loudoun County 140.87 Prince William County 217.40 Manassas City 15.79 Manassas Park City 0.00 Region Total 2663.40

B-193.4.1.3 Losses from Gasoline Tank Trucks in Transit

Description:

Breathing losses from tank trucks during th e transport of gasoline are caused by leaking delivery trucks, pressure in the tanks, and thermal effects on the vapor and on the liquid. A worst case situation aris es if a poorly sealed tank has been loaded with gasoline and pure air becomes saturated. During the vapo rization process, pressure increases and venting occurs.

Method and Data Sources:

Staff followed the methods detailed in EIIP

.

Data for fuel sales were obtained from st ate fuel sale data (gallons) and were apportioned to each county in the nonattainment area.. In Virginia, apportionment by county was done by using county retail fuel sales, obtained from 1997 Census of Retail
Trade , as a percentage of states retail fuel sales. These percentages were applied to
statewide fuel sales data to obtain the county estimates.

County/city distributions were then multip lied by 1.25, to reflect an EPA estimate (Procedures, Volume I, section 4.2.2.3) that nationally 25% of a ll gasoline consumed goes through bulk facilities.

For an activity period, a 30.42-day (365/12) month was used as recommended assumed. Emissions factors taken from AP-42, Table 4.4-5, were adjusted based upon a regional measured RVP of 6.8 ps i and a study temperature of 82 degrees F. State/District data on control efficiencies, rule penetration and rule effectiveness were used in the
calculations.

Factors:

Tank Truck Emissions
Loaded 0.007 lbs VOC /kgal Virginia 0.005 lbs VOC/kgal District
Unloaded 0.079 lbs VOC/kgal Virginia 0.055 lbs VOC/kgal District Bulk Facility Throughput Factor 1.25
Units Conversion Factor 0.0005 tons/lb Activity Days Per Period 26.0 days/month

B-20Emission Controls Rule Penetration Control Efficiency Rule Effectiveness Vapor Recovery Systems
-- District 100% 95% 80% -- Virginia 80% 90% 80%

Equation:

[SFS x (CRS/SRS)] x TAF x (EF1 + EF2) x [1 - (CE x RP x RE)] x CF / AD = F

SFS State Fuel Sales CRS County Service Station Retail Sales
SRS State Service Station Retail Sales TAF Bulk Facility Throughput Adjustment Factor
EF1 Loaded Tank Truck Emissions Factor EF2 Empty Tank Truck Emissions Factor
RP Rule Penetration CE Control Efficiency
RE Rule Effectiveness
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

Summary of Jurisdictional Estimates, Losses from Gasoline Tank Trucks in
Transit:

Jurisdiction VOC (TPY)
District of Columbia 5.27 Charles County 2.47 Frederick County 4.31 Montgomery County 15.77 Prince George’s County 13.25 Arlington County 1.34 Alexandria City 0.94 Fairfax County 6.40 Fairfax City 0.49 Falls Church City 0.24 Loudoun County 1.22 Prince William County 2.28 Manassas City 0.50 Manassas Park City 0.00 Region Total 54.48

B-213.4.1.4 Aircraft Refueling

Description:

Jet kerosene, jet naphtha and aviation ga soline are the three most common types
of aircraft fuels used in the United States. Emissions occur when the aircraft's tank is refilled, as vapor-laden air in the fuel tank is displaced to the atmosphere.

Method and Data Sources:

Staff followed the methods detailed in EIIP, section 4.2.3.

Emissions for this category are very sma ll for Virginia and so instead of using new 2002 survey data, inventor ies were grown from 1990 data using Virginia in-house growth factors for each jurisdiction. See the 1990 Inventory Document for additional
details for 1990 emissions.

Refueling emissions factors were comput ed from AP-42, page 4.4-5, Equation 1. The splash loading saturation factor was taken from AP-42, Table 4.4-1. True vapor pressure and molecular weight data based upon a regional m easured gasoline RVP of 8.2 were extrapolated from AP-42, Table 4.3- 2. The assumed study temperature was 83 degrees Fahrenheit. For the activity period, a 365-day year was assumed.

Factors:

Fuel Type True Vapor Pressure 83 Degrees F (psia) Molecular Weight 83 Degrees F

(lbs/lbmol) a-Jet Kerosene (JP-5) 0.017 – VA 130 – VA

b-Aviation Gasoline 5.2 – VA 67 – VA c-Jet Naptha (JP-4) 2.1 – VA 80 – VA Splash Loading Saturation Factor 1.45 VA Study Temperature 543 degrees R – VA

EF = 12.46 x S x P i x M i / T

i Fuel Type EF Refueling Emissions Factor (lbs VOC/kgal) S Splash Loading Saturation Factor P True Vapor Pressure M Molecular Weight T Study Temperature

Units Conversion Factor 0.0005 tons/lb Activity Days per Period 365 days/year

B-22Equation:

SFS a x (PTA c / STA c ) x (CTA c / MTA c ) x EF a x CF / AD = E a

SFS b x (PTA d / STA d ) x (CTA d / MTA d ) x EF b x CF / AD = E b E a – E b = E

c Air Carriers/Air Taxis/Military
d General Aviation
SFS State Aircraft Fuel Sales
PTA MSA's Pardon of State Aircraft Activity (FAA Air Traffic Activity) STA State Aircraft Activity (FAA Air Traffic Activity) CTA County Aircraft Activity (Airport Activity Statistics and States) MTA MSA Aircraft Activity (Airport Activity Statistics and States) EF Refueling Emissions Factor
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

Summary of Jurisdictional Estimates, Aircraft Refueling:

Jurisdiction VOC (TPY)
District of Columbia 0.00 Charles County 1.29 Frederick County 1.21 Montgomery County 1.77 Prince George’s County 8.30 Arlington County 0.00 Alexandria City 0.00 Fairfax County 6.56 Fairfax City 0.00 Falls Church City 12.44 Loudoun County 4.93 Prince William County 0.00 Manassas City 0.00 Manassas Park City 0.00 Region Total 36.50

B-233.4.1.5 Petroleum Vessel Loading and Unloading Losses

Description:

Evaporative VOC emissions from oceanic ships and barges carrying petroleum liquids result from loading losses, ballasting losses and transit losses. Loading losses are the primary source of evaporative emissions fr om marine vessel oper ations. However, it was assumed that very little loading activity occurred in the region and that most emissions resulted from ballasting activitie s associated with fuel delivery. Ballasting emissions occur as vapors inside empty car go tanks are displaced by ballast water pumped into the tanks to provide stability for the departing vessel.

Method and Data Sources:

Staff followed the methods detailed in EIIP

.

Vessel fuel payload data were taken from the U.S. Army Corps of Engineers'
1989 Waterborne Commerce of the United States using sites that are known to be in the
MSA.

True vapor pressures were extrapolated from AP-42 , Table 4.3-2, based upon a measured regional gasoline RVP of 6.8 and a study temperature of 82 degrees F. It was assumed that vessels arrived full (arrival ullage = 2ft) and that they were ballasted to 20 percent of capacity when emptied. Emission were computed from AP-42 , page 4.4-10, Equation 4. For an activity period, a 365-day year was assumed.

Factors:

Fuel Type True Vapor Pressure at 83 Degrees F (psia)
a-Jet Kerosene 0.017
b-Distillate Fuel Oil 0.013
c-Residual Fuel Oil 0.0001
d-Gasoline 6.2 Arrival Ullage 2 feet

EF i = 0.31 + (0.20 x P i ) + (0.01 x P i x U)

i Fuel Type P True Vapor Pressure at 83 Degrees F U Arrival Wage EF Tanker Ballasting Emissions Factor In lbs VOC/kgal

B-24Vessel Capacity Ballasted 20%
Units Conversion Factor 0.0005 tons/lb Activity Days per Period 365 days/year Units Conversion Factor (1/Density)
CFa Jet Kerosene 0.29
CFb Distillate Fuel Oil 0.28
CFc Residual Fuel Oil 0.25 CFd Discharged Gasoline 0.36

Equation:

(DC
a X EF
a x CP
a ) + (DC b x EF b x CF b ) + (DC
c x EF
c x CF
c ) + (DC d x EF d x CF d )] x VCB x CF1 x CF2 / AD = E

DC Discharged Cargo in Tons EF Ballasting Emissions Factor VCB Vessel Capacity Ballasted
CF Units Conversion Factor (kgal/ton) CF2 Units Conversion Factor (.0005 tons/lb) AD Activity Days Per Period
E Total Emissions

Summary of Jurisdictional Estimates, Petroleum Vessel Loading and Unloading
Losses:

Jurisdiction VOC (TPY)
District of Columbia 4.60 Charles County 52.29 Frederick County 0.00 Montgomery County 0.00 Prince George’s County 0.00 Arlington County 0.00 Alexandria City 0.00 Fairfax County 0.00 Fairfax City 0.00 Falls Church City 0.00 Loudoun County 0.00 Prince William County 0.00 Manassas City 0.00 Manassas Park City 0.00 Region Total 56.89

B-253.4.2 Stationary Source Solvent Evaporation

3.4.2.1 Dry Cleaning

Dry cleaning facilities that use perchloroethylene are no longer accounted for in the inventory, per EPA guidance. Emissions ar e negligible due to controls required since 1990. These controls virtually eliminate perc hloroethlyene emissions from dry cleaning machines by recapturing vapors.

Maryland’s inventory includes VOC emi ssions for dry cleaning operations that use the Stoddard process. The methods and data sources used to prepare the Maryland inventory for this category are documented in the Attachment B3 for Maryland’s 2002 Base Year Area Source Emissions Inventory.

Summary of Jurisdictional Estimates, Dry Cleaning (Stoddard Process):

Jurisdiction VOC (TPY)
District of Columbia 0.00 Charles County 0.00 Frederick County 0.00 Montgomery County 18.73 Prince George’s County 0.00 Arlington County 0.00 Alexandria City 0.00 Fairfax County 0.00 Fairfax City 0.00 Falls Church City 0.00 Loudoun County 0.00 Prince William County 0.00 Manassas City 0.00 Manassas Park City 0.00 Region Total 18.73

B-263.4.2.2 Surface Cleaning

Description:

In the area source category, there are two types of surface cleaning: cold cleaning and small-scale vapor cleaning. Cold cleaning is seen primarily at auto repair stations or manufacturing facilities, where solvents at room temperature (or slightly warmed) are used to clean parts via immersion or rinsing. Vapor cleaning involves heating the solvent, which is sprayed onto the part to be cleaned in order to dissolve the foreign material.

Method and Data Sources:

Staff followed the methods detailed in Procedures , section 4.3.2.2. Virginia applied emission factors from Procedures , on an employment basis. District applied EIIP population-based factors.

In Virginia, employment data for auto mobile repair (SIC codes 417,423,551-2,554-6 and 753), manufacturing (SIC codes 25 and 33-39), and electronics/ technical operations (SIC code 36) were used. Staff assumed that no so lvents were destroyed or removed as waste, and that there had been no solvent recycling. Staff also assumed that the surface cleaning
sources were uncontrolled. For an activ ity period, a 312-day year was assumed.

Employment figures for facilities include d in the point source inventory were subtracted from the County Business Patterns employment figures to prevent doublecounting of emissions.

Factors:

Virginia Automobile Repair – Cold Cleaning 270.0 lbs/employee Manufacturing – Open Top Vapor 24.0 lbs/employee Electronics – In-Line Vapor 29.0 lbs/employee
District of Columbia
Combined 4.03 lbs/capita

Emission Controls Rule Penetration Control Efficiency Rule Effectiveness Vapor Recovery
-- District 0% 0% 0% -- Virginia 0% 0% 0%
Solvents Removed as Waste 0%
Units Conversion Factor 0.0005 tons/lb Activity Days Per Period 312 days/year

B-27Equation: {[(EM1 - PE1) x (EF1 + EF4)] + [(EM2 - PE2) x (EF2 + EF4)]

+ [(EM3 – PE3) x EF3]} x (1 - SR) x [1 – (RP x CE x RE)]

x CF / AD = E

EM1 Auto Repair Employment (SIC Codes 417, 423, 551-2, 554-6, 753) PE1 Point Source Auto Repair Employment EM2 Manufacturing Employment (SIC Codes 25, 33-39) PE2 Point Source Manufacturing Employment EM3 Electronics Employment (SIC Code 36) PE3 Point Source Electronics Employment EF1 Automobile Repair Cold Cleaning Emissions Factor EF2 Manufacturing Cold Cleaning Emissions Factor EF3 Electronics Vapor and In-L ine Cleaning Emissions Factor EF4 Automobile Repair and Manufacturi ng Vapor and in-Line Cleaning Emissions
Factor SR Solvent Removed as Waste or Destroyed CE Vapor Recovery Control Efficiency
RP Rule Penetration
RE Rule Effectiveness
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

Summary of Jurisdictional Estimates, Surface Cleaning:

Jurisdiction VOC (TPY)
District of Columbia 189.05 Charles County 128.73 Frederick County 208.62 Montgomery County 907.97 Prince George’s County 831.08 Arlington County 111.92 Alexandria City 124.03 Fairfax County 525.14 Fairfax City 102.43 Falls Church City 42.51 Loudoun County 116.50 Prince William County 180.96 Manassas City 63.72 Manassas Park City 17.69 Region Total 3,550.35

B-283.4.2.3 Surface Coating

Description:

Surface coating includes paints, enamels, varnishes, lacquers and other product finishes. Same of those coatings contain a so lvent-based liquid carrier ; others use a waterbased liquid carrier but still c ontain a small portion of solvents. Solvents are also used to clean up painting equipment.

The primary types of surface coating app lications are archite ctural coatings, automobile refinishing and traffic paints.

Method and Data Sources:

Staff followed the methods detailed in Procedures , section 4.3.3.2 and EIIP

.

For auto refinishing and industrial coating, employment data were used with the
emission factors listed in Procedures Table 4.3-6. For architectural coating and traffic paints, population data were used. As an activity period, a 365-day year was used for architectural surface coating, and a 260-day year was used for all other surface coatings.

Employment figures for facilities include d in the point source inventory were subtracted from the County Business Patt erns employment figures for automobile refinishing and all manufactur ing activities to prevent double-counting of emissions.

A consumption-based emission factor wa s applied, using national consumption data from 1998 apportioned to the county level.

B-29Factors:

Surface Coating Emissions
Architectural 3.87 lbs VOC/gal – Solvent-based 0.74 lbs VOC/gal – Water-based Painting of Traffic Markings 0.5 lbs VOC/capita/year – VA Automobile Refinishing 3519 lbs VOC/employee/year – VA 719.1 lbs VOC/employee/year – DC
Wood Furniture & Fixtures 944 lbs VOC/employee/year – VA-DC
Metal Furniture & Fixtures 944 lbs VOC/employee/year – VA-DC
Metal Containers 6029 lbs VOC/employee/year – VA-DC
Motor Vehicles 794 lbs VOC/employee/year – VA-DC Machinery and Equipment 77 lbs VOC/employee/year – VA-DC Large Appliances 463 lbs VOC/employee/year – VA-DC Marine Coatings 308 lbs VOC/employee/year – VA-DC Rail Coatings 424 lbs VOC/employee/year – VA-DC Other Coatings 35 lbs VOC/employee/year – VA-DC

Miscellaneous Metal 2877 lbs VOC/employee/year – VA-DC Factory Finished Wood 131 lbs VOC/employee/year – VA-DC
Electric Insulation 290 lbs VOC/employee/year – VA-DC Other Product Coatings 0.6 lbs VOC/capita/year – VA-DC High-Performance Maintenance 0.8 lbs VOC/capita/year – VA-DC Other Special Purpose Coatings 0.8 lbs VOC/capita/year - VA-DC

Emission Controls Rule Penetration Control Efficiency Rule Effectiveness Automobile Refinishing

-- District 100% 80% 100% -- Virginia 36% 100% 100% Industrial Product Coating

-- District 0% 0% 0%

-- Virginia 0% 0% 0%

Seasonal Adjustment
Factor Activity Days Per Period

Architectural Surface Coating 1.3 365 days/year
All Other Sources 260 days/year
Units Conversion Factor 0.0005 tons/lb

Equation:

The 1990 Inventory Document presents equations for each surface coatings subcategory.

B-30Summary of Jurisdictional Estimates, Surface Coating (VOC tons/year):

Jurisdiction Arch. Coatings Highway Marking Auto Refinishing Industrial Special Industry Total
District of Columbia 756.40 134.51 82.96 400.75 187.54 1,562.16 Charles County 166.55 5.61 55.36 216.93 41.29 485.74 Frederick County 269.91 9.03 79.85 391.02 66.92 816.73 Montgomery County 1,174.70 9.63 267.59 1,572.67 291.25 3,315.84 Prince George’s County 1,075.22 6.39 212.58 1,524.85 266.59 3,085.63 Arlington County 253.00 38.53 163.66 136.71 61.64 653.54 Alexandria City 172.82 26.32 216.58 105.64 42.11 563.47 Fairfax County 1,313.20 199.97 635.86 881.68 319.95 3,350.66 Fairfax City 30.37 4.62 107.35 16.22 7.40 165.96 Falls Church City 13.73 2.09 75.45 6.48 3.35 101.10 Loudoun County 259.35 39.49 305.92 188.85 63.19 856.80 Prince William County 399.84 60.89 386.62 274.88 97.42 1,219.65 Manassas City 46.72 7.12 58.18 38.38 11.38 161.78 Manassas Park City 15.88 2.42 77.32 12.05 3.87 111.54

Total 5,947.69 546.62 2,725.28 5,767.11 1,463.90 16,450.60

B-313.4.2.4 Graphic Arts

Description:

Graphic arts include operations that ar e involved in the printing of newspapers, magazines, books and other printed material s. In 1989, nationwide graphic arts solvent consumption exceeded 550 million pounds; the majo rity of those solvents are consumed in printing ink formulations.

There are six basic operations used in graphic arts: lithography, gravure, letterpress, flexography, screen printing and metal decorating. Lithography accounts for nearly half of all gr aphic arts operations.

Method and Data Sources:

Staff followed the methods detailed in Procedures , Volume I, section 4.3.4.2.

Population data were used with the emission factors listed in Procedures Table 4.3-9. For an activity period, a 260-day y ear was assumed. Total emissions from facilities included in the point source inventory with annua l emissions of less than 100 tons per year were subtracted from the area source inventory.

Factors:

Graphic Arts Emissions 1.3 lbs VOC/capita/year
Emission Controls Rule Penetration Control Efficiency Rule Effectiveness Vapor Recovery Systems

- District 0% 0% 0%

- Virginia 0% 0% 0%
Units Conversion Factor 0.0005 tons/lb Activity Days Per Period 260 days/year

Equation:

(POP x EF x [1 - (RP x CE x RE)] x CF / AD) - PE = E

POP Population EF Graphic Arts Emissions Factor CE Control Efficiency
RP Rule Penetration
RE Rule Effectiveness
CF Units Conversion Factor AD Activity Days Per Period
PE Point Source Emissions
E Total Emissions

B-32Summary of Jurisdictional Estimates, Graphic Arts:

Jurisdiction VOC (TPY)
District of Columbia 127.48 Charles County 30.12 Frederick County 53.08 Montgomery County 187.20 Prince George’s County 140.05 Arlington County 71.13 Alexandria City 52.69 Fairfax County 400.34 Fairfax City 9.258 Falls Church City 4.187 Loudoun County 79.06 Prince William County 121.89 Manassas City 14.24 Manassas Park City 4.840 Region Total 1,295.57

B-333.4.2.5 Asphalt Paving

Description:

There are three basic types of asphalt us ed for paving and roofing. The first, cutback asphalt, is a liquefied road surf ace prepared by blending (or "cutting back") asphalt cement wit different petroleum distilla tes. The second type, emulsified asphalt, is also a liquefied road surface, but is prepar ed with a water/soap mixture instead of petroleum distillates and relies upon ionic bonding. The third, hot-mix asphalt is heated at a central facility and delivered to a cons truction site for immediate application. Since cutback asphalt emits large amounts of VOCs, its use has been limited in many areas to "non-ozone season" use (i.e., October th rough March). Although very few emissions occur on-site from emulsified asphalt use, significant emissions do occur as hot-mix asphalt cools after application.

Method and Data Sources:

Staff followed the methods detailed in Procedures , section 4.3.5.

Virginia uses a consumption-based emi ssion factor and applies that to county asphalt consumption.

DC prohibits the use of cutback asphalt in the summer season. Virginia has minor emissions from cutback asphalt during the summer season.

Factors:

Emulsified Asphalt Paving Emissions 0.004 lbs VOC/capita – MD and DC
0.219 lbs/ton – VA Cutback Asphalt Emissions 2.095 lbs/ton – VA
Units Conversion Factor 0.0005 tons/lb Activity Days 260 days/year

Equation:

POP x EF x CF / AD = E

POP Population EF Hot-Mix Asphalt Emissions Factor
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

B-34Summary of Jurisdictional Estimates, Asphalt Paving:

Jurisdiction VOC (TPY)
District of Columbia 1.17 Charles County 0.26 Frederick County 0.42 Montgomery County 1.82 Prince George’s County 1.67 Arlington County 0.00 Alexandria City 0.00 Fairfax County 0.36 Fairfax City 0.00 Falls Church City 0.00 Loudoun County 0.00 Prince William County 0.03 Manassas City 0.00 Manassas Park City 0.00 Region Total 5.73

B-353.4.2.6 Pesticide Application

Description:

Pesticides broadly include any s ubstances used to ki ll or retard the growth of insects, rodents, fungi, weeds, or microorganisms. The pest-killing compounds in pesticide formulations are labeled as "active" Ingredients, and the solvents acting as carriers or diluents for the ingredients are labeled as "ine rt'. Both the active and the inert ingredients of the pesticides are considered re active in the formation of ozone.

The pesticide usage can be br oadly divided into agricultura l and non-agricultural. The non agricultural use of pesticide is to control mosquitoes, insects that threaten trees, and weed growth in shallow lakes or marches.

Herbicide application has b een included based on the pres umption that herbicides are applied during the peak growing season.

Method and Data Sources:

Staff followed the methods detailed in Procedures , section 4.3.6.

Pesticide application data were gathered for the categories of agriculture, industrial/commercial/governmental, and resi dential (home and garden). The amount (pounds) of active ingredients applied per coun ty was determined. The vapor pressure, percentage of inert ingredients, and application method were considered.

As recommended in Procedures , active ingredient appl ication figures were multiplied by 2.45 to estimate usage figures reflecting both the active ingredients and the photochemically reactive "inert" ingredients of the pesticides. For an activity period, a 312-day year was assumed.

Procedures notes that 100 percent of th e organic components evaporate suggesting that the emission factor should be 1 lb of VOC per pound.

Emissions in DC were based on 1990 emissions assuming no growth.

B-36Factors:

Organic Content Adjustment Fact or 2.45 lbs/lb active ingredient
Pesticide Emissions Factor 1.0 lbs VOC/lb Seasonal Adjustment Factor 1.3
Units Conversion Factor 0.0005 tons/lb Activity Days Per Period 312 days/year

Equation:

CPA x OCF x EF x SAF x CF / AD = E

CPA County Annual Pesticide Us e (lbs active ingredient) OCF Organic Content Adjustment Factor
EF Emissions Factor SAF Seasonal Adjustment Factor
CF Units Conversion Factor AD Activity Days Per Period E Emissions (tons per day)

Summary of Jurisdictional Esti mates, Pesticide Application:

Jurisdiction VOC (TPY)
District of Columbia 489.59 Charles County 32.43 Frederick County 423.67 Montgomery County 335.90 Prince George’s County 154.77 Arlington County 214.12 Alexandria City 140.00 Fairfax County 1185.07 Fairfax City 27.39 Falls Church City 12.90 Loudoun County 378.36 Prince William County 377.74 Manassas City 40.95 Manassas Park City 13.41 Region Total 3,826.30

B-373.4.2.7 Commercial/Consumer Solvent Use

Description:

Certain commercial/consumer uses of products containing volatile organics cannot easily be identified by usual invent ory procedures yieldi ng locale-specific emission estimates. This category includes the following commercial/consumer subcategories: household products, toiletrie s, aerosol products , rubbing compounds, windshield washing fluids, polishes and waxes, non-indus trial adhesives, space deodorants, moth control, and laund ry detergents and treatments.

This category does not include the following subcategories: small cold cleaning degreasing operations; dry cleaning plants; au to refinishing shops; architectural surface coating applications; graphics arts plants; cutback aspha lt paving applications; and agricultural and municipal pesticide applications.

Method and Data Sources:

Staff followed the methods detailed in Procedures , section 4.3.7.

Population data were gathered and used with the emission factors contained in
Procedures section 4.3.7 and AP-42, Appendix A conversion tables. For an activity period, a 365-day year was assumed. A conversion factor of 0.005 was used.

Virginia applied a factor of 6.2 lbs/capita, with:

• reactivity = 100%

• control efficiency = 20%

• rule effectiveness = 100%

• rule penetration = 100%

District applied a factor of 7.84 lbs per pe rson to determine uncontrolled emissions and
subtracted a controlled subset of consumer solvent use of 20% that has an emission factor of 3.9 lbs/capita.

Equation:

Virginia:
POP x EF x CF / AD = E

DC: (POP x EF U x CF / AD) + (POP x EF C x CF x 0.20 / AD) = E

POP Population
EF Comm./Cons. Solvent Use Emissions Factor
EF U Uncontrolled Comm./Cons. Solvent Use Emissions Factor

B-38EF C Controlled Comm./Cons. Solvent Use Emissions Factor
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

Summary of Jurisdictional Estimate s, Commercial/Consumer Solvent Use:

Jurisdiction VOC (TPY)
District of Columbia 1376.06 Charles County 455.51 Frederick County 738.21 Montgomery County 3212.85 Prince George’s County 2940.79 Arlington County 679.97 Alexandria City 464.48 Fairfax County 3529.47 Fairfax City 81.62 Falls Church City 36.91 Loudoun County 697.04 Prince William County 1074.63 Manassas City 125.58 Manassas Park City 42.67 Region Total 15,455.79

B-393.4.2.8 Synthetic Organic Chemical Storage Tanks

Description:

Chemical manufacturers make organic ch emicals for a variety of end-users. Manufacturers of such chemicals are genera lly located around indus trialized areas, or anywhere else that base chemicals are r eadily available. E nd-users may be more
concentrated in industrialized areas. The s ynthesized chemicals may be stored by the
manufacturer before distributi on, by chemical wholesalers or intermediaries, or by the
final consumer.

VOCs are emitted during the manufacture process, upon decanting to storage tanks, upon decanting to transport vessels, and during storage. Individual storage tanks generally emit negligible amounts of VOCs, a nd thus are inventoried as area sources. However, these tanks are often located in facilities containing many such tanks. When these facilities emit 25 tons VOCs/year or mo re, they are inventoried as point sources.

Method and Data Sources:

It was determined that there are no synt hetic organic chemical manufacturers in the Washington, DC MSA. It was also observe d that most of the end-users in the MSA are dry cleaners, printers, automobile refinishers, surface cleaners and surface coaters. Storage at these end-users will generally be in drums rather than tanks. Thus, it was concluded that any emissions at these end-users will be captured as their source-specific

area sources.

Hence, Synthetic Organic Chemical Stor age Tanks were not inventoried as an independent area source.

B-403.4.2.9 Barge, Tank, Tank Truck, Rail Car and Drum Cleaning

Description:

Barges, tanks, tank trucks, rail cars and drums are used to transport a broad range
of commodities. Rail tank cars and most tank trucks and drums are in dedicated service (carrying one commodity only) and, unless cont aminated, are cleaned on ly prior to repair or testing. Non-dedicated tank trucks and drums are cleaned after every trip. Cleaning activities may be interrupted due to extreme weather conditions when the ambient temperature is either higher than the flash poi nt or below the freezing point of either the compound or the cleaning agent. Cleaning ag ents include water, steam, detergents, bases, adds and solvents.

The cleaning of these transport vessels ma y result in emissions of VOC, NOx and PM10. Emissions types and levels depend on the commodity transported, the cleaning agent and the management of chemical residue s. Emissions associated with the chemical residue depend on the compound and the quantity remaining in the container. They may be affected both by viscosity and vapor pressure. Emissions associated with cleaning agents used to dean the vessels depend pr imarily on the type of agent used, quantity, ambient temperature and recovery method.

Method and Data Sources:

This category is accounted for in Publicly Owned Treatment Works.

B-413.4.2.10 Industrial Adhesives and Sealants

Description:

Industrial adhesive and seal ant surface coating is the ap plication of a liquid or powder substance, such as solv ent type paints, varnishes, a nd lacquers to a surface for decorative or protective purposes. The substances can be applied by brushing, rolling, spraying, dipping or flow coating. VOCs are rel eased into the air as the substance dries. Powder coatings are applied to a hot surface and then melted; VOCs are released as the powder melts and dries.

Method and Data Sources:

District and Virginia used EPA’s “Solvent Mass Balance” methodology for estimating emissions from nonpoint solvents, which uses the total solvent production and sales for a particular source category to estim ate overall emissions then subtracting out emissions due to point sources, waste management, and recycling.

EPA used the Freedonia 2 market research report on nonpoint solvents to obtain solvent utilization data for this source categ ory. Some solvent usage estimates came from a National Paint and Coating Association (NP&CA) 3 . A breakdown of the methods used to derive the data for painting and coating sources are described in the report and is
attached as section 3.4.1 Industrial Adhesive s and Sealants. VOC emission estimates
were then allocated to the st ate and county levels and adopted by District and Virginia for this source category.

2 Data were estimated from Freedonia Group, Inc. - Freedonia Reports from 1999 and 2004

3 National Paint and Coating Association (NP& CA) “Paints and Coatin gs ‘2000': Review
and Forecast”

B-42Summary of Jurisdictional Estimates, Industrial Adhesives and Sealants:

Jurisdiction VOC (TPY)
District of Columbia 62.878 Charles County 56.875 Frederick County 86.048 Montgomery County 187.467 Prince George’s County 242.063 Arlington County 22.985 Alexandria City 33.283 Fairfax County 204.097 Fairfax City 26.893 Falls Church City 6.804 Loudoun County 43.508 Prince William County 70.636 Manassas City 11.608 Manassas Park City 3.529 Region Total 1,058.67

B-433.4.2.11 Portable Fuel Containers

Description:

Portable fuel containers (PFCs) store and transport fuel from gasoline service stations to
residential homes and businesses. Emissions from PFC use include:

• Permeation Emissions , which are produced after fuel has been stored long enough
in a can for fuel molecules to infiltrate and saturate the can material.

• Diurnal Emission s , which result when stored fuel vapors escape to the outside of a gas can through any possible openings whil e the gas can is s ubjected to daily cycle of increasing and decreasing ambien t temperatures. Diurnal emissions are dependent on the closed- or open-storage condition of a gas can.

• Transport Emissions arise when fuel escapes (e.g., spills,etc.) from gas cans that
are in transit.

• Equipment Refueling Emissions results when fuel escapes (e.g., spillage, vapor displacement) during the refueling of nonroad equipment; however these emissions are handled by EPA’s NONROAD model. Activity data from the
NONROAD model were used to estimate these emissions (described below).

Both residential and commercial PFCs are included.

Method and Data Sources:

The method used to calculate emissions (a ll VOC) for District is adopted from a
CARB 1 survey and methodology adopted by OTC 2 is being described below. Virginia used a different methodology, which is being described at the end of this section.

Portable fuel container emissions are cal culated by accounting for emissions from five different components related to gas c ontainer use: permeati on, diurnal, transportspillage, refueling spillage and refueling va por displacement emissions. The permeation, diurnal emissions (associated with storage) and transport-spillage (associated with filling the can) emissions are included in the area source inventory. The equipment refueling spillage and refueling vapor displacement emissions are calculated from the non-road
model and are included in the non -road inventory. The reside ntial portable fuel container population is developed using the number of residential housing un its in 2002 by county. For commercial portable fuel containers, popu lation is estimated using by the NAICS that are expected to have at least one gas can by county in 2002. These NAICS are: 11, 23, 31-33, 441, 45299, 447, 484, 488, 493, 53131, 5321, 532291, 5323, 5324, 54132, 54162, 54169, 56173, 71391, 71393, 7212, 811, 81293.

For the residential PFC SCCs, emissions were allocated to the local area level based on a housing surrogate. Commercial PFC emissions were allo cated to the local

1 ARB’s Mailout MSC 99-25, “Public Meeting to Consid er Approval of CA’s Po rtable Gasoline-Container Emissions Inventory”, (ARB, 199b)

2 Control Measure Development Support Analysis of Ozone Transport Commission Model Rules, E.H. Pechan & Associates, Inc. 5528-B Hempstead Way, Springfield, VA 22151, March 31, 2001.

B-44area level based on commercial and industrial business location. For the residential PFC SCCs, the emissions were allocated base d on the monthly and weekday/weekend day temporal profiles for residential lawn and garden equipment in the NONROAD model. For the commercial PFC SCCs, these emissi ons were allocated based on temporal profiles for the NONROAD model engines used in commercial applications. A seasonal adjustment factor of 1 was used.

Separate emission factors were develope d for permeation, diurnal, transport and spillage emissions for PFC (both for commerci al and residential PFCs). These emission
factors were derived from CA RB’s survey data (CARB, 1999) . A weekly activity period of 7 days/week was used.

Equation:

The residential-gas-can populati on is calculated as follows:

Pop R = (N)*(A)*(Count R ) (Eq. 1)

where: Pop R = Statewide Residential-Gas-Can Population N = Number of Occupied-Housing Units in OTC State A = Percentage of House holds with Gas Cans (46%)
Count R = Average Number of Residential-Gas Cans per Household

Statewide residential-gas-can-permeation emissions are computed as follows:

HC PR = Σ (Pop R )*(S)*(EF P )*(B R )*(Size R )*(Level)/CF (Eq. 2)

where: HC PR = Permeation Emissions in tons per day (tpd) Pop R = Statewide Residential-Gas-Can Population
EF P = Appropriate Permeation-Em ission Factor (g/gal-day) S = Percentage of Gas Ca ns Stored with Fuel (70%)
B R = Percentage of Cans Stored in Closed Condition with respect to Material (Plastic 53%; Metal 13%)
Size R = Weighted Average Capacity of Residential-Gas Cans (2.34 gal.) Level = Weighted Average Amount of Stored Fuel (49%) CF = 908,105 g/ton

Diurnal emissions from both open- and closed -system-residential-ga s cans are calculated
as follows:

HC DR = (Pop R )*(S)*(EF D )*(B R )*(Size R )*(Level) (Eq. 3)

where: HC DR = Diurnal Emissions (tpd) for Residential-Gas Cans with respect to Storage Condition (O pen or Closed) and Material (Plastic or Metal)

B-45Pop R = Statewide Residential-Gas-Can Population S = Percentage of Gas-Can Popul ation Stored with Fuel (70%)
EF D = Appropriate Diurnal-Emissi on Factor with respect to Storage Condition and Material (g/gal-day or g/day)
B R = Percentage of Gas-Can Popul ation with respect to Storage
Condition and Material
Size R = Weighted Average Capacity of Residential-Gas Cans (2.34 gal.) Level = Weighted Average Am ount of Stored Fuel (49%)
CF = 908,105 g/ton

Residential-transport-spillage emissions are determined as:

HC TR = (Pop R )*(S)*(Refill R )*(EF T )*(B R ) (Eq. 4)

where: HC TR = Residential-Gas-Can-Trans port-Spillage Emissions (tpd) Pop R = Statewide Residential-Gas-Can Population S = Percentage of Gas Cans Stored with Fuel (70%)
Refill R = Average Number of Residential-Gas-Cans-Pump-Refills per Day per Can (refill/day from survey)
EF T = Transport-Emission Factor with respect to Storage Condition (g/refill)
B R = Percentage of Gas Cans w ith respect to Storage Condition
and Material
CF = 908,105 g/ton

The commercial-gas-can populati on is calculated as follows:

Pop C = (N C )*( Count C ) (Eq. 5)

where: Pop C = Statewide Commercial-Gas-Can Population
N C = Number of Occupied Businesses in State
Count C = Average Number of Gas Cans per Business

Statewide commercial-gas-can-permeation emissions are computed as follows:

HC PC = Σ (Pop C )*(S)*(EF P )*(B C )*(Size C )*(Level) (Eq. 6)

where: HC PC = Permeation Emissions (tpd) Pop C = Statewide Commercial-Gas-Can Population
EF P = Appropriate Permeation-Em ission Factor (g/gal-day) S = Percentage of Gas Cans Stored with Fuel (70% for Residential Survey)
B C = Percentage of Applicable Gas Cans Stored in Closed
Condition

B-46Size C = Weighted Average Capacity of Commercial-Gas Cans (3.43 gal) Level = Weighted Average Amo unt of Stored Fuel (49% from Residential Survey)
CF = 908,105 g/ton

The amount of diurnal emissions from both open- and closed-system commercial-gas
cans is calculated as follows:

HC DC = (Pop C )*(S)*(EF D )*(B C )*(Size C )*(Level) (Eq. 7)

where: HC DC = Diurnal Emissions (tpd) fo r Commercial-Gas Cans with respect to Storage Condition (O pen or Closed) and Material (Plastic or Metal) Pop C = Statewide Commercial-Gas-Can Population
EF D = Appropriate Diurnal-Emissi on Factor with respect to Storage Condition and Material (g/gal-day or g/day) S = Percentage of Gas Cans Stored with Fuel (70% from Residential Survey)
B C = Percentage of Gas Cans w ith respect to Storage Condition
and Material
Size C = Weighted Average Capacity of Commercial-Gas Cans (3.43 gal.) Level = Weighted Average Amo unt of Stored Fuel (49% from Residential Survey)
CF = 908,105 g/ton

The non-lawn-and-garden-equipment commercial-ga s-can refills at the pump is derived
as follows: 

# ( ) ( ) ( )() ⎥ ⎦ ⎢ ⎣ S POP SIZ NON C * *

Average Nu ⎥ ⎢

= E REFILL

C (Eq. 8)

where: Refill = mber of Non-Lawn-and-Garden Equipment

P NO ect to en Businesses d with Fuel (70% from Residential Survey) ⎤ ⎡ 

## ∑ Fuel

C Commercial-Gas-Cans Pump Refills per Day per Can (refill/day)
Fuel = Non-Lawn-and-Garden Equipment Fuel Consumption (gal/day) for 2000
Size C = Weighted Average Capacity of Commercial-Gas Cans (3.43 gal/can-refill)
PO N = Statewide Commercial-Gas-Can Population with resp
Non-Lawn-and-Gard S = Percentage of Gas Cans Store

B-47CF = 908,105 g/ton

The commercial-transport-spillage emissions are dete rmined as:

here: TC tpd) Pop C = al-Gas-Can Population

rvey)
ondition

Factor (g/refill) with respect to Storage Condition

The tot ed as follows:

PFC - A = HC PR +HC DR +HC TR +HCPC+HC DC +HC TC

PFC - SD = E PFC - A *SAF / /ADDF

Where ty er day emission of pollutant ADF = Annual activity day fact or (WAF * 52 weeks/year)

nt 2). Total

rn

s from refueling equipment in the above mentioned EPA report as these emissions were already
included in the nonroad model emissions (see pages 4-5 of the EPA report). HC TC = (Pop C )*(S)*(B C )*(Refill C )*(EF TC ) (Eq. 9)

w HC = Commercial-Gas-Can-Trans port-Spillage Emissions (
Statewide Commerci S = Percentage of Gas Cans Stored with Fuel (70% from
Residential Su
B C = Percentage of Gas Cans w ith respect to Storage C
and Material
Refill C = Average Number of Gas-Cans Pump Refills per Day per Can
EF TC = Transport-Spillage Emission

CF = 908,105 g/ton

al area source portable fuel cont ainer emissions are summ

E
E

: E PFC - A = (tons/yr) for an annual emission of pollutant by coun
E PFC - SD = (tons/day) for a typical summ
A SAF = Seasonal adjustment factor

Virginia used a methodology developed by th e EPA, which is essentially a modified CARB approach. EPA’s methodology is described in deta il in its report 3 . EPA provided in this report state level annual emissions for the year 2005 for Virginia for differe processes through which portable fuel containe rs emit VOCs (see Attachment B Virginia emissions were then allocated to different counties in Virginia including Northern Virginia by MACTEC Federal Programs, Inc. for the year 2002 (see Attachment B5). MACTEC assumed the EP A’s 2005 inventory to be uncontrolled for 2005 and also valid for the year 2002. MACTEC then allocated EPA’s total Virginia emissions (except for the refueling portion) to all Virginia counties (including Northe Virginia counties) based on fuel usage data for SCCs using PFCs for refueling, in those counties. MACTEC did not include vapor displacement and spillage emission

3 Estimating Emissions Associated with Portable Fuel Containers (PFCs), Draft Report, EPA420-D-06-003, February 2006.

B-48Summary of Jurisdict le Fuel Containers:

VOC (TPY) ional Estima tes, Portab

Jurisdiction
District of Columb ia 1 ,061.41 Charles County 321.32 Frederick County 668.02 Montgomery Coun ty 2 ,279.73 Prince George’s C ounty 1 ,696.50 Arlington Count y 86.845
Alexandria C ity 88.952 Fairfax County 10 46.161 Fairfax City 37.091 Falls Church City 22.422
Loudoun Count y 4 60.025
Prince William Coun ty 2 80.710 Manassas City 18.351 Manassas Park City 21.030 Region Total 8,088.57

B-493.4.3 Bioprocess Sources

3.4.3.1 Bakeries

Description:

Bakeries emit VOCs, primarily ethanol formed by yeast fermentation of bread or dough, during the baking process. Ethanol is emitted through a vent, along with any combustion gases. Large commercial bakeries ar e typically inventorie d as point sources. Smaller in-store and neighborhood bakeries have lower emissions, and thus are
considered area sources.

Method and Data Sources:

Staff followed the methods detailed In an April 24, 1992 Memorandum from Lucy Adams of Radian.

Virginia used per capita emission factors (shown in the table below) and multiplied these by population per county. Distri ct used an employment-based emission
factor from Table 3 of the above source.

Factors:

Emissions Factor 0.31 lbs VOC/capita – VA 0.11 tons VOC/employee – MD and DC Activity Days Per Period 312 days/year – VA 260 days/year – MD and DC
Units Conversion Factor 0.0005 tons/lb

Equation:

Virginia:
POP x EF x UF / AD = E

DC:
EMP x EF x UF / AD = E

POP County Population
EF Emission Factor EMP Employees
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

B-50Summary of Jurisdictional Estimates, Bakeries:

Jurisdiction VOC (TPY)
District of Columbia 46.20 Charles County 2.640 Frederick County 0.000 Montgomery County 95.48 Prince George’s County 9.230 Arlington County 29.86 Alexandria City 20.40 Fairfax County 154.98 Fairfax City 3.584 Falls Church City 1.621 Loudoun County 30.61 Prince William County 47.19 Manassas City 5.514 Manassas Park City 1.874 Region Total 449.18

B-513.4.3.2 Breweries

Description:

During the fermentation process, breweries wi ll emit ethanol and other VOCs. Because of their relatively large emissions, large-sc ale commercial breweries will be inventoried as point sources. Microbreweries and br ewpubs will emit lower levels of VOCs, however, and thus must be inventoried as area sources.

Method and Data Sources:

Staff followed guidance provi ded in a February 5, 1992 Memorandum from Lucy Adams at Radian. The guidance requires inqu iries into a brewery' s annual production and the types of brewing pro cess structures it uses.

In Virginia, gallons of beer brewed per county were obtained and multiplied by the emission factors used in each jurisdiction. In the District, emissions were grown from the 1990 Inventory (refer to 1990 Inventory Document).

Factors:

Emissions 0.0043656 lbs VOC/barrel – VA
0.05674 lbs VOC/barrel– MD 0.001982 kg VOC/barrel - DC Activity Days Per Period 156 days/ozone season – VA and DC 120 days/ozone season – MD
Units Conversion Factor 0.0005 tons/lb

Equation:
CBP x EF x UF / AD = E

CBP Summer Season County Beer Production (barrels)
EF Emission Factor
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

B-52Summary of Jurisdictional Estimates, Breweries:

Jurisdiction VOC (TPY)
District of Columbia 0.100 Calvert County 0.000 Charles County 0.000 Frederick County 1.036 Montgomery County 0.063 Prince George’s County 0.013 Arlington County 0.000 Alexandria City 0.000 Fairfax County 0.000 Fairfax City 0.000 Falls Church City 0.000 Loudoun County 0.004 Prince William County 0.000 Manassas City 0.000 Manassas Park City 0.000 Region Total 1.216

B-533.4.3.3 Wineries

Description:

Like beer, wine will emit ethanol during its fermentation. The emissions vary, depending upon the type of wine (red vs. wh ite), the fermentation temperature and the sugar content of th e grape(s) used.

Method and Data Sources:

Staff followed the methods detailed in the 3/10/92 Memorandum from Lucy
Adams of Radian. The Memorandu m requires inquiries into the gallons and types of wine produced at each winery (red vs. white), a nd the fermentation period for each type.

For Virginia, emissions from the 1990 Inventory (refer to 1990 Inventory Document) were grown. Staff assumed that there are no wi neries in the District of
Columbia.

Factors:

Fermentation Emissions
- White Wine 0.00176 lb/VOC/gal
- Red Wine 0.00552 lb VOC/gal Activity Days Per Period 61 days/season
Units Conversion Factor 0.0005 tons/lb

Equation:

[(CWP a x EF a ) + (CWP b X EF b )] x UF / AD = E

a White Wine
b Red Wine CWP Summer Season County Wine Production (gallons)
EF Emission Factor
UP Units Conversion Factor AD Activity Days Per Period
E Emissions

B-54Summary of Jurisdictional Estimates, Wineries:

Jurisdiction VOC (TPY)
District of Columbia 0.000 Charles County 0.000 Frederick County 0.006 Montgomery County 0.005 Prince George’s County 0.000 Arlington County 0.000 Alexandria City 0.000 Fairfax County 0.000 Fairfax City 0.000 Falls Church City 0.000 Loudoun County 0.049 Prince William County 0.000 Manassas City 0.000 Manassas Park City 0.000 Region Total 0.06

B-553.4.3.4 Distilleries

Description:

Ethanol emissions are the largest component of the VOCs emitted from distilleries. Distilleries pr oduce both grain alcohol for indu strial and fuel purposes, and distilled spirits such as whiskey and br andy for consumption purposes. The emissions points In the distilled spirit s manufacturing process are likely to be the same as in breweries and wineries, with the aging process as an additional source of emissions.

Method and Data Sources:

No distilleries operated in th e Washington, DC-MD-VA MSA during 2002.

B-563.4.4 Waste Management Practices

3.4.4.1 Publicly Owned Wastewater Treatment Works (POTWs)

Description:

Research indicates that when a POTWs influent is heavily laden with chemicals, nearly 85% of those chemical pollutants will be stripped to the ambient air. Hence, POTWs VOC emissions are directly related to the amount of industr ial contribution to
POTW Influent.

Method and Data Sources:

The 1990 Inventory (refer to 1990 Inventor y Document) relied upon the work of a contractor to inventory POTW emissions. The contractor firs t compared the accuracy of the Surface Impoundment Modeling System (SIMS) against estimates based on total industrial flow per POTW, mu ltiplied by an EPA emissions factor. The SIMS method was found to be more accurate, as the emissi ons factor estimation system was seen as overestimating actual emissions. Thus, the SIMS data was used for Washington, DC
MSA POTW emissions.

The contractor attempted to use sour ce-specific data wherever possible, contacting each POTW in the area. When data could not be obtained directly from a POTW, average industrial cont ribution was applied, along with device parameters (or, treatments) from a typical POTW collecti on and treatment scheme, as described in AP42 . The contractor also relied upon approximate impoundment surface areas found in
EPA's Background Information Document fo r Industrial Wastewater (1990)

.

Because of the direct rela tion between industrial influe nt and VOC emissions, and because the Washington, DC MSA is a relati vely non-industrial area, the VOC emissions from POTWs in this MSA are fairly minor. The largest POTW facility, and the majority of the regions flow rate, has an industrial flow component of approximately 2 percent and produces total VOC emission well below a point source threshold.

In Virginia, 1990 emissions were grow n using employment-based growth factors for developing the 2002 emissions for this ca tegory. The Waste and Sewer Authority in Washington, DC provided the 2002 emissions data for POTWs in the District. NH3 emission for Virginia was prepared using CMU ammonia model version 3.6.

The method and data source used to prepare NH3 emission for Washington, DC for this category is documented in MANE-VU 2002 Ammonia Emissions Inventory for
Miscellaneous Sources: Final Technical Memorandum 1 (see Attachment B2)

.

1 Mid-Atlantic Regional Air Management Association, MANE-VU 2002 Ammonia Emissions Inventory for
Miscellaneous Sources: Final Technical Memorandum , prepared by E.H. Pechan & Associates, Inc., Research Triangle Park, NC. March 31, 2004.

B-57Summary of Jurisdictional Estimates, POTWs:

Jurisdiction VOC (TPY) NH 3 (TPY)
District of Columbia 11.20 2.80 Charles County 0.000 0.000 Frederick County 20.66 0.000 Montgomery County 20.29 0.000 Prince George’s County 61.37 0.000 Arlington County 0.204 0.49 Alexandria City 1.607 0.80 Fairfax County 0.450 0.65 Fairfax City 0.000 0.000 Falls Church City 0.000 0.000 Loudoun County 0.024 0.06 Prince William County 0.094 1.12 Manassas City 0.000 0.000 Manassas Park City 0.000 0.000 Region Total 115.90 5.92

B-583.4.4.2 Industrial Wastewater Treatment

Research was conducted to determine the number of larger VOC-emitting facilities from the SAMS inventory likely to produce industrial wastewater. All of the facilities contacted reported that industrial wastewater was shipped to a treatment facility without pretreatment. This validates the a ssumption that emissions from industrial
wastewater were included in the emissi ons from publicly owned treatment works. Therefore, there is no need to inventory this source separately.

B-593.4.4.3 Hazardous Waste Treatment, Storage , and Disposal Fa cilities (TSDFs)

In the 1990 Inventory (refer to 1990 Inventor y Document), a list of TSDFs in the region was compiled from the RCRI S database. These facilities are primarily involved in temporary storage. Conseque ntly, it was determined that TSDFs are not a significant source of VOC emissions in the Washington DC MSA. This also applies for the 2002 Inventory.

B-603.4.4.4 Municipal Solid Waste Landfills

Description:

Solid waste landfills generate summer precursor emissions - primarily nonmethane organic compounds (NMOCs) - in one of three ways: (1) volatilization; (2) chemical reaction; and (3) biological deco mposition of liquid and solid compounds into other chemical species. Volatilization is a ffected by partial pressure of the volatile substance, substance concentration at the ai r/liquid interface, temper ature, and confining pressure. Chemical reaction is affected by temperature, waste composition, moisture content, and whether differe nt waste types are disposed of in different areas. Decomposition is affected by nutrient and oxygen availability, refuse composition, landfill age, moisture content, temperature, Ph, and waste that are toxic to bacteria.

Method and Data Sources:

Virginia used the Landfill Air Emissions Estimation Model. The model requires landfill-specific data on landfill capacity, landfi ll age, and total refuse deposited in the study year. The model is more accurate if provid ed with the rate of refuse deposit, but it can generate that variable if needed. The mo del will supply defaults for other, more difficult to obtain variables (i.e., chemical composition and air toxics in the landfill, methane generation rate, cellulose content of refuse, and atmo spheric factors). There are
no landfills in the District of Columbia.

Summary of Jurisdictional Estimates, Municipal Solid Waste Landfills:

Jurisdiction VOC(TPY) NO
x (TPY)

District of Columbia 0.000 0.000 Charles County 5.087 0.000 Frederick County 4.934 6.320 Montgomery County 6.525 1.540 Prince George’s County 0.000 0.000 Arlington County 0.000 0.000 Alexandria City 0.000 0.000 Fairfax County 0.774 0.000 Fairfax City 0.000 0.000 Falls Church City 0.000 0.000 Loudoun County 1.230 0.170 Prince William County 0.430 0.000 Manassas City 0.000 0.000 Manassas Park City 0.000 0.0000 Region Total 18.98 8.03

B-613.4.4.5 Solid Waste Burning

3.4.4.5.1 On-Site Incineration

Description:

Here many jurisdictions allow waste burning in small-scale on-site incinerators. Typically, such incinerators are found at hospi tals, nursing homes, veterinarians' offices, funeral homes, biomedical/b iotechnological laboratories, and other laboratories.
Emissions result from waste combustion.

Method and Data Sources:

Staff followed the methods detailed in Procedures, section 4.6.1.

All sources less than 10 tons VOC per y ear were included. Sources above 10 tons VOC per year will be include d in point source inventory.

For the Virginia counties, employment and population data were used with EPA emission factors ( AP- 42 , Table 2.1-1; Procedures Table 4.6-1) relating to small-scale
industrial and commercial on-site incinerators.

For the District of Columbia, there are no registered on-site incineration activities below 10 tons/yr that are not he ld in the point source category.

A 365-day activity year was assumed.

Factors (Virginia):

Emission Factors (lbs/ton) Sector Incinerated Waste VOC NOx
a-Residential 0.004 tons/capita 15.00 2.00
b-Commercial 0.054 tons/capita 5.94 2.89
c-Industrial 0.560 tons/employee 7.44 2.90
Units Conversion Factor 0.0005 tons/lb Activity Days Per Period 365 days/year

B-62Equation:

Virginia

POP x [(IC a x EF a ) + (IC b X EF b ) + (IC c x EF c ] x UF / AD = E

POP County Population
IC Incinerated Waste Factor
EF Emissions Factor
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

Summary of Jurisdictional Estimates, On-Site Incineration:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) PM 10 (TPY)

District of Columbia 0.000 0.00 0.000 0.00 0.00 Charles County 0.000 0.00 0.259 0.18 0.00 Frederick County 0.372 11.90 5.778 2.96 11.90 Montgomery County 2.674 12.50 937.51 84.26 12.50 Prince George’s County 0.909 1.55 17.902 1.56 1.55 Arlington County 42.66 13.76 18.13 12.63 48.64 Alexandria City 28.81 9.16 12.26 8.50 32.56 Fairfax County 219.67 70.23 93.44 64.95 249.14 Fairfax City 4.682 1.33 2.006 1.35 4.94 Falls Church City 2.590 0.93 1.091 0.78 3.14 Loudoun County 47.11 16.45 19.91 14.11 56.33 Prince William County 63.89 19.30 27.28 18.73 70.08 Manassas City 10.20 4.15 4.255 3.13 13.42 Manassas Park City 2.533 0.76 1.082 0.74 2.76 Region Total 426.10 162.02 1,140.90 213.88 506.96

B-63B-64 3.4.4.5.2 Open Burning

Description:

Open burning includes the incineration of solid materials such as wood and leaves as a waste management practice. Emissions result from the materials' combustion.

Method and Data Sources:

There are no seasonal or annual emissions from open burning in the District of Columbia that has a rule that prohibits open burning activity. Si milarly, VA’s inventory
does not include emissions associated with the open burning of la nd clearing debris due to restrictions imposed in jurisdictions, which are greater than 80% urban. However, emissions for other open burning categories, such as, yard and residential household waste burning are included. VA staff followe d the methods detailed in Procedures

, section 4.6.2. Open burning permit issuan ce data were obtained from the county governments in each jurisdiction. Some juri sdictions also provide d information on the materials and/or the acreage burne d in the permitted fires.

Emission factors were taken from AP-42 (Table 2.4.5). A 365-day activity year
was assumed.

Factors:

Fuel Loading Factor 70 tons/acre Emission Factor (lbs/ton)
-VOC 19
- NOx 4 Activity Days Per Period 365 days/year
Units Conversion Factor 0.0005 tons/lb

Equation:

CPI x ABP x FLF x EF x UF / AD = E

CPI County Open Bum Permits Issued
ABP Acres Burned Per Permit FLF Fuel Loading Factor
EF Emission Factor
UF Units Conversion Factor AD Activity Days Per Period
E EmissionsB-65 Summary of Jurisdictional Estimates, Open Burning:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) NH 3 (TPY) PM 10 (TPY)

District of Columbia 0.000 0.00 0.000 0.00 0.00 0.00 Charles County 200.69 269.21 79.85 1.15 0.53 271.15 Frederick County 214.20 602.73 172.05 1.94 0.92 606.01 Montgomery County 1,089.33 1645.08 482.60 0.78 0.55 1646.45 Prince George’s County 696.24 613.34 180.39 0.01 0.01 613.34 Arlington County 0.00 0.00 0.00 0.00 0.00 0.00 Alexandria City 0.00 0.00 0.00 0.00 0.00 0.00 Fairfax County 133.93 0.00 28.20 0.00 0.00 0.00 Fairfax City 0.00 0.00 0.00 0.00 0.00 0.00 Falls Church City 0.00 0.00 0.00 0.00 0.00 0.00 Loudoun County 75.81 9.69 15.96 0.00 0.00 6.75 Prince William County 32.85 0.00 6.92 0.00 0.00 2.94 Manassas City 0.00 0.00 0.00 0.00 0.00 0.00 Manassas Park City 0.00 0.00 0.00 0.00 0.00 0.00 Region Total 2,443.05 3,140.05 965.97 3.88 2.01 3,146.64. 3.4.5 Small Stationary Source – Reside ntial/Commercial/Industrial Fuel
Combustion

3.4.5.1 Fuel Oil Consumption

Description:

Data collection for fuel oil consumption covers the use of both distillate and residual oil. Distillate oil includes fuel oil gr ades 1, 2 and 4. Diesel fu el and kerosene also
can be considered distillate oils. Nationw ide, residential and commercial/institutional sources are the largest consumer s of distillate oil. Residual oil includes fuel oil grades 5 and 6. In most areas, residual oil is not used by residential sources, but significant amounts may be consumed by industrial and commercial/institutional users.

Method and Data Sources:

Staff followed the methods detailed in Procedures , section 4.7.1.

Fuel consumption data were obtaine d and apportioned to the counties by population. For activity periods, a 365-day year was assumed for residential consumption and a 312-day year was assumed for both commercial and indus trial consumption.
Emissions factors were taken from AP-42 (Table 1.3.1).

Total emissions from sources included in point source files are subtracted from the area source inventory.

Factors:

Emissions Factor (lbs/kgal)
Market Sector NOx VOC
a-Residential
Distillate 18 – VA
20 – DC 0.713

Residual
b-Commercial
Distillate 20 0.34
Residual 55 1.13
c-Industrial
Distillate 20 0.2
Residual 55 0.25

B-66Seasonal Adjustment Factor (Summer) Seasonal Adjustment Factor (winter) Activity Days Per Period (days/year)

Residential 0.3 1.7 365
Commercial 0.6 1.4 312
Industrial Uniform Uniform 312
Units Conversion Factor 42 gal/bbl
Units Conversion Factor 0.0005 tons/lb

Equation:

{[(((DFC i + OFC i ) x (CP / SP)) – PDC i ) x EF1 i ] + [((RFC i x (CP / SP)) - PRC i ) x EF2 i ]}
x SAF i x CF1 x CF2 / AD i = E i

E a + E b + E c = E

DFC State Distillate Fuel Oil C onsumption (Grades 1, 2, and 4) OFC State Diesel Fuel and Kerosene Consumption PDC Point Source Distillate, Dies el, and Kerosene Fuel ConAunip.
RFC State Residual Fuel Oil Consumption (Grades 5 and 6) PRC Point Source Residual Fuel Oil Consumption
I Market Sector SP State Population CP County Population
EF1 Distillate Fuel Oil Emissions Factor
EF2 Residual Fuel Oil Emissions Factor SAF Seasonal Adjustment Factor CF1 Units Conversion Factor (gal/bbl) CF2 Units Conversion Factor (tons/lb) AD Activity Days Per Period
E Total Emissions

B-67Summary of Jurisdictional Esti mates, Fuel Oil Consumption:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) PM 10 (TPY)

District of Columbia 7.069 54.20 273.15 323.74 60.54 Charles County 3.320 16.74 129.47 346.71 20.88 Frederick County 4.000 20.19 156.07 417.92 25.21 Montgomery County 6.450 29.13 251.70 561.2 35.17 Prince George’s County 6.290 28.35 244.94 546.13 34.23 Arlington County 4.127 28.69 183.76 108.18 33.98 Alexandria City 2.653 17.83 115.31 65.51 21.06 Fairfax County 18.06 111.83 759.61 395.71 131.87 Fairfax City 0.480 3.37 20.05 11.85 3.98 Falls Church City 0.313 2.47 15.71 10.41 2.97 Loudoun County 3.393 19.19 149.88 72.59 22.82 Prince William County 4.433 22.94 163.48 66.01 26.64 Manassas City 0.748 4.54 39.15 21.13 5.52 Manassas Park City 0.162 0.76 5.68 1.92 0.86 Region Total 61.50 360.23 2,507.96 2,949.01 425.73

B-683.4.5.2 Coal Consumption

Description:

Two types of coal are commonly used: an thracite, or hard coal; and bituminous,
or soft coal. Anthracite is mined almost ex clusively in Pennsylvania, and is consumed primarily in states within eas y shipping distance of PA. B ituminous coal mining is more widespread, and is thus consumed in most areas of the country. Subbituminous coal and lignite are also considered as bituminous coal.

Method and Data Sources:

Staff followed the methods detailed in Procedures , Volume I, section 4.7.2.

Fuel consumption data were obtaine d and apportioned to the counties by population. For activity periods, a 365-day year was assumed for residential consumption and a 312-day year was assumed for both commercial and indus trial consumption.
Emissions factors were taken from AP-42 (Table 1.1.1).

Total emissions from sources included in point source files are subtracted from the area source inventory.

Factors:

Emissions Factor (lbs/ton)
VOC NOx
Residential
-Bituminous 10.0 9.1
-Anthracite 10.0 9.1
Commercial
-Bituminous 1.3 – VA
0.675 – DC 9.5 – VA
8.5 – DC
-Anthracite 1.3 – VA
0.675 –DC 9.5 – VA
8.5 – DC
Industrial
-Bituminous 0.675 8.5
-Anthracite 0.675 8.5

Market Sector Seasonal Adjustment Factor (Summer)* Activity Days Per Period (days/year)
a-Residential 0.3 365
b-Commercial 0.6 312
c-Industrial Uniform 312
Units Conversion Factor 0.0005 tons/lb

B-69Equation:

{[(BCC i + ACC i ) x (CP / SP)] - (PBC + PAC)} x EF x SAF x CF / AD = E i

E a + E b + E c = E

BCC State Bituminous Coal Consumption ACC State Anthracite Coal Consumption PBC Point Source Bituminous Coal Consumption PAC Point Source Anthracite Coal Consumption
i Market Sector
EF Emissions Factor CP County Population SP State Population SAF Seasonal Adjustment Factor
CF Units Conversion Factor AD Activity Days Per Period
E Total Emissions

Summary of Jurisdictional Estimates, Coal Consumption:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) PM 10 (TPY)

District of Columbia 5.15 11.22 37.55 129.50 16.94 Charles County 0.34 2.04 4.29 55.19 3.60 Frederick County 1.37 4.41 9.20 98.44 7.70 Montgomery County 1.71 6.45 13.49 148.31 11.30 Prince George’s County 1.07 2.39 4.96 77.89 4.13 Arlington County 20.32 23.32 224.99 898.95 97.86 Alexandria City 12.73 14.67 140.61 561.79 61.53 Fairfax County 95.10 113.76 1067.15 4275.20 479.12 Fairfax City 1.27 1.21 12.31 48.24 4.77 Falls Church City 1.97 2.28 22.40 89.74 9.69 Loudoun County 28.15 35.85 331.63 1336.62 153.61 Prince William County 19.34 23.54 212.54 850.69 98.09 Manassas City 9.77 12.69 118.20 477.68 54.93 Manassas Park City 0.73 0.91 8.14 32.64 3.82 Region Total 199.02 254.74 2,207.46 9,080.88 1,007.09

B-703.4.5.3 Natural Gas and Liquefied Pe troleum Gas (LPG) Consumption

Description:

The LPG use contribution to total emission s is not significant in most areas. Wherever LPG use is considerable, however, it may be reported as "equivalent natural gas” by assuming for emission calculations that each ga llon of LPG is equivalent to 100 cubic feet of natural gas.

Method and Data Sources:

Staff followed the methods detailed in Procedures , Volume I, Section 4.7.1.

Fuel consumption data were obtained and apportioned to the counties by population. For activity periods, a 365-day year was assumed for residential consumption and a 312-day year was assumed for both commercial and indu strial consumption. Emissions factors were
taken from AP-42 , Table 1.4-2, 1.4-3, 1.5-1 (8/82), an d 1.5-1 (Supplement E, 10/92). Emissions in the district were grown from the 1990 Inventory (refer to 1990 Inventory Document) using population gr owth as the surrogate.

Total emissions from sources included in point source files are subtracted from the area source inventory.

Factors:

Market Sector Emission Factors
NOx VOC
a-residential
Natural Gas 1 94 7.3

Liquid Petroleum Gas 2 14 0.5
b-Commercial
Natural Gas 1 100 5.8 – VA
2.8 – DC Liquid Petroleum Gas 2 14 0.5
c-Industrial
Natural Gas 1 140 – VA
100 – DC 5.8 – VA
2.8 – DC Liquid Petroleum Gas 2 19 – VA
14 – DC 0.5

1 - pounds per million cubic feet 2 - pounds per kilo gallon

B-71Seasonal Adjustment Factor (Summer) Seasonal Adjustment Factor (winter) Activity Days Per Period (days/year)

Residential 0.3 1.7 365
Commercial 0.6 1.4 312
Industrial Uniform Uniform 312
Units Conversion Factor 42 gal/bbl (LPG only)
Units Conversion Factor 0.0005 tons/lb

Equation:

{[((NGC i x (CP / SP)) – PNC i ) x EF1 i ] + [((LPC i x (CP / SP)) – PLC i ) x EF2 i x CF1]} x
SAF i x CF2 / AD = E i

E a + E b + E c = E

NGC State Natural Gas Consumption LPC State Liquid Petr oleum Gas Consumption PNC Point Source Natural Gas Consumption PLC Point Source Liquid Petroleum Gas Consumption
i Market Sector
EF1 Natural Gas Emissions Factor EF2 Liquid Petroleum Gas Emissions Factor CP County Population SP State Population SAF Seasonal Adjustment Factor CF1 Units Conversion Factor (gal/bbl) CF2 Units Conversion Factor (tons/Ib) AD Activity Days Per Period
E Total Emissions

B-72Summary of Jurisdictional Estimates, Natural Gas and LPG Consumption:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) NH 3 (TPY) PM 10 (TPY)

District of Columbia 75.00 124.35 1320.88 8.17 5.14 125.48 Charles County 2.809 3.77 52.51 0.28 0.00 3.77 Frederick County 5.925 8.02 107.97 0.61 0.00 8.02 Montgomery County 66.10 91.09 1139.85 7.15 0.00 91.09 Prince George’s County 60.08 82.74 1037.87 6.49 0.00 82.74 Arlington County 17.07 57.70 387.36 2.23 0.00 64.56 Alexandria City 10.91 37.18 243.26 1.39 0.00 41.63 Fairfax County 73.52 269.75 1606.44 9.19 0.00 304.18 Fairfax City 1.965 5.41 42.19 0.23 0.00 5.93 Falls Church City 1.335 4.64 33.04 0.20 0.00 5.20 Loudoun County 13.88 63.85 318.16 1.88 0.00 73.20 Prince William County 17.52 64.97 347.25 1.92 0.00 73.39 Manassas City 3.173 17.93 83.12 0.52 0.00 20.8 Manassas Park City 0.632 2.46 12.11 0.07 0.00 2.79 Region Total 349.92 833.86 6,732.01 40.33 5.14 902.78

B-733.4.5.4 Other Fuels Consumption (Residential Wood Burning)

Description:

Many households burn wood in fireplaces or wood stoves for heating or other purposes; some households burn wood in cooking stoves. The combustion of wood generates several pollutants, among them carbon monoxide.

Method and Data Sources:

District used the 2002 residential wood burning inventory de veloped by MARAMA for the MANE-VU states. This inventory was developed using a survey-based approach to estimate sub-county level activity (i.e., wood burne d) and to apportion activity between rural, urban, and suburban areas. Details on the met hods, data sources, survey instrument, and calculation methods are provi ded in the report titled MANE-VU Residential Wood Combustion Emission Inventory 1 . The MANE-VU inventory in cludes emissions estimates associated with the use of indoor wood burning equipment (i.e., fireplaces and woodstoves) and outdoor wood burning equipment (i.e., barbeques, fireplaces, fire pits, and chimineas). The summaries of emissions presented at the end of this section are provided separately for indoor and outdoor wood burning equipment.

The remainder of this section discusses the methodology for Virginia.

In the 1990 Inventory (refer to 1990 Invent ory Document), Virginia staff relied upon
the work of their contractor to estimate w ood-burning emissions. The contractor apportioned state wood fuel consumption to the county le vel based upon the number of households using wood for heat. The number of "heating degree days" was used to determine the days on
which wood was burned.

A heating degree day occurs when th e temperature drops below 65 degrees Fahrenheit; one "heating degree day" is regist ered for each degree below 65. Hence, a day of 60 degrees Fahrenheit would yield 5 heating degree days.

The emissions calculations are based on a product of the number of houses burning wood, the number of heating degree days, and an emissions factor. It is assumed that
emissions from the stoves are uncontrolled.

1 MANE-VU Residential Wood Combustion Emission Inventory, Final Report , Prepared for the Mid-Atlantic Regional Air Management Association by E.H. Pechan & Associates, Inc., June 22, 2004. The report and supporting files may be downloaded from the MARAMA’s website at: http://www.marama.org/visibility/ResWoodCombustion/index.html.

B-74Factors: Emissions (EIIP Volume III, Chapter 2) 252.6 lbs CO/ton Activity Days Per Period 151 days/cool season
Units Conversion Factor .0005

Equation:

SWC x (CHP / SHP) x (CHD / SHD) x EF x UF / AD = E

SWC State Wood Fuel Consumption (kilotons) CHP County Wood Fueled Households
SHP State Wood Fueled Households CHD County Heating Degree Days SHD State Heating Degree Days EF Wood Burning Emissions Factor
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

B-75Summary of Jurisdictional Estimates, Ot her Fuels Consumption (Residential Wood Burning; Indoor Equipment): 1

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) NH 3 (TPY) PM 10 (TPY)

District of Columbia 246.85 84.44 7.73 1.18 0.00 84.44 Charles County 116.82 85.57 8.57 1.14 4.58 85.57 Frederick County 248.44 177.26 18.10 2.46 9.53 177.26 Montgomery County 345.59 328.24 28.56 3.78 17.30 328.24 Prince George’s County 555.51 527.32 45.66 5.93 27.73 527.32 Arlington County 888.65 159.38 17.02 2.43 0.00 159.38 Alexandria City 607.03 22.31 11.62 0.33 0.00 22.31 Fairfax County 4612.64 1268.95 88.33 17.82 0.00 1268.95 Fairfax City 106.67 24.52 2.04 0.37 0.00 24.52 Falls Church City 48.24 12.89 0.92 0.19 0.00 12.89 Loudoun County 1369.57 167.45 26.23 2.34 0.00 167.45 Prince William County 2111.47 328.55 40.43 4.61 0.00 328.55 Manassas City 246.74 26.33 4.72 0.40 0.00 26.33 Manassas Park City 83.84 9.34 1.61 0.14 0.00 9.34 Region Total 11588.06 3,222.55 301.54 43.12 59.14 3,222.55

1 Indoor equipment includes fireplaces and woodstoves.

Summary of Jurisdictional Estimates, Ot her Fuels Consumption (Residential Wood Burning; Outdoor Equipment): 1

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) NH 3 (TPY) PM 10 (TPY)

District of Columbia 485.96 17.06 54.52 0.85 3.82 0.000 Charles County 112.89 28.36 1.28 0.30 0.89 17.06 Frederick County 187.73 95.14 2.13 0.57 1.48 28.36 Montgomery County 629.66 86.13 7.15 1.14 4.95 95.14 Prince George’s County 570.05 0.000 6.47 1.06 4.48 86.13 Arlington County 0.000 0.000 0.000 0.000 0.000 0.000 Alexandria City 0.000 0.000 0.000 0.000 0.000 0.000 Fairfax County 0.000 0.000 0.000 0.000 0.000 0.000 Fairfax City 0.000 0.000 0.000 0.000 0.000 0.000 Falls Church City 0.000 0.000 0.000 0.000 0.000 0.000 Loudoun County 0.000 0.000 0.000 0.000 0.000 0.000 Prince William County 0.000 0.000 0.000 0.000 0.000 0.000 Manassas City 0.000 0.000 0.000 0.000 0.000 0.000 Manassas Park City 0.000 0.000 0.000 0.000 0.000 0.000 Region Total 1,986.29 226.69 71.55 3.92 15.62 226.69

1 Outdoor equipment includes barbeques, fireplaces, fire pits, and chimineas.

B-763.4.5.5 Small Electric Utility Boilers

Emissions from this source were included in the methods used to determine emissions from fuel oil, coal, and natural gas consumption. Therefore, there is no need to inventory this source separately.

B-773.4.6 Other Area Sources

3.4.6.1 Slash/Prescribed Burning and Forest Fires

Description:

Waste from logging operations is often burned under controlled conditions to reduce the potential fire hazard in fore sts, and to remove brush that can serve as a host to destructive insects. Prescribed burning is used as a fore st management practice to establish favorable seedbeds, remove competing underbrush, accelera te nutrient recycling, control tree pests and contribute other ecological benefits.

Organic emissions from forest fi res in certain rural areas may be very large, at if least
in the short term.

Method and Data Sources:

Staff followed the methods detailed in Procedure section 4.8.1 and 4.8.2. The data required for slash/prescribed burni ng emissions calcula tion were estimates of the area burned and the fuel loading (material burned per acre). The data required for forest fires emissions calculation were acres burned pe r fire, fuel loading, and type s of wood burned per fire. The
emissions from Slash/Prescribed and Fo rest burning were calculated separately.

The National Park Service National Capita l Region provided data on NPS parkland forest fires, including fuel type, in the District of Columbia and in th e northern VA counties.
Staff assumed that the National Park Service fo rest lands are the only forest lands in the District of Columbia, and would thus be the only places at which slash, prescribed or forest fire burnings would occur.

Emissions factors were taken from AP-42, Section 11.1 or Table 13-1.

Factors:

Fuel Loading (tons/acre) Wood/Grass Type
DC Hardwood (10) Softwood (12) Virginia Hardwood (9) Softwood (9)

Emissions Factors VOC NO X Forest Fires (lbs/ton) 24 4 Slash/Prescribed (g/kg) Marsh Grass (lb/ton) Pine Slash (lb/ton) 1.8 – VA
18 – DC
19 – DC 4 – VA
0 – DC
4 – DC

B-78Seasonal Adjustment Factors Summer
Forest Fires 1
Slash/Prescribed 2.16 - VA

Activity Day Per Period 365 days/year
Units Conversion Factor #2 .0005 tons/lb
Units Conversion Factor #2 .001 kg/g

Equation:

[(HFF x HFL) + (SFF X SFL) + (GWF X SFL)] x EF1 x SAF x UF1 – E1

PB x SFL x EF2 x SAF X UF2 = E2

HFF Hardwood Forest Fires HFL Hardwood Fuel Loading Factor
SFF Softwood Forest Fires
GWF Grass Wild Fires
PB Prescribed/Slash Burns SFL Softwood Fuel Loading Factor
EF1 Forest Fire Emissions Factor
EF2 Prescribed/Slash Burn Emissions Factor SAF Seasonal Adjustment Factor
UF1 Units Conversion Factor #1
UF2 Units Conversion Factor #1
E1 Forest Fire Emissions
E2 Prescribed/Slash Burn Emissions

NH3 emissions for both categories for Virgin ia was prepared using CMU ammonia model
version 3.6.

B-79Summary of Jurisdictional Estimates:

Forest Fires:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) NH 3 (TPY) PM 10 (TPY)

District of Columbia 0.000 0.000 0.000 0.000 0.000 0.00 Charles County 4.429 12.55 2.952 0.000 0.000 0.00 Frederick County 0.878 2.49 0.585 0.000 0.000 0.00 Montgomery County 2.769 7.84 1.846 0.000 0.000 0.00 Prince George’s County 1.370 3.88 0.913 0.000 0.000 0.00 Arlington County 0.000 0.000 0.000 0.000 0.000 0.00 Alexandria City 0.000 0.000 0.000 0.000 0.000 0.00 Fairfax County 0.000 0.000 0.000 0.000 0.000 0.00 Fairfax City 0.000 0.000 0.000 0.000 0.000 0.00 Falls Church City 0.000 0.000 0.000 0.000 0.000 0.00 Loudoun County 0.040 0.0751 0.020 0.01 0.000 0.0875 Prince William County 0.210 0.3753 0.100 0.03 0.02 0.4376 Manassas City 0.000 0.000 0.000 0.000 0.000 0.00 Manassas Park City 0.000 0.000 0.000 0.000 0.000 0.00 Region Total 9.70 27.21 6.42 0.04 0.02 0.53

Slash/Prescribed:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) NH 3 (TPY) PM 10 (TPY)

District of Columbia 0.002 0.00 0.001 0.000 0.000 0.01 Charles County 1.516 1.77 0.000 0.000 0.000 1.77 Frederick County 0.000 0.00 0.000 0.000 0.000 0.000 Montgomery County 0.000 0.00 0.000 0.000 0.000 0.000 Prince George’s County 0.558 0.65 0.000 0.000 0.000 0.651 Arlington County 0.000 0.01 0.000 0.000 0.000 0.01 Alexandria City 0.000 0.01 0.000 0.000 0.000 0.01 Fairfax County 0.020 32.41 0.040 0.14 0.01 36.01 Fairfax City 0.000 0.00 0.000 0.000 0.000 0.000 Falls Church City 0.000 0.00 0.000 0.000 0.000 0.000 Loudoun County 0.000 42.14 0.000 0.19 0.000 46.82 Prince William County 0.140 40.6 0.320 0.18 0.05 45.11 Manassas City 0.000 0.04 0.000 0.000 0.000 0.04 Manassas Park City 0.000 0.02 0.000 0.000 0.000 0.02 Region Total 2.24 117.65 0.36 0.51 0.06 130.45

B-803.4.6.2 Agricultural Burning

Description:

Agricultural burning is used to clear and/or prepare land for planting. Operations under this category include st ubble burning, burning of agri cultural crop residues and burning of standing field crops as part of harvesting (i.e., sugar cane).

Method and Data Sources:

Virginia Department of Agriculture stated that in the MSA counties agricultural burning is not encouraged, is not a procedure, and generally should not exist as an active practice.

Staff assumed that large-scale agriculture is not practiced in the District of Columbia, and thus agricultural burni ng is also assumed not to be practiced in District.

B-813.4.6.3 Structure Fires

Description:

A structural fire is defined as any controlled or accidental burning of a house or any building larger than a house. Emissions resu lt from the combustion of materials which comprise or are contained within the building.

Method and Data Sources:

Staff followed the methods detailed in Procedures section 4.8.4. The data required
for structure fire emissions calculations were the numbers of structure fires, which are multiplied by a fuel loading factor, stated in tons of material per fire ( Procedures page 4-44, EIIP – Structure Fires).

Where possible, the number of structural fires per county was re ported. When this information was unavailable, the recommendations of Procedures were followed using a population surrogate and a default figure of 6 fires/1000 people (see Procedures page 444). Emissions in the District were grown from the 1990 Inventory (ref er to 1990 Inventory Document) using population as the growth surrogate.

Emission factors from Procedures page 4-44 were used.

Factors:

Fires Per Capita (when ac tuals were unavailable) .006 Fuel Loading Factor 1.15 tons solid material/fire

Emissions
- VOC 11 lbs/ton solid material burned
- NO X 1.4 lbs/ton solid material burned

Activity Day Per Period 365
Units Conversion Factor .0005 tons/lb

B-82Equation:

POP x FPC x FLF x EF x UF / AD = E

Or

F x FLF x EF x UF / AD = E

POP County Population
F Number of Structural Fires Per Jurisdiction FPC Average Number of Fires Per Capita FLF Fuel Loading Factor
EF Emission Factor
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

Summary of Jurisdictional Estimates, Structure Fires:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) PM 10 (TPY)

District of Columbia 6.799 6.08 0.865 6.68 Charles County 1.056 0.94 0.134 1.04 Frederick County 1.404 1.25 0.179 1.38 Montgomery County 1.954 1.75 0.249 1.92 Prince George’s County 9.835 8.79 1.252 9.66 Arlington County 7.256 4.77 0.923 5.24 Alexandria City 4.748 3.11 0.604 3.42 Fairfax County 5.465 3.58 0.696 3.93 Fairfax City 0.101 0.05 0.013 0.06 Falls Church City 0.391 0.26 0.050 0.28 Loudoun County 0.531 0.31 0.068 0.34 Prince William County 10.163 6.69 1.293 7.35 Manassas City 0.392 0.26 0.050 0.28 Manassas Park City 0.327 0.21 0.042 0.23 Region Total 50.42 38.05 6.42 41.81

B-833.4.6.4 Orchard Heaters

Description:

Orchard heaters are used in certain climates to prevent frost damage in the colder months. Most heaters are combustion- power ed, and thus will emit VOCs during operation.

Method and Data Sources:

Virginia Department of Agriculture both st ated that orchards in the MSA do not use
orchard heaters. Staff assumed that there are no orchards in the District of Columbia. This category is therefore irre levant to the inventory.

B-843.4.6.5 Leaking Underground Storage Tanks

Description:

Leaking Underground Storage Tanks (LUSTs) are environmentally important because they may result in the contamination of dr inking water, subsurface soils, and ground and surface water, and may emit toxic and/or explosive vapors. The contaminated soil and water may also emit VOCs. However, those emissi ons are negligible until LUST remediation occurs. Upon remediation, the VOCs are vented into the atmosphere.

Remediation of LUSTs may follow severa l methods, among them soil venting, air stripping of VOCs in ground wate r, excavation and soil aerat ion, product recover and carbon adsorption. Each of the respectiv e jurisdictions in the MSA fo llows one or more of those techniques.

Method and Data Sources:

Staff followed the methods detailed in an April 30, 1992 Memorandum from Glenn
Rives and Lauren Elmore of Radian. The Me morandum requires inves tigating the number of LUST remediations; each remediation is to be multiplied by an emission factor.

Virginia applied an emission factor of 3 lb s VOC/remediation day to the number of leaking underground storage tanks reported by each co unty. In the 1990 Inventory (refer to 1990 Inventory Document), the District of Columbia's state agency stated that no excavated soil is
aerated within the District's bounda ries; it is all trucked to othe r jurisdictions for land farming or disposal. Because of this, staff assumed th at the soil from each excavation spent only one day within the District's boundaries. This still applies for the 2002 Inventory.

Factors:

Emissions 3 lbs VOC/remediation-day DC Adjustment Factor .4
Units Conversion Factor .0005 tons/lb

Equation:

District of Columbia
NR x EF x AF x UF = E

Virginia Jurisdictions
NR x EF x UF = E

NR Number of Summer Season Remediations
EF Emission Factor AF District of Columbia Adjustment Factor
UF Units Conversion Factor

B-85Summary of Jurisdictional Estimates, Leaking Underground Storage Tanks:

Jurisdiction VOC (TPY)
District of Columbia 124.10 Charles County 21.90 Frederick County 10.95 Montgomery County 38.14 Prince George’s County 113.52 Arlington County 0.020 Alexandria City 0.014 Fairfax County 0.008 Fairfax City 0.095 Falls Church City 0.006 Loudoun County 0.057 Prince William County 0.044 Manassas City 0.018 Manassas Park City 0.002 Region Total 308.87

B-863.4.6.6 Oil Spills

Description:

Oil spills involve oil tanker accidents, ta nker truck accidents, a nd spills and blowouts from oil rigs or pipelines in coastal and inland areas. Because a wide range of fuel types may be spilled, the nature and quantity of emissions can vary. Emissions are also influenced by the clean-up procedure and by disp ersion and weathering processes.

Oil spill evaporation produces local VOC em issions. If spills catch fire, additional S02, CO, CO2, PM, NOx and VOC emissions may result. Other potentially toxic chemical compounds may also be released as a result of chemical cleanup.

Method and Data Sources:

Data on oil spills were obtained from the Virginia State Water Control Board, the Coast Guard National Response Center, and the Maryland Department of the Environment's Hazardous Waste Emergency Response Department.

Staff relied on the emission factor reco mmended in the 1990 Inventory (refer to 1990 Inventory Document). This emission factor was based on a California Air Resources Board (CARB) study of air emissions from large oil spills (10,000,000 gallons of oil). Based on the study, a range of evaporation estimates for r eactive organic gases was found to be between 5,500 and 13,000 tons. Using this information, an average emission factor is calculated.

Factors:

Emissions (tons VOC/gal oil 0.000093 Activity days per period 365

B-87Summary of Jurisdictional Estimates, Oil Spills:

Jurisdiction VOC (TPY)
District of Columbia 0.000 Charles County 0.582 Frederick County 4.046 Montgomery County 0.320 Prince George’s County 0.532 Arlington County 0.000 Alexandria City 0.000 Fairfax County 0.000 Fairfax City 0.000 Falls Church City 0.000 Loudoun County 0.000 Prince William County 0.000 Manassas City 0.000 Manassas Park City 0.000 Region Total 5.48

B-883.4.6.7 Commercial Cooking

Description:

DC’s 2002 inventory includes emissions for conveyorized charbroiling and underfired charbroiling commercial cooking operations . These processes generate VOC and CO emissions associated with the cooking of meat (i.e., hamburger, steak, fish, pork, and chicken).

• Chain-driven (conveyorized) ch arbroilers: this ty pe of broiler has conveyor belts to carry the meat through the flame area. It also may have a belt to carry buns through the appliance. Typically, flames broil th e meat on the top and bottom simultaneously.
Most chain-driven charbr oilers burn natural gas.

• Under-fired charbroilers: these appliances co nsist of three main components - a heating source, a high-temperature radiant surface, and a slotted grill. The grill holds the meat, or other food, while exposing it to the ra diant heat. Emissions are generated when grease from the meat falls onto the high-temperature radiant surface. Most
under-fired charbroilers burn natural gas; however, solid fuels, such as charcoal or wood, with or without the addition of ceram ic stones, are some times used. This category includes broilers, grill charbro ilers, flame broilers, and direct-fired
barbecues.

Method and Data Sources:

District’s inventory is ta ken from the 2002 National Emissions Inventory (NEI). The methods and data sources used to prepare the NEI for this category are documented in Methods for Developing a National Emission Inventory for Commercial Cooking Processes:
Technical Memorandum 2 (see Attachment B1).

2 U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Methods for Developing a National Emission Inven tory for Commercial Cooking Processes: Technical Memorandum

, prepared by E.H. Pechan & Associates, Inc., Research Triangle Park, NC. September 2003.

B-89Summary of Jurisdictional Es timates, Commercial Cooking:

Jurisdiction VOC (TPY) PM 2.5 (TPY) PM 10 (TPY)

District of Columbia 30.14 214.77 222.09 Charles County 3.67 25.09 27.04 Frederick County 7.11 48.23 52.01 Montgomery County 33.93 235.53 253.92 Prince George’s County 26.77 181.33 195.23 Arlington County 0.000 0.00 0.00 Alexandria City 0.000 0.00 0.00 Fairfax County 0.000 0.00 0.00 Fairfax City 0.000 0.00 0.00 Falls Church City 0.000 0.00 0.00 Loudoun County 0.000 0.00 0.00 Prince William County 0.000 0.00 0.00 Manassas City 0.000 0.00 0.00 Manassas Park City 0.000 0.00 0.00 Region Total 101.62 704.95 750.29

B-903.4.6.8 Composting

Description:

Composting refers to the use of both aer obic and anaerobic micr obial processes to degrade waste materials for beneficial reuse. Compostable wastes include biosolids (sewage sludge), manure, green waste (e.g., landscap e trimmings, grass clippings), and other biodegradable materials.

Method and Data Sources:

District’s inventory is taken from the 2002 MANE-VU inventory. The methods and data sources used to prepare the NEI for this category are documented in MANE-VU 2002 Ammonia Emissions Inventory for Miscell aneous Sources: Final Technical Memorandum 1 (see Attachment B2)

.

NH3 emission for Virginia was prepared using CMU ammonia model version 3.6.

Summary of Jurisdictional Estimates, Composting:

Jurisdiction VOC (TPY) NH 3 (TPY)

District of Columbia 3.80 0.83 Charles County 0.000 0.000 Frederick County 0.000 0.000 Montgomery County 0.000 0.000 Prince George’s County 0.000 0.000 Arlington County 0.000 0.000 Alexandria City 0.000 0.000 Fairfax County 0.000 0.000 Fairfax City 0.000 0.000 Falls Church City 0.000 0.000 Loudoun County 0.000 15.66 Prince William County 0.000 0.000 Manassas City 0.000 0.000 Manassas Park City 0.000 0.000 Region Total 3.80 16.49

1 Mid-Atlantic Regional Air Management Association, MANE-VU 2002 Ammonia Emissions Inventory for
Miscellaneous Sources: Final Technical Memorandum , prepared by E.H. Pechan & Associates, Inc., Research Triangle Park, NC. March 31, 2004.

B-913.4.6.9 Motor Vehicle Fires

Description:

Maryland’s inventory includes VOC, NO x, PM2.5, and PM10 emissions associated
with motor vehicle fires. Vehicles include d are any commercial or private mode of transportation that is author ized for use on public roads.

Method and Data Sources:

The methods and data sources used to prepare the Maryland’s inventory for this category are documented in the Attachment B3 for Maryland’s 2002 Base Year Emissions Inventory Document.

Summary of Jurisdictional Estimates, Motor Vehicle Fires:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) PM 10 (TPY)

District of Columbia 0.000 0.000 0.000 0.000 Charles County 0.35 1.00 0.04 1.10 Frederick County 0.46 1.31 0.06 1.44 Montgomery County 1.31 3.72 0.16 4.09 Prince George’s County 5.51 15.68 0.69 17.23 Arlington County 0.000 0.000 0.000 0.000 Alexandria City 0.000 0.000 0.000 0.000 Fairfax County 0.000 0.000 0.000 0.000 Fairfax City 0.000 0.000 0.000 0.000 Falls Church City 0.000 0.000 0.000 0.000 Loudoun County 0.000 0.000 0.000 0.000 Prince William County 0.000 0.000 0.000 0.000 Manassas City 0.000 0.000 0.000 0.000 Manassas Park City 0.000 0.000 0.000 0.000 Region Total 7.63 21.71 0.95 23.86

.

B-923.4.6.10 Construction

Description:

This includes PM2.5 and PM10 emissions from residential, commercial, institutional, industrial, and road sector s for Maryland and Virginia.

Method and Data Sources:

The methods and data sources used to prepare the Maryland’s inventory for these categories are documented in the Attachment B3 for Maryland’s 2002 Base Year Emissions Inventory Document.

Data for Virginia was extracted from the EPA’s 1999 National Emissions Inventory (NEI) by VISTAS and grown to the base year 2002 becau se the 2002 NEI estimates weren’t available yet. Description of methodologies can be found in the EPA’s document titled “Documentation For The Final 2002 Nonpoint S ector (Feb 06 Version) National Emission Inventory For Criteria And Hazardous Air Pollutants”, July 2006.

Summary of Jurisdictional Estimates, Construction:

Jurisdiction PM 2.5 (TPY) PM 10 (TPY)

District of Columbia 0.00 0.00 Charles County 109.82 1098.22 Frederick County 139.45 1394.51 Montgomery County 599.46 5994.63 Prince George’s County 324.89 3248.90 Arlington County 27.42 204.58 Alexandria City 49.05 366.04 Fairfax County 371.61 2773.18 Fairfax City 10.72 79.93 Falls Church City 14.23 106.21 Loudoun County 563.88 4208.10 Prince William County 144.32 1077.04 Manassas City 19.44 145.12 Manassas Park City 9.88 73.69 Region Total 2,384.17 20,770.15

B-933.4.6.11 Mining & Querying

Description:

This includes PM2.5 and PM10 emissions from mining and querying activities for Virginia.

Method and Data Sources:

Data for Virginia was extracted from the EPA’s 1999 National Emissions Inventory (NEI) by VISTAS and grown to the base year 2002 becau se the 2002 NEI estimates weren’t available yet. Description of methodologies can be found in the EPA’s document titled “Documentation For The Final 2002 Nonpoint S ector (Feb 06 Version) National Emission Inventory For Criteria And Hazardous Air Pollutants”, July 2006.

Summary of Jurisdictional Es timates, Mining & Querying:

Jurisdiction PM 2.5 (TPY) PM 10 (TPY)

District of Columbia 0.00 0.00 Charles County 48.99 244.96 Frederick County 48.99 244.96 Montgomery County 48.99 244.96 Prince George’s County 48.99 244.96 Arlington County 0.00 0.00 Alexandria City 48.99 244.96 Fairfax County 48.99 244.96 Fairfax City 0.00 0.00 Falls Church City 48.99 244.96 Loudoun County 48.99 244.96 Prince William County 48.99 244.96 Manassas City 48.99 244.96 Manassas Park City 0.00 0.00 Region Total 489.90 2,449.60

B-943.4.6.12 Crop Tilling

Description:

This includes PM2.5 and PM10 emissions from crop tilling activities for Maryland and Virginia.

Method and Data Sources:

Data for Virginia was extracted from the EPA’s 1999 National Emissions Inventory (NEI) by VISTAS and grown to the base year 2002 becau se the 2002 NEI estimates weren’t available yet. Description of methodologies can be found in the EPA’s document titled “Documentation For The Final 2002 Nonpoint S ector (Feb 06 Version) National Emission Inventory For Criteria And Hazardous Air Pollutants”, July 2006.

Summary of Jurisdictional Estimates, Crop Tilling:

Jurisdiction PM 2.5 (TPY) PM 10 (TPY)

District of Columbia 0.00 0.00 Charles County 62.28 311.40 Frederick County 233.25 1166.24 Montgomery County 81.31 406.54 Prince George’s County 28.08 140.39 Arlington County 0.00 0.00 Alexandria City 0.00 0.00 Fairfax County 3.11 15.55 Fairfax City 0.00 0.00 Falls Church City 0.00 0.00 Loudoun County 150.94 754.68 Prince William County 16.51 82.58 Manassas City 0.00 0.00 Manassas Park City 62.28 311.40 Region Total 637.76 3,188.78

B-953.4.6.13 Livestock, Beef Cattle, Feed lots, Dust Kicked-up by Hooves

Description:

This includes PM2.5 and PM10 emissi ons from dust kicked-up by hooves of livestock and beef cattle for Maryland and Virginia.

Method and Data Sources:

Data for Virginia was extracted from the EPA’s 1999 National Emissions Inventory (NEI) by VISTAS and grown to the base year 2002 becau se the 2002 NEI estimates weren’t available yet. Description of methodologies can be found in the EPA’s document titled “Documentation For The Final 2002 Nonpoint S ector (Feb 06 Version) National Emission Inventory For Criteria And Hazardous Air Pollutants”, July 2006.

Summary of Jurisdictional Estimates, Livest ock, Beef Cattle, Feedlots, Dust Kicked-up by Hooves:

Jurisdiction PM 2.5 (TPY) PM 10 (TPY)

District of Columbia 0.00 0.00 Charles County 0.00 12.55 Frederick County 0.00 2.49 Montgomery County 0.00 7.84 Prince George’s County 0.00 3.88 Arlington County 0.00 0.00 Alexandria City 0.00 0.00 Fairfax County 5.06 33.72 Fairfax City 0.00 0.00 Falls Church City 0.00 0.00 Loudoun County 45.51 303.41 Prince William County 9.43 62.85 Manassas City 0.00 0.00 Manassas Park City 0.00 12.55 Region Total 60.00 439.29

B-963.4.6.14 Fugitive Emissions – Paved and Unpaved Roads

Description:

This includes fugitive dust emissions of PM2.5 and PM10 from paved and unpaved roads for Maryland and Virginia.

Method and Data Sources:

Data for Virginia was extracted from the EPA’s 1999 National Emissions Inventory (NEI) by VISTAS and grown to the base year 2002 becau se the 2002 NEI estimates weren’t available yet. Description of methodologies can be found in the EPA’s document titled “Documentation For The Final 2002 Nonpoint S ector (Feb 06 Version) National Emission Inventory For Criteria And Hazardous Air Pollutants”, July 2006.

Summary of Fugitive Emission s – Paved and Unpaved Roads:

Jurisdiction PM 2.5 (TPY) PM 10 (TPY)

District of Columbia 0.00 0.00 Charles County 138.03 1033.34 Frederick County 156.45 1127.76 Montgomery County 135.56 1479.89 Prince George’s County 84.38 490.96 Arlington County 18.13 519.49 Alexandria City 14.59 344.37 Fairfax County 227.78 4352.53 Fairfax City 3.25 63.92 Falls Church City 0.84 16.53 Loudoun County 190.03 2127.02 Prince William County 232.39 2832.95 Manassas City 5.44 82.48 Manassas Park City 0.70 10.68 Region Total 1,207.57 14,481.92

B-973.4.7 Non-Road Engines and Vehicles

3.4.7.1 Commercial Aviation

Description:

There are two commercial airports in th e study area: Ronald Reagan Washington National and Washington-Dulles International Ai rports. National Airport is located in Arlington County, VA and Dulles is located in both Fairfax and Loudoun Counties, VA. The emissions from the Dulles International airpor t are split equally between Fairfax County and Loudoun County.

Method and Data Sources:

The Metropolitan Washington Airports Authority (MWAA) performed emission estimates for the two commercial airports, us ing the Emissions Dispersion and Modeling System (EDMS). MWAA supplied the emission results for inclusion in this document. Details of the methodologies and data sources used to prepare the VA inventory for this category are documented in Air Pollution Emission Inventories for Washington Dulles International Airport and R onald Reagan Washington National Airport for Calendar Years 2002, 2008, 2009. 1

Summary of Jurisdictional Estimates, Commercial Aviation:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) PM 10 (TPY)

District of Columbia 0.000 0.000 0.000 0.000 0.000 Charles County 0.000 0.000 0.000 0.000 0.000 Frederick County 0.000 0.000 0.000 0.000 0.000 Montgomery County 0.000 0.000 0.000 0.000 0.000 Prince George’s County 0.000 0.000 0.000 0.000 0.000 Arlington County 55.80 9.1 477.60 45.70 9.1 Alexandria City 0.000 0.000 0.000 0.000 0.000 Fairfax County 128.55 11.65 432.15 35.95 11.65 Fairfax City 0.000 0.000 0.000 0.000 0.000 Falls Church City 0.000 0.000 0.000 0.000 0.000 Loudoun County 128.55 11.65 432.15 35.95 11.65 Prince William County 0.000 0.000 0.000 0.000 0.000 Manassas City 0.000 0.000 0.000 0.000 0.000 Manassas Park City 0.000 0.000 0.000 0.000 0.000 Region Total 312.90 32.40 1,341.90 117.60 32.40

1 Metropolitan Washington Airports Authority, Air Pollution Emission Inventories for Washington Dulles International Airport and Ronald Reagan Washington National Airport for Calendar Years 2002, 2008, 2009, prepared by URS Corporation, Washington, D.C. March 2006.

B-983.4.7.2 General Aviation & Air Taxi

Description:

The Washington metropolitan area contains 12 public-use genera l aviation airports.

Method and Data Sources:

Composite emissions factors for general aviation, as reported in Procedures , table 5-3,
were used.

Virginia obtained 2002 activity data for Virginia airports from the Virginia Department of Aviation, the Federal Aviation Administration and from certain individual airports, then applied the emissions factors listed in the table below.

No general aviation emissions were re ported for the District of Columbia.

Factors:

Sector VOC NO X a – General Aviation 0.382 0.065
b – Air Taxi 1.223 0.158

Units Conversion Factor .0005 tons/lb Activity Days Per Period 365 days/year

Equation:

[(LTO a x EF a ) + (LTO b x EF b )] x UF / AD = E

LTO Landing/Takeoff Cycle
EF Emission Factor
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

B-99Summary of Jurisdictional Estimates, General Aviation:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) PM 10 (TPY)

District of Columbia 0.00 0.00 0.00 0.00 0.00 Charles County 2.40 0.13 0.41 0.63 0.13 Frederick County 29.56 1.55 5.02 7.74 1.55 Montgomery County 13.89 0.73 2.36 3.67 0.73 Prince George’s County 16.07 0.84 2.73 4.21 0.84 Arlington County 0.000 0.000 0.000 0.000 0.000 Alexandria City 0.000 0.000 0.000 0.000 0.000 Fairfax County 0.000 0.000 0.000 0.000 0.000 Fairfax City 0.000 0.000 0.000 0.000 0.000 Falls Church City 0.000 0.000 0.000 0.000 0.000 Loudoun County 10.33 3.34 1.76 0.05 3.34 Prince William County 1.60 0.52 0.27 0.01 0.52 Manassas City 12.44 4.02 2.12 0.06 4.02 Manassas Park City 0.000 0.000 0.000 0.000 0.000 Region Total 86.29 11.13 14.67 16.37 11.13

B-1003.4.7.3 Military Aviation

Description:

There are three Washington area airports that serve military airport traffic: Andrews Air Force Base, Davison Army Airfield at Ft. Belvoir, and Quantico Marine Corps Air Station. All three facilities handle both military and general aviation activity, and Andrews handles a very small number of co mmercial air carrier operations.

Method and Data Sources:

In Maryland, emissions for Andrews AFB military aviation were calculated using EDMS version 3.2 with the following inputs:

• 2002 LTO data acquired from Andrews AFB

• Total Taxi In and Taxi Out Time = 15.9 minutes (EDMS Default for Military Aircraft)

• Total Taxi In and Taxi Out Time = 26.0 minutes (EDMS Default for Commercial Aircraft)

• Queue Time = 6 minutes

Virginia’s 2002 military aviation emissions are assumed to be identical to 1990 emissions (no growth). For the 1990 inventory, Staff followed the met hods detailed in the Procedures document, Volume IV, section 5.2.5. Data on LTO cycles were obtained from FAA Air Traffic Activity 1990 and were applied to the composite emissions factors listed in Volume IV, section 5.2.5.

No military aviation emissions were re ported for the District of Columbia.

Factors:

Emissions
- VOC 1.234
- NO X 0.158 Activity Day Per Period 365 days/year
Units Conversion Factor .0005 tons/lb

Equation:

LTO x EF x UF x AD = E

LTO Military Landing/Takeoff Cycle
EF Emission Factor
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

B-101Summary of Jurisdictional Estimates, Military Aviation:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) PM 10 (TPY)

District of Columbia 0.00 0.00 0.00 0.00 0.00 Charles County 13.55 7.62 4.58 0.72 7.62 Frederick County 4.91 2.76 1.66 0.26 2.76 Montgomery County 0.000 0.00 0.000 0.00 0.000 Prince George’s County 17.74 9.97 6.00 0.94 9.97 Arlington County 0.000 0.000 0.000 0.000 0.000 Alexandria City 0.000 0.000 0.000 0.000 0.000 Fairfax County 200.68 23.13 26.82 4.70 23.60 Fairfax City 0.000 0.000 0.000 0.000 0.000 Falls Church City 0.000 0.000 0.000 0.000 0.000 Loudoun County 0.000 0.000 0.000 0.000 0.000 Prince William County 27.36 9.38 11.64 43.13 9.38 Manassas City 0.000 0.000 0.000 0.000 0.000 Manassas Park City 0.000 0.000 0.000 0.000 0.000 Region Total 264.24 52.86 50.70 49.75 53.33

B-1023.4.7.4 Railroad Locomotives

Description:

Diesel-powered railroad locomotives genera te emissions during fuel combustion and
are inventoried as area sources. Electric loco motives are not inventor ied under area sources, as they take their locomotive power fr om electricity supplied by power plants.

Method and Data Sources:

Two types of locomotive categories are invent oried: line haul and yard locomotives.
Locomotive emissions calculations are based on the amount of fuel consumed in an inventory area and an emission factor for th e pollutant being inventoried. Where specific county-level fuel consumption data is unavail able, two methods can be used. Method one involves obtaining regional locomotive traffic density, and multiplying that density by a fuel consumption index. Method two, which yields a region-specific fuel consumption estimate, involves multiplying a total fuel consumption figure by the quotient of track miles in the region divided by total track miles.

Yard locomotive emissions were calculat ed by multiplying the number of yard locomotives by an estimate of the fuel consumed per locomotive and by the emissions factor and by unit conversion factors. In most instan ces, the amount of fuel consumed by the yard locomotives was provided and multiplied by the emission factor.

In some cases, the states obtained raw data by direct inquiry to the railroad companies operating in the MSA. Not all company data we re county-specific; for those data, the states estimated fuel consumption thr ough one of the two methods a bove. District obtained the 2002 data by direct inquiry to the railro ad companies operating in the District.
2002 railroad emissions in the District are based on the activity and fuel data information from the operations. In Virginia , locomotive emission factors from a 1997 EPA
Technical Memorandum were used (EPA420-F-97-051, available at www.epa.gov/otaq/locomotv.htm ).

Factors:

Emission Factors (lbs/gal) VOC NO X Maryland
- Line Haul 0.0213 0.4931
- Yard 0.0509 0.5044 Virginia
- Line Haul 0.0221 0.5954
- Yard 0.0463 0.7982 Activity Day Per Period 365 days/year
Units Conversion Factor .0005 ton/lb

B-103Equation:

[(LFC x EF1) + (YFC x EF2)] x UF / AD = E

LFC Line Haul Fuel Consumption (gallons)
EF1 Line Haul Emissions Factor YFC Yard Operations Fuel Consumption (gallons) EF2 Yard Operations Emissions Factor
UF Units Conversion Factor AD Activity Days Per Period
E Emissions

Summary of Jurisdictional Estimates, Locomotives:

Jurisdiction NO
x (TPY) SO 2 (TPY) PM 10 (TPY) VOC (TPY) PM 2.5 (TPY)

District of Columbia 19.54 10.73 469.44 33.35 11.66 Charles County 0.000 0.00 0.000 0.00 0.00 Frederick County 31.69 15.29 509.50 36.92 16.98 Montgomery County 15.82 8.75 310.20 22.58 9.72 Prince George’s County 9.133 5.70 211.36 15.43 6.33 Arlington County 0.000 0.00 0.00 0.00 0.000 Alexandria City 0.165 0.46 3.97 1.22 0.50 Fairfax County 7.241 20.22 174.81 53.57 22.48 Fairfax City 0.000 0.00 0.000 0.00 0.00 Falls Church City 0.000 0.00 0.000 0.00 0.00 Loudoun County 0.000 0.00 0.000 0.00 0.00 Prince William County 23.04 64.39 556.22 170.46 71.58 Manassas City 18.10 50.60 437.03 133.93 56.23 Manassas Park City 5.266 14.71 127.14 38.96 16.36 Region Total 130.00 190.85 2,799.67 506.42 211.84

B-1043.4.7.5 Aircraft Auxiliary Power Units

Description:

Aircraft Auxiliary Power Units (APU) ar e onboard, turbine powered engines used primarily to provide electricity and air conditioning to an aircraft when the main engines are
shut down.

Method and Data Sources:

The methods and data sources used to prep are the Virginia inventory for this category
are documented in Air Pollution Emission Inventories fo r Washington Dulles International Airport and Ronald Reagan Washington National Airport for Cale ndar Years 2002, 2008,
2009. 1

Summary of Jurisdictional Estimates, Aircraft Auxiliary Power Units:

Jurisdiction VOC (TPY) PM 2.5 (TPY) NO
x (TPY) SO 2 (TPY) PM 10 (TPY)

District of Columbia 0.000 0.000 0.000 0.000 0.000 Calvert County 0.000 0.000 0.000 0.000 0.000 Charles County 0.000 0.000 0.000 0.000 0.000 Frederick County 0.000 0.000 0.000 0.000 0.000 Montgomery County 0.000 0.000 0.000 0.000 0.000 Prince George’s County 0.000 0.01 0.000 1.00 0.01 Arlington County 0.600 0.000 7.30 0.000 0.000 Alexandria City 0.000 0.05 0.000 3.15 0.05 Fairfax County 2.150 0.000 22.90 0.000 0.000 Fairfax City 0.000 0.000 0.000 0.000 0.000 Falls Church City 0.000 0.05 0.000 3.15 0.05 Loudoun County 2.150 0.000 22.90 0.000 0.000 Prince William County 0.000 0.000 0.000 0.000 0.000 Manassas City 0.000 0.000 0.000 0.000 0.000 Manassas Park City 0.000 0.000 0.000 0.000 0.000 Region Total 4.90 0.11 53.10 7.30 0.11

1 Metropolitan Washington Airports Authority, Air Pollution Emission Inventories for Washington Dulles International Airport and Ronald Reagan Washington National Airport for Calendar Years 2002, 2008, 2009, prepared by URS Corporation, Washington, D.C. March 2006.

B-1053.4.7.6 Commercial Marine Vessels

Description:

Commercial Marine Vessels include all boa ts and ships used either directly or indirectly for commerce or military activity. These include vessels ranging in size from 20- foot charter boats to the larg est tankers and military vessels, which can exceed 1,000 feet in length.

Method and Data Sources:

The Emissions were not reported by any jurisdiction for this category.

B-1063.4.8 EPA Non-Road Source Estimates

3.4.8.1 Description:

The "Other Non-road Engines and Vehicles" category includes a varied collection of equipment including lawn mowers and chain sa ws, recreational equipment, farm equipment and construction equipment. Nonroad emissions result from the use of fuel in a diverse collection of vehicles and equipment, includ ing vehicles and equipment in the following categories:

• Recreational vehicles, such as all-terra in vehicles and off-road motorcycles; • Logging equipment, such as chain saws; • Agricultural equipment, such as tractors; • Construction equipment, such as graders and back hoes; • Industrial equipment, such as fork lifts and sweepers; • Residential and commercial lawn and garden equipment, such as leaf and snow blowers.

3.4.8.2 Method and Data Sources:

EPA’s NONROAD2005 model versi on 2005a (February 8, 2006) together with its associated graphic user interface NONROAD2005.1.0 (June 12, 2006), reporting utility version 2005c (March 21, 2006), and all geographi cal allocation data files updated until February 1, 2006 was used by COG staff to calculate base ye ar 2002 annual emissions. The model includes more than 80 basic and 260 specific types of nonroad equipment, and further stratifies equipment types by horsepower rating. Fuel t ypes include gasoline, diesel, compressed natural gas (CNG), and liquefied petroleum gas (LPG). This model calculates emissions from all equipment categories listed above with the exception of commercial marine, locomotive,
and aircraft emissions. The NONROAD model estimates emissions for six exhaust pollutants: hydrocarbons (HC), NO X , carbon monoxide (CO), carbon dioxide (CO2), sulfur dioxides (SO2), and PM. For the purpose of ba se year 2002 SIP emissions inventory, it was run to provide emissions for VOC, NOx, SO2, and PM for the Washington, DC-MD-VA
nonattainment area.

The NONROAD2005 model estimates emission s for each specific type of nonroad equipment by multiplying the following input data estimates:

• Equipment population for base year (or base year population grown to a future year),

distributed by age, power, fuel type, and application; • Average load factor expressed as average fraction of available power; • Available power in horsepower; • Activity in hours of use per year; and
• Emission factor with deterior ation and/or new standards.

The emissions are then temporally and geograp hically allocated using appropriate allocation
factors.

B-107There are several input files that provide nece ssary information to cal culate and allocate emissions estimates. These input files correspond to the basic data n eeded to provide the calculations: emission factors, base year equi pment population, activity, load factor, average lifetime, scrappage function, growth estimat es, and geographic and temporal allocation. Default values are provided for all input files. The user can replace the default data files when better information becomes available, eith er from EPA for national defaults or from local sources for locality-specifi c data. The input files are also modifiable to test control strategies.

Details of this model can be found in its us er guide named “User’s Guide for the Final NONROAD2005 Model” (EPA420-R-05-013; Decem ber 2005) available from the EPA.

The NONROAD2005 model was run for the me tropolitan Washington region for annual emissions. Four season approach was adapted for developing annual emissions. Four seasons considered were Winter (December, January, and February), Spring, (March, April, and May), Summer (June, July, and August), and Au tumn (September, October, and November). Model inputs (Temperature, fuel, and other parameters) were pr epared for the four seasons
used for annual model runs and are listed below for each jurisdiction:

District of Columbia Annual NONROAD Model Inputs
Values Parameters Winter Spring Summer Fall Min. Temperature 27.1 45.7 66.7 49.5 Max. Temperature 44.0 66.2 84.7 67.5 Avg. Temperature 35.6 56.0 75.7 58.5 Gas Sulfur (%) 0.02199 0.01725 0.0159 0.01725 Diesel Sulfur (%) 0.2457 0.2457 0.2457 0.2457 Marine Diesel Sulfur (%) 0.2638 0.2638 0.2638 0.2638 CNG/LPG Sulfur (%) 0.003 0.003 0.003 0.003 Fuel Reid Vapor Pressure 12.2 8.0 6.8 8.0 Oxygen Weight (%) 2.1 1.8 2.1 1.8 Stage II Control (%) 0 0 0 0

Virginia Annual NONROAD Model Inputs
Values Parameters Winter Spring Summer Fall Min. Temperature 27.1 45.7 66.7 49.5 Max. Temperature 44.0 66.2 84.7 67.5 Avg. Temperature 35.6 56.0 75.7 58.5 Gas Sulfur (%) 0.0279 0.0229 0.0129 0.0229 Diesel Sulfur (%) 0.2283 0.2283 0.2283 0.2283 Marine Diesel Sulfur (%) 0.2638 0.2638 0.2638 0.2638 CNG/LPG Sulfur (%) 0.003 0.003 0.003 0.003 Fuel Reid Vapor Pressure 12.9 10.8 6.7 10.8 Oxygen Weight (%) 2.1 1.8 2.1 1.8 Stage II Control (%) 0 0 0 0

B-108Maryland Annual NONROAD Model Inputs
Values Parameters Winter Spring Summer Fall Min. Temperature 27.1 45.7 66.7 49.5 Max. Temperature 44.0 66.2 84.7 67.5 Avg. Temperature 35.6 56.0 75.7 58.5 Gas Sulfur (%) 0.0279 0.0229 0.0129 0.0229 Diesel Sulfur (%) 0.2283 0.2283 0.2283 0.2283 Marine Diesel Sulfur (%) 0.2638 0.2638 0.2638 0.2638 CNG/LPG Sulfur (%) 0.003 0.003 0.003 0.003 Fuel Reid Vapor Pressure 12.7 10.4 6.6 9.5 Oxygen Weight (%) 2.1 1.8 2.1 1.8 Stage II Control (%) 0 0 0 0

Details of methodology for preparing annual mo del run inputs are being provided below.

Model was run for the four seasons (winter, spring, summer, and autumn) and then seasonal emissions were summed up to get the annual emissions. Methodology to prepare inputs for four seasons is being provided below.

Temperature: Temperature data were acquired from the Natio nal Climatic Data Center (NCDC). Monthly maximum, minimum, and average temperature data were collected for Dulles (IAD) and Reagan National (DCA) stations for the period during the period 2002-2004. Then the two datasets were averaged together to get one dataset. Then season average minimum, maximum, and average temperatures were computed for the four seasons from this dataset.

Fuel inputs: Month specific data for fuel parameters (Sul fur percent in gas and diesel, fuel RVP, and oxygen weight percent) were pr ovided by the state air agencies . These data were averaged for each of the four seasons to get season average inputs. Model defaults were used for CNG/LPG sulfur percent and mari ne diesel sulfur percent. Zero % Stage II controls were
assumed for the model runs.

Ground Support Equipment Emissions Ground Support Equipment Emissions for Arlington, Fairfax, and Loudoun counties were taken from Metropolitan Washi ngton Airports Authority docum ent (see Attachment B4). NONROAD2005 model generated GSE emission for Arlington and Loudoun counties were replaced by MWAA emissions. Since Dulles airport is spr ead across Fairfax and Loudoun counties, MWAA emission from Dulles airport were divide equally between Fairfax and
Loudoun counties.

B-109B-110 3.4.8.3 Results:

Following table lists emissions for different counties in the Washington, DC-MD-VA PM2.5 nonattainment region. Detailed NONROAD2005 model output files are being provided separately in electronic fo rmat (NIF3.0) as Attachme nt C3 of this document.

Jurisdiction VOC (TPY) PM2.5 (TPY) NO
x (TPY) SO2 (TPY) PM10 (TPY)

District of Columbia 2023.30 287.98 3066.20 343.11 298.52 Charles County 1592.06 89.34 817.22 80.70 93.68 Frederick County 1838.12 145.62 1409.34 121.27 152.44 Montgomery County 6505.40 393.03 3524.52 301.53 413.76 Prince George’s County 4128.99 326.06 3167.34 297.60 341.07 Arlington County 758.74 146.35 1533.29 171.99 151.59 Alexandria City 514.82 17.80 162.89 9.38 18.94 Fairfax County 6626.15 415.81 3881.66 339.23 437.26 Fairfax City 201.46 7.51 61.71 3.46 8.01 Falls Church City 125.46 4.49 33.62 1.77 4.81 Loudoun County 3078.50 296.98 2891.80 280.84 310.38 Prince William County 2059.01 190.08 1777.32 178.49 198.59 Manassas City 117.75 5.58 101.78 4.49 5.85 Manassas Park City 117.34 4.33 32.51 1.76 4.63 Region Total 29,687.08 2,330.96 22,461.20 2,135.61 2,439.53B-111 

# Chapter 4

Onroad Mobile SourcesB-112 4.0 ONROAD MOBILE SOURCES

4.1 Introduction

This section describes the pr eparation of the base year 2002 onroad mobile source emissions for the Washington DC-M D-VA PM2.5 nonattainment area. The MOBILE6.2.03 model was used for developing the on-road mobile emission factors for developing annual emissions. A broader documentation describing the Mob6 input assumptions, methodology to allocate VMT and emissions by road, vehicle, and emission types for the Washington, DC-MD-VA nonatta inment area counties for the purpose of putting them in the NIF3.0 format, and em issions and VMT summaries allocated using this methodology, is presented in Appendix D 1. Mobile6.2.03 input file s, external input files, and output files are being provided separately in an electronic format as Appendix
D2. The NIF3.0 file is available in an electronic format as Attachment D3.

Metropolitan Washington Air Quality Commit tee (MWAQC) staff is responsible for preparing mobile emission factors for the base year 2002. The National Capitol Region Transportation Planning Board (TPB) is the le ad agency responsible for post-processing these mobile emission factors using a comp rehensive travel demand modeling process and compiling on-road mobile source emissions.

Except for updating the input data such as vehi cle age distributions, diesel sales fraction, temperature, I/M programs, and vehicle miles traveled fractions data, the on-road mobile emissions analysis process is essentially th e same as the one used for developing the 1990
Base Year Emissions Inventories. A detaile d description of travel demand modeling and emissions analysis process can be found in “ 1990 Base Year Emission Inventory for Stationary Anthropogenic, Biogenic Sources a nd Highway Vehicle Emissions of Ozone Precursors in the Washington, DC-MD-VA metr opolitan Statistical Area, September
1993 ”.

4.2 Summary of Onroad Mobile Source Emissions

The table below summarizes annual emissi ons in the nonattainment area for PM2.5- Direct, NOx, SO2, VOC, NH3, and PM10.B-113Onroad Mobile Source Emissions –Base Year 2002Annual Emissions Inventory (Tons Per Year)Metropolitan Washington NAA1

Pollutant Charles County Frederick County Montgomery County Prince George's County Arlington County Alexandria City Fairfax County Loudoun County Prince William County District Of Columbia MD Total VA Total NAA TotalPM2.5-Direct41.73 128.21 322.65 348.59 69.07 38.65 420.26 80.57 118.69156.27 841.18 727.24 1724.69NOx2,016.57 7,922.53 17,929.45 19,771.57 4,141.40 2,161.24 23,317.38 4,482.29 7,005.518,827.37 47640.12 41107.82 97575.31SO2272.63 81.63 676.05 704.57 141.06 78.56 876.35 169.36 249.90289.88 1734.88 1515.23 3539.99VOC2696.75 1208.25 8183.30 8406.81 1992.18 1261.24 10076.33 2044.61 3121.134913.24 20495.11 18495.49 43903.84NH394.96 316.59 792.88 830.76 175.63 97.22 1,034.57 208.63 311.00383.37 2035.19 1827.05 4245.61PM1058.78 184.20 461.49 495.90 99.71 55.47 603.08 116.89 173.05223.62 1200.37 1048.2 2472.191Fairfax County emissions include onroad emissions from Fairfax City and Falls Church City. Prince William County emissions includeemissions from Manassas City and Manassas Park City.* Small discrepancies may result due to rounding

# Chapter 5

Quality Assurance Procedures

B-114

## District of Columbia

5.0 QUALITY ASSURANCE

PROCEDURES

Quality assurance activities are distinguished from QC activities in that they provide a more objective assessment of data quality. St aff involved in the i nventory preparation will perform the QA checks. Several quality assurance checks will be employed to address the data quality objectives: reality/ peer review checks, sample calculations, sensitivity analysis, and range checks. Deta ils on each check are provided below. The product of the quality checking process will be a completed summary of items checked, summary of results, and recommended fo llow-up action. At the completion of the process, the inventory will be evaluated according to the data quality objectives.

5.1 REALITY CHECK/PEER REVIEW CHECK

Definition:
Independent review by a knowledgeable expert

Benefit:
Ensure data, assumptions, and procedures are reasonable

Objective(s) Addressed:
Accuracy, completeness, comparability, representativeness

Check(s):
Reasonableness of methods, assumptions, and emissions estimates will be assessed. This will be accomplished by 1) comparing data sources used in the final inventory to those specified in the Inventory Preparation Plan, 2) reliance on reviewer expertise, and 3) comparison of emissions estimates to other i nventory efforts, particularly the 1990 base year inventory and the 1999 PEI.

Limitations:
None

B-1155.2 SAMPLE CALCULATIONS

Definition:
Verification of values by replicating calculations

Benefit:

Ensure calculations are done correctly

Objective(s) Addressed:
Accuracy

Check(s):
Emissions calculations will be duplicated to check the accuracy of the arithmetic and, therefore, the resulting emissions estimate. Priority will be given to those categories identified as the largest PM 10 and CO contributors.

Limitations:
Estimates calculated using computer mode ls such as MOBILE6.2 are checked using simplified assumptions to arrive at a ”ballpark” value to use as a comparison to the actual
calculated value.

5.3 SENSITIVITY ANALYSIS

Definition
Systematic study of how changes in parameters affect data

Benefit
Identify the parameters that ha ve the greatest effect on data

Objective(s) Addressed
Generally addresses all objectives

Check(s)
A sensitivity analysis in the form of source category emissions rankings by pollutant will be performed. The ranking will help determin e where efforts should be concentrated.

Limitations

None

B-1165.4 STANDARD RAN GE CHECKS

Definition
Standard range checks address the data quality objective of comparability

Benefit
Identify the source categories that have th e greatest change in emission levels from previous emission estimates.

Objective(s) Addressed
Generally addresses all objectives

Check(s)
The 2002 base year inventory will be compared to the most recent inventory (base year 1990, 1999 PEI, 2002 NEI). Any discrepancies (d ata outliers) greater than 20% involving sources that made up great er than 5% of the 1990 PM 10 , 1999 CO, or 2002 inventories will be corrected or justified.

The projection inventories will be compar ed to the 2002 base year inventory. Any discrepancies (data outliers) between the base year and a given projection year greater than the population increase percentage pl us 10% and involving sources that made up greater than 5% of the 2002 or projection year daily inventorie s will be investigated and either corrected (see Corrective Action Plan below) or justified. The justification will include whether there was a change in methodology (e.g., different emission factor, allocation method, activity data) or if there is a real antici pation of emissions increasing or decreasing (e.g., decreases in the onr oad sector due to fleet turnover).

Limitations

None.

5.5 CORRECTIVE ACTION PLAN

Corrective and follow-up actions identified dur ing the quality checking process will be noted and referred to the appr opriate staff. Both the corrective actions identified and results of actions taken in response will be documented.

B-117

## Maryland

5.0 QUALITY ASSURANCE

PROCEDURES

Quality assurance activities are distinguished from QC activities in that they provide a more objective assessment of data quality. The QA checks (except the sensitivity analysis and range checks) will be performed by sta ff not involved in the inventory calculations. Several quality assurance checks will be employed to address the data quality objectives: reality/peer review checks, sample calculatio ns, sensitivity analysis, and range checks. Details on each check are provided below. The product of the quality checking process will be a completed summary of items checked, summary of results, and recommended follow-up action. At the completion of the pr ocess, the inventory will be evaluated according to the data quality objectives.

5.1 REALITY CHECK/PEER REVIEW CHECK

Definition:
Independent review by a knowledgeable expert

Benefit:
Ensure data, assumptions, and procedures are reasonable

Objective(s) Addressed:
Accuracy, completeness, comparability, representativeness

Check(s):
Reasonableness of methods, assumptions, and emissions estimates will be assessed. This will be accomplished by 1) comparing data sources used in the final inventory to those specified in the Inventory Preparation Plan, 2) reliance on reviewer expertise, and 3) comparison of emissions estimates to other i nventory efforts, particularly the 1990 base year inventory and the 1999 PEI.

Limitations:
None

B-1185.2 SAMPLE CALCULATIONS

Definition:
Verification of values by replicating calculations

Benefit:

Ensure calculations are done correctly

Objective(s) Addressed:
Accuracy

Check(s):
Emissions calculations will be duplicated to check the accuracy of the arithmetic and, therefore, the resulting emissions estimate. Priority will be given to those categories identified as the largest PM 10 and CO contributors.

Limitations:
Estimates calculated using computer mode ls such as MOBILE6.2 are checked using simplified assumptions to arrive at a ”ballpark” value to use as a comparison to the actual
calculated value.

5.3 SENSITIVITY ANALYSIS

Definition
Systematic study of how changes in parameters affect data

Benefit
Identify the parameters that ha ve the greatest effect on data

Objective(s) Addressed
Generally addresses all objectives

Check(s)
A sensitivity analysis in the form of source category emissions rankings by pollutant will be performed. The ranking will help determin e where efforts should be concentrated.

Limitations

None

B-1195.4 STANDARD RAN GE CHECKS

Definition
Standard range checks address the data quality objective of comparability

Benefit
Identify the source categories that have th e greatest change in emission levels from previous emission estimates.

Objective(s) Addressed
Generally addresses all objectives

Check(s)
The 2002 base year inventory will be compared to the most recent inventory (base year 1990, 1999 PEI, 2002 NEI). Any discrepancies (d ata outliers) greater than 20% involving sources that made up great er than 5% of the 1990 PM 10 , 1999 CO, or 2002 inventories will be corrected or justified.

The projection inventories will be compar ed to the 2002 base year inventory. Any discrepancies (data outliers) between the base year and a given projection year greater than the population increase percentage plus 10% and in volving sources that made up greater than 5% of the 2002 or projection year daily inve ntories will be inve stigated and either corrected (see Corrective Action Plan below) or justified. The justification will include whether there was a change in methodology (e .g., different emission factor, allocation method, activity data) or if th ere is a real anticipation of emissions increasing or decreasing (e.g., decreases in the onroa d sector due to fleet turnover).

Limitations

None.

5.5 CORRECTIVE ACTION PLAN

Corrective and follow-up actions identified dur ing the quality checking process will be noted and referred to the appr opriate staff. Both the corrective actions identified and results of actions taken in response will be documented.

5.5 QUALITY ASSURANCE FINAL REPORT

The final inventory report will include discus sions on inventory quality considerations for each major source category. It will summarize the results of the quality checking procedures and provide an evaluation of th e inventory according to the data quality objectives. The report will include an assessmen t of the limitations of the inventory data.

B-120

## Virginia

5.0 QUALITY ASSURANCE

PROCEDURES

Quality assurance activities are distinguished from QC activities in that they provide a more objective assessment of data quality. The QA checks (except the sensitivity analysis and range checks) are by staff not involved in the inventory calcula tions. Several quality assurance checks will be employed to addre ss the data quality objectives: reality/peer review checks, sample calculations, sensitiv ity analysis, and range checks. Details on each check are provided below.

5.1 REALITY CHECK/PEER REVIEW CHECK

Definition:
Independent review by knowledgeable staff

Benefit:
Ensure data, assumptions, and procedures are reasonable

Objective(s) Addressed:
Accuracy, completeness, comparability, representativeness

Check(s):
Reasonableness of methods, assumptions, and emissions estimates are assessed. This is accomplished by 1) comparing data sources used in the final inventory to those specified in the Inventory Preparation Pl an, 2) reliance on reviewer expe rtise, and 3) comparison of emissions estimates to other previous inventor y efforts, particularly the 1990 base year inventory and the 1999 PEI and other inve ntories developed by EPA, regional organizations, or other states.

Limitations:
None

B-1215.2 SAMPLE CALCULATIONS

Definition:
Verification of values by replicating calculations

Benefit:

Ensure calculations are done correctly

Objective(s) Addressed:
Accuracy

Check(s):
Emissions calculations are duplicated to check the accuracy of the arithmetic and, therefore, the resulting emissi ons estimate. Priority is give n to those categories identified as the largest emissions contributors.

Limitations:
Estimates calculated using computer mode ls such as MOBILE6.2 are checked using simplified assumptions to arrive at a ”ballpark” value to use as a comparison to the actual
calculated value.

5.3 SENSITIVITY ANALYSIS

Definition
Systematic study of how changes in parameters affect data

Benefit
Identify the parameters that ha ve the greatest effect on data

Objective(s) Addressed
Generally addresses all objectives

Check(s)
A sensitivity analysis in the form of source category emissions rankings by pollutant is performed. The ranking helps determine wh ere efforts should be concentrated.

Limitations

None

B-1225.4 STANDARD RAN GE CHECKS

Definition
Standard range checks address the data quality objective of comparability

Benefit
Identify the source categories that have th e greatest change in emission levels from previous emission estimates.

Objective(s) Addressed
Generally addresses all objectives

Check(s)
The 2002 base year inventory is compared to the most recent inventory (base year 1990, 1999 PEI, 2002 NEI). Any discrepancies (data outliers) greater than 20% involving sources that made up great er than 5% of the 1990 PM 10 , 1999 CO, or 2002 inventories are corrected or justified.

The projection inventories are compared to the 2002 base year inventory. Any discrepancies (data outliers) between the base year and a given projection year greater than the population increase percentage pl us 10% and involving sources that made up greater than 5% of the 2002 or projection ye ar daily inventories are investigated and either corrected (see Corrective Action Plan be low) or justified. The justification includes whether there was a change in methodology (e .g., different emission factor, allocation method, activity data) or if th ere is a real anticipation of emissions increasing or decreasing (e.g., decreases in the onroa d sector due to fleet turnover).

Limitations

None.

5.5 CORRECTIVE ACTION PLAN

Corrective and follow-up actions identified dur ing the quality checki ng process are noted and referred to the appropriate staff. Both th e corrective actions identified and results of actions taken in response are documented.

B-123

# Attachment A1

BY 2002 Point Source Emissions Summary2 

## Summary of Point Source Emissi ons: District of Columbia
Point Sources (District of Columbia Portion of Washington Nonattainment Area only)
2002 Annual Emissions

Annual Emissions (Tons/Year)

FACILITY PM2.5 NOx SO2 VOC NH3 PM10

Bureau of Engraving & Printing 0.000 0.00 0.000 54.85 0.000 0.000 Georgetown University 2.373 33.26 15.124 1.74 0.228 2.544 GSA Central Heating Plant* 11.757 217.34 7.658 8.51 0.038 11.842 Howard University 2.547 33.73 1.785 1.84 0.172 2.565 Naval Research Laboratory 0.196 3.60 7.541 0.15 0.050 0.282 Pepco Benning Road Generating Station 15/16* 15.356 452.580 1466.901 1.953 7.813 66.97 Pepco Benning Road Generating Station Pkg Boilers* 0.439 15.417 60.851 0.080 0.319 2.07 Pepco Buzzard Point Generating Station* 4.634 339.849 390.054 0.158 0.000 4.63 St. Elizabeth's Hospital 2.249 29.62 0.377 1.63 0.146 2.252 U.S. Capitol Power Plant 82.513 128.60 482.666 0.76 1.900 83.543 U.S. Government Printing Office 0.000 0.00 0.000 12.84 0.000 0.000 U.S. Soldiers and Airmen's Home 0.812 10.72 0.343 0.59 0.054 0.815 Walter Reed Army Medical Center 1.986 29.33 23.670 1.45 0.246 2.256 Washington Hospital Center 1.671 23.41 10.580 1.21 0.160 1.791 Total 126.53 1,317.46 2,467.55 87.76 11.13 181.563 

## Summary of Point Source Emissions: Virginia
Point Sources (Virginia Portion of Washi ngton Nonattainment Area only) 2002 Annual Emissions
Annual Emissions (Tons/Year) FACILITY PM2.5 NOx SO2 VOC NH3 PM10

America Online Inc - Prince William 0.00 24.72 3.47 1.24 0.92 America Online Incorporated - Loudon 0.00 11.09 0.60 0.25 0.37 America Online Incorporated - Fairfax 0.00 12.29 2.14 0.26 0.36 APAC Virginia Incorporated- Manassas Plant 0.00 20.37 10.01 7.42 6.06 Bergmanns Inc 0.00 2.02 0.12 0.11 0.15 BP Products North America - Fairfax 0.00 0.00 0.00 32.00 0.00 Bull Run Stone 0.00 0.00 0.00 0.00 10.72 Bush Center for Intelligence (CIA) 0.00 31.77 8.41 5.52 1.35 CITGO Terminal 0.00 0.00 0.00 33.07 0.00 City of Manassas/VMEA 0.00 85.57 14.11 2.46 2.45 Columbia Gas Transmission Corp 0.00 28.59 0.81 6.90 1.69 ConcoPhillips - Manassas Terminal 0.00 0.00 0.00 36.23 0.00 Covanta Alexandria/Arlington, Inc. 0.00 570.80 3.20 3.06 1.43 Covanta Fairfax, Inc. 0.13 1,822.91 89.02 5.56 5.10 Crown Central Petroleum-Newington Terminal 0.00 0.00 0.00 10.89 0.00 Dominion - Possum Point 292.89 5,044.23 21,010.34 51.15 365.83 Dominion Transmission Inc - CNG Leesburg Station 0.00 14.59 0.00 6.03 0.25 Exxon Mobil Corporation 0.00 0.00 0.00 70.28 0.00 Glen-Gery Corporation - Capitol Plant 2.82 9.35 1.77 0.44 11.63 Hallmark Iron Works 0.00 0.00 0.00 14.30 0.00 HB Mellott Estate Incorporated 0.00 2.36 10.71 0.71 1.25 Inova Fairfax Hospital 0.00 17.11 0.26 0.92 1.22 Jefferson Millwork and Design 0.00 0.00 0.00 10.02 0.00 Lockheed Martin Manassas 0.00 14.07 0.29 0.65 0.62 Loudoun Co Asphalt -NEWTON ASPHALT 0.00 9.26 11.93 6.90 3.19 Manassas City of - Dominion Station 0.00 16.20 7.70 0.52 0.51 Manassas City of/Church Street 0.00 15.15 2.31 0.36 0.41 MASTER PRINT, INC 0.00 0.00 0.00 17.31 0.00 Michigan Cogeneration Systems Inc 13.28 102.67 4.56 12.32 13.28 Micron Technology Incorporated 0.00 6.37 0.94 12.31 11.95 Motiva Enterprises LLC 0.00 0.00 0.00 29.28 0.00 Motiva Springfield Terminal 0.00 0.00 0.00 41.10 0.00 National Reconnaissance Office 0.00 17.55 2.99 0.33 0.40 Noman M Cole Jr Pollution Control Plant 4.88 111.96 4.05 3.63 4.98 Pentagon Reservation 0.00 17.50 2.98 4.46 11.53 Potomac River Generating Station 220.42 5,725.80 16,119.80 33.88 492.90 Prince William County Sanitary Landfill 7.19 41.10 14.02 6.68 7.19 Science Applications International Corp. 0.00 17.05 2.69 0.48 0.51 Superior Paving Corp - Centreville Plt 0.00 7.76 0.85 13.18 0.02 Superior Paving Corp - Leesburg Plant 0.00 8.01 0.99 13.29 2.01 Transcontinental Gas Pipeline-Station 185 0.00 230.30 0.01 15.97 0.20 TransMontaigne Product Serv ices Inc - Fairfa x 0.00 0.00 0.00 24.34 0.00 Tuscarora Incorporated 0.00 2.19 0.11 70.56 0.24 US Army - Fort Belvoir 0.96 33.14 19.17 14.86 4.26 US Army - Fort Myer 0.00 14.36 2.85 5.46 1.05 US Marine Corps - Quantico 3.14 24.94 25.02 19.57 3.48 Vertis Inc. 0.00 2.70 0.02 40.11 0.21 Virginia Paving Company Alexandria Plant 0.00 18.75 21.94 10.42 7.48 Vulcan Construction Materials, LP 0.00 0.00 0.00 0.00 15.53 Washington Gas Light Company 0.00 61.10 0.04 5.15 4.89 Total 545.71 14,195.67 37,400.23 701.94 0.00 997.634 

## Summary of Point Source Emissions: Maryland
Point Sources (Maryland Portion of Washington Nonattainment Area only)
2002 Annual Emissions

Annual Emissions (Tons/Year)
FACILITY PM2.5 NOx SO2 VOC NH3 PM10

ANDREWS AIR FORCE BASE 5.39 26.00 3.76 4.80 5.57 ANDREWS AIR FORCE BASE - QUASI-POINT SOURCES 14.87 734.31 49.46 280.35 16.88 AUTOMATED GRAPHIC SYSTEMS 6.24
BROWN STATION ROAD LANDFILL 4.13 7.87 0.79 31.62 7.26
CANAM STEEL 1.57 4.50 138.40 1.89 CORPORATE PRESS - BRIGHTSEAT ROAD 8.86
COVANTA ENERGY-8309 TUJUNGA AVENUE CORP. 1.20 20.80 0.30 0.40 1.20
CRAFTSMAN PRESS - CRAFTSMAN CIRCLE 1.45 17.97 DAY, F.O. BITUMINOUS - PINEY MTG 0.21 8.30 5.79 6.91 1.76
DOW JONES & COMPANY 0.37 24.64 DURON, INCORPORATED 0.46 17.73 0.87 EASTALCO ALUMINUM 385.33 74.85 3,014.06 76.35 385.33
EDITORS PRESS 1.08 6.88
ESSROC CEMENT 77.10 1634.07 1,137.48 5.91 22.33 140.83 EU SERVICES 9.64
FORT DETRICK 42.56 89.96 283.65 3.29 44.19 GEORGE WESTON BAKERIES, INC. 2.16 47.60 GODDARD SPACE FLIGHT CENTER 5.47 29.02 0.91 2.27 6.35
KELLY PRESS 9.45 KLINE, RICHARD F., INCORPORATED 0.33 5.43 0.71 6.76 2.75 LEHIGH PORTLAND CEMENT 130.45 172.50 2,297.11 0.64 238.72
MCARDLE PRINTING 0.21 14.58 0.26
MIIRANT STATION H 19.53 155.62 6.42 1.38 19.53 MIRANT MID-ATLANTIC - MORGANTOWN 2342.84 18798.50 70,359.81 102.76 3731.98
MIRANT MID-ATLANTIC - DICKERSON 7243.20 33,905.81 41.01
MNCPPC - SANDY HILL LANDFILL 3.75 56.10 7.38 11.63 4.00 MONTGOMERY COUNTY RRF 11.06 1036.70 93.40 3.10 3.00 13.00
MOORE COMMUNICATIONS SERVICES 0.50 1.07 5.85
NATIONAL INSTITUTE OF HEALTH 3.97 64.55 1.76 1.50 3.97 NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY 5.08 28.78 1.88 1.45 5.08
NATIONAL NAVAL MEDICAL CENTER 4.68 13.88 23.52 4.61 4.68
NAVAL SURFACE WARFARE CNTR-INDIAN HD 54.79 180.76 1,038.08 8.33 54.79 PANDA BRANDYWINE, L.P. 7.16 44.44 29.54 2.04 7.16
PEAKE PRINTERS 0.34 10.20
PEPCO - CHALK POINT 339.73 15281.70 52,520.90 101.40 474.67 REPRODUCTIONS - RICKENBACKER DRIVE 12.91
S & S GRAPHICS 0.26 11.44
SAFEWAY STORES - BREAD PLANT 0.05 1.62 15.82 0.12 SMITH LITHOGRAPH 1.04 22.08
TAMKO ROOFING PRODUCTS 28.20 8.57 14.24 28.20
UNIVERSITY OF MARYLAND 6.24 98.02 0.48 3.79 6.24 WASHINGTON POST, THE 0.96 2.19 15.33 0.96 Total 3,497.31 45,829.43 164,784.06 1,112.16 25.33 5,208.23

# Attachment B1

Technical Memorandum on Commercial Cooking Emissions

# PECHAN

5528-B Hempstead Way Springfield, VA 22151

703-813-6700 telephone

703-813-6729 facsimile

3622 Lyckan Parkway

Suite 2002
Durham, NC 27707

919-493-3144 telephone

919-493-3182 facsimile

P.O. Box 1345
El Dorado, CA 95623

530-295-2995, ext. 200 telephone

530-295-2999 facsimile 

### METHODS FOR

DEVELOPING A

NATIONAL EMISSION

INVENTORY FOR

COMMERCIAL

COOKING PROCESSES:

TECHNICAL

MEMORANDUM

Prepared for:

Emission Factor and Inventory Group Emissions Monitoring and Analysis Division Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, NC 27711

Prepared by:

E.H. Pechan & Associates, Inc.

P.O. Box 1345
El Dorado, CA 95623

September 30, 2003

Contract No. 68-D-02-063 Work Assignment No. 1-09[This page intentionally left blank]PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum iii 

### CONTENTS Page

TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

I. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
A. POLLUTANTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 B. COMMERCIAL COOKING PROCESSES (SOURCE CATEGORIES) . . . . . . . . . . . 2

II. LITERATURE REVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
A. EMISSION FACTORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
B. ACTIVITY DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

III. METHODOLOGY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
A. ACTIVITY DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
B. SAMPLE CALCULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
C. CONTROLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

IV. RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

V. REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum iv 

### TABLES

1A. Summary of Commercial Cooking Test Results: Criteria Pollutants (g/kg) . . . . . . . . . . . . . 4 1B. Summary of Commercial Cooking Test Results: Criteria Pollutants (lb/ton) . . . . . . . . . . . . 5 2A. Summary of Commercial Cooking Test Results: Hazardous Air Pollutants (g/kg) . . . . . . . 6 2B. Summary of Commercial Cooking Test Results: Hazardous Air Pollutants (lb/ton) . . . . . . 9
3. Emission Factor Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4. Restaurant Classification System Used for the SCAQMD Survey . . . . . . . . . . . . . . . . . . . . 17 5. Restaurant Classifications Used in the PRI Study for CARB . . . . . . . . . . . . . . . . . . . . . . . . 17 6. Recommended Source Categories for Commercial Cooking . . . . . . . . . . . . . . . . . . . . . . . . 18 7. Percent of Restaurants with Each Type of Cooking Equipment . . . . . . . . . . . . . . . . . . . . . . 19 8. Average Number of Equipment Pieces by Restaurant Type . . . . . . . . . . . . . . . . . . . . . . . . 1 19 9. Average Pounds of Meat Cooked on Each Type of Equipment Per Week . . . . . . . . . . . . . . 19 10. Mapping of Criteria Pollutant EFs to Activity Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 11. Mapping of HAP EFs to Activity Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 12. HAP Pollutants and CE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 13. 2002 National Criteria and Hazardous Air Pollutant Emissions for Commercial Cooking . 25



### FIGURES

2.5 1. PM Emissions by Commercial Cooking Source Category . . . . . . . . . . . . . . . . . . . . . . . . 27

2.5 2.5 2. Comparison of Commercial Cooking PM Emissions to NEI 2001 PM Emissions . . . . 28 3. Total Polycyclic Aromatic Hydrocarbon (PAH) Emissions by Commercial Cooking Source Category . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 4. Comparison of Commercial Cooking PAH Emissions to NEI 1999 PAH Emissions . . . . . 30PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 1 

### I. INTRODUCTION

The Emission Factor and Inventory Group (EFIG) produces the National Emission

3 Inventory (NEI) for criteria and hazardous air pollutants (HAPS) and ammonia (NH ). These data are needed by EPA and State agencies to evaluate emission trends and as a basis for various EPA modeling and regulatory analyses. Since the early 1990’s, there have been several investigations and tests conducted to determine emissions from commercial cooking activities. Commercial cooking activities were believed to be capable of producing significant amounts of criteria pollutants (especially fine particulate matter) and HAPS.

2.5 Emissions from commercial cooking may contribute to exceedances of the Federal PM air quality standards in certain regions. Commercial cooking processes are important contributors of secondary organic aerosols (SOA) and organic carbon (OC) and elemental carbon (EC). SOA is formed from the condensation of gaseous organic emissions at ambient temperatures, sometimes following photo-chemical processes. Estimated contributions of various source categories, including meat charbroiling, to carbonaceous PM in Pittsburgh, Pennsylvania are described by Cabada et al. (2002).

This technical memorandum contains data and methods for quantifying these emissions on a national level to determine the impact of commercial cooking activities on national air quality. The approach for producing an emissions inventory (EI) of criteria pollutants and HAPS from commercial cooking for the calendar year 2002 are described (note that no emission factors for

3 NH were identified). The most challenging aspect of the work was to identify appropriate activity data for the existing emission factors. This memorandum provides information on emission factors developed from recent test programs for commercial cooking followed by a discussion of the activity data that were used to construct the national inventory.



### A. POLLUTANTS

Based on previous tests conducted by EPA and State and local environmental agencies, the focus of the emissions inventory is commercial cooking of meat, which is the greatest source of commercial cooking emissions. In particular, emissions of particulate matter (PM) and volatile organic compounds (VOCs) are the most significant. Of the commercial cooking processes that have been studied, charbroiling is the most important air pollutant emissions contributor. Commercial cooking processes are described in more detail below.

Particulate matter is the general term used for a mixture of solid particles and liquid droplets

10 suspended in air. EPA defines PM as particle matter having a nominal aerodynamic diameter

2.5 of 10 micrometer ( : m) or less. PM is defined as PM that is less than or equal to 2.5 : m in

10 aerodynamic diameter. The Federal Government has established emission standards for PM .

2.5 2.5 In 1997, new standards for PM were proposed by EPA due to the negative impact of PM on human health and visibility in the United States.

VOCs contribute to the formation of ozone and SOA in some cases. Ozone is not directly emitted from stationary or mobile sources, but is formed through photo-chemical reactions in the

x atmosphere with other air pollutants (e.g., nitrogen oxides or NO ). Commercial charbroilingPECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 2 processes also produce HAP emissions. Notable among these are emissions of polycyclic aromatic hydrocarbons (PAHs).



### B. COMMERCIAL COOKING PROCESSES (SOURCE CATEGORIES)

Pechan categorized the commercial cooking EI into five source categories based on equipment type. For the purposes of this EI, commercial cooking processes and source categories are synonymous. Source categories comprise emissions from all meat types for a particular equipment type. The following types of meat are included: hamburger, steak, fish, pork, and chicken. The five equipment types have been adopted from work carried out by the South Coast Air Quality Management District (SCAQMD, 1997):

• Chain-driven (conveyorized) charbroilers: this type of broiler has conveyor belts to carry the meat through the flame area. It also may have a belt to carry buns through the appliance. Typically, flames broil the meat on the top and bottom simultaneously. Most chain-driven charbroilers burn natural gas. This appliance normally produces lower PM and VOC emissions than under-fired charbroilers;

• Under-fired charbroilers: these appliances consist of three main components - a heating source, a high-temperature radiant surface, and a slotted grill. The grill holds the meat, or other food, while exposing it to the radiant heat. When grease from the meat falls onto the high-temperature radiant surface, both PM and VOC emissions occur. Most under-fired charbroilers burn natural gas; however, solid fuels, such as charcoal or wood, with or without the addition of ceramic stones, are sometimes used. This category includes broilers, grill charbroilers, flame broilers, and direct-fired barbecues. This category contributes the bulk of emissions for the commercial cooking sector;

• Deep Fat Fryers: fryers use an exposed hot metal surface to heat cooking oil, which is then used to cook the food. Typically, the food is totally immersed in hot melted shortening at about 177°C (350 / F). The fryers may be either gas-fired or electric with fuel type not affecting PM or VOC emissions. Most of the raw food products have a water content in the range of 10% to 75% by weight prior to deep fat frying. Most of the water at the surface of the product vaporizes during the cooking process causing a carry-over of oil mist and oil distillation, resulting in VOC and PM emissions. Practically all fast-food establishments utilize deep fat fryers to prepare food in batches;

• Griddles: these appliances consist of an exposed metal plate used to cook food. The temperatures on the hot surface are typically lower than those encountered in broiling. Unlike deep fat frying, the food is not immersed in shortening, rather the process is similar to sautéing, and the emissions include light oil particulates and odors. Some griddles are grooved in order to give a “broiled” appearance to the food. Most griddles are gas-fired, although electric griddles are also used. Fuel type does not affect emissions of PM or VOC; and

• Clam Shell Griddles: a newer griddle type, which employs a two-sided cooking configuration, lowering an upper hot plate on top of the food product to cook that side while a lower plate cooks the bottom of the product. This reduces cooking time and
decreases emissions.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 3 The studies reviewed by Pechan indicate that the type of fuel used by each cooking equipment category was not important to estimating emissions of PM or VOC. However, the testing programs were often designed to measure VOC, PM, and their components, and did not focus on

x 2 other combustion products, such as NO , carbon monoxide (CO), or sulfur dioxide (SO ), which may be more strongly associated with fuel combustion.



### II. LITERATURE REVIEW

A. EMISSION FACTORS

Pechan reviewed an EPA report entitled “Emissions from Street Vendor Cooking Devices (Charcoal Grilling)” that was prepared by the Office of Air Quality Planning and Standards (OAQPS) (EPA, 1999). This report discusses tests that were conducted by EPA to quantify emissions due to charcoal grilling of meat by street vendors in Mexicali, Mexico. The emissions of interest included PM, VOC, semi-volatile compounds (SVOC), aldehydes, carbon monoxide

2 x 2 (CO), carbon dioxide (CO ), NO , total hydrocarbons (THC), and sulfur dioxide (SO ). Emissions were tested for charcoal grilling of both beef and chicken, including marinated and non-marinated meat. Test results are summarized in Tables 1A, 1B, 2A, and 2B. In Tables 1A and 2A, the emission factors are expressed in grams per kilogram (g/kg); whereas, in Tables 1B and 2B, they are expressed in pounds per ton (lb/ton).

For the street vendor charcoal grilling test program, EPA (1999) noted that charcoal did not contribute significantly to total PM, VOC or SVOC emission levels. Marinated meat had higher VOC and total PM emissions than non-marinated meat. No significant differences were seen in emission rates between chicken and beef (chicken was whole chicken with skin). Emissions of CO and nitric oxide (NO) appeared to be primarily from the charcoal fire and not the cooking of meat. THC emissions were almost all from the initial burning of charcoal (e.g., first half hour),

2 however there appears to be some contribution from meat cooking. Emission rates for SO were not reported due to problems with the analyzer. The emission factors reported in Tables 1A and 1B were developed as the average of two test results. When one test result was a non-detect, the emission factor from the detected result is reported as the emission factor. This was done since the report did not list the detection limits for each pollutant.

Emission tests supporting rule development in the SCAQMD were conducted by the University of California, Riverside Bourns College of Engineering - Center for Environmental Research and Technology [(CE-CERT); Norbeck 1997]. These tests focused on PM and VOC (see Tables 1A and 1B). McDonald et al. (2003) used additional test data from CE-CERT to develop emission estimates for the Colorado Front Range Study. These data include emission factors for CO and some HAPs (mainly PAHs; see Tables 1A, 1B, 2A, and 2B).

Cabada et al. (2002) used organic carbon (OC) emission factors for meat frying and charbroiling in their development of a carbonaceous PM inventory for Pittsburgh. The source of their data was a 1991 study.4 Table 1A. Summary of Commercial Cooking Test Results: Criteria Pollutants (g/kg)

Equipment Type (fuel) Meat/Food Emission Factor (g/kg meat) 1

10 2.5 x 2 PM PM PM CO NO VOC SO Notes

Under fired-Charbroiler (charcoal) Beef 8.1 7.5 7.1 163.5 2.4 4.7 n/a Source: EPA, 1999. Beef was flank steak. Chicken

2 was thigh meat. SO analyzer malfunctioned, so no

x emissions data reported. CO and NO emissions appear to be mainly from charcoal burning. VOC was measured as total hydrocarbons (THC). Some of the VOC is attributed to the burning of charcoal (most of which burns off after the first 30 minutes of light-off). Beef (marinated) 9.5 9.2 8.7 167.6 3.6 5.8 n/a

Chicken (marinated) 9.8 9.4 9.1 157.9 4.2 4.5 n/a

Under-fired Charbroiler (natural gas) Hamburger (25% fat) 32.7 32.7 31.9 13.72 n/a 3.94 n/a Source: Norbeck, 1997. VOC measured as reactive organic gases (ROG). CO taken from McDonald et al., 2003.

Steak 17.2 17.2 16.8 4.97 n/a 0.86 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Chicken (whole) 10.5 10.5 9.9 4.84 n/a 1.82 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Seafood 3.3 3.3 3.2 n/a n/a 0.38 n/a Source: Norbeck, 1997. Seafood - Atlantic salmon.

Deep fat fryer (natural gas) Shoestring potatoes n/d n/a n/a n/a n/a 0.21 n/a Source: Norbeck, 1997. EF is in g/kg potatoes

Breaded chicken n/d n/a n/a n/a n/a 0.12 n/a Source: Norbeck, 1997.

Breaded fish n/d n/a n/a n/a n/a 0.14 n/a Source: Norbeck, 1997.

Griddle (electric) Hamburger (24% fat) 5.0 5.0 3.8 0.38 n/a 0.07 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Chicken (boneless breast) n/d n/a n/a 0.45 n/a 0.4 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Seafood n/d n/a n/a n/a n/a 0.11 n/a Source: Norbeck, 1997. Seafood - cod fillets.

Conveyorized Charbroiler (natural gas) Hamburger (21% fat) 7.4 7.4 7.3 8.29 n/a 2.27 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Double-sided (clamshell) Griddle (electric) Hamburger (24% fat) 0.85 0.85 0.72 n/a n/a 0.01 n/a Source: Norbeck, 1997.

n/d - not detected; n/a - not analyzed. Emission factors in bold were used in this project. For PM, all testing was performed using dilution sampling techniques. Hence, both 1
filterable and condensible fractions are represented.5 Table 1B. Summary of Commercial Cooking Test Results: Criteria Pollutants (lb/ton)

Equipment Type (fuel) Meat/Food Emission Factor (lb/ton meat) 1

10 2.5 x 2 PM PM PM CO NO VOC SO Notes

Under fired-Charbroiler (charcoal) Beef 16.2 15.0 14.2 327 4.8 9.4 n/a Source: EPA, 1999. Beef was flank steak. Chicken

2 was thigh meat. SO analyzer malfunctioned, so no

x emissions data reported. CO and NO emissions appear to be mainly from charcoal burning. VOC was measured as total hydrocarbons (THC). Some of the VOC is attributed to the burning of charcoal (most of which burns off after the first 30 minutes of light-off). Beef (marinated) 19.0 18.4 17.4 335.2 7.2 11.6 n/a

Chicken (marinated) 19.6 18.8 18.2 315.8 8.4 9.0 n/a

Under-fired Charbroiler (natural gas) Hamburger (25% fat) 65.4 65.4 63.8 27.44 n/a 7.88 n/a Source: Norbeck, 1997. VOC measured as reactive organic gases (ROG). CO taken from McDonald et al., 2003.

Steak 34.4 34.4 33.6 9.94 n/a 1.72 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Chicken (whole) 21.0 21.0 19.8 9.68 n/a 3.64 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Seafood 6.6 6.6 6.4 n/a n/a 0.76 n/a Source: Norbeck, 1997. Seafood - Atlantic salmon.

Deep fat fryer (natural gas) Shoestring potatoes n/d n/a n/a n/a n/a 0.42 n/a Source: Norbeck, 1997. EF is in g/kg potatoes

Breaded chicken n/d n/a n/a n/a n/a 0.24 n/a Source: Norbeck, 1997.

Breaded fish n/d n/a n/a n/a n/a 0.28 n/a Source: Norbeck, 1997.

Griddle (electric) Hamburger (24% fat) 10.0 10.0 7.6 0.76 n/a 0.14 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Chicken (boneless breast) n/d n/a n/a 0.9 n/a 0.8 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Seafood n/d n/a n/a n/a n/a 0.22 n/a Source: Norbeck, 1997. Seafood - cod fillets.

Conveyorized Charbroiler (natural gas) Hamburger (21% fat) 14.8 14.8 14.6 16.58 n/a 4.54 n/a Source: Norbeck, 1997. CO taken from McDonald et al., 2003.

Double-sided (clamshell) Griddle (electric) Hamburger (24% fat) 1.70 1.70 1.44 n/a n/a 0.02 n/a Source: Norbeck, 1997.

n/d - not detected; n/a - not analyzed. Emission factors in bold were used in this project. For PM, all testing was performed using dilution sampling techniques. Hence, both 1
filterable and condensible fractions are represented.6 Table 2A. Summary of Commercial Cooking Test Results: Hazardous Air Pollutants (g/kg)

Equipment Type (fuel) Meat Emission Factor (g/kg meat) 1

Ben Tol EBen o-xyl m,p-xyl Sty Form Acet Prop EdCl MeCl Phen Notes

Under firedCharbroiler (charcoal) Beef 0.392 0.154 0.026 0.023 0.023 0.151 0.337 0.251 0.068 0.017 0.012 0.016 Source: EPA, 1999. Beef

was flank steak. Chicken was thigh meat. W here 2 test runs were performed,

the listed value is the average (non-detects were not averaged into
the emission factor due

to lack of data on detection limits). Fat content: beef = 7%; chicken = 18%;
marinated beef = 19%. Beef (marinated) 0.502 0.184 0.038 0.030 0.025 0.218 0.526 0.329 0.084 0.015 0.010 0.021

Chicken (marinated) 0.504 0.200 0.040 0.033 0.028 0.190 0.393 0.282 0.076 0.014 0.012 0.023

Ben = benzene; Tol = toluene; Eben = ethyl benzene; Sty = styrene; Form = formaldehyde; Acet = acetaldehyde; Prop = propionaldehyde; EdCl = ethylene dichloride; MeCl = 1
methylene chloride; Phen = phenol. Emissions of MeCl appear to come mainly from the burning of charcoal; all other emission factors were used in this project.7 Table 2A (continued)

Equipment Type (fuel) Meat Emission Factor (g/kg meat) 1

AcPh o-Cre p-Cre Nap BaP Ace Flu Phn Fla Pyr dnBP 4nPh Notes

Under firedCharbroiler (charcoal) Beef 1.83

E-03 9.18

E-04 1.77

E-03 2.15

E-02 n/a 0.00 n/d 2.14

E-03 6.51

E-04 6.51

E-04 1.03

E-03 n/d Source: EPA, 1999.

Beef was flank steak. Chicken was thigh

meat. W here 2 test runs were performed,

the listed value is the average (non-detects were not averaged

into the emission
factor due to lack of data). Fat content: beef = 7%; chicken = 18%; marinated beef
= 19%. Charcoal

contributed to
emissions for about

half of these HAPs. Beef (marinated) 2.73

E-03 1.28

E-03 2.16

E-03 2.54

E-02 n/a 1.42

E-03 6.81

E-04 3.17

E-03 5.39

E-04 7.04

E-04 n/d n/d

Chicken (marinated) 2.43

E-03 1.68

E-03 3.43

E-03 2.29

E-02 n/a 1.57

E-03 8.25

E-04 3.56

E-03 7.14

E-04 5.00

E-04 1.92

E-03 6.60

E-03

Conveyorized

Charbroiler (natural gas) Hamburger n/a n/a n/a 2.30

E-02 1.70

E-04 4.89

E-03 1.09

E-03 4.88

E-03 8.80

E-04 1.15

E-03 n/a n/a Source: McDonald et al., 2003.

Under-fired

Charbroiler (natural gas) Hamburger n/a n/a n/a 1.90

E-02 1.50

E-04 4.24

E-03 1.26

E-03 4.88

E-03 1.40

E-03 1.90

E-03 n/a n/a

Steak n/a n/a n/a 1.50

E-02 7.00

E-05 4.28

E-03 1.17

E-03 5.31

E-03 1.28

E-03 1.56

E-03 n/a n/a

Chicken n/a n/a n/a 8.75

E-03 1.00

E-04 2.06

E-03 7.20

E-04 3.46

E-03 1.28

E-03 1.80

E-03 n/a n/a

Griddle (electric) Hamburger n/a n/a n/a 6.10

E-03 2.00

E-05 1.60

E-04 2.10

E-04 2.07

E-03 8.60

E-04 1.15

E-03 n/a n/a

Chicken n/a n/a n/a 1.00

E-03 1.00

E-05 1.30

E-04 1.80

E-04 1.87

E-03 6.20

E-04 8.20

E-04 n/a n/a

n/d = not detected; AcPh = acetophenone; o-Cre = ortho-cresol; p-Cre = para-cresol; Nap = naphthalene; BaP = benzo[a]pyrene; Ace = acenaphthylene; Flu = fluorene; Phn = 1
phenanthrene; Fla = fluoranthene; Pyr = pyrene; dnBP = di-n-butyl phthalate; 4nPh = 4-nitrophenol. The emission factors in bold were used for this project.8 Table 2A (continued)

Equipment Type (fuel) Meat Emission Factor (g/kg meat) 1

BbFl BkFl BaA Chr dBa,hA InP Acn An BghiP PAHt BiP Notes

Conveyorized

Charbroiler (natural gas) Hamburger n/a n/a 2.20

E-04 n/a n/a 1.00

E-04 2.80

E-04 9.10

E-04 1.60

E-04 0.05 2.43

E-03 Source: McDonald et

al., 2003. Most PAH species were analyzed; however some were grouped with other species (e.g.,benzo[b+j+k]fluoranthene). Hence, species specific

emission factors were

not available. Under-fired

Charbroiler (natural gas) Hamburger n/a n/a 2.20

E-04 n/a n/a 9.00

E-05 1.50

E-04 9.40

E-04 1.70

E-04 0.05 1.72

E-03

Steak n/a n/a 1.10

E-04 n/a n/a 5.00

E-05 1.50

E-04 1.03

E-03 9.00

E-05 0.04 1.54

E-03

Chicken n/a n/a 3.40

E-04 n/a n/a 6.00

E-05 1.00

E-04 8.80

E-04 9.00

E-05 0.03 9.10

E-04

Griddle (electric) Hamburger n/a n/a 7.00

E-05 n/a n/a n/d 2.00

E-05 1.70

E-04 n/d 7.96

E-03 6.00

E-05

Chicken n/a n/a 1.20

E-04 n/a n/a n/d 5.00

E-05 4.40

E-04 n/d 9.51

E-03 1.30

E-04

n/d = not detected; n/a = not analyzed; BbFl = benzo[b]fluoranthene; BkFl = benzo[k]fluoranthene; BaA = benz[a]anthracene; Chr = chrysene; dBa,hA = dibenzo[a,h]anthracene; 1
InP = indeno[1,2,3-c,d]pyrene; Acn = acenaphthene; An = anthracene; BghiP = Benzo[g,h,i,]perylene; PAHt = total PAH; BiP = Biphenyl. All emission factors were used in this project.9 Table 2B. Summary of Commercial Cooking Test Results: Hazardous Air Pollutants (lb/ton)

Equipment Type (fuel) Meat Emission Factor (lb/ton meat) 1

Ben Tol EBen o-xyl m,p-xyl Sty Form Acet Prop EdCl MeCl Phen Notes

Under firedCharbroiler (charcoal) Beef 0.784 0.308 0.052 0.046 0.046 0.302 0.674 0.502 0.136 0.034 0.024 0.032 Source: EPA, 1999. Beef

was flank steak. Chicken was thigh meat. W here 2 test runs were performed,

the listed value is the average (non-detects were not averaged into
the emission factor due

to lack of data on detection limits). Fat content: beef = 7%; chicken = 18%;
marinated beef = 19%. Beef (marinated) 1.004 0.368 0.076 0.060 0.050 0.436 1.052 0.658 0.168 0.030 0.020 0.042

Chicken (marinated) 1.008 0.400 0.080 0.066 0.056 0.380 0.786 0.564 0.152 0.028 0.024 0.046

Ben = benzene; Tol = toluene; Eben = ethyl benzene; Sty = styrene; Form = formaldehyde; Acet = acetaldehyde; Prop = propionaldehyde; EdCl = ethylene dichloride; MeCl = 1
methylene chloride; Phen = phenol. Emissions of MeCl appear to come mainly from the burning of charcoal; all other emission factors were used in this project.10 Table 2B (continued)

Equipment Type (fuel) Meat Emission Factor (lb/ton meat) 1

AcPh o-Cre p-Cre Nap BaP Ace Flu Phn Fla Pyr dnBP 4nPh Notes

Under firedCharbroiler (charcoal) Beef 3.66

E-03 1.84

E-03 3.54

E-03 4.30

E-02 n/a 0.00 n/d 4.28

E-03 1.30

E-03 1.30

E-03 2.06

E-03 n/d Source: EPA, 1999.

Beef was flank steak. Chicken was thigh

meat. W here 2 test runs were performed,

the listed value is the average (non-detects were not averaged into
the emission factor due to lack of data). Fat content: beef = 7%; chicken = 18%;
marinated beef = 19%.

Charcoal contributed to

emissions for about half

of these HAPs. Beef (marinated) 5.46

E-03 2.56

E-03 4.32

E-03 5.08

E-02 n/a 2.84

E-03 1.36

E-03 6.34

E-03 1.08

E-03 1.41

E-03 n/d n/d

Chicken (marinated) 4.86

E-03 3.36

E-03 6.86

E-03 4.60

E-02 n/a 3.14

E-03 1.65

E-03 7.12

E-03 1.43

E-03 1.00

E-03 3.84

E-03 1.32

E-02

Conveyorized Charbroiler (natural gas) Hamburger n/a n/a n/a 4.60

E-02 3.40

E-04 9.78

E-03 2.18

E-03 9.76

E-03 1.76

E-03 2.30

E-03 n/a n/a Source: McDonald et al., 2003.

Under-fired Charbroiler (natural gas) Hamburger n/a n/a n/a 3.80

E-02 3.00

E-04 8.48

E-03 2.52

E-03 9.76

E-03 2.80

E-03 3.80

E-03 n/a n/a

Steak n/a n/a n/a 3.00

E-02 1.40

E-04 8.56

E-03 2.34

E-03 1.06

E-02 2.56

E-03 3.12

E-03 n/a n/a

Chicken n/a n/a n/a 1.75

E-02 2.00

E-04 4.12

E-03 1.44

E-03 6.92

E-03 2.56

E-03 3.60

E-03 n/a n/a

Griddle (electric) Hamburger n/a n/a n/a 1.22

E-02 4.00

E-05 3.20

E-04 4.20

E-04 4.14

E-03 1.72

E-03 2.30

E-03 n/a n/a

Chicken n/a n/a n/a 2.00

E-03 2.00

E-05 2.60

E-04 3.60

E-04 3.74

E-03 1.24

E-03 1.64

E-03 n/a n/a

n/d = not detected; AcPh = acetophenone; o-Cre = ortho-cresol; p-Cre = para-cresol; Nap = naphthalene; BaP = benzo[a]pyrene; Ace = acenaphthylene; Flu = fluorene; Phn = 1
phenanthrene; Fla = fluoranthene; Pyr = pyrene; dnBP = di-n-butyl phthalate; 4nPh = 4-nitrophenol. The emission factors in bold were used for this project.11 Table 2B(continued)

Equipment Type (fuel) Meat Emission Factor (lb/ton meat) 1

BbFl BkFl BaA Chr dBa,hA InP Acn An BghiP PAHt BiP Notes

Conveyorized Charbroiler (natural gas) Hamburger n/a n/a 4.40

E-04 n/a n/a 2.00

E-04 5.60

E-04 1.82

E-03 3.20

E-04 0.10 4.86

E-03 Source: McDonald et al.,

2003. Most PAH species were analyzed; however some were grouped with other species (e.g.,benzo[b+j+k]fluoranthene). Hence, species specific emission factors

were not available. Under-fired Charbroiler (natural gas) Hamburger n/a n/a 4.40

E-04 n/a n/a 1.80

E-04 3.00

E-04 1.88

E-03 3.40

E-04 0.10 3.44

E-03

Steak n/a n/a 2.20

E-04 n/a n/a 1.00

E-04 3.00

E-04 2.06

E-03 1.80

E-04 0.08 3.08

E-03

Chicken n/a n/a 6.80

E-04 n/a n/a 1.20

E-04 2.00

E-04 1.76

E-03 1.80

E-04 0.06 1.82

E-03

Griddle (electric) Hamburger n/a n/a 1.40

E-04 n/a n/a n/d 4.00

E-05 3.40

E-04 n/d 1.59

E-02 1.20

E-04

Chicken n/a n/a 2.40

E-04 n/a n/a n/d 1.00

E-04 8.80

E-04 n/d 1.90

E-02 2.60

E-04

n/d = not detected; n/a = not analyzed; BbFl = benzo[b]fluoranthene; BkFl = benzo[k]fluoranthene; BaA = benz[a]anthracene; Chr = chrysene; dBa,hA = dibenzo[a,h]anthracene; 1
InP = indeno[1,2,3-c,d]pyrene; Acn = acenaphthene; An = anthracene; BghiP = Benzo[g,h,i,]perylene; PAHt = total PAH; BiP = Biphenyl. All emission factors were used in this project.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 12 In constructing the national inventory, Table 3 provides the sources for emission factors (i.e., the emission factors shown in Tables 1A, 1B, 2A, and 2B). The emission factors from Norbeck (1997) and McDonald et al. (2003) were generally favored since they are based on common commercial cooking operations. The EPA (1999) study was performed to characterize emissions from street vendors in Mexico (e.g., using charcoal-fired charbroilers and marinated meat). Several HAP emission factors from the EPA study were used where these factors were not available from the other studies and where the emissions do not appear to be mainly from the burning of charcoal.

Table 3. Emission Factor Sources

Pollutants Emission Factor Source

10 2.5 Criteria Pollutants: PM , PM , VOC Norbeck (1997)

CO, PAHs, Biphenyl McDonald (2003)

ethylene dichloride, benzene, toluene, ethyl benzene, xylenes, styrene, formaldehyde, acetaldehyde, propionaldehyde, acetophenone, o-cresol, p-cresol EPA (1999); emissions that appeared to be associated with the burning of charcoal
were excluded.



### B. ACTIVITY DATA

The emission factors are specific both to meat type and type of cooking equipment. Pechan performed a literature search for activity data including the amount of meat cooked at various types of commercial facilities and number of restaurants/other commercial cooking facilities which perform these activities. This involved a review of U.S. Census Bureau data and reports, U.S. Department of Agriculture data, the scientific literature, industry journals, and reports on commercial cooking emissions from State and local environmental agencies.

U.S. Census Data

In the Statistical Abstract of the United States, the U.S. Census Bureau presents per capita expenditures on food consumed both at home and away from home (BOC, 2002). At-home food expenditures are broken down into categories, such as meat, and subcategories, such as, beef, pork, other meats, poultry, fish and seafood, and eggs. However, expenditures on food consumed away from home is not tracked by food category.

Pechan also examined the U.S. Census Bureau sector report on food wholesaling. According to the sector report on wholesaling, food service outlets buy over 20% of wholesale grocery and related products. The food service industry includes a broad range of business types. Data specific to commercial cooking facilities such as restaurants and cafeterias were not
available.

The U.S. Census Bureau provides basic data on “eating and drinking places” including sales, earnings, number of establishments, number of employees, and payroll. The sales data are broken down into various types of eating and drinking places. These data are also provided by the National Restaurant Association (NRA, 2002).PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 13 Lastly, the Statistical Abstract of the United States contains both producer price indexes and consumer price indexes for food, including meat by type and cut (i.e., ground beef, ham, whole chicken, etc.). The consumer price index data are based on information for retail sales of food such as sales at grocery stores.

The U.S. Bureau of Census’ County Business Patterns provides facility counts by county and North American Industry Classification System (NAICS) code. While these data provide detailed resolution of restaurant categories, the available survey data described below are categorized by Standard Industrial Classification (SIC) code instead of NAICS code.

US Department of Agriculture

Pechan contacted Judy Putnam of the U.S. Department of Agriculture (USDA) regarding food consumption data. Ms. Putnam stated that USDA does not track food away from home consumption or sales data which are specific to meat or meat cuts. She said panel and individual survey data on food consumption was available which contains the amount of food consumed away from home. However, these data may not specify the meat cut or how the meat was cooked. The surveys were generally conducted for 2 week periods.

Scientific and Industry Literature

Pechan researched the scientific and industry literature to obtain information on the consumption and expenditures of meat products in the “away from home” market and sales of meat to restaurants and other food service facilities. The business, hospitality, and agriculture literature was reviewed. Several reports were obtained for expenditures in the “away from home” market and sales of meat, however, no information was obtained that was usable as activity data. The available agriculture data focused on the cost and sales of meat at the wholesale level, which as stated previously, does not distinguish between different types of food service suppliers, such as restaurants versus grocery stores. The hospitality literature focused ontotal sales of food by restaurant type and trends in the food and type of restaurants such as fastfood and national chains. The business literature focused on sales information by type of restaurant. There was limited information on sales at specific franchises and regional/national chains and types of meat such as hamburger.

Pechan reviewed one article which mentioned estimating emissions from meat cooking (Cabada, et al., 2002). The work was part of an effort to estimate atmospheric carbonaceous PM for a number of source categories in the Pittsburgh, PA metropolitan area. The emissions estimate for meat cooking was developed using the total population of the Pittsburgh area and the annual per capita consumption of meat in the United States from the U.S. Census Bureau State and Metropolitan Data Book. The estimate assumed that 90% of the meat consumed was fried and 10% was charbroiled. Meat cooking operations were assumed to remain constant during the year. In addition, no distinction was made between in home consumption and “away from home” consumption.

Meat and Food Service Industry Associations and Consultants

Pechan contacted the following industry groups to request information on the sales, consumption and expenditures of meat products in restaurants and the food service industry:PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 14 • National Restaurant Association; • The Food Institute; •. The Food Marketing Institute; • American Meat Institute; • National Cattleman’s Association; and
• International Food Service Manufacturers Association.

None of these associations or institutions reported having data available on sales, consumption or expenditures of meat at restaurants or other commercial cooking facilities. The food consumption, sales and expenditure data that are readily-available are generally provided at a higher level than that desired for activity data. This included the National Restaurant Association report entitled Restaurant Industry Operations Report (NRA, 2002). The report is based on an annual survey that provides information on typical operational costs in a restaurant, including the percentage of sales allocated to employee benefits, food-and-drink purchases, services and more. The report only distinguishes between food and beverages, not by type of
food.

Pechan also contacted Sterling Marketing, the current publishers of the American Meat Institute report Meat & Poultry Facts (Appel, 2003). Pechan reviewed the Table of Contents for the report. This report contained similar data to that provided in the Statistical Abstract of the United States such as per capita consumption and consumer/producer price indices, therefore, Pechan did not obtain a copy.

Several of the associations suggested contacting food service consultants. Pechan contacted two such companies. Pechan spoke with Tracy Ethridge of Technomic. Ms. Ethride stated that data on the amount of meat cooked or meat sales specific to the restaurant industry were not readily available. She stated that the data could be developed by their company. Pechan also spoke with Harry Balzer of the ND&P Group. Mr. Balzer stated that their CREST-Restaurant Purchases database contained data on food purchases at commercial restaurants by type of food. CREST collects data from a sample of 13,000 households reporting on 33,000 individuals. The data would include restaurant name and type of food purchased, but would not indicate the cooking method. The estimated cost for providing these data was on the order of $50,000.

Dun & Bradstreet

The Dun & Bradstreet Marketplace data provide facility counts by county and 8-digit SIC code (Dun & Bradstreet, 2002). These data also include facility counts by revenue class, which may be useful in future inventory development (e.g., at regional/local levels, if relationships are established between revenue and the amount of meat processed).

Environmental Agency Reports

EPA’s Emission Inventory Improvement Program (EIIP) Area Source Method Abstract on charbroiling provides an average ground beef throughput per restaurant with a charbroiler of 1,160 pounds (lbs) cooked per week (EPA, 2000). This estimate was based on Whopper and ® hamburger sales as posted on the Burger King website (www.burgerking.com), and assumes an ® average hamburger weight of 0.25 lb.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 15 Pechan contacted the Massachusetts Department of Environmental Protection (MADEP) to gather underlying information for their emission estimates for this source category (Santal, 2003). MADEP estimated VOC emissions from commercial charbroilers and commercial deep fat fryers using emission factors obtained from a 1992 EPA report (EPA, 1992). The EPA report provided equipment fractions (e.g., 9% of restaurants have charbroilers) and VOC emission factors to apply to facility counts (e.g., number of restaurants from the County Business Patterns). These VOC emission factors were 1,000 lb VOC/restaurant-yr for charbroiling and 101 lb/restaurant-yr for deep fat fryers.

Pechan reviewed documents pertaining to the SCAQMD Rule 1138 development process. This includes a staff report for the proposed Rule 1138 (SCAQMD, 1997) and a survey of commercial cooking operations in the SCAQMD conducted by PES (1999). In the staff report on the proposed rule, the average daily amount of hamburger cooked on a chain-driven charbroiler was estimated to be 233 lb. This value was based on confidential data provided by affected restaurants. No other meat types were discussed in the report. For comparison, Pechan calculated a value of 154 lb/day based on information provided on Burger King’s web-site (Burger King, 2003). This estimate assumes one chain-driven charbroiler per facility, each hamburger patty weighs 0.25 lb prior to cooking, and 365 days of operation per year.

The study conducted by PES was to obtain accurate estimates of the total number of restaurants in the SCAQMD, to classify restaurants using a scheme that is relevant to meat cooking operations, and to obtain the distribution in the SCAQMD of the following:

• Types of cooking equipment; • Types and amount of meats cooked for each equipment; • Fuels used by cooking equipment; • Fat content of hamburger cooked; • Days per year of operation; • Ventilation hoods and stacks; and • Percentage of small businesses.

The total number of restaurants was obtained by reviewing lists of facilities regulated by the county health departments in the District. This total was adjusted to account for restaurants which had gone out of business. The remaining information was obtained by a detailed survey
of restaurants.

CARB began work on estimating emissions from charbroiling activities at restaurants in the State of California. A detailed survey of restaurants was conducted by the Public Research Institute of San Francisco State University (PRI). The draft report was submitted in June of 2001 (PRI, 2001). Pechan contacted CARB regarding further development of an emission inventory from charbroiling activity but was told that there were no plans for developing an inventory.

The PRI survey was similar to the PES survey, with a few key differences. First, PRI surveyed restaurants using computer-assisted telephone interviews instead of a self-administered (mail-out) questionnaire. Second, PRI used a more detailed restaurant classification scheme, and not all restaurant categories were surveyed. PRI surveyed a subset of restaurants most likely to employ charbroilers. Third, PRI surveyed fewer types of cooking devices.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 16 In 2002, the San Joaquin Valley Unified Air Pollution Control District promulgated a rule regarding commercial charbroiling (SJVUAPCD, 2002). The Final Draft of the Staff report for Rule 4692 utilized the average pounds of meat cooked per day that SCAQMD utilized in its staff report for the proposed Rule 1138 (SCAQMD, 1997). The number of restaurants was determined from health department records on permitted restaurants.



### III. METHODOLOGY

A. ACTIVITY DATA

After reviewing the literature; Pechan developed activity data based on data provided by the PRI survey (PRI, 2001). The PRI survey data were chosen over the PES survey data for several

reasons:

• The PRI survey sample size and geographic area were larger than in the PES survey;. • The PRI survey used a more detailed classification of restaurants that focused on restaurant types most likely to use charbroilers (the most important emissions process);
and • National restaurant facility counts are available for the same restaurant classifications used by PRI.

From the 4,518 surveys sent to restaurants in the SCAQMD, PES obtained 543 usable responses. The PRI survey included a slightly larger sample, with 655 completed interviews. The PRI survey sample included restaurants from all over the State of California. Although the sample size of the PRI survey was only slightly larger than the PES survey, the PRI survey covered the entire State of California. This broader geographic coverage makes for a better fit with the national scope of this project.

PES categorized restaurants into 9 different types, as shown in Table 4. The categorization used a 6-digit SIC categorization approach. This type of approach does not fully resolve the types of restaurants that are thought to contribute the most emissions. For example, fast food chains were associated with a more generic group of establishments called “restaurants” rather than breaking out the type of restaurant into “limited service”and “full-service” restaurants. As shown in the table, neither the 6-digit SIC code used by PES nor the associated NAICS code allow for the identification of establishments of most interest (e.g., fast food chains).

The CARB study conducted by PRI did not survey all types of restaurants. Instead, this study focused on a subset of restaurants most likely to employ charbroilers. These restaurant categories, shown in Table 5, were classified using a system developed by Dun & Bradstreet (a 2-digit extension of the 4-digit SIC code). Survey data from this study can be directly applied to national, county-level facility counts available from Dun & Bradstreet.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 17 Table 4. Restaurant Classification System Used for the SCAQMD Survey

Restaurant Type Primary 6-Digit
SIC Code Associated
NAICS Code # Facilities

in SCAQMD

Banquet Rooms 5812-23 72211 305

Barbecue 5812-24 72211 16

Cafes 5812-14 72211 32

Cafeterias 5812-13 722212 52

Foods-Carry Out & Foods Delivered 5812-06,
5812-30 72221 2,140

Caterers 5812-12 72232 912

Coffee Shops 5812-28 722213 255

Delicatessens 5812-09 72221 708

Pizza 5812-22 72211, 72221 1,120

Restaurants 5812-08 72211, 72221 19,361

Sandwich Shops 5812-19 72221 352

Total 25,253

Table 5. Restaurant Classifications Used in the PRI Study for CARB

Restaurant Type Dun & Bradstreet Code

Ethnic food 5812-01

Fast food 5812-03
Family 5812-05

Seafood 5812-07

Steak & Barbecue 5812-08

Table 6 provides the recommended source categories for the commercial cooking and charbroiling inventory. Note that the following sources/pollutants will not be included in the inventory: residential or special-event cooking and charbroiling (e.g., county fairs, other public gatherings); cooking processes at institutional facilities (e.g., school or prison cafeterias); commercial cooking processes at facilities that do not fall within the surveyed facility categories; and most criteria pollutant emissions associated with fuel combustion (e.g., natural gas or propane used to fire a charbroiler). Criteria pollutant emissions associated with fuel combustion

x (e.g., NO , CO) in cooking equipment are included in the commercial fuel combustion emissions

x sector of the NEI. Pechan recommends no changes to these emission estimates. NO emissions were typically not measured for the test programs reviewed during this project. Also, most of the measured CO emissions from the available studies appear to be from the cooking of meat,
not fuel combustion.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 18 Table 6. Recommended Source Categories for Commercial Cooking

SCC Descriptor 1 Descriptor 2 Descriptor 3

2302002000 Industrial

Processes Food and Kindred Spirits:
SIC 20 Commercial Cooking, Total

2302002100 Industrial

Processes Food and Kindred Spirits:
SIC 20 Commercial Cooking, Conveyorized Charbroiling

2302002200 Industrial

Processes Food and Kindred Spirits:
SIC 20 Commercial Cooking, Under-fired Charbroiling

2302002300 Industrial

Processes Food and Kindred Spirits:
SIC 20 Commercial Cooking, Flat Griddle Frying

2302002400 Industrial

Processes Food and Kindred Spirits:
SIC 20 Commercial Cooking, Clamshell Griddle Frying

2302002500 Industrial

Processes Food and Kindred Spirits:
SIC 20 Commercial Cooking, Deep Fat Frying

Tables 7 - 9 provide data from the PRI survey that were used to construct the activity data for each source category (i.e., pounds of meat/year). There are no emission factors for pork; therefore, Pechan used emission factors for chicken to estimate emissions from cooking of pork. Pechan used steak emission factors for the “other” category; which includes lamb, veal, and
venison. Tables 10 and 11 provide a map of the criteria pollutant and HAP emission factors to the national activity data (i.e., average pounds of meat cooked by each equipment type per week).

Pechan also estimated emissions from deep fat frying of french fries. The per capita consumption of frozen potatoes in 2001 was obtained from Economic Research Service, USDA (USDA, 2003). French fries account for 95 percent of frozen potatoes servings, and 80% of french fries are purchased in restaurants (USDA, 2001). From this information, the per capita consumption of french fries in restaurants were estimated. The activity data for deep fat frying of french fries were the 2002 county-level population data from the BOC.

Note that emissions from residential charbroiling were not included in this inventory effort. Also, note that commercial cooking operations that take place outside of the source sector universe described above are not included (e.g., restaurants not classified into one of the SIC codes listed in Table 5). While Pechan anticipates that the bulk of emissions occur within the universe defined in Table 5, it is not possible with existing information to estimate the amount of commercial activity that is being missed. Other related sources include institutional cooking processes (e.g., schools and prisons) and episodic commercial processes, such as county or state
fairs.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 19 Table 7. Percent of Restaurants with Each Type of Cooking Equipment

Restaurant Category Chain-Driven

Charbroilers Underfired

Charbroilers Deep-Fat Fryers Flat Griddles Clamshell
Griddles

Ethnic 3.5 47.5 81.9 62.7 4

Family 10.1 60.9 91.4 82.9 1.4

Fast Food 18.6 30.8 96.8 51.9 14.7

Seafood 0 52.6 100 36.8 10.5

Steak & BBQ 6.9 55.2 82.8 89.7 0

Table 8. Average Number of Equipment Pieces by Restaurant Type 1

Restaurant Category Chain-Driven

Charbroilers Underfired

Charbroilers Deep-Fat Fryers Flat Griddles Clamshell
Griddles

Ethnic 1.62 1.54 1.63 1.88 1.8

Family 1.71 1.29 2.34 2.03

– 1

Fast Food 1.07 1.58 3.1 1.43 2.09

Seafood

-- 1.1 2.47 1.11 1.5

Steak & BBQ – 1.63 2.42 1.35

-- 2,3
Average number of equipment pieces only for the segment of restaurants estimated as having such equipment. 1 Not clear why the number of pieces of equipment was not reported for this category. 2 Steak and BBQ restaurants are not likely to employ chain-driven charbroilers. 3

Table 9. Average Pounds of Meat Cooked on Each Type of Equipment Per Week

Type of Meat Chain-Driven
Charbroilers Underfired

Charbroilers Deep-Fat

Fryers Flat

Griddles Clamshell

Griddles

Steak 236 180 181 166 94

Hamburger 798 270 274 362 1314

Poultry, W ith Skin 147 144 365 88 113

Poultry, Skinless 266 179 208 111 108

Pork 57.6 148 58.6 112 118

Seafood 119 143 159 92.1 632

Other

-- 41.5 274 57.5

–20 Table 10. Mapping of Criteria Pollutant EFs to Activity Data

Type of Meat Chain-Driven Charbroilers Underfired Charbroilers Deep-Fat Fryers Flat Griddles Clamshell Griddles

Steak Hamburger EF Steak EF No EFs Hamburger EF Hamburger EF

Hamburger Hamburger EF Hamburger EF No EFs Hamburger EF Hamburger EF

Poultry, with skin Chicken (whole) EF Chicken (whole) EF Breaded Chicken EF Chicken (boneless breast) EF Flat Griddle Chicken (boneless breast) EF reduced by % VOC Hamburger EF

Poultry, skinless Chicken (whole) EF Chicken (whole) EF Breaded Chicken EF Chicken (boneless breast) EF Flat Griddle Chicken (boneless breast) EF reduced by % VOC Hamburger EF

Pork Chicken (whole) EF Chicken (whole) EF Breaded Chicken EF Chicken (boneless breast) EF Flat Griddle Chicken (boneless breast) EF reduced by % VOC Hamburger EF

Seafood Seafood EF Seafood EF Breaded Fish EF Seafood EF Flat Griddle Seafood EF reduced by % VOC Hamburger EF

Other Meat No Activity Steak EF No EFs Hamburger EF No Activity

Notes:

Chain-Driven Charbroilers:

Hamburger emission factors used for "Steak".

Underfired Charbroilers Chicken (whole) emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

Underfired Charbroilers Seafood emission factors used for "Seafood".

Underfired Charbroilers:

Chicken (whole) emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

Steak emission factors used for "Other Meat".

Deep-Fat Fryers:

Did not estimate "Steak", "Hamburger", and "Other Meat" emissions due to lack of emission factor data.

Breaded Chicken emission factors used for both "Poultry, with skin" and "Poultry, skinless".

Breaded Fish emission factors used for "Seafood".

VOC emissions for cooking french fries estimated with the EF of 0.21 g/kg potatoes cooked.

Flat Griddles:

Hamburger emission factors used for "Steak" and "Other Meat".

Chicken (boneless breast) emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

Clamshell Griddles:

Hamburger emission factors used for "Steak".

To develop a VOC emission factor for Chicken, estimated the percent VOC of the Hamburger EFs (Flat Griddle/Clamshell Griddle) and reduced the Flat Griddle Chicken (boneless breast) VOC EF by this percent. This Chicken VOC emission factor was applied to "Poultry, with skin", "Poultry, skinless", and "Pork".

To develop a VOC emission factor for Seafood, estimated the percent VOC of the Hamburger EFs (Flat Griddle/Clamshell Griddle) and reduced the Flat Griddle Seafood VOC EF by this percent.21 Table 11. Mapping of HAP EFs to Activity Data

Type of Meat Chain-Driven Charbroilers Underfired Charbroilers Deep-Fat Fryers Flat Griddles Clamshell Griddles

Steak Hamburger EF Steak EF, Beef EF No EFs Hamburger EF No EFs

Hamburger Hamburger EF Hamburger EF No EFs Hamburger EF No EFs

Poultry, with skin Chicken EF, Chicken (Marinated) EF Chicken EF, Chicken (Marinated) EF No EFs Chicken EF No EFs

Poultry, skinless Chicken EF, Chicken (Marinated) EF Chicken EF, Chicken (Marinated) EF No EFs Chicken EF No EFs

Pork Chicken EF, Chicken (Marinated) EF Chicken EF, Chicken (Marinated) EF No EFs Chicken EF No EFs

Seafood No EFs No EFs No EFs No EFs No EFs

Other Meat No Activity Steak EF, Beef EF No EFs Hamburger EF No Activity

Notes:

Chain-Driven Charbroilers:

Hamburger emission factors used for "Steak".

For certain HAPs, Underfired Charbroilers Chicken emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

For certain HAPs, Underfired Charbroilers Chicken (marinated) emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

Underfired Charbroilers:

For certain HAPs, Chicken emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

For certain HAPs, Chicken (Marinated) emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

For certain HAPs, Steak emission factors used for "Other Meat".

For certain HAPs, Beef emission factors used for "Steak" and "Other Meat".

Deep-Fat Fryers:

Did not estimate HAP emissions for Deep-Fat Fryers due to lack of emission factor data.

Flat Griddles:

Hamburger emission factors used for "Steak" and "Other Meat".

For Flat Griddles, Chicken emission factors used for "Poultry, with skin", "Poultry, skinless", and "Pork".

Clamshell Griddles:

Did not estimate HAP emissions for Clamshell Griddles due to lack of emission factor data.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 22 

### B. SAMPLE CALCULATION

The following sample calculation illustrates how activity data (pounds of meat) were estimated for SCC 2810060020, under-fired charbroiling, for one county. The facility counts for each type of restaurant in the county were used with the survey data in Tables 6-9 to estimate activity. The steps in this process are:

Step 1. Multiply county-level facility counts by the fraction of each restaurant type with each type of cooking equipment (Table 6):

ethnic ethnic, ufc ethnic, ufc N * f = N

ethnic where: N = Number of ethnic food restaurants in county;

ethnic, ufc f = fraction of ethnic food rest. with under-fired charbroilers; and

ethnic, ufc N = Number of ethnic food rest. with under-fired charbroilers.

538 restaurants x 0.475 = 256 ethnic food rest. with under-fired charbroilers

Step 2. Multiply number of restaurants with each type of cooking equipment by number of pieces of equipment (Table 7):

ethnic, ufc ethnic, ufc ethnic, ufc N * e = E

ethnic, ufc where: N = Number of ethnic food rest. with under-fired charbroilers;

ethnic, ufc e = Number of under-fired charbroilers at ethnic food restaurants with at

least one under-fired charbroiler;

ethnic, ufc E = Total number of under-fired charbroilers at ethnic food restaurants.

256 ethnic food rest. with under-fired charbroilers * 1.54 under-fired charbroilers

= 394 under-fired charbroilers at ethnic food restaurants

Step 3. Sum number of pieces of cooking equipment across restaurant types:

ethnic,ufc family,ufc fast,ufc seafood,ufc S&B,ufc all,ufc E + E + E + E + E = E

ethnic,ufc where: E = Total number of under-fired charbroilers at ethnic food restaurants;

family,ufc E = Total number of under-fired charbroilers at family restaurants;

fast,ufc E = Total number of under-fired charbroilers at fast food restaurants;

seafood,ufc E = Total number of under-fired charbroilers at seafood restaurants;

S&B,ufc E = Total number of under-fired charbroilers at steak & barbecue restaurants;

and

all,ufc E = Total number of under-fired charbroilers at all restaurants.

394 ethnic + 238 family + 62 fast food + 14 seafood + 32 steak & barbecue

= 737 under-fired charbroilers at all restaurants

Step 4. Multiply total number of under-fired charbroilers by average pounds of meat cooked on each type of equipment per week (Table 9):PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 23 all,ufc steak,ufc steak,ufc E * m = M

all,ufc where: E = Total number of under-fired charbroilers at all restaurants

steak,ufc m = Average pounds per week of steak cooked on one under-fired charbroiler

steak,ufc M = Total pounds per week of steak cooked on all under-fired charbroilers in

the county

(737 under-fired charbroilers x 180.06 lbs/week) / (2000 lbs/ton)

= 66.4 tons of steak per week

The mass of meat was then multiplied by the appropriate emission factor. Emissions for all meat types were summed at the equipment level and reported by SCC.



### C. CONTROLS

The only known area with controls in place with regards to commercial charbroiling is the South Coast Air Quality Management District (SCAQMD) in California. Controls consistent with the requirements of Rule 1138 currently only affect chain-driven charbroilers (SCAQMD, 1997). Pechan applied an 86% control efficiency (CE) for VOC and an 83% CE for PM to uncontrolled chain-driven charbroiler emissions in the following SCAQMD counties: Los Angeles, Orange, Riverside, and San Bernardino. For uncontrolled HAP emissions in these counties, Pechan applied either the CE that was used to estimate controlled VOC emissions or
the CE used to estimate controlled PM emissions. Rule effectiveness for these four counties was set to 100%. Los Angeles and Orange counties are assumed to have 100% rule penetration. San Bernardino and Riverside counties were assumed to have 80% rule penetration, since about 80% of the population of these counties resides within the SCAQMD.

For HAPs, Table 12 lists the pollutant and the CE used to estimate controlled emissions. Controlled emissions of volatile organic HAP species were estimated by using the VOC CE,

10 while those associated with PM were estimated using the PM CE.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 24 Table 12. HAP Pollutants and CE

Pollutant Pollutant Code CE Used

10 4-Nitrophenol 100027 PM

10 Acenaphthene 83329 PM

10 Acenaphthylene 208968 PM

Acetaldehyde 75070 VOC

Acetophenone 98862 VOC

10 Anthracene 120127 PM

10 Benz[a]Anthracene 56553 PM

Benzene 71432 VOC

10 Benzo[a]Pyrene 50328 PM

10 Benzo[g,h,i,]Perylene 191242 PM

10 Biphenyl 92524 PM

10 Dibutyl Phthalate 84742 PM

Ethyl Benzene 100414 VOC

Ethylene Dichloride 107062 VOC

10 Fluoranthene 206440 PM

10 Fluorene 86737 PM

Formaldehyde 50000 VOC

10 Indeno[1,2,3-c,d]Pyrene 193395 PM

m,p-xylenes 1330207 VOC

Naphthalene 91203 VOC

o-Cresol 95487 VOC

o-Xylene 95476 VOC

p-Cresol 106445 VOC

10 Phenanthrene 85018 PM

Phenol 108952 VOC

Propionaldehyde 123386 VOC

10 Pyrene 129000 PM

Styrene 100425 VOC

Toluene 108883 VOC

10 Total PAH 234 PMPECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 25 

### IV. RESULTS

2002 National criteria pollutant and hazardous air pollutant (HAP) emissions are summarized in Table 13 by SCC and pollutant type. Emissions are expressed in tons per year (tpy).

Table 13. 2002 National Criteria and Hazardous Air Pollutant Emissions for Commercial Cooking

Source Classification Code (SCC)

Pollutants 2302002000 (tpy) 2302002100

(tpy) 2302002200

(tpy) 2302002300

(tpy) 2302002400

(tpy) 2302002500

(tpy)

VOC 11,532 2,113 7,234 940 38.9 1,206

CO 33,004 7,401 23,662 1,941

PM 85,515 8,460 60,304 15,679 1,073

10 PM 85,515 8,460 60,304 15,679 1,073

2.5 PM 79,320 8,201 58,295 11,916 909

NAPHTHALENE 80.9 18.1 42.0 20.8

BENZO[A]PYRENE 0.57 0.15 0.34 0.08

ACENAPHTHYLENE 14.9 3.93 10.2 0.72

FLUORENE 5.05 0.95 3.13 0.96

PHENANTHRENE 27.7 4.35 13.8 9.61

FLUORANTHENE 8.94 0.99 4.22 3.73

PYRENE 12.00 1.33 5.70 4.97

BENZ[A]ANTHRACENE 1.49 0.25 0.81 0.42

INDENO[1,2,3-C,D]PYRENE 0.30 0.09 0.21

ACENAPHTHENE 0.77 0.22 0.40 0.15

ANTHRACENE 5.14 0.88 2.99 1.27

BENZO[G,H,I,]PERYLENE 0.50 0.14 0.36

PAH, TOTAL 205.6 42.9 121.9 40.8

BIPHENYL 6.44 1.92 4.12 0.40

BENZENE 1,237 154.3 1,083

TOLUENE 489.7 61.2 428.5

ETHYL BENZENE 94.4 12.2 82.2

O-XYLENE 79.0 10.1 68.9

XYLENES (MIXTURE OF O, M, AND P ISOMERS) 69.6 8.57 61.1

STYRENE 468.7 58.2 410.6

FORMALDEHYDE 987.8 120.3 867.5

ACETALDEHYDE 715.6 86.3 629.3

PROPIONALDEHYDE 193.1 23.3 169.9

ETHYLENE DICHLORIDE 38.9 4.28 34.6

PHENOL 55.1 7.04 48.0

ACETOPHENONE 5.92 0.74 5.18

O-CRESOL 3.84 0.51 3.32

P-CRESOL 7.75 1.05 6.70

DIBUTYL PHTHALATE 4.37 0.59 3.78

4-NITROPHENOL 12.4 2.02 10.4PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 26 2.5 Pechan reviewed the percent contribution of PM emissions by source category to the total

2.5 PM commercial cooking emissions. The percentages are summarized in Figure 1. The total

2.5 2.5 PM commercial cooking emissions were also compared to various source category PM emissions obtained from EPA’s 2001 NEI (EPA, 2003a). Percent contributions, by source

2.5 category, to the total 2001 area source NEI PM emissions are summarized in Figure 2.

Pechan reviewed the percent contribution of total polycyclic aromatic hydrocarbon (PAH) emissions by source category to the total PAH commercial cooking emissions. The percentages are summarized in Figure 3. The total PAH commercial cooking emissions were compared to various source category PAH emissions obtained from EPA’s 1999 National Emissions Inventory (NEI) (EPA, 2003b). In the NEI, PAH emissions are expressed as total PAH, 16- PAH, 7-PAH, and by PAH species. For the comparison, Pechan used all available PAH emissions from the NEI. Percent contributions, by source category, to the total 1999 area source NEI PAH emissions are summarized in Figure 4.271. PM2.5Emissions by Commercial Cooking Source CategoryFigure 1. PM2.5Emissions by Commercial Cooking Source Category1%Clamshell Griddle Frying15%Flat Griddle Frying74%Underfired-Charbroilers10%ConveyorizedCharbroiling282. Comparison of Commercial Cooking PM2.5Emissions to NEI 2001 PM2.5Emissions1. Agriculture & Forestry consists ofagricultural crops andagricultural livestock.2. Stationary Source Fuel Combustion consists of electric utilities oil, gas,other, and internal combustion; industrial coal, oil, other, and internal combustion;commercial/institutional coal, oil, and gascombustion; miscellaneous fuel combustion (except residential), and residential other fuel combustion.3. Other Combustion consists of structural fires, agricultural fires, slash/prescribed burning, and other miscellaneous area source combustion.Figure 2. Comparison of Commercial Cooking PM2.5 Emissionsto NEI 2001 PM2.5 Emissions1%Agriculture, Food,& Kindred Products1%Commercial Cooking1%Wood, Pulp & Paper, & PublishingProducts1%Mineral Products2%Industrial Gas Combustion2%Metals Processing2%On-Road Vehicles4%Non-RoadEngines &Vehicles5%ResidentialWoodCombustion5%OtherCombustion36%Open Burning6%Stationary SourceFuel Combustion27%Electric UtilitiesCoal Combustion8%ForestWildfires13%Agriculture & Forestry1293. Total Polycyclic Aromatic Hydrocarbon (PAH)Emissions by Commercial Cooking Source CategoryFigure 3. Total Polycyclic Aromatic Hydrocarbon (PAH) Emissionsby Commercial Cooking Source Category20%Flat Griddle Frying21%ConveyorizedCharbroiling59%Underfired-Charbroiling304. Comparison of Commercial Cooking PAH Emissions to NEI 1999 PAH EmissionsFigure 4. Comparison of Commercial Cooking PAH Emissionsto NEI 1999 PAH Emissions3%Surface Coating Solvent Utilization2%Storage & Transport-Service Stations:Stage I1%Storage & Transport-Service Stations:Stage II1%Commercial Cooking1%Storage & Transport-Bulk Terminals &Plants1%Solvent Utilization: NEC11%POTW's1%Graphic Arts SovlentUtilization5%Catastrophic/Accidental Releases7%ResidentialWoodCombustion22%Other Combustion55%Nonindustrial SolventUtilization1. Not Elsewere Classified.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 31 

### V. REFERENCES

Appel, 2003: Kathryn Appel, WATT Meat Book Services, personal communication with P. Hemmer, E.H. Pechan & Associates, Inc., March 2003.

BOC, 2002: United States Bureau of the Census, “Table 195. Per Capita Consumption of Major Food Commodities: 1980 to 2000,” Statistical Abstract of the United States, 121st ed., Washington: GPO, 2001, 5 Jun. 2002.

Burger King, 2003: Burger King, “Corporate Facts,” accessed from www.burgerking.com in
March 2003.

Cabada, et al., 2002: Cabada, Juan, Spyros Pandis, and Allen Robinson, “Sources of Atmospheric Carbonaceous Particulate Matter in Pittsburgh, Pennsylvania,” J. Air & Waste Management Assoc ., 52:732-741, June 2002.

Dun & Bradstreet, 2002: Dun & Bradstreet, Inc., MarketPlace CD-ROM, Jan-Mar, 2002, Waltham, MA, 2002.

EPA, 1992: U.S. Environmental Protection Agency, Identification and Characterization of Missing or Unaccounted for Area Source Categories , Air and Energy Engineering Research Laboratory, EPA-600-92-006, January 1992.

EPA, 1999: U.S. Environmental Protection Agency, Emissions from Street Vendor Cooking Devices (Charcoal Grilling) , EPA-600/R99-048, Washington, DC, June 1999.

EPA, 2000: U.S. Environmental Protection Agency, Emission Inventory Improvement Program (EIIP), Volume III, Area Source Category Method Abstracts - Charbroiling , December
2000.

EPA, 2003a: U.S. Environmental Protection Agency, Average Annual Emissions, All Criteria Pollutants Years Including 1970 - 2001, [Data file]. Available from EPA Web site http://www.epa.gov/ttnchie1/trends/index.html

EPA, 2003b: U.S. Environmental Protection Agency, 1999 Nonpoint Area Source National Emission Inventory for Hazardous Air Pollutants, Version 3, July 2003.

McDonald, et al., 2003: McDonald, J.D., B. Zielinska, E.M. Fujita, J.C. Sagebiel, J.C. Chow, and J.G. Watson, “Emissions from Charbroiling and Grilling of Chicken and Beef,” J. Air & Waste Management Assoc. , vol. 53:185-194, 2003.

Norbeck, 1997: Norbeck, J.M., Further Development of Emission Test Methods and Development of Emission Factors for Various Commercial Cooking Operations , Final Report for SCAQMD, July 24, 1997.

NRA, 2002: National Restaurant Association, Restaurant Industry Operations Report—2002

, August 1, 2002.PECHAN September 30, 2003

Methods for Developing a NEI for Commercial Cooking Processes: Technical Memorandum 32 PES, 1999: A Detailed Survey of Restaurant Operations in the South Coast Air Basin , Final Report, prepared by Pacific Environmental Services, prepared for the South Coast Air Quality Management District, February 5, 1999.

PRI, 2001: Public Research Institute, Potepan, Michael, “Charbroiling Activity Estimation, Draft Report,” prepared for California Environmental Protection Agency, California Air Resources Board, June 30, 2001.

Santal, 2003: K. Santal, Massachusetts Department of Environmental Protection, personal communication with S. Roe, E.H. Pechan & Associates, Inc., March 2003.

SCAQMD, 1997: South Coast Air Quality Management District, Perryman, Pamela and Peter Votlucka, “Staff Report for Proposed Rule 1138 - Control of Emissions from Restaurant Operations,” October 10, 1997.

SJVUAPCD, 2002: San Joaquin Valley Unified Air Pollution Control District, “Final Draft Staff Report: Rule 4692,” February, 2002.

USDA, 2001: U.S. Department of Agriculture, “Food Review,” Volume 24, Issue 1, Economic Research Service, January-April, 2001.

USDA, 2003: U.S. Department of Agriculture, “Potatoes, U.S. per capita utilization, by category, 1971 - 2001,” Economic Research Service, www.ers.usda.gov/Briefing/Potatoes/ potatofacts.htm, 2003.

# Attachment B2

Technical Memorandum on Composting Emissions

# Appendix B2

Technical Memorandum on Composting Emissions

# PECHAN

P.O. Box 1345 6245 Pleasant Valley Road El Dorado, CA 95623

530-295-2995 telephone 530-295-2999 facsimile

3622 Lyckan Parkway
Suite 2002 Durham, NC 27707

919-493-3144 telephone 919-493-3182 facsimile

5528-B Hempstead Way Springfield, VA 22151

703-813-6700 telephone 703-813-6729 facsimile 

# Technical Memorandum:
MANE-VU 2002 Ammonia Emissions Inventory f or Miscellaneous
Sources

FINAL

Prepared for:

MARAMA Mid-Atlantic Regional Air Management Association 711 W. 40th Street, Suite 318 Baltimore, MD 21211-2109

Prepared by:

Stephen M. Roe Ying K. Hsu Holly C. Lindquist E.H. Pechan & Associates, Inc.
P.O. Box 1345 6245 Pleasant Valley Road El Dorado, CA 95623

March 31, 2004PECHAN March 31, 2004



### A. INTRODUCTION

E.H. Pechan & Associates, Inc. (Pechan) developed 2002 ammonia (NH 3 ) emission estimates for several miscellaneous source categories for the Mid-Atlantic – North east Visibility Union (MANE-VU) Regional Planning Organization (RPO). The source categories are a part of four different source sectors: indus trial refrigeration (Section B); cement plants (Section C); and publicly-owned treatment works (POTWs) a nd composting (Section D). For composting, Pechan developed 2002 emission estimates for volat ile organic compounds (VOC) in addition to
NH 3 . Methods and data sources for developing the 2002 inventory are describe d in the first three sections of this technical me morandum. Section E provides th e results of this project.



### B. INDUSTRIAL REFRIGERATION

In order to estimate NH 3 emissions from industrial refrig eration sources for the 2002 MANE-VU Ammonia Inventory, Pechan attempted both top-dow n and bottom-up approaches as described in the work plan (Pechan, 2003a). The top-down a pproach was based on methods used to construct the South Coast Air Quality Management District ’s (SCAQMD) inventory. For this inventory,
NH 3 suppliers were surveyed to gather information on annual sales and end use (including refrigeration). Part of what made this a successful method in the SCAQMD is that the researchers had determined that only thr ee companies supplied nearly all of the NH 3 (Chitjian et al, 2000).

Pechan attempted to obtain data on NH 3 purchases and the amount of NH 3 lost by facilities using
NH 3 refrigeration systems. Pechan first tried to collect data from NH 3 suppliers. This attempt
was unsuccessful for two reasons. Firs t, finding a comprehensive list of NH 3 suppliers was difficult. Many of the companies listed as supplying NH 3 in chemical supplier databases either
did not sell NH 3 , sold NH 3 in another form, or only sold small amounts of NH 3 for laboratory use. Second, few of the companies contacted re sponded to our request for sales data.

Once it was determined that surveying suppliers would not yield sufficien t data for inventory development, Pechan began collecting data directly from facilities operating NH 3 refrigeration systems. Pechan’s starting point was EPA’s Ri sk Management Program (RMP) database (EPA, 2003a). This information included data on the location of 188 RPO f acilities that submitted
RMPs to EPA with NH 3 refrigeration systems. The th reshold for RMP reporting is 10,000 pounds (lbs) of storage. These RMP data did not include any facilities in Delaware (DE), Rhode Island (RI), or the District of Columbia (DC). The basic content of the RMP data was facility
contact information and an indication of an NH 3 refrigeration process at the facility (in a process field). Pechan attempted to obtain informati on from the Offsite Consequence Analysis (OCA) portion of the RMP, which is likely to include information on the capacity of the system. However, these data are currently considered se nsitive (due to terrorism), and Pechan was not
able to obtain them.

Pechan gathered the following data from 30 RMP facilities covering a wide range of industries:

• The amount of NH 3 typically lost by the refrigeration sy stem in one year or the amount of
NH 3 purchases over the past few year s to recharge the system; and

1 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

• The operating capacity of the system (in lbs of NH 3 ).

In addition to the RMP database, Pechan obtained survey data from the Delaware Department of Natural Resources and Environmental Control ( DNREC) for an additional 22 facilities in DE (Fees, 2004). These data included 2002 charges to the refrigeration system and system capacity.
Pechan added the DE data to the RMP data for facilities with capacitie s near or above the 10,000
lb RMP threshold. This resulted in 43 facilities. An analysis of the data from these facilities showed an average system capacity of about 32,000 lb of NH 3 (±7,000 lb at 95% confidence) and an annual loss rate of approximately 8% (±3% at 95% confidence) . Note that not all facilities recharge their systems every year. Approximately one-third of the RMP/DNREC facilities reported zero recharge s during the prev ious year(s).

For all of the surveyed facilities, Pechan estimated annual NH 3 losses by multiplying the capacity by the 8% loss factor. This was done in stead of using the valu es supplied directly by the facilities, since: a) some facilities reported zero recharges during the survey period, and b) facilities that did report losses during the surv ey period likely did not emit that amount of NH 3 during a single year. For the remaining RMP fac ilities that were not surveyed, Pechan assigned the average 32,000 lb capacity and the 8% loss rate . To these data, Pechan also added system capacity data for six facilities supplied by the New Jersey Department of Environmental
Protection that could be matched to the RMP database (Papalski, 2004).

After compiling the RMP data, it was noted th at there were a few instances where potential duplicate facilities appeared. With the available data, Pechan could not determine if these were indeed duplicate records or if a f acility had more than one refrigeration system. Therefore, these potential duplicates were left in the database. The overall effe ct on the inventory estimates is
small.

The information described above shoul d cover facilities with large NH 3 refrigeration systems (>10,000 lb) based on the assumption that faciliti es required to report under the RMP program
have done so. For facilities that have smaller re frigeration systems, Pechan requested data from the MANE-VU states from the Superfund Amendmen ts and Reauthorization Act of 1986 (SARA) Tier II reporting requirements. Under these requirements, facilities s ubject to Section 311 of SARA must supply information on the type a nd amount of hazardous substances at their facilities each year. For NH 3 , the threshold quantity is 500 lb.

Pechan again had difficulty obtaini ng data on these Tier II facilities. There were two reasons for this. First, as with the RMP data, much of the SARA reporting data are now considered sensitive. Second, many states do not have these data in an electronic format (only hard copy reporting forms). Pechan was able to obtain data on nine Tier II f acilities from RI. Of these nine facilities, one was larger than the 10,000 RMP reporting threshol d. Pechan also received Tier II data from NJ. Pennsylvania refused to provi de Tier II data for this proj ect and no other states provided data. After extracting data for facilities within th e SIC codes of interest (see Table 1), there were less than 30 facilities (some of which were already in the RMP data). Even with the addition of several more smaller facilities from DE, the avai lable information for smaller capacity facilities

2 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

was not sufficient to develop estim ates that could be extrapolated to the RPO. The data from RI and NJ were added to the database for larger facilitie s described above.

In order to fill out the rest ofthe inventory for this source category, Pechan used an employeebased emission factor to be in cluded in the Emission Invent ory Improvement Program (EIIP) guidance to estimate total county-level refrigerati on loss emissions (30 lb/employee-yr). This emission factor was derived from data in the SC AQMD inventory (Chitjian et al, 2000). No data are available to estimate certainty bounds around this emission factor. The employment data were taken from the 2001 U.S. Bureau of Census County Business Patterns (BOC, 2003; 2002 data are not yet available). Th e Standard Industrial Classificati on (SIC) codes used to develop the county-level employment data are shown in Table 1 below (the North American Industrial Classification System co des are also shown).

The emission estimates in the NIF formatted file correspond to the total county-level estimates made with the EIIP emission factor. The only case where this does not appl y is for the State of Delaware. The DNREC contact feel s that their coverage of industrial refrigeration sources is complete (Fees, 2004). It is intere sting to note that the use of the emission factor above yields an estimate for DE that is about an order of magn itude higher than that de veloped through the DE survey data. While some smaller industrial refrigeration systems could be missing in DE’s survey data, the missing emissions are probably no t significant. This comparison shows that the use of the EIIP emission factor probably provides order of magnitude emission estimates of industrial refrigeration losses.

Table 1. SIC Codes Associated with Ammonia (NH 3 ) Refrigeration Facilities

SIC Code Description NAICS Code
2011 Meat Packing Plants 311611
2013 Sausages/Other Prepared Meats 311612, 311613
2015 Poultry Slaughtering/Processing a 311615
2021-2026 Dairy Products 311512-311514, 31152
2032-2038 Dried, Canned, Frozen Fruits /Vegetables 311411, 311412, 311421-311423
2051-2053 Bread and Bakery Product Mfg. 31181 2064, 2066 Chocolate and Confectionery Mfg. 31132, 31133
2082-2086 Malt Beverages, Wines, Liquors, Soft Drinks 31211-31213
2091-2092 Canned, Fresh or Frozen Seafood 31171
2097 Ice Manufacturing 312113
2099 Food Preparations, not elsewhere classified 311991, 311999
2821 Plastics Material and Resin Mfg. 325211 4222, 4226 Refrigerated Warehousing & Storage 49312
514x Various Food Wholesalers 4224, 311612
518x Various Beverage Wholesalers 42281,42282

a Sometimes listed under 1123xx “Poultry & Egg Production”.

Pechan also submitted a spreadsheet with the “poi nt-source” data from the facility database
described above. There were no instances where th e total county-level estimate from the facility database was more than the employment-based es timate. State-level results are provided in Section E.

3 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004



### C. 2002 CEMENT PLANT EMISSION ESTIMATES

Pechan contacted Garth Hawkins of the Port land Cement Association (PCA) to request throughput data for cement production facilities. PCA did not have any facility level data on clinker throughput. Therefore, Mr . Hawkins sent an email to PC A member facilities requesting that they provide this information to Pechan dire ctly. Pechan did not re ceive any responses from facilities, and because Mr. Hawkins did not feel comfortable releasing member contact information, Pechan was unable to contact facili ties directly.

Since the attempt to collect activity data from facilities was not successful, Pechan turned to other sources of data. Actual 2002 throughput da ta for facilities in Maryland and New York were obtained from state agency contacts (Lang, 2004; King, 2004; Mancilla, 2004). For facilities in Pennsylvania and Ma ine, emissions were estimated using 2001 kiln clinker capacity, obtained from the PCA (Hawkins, 2003a).

An NH 3 emission factor of 0.145 lb/ton clinker base d on data obtained from the PCA (Hawkins, 2003b) was used to estimate emissions for all pl ants, including the Glens Falls plant in NY. Based on comments from NYDEC, Pechan did not use an emission factor based on a source test conducted at this facility (Weston, 2001). From th e source test, the emission factor for this plant
was estimated to be 1.31 lb NH 3 /ton clinker produced.

The emission factor based on PCA data will be the emission factor used in the EIIP guidance document being finalized by Pechan (Pechan, 2003b). (Please see the new EIIP guidance document (scheduled to be finalized April 2004) for a discussion on emissions uncertainties and for recommendations to improve em ission factors from cement plan ts). This average emission factor (0.145lb/ton clinker) is not specific to kiln type (e.g., wet versus dry). Discussions with PCA indicate that the biggest driver in the magnitude of NH 3 emissions is the reduced nitrogen
content of the raw materials fed to the kiln. The composition of these raw materials can vary considerably from site to site. As a resu lt, the minimum, average, and maximum emission factors based on the PCA data vary over thr ee orders of magnitude (0.002 to 1.29 lb NH 3 /ton clinker). The average emission factor was applied to all of the kilns in the RPO. Results are provided in Section E of this memorandum. The data provided from PCA is included in the Appendix.



### D. 2002 NH 3 

### EMISSIONS INVENT ORY FOR POTWs AND
COMPOSTING SOURCES IN THE MANE-VU REGION

1. Publicly-Owned Treatment Works (POTWs)

Pechan collected biosolids generation, wastewater flow rate, and other associated data from the EPA Office of Wastewater Ma nagement (OWM; EPA, 2003b), Envirofacts (EPA, 2003c), BioCycle (2000), the New England Biosolids & Resi duals Association (NEBRA, 2003), and the States of New Jersey (Pilawski, 2003) and Delaware (Fees, 2003).

4 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

OWM conducted the Year 2000 Clean Watersheds Needs Survey (CWNS), which was a joint effort between States and EPA, in response to Section 205(a) and 516 of the Clean Water Act. The CWNS has information on publicly-owned wast ewater collection and treatment facilities, facilities for control of sanitary sewer overflo ws (SSOs), combined sewer overflows (CSOs), storm water control activities, nonpoint sources, and programs de signed to protect the nation's estuaries. Information obtained from the survey is maintained in the CWNS database. The collected data are used to pr oduce a Report to Congress, which provides an estimate of clean water needs for the United States.

The CWNS 2000 Survey database was augmented w ith statewide biosolids generation data from sources including NEBRA (2003), BioCycle (2000), New Jersey (Pilawski, 2003) and Delaware (Fees, 2003). Facility geographic coordinates (latitude and longitude) were collected from the CWNS 2000 Survey (Harcum, 2003) and Envirofacts (EPA, 2003c).

The contents of databases used by Pechan were as follows:

• CWNS 2000 Survey – Individual facility number, facility name, state, county, watershed, municipal and industrial flows, and geographic coordinates (latitude and longitude). This survey contributes most of the data in th e MANE-VU database and is supplemented with the following data;

• Envirofacts – Multiple environmental databases fo r facility information, including toxic chemical releases, water discharge permit co mpliance, latitude and longitude, hazardous waste handling processes, Superfund status, and air emission estimates;

• State of New Jersey – Individual facility number, fac ility name, county, existing flow, biosolids generation, and breakdown of: incine ration and landfill, out of state disposal, composting, and farmland beneficial uses. This data set is newer than CWNS 2000 Survey, and therefore replaced all CWNS data for New Jersey (NJ);

• State of Delaware – Individual facility number, faci lity name, county, existing flow, and farmland beneficial use. The updated flow rates substituted those provided in CWNS 2000 Survey;

• BioCycle – Year 2000 statewide biosolids gene ration, breakdown of land application, composting, lime stabilization, heat drying- pelletization, landfilli ng, incineration, surface disposal, lagoon storag e and other; and

• NEBRA – Biosolids generation of six New Engl and states in 2000, breakdown of land application, compost, landfilling, and incinerati on disposal. This data set replaced six New England states biosolids production da ta reported in the CWNS 2000 Survey.

For POTWs, Pechan developed emission estimates for wastewater treatmen t processes, biosolids processes at POTWs, and biosolid s management practices (mainly at an off-site location). The emission factors were taken from draft EIIP gui dance (Pechan, 2003b; estimated to be finalized in April 2004). The following sections descri be the methods for assembling the activity data.

5 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

a. Wastewater Generation

Facility-level wastewater flows were taken from the CWNS 2000 Survey or State-supplied data for NJ and DE.

b. Biosolids Generation

Aggregated statewide biosolids gene ration data were taken from the BioCycle 2000 Survey and NEBRA. In addition, NJ provided detailed facili ty-level biosolids produ ction data (Pilawski, 2003). In order to spatially-allocate NH 3 emissions, facility-level biosolids production was
allocated based on wastewater flows. Bioso lids generation per gallon of wastewater has remained approximately the same from 1988 to 1998 (EPA, 1999). As part of this task, Pechan found a good correlation (R 2 = 0.90) of wastewater flow rates a nd biosolids generation data in all 12 MANE-VU states. The POTWs operating in the United States generate about 0.16 pounds (dry weight basis) of sewage sludge each day fo r every person that the sewage system services (Stehouwer, 1999a). The state of New Jersey estimated 0.2 pounds per capita per day of biosolids production. Therefore, for states ot her than New Jersey in the MANE-VU region, facility-level biosolids production for the year 2000 was allocated based on the facilities’
wastewater flow rates and annual statew ide biosolids production reported in the BioCycle 2000 Survey and NEBRA. Biosolids production is not available for DC. It was estimated based on the wastewater flow from the regres sion equation mentioned previously.

Except for NJ, year 2002 biosolids generation wa s grown from Year 2000 to Year 2002 based on the population for each state. For New Jersey, 2 002 biosolids generation data were available at individual facilities (Pilawski, 2003).

All reported biosolids produc tion data are in units of dry tons per year. Since the available NH 3 emission factor for this sector is in units of pounds per wet ton biosolids, dry biosolids production data were adjusted according to an assumed average solids content of 5 percent (Stehouwer, 1999b).

c. Biosolids Management Practices

For NH 3 emission estimates, biosolids management practices are aggregated into: land application; composting; heat drying- pelletiz ation; landfilling; and incineration. Ammonia emission factors are available for land application and composting (Pechan, 2003b). Landfilling emissions are assumed to be incorporated into the landfill emission fa ctor contained in the upcoming EIIP guidance, and are not included in this inventory (estimates of landfill methane
emissions are needed to estimate landfill NH 3 emissions). For biosolids sent to landfills for use as daily cover, this activity is included in th e land application estimat es. Ammonia emissions
associated with incineration are assumed to be negligible. For heat -drying – pelletization, no emissions data are available. Therefore, Pech an developed emission estimates for two biosolids management practices: land application and composting.

6 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

Table 2 lists the fraction of bi osolids applied to land includin g farm land application, lime stabilization, surface disposal, lagoon storage and “other” land application as summarized in the BioCycle Year 2000 Survey, NEBRA, and New Jersey reports.

New Jersey provided facility-level biosolids production and management methods, which are categorized somewhat differen tly from those listed in the BioCycle Year 2000 Survey. Land application fractions of biosolids were estima ted by summing a portion of the beneficial use, disposal, and other categories. Incineration, beneficial use Class A (composting), and landfill
cover biosolids were not included in this estimate.

Table 2. Fraction of Biosolids Applied to Land

State Fraction Applied to Land
Connecticut 0.00

Delaware 0.98

Maine 0.31 Maryland 0.80
Massachusetts 0.61 New Hampshire 0.11

New Jersey fa cility-specific a

New York 0.52 District of Columbia 1.00 b

Rhode Island 0.00 Pennsylvania 0.55
Vermont 0.26

a Individual facility reported values used.

b 96% is land-applied to crop lands in Virginia and 4% to crop lands in MD.

Biosolids management activity was allocated to th e county in which each POTW is located. This is an area requiring further study, since biosolid s may be landfilled, composted, or land applied in different counties or states. The only inst ance where this allocation method changed was for DC-generated biosolids. Information from the District of Columbia Water and Sewer Authority (DCWASA, 2004) indicated that bi osolids were land applied mainly to crop lands in Virginia and Maryland. DCWASA provided es timates that 96% of the biosol ids were applied to Virginia crop lands with the remainder going to MD cropla nds. Pechan assumed that the counties in MD were those six MD counties surrounding DC. Th e fraction of biosolids applied to each MD county were derived based on harvested acreag e in the 1997 Census of Agriculture (NASS, 2004). The fractions are as follo ws: Charles – 0.17; Prince Georges – 0.14; Calvert – 0.09; Anne Arundel – 0.12; Howard – 0.16; and Montgomery – 0.32.

Facility geographic coordinate s (latitudes and longitudes) were acquired from the CWNS 2000 Survey and EPA Envirofacts (EPA, 2003c). For those facilities that did not have geographic coordinates, geocoded latitude s and longitudes were estimate d based on the county centroids
where the facilities were locate d. The facility identification numbers (ID) used by Pechan are consistent with the CWNS 2000 Survey, except for Delaware and New Jersey where National Pollutant Discharge Elimination System (NPDES) numbers were provided and used.

7 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

d. Estimates of NH 3 Emissions from POTWs

Ammonia emissions from POTWs we re assigned to the three sour ce classification codes (SCCs)
as shown in Table 3 below. The emission factors used to estimate emissions were taken from the draft EIIP guidance (Pechan, 2003b). These emission factors are not expected to change in the final version of the guidance. The water trea tment emission factor reflects recent testing in southern California that showed much lower NH 3 emission levels than had previous been used (e.g. previous EPA guidance). For water treatment, mu ch of this difference is due to the fact that typical POTWs operate at a pH that does not favor ammonia emissions (e.g. less than 8).

Table 3. Ammonia (NH 3 ) Emission Factors for POTWs

SCC Description EF (lb/SCC unit) SCC Units EF Rating 2630020010 Waste Disposal, Treatment and Recovery; Wastewater Treatment; Public Owned; Wastewater Treatment Processes Total 0.027 10 6 gallons D; range is 0.004 to 0.051.

2630020020 Waste Disposal, Treatment and Recovery; Wastewater Treatment; Public Owned; Biosolids Processes Total 0.142 10 6 gallons D; estimated range is 0.10 to 0.57.

2630050000 Waste Disposal, Treatment and Recovery; Wastewater Treatment; Public Owned; Land Application - Digested Sludge 0.109 ton wet digested biosolids E; no data available to estimate the EF
range.

2. Composting

Composting refers to the use of both aerobic and anaerobic microbial processes to degrade waste materials for beneficial reuse. Compostable wa stes include biosolids (sewage sludge), manure, green waste (e.g., landscape trimmings, grass cli ppings), and other biodegradable materials. Pechan has searched/contacted EPA, state agencies, BioCycle , and the internet for composting information. Of all the sources, BioCycle provided the most complete and detailed information.

For municipal solid waste (MSW) composting, BioCycle surveyed Year 2000 statewide MSW production activities ( BioCycle , 2001). The survey included que stions on the fraction of MSW recycled, including the amount composted. While r ecycle rates were reported by all states, only 20 states responded to composting. The tonnage of MSW composted was calculated based on reported solid waste production a nd composting fractions. For thos e states that did not report a composting fraction, an average of all reported 20 state fractions was assumed. This average MSW composting fraction (5.3%) is very clos e to the one reported (5.4%) by EPA (1998). However, using the average fraction of MSW composted, the estimates for DC, Maine and Pennsylvania exceeded the total amount of recycled MSW reported by these states. Therefore,

8 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

for these states, the recycled yard trimmings quan tities were used to re present total composting activity.

An NH 3 emission factor of 2.81 lb/ton of mixed wa ste composted was applied to estimate NH 3 emissions (see Table 4). This emission factor was derived from SCAQMD test data of a 50:50 mixture by weight of biosolids and green wast e (Pechan, 2003b). Pechan believes that this emission factor represents the best match to th e available data. The EIIP guidance will also
contain a set of emission factor s strictly for green waste (e.g., yard trimmings); however these emission factors should only be applied to green waste composting facilities. This is because
NH 3 emissions are much lower and VOC estimates are higher during gree n waste composting as shown in Table 4 (due to a much lower nitrogen content of the waste compared to mixed waste composting). Green waste composting facilitie s exist in the MANE-VU states; however, the BioCycle data did not report throughput data for th ese facilities. The only place where Pechan applied a different composting emission f actor was for DC. Information from Biocycle and DCWASA indicated that only green waste was composted. Theref ore, the emission factors for green waste were used to estimate emissions fo r DC (the SCC associated with green waste composting was also used for reporting DC emissions).

For biosolids composting, the BioCycle biosolids composting survey for 1998 ( BioCycle , 1999) has more complete data than the 1999 survey pu blished in the November 2000 issue. The survey conducted in 1999 had only one third of the operating facilities returning ques tionnaires. In total, there were 115 biosolids composting fac ilities identified in MANE-VU region. The BioCycle
data does not describe whether biosolids were mixed or partially mixed with other wastes. Therefore, 100% biosolids composting was assumed, and the emission factor of 3.28 lb NH 3 /wet ton was applied (see Table 4). Solids conten t was assumed to be 10% when adjusting dry
biosolids to the moisture cont ent of composted biosolids ( BioCycle, 2000). A few facilities reported biosolids in units of cubic yards. For these facilities, a biosol ids density of 1000 wet lb/cubic yard was applied to convert biosolid s volume into mass (EPA, 1993). Table 4 provides the SCCs and emission factors for composting op erations (Pechan, 2003b). The emission factor for green waste composting is provided for information only (no data specific to green waste composting in the MANE-VU region was identified).

Table 4. Emission Factors for Composting Operations

Emission Factor (lb/SCC unit) SCC Description NH 3 VOC SCC Units
2680001000 Waste Disposal, Treatment and Recovery; Composting; Biosolids, All Processes 3.28 1.70 ton

2680002000 Waste Disposal, Treatment and Recovery; Composting; Mixed Waste, All Processes 2.81 3.12 ton

2680003000 Waste Disposal, Treatment and Recovery; Composting; Green Waste, All Processes 0.82 3.76 ton

9 Ammonia Emissions Inventory for Miscellaneous Sources - FINALPECHAN March 31, 2004

The state-level composting activity data were grown from 1998 to 2002 using population data. The 2002 state-level compos ting activity was then allocated to the county-level using population data. As specified in the work plan, P echan developed emission estimates for both NH 3 and VOC for composting.



### E. RESULTS

Table 5 provides a summary of 2002 NH 3 emission estimates developed during this project. Table 6 provides facility-level emission estimat es for cement plants in the MANE-VU region. Also, as specified in the work plan, Pechan developed VOC emission estimates for composting processes. These are provided in Table 7.

Figures 1 through 3 are county-level emission de nsity maps showing th e distribution of RPO emissions for industrial refrigeration losses, POTWs and biosolids management, and composting, respectively.

Figures 4 and 5 are pie charts showing NH 3 emission estimates for the entire RPO and the New York City metropolitan (NYC metro) area, respec tively. For the purposes of this analysis, the NYC metro area is comprised of six New York and four New Jersey counties (Bronx, Kings, Nassau, New York, Queens, Richmond, Bergen, E ssex, Hudson, and Union counties). Also, the emission estimates underlying these figures are take n from a variety of sources and are not based on a rigorous analysis of the emissions data. The area source data, including the estimates from this project, are for the year 2002 (Pechan, 2004). Point, nonroad, and onroad emissions data are taken from the 1999 NEI (EPA, 2003).

What these two charts show is a significant change in source contribution between large regional areas (e.g., RPO to national levels) and urban areas. At regional le vels, primary contributors are from the agricultural sector, although onroad s ources are also significan t contributors at the regional level (see Figure 4). As shown in Figur e 5, most of the primary contributors at the urban scale are relatively unimpor tant at the regional to nationa l level. The onroad sector dominates in the NYC metro area and other source sectors become more si gnificant contributors. This has important implications for understa nding fine PM formation in urban areas.

Regarding cement plants, while these sources also do not appear to be la rge contributors at the regional level, they can be signi ficant point sources of emissions. Depending on their proximity to Class I areas, cement plants could be important contributors to regional haze in these areas.

10 Ammonia Emissions Inventory for Miscellaneous Sources - FINAL11Table 5. Summary of 2002 Ammonia (NH3) Emission EstimatesEmissions (tons/year)aSCCDescriptionCTDCDEMAMDMENHNJNYPARIVTRPO2399010000Industrial Processes;IndustrialRefrigeration; RefrigerantLosses;All Processes3714620.1756524241124105118171629921146,785305006xx305007xxIndustrial Processes;MineralProducts; CementManufacturing; Kilns0.00.00.00.015731.30.00.02524280.00.08682630020010Waste Disposal,Treatment and Recovery;Wastewater Treatment;Public Owned;Wastewater TreatmentProcesses Total1.91.70.53.92.30.70.44.939.17.40.70.263.72630020020Waste Disposal,Treatment and Recovery;Wastewater Treatment;Public Owned;Biosolids Processes Total10.28.72.420.612.33.62.325.620538.83.51.13342630050000Waste Disposal,Treatment and Recovery;Wastewater Treatment;Public Owned; LandApplication – DigestedSludge0.00.023.117913811.72.21072061840.02.48522680001000Waste Disposal,Treatment and Recovery;Composting; Biosolids, AllProcesses2050.04.646865524714962735071210623.63,5472680002000Waste Disposal,Treatment and Recovery;Composting; Mixed Waste,All Processes2480.83b163128992498.231.7710236560713725.06,599Totals83657.22142,7162,4126343102,5265,2343,60633916619,049aTotals do not always add exactly due to rounding.bReported under SCC 2680003000 (green waste composting).12Table 6. 2002 Cement Kiln EmissionsFacilityKilnTypeStateClinker(ton/yr)EF(lb/tonclinker)2002Emissions(tons)SourceLehigh Portland CementpreheaterMD1,291,6280.14593.6Steve Lang, MDEIndependent Cement/St. Lawrencelong dryMD569,9930.14541.3Duane King, MDEEssroc Cement Corplong wetMD308,0000.14522.3Duane King, MDEDragon Products CompanywetME432,1800.14531.3Garth Hawkins, PCA (2001 capacity)Norlite CorpdryNY240,9420.14517.5Carlos Mancilla, NYSDECNortheast Solite CorporationdryNY241,9960.14517.5Carlos Mancilla, NYSDECGlens Falls Lehigh Cement CompanypreheaterNY563,6180.14540.9Carlos Mancilla, NYSDECSt Lawrence Cement CompanywetNY622,0910.14545.1Carlos Mancilla, NYSDECGlens Falls Lehigh Cement CompanywetNY81,4720.1455.9Carlos Mancilla, NYSDECLafarge North America Inc.wetNY1,727,2410.145125Carlos Mancilla, NYSDECAllentown Cement Co /EvansvilledryPA853,3350.14561.9Garth Hawkins, PCA (2001 capacity)Essroc/BessemerwetPA621,8100.14545.1Garth Hawkins, PCA (2001 capacity)Cemex Inc/Wampum Cement PltdryPA837,9000.14560.8Garth Hawkins, PCA (2001 capacity)Lafarge Corp/Whitehall PltpreheaterPA793,8000.14557.6Garth Hawkins, PCA (2001 capacity)Essroc/Nazareth Lower Cement PltpreheaterPA1,230,3900.14589.2Garth Hawkins, PCA (2001 capacity)Essroc/Nazareth Cement Pltlong dryPA572,1980.14541.5Garth Hawkins, PCA (2001 capacity)Hercules Cement Co/StockertownpreheaterPA999,9680.14572.5Garth Hawkins, PCA (2001 capacity)Totals11,988,56286913Table 7. Summary of2002 VOC Emission EstimatesEmissions (tons/year)SCCDescriptionCTDCDEMAMDMENHNJNYPARIVTRPO2680010000Waste Disposal,Treatment andRecovery; Composting;Biosolids, All Processes1060.02.424333912877.432518136955121,8382680020000Waste Disposal,Treatment andRecovery; Composting;Mixed Waste, AllProcesses2753.8a1811432102511035.2788262667415227.87,330Totals3813.8183.41,6751,364238112.61,1132,8071,04320739.89,168aReported under SCC 2680030000 (green waste composting).14Figure 1. MANE-VU RPO 2002 NH3 EmissionsIndustrial Refrigeration<10.0 (tons/yr)10.0 - 36.0 (tons/yr)36.0 - 90.0 (tons/yr)90.0 - 210.3 (tons/yr)Feb. 26, 2004Prepared by M. MaE.H. Pechan & Associates Inc.6245 Pleasant Valley RoadEl Dorado, CA 9562315Figure 2. MANE-VU RPO 2002 NH3 EmissionsPOTWs and Biosolids Management<1.0 (tons/yr)1.0 - 10.0 (tons/yr)10.0 - 50.0 (tons/yr)50.0 - 320 (tons/yr)Feb. 26, 2004Prepared by M. MaE.H. Pechan & Associates Inc.6245 Pleasant Valley RoadEl Dorado, CA 9562316Figure 3. MANE-VU RPO 2002 NH3 EmissionsComposting<5.0 (tons/yr)5.0 - 10.0 (tons/yr)10.0 - 60.0 (tons/yr)60.0 - 403.1 (tons/yr)Feb. 26, 2004Prepared by M. MaE.H. Pechan & Associates Inc.6245 Pleasant Valley RoadEl Dorado, CA 95623PECHAN March 31, 2004

Figure 4. MANE-VU RPO NH 3 Emission Contributors

Livestock

53.3%

Ag Fertilizer
10.5% Domestic

1.5% Cement Kilns
0.3% Other
1.6% Landfills

7.4% Composting
3.5% Industrial

2.5%

Ind. Refrigeration
2.4%

Onroad
16.7%

POTWs/Biosolids Mgmt.
0.4%

Note: “Domestic” includes human perspiration and respiration, cigarette smoke, household NH 3 use. “Other Point” includes nonindustrial point sources. It is not clear the degree of over lap between the point source inventory and industrial refrigeratio n emission estimates. “Other” includes: nonroad mobile, commercial and residential fuel combustion, forest fires and prescribed burning, storage and transport, incinerati on, and industrial waste water treatment.

17 Technical Memorandum: MANE-VU 2002 Ammonia Emissions Inventory for

Miscellaneous Sources - FINALPECHAN March 31, 2004

Figure 5. NYC Metro Area NH 3 Contributors

Industrial Point
0.7% Composting
11.0% POTWs/ Biosolids Mgmt.
2.8% Landfills
0.0% Other Point

11.0%

Domestic
22.9%

Onroad Mobile
40.0% Ind. Refrigeration
7.6% Livestock
0.8% Ag. Fertilizer
3.2%

Note: “Domestic” includes human perspiration and respiration, cigarette smoke, household NH 3 use. “Other Point” includes nonindustrial point sources. It is not clear the degree of over lap between the point source inventory and industrial refrigeratio n emission estimates. “Other” includes: nonroad mobile, commercial and residential fuel combustion, forest fires and prescribed burning, storage and transport, incineration, and industrial waste water treatment. Data were not identified to estimate NH 3 emission estimates from NYC metro area landfills (e.g., Fresh Kills).

18 Technical Memorandum: MANE-VU 2002 Ammonia Emissions Inventory for

Miscellaneous Sources - FINALPECHAN March 31, 2004



### E. REFERENCES

BioCycle , 1999. “Biosolids Composti ng in the United States” , BioCycle, January 1999.

BioCycle , 2000. “2000 BioCycle National Survey – Solid Waste Composting Trends in the U.S.”, BioCycle , November 2000.

BioCycle , 2001, “13th Annual BioCycle Nationwide survey - The State of Garbage in America”, BioCycle, December 2001.

BOC 2003. County Business Patterns 2001, U.S. Bureau of Census, 2003.

Chitjian et al., 2000. M. Chitjian, J. Koizumi, C. Botsford, G. Mansell, and E. Winegar, 1997 Gridded Ammonia Emission Inventory Update for the South Coast Air Basin , prepared for the South Coast Air Quality Management District. June 2000.

DCWASA, 2004. Biosolids Management Program – Blue Plains Advanced Wastewater
Treatment Plant , District of Columbia Water a nd Sewer Authority, downloaded from http://www.dcwasa.com/educa tion/biosolids_brochure.pdf , February 2004.

EPA, 1993. Markets for Compost , U.S. EPA, EPA/530-SW-90-073A.

EPA, 1998, Characterization of Municipal So lid Waste in the United States , U.S. EPA, EPA
530-R-98-007.

EPA, 1999. Biosolids Generation, Use, and Di sposal in the United States , EPA 530-R-99-009, September 1999.

EPA, 2003a. RMP National Database, Version 2. 1 (Excludes Offsite Consequence Analysis Data), U.S. EPA, Chemical Emergency Pr eparedness and Prevention Office, October
2003.

EPA, 2003b. Clean Watersheds Needs Survey 2000 , U.S. EPA, Office of Wastewater Management, downloaded from http://cfpub.epa.gov/cwns/ , accessed December 2003.

EPA, 2003c. Envirofacts Data Warehouse , U.S. EPA, http://www.epa.gov/enviro/html/ef_overview.html , accessed December 2003.

EPA 2003. 1999 NEI Version 3. U.S. EPA, Office of Air Quality Planning and Standards. http://www.epa.gov/ttn/chie f/net/1999inventory.html , 2003.

Fees, 2004. D. Fees, Delaware Department of Natural Resources and Environmental Control, personal communications with S. Roe, E.H. Pechan & Associates, Inc, January and March 2004.

19 Technical Memorandum: MANE-VU 2002 Ammonia Emissions Inventory for

Miscellaneous Sources - FINALPECHAN March 31, 2004

Fees, 2003. D. Fees, Delaware Department of Natural Resources and Environmental Control, personal communication with Y. Hsu, E.H. Pechan & Associates, Inc, December 2003.

Harcum, 2003. J. Harcum, Tetra Tech Inc., personal communication with Y. Hsu, E.H. Pechan & Associates, Inc, December 2003.

Hawkins, 2003a. Garth Hawkins, Portland Ceme nt Association, 2001 kiln capacity personal communication with Cristina Mackay, E.H. Pechan & Associates, December 2004.

Hawkins, 2003b. Garth Hawkins, Portland Ceme nt Association, ammonia emission factors, personal communication with S. Roe, E.H. Pechan & Associates, Inc., October 2004.

King, 2004. Duane King, Maryland Department of the Environment, 2002 clinker throughput, personal communication with Ho lly Lindquist, E.H. Pechan & Associates, January 2004.

Lang, 2004. Steve Lang, Maryland Department of the Environment, 2002 clinker throughput, personal communication with Ho lly Lindquist, E.H. Pechan & Associates, January 2004.

Mancilla, 2004. Carlos Mancilla, New York Stat e Department of Environmental Conservation, 2002 clinker throughput, personal communication with Holly Lindquist, E.H. Pechan & Associates, January 2004.

NASS, 2004. 1997 Census of Agriculture , U.S. Department of Agriculture, National Agricultural Statistics Service, http://www.nass.usda.gov/census/ , accessed February
2004.

NEBRA, 2003. New England Bios olids & Residuals Association, http://www.nebiosolids.org/savingsoil.html , accessed December 2003.

Papalski, 2004. R. Papalski, New Jersey Depa rtment of Environmental Protection, personal communication with H. Lindquist, E.H. Pechan & Associates, Inc., January 2004.

Pechan, 2004. Documentation for the 2002 Nonpoint Sour ce National Emission Inventory for Criteria and Hazardous Air Pollutants , prepared for the U.S. EPA, Office of Air Quality Planning and Standards, Emissions, Monitori ng and Analysis Divi sion, Emission Factor and Inventory Group, prepared by E.H. P echan & Associates, Inc., February 2004.

Pechan, 2003a. Work Plan for Preparation of a 2 002 Ammonia Emissions Inventory for Selected Source Categories for the Mid-Atlant ic/Northeast Visibility Union (MANE-VU)

, prepared for the Mid-Atlantic Regional Ai r Management Association, prepared by E.H. Pechan & Associates, Inc., August 29, 2003.

Pechan, 2003b. Estimating Ammonia Emissions from An thropogenic Sources – Draft Report, prepared for the U.S. EPA, Emission Invent ory Improvement Program, prepared by E.H. Pechan & Associates, Inc., September 2003

.

20 Technical Memorandum: MANE-VU 2002 Ammonia Emissions Inventory for

Miscellaneous Sources - FINALPECHAN March 31, 2004

Pilawski, 2003. A. Pilawski, New Jersey Depa rtment of Environmental Protection, personal communication with Y. Hsu, E.H. Pechan & Associates, Inc., December 2003.

Stehouwer, R. 1999a. Stehouwer, R., What is sewage sludge and what can be done with it?, http://www.agronomy.psu.edu/Extension/Facts/WhatIs.pdf , accessed December 17,
2003.

Stehouwer, R. 1999b. R. Stehouwer, Use of Biosolids in Crop Production, http://www.agronomy.psu.edu/Extension/Facts/Use%20of%20Biosolids.pdf , accessed December 17, 2003.

Weston, 2001. Stack Test Report Glens Falls Lehigh Ce ment, Glens Falls, New York, Cement Kiln/Raw Mill System Emission Test Report , prepared by Roy F. Weston, Inc. and Environmental Quality Management Inc., December 2001.

21 Technical Memorandum: MANE-VU 2002 Ammonia Emissions Inventory for

Miscellaneous Sources - FINALPECHAN March 31, 2004

Appendix A. Supporting Documentation

22 Technical Memorandum: MANE-VU 2002 Ammonia Emissions Inventory for

Miscellaneous Sources - FINALPECHAN March 31, 2004

23 Technical Memorandum: MANE-VU 2002 Ammonia Emissions Inventory for

Miscellaneous Sources - FINAL

# Attachment B3

BY 2002 Emissions Inventory Document for Maryland (Maryland Department of the Environment)

## M ARYLAND 

## D EPARTMENT OF THE 

## E NVIRONMENT



## A IR AND 

## R ADIATION 

## M ANAGEMENT 

## A DMINISTRATIONState Implementation Plan



# 2002 Base Year State Implementation Plan

Emissions Inventory and Methodologies for
PM 2.5 

# and Precursors

Prepared for:

U.S. Environmental Protection Agency

Prepared By:

Maryland Department of the Environment

### Maryland Department of the Environment 2002 Base Year State Implementation Plan Emissions Inventory and Methodologies for PM 2.5 

### and Precursors

© Maryland Department of the Environment Air and Radiation Management Administration 1800 Washington Boulevard, Suite 730 Baltimore, Maryland 21230 Phone 410.537.3240 • Fax 410.631.3202

# Table of Contents

1.0 INTRODUCTION ........................................................................................................................5

1.1 OVERVIEW AND BACKGROUND ............................................................................................5

1.2 GEOGRAPHIC AREA...................................................................................................................6 1.2.1 PARTICULATE MATTER NONATTAINMENT AREA(S)...................................................... 6

1.3 TEMPORAL RESOLUTION.........................................................................................................7

1.4 QUALITY ASSURANCE POLICY AND OBJECTIVES.............................................................8

1.5 PLAN INFORMATION SOURCES ..............................................................................................8

1.6 INVENTORY DEVELOPMENT AND QUALITY CONTROL PROCEDURES........................9

1.7 ESTIMATION METHODS AND DATA GATHERING ..............................................................9
1.7.1 COMBINED APPROACH FOR O 3 , PM 10 and CO BASE YEAR EMISSIONS ........................ 9

1.8 MISSING DATA..........................................................................................................................10

1.9 APPLICATION OF RULE EFFECTIVE AND RULE PENETRATION....................................10

1.10 CORRECTIVE ACTION .............................................................................................................10

2.0 POINT SOURCES.................................................................................................................. ....11

2.1 INTRODUCTION............................................................................................................... .........11

2.2 COMPILING THE POINT SOURCE LIST.................................................................................11
2.2.1 EMISSION CALCULATIONS................................................................................................... 1 2 2.2.1.1 Seasonal Adjustments................................................................................................... ............13
2.2.2 CONSOLIDATED EMISSIONS REPORTING RULE (CERR) ............................................... 13

3.0 QUASI - POINT SOURCES......................................................................................................14

3.1 INTRODUCTION............................................................................................................... .........14

3.2 ABERDEEN PROVING GROUNDS ..........................................................................................14

3.3 ANDREWS AIR FORCE BASE..................................................................................................21

3.4 BALTIMORE-WASHINGTON INTERNATIONAL AIRPORT (BWI)....................................26

4.0 AREAS SOURCES.................................................................................................................. ...30

4.1 EMISSION ESTIMATION METHOD BY CATEGORY ...........................................................30
4.1.1 PETROLEUM DISTRIBUTION LOSSES................................................................................. 30 4.1.1.1 Tank Truck Unloading ................................................................................................... ..........31 4.1.1.2 Stage II Refueling..................................................................................................... ................36 4.1.1.3 Underground Tank Breathing...................................................................................................38 4.1.1.4 Gasoline Tank Trucks in Transit ..............................................................................................41 4.1.1.5 Aircraft Refueling..................................................................................................... ................44 4.1.1.6 Petroleum Vessel Unloading Losses ...................................................................................... ..464.1.1.7 Portable Fuel Containers ..........................................................................................................51
4.1.2 STATIONARY SOURCE SOLVENT APPLICATION ............................................................ 57 4.1.2.1 Dry Cleaners........................................................................................................... ..................57 4.1.2.2 Surface Cleaning (Cold Cleaning Degreasing) ........................................................................57 4.1.2.3 Architectural Surface Coating .......................................................................................... ........61 4.1.2.4 Auto Refinishing ....................................................................................................... ...............68 4.1.2.5 Traffic Markings....................................................................................................... ................71 4.1.2.6 Industrial Surface Coating........................................................................................................75 4.1.2.7 Industrial Adhesives and Sealants............................................................................................81 4.1.2.8 Graphic Arts ........................................................................................................... ..................82 4.1.2.9 Asphalt Paving......................................................................................................... .................86 4.1.2.10 Synthetic Organic Chemical Storage Tanks.........................................................................88 4.1.2.11 Pesticide Application................................................................................................. ...........89 4.1.2.12 Commercial/Consumer Solvent Use ....................................................................................94
4.1.3 BIOPROCESS EMISSIONS SOURCES.................................................................................... 96 4.1.3.1 Bakeries ............................................................................................................... .....................96 4.1.3.2 Breweries.............................................................................................................. ....................99 4.1.3.3 Wineries............................................................................................................... ...................101 4.1.3.4 Distilleries........................................................................................................... ....................102 4.1.4 CATASTROPHIC/ACCID ENTAL RELEASES ..................................................................... 103 4.1.4.1 Oil Spills............................................................................................................. ....................103 4.1.4.2 Leaking Underground Storage Tanks.....................................................................................1 05 4.1.5 SOLID WASTE DISPOSAL, TR EATMENT, AND RECOVERY ......................................... 107 4.1.5.1 On-site Incineration................................................................................................... .............107 4.1.5.2 Publicly Owned Treatment Works (POTWs).........................................................................108 4.1.5.3 Open Burning – Land Clearing Debris...................................................................................110 4.1.5.4 Open Burning – Residential Municipal Solid Waste .............................................................113 4.1.5.5 Open Burning – Residential Yard Waste ...............................................................................119 4.1.5.6 Cremation – Animal and Human........................................................................................... .125 4.1.5.7 Municipal Solid Waste Landfills........................................................................................ ....128
4.1.6 SMALL STATIONARY SOU RCE FOSSIL FUEL USE ........................................................ 132 4.1.6.1 Small Electric Utility Boilers ......................................................................................... ........132 4.1.6.2 Other Fuel Consumption ................................................................................................. .......132 4.1.6.3 Fuel Oil Combustion ..............................................................................................................133 4.1.6.4 Coal Combustion........................................................................................................ ............135 4.1.6.5 Natural Gas Combustion ................................................................................................. .......142 4.1.6.6 Liquified Petroleum Gas Combustion ....................................................................................1 47 4.1.6.7 Wood Combustion........................................................................................................ ..........153
4.1.7 FUGITIVE SOURCES......................................................................................................... ..... 160 4.1.7.1 Residential Construction Activity ...................................................................................... ....160 4.1.7.2 Heavy Construction Activity..................................................................................................164 4.1.7.3 Road Construction Activity............................................................................................. .......167 4.1.7.4 Agricultural Land Preparation................................................................................................170
4.1.7.5 Paved Roads ............................................................................................................ ...............174 4.1.7.6 Unpaved Roads.......................................................................................................... .............178
4.1.8 FIRE SOURCES ............................................................................................................. .......... 179 4.1.8.1 Vehicle Fires.......................................................................................................... .................1794.1.8.2 Forest Fires ........................................................................................................... ..................181 4.1.8.3 Slash/Prescribed Burning ............................................................................................... ........184 4.1.8.4 Agricultural Burning ................................................................................................... ...........186 4.1.8.5 Structure Fires ........................................................................................................ ................186 4.1.8.6 Orchard Heaters........................................................................................................ ..............189
4.1.9 AMMONIA SOURCES .......................................................................................................... .. 190 4.1.9.1 Cows (Milk Cows, Beef Cows, Heifers, and Steers) .............................................................191 4.1.9.2 Hogs and Pigs.........................................................................................................................193 4.1.9.3 Chickens (Pullets, Layers, and Broilers) ............................................................................... .195 4.1.9.4 Sheep .................................................................................................................. ....................197 4.1.9.5 Goats (Angora and Milk)........................................................................................................199
4.1.9.6 Horses................................................................................................................. ....................201 4.1.9.7 Ducks, Geese and Turkeys .....................................................................................................203 4.1.9.8 Agricultural Fertilizer Application .................................................................................... .....205 4.1.9.9 Human Breath and Perspiration.......................................................................................... ....209

5.0 NONROAD SOURCES............................................................................................................211

5.1 NONROAD VEHICLES/ENGINES..........................................................................................211

5.2 NONROAD MODEL .................................................................................................................212 5.2.1 NONROAD Model Equipment ................................................................................................. 2 15

5.3 RAILROADS .................................................................................................................. ...........217

5.4 AIRCRAFT ................................................................................................................... .............222 5.4.1 Commercial Aircraft...................................................................................................... ............ 224 5.4.2 General Aviation ......................................................................................................... .............. 227 5.4.3 Military Aircraft ........................................................................................................ ................ 229

5.5 M ARINE V ESSELS ........................................................................................................................232

6.0 ONROAD MOBILE SOURCES.............................................................................................236

6.1 INTRODUCTION............................................................................................................... .......236

6.2 EMISSION FACTORS ..............................................................................................................238

6.3 VEHICLE MILES TRAVELED ................................................................................................238

6.4 KEY TRAVEL DATA INPUTS.................................................................................................238

6.5 MOBILE INPUT PARAMETERS.............................................................................................242

6.6 OTHER DATA INPUTS ............................................................................................................243

6.7 EMISSION PROCESS OUTPUTS ............................................................................................244

6.8 CONVERSION TO NIF FORMAT............................................................................................245

7.0 BIOGENIC EMISSIONS ........................................................................................................246

7.1 INTRODUCTION............................................................................................................... .......246

8.0 QUALITY ASSURANCE PROCEDURES ...........................................................................2488.1 REALITY CHECK/PEER REVIEW CHECK ...........................................................................248

8.2 SAMPLE CALCULATIONS.....................................................................................................248

8.3 SENSITIVITY ANALYSIS .......................................................................................................249

8.4 STANDARD RANGE CHECKS ...............................................................................................249

8.5 CORRECTIVE ACTION PLAN................................................................................................250

8.6 QUALITY ASSURANCE FINAL REPORT .............................................................................250

9.0 RESPONSIBILITY ................................................................................................................. .251

9.1 U PDATES (P LEASE D ELETE ) ........................................................................................................2525 

## 1.0 INTRODUCTION

1.1 OVERVIEW AND BACKGROUND

The 2002 Base Year State Implementation Plan Emissions Inventory and Methodologies for PM 2.5 and Precursors (Base Year) is being prepared for the pur pose of describing the Scope of Work required to prepare an emission inventory of sulfur dioxide (SO2), nitrogen dioxide (NO2), ammonia (NH3), particulate matter (PM10 and PM2.5), and volatile or ganic compounds (VOC) emi ssions for the State of Maryland. The federal Clean Air Act (CAA), 42 U.S.C.A § 7401 et seq , as amended by the Clean Air Act Amendments of 1990, P.L. 101-549, (referred to hereafter as the Act) requ ires all areas of the nation to attain and maintain compliance with the federal ambien t air quality standards. These federal standards are designed to protect the pub lic health and welfare from these six criteria pollutants. These standards are
referred to as the National Ambien t Air Quality Standards (NAAQS). Areas that meet the NAAQS are referred to as “attainment areas”; those that do not ar e referred to as “nonatta inment areas.” The Base Year will provide an outline for content and organizat ion review of the inventory. The goal of the Base Year is to provide guidance on the development of a reliable inventory, the quality of emissions data collected and provide for acceptable documentation and reporting of this information. The Maryland Department of the Environment Air and Radiat ion Management Administration (MDE-ARMA), the Maryland Department of Transportation (MDOT), and the Metropolitan Washington Council of Government (MWCOG) will be involved in preparing various portions of the inventory by contributing information that is necessary fo r developing emissions estimates.

The final inventory document will include emissions from point sources, mobile sources, biogenic emissions, non-road mobile sources, and area sour ces. MDE-ARMA will use the Non-Road Mobile Emissions Model, NONROAD, for small engine em issions. MDE-ARMA will supply emissions for major point sources and area sources, and will accep t EPA estimates for biogenic emissions. Mobile source emissions will be estimated by a separate MDE-ARMA work plan with MDOT and MDE-ARMA Mobile Sources Control Program (MSCP) as well as the MWCOG.

The applications for emissions inventory data include use of the data in annual trends reports, State Implementation Plans (SIPs), compliance demonstrati ons, emissions trading, em issions fees programs, and in modeling activities designed to evaluate ambient air concentrations encountered by the general public. For the SIP program, the air emission inventory is a fundamental building block in developing an air quality control and maintenance strategy. Section 172, Part C, of the Clean Air Act (CAA) as amended in 1990, which addresses SIP requirements, states that “. . . plan provisions shall include a comprehensive, accurate, current inventory of actual em issions from all sources or the relevant pollutants or pollutants in such area . . .”. Regulatory agencies and industrial f acilities rely on emission inventories on an ongoing basis as indicators of air quality ch anges and for setting permit requirements.

The end use of emission inventories re quires that they be of the highest quality obtainable. They are the foundation of air quality decisions. Inventory quality is cr itical to defining realistic regulations and attainment strategies. Deficiencies and inconsiste ncies in existing compilation processes accentuate the need for developing and implementing more uniform and systematic approaches to collecting and reporting data. One of the primary goals of the Base Year is to improve the qua lity of inventory data
collection so that it is a reliable source of information for sound decision-making.6 1.2 GEOGRAPHIC AREA

The area that will be inventoried in cludes the entire State of Maryland. The area can be divided into the distinct Non-attainment areas (NAA). Categories th at will be inventoried ar e point, mobile, biogenic,
non-road mobile and area sources.

1.2.1 PARTICULATE MATTER NONATTAINMENT AREA(S)

In December of 2004, EPA designated the following particulate matter less than 2.5 microns (PM 2.5 ) nonattainment areas in Maryland:

TABLE 1.1 MARYLAND PM 2.5 CLASSIFICATIONS

AREA CLASSIFICATION ATTAINMENT
DATE (NOVEMBER 15)

BALTIMORE, MD

Anne Arundel County, Baltimore City, Baltimore County, Carroll County, Harford County, Howard County Nonattainment April 5, 2010

WASHINGTON, D.C.

Charles County, Frederick County, Montgomery County, Prince George's County Nonattainment April 5, 2010

BERKELEY, WV

Washington County Nonattainment April 5, 2010

OTHER MARYLAND COUNTIES

Allegany, Calvert, Caroline, Cecil, Dorchester, Kent, Garrett, Queen Anne’s, Some rset, St. Mary's, Talbot, Wicomico, Worcester Unclassifiable (Insufficient data to classify) 1 N/A

1 Areas which are unclassified are not nonattainment areas.7 

### FIGURE 1-2: MARYLAND PM2.5 DESIGNATIONS

1.3 TEMPORAL RESOLUTION

Another step of inventory devel opment is the temporal allocation of emissions. Because air quality modeling attempts to represent the actual physical and chemical processes as th ey occur over a specific duration of time, it is important that the temporal allocation of emissions be as accurate as possible. Temporal allocation can be thought of as an accounti ng of emissions variation over time. The simplest temporal allocation is for a steady-st ate emissions source that continually releases emissions at the same rate all the time. Under actual c onditions, however, steady-state emissi on sources are quite rare. Instead, under actual conditions, emissions sources may operate only in the winter not ope rate on Sundays, or their activity may peak during certain hours of the day.

The planning period for particle matt er is based on annual emissions.8 1.4 QUALITY ASSURANCE POLI CY AND OBJECTIVES

In order to provide data of suffic ient quality for maintenance planning needs, quality assurance (QA) and quality control (QC) procedures are implemented as pa rt of the inventory proce ss. The procedures address data quality objectives of accuracy, completeness, comparability and representativeness. A brief discussion of the data qualit y objectives is given below.

Data quality objectives of accuracy, completeness, co mparability, and representativeness are addressed to ensure an inventory of high quality. The targ et goals for each objective are listed below.

Accuracy: All estimates must be calculated and documented using acceptable methods. Individual source requirements and av ailability of data and resources will affect the estimation method
selection.

Completeness: Completeness is addressed by ensuring that all applicable source catego ries are included in the inventory, and that all informa tion required to estimate emissions is present. Applicable source categories are listed in Appendix A.

Comparability: Data will be compared to the most recent base year inventories: 1990 for PM 10 and 1999 for CO. Any discrepancies (data outliers) greater th an 20% involving sources th at made up greater than 5% of either the 1990 or the 2002 inventories for PM 10 , or the 1999 and 2002 inventories for CO will be corrected or justified.

Representativeness: Actual 2002 annual and seasonal daily emissions will be calculated for the base year inventory. Local data will be used in inventory calcul ations wherever possible.

1.5 PLAN INFORMATION SOURCES

This plan draws upon inventory, quality assurance, a nd emissions projections guidance available from state and federal agencies and partnerships. 2, 3, 4, 5, 6, 7, 8 The effort will also draw upon experience gained with the 1990 Ozone and 1996/1999/ periodic emission i nventory reviews and prior SIP inventory efforts in other areas and for other pollutants.

A primary source of emissions inventory data will be the 2002 Consolidated Emissions

2 PM-10 Emission Inventory Requirements. Final Report. U.S. Environmental Protection Agency, Research Triangle Park, NC, September 1994.

3 Emission Inventory Improvement Program, Volume IV: Qua lity Assurance Procedures. EP A-454/R-97-0041. July 1997.

4 Procedures Document for National Emissions Inventory, Criteria Air Pollutants 1985-1999. United States Environmental Protection Agency. Office of Air Quality Planning and Standa rds. Research Triangle Park NC 27711. EPA-454/R-01-006.
March 2001.

5 Procedures for Preparing Emissions Projections. U.S. Environmental Protection Agency, Research Triangle Park, NC, July
1991

6 Emission Inventory Requirements for Carbon Monoxide State Implementation Plans, EPA-450/4-91-011, March 1991

7 June 4-6, 1991 EPA manual Workshop for Implementation of Clean Air Act Provisions Relating to Ozone and Carbon Monoxide Emission Inventories, June 4-6, 1991 EPA.
8 Guidance for the Preparation of Quality Assurance Plan s for O3/CO SIP Emission Inventories. EPA-450/4-88-023.
December 1988.9 Reporting Rule (CERR) submittal recently submitted to the U.S. EPA by MDE-ARMA. Another source
of information will be EPA’s National Emissions Inventory (NEI). The MD DOT and MDE-ARMAMobile Department will provide base year and project ion year onroad mobile source emissions data and additional activity data to be used in estimating em issions for other source cat egories (paved and unpaved road dust). Finally, information from local sour ces, including Maryland Transportation Authority, Maryland Aviation Authority, Maryland Port Authority, un iversity sources, and agricultural experts will be used to develop emission estimates for select source categories (as de scribed in Chapter 6).

1.6 INVENTORY DEVELOPMENT AND QUALITY CONTROL PROCEDURES

An inventory of actual emissions will be develo ped for base year 2002. Annual and typical VOC, NO X , SO 2 , PM 10 and CO season day emissions estimates will be made. A list of potential VOC, NO X , SO 2 , PM 10 and CO sources was developed using the 1990 ba se year inventory, 1996/1999 periodic emission inventories, local knowledge, categ ories as defined in references , and the 2002 National Emissions Inventory (NEI) for VOC, NO X , SO 2 , PM 10 and CO source categories. The source categories are listed in Appendix A.

The inventory development process consists of severa l steps. A description of each step and the quality control procedures implemented are discussed individually in the following sub-sections:

• Estimation methods and data gathering;

• Emissions calculations and data checking;

• Missing data;

• Application of rule effectiv eness and rule penetration;

• Corrective action; and

• Documentation.

1.7 ESTIMATION METHOD S AND DATA GATHERING

Guidance listed under Plan Information Sources will be utilized to select estimation methods and gather information necessary to develop the inventory. QC activities during data gathering include thorough documentation of methods and data sources, and check ing for reasonableness of data obtained. General
estimation methods and data s ources anticipated for each sour ce category are listed below.

1.7.1 COMBINED APPROACH FOR O 3 , PM 10 and CO BASE YEAR EMISSIONS

This section of the Base Year document is an overview of MD E-ARMA’s proposed approach to preparing the 2002 emission estimates. This is followed by approaches specific to the source categories.

For PM 10 , the top-emitting PM 10 categories are point sources, re sidential wood combustion, open burning, paved and unpaved road fugitive dust. In a ddition, agricultural tilling and other fugitive dust source categories were not quantified in the 1990 Base Year Emissions Inventory. For agricultural tilling, MDE-ARMA will evaluate the potential importance of this activity during the planning period through contacts with local agricultural experts. If little or no agricultu ral tilling occurs within the state during the planning period, no effort will be made to quantify these emissions. For windblown dust, emissions are dominated by sources outside of th e NAA. MDE-ARMA does not intend to estimate
these emissions.10 MDE-ARMA plans to focus most of its CO emissi on inventory and emissions projection effort on the top-emitting source categories in the area. For CO, th e priority source categories are onroad mobile sources, point sources, residen tial wood combustion, open burning, and nonroad engines/vehicles.

1.8 MISSING DATA

Missing data will be identified by the inability to co mplete the calculations. If data are found to be missing, a reasonable effort will be ma de to acquire the data. If this is unsuccessful, estimates will be made based on past years' data or default informa tion contained in EPA documents and models. Sources
of all data will be documented.

1.9 APPLICATION OF RULE EFFECTIVE AND RULE PENETRATION

Rule effectiveness (RE) reflects th e ability of a control device or re gulation to achieve all the emission reductions that could be achieved by full compliance at all times. Rule penetrati on (RP) is a measure of the extent to which a regulation covers emissions fr om a source category. RE/RP has been the subject of ongoing discussion nationally and is the topic of a dr aft report by the Emissions Inventory Improvement Program (EPA/STAPPA/ALAPCO). 9 Briefly, the report reco gnizes that control efficiencies are often based on in-use conditions, and when this is the case, RE has already been taken into account. This is the situation for point sources in th e NAAs. Additionally, some point source emissions are estimated through source testing, and therefore do not use control effici encies and RE/RP to calculate emissions. For area sources, MDE will evaluate each control measure to determine whether EPA default RE and RP estimates (80% and 100%) should be applied or some more representative values.

1.10 CORRECTIVE ACTION

Corrective and follow-up actions identified during the inventory development process will be noted and referred to the appropriate staff. Both the corrective actions identified and resu lts of actions taken in response will be documented and kept on file.

Written documentation specifying inventory methodol ogy and information sources will be provided. Emission summaries will be presented.

9 "Emissions Inventories and Proper Use of Rule Effectiveness." September 23, 1998. Memorandum from EIIP Point Sources Committee Members to EIIP Steering Comm ittee Members. September 23, 1998.11 

## 2.0 POINT SOURCES

2.1 INTRODUCTION

The Maryland Department of the Environment Air and Radiation Management Administration (ARMA) is the lead agency responsible for compiling the point source emissions invent ory, including identification of sources, documenting the method used to calculat e emissions from each source, and presenting the findings. In order to provide EPA with a written documentation of emi ssions calculations for major point sources, confidential information was included in the documentation. It is included with the understanding that EPA is also bound to respect the confidentiality of the information, including appropriate storage of the information. Any contr actors employed by EPA to re view the inventory are also subject to confidentiality provisions, or the EPA must remove the confidential material before submitting the document for review. This information doe s not appear in copies prepared public review.

The Maryland stationary point source inventory is th e result of efforts to ch aracterize air emissions sources since the early 1970's. Th is section describes da ta collection, verificati on and emission estimation methods used to estimate point source emissions from stationary sources. For the 2002 Periodic Emissions Inventory, point sources are defined as stationary commercial or industria l operations that emit more than 10 tons per year of volatile organic compounds (VOC); 100 tons pe r year of carbon monoxide (CO), sulfur oxides (SO
x ), particulate matter with an aerodynami c diameter less than 10 micrometers (PM 10 ), and total suspended particul ates (TSP); or 25 tons per year of oxides of nitrogen (NO
x . In addition, stationary sources included in previous PEI submissions were included herein re gardless of the amount of air pollutants emitted. These emissions criter ia are more commonly referred to as “emissions thresholds” or simply, “thresholds.”

2.2 COMPILING THE POIN T SOURCE LIST

Maryland has a substantial database of both small a nd large air emission sources compiled over the last eighteen years. Since the thirt een central counties of Maryland and Baltimore City have been nonattainment for ozone since before 1982 and 80% of the state's population and major industrial sources lie within these counties, the da tabase of over 10,700 sources (both a bove and below the point source thresholds) is reasonably complete. The list of point sources in this inventor y was developed by applying the appropriate thresholds to the em ission levels in the database to di fferentiate between point and area stationary sources. Sources with emi ssion levels greater than the thresh old or sources previously included in PEI submittals are by definition point sources wh ile sources with emissions levels less than the thresholds are by definition area sources.

Several methods of source identifica tion are used by ARMA to ensure th e point source inventory is as complete as possible. The primary data source is the Permitting Program, which overseas the registration requirements found in Title 26, Subtitle 11, Chapter 02, Code of Maryland Regulations (COMAR). The Compliance Program identifies other point source s though annual facility inspections and through investigations conducted in re sponse to citizen complaints.

The primary means of new source iden tification is the steady influx of permit applications and equipment registrations. Many sources are required by CO MAR 26.11.02, Permits, Approvals and Registration, to register with ARMA. From 700 to 1,000 new sources ar e registered with the Department each year.12 Most of these sources are not cons idered to be point sources as de fined for inventory purposes, even though they require permits. As an example, emissions from some sources can be less than one ton per year. However, all sources that are registered wi th the Department are tracked until the Department receives notification that the equipm ent or emission source has ceased operations. An emissions source or its equipment is not permanently deleted from th e registration database until the installation is
demolished.

The Department has established a Small Business Assi stance Program as required by the Clean Air Act Amendments to acquaint the owners of potential sources with the State’s permitting requirements, including air quality permits. The Department has also published a guidebook, Environmental Regulation: A Business Guide to the Maryland Depa rtment of the Environment's Permitting Process as part of its outreach program.

A secondary means of new source identification are the emission sources identified by Compliance Program staff during annual field inspections of major point sour ces. During these inspections, unregistered equipment is sometimes discovered. St atewide response to the Ai r Pollution Report and the Air Quality Complaint Hotline, has also led to the discovery of previously unidentified emissions sources. Sources discovered in this manner may be the result of the citizen complaints, or the result of further investigation of visual evidence such as buildings, storage yards, visibl e emissions, etc., sighted elsewhere during the response.

2.2.1 EMISSION CALCULATIONS

The ARMA technical staff uses one of the followi ng methodologies to calcul ate criteria pollutant
emissions:

• EPA-supplied emission factors

• EPA-supplied emission models

• Material balances

• Emissions based on source test data

• Agency or company-generated emission factors

The Compliance Program facility insp ectors calculate annual emissions estimates following their annual facility inspections. The results are then entered into ARMA’s Registration Files for Facilities and Equipment, which lists facilities by premise numb ers and equipment by registration numbers under each facility. The emissions, both stack and fugitive, from all registered equipment at a specific facility are summed to yield the annual facility emissions estimate. This total facility estimate is used to determine whether the facility satisfies the criteria for classification of as a point source.

The estimation of emissions on a facility-wide basis can result in emissions from equipment in some subcategories, such as boilers, being obscured. For example, boiler emissions are included in the Amerada Hess Corporation’s total emissions. Ther efore, these boiler emi ssions are included with emissions from gasoline storage and handling operations and included in the Storage, Transportation and Marketing of Petroleum Products and Volatile Organic Liquids source cat egory rather than in External Combustion Sources category.13 Emissions from specific subcategories of sources can be extracted from the inventory to estimate possible
reductions from various control st rategies. However, the emissions from specific equipment subcategories cannot be excluded from the facility -wide emissions because of the limitations of the software used to create the Regist ration File. Therefore, subcategor ies of equipment emissions are not included in the inventory as separa te line items for to do so would re sult in the double counting of those
emissions.

The estimates prepared by the facility inspectors following the annual inspecti on of each facility are compared to the annual emissions reported by each facility in its Annual Em issions Certification. A person who owns or operates a major facility as defined in COMAR 26.11.01.05-1 must submit to the Department an emissions statement by April 1 of each year for the previous calendar year. The owner or operator of the facility must furthe r certify that the emissions statemen t is accurate to the best of the owner/operator’s best knowledge. Af ter the certified emissions statem ents are logged in, they are thoroughly reviewed by the assigned f acility inspectors. Each inspector compares their emissions estimate to that prepared by the respective company for consistency of methodology and final emissions estimate results. The facility inspectors resolve a ny discrepancies between the two estimates with the owner/operator of the facility in qu estion. When all discrepancies are reso lved to the satisfaction of MDE,
the final emissions estimates are then submitted as an update to ARMA’s Regist ration File for Facilities and Equipment.

2.2.1.1 Seasonal Adjustments

ARMA has not collected extensive data on the temporal allocation of emissions. Typically, companies are required to partition annual emissions by calendar quarter. More specific information to allow allocation of emissions to time of day, peak ozon e season, ozone season, or even monthly periods of activity was not collected in 2002. More specific information may be collected in the future.

In cases where the facilities did not provide peak ozone season emission estimates, the peak ozone season emissions were calculated by the following method a nd are included in the emissions summary tables, by county, at the end of this section: 1) Annual emissions in pounds per year were conve rted into pounds per day emissions by dividing annual emissions by operating days, 2) Pounds per day emissions were then mu ltiplied by a seasonality factor, 3) The seasonality factor was based on the quarterly percentage of operations estimated by the company adjusted for June, July, and August. 4) The ratio obtained in Step 3 was multiplied by the da ily emissions calculated in Step 1 to generate the seasonally adjusted emissions.

2.2.2 CONSOLIDATED EMISSIONS REPORTING RULE (CERR)

MDE-ARMA compiled a 2002 point source emission i nventory in order to satisfy EPA reporting requirements under the Consolidated Emissions Repor ting Rule. This will be the primary resource for developing refined estimates of PM 2.5 and NH 3 emissions.14 

## 3.0 QUASI - POINT SOURCES

3.1 INTRODUCTION

The Maryland Department of the Environment Air and Radiation Management has identified several
facilities that due to size and/or function are considered point sources . These establishments contain a wide variety of air emission sources, including traditional point sources, on-road mobile sources, off-road
mobile sources and area sources. Fo r each particular establishment, th e emissions from these sources are totaled under a single point source and summary documents include these “quasi-point” sources as point

sources.

Sample calculations presented below are for illustrative purposes only and may not reflect actual
emissions.

3.2 ABERDEEN PROVING GROUNDS

Aberdeen Proving Ground (APG) occupies more than 72,500 acres in Harford County, Md. Its northernmost point is marked by the confluence of the Susquehanna River and the Chesapeake Bay. On the south the Gunpowder River borders it.
The installation comprises two principal areas, sepa rated by the Bush River. The northern area is known as the Aberdeen Area, and the southern sector, fo rmerly Edgewood Arsenal (established in November, 1917 - as a chemical weapons research, development a nd testing facility), is the Edgewood Area. The two areas were administratively combined in 1971.
Aberdeen Proving Ground is home to 66 tenants and a host of satellite activities. Among the major tenants are the U.S. Research, Development and E ngineering (RDECOM), U.S. Army Ordnance Center and Schools, U.S. Army Developmen tal Test Command, U.S. Army Aber deen Test Center, U.S. Army Center for Health Promotion and Preventive Medici ne, Northeast Region Civilian Personnel Operations Center, U.S. Army Medical Research Institute of Chemical Defense, Program Manager for Chemical Demilitarization and major elements of the Army Research Laboratory.
As a center for Army materiel testin g, laboratory research and military training, the post is a key element in the nation's defense. All tanks and wheeled vehicles which have served U.S. forces for the past 50 years have been tested for performance and durability at APG - from the M4 Sherman tank of World War II to the M1 tank and High Mobility Multipurpose Wheeled Ve hicle and Family of Stryker Vehicles of today.

Known as the "Home of Ordnance," APG has been training Army ordnance pe rsonnel since 1918. The Army's ordnance training was consolidated at the proving ground during Worl d War II, and today the U.S. Army Ordnance Center and School provides mechanical maintenance training for more than 20,000 U.S. and foreign personnel each year. APG is the regimental headquarters for the Army's Chief of
Ordnance.

APG's Edgewood Area has been a center for chemical warfare research and development since it was established. From the trenches of France and Belgium in World War I to the desert battlefields of Iraq nearly 80 years later, the work done at APG has contri buted to the defense and safety of American forces threatened by chemical weapons. Description15 More than 7,500 civilians work at Aberdeen Prov ing Ground, and more than 5,000 military personnel are assigned there. In addition, there are nearly 3,000 contractors and private business employees working on the proving ground.

There are 2,148 military family members living on th e post and another 155 off post. The post supports more than 16,000 military retirees and retiree family members. The post is Harford County's largest employer and one of the largest empl oyers in the state of Maryland.

U.S. Army Garrison, Aberdeen Prov ing Ground, provides general, administ rative and logistical support to the post's tenants and satellite activiti es, and is responsible for the mana gement and operation of the entire installation, which in many wa ys is like a small city.

Environmental stewardship is an es sential component of all activity at APG. The installation and its tenants are actively involved in a wide variety of environmental compliance, pollution prevention, conservation, and restoration programs. In FY 2 004 APG spent a total of $31 million on environmental programs, installation programs and in stallation restoration activities.

VOC, NOx, CO, PM, Toxics

MDE staff reviewed emission estimat es prepared for Aberdeen Proving Grounds by a private contractor. These emission estimates included data for the following source categories:

• Mobile On-Road Source Emissions

o Mobile - LDGV Emissions

o Mobile - LDGT 1&2 Emissions

o Mobile - LDGT 3&4 Emissions

o Mobile - HDGV

o Mobile - LDDT 1-4

o Mobile - HDDV

o Mobile - HDDV Exhaust

o Mobile – HDDB

o Mobile - HD CNG Trucks

o Mobile - LD CNG Trucks

• Mobile Nonroad Source Emissions

o 2-Stroke Gas Eng; Lawn & Ga rden Equip; Other Equipment

o 4-Stroke Gas Eng; Recrea tional Equip; Golf Carts

o 4-Stroke Gas Eng; Recreational E quip; Specialty Vehicles/Carts

o 4-Stroke Gas Eng; Construction & Mining Equip; Off-Highway Trucks

o 4-Stroke Gas Eng; Indus trial Equip; Forklifts

o 4-Stroke Gas Eng; Lawn & Garden Equip; Chain Saws

o 4-Stroke Gas Eng; Lawn & Garden Equip; Leaf blowers/Vacuums

o 4-Stroke Gas Eng; Lawn & Garden E quip; Rear Eng Riding Mowers Pollutants

Emission Source Categories16 o 4-Stroke Gas Eng; Lawn & Ga rden Equip; Front Mowers

o 4-Stroke Gas Eng; Lawn & Garden Equip; Other Lawn & Garden Equip

o 4-Stroke Gas Eng; Commerci al Equip; Generator Sets

o LPG Eng; Construction & Mining Equip; Off-Highway Trucks

o Diesel Eng; Construction & Mining Equip; Rollers

o Diesel Eng; Construction & Mining Equip; Cranes

o Diesel Eng; Construction & Mining Equip; Graders

o Diesel Eng; Construction & Mi ning Equip; Off-highway Trucks

o Diesel Eng; Construction & Mini ng Equip; Tractors/Loaders/Backhoes

o Diesel Eng; Construction & Mini ng Equip; Other Construction Equip

o Diesel Eng; Industria l Equip; Forklifts

o Diesel Eng; Industrial E quip; Sweepers/Scrubbers

o Diesel Eng; Lawn & Gard en Equip; Front Mowers

o Diesel Eng; Agricultural E quip; Agricultural Tractors

o Diesel Eng; Commercial Equip; Generator Sets

o Recreational marine 4-str oke gasoline equipment

o Recreational marine diesel compression ignition equipment

o Aircraft

• Area Source Emissions

o Emissions from aircraft refueling.

o Construction Welding

o Solvent-based architectural surface coatings.

o Water-based architectural surface coatings.

o Cold cleaning solvents.

o Solvent Utilization - Miscellaneous

o Commercial/consumer solvents.

o Open Burning Detonation

o Landf ills - All Categories

o Munitions Detonation

o Firefighting Training

o Industrial Process - Miscellaneous

o Commercial/institutional distillate oil combustion.

o Commercial/institutional natural gas combustion.

• Point Source Emissions

o MDE staff also reviewed and included em ission estimates from emission certification reports prepared by Aberdeen Proving Grounds and submitted on an annual basis to MDE’s Compliance and Enforcement Program. These emission estimates include major

sources.

Emission estimation methodologies varied by source ca tegory. A brief synopsis of the methodologies is presented below. Emission Estimation Methodologies17 Mobile On-Road Source Emissions Information on the privately owned vehicles for APG was estimated from a 2001 traffic study conducted for all gates at both Aberdeen and Edgewood.

Emissions for the on-road vehicles were calcula ted only for the estimated miles and hours of onbase vehicle operation. Miles traveled off the base were not included in the emission calculations. AP-42, Volume 11, Fifth Edition includes the emission factors for NOx, CO, and VOC, which were calculated using EPA's MOBILE 5 model for gasolin e and diesel operated ve hicles. AP-42 has not been updated with NOx, CO, and VOC emission fact ors from the latest version of EPA's MOBILE 6.2.03 model, released in Octobe r 2002, which also includes em ission factors for PM-10, PM-25, S02, and HAPS. Therefore, the emission factors fo r on-road vehicles were obtained by running the MOBILE 6.2.03 model.

APG government-owned vehicles were grouped into vehicle categories accor ding to vehicle type, gross vehicle weight (GVW), and fuel type. The CY 2002 mileage for each vehicle, if available, was provided by each organization, as were estimate s of on-base mileage or a percentage of the total miles per vehicle that were driven on the base . If the mileage data was not available, it was estimated based on mileage for similar types of vehi cles from other organiza tions or from estimates provided by organization personnel.

Emission estimates for privately owned vehicles (POVs) are based on traffic studies for CY 2000 and CY 2001. Each traffic study tracked incoming vehicles at all gates at both Aberdeen and Edgewood over a three-week period. The average number of vehicles coun ted at each gate over both years was used to estimate the number of P OVs entering each day. The average values were 7,680 POVs per day at Aberdeen and 5,277 per day at Edgewood.

POV miles traveled were determined by using the distance from each gate to a central location at both Aberdeen and Edgewood. Each POV that entere d a specific gate was assumed to drive that distance each day. The daily on-base mileage was determined by multiplying the number of POVs by the round-trip distance to a specific gate. The POV vehicles from the traffic study were conservatively estimated to be in th e above-referenced vehicle categories.

Emissions of NOx, CO, VOC, PM-1 0, PM-2.5, and SO2 from daily employee POVs were estimated by multiplying the annual on-base mileage of eac h vehicle category with the emission factors obtained from the MOBILE 6.2.03. Since the model ye ars of POVs traveling on the base would vary greatly, it is impractical to estimate the emissi ons from each vehicle in that model year range. Instead the year 2000 was considered the average vehicle model year , and the emission factors for the 2000 model year vehicles were used. The emissi on factors were used in the following equation
to estimate annual emissions:

1.1.1.1.1.1.1 E = V * F * C

Where:
E = Annual emissions of particular polluta nt from each vehicle category (lb/yr)
V = Vehicle miles traveled on-base per ye ar for each vehicle category (mi/yr)
F = Average model year emission factor in the applicable vehicle category (g/mi)
C = Conversion factor (2.205 

### x 10 lb/g)18 The information on the vehicles tested and miles driven on unpaved test tracks at APG was obtained from 2002 logs for each track. Th e test vehicles we re divided equally into the HDDV and HDGV
vehicle classes.

Mobile Nonroad Mobile Source Emissions

APG gathered information about the number of ve hicles, model year, horsepower rating, fuel type, engine cycle type, and estimated operating hours for CY 2002. In the majority of instances, horsepower ratings and operating hour s were not readily available a nd have been assumed based on the typical horsepower of similar types equipment. If data was not available for CY 2002, then data was obtained for the closest available year.

Criteria pollutant emission f actors were obtained from Air Emissions Inventory Guidance Document for Mobile Sources at Air Force Installations, Un ited States Air Force Institute for Environment, Safety & Occupational Health Risk Analysis (IERA), January 2002, which includes the emission factors used in EPA's NON-ROAD 2002 model. Emi ssion factors to estimate PM-2.5 from PM-10 emissions were obtained from EPA's NON-ROAD 2002a model. The Non-road model incorporates
research results from U.S. EPA 's Non-road Engine and Vehi cle Emission Study (NEVES),
November 1991, as well as from the California Air Resour ces Board's off-road model, test results, and regulatory emission standards. These factors we re used to estimate the emissions from non-road vehicles and equipment.

Emission factors for stationary internal combustion engines were used to es timate criteria pollutant emissions for the non-mobile equipment. These factors are found in Table 3.3-1, AP-42 Section 3.3, Gasoline and Diesel Industrial Engines. Emissions were calculated by multiplying the power output by the emission factors applicable to the type of fuel used by the non-mobile equipment, either gasoline or diesel. The power output was calculate d by multiplying the power of the equipment in horsepower times the estimated hours of operation. Net workdays were derived from the equipment rental records. It was assumed that the light to wers were used 8 hours per day and that all other equipment was used 10 hours per day.

The total emissions for all non-road vehicles a nd equipment were separated into emissions for Aberdeen and Edgewood. In cases were vehicles were used at both Aberdeen and Edgewood the total emissions were divided equally.

Aircraft operations are conducted at Phillips Airfie ld at Aberdeen and Weide Heliport at Edgewood. These operations include landings and takeoffs (LTOs), touch and go's (T&Gs), low approaches (LAs), and trim and power checks (T&Ps). Emi ssions from aircraft operations were estimated using the EDMS (version 4.4) model.

Emissions of criteria pollutants for watercra ft were calculated using factors provided in AP-42,
Volume 11. Inboard emissions were calculated based on fuel consumption or operating time. Outboard emissions were calculat ed using factors related to fuel consumption. Fuel consumption was rarely known, so a generic fuel usage of 3 ga llons per hour was used to calculate consumption from operating time.19 The inventory of watercraft includes APG vessels , privately owned boats, and rental boats. The inventory included the size of vesse ls, whether the boat has an inboa rd or outboard motor, whether the boat uses gasoline or diesel, on-site fuel usage, and on-site estimated usage.

Many assumptions were necessary to calculate emissions from th e limited information known about many of the watercraft. The numbe r of memberships to the privat e boat clubs located at APG and number of permits to launch boats at APG was know n, but no information as to the size and type of boats was, nor the time or distan ce they traveled with in the boundaries of APG. All privately
owned boats launched in the Aber deen Area were considered outsi de of the APG boundary once in the water, so no emissions were counted from th ese boats. For privately owned watercraft it was assumed that 80% have outboard motors and 20% have inboard and that all ar e gasoline fueled. An assumption was made that privately owned watercraft were used 5 times per year and spent 2 hours on site each usage for a total of 10 hours each. For re ntal outboards it was assumed that they were used 3 hours on-site per rental weekend and that there were 40 rentals in 2002.

Area Source Emissions

Emissions from the various area source categorie s were estimated using a variety of methods, including population based, fuel consumption, and mass balance. Emission factors were derived from the EPA document titled 'Emission Inventory Improvement Program', and AP-42. Landfill losses as VOC were calculated fo r Michaelsville landfill using Landfill Gas Emissions Model (LandGEM) version 3.02 available through the EPA. Land GEM is based on a first-order decomposition rate equation for quantifying emi ssions from the decomposition of waste in municipal solid waste landfills. Activity

An activity level of 7 days a week with no seasonal adjustment factor was used.

Emission Factors Emission factors were derived from the Emissi on Inventory Improvement Program (EIIP); AP-42, Volume 11, Fifth Edition; EP A's NON-ROAD 2002 model; EPA' s MOBILE 5 model; and the Landfill Gas Emissions Model (LandGEM) version 3.02.

Collecting all emissions estimates unde r one facility effectively creates a single point source for all of the emissions. No other point sources were subtract ed from the area source inventory to avoid double counting.

Controls were applied when applicable to a particular source category. Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations20 Spatial Spatial allocation of the emission estimates to specific areas within APG is not available.

Temporal Data for temporal allocation is not available for this source.21 3.3 ANDREWS AIR FORCE BASE

Andrews Air Force Base (ICAO code KADW) is a United States Air Force base near Washington, DC and the home base of the U. S. presidential aircraft, Air Force One.

The base is located a few miles southeast of Washington, in Prince George's County, Maryland near the town of Morningside. Acco rding to the United States Census Bureau,
the town has a total land area of 6.8 mi2 and none of it is covered by water. There are two runways on the base; the western runway is 3,440 meters in length, and the eastern runway is 3,570 meters in length.

The host unit for Andrews AFB is the 89th Ai rlift Wing which falls under Air Mobility Command. The primary mission at Andrews AFB is to trans port the President of the United States. The base is also tasked, unde r what is known as "SAM FOX", to provide
worldwide airlift for the vice president, the president's Cabinet, members of Congress, military leaders and other high ranking dignita ries. At one time, "SAM FOX", was used as a prefix to an aircraft tail number, during radio transmissions to identify Air Force aircraft that were transpor ting high-ranking VIPs, typically on foreign flights. The call sign prefix was constructed from the acronym SAM (Special Air Missi on) and the initial F (Foreign), which at the time was re presented by the phonetic word "Fox."

Andrews is also the home of the 89th Communication Group, a unit that provides communications to military installations all ov er the world. The technical control facility is one of the largest in the world, and hosts a myriad of sophisticat ed telecommunications equipment. One of the squadrons within the 89th Communications Group is the 789th Communications Squadron, whose CNCS remotely operates 15 HF Global radio stations from around the Globe. Other major tenants include the District of Columbia Air National Guard (DC-ANG), Naval Air Facility (NAF), and the Maryland State Police.

VOC, NOx, CO, PM, Toxics

MDE staff reviewed emission estimates pr epared for Andrews Air Force Base by a private contractor. These emission estimat es included data for the following source categories:

• Mobile On-Road Source Emissions

o Mobile - LDGV

o Mobile - LDGT12 Description

Pollutants

Emission Source Categories22 o Mobile - LDGT34

o Mobile - HDGV / Buses

o Mobile - MC

o Mobile - LDDV

o Mobile - LDDT

o Mobile - HDDBT

o Mobile - HDDV

o Mobile - HDDBS

o Mobile - Heavy Duty Trucks

o Mobile - Light Duty Vehicles

• Mobile Nonroad Source Emissions

o Nonroad Mobile - Recreational

o Nonroad Mobile - Construction

o Nonroad Mobile - Industrial

o Nonroad Mobile - Lawn and Garden

o Nonroad Mobile – Agricultural

o Gas-Fired Non-road vehicle- 4-stroke gasoline engine

o Gas-Fired Non-road vehicle- 2-stroke gasoline engine

o Aircraft - All Aircraft Types and Operations

o Emissions from military aviation aircraft landing and takeoff.

o Emissions from commercial aviatio n aircraft landing and takeoff.

o Diesel Generators

o Off-highway Vehicle Gasoline, 2-Stroke Total without APUs

o Off-highway Vehicle Gasoline, 4-Stroke Total without APUs

o Off-highway Vehicle Gasoline, 4-Stroke APU emissions

o Off-highway Vehicle Diesel APU emissions

o Nonroad Mobile Aircraft Ground Equipment - All Gasoline Engines

o Nonroad Mobile Aircraft Ground Equipment - All JP-8 Engines

• Point Source Emissions

o MDE staff also reviewed and includ ed emission estimates from emission certification reports prepared by A ndrews Air Force Base and submitted on an annual basis to MDE’s Comp liance and Enforcement Program. These emission estimates include major sources.

Emission estimation methodologies varied by source category. A brief synopsis of the methodologies is presented below. Emission Estimation Methodologies23 Mobile On-Road Source EmissionsThe Andrews AFB on-road vehicle inventory consists of a mix of light- and heavyduty gasoline-, diesel-, and natural gas- powered government-, and privately owned vehicles (POVs). POVs include vehicl es owned by both daily employees and weekend personnel. The inventory contains the vehicle type, model year, number of vehicles, and annual on-base mileage. To distinguish leased General Services Administration (GSA) government-owned ve hicles (GOVs) from the regular fleet, vehicle tag numbers are provided in cases where they are known.

On the basis of inventory data prov ided by vehicle maintenance personnel, government-owned vehicles (GOVs) were grouped into eight vehicle categories according to vehicle type, gross vehicle weight (GVW), and fuel type. The 2002 mileage for each vehicle was provided by vehicle maintenance personnel, as were estimates of on-base mileage or a percentage of the total miles per vehicle that were
driven on the base.

Emissions were calculated only for th e estimated miles and hours of on-base vehicle and equipment operation. Miles travel ed off the base were not included in
the emission calculations. The Fifth Ed ition of AP-42, Volume II includes the emission factors for NOx, CO, and VOC, which were calculated using EPA’s MOBILE 5 model for gasoline and diesel operated vehicles. AP-42 has not been updated with NOx, CO, and VOC emission fact ors from the latest version of EPA’s MOBILE 6.2.03 model, released in Oct ober 2002, which also includes emission factors for PM-10, PM-2.5, SO2, and HAPs. Therefore, the emission factors for onroad vehicles were obtained by running the MOBILE 6.2.03 model. The MOBILE model does not address compressed natural gas vehicles, so emission factors for
these vehicles have been obtai ned from 40CFR86.1708-99, 40CFR88.105-94, and
40CFR88.104.94.

Emission estimates for privately owned vehicles (POVs) are based on traffic studies supplied by base personnel (89th AW Civil Engineering, July 2004). Andrews AFB has approximately 61, 738 vehi cles traveling on base each workday. This number assumes a working schedule of employees of 40 hours per week. In addition, 25% of the daily personnel ar e assumed to be on the base on the
weekends.

The emission factors were used in th e following equation to estimate annual
emissions:

E = V * F * C

Where:
E = Annual emissions of particular polluta nt from each vehicle category (lb/yr)
V = Vehicle miles traveled on-base per ye ar for each vehicle category (mi/yr)
F = Average model year emission factor in th e applicable vehicle category (g/mi)
C = Conversion factor (2.205 

### x 10 lb/g)24 Mobile Nonroad Mobile Source Emissions

The Andrews AFB non-road vehicle invent ory consists of various equipment including forklifts, loaders, riding lawn care equipment, and towing equipment. The inventory contains the equipmen t name, model year, horsepower rating, number of vehicles, fuel type, engine cycle type, and operating hours for CY 2002. The inventory specifies whether the opera ting hours are a total operating time for CY 2002 for the number of units listed or an operating time for each unit.

Criteria pollutant and HAP emission factors were obtained from Air Emissions Inventory Guidance Document for Mobile Sources at Air Force Installations, United States Air Force Institute for En vironment, Safety & Occupational Health Risk Analysis (IERA), January 2002

, which includes the emission factors used in EPA’s NONROAD 2002a model. Emission factors to estimate PM-2.5 from PM10 emissions were obtained fr om EPA’s NONROAD 2002a model.

The Andrews AFB aircraft operations invent ory consists of info rmation related to landings and takeoffs (LTOs) , touch and go’s (T&Gs), low approaches (LAs), and trim and power checks (T&PCs). Calendar year 2002 was used for the calculations of the baseline emissions inventory because 2002 is the baseline year selected by
the MDE for use in the revisi on of its SIP. The inventory contains the aircraft type and manufacturer, engine model and ma nufacturer, the number of LTOs, T&Gs, LAs, and T&PCs. The calendar year 2002 inventory was generated using information compiled from the Aerial Port Squadron, the Andrews AFB Federal Aviation Administration (FAA) Liason, a nd Allan Holtzman, Andrews AFB Air Quality Program Manager. This inventor y will also be submitted to MDE for incorporation into ED MS (version 4.4).

Activity

An activity level of 7 days a week with no seasonal adjustment factor was used.

Emission Factors Emission factors were derived from the EDMS Airport Emission Model, Version 4.4; EPA's NON-ROAD 2002 model; and EPA's MOBILE 6.02.03 model.

Collecting all emissions estimates under one facility effectively creates a single point
source for all of the emissions. No other point sources were subtracted from the area source inventory to avoid double counting. Point Source Adjustments25 Controls were applied when applicable to a particular source category.

Spatial Spatial allocation of the emission estimate s to specific areas within Andrews Air
Force Base is not available.

Temporal Data for temporal allocation is not available for this source. Adjustment for Controls

Spatial and Temporal Allocations26 3.4 BALTIMORE-WASHINGTON INTE RNATIONAL AIRPORT (BWI)

Baltimore-Washington International Airport (BWI) is located in Anne Arundel County, Maryland, approximately 9 miles south of the City of Baltimore and approximately 30 miles northeast of Washington, D.C. BWI Airport is generally bounded on the north, east, and west by Aviation Boulevard (MD Route 170 and MD Rout e 162) and on the south by Dorsey Road (MD Route 176). Interstate 195 (I-195) is a four-lane divided highway that serves as the primary access point to the airport terminal area. Elm Road and Aviation Boulev ard provide secondary access to the terminal and cargo facilities.

BWI is operated by the Maryland Aviation Administration, Maryland Department of Transportation. BWI Airport encompasses 3,596 acres of land. The passenger terminal contains 1.4 million square feet; 4 concourses (3 domestic, 1 international/swing); 69 jet gates with 12 gates dedicated to commuter aircraft.

The emission sources at BWI include aircraft, ai rcraft ground support service equipment, motor vehicles (on roadways, in parking facilities, and at terminal curbsides), the heating plant, fuel storage and handling, an d training fires.

VOC, NOx, CO, PM, Toxics

MDE staff reviewed emission estimates prepared for BWI Airport by a private contractor. These
emission estimates included data fo r the following source categories:

• Mobile Onroad Source Emissions

o Mobile - LDGV Emissions

o Mobile - Parking Facility Emissions

o Mobile - LDGT 1&2 Emissions

o Mobile - LDDT 1-4

o Mobile – HDDV

• Mobile Nonroad Source Emissions

o Emissions from airport service di esel compression ignition equipment

o Emissions from military aircraft LTOs

o Emissions from commercial aircraft LTOs

o Emissions from general aviation aircraft LTOs

o Emissions from aircraft auxiliary power units Description

Pollutants

Emission Source Categories27 • Mobile Nonroad Source Constr uction Equipment Emissions

o 2-Stroke Gas Eng; Constructi on & Mining Equip; Paving Equip

o 4-Stroke Gas Eng; Construction & Mining Equip; Plate Compactors

o 4-Stroke Gas Eng; Construction & Mi ning Equip; Concrete/Industrial Saws

o Diesel Eng; Construction & Mining Equip; Pavers

o Diesel Eng; Construction & Mining Equip; Rollers

o Diesel Eng; Construction & Mining Equip; Scrapers

o Diesel Eng; Constructi on & Mining Equip; Sign al Boards/Light Plants

o Diesel Eng; Construction & Mining Equip; Trenchers

o Diesel Eng; Construction & Mining Equip; Excavators

o Diesel Eng; Construction & Mining Equip; Cranes

o Diesel Eng; Construction & Mining Equip; Graders

o Diesel Eng; Construction & Mi ning Equip; Off-highway Trucks

o Diesel Eng; Construction & Mi ning Equip; Rubber Tire Loaders

o Diesel Eng; Construction & Mini ng Equip; Tractors/Loaders/Backhoes

o Diesel Eng; Construction & Mini ng Equip; Crawler Tractor/Dozers

o Diesel Eng; Industrial Equip; Aerial Lifts

o Diesel Eng; Industria l Equip; Forklifts

o Diesel Eng; Industrial E quip; Sweepers/Scrubbers

o Diesel Eng; Commercial Equip; Generator Sets

o Diesel Eng; Commercial Equip; Air Compressors

o Diesel Eng; Commerci al Equip; Welders

• Mobile Onroad Source Emissions

o Firefighting Training

• Point Source Emissions

o MDE staff also rev iewed and includ ed emission estimates from emission certification reports prepared by BWI and submitted on an annual basis to MDE’s Compliance and Enforcement Program. These emission estimates include major

sources.

Emission estimation methodologies varied by source category. A brief synopsis of the methodologies is presented below.

Emissions and Dispersion Modeli ng System (EDMS) Version 4.4

• Aircraft Emission Estimation Methodologies28 FAA’s EDMS computer program contains a data base of aircraft e ngine emission factors based on engine make and model and four e ngine operation modes (t axi/idle, takeoff, climb out, and approach). EDMS also contai ns a database of em ission factors for an aircraft’s auxiliary power units (APUs). Time-in-mode data is also used as an input into the emission inventory. EDMS time-in-mode da ta include the time that aircraft spend in each of the four operating modes.

• Ground Support Equipment

FAA’s EDMS computer program contains a database of the ground support equipment (GSE) used to service specific types of aircra ft. Also included in the database are the emission factors for each piece of GSE, as well as the time that each piece of equipment spends servicing the aircraft.

• Roadways

FAA’s EDMS computer program uses EPA’ s MOBILE 6.2 model to estimate on-road
mobile vehicle emissions.

• Parking Facilities

FAA’s EDMS computer program uses EPA’ s MOBILE 6.2 model to estimate on-road
mobile vehicle emissions fr om parking facilities.

• Training Fires

FAA’s EDMS computer program contains a da tabase of emission factors for five fuel types (JP-4, JP-5, JP-8, Tekflame and Propane). Training fire emissions are estimated by choosing the fuel type and specifying the amount of fuel consumed in the training exercise.

Nonroad Mobile Source Emissions

• Construction Equipment

Emissions from construction ac tivities were estimated based on the construction activity schedule, including the number and types of construction vehicles and equipment units and
their utilization rates. Emission rates we re taken from EPA’s NONROAD program and MOBILE6.2. Emissions from several components of construction activities were calculated, specifically: onsite construction equipment (back hoes, bull dozers, graders, etc.), haul vehicles idling onsite (cement trucks, dump truc ks, etc.), and haul ve hicles and construction worker vehicles accessing the site. An industr y-wide, representative mix of the number and types of construction equipment, average power rating (horse power), and equipment load factors was used in the analys is. Construction-related motor vehicles (dump trucks, pick-up29 trucks, etc.) were assumed to travel a round trip on-site di stance of 5 miles while on the Airport construction site.

Activity

An activity level of 7 days a week with no seasonal adjustment factor was used.

Emission Factors Emission factors were derived from FAA’ s EDMS computer program (Version 4.4). Vehicular emission factors contained in EDMS are obtained from the EPA's MOBILE 6.2 model. Construction emission factors were derived from EPA’s NONROAD Model.

Collecting all emissions estimates under one facility effectively cr eates a single point source for all of the emissions. No other point sources we re subtracted from the area source inventory to avoid double counting.

Controls were applied when applicable to a particular source category.

Spatial Spatial allocation of the emission estimates to specific areas within Baltimore Washington International Airport is not available.

Temporal Data for temporal allocation is not available for this source. Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations30 

## 4.0 AREAS SOURCES

4.1 EMISSION ESTIMATION METHOD BY CATEGORY

Sample calculations presented below are for illust rative purposes only and may not reflect actual
emissions.

4.1.1 PETROLEUM DISTRIBUTION LOSSES

Evaporative emissions occur at all points in th e gasoline distribution proc ess. These operations, generally inventoried as area sources, are gasoline dispensing outlets and gasoline tank trucks in transit. Bulk terminals and gasoline bulk plants, which are intermediate distribution points between refineries and outlets, have been inventor ied as point sources. Most gasoline dispensing outlets emit less than 10 tons of VOC per year and therefore have been inventoried using area
source methods.

VOC emissions from gasoline di spensing outlets result from vapor losses during tank truck unloading into underground storage tanks, vehicle fueling (boat fueling at marinas), and underground storage tank breathing. Evaporativ e losses from each activity in this source category have been tabulated separately so th at various emission reduction control measures could be easily evaluated.

Emissions from vehicle fueling, including spilla ge during fueling, were calculated with the MOBILE6 model and the methodology is described in Section 5.0 Mobile Sources. Tank truck unloading, underground tank breathing, tank trucks in transit and aircraft refueling were calculated using emissions factors from AP-42 and EIIP.31 4.1.1.1 Tank Truck Unloading
SCC: 25 01 060 053

Emissions from tank truck unloading are aff ected by whether the service station tank is equipped for submerged, splash or balance fil ling. Therefore calcula tions were based on the filling method used and gallons sold.

VOC

The method used to calculate emissions (all VOC), is presented in EIIP 10 , Chapter 11, Gasoline Marketing, which extracts the emission factors from AP-42 , Volume I, Table 5.2-7.

Activity

The Maryland Comptroller of the Treasur y, Gasoline Tax Divisi on provided annual gallons of gasoline and diesel fuel sold. This data includes taxable and non-taxed gasoline purchased by the U.S. Government. State an d local government sale s are included in the taxable sales data. The statewid e total of gallons of fuel so ld was allocated to the county level proportional to the number of regist ered vehicles within the county. Vehicle registration data was collected from the Ma ryland Department of Transportation, Motor Vehicle Administration that supplied the data to MDE’s Mobile Sources Control Program. Diesel fuel powered vehicle totals were subtracted from the Maryland and county registration numbers.

Percentages of submerged, balanced submerged and splash-fill tanks were determined with the assistance of MDE Waste Management. MDE staff reported no splash filling at Maryland service stations in 2002. All underground storage ta nks within the nonattainment areas of the State of Maryland are required to use vapor-balance submerged filling methods. Waste Management's underground tank inspection program and regulations concerning underground storage ta nks have eliminated splash-fill tanks in the state. A recent SSCD study determined that the rule eff ectiveness factor for vapor balance controls
was 91%.

An activity level of 7 days per week was used, based on observations by MDE staff of unloading at Maryland retail ga s stations. A rule effectiveness of 91% was determined from a study of Stage I compliance performe d in Regions III and IV by the MDE/ARMA enforcement program in 1991. In the attainment counties outside of Regions III and IV, a
default rule effectiveness of 80 % was used. This survey data was used to determine the penetration of each filling technology. The tota l fuel sales in the county were multiplied

10 Emission Inventory Improvement Program Description:

Pollutants

Method and Data Sources:32 by the fraction using each filling technology. The AP-42 technology-specific emission factors were then used to estimate emissions from submerged filling and balanced submerged filling. The emissions from each filling technology were summed to estimate
total emissions.

Filling Method Non-Attainment
Area Transport Region Attainment Area

Submerged 9% 9% 20% Balanced Submerged 91% 91% 80% Splash 0% 0% 0%

Activity Days per Year 365

Emission Factors Emission factors are affected by true vapor pr essure and temperature. Emissions from loading petroleum liquid can be estimated (with a probable e rror of ±30 percent) using the following expression 11 :

T MPS L

L ** *46.12 =

where:
L L = loading loss, pounds per 1000 gallons (lb/10 3 gal) of liquid loaded (The loading loss is equivalent to an emission factor) S = a saturation factor (see Table 5.2-1) P = true vapor pressure of liquid load ed, pounds per square inch absolute (psia) (see Figure 7.1-5, Figur e 7.1-6, and Table 7.1-2) M = molecular weight of vapors , pounds per pound-mole (lb/lb-mole) (see Table 7.1-2) T = temperature of bulk liquid loaded, °R (°F + 460)

Table 5.2-1 from AP-42 shows that the saturati on factor (S) is a constant for a specific petroleum liquid, carrier and type of loading service

The true vapor pressure (P) can be estimate d from the Reid vapor pressure using the following equation:

The molecular weight varies slightly with temperature and pressure, however for this analysis it is assumed to be constant.

11 AP42, Chapter 5.2: Transportation and Marketing of Petroleum Liquids ( ) ( ) ⎭ ⎬ ⎫
⎩ ⎨ ⎧

+ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ − ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

− ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ + ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ −− ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ − = 64.15 6.459 8742 log013.2 6.459 2416

6.459 1042 854.1 log* 6.459 0.413 7553.0exp 10 5.0
10 5.0 T RVP T S T RVP S T P33 Proportioning the loading factors yields

2*1 1*2

1 1*1*1*46.12 2 2*2*2*46.12

1 2

TP TP

T MPS T MPS

LL LL

= = 2*1 1*2 *12 T P TP LLLL =

The loading factor or emission factor is directly proportional to true vapor pressure and inversely proportional to temp erature in degrees Rankin.

LL1 = 0.3 at RVP of 10 and 60 F; this yields LL1 =0.3; P =5.186; T=520 R

To calculate LL2 at RVP of 6.7 a nd 81.8 F or P = 5.094; T = 541.8 R

2828.0 8.541*186.5

520*094.5 *3.0 2*1 1*2 *12 = = = T P TP LLLL

Initial emission factors of 0.3 lb VOC per 1000 gallons throughput for balanced submerged filling and 7.3 lb VOC per 1000 gallons throughput for submerged filling were used in all Maryland counties. These factors were then adjusted with county-specific monthly average temperature and true vapor pre ssure values using the above technique.

Filling Method Base Emission Factor Lb. VOC per 1,000 gallon Balanced Submerged 0.3 Submerged 7.3 Diesel Fuel Unloading 0.014

No subtraction of emissions fr om point sources is necessary.

Controls for this source category are reflected in the emission factors.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source. Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations34 The equation for estimating emissions from tank truck unloading is:

(G i x F i (fm) x EF fm ) + (G i x F i (fm) x EF fm ) E fj = 2000 x 365 Where:

E fj = Emissions of VOC in tons per da y from tank truck unl oading per county i

G i = Gallons of gasoline sold in county i during 2002

F i (fm) = Fraction of gasoline dispensed per county i per filling method (balanced submerged or submerged) during 2002

EF fm = Emission factor per filling method fo r tank truck unloading adjusted by RVP and temperature: (0.3 lb. VOC/1000 gallon throughput or 7.3 lb. VOC/1000 gallon throughput )

Tank Truck Unloading Sample Calculation (Carroll County)

To calculate fuel usage for Carroll County:

Filling Method Carroll County Adjusted Emission Factor Lb. VOC per 1,000 gallon Balanced Submerged 0.2453 Submerged 5.9691 Diesel Fuel Unloading 0.014

Total fuel sold in Maryland in 2002 12
= 2,570,356,195 gallons

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration proportion:

Carroll County vehicle registration 13 138,645 Total MD vehicle registration = 4,100,225 = 0.0338

2,570,356,195 x 0.0338 = 86,914,019.269 gallons sold in Carroll County

12 Annual sales of gasoline from Maryland Comp troller of the Treasury, Gasoline Tax Division

13 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program. Emissions Calculation35 [86,914,019.269 gallons of gasoline so ld in Carroll County in 2002 x 91 percent 14 filled by balanced submerged filling method x 0.2453 lbs.. VOC per 1000 gallons of gasoline 15 ] + [86,914,019.269 gallons of gasoline so ld in Carroll County in 2002 x 9 percent filled by submerged filling method x 5.9691 lbs.. VOC per 1000 gallons of gasoline 16 ] = 66,093.07 lbs..

VOC emitted.

Convert to tons per day: 66,093.07 lbs. VOC / (365 days per year x 2000 lbs. per ton) = 0.09 tons VOC per day

14 A rule effectiveness of 91% was determined from a study of Stage I compliance performed in Regions III and IV by the MDE/ARMA enforcement program in 1991. In the attainment counties outside of Regions III and IV, a default rule effectiveness of 80 % was used.

15 Emission factor for balanced submerged filling from AP-42 Volume I, Table 5.2-7.

16 Emission factor for submerged filling from AP-42 Volume I, Table 5.2-7.36 4.1.1.2 Stage II Refueling
SCC: 25 01 060 100

Emissions from Stage II refueling are substantiall y less than those from Stage I because gasoline vapors that ordinarily might ha ve escaped during vehicle fueli ng are recirculated by a special nozzle back into the pump. Th e start year for Stage II refu eling in all Maryland ozone nonattainment areas was 1993. Gasoline stations were required to have St age II nozzles installed by November of that year. Calculations were ba sed on the filling method used and gallons sold.

VOC

EPA recommends that the MOBILE6 model be used to generate refuelin g (Stage II) emission factors for highway vehicle em ission inventories (EPA, 1992b). The model, designed to support the evaluation of air pollution from gasoline- and diesel-fueled vehicl es, generates emission factors for tailpipe emissions and refueling activities. A detailed discussion of using this model is available from EPA (EPA, 1994).

Activity The MOBILE6 model produces estimates of re fueling emissions in units of grams per mile. These values are multiplied by fuel ec onomy (in units of miles per gallon) and total gasoline sales (in units of gallons purchased/so ld) in the study area resulting in refueling emissions in terms of grams. It should be noted that MOBILE makes use of improved predictive equations to calculate refueli ng emission factors, including sensitivity to temperature and Reid vapor pre ssure (RVP), and these have no t yet been incorporated into published AP-42 factors for refueling. Additi onally, the user may provide information on local Stage II emission controls to develop an emission factor for controlled emissions.

Refueling emissions have two mechanisms of introducing emissions to the environment: (1) vapor displacement from the vehicle fuel ta nk during refilling; and (2) gasoline spillage during refueling. The MOBILE user may reque st either a single emission factor that combines the two mechanisms or separate em ission factors for displacement and spillage. Because both mechanisms should be taken into account when estimating refueling emissions, the preferred approach is to request the combined emission factor.

Emission Factors ARMA mobile sources staff ran the MOBILE6 model to estimate the refueling emissions using the grams per mile (g/mile) methodology described above. The emission estimates were converted from grams to tons. Description

Pollutants

Method and Data Sources37 No subtration of emissions fr om point sources is necessary.

Controls for this source category include St age II Vapor Recovery Systems and Onboard Refueling Vapor Recovery (ORVR) systems. The controls are reflected in the emission estimates produced by the MOBILE6 model.

Spatial The MOBILE6 model uses user -supplied county-level gasoline sales data to spatially allocate emission estimates.

Temporal Data for temporal allocation is not available for this source.

The equation for estimating emissions from tank truck unloading is:

(G i x EF StII x MPG x SAF) E StII = 2000 x 365 Where:

E StII = emissions of VOC in tons per day from stage II refueling

G i = gallons of gasoline sold in county i during 2002

EF StII = emission factor for stage II refueling from the MOBILE6 model (grams/mile)

MPG = average fuel economy (miles/gallon)

SAF = seasonal adjustment factor to reflect summer weekday emissions

Stage II Refueling Sample Calculation

Since all calculations are incl uded in the MOBILE6 model output , a sample calculation is not available for this source category. Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation38 4.1.1.3 Underground Tank Breathing
SCC: 25 01 060 201

Underground tank breathing occurs when gasoline is drawn out of the tanks and into the pump lines. During this process air moves into th e tank evaporating gasoline and emitting vapors.

VOC

The method used to calculate emissions (all VOC), is presented in EIIP 17 , Chapter 11, Gasoline Marketing, which extracts th e emission factors from AP-42 , Volume I, Table 5.2-7.

Activity The Maryland Comptroller of the Treasury, Gasoline Tax Divisi on provided annual gallons of gasoline and diesel fuel sold. This data includes taxable and non-taxed gasoline purchased by the U.S. Government. State an d local government sale s are included in the taxable sales data. The statewid e total of gallons of fuel so ld was allocated to the county level proportional to the number of register ed vehicles within the county. Vehicle registration data was collected from the Ma ryland Department of Transportation, Motor Vehicle Administration that supplied the data to MDE’s Mobile Sources Control Program. Diesel fuel powered vehicle totals were subtracted from the Maryland and county registration numbers.

An activity level of 7 days per week was used.

Activity Days per Year 365

Emission Factors An emission factor of 1.0 lbs. VOC per 1000 gallons throughput was used. The emission factor was taken from EIIP , Chapter 11, Gasoline Marketing, which extracts the emission factors from AP-42 , Volume I, Table 5.2-7.

MDE used the same sources for gasoline sa les and car registrati on as in tank truck unloading.

17 Emission Inventory Improvement Program Description:

Pollutants

Method and Data Sources:39 No subtration of emissions fr om point sources is necessary.

Controls for this source category are reflected in the emission factors.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissi ons from underground tank breathing is:

(G i x EF utb ) E utb = 2000 x 365 Where:

E utb = emissions of VOC in tons per day from underground tank breathing and emptying

G i = gallons of gasoline sold in county i during 2002

EF utb = emission factor for underg round tank breathing (1.0 lbs. VOC /1000 gallon throughput)

Underground Tank Breathing Sample Calculation (Carroll County)

To calculate fuel usage for Carroll County:

Total fuel sold in Maryland in 2002 18
= 2,570,356,195 gallons

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration proportion:

18 Annual sales of gasoline from Maryland Comp troller of the Treasury, Gasoline Tax Division Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation40 Carroll County vehicle registration 19 138,645 Total MD vehicle registration = 4,100,225 = 0.0338

2,570,356,195 x 0.0338 = 86,914,019.269 gallons sold in Carroll County in 2002.

22,376,721 = gallons of gasoline sold in Carroll County during the summer of 2002.

[22,376,721 gallons of gasoline sold in Carroll County in 2002 x 0.000818 lbs. VOC per gallons of gasoline 20 ] = 18,304.16 lbs. VOC emitted.

Convert to tons per summer day: 18,304.16 / (92 days per year x 2000 lbs. per ton) = 0.0994 tons

VOC per day emitted from underground tank breathing in Carroll County.

19 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program.

20 Emission factor from AP-42 Volume I, Table 5.2-7.41 4.1.1.4 Gasoline Tank Trucks in Transit
SCC: 25 05 030 120

Breathing losses from tank trucks during the transport of gasoline are caused by leaking delivery trucks, pressure in the tanks, and thermal effect s on the vapor and on the liquid. A worst case situation arises if a poorly sealed tank has been loaded with gasoline and pure air becomes saturated. During the vaporization process, pres sure increases and venting occurs. Emissons from this source category include the evaporation of petroleum vapor from:

• loaded tank trucks during transportation of gasoline from the bulk plant/terminal to the service station or othe r dispensing outlet, and

• from empty tank trucks returning from se rvice stations to bul k plant/terminals.

VOC

The method used to calculate emissions (all VOC), is presented in EIIP 21 , Chapter 11, Gasoline Marketing (Stage I & Stage II), dated September 1997.

Activity

Emission Factors EPA documents the emission factors in AP-42, Table 5.2-5 and EIIP states the emission factors within the above-referenced docume nt in Table 11.3-1. The AP-42 emission factors represent a typical range of values. EIIP averages th e “typical range values” within AP-42 and arrives at average emission factor values of 0.055 and 0.005 lbs.. VOC per 1000- gallon gasoline, respectively for emissions from empty tank trucks and emissions from full tank trucks.

Emission Source EIIP Table 11-3.1 Lb/1000 gallon “Average” AP-42 Table 5-2.5 Lb/1000 gallon “Typical Range”
Gasoline Tank Trucks in Transit Empty Tank Trucks 0.055 0 - 0.11
Full Tank Trucks 0.005 0 - 0.01

MDE used the same sources for gasoline sales an d car registration as in tank truck unloading.

MDE used the emission factors from EIIP, Volu me I, Table 5.2-5, of 0.06 pounds VOC per 1000 gallons throughput (combines 0.005 lb VOC /1000 gallon full tank truck delivery and 0.055 lb VOC

21 Emission Inventory Improvement Program Description

Pollutants

Method and Data Sources42 /1000 gallon empty tank return). MDE also used a bulk facility throughput adjustment factor of 1.25 and calculated throughput by a ratio of county re tail sales and state retail sales times state fuel sales. MDE used the same sources for gaso line sales and car regist ration as in tank truck unloading.

Emission Factors:

Full tank truck delivery 0.005 lbs. VOC per 1000 gallons Empty tank truck return 0.055 lbs. VOC per 1000 gallons Combined (full & empty) 0.060 lbs. VOC per 1000 gallons

Bulk Facility Throughput Adjustment Factor: 1.25 Activity Days Per Year: 312

Equation:

(G i x 1.25 x EF tt ) E tt = 2000 x 312 Where:

E tt = emissions of VOC in tons per day from tank trucks in transit

G i = thousand gallons of fuel sold in county i

EF tt = Combined (full & empty) tank trucks in transit emission factor

2002 Gasoline Tank Trucks in Transit Sample Calculation (Carroll County)

To calculate fuel usage for Carroll County:

Total fuel sold in Maryland in 2002 22
= 2,570,356,195 gallons

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration proportion:

Carroll County vehicle registration 23 138,645 Total MD vehicle registration = 4,100,225 = 0.0338

2,570,356,195 x 0.0338 = 86,914,019.269 gallons

[86,914,019.269 gallons of gasoline sold in Carroll County in 2002 x 1.25 x 0.06 lbs. VOC per 1000 gallons of gasoline 24 ] = 6,518.55 lbs. VOC emitted.

22 Annual sales of gasoline from Maryland Comp troller of the Treasury, Gasoline Tax Division

23 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program .43 Convert to tons per day: 6,518.55 / (312 days per year x 2000 lbs. per ton) = 0.010446 tons VOC per day emitted from tank trucks in transit in Carroll County.

24 Emission factor from AP-42 Volume I, Table 5.2-7.44 4.1.1.5 Aircraft Refueling
SCC: 22 75 900 000

Jet kerosene (used primarily by commercial turbojet and turbopr op aircraft), jet naphtha (used primarily by military aircraft) and aviation gaso line (used by aviation reciprocating engines) are the three most common types of aircraft fuels us ed in the United States. Emissions occur when vapor-laden air in a partially empty fuel tank is displaced to the atmosphere when the tank is refilled.

VOC

MDE staff apportioned state level fuel sales to aircraft activit y as suggested in Procedures

, Section 4.2.3.

Activity MDE used selected data from the Department of Energy’s State Energy Data System, to obtain fuel consumption data. MDE used ai rport survey data and the Maryland Aviation Administration’s 2002 Operations Count for P ublic-Use Airports to obtain operational counts. A few airports, such as Andrews Ai r Force Base, provided their own operations

count.

Fuel Type Fuel Consumption (1,000 Barrels)
Jet Kerosene 3,938.000 Aviation Gasoline 38.877 Jet Naphtha 39.380

Emission Factors Emission factors, splash loadi ng factor and physical properties of aviation fuel are taken from AP-42 , Tables 5.2-1, 5.2-5, 7.1-2, and are summarized below. Note the relatively high emission factor for aviation gasoline which contributes to high em issions at airports with large amounts of ge neral aviation (piston e ngine aircraft).

Fuel Type Vapor Pressure (60 ° F) Molecular Weight (at 60 ° F)
Jet Kerosene 0.0085 130 Aviation Gasoline 6.9 62 Jet Naphtha 1.3 80

Splash loading satu ration factor: 1.45 Description

Pollutants

Method and Data Sources45 Units conversion factor 42 gals/barrel Activity days per period 365 days/year Study Temperature 520 deg. R (unit used in Procedures )

Emission Factor Equation:

Refueling EF = 12.46 x splash loading

factor x true

vapor
pressure x molecular weight at the study temperature

Refueling EF (RE i ) Fuel Type (lbs. VOC/kgal)
Jet Kerosene 0.03839 Aviation Gasoline 14.86358 Jet Naphtha 3.61340

Emission Estimate Equation:

CA I S i x SA i X RE i E ar = 2000 x 365

where:
S i = State aircraft fuel sales for fuel type i
CA i = County aircraft activity (LTO) for fuel type i
SA i = State aircraft activity (LTO) for fuel type i
RE i = Refueling emission f actor for fuel type i
E ar = Emissions from aircraft refueling in tons VOC per day

2002 Sample Calculation for Aircraft Refu eling- General Aviation (Allegany County)

Maryland aviation gasoline fuel sales = 105,000 barrels 25 = 1,632,826.86 gallons

Allegany County General Aviation LTOs 7650.5 Maryland general aviation LTOs = 723,256 = 0.010578

Gallons of AvGas used Allegany = 1,632,826.86 x 0.010578 = 17,271.81

Emissions-GA Refueling Allegany = 17,271.81 ÷ 1,000 x 14.86358 26 = 256.721 lbs. VOC /year Emissions-GA Refueling Allegany = 256.721 ÷ (2000 x 365) = 0.0004 tons VOC /day

25 From Department of Energy State Energy Data Report

26 Emission factors, splash loading factor and physical properties of aviation fuel are taken from AP-42 , Tables 5.2- 1, 5.2-5, 7.1-2,46 4.1.1.6 Petroleum Vessel Unloading Losses
SCC: 25 05 020 000

Petroleum liquids are transported via ships and barges, and on-land transportation. The procedures discussed below relate to marine transpor t of petroleum liquids. This category does not include emissions from fuel consumed by vessels while in transit or in port. Evaporative VOC emissions from ocean going ships and barg es carrying petroleum liquids result from loading losses, ballasting losses and transit losses. Pe troleum liquids are classified into groups which are represented by crude oil, gasoline, jet naptha, distillate oil/kerosene, or residual oil. Loading and ballasting losses do not occur with pi peline transport of petroleum products (AP-42

, Section 5.2).

Loading losses occur as organic vapors in “empty” car go tanks are displaced to the atmosphere by the liquid being loaded into the tanks. These va pors are a composite of vapors formed in three

ways:

 Vapors which are formed in the “empty” ta nk by evaporation of residual product from previous loads;

 Vapors transferred to the tank fr om a vapor balance system that was used when the previous load was being unloaded; and

 Vapors generated in the tank as the new product is being loaded.

Loading losses are usually the largest source of evaporative emissions from petroleum vessels (EPA, 1996).

Ballasting losses are associated with the unloading of pe troleum liquids at marine terminals and refinery loading docks. It is co mmon practice to load several cargo tank compartments with sea water after the cargo has been unloaded. This water, called “ballast,” improves the stability of the empty tanker during the subsequent voyage. Ballasti ng emissions occur as vapor-laden air in the empty cargo tank is displaced to the atmosphere by ballast water being pumped into the tank.

Transit losses are similar to breathing losses associated with petroleum storage. Transit loss is the expulsion of vapor from a vessel compartm ent through vapor contraction and expansion, which are the result of changes in temperature and barometric pressure. This loss may be accompanied by slight changes in the level of th e liquid in the tank due to liquid expansion or contraction due to the temperat ure change. Some ships are equi pped with controls for these losses.

VOC Description

Pollutants47 Activity

The method used to calculate emissi ons (all VOC) is presented in EIIP 27 , Chapter 12, Marine Vessel Loading, Ballasti ng and Transit, dated May 1998.

A significant part of the emissions from th is source are from the Eastern Shore of Maryland because petroleum products are deliver ed to this area by barge rather than by pipeline as in the rest of the state. To compile emissions MDE used guidance in EIIP

, Chapter 12, Marine Vessel Loading, Ballasti ng and Transit, Water borne Commerce of the United States, Atlantic Region Freight Tables, Part 1, 1998 , and AP-42, Table 7.1-2 and Section 5.2. Wate rborne Commerce supplied tonnage and type of petroleum products delivered to the various ports in Maryla nd for the year 2001. Tonnages of petroleum delivered were converted into Kgal.s (1000 ga llons) and then used to calculate emissions.

Factors

UNCONTROLLED VOC EMISSION FACT ORS FOR PETROLEUM CARRYING MARINE VESSELS (EPA, 1996)

Petroleum Liquid Ship/Ocean Vessel Loading

(Lbs. VOC per 1,000 gallons Transferred) Barge Loading (Lbs. VOC per 1,000 gallons Transferred) Ballasting (Lbs. VOC per 1,000 gallons Transferred) Transit (Lbs. VOC per 1,000 gallons Transferred)

Crude Oil 0.61 1 1.1 1.3
Gasoline 1.8 3.4 0.8 2.7 Jet Naphtha / Other 0.5 1.2 NA 0.7

Distillate Oil /
Kerosene 0.005 0.012 NA 0.005

Residual Oil 4 x 10 -5 9 x 10 –5 NA 3 x 10 -5

Data obtained from sources such as the Waterborne Commerce of the United States are typically provided in terms other than 1,000 gallons (Mgal) as is required in Equation 12.4-1 and must be converted. Equation 12.4-3 can be used to c onvert units from 1,000 ton (Mtons) to Mgal. where:

27 Emission Inventory Improvement Program Method and Data Sources48 PP V = (PP M / d) x ( 2,000 lb/ton) x ( Mgal/1 ,000 gallons) x ( 1,000 tons/Mtons)

PP V = Amount of petroleum liquid (Mgal)
PP M = Amount of petroleum liquid (Mtons) d = Density of petroleu m liquid; see Table 7.1- 2 in AP-42 (lb/gallon)

Density 28 (lb/gal)
Distillate Oil 7.10 Residual Oil 7.90

Gasoline 5.60
Kerosene 7.00 Crude Oil 7.10 Jet Naphtha 6.40

If controls exist, then contro l efficiency can be calculated:

PP C = PP U x (1 - CE/100)

where:

PP C = Controlled emissions (tons)
PP U = Uncontrolled emissions (tons) CE = Control efficiency (%)

Equation:

[(SOEF P x PP S,P ) + (BREF P x PP B,P ) + (BLEF P,U x 0.30 x PP BL,P ) + (TREF P x PP T,P )] PV P = 2000

Where:

PV P : Total VOC emissions from petroleum vessel loading, ballasting, and transit for each of the petroleum liquids (p) transported: crude oil, gasoline, kerosene, distillate oil, and residual oil (tons)
SOEF P : Ship/ocean vessel loading emission f actor (pounds VOC per 1,000 gallons transferred)
PP S,P : Amount of petroleum liquid (p) loaded into ships and ocean vessels in the inventory region (1,000 gallons)

BREF P : Barge vessel loading emission fact or (pounds VOC per 1,000 gallons transferred)
PP B,P : Amount of petroleum liquid (p) loaded into barges in the inventory region (1,000 gallons)

28 AP-42, Table 7.1-249 BLEF P,U : Ballasting emission factor (pounds VOC per 1,000 gallons water ballasted)
PP BL,P : Amount of petroleum liquid (p) unload ed from vessels that are ballasted (1,000 gallons)
TREF P : Vessel transit emission factor ( pounds VOC per week per 1,000 gallons transferred)
PP T,P : Amount of petroleum liquid (p) transpor ted by marine vessels in the inventory region (1,000 gallons)

2002 Petroleum Vessel Unloading Losses Sample Calculation (Gasolin e - Baltimore City)

Gallons (in Thousands) of Petrol eum Shipped in Baltimore Harbor

Crude Oil Distillate Oil Gasoline Jet Naphtha Residual Oil Kerosene

Baltimore Harbor 0.00 1690.14 33214.29 625 56202.53 0.00

Tonnage of distillate oil shipped in Baltimore Harbor (from Waterborne Commerce of the U.S., 2001) were converted in thousands of gallons (Kga l.s) and then used to calculate emissions.

Vessel Loading Emissions For vessel loading operations, 90 percent of the to tal throughput was loaded at terminals with a control system of 95 percent efficiency. According to the local port authoriti es, transit time in the inventory area is two days (2/7 of a week). Emissions for eac h emission point are calculated using Equation 12.4-1 and the emission factors from Table 12.4-5. In this example, emissions for each emission point are calculated separately and then totaled. Note that CE is applied to vessel loading emissions, and transit emissions are apportioned to two days per week by multiplying emissions by 2/7.

Vessel Loading (gasoline) emissions are calculated:
PV GAS = [(1.8 lbs VOC /Kgal) x (31785.71 Kgal/yr) x {0.10 + [0.9 ( 1 – 95/100)]}÷ 2,000 lb/ton
PV GAS = 4.1480 tons/year

Barge Loading emissions are calculated:
PV GAS = [(3.4 lbs VOC /Kgal) x ( 113928.57 Kgal/yr)] ÷ 2,000 lb/ton
PV GAS = 193.6786 tons/year

Ballasting emissions are calculated:
PV GAS = [(0.8 lbs VOC /Kgal) x (477857.14 Kgal/yr) x ( 0.20)] ÷ 2,000 lbs/ton
PV GAS = 38.2286 tons/year50 Note that the calculation for ballasting emissions in the equation include s a correction term of 0.20. This correction term refl ects the practice of loading a ship or barge at some fraction of capacity when ballasting.

Transit emissions are calculated:
PV GAS = (2.7 lbs VOC /Kgal) x ( 1271071.43 Kgal/yr) x ( 2/7wk) ÷ 2,000 lbs/ton
PV GAS = 490.2704 tons/year

Total VOC emissions are calculated as follows: Total VOC = 4.1480 tons/year + 193.6786 tons/year + 38.2286 tons/year + 490.2704 tons/year Total VOC = 726.3256 tons/yr

There are 260 activity days per year Total Daily VOC = (726.3256 tons/yr ÷ 260 days/yr = 2.7936 tons/day for Baltimore City.

True vapor pressure of distil late oil at 60 deg. F: 0.007451 4.1.1.7 Portable Fuel Containers SCC: 25 01 011 011 (Residential – Permeation) 25 01 011 012 (Residential – Diurnal) 25 01 011 016 (Residential – Transport) 25 01 012 011 (Commercial – Permeation) 25 01 012 012 (Commercial – Diurnal) 25 01 012 016 (Commercial – Transport)

Portable fuel containers (PFCs) store and transport fuel from gasoline service stations to residential homes and businesses. Emissions from PFC use include:

• Permeation Emissions , which are produced after fuel ha s been stored long enough in a can for fuel molecules to infiltra te and saturate the can material.

• Diurnal Emissions , which result when stored fuel vapors escape to the outside of a gas can through any possible openings while the ga s can is subjected to daily cycle of increasing and decreasing ambient temperatur es. Diurnal emissions are dependent on the closed- or open-storage condition of a gas can.

• Transport Emissions arise when fuel escapes (e.g., spill s,etc.) from gas cans that are in transit.

• Equipment Refueling Emissions results when fuel escapes (e.g., spillage, vapor displacement) during the refueling of nonroa d equipment; however these emissions are handled by EPA’s NONROAD model. Activ ity data from the NONROAD model were used to estimate these emissions (described below).

Both residential and commercial PFCs are include d. The SCCs for PFCs are also new and are shown above.

VOC

The method used to calculate emissions (all VOC), is adoped from a CARB 29 survey and methodology adopted by OTC 30

.

Portable fuel container emissi on are calculated by accounting for emissions from five different components related to gas container use: permeat ion, diurnal, transport-spillage, refueling spillage and refueling vapor displacement em issions. The permeation, diurnal emissions

29 ARB’s Mailout MSC 99-25, “Public Meeting to Consid er Approval of CA’s Po rtable Gasoline-Container Emissions Inventory, “ (ARB, 199b)

30 Control Measure Development Suppoort Analysis of Ozone Trnasport Commission Model Rules, E.H. Pechan & Associates, Inc. 5528-B Hempstead Way, Springfield, VA 22151, March 31, 2001. Description

Pollutants

Method and Data Sources52 (associated with storage) and transport-spillage (associated with filli ng the can) emissions are included in the area source inventory. The e quipment refueling spillage and refueling vapor displacement emissions are calcul ated from the non-road model and are included in the non-road inventory

Activity The following input data is re quired to calculate emissions for this source category.

1. Number of residential hous ing units in 2002 by county, N
2. Number of commercial businesses 31 2002 expected to have at least one gas can by county, NAICS 11, 23, 31-33, 441, 45299, 447, 484, 488, 493, 53131, 5321, 532291, 5323, 5324, 54132, 54162, 54169, 56173, 71391, 71393, 7212, 811, 81293
3. Weekly activity, WAF = 7 days/week
4. Seasonal adjustment factors, SAF = 1

Emission Factors Separate emission factors were developed for permeation, diurnal, transport and spillage emissions for PFC (both for co mmercial and residential PFC s). These emission factors were derived from CARB’s survey data (CARB, 1999).

Because the application of archite ctural surface coating is defined as an area source, there is no need to subtract point source emissions from the to tal, and all emissions estimated for this source are area source emissions.

No controls are available for this source category.

Spatial For the residential PFC SCCs, emissions were allocated to the local area level based on a housing surrogate. Commercial PFC emissions we re allocated to the local area level based on commercial and industria l business location.

Temporal For the residential PFC SCCs, the emissions were allocated based on the monthly and weekday/weekend day temporal profiles for re sidential lawn and garden equipment in the

31 Total 2002 employment and business establishments by 6 digit NAICS code and by county, County Business
Patterns Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations53 NONROAD model. For the commercial PFC S CCs, these emissions were allocated based on temporal profiles for the NONROAD model engines used in commercial applications.

The equation used to estimate emissions from portable fuel containers is:

Equation:

The residential-gas-can populati on is calculated as follows:

Pop R = (N)*(A)*(Count R ) (Eq. 1)

where: Pop R = Statewide Residential-Gas-Can Population N = Number of Occupied -Housing Units in OTC State A = Percentage of House holds with Gas Cans (46%)
Count R = Average Number of Residential-Gas Cans per Household

Statewide residential-gas-can-permeati on emissions are computed as follows:

HC PR = Σ (Pop R )*(S)*(EF P )*(B R )*(Size R )*(Level)/CF (Eq. 2)

where: HC PR = Permeation Emissions in tons per day (tpd) Pop R = Statewide Residential-Gas-Can Population
EF P = Appropriate Permeation-Em ission Factor (g/gal-day) S = Percentage of Gas Ca ns Stored with Fuel (70%)
B R = Percentage of Cans Stored in Closed Condition with respect to Material (Plastic 53%; Metal 13%) Size R = Weighted Average Capacity of Residential-Gas Cans (2.34 gal.) Level = Weighted Average Amount of Stored Fuel (49%) CF = 908,105 g/ton

Diurnal emissions from both open- and closed-system-residentia l-gas cans are calculated as follows:

HC DR = (Pop R )*(S)*(EF D )*(B R )*(Size R )*(Level) (Eq. 3)

where: HC DR = Diurnal Emissions (tpd) for Resi dential-Gas Cans with respect to Storage Condition (Open or Closed ) and Material (Plastic or Metal) Pop R = Statewide Residential-Gas-Can Population S = Percentage of Gas-Can Popul ation Stored with Fuel (70%)
EF D = Appropriate Diurnal-Emission F actor with respect to Storage Condition and Material (g /gal-day or g/day) Emissions Calculation54 B R = Percentage of Gas-Can Popul ation with respect to Storage Condition and Material Size R = Weighted Average Capacity of Residential-Gas Cans (2.34 gal.) Level = Weighted Average Am ount of Stored Fuel (49%)
CF = 908,105 g/ton

Residential-transport-spillage emissions are determined as:

HC TR = (Pop R )*(S)*(Refill R )*(EF T )*(B R ) (Eq. 4)

where: HC TR = Residential-Gas-Can-Trans port-Spillage Emissions (tpd) Pop R = Statewide Residential-Gas-Can Population S = Percentage of Gas Cans Stored with Fuel (70%) Refill R = Average Number of Residential-Gas-Cans-Pump-Refills per Day per Can (refill/day from survey)
EF T = Transport-Emission Factor w ith respect to Storage Condition (g/refill)
B R = Percentage of Gas Cans with respect to Storage Condition and Material
CF = 908,105 g/ton

The commercial-gas-can populati on is calculated as follows:

Pop C = (N C )*( Count C ) (Eq. 5)

where: Pop C = Statewide Commercial-Gas-Can Population
N C = Number of Occupied Businesses in State
Count C = Average Number of Gas Cans per Business

Statewide commercial-gas-can-permeation emissions are computed as follows:

HC PC = Σ (Pop C )*(S)*(EF P )*(B C )*(Size C )*(Level) (Eq. 6)

where: HC PC = Permeation Emissions (tpd) Pop C = Statewide Commercial-Gas-Can Population
EF P = Appropriate Permeation-Em ission Factor (g/gal-day) S = Percentage of Gas Cans Stored with Fuel (70% for Residential Survey)
B C = Percentage of Applicable Gas Cans Stored in Closed Condition Size C = Weighted Average Capacity of Commercial-Gas Cans (3.43 gal) Level = Weighted Average Amount of Stored Fuel (49% from Residential Survey)
CF = 908,105 g/ton55 The amount of diurnal emissions from both open- and closed-s ystem commercial-gas cans is calculated as follows:

HC DC = (Pop C )*(S)*(EF D )*(B C )*(Size C )*(Level) (Eq. 7)

where: HC DC = Diurnal Emissions (t pd) for Commercial-Gas Cans with respect to Storage Condition (Open or Closed ) and Material (Plastic or Metal) Pop C = Statewide Commercial-Gas-Can Population
EF D = Appropriate Diurnal-Emission F actor with respect to Storage Condition and Material (g /gal-day or g/day) S = Percentage of Gas Cans Stored with Fuel (70% from Residential Survey)
B C = Percentage of Gas Cans with respect to Storage Condition and Material Size C = Weighted Average Capacity of Commercial-Gas Cans (3.43 gal.) Level = Weighted Average Amount of Stored Fuel (49% from Residential Survey)
CF = 908,105 g/ton

The non-lawn-and-garden-equipment commercial-gas- can refills at the pump is derived as follows: 

# ( ) ( )( )() ⎥ ⎥ ⎦ ⎤
⎢ ⎢ ⎣ ⎡

= 

## ∑

S POP SIZE Fuel REFILL

NON C C * * (Eq. 8)

where: Refill C = Average Number of Non-Lawn-and-Garden Equipment Commercial-Gas-Cans Pump Refills per Day per Can (refill/day) Fuel = Non-Lawn-and-Garden Equipm ent Fuel Consumption (gal/day) for
2000 Size C = Weighted Average Capacity of Commercial-Gas Cans (3.43 gal/can-refill)
POP NON = Statewide Commercial-Gas-Can Population with respect to NonLawn-and-Garden Businesses S = Percentage of Gas Cans Stored with Fuel (70% from Residential Survey)
CF = 908,105 g/ton

The commercial-transport-spillage emissions are determined as:

HC TC = (Pop C )*(S)*(B C )*(Refill C )*(EF TC ) (Eq. 9)

where: HC TC = Commercial-Gas-Can-Trans port-Spillage Emissions (tpd)56 Pop C = Statewide Commercial-Gas-Can Population S = Percentage of Gas Cans Stored with Fuel (70% from Residential Survey)
B C = Percentage of Gas Cans with respect to Storage Condition and Material Refill C = Average Number of Gas-Cans Pump Refills per Day per Can
EF TC = Transport-Spillage Emission Factor (g/refill) with respect to Storage Condition
CF = 908,105 g/ton

The total area source portable fuel cont ainer emissions are summed as follows:

E PFC - A = HC PR +HC DR +HC TR +HCPC+HC DC +HC TC

E PFC - SD = E PFC - A *SAF / /ADDF

Where:
E PFC - A = (tons/yr) for an annual emission of pollutant by county
E PFC - SD = (tons/day) for a typical summer day emission of pollutant AADF = Annual activity day fact or (WAF * 52 weeks/year) SAF = Seasonal adjustment factor57 4.1.2 STATIONARY SOURCE SO LVENT APPLICATION

4.1.2.1 Dry Cleaners
SCC: 24 20 000 000

Since perchloroethylene has been removed from the EPA list of reactive VOCs, it has been removed from the inventory total. Table 4.3-3 in Procedures lists three compounds under halogenated solvents for dry cleaning: 1,1,1 trichloroethane, trifl uorotrichloroethane and perchloroethylene. None of these solvents is on the VOC list. The la test Emission Inventory Improvement Program guidance on dry cleaning (Vol. III, Chapter 4, Dry Cleaning Final Report , May 2002), also states that the synthetic solvents used in dry cleaning are not photochemically reactive and should not be included in a VOC inve ntory of ozone precursors. Therefore this category ha s been eliminated from the 2002 periodic inventory.

4.1.2.2 Surface Cleaning (Cold Cleaning Degreasing)
SCC: 24 15 300 000

Cold cleaning is seen primarily at auto repair st ations or manufacturing fa cilities, where solvents at room temperature (or slightly warmed) are us ed to clean parts via immersion or rinsing.

Cold cleaners are usually individually small em ission sources and, becau se they are widely scattered and frequently used, they are most easil y treated as area sources. If they are collocated at a major source, they may be included in the point source inventory a nd those emissions will need to be subtracted from the area source estimate.

There are two basic types of cl eaning machines: batch and in-lin e cleaning machines (also called continuous cleaning machines). Both of these eq uipment types are designed to use solvent to clean parts. The solvent is either used to cl ean in its non-vapor liquid form (at a temperature below the boiling point, referred to as cold cleani ng), or heated to a temperature above its boiling point (referred to as vapor clea ning). Other solvent cleaning operati ons involve the use of solvent in wipe-cleaning and equipment cleanup. Emissions from solvent cleaning machines can also be considered to be point sources; therefore, the estimation process for the source category must take this into account to prevent double count ing of emissions. Additionally, emissions from solvent cleanup may be included as a part of an industry- or pro cess-specific emission estimate.

VOC Description

Pollutants58 MDE staff used an alternative per capita emission estimation method documented in EIIP 32

, Chapter 6, Solvent Cleaning, dated September 1997.

Activity The U.S. Census Bureau reports population statistics for the counties of Maryland. Population statistics for 2002 for the counties of Maryland were collected from the U.S. Census Bureau Internet address ( http://www.census.gov ).

An activity level of 6 days a week with no seasonal adjustment factor was used as recommended in the EIIP document. Solvent storage and recycling centers such as Safety Kleen are included in the point source inve ntory. The U.S. Census Bureau reports population statistics for the counties of Mary land. Population statistics for 2002 for the counties of Maryland were collected from th e U.S. Census Bureau Internet address ( http://www.census.gov ). A 2002 reduction factor (Pha se II Attainment Plan for the Baltimore Nonattainment Area and Cecil County) of 53.60% was applied to the calculated emissions. This factor combines reducti ons from technology rules and good housekeeping practices and the applic ation of rule effectiv eness as shown below:

Reduction factor = (contr ol efficiency) x (rule effectiveness) x (rule penetration)

Reduction factor = 0.67 x 0.80 x 1.00

Reduction factor = 0.5360

Emission Factor Table 6.5-4 of the EIIP document lists a tota l emission factor of 4.3 lbs. VOC per capita per year for solvent cleaning operations. The em ission factor is a composed of a total from four categories; including automobile repair (2.5 lbs. VOC per capita), manufacturing (1.1 lbs. VOC per capita), electronics and electrical (0.21 lbs. VOC per capita), and other (0.49 lbs.

VOC per capita).

Factors

E cc = 4.3 lbs VOC per capita per year for cold cleaning degreasers
CE cc = 67%
RE cc = 80%
RP cc = 100%

Note:

32 Emission Inventory Improvement Program Method and Data Source59 Emissions from this source category have increased because of a change in the emission factor and emission estimation methodology. In previo us emission inventorie s, only cold cleaning degreasing operations were considered an area source and open top and conveyor degreasing operations were considered point sources that were listed in the MDE/ARMA registration files. No point source emissions were then subtract ed from the area source inventory. MDE previously used an emission factor from AP-42 , Section 4.6 – Solvent Degreasing, Table 4.6-1 33

. This table reports a 4.0 lbs. VOC per capita emi ssion factor that includes 25 percent non-reactive VOCs, yielding an effective emission factor of 3.0 lbs. VOC per capita. A 1996 reduction factor of 0.70 was applied to th e calculated emissions (rule effectiven ess was not applied). This factor combines reductions from technology rules a nd good housekeeping practices. In effect, MDE increased the emission factor from 3.0 to 4.3.

Solvent cleaning emissions from facilities identified as point sources were subtracted from the area source inventory to avoid double counting.

Maryland has adopted a cold and vapor degrea sing regulation (COMAR 26.11.19.09). The regulation mandates that all cold degreasing material must have a vapor pressure less than or equal to 1 mm Hg at 20 degrees centigrade after May 15, 1996. The regulation also requires that good operating practices be implemented to minimize VOC losses. MDE estimates a 67 percent control efficiency for this control.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissi ons from cold cleaning/degreasing is:

33 Nonmethane VOC Emissions from small cold cleaning degreasing operations Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation60 Equation:



## [ ] PtSourceCC CC CC CC ccj CC ERPRECE EFPOP E

− ⎭ ⎬ ⎫ ⎩ ⎨ ⎧

− = )**(1* 312*2000 *

Where:

E cc = Emissions of VOC in tons/day from cold cleaners
POP j = 2002 population of county j
EF cc = VOC emissions factor for cold cleaning degreasing
CE cc = Control efficiency fo r cold cleaning degreasing
RE cc = Rule Effectiveness for cold cleaning degreasing
RP cc = Rule Penetration fo r cold cleaning degreasing
E PtSourceCC = Point Source Emissions from cold cleaning degreasing

2002 Sample Calculation for Cold Cl eaning Degreasing (Anne Arundel County)

(503,388 34 people x 4.3 lb/capita/year)/(2000 lb s./ton x 312 operating days/year) = 3.469 tons/day. 503,388 x 4.3 lbs. VOC/ person/year 35 = 2,164,568 lbs. per person VOC emitted.

Converting to tons per day: 2,164,568 / (312 operating days per year 36 x 2000 pounds per ton) =
3.469tons VOC per day emitted (there is no seasonal adjustment 37 ).

To adjust for controls
3.469 x [1 – (0.67 x 0.80 x 1.00)] = 1.610 tons VOC / day emitted with 2002 controls applied

To adjust for point sources
1.610 tons VOC / day – 0.076 tons VOC / day = 1.534 tons VOC / day

34 Population data from the U.S. Bureau of Census, Population Estimates Branch

35 Emission factor from EIIP

36 6 days per week operation from EIIP

37 No seasonal adjustment from EIIP61 3.3.2.3 Surface Coating

Surface coating includes paints, enam els, varnishes, lacquers and other product finishes. Some of those coatings contain a solv ent-based liquid carrier; others use a water-based liquid carrier but still contain a small portion of solvents. Solvents are also used to clean up painting equipment. The primary types of surface coa ting applications are architectural coatings, automobile refinishing and traffic paints.

4.1.2.3 Architectural Surface Coating
SCC: 24 01 001 000

Architectural surface coating is an area source that occurs from homeowners and contractors painting homes, buildings and signs.

VOC

MDE staff used an alternative per capita emission estimation method documented in EIIP 38

, Chapter 3, Architectural Surface Coating, da ted November 1995. The document provides an outline for developing a per capita usage factor, a nd for using that usage factor and an emission factor to calculated a VOC emission estimate.

Activity

Determine the per capita usage factor by divi ding the national total architectural surface coating quantities 39 for solvent- and water-based coatings by the U.S. population 40 for that

year.

Per Capita Usage Factor Development

The table below shows a portion of Table 2 fr om the U.S. Bureau of Census MA28F - Paint and Allied Products. This section of the table summarizes the market information available on architectural coatings for the year of 2002. In the table, types of paints are identified as being either solvent- or water-bas ed paints, except for the two types listed as Architectural Lacquers and Arch itectural Coatings N.S.K. These latter types of paints can be assumed to be entirely solvent-based co atings. The calculation to obtain the number of gallons of solvent based paints totals the gallons for Exterior Solvent Type, Interior Solvent Type, Architectural Lacquers and Architectural Coatings N.S.K:

38 Emission Inventory Improvement Program

39 Total national coating usage is compiled by the Bureau of the Census, Report MA28F—Paint and Allied Products, available on the Census Bureau Bulletin Board, (301)457-2310.

40 Population data from the U.S. Bureau of the Census, Population Estimates Branch . Description

Pollutants

Method and Data Sources62 Solvent-Based Paints = 70,967 + 48,947 + 5,808 + 1,981 = 127,703 thousand gallons of paints

The calculation to obtain the number of gallons of water based paints totals the gallons for Exterior Water Type and Interior Water Type:

Water-Based Paints = 182,423 + 407,104 = 589,527 thousand gallons of paints

The per capita usage factor is calculated by divi ding the total usage of solvent based paints by the U.S. population, and the total usage of water based paint by the U.S. population.

Gallons of Solvent Based Paints Per Capita Solvent Based Usage Factor = U. S. Population 127,703,000

= 288,368,698

= 0.442846

Gallons of Water Based Paints Per Capita Water Based Usage Factor = U. S. Population 589,527,000

= 288,368,698

= 2.04435263 Table 2. Quantity and Value of Shipments of Paint and Allied Products: 2002

Product

code Product description 2002 Quantity

325510 Paint and allied products 1/ 1,448,755

3255101 Architectural coatings 717,230 Exterior solvent-type 70,967 3255101111 Solvent thinned paints and tinting bases, including barn and roof paints 19,874 3255101115 Solvent thinned enamels and tinting bases, including

exterior-int erior floor enamels 11,444 3255101119 Solvent thinned undercoaters and primers 9,184
3255101121 Solvent thinned clear finishes and sealers 5,701 3255101125 Solvent thinned stains, including shingle and shake 14,665 3255101129 Other exterior solvent thinned coatings, including bituminous paints 10,099 Exterior water-type 182,423 3255101131 Water thinned paints and tinting bases, including barn and roof paints 118,492
3255101135 Water thinned exterior-interior deck and floor enamels 4,186 3255101139 Water thinned undercoaters and primers 13,786
3255101141 Water thinned stains and sealers 16,773 3255101145 Other exterior water thinned coatings 29,186 Interior solvent-type 48,947 3255101211 Flat solvent thinned wall paint and tinting bases, including mill white paints 6,288 3255101215 Gloss and quick drying enamels and other gloss solvent thinned paints and enamels 4,164 3255101219 Semigloss, eggshell, satin solvent thinned paints and tinting bases 9,674 3255101221 Solvent thinned undercoaters and primers 11,602
3255101225 Solvent thinned clear finishes and sealers 7,429
3255101229 Solvent thinned stains 1,892 3255101231 Other interior solvent thinned coatings 7,898 Interior water-type 407,104 3255101235 Flat water thinned paints and tinting bases 162,810 3255101239 Semigloss, eggshell, satin, and other water thinned paints and tinting bases 164,419 3255101241 Water thinned undercoaters and primers 43,051 3255101245 Other interior water thinned coatings, stains, and sealers 36,824 3255101249 Architectural lacquers 5,808 3255101YWV Architectural coatings, n.s.k. 1,981

3255104 Product finishes for original equipment manufacturers (OEM), excluding marine coatings 414,943 3255104111 Automobile, light truck, van, and sport utility vehicle finishes 47,99464 3255104121 Automobile parts finishes 5,636 3255104131 Heavy duty truck, bus, and recreational vehicle finishes 12,481 3255104141 Other transportation equipment finishes, including aircraft

and railroad 11,558 3255104211 Appliance, heating equipment, and air-conditioner finishes 7,329 3255104215 Wood furniture, cabinet, and fixture finishes 43,725 3255104219 Wood and composition board flat stock finishes 10,060 3255104221 Metal building product finishes (including coatings for aluminum extrusions and siding) 35,855
3255104225 Container and closure finishes 43,393 3255104229 Machinery and equipment finishes, including road building equipment and farm implement 18,865

3255104231 Nonwood furniture and fixture finishes, including business 38,842 equipment finishes 3255104235 Paper, paper board, film, and foil finishes, excluding pigment 14,241
binders 4,447 3255104239 Electrical insulating coatings 77,567 3255104241 Appliance powder coatings 2/ 11,889 3255104245 Automotive powder coatings 2/ 8,903 3255104249 Architectural powder coatings (such as aluminum extrusions) 2/ 2,062 3255104251 Lawn and garden powder coatings 2/ 2,434 3255104255 General metal finishing powder coatings 2/ 22,203 3255104259 Thermoset functional powder coatings (for pipe, rebar,

electrical insula tion, etc.) 2/ (D) 3255104261 Thermoplastic powder coatings (all) 2/ (D) 3255104265 Other industrial product finishes 38,485 3255104YWV Product finishes for original equipment manufacturers (OEM), excluding marine coatings, n.s.k. 4,465

3255107 Special purpose coatings, including all marine coatings 174,114 Industrial new construction and maintenance paints (especially formulated coatings for special conditions of industrial plants and/or facilities requiring protection against extreme temperatures, funge, chemicals, fumes, etc.):

3255107011 Interior 23,370
3255107015 Exterior 34,207 3255107021 Traffic marking paints (all types; shelf goods and highway department) 39,397 3255107031 Automotive, other transportation and machinery refinish paints and enamels, including primers 45,979 3255107041 Marine paints, ship and off-shore facilities and shelf goods for

both new construction and marine refinish and maintenance. Excludes spar varnish 13,565 3255107051 Marine paints for yacht and pleasure craft, new construction,

refinish and maintenance (D)

3255107061 Aerosol - Paint concentrat es produced for packaging in65 aerosol containers (D) 3255107YWV Special purpose coatings, n.s.k. 4,233

325510A Miscellaneous allied paint products 142,468
325510A011 Paint and varnish removers 6,433 325510A021 Thinners for lacquers and other solvent based paint products 31,386 325510A031 Pigment dispersions 25,151 325510A041 Other miscellaneous allied paint products, including brush cleaners, ink vehicles, putty and glazing compounds, etc. 78,512 325510AYWV Miscellaneous allied paint products, n.s.k. 986

Total Solvent-Based 127,703

Total Water-Based 589,527

Emission Factor Use the emission factors for architectural su rface coatings (EPA, 1993A), that are shown in Table 5-2 of the EIIP document and reproduced below:

Coating Type VOC Content Lbs / gallon
Water-based 0.74
Solvent-based 3.87
Total 4.61

This activity occurs 7 days a week and is usually more common in the summer months as indicated by a seasonal adjustment factor of 1.3 (see Table 5.8-1 in Procedures) . It should be noted that 99% of solvents in these coatings are VOC.

Because the application of archite ctural surface coating is defined as an area source, there is no need to subtract point source emissions from the to tal, and all emissions estimated for this source are area source emissions.

EPA surface coating regulation provides a 20 percent reduction.

Spatial Data for spatial allocation is not available for this source. Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations66 Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissions from architectural surface coatings is:

Equation to calculate solv ent-based emissions is:

POP i x UF ASC - SB x EF ASC - SB x SAF ASC x [(1 – (CE ASC x RE ASC x RP ASC )] E ASC – SB = 2000 x 365

Where:

E ASC – SB = VOC emissions in tons per day from solvent-based architectural surface coatings
POP i = 2002 population of county i
UF ASC – SB = Usage factor for solvent-ba sed architectural surface coatings
EF ASC – SB = VOC emission factor for solvent- based architectural surface coatings
SAF ASC = Seasonal adjustment factor for architectural surface coatings
CE ASC = Control efficiency 41 for architectural surface coatings
RE ASC = Rule effectiveness 42 for architectural surface coatings
RP ASC = Rule penetration for architectural surface coatings

Equation to calculate water-based emissions is:

POP i x UF ASC - WB x EF ASC - WB x SAF ASC x [(1 – (CE ASC x RE ASC x RP ASC )] E ASC – WB = 2000 x 365

Where:

E ASC – WB = VOC emissions in tons per day from water-based architectural surface coatings
POP i = 2002 population of county i
UF ASC – WB = Usage factor for water-based architectural su rface coatings
EF ASC – WB = VOC emission factor for water-bas ed architectural surface coatings
SAF ASC = Seasonal adjustment factor for architectural surface coatings
CE ASC = Control efficiency for architectural surface coatings
RE ASC = Rule effectiveness for architectural surface coatings
RP ASC = Rule penetration for architectural surface coatings

41 A 20% reduction in emissions is due to EPA’s AIM regulation

42 EPA’s AIM regulation is a federal rule applying to architectural surface coatings Emissions Calculation67 2002 Example Calculation Architectural Surface Coating (Anne Arundel County)

Solvent-Based 503,388 1 x 0.442846 gal/capita x 3.87 lbs. VOC /gal/year 2 = 862,713.4 lbs. VOC per person per yr

To adjust for controls 862,713.4 x [1 – (0.20 x 1.00 x 1.00)] = 690170.7 lbs. VOC / year with 2002 controls Converting to tons per day: 690,170.7 / (365 days per year x 2000 lbs. per ton) = 0.945439 tons VOC per average day

To seasonally adjust:
0.945439 x 1.3 3 = 1.229 tons VOC per ozone season day emitted from solvent-based architectural surface coating

Water-Based 503,388 1 x 2.044352 gal/capita x 0.74 lbs. VOC /gal/year 2 = 761,535.7 lbs. VOC per person per yr

To adjust for controls 761,535.7 x [1 – (0.20 x 1.00 x 1.00)] = 609,228.6 lbs. VOC / year with controls applied

Converting to tons per day: 609,228.6 / (365 days per year x 2000 lbs. per ton) = 0.83456 tons VOC per average day

To seasonally adjust:
0.83456 x 1.3 3 = 1.085 tons VOC per ozone season day emitted from water-based architectural surface coating68 4.1.2.4 Auto Refinishing
SCC: 24 01 005 000

Automobile refinishing is the re painting of worn or damaged auto mobiles, light trucks and other vehicles. Coating of new cars is not included in this category but falls under industrial coating. In automobile refinishing, lacquers and enam els are usually applied with hand-operated spray guns. Because the vehicles contain heat-sensitive plastics and rubber, the coatings are dried or cured in low-temperature ovens or at ambient conditions. MD E adopted a regulation based upon federal guidance that requires the use of refo rmulated coatings and equipment with greater transfer efficiency in the application of coatings.

VOC

MDE staff used an alternative per employ ee emission estimation methodology documented in
EIIP 43 , Chapter 13, Auto Body Refinishing, date d January 2000. The document provides an outline for developing a per employee emission f actor using a national VOC emission estimate and national employment data.

Activity MDE calculated an emission factor of 0.3858 tons VOC per employee per year by utilizing the national VOC emission estimate found in the EIIP document (79,429.39 tons) and totaling all of the reported stat e employment totals within SIC 7532 for the entire U. S. The national VOC emission estimate of 79,429.39 tons per year has been developed using 1997 activity and 1998 and 1999 emission rate information and are thus controlled emissions. An EPA memo on auto body refinish ing allows a 37% reduction for the federal rule. Maryland’s auto body regulation is more stringent than the national rule, which allowed MDE to take an additional 8% reduction.

County Business Patterns lists employee data by Standard Industry Code (SIC). Many values are based on actual data. However, so me county SICs list a range for the number of employees through a letter code. In this cas e the arithmetic average number of employees per letter code per county was ad justed so that the state total employment in a SIC matched the sum of the number of employees reported per county.

43 Emission Inventory Improvement Program Description

Pollutants

Method and Data Sources69 The autobody refinishing category does not in clude new car coating. Applicable point source emissions (those within the same SIC) taken from the MDE/ARMA registration files have been subtracted from the calculate d emissions, and their emissions are separated from the totals presented below. Table 5.8-1 in Procedures shows th at there is no seasonal variation in this category and the activity level is 5 days a week.

Emission Factor:

MDE calculated an emission factor of 0.3858 tons VOC per employee per year by utilizing the national VOC emission estimate found in the EIIP document (79,429.39 tons) and totaling all of the reporte d state employment totals within SIC 7532 for the entire U. S.

0.3858 tons VOC per employee per year

Autobody refinishing emissions from facilities identified as point sources were subtracted from the area source inventory to avoid double counting.

The national VOC emission estimate of 79,429.39 tons per year has been developed using 1997 activity and 1998 and 1999 emission rate informati on and are thus controlled emissions. An EPA memo on auto body refinishing allows a 37 % reduction for the federal rule. Maryland’s auto body regulation is more stringent than the national rule, which allowed MDE to take an additional 8% reduction.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissi ons from automobile refinishing is:

EMP J x EF AR x [ 1- (RE x RP x CE)] E AR = 260 - E Point Source AR Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation70 Where:

E AR = VOC emissions in tons per day from auto refinishing

EMP J = Number of employees in county j for SIC 7532 (auto refinishing), from County Business Patterns

EF AR = VOC emission factor for auto refinishing

E Point Source AR = Point source emissions from auto body refinishing

2002 Example Calculation Auto Refinishing (Baltimore County)

594 44 x 0.3858 45 x [ 1- (1.0 x 1.0 x .08)] E AR = 260 - 0.00

210.832 E AR = 260 - 0.00

E AR = 0.811 Tons VOC / day

44 Employee data from County Business Patterns - Maryland

45 Emission factor from EIIP Chapter 13 – Auto Body Refinishing71 4.1.2.5 Traffic Markings SCC: 24 01 008 000 - Traffic paints SCC: 24 01 008 999 - Traffic paint solvents

Traffic paints are used to mark pavement, the majo rity of which is used to create dividing lines for traffic lanes. These markings are applied by state or local highway maintenance crews or by contractors. VOC emissions result from the evap oration of organic solv ents during and shortly after the application of the marking paint. Al l traffic paint emissions are included in the area source inventory.

VOC

MDE staff were not able to ut ilize EPA's recommended "pounds per lane-mile painted" emission factor due to the fact that several jurisdictions did not keep records on lane-miles painted. Instead MDE surveyed agencies for gallons of paint used and the VOC content of the paint used.

Activity The Maryland State Highway Ad ministration (SHA) keeps data on gallons of traffic marking paint used by district and not by indi vidual county. For emissions from SHA line painting, each county’s proportion of the total di strict’s lane miles was multiplied by total gallons painted in a district to get an estimat ed amount of gallons used for each county. In a few counties, SHA does all th e line painting. Also, da ta was collected from the Maryland Aviation Addministration (MAA) a nd the Mass Transit Addministation (MTA).

MDE was able to gather information on gall ons of traffic paint used during the ozone season and during a year. The Material Safety Data Sheets and Environmental Data Sheets were collected for each paint and solvent used by each local jurisdiction and State agency doing the striping. It was necessary to colle ct data on yellow and white paint separately because the amount of VOCs per gallon is different for each type of paint.

The emission totals are slightly lower than in previous inventories because many jurisdictions have switched to latex (water-b orne) paints for traffic marking, and those areas already using latex paints have switched to using a late x paint that is lower in VOC content than what was previously used. The widespread use of latex paints means that there are no longer any emissions from the solvents used to clean painting equipment when oil based paints are used. Description

Pollutants

Method and Data Sources72 The following information was collected from all public agencies using traffic marking paint in Maryland:

Gallons of yellow traffic pain t and solvent used in 2002. Gallons of white traffic pain t and solvent used in 2002.

The MSDS and Environmental Data Sheets per type of paint provided the following information:

• Percent volatile by weight

• Percent water by weight

• Percent volatile organic compounds by weight

• Total VOC (lbs./gal)

• VOC/gallon less water

Emission Factor

No subtraction of emissions from point sources is necessary.

MDE surveyed the various state agenicies that a pply coatings to road surfaces and transportation projects. MDE collected data on the gallons of pa int applied and the VOC content of the paint. MDE made emission estimates based on this data a nd therefore no controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

Traffic Paint Sample Calculation (Caroline County) Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation73 (1) Calculate VOC emissions from yellow a nd white traffic paints for ozone season

a. State Highway Administrati on (SHA) Traffic Paint Use

Total yellow gallons used April - October 46 = 4,671 gallons Total VOC per gallon of yellow paint used 47 = 0.78 lbs. VOC /gallon Total white gallons us ed April – October 48 = 6,481 gallons Total VOC per gallon of white paint used 49 = 0.77 lbs. VOC /gallon

(4,671 gallons) x (0.78 lbs. VOC /gallon) E Yellow Paint = (2,000 lbs./ton) x (214 days / ozone season)

E Yellow Paint = 0.0085 tons / ozone day

(6,481 gallons) x (0.77 lbs. VOC /gallon) E White Paint = (2,000 lbs./ton) x (214 days / ozone season)

E White Paint = 0.0117 tons / ozone day

E Local Paint Total = E Yellow Paint + E White Paint

E Local Paint Total = 0.0085 + 0.0117

E Local Paint Total = 0.0202 tons / ozone day

b. Maryland Aviation Administration (MAA) Traffic Paint Use

The MAA did not apply any pa int in Caroline County.

c. Maryland Transportation Administ ration (MTA) Traffic Paint Use

The MTA did not apply any pa int in Caroline County.

d. Local Jurisdiction Traffic Paint Use

The Local Jurisdictions did not appl y any paint in Caroline County.

46 Reported by Caroline County's Department of Public Works, Division of Highways

47 MSDS from Caroline County's Department of Public Works, Division of Highways

48 Reported by Caroline County's Department of Public Works, Division of Highways

49 MSDS from Caroline County's Department of Public Works, Division of Highways74 (2) Calculate VOC emissions from paint cleaning solvent use for ozone season

a. Local Jurisdiction Traffic Paint Use

The Local Jurisdictions did not use any paint cleaning solvents in Caroline County.

b. State Highway Administration (SHA) Solvent Use - None

The SHA did not use any paint cleaning solvents in Caroline County.

c. Maryland Aviation Administration (MAA) Solvent Use - None

The MAA did not use any paint cleaning solvents in Caroline County.

d. Maryland Transportation Admini stration (MTA) Solvent Use - None

The MTA did not use any paint cleaning solvents in Caroline County.

(3) Total VOC emissions from traffic paint us e and paint cleaning solvent use for ozone

season

E Paint Total = E Local Paint Total + E SHA Paint Total + E MAA Paint Total + E MTA Paint Total + E Paint Solvent

E Paint Total = 0.0202 + 0.0 + 0.0 + 0.0 + 0.0

E Paint Total = 0.020275 4.1.2.6 Industrial Surface Coating

Industrial surface coatings are ap plied during the manufacture of a wide variety of products, including furniture, cans, automobiles, other tr ansportation equipment, machinery, appliances, metal coil, flat wood, wire and other miscellane ous products. In addition, coatings are used in maintenance operations at industrial facilities but these are considered paint sources.

VOC

MDE used the methods and procedures documented in EIIP 50 , Chapter 8, Industrial Surface Coatings, dated September 1997. Applicable poi nt source emissions (those within the same NAICS) taken from the MDE/ARMA registration f iles have been subtracted from the emissions calculated on a per capita and per employee basis that are presented below.

Activity The choice between using per capita factors an d per employee factors in categories where a choice of factors was offered was made base d on the quality of data. County Business
Patterns lists employee data by North American Industry Classification System (NAICS). Many values are based on actual data. Howeve r, some county NAICS list a range for the number of employees through a letter code. In th is case the arithmetic average number of employees per letter code per c ounty was adjusted so that the state total employment in a NAICS matched the sum of the number of employees reported per county. For those categories where all or most of the employment data was listed as a range, the per capita factor was assumed to be more reliable and was used to calculate emissions. The U.S. Census Bureau reports populat ion statistics for the countie s of Maryland. Population statistics for 2002 for the counties of Maryla nd were collected from the U.S. Census Bureau Internet address ( http://www.census.gov ).

Because the emission factors were develope d based on NAICS empl oyment data and 2001 was the last year employment data was av ailable per NAICS, MDE used the 2001 County Business Patterns as the sour ce for employment figures.

Emission Factor Per employee factors were used for the following SIC and NAICS because they are generally more reliable (see Procedures , Table 4-10.1), and a comparison with per capita emissions in one county showed that for these SICs, the per capita factors led to a large overestimation of emissions.

50 Emission Inventory Improvement Program Description

Pollutants

Method and Data Sources76 Industry SCC SIC NAICS

Factory Finished Wood 24 01 015 000 2426, 2427, 2428, 2429, 2430, 2440, 2450, 2493, 2499 32121

Metal Furniture and Fixtures 24 01 025 000 2500 33636, 33791, 33792, 337121, 337122, 337124, 337125, 337127, 337129, 337211, 337212, 337214, 337215, 339111, 339942 Machinery and Equipment 24 01 055 000 3500 33272 Other Transportation Equipment 24 01 990 000 3700 except 3711
and 3730 333924

Marine Coatings 24 01 080 000 3730 48839, 81149, 336611, 336612

NAICS were used that best corresponded to SIC for each source category so that emission factors that were generated from E IIP SIC data could be used. EPA provided the correlation between NAICS and SIC. Emi ssion factors are listed in Table 8.5-1 in the EIIP Industrial Surface Coating document and below. As an example, MDE has chosen finished wood for presentation of an equa tion and emissions by county. The EIIP document lists no seasonal adjustment factor and 5 days per week activity. For counties with no employees listed in Count y Business Patterns 2001- Maryland , MDE assumed no emissions were generated because these proce sses were not located in those counties.

Appliances (SIC 363) , and Electrical Insulation (SIC 3357,3612) , had no employees listed in County Business Patterns in Maryland, thus no emissions were calculated. Emissions from New Motor Vehicles (SIC 3711) , were assigned to the point source section of the inventory since they are all from the General Motors Truck and Bus Group in Baltimore City.

Industry VOC Emission Factor (lbs. VOC /employee/year) Factory Finished Wood 131
Metal Furniture and Fixtures 944 Machinery and Equipment 77 Other Transportation Equipment 35 Marine Coatings 308 Appliances 463
Electrical Insulation 290
New Motor Vehicles 79477 Applicable point source emi ssions (those within the same SIC or NAICS) taken from the MDE/ARMA registration files ha ve been subtracted from the calculated emissions, and their emissions are separated from the totals presented below.

MDE surveyed the various state agenicies that a pply coatings to road surfaces and transportation projects. MDE collected data on the gallons of pa int applied and the VOC content of the paint. MDE made emission estimates based on this data a nd therefore no controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

Equation:

EMP i x EF FW

E FW = 2000 x 260

Where:
E FW = VOC emissions in t ons per day from finished wood
EMP i = employees in county i employed in NAICS 32121.
EF FW = VOC emission factor for finished wood which is 131 lbs. VOC per employee per year

To adjust for control efficiency, etc.:

E FWA = (E FW - E FWR ) x [1

- (CE x RE x RP)] where:

E FWA = finished wood adjusted emissions Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation78 E FWR = emissions from factory finished wood sources in ARMA re gistration files that emit more than 10 tons per year VOC

CE = Control Efficiency RE = Rule Effectiveness RP = Rule Penetration

2002 Example Calculation Industrial Surface Coa ting – Machinery Coating (Baltimore County)

Number of employees in NAI CS 33272 in Baltimore County (2001 County Business Patterns ): 4543

Emission factor for other transportation equipment (lbs. VOC/employee/year): 77 51

5 days per week activity level, no seasonal adjustment factor

(4543 x 77) x [1 – (0 * 1.00 * 1.00)] E MC – Baltimore = (260 x 2000)

E MC – Baltimore = 0.6727 tons VOC per day

Adjusting for registered point sources:

E MC-ADJ – Baltimore = E MC – Baltimore - E MC Pt. Sources - Baltimore 52

E MC-ADJ – Baltimore = 0.6727 – 0.00
E MC-ADJ – Baltimore = 0.6635 tons VOC per day

51 Table 8.5-1, EIIP Chapter 8 Industrial Surface Coatings

52 Point Source Reduction from JCB Incorporated (SIC 3531)79 Industrial Surface Coating- per Capita Emissions

The following sources had their emissions calc ulated by per capita emission factors because employment data was not definitive.

Industry VOC Emission Factor (lbs. VOC /person/year)

Metal Cans 1.3 Misc. Manufacturing 0.6
Industrial Maintenance 0.8 Other Special Purpose Coatings 0.8
Misc. Finished Metals 0.5

Equation:

POP i x EF MFM E MFM = 2000 x 260 x [1 – (CE x RE x RP)]

where:
E MFM = VOC emissions in tons per day from miscellaneous finished metals
POP i = 2002 population of county i
EF MFM = VOC emission factor for mi sc. finished metals (0.5 lbs. VOC per person per year) CE = Control Efficiency RE = Rule Effectiveness RP = Rule Penetration80 To adjust for Point Sources:
E MFMA = (E MFM - E mfmar )

Where:
E MFMA = adjusted emissions fr om miscellaneous finished metals
E MFMAR = emissions from miscellaneous finished metal coating facilities in ARMA registered premise files

2002 Per Capital Sample Calculation for Misc. Manufacturing Coating in Anne Arundel County

503,388 53 x 0.6 lbs. VOC/capita/year 54 x [1 – (0.0 x 1.0 x 1.0)] = 302,032.8 lbs. VOC per person

Converting to tons per day: 302,032.8 / (260 days per year x 2000 lbs. per ton) = 0.5808 tons VOC per day

53 2002 estimated population from U.S. Bureau of the Census, Population Estimation Branch .

54 Emission factor from EIIP Industrial Surface Coating81 4.1.2.7 Industrial Adhesives and Sealants
SCC: 2440020000

Industrial adhesive and sealant surface coating is the application of a liquid or powder substance, such as solvent type paints, varnishes, and l acquers to a surface for decorative or protective purposes. The substances can be applied by brushing, rolling, spraying, dipping or flow coating. VOCs are released into the air as the substance dries. Powder coatings are applied to a hot surface and then melted; VOCs are released as the powder melts and dries.

VOC

MDE staff used EPA’s “Solvent Mass Bala nce” methodology for estimating emissions from nonpoint solvents, which uses the total solven t production and sales fo r a particular source category to estimate overall emissions then subtr acting out emissions due to point sources, waste management, and recycling.

Activity

EPA used the Freedonia 55 market research report on nonpoi nt solvents to obtain solvent utilization data for this source category. Some solvent usage estimates came from a National Paint and Coating Association (NP&CA) 56 . A brakedown of the methods used to derive the data for painting and coating sources are described in the report and is attached as section 3.4.1 Industrail Adhesives and Sealants . VOC emission estimates were then allocated to the state and county levels a nd adopted by MDE for this source category.

55 Data were estimated from Freedonia Group, Inc. - Freedonia Reports from 1999 and 2004

56 National Paint and Coating Association (N P&CA) “Paints and Coatings ‘2000': Review
and Forecast” Description

Pollutants

Method and Data Sources82 4.1.2.8 Graphic Arts
SCC: 24 25 000 000

Graphic arts includes operations that are involv ed in the printing of newspapers, magazines, books and other printed materials. There are six basic operations used in graphic arts: lithography, gravure, letterpress, flexography, screen printing and metal decorating. Lithography accounts for nearly half of all graphic arts operations.

VOC

MDE staff used an alternative per capita emission estimation method documented in EIIP 57

, Chapter 7, Graphic Arts, dated November 1996. The EIIP methodology recommended an emission factor of 1.3 lbs. VOC per capita per year emission fact or (EPA, 1991) for graphic arts sources emitting less than 100 tons VOC per year. An activity level of 5 days per week was used with no seasonal adjustment factor as r ecommended in Table 5.8-1 in Procedures . Any point source graphic arts facility (SIC 275) in the ARMA re gistration files that had 2002 emissions of between 10 and 100 tons VOC per year had its emissions subtracted from the area source inventory.

Activity The estimated percentage of market share, reported in Table 7.2-3 of the EIIP document and reproduced below, was used to allocate th e total graphic arts emissions to specific printing types. Maryland has different regulations regarding specific types of printing operations and thus to calculate controlled em issions the estimated percentage that each type of printing operation contributes to the total had to be determined.

Type of Printing Estimated Percentage of Product Market Share Rotogravure 18 Flexography 18 Offset Lithography 47 Letterpress 8
Screen 3
Plateless 3

Emission Factor 1.3 lbs. VOC per capita per year

57 Emission Inventory Improvement Program Description

Pollutants

Method and Data Sources83 Graphic arts emissions from facilities identified as point sources were subtracted from the area source inventory to avoid double counting.

Control efficiency is based on Maryland regulati ons for each type of printing process and has been developed within technica l support documents for the gra phic arts printing regulations. Rule penetration has been defined as the estim ated percentage that each type of printing operation. Rule effectiveness has been assi gned the EPA default value of 80 per cent.

Lithographic Rotogravure Flexographic Screen Rule Effectiveness (RE) 0.800 0.800 0.800 0.800 Rule Penetration (RP) 0.640 0.180 0.180 0.050 Control Efficiency (CE) 0.750 0.630 0.540 0.350 Reduction factor (RE x RP x CE) 0.3840 0.0907 0.0778 0.0140

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissions from graphic arts is:

Equation:

POP i x EF GA E GA = 2000 x 260 x [ 1 - RF L – RF R – RF F – RF S ]

Where:

E GA = VOC emissions in tons per day from graphic arts
POP i = 2002 population of county i
EF GA = VOC emission factor fo r graphic arts (1.3 lbs. VOC per person per year) Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation84 RF L = Reduction Factor for Lithographic Printing
RF R = Reduction Factor for Rotogravure Printing
RF F = Reduction Factor for Flexographic Printing
RF S = Reduction Factor for Screen Printing

To adjust for point sources emitting below 100 tons per years:

E GAA = (E GA - E GAR )

Where:

E GAA = adjusted emissions
E GAR = emissions from printers in MDE/ARMA re gistered premise files th at emit more than
10 tons VOC /year85 2002 Example Calculation Graphic Arts (Anne Arundel County)

E GA = 503,388 58 x 1.3 lbs. VOC /capita/year 59 x [1 – 0.384 – 0.0907 – 0.0778 – 0.014]
E GA = 283684.3 lbs. VOC per person

Converting to tons per day:
E GA = 283684.3 / (260 days per year x 2000 lbs. per ton)
E GA = 0.5455 tons VOC per day

Adjusting for registered point sources emitting between 10 and 100 tons per year:
E GAA = (E GA - E GAR )
E GAA = 0.5455 – 0.1035
E GAA = 0.4420 tons VOC per day

58 2002 estimated population from U.S. Bureau of the Census, Population Estimation Branch .

59 Emission factor from EIIP Chapter 7 Graphic Arts86 4.1.2.9 Asphalt Paving
SCC: 24 61 022 000

The two types of asphalt paving used for road paving and repair are cutback asphalt and emulsified asphalt. Cutback asphalt is a liquefied road surface prepared by blending (or "cutting back") asphalt cement with diffe rent petroleum distillates. Th e second type, emulsified asphalt, is also a liquefied road surface, but is prepared with a water/soap mixture instead of petroleum distillates. Cutback asphalt emits more VOCs, and its use has been limited in Maryland to the non-ozone period of April 15 to October 15.

VOC

MDE calculated emissions from this category ba sed on a per capita emission factor of 0.004 pounds VOC per person per year for emulsified as phalt from the Short List of AMS SCCs and
Emission Factors prepared by EPA's National Air Data Branch. All emissions from this source are reactive VOC. An activity le vel of 5 days a week and no seasonal variation were assumed. State of Maryland Department of Environment regulations (COMAR 26.11.11.02B), prohibit use of cutback asphalt paving from April 15 to October 15 so ozone precursor emissions from cutback asphalt application were not calculated. Cutback asphalt is made by blending asphalt cement with petroleum distillates that evapor ate when the road surface is "cured" after application. Emulsified asphalt is asphalt cement mixed with a blend of water and an emulsifier, usually soap. The equations for calculating VOC emissions from emulsifi ed asphalt paving are presented below.

Activity The U.S. Census Bureau reports population statistics for the counties of Maryland. Population statistics for 2002 for the counties of Maryland were collected from the U.S. Census Bureau Internet address ( http://www.census.gov ).

Emission Factors: Emulsified Asphalt 0.004 pounds VOC per person per year

No subtraction of emissions from point sources is necessary.

State of Maryland Department of Environment regulations (COMAR 26.11.11.02B), prohibit use of cutback asphalt paving from April 15 to October 15 so ozone precursor emissions from Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls87 cutback asphalt application were not calculated. Cutback asphalt is made by blending asphalt cement with petroleum distillates that evapor ate when the road surface is "cured" after application. Emulsified asphalt is asphalt cement mixed with a blend of water and an emulsifier, usually soap.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The per capita equation used to estima te emissions from asphalt paving is:

POP i x EF EA E EA = 2000 x 260 Where:

E EA = VOC emissions in tons per day from emulsified asphalt
POP i = 2002 population of county i
EF EA = VOC emission factor for emul sified asphalt which is 0.004 lbs. VOC per person per yr

2002 Emulsified Asphalt Sample Calculations: Anne Arundel County

• No seasonal variation assumed

• Activity of five days per week

• Emission factor of 0.004 lbs. VOC/person/year

503,388 (2002 County Population) x 0.004 = 0.0039 tons VOC per day 2000 lbs. per ton x 260 days per year

503,388 60 x 0.004 lbs. VOC/capita/year 61 = 2,013.552 pounds per person VOC emitted

Converting to tons per day: 2,013.552 / (260 days per year x 2000 lbs. per ton) = 0.0039 tons VOC per day emitted

60 Population data from U.S. Bureau of the Census, Population Estimates Branch

61 Emission factor from the Short List of AMS SCCs and Emission Factors from EPA National Air Data Branch. Spatial and Temporal Allocations

Emissions Calculation88 4.1.2.10 Synthetic Organic Chemical Storage Tanks

This category is fully represente d in the point source inventory.89 4.1.2.11 Pesticide Application
SCC: 24 61 800 000

Pesticides are substances or mi xtures used to control plant an d animal life for the purposes of: agricultural production, public heal th from pest-borne disease, reducing property damage due to pests, and improving the aesthet ic quality of outdoor and ind oor surroundings. Agriculture, homeowners, industry, and governme nt agencies use pesticides. Th e largest usage of pesticides by weight is in agriculture. Agricultural pe sticides control weeds, insects, mites, fungi, nematodes, and other threats to the yiel d, quality, or safety of food production.

Emissions arise from pesticide use because of the volatile nature of many ingredients, solvents, or other additives used in the fo rmulations. Many pesticide formul ations use solvents as carriers for more active organic or inorga nic ingredients. In pesticid e formulations, the organic or inorganic solute is the "active ingredient" (AI), wh ile the solvent carrier is the "inert carrier." Thus, the terms "active" and "inert" in pesticide formulations refer to t oxicological action, and are not indicators of photochemical activity. Bo th the active and inert ingredients in these formulations evaporate and c ontribute to VOC emissions.

VOC

Maryland Agricultural Statistics service in cooperation with the Pesticide Regulation Section of the Maryland Department of Agriculture compiled information for Maryland's 2000 pesticide statistics document. The document, Maryland Pesticide Statistics for 2000 , reported pesticide usage in pounds used in a year by active ingr edient for each Maryland county. Along with the pounds of AI applied, the document also listed th e form of many pesticid es and the formulation of some selected pesticides. From this, MD E used the EIIP’s emission inventory reference document titled Pesticides – Agricultural and Nonagricultural , December 1997, Section 9.2.2 to generate the VOC emissions for the active ingredie nt and inert carrier of the pesticide. This required assumptions and other refere nces to collect the best inform ation used in the calculations.

The EPA method for estimating pesticide emissions uses a six-step procedure, as follows: 1. Determine both the application method and the quantity of pesticide product applied. 2. Determine the type of formulation used. 3. Determine the specific AI(s) in the formulation and their vapor pressure(s). 4. Determine the percentage of the AI (or each AI) present. 5. Determine the VOC content of the formulation. 6. Calculate the emissions. Description

Pollutants

Method and Data Source:90 MDE slightly deviated from this method, sin ce information was presented to MDE in pounds of active ingredient. With the activ e ingredient, the vapor pressure and general application method (surface application or soil incorporation) was determined from the EPA's AP-42 document or The SCS/ARS/CES Pesticide Properties Data base For Environmental Decision-Making , by R. D. Wauchope, et al. Then the form (i.e. wettable powder, emulsified concentrate, granule, etc.) of the most likely pesticide was determined from a list in the Maryland Pest icide Statistics for 2000

. Also, the statistics listed some formulations, for example 80% inert, 20% AI. Most of the formulations were assumptions based on the inform ation provided with the form of the pesticide in the Maryland Pesticide Statistics for 2000

.

The table below lists the EIIP emissions factors taken from AP-42 (Table 9.2.2-4) used to calculate this category.

Uncontrolled Emission Factors fo r Pesticide Active Ingredients

Vapor Pressure Range Emission Factor

(mm Hg at 20 ° to 25 ° C) kg/Mg lbs./ton

Surface Application

1 x 10 -4 to 1 x 10 -6 350 700

> 1 x 10 -4 580 1160

Soil Incorporation

< 1 x 10 -6 2.7 5.4

1 x 10 -4 to 1 x 10 -6 21 42

> 1 x 10 -4 52 104

Equations:

E pest = VOC Emissions from Active Ingredient (AI) + VOC Emissions from the Inert Ingredients (Inert).

VOC Emissions Active Ingredients (AI) = (lbs AI / year) x (lbs VOC / lb AI )

VOC Emissions Inert Ingredients = [(lbs AI / year) / % AI] x % In ert Ingredients x % VOC INERT INGREDIENTS

(lbs AI/year) x EF AI in lbs VOC/ton AI (lbs AI/year) E pest = 2000 lbs. Per ton + (1 - % Inert) x (% Inert) x (% VOC in Inert)

Annual Emissions Daily Emissions = 312 days / year x Seasonal Adjustment Factor91 where: AI = Active Ingredient ( lbs. / yr. )
EF AI = Emission Factor ( lbs. VOC / ton AI ) % inert = percentage of formulati on that contains the Inert Carrier % VOC in the inert = percentage of VOCs in the Inert Carrier portion of the pesticide SAF = seasonal adjustment factor of 1.3 to adjust for the summer ozone season

MDE assumed six working days per week and 100% volatilization of the VOC portion of the inert carrier.

Sample Calculations:

The following information was compiled from The Maryland Pestic ide Statistics for 2000 and The SCS/ARS/CES Pesticide Properties Data base for Environmental Decision-Making :

Table 3-26 Allegany County Pesticide Information

VOC
V. Press Formulation Formula % VOC EF Alleg. Alleg.

Pesticide mm Hg Applicatio n Type (% Inert) Inert lbs. VOC/
lbs. A.I. lbs of A.I. Lbs/yr

2,4-D 8E-06 foliar spray gas 0.8 0.29 0.35 2,058 3107.580 Acephate 1.7E-06 crop spray gas 0.8 0.29 0.35 62 93.620
Alachlor 1.4E-05 soil spray gas 0.15 0.29 0.35 19 7.622
Amitrole 4.40E-07 foliar spray gas 0.784 0.29 0.35 6 8.416
Atrazine 2.89E-07 soil surface wp 0.8 0.25 0.35 478 645.300 Azinphos-Methyl 2E-07 crop spray ec 0.35 0.56 0.35 33 21.501 Azoxystrobin crop spray gas 0.77 0.29 0.35 1 1.321 Bacillus thuringiensis neg crop spray gr 0.96 0.25 0.35 107 679.450 Benomyl 1E-10 crop spray wp 0.8 0.25 0.35 9 12.150
Bifenthrin 1.8E-07 crop spray gas 0.1 0.29 0.35 2 0.764
Boric Acid 0.0001 spray wp 0.1 0.25 0.35 4 1.511 Captan 8E-08 crop spray gas 0.5 0.29 0.35 727 465.280 Carbaryl 1.2E-06 crop spray gas 0.5 0.29 0.35 93 59.520
Carbofuran 6E-07 foliar spray fog 0.56 0.39 0.35 1 0.846
Chloroneb 0.003 spray wp 0.35 0.25 0.58 17 12.148
Chlorothalonil 1E-03 crop spray gas 0.8 0.29 0.58 368 640.320 Chlorpyrifos 1.7E-05 soil incorporation gas 0.15 0.29 0.021 36 2.598

Clomazone 1.4E-04 soil incorporation ec 0.3 0.56 0.052 3 0.876

Clopyralid 0 foliar spray gas 0.8 0.29 0.35 1 1.510 Cyanazine 1.6E-09 crop spray dust 0.8 0.21 0.35 31 36.890 Cyfluthrin 1.6E-08 crop spray wp 0.3 0.25 0.35 153 69.943 Cypermethrin 1.4E-09 crop spray wp 0.3 0.25 0.35 5 2.286
Diazinon 6E-05 crop spray pellet 0.143 0.27 0.35 21 8.296
Dicamba 0 spray gas 0.8 0.29 0.35 126 190.260
Dichlobenil 1E-03 crop spray wp 0.8 0.25 0.58 3 4.740
Dicofol 4E-07 crop spray wp 0.3 0.25 0.35 25 11.42992 VOC
V. Press Formulation Formula % VOC EF Alleg. Alleg.

Pesticide mm Hg Applicatio n Type (% Inert) Inert lbs. VOC/
lbs. A.I. lbs of A.I. Lbs/yr

Diflubenzuron 9E-10 crop spray wp 0.25 0.25 0.35 80 34.667
Dimethenamid > 1.0 soil spray gas 0.468 0.29 0.35 5 3.026
Diuron 6.9E-08 soil surface wp 0.8 0.25 0.35 310 418.500
Endosulfan 1.7E-07 crop spray gas 0.5 0.29 0.35 2 1.280
Esfenvalerate 1.1E-08 crop spray dust 0.3 0.21 0.35 7 3.080
Fenarimol 2.2E-07 crop spray wp 0.3 0.25 0.35 1 0.457
Flumetsulam ND spray aq 0.18 0.21 0.35 12 4.753
Fluvalinate 1E-07 crop spray rtu 0.8 0.2 0.35 69 79.350
Fosamine Ammonium 4E-06 foliar spray aq 0.8 0.21 0.35 8 9.520 Glyphosate 0 foliar spray aq 0.8 0.21 0.35 2,610 3105.900 Hydroprene ? ? gr 0.09 0.25 2 0.049 Imidacloprid 1.50E-09 spray aq 0.786 0.21 0.35 1,426 1598.986 Iprodione 1E-07 crop spray wp 0.8 0.25 0.35 24 32.400 Lambda-cyhalothrin 1.50E-09 spray ec 0.87 0.56 0.35 8 32.782
MCPP 0 foliar spray aq 0.5 0.21 0.35 49 27.440
Malathion 8E-06 contact spray ec 0.3 0.56 0.35 7 4.130
Mancozeb 0 crop spray Fl aq conc 0.8 0.21 0.35 165 196.350
Maneb 0 crop spray wp 0.8 0.25 0.35 26 35.100 Metalaxyl 5.62E-06 soil spray wp 0.25 0.25 0.35 7 3.033
Metam-Sodium 20 soil spray aq 0.8 0.21 0.58 334 474.280 Methoprene 17.5 spray aq 0.8 0.21 0.58 26 36.920 Methoxychlor 0 spray wp 0.25 0.35 3 1.050 Methyl Bromide 1824 release of gas Fl aq conc 0.8 0.21 0.58 58 82.360
Metolachlor 3.135E-05 soil spray ec 0.3 0.56 0.35 488 287.920
Metribuzin 1E-05 soil surface Fl aq conc 0.75 0.21 0.35 3 2.940 Metsulfuron Methyl 2.5E-12 foliar spray gr 0.2 0.25 0.35 1 0.413
Nicosulfuron 1.20E-16 grass spray gr 0.162 0.25 0.35 2 0.797 Oryzalin 1E-08 soil spray wp 0.75 0.25 0.35 77 84.700
PCNB 1.1E-04 soil spray wp 0.6 0.25 0.58 88 84.040
Paclobutrazol 6.00E-10 spray wp 0.5 0.25 0.35 13 7.800 Paraquat 0 target spray aq 0.8 0.21 0.35 124 147.560
Pendimethalin 9.4E-06 soil spray ec 0.6 0.56 0.35 1,257 1495.830
Permethrin 1.3E-08 crop spray ec 0.3 0.56 0.35 9,455 5578.450
Petroleum Oils 1.0E-03 spray ec 0.56 0.58 1,503 871.740
Phosmet 4.9E-07 crop spray wp 0.5 0.25 0.35 26 15.600
Picloram Neg foliar spray aq 0.8 0.21 0.35 252 299.880 Primisulfuron-methyl 1.50E-05 crop spray gr 0.49 0.25 0.35 2 1.180 Propachlor 7.90E-05 spray gr 0.35 0.25 0.35 2 0.969 Propoxur 9.7E-06 crop spray ec 0.3 0.56 0.35 2 1.180 Quizalofop-ethyl 3E-07 foliar spray ec 0.2 0.56 0.35 1 0.490 Sethoxydim 1.6E-07 foliar spray ec 0.3 0.56 0.35 1 0.590
Simazine 2.21E-08 soil spray wp 0.8 0.25 0.35 776 1047.600
Sulfentrazone spray gr 0.25 0.25 0.56 1 0.643 Sulfometuron Methyl 6E-16 soil spray gr 0.2 0.25 0.35 7 2.888
Sulfur 0 dust dust 0.2 0.21 0 96 5.040
Terbacil 3.1E-07 soil spray wp 0.8 0.25 0.35 4 5.400 Thifensulfuron methyl 1.3E-10 foliar spray gr 0.2 0.25 0.35 1 0.413 Thiophanate-methyl 1E-07 crop spray wp 0.5 0.25 0.35 37 22.200
Triadimefon 1.5E-08 crop spray wp 0.8 0.25 0.35 7 9.45093 VOC
V. Press Formulation Formula % VOC EF Alleg. Alleg.

Pesticide mm Hg Applicatio n Type (% Inert) Inert lbs. VOC/
lbs. A.I. lbs of A.I. Lbs/yr

Trichlorfon 2E-06 crop spray sp 0.8 0.12 0.35 36 29.880 Triclopyr 1.26E-06 foliar spray ec 0.8 0.56 0.35 454 1175.860
Trifluralin 1.1E-04 soil incorporation ec 0.015 0.56 0.052 3 0.182

Vinclozolin 120.0099 spray ec 0.5 0.56 0.58 16 18.240 Zinc Phosphide 0 powder pellet 0.8 0.27 0 1 1.080 County Total 24529 23472.544

Emissions are calculated for each pesticide ac tive ingredient per county and then summed.

Example calculation for the emissions from Pendi methalin pesticide use in Allegany county.

Lbs lbs. VOC 1257 Emis

Pendimethalin 1257 year x 0

lbs. AI + (1-0.6) x 0.6 x 0.56

Emis

Pendimethalin = 1495.83 lbs. VOC / year

Emis

Pendimethalin = 1495.83 / 2000 = 0.7479 tons VOC / year

Emis

Pendimethalin = (0.7479 tons VOC / year) * (1 year / 312 days) * (1.3)

Emis

Pendimethalin = 0.0031 tons VOC / day

The remaining pesticides used in Allegany c ounty are calculated in a similar manner.

Results: Since the EPA has released new guidance on the calcu lation of agricultural pesticide application, the new methodology vastly differs from the me thod used in 1990. In the Maryland Ozone Precursor Inventory for 1990 , Air and Radiation Management, MDE, September 1993, pesticide application for the state totaled 42 tons per day. This method assumed 90% volatilization of the AI. The method also assumed the inert carrier content to be 145% by weight of the AI. Another major assumption is 100% volatilization of the inert carrier.

Since publication, the accuracy of the old pesticide methodology ha s been debated by different groups. General thoughts from scholars and priv ate industry is the ol d methodology overpredicts the volatility of the organics in the pesticid e. The new methodology, presented here, requires many assumptions and uses data that takes account for the different vapor pressures of individual active ingredients. Th is method, along with some genera l assumptions, estimated pesticide emissions at 8.7 tons per day for the state. Th e decrease is due to th e change in method, along with a decline in pounds of pes ticides applied in the state.94 4.1.2.12 Commercial/Consumer Solvent Use
SCC: 24 65 000 000

Certain commercial/consumer uses of products containing volatile organi cs cannot easily be identified by questionnaires, su rveys or other inventory proced ures yielding locale-specific emission estimates. This category includes th e following sources: household products, toiletries, aerosol products, rubbing compounds, windshield washing fluid, polishes, waxes, non-industrial adhesives, space deodorants, moth control agents and laundry detergents.

VOC

The recommended emission factor that combines emissions from all these sources is 7.84 pounds VOC per person per year, from EIIP Volume III , Area Sources, Preferre d and Alternate Methods (July, 1997). This emission factor excludes non -reactive VOC and takes into account more recent volatility levels based on product reformulation, than does AP-42 , Fifth Edition. MDE used an activity level of 7 days a week and no seasonal adjustment factor as suggested in Table 5.8-1 in Procedures

.

Activity The U.S. Census Bureau reports population statistics for the counties of Maryland. Population statistics for 2002 for the counties of Maryland were collected from the U.S. Census Bureau Internet address ( http://www.census.gov ).

Emission Factors: Commercial and Consumer Products (All) 7.84 lbs. VOC /person/year

No subtraction of emissions from point sources is necessary.

Federal regulations provide a 20 percent reduction in emissions from a 3.9 lbs. VOC /person subset of the total commercial and consumer products category.

Spatial Data for spatial allocation is not available for this source. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations95 Temporal Data for temporal allocation is not available for this source.

The per capita equation used to estimate emissi ons from commercial and consumer solvents is:

[ POP i x EF CC ] - [ (POP i x CS CC ) x CE CC ] E CC = 2000 x 365

Where:

E CC = VOC emissions in tons per day from commercial and consumer solvents
POP i = 2002 population of county i
EF CC = VOC emission factor for commercia l and consumer solvents (7.84 lbs. VOC /person)
CS CC = Controlled subset of commercial and consumer solvents (3.9 lbs. VOC /person)
CE CC = Control efficiency for controlled subset of commercial and consumer solvents (20%)

2002 Sample Calculation Commercial/Cons umer Solvent Use (Anne Arundel County)

[ (503,388 62 ) x (7.84 63 ) ] - [ (503,388 x 3.9 64 ) x (0.20) 65 ] E CC = 2000 x 365

E CC = 4.868 tons VOC per day

62 Population data from U.S. Bureau of Census, Population Estimates Branch

63 Emission factor from EIIP Chapter 5 Commercial and Consumer Solvent Use

64 EPA memo from John Sietz

65 EPA memo from John Sietz Emissions Calculation96 4.1.2.12.1 Barge, Tank, Tank Truck, Rail Car and Drum Cleaning

SCC: 24 61 160 000

The EPA explained to MDE staff that the agency has not developed an emission factor for this category. The EPA also stated that most barge, tank truck, rail car and drum cleaning is done by steam cleaning and the residue goes to industrial and public waste disposal treat ment plants. It is impossible to separate this category's portion of the treatment plant emissions. The EPA considers the emissions from this category to be insignificant. Emissions from this category are calculated for the appropriate facilities in the point source inventory.

4.1.3 BIOPROCESS EMISSIONS SOURCES

4.1.3.1 Bakeries
SCC: 23 02 050 000

Bakeries emit VOC, primarily ethanol formed by yeast fermentation of bread or dough, during the baking process. Ethanol is emitted through a vent, along with combustion product gases. Large commercial bakeries are inventoried as poin t sources. In-store and neighborhood bakeries have lower emissions, and thus are considered area sources.

VOC

MDE staff followed methodology described in an EIIP Area Source Category Method Abstract – Bakeries, dated June 1999 and an emission factor of 0.11 tons VOC per employee cited in an April 24, 1992 Technical Memorandum prepared by Radian Corporation for EPA. Applicable point source emissions (those within the same NAICS) taken from the MDE/ARMA registration files have been subtracted from the emissions calcul ated on a per employee basis that are presented below.

Activity Employee numbers were taken from C ounty Business Patterns 2001 - Maryland , NAICS 311812, Bakery Products and 311811, Retail Bakeries. Some county employment data is represented by a letter code i ndicating a range for the number of employees for that SIC. In this case the arithmetic average number of employees per letter code per county was adjusted so that the state total employment in a SIC matched the sum of the number of employees reported per county Description

Pollutants

Method and Data Sources97 Emission Factor An emission factor of 0.11 tons VOC per employee cited in an April 24, 1992 Technical Memorandum prepared by Radian Cor poration for EPA was utilized.

Bakery emissions from faciliti es identified as point source s (NAICS 311812 and 311811) were subtracted from the area source in ventory to avoid double counting.

No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissions from bakeries is:

Equation :

EF BAK x EMPj E BAK = 260

Where:

E BAK = VOC emissions from small bakeries in tons per day
EF BAK = per employee emission factor for bakeries EMPj = number of employees at small (le ss than 20 employees), bakeries in county j Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation98 Point Source Adjustments

E BAK-ADJ = E BAK - E BAK – Pt. Sources 66

Where:
E BAK-ADJ Point source adjusted bakery emissions
E BAK Calculated area source bakery emissions
E BAK – Pt. Sources Point source emissions from MDE ARMA registration files

2002 Sample Calculation for Bakery VOC Emissions (Prince George’s County) :

Employees in NAICS 311811 in Prince George’s County: 256

0.11 x 256 E BAK = 260

E BAK = 0.108 tons VOC per day

Point Source Adjustment

E BAK – Pt. Sources (Prince George’s County) = 0.0728 tons VOC per day

E BAK-ADJ = E BAK - E BAK – Pt. Sources E BAK-ADJ = 0.1083 – 0.0728
E BAK-ADJ = 0.0355 tons VOC per day

66 Point Source Reduction from MDE ARMA registration files99 4.1.3.2 Breweries
SCC: 23 02 070 001

During the fermentation process, breweries emit ethanol and other VOCs. Although large-scale commercial breweries have been inventoried as point sources, there are microbreweries and brewpubs that emit lower levels of VOCs and therefore must be inventoried as area sources. These smaller breweries emit most of their VOC s from the fermentation room, not the brew kettle as is the case with the large breweries.

VOC

MDE/ARMA staff surveyed small brewpubs and microbreweries in Maryland.

Activity The survey questionnaire aske d the brewing facilities to provide MDE/ARMA with the amount of barrels brewed per month for the cal endar year 2002. For those facilities that reported only annual production amounts, an average monthly value was used.

Emission Factor Emissions from the small breweries were calcu lated using an emissi on factor cited in a February 5, 1992 Technical Memorandum prepared by Radian Corporation for EPA. This emission factor is 56.743 lbs. VOC per 1000 barrels produced. On e barrel equals 31 gallons.

No subtraction of emissions from point sources is necessary.

No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations100 Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissions from bakeries is:

EF BREW x BPj E BREW = 2000 x 260

Where:

E BREW = VOC emissions from small bakeries in tons per day
EF BREW = emission factor for small breweries BPj = 2002 beer production in barrels 260 = 5 days/week activity level

2002 Sample Calculation for Small Brew ery VOC Emissions (Anne Arundel County) :

Number barrels produced by microbrewe ries in Anne Arundel County: 1470.25

0.05674 x 1506.40 E BREW = 2000 x 260

E BREW = 0.000164 lbs. VOC per day Emissions Calculation101 4.1.3.3 Wineries

Ethanol emissions from wineries occur during the fermentation pr ocess. The emissions vary, depending upon the type of wine (red vs. white), the fermentation temperature and the sugar content of the grapes used.

VOC

MDE used the methods and procedures documented in AP-42 67 , Chapter 12, Beverages, Section 2, Wines and Brandies dated September 1995. AP42 Chapter 9.12.2

Activity State of Maryland Comptrollers Office and the State of Maryland Department of Agriculture informed MDE staff that in 2002 Maryland wineries produced approximately 99,701 gallons of wine. An informal survey of wineries in the ar ea suggests that 64,233 gallons of white and 57,303 gallons of red wi ne yielding approximately 121,536 gallons of wine was actually produced.

Emission Factor Table 9.12.2-1 of AP-42 shows that ethanol emissions are 1.8 lbs. VOC per 1000 gallons of white wine fermented and 4.6 lbs. VOC per 1000 gallons of red wine fermented.

No subtraction of emissions from point sources is necessary.

No controls are available for this source category.

67 AP42, Chapter 9.12.2: Food and Agricultural Industries, Beverages, Wines and Brandies Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations102 Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

Using the above figures, the production of wine by all Maryland wineries in 2002 resulted in the production of 379.2 pounds of ethanol. MDE has d ecided not to include this source in the periodic inventory due to the insignificance of the 2002 emissions.

4.1.3.4 Distilleries

Ethanol emissions are the largest component of th e VOCs emitted from distilleries. Distilleries produce both grain alcohol for industrial and fuel purposes, and distilled sp irits such as whiskey and brandy for consumption purposes. The em issions points in th e distilled spirits manufacturing process are likely to be the same as in brewerie s and wineries, with the aging process as an additional source of emissions. Du ring the aging process, ethanol and water seep through the wooden barrels used to age whiskey and evaporate into the air. Aging and barrel emptying are the major sources of VOC emissions from whiskey production.

VOC

MDE staff indicated that no distilleries below th e 10 ton per year point source cutoff operated in the inventory area during 2002. Fugitive VOC em issions from the aging process at large distillery operations can be substa ntial and will be included in the point source inventory. Emissions Calculation

Description

Pollutants

Method and Data Sources103 4.1.4 CATASTROPHIC/ACCIDENTAL RELEASES

4.1.4.1 Oil Spills
SCC: 28 30 000 000

Oil spills involve oil tanker acc idents, tanker truck accidents, and spills and blowouts from oil rigs or pipelines in coastal and inland areas. Because a wide range of fuel types may be spilled, the nature and quantity of emissions can vary. Emissions are also influenced by the clean-up procedure and by dispersion and weathering processes.

Oil spill evaporation produces local VOC emissions. If spills catch fire, additional SO2, CO, CO2, PM, NOx and VOC emissions may result. Other potentially toxic chemical compounds may also be released as a result of chemical cleanup

VOC

Activity Data on oil spills in Maryland were obtai ned from MDE's Hazardous Waste Emergency Response Department. They provided MDE/ARMA st aff a monthly list of all oil spills that occurred in Maryland during 1999, by county. Gall ons of oil spilled per ozone season were summed by county for the ozone season period of April 1 through October 31 (214 days).

Emission Factor MDE staff used an emission factor recomme nded to the Metropolitan Washington Council of Governments by E.H. Pechan and Associat es, Inc., the contractor used by MWCOG to prepare their 1990 base year inventory. This emission factor was based on a California Air Resources Board (CARB), study of air emissi ons from large oil spills (over 10 million gallons of oil). Based on this study, a range of evaporation estimates for reactive organic gases was found to be between 5,500 and 13,000 tons. Using this information, an average emission factor was calculated to be 0.0000925 tons VOC per ga llon of oil spilled. below.

No point source adjustments were made. Description

Pollutants

Method and Data Sources

Point Source Adjustments104 No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissions from oil spills:

EF Oil Spills x GOSj E Oil Spills = 2000 x 365

Where:

E Oil Spills = VOC emissions from oil spills in tons VOC per day
EF Oil Spills = emission factor for small breweries GOSi = gallons of oil spilled in county I

2002 Sample Calculation for Oil Spill VOC Emissions (Baltimore County) :

Annual Emissions: Number gallons oil spilled in Baltimore County, 2002:

(0.0000925) x (Gal) E Oil Spills = 2000

E Oil Spills = tons VOC per year

Number gallons oil spilled in Ba ltimore County, April-October, 2002

(0.0000925) x (Gal) E Oil Spills = 2000 x 214

E Oil Spills = tons VOC per ozone season day Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation105 4.1.4.2 Leaking Underground Storage Tanks
SCC: 26 60 000 000

Many underground storage tanks (USTs) are over 15 years old and are constructed of steel, which may rust over time. The underground pipi ng connected to these tanks also has the potential to leak. Leaking USTs are of concern because they may result in the contamination of drinking water, subsurface so ils, and ground and surface water, and may emit toxic and/or explosive vapors. The contaminated soil and water may also emit VOC.

VOC

Activity As suggested in section 4.8.6 of Procedures , MDE staff used emissions from soil and groundwater remediation to estimate VOC emissions from leaking underground storage tanks. From the MDE/ARMA registration file s, inventory staff obtained location of soil and groundwater remediation sites and obtained fugitive VOC emissions from each site in pounds per day. No seasonal variation was assumed.

Emission Factor VOC emissions are those allowable in each remediation permit- there are different allowable emissions for each permit.

No point source adjustments were made.

No controls are available for this source cate gory. Because MDE staff used maximum allowable emissions from permit information, MDE believes that Rule Effectiveness, Control Efficiency, and Rule Penetration are not applicable to this source. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls106 Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

RS1 j + RS2 j + RS3 j

.... E UST = 2000

where:
E UST = VOC emissions in tons per day from leaking underground storage tanks

RS1 j , RS2 j = pounds VOC per day allowed from remedi ation site(s) in county j

2002 Sample Calculation for Leaking Underg round Storage Tanks (Anne Arundel County)

No seasonal variation assumed

Annual VOC emissions in pounds per day: (f rom soil and groundwater remediation) Activity level: 7 days/week (see text)

VOC emissions in tons per day: pounds/day total from registration data: pounds/day/ 2000 = tons VOC per day from leaking underg round storage tanks in Anne Arundel County Spatial and Temporal Allocations

Emissions Calculation107 4.1.5 SOLID WASTE DISPOSAL, TREATMENT, AND RECOVERY

4.1.5.1 On-site Incineration
SCC: 26 01 000 000

On-site incineration is the confin ed burning of waste on a small scale by institutions such as hospitals, nursing homes, veterinary offices, funeral homes and laboratories. Large-scale incineration is included in the point source inventory.

VOC, NOx, SOx, CO, and PM 10

In Maryland incinera tors are regulated under COMAR 26. 11.08. Maryland began regulating incinerators for control of particulates in the 1970's. In AQCRs III and IV single chamber incinerators, the type that would be used for on- site residential incineration, were banned. All such incinerators were rendered inoperative under the direction of the Maryland Department of the Environment (MDE). Over 1700 small incine rators were eliminated under this requirement.

In the other Maryland counties included in the Washington, D.C. nonattainment area, incineration of trash in on-site incinerators is prohibited except in areas where public trash collection is not provided.

COMAR 26.11.08.09 now requires a ll incinerators to obtain a pe rmit to operate and any person who owns or operates an inci nerator must obtain certificat ion from MDE and renew the certification annually.

MDE/ARMA maintains a registry of all incine rators within the State. Because of the requirements prohibiting single cham ber incinerators, the requirement for a permit to operate, and the operator certification require ments, staff used the sum of the incinerators in the registry as representing the total area source emissions from incinerators of all types emitting less than 10 tons/VOC, 100 tons/yr CO and 50 tons per year NO
x . Incinerators from the registry with emissions above these thresholds are in cluded in the point source inventory.

No seasonality is applied. The emission factor is chosen by type of incinerator: waste, pathological, hazardous, industrial, special medical, sewage sludge and municipal waste combustors. The burn rate is determined by stack test or AP-42. Hours of operation and tons of waste per day are supplied by the operator. Description

Pollutants

Method and Data Sources108 4.1.5.2 Publicly Owned Treatment Works (POTWs)
SCC: 26 30 020 000

EPA Procedures mentions that research into VOC emi ssions from POTWs has found that in the event of "heavy chemical loading", 85% of volatil e pollutants discharged to these facilities "are stripped to the ambient air" (Section 3.5.1). Also, VOC concentration in POTW influent is directly proportional to the industrial contributio n to POTWs as stated in Procedures , Page 3-14.

VOC, NH 3

The emissions from these facilities were calcul ated based on the method described in Procedures

, Section 3.5.1.

Activity The percent industrial flow for each POTW in Maryland was supplied by the Maryland Water Management Administration. MDE st aff multiplied this amount by the emission factor listed above to get VOC emissions from each POTW. The individual POTW emissions were then totaled by county. Some counties are not listed in this table because their industrial effluent is discharg ed to a POTW in another county.

Emission Factor This method uses an emission factor of 1.1 x 10 -4 pounds VOC emitted per gallon of industrial wastewater disc harged to a POTW.

VOC stack emissions in the Air Management regi stration files from the Patapsco Wastewater Treatment Plant in Baltimore City were subtracted from the totals below.

No controls are available for this source category. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls109 Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissions from POTWs is:

DF I J x PIF I J x EF POTW x SAF POTW E POTW = 2000

Where:
E POTW = VOC emissions in tons VOC per day from POTWs
DF I J = Daily flow into POTW i in county j
PIF I J = Percent industrial fl ow from POTW i in county j
EF POTW = VOC emission factor 68 for POTWs
SAF POTW = Seasonal adjustment factor 69 for peak ozone season which is 1.4

2002 Sample Calculation for POTW VOC Emissions (Anne Arundel County) :

Back River Sewage Treatment Plant statistics 70 : Average daily flow (MGD) 71 : 152.0 Percent industrial flow: 4.2%

(843,800) x (4.2%) x (1.1 x 10 -4 lbs. VOC / gal) x 1.4 E POTW = 2000

E POTW = 0.0639 tons VOC / day

68 Emission factor taken from Procedures, Section 3.5.1

69 Seasonal adjustment factor taken from Procedures, Table 5.8.1

70 Supplied by the Maryland Water Management Administration

71 MGD : Million Gallons per Day Spatial and Temporal Allocations

Emissions Calculation110 4.1.5.3 Open Burning – Land Clearing Debris
SCC: 26 10 000 500

Open burning of land clearing debr is refers to the clearing of land for new construction and the burning of organic material (i.e., trees, shrubs and other vegetation). The clearing of land for the construction of new buildings and highways often re sults in debris consisting of trees, shrubs, and brush. This debris may be burned in place but it is usually collected in piles for burning. The burning of land clearing wastes may be practi ced by private individua ls, corporations, and government agencies (e.g., highway constructio n department). There are no federal laws restricting the open bur ning of land clearing wastes, although state or local laws may exist.

Residential open burning without a permit is pr ohibited in Maryland, COMAR 26.11.07, where trash and leaf collection is available. The basic difference between the regulation as it applies to counties in AQCRs III and IV and the rest of the state is the requirements under which the burn takes place, i.e., minimum setbacks from property lin es, etc. In the more rural counties, areas with no available trash collection are more preval ent. MDE adopted a regulation that prohibits open burning during the peak oz one period (June to August). The seasonal prohibition only affects those counties that lie within serious and severe ozone nonattain ment areas. Certain exemptions must be in place however so as not to adversely affect agriculture or restrict fire training and recreational activitie s. Commercial open burning w ithout a permit is prohibited in Maryland.

VOC, NOx, SOx, CO, PM 10 and PM 2.5

The method used to calculate emissions, is presented in EIIP 72 , Chapter 16, Open Burning (Revised Final 2001).

Activity The number of acres disturbed by residential, non-residential and ro adway construction are estimated and then these values are added togeth er to obtain a county- level estimate of total acres disturbed by land-clearing. County-level emissions from land clearing debris are then calculated by multiplying the total acres disturbed by construction by a weighted loading factor and emission factor.

72 Emission Inventory Improvement Program Description

Pollutants

Method and Data Sources111 The BELD database in BEIS was used to determine the number of acres of hardwoods, softwoods, and grasses in each county. Average loading factors were weighted according to the percent contribution of each t ype of vegetation class to the total land area for each county. The loading factors for slash hardwood and slas h softwood were further adjusted by a factor
of 1.5 to account for the mass of tree that is below the soil surface that would also be subject to burning once the land is cleared.

Fuel loading factors are as follows:

Fuel Type Fuel Load Factor (tons/acre) Adjusted Load Factor (tons/acre) Hardwood 99 148.5 Softwood 57 85.5
Grass 4.5 4.5

Average fuel loading factors were calculated as follows:

(Acres HW-COi x LF Adj-HW ) +(Acres SW-COi x LF Adj-SW ) +(Acres GR-COi x LF Adj-GR ) LF OB –LCD – COi Acres TOT-COi

LF OB –LCD – COi = Average Load Factor in County i
Acres HW-COi = Acres of hardwood in County i from BELD database
LF Adj-HW = Adjusted Load Factor for Hardwood
Acres SW-COi = Acres of softwood in County i from BELD database
LF Adj-SW = Adjusted Load Factor for Softwood
Acres GR-COi = Acres of grasses in Coun ty i from BELD database
LF Adj-GR = Adjusted Load Factor for Grasses
Acres TOT-COi = Total Land Acres in County i

Emission Factors 73
Emission factors in lbs. /ton were taken from AP-42 Table 2.5-1, Emission Factors for Open Burning of Municipal Refuse and are listed below:

VOC 13 Lbs. VOC / ton SOx 1.0 Lbs. SOx / ton CO 85 Lbs. CO / ton
PM 10 16 Lbs. PM10 / ton
PM 2.5 17 Lbs. PM2.5 / ton

Ozone Season Daily (OSD) emissions calculated by multiplying annual emissions by 0.25 then dividing by 92.

73 Emissions factors for VOC NOx, CO, SO 2 , PM 10 and PM 2.5 were obtained from AP-42 Table 2.5-1.112 No subtraction of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

Annual Emissions

AD R-NR-Road x LF OB –LCD – COi x EF OB i E OB –LCD – Ann = 2000

E OB –LCD – Ann = Annual emissions from open burning of land clearing debris
AD R-NR-Road = Acres disturbed from Resident ial, Non-residential and Roadway construction in the county
LF OB –LCD – COi = Average Load Factor in County i
FL HW-SW-G = Fuel loading factor for hardwoods, softwoods, and grasses
EF OB i = Open burning emission factor for pollutant i in lbs. / ton

Ozone Season Daily Emissions

E OB –LCD – Ann E OB –LCD – Day = 4 x 92

E OB –LCD – Day = Ozone Season Daily emissions from open burning
E OB –LCD – Ann = Annual emissions from open burning of land clearing debris 4 = Number of seasons in the year 92 = Days in the season Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations

Emissions Calculation113 4.1.5.4 Open Burning – Residential Municipal Solid Waste
SCC: 26 10 030 000

Open burning is the unconfined burning of wood, leaves, land cl earing debris, household waste, and agricultural crop waste. Household waste, of ten referred to as residential municipal solid waste (MSW), is a term for nonhazardous refuse produced by households (e.g., paper, plastics, metals, wood, glass, rubber, leathe r, textiles, and food wastes).

Open burning without a permit is prohibited in Maryland where trash and leaf collection is available, COMAR 26.11.07. The basic differe nce between the regula tion as it applies to counties in AQCRs III and IV and the rest of the state is the requirements under which the burn takes place, i.e., minimum setbacks from property lin es, etc. In the more rural counties, areas with no available trash collection are more preval ent. MDE adopted a regulation that prohibits open burning during the peak oz one period (June to August). The seasonal prohibition only affects those counties that lie within serious and severe ozone nonattain ment areas. Certain exemptions must be in place however so as not to adversely affect agriculture or restrict fire training and recreational activities.

VOC, NOx, SOx, CO, PM 10 , PM 2.5 , and Toxics

The method used to calculate emissions is pres ented in a study/survey conducted by the MidAtlantic/Northeast Visibility Union (MANE-VU), titled “Open Burning in Residential Areas Emissions Inventory Development Report.” 74

Activity The purpose of the survey was to obtain data for developing activity estimates and control information (e.g., bans on burning) that woul d form the basis of an improved open burning emission inventory for Mid-Atlantic/Northeas t Visibility Union (MANE-VU) states and tribes for the year 2002.

A rule effectiveness (RE) survey was also pe rformed to estimate controlled emissions for areas that prohibit open burning. Househol d waste burning surveys were completed for 72 respondents or jurisdictions, while yard wast e surveys were conducted for 181 espondents. The respondents for this survey were typi cally local fire wardens or chiefs. Rule

74 Open Burning in Residential Areas Emissions Inventory Development Reprt, Preparted by E.H. Pechan & Associates, Inc. for the Mid-Atlantic/Northeast Visibility Union, dated January 31, 2004. Description

Pollutants

Method and Data Sources114 effectiveness surveys related to residentia l MSW rules were conducted for 49 respondents, while RE surveys for yard waste burning rules were performed for 51 respondents. In obtaining survey responses, Pechan collected activity data and control information for areas classified as urban, s uburban, and rural, or a comb ination of these designations (defined using data from the 2000 U.S. Census). Pechan also developed a control database for each open burning category that describes the recommended control efficiency (CE) and rule penetration (RP) va lues by state and county, and by subcounty, where applicable.

Open burning activity estimates recorded from the survey were used directly to estimate emissions for the surveyed ju risdictions. For the non-surveyed areas, including tribal lands, the default activity data derive d from all survey responses we re applied. Households are defined as detached single-family unit dw ellings as provided by the 2000 U.S. Census.

Emission Factors

Emission factors in lbs/ton total mass were taken from AP-42 Table 2.5-1, Emission Factors for Open Burning of Municipal Re fuse and from a 1997 EPA research paper on open burning 75 are listed below:

Pollutant Emission Factor Lb/ton total mass burned
VOC 8.556
NOx 6
CO 85
PM 10 38
PM 2.5 34.8
SO 2 1.0

No subtration of emissions fr om point sources is necessary.

If an area has controls or prohibitions on residential burning, controlled emissions were calculated from uncontrolled emission s using the following equation:

E c = E uc * [(1-(CE)(RP)(RE)]

75 EPA. 1997. Evaluation of Emissions from the Open Burning Of Household Waste in Barrels. EPA-600/R-97- 134a. U.S. Enivironmental Protection Agency, Control Technologies Center. Research Triangle Park, North Carolina. Point Source Adjustments

Adjustments for Controls115 where:
E c = Controlled area source emissions
E uc = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100

The following sections describe how values for CE, RP and RE were derived from the

survey.

Rule Effectiveness Pechan evaluated differences in RE between rural/suburban and urban areas, as well as differences in RE for MSW and yard waste burni ng. Although one may expect that RE would be higher for urban than for suburban or rural ar eas, ANOVA of the survey results from these geographic subdivisions, as well as for the different open burning categories, did not show that RE values were drawn from dis tinct populations. Therefore, the fi nal selection of RE reflects a value for all areas and all burning categories.

There was a total of 26 RE survey responses that included information on the number of violating households. To calculate RE, Pechan used the number of households violating the rule, and the number of households expected to perf orm open burning for areas in the region where there is no rule (i.e., # househol ds x fraction of open burning hous eholds by region from survey).

The RE values obtained from the survey responses will be used for the specific State or jurisdiction surveyed. Non-surveyed areas could not be assigned a jurisdiction-specific RE, because no survey responses were obtained for t hose areas. Pechan did not develop statespecific RE values since we had no reason to believe th at local jurisdictions in individual states implemented their rules differently than local ju risdictions in the rest of the MANE-VU region. To estimate a default RE value for the remaining areas, the survey data were statistically analyzed. After evaluating the da ta using the Census 2000 data, a mean value of 96.8 percent reflected the best estimator of central tendency. As such, Pechan applied a rule effectiveness of 96.8 percent to all areas and for both MS W and yard waste burning (Pechan, 2002b).

Control Efficiency and Rule Penetration For those areas identified to have a control, CE is assume d to be 100 percent (since the control is typically a ban on burning activity). For MSW bur ning, with the exception of Pennsylvania, Pechan assigned 100 percent CE and 100 percent RP to urban and suburban areas in the MANE-VU region (i.e., even if the stat e did not have a statew ide ban on burning). In Pennsylvania, unless a jurisdic tion or county (e.g., Allegheny County) was determined via survey to have a ban, it will be assumed that suburban and rural areas allow open burning. For yard waste burning, Pechan assigned 100 percent CE and RP to all urban areas in the MANE-VU region. Yard waste emissions calculated for suburban and urban areas were assumed to be116 uncontrolled, unless the survey data or other st atewide or local control information indicated otherwise. For municipal yard waste burning, area s were assumed to either perform this activity and have associated emissions, or did not c onduct burns and therefore were assigned zero emissions.

In determining annual emissions for those areas w ith a seasonal ban, Pechan adjusted the RP by the length of the seasonal ban relative to the entire year. The RP value also depends on how the time period of the ban overlaps with the activ ity profile for the specific category of burning. For example, for brush waste burning, the survey data revealed an average activity profile as follows: Winter–20%; Spring–46%; Summer–6%; a nd Fall–28%. So, for an area that has a brush burning ban in the summer, although some pe rcentage of burning is likely to be prevented during this season, we assume th at 2 percent of the summer season brush burning in August is delayed until September when burning is permitted, resulting in an RP of 4 percent to apply to annual brush waste burning emissions. As mentione d in the discussion of temporal allocation profiles, this also has an aff ect on the monthly activity profile. A summer RP value of 4 percent would result in a revised temporal allocati on profile to be: Wint er–20%; Spring–46%; Summer– 4%; and Fall–30%.

Spatial Pechan collected activity data and control in formation for areas classified as urban, suburban, and rural, or a combination of thes e designations (defined using data from the 2000 U.S. Census).

Temporal Activity estimates and associated emissions are calculated on an annual basis. Pechan proposes the following temporal allocation profile s to represent monthly, weekly, and daily activity profiles by SCC (see Tables II-2 thr ough II-5). The monthly activity profiles were developed based on data obtained from the survey. The weekly and weekday/weekend profiles were developed based on engineering judgment. These profiles will be applied to annual activity for all areas of MANE-VU (i.e., variations in regional, State, or tribal areas are not accounted for).

Temporal Allocation Profile Formats (monthly)

Month

SCC Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2610030000 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083

2610000400 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067

2610040400 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067

2610000100 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.333 0.333 0.333 0.000

Temporal Allocation Profile Formats (weekly)

Day of Week Spatial and Temporal Allocations117 Mon Tue Wed Thu Fri Sat Sun

2610030000 0.111 0.111 0.111 0.111 0.111 0.222 0.222

2610000400 0.111 0.111 0.111 0.111 0.111 0.222 0.222

2610040400 0.200 0.200 0.200 0.200 0.200 0.000 0.000

2610000100 0.111 0.111 0.111 0.111 0.111 0.222 0.222

Temporal Allocation Profile Formats (daily; weekday)
Weekday Hour

SCC 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200

2610030000 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610040400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000100 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

Weekday Hour

SCC 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 0000

2610030000 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610040400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000100 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

Temporal Allocation Profile Formats (daily; weekend day)

Weekend Day Hour

SCC 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200

2610030000 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610040400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000100 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

Weekend Day Hour

SCC 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 0000

2610030000 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610040400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000100 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

Emissions were caculated at a census tract level and summed over a county for county level emissions. A county level sample emission calcu lation will not be presented here, however the equations for a particular census tract are presente d below. All of the census tracts in a county would then be summed for county level emission estimates.

The equation for estimating the mass of waste burned is:

PUT EQUATION HERE Emissions Calculation118 Wt MSW = Mass of waste burned per time period HH = Number of households that burn (Question 1, Part 2 of survey) Bt = Number of burns per tim e period (Question 3, Part 2) M = Mass of waste per burn (Question 5, Part 3)

Uncontrolled emissions were then calculated using the following equation:

E UNC = Wt MSW * EF

where:
E UNC = Uncontrolled area source emissions
Wt MSW = Mass of waste burned per time period EF = Emission factor per pollutant

Controlled emissions were then calcu lated using the following equation:

E C = E UNC * [(1-(CE)(RP)(RE)]

where:
E C = Controlled area source emissions
E UNC = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100119 4.1.5.5 Open Burning – Residential Yard Waste SCC: 26 10 000 100 (Leaf Debris) SCC: 26 10 000 400 (Brush Debris)

Open burning is the unconfined burning of wood, leaves, land cl earing debris, household waste, and agricultural crop waste. Household waste, of ten referred to as residential municipal solid waste (MSW), is a term for nonhazardous refuse produced by households (e.g., paper, plastics, metals, wood, glass, rubber, leathe r, textiles, and food wastes).

Open burning without a permit is prohibited in Maryland where trash and leaf collection is available, COMAR 26.11.07. The basic differe nce between the regula tion as it applies to counties in AQCRs III and IV and the rest of the state is the requirements under which the burn takes place, i.e., minimum setbacks from property lin es, etc. In the more rural counties, areas with no available trash collection are more preval ent. MDE adopted a regulation that prohibits open burning during the peak oz one period (June to August). The seasonal prohibition only affects those counties that lie within serious and severe ozone nonattain ment areas. Certain exemptions must be in place however so as not to adversely affect agriculture or restrict fire training and recreational activities.

VOC, NOx, SOx, CO, PM 10 , PM 2.5 , and Toxics

The method used to calculate emissions is pres ented in a study/survey conducted by the MidAtlantic/Northeast Visibility Union (MANE-VU), titled “Open Burning in Residential Areas Emissions Inventory Development Report.” 76

Activity The purpose of the survey was to obtain data for developing activity estimates and control information (e.g., bans on burning) that woul d form the basis of an improved open burning emission inventory for Mid-Atlantic/Northeas t Visibility Union (MANE-VU) states and tribes for the year 2002.

A rule effectiveness (RE) survey was also pe rformed to estimate controlled emissions for areas that prohibit open burning. Househol d waste burning surveys were completed for 72

76 Open Burning in Residential Areas Emissions Inventory Development Reprt, Preparted by E.H. Pechan & Associates, Inc. for the Mid-Atlantic/Northeast Visibility Union, dated January 31, 2004. Description

Pollutants

Method and Data Sources120 respondents or jurisdictions, while yard waste surveys were conducted for 181 respondents. The respondents for this survey we re typically local fire wardens or chiefs. Rule effectiveness surveys related to residential MSW rules were conducted for 49 respondents, while RE surveys for yard wa ste burning rules we re performed for 51 respondents. In obtaining surv ey responses, Pechan collected activity data and control information for areas classified as urban, s uburban, and rural, or a combination of these designations (defined using data from the 2000 U.S. Census). Pechan also developed a control database for each open burning categor y that describes the recommended control efficiency (CE) and rule penetration (RP) values by state and county, and by subcounty, where applicable.

Open burning activity estimates recorded from the survey were used directly to estimate emissions for the surveyed ju risdictions. For the non-surveyed areas, including tribal lands, the default activity data derive d from all survey responses we re applied. Households are defined as detached single-family unit dw ellings as provided by the 2000 U.S. Census.

Emission Factors

Emission factors in lbs/ton total mass were taken from AP-42 Table 2.5-1, Emission Factors for Open Burning of Municipal Re fuse and from a 1997 EPA research paper on open burning 77 are listed below:

Pollutant Emission Factor Lb/ton total mass burned
VOC 8.556
NOx 6
CO 85
PM 10 38
PM 2.5 34.8
SO 2 1.0

No subtration of emissions fr om point sources is necessary.

77 EPA. 1997. Evaluation of Emissions from the Open Burning Of Household Waste in Barrels. EPA-600/R-97- 134a. U.S. Enivironmental Protection Agency, Control Technologies Center. Research Triangle Park, North Carolina. Point Source Adjustments

Adjustments for Controls121 If an area has controls or prohibitions on residential burning, controlled emissions were calculated from uncontrolled emission s using the following equation:

E c = E uc * [(1-(CE)(RP)(RE)]

where:
E c = Controlled area source emissions
E uc = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100

The following sections describe how values for CE, RP and RE were derived from the

survey.

Rule Effectiveness Pechan evaluated differences in RE between rural/suburban and urban areas, as well as differences in RE for MSW and yard waste burni ng. Although one may expect that RE would be higher for urban than for suburban or rural ar eas, ANOVA of the survey results from these geographic subdivisions, as well as for the different open burning categories, did not show that RE values were drawn from dis tinct populations. Therefore, the fi nal selection of RE reflects a value for all areas and all burning categories.

There was a total of 26 RE survey responses that included information on the number of violating households. To calculate RE, Pechan used the number of households violating the rule, and the number of households expected to perf orm open burning for areas in the region where there is no rule (i.e., # househol ds x fraction of open burning hous eholds by region from survey).

The RE values obtained from the survey responses will be used for the specific State or jurisdiction surveyed. Non-surveyed areas could not be assigned a jurisdiction-specific RE, because no survey responses were obtained for t hose areas. Pechan did not develop statespecific RE values since we had no reason to believe th at local jurisdictions in individual states implemented their rules differently than local ju risdictions in the rest of the MANE-VU region. To estimate a default RE value for the remaining areas, the survey data were statistically analyzed. After evaluating the da ta using the Census 2000 data, a mean value of 96.8 percent reflected the best estimator of central tendency. As such, Pechan applied a rule effectiveness of 96.8 percent to all areas and for both MS W and yard waste burning (Pechan, 2002b).

Control Efficiency and Rule Penetration For those areas identified to have a control, CE is assume d to be 100 percent (since the control is typically a ban on burning activity). For MSW bur ning, with the exception of Pennsylvania, Pechan assigned 100 percent CE and 100 percent RP to urban and suburban areas in the MANE-VU region (i.e., even if the stat e did not have a statew ide ban on burning). In Pennsylvania, unless a jurisdic tion or county (e.g., Allegheny County) was determined via survey to have a ban, it will be assumed that suburban and rural areas allow open burning. For122 yard waste burning, Pechan assigned 100 percent CE and RP to all urban areas in the MANE-VU region. Yard waste emissions calculated for suburban and urban areas were assumed to be uncontrolled, unless the survey data or other st atewide or local control information indicated otherwise. For municipal yard waste burning, area s were assumed to either perform this activity and have associated emissions, or did not c onduct burns and therefore were assigned zero emissions.

In determining annual emissions for those areas w ith a seasonal ban, Pechan adjusted the RP by the length of the seasonal ban relative to the entire year. The RP value also depends on how the time period of the ban overlaps with the activ ity profile for the specific category of burning. For example, for brush waste burning, the survey data revealed an average activity profile as follows: Winter–20%; Spring–46%; Summer–6%; a nd Fall–28%. So, for an area that has a brush burning ban in the summer, although some pe rcentage of burning is likely to be prevented during this season, we assume th at 2 percent of the summer season brush burning in August is delayed until September when burning is permitted, resulting in an RP of 4 percent to apply to annual brush waste burning emissions. As mentione d in the discussion of temporal allocation profiles, this also has an aff ect on the monthly activity profile. A summer RP value of 4 percent would result in a revised temporal allocati on profile to be: Wint er–20%; Spring–46%; Summer– 4%; and Fall–30%.

Spatial Pechan collected activity data and control in formation for areas classified as urban, suburban, and rural, or a combination of thes e designations (defined using data from the 2000 U.S. Census).

Temporal Activity estimates and associated emissions are calculated on an annual basis. Pechan proposes the following temporal allocation profile s to represent monthly, weekly, and daily activity profiles by SCC (see Tables II-2 thr ough II-5). The monthly activity profiles were developed based on data obtained from the survey. The weekly and weekday/weekend profiles were developed based on engineering judgment. These profiles will be applied to annual activity for all areas of MANE-VU (i.e., variations in regional, State, or tribal areas are not accounted for).

Temporal Allocation Profile Formats (monthly)

Month

SCC Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2610030000 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083

2610000400 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067

2610040400 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067

2610000100 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.333 0.333 0.333 0.000

Temporal Allocation Profile Formats (weekly) Spatial and Temporal Allocations123 Day of Week SCC Mon Tue Wed Thu Fri Sat Sun

2610030000 0.111 0.111 0.111 0.111 0.111 0.222 0.222

2610000400 0.111 0.111 0.111 0.111 0.111 0.222 0.222

2610040400 0.200 0.200 0.200 0.200 0.200 0.000 0.000

2610000100 0.111 0.111 0.111 0.111 0.111 0.222 0.222

Temporal Allocation Profile Formats (daily; weekday)
Weekday Hour

SCC 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200

2610030000 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610040400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000100 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

Weekday Hour

SCC 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 0000

2610030000 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610040400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000100 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

Temporal Allocation Profile Formats (daily; weekend day)

Weekend Day Hour

SCC 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200

2610030000 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610040400 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

2610000100 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

Weekend Day Hour

SCC 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 0000

2610030000 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610040400 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

2610000100 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

Emissions were caculated at a census tract level and summed over a county for county level emissions. A county level sample emission calcu lation will not be presented here, however the equations for a particular census tract are presente d below. All of the census tracts in a county would then be summed for county level emission estimates.

The equation for estimating the mass of waste burned is: Emissions Calculation124 Where:
Wt MSW = Mass of waste burned per time period HH = Number of households that burn (Question 1, Part 2 of survey) Bt = Number of burns per tim e period (Question 3, Part 2) M = Mass of waste per burn (Question 5, Part 3)

Uncontrolled emissions were then calculated using the following equation:

E UNC = Wt MSW * EF

where:
E UNC = Uncontrolled area source emissions
Wt MSW = Mass of waste burned per time period EF = Emission factor per pollutant

Controlled emissions were then calcu lated using the following equation:

E C = E UNC * [(1-(CE)(RP)(RE)]

where:
E C = Controlled area source emissions
E UNC = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100125 4.1.5.6 Cremation – Animal and Human
SCC: 31 502 102

Propane-fired burners (afterburne r and ignition) are typically us ed at cemeteries for human body and animal cremation. Burners are usually ra ted at 2,115,000 Btu per hour capacity. Newer units installed in thelate 1980's are equipped with a modulating ignition burner. When afterburner temperatures reach about 1800 F (980 C), the igniti on burner modulates to a low-fire mode that will reduce the Btu per hour usage.

When the crematory reaches an operating temper ature of 1,250 F (680 C) the body container is placed on the combustion chamber grate and the i gnition burner is fired to attain a target combustion temperature sufficient for the prop er reduction of human remains. The chamber preheat by the afterburner reaches 1,250 F (680 C) in about 30 to 45 minutes prior to ash removal. When the body containe r is introduced into the combus tion chamber, and the burner is ignited, cremation begins at about 1600 to 1800 F (870 to 980 C). Flame impingement on the body takes two to three minutes; cremation occurs for about two hours. The remains are then raked towards the ignition burner for about two minutes. Cooldown follows for 45 minutes to 1.5 hours.

Air Toxics (Criteria Polluta nts were not calculated)

The method used to calculate emissions, is pres ented in “Documentation for the 1996 Base Year National Toxics Inventory for Area Sources” prepar ed by Eastern Research Group, Inc. (May 31, 2001) and distributed by U.S. EPA Emissions, Monitoring and Analysis Division, Emission Factor and Inventory Group.

Activity In Maryland crematories are regulated under COMAR. COMAR now requires all crematories to obtain a permit to operate and any person who owns or operates an crematory must obtain certification from MDE and renew the cer tification annually.

MDE/ARMA maintains a registry of all crematories within the State. Because of the requirement for a permit to operate, and the ope rator certification requirements, staff used the sum of the crematories in the registry as representing the total area source emissions from crematories of all types emitting less th an 10 tons/VOC, 100 tons/yr CO and 50 tons per year NO
x . Description

Pollutants

Method and Data Sources126 Emission Factors

Emission factors these hazardous air pollutants, except formaldehyde, were taken from the State of California Air Resources Board Test Report No. C-90-004 78 . The emission factor used for formaldehyde was reported in the USEPA FIRE 79 system database.

Emission factors were converted to a pound pe r ton basis using the procedure provided by the Emission Standards Division 80 . National activity was provided by the Emissions Standards Division based on an assumed body weight of 150 pounds and information reported by the Cremation Association of North America 81 that 21.13 percent of bodies were cremated and that there were 2, 322,265 deaths in the United States in 1996 82

.

Animal and Human Cremation Emission Factor Pollutant
Lbs. pollutant / ton cremated
arsenic 4.00E-04 beryllium 1.84E-05 cadmium 1.48E-04 chromium 3.99E-04 formaldehyde 2.89E-09 nickel 5.09E-04
POM as 16-PAH 9.63E-04
POM as 7-PAH 1.03E-09 Mercury 4.39E-02

No subtration of emissions fr om point sources is necessary.

78 State of California Air Resources Board, Engineering Evaluation Branch, Monitoring and Laboratory Division. “Evaluation Test on Two Propane Fired Crematories at Ca mellia Lawn Cemetary.” Test Report No. C-90-004. October 29, 1992

79 U.S. EPA. Factor Information Retrieval (FIRE) System Database, Version 5.1a. Research Triangle Park, NC. September 1995.

80 Crume, Richard, U.S. EPA, Emission Standards Division. Note to Anne Pope, U.S. EPA/Emissions Monitoring and Analysis Division. Comments on Human and Anim al Cremation information in the “Baseline Emission Inventory of HAP Emissions from MACT Sources – Interim Final Report,” September 18, 1998. October 30, 1998.

81 Cremation Association of North Ameri ca. 1996 Statistics as found on the Internet Cremation Society, Cremation Stats Nationwide webpage: ww w.cremation.org/stats.htm

82 Ventura, S. et al. “Births and Deaths: United States, 1 996.” Monthly Vital Statistics Report, Vol. 64, No. 1, Supplement 2. Setpember 11, 1997. U.S. Department of Health and Human Services, Centers for Dieseas Control and Prevention, National Center for Health and Statistics. Point Source Adjustments

Adjustments for Controls127 No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

The equation for estimating emissions from crematories is:

where:
E CREM = Annual emissions from crematories
TON cty = Tons cremated per year in county EF = Emission Factor per pollutant (lbs/ton)

2002 Sample Calculation (Harford County)

Arsenic Annual Emissions:

TON cty = 26 EF = 0.0004 lbs Arsenic/Ton Cremated

(26) x (0.0004) E CREM = (2000 lbs/ton)

E CREM = 5.20E-06 tons Arsenic per Year Spatial and Temporal Allocations

Emissions Calculation128 4.1.5.7 Municipal Solid Waste Landfills
SCC: 26 20 030 000

Municipal solid waste landfills receive household and commercial trash. VOC emissions are produced from volatilization, chemical reaction a nd biological decomposition of waste. Methane and Carbon dioxide are the primary constituents of landfill gas, and are produced during anaerobic decomposition of cellulose and proteins in the landfilled waste. 98.7 percent of landfill emissions are methane and carbon dioxide according to the Volatile Organic Compounds Species Data Manual , an EPA publication. In addition to methane and carbon dioxide, nonmethane organic carbons (NMOCs) are produced as a small fraction of the landfill gas emissions (less than 1%). NMOCs include hazar dous air pollutants and reactive VOCs.

VOC

The method used to calculate em issions, is presented in AP-42 , Chapter 2.4, Municipal Solid Waste Landfills and EIIP 83 , Volume III, Chapter 15, La ndfills, dated September 1997.

Emission estimation assumptions were also ma de using supporting documents Standards of Performance for New Stationary Sources (NAR A, 1991a) and Emission Guidelines for Control of Existing Sources (NARA, 1997b).

To estimate uncontrolled emissions of the va rious compounds present in landfill gas, total landfill gas emissions must first be estimated. Emissions of landfill gas depend on several factors including: (1) the size, configuration, and operating conditi ons of the landfill; and (2) the characteristics of the refuse such as moisture content, age, and composition. Uncontrolled CH 4 emissions may be estimated for individual landfills by using a theoretical first-order kinetic model of methane production developed by the EPA. A computer program that uses this model is known as the Landfill Gas Emissions Model (La ndGEM). The model equation is as follows:

Q CH4 = L O R (e -kc - e -kt ) (1)

Where:

Q CH4 = Methane generation rate at time t, m 3 /yr;

83 Emission Inventory Improvement Program Description

Pollutants

Method and Data Sources129 L o = Methane generation potential, m 3 CH 4 / Mg (megagrams) refuse;

R = Average annual refuse acceptance rate during active life, Mg/yr;

e = Base log, unitless;

k = Methane generation rate constant, yr -1;

c = Time since landfill closure, years (c = 0 for active landfills); and

t = Time since the initial refuse placement, yrs.

Site-specific landfill information is generally available for variables R, c, and t. When refuse acceptance rate information is scant or unknown, R can be estimated by dividing the refuse in place by the age of the landf ill. Also, nondegradable refuse should be subtracted from the refuse in place to prevent over estimation of CH 4 generation. The average annual acceptance rate should only be estimated by this method when ther e is inadequate information available on the actual annual acceptance rate.

The following LandGEM parameters are needed to estimate emissions from a landfill:

 The methane generation rate (k),

 The potential methane generation capacity (Lo),

 The number of years past closure that the model will estimate emissions,

 The estimated percentage composition of methan e and carbon dioxide in the gas (the default value is a 50/50 split),

 The concentration of nonmethane organic co mpounds (NMOC) found in the landfill gas,

 The concentrations of toxic air pollutants found in the landfill gas, and whether the landfill has been used for disposal of hazardous waste (co-disposal).

 The years the landfill has been in op eration (including the closure year),

 The design capacity of the landfill,

The Landfill Gas Emissions Model has several different default values for k, Lo and NMOC concentration. The EIIP document recommends using AP-42 default values for k, Lo and NMOC concentration when site-specific informa tion is not known. The AP-42 default value for k (0.04/yr) was used for Maryland since it has normal or above nor mal precipitation, rather than

the default value. This recommendation is ba sed on a comparison of gas-yield forecasts with landfill gas recovery data. The LandGEM contains a proposed regulatory default value for total VOCs of 595 ppmv expressed as hexane for non-codisposal and 2,420 ppmv for codisposal. However, there is a wide range for total VOC va lues from landfills. The proposed regulatory default value for VOC concentration was develope d for regulatory complia nce purposes and to provide the most cost-effective defa ult values on a national basis fo r the regulation. Therefore, if the landfill is known to contain only municipal solid waste or have very little organic commercial/industrial wastes, then the mean va lue of all VOC concentrations, 595 ppmv as hexane should be used. This was done for Mary land. The AP-42 default values used in the LandGEM to develop Maryland’s landfill inventory are shown in the table below:130 Landgem Model Parameters AP-42 Default Values

Lo : 100.00 m 3 / Mg Methane Generation Potential k : 0.0400 1/yr Decay Rate/Rate of Decomposition NMOC : 595.00 ppmv Non-methane Concentration Methane : 50.00 % volume Carbon Dioxide : 50..00 % volume

Activity Data was obtained from MDE’s Solid Waste Program and from the landfill facilites directly.

Emission Factors All factors are incorparted into the LandGEM itself.

The Brown Station Sites A & B, Sandy Hill La ndfill, Montgomery County RRF, and Newland Park Landfill are considered Point Sources. La ndGEM model runs for these landfills are not included in the area source emi ssion estimates for landfills.

Emission reductions were calculated for landf ills that used control technology to reduce emissions. Controlled emissions from landfills were calculated in the following manner:

Equation:

E CON-LF = {E UNC-LF x (1 – C EFF )} + {E UNC-LF x C EFF x [1 – (D EFF x RE)]}

Where:
E CON-LF = Controlled emissions from landfills

E UNC-LF = Uncontrolled emissions from landfill s (generated from the LandGEM model)

C EFF = Landfill collection efficiency (EPA default = 75%)

D EFF = Control device destruction efficiency (98%)

RE = Rule effectiveness (EPA default 80%) Point Source Adjustments

Adjustments for Controls131 Data for spatial and temporal allocation is not available for this source. Spatial and Temporal Allocations132 4.1.6 SMALL STATIONARY SO URCE FOSSIL FUEL USE

4.1.6.1 Small Electric Utility Boilers

All small electric utility boilers are inventoried in the point sour ce category. The list of small boilers from Inventory of Powe r Plants in the United States , DOE/EIA-0095(88) was obtained and indicated that all small electric boilers were included in the poi nt source inventory.

4.1.6.2 Other Fuel Consumption

Coke and process gas emissions will be inventoried as point sources.133 4.1.6.3 Fuel Oil Combustion

SCC: 21 04 011 000 (residential kerosene) SCC: 21 03 011 000 (commercial/institutional kerosene) SCC: 21 04 004 000 (reside ntial distillate oil) SCC: 21 03 004 000 (commercial/institutional distillate oil) SCC: 21 02 004 000 (industrial distillate oil) SCC: 21 03 005 000 (commercial/institutional residual oil) SCC: 21 02 005 000 (industrial residual oil)

Data collection for fuel oil consumption covers the use of both distil late and residual oil. Distillate oil includes fuel oil grades 1,2 and 4. Diesel fuel and kerosene also can be considered as distillate oils. Residential and commercial/in stitutional sources are the largest consumers of distillate oil, nationwide. Residual oil includes fuel oil grades 5 and 6. In most areas residual oil is not used by residential sources, but industr ial and commercial/institutional users may consume significant amounts.

PM 10 , PM 2.5 , SOx, NOx, CO, VOC

Activity Total sales statistics of kerosene, distillate o il, and residual oil in the State of Maryland were obtained from the Annual Report on Sale s of Fuel Oil and Kerosene, 2002, published by Energy Information Administrati on, U.S. Department of Energy 84

.

Emission Factors Emission factors were obtained from AP-42 85 , Tables 1.3-1 and 1.3-3 (hand-fed units).

Uncontrollled Emission Factors – AP-42 Tables 1.3-1 and 1.3-3
Residential Commercial Commercial I ndustrial Industrial Commercial Industrial
Distillate Distillate Residual Distillate Residual Residual 1% S Residual 1% S

84 Total residential distillate oil use in the State of Maryland in 2002 from U.S Department of Energy, Energy Information Administration, Office of Oil and Gas, Petroleum Marketing Monthly, "Annual Report on Sales of Fuel Oil and Kerosene, 2002".

85 Emission Factors from AP-42 Tables 1.3-1 and 1.3-3 Description

Pollutants

Method and Data Sources134 lbs/Kgal lbs/Kgal lbs/Kgal lbs/ Kgal lbs/Kgal lbs/Kgal lbs/Kgal
PM10 1.080 1.080 13.494 1.000 18.714 7.703 10.683
PM2.5 0.830 0.830 5.011 0.250 12.189 2.861 6.958

SOx 43.200 43.200 318.000 43.200 318.000 159.000 159.000
NOx 18.000 20.000 55.000 20.000 55.000 55.000 55.000
CO 5.000 5.000 5.000 5.000 5.000 5.000 5.000
VOC 0.713 0.340 1.130 0.200 0.280 1.130 0.280

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial This information on total sales of kerosene, di stillate oil and residual oil was broken down to the county level using a spatial allocation factor documented and recommended by
EIIP 86 in an Area Source Method Abstract for Residential and Comm ercial/Institutional Fuel Oil and Kerosene combustion.

MDE developed an allocation factor from local and state totals of annual heating-degree days and population with fuel oil to spatially allocate fuel oil consumption. The method is

A “heating-degree day” is a unit of measure us ed to indicate how cold it has been over a 24-hour period. Daily heating-degree days ar e calculated as the di fference between the base value of 65°F and the mean temperature for the day (mean of the high and low temperatures for the day).

Annual heating degree days are the sum of the daily heating degree days. Heating degree data is available from the National Oceanographic and Atmospheric Administration (NOAA). 87

86 Emissions Inventory Improvement Program (EIIP) Area Source Method Abstract – Residential and Commercial/Institutional Fuel Oil and Kerosene Combustion, dated April 2002

87 http://www.noaa.gov (home page) or http://www.ncdc.noaa. gov/ol/climate/climateproduc ts.html#PUBS (for a list of available data) Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations135 4.1.6.4 Coal Combustion SCC: 21 04 002 000 (Residential Coal) SCC: 21 03 002 000 (Commercial/Institutional Coal)

This source category covers air emissions from coal combustion in the residential sector. Bituminous coal, mined here in Maryland, represen ts the bulk of the coal used residentially for space heating in the State. Although mined n earby in Pennsylvania, readily available, and cleaner burning, anthracite coal is not used much in Maryland because of its expense.

PM 10 , PM 2.5 , SOx, NOx, CO, VOC

Activity The following assumptions were made in th e computation of emissions from coal combustion from the residential sources.

(i) Number of Dwelling Units using Coal

The number of dwelling units using coal fo r space heating for 2002 was obtained from 1990 Census Profile Series, Social and Economic Characteristics of Population and Housing. The number of new housing units authorized for construction between 1990 and 2002 was obtained from the Maryland Office of Planni ng – New Residential Units Authorized for Construction by Building Permits ( http://www.op.state.md.us) . MDE estimated that no new housing units would be equipped to burn coal as a home heating fuel.

COMAR 26.11.09.04 prohibits the use of solid fu el-burning equipment that has a rated heat input of less than 35 million BTU per hour.

(ii) Residential Coal Activity Consumption Data

The State Energy Data Report, Consump tion Estimates, by the Energy Information Administration, provided information on estimated coal consumption. The report indicates that in Maryland mostly bituminous coal was used in 2002. It was assumed, therefore, that bituminous coal was consumed by most of the ha nd-fired residential coal sources in the State of Maryland. Description Residential Coal

Pollutants

Method and Data Sources136 Emission Factors

Emission factors were obtained from AP-42 , Tables 1.1-3 and 1.1-19 (hand-fed units).

Coal Emission Factors
NOx (lbs./kgal) CO (lbs./kgal) VOC (lbs./kgal) PM 10 (lbs./kgal) SOx 88 (lbs./kgal)
Residential 9.10 275.00 10.00 6.20 62.00

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial MDE developed an allocation factor from local and state totals of annual heating-degree days and housing units heating with coal to spatially allocated coal consumption. The method is documented and recommended by EIIP 89 in an Area Source Method Abstract for natural gas and LPG combustion. Because the em ission factor was specifically adjusted to reflect seasonal emissions through heating de gree days, no further seasonal adjustment factor is necessary.

A “heating-degree day” is a unit of measure us ed to indicate how cold it has been over a 24-hour period. Daily heating-degree days ar e calculated as the di fference between the base value of 65°F and the mean temperature for the day (mean of the high and low temperatures for the day).

Annual heating-degree days are the sum of th e daily heating-degree days. Heating degree data is available from the National Oceanographic and Atmospheric Administration (NOAA). 90

88 MDE assumed an average sulfur content in coal of 2%

89 Emissions Inventory Improvement Program (EIIP) Area Source Method Abstract – Natural Gas and LPG Combustion, dated April 2002

90 http://www.noaa.gov (home page) or http://www.ncdc.noaa. gov/ol/climate/climateproduc ts.html#PUBS (for a list of available data) Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations137 

## ∑ =

sInState AllCountie County County ounty InventoryC ounty InventoryC ounty InventoryC CHU HDD CHU HDD SAF )*( *

Where:
SAF INVENTORY COUNTY = Spatial apportioning factor for inventory county
HDD INVENTORY COUNTY = Annual heating degree days for inventory county
CHU INVENTORY COUNTY = Housing units using coal in inventory county
HDD COUNTY = Annual heating degree days for each county in the state
CHU COUNTY = Housing units using coal for each county in the state

The spatial apportioning factor is used to allocate the state fuel total to the county level using the following equation:

Coal INVENTORY COUNTY = SAF INVENTORY COUNTY x Coal TOTAL STATE

Where: Coal INVENTORY COUNTY = Total Coal fuel consum ed in the inventory county Coal TOTAL STATE = Total Coal fuel consum ed in the inventory county

Temporal
MDE assumed that all residential coal combus tion is used for space heating purposes. The total coal consumed in the county can be a llocated by month or peri od using proportions of annual and monthly (or period) heating-degree days.

HDD MONTH Residential Fuel MONTH = Residential Fuel ANNUAL x HDD ANNUAL

where: Residential Fuel MONTH = Space heating fuel use for inventory month Residential Fuel ANNUAL = Space heating fuel use for inventory year
HDD MONTH = Heating degree da ys for inventory month
HDD ANNUAL = Heating degree days for inventory year

Ozone Season Daily Emissions Equation:

(EF COAL i x Coal Space Heat - J ) HDD Co Oz Season 2000 x HDD Co Annual E COAL =
Ozone DAYS Emissions Calculation138 E COALG = Ozone Season Daily emissions from residential coal combustion
EF COAL i = Emission factor for coal combustion for pollutant i Coal Space Heat - J = Coal consumed for space heating in county j
HDD Co Oz Season = Number of heating degree da ys in county for ozone season
HDD Co Annual = Number of heating degree da ys in county in the calendar year 2002
Ozone DAYS = Number of days in the ozone season: 214 Residential; 168 Commercial

Residential Coal Combustion Sample Calcula tion (Allegany County) (tons / ozone season day)

Total Residential Coal Consumpti on – State of Maryland 8,360 tons

To calculate spatial apportioni ng factor for Allegany County:

HDD INVENTORY COUNTY x CHU INVENTORY COUNTY SAF ALLEGANY COUNTY = ∑ ALL COUNTIES IN STATE (HDD COUNTY x CHU COUNTY )

SAF ALLEGANY COUNTY = 0.045531139 To calculate tons of coal used in Allegany County:

Residential Coal ALLEGANY COUNTY = SAF ALLEGANY COUNTY x Coal TOTAL STATE Residential Coal ALLEGANY COUNTY = 0.045531 x 8,360 Residential Coal ALLEGANY COUNTY = 380.6408 tons

Coal used for space heating in ozone season in Allegany County

HDD PERIOD Residential Space Heating Fuel PERIOD = Space Heating Fuel ANNUAL x HDD ANNUAL 1093 Residential Space Heating Fuel PERIOD = 380.6408 x 5234

Residential Space Heating Fuel PERIOD = 79.48804 tons

Equation:

Residential Coal VOC Ozone Season Day Emission Calculation for Allegany County

(EF COAL i x Coal Space Heat - J ) (2000 x 214) E COAL =

(10.0 x 79.48804 ) E COAL = (2000 x 214)

E COAL = 0.0019 tons VOC / Ozone season day140 Commercial and Institutional sources of coal combustion above the point source threshold are included in the point source portion of the i nventory. The following table lists area source emissions from commercial and institutional sources smaller than the threshold values.

The following assumptions were made in the co mputation of emissions from coal combustion from the commercial and institutional sources not included in the point source inventory.

Activity (i) Coal Consumption Data

The State Energy Data Report (SEDR) estimated that approximately 68, 000 tons/year of total coal was used commerically by Maryland in 2002.

(ii) Number of Dwelling Units using Coal

The number of dwelling units using coal fo r space heating for 2002 was obtained from 1990 Census Profile Series, Social and Economic Characteristics of Population and Housing. The number of new housing units authorized for construction between 1990 and 2002 was obtained from the Maryland Office of Planni ng – New Residential Units Authorized for Construction by Building Permits ( http://www.op.state.md.us) . MDE estimated that no new housing units would be equipped to burn coal as a home heating fuel.

COMAR 26.11.09.04 prohibits the use of solid fu el-burning equipment that has a rated heat input of less than 35 million BTU per hour.
Emission Factors

Emission factors were obtained from AP-42 , Tables 1.1-3 and 1.1-19 (average of overfeed and underfeed stoker).

Coal Emission Factors
NOx (lbs./kgal) CO (lbs./kgal) VOC (lbs./kgal) PM 10 (lbs./kgal) SOx 91 (lbs./kgal)
Commercial / Institutional 8.50 8.50 0.675 6.10 69

91 MDE assumed an average sulfur content in coal of 2% Description – Commercial and Institutional Coal

Methods and Data Sources141 No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial Spatial and temporal allocation to this source category were calculated in the same manner as the residential coal combustion category.

Temporal Spatial and temporal allocation to this source category were calculated in the same manner as the residential coal combustion category. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations

Emissions Calculation142 4.1.6.5 Natural Gas Combustion SCC: 21 04 060 000 (Residential Natural Gas) SCC: 21 03 060 000 (Commercial/Institutional Natural Gas)

This source category covers air emissions from natural gas combustion in the residential and commercial/institutional sectors for space heating, water heating, and cooking. This category includes small boilers, furnaces, heaters and other h eating units that are not inventoried as point sources. Residential and commercial sectors co mprise housing units; wholesale and retail businesses; health institutions; social and educat ional institutions; and Federal, state and local government institutions (e.g., military installations , prisons, office buildings). Natural gas is one of the major fuels used throughout the country. It is used mainly for power generation, for industrial process steam and heat production, and for domestic and commercial space heating. It is also used for domestic c ooking and hot water heating.

PM 10 , PM 2.5 , SOx, NOx, CO, VOC

The following assumptions were made in the com putation of the emissions from natural gas combustion.

Activity (i) Number of Dwelling Units using Natural Gas

The number of dwelling units using natura l gas for space heating for 2002 was obtained from 1990 Census Profile Series, Social and Economic Characteristics of Population and Housing. The number of new housing units au thorized for construction between 1990 and 2002 was obtained from the Maryland Offi ce of Planning – New Residential Units Authorized for Construction by Building Permits ( http://www.op.state.md.us) . The total number of additional housing units constructe d in the county was apportioned to type of home heating fuel by the same ratio as the 1990 Census figures.

(ii) Residential and Commerci al/Institutional Natural Gas Consumption Data

Total residential and commercial/institutional na tural gas consumption data in the State of Maryland for 2002 was obtained from surveying the following companies: Baltimore Gas and Electric ( Constellation Energy Group ), Washington Gas Ener gy Services (Maryland Description

Pollutants

Method and Data Sources143 Division), Chesapeake Utilities Corporation, Columbia Gas of Maryland, Easton Utility Commission, and Elkton Gas Co mpany. The companies provided natural gas sales statistics for the year 2002 in therms or cubi c feet for all counties in their service area for the residential, commercial, and industrial cate gories. These statistics were then converted into million cubic feet using a conversion factor of 1 therm equals 100 cubic feet.

Emission Factors (iii) Emission Factors – Natural Gas

Emission factors for combustion of natural gas in commercia l boilers are presented in Table 1.4-1 and 1.4-2 of Section 1.4 of AP-42 . The emission factors for PM are assumed to be less than 1.0 micrometers in diameter. Therefore the PM emisson facotrs preseneted may be used to estimate PM10, PM2.5 or PM1. Total PM is the sum of filterable and condensable PM. AP-42 Tables 1.4-1 - 1.4-2.

Natural Gas Emission Factors
Nox (lbs./10 6 scf) CO (lbs./10 6 scf) VOC (lbs./10 6 scf) PM 10 (lbs./10 6 scf) PM 2.5 (lbs./10 6 scf) SOx (lbs./10 6 scf)
Residential 94 40 5.50 1.90 1.90 0.60
Commercial 94 84 5.50 1.90 1.90 0.60

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial The natural gas survey of suppliers provide d MDE with county totals for natural gas consumption. Therefore MDE did not have to use an allocation factor derived from local and state totals of annual heating degree days and housing units heating with natural gas to spatially allocated natural gas c onsumption to the county level.

1 The VOC emission factor is 11.0 with 34% methane. The number listed is the nonmethane emission factor.

2 The VOC emission factor is 5.80 with 52% methane. The number listed is the nonmethane emission factor. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations144 Temporal In addition to space heating, natural gas is of ten used for cooking and water heating. For ozone and other seasonal inventories, cons umption for cooking and water heating may be assumed to be constant through the year, but fuel used for space heating must be apportioned according to heating needs.

To separate residential space heating natura l gas usage from cooking and water heating, MDE used data from the State Energy Da ta Report, Consumption Estimates, Energy Information Administration, Office of Energy Markets and End Use, U.S. Department of Energy. Specifically data was collected fr om Table 15 – Natural Gas Deliveries to Residential Customers, by State, 1998-2002. Th e residential deliveries for the month with the lowest deliveries can be assumed to be only for cooking and water heating. The percentage of residential na tural gas consumption for cooking and water heating may then be calculated:

12 * Lowest Monthly Fuel Use Annual Non-Space Heating Percent = Annual Fuel Use * 100

12 * 1635 Annual Non-Space Heating Percent = 80,447 * 100

Annual Non-Space Heating Percent = 24.389 %

The annual non-space heating percent can be calculated in a similar manner for commercial/institutional natural gas usage. The percentage of commercial/institutional natural gas consumption for non-space heating may then be calculated:

12 * Lowest Monthly Fuel Use Annual Non-Space Heating Percent = Annual Fuel Use * 100

12 * 2440 Annual Non-Space Heating Percent = 65323 * 100

Annual Non-Space Heating Percent = 44.823 %

This percentage may be applied to the i nventory area’s total residential and/or commercial/institutional natural gas consumpti on to calculate the non-space heating portion of usage. This portion can be subtracted from the annual total, and the remaining consumption, which is being used for space h eating, can be allocated by month or period using proportions of annual and mont hly or period heating degree days.

HDD MONTH Space Heat Fuel MONTH = Space Heat Fuel ANNUAL x HDD ANNUAL

Where:145 Space Heat Fuel MONTH = Space heating fuel use for inventory month Space Heat Fuel ANNUAL = Space heating fuel use for inventory year
HDD MONTH = Heating degree days for inventory month
HDD ANNUAL = Heating degree days for inventory year

Emission Calculation – Resident ial Ozone Season Daily Emissions

Equation:

Days Jp HotWaterAp iNatGas

CoAnnual CoOzSeason J SpaceHeat iNatGas

NatGas Ozone NG EF

HDD HDD NG EF

E ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

+ ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

= − − − − 2000 * * 2000 ) *(

E NatGas = Ozone Season Daily emissions from natural gas combustion
EF NatGas-i = Emission factor for natu ral gas combustion for pollutant i
NG Space Heat - J = Natural gas consumed for space heating in county j
HDD Co Oz Season = Number of heating degree days in county for ozone season
HDD Co Annual = Number of heating degree da ys in county in the calendar year 2002
NG Hot water/App - J = Natural gas consumed for dur ing ozone season by hot water and appliances in county j
Ozone DAYS = Number of days in the ozone season: 214 Residential; 168 Commercial

Total Residential Natural Gas Consumption – Baltimore City 92 14,483 M ft 3

Percent natural gas used for cooking & appliances in the State of Maryland 93

Total Natural Gas
Delivered Lowest Monthly Delivery of Natural Gas Percent of Natural Gas used for Cooking & Water Heating
Res Comm Res Comm Res Comm
State of Maryland 80,447 65323 1635 2440 24.389 % 44.823 %

Percent natural gas used for cooking & appliances in Baltimore City

Residential NG Hot water/App - J = 24.389 % x NG BALTIOMORE COUNTY Residential NG Hot water/App - J = 24.389 % x 14,483

3 Natural gas consumption data gathered from MDE survey – Baltimore County data from BGE

4 Lowest summer monthly total is assumed to be for cooking and appliances. Emissions Calculation146 Residential NG Hot water/App - J = 3,532.130 M ft 3

Natural gas used for space heating in Baltimore County

Residential NG Space Heat - J = 14,483 – 3,532.130 M ft 3

Residential NG Space Heat - J = 10,951 M ft 3

Natural gas used for space heating in ozone season in Baltimore City

HDD PERIOD Residential Space Heating Fuel PERIOD = Space Heating Fuel ANNUAL x HDD ANNUAL 605 Residential Space Heating Fuel PERIOD = 10,951 x 3884

Residential Space Heating Fuel PERIOD = 1,705.807 M ft 3

Natural gas used for hot water and applia nces in ozone season in Baltimore City

Months ozone season Residential Hot Water Fuel PERIOD = Hot Water Fuel ANNUAL x Months Year

7 Residential Hot Water Fuel PERIOD = 3532.130 x 12

Residential Hot Water Fuel PERIOD = 2,060.409 M ft 3

Equation:

VOC Ozone Season Day Emission Calculation

(EF NG i x NG Space Heat - J ) + (EF NG i x N Hot water/App - J ) (2000 x 214) E NatGas =

(5.5 x 1,705.807) + (5.5 x 2,060.409) E NatGas = (2000 x 214)

E NatGas = 0.0484 tons VOC / Ozone season day

The same equation and methodology can be used to estimate emission of various pollutants.147 4.1.6.6 Liquified Petroleum Gas Combustion SCC: 21 04 007 000 (Residential LPG) SCC: 21 03 007 000 (Commercial/Institutional LPG)

This source category covers air emissions from liquefied petroleum gas (LPG) combustion in the residential and commercial sectors for space heating, water heating, or cooking. LPG includes propane, propylene, butane, and butylenes. The product used for domestic heating is composed primarily of propane. This category includes sm all boilers, furnaces, heaters and other heating units that are not inventoried as point sources. Residential a nd commercial sectors comprise housing units; wholesale and retail businesses; health institutions; so cial and educational institutions; and Federal, state and local government institutions (e.g., military installations, prisons, office buildings).

PM 10 , PM 2.5 , SOx, NOx, CO, VOC

The following assumptions were made in the co mputation of the emissions from liquified petroleum gas (LPG) combustion.

Activity
1. Number of Dwelling Units using LPG

The number of dwelling units using LPG fo r space heating for 2002 was obtained from 1990 Census Profile Series, Social and Ec onomic Characteristics of Population and Housing. The number of new housing units au thorized for construc tion between 1990 and 2002 was obtained from the Maryland Offi ce of Planning – New Residential Units Authorized for Construction by Building Permits ( http://www.op.state.md.us) . The total number of additional housing units constructe d in the county was apportioned to type of home heating fuel by the same ratio as the 1990 Census figures.

2. Residential and Commercial LPG Activity Consumption Data

Total residential and commercial LPG consump tion data for space heating in the State of Maryland (LPG ST ) for 2002 were obtained from State Energy Data Report, Consumption Estimates, Energy Information Administration, Office of Energy Markets and End Use, U.S.Department of Energy. Description

Pollutants

Method and Data Sources148 Emission Factors Emission factors for combustion of LPG in comm ercial boilers are presented in Table 1.5- 1 of Section 1.5 of AP-42 (EPA, 1998a). The LPG emission f actor for PM may be assumed to represent PM 10 emissions. Because no emission factors were located for the combustion of LPG for residential consumption, emission factors for commercial boilers may be used for residential emissions. PM 10 and SOx emission factors listed below are averages of the commercial emission factors for boilers that use propane and butane. The SOx emission factors reported below were calculated usi ng the AP-42 emission factor and multiplied by the sulfur content of th e fuel (S = 0.18).

LPG Emission Factors

NOx (lbs./kgal) CO (lbs./kgal) VOC (lbs./kgal) PM 10 (lbs./kgal) PM 2.5 (lbs./kgal) SOx (lbs./kgal)
Residential 14 1.9 0.5 0.45 0.0 0.0171
Commercial 14 1.9 0.5 0.45 0.0 0.0171

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial MDE developed an allocation factor from local and state totals of annual heating degree days and housing units heating with liquid propane ga s to spatially alloca ted liquid propane gas consumption. The method is documented and recommended by EIIP 94 in an Area Source Method Abstract for natura l gas and LPG combustion.

A “heating degree day” is a unit of measure us ed to indicate how cold it has been over a 24- hour period. Daily heating degree days are calc ulated as the difference between the base value of 65°F and the mean temperature for th e day (mean of the high and low temperatures for the day).

94 Emissions Inventory Improvement Program (EIIP) Area Source Method Abstract – Natural Gas and LPG Combustion, dated April 2002 Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations149 Annual heating degree days are the sum of the daily heating degree days. Heating degree data is available from the National Oceanographi c and Atmospheric Ad ministration (NOAA). 95

HDD INVENTORY COUNTY x LP-HU INVENTORY COUNTY SAF INVENTORY COUNTY = ∑ ALL COUNTIES IN STATE (HDD COUNTY x LP-HU COUNTY )

Where:
SAF INVENTORY COUNTY = Spatial apportioning factor for inventory county
HDD INVENTORY COUNTY = Annual heating degree days for inventory county
LP-HU INVENTORY COUNTY = Housing units using LP gas for inventory county
HDD COUNTY = Annual heating degree da ys for each county in the state
LP-HU COUNTY = Housing units using LP gas for each county in the state

The spatial apportioning factor is used to allocate the state fu el total to the county level using the following equation:

LPG INVENTORY COUNTY = SAF INVENTORY COUNTY x LPG TOTAL STATE

Where:
LPG INVENTORY COUNTY = Total LPG fuel consumed in the inventory county
LPG TOTAL STATE = Total LPG fuel consumed in the inventory county

Temporal In addition to space heating, liquid propane gas is often used for cooking and water heating. For ozone and other seasonal inventories, cons umption for cooking and water heating may be assumed to be constant through the year, but fu el used for space heating must be apportioned according to heating needs.

To separate residential space heating usage fr om cooking and water heating, MDE used data from the State Energy Data Report, Consumption Estimates, Energy Information Administration, Office of Energy Markets and En d Use, U.S. Department of Energy. Data was obtained from the follow reports:

1. Water-Heating Energy Consumption in U.S. Households by South Census Region 2000
2. Appliances Energy Consumption in U.S. Households by South Census Region 2000
3. Total Energy Consumption in U.S. H ouseholds by South Census Region 2000
4. Data from Maryland Office of Planning - New Residential Units Authorized for Construction by Building Permits

The percentage of liquid propane gas consum ption for cooking and water heating may then be calculated by developing a ratio between the amount of LPG used for hot water, appliances, and the total amount of LPG consumed (space heating + hot water + appliances).

95 http://www.noaa.gov (home page) or http://www.ncdc.noaa. gov/ol/climate/climateproduc ts.html#PUBS (for a list of available data)150 Also, 2002 residential LPG usage was estimate d by taking the percent of new housing units constructed in 2000 and applying it to 2001 and 2002 new housing construction data from the Maryland Department of Planning.

amount of LPG used for hot water and appliances Percent of LPG used for cooking & appliances = total amount of LPG consumed (100 + 43)

= 572

= 0.25

Therefore 25 percent of the annual LPG cons umed is used for non-space heating and an individual county’s residential LPG consump tion total for hot water and appliances can be calculated as follows:

LPG Hot water/App - J = 25% x LPG INVENTORY COUNTY

Where:
LPG Hot water/App - J = LPG consumed for hot wate r and appliances in county j

This percentage may be applied to the invent ory area’s total reside ntial liquid propane gas consumption to calculate the cook ing and water heating portion of usage. This portion can be subtracted from the annual total, and the remain ing consumption, which is being used for space heating, can be allocated by m onth or period using proportions of annual and monthly or period heating degree days.

HDD MONTH Residential Fuel MONTH = Residential Fuel ANNUAL x HDD ANNUAL

where: Residential Fuel MONTH = Space heating fuel use for inventory month Residential Fuel ANNUAL = Space heating fuel use for inventory year
HDD MONTH = Heating degree da ys for inventory month
HDD ANNUAL = Heating degree days for inventory year

Emission Calculation

Ozone Season Daily Emissions

Equation: Emissions Calculation151 (EF LPG i x LPG Space Heat - J ) HDD Co Oz Season (EF LPG i x LPG Hot water/App -

J )
2000 x HDD Co Annual + 2000 E LPG =

Ozone DAYS

E LPG = Ozone Season Daily emissions from liquid propane gas combustion
EF LPG i = Emission factor for LPG combustion for pollutant i
LPG Space Heat - J = LPG consumed for space heating in county j
HDD Co Oz Season = Number of heating degree da ys in county for ozone season
HDD Co Annual = Number of heating degree days in county in the calendar year 2002
LPG Hot water/App - J = LPG consumed for during ozone se ason by hot water and appliances in county j
Ozone DAYS = Number of days in the ozone season: 214 Residential; 168 Commercial

Residential LPG Combustion Sample Calculation (Baltimore City) (tons / ozone season day)

Total Residential LPG Consumption – State of Maryland 56,532 kgal

To calculate spatial apportioning factor for Baltimore City:

HDD INVENTORY COUNTY x NHU INVENTORY COUNTY SAF BALTIMORE CITY = ∑ ALL COUNTIES IN STATE (HDD COUNTY x NHU COUNTY )

SAF BALTIMORE CITY = 0.07543338

To calculate kilogallons of liquified petroleum gas (LPG) used in Baltimore County:

Residential LPG BALTIMORE CITY = SAF BALTIMORE COUNTY x LPG TOTAL STATE Residential LPG BALTIMORE CITY = 0.07543338 x 56,532 Residential LPG BALTIMORE CITY = 4,264.4 kilogallons

LPG used for cooking & appliances in Baltimore City Residential LPG Hot water/App - J = 25% x LPG BALTIOMORE COUNTY Residential LPG Hot water/App - J = 25% x 4,264.4 Residential LPG Hot water/App - J = 1,066.1 kilogallons

LPG used for space heating in Baltimore County Residential LPG Space Heat - J = 4,264.4 – 1,066.1 Residential LPG Space Heat - J = 3,198.3152 LPG used for space heating in ozone season in Baltimore City

HDD PERIOD Residential Space Heating Fuel PERIOD = Space Heating Fuel

ANNUAL x HDD ANNUAL 0.00 Residential Space Heating Fuel PERIOD = 3,198.3 x 3884

Residential Space Heating Fuel PERIOD = 0.00 kgal

LPG used for hot water and appliances in ozone season in Baltimore County

Months ozone season Residential Hot Water Fuel PERIOD = Hot Water Fuel ANNUAL x Months Year

7 Residential Hot Water Fuel PERIOD = 1,066.1 x 12

Residential Hot Water Fuel PERIOD = 621.89 kgal

Equation:

VOC Ozone Season Day Emission Calculation

(EF LPG i x LPG Space Heat - J ) + (EF LPG i x LPG Hot water/App - J ) (2000 x 214) E LPG =

(0.5 x 0.00 ) + (0.5 x 621.89) E LPG = (2000 x 214)

E LPG = 0.00073 tons VOC / Ozone season day153 4.1.6.7 Wood Combustion SCC: 21 04 008 000 (Residential Wood Combustion)

This source category covers air emissions from wood combustion in th e residential sectors primarily for space heating and aesthetics. This MANE-VU RWC inve ntory includes emission estimates for indoor wood-burning equipment (e.g . fireplaces, woodstoves, pellet stoves,furnaces/boilers) and outdoor woodburning equipment (e.g. outdoor fireplaces, fire pits, woodfired barbecues, chimineas).

PM 10 , SOx, NOx, CO, VOC, and Toxics

The method used to calculate emissions is pres ented in a study/survey conducted by the MidAtlantic Regional Air Management Associ ation (MARAMA), titled “Residential Wood Combustion Emission Inventory.” 96

Activity In order to improve the RWC inventory fo r MANE-VU, a survey was developed and implemented in the region. The data sources used to construct the inventory include census tract-level housing data from the 2000 census. At the census tract-level, housing units are broken out into two categories: singlefamily units (including both detached and attached units up to two units ) and multi-family units (all other housing un its, including mobile homes). In previous technical memora nda, Pechan described the development of these data and the methods used to designate MANE-VU census tracts into one of three categories: urban, suburban, and rural. The rural category was furt her broken out into forested and non-forested categories.

The survey results were converted to emissions per survey response, and were then used to develop an emissions model for the source ca tegory. For indoor wood burning equipment, the survey was designed to obtain inform ation on equipment type. Indoor equipment includes fireplaces, woodstoves (both conventio nal and certified), furnace/boilers and pellet stoves. However, due to concerns re garding the loss of statistical precision in estimating equipment level emissions, estimates at the equipment level were not made.

96 Residential Wood Combustion Emission Inventory, Preparted by E.H. Pechan & Associates, Inc. for the MidAtlantic Regional Air Management Association, dated June 22, 2004. Description

Pollutants

Method and Data Sources154 Emissions were estimated at a more genera l level: outdoor and indoor equipment. Outdoor equipment includes barbeques, fireplaces, fire pits, and chimineas.

During this project, Pechan prepared six te chnical memoranda (TM) to document different phases of the project. The reader should consult these documents, located on the MidAtlantic/Northeast Visibility Union (MANE-VU) website www.mane-vu.org or on the Mid-Atlantic Regional Air Management Association’s (MARAMA’s) website

www.marama.org for details on each component of the project. The technical memoranda and important follow-up notes are as follows:

• TM#1- MANE-VU Residential Wood Combus tion EI Project: Sample Frame Development – this TM described the development of the sample frame to be used during the project. Note that the sample fr ame had incorrect values of the number of homes in the MANE-VU Region. This issue was resolved prior to data analysis and inventory development. The correct values are shown in Table 1 below. The total number of MANE-VU single- family households was 12,660,767 and the total number of multi-family units was 12,265,129;

• TM#2 - MANE-VU Residential Wood Combustion EI Project: Format for Activity Data in the Wood Consumption Model – This TM described the data formats for developing the wood consumption model from the survey data, including temporal profiles. Note that for indoor equipment, most of the me thods were not used si nce equipment-specific consumption estimates were not used to develop emission estimates (instead, the general linear model presented in TM#5 was used);

• TM#3 - MANE-VU Residential Wood Combustion EI Project: Pilot Survey and Final Survey Instrument – This TM provided the results of the pilot survey and the final survey instrument (questionnaire) for the survey);

• TM#4 - Results of MANE-VU Residentia l Wood Combustion Activity Survey – This TM provided statistical summaries of the survey results;

• TM#5 - MANE-VU Residential Wood Combusti on Survey Data Analysis and Emission Inventory Inputs – this TM provided a description of the methods used to analyze the survey data, the development of activity va riables to estimate emissions from indoor and outdoor equipment, and the emission fact ors to be applied. It was during the review of this TM that a different met hod was developed to estimate emissions for indoor equipment based on emission estimates constructed from each survey response (instead of estimating equipment level activ ity, which was originally envisioned for this project). This new method avoided the lo wering of statistical precision (error) in the extrapolation of survey data, since i ndividual responses were not divided into multiple equipment types. A description of the development of the general linear model for estimating emissions from indoor equipm ent was incorporated into the final TM. Outdoor equipment emissions were estimated using a user fraction (UF) and annual consumption (AC) estimate developed from the survey data; and

• TM#6 - MANE-VU Residential Wood Combustion Emission Inventory – this TM provided the results of the emission inve ntory constructed from the number of households in the 2000 Census (no adjustme nts to reflect 2002 housing changes were made) and the activity variables and emi ssion factors documented in TM#5. During a155 review of the draft TM#6, reviewers que stioned the wood density value used by Pechan to construct the activity variables in TM#5 (2.1 tons/cord; based on the high end of the range reported for oak species). Pe chan reviewed the primary types of wood reported by the survey respondents. Oak/hic kory was the most popular choice provided in the survey and very little softwood (e.g., pine, hemlock) was reported. The next most popular choice was “other hardwood”. Pechan developed a weighted estimate of wood density from the survey responses of 1.8 tons/cord that was used to scale the emission estimates by a factor of 0.86 (1.8/2.1).

Emission Factors Emission factors for wood combustion in residen tial fireplaces are presented in Table 1.9-1 Section 1.9 of AP-42 . The wood combustion emission factor for PM may be assumed to represent PM 10 emissions. Because no emission factor s were located for the combustion of wood for commercial consumption, emission factor s for residential fireplaces were used to estimate commercial emissions.

Residential Wood Combusti on Emission Factors
NOx (lbs./ton) CO (lbs./ton) VOC (lbs./ton) PM 10 (lbs./ton) SOx (lbs./ton)
Residential 2.6 252.6 229 34.6 0.4

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial To produce county-level temporal profiles, the same process used to go from response level profiles to group-level prof iles was used to go from gr oup profiles to county profiles. Activity or emissions for each census tract we re assigned to each temporal unit based on the tract level temporal profiles. These values were then summed across all tracts in the county and normalized to gi ve activity fractions. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations156 Temporal Temporal allocation profiles were also devel oped for this project using the residential wood survey data. Profiles were first deve loped for each sample group. Activity (for outdoor equipment) or emissions (for indoor equipment) for each respondent was divided among the different temporal units (e.g., di urnal, weekly, monthly), based on their response to the temporal survey questions. For example, if a respondent reported only burning wood on weekdays, the activity value di vided by 5 was assigned to each weekday, with zero activity assigned to Saturday and Sunday. For the diurnal profiles, the survey data indicated whether respondents burned wood in the morning, evening, or both. Since it is unlikely that emissions take place only in the morning and evening hours, activity was allocated to the entire 24-hour period by assigning 75% of mo rning activity to the hours of 6 a.m. to 12 p.m. and 25% of the morning ac tivity to the hours 12 midnight to 6 p.m. The hours of 6 p.m. to 12 noon were assigned 75% of the evening activ ity; and 25% of the evening activity went to the hours 12 midnight to 6 a.m.

Once a fraction of the total activity was assi gned to each temporal unit for each survey response, the temporal unit activity was summed across all respondents in that sample group. (i.e., survey frame cell; sample groups used for the temporal profiles are the same as those use to develop model parameters.) Th e resulting activity values were used to calculate activity fractions (i.e., activity for Monday was divided by the sum of activity for Monday through Sunday). The resulting profiles were then assigned to each census tract based on the sample group (survey frame cell).

Monthly Temporal Allocation Files

FIPS ST FIPS CNTY May June July Aug Sept Oct Nov Dec Jan Feb March April

INDOOR EQUIPMENT

24 001 0.0201 0.0061 0.0053 0.0059 0.0330 0.0703 0.1329 0.1895 0.2107 0.1835 0.1018 0.0408

24 003 0.0300 0.0079 0.0004 0.0004 0.0155 0.0679 0.1351 0.2086 0.2263 0.1826 0.0954 0.0299

24 005 0.0192 0.0051 0.0004 0.0004 0.0154 0.0676 0.1330 0.2111 0.2343 0.1868 0.0997 0.0269

24 009 0.0302 0.0069 0.0003 0.0003 0.0196 0.0821 0.1376 0.1881 0.2271 0.1751 0.0992 0.0336

24 011 0.0411 0.0108 0.0049 0.0049 0.0213 0.0747 0.1464 0.1912 0.1869 0.1594 0.1101 0.0483

24 013 0.0381 0.0096 0.0015 0.0015 0.0197 0.0801 0.1412 0.1878 0.2108 0.1688 0.1021 0.0388

24 015 0.0272 0.0063 0.0012 0.0012 0.0201 0.0792 0.1387 0.1913 0.2234 0.1748 0.1015 0.0349

24 017 0.0264 0.0059 0.0004 0.0004 0.0192 0.0798 0.1365 0.1922 0.2298 0.1773 0.0995 0.0324

24 019 0.0396 0.0104 0.0052 0.0052 0.0214 0.0739 0.1464 0.1923 0.1866 0.1596 0.1109 0.0485

24 021 0.0270 0.0062 0.0003 0.0003 0.0192 0.0807 0.1367 0.1908 0.2296 0.1770 0.0999 0.0324

24 023 0.0135 0.0028 0.0001 0.0001 0.0308 0.0830 0.1328 0.1922 0.2346 0.1795 0.0992 0.0315

24 025 0.0258 0.0059 0.0002 0.0002 0.0186 0.0785 0.1361 0.1942 0.2311 0.1790 0.0991 0.0313

24 027 0.0171 0.0037 0.0002 0.0002 0.0171 0.0728 0.1326 0.2046 0.2397 0.1855 0.0988 0.0275

24 029 0.0354 0.0091 0.0062 0.0062 0.0220 0.0718 0.1465 0.1953 0.1853 0.1591 0.1130 0.0500

24 031 0.0283 0.0084 0.0005 0.0005 0.0132 0.0612 0.1342 0.2179 0.2238 0.1861 0.0978 0.0278

24 033 0.0288 0.0084 0.0005 0.0005 0.0141 0.0642 0.1351 0.2134 0.2234 0.1845 0.0985 0.0286

24 035 0.0420 0.0110 0.0048 0.0048 0.0213 0.0751 0.1465 0.1905 0.1870 0.1592 0.1095 0.0483

24 037 0.0232 0.0050 0.0016 0.0016 0.0203 0.0787 0.1377 0.1930 0.2259 0.1755 0.1026 0.0349157 Monthly Temporal Allocation Files

FIPS
ST FIPS
CNTY May June July Aug Sept Oct Nov Dec Jan Feb March April

24 039 0.0388 0.0102 0.0053 0.0053 0.0214 0.0735 0.1464 0.1929 0.1865 0.1598 0.1115 0.0485

24 041 0.0405 0.0106 0.0050 0.0050 0.0214 0.0744 0.1464 0.1917 0.1867 0.1594 0.1104 0.0485

24 043 0.0282 0.0067 0.0007 0.0007 0.0192 0.0793 0.1377 0.1918 0.2257 0.1761 0.1006 0.0334

24 045 0.0454 0.0122 0.0035 0.0035 0.0200 0.0758 0.1455 0.1900 0.1908 0.1616 0.1063 0.0454

24 047 0.0454 0.0127 0.0016 0.0016 0.0189 0.0790 0.1444 0.1864 0.1981 0.1655 0.1059 0.0405

24 510 0.0155 0.0090 0.0017 0.0017 0.0106 0.0548 0.1384 0.2232 0.2074 0.1892 0.1241 0.0245

OUTDOOR EQUIPMENT

24 001 0.11361 0.16657 0.20437 0.18379 0.12888 0.05809 0.02881 0.02123 0.01978 0.00000 0.02695 0.02802

24 003 0.13179 0.16662 0.19877 0.17039 0.12977 0.04442 0.02922 0.01872 0.01575 0.00000 0.04004 0.03449

24 005 0.12837 0.16509 0.19193 0.16790 0.12382 0.05275 0.03363 0.02165 0.01721 0.00000 0.03996 0.03403

24 009 0.11321 0.16773 0.21049 0.18790 0.13325 0.05402 0.02540 0.01941 0.01934 0.00000 0.02486 0.02731

24 011 0.10593 0.16687 0.20836 0.19049 0.12970 0.06266 0.02771 0.02177 0.02134 0.00000 0.02094 0.02514

24 013 0.11553 0.16720 0.20701 0.18443 0.13134 0.05428 0.02702 0.01995 0.01907 0.00000 0.02736 0.02840

24 015 0.11000 0.16659 0.20563 0.18655 0.12881 0.06069 0.02865 0.02168 0.02057 0.00000 0.02431 0.02673

24 017 0.11655 0.16681 0.20465 0.18238 0.12990 0.05500 0.02820 0.02045 0.01902 0.00000 0.02871 0.02896

24 019 0.10548 0.16661 0.20714 0.18996 0.12868 0.06400 0.02848 0.02226 0.02157 0.00000 0.02102 0.02511

24 021 0.11607 0.16641 0.20270 0.18141 0.12834 0.05690 0.02938 0.02117 0.01932 0.00000 0.02900 0.02899

24 023 0.10116 0.16661 0.20852 0.19317 0.12850 0.06721 0.02835 0.02284 0.02252 0.00000 0.01790 0.02357

24 025 0.12098 0.16625 0.20030 0.17722 0.12792 0.05386 0.03000 0.02077 0.01831 0.00000 0.03280 0.03082

24 027 0.12475 0.16568 0.19613 0.17253 0.12590 0.05323 0.03180 0.02119 0.01774 0.00000 0.03642 0.03245

24 029 0.10113 0.16672 0.20914 0.19358 0.12895 0.06678 0.02800 0.02265 0.02247 0.00000 0.01770 0.02350

24 031 0.13241 0.16548 0.19262 0.16615 0.12544 0.04830 0.03262 0.02049 0.01614 0.00000 0.04228 0.03528

24 033 0.13175 0.16539 0.19237 0.16636 0.12508 0.04913 0.03286 0.02073 0.01633 0.00000 0.04194 0.03509

24 035 0.10592 0.16713 0.20975 0.19138 0.13071 0.06167 0.02693 0.02135 0.02122 0.00000 0.02051 0.02500

24 037 0.10505 0.16657 0.20711 0.19017 0.12854 0.06444 0.02856 0.02237 0.02168 0.00000 0.02076 0.02497

24 039 0.10571 0.16636 0.20580 0.18898 0.12776 0.06475 0.02920 0.02262 0.02163 0.00000 0.02157 0.02531

24 041 0.10549 0.16682 0.20825 0.19066 0.12950 0.06317 0.02784 0.02191 0.02146 0.00000 0.02069 0.02501

24 043 0.11722 0.16613 0.20092 0.17965 0.12735 0.05707 0.03022 0.02146 0.01919 0.00000 0.03026 0.02953

24 045 0.11599 0.16691 0.20535 0.18312 0.13025 0.05505 0.02790 0.02036 0.01910 0.00000 0.02815 0.02871

24 047 0.12227 0.16445 0.19054 0.17033 0.12113 0.05972 0.03535 0.02351 0.01886 0.00000 0.03655 0.03217

24 510 0.12772 0.16163 0.17411 0.15695 0.11060 0.06637 0.04384 0.02736 0.01896 0.00000 0.04492 0.03553

Weekly Temporal Allocation Files

FIPS ST FIPS CNTY Monday Tuesday Wednesday Thursday Friday Saturday Sunday

INDOOR EQUIPMENT

24 001 0.13598 0.13598 0.13598 0.13598 0.13598 0.16005 0.16005

24 003 0.11604 0.11604 0.11604 0.11604 0.11604 0.20989 0.20989

24 005 0.12313 0.12313 0.12313 0.12313 0.12313 0.19219 0.19219

24 009 0.12450 0.12450 0.12450 0.12450 0.12450 0.18875 0.18875

24 011 0.12238 0.12238 0.12238 0.12238 0.12238 0.19406 0.19406158 Weekly Temporal Allocation Files

FIPS ST FIPS
CNTY Monday Tuesday Wednesday Thursday Friday Saturday Sunday

24 013 0.12112 0.12112 0.12112 0.12112 0.12112 0.19719 0.19719

24 015 0.12648 0.12648 0.12648 0.12648 0.12648 0.18380 0.18380

24 017 0.12558 0.12558 0.12558 0.12558 0.12558 0.18605 0.18605

24 019 0.12332 0.12332 0.12332 0.12332 0.12332 0.19169 0.19169

24 021 0.12565 0.12565 0.12565 0.12565 0.12565 0.18588 0.18588

24 023 0.13346 0.13346 0.13346 0.13346 0.13346 0.16634 0.16634

24 025 0.12496 0.12496 0.12496 0.12496 0.12496 0.18760 0.18760

24 027 0.12650 0.12650 0.12650 0.12650 0.12650 0.18374 0.18374

24 029 0.12617 0.12617 0.12617 0.12617 0.12617 0.18458 0.18458

24 031 0.11428 0.11428 0.11428 0.11428 0.11428 0.21429 0.21429

24 033 0.11579 0.11579 0.11579 0.11579 0.11579 0.21053 0.21053

24 035 0.12180 0.12180 0.12180 0.12180 0.12180 0.19549 0.19549

24 037 0.12892 0.12892 0.12892 0.12892 0.12892 0.17769 0.17769

24 039 0.12380 0.12380 0.12380 0.12380 0.12380 0.19051 0.19051

24 041 0.12278 0.12278 0.12278 0.12278 0.12278 0.19305 0.19305

24 043 0.12502 0.12502 0.12502 0.12502 0.12502 0.18744 0.18744

24 045 0.11804 0.11804 0.11804 0.11804 0.11804 0.20490 0.20490

24 047 0.11800 0.11800 0.11800 0.11800 0.11800 0.20500 0.20500

24 510 0.12785 0.12785 0.12785 0.12785 0.12785 0.18038 0.18038

OUTDOOR EQUIPMENT

24 001 0.05066 0.05066 0.05066 0.05066 0.05066 0.37335 0.37335

24 003 0.05127 0.05127 0.05127 0.05127 0.05127 0.37182 0.37182

24 005 0.05036 0.05036 0.05036 0.05036 0.05036 0.37410 0.37410

24 009 0.05125 0.05125 0.05125 0.05125 0.05125 0.37187 0.37187

24 011 0.05056 0.05056 0.05056 0.05056 0.05056 0.37359 0.37359

24 013 0.05105 0.05105 0.05105 0.05105 0.05105 0.37237 0.37237

24 015 0.05055 0.05055 0.05055 0.05055 0.05055 0.37362 0.37362

24 017 0.05088 0.05088 0.05088 0.05088 0.05088 0.37280 0.37280

24 019 0.05041 0.05041 0.05041 0.05041 0.05041 0.37397 0.37397

24 021 0.05065 0.05065 0.05065 0.05065 0.05065 0.37337 0.37337

24 023 0.05027 0.05027 0.05027 0.05027 0.05027 0.37432 0.37432

24 025 0.05073 0.05073 0.05073 0.05073 0.05073 0.37318 0.37318

24 027 0.05055 0.05055 0.05055 0.05055 0.05055 0.37363 0.37363

24 029 0.05033 0.05033 0.05033 0.05033 0.05033 0.37417 0.37417

24 031 0.05069 0.05069 0.05069 0.05069 0.05069 0.37327 0.37327

24 033 0.05062 0.05062 0.05062 0.05062 0.05062 0.37344 0.37344

24 035 0.05070 0.05070 0.05070 0.05070 0.05070 0.37324 0.37324

24 037 0.05038 0.05038 0.05038 0.05038 0.05038 0.37405 0.37405

24 039 0.05029 0.05029 0.05029 0.05029 0.05029 0.37427 0.37427

24 041 0.05053 0.05053 0.05053 0.05053 0.05053 0.37369 0.37369

24 043 0.05054 0.05054 0.05054 0.05054 0.05054 0.37364 0.37364

24 045 0.05091 0.05091 0.05091 0.05091 0.05091 0.37272 0.37272

24 047 0.04982 0.04982 0.04982 0.04982 0.04982 0.37544 0.37544

24 510 0.04852 0.04852 0.04852 0.04852 0.04852 0.37871 0.37871159 A sample calculation for annual activity is provi ded below for a specified census tract and SCC:

Activity (tons/yr) = (HUs x UFs x As ) + (HUo x UFo x A0) (equation 1)

Where: HUs = single-family housing units; UFs = single-family housing units user fraction for equipment type (SCC); As = single-family housing units annual activity (tons/yr); HUo = other housing units; UFo = other housing units user fract ion for equipment type (SCC); and Ao = other housing units annual activity (tons/yr).

For each SCC, the annual activity can be aggregated from the census tract to the county or state levels using the FIPS code in Table 3a. If, durin g the analysis of survey data, Pechan finds a good correlation between wood consumption and a nnual HDD, the activity variable will take the form of tons/HDD-yr (where HDD are annual he ating-degree days). Th e calculation of annual activity for a specified census tract and SCC woul d take the form shown in equation 2 below:

Activity (tons/yr) = [HUs x UFs x (As x HDD )] + [HUo x UFo x (A0 x HDD)] (equation 2)

Where: HUs = single-family housing units; UFs = single-family housing units user fraction for equipment type (SCC); As = single-family housing units annual activity (tons/HDD-yr); HDD = annual heating-degree da ys for the census tract; HUo = other housing units; UFo = other housing units user fract ion for equipment type (SCC); and Ao = other housing units an nual activity (tons/HDD-yr). Emissions Calculation160 4.1.7 FUGITIVE SOURCES

Other area sources include forest fires, slash and prescribed burning, agricultural burning, structure fires, orchard heaters, leaking underground storage tanks and natural organic sources. Although often intermittent in nature, many of these sources can produce large quantities of air pollutant emissions.

4.1.7.1 Residential Construction Activity
SCC: 23 11 010 000

This source category covers fugiti ve dust emissions from resident ial construction activities.

PM 10 and PM 2.5

Activity For residential construction, housing permit da ta for single-family units, two-family units, and apartments were obtained at the count y level from the U.S. Department of Commerce’s (DOC) Bureau of the Census. Adju sted county permit data to equal regional housing start data that was also obtain ed from the Bureau of the Census.

Estimated the number of buildings in each ca tegory, and then estimated the total acres disturbed by construction by applying conversio n factors to the housing start data for each category as follows:

• Single-family 1⁄4 acre/building • Two-family 1⁄3 acre/building • Apartment 1⁄2 acre/building

Housing construction PM10 emissions are calc ulated using an emission factor of 0.032 tons PM10/acre/month, the number of housing units created, a units-to-acres conversion factor, and the duration of construction activ ity. The duration of c onstruction activity for houses is assumed to be 6 months.

Apartment construction emissions are calculate d separately using an emission factor of 0.11 tons PM10/acre/month. A duration of 12 months was assumed for apartment construction. Description

Pollutants

Method and Data Sources161 For areas in which basements are constructed to estimate the cubic yards of dirt moved per house, an average value of 2000 square feet is assumed for both single family and twofamily homes. Multiplying the average total s quare feet by an average basement depth of 8 feet and adding in 10 percent of the cubic f eet calculated for peripheral dirt removed produces an estimate of the cubic yards of ear th moved during resident ial construction. The percentage of one-family houses with ba sements was obtained from the DOC. The percentage of houses per Census region (Nor theast, Midwest, South, and West) that contain full or partial baseme nts is applied to the housing start estimates for each of these respective regions. The best available c ontrol measures (BACM) Level 2 equation (emission factor of 0.011 tons PM10/acre/m onth plus 0.059 tons PM10/1000 cubic yards of on-site cut/fill) is applied once the numb er of acres disturbed due to the estimated number of houses built with basements is determined.

Emission Factors

Single-family Construction Two-family Construction Multi-family Construction

ton PM 10 /acre/month ton PM 10 /acre/month ton PM 10 /acre/month

PM 10 Emission
Factor 0.032 0.032 0.11

Duration of Activity 6 months 6 months 12 months

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations162 E RC I = E RC – SFH + E RC – 2FAM + E RC – MF

where:
E RC i = Emissions of pollutant i in tons per year from residentia l construction activity

E RC - SFH = Emissions of pollutant i in tons pe r year from residential single-family home construction activity
E RC – 2FAM = Emissions of pollutant i in tons per year from residential two-family home construction activity
E RC – MF = Emissions of pollutant i in tons per year from residential multi-family construction activity

and:

E RC – SFH = E RC – SFH, w BM + E RC – SFH , w/o BM

where:
E RC – SFH, w BM = Emissions of pollutant i in tons per year from resi dential single-family home construction activity of homes with basements
E RC – SFH, w/o BM = Emissions of pollutant i in tons pe r year from residential single-family home construction activity of homes without basements

HS SFH x (1- HS SFH,w BM ) x (AD RC – SFH ) x (PD RC – SFH ) x EF RC – SFH E RC – SFH, w/o BM = 2000

where:
E RC – SFH, w/o BM = Emissions of pollutant i in tons pe r year from residential single-family home construction activity
HS SFH = Residential single-family housing starts
HS SFH, w BM = Percent of residential single-f amily housing starts with basements
AD RC - SFH = Acres disturbed per housing t ype (residential single-family)
PD RC - SFH = Average project duration in months
EF RC – SFH i = Emissions factor in tons PM10/acre/month for pollutant i Emissions Calculation163 E RC – SFH, w BM = Emissions from residential construction + Emissions from basement excavation

[HS SFH x HS SFH,w BM x (AD RC – SFH ) x (PD RC – SFH ) x EF RC – SFH ] + [HS SFH x HS SFH,w BM x AHS RC – SFH x ABD RC – SFH x PDE RC – SFH x EF Acres-Disturb ] E RC – SFH, w BM = 2000

where:
E RC – SFH, w BM = Emissions of pollutant i in tons pe r year from residential single-family home construction activity
HS SFH = Residential single-family housing starts
HS SFH, w BM = Percent of residential single-f amily housing starts with basements
AD RC - SFH = Acres disturbed per housing t ype (residential single-family)
PD RC - SFH = Average project duration in months
EF RC – SFH i = Emissions factor in tons PM10/acre/month for pollutant i
AHS RC - SFH = Average residential single-family house size (national default = 2000 ft 2 )
ABD RC - SFH = Average basement depth for re sidential single-family homes (national default = 8 ft)
PDE RC – SFH = Peripheral dirt excavated for residential single-family homes (national default = 10 percent)
EF Acres-Disturb = Emissions factor for the acres disturbed during basement excavation activities during residential single-fa mily home construction in tons
PM 10 /1000 cubic yards164 4.1.7.2 Heavy Construction Activity
SCC: 28 10 001 000

Emissions produced from the construction of nonr esidential buildings are estimated using the value of construction put in place. The nationa l value of construction put in place is obtained from the Bureau of the Census 97 . The national value of construc tion put in place is allocated to the state level using non-resid ential building construction em ployment data within NAIC 2333 obtained from 2002 County Business Patterns 98 . The state value of construction put in place is allocated to the county level usi ng non-residential building constr uction employment data within NAIC 2333 obtained from the 2002 County Business Patterns 99 for the State of Maryland.

PM 10 and PM 2.5

Activity

ARMA used data from the U.S. Census Bureau on the national value of construction put in place. The national value of construction put in place is allocated to the state level and then to the county level us ing non-residential building c onstruction employment data within NAIC 2333 obtained from 2002 County Business Patterns.

A conversion factor of 1.6 acres/10 6 dollars ($) is applied to the construction valuation
data. This conversion factor is developed by adjusting the1992 value of 2 acres/$10 6 to 2002 and 2000 constant dollars using the Price and Cost Indices for Construction. The duration of construction activity for nonresidential construc tion is estimated to be 11 months.

Employee numbers were taken from C ounty Business Patterns 2002 - Maryland , NAIC 2333, Non-residential Building Construction. Some county employment data is represented by a letter code i ndicating a range for the number of employees for that SIC. In this case the arithmetic average number of employees per letter code per county was

97 Bureau of Census, Table 1. Annual Value of Construction Put in Place in the United States : 1997 – 2001; http://www.census.gov/const/c30/tab101.txt

98 U.S. Census Bureau, County Business Patterns, 2002 http://censtats.census. gov/cbpnaic/cbpnaic.shtml Select U.S. then 2002 then Compare fo r the “Construction” Industry then Compary NAIC 2333

99 U.S. Census Bureau, County Business Patterns, 2002 http://quickfacts.census. gov/qfd/states/24000.html Select county then “Browse more data sets” then County Business Patte rns Economic Profile for 2002 – Repeat for each county. Description

Pollutants

Method and Data Sources165 adjusted so that the state to tal employment in a NAIC matc hed the sum of the number of employees reported per county.

Emission Factors

PM 10 PM 2.5 (tons/acre/month) (tons/acre/month)
Emissions 0.11 20% of PM 10 Duration of Project 11 months

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

Number of Employees within NAIC 2333 in Maryland Value of Construction Work in Maryland = Value of Construction Work in the U.S. x Number of Employees within NAIC 2333 in the U.S.

Value of Construction Work in the U.S. $167,084,000,000.00

Number of Employees within NAIC 2333 in the
U.S. 855,483 Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations

Emissions Calculation166 Number of Employees within NAIC 2333 in Maryland 19,267

19,267 Value of Construction Work in Maryland = $167,084,000,000.00 x 855,483 Value of Construction Work in Maryland = $3,763,029,105

HC j x CF HC x EF HC i x DC HC E HC i = 365

where:
E HC,i = Emissions of pollutant i in t ons per day from heavy construction
HC J = Value of heavy construction (million dollars) in county j in 2002
CF HC = Conversion factor (acres/million dollars) for heavy construction (1.6 )
EF HC i = Emissions factor in tons pe r acre per month for pollutant i
DC HC = Duration of construc tion activity (11 months)

2002 Sample Calculation Heavy C onstruction (Anne Arundel County)

HC j x CF HC x EF HC i x DC HC E HC i = 365
196.68 x 1.6 x 0.11(PM 10) x 11 E HC i = 365

E HC i = 1.04 tons/day PM 10167 4.1.7.3 Road Construction Activity
SCC: 28 10 001 000

This source category covers fugitive dust em issions from road c onstruction activity. PM 10 emissions produced by road construction are estimated using an emission factor for heavy construction and the State capital ou tlay for new road construction.

PM 10 and PM 25

Activity To estimate the acres disturbed by road cons truction, the Federal Highway Administration (FHWA) State expenditure data for capit al outlay according to the following six classifications was obtained: • Interstate, urban; • Interstate, rural; • Other arterial, urban; • Other arterial, rural; • Collectors, urban; and • Collectors, rural

Dollar expenditures are converted to miles contructed using data obtained from the North Carolina Department of Transportation (NC DOT) on the $/mile sp ent on various road construction projects. For interstate expenditu res, used an average of $4 million/mile corresponding to freeways and interstate projec ts listed for: 1) new location; 2) widen existing 2-lane shoulder section; and 3) widen existing 4-lane w/ median. For expenditures on other arterial and collectors, used an average of $1.9 million/mile corresponding to all other projects (excluding fr eeways and interstate pr ojects) listed for: 1) new location; 2) widen existing 2-lane shou lder section; and 3) widen existing 4-lane w/ median.

Miles are converted to acres fo r each of the 6 road types us ing the following estimates of acres disturbed per mile: • Interstate, urban and rural; Othe r arterial, urban - 15.2 acres/mile • Other arterial, rural - 12.7 acres/mile • Collectors, urban - 9.8 acres/mile • Collectors, rural - 7.9 acres/mile Description

Pollutants

Method and Data Sources168 Emission Factors

An PM 10 emission factor of 0.42 tons/acre/month is used to account for the large amount of dirt moved during the construction of ro adways. The duration of construction activity for road construction is estimated to be 12 months.

PM 25 emissions are estimated by applying a particle size multiplier of 0.20 to PM 10 emissions.

Soil Moisture Level To account for the soil moisture level, base emissions were multiplied by 24 divided by the precipitation-evaporation (PE) value. Precipitation-Evaporation (PE) values were obtained from Thornthwaite’s PE Index. Average PE values for each State were estimated based on PE values for specific climatic divisions within a State.

Silt Content To account for the silt content, base emissions were multiplied by percent dry silt content in soil divided by 9 percent. County-leve l dry silt values were applied to PM 10 emissions for each county

. .

No subtration of emissions fr om point sources is necessary.

For construction emissions, a control efficiency of 50 percent is used for both PM 10 and PM 2.5 for PM nonattainment areas.

Spatial

State-level estimates of acres disturbed ar e distributed to counties according to the housing starts per county, estimated for the residential construction category.

Temporal Data for temporal allocation is not available for this source. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations169 Exp x MC i x ADi x EF RC i x DUR E RC, i = 2000 x 365

where:
E RC,i = Emissions of pollutant i in t ons per day from road construction Exp RC,i = Expenditures per road type i
MC RC,i = Miles contructed per road type i
AD i = Acres disturbed per road type i
EF RC i = Emissions factor (tons per acre per month for pollutant i) DUR = Duration of project (months) Emissions Calculation170 4.1.7.4 Agricultural Land Preparation
SCC: 28 01 000 003

The land preparation source category includes estimates of the airborne soil particulate emissions produced during the preparation of agricultural lands for planting and after harvest activities. Operations included in this met hodology are discing, tilling, leve ling, chiseling, plowing, and other mechanical operations used to prepar e the soil. Dust emissions are produced by the mechanical disturbance of the soil by the im plement used and the tractor pulling it. Soil preparation activities tend to be performed in the early spring and fall months.

Particulate emissions from land preparation ope rations are computed by multiplying an emission factor (EF) by an activity fact or. The agricultural tilling emi ssion factor provided in the 4th edition of U.S. EPA’s AP-42 document is used to estimate soil preparation emissions. The activity factor is based on the number of acres of each crop in production for each county in the State. Because different crops n eed different operations to prepar e the soil, each crop also has its own acre-pass value. Acre-passes ar e the number of passes, per acre, that are typically needed to prepare a field for planting a particular crop. By combining the crop acre age, crop specific acrepass data, and the agricultural ti lling emission factor, we estimate the particulate matter produced by agricultural land pr eparation operations.

Agricultural soil preparation partic ulate dust emissions are estimated for each crop in each county in Maryland using the following equation:

Emissions CROP = Emission Factor x Acres CROP x Acre-passes/acre CROP

The crop emissions for each county are su mmed to produce the county and statewide particulate matter (PM) and PM emission estimates.

PM 10 and PM 2.5

Activity

The acreages used for estimating soil preparation emissions were collected from the Maryland Cooperative Extension Service and the Maryland Agricultural Statistics Service. A summary of crop acreage harvested in 2002 from individual county agricultural commissioner reports was used to calculate emissions. Description

Pollutants

Method and Data Sources171 In computing land preparation PM emissi ons, acre-passes are the number of passes typically performed to prepare a crop for planting. These operations may occur following harvest, or closer to planting, and can incl ude discing, tilling, land leveling, and other operations. Each crop is different in the type of soil operati ons performed and when they occur. MDE used acre-pass estimates compiled by the California Air Resources Board (CARB). For the crops that were not explici tly updated, we either applied an updated crop profile from a similar crop, or used one of the existing CARB profiles. Table 3.4-a Summary of Crop Acre-Passes , presented in Section 3.4, provides a listing of the crop acre-passes used in California.

Emission Factors

The emission factor used to estimate the dust emissions from agricultu ral land preparations is from U.S. EPA’s AP-42 100 . This emission factor was de veloped in 1981 based on test data measured in California and Kansas by Midw est Research Institute. Because of a lack of more detailed estimates, this single emissi on factor is used for all land preparation operations, all locations, and all seasons. The form of the emission factor is:

Emission Factor (lbs PM/acre-pass) = k (4.8) (s) 0.6

Where:

k = particle size fraction of inte rest (EPA default = 0.042 for PM 2.5 or 0.21 for PM 10 ) s = average percent soil silt content (EPA default = 18%)

For PM the value of ‘k’ used in California is 0.148. This is based on the EPA estimate that 33% of the total particulate entrained to the air during agricultural operations is 30 microns or less. Of this, analysis of California soil samples indicates that about 45% of the 30 micron or less sized particles are 10 microns or less in aerodynamic size (i.e., PM ). So, the California PM particle size multiplier is 0.148 (i.e., 0.33 x 0.45 = 0.148). Maryland decided to use the EPA default values listed ab ove for the particle size fraction. For the percent soil silt value, the EPA default value of 18% soil silt is used for most counties.

PM 2.5 PM 10 (Lbs. PM 2.5 /acre-pass) (Lbs. PM 10 /acre-pass)
Emission Factor 1.141968254 5.709841268

The EPA emission factor does not include an association between soil moisture and emissions. Because it is known that dust emi ssions are reduced when soil moisture is higher, California ARB staff has incorporat ed an emission correction during the wettest months of the year. The correction was based on some limited agricultural dust source test data, as well as the control factor used fo r watering at constructi on sites and their best judgement. During December and March, Califo rnia ARB reduced the emission factor by

100 U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission Factors, AP-42, Section 11.2.2, Fourth Edition. September 1985.172 25% from the standard uncorrected value. In January and February, often the wettest months, the emission factor is reduced by 50%. This produces a seasonal emissions profile that is more consistent with California’s actual ambient air dust levels, and also better reflects that soil preparation ope rations typically do not occur while the soil is excessively wet or muddy.

Precipitation data for calendar year 2002 in Maryland is presented in Section 3.4, Table 3.4-b 2002 Precipitation Data , since Maryland does not have a correlation between soil moisture and emissions, the emission factors were not redacted.

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial Crop acreages are collected on a county basis.

Temporal Data for temporal allocation is not available for this source in Maryland.

In collecting updated acre-pass data, Californi a also collected detailed information on when agricultural operations occur. Using thes e data, it was possible to create detailed temporal profiles that help to indicate when PM emissions from land preparations may be highest. The more detailed background documen t includes detailed crop calendars for each crop with updated information. For all of th e acre-pass and crop calendar information, the farmers and other agricultural experts of the San Joaquin Valley were instrumental in helping us to update our crop information. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations173 EF ALP i x A I x AP I E ALP i = 2000

where:
E ALP = Annual PM emissions of pollutant i in tons per day from agricultural land preparations.
EF ALP i = Emissions factor in pounds per acre-pass for pollutant i
A i = Acres of crop I harvested in county j in 2002
AP i = Acre-passes per acres for crop i

2002 Sample Calculation Agricultural Land Preparation (Anne Arundel County)

EF ALP PM2.5 x [(A wheat x AP wheat ) + (A corn-gr x AP corn-gr ) + (A corn-silage x AP corn-silage ) + (A

hay x AP hay ) + (A soy x AP soy ) + (A barley x AP barley ) + (A tobacco x AP tobacco )] E ALP PM2.5 = 2000 1.141968254 x [(2500 x 1) + (5700 x 4) + (0 x 4) + (3100 x 1) + (5200 x 6) + (175 x 1) + (100 x 0)] E ALP PM2.5 = 2000 1.141968254 x 60475 E ALP PM2.5 = 2000

E ALP PM2.5 = 34.530 tons per year of PM 2.5 Emissions Calculation174 4.1.7.5 Paved Roads
SCC: 22 94 000 000

This source category covers fugitive dust em issions from activity on paved roads.

PM 10 and PM 2.5

ActivityThe basis for the activity data for fugitive dust emissions from paved roads is the statelevel vehicle miles traveled per paved road t ype and the state-level vehicle miles traveled per unpaved road per road type.

Emission Factors

The emission factor for paved roads is calcul ated from an empirical formula from AP-42 and then is adjusted for precipitation.

AP-42 Paved Roads Emission Factor Formula

EF PAVED RD = PSDPVD x (PVSILT/2) 0.65 x (WEIGHT/3) 1.5

where:
EF PAVED RD Paved road dust emission factor for all vehicle classes combined (grams per mile) PSDPVD Base emission factor for particles of less than 10 microns in diameter from paved road dust (default va lue = 7.3 grams PM 10 per mile) PVSILT Road surface silt loading factor in grams per square mile WEIGHT Average weight of all ve hicle types combined in tons

And where: PVSILT varies by road type and the average daily traffic volume (ADTV) that has been assigned the default values presented below: Description

Pollutants

Method and Data Sources175 Road Surface Silt Loading Constants ADTV
< 500 ADTV 500 - 5,000 ADTV 5,000 – 10,000 ADTV > 10,000 gram/mile 2 gram/mile 2 gram/mile 2 gram/mile 2

PVSILT 0.60 0.20 0.06 0.03

WEIGHT An average default value of 6,360 pounds (3.19 tons) has been assigned for all vehicles.

Calculate Paved Roads Emission Factors

EF PAVED-LOCAL < 500 = [PSDPVD x (PVSILT/2) 0.65 x (WEIGHT/3) 1.5 ] - C

EF PAVED-LOCAL < 500 = [7.3 x (0.60 / 2) 0.65 x (3.18 / 3) 1.5 ] – 0.2119

EF PAVED-LOCAL < 500 = 3.430692 gram/mile 2

EF PAVED_ADTV 500 – 5000 = [PSDPVD x (PVSILT/2) 0.65 x (WEIGHT/3) 1.5 ] - C

EF PAVED_ADTV 500 – 5000 = [7.3 x (0.2 / 2) 0.65 x (3.18 / 3) 1.5 ] – 0.2119

EF PAVED_ADTV 500 – 5000 = 1.571635 gram/mile 2

EF PAVED_ADTV 5000 – 10,000 = [PSDPVD x (PVSILT/2) 0.65 x (WEIGHT/3) 1.5 ] - C

EF PAVED_ADTV 5000 – 10,000 = [7.3 x (0.06 / 2) 0.65 x (3.18 / 3) 1.5 ] – 0.2119

EF PAVED_ADTV 5000 – 10,000 = 0.603575 gram/mile 2

EF PAVED_ADTV >10000 = [PSDPVD x (PVSILT/2) 0.65 x (WEIGHT/3) 1.5 ] - C

EF PAVED_ADTV >10000 = [7.3 x (0.03 / 2) 0.65 x (3.18 / 3) 1.5 ] – 0.2119

EF PAVED_ADTV >10000 = 0.307786 gram/mile 2

Adjust Emission Factor for Precipitation

EF PAVED ADJ = EF PAVED x CF RAIN

Where:
EF PAVED ADJ = Adjusted Paved Road Emission Factor (grams/mile)
EF PAVED = PM size-specific emission fact or (grams/mile) for paved roads
CF RAIN = Correction Factor for Rain/Precipitation

And Where:176 CF RAIN = 1 - (P / 4 N )

Where:
CF RAIN = Correction Factor for Rain/Precipitation p = number of days in a given month w ith greater than 0.01 inches of rainfall (data collected from mo nthly climatological data files from National Weather Service stations near or in the county of reference.)
N

= number of days in the averaging period (e.g., 365 for annual, 91 for seasonal, 30 for monthly).

MDE altered the precipitation adjustment equati on by collecting data on the number of days in a given year that greater than 0.01 inches of rainfall fell and removing the x 12 from the equation.

CF RAIN = 1 – (104 / (4 x 365))

CF RAIN = 0.928767

Calculate Paved Roads Emission Factors Adjusted for Precipitation

EF PAVED-LOCAL < 500 ADJ = EF PAVED_LOCAL x CF RAIN

EF PAVED-LOCAL < 500 ADJ = 3.430692 x 0.928767

EF PAVED-LOCAL < 500 ADJ = 3.186314 gram/mile 2

EF PAVED_ADTV 500 - 5000 ADJ = EF PAVED_LOCAL x CF RAIN

EF PAVED_ADTV 500 - 5000 ADJ = 1.571635 x 0.928767

EF PAVED_ADTV 500 - 5000 ADJ = 1.459683 gram/mile 2

EF PAVED_ADTV 5000- 10,000 ADJ = EF PAVED_LOCAL x CF RAIN

EF PAVED_ADTV 5000- 10,000 ADJ = 0.603575 x 0.928767

EF PAVED_ADTV 5000- 10,000 ADJ = 0.560581 gram/mile 2

EF PAVED_ADTV >10,000 ADJ = EF PAVED_LOCAL x CF RAIN

EF PAVED_ADTV >10,000 ADJ = 0.310239 x 0.928767

EF PAVED_ADTV >10,000 ADJ = 0.285861 gram/mile 2177 Equation:

EM PAVED RD, i = ∑ ( VMT ADTV, i x EF PAVED_ADTV ADJ, i x ( 1- CE x RE x RP) x 1.10231E-06 )

where:

EM PAVED RD ,i = Sum of PM 10 emissions in tons per year for paved roads in county i VMT ,i = VMT ( million miles of Vehicle Miles Traveled for county i )
EF PAVED_ADTV ADJ, i = Paved road emission factor adjusted for precipitation in county I (grams/mile)

CE = Control efficiency of 0% applied to Urban and Rural roads RE = Rule effectiveness of 100% applied to Urban and Rural roads RP = Rule penetration of 100% a pplied to Urban and Rural roads 1 gram = 1.10231E-06 tons

2002 Sample Calculation Paved Roads (Anne Arundel County)

EM PAVED RD, i = [( VMT _ADTV < 500, i x EF PAVED-LOCAL < 500 ADJ ) + ( VMT _ADTV 500 - 5000,i x EF

PAVED_ADTV 500 - 5000 ADJ ) + ( VMT _ADTV 5000 – 10,000, i x EF PAVED_ADTV 5000- 10,000 ADJ )

+ ( VMT _ADTV >10,000,i x EF PAVED_ADTV >10,000 ADJ )] x ( 1- CE x RE x RP) x 1.10231E-06

EM PAVED RD, i = [(355524175 x 3.186314) + (167099106 x 1.459683) + (279697255 x 0.560581) + (4.64E+09 x 0.285861)] x (1 – 0 x 1 x 1) x 1.10231E-06

EM PAVED RD, i = 3,152.509 tons per year of PM 10 or (3,152.509 / 365) = 8.64 tons per day of PM

10178 4.1.7.6 Unpaved Roads
SCC: 22 96 000 000

Description

This source category covers fugitive dust em issions from activity on unpaved roads. The activity data needed to cal culate emissions from unpaved ro ads was not available. Methods are still being researched as to how to properly gather this data. MDE cannot submit any emissions for this source categ ory at the present time.179 4.1.8 FIRE SOURCES

Other area sources include forest fires, slash and prescribed burning, agricultural burning, structure fires, orchard heaters, leaking underground storage tanks and natural organic sources. Although often intermittent in nature, many of these sources can produce large quantities of air pollutant emissions.

4.1.8.1 Vehicle Fires
SCC: 28 10 001 000

This emission guidance report covers air emission s from accidental vehicle fires. Vehicles included are any commercial or private mode of transportation that is authorized for use on public roads.

PM 10 , NOx, CO, VOC

Activity Local data was collected from state or local fire marshals and public safety departments. See the spatial apportioning sect ion for available information

sources.

Emission Factors Emission factors are available for open burning of automobile components including upholstery, belts, hoses, and tires (AP-42, Section 2.5 Open Burning) (EPA, 1996) 101 . The amount of vehicle material burned (the fuel loading) in a vehicle fire must be estimated to use these factors. A conserva tive assumption is that an average vehicle has 500 pounds of components that can burn in a fire, ba sed on a 3,700 pound average vehicle weight (CARB, 1995) 102 . Maryland used a more conservative assumption based on a 2,000 pound average vehicle weight.

Pollutant Lbs/ton burned

101 EPA. 1996. Compilation of Air Pollutant Emission Factors--Vol ume I: Stationary Point and Area Sources. Fifth Edition, AP-42. U. S. Environmental Protection Agency, Office of Air Quality Planning and Standards. (GPO 055- 000-00251-7). Research Triangle Park, North Carolina

102 CARB. 1995. Emission Inventory Procedural Manual, Vol. III: Methods for Assessing Area Source Emissions. California Environmental Protection Agency: Air Resources Board. Description

Pollutants

Method and Data Sources180 VOC 32
NOx 4
CO 125
PM10-PRI 100

No subtraction of emissions from point sources is necessary.

No controls are available for this source category.

Spatial The activity data for vehicle fi res was collected at a county- level. No other method to spatially profile the vehicle fire source category was used.

Temporal Data for temporal allocation is not available for this source.

VB j x FLF VF x EF VF i E VF, i = 2000 x 365

where:
E VF,i = Emissions of pollutant i in tons per day from vehicle fires
VB J = Vehicles burned in county j in 2002
FLF VF = Fuel loading factor (tons/vehicle bur ned) for vehicle fire s (500 lbs/2000 lb auto)
EF VF i = Emissions factor in pounds per ton burned for pollutant i

2002 Sample Calculation Forest Fires (Anne Arundel County)

VB j x FLF VF x EF VF, I E VF, i = 2000 x 365
500 x (500/2000) x 4 E VF, i = 2000 x 365

E VF, i = 0.0007 tons NOx per day emitted from ve hicle fires in Anne Arundel County in 20002 Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations

Emissions Calculation181 4.1.8.2 Forest Fires
SCC: 28 10 001 000

Forest fires in certain rural areas can produ ce very large, short term organic emissions.

PM 10 and PM 2.5

Activity ARMA used data from the Maryland Forest, Park and Wildlife Service 103 on the number of fires and acreage burned per county. Emi ssion factors were obtained from AP-42, Table 13.1-2. A fuel loading factor (tons of growth burned per acre ) of 11 tons/acre was obtained from Table 13.1-1 (Eastern Region) of AP-42 Wildfires and Prescribed Burning, October 1996. An activity level of 7 days a week from Procedures , Table 5.8-1 was used. The 2002 fire data from the Forest, Park and Wildlife Service showed no apparent increase in number or size of forest fires in the ozone season, thus no seasonal adjustment was used.

Emission Factors

VOC NOx CO PM TOT (Lbs./ton) (Lbs./ton) (Lbs./ton) (Lbs./ton)
Emissions 24.0 4.0 140.0 17.0 Fuel loading factor: 11.0 Tons/acre burned

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

103 Forest fire data collected from Mr. Bob Hartlove, Acting Fire Supervisor for the Maryland Forest Service Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustments for Controls182 Spatial The activity data for forest fi res was collected at a county- level. No other method to spatially profile the forest fire source category was used.

Temporal Data for temporal allocation is not available for this source.

AB j x EF FF i x FLF FF E FF I = 2000 x 365

where:
E FF,i = Emissions of pollutant i in tons per day from forest fires
FLF FF = Fuel loading factor (tons/acre burned) for forest fires (11.0)
AB J = Acres burned by wildfire in county j in 2002
EF FF i = Emissions factor in pounds per acre or pounds per ton for pollutant i

2002 Sample Calculation Forest Fires (Anne Arundel County)

AB j x EF f,i x FLF FF E FF i = 2000 x 365

where: Spatial and Temporal Allocations

Emissions Calculation183 E FF i = (0.3 acres burned 104 x 11 tons per acre 105 x 24.0 lbs. VOC per ton) / (2000 x 365)

106

E FF i = 0.0001 tons per day of VOC emitted from forest fires in Anne Arundel County in
2002

104 Number of acres burned by wildfire in Anne Arundel County in 2002 from Maryland Forest, Parks and Wildlife
Service .

105 Fuel loading factor from AP-42 , Table 13.1-1.

106 Emission factor from AP-42 , Table 13.1-2.184 4.1.8.3 Slash/Prescribed Burning SCC: 28 10 015 000 (prescribed burn) SCC: 28 10 005 000 (slash burn)

Waste from logging operations is often burned under controll ed conditions to reduce the potential fire hazard in forests and to remove brush that can serve as a host for destructive insects. Prescribed burning is used as a fo rest management practice to establish favorable seedbeds, remove competing unde rbrush, accelerate nut rient cycling, control tree pests and contribute other ecological benefits.

PM 10 and PM 2.5

Activity

Emissions from this source were calculated using data from the Maryland Forest Service for prescribed burning by county and type of material burned. Emission and fuel loading factors for marsh grass was assumed to be the same as that for unspecified field crops in
AP-42 , Table 2.5-5, and the factor for pine wa s supplied by staff at the Maryland Forest Service.

Emission Factor

VOC CO NOx PM TOT (Lbs./ton) (Lbs./ton) (Lbs./ton) (Lbs./ton)

Marsh Grass Emissions Factors 18.0 117.0 NA 21.0 Fuel loading factor 2.0 tons/acre

Pine Slash Emission factor 19.0 140.0 4.0 17.0 Fuel loading factor: 30.0 tons/acre Description

Pollutants

Method and Data Sources185 No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial The activity data for prescribed burning was collected at a county-level. No other method to spatially profile the prescribed burning source category was used.

Temporal Because prescribed burning is done at differe nt times of the year, ARMA used no seasonal adjustment factor. The activity level is seven days per week.

AB j x EF PB i x FLF J E PB i = 2000 x 365

where:
E PB,i = Emissions of pollutant i in t ons per day from prescribed burning
FLF J = Fuel loading factor for type of materi al burned j (for marsh grass the factor is 2 tons per acre and for pine slash it is 30 tons per acre burned)
AB J = Acres burned in county j in 2002
EF PB,i = Emission factor for pollutant k

2002 Sample Calculation Slash/Pres cribed Burning (Worcester County)

AB j x EF PB i x FLF J E PB i = 2000 x 365

(20 acres of pine slash burned x 19 lbs. VOC per ton x 30 tons per acre burned) E PB i = 2000 x 365

E PB i = 0.016 tons VOC /day

Slash burning calculations ar e done in a similar manner. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations

Emissions Calculation186 4.1.8.4 Agricultural Burning
SCC: 21 01 500 000

This source category covers agricultural burning practices used to clear and/or prepare land for planting. Operations included under this category are stubble bur ning, burning of agricultural crop residues, and burning of standing field crop s as part of harvesting (e.g., sugar cane).

PM 10 and PM 2.5

Emissions from this source were assigned to the open burning category because the county permits issued in 2002 did not require informa tion distinguishing the amount of agricultural waste to be burned versus other materials.

4.1.8.5 Structure Fires
SCC: 28 10 030 000

Building fires produce short-term emissions of organic compounds.

PM 10 and PM 2.5

MDE staff used emission factors, fuel load ing factors and methodology documented in EIIP 107

, Structure Fires, dated July 1999.

Activity The Maryland State Fire Marshal's office provide d the number of structure fires by county.

107 Emission Inventory Improvement Program Description

Pollutants

Method and Data Sources

Description

Pollutants

Method and Data Sources187 Emission Factors

VOC NOx CO PM TOT (Lbs./ton) (Lbs./ton) (Lbs./ton) (Lbs./ton)
Emissions 11.0 1.4 60.0 10.8 Fuel loading factor: 1.15 Tons/fire

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial The activity data for structure fires was collected at a county -level. No other method to spatially profile the prescribed burning source category was used.

Temporal Because structure fires occur at different times of the year, ARMA used no seasonal adjustment factor. The activity level is seven days per week.

SF j x EF SF i x FLF SF E SF i = 2000 x 365

where:

E FF,i = Emissions of pollutant i in tons per day from structure fires

FLF FF = Fuel loading factor (tons/acre burned) for structure fires

SF J = Structure fires in county j in 2002 Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations

Emissions Calculation188 EF SF,i = Emission factor for pollutant i in tons per day from structure fires

ARMA used an activity level of 7 days a week with no seasonal va riation as given in Table 5.8-1 in the EIIP document.

2002 Sample Calculation Struct ure Fires (Baltimore City)

Equation:

SF j x EF SF i x FLF SF E SF i = 2000 x 365
2386 108 x 11 109 x 1.15

110 E SF i = 2000 x 365

E SF i = 0.0413 tons VOC / day

108 Number of structure fires in Baltimore City in 2002 from Maryland State Fire Marshal's Office .

109 Emission factor from EIIP Structure Fires.

110 Fuel loading factor from EIIP Structure Fires189 4.1.8.6 Orchard Heaters
SCC: 28 01 520 000

In areas of the country where frost threatens orchar ds, heaters may be used in cold portions of the growing season.

PM 10 and PM 2.5

Calls to several orchards in Washington and Fred erick Counties (where most of the orchards in Maryland are located), revealed th at no heaters were used. One orch ard used fans to move air on still nights when there would be danger of frost to fruit tree blo ssoms. Therefore, orchard heaters are not included in Maryland' s 2002 baseline inventory. Description

Pollutants

Method and Data Sources190 4.1.9 AMMONIA SOURCES

Ammonia (NH 3 ) is a pungent colorless gaseous compound of nitrogen and hydrogen that is very soluble in water and can be conde nsed into a liquid by cold and pr essure. Ammonia gas reacts in the atmosphere with NOx or SOx to produce am monium nitrate or ammonium sulfate, major
PM 2.5 components in the United States.

In preparing an ammonia inventor y, it is worthwhile to priori tize which of the many potential ammonia sources should receive attention. Previous studies conducted by Battye 111 and the State of California Air Resources Bureau (CARB), provide list s of ammonia sources that can be used to evaluate which sources are present within a re gion. These sources may then be ranked in terms of priority for estimating emissions.

Currently, there is a significant amount of un certainty concerning the contribution of soil to ammonia emission levels. High quality emission fact ors for this category do not exist, and even the physics of ammonia-surface exchange is no t well understood. Soils emit and uptake ammonia so it is difficult to evaluate the net contribution, emissions may be potentia lly significant in some regions if the uptake is not subs tantial. Indeed, th e literature shows th at a soil-plant canopy system can be a source of ammonia emissions under certain conditions and a sink under other conditions. Because of this uncertainty, the St ate of Maryland has decided not to include emissions from soils.

This section contains the a mmonia emission inventory for

• Agricultural Livestoc k Production Operations

• Agricultural Fertilizer Application,

• Human activity.

111 Battye, R., Battye, W., C. Ov ercash, C., Fudge, S., 1994. Development and Selection of Ammonia Emission Factors, Final Report. EC/R Incorporated for U.S. EPA, EPA/ 600/R-94/190 (Prepared for William Benjey).191 4.1.9.1 Cows (Milk Cows, Beef Cows, Heifers, and Steers) SCC: 28 05 020 000 (Cows Composite)

These animals, and all livestock, are sources of ammonia emissions due to the biological decomposition of their waste products

NH 3

Conceptually, the method for estimating emissions from cattle is simple: count the number of animals, then multiply this by the average emissi ons per animal, and the resulting value provides the emissions. The CMU-NH3 Inventory (ver sion 2.0) program utilizes this approach, a methodology approved by the EPA for developing th e emissions inventory for other categories

Activity Activity levels were collected from the USDA Census of Agriculture data for 1997.

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Livestock Category Emission
Factor Source of Emission Factor

Milk cows 39.72 Kg/ cow/ year Battye, et al. (1994) Beef cows 39.72 Kg/ cow/ year Battye, et al. (1994) Heifers 9.67 Kg/ heifer/ yea r Battye, et al. (1994)
Steers 11.65 Kg/ steer/ yea r Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations192 Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions for cows in an individual county

EM COWS-99 Total = 1999 EM BC + 1999 EM MC + 1999 EM HF + 1999 EM ST

Where:
EM COWS-99 Total = Total NH3 emissions from cows, all categories
EM BC = 1999 Uncontrolled emissions from beef cows
EM MC = 1999 Uncontrolled emissions from milk cows
EM HF = 1999 Uncontrolled emissions from heifers
EM ST = 1999 Uncontrolled emissions from steers

Where:
EM BC = (AC BC * EF BC )
EM MC = (AC BC * EF MC )
EM HF = (AC BC * EF HF )
EM ST = (AC BC * EF ST )

Where:
AC BC = Activity level (number) of beef cows
AC MC = Activity level (number) of milk cows
AC HF = Activity level (number) of heifers
AC ST = Activity level (number) of steers
EF BC = Emission factor for beef cows
EF MC = Emission factor for milk cows
EF HF = Emission factor for heifers
EF ST = Emission factor for steers Emissions Calculation193 4.1.9.2 Hogs and Pigs SCC: 28 05 025 000 (Swine Composite)

These animals, and all livestock, are sources of ammonia emissions due to the biological decomposition of their waste products.

NH 3

Conceptually, the method for estimating emissions from cattle is simple: count the number of animals, then multiply this by the average emissi ons per animal, and the resulting value provides the emissions. The CMU-NH3 Inventory (ver sion 2.0) program utilizes this approach, a methodology approved by the EPA for developing th e emissions inventory for other categories

Activity Activity levels were collected from the USDA Census of Agriculture data for 1997.

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Livestock Category Emission
Factor Source of Emission Factor Hogs 9.2 Kg/ hog/ year Battye, et al. (1994) Pigs 9.2 Kg/ pig/ year Battye, et al. (1994)

Steers 11.65 Kg/ steer/ yea r Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls194 Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions for swine in an individual county

EM SWINE-99 Total = 1999 EM HOGS + 1999 EM PIGS

Where:
EM SWINE-99 Total = Total NH3 emissions from swine, all categories
EM HOGS = 1999 Uncontrolled emissions from hogs
EM PIGS = 1999 Uncontrolled emissions from pigs

Where:
EM HOGS = (AC HOGS * EF HOGS )
EM PIGS = (AC PIGS * EF PIGS )

Where:
AC HOGS = Activity level (number) of hogs
AC PIGS = Activity level (number) of pigs
EF HOGS = Emission factor for hogs
EF PIGS = Emission factor for pigs Spatial and Temporal Allocations

Emissions Calculation195 4.1.9.3 Chickens (Pullets, Layers, and Broilers) SCC: 28 05 030 000 (Chickens Composite)

These animals, and all livestock, are sources of ammonia emissions due to the biological decomposition of their waste products.

NH 3

Conceptually, the method for estimating emissions from cattle is simple: count the number of animals, then multiply this by the average emissi ons per animal, and the resulting value provides the emissions. The CMU-NH3 Inventory (ver sion 2.0) program utilizes this approach, a methodology approved by the EPA for developing th e emissions inventory for other categories

Activity Activity levels were collected from the USDA Census of Agriculture data for 1997.

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Livestock Category Emission
Factor Source of Emission Factor

Pullets 0.269 Kg/ pullet/ year Battye, et al. (1994) Layers 0.598 Kg/ layer/ year Battye, et al. (1994) Broilers 0.167 Kg/ broiler/ yea r Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls196 Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions for chic kens in an individual county

EM CHICKENS-99 Total

= 1999 EM PULLET + 1999 EM LAYER + 1999 EM BROILER

Where:
EM CHICKENS-99 Total = Total NH3 emissions from chickens, all categories
EM PULLET = 1999 Uncontrolled emissions from pullets
EM LAYER = 1999 Uncontrolled emissions from layers
EM BROILER = 1999 Uncontrolled emissions from broilers

Where:
EM PULLET = (AC PULLET * EF PULLET )
EM LAYER = (AC LAYER * EF LAYER )
EM BROILER

= (AC BROILER * EF BROILER )

Where:
AC PULLET = Activity level (number) of pullet chickens
AC LAYER = Activity level (number) of layer chickens
AC BROILER = Activity level (number) of broiler chickens
EF PULLET = Emission factor for pullet chickens
EF LAYER = Emission factor for layer chickens
EF BROILER = Emission factor fo r broiler chickens Spatial and Temporal Allocations

Emissions Calculation197 4.1.9.4 Sheep SCC: 28 05 040 000 (Sheep Composite)

These animals, and all livestock, are sources of ammonia emissions due to the biological decomposition of their waste products.

NH 3

Conceptually, the method for estimating emissions from cattle is simple: count the number of animals, then multiply this by the average emissi ons per animal, and the resulting value provides the emissions. The CMU-NH3 Inventory (ver sion 2.0) program utilizes this approach, a methodology approved by the EPA for developing th e emissions inventory for other categories

Activity Activity levels were collected from the USDA Census of Agriculture data for 1997.

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Livestock Category Emission
Factor Source of Emission Factor Sheep 3.37 Kg/ sheep/ year Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls198 Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions for sh eep in an individual county

EM SHEEP

= AC SHEEP * EF SHEEP

Where:
EM SHEEP = Total NH3 emissions from sheep, all categories
AC SHEEP = Activity level (number) of sheep
EF SHEEP = Emission factor for sheep Spatial and Temporal Allocations

Emissions Calculation199 4.1.9.5 Goats (Angora and Milk) SCC: 28 05 045 001(Goats Composite)

These animals, and all livestock, are sources of ammonia emissions due to the biological decomposition of their waste products.

NH 3

Conceptually, the method for estimating emissions from cattle is simple: count the number of animals, then multiply this by the average emissi ons per animal, and the resulting value provides the emissions. The CMU-NH3 Inventory (ver sion 2.0) program utilizes this approach, a methodology approved by the EPA for developing th e emissions inventory for other categories

Activity Activity levels were collected from the USDA Census of Agriculture data for 1997.

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Livestock Category Emission
Factor Source of Emission Factor Angora goats 2.2 Kg/ goat/ year Battye, et al. (1994) Milk goats 2.2 Kg/ goat/ year Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls200 Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions for go ats in an individual county

EM GOATS-99 Total

= 1999 EM AG + 1999 EM MG

Where:
EM GOATS-99 Total = Total NH3 emissions from goats, all categories
EM AG = 1999 Uncontrolled emissions from angora goats
EM MG = 1999 Uncontrolled emissions from milk goats

Where:
EM AG = (AC AG * EF AG )
EM MG

= (AC AG * EF AG )

Where:
AC AG = Activity level (number) of angora goats
AC MG = Activity level (number) of milk goats
EF AG = Emission factor for angora goats
EF MG = Emission factor for milk goats Spatial and Temporal Allocations

Emissions Calculation201 4.1.9.6 Horses SCC: 28 05 035 000 (Horses)

These animals, and all livestock, are sources of ammonia emissions due to the biological decomposition of their waste products.

NH 3

Conceptually, the method for estimating emissions from cattle is simple: count the number of animals, then multiply this by the average emissi ons per animal, and the resulting value provides the emissions. The CMU-NH3 Inventory (ver sion 2.0) program utilizes this approach, a methodology approved by the EPA for developing th e emissions inventory for other categories

Activity Activity levels were collected from the USDA Census of Agriculture data for 1997.

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Livestock Category Emission
Factor Source of Emission Factor

Horses 12.2 Kg/ horse/ year Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category.

Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations202 Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions for ho rses in an individual county

EM HORSE = AC HORSE * EF HORSE

Where:
EM HORSE = Total NH3 emissions from horses, all categories
AC HORSE = Activity level (number) of horses
EF HORSE = Emission factor for horses Emissions Calculation203 4.1.9.7 Ducks, Geese and Turkeys SCC: 28 05 035 001 (Ducks) SCC: 28 05 035 002 (Turkeys) SCC: 28 05 035 003 (Geese)

These animals, and all livestock, are sources of ammonia emissions due to the biological decomposition of their waste products.

NH 3

Conceptually, the method for estimating emissions from cattle is simple: count the number of animals, then multiply this by the average emissi ons per animal, and the resulting value provides the emissions. The CMU-NH3 Inventory (ver sion 2.0) program utilizes this approach, a methodology approved by the EPA for developing th e emissions inventory for other categories

Activity Activity levels were collected from the USDA Census of Agriculture data for 1997.

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Livestock Category Emission
Factor Source of Emission Factor

Ducks 0.117 Kg/ duck/ year Battye, et al. (1994)
Geese 0.890 Kg/ duck/ yea r Battye, et al. (1994) Turkeys 0.858 Kg/ duck/ year Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls204 Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions for du cks in an individual county

EM DUCKS = AC DUCKS * EF DUCKS

Where:
EM DUCKS = Total NH3 emissions from ducks, all categories
AC DUCKS = Activity level (number) of ducks
EF DUCKS = Emission factor for ducks Spatial and Temporal Allocations

Emissions Calculation205 4.1.9.8 Agricultural Fertilizer Application SCC: 28 01 700 001 (Fertilizer Composite)

Fertilizer applicati on is typically considered to be the s econd or third most important source on a national level, depending on whether the inventor y includes soil emissions. Existing inventories usually estimate the contribution from fertilizer a pplication to be 10-20% of the national total. Substantial progress was made in improving spatial and temporal resolution of emissions in this category.

Activity level data for fertilizer application ar e for 1995 from the Associat ion of American Plant and Food Control Officials (AAPFCO), which reports fertilizer sales to farmers at the county level. This is an improvement on some existing i nventories, which are based on sales of fertilizer to dealers rather than to farmer s. The dealers may subsequently sell the fertilizer to farmers in other locations, resulting in an inaccurate sp atial distribution of activity levels. A better approximation (in the absence of act ual application data) is to use sales from dealers to farmers. The AAPFCO datasets contain county-level reso lution for the top producing states for each crop (usually about 30 states), and st ate-level resolution for the othe r states. USGS also has countylevel records of fertilizer application for y ears up until 1991. For states where the AAPFCO dataset only contained state-level resolution, the USGS dataset was used to allocate the AAPFCO state-level data to county-level.

Although there are almost 200 different commercial fertilizers used in th e United States, roughly 13 of them account for the majority of fertilizer use. Emission factors for these 13 were obtained from Battye et al. (1994) and Asma n et al. (1992). Quantities of the rest of the fertilizers have been combined into a ‘miscellaneous’ category, and assigned an emission factor equal to the average emission factor for all major fertilizers. The amount of fertilizer in the ‘miscellaneous’ category is typically less th an 3-4% of the total.

Finally, ammonia emissions from fertilizer application have a strong temporal component that has previously been ignored; yearly averages have been used in existing inventories. Significantly more fertilizer is applied in th e spring and fall than in the summer and winter, corresponding to crop cycles. To improve tem poral allocation, USDA data on crop planting times and fertilizer application times and rates we re used to generate a monthly distribution of fertilizer application (U SDA, 1997; USDA-ERS, 1991; US DA-ERS, 1996; USDA-ERS, 1996- 1997; USDA-NASS, 1992-1997a; USDA- NASS, 1992-1997b; USDA-NASS, 1992-1997c; USDA-NASS, 1992-1997d; USDA-NASS, 1992- 1997a; USDA-NASS, 1995; USDA-NASS, 1997). Results show that assuming a yearly average for this category results in a substantial error for most months of the year.

NH 3 Description:

Pollutants206 Conceptually, the method for estimating emissions fr om mobile sources is simple: collect data on the amount of fertilizer sold to farmers in a spec ific county, then multiply this by the per cent of ammonia released per fertilizer application, and the resulting va lue provides the emissions. The CMU-NH3 Inventory (version 2.0) program utilizes this approach, a methodology approved by the EPA for developing the emissions inventory for other categories.

Activity Activity levels, amount of fertilizer sold to farmers per county, were collected from the Association of American Plant a nd Food Control Offi cials (AAPFCO).

Emission Factors

Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Fertilizer Type Per Cent NH 3 Released to the Atmosphere Source of Emission Factor

Ammonium nitrate 0.01 Battye, et al. (1994) Ammonium sulfate 0.01 Battye, et al. (1994) Ammonium thiosulfate 0.02 Battye, et al. (1994) Calcium ammonium nitrate 0.08 Battye, et al. (1994) Nitrogen solutions 0.025 Battye, et al. (1994)
Urea 0.02 Battye, et al. (1994) Diammonium phosphate 0.08 Battye, et al. (1994) Monoammonium phosphate 0.15 Battye, et al. (1994) Liquid ammonium polyphosphate 0.04 Battye, et al. (1994) Potassium nitrate 0.04 Battye, et al. (1994) Miscellaneous 0.04 Battye, et al. (1994) Potassium nitrate 0.02 Battye, et al. (1994) Miscellaneous 0.15 Battye, et al. (1994)
Mix 0.04 Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category. Method and Data Sources

Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations207 Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Finally, ammonia emissions from fertilizer application have a strong temporal component that has previously been ignored; yearly averages have been used in existing inventories. Significantly more fertilizer is applied in th e spring and fall than in the summer and winter, corresponding to crop cycles. To improve tem poral allocation, USDA data on crop planting times and fertilizer application times and rates we re used to generate a monthly distribution of fertilizer application (U SDA, 1997; USDA-ERS, 1991; US DA-ERS, 1996; USDA-ERS, 1996-1997; USDA-NASS, 1992-1997a; USDA- NASS, 1992-1997b; USDA-NASS, 1992- 1997c; USDA-NASS, 1992-1997d; USDA-NASS , 1992-1997a; USDA-NASS, 1995; USDANASS, 1997). Results show that assuming a yearly average fo r this category results in a substantial error for most months of the year.

Equation:

1999 TPY ammonia emissions for agricultural fe rtilizer sources in an individual county

EM FERT-99 Total = EM AmmNit + EM AmmSul + EM AmmThio + EM CalAmmNit + EM NitSol + EM Urea + EM DiAmmPhos + EM MonoAmmPhos + EM LiqAmmPhos + EM PotNit + EM Misc +
EM Mix

Where:
EM MOBILE-99 Total = Total NH3 emissions from agricultural fertilizer application, all categories
EM AmmNit = Emissions from Ammonium Nitrate fertilizer
EM AmmSul = Emissions from Ammonium Sulfate fertilizer
EM AmmThio = Emissions from Ammonium Thiosulfate fertilizer
EM CalAmmNit = Emissions from Calcium Ammonium Nitrate fertilizer
EM NitSol = Emissions from Nitrogen Solutions fertilizer
EM Urea = Emissions from Urea fertilizer
EM DiAmmPhos = Emissions from Diammonium Phosphate fertilizer
EM MonAmmPhos = Emissions from Monoammonium Phosphate fertilizer
EM LiqAmmPhos = Emissions from Liquid Ammonium Polyphosphate fertilizer
EM PotNit = Emissions from Potassium Nitrate fertilizer
EM Misc = Emissions from Miscellaneous fertilizer
EM Mix = Emissions from Mixed fertilizer

Where:
EM AmmNit = (AC AmmNit * Per Cent Released AmmNit )
EM AmmSul = (AC AmmSul * Per Cent Released AmmSul )
EM AmmThio (AC AmmThio * Per Cent Released AmmThio )
EM CalAmmNit = (AC CalAmmNit * Per Cent Released CalAmmNit )
EM NitSol = (AC NitSol * Per Cent Released NitSol )
EM Urea (AC Urea * Per Cent Released Urea ) Emissions Calculation208 EM DiAmmPhos = (AC DiAmmPhos * Per Cent Released DiAmmPhos )

EM MonAmmPhos = (AC MonAmmPhos * Per Cent Released

MonAmmPhos )
EM LiqAmmPhos = (AC LiqAmmPhos * Per Cent Released LiqAmmPhos )
EM PotNit = (AC PotNit * Per Cent Released PotNit )
EM Misc (AC Misc * Per Cent Released Misc )
EM Mix = (AC Mix * Per Cent Released Mix )

Where:
AC AmmNit = Activity level (amount of Ammonium Nitrat e fertilizer applied per county) Per Cent Released AmmNit = Per Cent of NH3 released during fertilizer application209 4.1.9.9 Human Breath and Perspiration SCC: 28 10 010 000 (Human Perspiration)

Ammonia emissions from human br eath and perspiration comprise a few percent of the national ammonia emission inventory.

NH 3

Conceptually, the method for estimating emissions from human breathe and perspiration is simple: count the number of people, then multiply this by the average emissions per person, and the resulting value provides the emissions. The CMU-NH3 Inventory (version 1.2) program utilizes this approach, a methodology approve d by the EPA for developing the emissions inventory for other categories.

Activity The US Census (U.S. Census Bureau, 1999) was used to obtain activity level data for this category.

Emission Factors Emission factors were collected from a paper published by Battye, 111 et al. in 1994 and are presented in the table below:

Emission Factors and Source

Emission Category Emission
Factor Source of Emission Factor Human Breathe and Perspiration 0.44 Kg / person/ year Battye, et al. (1994)

No subtraction of emissions from point sources is necessary.

No controls are available for this source category.

Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations210 Temporal Data for temporal allocation is not available for this source.

Equation:

1999 TPY ammonia emissions from human breathe and perspirati on in an individual county

EM HUMAN B&P = AC HUMAN * EF HUMAN B&P

Where:
EM HUMAN B&P = Total NH3 emissions from human breathe and perspiration
AC HUMAN = Activity level (number) of people per county
EF HUMAN B&P = Emission factor for human breathe and perspiration Emissions Calculation211 

## 5.0 NONROAD SOURCES

5.1 NONROAD VEHICL ES/ENGINES

This section contains the nonroad source emi ssion inventory for vol atile organic compounds (VOCs), nitrogen oxides (NOx), and carbon mon oxide (CO) and if po ssible carbon dioxide (CO 2 ), sulfur oxides (SO X ), particulate matter (PM), ammonia (NH3), and toxic air pollutants. Nonroad mobile sources include motorized ve hicles and equipment that are normally not operated on public roadways to provide transporta tion. For nonroad mobile sources, the source categories of interest are aircraft, locomotives, marine vessels and the source types included in EPA’s NONROAD model. Nonroad mobile sources are broken up into the following categories:

• lawn and garden equipment

• airport service equipment

• logging equipment

• recreational marine equipment

• light commercial equipment

• industrial equipment

• construction equipment

• agricultural or farm equipment

• recreational land vehicles or equipment

• railroads

• commercial aviation

• air taxis

• general aviation

• military aviation

• commercial marine vessels

The Department used two methodologies a pproved by the EPA for developing the 2002 emissions inventory for nonroad categories. One of the methodologies used consisted of employing EPA’s NONROAD Emission Inventory Model 112 . In a memorandum 113 , dated June 16, 2003, EPA allowed the use of the draft NONRO AD Model and associated default inputs in the development of inventories supporting St ate Implementation Plans (SIPs). The second methodology entailed the use of EPA emission factors.

Sample calculations presented below are for illust rative purposes only and may not reflect actual emissions.

112 NONROAD2005

113 USEPA Memorandum , dated June 16, 2003, from Gene Tierney or the Air Quality and Modeling Centery and Leila H. Cook of the Transportation and Regional Programs Division; to Regional Mobile Source Program Manages and Staff.212 5.2 NONROAD MODEL

As stated previously, the 2002 emissions estim ate for all nonroad equipment categories listed above except commercial marine, railroad locomotives, and aviation emissions were determined by running EPA’s NONROAD MOBILE Model, as suggested by EPA guidance. The model includes more than 80 basic and 260 specific types of nonroad equipment, and further stratifies equipment t ypes by horsepower rating. Fuel t ypes include gasoline, diesel, compressed natural gas (CNG), and liquefied petroleum gas (LPG).

The NONROAD model consists of three separa te components: a graphical user interface written in Visual Basic, the core model written in Fortran, and a reporting utility written in Microsoft ACCESS. The install utility supplie d with the model easily installs all three components of the model onto a personal computer.

The primary purpose of the user interface is to provide the user with an easy method to specify the options for a model run. With simple Windows-type screens and pull-down menus, the user can quickly set up, execute, and view a modeling sc enario. Once the model options are specified, the user can then run th e Fortran core model from within the interface, and then can move directly to the reporti ng utility to view and summarize the modeling results.

The core model of NONROAD, written in Fortran, contains all of the algorithms used by the model for calculating emissions estimates. The co re model can be operated as a stand-alone application; however, as a st and-alone application it require s some basic knowledge of the DOS operating system. Also, note that while the user interface runs the core model for one specified set of conditions, it cannot run multiple runs in batch mode. Multiple runs can be performed by creating and running a batch file in DOS or in a DOS window in a Windows 3.1 or 95 environment.

The reporting utility, written usi ng Microsoft’s ACCESS database so ftware, is used to create standardized reports using output data generated in the core m odel. Like the graphical user interface, the reporting utility is a fully operational Windows program, with pull-down menus, designed as a separate module in order to take advantage of the many reporting and formatting options available when using a databa se application. Although the reporting utility is written in ACCESS, it is a st and-alone application, and you do not need to know how to use ACCESS to generate reports.

The NONROAD model estimates emissions for si x exhaust pollutants: hydrocarbons (HC), NOx, carbon monoxide (CO) , carbon dioxide (CO 2 ), sulfur oxides (SO X ), and PM. The user selects among five different types for reporti ng HC — as total hydroc arbons (THC), total organic gases (TOG), non-methane organi c gases (NMOG), non-methane hydrocarbons (NMHC), or volatile organic compounds (VOC). Pa rticulate matter can be reported as PM of 10 microns or less (PM 10 ) or PM of 2.5 microns or less (PM 2.5 ). The model also estimates emissions of non-exhaust HC for four mode s — diurnal, refue ling spillage, vapor displacement, and crankcase emissions. All emi ssions are reported as short tons (i.e., 2000 lbs). Ammonia (NH3) emissions from NONR OAD Model equipment were post-processed outside of the actual model.213 The NONROAD model estimates emissions for each specific type of nonroad equipment by multiplying the following input data estimates:

• Equipment population for base year (or base year population grown to a future year), distributed by age, power, fu el type, and application;

• Average load factor expressed as average fraction of available power;

• Available power in horsepower;

• Activity in hours of use per year; and

• Emission factor with deteriorat ion and/or new standards.

The emissions are then temporally and geograp hically allocated using appropriate allocation
factors.

There are several input files that provide nece ssary information to cal culate and allocate emissions estimates. These input files correspond to the basic data n eeded to provide the calculations: emission factors, base year equi pment population, activity, load factor, average lifetime, scrappage function, growth estimat es, and geographic and temporal allocation. Default values are provided for all input files. The user can replace the default data files when better information becomes available, either from EPA for national defaults or from local sources for locality-specific data. The input files are also modifiable to test control strategies. MDE input files that differ from the EPA na tional defaults are pres ented in Section 4.7 – NONROAD Model Appendices.’

Input parameters for the nonroa d Model are listed below:

2002 NONROAD MODEL INPUTS

Winter Spring Fall All Maryland Counties All Maryl and Counties All Maryland Counties Temp MIN 28.29 43.87 47.68 Temp MAX 48.29 67.25 66.72 Temp AVG 38.70 55.83 58.03
RVP 12.6 9.6 9.3
Diesel S % 0.2318 0.2318 0.2318
Gas Sulfur % 0.0162 0.0162 0.0162
CNG/LPG Sulfur % 0.003 0.003 0.003
Marine Dsl sulfur % 0.2637 0.2637 0.2637 O2 Weight % 2.1 2.1 2.1
State II Control % 0 0 0214 2002 NONROAD MODEL SUMMER INPUTS

Summer Summer Summer (Transport Region) (MWCOG Counties) (BNNA Counties) Temp MIN 65.55 69.80 65.55 Temp MAX 87.60 92.50 87.60 Temp AVG 76,80 81.40 76,80
RVP 6.6 6.9 6.6
Diesel S % 0.2318 0.2283 0.2318
Gas Sulfur % 0.0162 0.0129 0.0162
CNG/LPG Sulfur % 0.003 0.003 0.003
Marine Dsl sulfur % 0.2637 0.2638 0.2637 O2 Weight % 2.1 2.1 2.1
State II Control % 0 0 0

The transport region includes the following counties: Allegany, Caroline, Dorchester, Garrett, Kent, Queen Anne’s, St Mary’s, Somerset, Talbot, Washington, Wicomico, Worcester The MWCOG region includes the following counties: Calver t, Charles, Frederick, M ontgomery, Prince Georges The BNAA region includes the following count ies: Anne Arundel, Baltimore, Carroll, Harford, Howard, Baltimore City, Cecil

Details of this model can be found in its user guide named “User’s Guide for the EPA Nonroad Emissions Model Draft NONROAD 2002” (EPA420-P-02-013; December 2002) available from the EPA.

Ammonia emissions from NONR OAD Model equipment were estimated by running the NR Model Reporting Tool for one county (Anne Ar undel). The reporting t ool provided the total fuel used per source classificati on code (SCC). Seasonal reports were used to ensure that all SCC were captured. EPA-supplied NH3 emission factors for gasoline and diesel fuel were used to estimate emissions on the SCC level for the county. A ratio of NH3 to CO2 emissions was obtained per SCC for the county. This ra tio was then applied to all the counties in Maryland to estimate ammonia emissions for the state.215 5.2.1 NONROAD Model Equipment SCC: 22 60 004 000 (2-Stroke) 22 65 004 000 (4-Stroke) 22 67 004 000 (LPG) 22 70 004 000 (Diesel)

NONROAD Model equipment includes a variety of types of machinery used in the maintenance of lawns and gardens. Examples of the type s of equipment included in this category are trimmers/edgers/brush cutters, lawn mowers, leaf blowers, rear engine riding mowers, front mowers, chainsaws (<4HP), shredders (<5HP), t illers (<5HP), lawn and garden tractors, wood splitters, snow blowers, chippers /stump grinders, commercial turf equipment, and other lawn and garden equipment. Emissions result from opera tion of the internal combustion engines that power the equipment.

PM 10 , PM 2.5 , SOx, NOx, CO, VOC, NH3

Data sources

A. " User’s Guide for the EPA Nonroad Emissions Model Draft NONROAD 2002" prepared for EPA by ENVIRON Internationa l Corporation under EPA Contract No. DW47926801 dated December 2002. This report, EPA420-P-02-013, constitutes the User’s Guide to the NONROAD model. Th e report contains an overview of the model, equipment types, pollutants reporte d, geographic an temporal coverage, the model components, model inputs, and output options. The guide documents how to install and run the model and the associated reporting utility.

B. http://www.epa.gov/oms/nonrdmdl.htm

Methods sources

Based upon EPA's requirements for determini ng nonroad emissions, the Department ran the NONROAD model to determine the emissi on estimate for 2002. MDE-ARMA opted to choose seasonal (Spring, Summer, Fall, Wint er) period totals as th e output files from the model. These period totals were divide d by the number of days in a season to reflect an average daily emission level for each season.

No subtration of emissions fr om point sources is necessary.

The NONROAD model automatically applies cont rols, when applicable , for a given year. Description

Pollutants

Method and Data Sources

Point Source Adjustments

Adjustments for Controls216 Spatial The NONROAD model spatially allocates equipment popula tions through the REGION data packet and the emissions th rough the ALLOC data packet.

The REGION input file specifies the state or county to model. When you initially install the NONROAD model, you are prompted to iden tify the state where you are located. This step sets up the population and allocati on factor data files for your state.

The ALLOC input file defines the spatia l allocation files read by the model.

Temporal The NONROAD model temporally allocates activity to the differenent seasons through the SEASONALITY, MONTHLY, and DAILY data packets.

The first temporal allocation, identified by the packet identifier /MONTHLY/, provides the monthly adjustment factors used by the model to calculate the frac tion of annual activity occurring in the given month. For periods l onger than a single m onth (e.g. season), the factors from each month spanned by the peri od are summed. The second, identified as /DAILY/, provides the day-of-the-week ad justments. The weekend and weekday allocations should sum to one for an entire week (i.e. 1 = 5 × weekday fraction + 2 × weekend fraction).

The seasonal and monthly activity allocation fractions for th e NONROAD engine emissions modeling is further documented in Report No. NR-004, dated December 9, 1997. The weekday and weekend day tempor atl allocation of activity in the NONROAD model is further documented in Report No. NR-015 114 , dated March 31, 1999.

The NONROAD calculations rely on emission factors--estimates of the amount of pollution emitted by a particular type of equipment during a unit of use. Typically, emission factors for nonroad sources are reported in grams per horsepower-hour (g/hp-hr), but they also may be reported in grams per mile, grams per hour, and grams per gallon. These emission factors are stored in NONROAD’s data inpu t files. NONROAD adjusts these emission factors as necessary to account for the effects of fuel sulfur. Emission changes with the age of the engine, often called ‘deterioration,’are also applied by the model. The core model of NONROAD, written in Fortran, contains all of the algorithms used by the m odel for calculating emissions estimates using the input file listed above.

114 Nonroad Engine Emission Modeling Team, Assessment and Modeling Division, EPA, Office of Mobile Sources Spatial and Temporal Allocations

Emissions Calculation217 5.3 RAILROADS SCC: 22 85 002 005 (Line Haul) SCC: 22 85 002 010 (Yard Engines)

Railroad locomotives used in the United States ar e primarily of two types: electric and dieselelectric. Electric locomotives are powered by elec tricity generated at sta tionary power plants. Emissions are produced only at the electrical generation plant, whic h is considered a point source and therefore not included here. Diesel-elect ric locomotives, on the other hand, use a diesel engine and an alternator or ge nerator to produce the electricity required to power its traction motors. Emissions produced by these diesel e ngines are of interest in emission inventory development. Other sources of emissions from railroad operations include the small gasoline and diesel engines used on refriger ated and heated rail cars. Th ese engines are thermostatically controlled, working independent ly of train motive power, and fall in the category of nonroad equipment, addressed elsewhere in this document.

Locomotives can perform two different types of operations: Line Ha ul (SCC: 2285002005) and Yard (SCC: 2285002010). Line haul locomotives, which perform the line haul operations, generally travel between distant locations, such as from one city to another. Yard locomotives, which perform yard operations, are primarily res ponsible for moving railcars within a particular railway yard.

PM, SOx, NOx, CO, VOC

The following thirteen railroad companies operate in Maryland and were asked to provide the amount of fuel used in 2002, and the distribut ion of the company's track mileage by Maryland County: 1. AMTRAK (National Railr oad Passenger Corporation) 2. Canton Railroad Company 3. Wheeling & Lake Erie Railway Company 4. CSX Transportation, Incorporated 5. Eastern Shore Railroad, Incorporated 6. Maryland & Delaware Railroad Company 7. Maryland Midland Railway, Incorporated 8. Norfolk and Southern Railway Company 9. Patapsco & Back Rivers Railroad Company 10. Western Maryland Scenic Railroad 11. Winchester and Western Railroad Company 12. MARC (Under the Maryland Transit Administration) 13. Walkersville Southern Railroad

For CSX and Norfolk railroad operating statistics contained in R-1 reports obtained from the Surface Transportation Board under the Office of Economics, Environmental Analysis and Administration were used to add in estimating the amount of fuel used within the state. Description

Pollutants

Method and Data Sources:218 MDE received fuel usage and track mileage data from all the railroads. Fuel usage was proportioned to each county by the amount of track miles each company util ized in a county.

Activity A survey of railroad petroleum consum ption and track mileage was conducted.

Emission Factor Emission factors were obtained from the EPA's Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources , 1992.

Line Haul Yard

VOC 0.0213 lbs/gal VOC 0.0509 lbs/gal

NOx 0.4931 lbs/gal NOx 0.5044 lbs/gal

CO 0.0626 lbs/gal CO 0.0894 lbs/gal

SO2 0.0360 lbs/gal SO2 0.0360 lbs/gal

PM10 0.0148 lbs/gal PM10 0.0203 lbs/gal

PM25 0.0133 lbs/gal PM25 0.0183 lbs/gal

SO 2 emissions were calculated based on a sulfur content of 0.25% by weight.

EPA estimates that yard locomotives operate 365 days per year (assuming that when a yard engine is taken in for repairs it is replaced dur ing this period) and consumes an average of 228 gallons per day.

No subtration of emissions fr om point sources is necessary.

No controls are available for this source category.

Spatial Emission estimates are based on fuel consump tion. Company supplied state total fuel usage was allocated to the county level by the pr opotion of track miles used in a particular county.

Temporal Data for temporal allocation is not available for this source. Point Source Adjustments

Adjustments for Controls

Spatial and Temporal Allocations219 When specific county information was not provi ded, the following equations were used to compute the amount of fuel consumed by each railroad in each Maryland County.

M CTY G CTY = M ST * G ST

Where:

M CTY = mileage of company tracks in the county
M ST = mileage of company tracks in the state
G ST = amount of total fuel used in gallons by the company in the state
G CTY = amount of total fuel used in gallons by the company in the county

The following equation was used to calculate the emissions for line haul locomotives from each railroad company operating in a county.

Fuel CTY x EF LH E LH – i – CTY j = 2000 x 365

Where:

E LH – i – CTY j = Emissions from line haul railroad locomotives for pollutant i in County j Fuel CTY j = Total amount of fuel consum ed by every railroad operating in the calculated county Fuel CTY j = (G cty1 + G cty2 + ... + G cty12 )
EF LH = line haul locomotive emi ssion factor for a given pollutant

The following equation was used to calculate th e emissions for yard locomotives from each railroad company operating in a county.

N YL – i – CTY j x 228 x EF YL E YL – i – CTY j = 2000 Where:

E YL – i – CTY j = Emissions from yard locomo tives for pollutant i in County j
N YL – i – CTY j = number of yard locomotives operated by each railroad company in county j
N YL – i – CTY j = (N cty1 + N cty2 + ... + N cty12 )
EF YL = Yard locomotive emission factor for a given pollutant Emissions Calculation220 Sample Calculations:

2002 Montgomery County Emissions

Line Haul Emission Estimate

AMTRAK, CSX, and MARC operated line haul lo comotives in the county. AMTRAK also operated one yard (switcher) locomotive in the county.

Amount of fuel used in gallons by AMTRAK’s line haul locomotives in Montgomery County:

G cty1 = 25,463.8 gallons used in Montgomery Co. per year by AMTRAK (information provided by AMTRAK)

Amount of fuel used in gallons used by CS X Transportation line haul locomotives in Montgomery County:

36.37 track miles in Montgomery Co. for CSX G cty4 = 514.97 track miles in the state for CSX x 10,512,431.53 gallons used in state per

year

G cty4 = 742,445.45 gallons used in Montgomery Co. per year by CSX

Amount of fuel in gallons used by MARC line haul locomotives in Montgomery county:

28 track miles in Montgomery Co. for MARC G cty12 = 156 track miles in the state for MARC x 1,782,750 gallons used in state per year

G cty12 = 319980.77 gallons used in Montgomery Co. per year by MARC

VOC Emissions from line haul lo comotives in Montgomery County:

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.0213 lbs. VOC /gal EM VOC = (2000 lbs. per ton) * (365 days per year)

EM VOC = 0.0316 tons VOC / day

NOx Emissions from line haul lo comotives in Montgomery County:

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.4931 lbs. NOX /gal EM NOX = (2000 lbs. per ton) * (365 days per year)

EM NOX = 0.7348 tons NOX / day

CO Emissions from line haul lo comotives in Montgomery County:

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.0626 lbs. CO / gal EM CO = (2000 lbs. per ton) * (365 days per year)

EM CO = 0.0933 tons CO / day221 Yard Locomotives Emission Estimate

CSX operated 2 yard locomotives in Montgomery County:

VOC Emissions from yard locomotives in Montgomery County:

(2 engine * 228 gallons per e ngine per day * 0.0509 lbs. VOC / gallon) EM VOC = (2000 lbs. per ton)

EM VOC = 0.0116 tons VOC / day

NOx Emissions from yard locomotives in Montgomery County:

(2 engine * 228 gallons per e ngine per day * 0.5044 lbs. NOX / gallon) EM NOX = (2000 lbs. per ton)

EM NOX = 0.1150 tons NOX / day

CO Emissions from yard locomotives in Montgomery County:

(2 engine * 228 gallons per e ngine per day * 0.0894 lbs. CO / gallon) EM CO = (2000 lbs. per ton)
EM CO = 0.0204 tons CO / day

Total Emissions

Emissions from maintenance equipment used in the switching yards was calculated using the EPA’s Non-Road Model and then adde d for the appropriate county. Example emissions for Montgomery county: 0.0013 tons VOC / day, 0.0005 tons NOx / day, 0.0518 tons CO / day

Total VOC Emissions for Montgomery county: Emis VOC = 0.0316 tons / day from line haul + 0.0116 tons / day from yard + 0.0013 tons VOC / day from EPA Non-Road Model.
Emis VOC = 0.0445 tons VOC / day

Total NOx Emissions for Montgomery county: Emis NOx = 0.7348 tons / day from line haul + 0.1150 tons / day from yard + 0.0005 tons NOx / day from EPA Non-Road Model.
Emis NOx = 0.8503 tons NOx / day

Total CO Emissions for Montgomery county: Emis CO = 0.0933 tons / day from line haul + 0.0204 tons / day from yard + 0.0518 tons CO / day from EPA Non-Road Model.
Emis CO = 0.1655 tons CO / day222 5.4 AIRCRAFT SCC: 22 75 020 000 (Commercial Aircraft) SCC: 22 75 050 000 (General Aviation) SCC: 22 75 001 000 (Military Aviation)

This category includes three sub- categories identified as: commercial aircraft, general aviation, and military aircraft. Commercial aircraft are used in regularly scheduled flights transporting passengers, freight, or both. General aviation, wh ich includes air taxis and commuter aviation, is used for recreational flying, business travel, persona l transportation, and vari ous other activities. Military aviation is the operation and activities of military aircraft at airports in Maryland.

PM 10 , PM 2.5 , SOx, NOx, CO, VOC

ARMA used a variety of sources for data and emission calculation methods as follows:

Data sources

1) Airport Activity Statistics of Certificated Route Air Carriers published by Federal Aviation Administration for the 12 months ending December 31,2002, pp 7-314 to 7-
320. 2) This report lists total depart ures performed for commercial air carriers and individual types of commercial aircraft.

3) Landing and takeoff cycle information by airport for 1995/2002 from the Maryland

4) Aviation Administration and the Federal Aviation Administration Airport License Renewal Applications. The applications li sts LTO cycles by airc raft operation type from all general aviation airports, Martin State Airport which has general, and Baltimore/Washington International Airport for the past 12 months.

Methods sources

1) For general aviation ARMA used emissi on factors supplied in Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources , EPA’s Office of Mobile Sources, 1992. This source pr ovided emission factors for specific commercial engine types, and alternative flee t average factors for general aviation, air taxis, and commuter aircraft.

2) For military aircraft ARMA used a composite factor from section 5.2.5, Table 5-7 of Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources , 1988. This method required ARMA to collect LTO data rather than specifi c aircraft data. ARMA also used this com posite factor method in its 1990 baseline inventory. For the final 2002inventory ARMA has requested op eration data from military aircraft by operation type from Maryland Army, Navy, and Air Force base environmental support offices. Description:

Pollutants

Method and Data Sources223 3) For commercial aviation ARMA used FAA’s EDMS 115 emissions model and databases. EDMS is designed to assess th e air quality impacts of airport emission sources, particularly aviation sources, which consist of aircraft, auxiliary power units, and ground support equipment. EDMS features the latest aircra ft engine emission factors from the International Civil Avia tion Organization (ICAO) Engine Exhaust Emissions Data Bank, vehicle emissi on factors from EPA MOBILE 5a, and EPAvalidated dispersion algorithms. Aircraft activity includes landside and airside operations. EDMS defines f our distinct modes of aircraft operation based upon EPA and FAA guidance: approach, taxi/idle, takeoff, and climb out. Together, these four modes constitute one Landing and Takeoff ( LTO) cycle. EDMS calculates aircraft emissions based on these four modes.

4) For all aircraft types, ARMA used a defa ult mixing height value of 3,000 feet above ground level. The mixing height is the laye r of air where airplane emission affect ground level emission concentrations. A bove the mixing level, pollutants are transported away according to sections 5.2. 2 of the 1992 Procedures. Because of the mixing height, ARMA assigned all aircraft em issions from a particular airport to the county where that airport was located. We assumed no seasonal va riation and a seven day per week activity level.

No subtraction of emissions from point sources is necessary.

No controls are available for this source category.

Spatial Data for spatial allocation is not available for this source.

Temporal Data for temporal allocation is not available for this source.

115 Emissions & Dispersion Modeling System (EDMS) Version 3.2 for Windows from CSSI, Inc. Point Source Adjustments

Adjustment for Controls

Spatial and Temporal Allocations224 5.4.1 Commercial Aircraft (SCC: 22 75 020 000)

Steps in Creating and Airport Emission Inventory in EDMS:

1) Open the EDMS model and create a new study for the airport in question. Enter the parameters (name, mixing height, average yearly temperature, and units of measurement) that are specific to each airport into the study. 2) Provide EDMS with information to compute the emissions inventory. Begin by matching engines with aircraft and assigning them to the study. Select the aircraft to be used in the study (data that is collected from the airport) by picking the aircraft name from the menus. EDMS automatically associates specific aircraft with certain engine types. 3) For each aircraft fill in the yearly LTO cy cles provided by surveying the airport. 4) For each aircraft fill in the average annual taxi time and queue time specific to the airport or use the EDMS provide default values. 5) Continue to add each aircraft/engine type, LTO cycle, taxi time and queue time to the study. 6) EDMS has tables built into the model that associat e aircraft type with the number of engines, auxiliary power units and ground support equipment. The model also a ssigns default values for Takeoff Time (typically 0.3 minutes), Climbout Time (typically 5 minutes), and Approach Time (typically 6 minutes). 7) If emissions from parking lots, roadways, stat ionary sources, and training fires are also required, complete the dialog boxes associated with each of these subcategories. 8) Run the EDMS emission inventory program and view the results.

The following calculation aircraft operating at Baltimore/Washington International Airport in Anne Arundel County during 1998. Tabled below is the aircraft, engine a ssigned to the aircraft, time for each mode of operation, annual LTO ope rations, average annual taxi time, and the average annual queue time.

Aircraft
Name Aircraft Type Engine Assigned Approach Time (min) Climbout Time (min) Takeoff Time (min) Annual LTO Taxi Time (min) Queue Time (min) Falcon 100 GA TFE731-3 1.60 0.50 0.40 1825 10.50 3.00 P-337P Skymaster GA TSIO-360C 4.50 2.50 0.50 9490 10.50 3.00 550 Citation GA JT15D-4 (B,C,D) 1.60 0.50 0.40 2190 10.50 3.00

A320 Comm CFM56-5B4 4.00 2.20 0.70 2555 10.50 3.00 AH-1 Military T53-L-11D 6.80 6.80 0.00 1825 10.50 3.00

ATR42 Comm PW120 4.50 2.50 0.50 2190 10.50 3.00

B727-100 Comm JT8D-7A 4.00 2.20 0.70 8030 10.50 3.00

B737-200 Comm JT8D-15A 4.00 2.20 0.70 21900 10.50 3.00

B737-300 Comm CFM56-3B 4.00 2.20 0.70 13140 10.50 3.00

B737-400 Comm CFM56-3B 4.00 2.20 0.70 3650 10.50 3.00

B737-500 Comm CFM56-3B 4.00 2.20 0.70 8030 10.50 3.00

B737-700 Comm CFM56-3C-1 4.00 2.20 0.70 730 10.50 3.00

B747-100 Comm JT9D-7A 4.00 2.20 0.70 183 10.50 3.00

B757-200 Comm PW2037 4.00 2.20 0.70 7665 10.50 3.00 Emissions Calculation225 B767-200 Comm CF6-80A (A1) 4.00 2.20 0.70 1095 10.50 3.00

BAE ATP Comm PT6A-45 4.00 2.20 0.70 2555 10.50 3.00

BH-1900 Comm PT6A-65B 1.60 0.50 0.40 3285 10.50 3.00 C-12A/B/C Military PT6A-41 3.50 0.80 0.40 730 10.50 3.00 C-130 Hercules Military T56-A-16 5.10 1.20 0.40 365 10.50 3.00 C-9A Military JT8D-9 5.10 1.20 0.40 365 10.50 3.00 Canadair Reg-100 Comm CF34-3A1 4.00 2.20 0.70 730 10.50 3.00

Cessna 150 GA O-200 6.00 5.00 0.30 5110 10.50 3.00
Convair liner Comm RDA10 4.50 2.50 0.50 365 10.50 3.00

DC10-10 Comm CF6-50C 4.00 2.20 0.70 730 10.50 3.00

DC9-10 Comm JT8D-7A 4.00 2.20 0.70 4380 10.50 3.00

DHC-8 Comm PW120 4.50 2.50 0.50 3650 10.50 3.00

DHC-8-400 Comm PW123 4.50 2.50 0.50 18250 10.50 3.00 F-16 Military F100-PW-100 3.50 0.80 0.40 183 10.50 3.00 F-27 Series Military RDa7 4.50 2.50 0.50 365 10.50 3.00
Fokker 100 GA TAY650 4.00 2.20 0.70 365 10.50 3.00 H-46 Sea Knight Military T58-GE-8F 6.80 6.80 0.00 183 10.50 3.00 Kingair B200 GA PT6A-41 1.60 0.50 0.40 5840 10.50 3.00 Learjet 25B GA CJ610-6 1.60 0.50 0.40 1460 10.50 3.00

MD-11 Comm CF6-80C2D1F 4.00 2.20 0.70 730 10.50 3.00

MD-80 Comm JT8D-209 4.00 2.20 0.70 4563 10.50 3.00

MD-80-88 Comm JT8D-217 4.00 2.20 0.70 1825 10.50 3.00

MD-90-10 Comm V2525-D5 4.00 2.20 0.70 365 10.50 3.00 Porter PC6/B2 Military PT6A-27 4.50 2.50 0.50 730 10.50 3.00

SF-340-A Comm CT7-5 4.50 2.50 0.50 730 10.50 3.00 Swearingen Merlin Comm TPE331-3 4.50 2.50 0.50 2920 10.50 3.00 Swearingen Merlin Comm TPE331-3 4.50 2.50 0.50 365 10.50 3.00 Once all of the data is entered into the model, the model produces an emission inventory. Annual emission inventory results are listed in th e table below:

NAME CO Tons/year HC 116 Tons/year NOX Tons/year SOX Tons/year PM10 Tons/year
Aircraft 767.886 128.821 905.493 41.586
GSE/AGE/APU 2810.992 71.658 221.278 6.027 7.871
Total 3578.878 200.476 1126.771 47.613 7.871

The model will also produce an inventory specific to each aircraft type, which allows the data to be separated into types (commercial, general aviation, and military) of operation. For BWI the separation results in the following:

NAME CO Tons/year HC Tons/year NOX Tons/year SOX Tons/year PM10 Tons/year
Commercial Aircraft 546.030 84.833 890.956 40.399 0.000
General Aviation 202.667 34.256 6.699 0.654 0.000 Military Aviation 19.189 9.732 7.838 0.533 0.000
Total 767.886 128.821 905.493 41.586 0.0

116 Requires a Hydrocarbon to VOC conversion factor of 1.0947.226 A daily emission inventory was produced assumi ng an airport activity of 365 days per year.

The model was run for all aircraft at BWI and a ll commercial aviation at Hagerstown Regional, Ocean City Municipal and military airc raft at Andrews Air Force Base.227 5.4.2 General Aviation
SCC: 22 75 050 000

A rough estimate of emissions were calculate d after information on the LTO operations of aircraft operation type was obtaine d from Maryland’s airports. Th is method used the alternative fleet-average procedure of S ection 5.2.4.2 of Procedures , 1992. The composite emission factors used are listed in the table below.

CO (lbs./LTO) HC* (lbs./LTO) NOx (lbs./LTO) SO2 (lbs./LTO) PM (lbs./LTO)

General Aviation 12.014 0.394 0.065 0.100 0.020

Air Taxis 28.130 1.234 0.158 0.015 0.020

* Requires Hydrocarbon to VOC conversion factor of 0.9708 for General Aviation and 0.9914 for Air Taxis.

1) Emiss VOC = LTO (GA) * EF (GA) VOC

Where: LTO (GA) = LTOs for General Aviation EF (GA)
xx = Emission Factors for General Aviation

2) Emiss VOC = L(AT) * EF(AT) VOC

Where: L(AT) = LTOs for Air Taxis EF(AT)
xx = Emission factors for Air Taxis

Sample Calculation – General Aviation:

This calculation is for Easton Airport/Newman Fi eld in Talbot County. The airport had 21,569 General Aviation LTOs over a twelve month period. Performing step 1 Equations (above) the calculations were:

Emiss VOC = [L(GA) * EF(GA) HC ]* CF (VOC/HC) Emiss VOC = [(21,569 LTOs / Year * 0.394 (lbs. HC / LTO)] * 0.9708 (lbs. VOC / lbs. HC)))) Emiss VOC = 8,250.0390 lbs. VOC / Year Emiss VOC = 0.0113 Tons VOC / Day

Emiss CO = [21,569 LTOs / Year * 12.014 (lbs. CO / LTO)] Emiss CO = 259,129.966 lbs. of CO / Year Emiss CO = 0.3550 Tons CO / Day Emiss NOx = [21,569 LTOs / Year * 0.065 (lbs. NOx / LTO)] Emiss NOx = 1,401.985 lbs. of NOx / Year Emission Calculation228 Emiss NOx = 0.0019 Tons NOx / Day

Emiss SO2 = [21,569 LTOs / Year * 0.100 (lbs. SO2 / LTO)] Emiss SO2 = 2,156.900 lbs. of SO2 / Year Emiss SO2 = 0.0030 Tons SO2 / Day

Emiss PM = [21,569 LTOs / Year * 0.020 (lbs. PM / LTO)] Emiss PM = 431.380 lbs. of PM / Year Emiss PM = 0.0006 Tons PM / Day

Sample Calculation – Air Taxi:

This calculation is for Easton Airport/Newman Fi eld in Talbot County. The airport had 4,557 Air Taxi Aviation LTOs over a twelve month peri od. Performing step 1 Equations (above) the calculations were:

Emiss VOC = [L(AT) * EF(AT) HC ]* CF (VOC/HC) Emiss VOC = [(4,557 LTOs / Year * 1.234 (lbs. HC / LTO)] * 0.9914 (lbs. VOC / lbs. HC)))) Emiss VOC = 5,574.9773 lbs. VOC / Year Emiss VOC = 0.0076 Tons VOC / Day

Emiss CO = [4,557 LTOs / Year * 28.130 (lbs. CO / LTO)] Emiss CO = 128,188.410 lbs. of CO / Year Emiss CO = 0.1756 Tons CO / Day

Emiss NOx = [4,557 LTOs / Year * 0.158 (lbs. NOx / LTO)] Emiss NOx = 720.006 lbs. of NOx / Year Emiss NOx = 0.0010 Tons NOx / Day

Emiss SO2 = [4,557 LTOs / Year * 0.015 (lbs. SO2 / LTO)] Emiss SO2 = 68.355 lbs. of SO2 / Year Emiss SO2 = 0.0001 Tons SO2 / Day

Emiss PM = [4,557 LTOs / Year * 0.020 (lbs. PM / LTO)] Emiss PM = 91.14 lbs. of PM / Year Emiss PM = 0.0001 Tons PM / Day229 5.4.3 Military Aircraft
SCC: 22 75 001 000

There are five military airports in Maryland. They are Andrews Air Force Base, Fort Meade/Tipton, Aberdeen, Patuxent River Naval Air Station, and Martin State Airport. ARMA received LTO information from all airports. The Aberdeen Airport reported no activity in 2002. Most of the county airports also receive a small number of military operations.

Since ARMA asked for and received LTO inform ation by aircraft operation type, ARMA used composite emission factors from Procedures fo r Emission Inventory Preparation, Volume IV: Mobile Sources, 1988 for all airports except Andrews Air Force Base. The EDMS model (version 3.2) was used to calcu late emissions from Andrews Ai r Force Base. Otherwise, the composite emission factors are listed in the table below.

CO (lbs./LTO) VOC (lbs./LTO) NOx (lbs./LTO) SO2 (lbs./LTO) PM (lbs./LTO)

Military Aircraft 48.80 27.10 9.160 1.430 15.230

1) Emiss VOC = L(MA) * EF(MA) VOC

Where: L(MA) = LTOs for Military Aircraft EF(MA)
xx = Emission factors for Military Aircraft

This calculation is for Patuxent River Naval Air Station in St. Mary’s county. The airport had 63,852 LTOs in 2002. Using step 1 from E quations (above) the calculations were:

Emiss VOC = [L(AT) * EF(MA) HC ] Emiss VOC = [(63,852 LTOs / Year * 27.10 (lbs. VOC / LTO)] Emiss VOC = 1,730,389.200 lbs. VOC / Year Emiss VOC = 2.3704 Tons VOC / Day

Emiss CO = [63,852 LTOs / Year * 48.80 (lbs. CO / LTO)] Emiss CO = 3,115,977.60 lbs. of CO / Year Emiss CO = 4.2685 Tons CO / Day

Emiss NOx = [63,852 LTOs / Year * 9.160 (lbs. NOx / LTO)] Emiss NOx = 584,884.32 lbs. of NOx / Year Emiss NOx = 0.8012 Tons NOx / Day Method and Data Sources

Emissions Calculation230 Emiss SO2 = [63,852 LTOs / Year * 1.430 (lbs. SO2 / LTO)] Emiss SO2 = 91,308.36 lbs. of SO2 / Year Emiss SO2 = 0.1251 Tons SO2 / Day

Emiss PM = [63,852 LTOs / Year * 15.23 (lbs. PM / LTO)] Emiss PM = 972,465.96 lbs. of PM / Year Emiss PM = 1.3321 Tons PM / Day231232 5.5 Marine Vessels SCC: 22 80 002 010 (diesel marine vessels)

Commercial vessels include all boats and ships used either directly or indirectly for commerce or military activity. These include vessels ranging in size from 20-foot charter boats to the largest tankers and military vessels, whic h can exceed 1,000 feet in length.

PM, SO 2 , NOx, CO, HC, CO 2

MDE used the emission inventory prepared for the Maryland Port Administration by Edwards and Kelcey (E&K). E&K analyzed the major categories of air emissions associated with ship and port operations and their relationship to air quality issues in the Ba ltimore non-attainment area.

E&K used the marine emission inventory guidan ce method outlined in Analysis of Commercial Marine Vessels Emissions and Fuel Consumption Data (EPA-450-R-00-002), February 2000, to calculate emissions from commerc ial marine vessels. The met hodology is based on a three-step calculation. The first step apportions the time spent by a vessel in a port area to different operating modes. The second calculates fuel consumption in each operating mode. The third step calculates emissions using fuel consumption specific emission factors, which is how ma rine engine emission factors have been historically sp ecified. All of these calculations are made by vessel type and class, with the type specifying whether th e vessel is a tanker, passenger line r, etc, and the class specifying either the weight or horsepower range.

This new methodology considers new information colle cted on marine vessels. The time-in-mode is a function of the particular port ar ea geography and was not considered in the report. The other factors used in the emission estimate computation are examined, with particular focus on the emission factors, for all pollutants of con cern. One reason for a detailed rec onsideration of the emission factors is that a number of large marine diesels have been tested for emissions and their tests results have become available in the last few years. In addi tion, both the EPA and ARB have recently sponsored studies to calculate marine vesse l emissions in the South Coast Ai r Basin and in some areas of Region IX, so that there is a body of new research available to update emission factors. Hence, the use of a larger and newer database on marine vessel emission is expected to substantially improve the quality of the derived emission factors.

Activity The computation of emissions can be performed by ship type for a given port and requires the following inputs:

• The number of calls to the port by ve ssel class and deadweight tonnage. Description

Pollutants

Method and Data Sources233 • The time spent, by ship type, in each of four operating modes de fines as: normal cruise, slow cruise, maneuvering, and hoteling.
Emission Factors

Emission rates were calculated per pollutant (except SO2) per vessel type per mode of operation within the guidance documen t using the following formula:

E (i) = a * (Fractional Load) –x + b

Where:

E (i) = Emission rate of pollutant i in grams per kilowatt-hour a = Coefficient x = Exponent b = Intercept

Emission rates were calculated per pollutant (S O2 only) per vessel type per mode of operation within the guidance document using the following formula:

E (SO2) = a * (Fuel Sulfur Flow in g/kW-hr) + b

The marine engine emission factor and fuel consumption algorith ms are presented in the table below:

Pollutant Exponent (x) In tercept (b) Coe fficient (a)

PM 1.5 0.2551 0.0059

NOx 1.5 10.4496 0.1255

SO2 1 0 2.3735

CO 1 0 0.8378

HC 1.5 0 0.0667

CO2 1 648.6 44.1

The marine engine emission rates in grams per k ilowatt-hour are presente d in the table below:

Vessel Type Cruise Slow Cr uise Maneuvering Hoteling

PM (gr/kw-hr) PM (gr/kw-hr) PM (gr/kw-hr) PM (gr/kw-hr)

Bulk Carriers & Tankers 0.2633 0.2784 0.3211 0.4417
General Cargo 0.2633 0.2836 0.3211 0.4417

Passenger 0.2633 0.3211 0.4417 0.7828

Container/ RORO/ Reefer/Auto Carrier 0.2633 0.291 0.3567 0.5424
All non-oceangoing 0.2633 0.2784 0.3211 0.4417
NOx (gr/kw-hr) NOx (gr/kw-hr) NOx (gr/kw-hr) NOx (gr/kw-hr)

Bulk Carriers & Tankers 10.625 10.9457 11.8527 14.4183234 Vessel Type Cruise Slow Cr uise Maneuvering Hoteling

General Cargo 10.625 11.0557 11.8527 14.4183

Passenger 10.625 11.8527 14.4183 21.6747

Container/ RORO/ Reefer/Auto Carrier 10.625 11.2134 12.6099 16.5597
All non-oceangoing 10.625 10.9457 11. 8527 14.4183
SO2 (gr/kw-hr) SO2 (gr/kw-hr) SO2 (gr/kw-hr) SO2 (gr/kw-hr)

Bulk Carriers & Tankers 26.5081 28.6027 32.7919 41.1704
General Cargo 26.5081 29.2012 32.7919 41.1704

Passenger 26.5081 32.7919 41.1704 57.9273

Container/ RORO/ Reefer/Auto Carrier 26.5081 29.9991 35.5847 46.756
All non-oceangoing 26.5081 28.6027 32. 7919 41.1704
CO (gr/kw-hr) CO (gr/kw-hr) CO (gr/kw-hr) CO (gr/kw-hr)

Bulk Carriers & Tankers 1.0473 2.0945 4.189 8.378
General Cargo 1.0473 2.3937 4.189 8.378

Passenger 1.0473 4.189 8.378 16.756

Container/ RORO/ Reefer/Auto Carrier 1.0473 2.7927 5.5853 11.1707
All non-oceangoing 1.0473 2.0945 4. 189 8.378
HC (gr/kw-hr) HC (gr/kw-hr) HC (gr/kw-hr) HC (gr/kw-hr)

Bulk Carriers & Tankers 0.0932 0.2637 0.7457 2.1092
General Cargo 0.0932 0.3221 0.7457 2.1092

Passenger 0.0932 0.7457 2.1092 5.9658

Container/ RORO/ Reefer/Auto Carrier 0.0932 0.4059 1.1481 3.2474
All non-oceangoing 0.0932 0.2637 0.7457 2.1092
CO2 (gr/kw-hr) CO2 (gr/kw-hr) CO2 (gr/kw-hr) CO2 (gr/kw-hr)

Bulk Carriers & Tankers 703.725 758.85 869.1 1,089.60
General Cargo 703.725 774.6 869.1 1,089.60

Passenger 703.725 869.1 1,089.60 1,530.60

Container/ RORO/ Reefer/Auto Carrier 703.725 795.6 942.6 1,236.60
All non-oceangoing 703.725 758.85 869. 1 1,089.60

No point source emissions were subtr acted from the area source inventory.

No controls are available for this source category.

Point Source Adjustments

Adjustment for Controls235 Spatial Data for spatial allocation is not available for this source. E&K emissions inventory focused on the City of Baltimore and allotted th e cruise emissions to the city.

Temporal Data for temporal allocation is not available for this source.

The equation used to estimate emissions from commercial marine vessels is:

CALLS VCC, DWT x LENGTH VCC, DWT x %TIME VCC, DWT,

MODE TIME VCC, DWT, MODE = 100

EMISSIONS VCC, DWT, MODE = (EF)(LF MODE ) x (HP) (DWT) x LF MODE x TIME VCC, DWT,

MODE Where: VCC is the vessel class (bulk carrier, tanker, container, general cargo, passenger, reefer, RORO, tug, vehicle carrier, or miscellaneous) DWT is the deadweight tons EF is the emissions factor LF is the mode specific load factor

For the calculation, the TIME equation requires port specific inputs, while the guidance method outlined in Analysis of Commercial Marine Vessels Emissions and Fuel Consumption Data(EPA450-R-00-002), February 2000, provides the EF and HP relationships.

Data on the type of vessels, numbe r of calls per vessel type, deadwe ight tons per vessel type, and time in each mode per vessel type using Baltimor e port facilities came from the Maryland Port Administration (MPA).

In addition, the MPA provided data that translated into approximately 85 percent of the vessels arriving from the south (up the Chesapeake Bay) and 15 percent of the vessels arriving from the north (down from the Chesapeake and Delaware Canal). The data allowed MDE to allocate slow cruising emissions to the appropriate counties to the north and south of the Port of Baltimore. Emissions associated with "normal cruising" were assumed by MDE not to have occurred while in the Maryland airshed.

All of the maneuvering and hoteling emissions were assigned to the City of Baltimore.

Spatial and Temporal Allocations

Emissions Calculation236 

## 6.0 ONROAD MOBILE SOURCES

6.1 INTRODUCTION

As detailed in the following sections, the official 2002 highway vehicle emissions estimates for the 8- hour ozone SIP submittal, have been developed base d on the highway traffic data obtained from the Maryland State Highway Administration (SHA)

The official highway vehicle em ission inventory for the Maryland portion of the Washington, D.C. Ozone Non-attainment Area (comprising the counties of Calvert, Charles, Frederick, Montgomery, and Prince George's) has been developed by the Metropolitan Washington Council of Governments (MWCOG) based on the transportation demand mode ling data and has been documented by that organization under separate cover.

In accordance with the standard methodology for th e development of highway vehicle emissions inventories, all of the emissions estimates documented herein are based on emission factors developed using the United States Environmental Pr otection Agency's (U.S. EP A's) latest version of the MOBILE6 emissions factor model and using a ppropriate activity levels i.e., vehicle miles traveled (VMT) estimates developed from the highw ay traffic data obtained from the SHA of the Maryland Department of Transportation (MDOT).

In its simplest form, highway vehicle emissions can be modeled by aggregating the products of emission factors of various vehicle types and vehicl e travel activity on various roadway classes, as illustrated in the following equation:

Emissions = (Emission Factors) x (Vehicle Activity)

The emission modeling computations (expressed in tons per summer weekday or tons per annum) involve application of appropriate conversion and seasonal adjustment factors on the two entities of the emission equation – emission factors in gr ams per mile and vehicle activity in VMT.

In the real world, development of highway vehicle emissions over a large network of roadways is a complicated and data intensive effort that requ ires the correct expertise and tools to produce emissions based on the federal and state requireme nts. MDE used the PPSuite system, a robust, systematic, and comprehensive software approach to develop the on-road em issions for the state.

This new post-processor, PPSUIT E was used for the first time in 2003 by MSCP for the 2005 Mobile Emission Budget effort. However this software syst em has been in use in Pennsylvania, Virginia, New Jersey, and the New York City Metropolitan Area, for previous inve ntory and conformity submissions. PPSUITE is also compatible with travel demand modeled activity data and as such used in the Baltimore Area’s for transportation confor mity analysis. The following table provides a summary of the emission proce ss and various data inputs.237 PPSUITE Emission Modeling Process

SHA Prepared Data

2002 Highway Data

- UNIV02 Database

(128,379 Statewide Records) Based on Highway Location Reference System

County Number
L anes 2002 Vehicle Classifications

(Statewide Avg. By FC)

From SHA Traffic Monitoring System Website

Percent of Fleet by FHWA vehicle classes

Map to vehicle type 2002 Seasonal Factors

(Statewide Average By FC Group)

Based on SHA Traffic Trends System: Functional
Class Reports

Percent of AADT for

monthly weekdays 2002 Hourly Pattern
Data

(Statewide Avg. By FC)

Based on SHA Traffic Trends System:
Functional Class Reports

Percent of volume in

each hour of day 

## A B C D

PPNET
N e t wo rk

MOBILE6 Highway Network
Data

POSTMOBILE

Pr oces s M 6

PEQUESTR
C r e at e R epo rt s PREMOBILE

Prepare M6 PPSUITE

PPSUITE Driver File Vehicle Mix File
(Vol by vehicle type)

SHA Statewide Patterns

(LDV, HDV, BUS, MC)

MPO Regional Pattern

(LDV, HDV, BUS, MC) prepared by

BMC, MWCOG, etc.,

Hourly Pattern File

(Volume by hour of day)

Vehicle Factor File

(Veh impact on capacity)

Speed Capacity Lookup

Develop data set with free flow speeds, lane capacities, default signal spacing, BPR

p arameters, etc., IM Parameters

Vehicle Age

VMT Seasonal Adjustments 

### Emission Calculation Scheme



## A

B

C

D238 6.2 EMISSION FACTORS

The heart of the highway vehicle emission’s ca lculation procedure is EPA’s highway vehicle emission factor model, MOBILE. This is a FORTRAN program that calculates average in-use fleet emission factors for specific pollutants for each of twenty-eight categories of vehicles under various conditions affecting in-use emission levels (e.g ., ambient temperatures, average traffic speeds, gasoline volatility) as specified by the model user . MOBILE6 model does not produce total emissions directly, but it generates emissi on factors as referred to in the previous section.

The first MOBILE model was developed as MOBILE1 in the late 1970s. It ha s been periodically updated to reflect the collection and analysis of add itional emission factor data over the years. It also has been upgraded to capture ch anges in vehicle/engine/emission control system technologies, and changes in applicable regulations, emission standards and test procedures, and improved understanding of in-use emission leve ls and the factors that influence them. For this inventory effort, the latest MOBILE model (MOBILE6.2 version 6.2.03 of 24-Sep-2003 - hitherto referred as MOBILE6) was utilized in generating the emission f actors and in building the emission inventories.

6.3 VEHICLE MILES TRAVELED

The traffic data source is the key data item that drives the VMT and speed calculations. This process uses highway data and volumes obtained from SHA. The objective was to utilize non-travel model data sources that will continue to be monitored and updated in the fu ture, which will facilitate future updates to the process. The proce ss utilizes the PPSUITE post proces sor that consists of a set of programs that perform the following functions:

• Analyzes highway operating conditions

• Calculates highway speeds

• Compiles vehicle miles of travel (VMT) and vehicle type mix data

• Prepares MOBILE6 input files a nd actually runs MOBILE6 model

• Calculates emission quantities from output MOBILE6 emission rates and accumulated highway VMT.

The PPSuite process utilizes a number of programs a nd operations assembled into a chain of jobs and steps. The management of these model chains and th eir operations can be difficu lt. At the front end, an interfacing software package called CENTRAL is deployed, providing MD E with the ability to efficiently manage the emission calculation process.

6.4 KEY TRAVEL DATA INPUTS239 This section describes the SHA da ta inputs to the emission calcula tion process. The inputs were prepared based on available 2002 data and include:

• Highway Data

• Vehicle Classifications

• Seasonal Factors / HPMS VMT Reconciliation

• Hourly Pattern Data

The remaining sections provide an overview of each of the key SHA data inputs.

Highway Data Inputs

The 2002 highway data set was obtaine d directly from SHA and is re ferred to as the “Universal” highway database . The file obtained is named HMIS.MDB ; it represents 2002 traffic data and contains the following roadway variables:

• Facility type and area type classifications

• Number of travel lanes

• Speed Limits

• Average Annual Daily Traffic volumes

The PPSUITE post processor require s a network database (in “DBF ” format) to support emission calculation runs and expects specific data fields to be present. A roadway network was created using the table “ UNIV2002 ” in the SHA ACCESS database file HMIS.MDB. This table was first saved as a separate database file. Then some specific opera tions on data fields such as addition, deletion, renaming and field value modificatio ns were conducted using the ACCESS database software. This is the key vehicle activity input to the emission modeling system.

Vehicle Mix Inputs

The vehicle mix distribution file is another key input file that can have a significant impact on emissions. The data is used in combination with diesel sales fractions by MOBILE6 to develop a composite emission rate for all the 28 output vehicl e types. The vehicle mixes are input to PPSUITE as hourly distributions of vehi cles by vehicle type. The mixe s are developed using 2002 data available from the Traffic Monitoring System section, from the SHA website that has a link named

“ Vehicle Classification by Functional Class ”. That link leads to a report file in PDF format, which reflects the percent of vehi cle classifications by functi onal class for the years 1998 through 2003.

The PPSUITE input 2002 SHA vehicle mix file wa s prepared based on 4 input vehicle groups:

• Vehicle Type 1 = Motorcycle240 • Vehicle Type 2 = Light-duty vehicles

• Vehicle Type 3 = Buses

• Vehicle Type 4 = Heavy-duty vehicles

For input to the emission calculation process, all the vehicle cla sses were grouped into 4 categories for each functional class: Auto , Truck, Bus, and Motorcycle . Vehicle class 1 category was used for motorcycles. Classes 2 and 3 were combined to obt ain the percentage autos. Class 4 was used for buses. Truck percentages were obtained by combining classes 5 to 13. The PPSUITE postprocessor automatically sp lits the four input vehicl e categories to the requ ired 16 MOBILE6 vehicle classes by using the MOBILE6 defaults, wh ich vary by the chosen analysis year.

Hourly Pattern Inputs

Speeds and emissions vary depending on the time of day because of temperature variations and congestion. Therefore, it is important to estima te the pattern by which roadway volume varies by hour of the day. The hourly patte rn distributions are not only input directly to MOBILE6, but are also a key input file to PPSUITE fo r estimating hourly congested speeds.

Hourly mixes of vehicles for each area and facili ty type combination are input to PPSUITE. These are used to determine the proportion of the daily vol ume in each hour of the day, so separate hourly speeds can be prepared and input to MOBILE6. Hourly pattern data was obtained from the Traffic Trends System Report Module from the SHA website. The above link leads to a screen with different Traffic Trends Reports Selection options. By clicking on the Group Reports section, a criteria screen will appear with the type of group report, year, and functional class to be chosen.

To get the hourly distribution data, the report type “ Hour Percent of Traffic by Month – Weekday ” was selected. Factors for 5 functional classes are available: Rural Interstate, Rural other, Urban Interstate, Urban other and summer seasonal. One functional class can be chosen at a time. Once these options are selected and the view report button clicked, the tabl e with the factors is obtained.

For the ozone daily emission calculation proces s, 2002 hourly pattern data for the 4 primary functional classes was used to creat e the PPSUITE input files. An av erage factor was calculated for 3 months – June, July and August to derive hourly percentage of vehicl es for a summer weekday. For the annual emission computation process, average factors were calc ulated for every month in the evaluation year 2002.

VMT Adjustments

The SHA network link volumes have been adjusted using the VMT adjustment factors, to account for differences with the HPMS VMT totals (differen ces primarily related to missing local VMT). The factors were developed upon completion of a 2002 analysis run (with no VMT adjustments or seasonal factors enabled) by comparing the results to the 2002 HPMS VMT.241 The adjustment factors are obtained by divi ding the 2002 HPMS VMT by the 2002 analysis run VMT for each county functional class grouping. Th ese calculated VMT adjustment factors are provided as ASCII input files to PPSUITE and are applied to each of the roadway segment volumes (see seasonal factor section for desc ription of PPSUITE VMT adjustment file format). These factors can be applied to any future year runs. The VMT added or subtracted to the SHA database assumes the speeds calculated using the original volumes fo r each roadway segment for each hour of the day.

Seasonal Adjustments a nd Temporal Allocation

Highway vehicles contribute signif icantly to air pollution, particul arly to ground-level ozone in the summer months. Ozone is not created directly, bu t it is formed in sunlight from VOCs and NO
x . Both VOCs and NO
x are emitted largely from highway vehicles.

Even though other pollutants such as CO, NH 3 , SO 2 , PM 2.5 , and PM 10 contribute to air pollution during summer also, but their si gnificance is much more during th e winter months. This is in accordance with the EPA’s guidance on preparati on and submission of emission inventories.

For annual inventories, MOBILE6 input parameters such as average hourly temperature, hourly humidity and atmospheric pressure, diesel sulfur content, RVP, etc., were developed for every month in the evaluation year 2002.

The seasonal factors are used to adjust the average annual day traffic (AADT) to represent the average summer weekday, which is needed for emission anal yses. The seasonal and monthly VMT adjustment factors were develope d using the traffic flow data available by day and month from ATR Station Reports in the Traffic Trends System Report Module from the SHA website accessed. The above link leads to a screen with different Traffic Trends Reports Selection options. By clicking on the Group Reports section, a criteria screen will appear with the type of group report, year, and functional class to be chosen.

To get the monthly variation of traffic flow for the year 2002, the report type “ Traffic Flow by Day by Month by Group ” was selected. Factors are available for 5 functional classes: Rural Interstate, Rural other, Urban Interstate, Urban ot her and summer seasonal. One func tional class can be chosen at a time. Once these options are selected and the view report button clicked, the table with the traffic flow data is obtained.

The AADT percentage is available fo r each of the 7 days of the week for all the 12 months, which is divided by 100 to get a daily factor. An average monthly weekday f actor was obtained for 12 months by calculating an average factor for 3 weekda ys, Tuesday, Wednesday and Thursday. The242 calculations were repeated for a ll the 4 functional classes. These functional class groups were then mapped to the 12 functional classes us ed within the emission process.

Average monthly adjustment factors were de veloped for every month in 2002. The summer adjustment factors were developed, by calculating the average of the monthly factors for June, July, and August.

The above factors are coded into ASCII files, which are input to PPSUITE.. A separate file is provided for each of the 12 monthly scenarios and for the summer seasons. These files are selected through the Central menu screen depending upon what season the analysis is being run for. The adjustment factors are applied by PPSUITE before the calculation of link-level speeds.

6.5 MOBILE INPUT PARAMETERS

The inputs to MOBILE that affect emissions include numerous vehicl e and environmental parameters including:

• Vehicle Mixes

• Vehicle age distributions a nd diesel sales fractions

• Fuel parameters

• Inspection/maintenance program parameters

• Other environmental variables

MOBILE model allows the user to choose default values for input parameters where data is not locally available. User supplied data is preferable in most cases.

VMT mixes, a significant piece of data with a si gnificant impact on emissi on levels, are generated on the go by the PPSuite system using from all the tra ffic related data such as highway network data, vehicle pattern file, vehi cle factor file, etc.,

The vehicle fleet age has a significant impact on regional emission estimates and these were computed by MSCP from the 2002 Maryland vehicle re gistration database. The diesel sales fractions also came out of the same source.

The fuel parameters such as , Reid Vapor Pressure diesel sulfur, etc., and environmental variables such as hourly temperatures, hourly humidity, atmo spheric pressure, etc., were also developed by MSCP tapping 2002 data from appropriate agencies.243 MOBILE modeling assumptions in clude selection of appropria te month and season and the appropriate fuel program for the modeling domain. In case of areas with reformulated gasoline requirements, fuel program ‘4’ was modeled with the gasoline sulfur matr ix supplied by U.S EPA.

North East Low Emission Vehicle (NLEV) program was selected for the state of MD and for the NOx correction, the MOBILE parameter REBUILD EFFECTS was modeled at a 11% value for 2002 for North East states, per U.S EPA.

PPSuite generates several MOBILE inputs for each county by roadway class, based on the above parameters using the PreMOBILE module. MOBILE m odel is then invoked a nd after the specific number of runs, the PostMOBILE module takes care of the emission aggregation process.

Finally the reporting routine comes in and formats th e report based on the pre- selection: summary or detailed emissions for selected pollutants by county, by roadway type, by vehicle group.

All the above input/output data has been gene rated based on the current emission inventory development guidelines issued by the U.S EPA. They are not included in this documentation due to their size and number and will be made available upon request.

6.6 OTHER DATA INPUTS

There are other files required by PP SUITE that are used for all analys is year runs. These files are illustrated in following table.

Other PPSUITE Input Files

File Name File Description
EQUIV.DBF Area equivalencies used for input pattern files and output aggregation.

NAME_COUNTY.DBF Used for the output emission reports. It relates the coded facility and area type numbers to text names. Th is file is used when the countylevel totals report type option is selected.

NAME_RURURB.DBF Used for the output emission reports. It relates the coded facility and area type numbers to text names. Th is file is used when the countyrural/urban totals report type option is selected.

VEHFC2_02SHA.DAT Contains the impacts of truck percentages on roadway capacity. As a result, the amount of trucks can have an impact on calculated congested speeds.

SPEEDCAP.DBF For each facility type, area type, and lane combination, this file contains:

• Free flow speeds

• Free flow capacities

• BPR Parameters (relationship between speed and congestion)244 VEHPATT_02SHA.DAT Contains the mix of VMT among the auto, truck, bus and motorcycle vehicle groups. Files were developed utilizing SHA
vehicle classes classification.

Zone/Area Equivalency

The zone/area equivalency file is a file used to provide equivalenc y between each link and the fields used for pattern (hourly and vehicl e mix) indexing and output emission indexes. The file is required by PPSUITE and relates to the equivalency ke yword in the PPSUITE driver file.

Names Database File

The names database file is used in the process of generating output emission reports. It relates the coded facility and area type numbers to text na mes. The emission process has the flexibility to generate two types of reports, one with county totals and the other with county rural/urban subtotals. To produce the reports with county totals, NAMES_COUNTY.DBF is used; for reports with county – rural/urban totals, the NAMES_RURURB.DBF file is used in the analysis.

Speed / Capacity Lookup Inform ation – Other PPSUITE Inputs

The speed-lookup table is a key file that has a signi ficant impact on calculat ed speeds and capacities for each roadway link. The file is used for the following purposes:

• Determine free-flow speeds for links without coded speed limits

• Determine link “ideal” capacity

• Determine signal densities and characteristics

• Determine speed/congestion relatio nships (BPR coefficients)

This dataset was developed through a speed calibration analysis u tilizing SHA 2002 speed monitoring data.

The remaining two databases are us ed in the VMT Mix computations.

6.7 EMISSION PROCESS OUTPUTS

After MOBILE model has been run, PPSUITE pro cesses the MOBILE output files and compiles the emission factors for each scenario. Using th e MOBILE emission factors, PPSUITE calculates emission estimates by multiplying the emission fact ors by the aggregated VMT totals. PPSUITE then produces an emissions database summari zing VMT, VHT, VOC, and NOx emissions. The output files are automatically output to individua l county subdirectori es located under the automatically created “OUT” directory. Files will have hard-coded names. The naming is done using the first four digits of the county name and the 2 -digit analysis year. In most cases, the user will not245 have to utilize these file s; however, they may be useful for i nvestigating potential errors that may occur in the process.

The summary results of all the summertime a nd annual runs for VOC, CO and NOx have been incorporated in Table 1-3 through 1-8.

6.8 CONVERSION TO NIF FORMAT

This is also an automated process through use of a NIF Conversion Program. This module basically reads the appropriate VMT and Emission databases a nd converts them into ACCESS databases in the NIF format. As such there are two tables in this submittal:

1) A database for summer day VOC , CO and NOx emissions for all counties in MD except for the MD counties under the jurisdiction of MWCOG, and 2) Another database for annual VOC, CO and NOx em issions for all counties in MD except for the MD counties under the jurisdiction of MWCOG.246 

## 7.0 BIOGENIC EMISSIONS

7.1 INTRODUCTION

Biogenic sources, a subset of natura l sources, include only those sources that result from some sort of biological activity. Biogenic emissions repres ent a significant portion of the natural source emissions, and VOC, NO
x , and the greenhouse gases can be emitted from biogenic sources.

Vegetation is the predominant biogeni c source of VOC and is typically the only source that is used to estimate biogenic VOC emissions. Microbial ac tivity is responsible for the emission of NO
x and the greenhouse gases of CO 2 , CH 4 , and N 2 O. Soil microbial activity is responsible for NO
x and N 2 O emissions from agricultural lands and grasslands. CH 4 is emitted through microbial action in waterlogged soils or in other anaerobic microenvironments. CO 2 is released through the aerobic decay of biomass (EPA, 1993; EPA,1990a).

Biogenic emissions is one category th at MDE is unable to control dire ctly, therefore, a majority of the resources were directed towards other categories of air pollution where direct control is feasible. For this reason, MDE used the data files created and made available by EPA (2002). These emissions were computed on an hourly basis with a specially-modified version of BEIS3 117 that utilized county land use data from EPA’s land use inventory and National Weat her Service first-order station data of temperature and cloud cover. However, due to the larg e size of the hourly data files, only the monthly data files were available when MDE gathered this information.

The data files EPA generated contained county-to tal estimates of 2002 biogenic emissions based on the BEIS3.12 model. The purpose of this spreadsh eet is to provide default 2002 estimates to the states for the purpose of biogenic emissions su bmittals by county required by the Consolidated Emissions Reporting Rule (CERR). These estima tes were created using the following data: 1) 2001 annual meteorology 2) BEIS3.12 model via the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system 3) Recently revised BEIS3.12 emission factors file (also provided as a separate file with this spreadsheet) 4) BELD3 land use data (1-km original data aggregated to 36-km grid). 5) Post processing summation of county-total em issions from SMOKE, calculated from 36-km gridded emissions using th e "land area" spatial surrogate. Th is means that when calculating the county-total numbers, the 36-km gridded emissions were assumed to be uniformly distributed over the grid cell for pu rposes of mapping to the counties.

Monthly emission estimates were given for each c ounty in Maryland for the following pollutants:

• CO: Carbon monoxide (a new species output by BEIS3.12 not previously included in BEIS3.09)

• NO: Nitrogen oxide

• ALD2: Aldehyde group from CB-IV chemical mechanism

117 BEIS 3.12 can be downloaded from an EPA website at: http://www.epa.gov/asmdnerl/biogen.html247 • ETH: Ethane group from CB- IV chemical mechanism

• FORM: Formaldehyde group from CB-IV chemical mechanism

• ISOP: Isoprene

• NR: Nonreactive VOC

• OLE: Olefin group from CB-IV chemical mechanism

• PAR: Parafin group from CB- IV chemical mechanism

• XYL: Xylene group from CB-IV chemical mechanism

• TOL: Toluene group from CB- IV chemical mechanism

• Total VOC: The sum of ALD2, ETH, FORM , ISOP, NR, OLE, PAR, XYL, and TOL

• TERPB: Terpenes (Note that the same ma ss accounted for by TERPB is also included in VOC

The daily emissions were calculated by summing th e monthly emissions from June, July, and August and dividing by the number of days in those three months (92).248 

## 8.0 QUALITY ASSURANCE PROCEDURES

Quality assurance activities are distinguished from QC activities in that they provide a more objective assessment of data quality. The QA checks (except th e sensitivity analysis a nd range checks) will be performed by staff not involved in the inventory calcula tions. Several quality assurance checks will be employed to address the data quality objectives: reality/peer review checks, sample calculations, sensitivity analysis, and range ch ecks. Details on each check are provided below. The product of the quality checking process will be a completed summary of items checked, summary of results, and recommended follow-up action. At the completion of the process, the inve ntory will be evaluated according to the data quality objectives (see Chapter IV).

8.1 REALITY CHECK/PEER REVIEW CHECK

Independent review by a knowledgeable expert

Ensure data, assumptions, a nd procedures are reasonable

Accuracy, completeness, comparability, representativeness

Reasonableness of methods, assumptions, and emissions estimates will be assessed. This will be accomplished by 1) comparing data sources used in the final inventory to those specified in the Inventory Preparation Plan, 2) reliance on review er expertise, and 3) comparison of emissions estimates to other inventory effo rts, particularly the 1990 base year inventory and the 1999 PEI.

Limitations:
None

8.2 SAMPLE CALCULATIONS

Verification of values by replicating calculations

Definition:

Benefit:

Objective(s) Addressed:

Check(s):

Definition:249 Ensure calculations are done correctly

Accuracy

Emissions calculations will be dupli cated to check the accuracy of the arithmetic and, therefore, the resulting emissions estimate. Priority will be give n to those categories identified as the largest PM 10 and CO contributors.

Estimates calculated using computer models su ch as MOBILE6.2 are checked using simplified assumptions to arrive at a ”ballpark” value to us e as a comparison to the ac tual calculated value.

8.3 SENSITIVITY ANALYSIS

Systematic study of how changes in parameters affect data

Identify the parameters that ha ve the greatest effect on data

Generally addresses all objectives

A sensitivity analysis in the form of source category emissions rankings by pollutant will be performed. The ranking will help determine where efforts should be concentrated.

None

8.4 STANDARD RANGE CHECKS

Standard range checks address the data quality objective of comparability

Benefit:

Objective(s) Addressed:

Check(s):

Limitations:

Definition

Benefit

Objective(s) Addressed

Check(s)

Limitations

Definition250 Identify the source categories that have the greates t change in emission levels from previous emission estimates.

Generally addresses all objectives

The 2002 base year inventory will be compared to the most recent inventory (base year 1990, 1999 PEI, 2002 NEI). Any discrepancies (data outliers) greater than 20% involving sources that made up greater than 5% of the 1990 PM 10 , 1999 CO, or 2002 inventories will be corrected or justified.

The projection inventories will be compared to the 2002 base year inventory. Any discrepancies (data outliers) between the base ye ar and a given projection year great er than the population increase percentage plus 10% and involving sources that made up greater than 5% of the 2002 or projection year daily inventories will be investigated and either corrected (see Corrective Action Plan below) or justified. The justification will include whether there was a change in methodology (e.g., different emission factor, allocation method, activity data) or if there is a real an ticipation of emissions increasing or decreasing (e.g., decreases in the onroad sector due to fleet turnover).

None.

8.5 CORRECTIVE ACTION PLAN

Corrective and follow-up actions identified during th e quality checking process will be noted and referred to the appropriate staff. Both the correcti ve actions identified and re sults of actions taken in response will be documented.

8.6 QUALITY ASSURANCE FINAL REPORT

The final inventory report will include discussion s on inventory quality considerations for each major source category. It will summarize the results of the quality checking pro cedures and provide an evaluation of the inventory according to the data quality objectives. The report will include an assessment of the limitations of the inventory data.

Benefit

Objective(s) Addressed

Check(s)

Limitations251 

## 9.0 RESPONSIBILITY

The inventory process will be a cooperative effort among MDE-ARMA Air Quality Policy and Planning Program, MDE-ARMA Air Quality Co mpliance Program, MDE-ARMA Air Quality Permits Program, MDE-ARMA Mob ile Source Control Program, Ba ltimore Metropolitan Council, Maryland State Highway Administration, and Metropolitan Washington Council of Governments Environmental Programs. A brief list of inventory responsibilities follows:

MDE-ARMA Air Quality Compliance Program (Compliance) will inventory calendar year 2002 actual emissions and provide allowable emissions from point sources under their jurisdiction. Compliance will perform a review of these data. Compliance will also provide information on local control programs that are expected to impact the base year or projection year inventories.

MDE-ARMA Mobile Source Control Program (MSCP) will provide estimates of actual 2002 and projected 2010 and 2015 emission estimates for onroad sources. MSCP will provide 2002, 2010, and 2015 VMT for both paved and unpaved roads in the NAAs . Data will be supplied to MSCP from the Baltimore Metropolitan Council (BMC), Maryla nd State Highway Administration (SHA), and Metropolitan Washington Counc il of Governments (MWCOG).

Metropolitan Washington Council of Governments will provide estimates of actual 2002 and projected 2010 and 2015 emission estimates for onr oad sources for the Maryland Counties within their jurisdiction. MWCOG will provide 2002, 2010, and 2015 VMT for both paved and unpaved roads in the NAAs.

MDE-ARMA Air Quality Policy and Planning (Planning) will inventory area and nonroad mobile sources. Planning will review the point source inventory estimates provided by Compliance. Planning will project area/nonroad mobile source emission s to 2010 and 2015. Planning will perform the final QA review of the inventories. Finally, Pla nning will prepare the inventory documentation.

MSCP, Compliance, and Planning will review all inventory products.252 9.1 Updates (Please Delete)

• New Title Page to Reflect PM2.5 Emission Inventory 10-22-2007

• Add NH3 for NR Model description 10-22-2007

• Add NH3 as Pollutant in NR Mode l Methodology Description 10-22-2007

• Added Chapters 7 & 8 10-23-2007

• Added Introduction sp ecific to PM SIP 10-24-2007

# Attachment B4

Airport Emissions (Metropolitan Washington Airports Authority)

## A IR 

## P OLLUTION 

## E MISSION 

## I NVENTORIES FOR


## W ASHINGTON 

## D ULLES 

## I NTERNATIONAL 

## A IRPORT

AND


## R ONALD 

## R EAGAN 

## W ASHINGTON 

## N ATIONAL 

## A IRPORT

FOR 

## C

ALENDAR 

## Y EARS 

## 2002, 2008, AND 

## 2009

Prepared for: Metropolitan Washington Airports Authority Washington, DC

Prepared by: URS Corporation Tampa, FL

MARCH 2006Air Pollutant Emission Inventories for W ashington Dulles International Airport and Ronald Reagan Washington National Airport for Calendar Years 2002, 2008, and 2009

Introduction
The Metropolitan Washington Council of Governments (MWCOG) is finalizing emissions inventories for their 8-Hour Ozone SIP and has requested the Metr opolitan Washington Airports Authority (MWAA) to provide aircraft operations, GSE, and motor vehicle da ta and pollutant emissions for calendar years 2002, 2008, and 2009 for Washington Dulles International Airport (IAD) and Ronald Reagan Washington National Airport (DCA). In addition, emissions from both IAD and DCA for each of the analysis years (2002, 2008, and 2009) for an “ozone season day” (whi ch requires using site specific “ozone season” mixing height and temperature data) were also requested.

Historical data and available forecasts of future year ac tivity levels at each airport were used as the basis for the emissions inventory calculations for 2002 and 2009. Emissions for 2008 were estimated by adjusting the activity levels calculated for 2009 by the difference in forecasted aircraft operations or enplanements for each airport between 2009 and 2008.

Operational Emissions Inventories
Emissions inventories are quantities of air pollutant s emitted over a given time period, and provide information about pollutant contributions from various sources. Annual and Ozone Season Day emissions of carbon monoxide (CO), volatile org anic compounds (VOC), nitrogen oxides (NOx), particulate matter of 10 microns and smaller (PM10), particulate matter of 2.5 microns and smaller (PM2.5), and sulfur dioxide (SO 2 ) in tons per year and tons per day were estimated separately for IAD

and DCA.

The airport-related sources of emissions that were included in these invent ories are aircraft, Ground Support Equipment (GSE), aircraft Auxiliary Power Unit s (APU), and onsite motor vehicles on roadways and in parking facilities. No stationary sources were included in these analyses. For the IAD analysis only, a subset of GSE emissions has been calculated for the Mobile Lounges, which are vehicles used
primarily as shuttles between the Main Terminal and the midfield concourse, and between the Main Terminal and aircraft parked on hardstands. Onsite motor vehicles include all traffic on major roads on airport property. Emissions from motor vehicles idling at the curbsides are not included in this assessment. Emissions from Parking Facilities incl ude emissions from vehicles idling and moving around inside the parking facilities.

For these analyses, emissions were calculated usi ng the latest version of the FAA approved program

EDMS 1 (currently Version 4.4) using standard EDMS parameters and databases except where airportspecific inputs were available and more appropriate as described below.

1 Emissions and Dispersion Modeling System (EDMS) . U.S. Department of Transportation, Federal Aviation Administration, Office

of Environment and Energy. Washington, DC. Version 4.4. November 2005.

1Aircraft

Historical data and available forecasts of future year aircraft operations at each airport were used as the basis for the emissions inventory calculations. Th e annual operations used in the analyses for each
airport are provided in Table 1 below. Aircraft operations and fleet mix data for the IAD 2002 analysis were taken from the IAD Final Environmental Impact Statement (FEIS) 2 , and data for the 2009 analysis were derived by taking the 2010 data from the IAD FEIS and adjusted for the difference in operations between 2010 and 2009. Aircraft operations and fleet mix data for the DCA 2002 analysis were taken from an emissions inventory prepared by Metropo litan Washington Airports Authority (MWAA) 3 , and data for the 2009 analysis were derived from the Draft Part 150 Study 4 prepared for DCA.

TABLE 1 ANNUAL OPERATIONS, ENPLAN EMENTS, AND TAXI TIMES

2002 2008 2009

Washington Dulles Intern ational Airport (IAD): Annual Operations 372,636 496,053 530,895 Annual Enplanements 8,515, 498 12,932,987 14,089,988 Annual Average Aircraft Taxi Time (min.) 20.36 22.02 1 22.02

Ronald Reagan Washington National Airport (DCA): Annual Operations 215,691 283,482 284,196 Annual Enplanements 6,440, 801 8,336,738 8,447,535 Annual Average Aircraft Taxi Time (min.) 16.93 18.12 1 18.12

1 The taxi time used for 2008 was assumed to be equal to the 2009 taxi time. Sources: URS Corporation, 2004 and 2006.

Aircraft/engine combinations and individual aircra ft engine emission factors were obtained from the EDMS database. The activities of an aircraft in its airborne and ground-based operational modes are referred to as a Landing and Takeoff (LTO) cycle. An LTO cycle equals two operations (i.e., one landing and one takeoff). LTO data are modeled in EDMS.

EDMS automatically calculates the times-in-mode for the approach/landing, climbout and takeoff modes for each aircraft classification type (e.g., heavy jet, turbo prop, etc.). For the IAD and DCA analyses in
2002, taxi/idle times were taken from the FAA’s ASPM data base 5 . For the IAD analysis for 2009, the

taxi/idle times were derived from the SIMMOD airfie ld operational analysis combined with measurements of aircraft taxiing distances at the air port under the alternative improvement plans 6 and adjusted to account for having the crosswind taxiways in place. For the 2009 analysis at DCA, data from the FAA’s

ASPM data base for 2004 were used and assum ed to remain unchanged between 2004 and 2009.

2 Final Environmental Impact Statement for New Runways, Te rminal Facilities and Related Facilities at Washington Dulles

International Airport, Department of Transportation, Federal Avia tion Administration, Washington Ai rports District Office, Dull es, VA. August 2005.

3 Supporting Data – 2002 Emissions Inv entory, Aircraft and Ground Support Equi pment, Ronald Reagan Washington National

Airport, Metropolitan Washington Airports Author ity, Office of Engineering, May 2003.

4 Ronald Reagan Washington National Airport, FAR Part 150 Noise Exposure Maps and Noise Compatibility Program , Metropolitan

Washington Council of Governments, September 2004.

5 FAA’s ASPM data based website www.apo.data.faa.gov/faamatsall.htm

. 6 Capacity Review and Alternatives for the Fourth and Fifth Runw ays at Washington Dulles International Airport – Final Report. HNTB, February 2002.

2Consistent with FAA guidelines 7 , it was also assumed that aircraft emissions above the atmospheric mixing height would have no ground-level effect and were not included in the inventory. See the table of Climatological Modeling Parameters in the discussion of the Ozone Season analysis below for the mixing heights and temperatures used in the analyses.

Ground Support Equipment

GSE used to service aircraft includes baggage and pushback tugs; baggage and cargo loaders; fuel trucks and other service vehicles. Aircraft Auxiliary Power Units (APU) are onboard, turbine powered engines used primarily to provide electricity and air conditioning to an aircraft when the main engines are shut down. For the IAD analysis, the GSE and APU fl eet, fuel types and operating times were derived from in-the-field surveys performed at the airport in February 2004 8 . Wherever necessary, these data were supplemented with information contained in t he EDMS database of GSE and APU, which is also the

source of the GSE emission factors. For the DCA analysis, GSE default equipment and time-in-mode data available in EDMS were used, except that all gasoline powered equipment was assigned to be diesel powered. In both analyses, EDMS default a ssignments for APUs were used and the time-in-mode was set to 7 minutes as recommended by FAA when all or most of an airport’s gates have electrical
connections and pre-conditioned air 9 . Also in both analyses, EDMS default assignments for deicer trucks

were included with the time-in-mode set to 1.5 10 minutes as was used in the IAD FEIS. While the use of deicer trucks during the ozone season (see below) does not occur, the very small error introduced by including this source in ozone season estimates is negligible: less than 0.01 tons per day of VOC and

NOx.

Mobile Lounges

For the IAD analysis only, a subset of GSE emissions has been calculated separately for the Mobile Lounges, which are vehicles used primarily as shu ttles between the Main Terminal and the midfield concourse. Emission rates and activity levels fo r 2002 for Mobile Lounges were obtained from the IAD FEIS, which was based on a 1999 Emission Inventory prepared by MWAA, in April 2001. For this analysis, it was assumed that the use of Mobile Loun ges at IAD for 2008 and 2009 would be the same as in 2002 because the Mobile Lounges will not be repl aced by the Automated People Mover that will

connect the terminals until the latter half of 2009. Th erefore, Mobile Lounge emissions are held constant from 2002 through 2009.

Motor Vehicles

For this analysis, onsite motor vehicles (i.e., cars , vans, limousines, buses, trucks, etc.) are the motor vehicles that are operating on the airport’s primary in ternal roadway network. These motor vehicles are primarily associated with airport patron, employee, and cargo truck trips operating within the airport’s borders. Traffic volumes on the roadways for the IAD analysis were based on the Project Definition

Document - North Area Roads 11 and roadway travel distances were derived from scaled drawings of the

7 Air Quality Procedures for Civilian Airports & Air Force Bases, AEE-120. U.S. Department of Transportation, Federal Aviation

Administration, Office of Environment and Energy. Wash ington, DC. Report Number FAA-AEE-97-03. April 1997.

8 Appendix G of the Final Environmental Impact Statement for New Runways, Terminal Facilities and Related Facilities at

Washington Dulles International Airport, Department of Transpor tation, Federal Aviation Administration, Washington airports District Office, Dulles, VA. August 2005.

9 Personal communication from J. Draper, FAA, to J. Pehrson, Camp Dresser & McKee Inc., November 4, 1998.

10 Personal communication from T. Thrasher, CSSI, Inc ., to D. Wilson, URS Corporation, February 25, 2004.

11 Project Definition Document – North Area Roads , HNTB Corporation, January 2001.

3IAD Airport Layout Plan (ALP). Traffic volumes on th e roadways for the DCA analysis were derived from traffic count data for 2003 supplied by HNTB 12 and adjusted based on enplanements. Roadway travel

distances were derived from scal ed drawings of the DCA ALP.

The motor vehicle engine emission factors were deri ved from the EPA mobile source emissions model,

MOBILE 6.2 13 . For the IAD analysis, Fairfax County-specific motor vehicle operating characteristics (i.e., fleet mix, emission control programs, operating temper atures, etc.) were obtained from the Metropolitan Washington Council of Governments (MWCOG) 14 for use in the IAD FEIS. For the DCA analysis, Arlington County-specific motor vehicle operating characteristics (i.e., fleet mix, emission control programs, operating temperatures, etc.) were obtai ned from the MWCOG SIP documents available on the

MWCOG website.

Parking Facilities

Emissions from motor vehicles accessing airport parking facilities were also quantified. Volumes of vehicles entering and exiting the parking facilities for the IAD analysis for 2002 were taken directly from
the IAD FEIS, and vehicle volumes for the IAD anal ysis for 2009 were derived from the 2010 vehicle volumes in the IAD FEIS and adjusted for the difference in aircraft enplanements between 2010 and

2009.

Volumes of vehicles entering and exiting the public parking facilities for the DCA analysis for 2002 were derived from vehicle volume data collected by MWAA in 2004 15 and adjusted for the difference in aircraft enplanements between 2004 and 2002. Vehicle volumes for the public parking facilities for 2009 were derived from vehicle volumes collected at DCA in 2004 by MWAA and adjusted for the difference in aircraft enplanements between 2004 and 2009.

Vehicle volumes for the DCA rental car park ing facility for 2002 were provided by MWAA 16 ; vehicle volumes for the rental car parking facility in 2009 were derived from the rental car volumes for 2002 and adjusted for the difference in aircraft enplanement s between 2002 and 2009. Vehicle volumes for the employee parking facilities for 2002 were developed fr om data collected at DCA in 2002 17 ; employee

vehicle volumes for 2009 were derived from vehicl e volumes collected at DCA in 2002 and adjusted for the difference in aircraft enplanements between 2002 and 2009.

Ozone Season/Ozone Day Emissions

Following FAA guidelines 7 , the operational emissions inventories for IAD and DCA were initially prepared for annual average conditions. However, the SI P for the Washington DC-MD-VA area is based on the management and control of Ozone precursors (i.e., NO x and VOCs), principally during the peak “Ozone production season” (i.e., May 1st to September 15th ). Because some climatic factors (i.e., ambient temperature and atmospheric mixing height) have an effect on aircraft and motor vehicle performance

12 Personal communication from G. Ceballos, HNTB Corporat ion, to A. Goldman, URS Corporation, December 2005.

13 Approved final version of MOBILE6.2 com puter program released by memorandum Policy Guidance on the Use of MOBILE6.2

and the December 2003 AP-42 Method for Re-entrained Road Dust for SIP Development and Transportation Conformity. Margo Tsirigotis Oge, Director, Office of Transportation and Air Quality, and Steve Page, Di rector, Office of Air Quality Planning an d Standards. U.S. Environmental Protection Agency. Washington, DC. February 24, 2004.

14 Personal communication from S. Kumar, MWCOG, to D. Wilson, URS Corporation, April, 2003.

15 Personal communication from C. Baummer, MWAA, to A. Goldman, URS Corporation, December 12, 2005.

16 Personal communication from C. Baummer, MWAA, to D. Wilson, URS Corporation, February 27, 2006.

17 Ronald Reagan Washington National Airport, Landside Planning Study, Facilities Planning Study of Public/E mployee Parking and Rental Car Facilities , HNTB Corporation, December 2004.

4characteristics, the operational em ission inventory results were recalculated to reflect these “Ozone Season” conditions. “Ozone Day” emissions are deri ved by using the “Ozone Season” mixing height and “Ozone Season” temperature to calculate the “Ozone Year” emissions and then dividing by 365.

This adjustment to the emissions inventory was accomp lished by factoring in the effects of the lower atmospheric mixing height and higher ambient tem peratures that are characteristic of the O 3 season in the region. These parameters, shown in Table 2 , are based on climatological data for the Sterling, Virginia area. The methodology used to determine the IAD mixing heights is provided in the IAD FEIS in Appendix G-3. For DCA, the mixing height calculated for IAD was increased by the difference in elevation between the two airports (+280 feet). Temperature data used in the MOBILE6.2 calculations

was obtained from the MWCOG MOBILE6.2 input files.

TABLE 2 CLIMATOLOGICAL MODELING PARAMETERS

Conditions Mixing Height (feet AGL) Minimum Ambient Temperature (° F) Maximum Ambient Temperature (° F)

Washington Dulles Intern ational Airport (IAD): Annual Average Daily 1,608 42.6 65.6 Ozone Season 1,412 68.5 95.0

Ronald Reagan Washington National Airport (DCA): Annual Average Daily 1,888 48.6 66.4 Ozone Season 1,692 68.5 95.0
Sources: NCDC; URS Co rporation, 2004 and 2006.

In both the Annual Average calculation and the Ozone Season calculation, the mixing height values are lower than the “default” 3,000-foot value available in EDMS. FAA guidelines 7 recommend using “real
world” data whenever it is available, as in this ca se. Within the EDMS model, these changes in mixing height and temperature have an effect on aircraft emissions in the approach and climb out modes; and within MOBILE6.2, changes in temperatures have an effect on the emissions from motor vehicles.

Emissions Inventories

The emissions inventories for IAD and DCA for 20 02, 2009, and 2008 are provided in the tables below. Aircraft emissions for 2008 were estimated by adjusti ng the aircraft emissions calculated for 2009 by the difference in forecasted aircraft operations fo r each airport between 2009 and 2008. GSE and APU emissions for 2008 were estimated by adjusting the GSE emissions calculated for 2009 by the difference in forecasted aircraft operations at each airpor t between 2009 and 2008. Emissions for Mobile Lounges at IAD for 2008 were kept the same as the data used in the IAD FEIS for the 2002 Conditions. Emissions from Onsite Motor Vehicles for 2008 were estimated by adjusting the Onsite Motor Vehicle emissions calculated for 2009 by the difference in forecasted aircraft enplanements at each airport between 2009 and 2008, and further adjusted to account for the differen ce in the motor vehicle emission factors for each pollutant for the 30 mph speed category between 2009 and 2008.

The annual air pollutant emissions inventories fo r IAD for 2002, 2009, and 2008 are presented in Tables
3, 5, and 7 , respectively; and the Ozone Day emissions for IAD are presented in Tables 4, 6, and 8 , for 2002, 2009, and 2008, respectively. The annual air pollutant emissions inventories for DCA for 2002,

52009, and 2008 are provided in Tables 9, 11, and 13 , respectively; and the Ozone Day emissions for DCA are provided in Tables 10, 12, and 14 , for 2002, 2009, and 2008, respectively.

6TABLE 3 WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2002 1

Pollutant Source CO VOCs NO x PM 2.5 PM 10 SO 2 Annual Emissions in Tons Per Year (tpy)

Aircraft 2 1,205.3 257.1 864.3 23.3 3 23.3 3 71.9 Ground Support Equipment (GSE) 4 3,453.4 134.4 208.4 8.5 8.9 19.9 Auxiliary Power Units (APU) 4 59.6 4.3 45.8 <0.1 <0.1 6.3 Mobile Lounges 5 3.6 6.1 125.1 2.7 2.7 6.7 Onsite Motor Vehicles 6 411.9 30.2 103.4 1.8 2.8 2.0 Parking Facilities 7 70.5 10.3 13.9 0.2 0.3 0.2 Total Annual Emissions (tpy) 5,204.3 442.4 1,360. 9 36.5 38.0 107.0 Daily 8 Emissions in Tons Per Day (tpd)

Aircraft 3.30 0.70 2.37 0.06 0.06 0.20 Ground Support Equipment (GSE) 9.46 0.37 0.57 0.02 0.02 0.05 Auxiliary Power Units (APU) 0.16 0.01 0.13 <0.01 <0.01 0.02 Mobile Lounges 0.01 0.02 0.34 0.01 0.01 0.02 Onsite Motor Vehicles 1.13 0.08 0.28 0.01 0.01 0.01 Parking Facilities 0.19 0.03 0.04 <0.01 <0.01 <0.01 Total Daily Emissions (tpd) 14.25 1.21 3.73 0.10 0.10 0.30

1 Annual 2002 emissions were computed using EDMS Version 4.4 and the latest versio n of MOBILE6.2, using the activity levels and data used in the IAD FEIS for 2002.

2 A total of 372,636 annual aircraft operations were modeled for 2002. An aircraft taxi time of 20.36 minutes taken from the FAA’s ASPM database for 2002 fo r IAD was used in the inventory.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 13.3 tpy from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE and APU emissions were determined based on onsit e data from surveys completed at IAD in February 2004.

5 Emissions for Mobile Lounges were kept the same as the data used in the IAD FEIS for the 2002 conditions. These calculations are not incl uded in the EDMS data files.

6 Onsite motor vehicles include all roads located on the ai rport property, except for the portions of Route 28 (Sully Road), Route 606 (Old Ox Road), and the Dulles Gree nway located on Airport property, and do NOT include emissions from vehicles idling at curbside or parking facility emissions. MOBILE6.2 emission factors were determined from files obtained from MWCOG.

7 Parking facilities include vehicles parking in the following parking facilities: Daily Garage 1, Daily Garage 2, Hourly Lot, Valet Lot, Blue Economy Lot (in 2002 only), Gold Economy Lot, Purple Economy Lot, Employee Lot 1, Employee Lot 2, and the Rental Car Lot. Vehicle volumes for 2002 were taken from the IAD FEIS.

8 Daily Emissions are the Annual Emissions divided by 365 and are in units of tons per day (tpd).

Source: EDMS Version 4.4 (URS Corporation, 2006); IAD FEIS, 2005.

7TABLE 4 WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) ESTIMATED OZONE DAY 1 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2002 IN TONS PER DAY (TPD)

Pollutant (tpd)
Source CO VOCs NO x PM 2.5 PM 10 SO 2 Aircraft 2 3.28 0.70 2.24 0.06 3 0.06 3 0.19 Ground Support Equipment (GSE) 4 9.46 0.37 0.57 0.02 0.02 0.05 Auxiliary Power Units (APU) 4 0.16 0.01 0.13 <0.01 <0.01 0.02 Mobile Lounges 5 0.01 0.02 0.34 0.01 0.01 0.02 Onsite Motor Vehicles 6 1.31 0.09 0.28 <0.01 0.01 0.01 Parking Facilities 7 0.19 0.03 0.04 <0.01 <0.01 <0.01 Total Ozone Day Emissions 14.41 1.22 3.60 0.09 0.10 0.29

1 “Ozone Day” emissions are derived by using t he “Ozone Season” mixing height and “Ozone Season” temperature to calculate the “Ozone Y ear” emissions and then dividing by 365.

2 A total of 372,636 annual aircraft operations were modeled for 2002. An aircraft taxi time of 20.36 minutes taken from the FAA’s ASPM database for 2002 fo r IAD was used in the inventory.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 0.04 t pd from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE and APU emissions were determined based on onsit e data from surveys completed at IAD in February 2004.

5 Emissions for Mobile Lounges were kept the same as the data used in the IAD FEIS for the 2002 conditions. These calculations are not incl uded in the EDMS data files.

6 Onsite motor vehicles include all roads located on the ai rport property, except for the portions of Route 28 (Sully Road), Route 606 (Old Ox Road), and the Dulles Gree nway located on Airport property, and do NOT include emissions from vehicles idling at curbside or parking facility emissions. MOBILE6.2 emission factors were determined from files obtained from MWCOG.

7 Parking facilities include vehicles parking in the following parking facilities: Daily Garage 1, Daily Garage 2, Hourly Lot, Valet Lot, Blue Economy Lot (in 2002 only), Gold Economy Lot, Purple Economy Lot, Employee Lot 1, Employee Lot 2, and the Rental Car Lot. Vehicle volumes for 2002 were taken from the IAD FEIS.

Source: EDMS, Version 4.4 (URS Corporation, 2006); IAD FEIS, 2005).

8TABLE 5 WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2009 1

Pollutant Source CO VOCs NO x PM 2.5 PM 10 SO 2 Annual Emissions in Tons Per Year (tpy)

Aircraft 2 2,109.8 410.7 1,471.2 26.8 3 26.8 3 125.0 Ground Support Equipment (GSE) 4 4,643.3 178.3 217.6 13.4 13.9 27.5 Auxiliary Power Units (APU) 4 72.1 5.8 91.6 <0.01 <0.01 12.3 Mobile Lounges 5 3.6 6.1 125.1 2.7 2.7 6.7 Onsite Motor Vehicles 6 332.9 26.1 66.7 1.6 2.8 0.7 Parking Facilities 7 63.4 8.9 11.1 0.2 0.3 0.1 Total Annual Emissions (tpy) 7,225.1 635.9 1,983. 3 44.7 46.5 172.3 Daily 8 Emissions in Tons Per Day (tpd)

Aircraft 5.78 1.13 4.03 0.07 0.07 0.34 Ground Support Equipment (GSE) 12.72 0.49 0.60 0.04 0.04 0.08 Auxiliary Power Units (APU) 0.20 0.02 0.25 <0.01 <0.01 0.03 Mobile Lounges 0.01 0.02 0.34 0.01 0.01 0.02 Onsite Motor Vehicles 0.91 0.07 0.18 <0.01 0.01 <0.01 Parking Facilities 0.17 0.02 0.03 <0.01 <0.01 <0.01 Total Daily Emissions (tpd) 19.79 1.75 5.43 0.12 0.13 0.47

1 Annual 2009 emissions were computed using EDMS Versi on 4.4 and the latest vers ion of MOBILE6.2, using forecasted activity levels for IAD for 2009.

2 A total of 530,895 annual aircraft operations were modeled for 2009. An estimated aircraft taxi time of 22.02 minutes for 2009 was used in the calculations. This value was derived from the SIMMOD model output for 2010 used in the IAD FEIS (HNTB, 2002) and adjusted to a ccount for having the crosswind taxiways in place.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 9.7 tpy from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE and APU emissions were determined based on onsit e data from surveys completed at IAD in February
2004.

5 Emissions for Mobile Lounges were kept the same as the data used in the IAD FEIS for the 2002 conditions. These calculations are not incl uded in the EDMS data files.

6 Onsite motor vehicles include all roads located on the ai rport property, except for the portions of Route 28 (Sully Road), Route 606 (Old Ox Road), and the Dulles Gree nway located on Airport property, and do NOT include emissions from vehicles idling at curbside or parking fa cility emissions. MOBILE6.2 emission factors for 2009 were derived from files obtained from MWCOG accounti ng for the appropriate calendar year. Vehicle volumes for 2009 were derived from the vehicle volumes for 2010 used in the IAD FEIS and adjusted for the difference in aircraft enplanements between 2010 and 2009.

7 Parking facilities include vehicles parking in the following parking facilities: Daily Garage 1, Daily Garage 2, Hourly Lot, Valet Lot, Gold Economy Lot, Purple Economy Lo t, Employee Lot 1, Employee Lot 2, the Future Lot, the Rental Car Bus Lot, and the Rental Car Lot. Vehicle volumes for 2009 were derived from the 2010 volumes used in the IAD FEIS and adjusted for the differenc e in aircraft enplanements between 2010 and 2009.

8 Daily Emissions are the Annual Emissions divided by 365 and are in units of tons per day (tpd).

Source: EDMS, Version 4.4 (URS Corporation, 2006).

9TABLE 6 WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) ESTIMATED OZONE DAY 1 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2009 IN TONS PER DAY (TPD)

Pollutant (tpd)
Source CO VOCs NO x PM 2.5 PM 10 SO 2 Aircraft 2 5.75 1.12 3.81 0.07 3 0.07 3 0.33 Ground Support Equipment (GSE) 4 12.72 0.48 0.60 0.04 0.04 0.08 Auxiliary Power Units (APU) 4 0.20 0.02 0.25 <0.01 <0.01 0.03 Mobile Lounges 5 0.01 0.02 0.34 0.01 0.01 0.02 Onsite Motor Vehicles 6 0.88 0.08 0.18 <0.01 0.01 <0.01 Parking Facilities 7 0.16 0.02 0.03 <0.01 <0.01 <0.01 Total Ozone Day Emissions 19.72 1.74 5.21 0.12 0.13 0.46

1 “Ozone Day” emissions are derived by using t he “Ozone Season” mixing height and “Ozone Season” temperature to calculate the “Ozone Y ear” emissions and then dividing by 365.

2 A total of 530,895 annual aircraft operations were modeled for 2009. An estimated aircraft taxi time of 22.02 minutes for 2009 was used in the calculations.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 0.03 t pd from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE and APU emissions were determined based on onsit e data from surveys completed at IAD in February 2004.

5 Emissions for Mobile Lounges were kept the same as t he data used in the IAD FEIS for the 2002 Conditions. These calculations are not incl uded in the EDMS data files.

6 Onsite motor vehicles include all roads located on the ai rport property, except for the portions of Route 28 (Sully Road), Route 606 (Old Ox Road), and the Dulles Gree nway located on Airport property, and do NOT include emissions from vehicles idling at curbside or parking fa cility emissions. MOBILE6.2 emission factors for 2009 were derived from files ob tained from MWCOG. Vehicle volumes fo r 2009 were derived from the vehicle volumes for 2010 used in the IAD FEIS and adjusted fo r the difference in aircraft enplanements between 2010 and 2009.

7 Parking facilities include vehicles parking in the following parking facilities: Daily Garage 1, Daily Garage 2, Hourly Lot, Valet Lot, Gold Economy Lot, Purple Economy Lo t, Employee Lot 1, Employee Lot 2, the Future Lot, the Rental Car Bus Lot, and the Rental Car Lot. Vehicle volumes for 2009 were derived from the 2010 volumes used in the IAD FEIS and adjusted for the differenc e in aircraft enplanements between 2010 and 2009.

Source: EDMS, Version 4.4 (URS Corporation, 2006).

10TABLE 7 WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008

Pollutant Source CO VOCs NO x PM 2.5 PM 10 SO 2 Annual Emissions in Tons Per Year (tpy)

Aircraft 1 1,971.3 383.8 1,374.7 25.1 25.1 116.8 Ground Support Equipment (GSE) 2 4,338.6 166.6 203.3 12.6 13.0 25.7 Auxiliary Power Units (APU) 2 67.3 5.5 85.6 <0.01 <0.01 11.5 Mobile Lounges 3 3.6 6.1 125.1 2.7 2.7 6.7 Onsite Motor Vehicles 4 324.9 26.1 70.3 1.6 2.8 0.6 Parking Facilities 5 61.9 8.9 11.7 0.2 0.3 0.1 Total Annual Emissions (tpy) 6,767.6 597.0 1,870. 7 42.2 43.9 161.4 Daily 8 Emissions in Tons Per Day (tpd)

Aircraft 5.40 1.05 3.77 0.07 0.07 0.32 Ground Support Equipment (GSE) 11.89 0.46 0.56 0.03 0.04 0.07 Auxiliary Power Units (APU) 0.18 0.01 0.23 <0.01 <0.01 0.03 Mobile Lounges 0.01 0.02 0.34 0.01 0.01 0.02 Onsite Motor Vehicles 0.89 0.07 0.19 <0.01 0.01 <0.01 Parking Facilities 0.17 0.02 0.03 <0.01 <0.01 <0.01 Total Daily Emissions (tpd) 18.54 1.63 5.12 0.11 0.13 0.44

1 Aircraft emissions for 2008 were es timated by adjusting the aircraft emissions calculated for 2009 by the difference in forecasted aircraft operations for IAD between 2009 and 2008. A total of 496,053 annual aircraft operations were assessed in 2008.

2 GSE and APU emissions for 2008 were estimated by adjust ing the GSE emissions calculated for 2009 by the difference in forecasted aircraft operations at IAD between 2009 and 2008.

3 Emissions for Mobile Lounges for 2008 were kept the same as the data used in the IAD FEIS for the 2002 conditions.

4 Emissions from Onsite Motor Vehicles for 2008 were es timated by adjusting the Onsite Motor Vehicle emissions calculated for 2009 by the difference in forecasted aircraft enplanements at IAD between 2009 and 2008, and the difference in the “All Vehicles” ca tegory of MOBILE6.2 emi ssion factors for each pollutant between 2009 and 2008.

5 Emissions from Parking Facilities for 2008 were estimated by adjusting the Parking Facilities emissions calculated for 2009 by the difference in forecasted aircraft enplanements at IAD between 2009 and 2008, and the difference in the “All Vehicles” ca tegory of MOBILE6.2 emi ssion factors for each pollutant between 2009 and 2008.

6 Daily Emissions are the Annual Emissions divided by 365 and are in units of tons per day (tpd).

Source: EDMS, Version 4.4 (URS Corporation, 2006).

11TABLE 8 WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) ESTIMATED OZONE DAY 1 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008 IN TONS PER DAY (TPD)

Pollutant (tpd)
Source CO VOCs NO x PM 2.5 PM 10 SO 2 Aircraft 2 5.37 1.05 3.56 0.07 0.07 0.31 Ground Support Equipment (GSE) 3 11.89 0.46 0.56 0.03 0.04 0.07 Auxiliary Power Units (APU) 3 0.18 0.01 0.23 <0.01 <0.01 0.03 Mobile Lounges 4 0.01 0.02 0.34 0.01 0.01 0.02 Onsite Motor Vehicles 5 0.87 0.08 0.18 <0.01 0.01 <0.01 Parking Facilities 6 0.16 0.02 0.03 <0.01 <0.01 <0.01 Total Ozone Day Emissions 18.48 1.64 4.90 0.11 0.13 0.43

1 “Ozone Day” emissions are derived by adjusting the 2009 “Ozone Season” estimated emissions to 2008 conditions and dividing by 365.

2 Aircraft emissions for 2008 were es timated by adjusting the aircraft emissions calculated for 2009 by the difference in forecasted aircraft operations for IAD between 2009 and 2008. A total of 496,053 annual LTO operations were assessed in 2008.

3 GSE and APU emissions for 2008 were estimated by adjust ing the GSE emissions calculated for 2009 by the difference in forecasted aircraft operations at IAD between 2009 and 2008.

4 Emissions for Mobile Lounges for 2008 were kept the same as the data used in the IAD FEIS for the 2002 conditions.

5 Emissions from Onsite Motor Vehicles for 2008 were es timated by adjusting the Onsite Motor Vehicle emissions calculated for 2009 by the difference in forecasted aircraft enplanements at IAD between 2009 and 2008, and the difference in the “All Vehicles” ca tegory of MOBILE6.2 emi ssion factors for each pollutant between 2009 and
2008.
6 Emissions from Parking Facilities for 2008 were estimated by adjusting the Parking Facilities emissions calculated for 2009 by the difference in forecasted aircraft enplanements at IAD between 2009 and 2008, and the difference in the “All Vehicles” ca tegory of MOBILE6.2 emi ssion factors for each pollutant between 2009 and
2008.

Source: EDMS, Version 4.4 (URS Corporation, 2006).

12TABLE 9 RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2002 1

Pollutant Source CO VOCs NO x PM 2.5 PM 10 SO 2 Annual Emissions in Tons Per Year (tpy)

Aircraft 2 512.4 55.8 477.6 9.1 3 9.1 3 45.7 Ground Support Equipment (GSE) 4 123.7 15.5 134.0 10.3 10.6 19.4 Auxiliary Power Units (APU) 4 8.5 0.6 7.3 <0.01 <0.01 1.0 Onsite Motor Vehicles 5 144.2 14.8 36.2 0.8 1.2 0.8 Parking Facilities 6 13.4 2.7 2.0 <0.1 0.1 <0.1 Total Annual Emissions (tpy) 802.2 89.4 657.1 20.2 21.0 66.9 Daily 7 Emissions in Tons Per Day (tpd)

Aircraft 1.40 0.15 1.31 0.02 0.02 0.13 Ground Support Equipment (GSE) 0.34 0.04 0.37 0.03 0.03 0.05 Auxiliary Power Units (APU) 0. 02 <0.01 0.02 <0.01 <0.01 <0.01 Onsite Motor Vehicles 0.40 0.04 0.10 <0.01 <0.01 <0.01 Parking Facilities 0.04 0.01 0.01 <0.01 <0.01 <0.01 Total Daily Emissions (tpd) 2.20 0.24 1.81 0.05 0.05 0.18

1 Annual 2002 emissions were computed using EDMS Versi on 4.4 and the latest vers ion of MOBILE6.2, using activity levels for DCA for 2002.

2 A total of 215,691 annual operations were modeled for 2 002. Aircraft emissions were based on aircraft fleet mix and operations data prepared by MWAA in May 2003 using an aircraft taxi time of 16.93 minutes taken from taken from the FAA’s ASPM database for 20 02 for DCA was used in the inventory.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 3.3 tpy from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE default equipment and time-in-mo de data available in EDMS Version 4.4 was used, except that deicer equipment was added to the GSE equipment list and all gasoline powered equipment was assigned to be diesel powered. For APU equipment, EDMS default assignments were used and the time-in-mode was set to 7 minutes as recommended by FAA when all or mo st of an airport’s gat es are electrified.

5 Onsite motor vehicles incl ude all roads located on the airport, except for the George Washington Memorial Parkway. Onsite Motor Vehicles do NOT include parking facility emissions. MOBILE6.2 emission factors were determined from files obtained from MWCOG. Vehicle vo lumes for 2002 were derived from vehicle volumes collected in 2003 by HNTB and adjusted for the difference in aircraft enplanements between 2003 and 2002.

6 Parking facilities include vehicles parking in the following public parking facilities: Garage A, Daily Lot A2, Garage B/C, Hourly Lot A, and the Economy Lot. Rental cars were located in Garage A; and 24 employee parking lots were consolidated at two locations – the Crew Lot U at the south end of the airport and a hypothetical central location near Garage A. Vehicle volumes for 2002 were derived from vehicle volumes collected at DCA in 2004 by MWAA and adjusted for the difference in aircraft enplanements between 2004 and 2002.

7 Daily Emissions are the Annual Emissions divided by 365 and are in units of tons per day (tpd).

Source: EDMS, Version 4.4 (URS Corporation, 2006).

13TABLE 10 RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) ESTIMATED OZONE DAY 1 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2002 IN TONS PER DAY (TPD)

Pollutant (tpd)
Source CO VOCs NO x PM 2.5 PM 10 SO 2 Aircraft 2 1.39 0.15 1.25 0.02 3 0.02 3 0.12 Ground Support Equipment (GSE) 4 0.34 0.04 0.37 0.03 0.03 0.05 Auxiliary Power Units (APU) 4 0.02 <0.01 0.02 <0.01 <0.01 0.01 Onsite Motor Vehicles 5 0.45 0.04 0.10 <0.01 <0.01 <0.01 Parking Facilities 6 0.04 0.01 0.01 <0.01 <0.01 <0.01 Total Ozone Day Emissions 2.24 0.25 1.75 0.05 0.05 0.18

1 “Ozone Day” emissions are derived by using t he “Ozone Season” mixing height and “Ozone Season” temperature to calculate the “Ozone Y ear” emissions and then dividing by 365.

2 A total of 215,691 annual operations were modeled for 2 002. Aircraft emissions were based on aircraft fleet mix and operations data prepared by MWAA in May 2003 using an aircraft taxi time of 16.93 minutes taken from the FAA’s ASPM database for 2002 for DCA was used in the inventory.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 0.01 t pd from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE default equipment and time-in-mo de data available in EDMS Version 4.4 was used, except that deicer equipment was added to the GSE equipment list and all gasoline powered equipment was assigned to be diesel powered. For APU equipment, EDMS default assignments were used and the time-in-mode was set to 7 minutes as recommended by FAA when all or mo st of an airport’s gat es are electrified.

5 Onsite motor vehicles incl ude all roads located on the airport, except for the George Washington Memorial Parkway. Onsite Motor Vehicles do NOT include parking facility emissions. MOBILE6.2 emission factors were determined from files obtained from MWCOG. Vehicle vo lumes for 2002 were derived from vehicle volumes collected in 2003 by HNTB and adjusted for the difference in aircraft enplanements between 2003 and 2002.

6 Parking facilities include vehicles parking in the following public parking facilities: Garage A, Daily Lot A2, Garage B/C, Hourly Lot A, and the Economy Lot. Rental cars were located in Garage A; and 24 employee parking lots were consolidated at two locations – the Crew Lot U at the south end of the airport and a hypothetical central location near Garage A. Vehicle volumes for 2002 were derived from vehicle volumes collected at DCA in 2004 by MWAA and adjusted for the difference in aircraft enplanements between 2004 and 2002.

Source: EDMS, Version 4.4 (URS Corporation, 2006).

14TABLE 11 RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2009 1

Pollutant Source CO VOCs NO x PM 2.5 PM 10 SO 2 Annual Emissions in Tons Per Year (tpy)

Aircraft 2 716.6 80.3 636.3 9.7 3 9.7 3 60.9 Ground Support Equipment (GSE) 4 143.8 13.7 108.4 12.6 12.9 24.3 Auxiliary Power Units (APU) 4 10.2 0.7 8.4 <0.01 <0.01 1.2 Onsite Motor Vehicles 5 100.9 11.3 22.7 0.6 1.0 0.3 Parking Facilities 6 8.8 1.8 1.2 <0.01 0.1 <0.01 Total Annual Emissions (tpy) 980.3 107.8 777.0 22.9 23.7 86.7 Daily 7 Emissions in Tons Per Day (tpd)

Aircraft 1.96 0.22 1.74 0.03 0.03 0.17 Ground Support Equipment (GSE) 0.39 0.04 0.30 0.03 0.04 0.07 Auxiliary Power Units (APU) 0. 03 <0.01 0.02 <0.01 <0.01 <0.01 Onsite Motor Vehicles 0.28 0.03 0.06 <0.01 <0.01 <0.01 Parking Facilities 0.02 <0.01 <0.01 <0.01 <0.01 <0.01 Total Daily Emissions (tpd) 2.68 0.29 2.12 0.06 0.07 0.24

1 Annual 2009 emissions were computed using EDMS Versi on 4.4 and the latest vers ion of MOBILE6.2, using forecasted activity levels for DCA for 2009.

2 A total of 284,196 annual operations were modeled for 2009. An aircraft taxi time of 18.12 minutes was taken from the FAA’s ASPM database for 2004 for DCA and was assumed to be the same in 2009.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 2.5 tpy from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE default equipment and time-in-mo de data available in EDMS Version 4.4 was used, except that deicer equipment was added to the GSE equipment list and all gasoline powered equipment was assigned to be diesel powered. For APU equipment, EDMS default assignments were used and the time-in-mode was set to 7 minutes as recommended by FAA when all or mo st of an airport’s gat es are electrified.

5 Onsite motor vehicles incl ude all roads located on the airport, except for the George Washington Memorial Parkway. Onsite Motor Vehicles do NOT include parking facility emissions. MOBILE6.2 emission factors were determined from files obtained from MWCOG. Vehicle vo lumes for 2009 were derived from vehicle volumes collected in 2003 by HNTB and adjusted for the difference in aircraft enplanements between 2003 and 2009.

6 Parking facilities include vehicles parking in the following public parking facilities: Garage A, Daily Lot A2, Garage B/C, Hourly Lot A, and the Economy Lot. Rental cars were located in Garage A; and 24 employee parking lots were consolidated at two locations – the Crew Lot U at the south end of the airport and a hypothetical central location near Garage A. Vehicle volumes for 2002 were derived from vehicle volumes collected at DCA in 2004 by MWAA and adjusted for the difference in aircraft enplanements between 2004 and 2009.

7 Daily Emissions are the Annual Emissions divided by 365 and are in units of tons per day (tpd).

Source: EDMS, Version 4.4 (URS Corporation, 2006).

15TABLE 12 RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) ESTIMATED OZONE DAY 1 2009 ESTIMATED AIRPORT-RELATED AIR POLLUTANT EMISSIONS IN TONS PER DAY (TPD)

Pollutant (tpd)
Source CO VOCs NO x PM 2.5 PM 10 SO 2 Aircraft 2 1.95 0.22 1.66 0.03 3 0.03 3 0.16 Ground Support Equipment (GSE) 4 0.39 0.04 0.30 0.03 0.04 0.07 Auxiliary Power Units (APU) 4 0.03 <0.01 0.02 <0.01 <0.01 <0.01 Onsite Motor Vehicles 5 0.27 0.03 0.06 <0.01 <0.01 <0.01 Parking Facilities 6 0.02 <0.01 <0.01 <0.01 <0.01 <0.01 Total Ozone Day Emissions 2.66 0.29 2.04 0.06 0.07 0.23

1 “Ozone Day” emissions are derived by using t he “Ozone Season” mixing height and “Ozone Season” temperature to calculate the “Ozone Y ear” emissions and then dividing by 365.

2 A total of 284,196 annual operations were modeled for 2009. An aircraft taxi time of 18.12 minutes was taken from the FAA’s ASPM database for 2004 for DCA and was assumed to be the same in 2009.

3 Results calculated in EDMS 4.4 for jet aircraft using th e FAA’s First Order Approximation (FOA) method. Results also include a contribution of 0.01 t pd from piston and turboprop aircraft calculated separately using the FAA’s FOA method and are not included in the EDMS data files.

4 GSE default equipment and time-in-mo de data available in EDMS Version 4.4 was used, except that deicer equipment was added to the GSE equipment list and all gasoline powered equipment was assigned to be diesel powered. For APU equipment, EDMS default assignments were used and the time-in-mode was set to 7 minutes as recommended by FAA when all or mo st of an airport’s gat es are electrified.

5 Onsite motor vehicles incl ude all roads located on the airport, except for the George Washington Memorial Parkway. Onsite Motor Vehicles do NOT include parking facility emissions. MOBILE6.2 emission factors were determined from files obtained from MWCOG. Vehicle vo lumes for 2009 were derived from vehicle volumes collected in 2003 by HNTB and adjusted for the difference in aircraft enplanements between 2003 and 2009.

6 Parking facilities include vehicles parking in the following public parking facilities: Garage A, Daily Lot A2, Garage B/C, Hourly Lot A, and the Economy Lot. Rental cars were located in Garage A; and 24 employee parking lots were consolidated at two locations – the Crew Lot U at the south end of the airport and a hypothetical central location near Garage A. Vehicle volumes for 2002 were derived from vehicle volumes collected at DCA in 2004 by MWAA and adjusted for the difference in aircraft enplanements between 2004 and 2009.

Source: EDMS, Version 4.4 (URS Corporation, 2006).

16TABLE 13 RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008

Pollutant Source CO VOCs NO x PM 2.5 PM 10 SO 2 Annual Emissions in Tons Per Year (tpy)

Aircraft 1 714.8 80.1 634.7 9.7 9.7 60.8 Ground Support Equipment (GSE) 2 143.4 13.7 108.1 12.5 12.9 24.3 Auxiliary Power Units (APU) 2 10.2 0.7 8.4 <0.01 <0.01 1.2 Onsite Motor Vehicles 3 105.7 12.1 25.4 0.7 1.1 0.3 Parking Facilities 4 9.2 1.9 1.4 <0.01 <0.1 <0.01 Total Annual Emissions (tpy) 983.3 108.5 778.0 22.8 23.7 86.4 Daily 7 Emissions in Tons Per Day (tpd)

Aircraft 1.96 0.22 1.74 0.03 0.03 0.17 Ground Support Equipment (GSE) 0.39 0.04 0.30 0.03 0.04 0.07 Auxiliary Power Units (APU) 0. 03 <0.01 0.02 <0.01 <0.01 <0.01 Onsite Motor Vehicles 0.29 0.03 0.07 <0.01 <0.01 <0.01 Parking Facilities 0.03 0.01 <0.01 <0.01 <0.01 <0.01 Total Daily Emissions (tpd) 2.70 0.30 2.13 0.06 0.07 0.24

1 Aircraft emissions for 2008 were es timated by adjusting the aircraft emissions calculated for 2009 by the difference in forecasted aircraft operations for DCA between 2009 and 2008. A total of 283,482 annual operations were assessed in 2008.

2 Ground Support Equipment and Auxiliary Power Unit emis sions for 2008 were estimated by adjusting the GSE emissions calculated for 2009 by the difference in fore casted aircraft operations at DCA between 2009 and 2008.

3 Emissions from Onsite Motor Vehicles for 2008 were es timated by adjusting the Onsite Motor Vehicle emissions calculated for 2009 by the difference in forecasted aircraft enplanements at DCA between 2009 and 2008, and the difference in the “All Vehicles” category of MOBILE 6.2 emission factors for each pollutant between 2009 and
2008.

4 Emissions from Parking Facilities for 2008 were estimated by adjusting the Parking Facilities emissions calculated for 2009 by the difference in forecasted aircraft enplanements at DCA between 2009 and 2008, and the difference in the “All Vehicles” category of MOBILE 6.2 emission factors for each pollutant between 2009 and
2008.

5 Daily Emissions are the Annual Emissions divided by 365 and are in units of tons per day (tpd).

Source: EDMS, Version 4.4 (URS Corporation, 2006).

17TABLE 14 RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) ESTIMATED OZONE DAY 1 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008 IN TONS PER DAY (TPD)

Pollutant (tpd)
Source CO VOCs NO x PM 2.5 PM 10 SO 2 Aircraft 2 1.95 0.22 1.65 0.03 0.03 0.16 Ground Support Equipment (GSE) 3 0.39 0.04 0.30 0.03 0.04 0.07 Auxiliary Power Units (APU) 3 0.03 <0.01 0.02 <0.01 <0.01 <0.01 Onsite Motor Vehicles 4 0.29 0.03 0.07 <0.01 <0.01 <0.01 Parking Facilities 5 0.02 <0.01 <0.01 <0.01 <0.01 <0.01 Total Ozone Day Emissions 2.68 0.30 2.04 0.06 0.07 0.23

1 “Ozone Day” emissions are derived by adjusting the 2009 “Ozone Season” estimated emissions to 2008 conditions and dividing by 365.

2 Aircraft emissions for 2008 were es timated by adjusting the aircraft emissions calculated for 2009 by the difference in aircraft operations between 2009 and 2008. A total of 283,482 annual operations were assessed in 2008.
3 Ground Support Equipment and Auxiliary Power Unit emis sions for 2008 were estimated by adjusting the GSE emissions calculated for 2009 by the difference in aircraft operations between 2009 and 2008.

4 Emissions from Onsite Motor Vehicles for 2008 were es timated by adjusting the Onsite Motor Vehicle emissions calculated for 2009 by the difference in forecasted aircraft enplanements at DCA between 2009 and 2008, and the difference in the “All Vehicles” category of MOBILE 6.2 emission factors for each pollutant between 2009 and
2008.

5 Emissions from Parking Facilities for 2008 were estimated by adjusting the Parking Facilities emissions calculated for 2009 by the difference in forecasted aircraft enplanements at DCA between 2009 and 2008, and the difference in the “All Vehicles” category of MOBILE 6.2 emission factors for each pollutant between 2009 and
2008.

Source: EDMS, Version 4.4 (URS Corporation, 2006).

18

# Attachment B5

Portable Fuel Container Calculation Methodology for VirginiaFrom: Barnard, Bill [mailto:WRBARNARD@mactec.com] Sent: Tuesday, December 19, 2006 9:27 AM To: Sunil Kumar Cc: Ballou,Thomas; Foster,Thomas; J oan Rohlfs; Pat.Brewer@ncmail.net; gms@alpinegeophysics.com

Subject: RE: Virginia PFC emissions (2002-2011)

Sunil, I'm off on holiday vacation right now but here's (hop efully) some of the answers you seek. We assumed that the 2005 estimates that we used (for 2002) were UNCONTROLLED. We based that on the fact that the EPA report says in Section 3.3 of their report:

"As noted in Section 3.1, EPA estimated the HC i nventory resulting from PFCs for calendar year 2005 to be 315,000 tons per year. A substantial portion of those emissions are due to the fact that many of the PFCs are left open by the users. If the PFCs were redesigned so that neither the vent nor the spout could be left "open" while being transported or stored, the resulting 2005 national inventory would decrease. Additionally, if the PFCs were redesigned to decreas e spillage by 50 percent, the reduction in HC emissions would be much greater.

Six states (California, Delaware, Maine, Maryland, New York, and Pennsylvania) will implement controls on the design of PFCs that will reduce HC emissions. A dditionally, seven other states plus the District of Columbia (Connecticut, Massachusetts, New Jersey , Rhode Island, Texas, Vermont, Virginia, and Washington DC) are also planning to adopt the California PFC programs which are expected to reduce (for the modified containers) spillage (while fueling the equipment) an d permeation (each reduced by 50 percent) and reduce evaporation by designing the PFCs so that they are not easily left open."

Since the total emissions in Appendix Table B-2 = the 315,000 tons per year discussed we ASSUMED that the emissions in that table represented uncontrolled amounts since the discussion in the two paragraphs cited above seems to indicate that levels wo uld be substantially below that if controls were in place. Also the discussion in the second paragraph disc usses the controls in the fu ture (as if they weren't implemented in the 2005 values), we took that as fu rther evidence that the emissions were uncontrolled.

Thus since we used the 2005 estimates as our 2002 equivalent, the controlled levels we estimated for 2009 and 2018 were based on the 2005 estimates in Appendix B-2. We did not specifically estimate a 2005 level but simply assumed that the 2002 levels were equa l to the 2005 estimates given in the EPA report.

Also we did NOT include the two amounts in the Refu eling Equipment (Vapor Displacement and Spillage)
in our estimates since those were alre ady included in our NONROAD estimates.

Our projections were based on 2002 (but the inventory we used was 2005). To get the projected usages we used the 2002, 2009 and 2018 fuel usage by SCCs that had a container entry in the NONROAD05 spillage file both to calculate growth and to determine the county allocation for the State total emissions.

Hope this helps. I'll be back in the office on 1/2/07.

Bill

# Attachment B6

PM2.5, PM10, and SO2 Emissions Calculation Methodology for VirginiaBY 2002 PM2.5, PM10, and SO2 Emissions Ca lculation Methodology for Virginia

VISTAS used a factor (NOx / Pollutant) to calculate em issions for PM2.5, PM10, and SO2 for each area source category on a Source Classification Code (SCC) level. Following table lists the ratios for each pollutant and area source SCC.

SCC Pollutant NOx/ Pollutant Ratio
2102002000 PM10-PRI 0.47
2102002000 PM25-PRI 0.11
2102004000 PM10-PRI 0.06
2102004000 PM25-PRI 0.04
2102004000 SO2 0.06
2102005000 PM10-PRI 0.05
2102005000 PM25-PRI 0.02
2102005000 SO2 1.32
2102006000 PM10-PRI 0.40
2102006000 PM25-PRI 0.33
2102006000 SO2 0.01
2102007000 PM10-PRI 0.59
2102007000 PM25-PRI 0.59
2102007000 SO2 0.00
2103002000 PM10-PRI 0.02
2103002000 PM25-PRI 0.02
2103004000 PM10-PRI 0.26
2103004000 PM25-PRI 0.23
2103004000 SO2 0.01
2103005000 PM10-PRI 0.17
2103005000 PM25-PRI 0.08
2103005000 SO2 4.14
2103006000 PM10-PRI 0.06
2103006000 PM25-PRI 0.06
2103006000 SO2 0.01
2104002000 PM10-PRI 2.10
2104002000 PM25-PRI 1.04
2104002000 SO2 0.11
2104004000 PM10-PRI 0.15
2104004000 PM25-PRI 0.14
2104004000 SO2 0.05
2104006000 PM10-PRI 0.30
2104006000 PM25-PRI 0.27
2104006000 SO2 0.01
2601010000 PM10-PRI 4.94
2601010000 PM25-PRI 1.78
2601010000 SO2 0.89
2601020000 PM10-PRI 2.47
2601020000 PM25-PRI 0.64
2601020000 SO2 0.70
2810030000 PM10-PRI 5.68
2810030000 PM25-PRI 5.17
2810030000 SO2 0.00

# Attachment C1

BY 2002 Area and Nonroad Source Emissions Summary2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaPM2.5Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD TotalArea Source2102002000 Coal Consumption213.6221.66 13.59 106.06 1.01 2.17 34.42 21.46 12.41 0.84 213.62 0.002102004000 Fuel Oil Consumption11.590.73 0.881.431.380.730.463.56 0.03 0.07 1.150.72 0.42 0.037.17 4.422102005000 Fuel Oil Consumption22.394.31 5.205.185.040.270.171.31 0.01 0.03 0.430.27 0.15 0.012.65 19.742102006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption184.7118.73 11.76 91.71 0.87 1.87 29.76 18.56 10.73 0.72 184.71 0.002102007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption18.981.921.219.43 0.09 0.19 3.061.91 1.10 0.07 18.98 0.002103002000 Coal Consumption26.30 8.802.04 4.086.122.040.510.301.72 0.06 0.05 0.250.26 0.07 0.013.23 14.272103004000 Fuel Oil Consumption187.21 44.903.85 4.647.477.2818.72 11.22 63.48 2.26 1.82 9.329.60 2.41 0.24 119.07 23.242103005000 Fuel Oil Consumption12.340.32 0.390.430.411.701.025.76 0.20 0.16 0.840.87 0.22 0.02 10.79 1.552103006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption196.60 65.670.84 1.8222.73 21.8413.167.89 44.62 1.59 1.28 6.556.75 1.69 0.17 83.70 47.232103007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption0.490.07 0.100.150.170.00 0.492103011000 Fuel Oil Consumption1.660.28 0.330.530.510.00 1.662104002000 Coal Consumption14.82 2.420.00 0.330.330.351.150.785.98 0.14 0.06 1.181.82 0.21 0.06 11.38 1.022104004000 Fuel Oil Consumption122.16 9.306.77 8.1613.17 12.817.274.96 37.72 0.87 0.39 7.45 11.48 1.34 0.46 71.94 40.922104006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption430.25 58.662.48 5.5267.34 59.7723.89 16.32 123.99 2.86 1.30 24.48 37.75 4.41 1.50 236.50 135.092104007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption2.82 0.020.39 0.580.870.960.00 2.802104008001 Other Fuels Consumption (ResidentialWood Burning)301.44 13.1418.73 42.6161.73 91.6214.312.00 36.47 2.20 1.16 4.829.44 2.37 0.84 73.61 214.692104008002 Other Fuels Consumption (ResidentialWood Burning)711.00 39.3673.57 10.30 398.33 11.32 5.95 52.56 103.14 12.16 4.31 671.64 0.002104008003 Other Fuels Consumption (ResidentialWood Burning)28.22 1.562.920.41 15.81 0.45 0.24 2.094.09 0.48 0.17 26.66 0.002104008004 Other Fuels Consumption (ResidentialWood Burning)11.86 0.661.230.176.64 0.19 0.10 0.881.72 0.20 0.07 11.20 0.002104008010 Other Fuels Consumption (ResidentialWood Burning)1973.22 28.1453.03 104.87 233.71 382.8363.758.92 768.39 9.81 5.16 101.39 198.96 10.53 3.74 1170.65 774.432104008030 Other Fuels Consumption (ResidentialWood Burning)51.29 0.472.14 4.249.45 15.481.070.15 12.81 0.16 0.08 1.693.31 0.17 0.06 19.50 31.322104008050 Other Fuels Consumption (ResidentialWood Burning)114.92 1.124.61 9.1220.32 33.292.530.36 30.50 0.39 0.20 4.027.89 0.42 0.15 46.46 67.342104008053Other Fuels Consumption (ResidentialWood Burning)4.831.11 2.570.490.660.00 4.832104008060Other Fuels Consumption (ResidentialWood Burning)25.775.94 13.852.543.440.00 25.772104008070 Other Fuels Consumption (ResidentialWood Burning; Outdoor Equipment)226.6917.06 28.3695.14 86.130.00 226.692104009000Other Fuels Consumption (ResidentialFirelog)30.002.625.958.63 12.800.00 30.002104011000 Fuel Oil Consumption 2.890.48 0.58 0.93 0.900.00 2.892199008000Stationary Source Fuel Combustion(Wood Burning)6.011.38 3.230.590.800.00 6.012294000000 Mobile: All Paved Roads - Total:Fugitives854.01135.54 144.27 128.61 78.2218.13 14.59 154.37 3.25 0.84 91.36 78.70 5.44 0.70 367.37 486.642296000000 Mobile: All Unpaved Roads - Total:Fugitives353.562.50 12.186.956.1773.4198.67 153.69325.77 27.792302002100 Commercial Cooking79.03 26.082.71 5.6623.96 20.620.00 52.952302002200 Commercial Cooking547.50 188.6918.39 34.75 173.54 132.140.00 358.812302003100Industrial Processes (CommercialCooking - Flat Griddle Frying)72.493.70 7.2535.36 26.170.00 72.492302003200Industrial Processes (CommercialCooking - Clamshell Griddle Frying)5.940.29 0.572.672.400.00 5.942311010000 Total Residential Construction: SIC 15- 17112.756.10 6.4015.73 10.810.553.27 17.47 0.25 0.01 39.92 11.23 0.22 0.79 73.71 39.042311020000 TotalIndustrial/Commercial/InstitutionalConstruction: SIC 15 - 17833.096.77 28.98 253.12 145.0521.53 20.99 195.51 7.56 14.15 108.73 13.72 16.98399.18 433.912311030000 Total Road Construction: SIC 15 - 17 1438.3396.95 104.07 330.62 169.035.33 24.79 158.64 2.91 0.07 415.23 119.37 2.24 9.09 737.66 700.672325000000 Industrial Processes: Mining andQuarrying: SIC 14 - All Processes293.9448.99 48.99 48.99 48.9948.99 48.99293.94 0.002401001000 Surface Coating - Architectural431.52 431.520.00 0.002401005000 Surface Coating - AutomobileRefinishing6.08 6.080.00 0.002601000000 On-Site Incineration25.950.00 11.9012.50 1.550.00 25.952601010000 On-Site Incineration41.044.162.61 20.40 0.18 0.41 6.614.13 2.38 0.16 41.04 0.002601020000 On-Site Incineration95.039.606.55 49.83 1.15 0.52 9.84 15.17 1.77 0.60 95.03 0.002610000100 Open Burning24.764.72 8.234.890.176.756.75 18.012610000400 Open Burning14.803.14 5.473.250.002.942.94 11.862610000500 Open Burning6293.71250.37 571.01 1632.54 613.1767.48 125.17 1539.7534.14 741.77 642.88 47.19 28.24 3226.62 3067.09C1-12002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaPM2.5Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD Total2610030000 Open Burning33.4010.98 18.02 4.40 0.000.00 33.402801000003 Crops Tilling575.4762.28 233.25 81.31 28.083.11150.94 16.51170.56 404.912805001000 Livestock, beef cattle, feedlots, DustKicked-up by Hooves60.005.0645.519.4360.00 0.002810001000 Forest Fires27.2112.55 2.497.843.880.080.380.45 26.762810015000 Slash/Prescribed Burning117.65 0.001.77 0.000.000.650.010.01 32.4142.14 40.60 0.04 0.02 115.23 2.422810030000 Structure Fires38.05 6.080.94 1.251.758.794.773.113.58 0.05 0.26 0.316.69 0.26 0.21 19.24 12.732810050000 Motor Vehicle Fires21.711.00 1.313.72 15.680.00 21.712002 Area Source Total17331.09 932.67 749.87 1444.49 3282.02 2003.10 449.64342.07 4066.81 98.85 72.68 2096.12 1601.48 138.01 53.28 8918.947479.48Nonroad Model SourceAgricultural Equipment59.090.00 4.67 24.86 9.04 3.54 0.00 0.00 0.41 0.00 0.00 13.21 3.36 0.00 0.0016.98 42.12Airport Equipment21.520.00 0.00 0.00 0.01 0.00 10.30 0.00 5.60 0.00 0.00 5.60 0.00 0.01 0.0021.51 0.01Commercial Equipment102.038.78 1.976.0622.81 17.42 2.463.18 26.30 1.50 0.49 5.153.99 1.40 0.5244.99 48.25Construction and Mining Equipmen1340.70242.82 50.22 60.27 169.59 193.67 119.84 0.00 192.90 0.00 0.00 185.09 126.29 0.00 0.00624.13 473.75Industrial Equipmen116.6113.81 2.788.9723.90 20.14 3.373.06 23.85 0.58 0.33 6.686.56 2.25 0.3247.00 55.80Lawn and Garden Equipment (Com)538.141.78 5.81 35.35139.61 68.21 6.478.58 144.10 5.08 3.47 76.13 38.96 1.31 3.28287.39 248.97Lawn and Garden Equipment (Res74.4211.32 1.94 3.23 14.33 12.83 3.81 2.77 15.45 0.32 0.20 3.08 4.48 0.51 0.1530.78 32.32Logging Equipment2.560.00 1.17 0.16 0.12 0.48 0.00 0.00 0.08 0.00 0.00 0.47 0.08 0.00 0.000.63 1.93Pleasure Craft41.857.70 16.53 1.85 4.63 5.25 0.00 0.00 3.13 0.00 0.00 0.39 2.37 0.00 0.005.89 28.27Railroad Equipment2.630.16 0.01 0.51 0.33 0.22 0.06 0.21 0.41 0.00 0.00 0.00 0.56 0.10 0.051.40 1.07Recreational Equipment31.401.61 4.24 4.35 8.66 4.32 0.03 0.00 3.55 0.02 0.00 1.18 3.44 0.00 0.008.23 21.57Nonroad Model Source2330.96287.98 89.34145.62393.03 326.06 146.3517.80 415.81 7.51 4.49 296.98 190.08 5.58 4.33 1088.92 954.05Other Nonroad Sources2275001000 Military Aviation52.847.62 2.76 0.00 9.9723.13 9.38 32.51 20.342275020000 Commercial Aviation32.400.00 0.000.000.009.1011.6511.6532.40 0.002275050000 General Aviation10.960.13 1.550.730.843.270.51 3.947.72 3.242275060000 Air Taxi0.200.00 0.020.060.010.020.100.12 0.082275070000 Aircraft Auxiliary Power Units0.110.010.050.050.11 0.002285002005 Railroad Locomotives142.010.00 9.217.235.700.37 16.1251.33 40.33 11.72 119.87 22.142285002006 Railroad Locomotives1.89 1.890.00 0.002285002008 Railroad Locomotives1.94 1.940.00 0.002285002009 Railroad Locomotives1.58 1.580.00 0.002285002010 Railroad Locomotives43.42 5.320.00 6.081.520.000.094.1013.06 10.27 2.99 30.51 7.60Other Nonroad Sources Total287.3510.73 19.619.5316.51 9.11 9.110.46 55.05 0.00 0.00 14.99 74.27 54.6414.71 223.23 53.392002 Nonroad Source Total2618.31 298.71 108.95155.15409.54335.17 155.46 18.26 470.86 7.51 4.49 311.97 264.36 60.22 19.041312.151007.45C1-22002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaNitrogen Oxides (NOx)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCityFairfaxCountyFairfaxCityFallsChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD TotalArea Source2102002000 Coal Consumption 1979.90200.75 125.99 982.97 9.38 20.09 318.98 198.93 115.02 7.78 1979.90 0.002102004000 Fuel Oil Consumption 227.15 1.929.43 11.36 18.32 17.8317.06 10.71 83.55 0.80 1.71 27.11 16.91 9.78 0.66 168.29 56.942102005000 Fuel Oil Consumption 215.5517.32 20.88 33.68 32.7711.247.06 55.06 0.53 1.13 17.87 11.14 6.44 0.44 110.90 104.652102006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption566.8457.47 36.07 281.43 2.69 5.75 91.32 56.95 32.93 2.23 566.84 0.002102007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption32.370.153.272.05 16.00 0.15 0.33 5.19 3.24 1.87 0.13 32.22 0.002103002000 Coal Consumption210.17 33.004.29 8.5812.87 4.2923.14 13.87 78.44 2.79 2.25 11.51 11.86 2.98 0.29 147.14 30.032103004000 Fuel Oil Consumption 872.86 134.4436.12 43.54 70.21 68.3381.81 49.03 277.34 9.87 7.96 40.71 41.93 10.53 1.04 520.22 218.202103005000 Fuel Oil Consumption152.902.74 3.305.335.1921.44 12.85 72.68 2.59 2.09 10.67 10.99 2.76 0.27 136.34 16.562103006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption2534.53 650.6410.33 22.54 281.13 270.16204.39 122.50 692.90 24.67 19.89 101.71 104.76 26.32 2.59 1299.73 584.162103007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption77.251.74 2.593.884.2810.186.10 34.52 1.23 0.99 5.07 5.22 1.31 0.13 64.75 12.492103007005 Natural Gas and Liquefied PetroleumGas (LPG) Consumption0.150.150.00 0.002103011000 Fuel Oil Consumption15.532.57 3.105.004.860.00 15.532104002000 Coal Consumption17.404.550.00 0.620.620.671.100.75 5.74 0.13 0.06 1.13 1.75 0.20 0.07 10.94 1.912104004000 Fuel Oil Consumption999.49 136.7957.24 69.00 111.28 108.2952.21 35.66 270.98 6.27 2.83 53.52 82.51 9.64 3.28 516.89 345.812104006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption3212.34 669.7030.61 68.21 832.86 739.2188.05 60.14 457.01 10.57 4.78 90.26 139.15 16.26 5.53 871.74 1670.902104007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption308.500.239.82 14.63 21.97 24.2224.00 16.39 124.58 2.88 1.30 24.60 37.93 4.43 1.51 237.63 70.642104008000 Other Fuels Consumption(Residential Wood Burning)192.9217.02 11.62 88.33 2.04 0.92 26.23 40.43 4.72 1.61 192.92 0.002104008001 Other Fuels Consumption(Residential Wood Burning)21.791.451.78 4.045.858.680.00 20.352104008002 Other Fuels Consumption(Residential Wood Burning)3.603.600.000.002104008004 Other Fuels Consumption(Residential Wood Burning)0.060.060.00 0.002104008010 Other Fuels Consumption(Residential Wood Burning)61.232.574.02 7.9417.70 29.000.00 58.662104008030 Other Fuels Consumption(Residential Wood Burning)3.79 0.050.26 0.511.131.850.00 3.742104008050Other Fuels Consumption(Residential Wood Burning)10.220.70 1.383.085.050.00 10.222104008053Other Fuels Consumption(Residential Wood Burning)6.001.38 3.190.600.820.00 6.002104008060Other Fuels Consumption(Residential Wood Burning)1.940.45 1.040.190.260.00 1.942104008070 Other Fuels Consumption(Residential Wood Burning; OutdoorEquipment)71.55 54.521.28 2.137.156.470.00 17.032104009000 Other Fuels Consumption(Residential Firelog)4.020.35 0.801.161.720.00 4.022104011000 Fuel Oil Consumption24.494.05 4.897.887.670.00 24.492199008000Stationary Source Fuel Combustion(Wood Burning)0.400.09 0.220.040.050.00 0.402601000000 On-Site Incineration961.450.26 5.78 937.51 17.900.00 961.452601010000 On-Site Incineration23.022.331.46 11.43 0.11 0.23 3.71 2.31 1.34 0.09 23.02 0.002601020000 On-Site Incineration148.8215.03 10.27 78.02 1.80 0.82 15.41 23.75 2.78 0.94 148.82 0.002601030000 On-Site Incineration7.630.770.53 4.00 0.09 0.04 0.79 1.22 0.14 0.05 7.63 0.002610000100 Open Burning5.081.33 2.321.380.050.00 5.082610000400 Open Burning3.901.03 1.801.070.000.00 3.902610000500 Open Burning73.6473.640.00 73.642610020000 Open Burning879.51167.94 480.16 180.3428.2015.96 6.9251.07 828.442610030000 Open Burning3.853.850.00 3.852620030000 Municipal Solid Waste Landfills8.036.321.540.000.170.17 7.862810001000 Forest Fires6.422.95 0.591.850.910.02 0.100.12 6.302810015000 Slash/Prescribed Burning0.360.000.00 0.000.000.000.040.320.36 0.002810030000 Structure Fires6.420.870.13 0.180.251.250.920.60 0.70 0.01 0.05 0.07 1.29 0.05 0.04 3.74 1.812810050000 Motor Vehicle Fires0.950.04 0.060.160.690.00 0.952002 Area Source Total13954.02 1694.70 279.80 479.47 2865.86 1542.81 832.19 523.66 3643.91 78.61 73.22 862.01 799.62 249.51 28.66 7091.38 5167.94Nonroad Model SourceAgricultural Equipment501.930.00 39.68 211.2076.82 30.03 0.000.00 3.50 0.00 0.00 112.17 28.53 0.00 0.00144.20 357.73C1-32002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaNitrogen Oxides (NOx)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCityFairfaxCountyFairfaxCityFallsChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD TotalAirport Equipment467.780.00 0.00 0.05 0.10 0.01 134.00 0.00 166.75 0.00 0.00 166.75 0.00 0.13 0.00467.63 0.15Commercial Equipment1288.28109.31 24.87 76.56288.26 220.21 31.11 40.27 332.67 18.99 6.22 65.16 50.42 17.68 6.55569.07 609.90Construction and Mining Equipment14147.822547.39 530.65 636.83 1791.96 2046.47 1266.240.00 2038.18 0.00 0.00 1955.68 1334.41 0.00 0.006594.51 5005.91Industrial Equipment2442.55271.98 48.43 259.69515.00 401.35 41.68 58.46 465.85 12.51 8.21 168.95 109.67 73.10 7.68946.11 1224.46Lawn and Garden Equipment (Com)2775.229.16 29.97 182.22719.71 351.64 33.35 44.23 742.90 27.17 17.88 392.47 200.83 6.77 16.921482.51 1283.55Lawn and Garden Equipment (Res)495.2675.30 12.87 21.5295.32 85.32 25.37 18.40 102.80 2.31 1.30 20.50 29.83 3.40 1.01204.92 215.03Logging Equipment27.060.00 12.33 1.731.32 5.02 0.000.00 0.84 0.00 0.00 5.00 0.82 0.00 0.006.66 20.40Pleasure Craft219.3543.41 112.10 5.9714.93 16.92 0.000.00 13.54 0.00 0.00 1.36 11.13 0.00 0.0026.02 149.92Railroad Equipment18.881.16 0.04 3.682.39 1.57 0.461.54 2.98 0.00 0.00 0.00 4.01 0.70 0.3610.05 7.67Recreational Equipment77.078.49 6.28 9.9018.71 8.81 1.080.00 11.65 0.72 0.00 3.76 7.67 0.00 0.0024.88 43.70Nonroad Model Source22461.20 3066.20 817.22 1409.34 3524.52 3167.34 1533.29 162.89 3881.66 61.71 33.62 2891.80 1777.32 101.78 32.51 10476.58 8918.42Other Nonroad Sources2275001000 Military Aviation50.694.58 1.666.0026.8211.6438.46 12.232275020000 Commercial Aviation1341.90477.60432.15432.151341.90 0.002275050000 General Aviation14.670.41 5.022.36 2.731.76 0.27 2.124.15 10.522275060000 Air Taxi0.890.02 0.140.44 0.060.040.200.24 0.652275070000 Aircraft Auxiliary Power Units53.107.3022.9022.9053.10 0.002285002005 Railroad Locomotives1861.54341.60268.22 211.363.18 139.99445.42 349.97 101.81 1040.36 821.182285002006 Railroad Locomotives95.00 95.000.00 0.002285002008 Railroad Locomotives89.73 89.730.00 0.002285002009 Railroad Locomotives73.31 73.310.00 0.002285002010 Railroad Locomotives680.08 211.40167.9041.980.79 34.82110.80 87.06 25.33 258.80 209.88Other Nonroad Sources Total4260.91 469.44 5.00 516.32313.00 220.14 484.903.97 656.68 0.00 0.00 456.84 568.12 439.34 127.14 2737.00 1054.462002 Nonroad Source Total26722.11 3535.64 822.23 1925.66 3837.51 3387.49 2018.19 166.87 4538.34 61.71 33.62 3348.65 2345.44 541.12 159.65 13213.58 9972.89C1-42002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaSulfur Dioxide (SO2)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD TotalArea Source2102002000 Coal Consumption8159.0520.36 24.5439.58 38.52814.80 511.35 3989.72 38.08 81.56 1294.69 807.43 466.84 31.56 8036.05 123.002102004000 Fuel Oil Consumption423.15100.17 120.7497.36 94.751.030.645.03 0.05 0.10 1.631.02 0.59 0.04 10.13 413.022102005000 Fuel Oil Consumption146.3714.849.31 72.69 0.69 1.48 23.58 14.71 8.50 0.57 146.37 0.002102006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption4.470.450.282.22 0.02 0.05 0.720.45 0.26 0.024.47 0.002103002000 Coal Consumption892.14 114.0034.83 69.66104.49 34.8384.03 50.36 284.86 10.14 8.18 41.82 43.07 10.82 1.07 534.33 243.812103004000 Fuel Oil Consumption475.7878.02 94.04151.66 147.590.700.422.39 0.08 0.07 0.350.36 0.09 0.014.47 471.312103005000 Fuel Oil Consumption629.8815.85 19.1115.41 14.9988.80 53.22 301.02 10.69 8.61 44.15 45.48 11.43 1.12 564.52 65.362103006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption15.573.900.070.141.79 1.721.250.754.23 0.15 0.12 0.620.64 0.16 0.027.94 3.732103007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption0.020.000.000.01 0.010.00 0.022103011000 Fuel Oil Consumption33.535.556.6910.79 10.500.00 33.532104002000 Coal Consumption29.70 15.500.004.244.24 4.540.120.080.62 0.01 0.01 0.120.19 0.02 0.011.18 13.022104004000 Fuel Oil Consumption1181.53 323.74137.39 165.61267.07 259.902.811.92 14.58 0.34 0.15 2.884.44 0.52 0.18 27.82 829.972104006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption20.164.270.200.445.32 4.720.530.362.74 0.06 0.03 0.540.83 0.10 0.035.22 10.672104007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption0.110.000.010.020.03 0.040.00 0.112104008001 Other Fuels Consumption (ResidentialWood Burning)5.540.22 0.240.560.81 1.20 0.490.071.24 0.07 0.04 0.160.33 0.08 0.032.51 2.812104008002 Other Fuels Consumption (ResidentialWood Burning)9.300.510.960.135.21 0.15 0.08 0.691.35 0.16 0.068.79 0.002104008003 Other Fuels Consumption (ResidentialWood Burning)0.560.030.060.010.32 0.010.040.08 0.010.53 0.002104008004 Other Fuels Consumption (ResidentialWood Burning)0.210.010.020.130.020.030.20 0.002104008010 Other Fuels Consumption (ResidentialWood Burning)20.250.37 0.310.621.38 2.27 0.830.11 10.05 0.13 0.07 1.322.60 0.14 0.05 15.30 4.582104008030 Other Fuels Consumption (ResidentialWood Burning)1.120.01 0.050.100.23 0.37 0.020.250.030.060.36 0.752104008050 Other Fuels Consumption (ResidentialWood Burning)2.760.02 0.120.240.54 0.89 0.050.010.62 0.010.080.16 0.010.94 1.792104008053Residential Wood Combustion: NonCatalytic Woodstoves: Pellet Fired0.50 0.12 0.27 0.05 0.070.502104008060Residential Wood Combustion -Outdoor Boilers & Furnaces0.30 0.07 0.16 0.03 0.040.302104009000Residential Firelog: 'Total: AllCombustor Types2.59 0.23 0.51 0.74 1.102.592104008070 Other Fuels Consumption (ResidentialWood Burning; Outdoor Equipment)3.47 0.85 0.20 0.33 1.10 1.000.00 2.622199008000Total Area Source Fuel Combustion:Wood - All Boiler Types0.440.10 0.24 0.04 0.060.442104011000 Fuel Oil Consumption 58.779.73 11.7318.91 18.400.00 58.772601000000 On-Site Incineration88.960.182.9684.26 1.560.00 88.962601010000 On-Site Incineration20.502.081.30 10.19 0.09 0.21 3.302.06 1.19 0.08 20.50 0.002601020000 On-Site Incineration104.4210.557.20 54.76 1.26 0.57 10.81 16.67 1.94 0.66 104.42 0.002610000100 Open Burning0.620.160.280.17 0.010.00 0.622610000400 Open Burning1.290.340.600.35 0.000.00 1.292610030000 Open Burning1.960.641.060.26 0.000.00 1.962810001000 Forest Fires0.030.010.030.03 0.002810015000 Slash/Prescribed Burning0.510.140.190.180.51 0.002002 Area Source Total12335.56463.44404.95524.89806.62 639.06 1024.42 637.52 4763.01 62.04101.32 1427.74942.17 502.86 35.51 9496.59 2375.52Nonroad Model SourceAgricultural Equipment51.000.00 4.03 21.46 7.81 3.05 0.00 0.00 0.36 0.00 0.00 11.40 2.90 0.00 0.0014.65 36.35Airport Equipment46.030.00 0.00 0.00 0.01 0.00 19.40 0.00 13.30 0.00 0.00 13.30 0.00 0.01 0.0046.01 0.02Commercial Equipment88.827.96 1.71 5.25 19.78 15.11 2.13 2.76 22.81 1.30 0.43 4.47 3.46 1.21 0.4539.01 41.85Construction and Mining Equipmen1629.93311.46 60.31 72.38 203.66 232.59 143.92 0.00 231.65 0.00 0.00 222.28 151.67 0.00 0.00749.51 568.95Industrial Equipmen142.4217.83 3.36 10.9428.96 24.37 4.053.71 28.91 0.70 0.41 8.127.91 2.75 0.3956.95 67.63Lawn and Garden Equipment (Com)140.170.46 1.51 9.20 36.35 17.76 1.68 2.23 37.52 1.37 0.90 19.82 10.14 0.34 0.8574.88 64.83Lawn and Garden Equipment (Res14.011.91 0.370.622.75 2.46 0.730.532.96 0.07 0.04 0.590.86 0.10 0.035.90 6.19Logging Equipment3.410.00 1.55 0.22 0.17 0.63 0.00 0.00 0.11 0.00 0.00 0.63 0.10 0.00 0.000.84 2.57Pleasure Craft14.352.84 7.49 0.37 0.93 1.05 0.00 0.00 0.87 0.00 0.00 0.09 0.72 0.00 0.001.68 9.84Railroad Equipment1.870.12 0.00 0.36 0.24 0.15 0.05 0.15 0.29 0.00 0.00 0.00 0.39 0.07 0.040.99 0.75Recreational Equipment3.610.52 0.36 0.45 0.88 0.43 0.03 0.00 0.44 0.02 0.00 0.14 0.34 0.00 0.000.97 2.12Nonroad Model Source2135.61 343.11 80.70 121.27301.53 297.60 171.999.38 339.23 3.46 1.77 280.84178.49 4.49 1.76 991.41 801.09Other Nonroad Sources2275001000 Military Aviation49.740.720.260.000.944.7043.1347.83 1.912275020000 Commercial Aviation117.600.00 0.00 0.00 0.00 45.7035.9535.95117.60 0.002275050000 General Aviation16.310.637.733.63 4.200.050.01 0.060.12 16.192275060000 Air Taxi0.120.000.010.04 0.010.010.050.06 0.06C1-52002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaSulfur Dioxide (SO2)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD Total2275070000 Aircraft Auxiliary Power Units7.301.003.153.157.30 0.002285002005 Railroad Locomotives395.690.00 24.9419.58 15.431.03 45.17143.74 112.95 32.85 335.74 59.952285002006 Railroad Locomotives6.366.360.00 0.002285002008 Railroad Locomotives6.556.550.00 0.002285002009 Railroad Locomotives5.355.350.00 0.002285002010 Railroad Locomotives92.47 15.090.00 11.983.00 0.000.198.4026.72 20.98 6.11 62.40 14.98Other Nonroad Sources Total697.49 33.35 1.34 44.9226.25 20.57 46.701.22 97.37 0.00 0.00 39.16 213.60 134.0438.96 571.0593.092002 Nonroad Source Total2833.10 376.46 82.04166.19327.78 318.18 218.69 10.60 436.60 3.46 1.77 320.00 392.09 138.53 40.72 1562.46894.19C1-62002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaVolatile Organic Compounds (VOC)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCityFairfaxCountyFairfaxCityFallsChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD TotalArea Source2102002000 Coal Consumption157.2315.94 10.00 78.06 0.75 1.60 25.33 15.80 9.13 0.62 157.23 0.002102004000 Fuel Oil Consumption2.26 0.020.09 0.110.18 0.180.17 0.11 0.84 0.01 0.02 0.27 0.17 0.10 0.01 1.68 0.562102005000 Fuel Oil Consumption1.100.09 0.110.17 0.170.06 0.04 0.28 0.00 0.01 0.09 0.06 0.03 0.00 0.56 0.542102006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption11.271.14 0.72 5.60 0.05 0.11 1.82 1.13 0.65 0.04 11.27 0.002102007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption0.85 0.010.09 0.05 0.42 0.00 0.01 0.14 0.09 0.05 0.00 0.85 0.002103002000 Coal Consumption22.67 0.150.34 0.681.02 0.343.17 1.90 10.73 0.38 0.31 1.58 1.62 0.41 0.04 20.13 2.392103004000 Fuel Oil Consumption14.18 1.630.61 0.741.19 1.161.39 0.83 4.71 0.17 0.14 0.69 0.71 0.18 0.02 8.84 3.702103005000 Fuel Oil Consumption3.150.06 0.070.11 0.110.44 0.26 1.49 0.05 0.04 0.22 0.23 0.06 0.01 2.80 0.352103006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption119.72 35.790.60 1.3216.45 15.817.82 4.69 26.52 0.94 0.76 3.89 4.01 1.01 0.10 49.75 34.182103007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption2.760.06 0.090.14 0.150.36 0.22 1.23 0.04 0.04 0.18 0.19 0.05 0.00 2.31 0.452103007005 Natural Gas and Liquefied PetroleumGas (LPG) Consumption0.01 0.010.00 0.002103011000 Fuel Oil Consumption0.250.04 0.050.08 0.080.00 0.252104002000 Coal Consumption19.12 5.000.00 0.680.68 0.731.21 0.83 6.30 0.15 0.07 1.24 1.92 0.22 0.08 12.02 2.102104004000 Fuel Oil Consumption39.59 5.422.27 2.734.41 4.292.07 1.41 10.73 0.25 0.11 2.12 3.27 0.38 0.13 20.47 13.702104006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption204.28 39.181.79 3.9948.73 43.256.80 4.65 35.30 0.82 0.37 6.97 10.75 1.26 0.43 67.33 97.772104007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption11.02 0.010.35 0.520.78 0.860.86 0.59 4.45 0.10 0.05 0.88 1.35 0.16 0.05 8.49 2.522104008000 Other Fuels Consumption (ResidentialWood Burning)10074.87888.65 607.03 4612.64 106.67 48.24 1369.57 2111.47 246.74 83.84 10074.87 0.002104008001 Other Fuels Consumption (ResidentialWood Burning)259.78 127.4611.55 26.2638.05 56.470.00 132.322104008002 Other Fuels Consumption (ResidentialWood Burning)68.18 68.180.00 0.002104008003 Other Fuels Consumption (ResidentialWood Burning)0.96 0.960.00 0.002104008004 Other Fuels Consumption (ResidentialWood Burning)0.48 0.480.00 0.002104008010 Other Fuels Consumption (ResidentialWood Burning)889.40 48.7457.57 113.84 253.69 415.570.00 840.662104008030 Other Fuels Consumption (ResidentialWood Burning)32.53 0.342.20 4.369.71 15.910.00 32.182104008050 Other Fuels Consumption (ResidentialWood Burning)91.25 0.686.20 12.2627.33 44.770.00 90.572104008053Other Fuels Consumption (ResidentialWood Burning)0.060.01 0.030.01 0.010.00 0.062104008060Other Fuels Consumption (ResidentialWood Burning)170.5739.2991.6816.80 22.790.00 170.572104008070 Other Fuels Consumption (ResidentialWood Burning; Outdoor Equipment)1986.29 485.96112.89 187.73 629.66 570.050.00 1500.332104009000Other Fuels Consumption (ResidentialFirelog)21.041.84 4.186.05 8.980.00 21.042104011000 Fuel Oil Consumption0.960.16 0.190.31 0.300.00 0.962199008000Stationary Source Fuel Combustion(Wood Burning)2.550.59 1.370.25 0.340.00 2.552275900000 Aircraft Refueling36.740.23 1.291.21 1.778.306.5612.44 4.9332.23 4.502302002100 Commercial Cooking20.40 6.730.70 1.466.18 5.320.00 13.672302002200 Commercial Cooking67.94 23.412.28 4.3121.53 16.400.00 44.522302003000Commercial Cooking7.320.39 0.743.31 2.880.00 7.322302003100Industrial Processes (CommercialCooking - Flat Griddle Frying)5.720.29 0.572.79 2.060.00 5.722302003200Industrial Processes (CommercialCooking - Clamshell Griddle Frying)0.250.01 0.020.11 0.100.00 0.252302050000 Bakeries449.17 46.202.64 0.0095.48 9.2329.86 20.40 154.98 3.58 1.62 30.61 47.19 5.51 1.87 295.62 107.352302070001 Breweries1.22 0.100.00 1.040.06 0.010.000.00 1.112302070005 Wineries0.060.00 0.010.01 0.000.050.05 0.012401001000 Surface Coating - Architectural756.40 756.400.00 0.002401002000 Surface Coating - Architectural2893.7788.46 143.36 623.94 571.10148.16 101.21 769.03 17.79 8.04 151.88 234.15 27.36 9.30 1466.91 1426.862401003000 Surface Coating - Architectural2297.5078.09 126.55 550.76 504.12104.84 71.61 544.17 12.58 5.69 107.47 165.68 19.36 6.58 1037.99 1259.522401005000 Surface Coating - AutomobileRefinishing2725.29 82.9655.36 79.85 267.59 212.58163.66 216.58 635.86 107.35 75.45 305.92 386.62 58.18 77.32 2026.94 615.392401008000 Surface Coating - Traffic Paints546.60 134.515.61 9.039.63 6.3938.53 26.32 199.97 4.62 2.09 39.49 60.89 7.12 2.42 381.44 30.652401015000 Surface Coating - Industrial127.90 5.465.96 14.1518.54 2.490.52 0.79 9.1539.45 28.27 0.46 2.66 81.31 41.132401020000 Surface Coating - Industrial129.1711.01 92.20 0.942.60 19.82 1.65 0.94 129.17 0.002401025000 Surface Coating - Industrial541.79 31.7211.33 8.97 139.71 220.9011.01 92.20 0.942.60 19.82 1.65 0.94 129.17 380.90C1-72002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaVolatile Organic Compounds (VOC)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCityFairfaxCountyFairfaxCityFallsChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD Total2401040000 Surface Coating - Industrial1367.9983.88 135.93 591.60 541.5015.0715.07 1352.912401045000 Surface Coating - Industrial34.048.6312.9512.4734.04 0.002401050000 Surface Coating - Industrial520.3532.26 52.28 227.54 208.270.00 520.352401055000 Surface Coating - Industrial145.66 0.213.50 44.0829.53 25.293.94 1.24 18.047.51 12.27 0.0443.04 102.412401065000 Surface Coating - Industrial2.082.082.08 0.002401070000 Surface Coating - Industrial44.544.1820.0914.27 5.94 0.0544.54 0.002401080000 Surface Coating - Industrial3.850.00 0.000.77 3.080.00 3.852401090000 Surface Coating - Industrial1372.40 175.8238.71 62.74 273.05 249.9357.79 39.47 299.96 6.94 3.14 59.24 91.33 10.67 3.63 572.16 624.422401100000 Surface Coating - Industrial1463.89 187.5441.29 66.92 291.25 266.5961.64 42.11 319.95 7.40 3.35 63.19 97.42 11.38 3.87 610.30 666.052401200000 Surface Coating - Special Industry1463.89 187.5441.29 66.92 291.25 266.5961.64 42.11 319.95 7.40 3.35 63.19 97.42 11.38 3.87 610.30 666.052401990000 Surface Coating - Industrial13.440.00 5.950.68 6.810.00 13.442415105000 Surface Cleaning1.61 1.610.00 0.002415120000 Surface Cleaning3.55 3.550.00 0.002415125000 Surface Cleaning1.28 1.280.00 0.002415130000 Surface Cleaning2079.63 3.22128.73 208.62 907.97 831.080.00 2076.412415135000 Surface Cleaning0.66 0.660.00 0.002415140000 Surface Cleaning1.77 1.770.00 0.002415145000 Surface Cleaning4.71 4.710.00 0.002415300000 Surface Cleaning64.904.58 4.69 29.66 3.62 1.53 7.47 8.16 4.21 0.97 64.90 0.002415305000 Surface Cleaning1.04 1.040.00 0.002415320000 Surface Cleaning1.03 1.030.00 0.002415325000 Surface Cleaning0.41 0.410.00 0.002415330000 Surface Cleaning21.49 0.541.03 0.08 7.35 0.08 0.18 3.71 0.25 8.2820.95 0.002415340000 Surface Cleaning0.38 0.380.00 0.002415345000 Surface Cleaning71.31 3.572.30 1.16 37.84 0.11 0.15 11.54 6.01 7.46 1.16 67.74 0.002415355000 Surface Cleaning53.87 53.870.00 0.002415360000 Surface Cleaning1242.72 111.40104.00 118.10 450.29 98.62 40.65 93.79 166.55 43.76 15.56 1131.32 0.002420000370 Dry Cleaners18.7318.730.00 18.732425000000 Graphic Arts1295.57 127.4830.12 53.08 187.20 140.0571.13 52.69 400.34 9.26 4.19 79.06 121.89 14.24 4.84 757.64 410.452440020000 Industrial Adhesives1058.67 62.8856.88 86.05 187.47 242.0622.98 33.28 204.10 26.89 6.80 43.51 70.64 11.61 3.53 423.34 572.452460100000 Commercial/Consumer Solvent Use 582.32 582.320.00 0.002460400000 Commercial/Consumer Solvent Use 353.39 353.390.00 0.002460500000 Commercial/Consumer Solvent Use 271.18 271.180.00 0.002460600000 Commercial/Consumer Solvent Use 149.20 149.200.00 0.002460800000 Pesticide Application482.29 482.290.00 0.002460900000 Commercial/Consumer Solvent Use19.98 19.980.00 0.002461020000 Asphalt Paving1.17 1.170.00 0.002461021000 Asphalt Paving0.120.000.110.00 0.010.12 0.002461022000 Asphalt Paving4.430.26 0.421.82 1.670.000.250.00 0.020.27 4.162461800000 Pesticide Application2582.39 7.3032.43 423.67 335.90 154.77164.46 112.34 853.65 19.74 8.93 168.59 259.91 30.37 10.32 1628.32 946.772461850000 Pesticide Application216.4311.43171.66 33.35216.43 0.002465000000 Commercial/Consumer Solvent Use 7347.36455.51 738.21 3212.852940.790.00 7347.362465800000 Pesticide Application545.1949.66 27.66 319.99 7.64 3.97 38.11 84.48 10.57 3.09 545.19 0.002465900000 Commercial/Consumer Solvent Use 6732.39679.97 464.48 3529.47 81.62 36.91 697.04 1074.63 125.58 42.67 6732.39 0.002501011011 Portable Fuel Containers220.96 54.379.94 16.4474.65 65.560.00 166.592501011012 Portable Fuel Containers1908.07 469.5085.87 141.97 644.63 566.100.00 1438.572501011016 Portable Fuel Containers104.72 25.774.71 7.7935.38 31.070.00 78.952501012011 Portable Fuel Containers17.92 2.421.04 2.377.21 4.890.00 15.512501012012 Portable Fuel Containers233.53 31.5113.59 30.8993.89 63.640.00 202.022501012016 Portable Fuel Containers3541.80 477.85206.16 468.56 1423.98 965.250.00 3063.952501060300Portable Fuel Containers2061.5986.84 88.95 1046.16 37.09 22.42 460.02 280.71 18.35 21.03 2061.59 0.002501060053 Tank Truck Unloading (Stage I)1244.10 75.3427.24 46.42 170.86 143.7877.80 54.77 372.30 28.76 13.75 71.16 132.71 29.22780.47 388.302501060100 Vehicle Fueling (Stage II) andUnderground Tank Breathing1282.41 235.41 62.84 143.81 383.04 457.310.00 1047.002501060103 Vehicle Fueling (Stage II) andUnderground Tank Breathing879.3680.52 44.30 506.45102.41 145.69879.36 0.002501060201 Vehicle Fueling (Stage II) andUnderground Tank Breathing919.28 79.86 29.29 49.91 183.73 154.7142.05 29.60 201.20 15.54 7.43 38.45 71.72 15.79421.78 417.632501080050 Aircraft Refueling1.17 1.170.00 0.002501080100 Aircraft Refueling0.07 0.070.00 0.002505020000 Petroleum Vessel Loading andUnloading Losses4.60 4.600.00 0.002505020120 Petroleum Vessel Loading andUnloading Losses52.2752.270.00 52.272505020180 Petroleum Vessel Loading andUnloading Losses0.020.020.00 0.022505030120 Losses from Gasoline Tank Trucks inTransit54.48 5.272.47 4.3115.77 13.251.34 0.94 6.40 0.49 0.24 1.22 2.28 0.5013.41 35.792601000000 On-Site Incineration3.960.00 0.372.67 0.910.00 3.962601010000 On-Site Incineration59.055.99 3.76 29.32 0.28 0.60 9.51 5.93 3.43 0.23 59.05 0.002601020000 On-Site Incineration305.8830.89 21.10 160.36 3.71 1.68 31.67 48.82 5.71 1.94 305.88 0.00C1-82002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaVolatile Organic Compounds (VOC)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCityFairfaxCountyFairfaxCityFallsChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD Total2601030000 On-Site Incineration57.225.78 3.95 30.00 0.69 0.31 5.92 9.13 1.07 0.36 57.22 0.002610000100 Open Burning22.926.01 10.476.22 0.220.00 22.922610000400 Open Burning14.813.92 6.834.06 0.000.00 14.812610000500 Open Burning2154.51188.06 192.47 1077.96 696.020.00 2154.512610020000 Open Burning242.59133.9375.81 32.85242.59 0.002610030000 Open Burning8.212.70 4.431.08 0.000.00 8.212620030000 Municipal Solid Waste Landfills18.985.09 4.936.53 0.000.771.23 0.432.43 16.552630020000 POTW115.90 11.2020.6620.29 61.370.20 1.61 0.450.02 0.092.38 102.322660000000 Leaking Underground Storage Tanks 308.87 124.1021.90 10.9538.14 113.520.02 0.01 0.01 0.09 0.01 0.06 0.04 0.02 0.00 0.26 184.512680003000 Composting3.80 3.800.00 0.002810001000 Forest Fires9.694.43 0.882.77 1.370.04 0.210.25 9.442810015000 Slash/Prescribed Burning2.24 0.001.520.560.020.140.16 2.072810030000 Structure Fires50.42 6.801.06 1.401.95 9.847.26 4.75 5.46 0.10 0.39 0.53 10.16 0.39 0.33 29.37 14.252810050000 Motor Vehicle Fires7.630.35 0.461.31 5.510.00 7.632830000000 Oil Spills5.480.58 4.050.32 0.530.00 5.482002 Area Source Total72377.396313.88 2165.863959.60 13550.7211991.533060.68 2285.40 16642.25620.87 304.72 4427.445991.35758.29 304.80 34395.8031667.71Nonroad Model SourceAgricultural Equipment71.440.00 5.64 30.05 10.93 4.27 0.00 0.00 0.50 0.00 0.00 15.98 4.06 0.00 0.0020.55 50.89Airport Equipment156.030.00 0.00 0.010.01 0.00 15.50 0.00 70.25 0.00 0.00 70.25 0.00 0.01 0.00156.01 0.02Commercial Equipment1851.27156.98 35.65 109.77 413.30 315.72 44.81 58.02 479.27 27.36 8.96 93.87 72.64 25.47 9.43819.85 874.44Construction and Mining Equipment2586.16464.81 96.98 116.38 327.48 373.99 231.67 0.00 372.90 0.00 0.00 357.81 244.14 0.00 0.001206.52 914.83Industrial Equipment545.4059.70 10.18 62.58 115.87 88.26 7.45 12.69 101.86 2.82 1.91 39.61 22.71 18.00 1.77208.83 276.88Lawn and Garden Equipment (Com)15633.4251.63 168.76 1026.18 4053.00 1980.23 188.09 249.42 4189.70 145.94 100.86 2213.43 1132.61 38.16 95.418353.62 7228.17Lawn and Garden Equipment (Res)5196.81779.96 134.95 225.57 999.12 894.40 267.89 194.29 1085.61 23.19 13.72 216.52 315.01 35.92 10.632162.81 2254.04Logging Equipment16.380.00 7.46 1.050.80 3.03 0.00 0.00 0.51 0.00 0.00 3.03 0.50 0.00 0.004.04 12.34Pleasure Craft2519.84460.16 989.98 112.51 281.27 318.78 0.00 0.00 190.19 0.00 0.00 23.48 143.47 0.00 0.00357.14 1702.54Railroad Equipment4.770.30 0.01 0.920.60 0.39 0.12 0.39 0.75 0.00 0.00 0.00 1.01 0.18 0.092.53 1.93Recreational Equipment1105.5649.75 142.45 153.11 303.02 149.91 3.21 0.00 134.61 2.14 0.00 44.51 122.84 0.00 0.00307.31 748.50Nonroad Model Source29687.082023.30 1592.061838.12 6505.40 4128.99 758.74514.82 6626.15201.46 125.46 3078.50 2059.01 117.75117.3413599.21 14064.57Other Nonroad Sources2275001000 Military Aviation264.2313.55 4.9117.74200.6827.36228.04 36.192275020000 Commercial Aviation312.9055.80128.55128.55312.90 0.002275050000 General Aviation86.292.40 29.5613.89 16.0710.33 1.60 12.44 24.37 61.922275060000 Air Taxi 6.86 0.12 1.05 3.43 0.430.29 1.55 1.84 5.032275070000 Aircraft Auxiliary Power Units 4.900.60 2.15 2.15 4.90 0.002285002005 Railroad Locomotives 74.21 14.76 11.59 9.13 0.12 5.21 16.58 13.03 3.79 38.72 35.482285002006 Railroad Locomotives 2.85 2.850.00 0.002285002008 Railroad Locomotives 3.88 3.880.00 0.002285002009 Railroad Locomotives 3.17 3.170.00 0.002285002010 Railroad Locomotives 45.89 9.64 16.93 4.23 0.05 2.03 6.46 5.08 1.48 15.09 21.16Other Nonroad Sources Total805.18 19.5416.07 67.2033.1443.38 56.40 0.16 338.62 0.00 0.00 141.31 52.00 32.09 5.27 625.86 159.782002 Nonroad Source Total30492.272042.831608.141905.32 6538.544172.36815.14514.98 6964.78 201.46 125.46 3219.81 2111.01 149.85122.60 14225.0814224.36C1-92002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaAmmonia (NH3)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD TotalArea Source2103006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption5.145.140.00 0.002104008001 Other Fuels Consumption (ResidentialWood Burning)12.661.10 2.513.645.400.00 12.662104008010 Other Fuels Consumption (ResidentialWood Burning)38.952.67 5.2711.75 19.250.00 38.952104008030 Other Fuels Consumption (ResidentialWood Burning)1.680.12 0.23 0.51 0.830.00 1.682104008050 Other Fuels Consumption (ResidentialWood Burning)4.040.28 0.55 1.22 1.990.00 4.042104008053Other Fuels Consumption (ResidentialWood Burning)0.470.11 0.25 0.05 0.060.00 0.472104008060Other Fuels Consumption (ResidentialWood Burning)1.340.31 0.72 0.13 0.180.00 1.342104008070 Other Fuels Consumption (ResidentialWood Burning; Outdoor Equipment)15.61 3.820.89 1.484.954.480.00 11.792104009000 Other Fuels Consumption (ResidentialFirelog)0.0020.00 0.000.000.000.00 0.002199008000Stationary Source Fuel Combustion(Wood Burning)0.430.10 0.23 0.04 0.060.00 0.432610000100 Open Burning1.030.27 0.47 0.28 0.010.00 1.032610000400 Open Burning0.980.26 0.45 0.27 0.000.00 0.982630020000 POTW5.91 2.800.49 0.80 0.65 0.06 1.123.11 0.002680003000 Composting16.490.8315.6615.66 0.002801700001Agriculture Production - Crops(Fertilizer Application)0.660.13 0.13 0.13 0.270.00 0.662801700002Agriculture Production - Crops(Fertilizer Application)4.570.00 4.57 0.00 0.000.00 4.572801700003Agriculture Production - Crops(Fertilizer Application)607.0717.89 555.590.01 13.10 0.121.7017.31 1.360.0020.49 586.582801700004Agriculture Production - Crops(Fertilizer Application)283.695.08 215.866.60 22.61 10.16 1.30 13.041.52 4.15 3.3633.54 250.152801700005Agriculture Production - Crops(Fertilizer Application)5.390.15 0.040.040.410.020.104.57 0.03 0.034.75 0.642801700006Agriculture Production - Crops(Fertilizer Application)34.080.1432.630.050.26 0.00 0.150.82 0.00 0.01 0.00 0.01 0.01 0.001.00 33.082801700007Agriculture Production - Crops(Fertilizer Application)19.600.00 0.000.000.000.0019.5819.59 0.012801700010Agriculture Production - Crops(Fertilizer Application)126.217.29 11.6830.01 25.08 0.80 2.54 29.31 6.22 0.58 0.04 8.33 3.45 0.8852.15 74.072801700011Agriculture Production - Crops(Fertilizer Application)0.000.00 0.000.000.000.00 0.002801700012Agriculture Production - Crops(Fertilizer Application)0.250.00 0.010.000.240.00 0.252801700013Agriculture Production - Crops(Fertilizer Application)37.750.00 32.060.000.04 0.540.294.825.64 32.102801700014Agriculture Production - Crops(Fertilizer Application)1.630.00 0.650.000.000.980.98 0.652801700015Agriculture Production - Crops(Fertilizer Application)4.440.00 4.400.000.000.020.00 0.020.05 4.402801700099Agriculture Production - Crops(Fertilizer Application)20.901.35 4.062.533.91 1.41 0.312.49 0.09 0.00 0.36 4.28 0.09 0.029.04 11.852805001100 Agriculture Production - Livestock44.414.17 17.379.071.657.95 4.2112.15 32.262805001200 Agriculture Production - Livestock0.010.00 0.000.000.000.00 0.000.00 0.012805001300 Agriculture Production - Livestock33.783.11 12.956.761.236.36 3.379.73 24.052805002000 Agriculture Production - Livestock4.434.434.43 0.002805003100 Agriculture Production - Livestock282.6912.67 102.97 24.90 4.76114.52 22.88137.40 145.292805007100 Agriculture Production - Livestock2.720.241.600.870.87 1.852805007300 Agriculture Production - Livestock0.060.000.040.020.02 0.042805008100 Agriculture Production - Livestock0.040.000.020.010.01 0.032805008200 Agriculture Production - Livestock0.110.010.060.040.04 0.072805008300 Agriculture Production - Livestock0.020.000.010.010.01 0.012805009100 Agriculture Production - Livestock10.891.356.772.33 0.442.77 8.122805009200 Agriculture Production - Livestock2.990.22 1.100.42 1.251.67 1.322805009300 Agriculture Production - Livestock8.561.09 5.451.90 0.122.02 6.542805010100 Agriculture Production - Livestock74.8874.82 0.050.010.01 74.872805010200 Agriculture Production - Livestock12.1412.13 0.010.000.00 12.142805010300 Agriculture Production - Livestock60.2060.16 0.040.010.01 60.192805018000 Agriculture Production - Livestock12.905.116.341.451.45 11.442805019100 Agriculture Production - Livestock18.8017.261.180.350.35 18.442805019200 Agriculture Production - Livestock52.5048.20 3.301.001.00 51.50C1-102002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaAmmonia (NH3)Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD Total2805019300 Agriculture Production - Livestock5.084.66 0.320.090.09 4.982805021100 Agriculture Production - Livestock223.05203.17 13.912.67 3.315.98 217.072805021200 Agriculture Production - Livestock242.00220.16 15.073.03 3.746.77 235.232805021300 Agriculture Production - Livestock490.85448.70 30.715.12 6.3211.44 479.412805022100 Agriculture Production - Livestock24.3021.951.500.37 0.480.85 23.452805022200 Agriculture Production - Livestock1.000.900.060.02 0.020.04 0.962805022300 Agriculture Production - Livestock13.7112.380.850.21 0.270.48 13.232805023100 Agriculture Production - Livestock183.79153.64 10.528.75 10.8819.64 164.152805023200 Agriculture Production - Livestock3.582.330.160.49 0.601.09 2.492805023300 Agriculture Production - Livestock229.82199.77 13.677.30 9.0716.37 213.442805025000 Agriculture Production - Livestock15.446.292.833.740.631.77 0.182.58 12.862805030000 Agriculture Production - Livestock11.063.333.363.150.09 1.144.37 6.682805030007 Agriculture Production - Livestock0.200.010.06 0.130.20 0.002805030008 Agriculture Production - Livestock83.210.0183.05 0.1583.21 0.002805035000 Agriculture Production - Livestock221.4818.77 76.3359.76 29.938.209.32 19.1736.70 184.792805039100 Agriculture Production - Livestock2.192.190.00 2.192805039200 Agriculture Production - Livestock5.085.080.00 5.082805039300 Agriculture Production - Livestock0.480.480.00 0.482805040000 Agriculture Production - Livestock15.180.64 5.421.491.250.465.50 0.426.37 8.812805045000 Agriculture Production - Livestock13.731.55 1.551.551.550.090.00 7.427.51 6.222805047100 Agriculture Production - Livestock7.497.490.00 7.492805047300 Agriculture Production - Livestock4.214.210.00 4.212805053100 Agriculture Production - Livestock0.070.070.00 0.072810001000Forest Fires0.020.020.02 0.002810015000 Slash/Prescribed Burning0.060.010.050.06 0.002002 Area Source Total3670.1412.59 93.78 2593.09263.18 163.79 13.515.12 66.86 6.31 0.59 327.58 115.92 6.93 0.90 543.72 3113.84Nonroad Model SourceAgricultural Equipment0.00 0.00Airport Equipment0.00 0.00Commercial Equipment0.00 0.00Construction and Mining Equipmen0.00 0.00Industrial Equipmen0.00 0.00Lawn and Garden Equipment (Com)0.00 0.00Lawn and Garden Equipment (Res0.00 0.00Logging Equipment0.00 0.00Pleasure Craft0.00 0.00Railroad Equipment0.00 0.00Recreational Equipment0.00 0.00Nonroad Model Source0.000.00 0.000.000.00 0.00 0.000.000.00 0.00 0.00 0.000.00 0.00 0.00 0.00 0.00Other Nonroad Sources2275001000 Military Aviation0.000.00 0.002275020000 Commercial Aviation0.000.00 0.002275050000 General Aviation0.000.00 0.002275060000 Air Taxi0.000.00 0.002275070000 Aircraft Auxiliary Power Units0.000.00 0.002280002010 Commercial Marine Vessels0.000.00 0.002285002005 Railroad Locomotives0.000.00 0.002285002006 Railroad Locomotives0.000.00 0.002285002008 Railroad Locomotives0.000.00 0.002285002009 Railroad Locomotives0.000.00 0.002285002010 Railroad Locomotives0.000.00 0.00Other Nonroad Sources Total0.000.00 0.000.000.00 0.00 0.000.000.00 0.00 0.00 0.000.00 0.00 0.000.00 0.002002 Nonroad Source Total0.000.00 0.000.000.00 0.00 0.000.000.00 0.00 0.00 0.000.00 0.00 0.000.00 0.00C1-112002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaPM10Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD TotalArea Source2102002000 Coal Consumption937.0795.01 59.63 465.24 4.44 9.51 150.97 94.15 54.44 3.68 937.07 0.002102004000 Fuel Oil Consumption16.421.081.312.12 2.051.000.634.89 0.05 0.10 1.590.99 0.57 0.049.86 6.562102005000 Fuel Oil Consumption34.486.367.687.46 7.260.580.362.84 0.03 0.06 0.920.57 0.33 0.025.71 28.772102006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption225.1822.83 14.33 111.81 1.06 2.28 36.28 22.63 13.08 0.88 225.18 0.002102007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption18.981.921.219.43 0.09 0.19 3.061.91 1.10 0.07 18.98 0.002103002000 Coal Consumption41.91 13.323.607.2110.81 3.600.530.321.80 0.06 0.05 0.260.27 0.07 0.013.37 25.222103004000 Fuel Oil Consumption208.99 50.154.305.188.35 8.1320.90 12.52 70.86 2.52 2.03 10.40 10.71 2.69 0.26 132.89 25.962103005000 Fuel Oil Consumption26.030.740.900.90 0.873.562.13 12.06 0.43 0.35 1.771.82 0.46 0.04 22.62 3.412103006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption197.86 66.800.841.8222.73 21.8413.187.90 44.69 1.59 1.28 6.566.76 1.70 0.17 83.83 47.232103007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption0.490.070.100.15 0.170.00 0.492103011000 Fuel Oil Consumption1.850.310.370.59 0.570.00 1.852104002000 Coal Consumption28.123.620.000.500.50 0.532.321.58 12.08 0.27 0.13 2.383.67 0.42 0.13 22.98 1.522104004000 Fuel Oil Consumption134.74 10.407.569.1214.72 14.327.945.42 41.22 0.95 0.43 8.14 12.55 1.47 0.50 78.62 45.732104006000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption457.44 58.662.485.5267.34 59.7726.63 18.19 138.25 3.19 1.45 27.30 42.09 4.92 1.67 263.69 135.092104007000 Natural Gas and Liquefied PetroleumGas (LPG) Consumption2.820.020.390.580.87 0.960.00 2.802104008001 Other Fuels Consumption (ResidentialWood Burning)301.44 13.1418.73 42.6161.73 91.6214.312.00 36.47 2.20 1.16 4.829.44 2.37 0.84 73.61 214.692104008002 Other Fuels Consumption (ResidentialWood Burning)711.00 39.3673.57 10.30 398.33 11.32 5.95 52.56 103.14 12.16 4.31 671.64 0.002104008003 Other Fuels Consumption (ResidentialWood Burning)28.221.562.920.41 15.81 0.45 0.24 2.094.09 0.48 0.17 26.66 0.002104008004 Other Fuels Consumption (ResidentialWood Burning)11.860.661.230.176.64 0.19 0.10 0.881.72 0.20 0.07 11.20 0.002104008010 Other Fuels Consumption (ResidentialWood Burning)1973.22 28.1453.03 104.87233.71 382.8363.758.92 768.39 9.81 5.16 101.39 198.96 10.53 3.74 1170.65 774.432104008030 Other Fuels Consumption (ResidentialWood Burning)51.290.472.144.249.45 15.481.070.15 12.81 0.16 0.08 1.693.31 0.17 0.06 19.50 31.322104008050 Other Fuels Consumption (ResidentialWood Burning)114.921.124.619.1220.32 33.292.530.36 30.50 0.39 0.20 4.027.89 0.42 0.15 46.46 67.342104008053Other Fuels Consumption (ResidentialWood Burning)4.831.112.570.49 0.664.832104008060Other Fuels Consumption (ResidentialWood Burning)25.775.94 13.85 2.54 3.4425.772104008070 Other Fuels Consumption (ResidentialWood Burning; Outdoor Equipment)226.6917.06 28.3695.14 86.130.00 226.692104009000Other Fuels Consumption (ResidentialFirelog)30.002.625.958.63 12.8030.002104011000 Fuel Oil Consumption 3.220.530.641.04 1.010.00 3.222199008000Stationary Source Fuel Combustion(Wood Burning)6.011.383.230.59 0.806.012294000000 Mobile: All Paved Roads - Total:Fugitives10960.551008.22 1005.07 1409.88 428.86519.49 344.37 3622.12 63.92 16.53 1145.23 1303.70 82.48 10.68 7108.52 3852.032296000000 Mobile: All Unpaved Roads - Total:Fugitives3521.3725.13 122.6970.00 62.10730.41981.79 1529.253241.45 279.922302002100 Commercial Cooking81.52 26.902.805.8424.72 21.270.00 54.632302002200 Commercial Cooking566.37 195.1919.02 35.94179.52 136.690.00 371.182302003100Industrial Processes (CommercialCooking - Flat Griddle Frying)95.384.879.5446.53 34.4495.382302003201Industrial Processes (CommercialCooking - Clamshell Griddle Frying)7.010.35 0.68 3.15 2.837.012311010000 Total Residential Construction: SIC 15- 17940.4260.98 64.03157.30 108.094.08 24.39 130.34 1.88 0.05 297.92 83.81 1.66 5.89 550.02 390.402311020000 TotalIndustrial/Commercial/InstitutionalConstruction: SIC 15 - 177385.8967.75 289.77 2531.17 1450.46160.68 156.65 1458.97 56.37 105.61 811.47 102.40 126.79 67.80 3046.74 4339.152311030000 Total Road Construction: SIC 15 - 17 12443.84969.49 1040.72 3306.16 1690.3439.82 185.00 1183.87 21.68 0.55 3098.71 890.83 16.67 5437.13 7006.712325000000 Industrial Processes: Mining andQuarrying: SIC 14 - All Processes1469.76244.96 244.96 244.96 244.96 244.96 244.96 1469.76 0.002401001000 Surface Coating - Architectural 2157.59 2157.590.00 0.002401005000 Surface Coating - AutomobileRefinishing6.68 6.680.00 0.002601000000 On-Site Incineration 25.950.00 11.9012.50 1.550.00 25.952601010000 On-Site Incineration 113.5611.52 7.22 56.46 0.49 1.14 18.29 11.42 6.58 0.44 113.56 0.002601020000 On-Site Incineration 367.4537.12 25.34 192.68 4.45 2.00 38.04 58.66 6.84 2.32 367.45 0.002610000100 Open Burning 24.764.728.234.89 0.176.756.75 18.012610000400 Open Burning18.324.077.094.22 0.002.942.94 15.382610000500 Open Burning6293.71250.37 571.01 1632.54 613.1767.48 125.17 1539.7534.14 741.77 642.88 47.19 28.24 3226.62 3067.09C1-122002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment AreaPM10Area and Nonroad Source Emissions by Jurisdiction (tons/year)SCC Code Category NameNAA TotalDistrict ofColumbiaCharlesCountyFrederickCountyMontgomeryCountyPrinceGeorge'sCountyArlingtonCountyAlexandriaCity Fairfax County Fairfax CityFalls ChurchCityLoudounCountyPrinceWilliamCountyManassasCityManassasPark City VA Total MD Total2610030000 Open Burning36.4711.98 19.68 4.80 0.000.00 36.472801000003 Crops Tilling2877.38311.40 1166.24406.54 140.3915.55754.68 82.58852.81 2024.572805001000 Livestock, beef cattle, feedlots, DustKicked-up by Hooves426.7412.552.497.84 3.8833.72303.41 62.85399.98 26.762810001000 Forest Fires0.530.000.000.00 0.000.090.440.53 0.002810015000 Slash/Prescribed Burning130.440.011.770.000.00 0.650.010.01 36.0146.82 45.11 0.04 0.02 128.02 2.422810030000 Structure Fires41.806.681.041.381.92 9.665.243.423.93 0.06 0.28 0.347.35 0.28 0.23 21.13 13.992810050000 Motor Vehicle Fires23.861.101.444.09 17.230.00 23.862002 Area Source Total55838.21 2680.452892.48 4619.47 10377.945469.941446.18 1263.0611432.89 433.01 191.058910.29 5592.91 396.11 132.43 29797.9323359.83Nonroad Model SourceAgricultural Equipment60.930.00 4.82 25.64 9.32 3.65 0.00 0.00 0.42 0.00 0.00 13.62 3.46 0.00 0.0017.50 43.42Airport Equipment22.220.00 0.00 0.00 0.01 0.00 10.60 0.00 5.80 0.00 0.00 5.80 0.00 0.01 0.0022.21 0.01Commercial Equipment106.289.15 2.05 6.31 23.76 18.15 2.56 3.32 27.40 1.56 0.51 5.37 4.15 1.46 0.5446.87 50.27Construction and Mining Equipmen1384.24250.71 51.85 62.23 175.09 199.96 123.73 0.00 199.17 0.00 0.00 191.10 130.39 0.00 0.00644.40 489.13Industrial Equipmen120.0714.22 2.879.2324.61 20.74 3.473.15 24.57 0.59 0.34 6.876.75 2.31 0.3348.40 57.45Lawn and Garden Equipment (Com)580.131.92 6.27 38.11 150.50 73.53 6.97 9.25 155.35 5.48 3.74 82.07 42.00 1.42 3.54309.81 268.40Lawn and Garden Equipment (Res80.8912.30 2.103.5215.57 13.94 4.143.01 16.80 0.35 0.21 3.354.87 0.56 0.1633.45 35.13Logging Equipment2.680.00 1.22 0.17 0.13 0.50 0.00 0.00 0.08 0.00 0.00 0.50 0.08 0.00 0.000.66 2.02Pleasure Craft45.368.34 17.90 2.01 5.03 5.70 0.00 0.00 3.40 0.00 0.00 0.42 2.57 0.00 0.006.38 30.63Railroad Equipment2.710.17 0.01 0.53 0.34 0.22 0.07 0.22 0.43 0.00 0.00 0.00 0.57 0.10 0.051.44 1.10Recreational Equipment34.021.72 4.60 4.71 9.39 4.68 0.03 0.00 3.86 0.02 0.00 1.28 3.73 0.00 0.008.93 23.38Nonroad Model Source2439.53 298.52 93.68 152.44413.76 341.07 151.59 18.94437.26 8.01 4.81 310.38 198.59 5.85 4.63 1140.061000.95Other Nonroad Sources2275001000 Military Aviation53.327.622.769.9723.609.3832.98 20.342275020000 Commercial Aviation32.409.1011.6511.6532.40 0.002275050000 General Aviation11.120.131.550.73 0.843.340.52 4.027.88 3.242275060000 Air Taxi0.200.000.020.06 0.010.020.100.12 0.082275070000 Aircraft Auxiliary Power Units0.110.010.050.050.11 0.002285002005 Railroad Locomotives157.8210.238.03 6.330.40 17.9257.05 44.82 13.03 133.22 24.602285002006 Railroad Locomotives2.052.050.00 0.002285002008 Railroad Locomotives2.112.110.00 0.002285002009 Railroad Locomotives1.721.720.00 0.002285002010 Railroad Locomotives48.155.786.751.690.104.5614.53 11.41 3.33 33.93 8.44Other Nonroad Sources Total309.00 11.66 7.74 21.3010.50 17.15 9.110.50 57.78 0.00 0.00 15.06 81.48 60.35 16.36 240.6456.702002 Nonroad Source Total2748.53 310.18 101.42 173.75424.26 358.21 160.70 19.44495.048.01 4.81 325.44280.07 66.20 20.99 1380.70 1057.65C1-13

# Attachment D1

BY 2002 Onroad Mobile Source Emissions Inventory and Documentation

D1-1

### On-Road Mobile Emissions Analysis – Me tropolitan Washington, DC-MD-VA PM2.5 Nonattainment Area

This appendix provides details of the MOBILE6.2.03 model input assu mptions that were used to develop the base year 2002 annual onroad mob ile emissions for PM2.5-Direct, NOx, SO2, VOC, NH3, and PM10 for the Washington, DC-MD-VA PM2.5 nonattainment area along with the
summaries of these emissions and vehicle miles of travel by vehicle, road and emission types. MOBILE6 input assumptions are presented in th e following section which is then followed by a memorandum describing the procedures followed to convert the base year 2002 onroad mobiles
emission inventories to EPA’s National Emi ssion Inventory (NEI) I nput Format (NIF3.0). MOBILE6 input and output files used in the de velopment of the base year 2002 annual onroad mobile emission analysis are availa ble in an electronic format as A ttachment D2. The NIF3.0 file is
available in an electronic format as Attachment D3.

Separate sets of input files were created to m odel emission factors corres ponding to travel in the COG region 1) on network and local roadways, 2) during auto access to transit, and 3) by diesel
transit and school buses. The data included in each of th ese inputs is discussed separately below.

A. MOBILE6 NETWORK AND LOCAL INPUT FILE SETUP

The MOBILE6 input files representing the ne twork and local roadway conditions include formatting commands, one-time inputs, and scen ario data. The one-time inputs include countyspecific registration distributions by age, county-specific diesel sa les fractions by model year, and inspection and maintena nce (I/M) programs.

1. MOBILE6 Run Data

Separate MOBILE6 input files were created for each of the following jurisdictions within the COG region: Washington, DC; Calvert County, Charle s County, Frederick County, Montgomery County, and Prince George’s County, MD; and Alexa ndria, Arlington County, Fairfax County, Loudoun County, and Prince William County, Stafford County, VA. Though MOBI LE6 inputs files for Calvert and Stafford counties were prepared as th ey are part of the travel demand modeling area, input data used for these counties are not being presented here as they are not part of the PM2.5
nonattainm ent area and their emissions were not counted. The MOBILE6 header and run
information common to all of these areas is shown in Table 1.

2. MOBILE6 Scenario Data

The MOBILE6 network/local input files each contain a number of different scenarios. Table 2 summarizes the scenario commands and inputs. Depending upon the input file purpose (network or auto access), a number of different scen arios are modeled in a specified order. Table 3 shows the order of the scenario s for modeling VOC and NOx emissi on factors for network, local, and auto-access. Table 4 shows the same information for modeling PM2.5, PM10, NH3 and SO2 emission factors. Fore each of these sets of inputs, all scenario s model the same ambient conditions (e.g., temperature, humidity, fuel parameters) for a given jurisdiction. Th e differences from one scenario to the next are the speeds, road types, operating modes, and, sometimes, the VMT mix

D1-2being modeled. As shown in Table 5, the scenario s for the annual inputs include three sets of seasonal inputs for each of the speeds, road t ypes, and operating mode combinations that are modeled. Annual onroad mobile emissions were developed base d on a three season approach. These three seasons are - Winter (January-April ), Summer (May-September), and Fall (OctoberDecember). Emissions for these three seasons were added together to develop an annual inventory for the metropolitan Washington region. The three se ts of seasonal inputs re present the differences in temperature, humidity, and fuel parameters as sociated with Winter, Summer, or Fall. The temperature and humidity inputs are the same regionw ide, while the fuel input parameters vary by region. Table 5 summarizes the various input para meters and how they were matched by season in the annual input files.

3. MWCOG Data Input Parameters

The trip length distribution da ta referenced in Table 1 is shown in Table 6. These data, developed by COG/TPB staff based on the MWCOG Version 2 model, were presented at the May 1, 2002 MOBILE6 Task Force meeting. This same trip length distribution was applied in 2002 input files.

Because the MWCOG region is in the Northeast Ozone Transport Region, the region follows a different implementation schedule for the National Low Emission Vehicle (NLEV) program than that included in the MOBILE6 default. Table 7 shows the LEV implementation schedule for the MWCOG region. This information is accessed through use of the 94+ LDG IMP command.

As shown in Table 3, each scenario is mode led with an operating mode input of either stabilized, hot start, or cold start. The input s used to model each of these operating modes are
shown in Table 8.

The hourly average temperatures modeled for the three seasons are shown in Table 9. Table 10 shows the hourly average humidity inputs for these seasons. All jurisdictions were modeled with the same temperature a nd humidity inputs.

The fuel inputs modeled in 2002 are shown in Tables 11, 12, 13, and 14. These include the gasoline and diesel sulfur content inputs, gasoli ne Reid vapor pressure inputs, and gasoline oxygen content inputs. These fuel inputs except for diesel sulfur content ar e used to define the reformulated gasoline program in place in the Washington area in 2002.

a. I/M and Anti-Tampering Program Inputs

Each jurisdiction provided I/M program input s and ATP inputs in MOBILE6 format for 2002. Table 15 shows the I/M program parameters fo r DC. As shown in this table, a separate cutpoint file is needed for the ve hicles included in the IM240 test. This cutpoint file is shown in Table 16. The I/M program parameters for Ma ryland are shown in Table 17. As with DC, a cutpoint file is needed to model the IM240 test . The Maryland cutpoints are the same as those shown in Table 16. Table 18 shows the I/M program parameters for Virginia. The ATP inputs for all three jurisdictions are shown in Table 19.

b. Registration Distributions

County-specific registration dist ributions were used in the MOBILE6 input files. These distributions show the fraction of registered vehicles from ages 1 through 25 for each of 16

D1-3MOBILE6 vehicle types. The registration dist ribution inputs used fo r 2002 are provided in Attachment 1. Below is a detailed explanation of how these distributio ns were derived for 2002. For the 2002 emission factor modeling, DC, Virginia, and Maryland obtained the most recent registration data available. Registration distributions input to MOBILE6 are assumed to represent July 1 registration data. Both Maryland and Virginia were able to obtain registration data sets extracted on July 1, 2002. DC ’s registration data set was ex tracted on August 26, 2002. Thus, an adjustment was made to the first model year of all vehicle types in the DC registration data. The number of registered LDVs and LDTs in the firs t model year was multiplied by 9/11. This fraction represents 9 months from the beginning of the 2002 model year (assumed to be October 1, 2001) as of July 1, 2002, but 11 months of registered vehicl es in the DC database for the 2002 model year. Similarly, the number of HDVs and MCs registered in DC in the 2002 model year were multiplied by 6/8. This represents six months from the begi nning of the model year (starts Jan 1) to July 1, 2002, but 8 months of registered HDVs and MCs in the DC database for the 2002 model year. For Maryland, Virginia, and DC, any 2003 model year ve hicles were included with the 2002 model year as the first model year in the registration data.

For each county in Virginia and Maryland, th e 2002 registration data included counts of registered vehicles by the MOBILE5 vehicle cat egories. For use with MOBILE6, the LDGV and LDDV vehicle counts by model year were group ed together and the fraction by model year
calculated. This was then used as the MOBILE6 LDV registration distri bution. The LDGT1 and LDDT vehicle counts by model y ear were grouped together to create the MOBILE6 LDT1 and LDT2 registration distributions. The MOBILE5 L DGT2 vehicle counts were converted to fractions by model year and applied to the MOBILE6 LDT3 and LDT4 vehicle categories. The HDGV and HDDV vehicle counts by model year were grouped together to crea te the registration distribution for the MOBILE HDV categories, except the MOBILE6 HDBT (transit bus) category. The MOBILE6 HDBT registration distribu tion was calculated from the HDDV data only. DC did not have breakdowns of the vehicle registrations by gasoline and diesel. Thus, the MOBILE6 default diesel sales fractions by model year DC HDV data were applie d to obtain the MOBILE6 HDBT registration distribution.

c. Diesel Sales Fractions

The diesel sales fractions i nput to MOBILE6 are specific to the calendar year being modeled. The MOBILE6 diesel sales frac tions for 2002 are shown in Attachment 2.

Diesel sales fractions were de veloped for each of the Maryland and Virginia counties based on 2002 year of analysis. The LDV diesel sale s fractions were calculated by model year by dividing the LDDV registrations by the total of the LDGV plus LDDV registrations for each model year. Similarly, the LDT diesel sales fraction was calculated by m odel year by dividing the LDDT registrations by the total of the MOBILE5 LDGT1 plus LDDT registrations for each model year. These diesel sales fractions were applied to the MOBILE6 LDT1 and LDT2 categories. The MOBILE6 defaults for a 2002 calendar year are used fo r the District as well as for all of the heavy duty categories for Maryland and Virginia, since th ese sales fractions vary significantly by the MOBILE6 weight classes and the registration data for these Stat es is not broken down by weight class. Appendix 2 shows the resu lting diesel sales fractions, w ith the defaults shown for the District, and only the locally-derived LDV and LD T1/2 data shown for Maryland and Virginia.

D1-4d. VMT Mix Fractions

VMT mix fractions by vehicle type for each jurisdiction in 2002 was based on an estimate of the overall non-bus HDV VMT fraction as output fr om COG’s travel demand model combined with county-specific registration distri butions and diesel sales fracti ons and MOBILE6 default data on the VMT mix by vehicle type within the heavy and light-duty vehicle ca tegories. The 2002 HDVs (excluding buses) account for 7.94 percent of th e network VMT and 1.73 percent of local road VMT. The LDV + MC group accounts for 92.06 percent of the total network VMT and 98.27 percent of the local ro ad total VMT in 2002.

A set of MOBILE6 input files was first prepared using each county’s registration distribution and the corresponding di esel sales fraction data for that county. These input files included no VMT mix information, and were run for a July evaluation month for a sample scenario. These MOBILE6 input files were run through MOBI LE6 and the database outputs for these inputs
were obtained. The MOBILE6 data base output format gives VMT fractions for each of the 28 MOBILE6 vehicle types, based on th e registration distribution and dies el sales fractions supplied in the input file, as well as the MOBILE6 defa ult VMT mix by vehicle category for 2002. Next, following the guidance included in EPA’s MOBILE6 technical guidance document (section 4.1.4),
the total VMT fractions in the LDV+MC and the HDV groups in the MO BILE6 database output files were separately totaled. Following the MO BILE6 technical guidance, the LDV and MC VMT fractions were multiplied by the ratio of COG’s estimated LDV + MC VMT fraction to the default
MOBILE6 LDV + MC VMT fractio n. The HDV VMT fractions, excluding the bus fractions (which were multiplied by 0), were multiplied th e ratio of COG’s estimat ed HDV VMT fraction to the default MOBILE6 default non-bus HDV VMT fraction. Finally, the new VMT mixes were allocated to the 16 vehicle types required when using VMT mix as an input to MOBILE6. These VMT mixes were then used in the MOBILE6 input files. This procedure was followed separately
for network road and local roads for 2002 for eac h county. Attachment 3 shows the resulting VMT mix fractions for 2002 network roads, local roads, and auto access to transit.

B. MOBILE6 AUTO ACCESS TO TRANSIT INPUT FILE SETUP AND PROCESSING

A separate set of MOBILE6 input files was cr eated for use in off-network calculations of emissions resulting from auto acc ess to transit. These input files were identical to the corresponding MOBILE6 netw ork/local input files, with the exception of the VMT mixes used. The same procedure was used for developing the VM T mixes to represent auto access to transit. However, as this analysis pert ains to vehicles accessing the tr ansit system, the vehicle types generating the VMT are believed to be strictly commuting vehicles . Therefore, the HDV fraction was assumed to be 0 percent in 2002, with th e LDV + MC accounting for 100 percent of the vehicles accessing the transit sy stem. The resulting VMT mix fr actions used for 2002 are reported
in Attachment 3.

The resulting MOBILE6 output file s representing auto access to transit were post-processed. Running VOC emission factors by speed were estimated by averaging the tota l exhaust plus running loss plus crankcase VOC emission factors expresse d in grams per mile over the 12 jurisdictions. Similarly, average NOx exhaust emission factor s were estimated at each speed over the 12 jurisdictions. The composite hot and cold st art VOC and NOx emission rates were calculated based on the start-up portion of the emission factors from the cold start and hot start scenarios in

D1-5grams per mile, combined with data from the MO BILE6 database output on the average daily miles driven by vehicle type, and the aver age trip starts made per day. On ce these values were calculated for each county, an average hot start and cold start emission factor was estimated over the 12- county region.

Start-up Rate (gm/trip) = (LDGV ef * LDGV_M / LDGV_S * LDGV_APCT) + (LDGT12 ef * LDGT12_M / LDGT12_S * LDGT12_APCT) + (LDGT34 ef * LDGT34_M / LDGT34_S * LDGT34_APCT) + (LDDV ef * LDDV_M / LDDV_S * LDDV_APCT) + (LDDT ef * LDDT_M / LDDT_S * LDDT_APCT) + (MC ef * MC_M / MC_S * MC_APCT)

Where: LDGV ef, ..., MC ef = vehicle-specific start-up emission factor (gm/mi) taken from the MOBILE6 database output LDGV_APCT,..., MC_APCT = vehicle-specific proportion of VMT of the total (gas & diesel) vehicle VMT LDGV_M,..., MC_M = vehicle- specific average da ily miles driven LDGV_T,..., MC_S = vehicle-spec ific average trip st arts made per day

C. MOBILE6 DIESEL SCHOOL BUS A ND DIESEL TRANSIT BUS INPUT FILE SETUP

Separate MOBILE6 files were set up to mode l diesel school bus and diesel transit bus emission factors. These input file s were set up on a regional rath er than county basis, with one input file per year for diesel schoo l buses and one input file per year for diesel transit buses. Based on the October 10, 2002 memo prepared by C OG DTP staff, a 2002 MOBILE6 registration distribution was developed for the school bus analysis by using the first 16 years of the default MOBILE6 HDBS registration distribu tion and renormalizing these data over these 16 years (i.e., zeroing out years 17 through 25). Th e registration distribution used to model diesel transit buses was based on the regional total fleet distribution survey data provided by COG DTP staff. The 2002 school bus and transit bus RDTs are also provi ded in Attachment 1. For the 2002 school bus MOBILE6 input files, the VMT mix in all scenar ios was set to 1 for the HDBS category and 0 for all other categories. For the 2002 transit bus MO BILE6 input files, the VM T mix in all scenarios was set to 1 for the HDBT category and 0 for all other categories. These VMT mix fractions are
shown in Attachment 3. In the MOBILE6 school bus input file, the diesel sa les fractions for all 25 years for the HDBS category were set to 1. The MO BILE6 default diesel sale s fractions were used in the transit bus input file. These defau lts are also 1 for the entire HDBT category.

Each of the MOBILE6 bus input files was m odeled with 201 scenarios for VOC and NOx. The first 195 scenarios apply to ‘Arterial’ roadway type with an average speed of 1 through 65 mph for three seasons. (The arterial and non-ramp emi ssion factors under these condi tions are identical at the same speed.) Scenarios 196 through 198 model freeway ramps at a fixed speed of 34.6 mph for
three seasons. Scenario s 199 through 201 model local roads at a fixed speed of 12.9 mph for three seasons. All scenario use the stabilized operati ng mode inputs and the same ambient and fuel

D1-6conditions as included in the ne twork/local MOBILE6 i nput files. These s cenarios are summarized in Table 20. Each of the MOBILE6 bus input files was modeled with 3 scenarios pertaining to three seasons for PM2.5, PM10, NH3, and SO2. All 3 scenario apply to ‘Arterial’ roadway type with a fixed speed of 35 mph and use the stabilized opera ting mode inputs and the same ambient and fuel
conditions as included in the ne twork/local MOBILE6 i nput files. These s cenarios are summarized
in Table 21.

Once these MOBILE6 bus input files were run through MOBILE6, the school bus and
transit bus emission factors were extracted from th e corresponding output files. No other emission factors from these output files were used.

D1-7Table 1 MOBILE6 Run Information Common to All MOBILE6 Input Files

Command Input Comment
RUN DATA Marks end of header section and beginning of Run section of input file
EXPRESS HC AS VOC Directs MOBILE6 to report HC in terms of volatile organic compounds (Not applicable to PM2.5/PM10 Input Files)
EXPAND EVAPORATIVE Display all ev aporative emission types in descriptive output file (Not applicable to PM2.5/PM10 Input Files)
EXPAND EXHAUST Display start, running, and total exhaust emission factors in descriptive output file (Not applicable to PM2.5/PM10 Input Files)
PARTICULATES Applicable only to PM2.5/PM10 Input Files

NO REFUELING Exclude refueling emissions from all emission factors

REBUILD EFFECTS 0.11 (in DC and MD) 0.25 (in VA) 0.18 (in regional bus files) NOx Rebuild Program effectiveness rate at reducing HDDV NOx off-cycle emissions through the EPA Rebuild Mitigation program--applied to HDDV classes 3 through 8 (MOBILE6 default is 0.90)
WE DA TRI LEN DI WeekTLD2.WDT Reads weekday trip length percentages from specified file (see Table 2)

FUEL PROGRAM 4 Specifies sulfur content of fuel. See Table 12 for inputs. (Sulfur inputs are specified at the scenario level for the annual input files.)
OXYGENATED FUELS See Table 14 Specifie s oxygen content input parameters for reformulated gasoline. (Oxygenated fuel inputs are specified at the scenario level for the annual input files.)
94+ LDG IMP NLEVNE.D Specifies that LEV implementation schedule should be read from specified file (see Table 7)

VMT FRACTIONS For Auto Access to Transit input files only (VMT fractions are specified at the scenario level in the Network input files.)
REG DIST Varies by county Registration distribution data (see Appendix 1)

ANTI-TAMP PROG Varies by jurisdiction See Table 19

I/M PROGRAM Varies by jurisdiction See Tables 15-18

DIESEL FRACTIONS Varies by county See Appendix 2

HOURLY TEMPERATURES Hourly temperature values are provided in Table 10. (Hourly temperatures are specified at the scenario level for the annual input files.)
FUEL RVP See Table 13 Gasoline Reid vapor pressure. (RVP is specified at the scenario level for the annual input files.)

D1-8Table 2 MOBILE6 Scenario Data Inputs

Command Input Comment

CALENDAR YEAR 2002/2003 2002 (Winter & Summer); 2003 (Fall)

EVALUATION MONTH 1/7 1 - January (Winter & Fall); 7 - July (Summer)*

ALTITUDE 1 Low altitude area

HOURLY TEMPERATURES Hourly temperature values See Table 10

FUEL RVP See Table 13 PARTICLE SIZE 2.5/10 Applicable only to PM2.5/PM10 Input Files
PARTICULATE EF Applicable only to PM2.5/PM10 Input Files
DIESEL SULFUR See Table 11 Applicable only to PM2.5/PM10 Input Files

RELATIVE HUMIDITY Hourly humidity values See Table 11

BAROMETRIC PRES 29.79 Season average barometric pressure in inches of mercury

AVERAGE SPEED varies See Tables 3-5.

VMT BY FACILITY varies See Tables 3-5.

SOAK DISTRIBUTION varies See Tables 3-5.

FUEL PROGRAM 4 Sulfur inputs. See Table 12.

OXYGENATED FUELS See Table 14

VMT FRACTIONS varies See Tables 3-5.

Notes:

* - Fall season 2002 modeled as Winter season 2003 as the fleet is si milar in characteristics to Winter 2003 as compared to Wi nter 2002.

Table 3 Summary of Scenarios Modeled in Each MOBILE6 Input File for Annual Network, Local, and Auto-Access Analyses for VOC and NOx

Scenario Number Operating Mode MOBILE6 Facility Type Speed VMT Mix Fractions Season Sequence*

1-195 Stabilized Arterial\Collectors 1-65 mph Network or Auto Access 1-3

196-390 Stabilized Freeways excluding Ramps 1-65 mph Network or Auto Access 1-3

391-393 Stabilized Freeway Ramps 34.6 mph Network or Auto Access 1-3

Cold Local Roadways 12.9 mph Network or Auto Access Hot Local Roadways 12.9 mph Network or Auto Access 394-402

Stabilized Local Roadways 12.9 mph Local or Auto Access 1-3 (for each season, data sequence is as follows: cold, hot, then stabilized) 403-537** Stabilized Local Roadways as Arterial 1-45 mph Local 1-3

Notes: * - Season Codes: 1 – Winter (January-April); 2 – Summer (May -September); 3 – Fall (October-December). In Scenarios 1 through 393, each speed is modeled at the three sets of seasonal conditions prior to moving to the next speed. For Scenarios 394 throu gh 402, all three operating modes are first modeled for one season before moving on to the next season.

** - Scenarios 403 through 537 apply to the Network input files only. They are not used in the Auto Access to Transit input fi les.

D1-9Table 4 Summary of Scenarios Modeled in Each MOBILE6 Input File for Annual Network, Local, and Auto-Access Analyses for PM2.5, PM10, SO2, and NH3

Scenario Number Operating Mode MOBILE6 Facility Type Speed VMT Mix Fractions Season Sequence*

1-3 Stabilized Arterial\Collectors 35 mph Network or Auto Access 1-3

4-6** Stabilized Local Roadways as Arterial 35 mph Local 1-3

Notes: * - Season Codes: 1 – Winter (January-April); 2 – Summer (May-September); 3 – Fall (October-December).

** - Scenarios 4 through 6 apply to the Network input files only. They are not used in the Auto Access to Transit input files.

Table 5 MOBILE6 Inputs by Season

Season Calendar Year Evaluation Month Fuel Parameters VMT Fraction Winter (1) 2002 January S eason Average Winter 2002

Summer (2) 2002 July Season Average Summer 2002

Fall (3) 2003 January Season Average Winter 2003

Table 6 Trip Length Distributions

Length of Trip MWCOG Regional Percentage of VMT (%) MOBILE6 Default Percentage of VMT (%)

< 10 Minutes 10.86 6.74

11 - 20 Minutes 24.98 18.51

21 - 30 Minutes 19.71 16.78

31 - 40 Minutes 13.44 13.11

41 - 50 Minutes 9.29 8.33

> 50 Minutes 21.72 36.53

D1-10Table 7 LEV Implementation Schedule for MWCOG Region

Percentage of New Vehicle Sales

Model Year Tier 1 Transitional LEV LEV Tier 2

1999 30 40 30 0

2000 0 40 60 0

2001 0 0 100 0

2002 0 0 100 0

2003 0 0 100 0

2004+ 0 0 0 100

D1-11Table 8 Soak Distributions Stabilized Operating Mode

SOAK DISTRIBUTION
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*1.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*1.00

Cold Start Operating Mode

SOAK DISTRIBUTION
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*1.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*1.00 24*0.00 24*0.00

Hot Start Operating Mode

SOAK DISTRIBUTION
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*1.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*1.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00
24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00 24*0.00

D1-12Table 9 2002 Region-wide Hourly Temperature Inputs

Average Hourly Temperature (degrees Fahrenheit) Annual Modeling
Hour Winter Summer Fall
6:00 AM 36.9 65.7 42.4
7:00 AM 37.4 67.6 42.6
8:00 AM 38.9 69.9 43.9
9:00 AM 41.2 72.3 46.3
10:00 AM 43.4 74.5 48.8
11:00 AM 45.5 76.3 50.7
NOON 47.2 77.9 52.4
1:00 PM 48.6 78.9 53.6
2:00 PM 49.7 79.5 54.2
3:00 PM 50.2 79.5 54.3
4:00 PM 50.2 79.1 53.7
5:00 PM 49.3 78.4 52.0
6:00 PM 47.5 76.9 50.1
7:00 PM 45.8 74.7 48.8
8:00 PM 44.3 72.5 47.7
9:00 PM 43.1 71.2 46.9
10:00 PM 42.3 69.9 46.3
11:00 PM 41.4 68.9 45.6
MIDNIGHT 40.6 68.0 45.0
1:00 AM 39.8 67.3 44.6
2:00 AM 39.0 66.6 44.1
3:00 AM 38.2 66.2 43.6
4:00 AM 37.6 65.8 43.2
5:00 AM 37.2 65.3 42.7

D1-13Table 10 2002 Region-wide Hourly Relative Humidity Inputs

Average Hourly Relative Humidity (%)
Annual Modeling
Hour Winter Summer Fall
6:00 AM 72.4 85.1 78.9
7:00 AM 71.7 81.0 78.7
8:00 AM 68.2 76.0 77.1
9:00 AM 63.4 70.4 71.6
10:00 AM 58.1 65.1 65.8
11:00 AM 54.2 60.6 60.8
NOON 50.7 57.6 56.6
1:00 PM 48.1 55.2 53.9
2:00 PM 46.5 53.6 52.7
3:00 PM 45.5 53.6 52.6
4:00 PM 45.5 54.5 53.9
5:00 PM 47.1 55.9 57.2
6:00 PM 49.9 59.2 61.7
7:00 PM 53.4 64.2 65.1
8:00 PM 56.9 69.8 67.5
9:00 PM 59.4 73.5 70.4
10:00 PM 60.8 76.7 71.6
11:00 PM 63.0 79.2 73.4
MIDNIGHT 65.0 81.1 74.9
1:00 AM 66.5 82.5 75.8
2:00 AM 68.0 83.5 76.8
3:00 AM 69.3 84.3 78.1
4:00 AM 71.0 84.7 78.1
5:00 AM 72.0 85.5 79.1

D1-14Table 11 Gasoline Sulfur Inputs Modeled by Season in 2002

Gasoline Sulfur Content (ppm)

MD/VA Average DC Average Regionwide Maximum Bus Average

Year Winter Summer Fall Winter Summer Fall All Seasons Winter Fall Summer

2000 300 150 300 300 150 300 1000 300 150 300
2001 299 149 299 299 149 299 1000 299 149 299
2002 279 129 279 197 159 196.2 1000 270.80 132.00 270.72
2003 259 120 279 259 120 196.2 1000 270.80 132.00 270.72
2004 121 120 121 121 120 121 303 121 120 121
2005 92 90 92 92 90 92 303 92 90 92
2006 33 30 33 33 30 33 87 33 30 33
2007 33 30 33 33 30 33 87 33 30 33 2008 and later 30 30 30 30 30 30 80 30 30 30

Table 12 Diesel Sulfur Inputs M odeled by Season in 2002

Season VA MD DC Bus
Winter (1) 337.0 480.5 325.0 393.20 Summer (2) 351.8 476.0 327.8 399.08 Fall (3) 339.3 481.3 325.3 394.70

Table 13 Reid Vapor Pressure Values Modeled by Season for 2002 Analysis

Season VA RVP MD RVP DC RVP Bus RVP
Winter (1) 12.9 12.4 10.2 12.43 Summer (2) 6.7 6.9 6.8 6.79 Fall (3) 12.9 11.2 10.1 11.94

Table 14 Oxygenated Fuel Inputs by Season for 2002 Analysis

Season Ether Market Share (%) Ethanol Market Share (%) Ether Oxygen Content (% by Weight) Ethanol Oxygen Content (% by Weight) Winter/Fall 70 30 1.5 3.5

Summer 100 0 2.1 0

D1-15Table 15 2002 I/M Program Parameters for DC

Test Type IDLE IM240 FP & GC IDLE I/M Program Start Year 1983 1983 1999 1983 Test Frequency Biennial Biennial Biennial Biennial

Program Type T/O T/O T/O T/O

Model Years 1972-1983 1984-2050 1972-2050 1972-2050 Stringency Rate (%) 20 20 N/A 20 Compliance Rate (%) 96 96 96 96 Waiver Rate (%) 3 3 N/A 3

Exemption Age 25 25 25 25 Cutpoint File N/A DC.C02 N/A N/A

Vehicles Tested LDGV Yes Yes Yes No

LDGT1 Yes Yes Yes No

LDGT2 Yes Yes Yes No

LDGT3 Yes Yes Yes No

LDGT4 Yes Yes Yes No

HDGV2B No No No Yes

HDGV3 No No No Yes

HDGV4 No No No Yes

HDGV5 No No No Yes

HDGV6 No No No Yes

HDGV7 No No No No

HDGV8A No No No No

HDGV8B No No No No

GAS BUS No No No No

D1-16Table 16 IM240 Cutpoint File for DC (DC.C02) and Maryland (MD.C02)

I/M CUTPOINTS : * Block 1 (LDGV, Light LDGT1 (EPA LD 1)

0.800 0.800 0.800 0. 800 0.800 0.800 0.800 1.200 1.200 1.200

1.200 1.200 2.000 2. 000 2.000 2.000 2.000 2.000 2.000 2.000

2.000 2.000 2.200 2.000 2.000

15.000 15.000 15.000 15. 000 15.000 15.000 15.00 0 20.000 20.000 20.000

20.000 20.000 30.000 30. 000 30.000 30.000 30.00 0 30.000 30.000 30.000

30.000 30.000 30.000 30. 000 30.000

2.000 2.000 2.000 2. 000 2.000 2.000 2.000 2.500 2.500 2.500

2.500 2.500 3.000 3. 000 3.000 3.000 3.000 3.000 3.000 3.000

3.000 3.000 3.000 3.000 3.000 * Block 2 (Heavy LDGT1, Light LDGT2 (EPA LD2 & 3)

1.000 1.000 1.000 1. 000 1.000 1.000 1.000 2.400 2.400 2.400

2.400 2.400 3.200 3. 200 3.200 3.200 3.200 3.200 3.200 3.200

3.200 3.200 3.200 3.200 3.200

20.000 20.000 20.000 20. 000 20.000 20.000 20.00 0 60.000 60.000 60.000

60.000 60.000 80.000 80. 000 80.000 80.000 80.00 0 80.000 80.000 80.000

80.000 80.000 80.000 80. 000 80.000

2.500 2.500 2.500 2. 500 2.500 2.500 2.500 3.000 3.000 3.000

3.000 3.000 3.500 3. 500 3.500 7.000 7.000 7.000 7.000 7.000

7.000 7.000 7.000 7.000 7.000 * Block 3 (Heavy LDGT2 (EPA LD4)

2.400 2.400 2.400 2. 400 2.400 2.400 2.400 2.400 2.400 2.400

2.400 2.400 3.200 3. 200 3.200 3.200 3.200 3.200 3.200 3.200

3.200 3.200 3.200 3.200 3.200

60.000 60.000 60.000 60. 000 60.000 60.000 60.00 0 60.000 60.000 60.000

60.000 60.000 80.000 80. 000 80.000 80.000 80.00 0 80.000 80.000 80.000

80.000 80.000 80.000 80. 000 80.000

4.000 4.000 4.000 4. 000 4.000 4.000 4.000 4.500 4.500 4.500

4.500 4.500 5.000 5. 000 5.000 7.000 7.000 7.000 7.000 7.000

7.000 7.000 7.000 7.000 7.000 * Block 4 (HDGV)

2.400 2.400 2.400 2. 400 2.400 3.000 3.000 3.000 3.000 3.000

3.000 3.000 3.200 3. 200 3.200 3.200 5.000 5.000 6.000 6.000

6.000 6.000 6.000 6.000 6.000

60.000 60.000 60.000 60. 000 60.000 60.000 60.00 0 60.000 60.000 60.000

60.000 60.000 80.000 80. 000 80.000 80.000 80.00 0 80.000 100.000 100.000

100.000 100.000 100.000 100. 000 100.000

4.000 4.000 4.000 4. 000 4.000 6.000 6.000 6.000 6.000 6.000

6.000 6.000 8.000 8. 000 8.000 8.000 8.000 8.000 8.000 8.000

8.000 8.000 8.000 8.000 8.000

Note: The 1996 and later cutpoints for LDGVs and LDGT1s are below the minimum allowable cutpoints in MOBILE6. Therefore, MOBILE6 ov errides the 1996 and later cutpoints for LDGVs and LDGT1s with 0.80 grams/mile for HC, with 15.0 grams per mile for CO, and with 2.0 grams per mile for NOx.

D1-17Table 17 2002 I/M Program Parameters for Maryland

Test Type IDLE IDLE IM240 I/M Program Start Year: Montgomery, Prince George’s Counties Calvert, Charles, Frederick Counties 1984 1995 1984 1995 1984 1995 Test Frequency Biennial Biennial Biennial

Program Type T/O T/O T/O

Model Years 1977-1983 1977-2050 1984-2050 Stringency Rate (%) 20 20 20 Compliance Rate (%) 96 96 96 Waiver Rate (%) 11 and 15 11 and 15 11 and 15 Grace Period (years) 2 2 2 Cutpoint File N/A N/A MD.C02 Vehicle Types LDGV Yes No Yes
LDGT1 Yes No Yes
LDGT2 Yes No Yes
LDGT3 Yes No Yes
LDGT4 Yes No Yes
HDGV2B Yes No Yes

HDGV3 No Yes No
HDGV4 No Yes No
HDGV5 No Yes No
HDGV6 No Yes No
HDGV7 No No No
HDGV8A No No No
HDGV8B No No No
GAS BUS No No No

D1-18Table 18 2002 I/M Program Parameters for Virginia

Test Type 2500/IDLE 2500/IDLE ASM 2525/5015 PHASE-IN GC
I/M Program Start Year* 1983 1983 1983 1998
Test Frequency Biennial Biennial Biennial Biennial
Program Type TRC TRC TRC TRC

Model Years 1968-1980 1981-2050 1981-2050 1973-2050
Stringency Rate (%) 35 35 35 N/A
Compliance Rate (%) 98 98 98 98
Waiver Rate (%) 2 2 2 2
I/M Effectiveness (%) N/A N/A 94 N/A

Vehicles Tested
LDGV Yes No Yes Yes

LDGT1 Yes No Yes Yes

LDGT2 Yes No Yes Yes

LDGT3 Yes No Yes Yes

LDGT4 Yes No Yes Yes

HDGV2B Yes Yes No Yes

HDGV3 No No No No

HDGV4 No No No No

HDGV5 No No No No

HDGV6 No No No No

HDGV7 No No No No

HDGV8A No No No No

HDGV8B No No No No

GAS BUS No No No No

*Program Start Year is 1998 for all test types for Loudoun County.

D1-19Table 19 Anti-tampering Program Parameters for 2002

Program Element DC MD VA Program Start Year 1983 1989* 1989**

First Model Year 1968 1977 1968
Last Model Year 2050 2050 2050

Program Type Test Only Test Only Test Only Inspection Frequency Biennial Biennial Biennial Compliance Rate (%) 96 96 98
Vehicle Types
LDGV Yes Yes Yes
LDGT1 Yes Yes Yes
LDGT2 Yes Yes Yes
LDGT3 Yes Yes Yes
LDGT4 Yes Yes Yes
HDGV2B Yes Yes Yes

HDGV3 Yes Yes No
HDGV4 Yes Yes No
HDGV5 Yes Yes No
HDGV6 Yes Yes No
HDGV7 No No No
HDGV8A No No No
HDGV8B No No No
GAS BUS No No No Inspections Performed Air pump system disablement No No Yes Catalyst removal Yes Yes Yes

Fuel inlet restrictor disablement Yes Yes No Tailpipe lead deposit test No No No
EGR disablement No No Yes Evaporative system disablement No No Yes PCV system disablement No No Yes Missing gas cap Yes Yes Yes *Program Start Year for Calvert, Charles, and Frederick Counties is 1995. ** Program Start Year for Loudoun County is 1998.

D1-20Table 20 Summary of Scenarios Modeled in Each MOBILE6 Input File

For School Bus or Transit Bus Analysis for VOC and NOx

Scenario Number Operating Mode Facility Type Speed Season Sequence*

1-195 Stabilized Arterial/Collectors 1-65 mph 1-3

196-198 Stabilized Freeway Ramps 34.6 mph 1-3

199-201 Stabilized Local Road 12.9 mph 1-3

Notes:* - Season Codes: 1 – Winter (January-April); 2 – Summer (May-September); 3 – Fall (OctoberDecember). In Scenarios 1 through 201, each speed is modeled at the three sets of seasonal conditions prior to moving to the next speed.

Table 21 Summary of Scenarios Modeled in Each MOBILE6 Input File For School Bus or Transit Bus Analys is for PM2.5, PM10, SO2, and NH3

Scenario Number Operating Mode Facility Type Speed Season Sequence*

1-3 Stabilized Arterial/Collectors 35 mph 1-3

Notes: * - Season Codes: 1 – Winter (January-April); 2 – Summer (May-September); 3 – Fall (October-December).

D1-21Attachment 1 Vehicle Registrati on Distributions

Registration distributions (RDT) specify the fraction of vehicles by age in the fleet. The distribution for each vehicle category is presented (in fraction) for the newest model year (2002) and progressing back for 25 model years. This information is given for each of t he 16 required vehicle classes used in MOBILE6, for each jurisdiction. For school and transit buses, the RD T reported were based on 2002 metropolitan Washington’s regional distribution.

D1-22District of Columbia —2002 Registration Data

* LDV M5 LDGV
0.0436 0.0625 0.0786 0.0638 0.0650 0.0678 0.0640 0.0740 0.0653 0.0565 0.0530 0.0488 0.0488 0.0436 0.0381 0.0320 0.0252 0.0177 0.0127 0.0071 0.0041 0.0034 0.0026 0.0041 0.0177 * LDT1 M5 LDGT1
0.0663 0.0951 0.0854 0.0832 0.0865 0.0767 0.0675 0.0649 0.0564 0.0496 0.0367 0.0348 0.0340 0.0327 0.0295 0.0252 0.0199 0.0129 0.0113 0.0063 0.0035 0.0027 0.0021 0.0032 0.0139 * LDT2 M5 LDGT1
0.0663 0.0951 0.0854 0.0832 0.0865 0.0767 0.0675 0.0649 0.0564 0.0496 0.0367 0.0348 0.0340 0.0327 0.0295 0.0252 0.0199 0.0129 0.0113 0.0063 0.0035 0.0027 0.0021 0.0032 0.0139 * LDT3 M5 LDGT2
0.0663 0.0951 0.0329 0.0811 0.0422 0.0631 0.0496 0.0654 0.0764 0.0453 0.0339 0.0383 0.0410 0.0461 0.0359 0.0385 0.0356 0.0298 0.0163 0.0132 0.0084 0.0056 0.0043 0.0067 0.0291 * LDT4 M5 LDGT2
0.0663 0.0951 0.0329 0.0811 0.0422 0.0631 0.0496 0.0654 0.0764 0.0453 0.0339 0.0383 0.0410 0.0461 0.0359 0.0385 0.0356 0.0298 0.0163 0.0132 0.0084 0.0056 0.0043 0.0067 0.0291 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0606 0.1248 0.0724 0.0923 0.0605 0.0517 0.0409 0.0615 0.0750 0.0601 0.0320 0.0356 0.0509 0.0337 0.0379 0.0291 0.0245 0.0145 0.0059 0.0045 0.0041 0.0035 0.0041 0.0038 0.0161 * HDBT M5 HDDVs 0.0741 0.1734 0.1144 0.0746 0.0537 0.0607 0.0369 0.0574 0.0693 0.0410 0.0291 0.0328 0.0537 0.0307 0.0209 0.0197 0.0189 0.0119 0.0057 0.0041 0.0029 0.0020 0.0041 0.0016 0.0066 * Motorcycles M5 MC
0.1036 0.1417 0.0866 0.0901 0.0415 0.0479 0.0551 0.0465 0.0258 0.0293 0.0222 0.3098 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-23Charles County, MD— 2002 Registration Data

* LDV M5 LDGV
0.0495 0.0696 0.0802 0.0724 0.0728 0.0715 0.0623 0.0730 0.0631 0.0559 0.0457 0.0435 0.0390 0.0356 0.0315 0.0271 0.0192 0.0160 0.0107 0.0063 0.0030 0.0023 0.0025 0.0030 0.0444 * LDT1 M5 LDGT1
0.0731 0.1015 0.1050 0.0993 0.0944 0.0849 0.0739 0.0688 0.0549 0.0467 0.0327 0.0282 0.0240 0.0274 0.0223 0.0179 0.0121 0.0097 0.0071 0.0039 0.0019 0.0013 0.0006 0.0021 0.0063 * LDT2 M5 LDGT1
0.0731 0.1015 0.1050 0.0993 0.0944 0.0849 0.0739 0.0688 0.0549 0.0467 0.0327 0.0282 0.0240 0.0274 0.0223 0.0179 0.0121 0.0097 0.0071 0.0039 0.0019 0.0013 0.0006 0.0021 0.0063 * LDT3 M5 LDGT2
0.0579 0.0821 0.0750 0.0673 0.0620 0.0651 0.0509 0.0575 0.0661 0.0452 0.0357 0.0355 0.0380 0.0400 0.0429 0.0380 0.0347 0.0247 0.0182 0.0116 0.0080 0.0053 0.0043 0.0081 0.0258 * LDT4 M5 LDGT2
0.0579 0.0821 0.0750 0.0673 0.0620 0.0651 0.0509 0.0575 0.0661 0.0452 0.0357 0.0355 0.0380 0.0400 0.0429 0.0380 0.0347 0.0247 0.0182 0.0116 0.0080 0.0053 0.0043 0.0081 0.0258 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0359 0.0721 0.0678 0.0611 0.0497 0.0546 0.0441 0.0613 0.0399 0.0449 0.0302 0.0325 0.0413 0.0492 0.0500 0.0447 0.0404 0.0294 0.0206 0.0122 0.0071 0.0096 0.0119 0.0158 0.0738 * HDBT M5 HDDVs 0.0149 0.0298 0.0437 0.0785 0.0656 0.0716 0.0636 0.0825 0.0557 0.0447 0.0318 0.0308 0.0467 0.0656 0.0686 0.0547 0.0427 0.0318 0.0159 0.0089 0.0060 0.0139 0.0060 0.0119 0.0139 * Motorcycles M5 MC
0.0944 0.1365 0.0971 0.0800 0.0576 0.0432 0.0512 0.0372 0.0375 0.0296 0.0273 0.3083 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-24Frederick County, MD—2002 Registration Data

* LDV M5 LDGV
0.0528 0.0761 0.0821 0.0730 0.0712 0.0732 0.0661 0.0745 0.0607 0.0541 0.0449 0.0414 0.0388 0.0338 0.0276 0.0233 0.0178 0.0122 0.0089 0.0045 0.0030 0.0021 0.0022 0.0031 0.0528 * LDT1 M5 LDGT1
0.0738 0.0984 0.1056 0.0973 0.0992 0.0825 0.0744 0.0767 0.0622 0.0455 0.0334 0.0281 0.0251 0.0239 0.0198 0.0158 0.0100 0.0083 0.0057 0.0029 0.0019 0.0009 0.0010 0.0024 0.0053 * LDT2 M5 LDGT1
0.0738 0.0984 0.1056 0.0973 0.0992 0.0825 0.0744 0.0767 0.0622 0.0455 0.0334 0.0281 0.0251 0.0239 0.0198 0.0158 0.0100 0.0083 0.0057 0.0029 0.0019 0.0009 0.0010 0.0024 0.0053 * LDT3 M5 LDGT2
0.0465 0.0741 0.0762 0.0733 0.0678 0.0677 0.0547 0.0645 0.0677 0.0434 0.0373 0.0377 0.0376 0.0430 0.0424 0.0353 0.0345 0.0210 0.0161 0.0105 0.0060 0.0060 0.0043 0.0081 0.0242 * LDT4 M5 LDGT2
0.0465 0.0741 0.0762 0.0733 0.0678 0.0677 0.0547 0.0645 0.0677 0.0434 0.0373 0.0377 0.0376 0.0430 0.0424 0.0353 0.0345 0.0210 0.0161 0.0105 0.0060 0.0060 0.0043 0.0081 0.0242 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0606 0.0805 0.0921 0.0899 0.0416 0.0700 0.0501 0.0531 0.0363 0.0314 0.0236 0.0237 0.0405 0.0412 0.0436 0.0311 0.0344 0.0268 0.0176 0.0108 0.0085 0.0085 0.0093 0.0146 0.0603 * HDBT M5 HDDVs 0.0353 0.0544 0.0616 0.1062 0.0387 0.1045 0.0624 0.0684 0.0506 0.0429 0.0255 0.0212 0.0344 0.0374 0.0527 0.0463 0.0391 0.0302 0.0221 0.0110 0.0068 0.0093 0.0072 0.0119 0.0200 * Motorcycles M5 MC
0.0841 0.1112 0.0905 0.0655 0.0528 0.0409 0.0389 0.0350 0.0285 0.0276 0.0223 0.4029 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-25Montgomery County, MD—2002 Registration Data

* LDV M5 LDGV
0.0635 0.0864 0.0846 0.0754 0.0730 0.0724 0.0652 0.0748 0.0626 0.0551 0.0480 0.0434 0.0422 0.0335 0.0273 0.0231 0.0164 0.0114 0.0075 0.0045 0.0027 0.0019 0.0016 0.0019 0.0216 * LDT1 M5 LDGT1
0.0951 0.1220 0.1208 0.1064 0.0931 0.0848 0.0725 0.0695 0.0543 0.0418 0.0289 0.0250 0.0201 0.0171 0.0141 0.0108 0.0071 0.0047 0.0037 0.0019 0.0011 0.0006 0.0005 0.0011 0.0027 * LDT2 M5 LDGT1
0.0951 0.1220 0.1208 0.1064 0.0931 0.0848 0.0725 0.0695 0.0543 0.0418 0.0289 0.0250 0.0201 0.0171 0.0141 0.0108 0.0071 0.0047 0.0037 0.0019 0.0011 0.0006 0.0005 0.0011 0.0027 * LDT3 M5 LDGT2
0.0726 0.0976 0.0894 0.0733 0.0622 0.0672 0.0562 0.0661 0.0638 0.0413 0.0335 0.0303 0.0354 0.0395 0.0370 0.0308 0.0296 0.0177 0.0143 0.0075 0.0058 0.0041 0.0031 0.0053 0.0164 * LDT4 M5 LDGT2
0.0726 0.0976 0.0894 0.0733 0.0622 0.0672 0.0562 0.0661 0.0638 0.0413 0.0335 0.0303 0.0354 0.0395 0.0370 0.0308 0.0296 0.0177 0.0143 0.0075 0.0058 0.0041 0.0031 0.0053 0.0164 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0589 0.0987 0.1176 0.0854 0.0497 0.0671 0.0405 0.0623 0.0356 0.0308 0.0199 0.0303 0.0407 0.0389 0.0366 0.0414 0.0277 0.0203 0.0138 0.0083 0.0067 0.0056 0.0111 0.0101 0.0419 * HDBT M5 HDDVs 0.0105 0.0309 0.0454 0.0725 0.0491 0.0949 0.0493 0.1019 0.0414 0.0456 0.0256 0.0533 0.0723 0.0594 0.0449 0.0850 0.0410 0.0230 0.0156 0.0072 0.0057 0.0048 0.0070 0.0037 0.0099 * Motorcycles M5 MC
0.0853 0.1188 0.0877 0.0634 0.0555 0.0416 0.0442 0.0413 0.0362 0.0325 0.0263 0.3673 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-26Prince George’s County, MD—2002 Registration Data

* LDV M5 LDGV
0.0418 0.0637 0.0732 0.0668 0.0691 0.0741 0.0664 0.0757 0.0664 0.0589 0.0523 0.0468 0.0466 0.0409 0.0352 0.0296 0.0222 0.0159 0.0106 0.0060 0.0034 0.0027 0.0022 0.0030 0.0263 * LDT1 M5 LDGT1
0.0669 0.0933 0.0973 0.0990 0.0984 0.0881 0.0732 0.0727 0.0588 0.0487 0.0349 0.0308 0.0293 0.0270 0.0235 0.0176 0.0114 0.0089 0.0063 0.0033 0.0019 0.0011 0.0009 0.0021 0.0045 * LDT2 M5 LDGT1
0.0669 0.0933 0.0973 0.0990 0.0984 0.0881 0.0732 0.0727 0.0588 0.0487 0.0349 0.0308 0.0293 0.0270 0.0235 0.0176 0.0114 0.0089 0.0063 0.0033 0.0019 0.0011 0.0009 0.0021 0.0045 * LDT3 M5 LDGT2
0.0472 0.0723 0.0759 0.0616 0.0580 0.0638 0.0536 0.0578 0.0648 0.0436 0.0361 0.0342 0.0425 0.0464 0.0445 0.0369 0.0397 0.0258 0.0204 0.0132 0.0084 0.0076 0.0049 0.0096 0.0312 * LDT4 M5 LDGT2
0.0472 0.0723 0.0759 0.0616 0.0580 0.0638 0.0536 0.0578 0.0648 0.0436 0.0361 0.0342 0.0425 0.0464 0.0445 0.0369 0.0397 0.0258 0.0204 0.0132 0.0084 0.0076 0.0049 0.0096 0.0312 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0431 0.0847 0.0871 0.0830 0.0509 0.0674 0.0405 0.0714 0.0485 0.0300 0.0215 0.0294 0.0650 0.0501 0.0531 0.0331 0.0271 0.0249 0.0200 0.0070 0.0057 0.0058 0.0050 0.0084 0.0374 * HDBT M5 HDDVs 0.0215 0.0421 0.0395 0.0724 0.0477 0.0828 0.0613 0.1030 0.0452 0.0363 0.0285 0.0478 0.1143 0.0746 0.0483 0.0414 0.0277 0.0206 0.0139 0.0053 0.0041 0.0038 0.0034 0.0041 0.0104 * Motorcycles M5 MC
0.0856 0.1345 0.1067 0.0854 0.0557 0.0470 0.0492 0.0407 0.0331 0.0341 0.0290 0.2989 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-27Alexandria, VA—2002 Registration Data

* LDV M5 LDGV
0.1006 0.0993 0.0778 0.0690 0.0673 0.0655 0.0588 0.0668 0.0571 0.0521 0.0458 0.0448 0.0417 0.0350 0.0298 0.0255 0.0178 0.0118 0.0071 0.0044 0.0024 0.0017 0.0014 0.0014 0.0149 * LDT1 M5 LDGT1
0.1357 0.1517 0.0854 0.0674 0.0720 0.0683 0.0590 0.0595 0.0540 0.0434 0.0342 0.0318 0.0266 0.0246 0.0208 0.0185 0.0146 0.0096 0.0064 0.0035 0.0029 0.0020 0.0012 0.0012 0.0056 * LDT2 M5 LDGT1
0.1357 0.1517 0.0854 0.0674 0.0720 0.0683 0.0590 0.0595 0.0540 0.0434 0.0342 0.0318 0.0266 0.0246 0.0208 0.0185 0.0146 0.0096 0.0064 0.0035 0.0029 0.0020 0.0012 0.0012 0.0056 * LDT3 M5 LDGT2
0.1475 0.2009 0.0913 0.0922 0.0647 0.0559 0.0407 0.0450 0.0379 0.0240 0.0209 0.0140 0.0205 0.0229 0.0195 0.0162 0.0125 0.0105 0.0074 0.0048 0.0027 0.0020 0.0017 0.0062 0.0380 * LDT4 M5 LDGT2
0.1475 0.2009 0.0913 0.0922 0.0647 0.0559 0.0407 0.0450 0.0379 0.0240 0.0209 0.0140 0.0205 0.0229 0.0195 0.0162 0.0125 0.0105 0.0074 0.0048 0.0027 0.0020 0.0017 0.0062 0.0380 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0721 0.1407 0.1120 0.1002 0.0465 0.0796 0.0519 0.0668 0.0441 0.0296 0.0211 0.0210 0.0301 0.0357 0.0454 0.0221 0.0238 0.0166 0.0107 0.0055 0.0033 0.0047 0.0030 0.0040 0.0097 * HDBT M5 HDDVs 0.0632 0.0977 0.1025 0.1188 0.0402 0.0872 0.0546 0.0728 0.0460 0.0326 0.0182 0.0249 0.0326 0.0364 0.0680 0.0239 0.0278 0.0172 0.0105 0.0048 0.0019 0.0048 0.0029 0.0048 0.0057 * Motorcycles M5 MC
0.1312 0.1213 0.1082 0.0829 0.0668 0.0407 0.0468 0.0453 0.0353 0.0253 0.0215 0.2748 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-28Arlington County, VA—2002 Registration Data

* LDV M5 LDGV
0.0714 0.0840 0.0803 0.0715 0.0677 0.0687 0.0624 0.0687 0.0595 0.0556 0.0481 0.0483 0.0439 0.0387 0.0314 0.0258 0.0193 0.0126 0.0088 0.0046 0.0032 0.0021 0.0019 0.0019 0.0196 * LDT1 M5 LDGT1
0.0900 0.1039 0.0949 0.0764 0.0794 0.0739 0.0670 0.0678 0.0619 0.0492 0.0374 0.0365 0.0282 0.0294 0.0258 0.0219 0.0189 0.0110 0.0074 0.0041 0.0031 0.0020 0.0012 0.0015 0.0071 * LDT2 M5 LDGT1
0.0900 0.1039 0.0949 0.0764 0.0794 0.0739 0.0670 0.0678 0.0619 0.0492 0.0374 0.0365 0.0282 0.0294 0.0258 0.0219 0.0189 0.0110 0.0074 0.0041 0.0031 0.0020 0.0012 0.0015 0.0071 * LDT3 M5 LDGT2
0.1000 0.1391 0.1040 0.1075 0.0731 0.0622 0.0472 0.0533 0.0445 0.0282 0.0230 0.0168 0.0221 0.0278 0.0247 0.0200 0.0163 0.0121 0.0089 0.0058 0.0029 0.0017 0.0018 0.0075 0.0494 * LDT4 M5 LDGT2
0.1000 0.1391 0.1040 0.1075 0.0731 0.0622 0.0472 0.0533 0.0445 0.0282 0.0230 0.0168 0.0221 0.0278 0.0247 0.0200 0.0163 0.0121 0.0089 0.0058 0.0029 0.0017 0.0018 0.0075 0.0494 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0461 0.1056 0.1376 0.0946 0.0598 0.0710 0.0545 0.0705 0.0464 0.0373 0.0248 0.0245 0.0290 0.0404 0.0354 0.0282 0.0244 0.0195 0.0135 0.0055 0.0052 0.0029 0.0046 0.0035 0.0152 * HDBT M5 HDDVs 0.0352 0.0803 0.1465 0.0972 0.0648 0.0592 0.0535 0.0718 0.0437 0.0493 0.0239 0.0324 0.0296 0.0394 0.0451 0.0352 0.0225 0.0225 0.0155 0.0028 0.0056 0.0014 0.0070 0.0028 0.0127 * Motorcycles M5 MC
0.0793 0.1187 0.1024 0.0619 0.0529 0.0394 0.0523 0.0400 0.0394 0.0298 0.0231 0.3607 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-29Fairfax County, VA—2002 Registration Data

* LDV M5 LDGV
0.0583 0.0848 0.0923 0.0803 0.0763 0.0738 0.0648 0.0709 0.0608 0.0552 0.0470 0.0429 0.0412 0.0340 0.0276 0.0230 0.0167 0.0113 0.0074 0.0042 0.0025 0.0018 0.0015 0.0017 0.0197 * LDT1 M5 LDGT1
0.0846 0.1045 0.1091 0.0880 0.0879 0.0802 0.0702 0.0679 0.0609 0.0457 0.0331 0.0309 0.0254 0.0255 0.0218 0.0186 0.0150 0.0093 0.0065 0.0035 0.0022 0.0017 0.0011 0.0013 0.0053 * LDT2 M5 LDGT1
0.0846 0.1045 0.1091 0.0880 0.0879 0.0802 0.0702 0.0679 0.0609 0.0457 0.0331 0.0309 0.0254 0.0255 0.0218 0.0186 0.0150 0.0093 0.0065 0.0035 0.0022 0.0017 0.0011 0.0013 0.0053 * LDT3 M5 LDGT2
0.0935 0.1402 0.1191 0.1243 0.0805 0.0673 0.0501 0.0535 0.0437 0.0263 0.0207 0.0143 0.0200 0.0235 0.0210 0.0165 0.0130 0.0103 0.0077 0.0052 0.0021 0.0017 0.0017 0.0069 0.0369 * LDT4 M5 LDGT2
0.0935 0.1402 0.1191 0.1243 0.0805 0.0673 0.0501 0.0535 0.0437 0.0263 0.0207 0.0143 0.0200 0.0235 0.0210 0.0165 0.0130 0.0103 0.0077 0.0052 0.0021 0.0017 0.0017 0.0069 0.0369 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0504 0.1074 0.1335 0.1051 0.0607 0.0810 0.0573 0.0753 0.0505 0.0322 0.0237 0.0227 0.0309 0.0360 0.0290 0.0254 0.0218 0.0171 0.0112 0.0059 0.0039 0.0033 0.0027 0.0031 0.0097 * HDBT M5 HDDVs 0.0523 0.0934 0.1151 0.1029 0.0590 0.0782 0.0563 0.0813 0.0542 0.0365 0.0250 0.0288 0.0362 0.0376 0.0329 0.0314 0.0236 0.0193 0.0117 0.0053 0.0044 0.0028 0.0024 0.0027 0.0069 * Motorcycles M5 MC
0.0881 0.1186 0.1092 0.0888 0.0641 0.0478 0.0475 0.0426 0.0335 0.0285 0.0268 0.3045 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-30Loudoun County, VA—2002 Registration Data

* LDV M5 LDGV
0.0747 0.0934 0.0972 0.0835 0.0811 0.0750 0.0671 0.0704 0.0581 0.0522 0.0414 0.0386 0.0347 0.0284 0.0236 0.0186 0.0143 0.0096 0.0066 0.0036 0.0020 0.0015 0.0012 0.0016 0.0216 * LDT1 M5 LDGT1
0.0849 0.1114 0.1148 0.0915 0.0884 0.0833 0.0697 0.0628 0.0570 0.0421 0.0298 0.0274 0.0221 0.0242 0.0211 0.0170 0.0153 0.0103 0.0069 0.0041 0.0025 0.0023 0.0015 0.0017 0.0081 * LDT2 M5 LDGT1
0.0849 0.1114 0.1148 0.0915 0.0884 0.0833 0.0697 0.0628 0.0570 0.0421 0.0298 0.0274 0.0221 0.0242 0.0211 0.0170 0.0153 0.0103 0.0069 0.0041 0.0025 0.0023 0.0015 0.0017 0.0081 * LDT3 M5 LDGT2
0.0918 0.1434 0.1212 0.1250 0.0789 0.0671 0.0480 0.0477 0.0398 0.0233 0.0182 0.0122 0.0169 0.0222 0.0198 0.0152 0.0130 0.0111 0.0079 0.0059 0.0024 0.0021 0.0025 0.0086 0.0557 * LDT4 M5 LDGT2
0.0918 0.1434 0.1212 0.1250 0.0789 0.0671 0.0480 0.0477 0.0398 0.0233 0.0182 0.0122 0.0169 0.0222 0.0198 0.0152 0.0130 0.0111 0.0079 0.0059 0.0024 0.0021 0.0025 0.0086 0.0557 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0546 0.1133 0.1217 0.1070 0.0560 0.0823 0.0550 0.0697 0.0489 0.0329 0.0218 0.0168 0.0278 0.0346 0.0356 0.0260 0.0255 0.0179 0.0131 0.0072 0.0045 0.0052 0.0033 0.0049 0.0144 * HDBT M5 HDDVs 0.0580 0.1063 0.1018 0.1056 0.0526 0.0808 0.0540 0.0734 0.0521 0.0372 0.0227 0.0180 0.0310 0.0355 0.0422 0.0303 0.0284 0.0187 0.0142 0.0071 0.0047 0.0054 0.0026 0.0052 0.0118 * Motorcycles M5 MC
0.1024 0.1392 0.1204 0.0871 0.0608 0.0500 0.0527 0.0368 0.0355 0.0239 0.0242 0.2669 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-31Prince William, VA—2002 Registration Data

* LDV M5 LDGV
0.0519 0.0765 0.0874 0.0754 0.0765 0.0769 0.0670 0.0733 0.0630 0.0562 0.0456 0.0431 0.0387 0.0355 0.0305 0.0244 0.0183 0.0123 0.0088 0.0047 0.0026 0.0019 0.0016 0.0020 0.0259 * LDT1 M5 LDGT1
0.0720 0.0897 0.0967 0.0810 0.0844 0.0802 0.0692 0.0676 0.0640 0.0492 0.0360 0.0328 0.0300 0.0306 0.0290 0.0231 0.0201 0.0119 0.0088 0.0047 0.0036 0.0025 0.0016 0.0018 0.0095 * LDT2 M5 LDGT1
0.0720 0.0897 0.0967 0.0810 0.0844 0.0802 0.0692 0.0676 0.0640 0.0492 0.0360 0.0328 0.0300 0.0306 0.0290 0.0231 0.0201 0.0119 0.0088 0.0047 0.0036 0.0025 0.0016 0.0018 0.0095 * LDT3 M5 LDGT2
0.0768 0.1187 0.1039 0.1136 0.0771 0.0670 0.0488 0.0528 0.0460 0.0281 0.0223 0.0149 0.0223 0.0283 0.0270 0.0209 0.0174 0.0133 0.0106 0.0071 0.0035 0.0025 0.0024 0.0094 0.0653 * LDT4 M5 LDGT2
0.0768 0.1187 0.1039 0.1136 0.0771 0.0670 0.0488 0.0528 0.0460 0.0281 0.0223 0.0149 0.0223 0.0283 0.0270 0.0209 0.0174 0.0133 0.0106 0.0071 0.0035 0.0025 0.0024 0.0094 0.0653 * HDV2B M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDV3 M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDV4 M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDV5 M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDV6 M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDV7 M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDV8a M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDV8b M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDBS M5 HDVs (Combined HDGV and HDDV)
0.0532 0.0985 0.1249 0.1119 0.0544 0.0761 0.0548 0.0682 0.0511 0.0359 0.0220 0.0178 0.0280 0.0385 0.0346 0.0290 0.0251 0.0215 0.0130 0.0073 0.0053 0.0045 0.0041 0.0042 0.0160 * HDBT M5 HDDVs 0.0625 0.0961 0.1203 0.1218 0.0508 0.0711 0.0535 0.0680 0.0523 0.0400 0.0204 0.0179 0.0274 0.0365 0.0361 0.0317 0.0239 0.0230 0.0118 0.0065 0.0049 0.0037 0.0039 0.0037 0.0119 * Motorcycles M5 MC
0.1235 0.1399 0.1087 0.0864 0.0563 0.0494 0.0532 0.0419 0.0313 0.0235 0.0199 0.2661 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

D1-322002 Regional School Bus Registration Data

* HDBS M5 HDVs (Combined HDGV and HDDV)

0.0522 0.0975 0.0911 0.0851 0.0795 0.0742 0.0693 0.0648 0.0606 0.0566

0.0528 0.0494 0.0461 0.0430 0.0402 0.0376 0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0000 0.0000

2002 Regional Transit Bus Registration Data

* HDBT M5 HDDVs

0.0324 0.0660 0.1071 0.0602 0.0478 0.1120 0.0333 0.0756 0.0336 0.0318
0.0457 0.0136 0.0867 0.0475 0.0592 0.0691 0.0654 0.0068 0.0000 0.0062
0.0000 0.0000 0.0000 0.0000 0.0000

D1-33Attachment 2 Diesel Sales Fractions

The diesel sales fractions are presented by vehicle, y ear-specific model year, and going back 25 model years. Maryland and Virginia use the defaults present for the Di strict for all categories other than LDVs and LDT12 for network and off-network analyses. The diesel sales fracti ons for the school bus analysis are also provided in this section.

District of Columbia—MOBILE6 2002 Default Diesel Sales Fractions

* LDV 0.0009 0.0009 0.0009 0.0009 0.0009 0.0009 0.0009 0.0006 0.0001 0.0003 0.0006 0.0013 0.0004 0.0004 0.0001 0.0027 0.0032 0.0097 0.0162 0.0241 0.0510 0.0706 0.0390 0.0269 0.0114 * LDT12 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0007 0.0033 0.0048 0.0120 0.0223 0.0656 0.0616 0.0439 0.0316 0.0259 * LDT34 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0115 0.0111 0.0145 0.0115 0.0129 0.0096 0.0083 0.0072 0.0082 0.0124 0.0135 0.0169 0.0209 0.0256 0.0013 0.0006 0.0011 0.0001 * HDV2B 0.1998 0.1998 0.1998 0.1998 0.1998 0.1998 0.1998 0.2578 0.2515 0.3263 0.2784 0.2963 0.2384 0.2058 0.1756 0.1958 0.2726 0.2743 0.3004 0.2918 0.2859 0.0138 0.0000 0.0000 0.0000 * HDV3 0.6774 0.6774 0.6774 0.6774 0.6774 0.6774 0.6774 0.7715 0.7910 0.8105 0.8068 0.8280 0.8477 0.7940 0.7488 0.7789 0.7842 0.6145 0.5139 0.5032 0.4277 0.0079 0.0000 0.0000 0.0001 * HDV4 0.8606 0.8606 0.8606 0.8606 0.8606 0.8606 0.8606 0.8473 0.8048 0.8331 0.7901 0.7316 0.7275 0.7158 0.5647 0.3178 0.2207 0.1968 0.1570 0.0738 0.0341 0.0414 0.0003 0.0000 0.0000 * HDV5 0.4647 0.4647 0.4647 0.4647 0.4647 0.4647 0.4647 0.4384 0.3670 0.4125 0.3462 0.2771 0.2730 0.2616 0.1543 0.0615 0.0383 0.0333 0.0255 0.0111 0.0049 0.0060 0.0000 0.0000 0.0000 * HDV6 0.6300 0.6300 0.6300 0.6300 0.6300 0.6300 0.6300 0.6078 0.5246 0.5767 0.5289 0.5788 0.5617 0.4537 0.4216 0.4734 0.4705 0.4525 0.4310 0.3569 0.3690 0.4413 0.3094 0.1679 0.1390 * HDV7 0.8563 0.8563 0.8563 0.8563 0.8563 0.8563 0.8563 0.8443 0.7943 0.8266 0.7972 0.8279 0.8177 0.7440 0.7184 0.7588 0.7567 0.7431 0.7261 0.6602 0.6717 0.7344 0.6107 0.4140 0.3610 * HDV8A 0.9992 0.9992 0.9992 0.9992 0.9992 0.9992 0.9992 0.9989 0.9987 0.9989 0.9977 0.9984 0.9982 0.9979 0.9969 0.9978 0.9980 0.9979 0.9976 0.9969 0.9978 0.9982 0.9974 0.9965 0.9964 * HDV8B 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 * HDBS 0.9585 0.9585 0.9585 0.9585 0.9585 0.9585 0.9585 0.8857 0.8525 0.8795 0.9900 0.9105 0.8760 0.7710 0.7502 0.7345 0.6733 0.5155 0.3845 0.3238 0.3260 0.2639 0.0594 0.0460 0.0291

D1-34Calvert County, MD—2002 Di esel Sales Fractions

* LDV 0.0006 0.0000 0.0004 0.0017 0.0029 0.0020 0.0015 0.0025 0.0010 0.0016 0.0013 0.0033 0.0022 0.0008 0.0000 0.0086 0.0027 0.0389 0.0284 0.1091 0.0855 0.1200 0.0543 0.0481 0.0011 * LDT1, LDT2 0.0009 0.0014 0.0048 0.0185 0.0068 0.0265 0.0185 0.0246 0.0082 0.0097 0.0070 0.0061 0.0095 0.0146 0.0407 0.0104 0.0249 0.0818 0.0660 0.0926 0.2000 0.1304 0.0000 0.0000 0.0000
Charles County, MD—2002 Di esel Sales Fractions

* LDV 0.0000 0.0000 0.0004 0.0029 0.0007 0.0010 0.0003 0.0002 0.0006 0.0000 0.0008 0.0020 0.0005 0.0005 0.0000 0.0046 0.0073 0.0165 0.0181 0.0279 0.0698 0.0451 0.0286 0.0058 0.0008 * LDT1, LDT2
0.0025 0.0018 0.0038 0.0212 0.0057 0.0259 0.0176 0.0215 0.0082 0.0106 0.0055 0.0159 0.0112 0.0147 0.0161 0.0376 0.0669 0.0369 0.0633 0.0682 0.1628 0.0357 0.0714 0.0435 0.0071 Frederick County, MD—2002 Diesel Sales Fractions

* LDV 0.0002 0.0003 0.0009 0.0033 0.0026 0.0007 0.0019 0.0010 0.0002 0.0002 0.0007 0.0013 0.0013 0.0012 0.0000 0.0049 0.0093 0.0367 0.0292 0.0389 0.0596 0.1330 0.0386 0.0169 0.0028 * LDT1, LDT2
0.0013 0.0019 0.0036 0.0203 0.0060 0.0272 0.0227 0.0317 0.0157 0.0115 0.0107 0.0127 0.0181 0.0229 0.0193 0.0363 0.0619 0.0802 0.0630 0.0976 0.1282 0.1892 0.0250 0.0303 0.0134 Montgomery County, MD—2002 Diesel Sales Fractions

* LDV 0.0001 0.0001 0.0004 0.0021 0.0015 0.0015 0.0012 0.0012 0.0008 0.0011 0.0014 0.0040 0.0006 0.0005 0.0008 0.0154 0.0102 0.0617 0.0864 0.1308 0.1700 0.1661 0.1152 0.0961 0.0096 * LDT1, LDT2 0.0005 0.0007 0.0017 0.0058 0.0033 0.0082 0.0083 0.0089 0.0068 0.0071 0.0093 0.0086 0.0110 0.0169 0.0158 0.0150 0.0501 0.0384 0.0862 0.0909 0.2108 0.1458 0.1842 0.0235 0.0126 Prince Georges County, MD—2002 Diesel Sales Fractions

* LDV 0.0001 0.0000 0.0001 0.0011 0.0009 0.0011 0.0009 0.0006 0.0002 0.0008 0.0008 0.0021 0.0006 0.0005 0.0005 0.0082 0.0068 0.0280 0.0404 0.0805 0.0974 0.0896 0.0658 0.0261 0.0052 * LDT1, LDT2 0.0008 0.0003 0.0018 0.0054 0.0019 0.0099 0.0088 0.0102 0.0087 0.0123 0.0097 0.0065 0.0154 0.0148 0.0156 0.0208 0.0289 0.0540 0.0498 0.0608 0.1306 0.1260 0.0841 0.0331 0.0077

Alexandria, VA—2002 Diesel Sales Fractions

* LDV
0.0014 0.0016 0.0020 0.0027 0.0023 0.0008 0.0009 0.0011 0.0002 0.0010 0.0011 0.0023 0.0000 0.0006 0.0000 0.0127 0.0058 0.0353 0.0626 0.1318 0.1164 0.1553 0.1471 0.0667 0.0112 * LDT1, LDT2 0.0036 0.0077 0.0168 0.0273 0.0119 0.0164 0.0167 0.0264 0.0141 0.0248 0.0079 0.0353 0.0101 0.0073 0.0194 0.0291 0.0185 0.0327 0.0629 0.1037 0.1222 0.0883 0.1484 0.0361 0.0160

D1-35Arlington County, VA—2002 Diesel Sales Fractions

* LDV 0.0012 0.0023 0.0026 0.0027 0.0029 0.0015 0.0008 0.0011 0.0001 0.0006 0.0013 0.0015 0.0006 0.0014 0.0006 0.0099 0.0087 0.0446 0.0685 0.0857 0.1922 0.1481 0.1132 0.0959 0.0126 * LDT1, LDT2 0.0056 0.0221 0.0167 0.0235 0.0126 0.0119 0.0206 0.0136 0.0155 0.0127 0.0246 0.0206 0.0222 0.0184 0.0227 0.0115 0.0310 0.0568 0.0508 0.1211 0.1077 0.2126 0.0711 0.0286 0.0176 Fairfax County, VA—2002 Di esel Sales Fractions

* LDV 0.0018 0.0018 0.0022 0.0028 0.0022 0.0013 0.0016 0.0015 0.0005 0.0012 0.0013 0.0029 0.0015 0.0011 0.0007 0.0114 0.0089 0.0573 0.0842 0.1384 0.1989 0.1766 0.1464 0.0780 0.0103 * LDT1, LDT2 0.0128 0.0206 0.0218 0.0213 0.0197 0.0172 0.0099 0.0126 0.0184 0.0093 0.0110 0.0112 0.0165 0.0424 0.0141 0.0460 0.0312 0.0441 0.0609 0.0619 0.1032 0.0866 0.0529 0.0337 0.0108 Loudoun County, VA—2002 Diesel Sales Fractions

* LDV 0.0024 0.0033 0.0027 0.0047 0.0036 0.0016 0.0016 0.0020 0.0008 0.0013 0.0018 0.0027 0.0030 0.0010 0.0008 0.0117 0.0126 0.0720 0.0560 0.1283 0.2330 0.2138 0.1440 0.0727 0.0075 * LDT1, LDT2 0.0162 0.0430 0.0358 0.0352 0.0264 0.0395 0.0255 0.0297 0.0279 0.0287 0.0157 0.0318 0.0249 0.0289 0.0231 0.0162 0.0318 0.0515 0.0742 0.0830 0.0777 0.1313 0.0137 0.0127 0.0104

Prince William County, VA— 2002 Diesel Sales Fractions

* LDV
0.0026 0.0041 0.0040 0.0025 0.0019 0.0013 0.0011 0.0009 0.0007 0.0010 0.0009 0.0026 0.0005 0.0008 0.0006 0.0075 0.0100 0.0263 0.0525 0.1135 0.1290 0.1344 0.1553 0.0571 0.0089 * LDT1, LDT2 0.0431 0.0305 0.0334 0.0250 0.0189 0.0182 0.0171 0.0189 0.0131 0.0163 0.0164 0.0268 0.0679 0.0394 0.0460 0.0174 0.0318 0.0349 0.0458 0.0589 0.0796 0.0988 0.0782 0.0275 0.0264

Stafford County, VA—2002 Diesel Sales Fractions

* LDV 0.0107 0.0065 0.0074 0.0068 0.0053 0.0021 0.0030 0.0018 0.0004 0.0000 0.0024 0.0043 0.0012 0.0030 0.0014 0.0109 0.0114 0.0440 0.0627 0.0488 0.1189 0.1772 0.0667 0.0606 0.0100 * LDT1, LDT2 0.0223 0.0288 0.0362 0.0375 0.0178 0.0289 0.0314 0.0291 0.0192 0.0187 0.0202 0.0116 0.0173 0.0240 0.0182 0.0196 0.0312 0.0424 0.0689 0.0878 0.1625 0.1320 0.1200 0.0704 0.0245
School Bus—2002 Regional Diesel Sales Fractions

* All Other Vehicle Categories 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 * HDBS 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

D1-36Attachment 3 VMT Mix Fractions (Network, Lo cal, and Auto-Access to Transit)

VMT mix fractions for network, local, and auto-access to transit analyses ar e being provided for the 16 vehicle categories listed below.

LDV LDT1 LDT2 LDT3 LDT4 HDV2B HDV3 HDV4

HDV5 HDV6 HDV7 HDV8A H DV8B HDBS HDBT MC

VMT fractions are arranged in the format belo w for network, local, and auto-access for each jurisdiction. Further deta ils on the format for VMT fractions are available in the Mobile6 model user guide.

Network
Winter VMT Fractions (Arrange d in blocks of 2 rows)
Summer VMT Fractions (Arrange d in blocks of 2 rows)
Fall VMT Fractions (Arranged in blocks of 2 rows)

Local
Winter VMT Fractions (Arrange d in blocks of 2 rows)
Summer VMT Fractions (Arrange d in blocks of 2 rows)
Fall VMT Fractions (Arranged in blocks of 2 rows)

Auto-Access
Winter VMT Fractions (Arrange d in blocks of 2 rows)
Summer VMT Fractions (Arrange d in blocks of 2 rows)
Fall VMT Fractions (Arranged in blocks of 2 rows)

D1-372002 VMT Mix Fractions – District of Columbia

Network
0.4713 0.0762 0.2538 0.0781 0.0359 0.0242 0.0024 0.0021
0.0016 0.0060 0.0072 0.0080 0.0280 0.0000 0.0000 0.0052

0.4638 0.0774 0.2576 0.0799 0.0367 0.0242 0.0024 0.0021
0.0016 0.0060 0.0072 0.0080 0.0278 0.0000 0.0000 0.0053

0.4568 0.0787 0.2620 0.0806 0.0371 0.0243 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0280 0.0000 0.0000 0.0051

Local
0.5030 0.0814 0.2709 0.0834 0.0384 0.0053 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0061 0.0000 0.0000 0.0056

0.4951 0.0826 0.2749 0.0852 0.0392 0.0053 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0061 0.0000 0.0000 0.0057

0.4877 0.0840 0.2797 0.0861 0.0396 0.0053 0.0005 0.0005
0.0004 0.0013 0.0016 0.0017 0.0061 0.0000 0.0000 0.0055

Auto-Access 0.5119 0.0828 0.2757 0.0849 0.0390 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0057

0.5038 0.0840 0.2798 0.0867 0.0399 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0058

0.4964 0.0855 0.2846 0.0876 0.0403 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0056

D1-382002 VMT Mix Fractions – Charles County

Network
0.4626 0.0785 0.2613 0.0775 0.0356 0.0250 0.0024 0.0021
0.0016 0.0059 0.0070 0.0077 0.0277 0.0000 0.0000 0.0051

0.4560 0.0796 0.2649 0.0788 0.0362 0.0250 0.0024 0.0021
0.0016 0.0060 0.0070 0.0077 0.0276 0.0000 0.0000 0.0051

0.4483 0.0809 0.2695 0.0799 0.0368 0.0251 0.0024 0.0021
0.0016 0.0060 0.0071 0.0077 0.0276 0.0000 0.0000 0.0050

Local
0.4938 0.0838 0.2790 0.0827 0.0380 0.0055 0.0005 0.0005
0.0003 0.0013 0.0015 0.0017 0.0060 0.0000 0.0000 0.0054

0.4868 0.0849 0.2828 0.0841 0.0387 0.0055 0.0005 0.0005
0.0003 0.0013 0.0015 0.0017 0.0059 0.0000 0.0000 0.0055

0.4786 0.0864 0.2877 0.0853 0.0392 0.0055 0.0005 0.0005
0.0004 0.0013 0.0015 0.0017 0.0061 0.0000 0.0000 0.0053

Auto-Access 0.5025 0.0853 0.2839 0.0841 0.0387 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0055

0.4953 0.0864 0.2878 0.0856 0.0393 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0056

0.4871 0.0880 0.2928 0.0868 0.0399 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0054

D1-392002 VMT Mix Fractions – Fredrick County

Network
0.4631 0.0785 0.2613 0.0774 0.0356 0.0246 0.0024 0.0021
0.0016 0.0060 0.0071 0.0079 0.0277 0.0000 0.0000 0.0047

0.4570 0.0796 0.2650 0.0783 0.0360 0.0245 0.0024 0.0021
0.0016 0.0060 0.0071 0.0079 0.0278 0.0000 0.0000 0.0047

0.4488 0.0809 0.2695 0.0798 0.0367 0.0246 0.0024 0.0021
0.0016 0.0060 0.0071 0.0079 0.0280 0.0000 0.0000 0.0046

Local
0.4944 0.0838 0.2790 0.0826 0.0380 0.0054 0.0005 0.0005
0.0003 0.0013 0.0015 0.0017 0.0060 0.0000 0.0000 0.0050

0.4878 0.0850 0.2829 0.0836 0.0384 0.0053 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0060 0.0000 0.0000 0.0051

0.4791 0.0864 0.2877 0.0852 0.0392 0.0054 0.0005 0.0005
0.0004 0.0013 0.0016 0.0017 0.0061 0.0000 0.0000 0.0049

Auto-Access 0.5031 0.0853 0.2839 0.0840 0.0386 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0051

0.4964 0.0865 0.2878 0.0850 0.0391 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0052

0.4876 0.0880 0.2928 0.0867 0.0399 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0050

D1-402002 VMT Mix Fractions – Montgomery County

Network
0.4594 0.0790 0.2630 0.0785 0.0361 0.0243 0.0024 0.0021
0.0016 0.0060 0.0071 0.0080 0.0279 0.0000 0.0000 0.0046

0.4526 0.0801 0.2667 0.0798 0.0367 0.0243 0.0024 0.0021
0.0016 0.0060 0.0072 0.0080 0.0278 0.0000 0.0000 0.0047

0.4450 0.0815 0.2712 0.0809 0.0372 0.0243 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0280 0.0000 0.0000 0.0045

Local
0.4903 0.0843 0.2808 0.0838 0.0385 0.0053 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0062 0.0000 0.0000 0.0049

0.4832 0.0855 0.2847 0.0852 0.0392 0.0053 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0060 0.0000 0.0000 0.0050

0.4751 0.0870 0.2896 0.0864 0.0397 0.0053 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0062 0.0000 0.0000 0.0048

Auto-Access 0.5019 0.0821 0.2732 0.0941 0.0434 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0053

0.4942 0.0833 0.2774 0.0957 0.0441 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0053

0.4865 0.0847 0.2818 0.0971 0.0447 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0052

D1-412002 VMT Mix Fractions – Prince George’s County

Network
0.4645 0.0785 0.2614 0.0761 0.0350 0.0246 0.0024 0.0021
0.0016 0.0060 0.0071 0.0079 0.0276 0.0000 0.0000 0.0052

0.4579 0.0796 0.2651 0.0773 0.0355 0.0246 0.0024 0.0021
0.0016 0.0060 0.0071 0.0078 0.0278 0.0000 0.0000 0.0052

0.4501 0.0810 0.2696 0.0785 0.0361 0.0246 0.0024 0.0021
0.0016 0.0060 0.0072 0.0079 0.0278 0.0000 0.0000 0.0051

Local
0.4958 0.0838 0.2790 0.0812 0.0373 0.0054 0.0005 0.0005
0.0003 0.0013 0.0015 0.0017 0.0062 0.0000 0.0000 0.0055

0.4887 0.0850 0.2830 0.0825 0.0379 0.0054 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0061 0.0000 0.0000 0.0055

0.4806 0.0865 0.2878 0.0838 0.0385 0.0054 0.0005 0.0005
0.0004 0.0013 0.0016 0.0017 0.0060 0.0000 0.0000 0.0054

Auto-Access 0.5046 0.0853 0.2839 0.0826 0.0380 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0056

0.4973 0.0865 0.2880 0.0839 0.0387 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0056

0.4891 0.0880 0.2929 0.0853 0.0392 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0055

D1-422002 VMT Mix Fractions – Arlington County

Network
0.4652 0.0752 0.2503 0.0857 0.0394 0.0240 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0280 0.0000 0.0000 0.0048

0.4582 0.0763 0.2540 0.0873 0.0401 0.0241 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0278 0.0000 0.0000 0.0048

0.4508 0.0775 0.2581 0.0884 0.0407 0.0241 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0282 0.0000 0.0000 0.0047

Local
0.4965 0.0803 0.2672 0.0915 0.0421 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0061 0.0000 0.0000 0.0051

0.4891 0.0814 0.2711 0.0931 0.0428 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0063 0.0000 0.0000 0.0051

0.4813 0.0828 0.2756 0.0944 0.0434 0.0053 0.0005 0.0005
0.0004 0.0013 0.0016 0.0018 0.0061 0.0000 0.0000 0.0050

Auto-Access 0.5053 0.0817 0.2719 0.0931 0.0428 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0052

0.4977 0.0829 0.2759 0.0948 0.0435 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0052

0.4899 0.0843 0.2805 0.0961 0.0441 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0051

D1-432002 VMT Mix Fractions – Fairfax County

Network
0.4621 0.0756 0.2516 0.0867 0.0398 0.0239 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0279 0.0000 0.0000 0.0049

0.4549 0.0767 0.2554 0.0881 0.0405 0.0240 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0281 0.0000 0.0000 0.0049

0.4477 0.0779 0.2594 0.0894 0.0411 0.0240 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0282 0.0000 0.0000 0.0048

Local
0.4933 0.0807 0.2685 0.0925 0.0425 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0061 0.0000 0.0000 0.0052

0.4856 0.0819 0.2726 0.0941 0.0433 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0060 0.0000 0.0000 0.0053

0.4780 0.0832 0.2769 0.0954 0.0439 0.0052 0.0005 0.0005
0.0004 0.0013 0.0016 0.0018 0.0062 0.0000 0.0000 0.0051

Auto-Access 0.5019 0.0821 0.2732 0.0941 0.0434 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0053

0.4942 0.0833 0.2774 0.0957 0.0441 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0053

0.4865 0.0847 0.2818 0.0971 0.0447 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0052

D1-442002 VMT Mix Fractions – Loudoun County

Network
0.4651 0.0755 0.2512 0.0848 0.0390 0.0239 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0280 0.0000 0.0000 0.0050

0.4588 0.0765 0.2545 0.0862 0.0396 0.0240 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0279 0.0000 0.0000 0.0051

0.4509 0.0778 0.2589 0.0875 0.0403 0.0240 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0282 0.0000 0.0000 0.0049

Local
0.4965 0.0805 0.2681 0.0905 0.0416 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0062 0.0000 0.0000 0.0054

0.4897 0.0816 0.2717 0.0920 0.0423 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0061 0.0000 0.0000 0.0054

0.4814 0.0830 0.2765 0.0935 0.0430 0.0052 0.0005 0.0005
0.0004 0.0013 0.0016 0.0018 0.0060 0.0000 0.0000 0.0053

Auto-Access 0.5052 0.0820 0.2728 0.0921 0.0424 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0055

0.4983 0.0830 0.2765 0.0936 0.0431 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0055

0.4899 0.0845 0.2814 0.0951 0.0437 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0054

D1-452002 VMT Mix Fractions – Prince William County

Network
0.4691 0.0748 0.2491 0.0838 0.0385 0.0240 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0281 0.0000 0.0000 0.0052

0.4618 0.0760 0.2530 0.0852 0.0392 0.0241 0.0024 0.0021
0.0016 0.0061 0.0072 0.0080 0.0280 0.0000 0.0000 0.0053

0.4545 0.0773 0.2572 0.0864 0.0397 0.0241 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0282 0.0000 0.0000 0.0051

Local
0.5007 0.0799 0.2659 0.0894 0.0411 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0062 0.0000 0.0000 0.0056

0.4930 0.0811 0.2701 0.0910 0.0418 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0017 0.0062 0.0000 0.0000 0.0057

0.4853 0.0825 0.2747 0.0923 0.0424 0.0053 0.0005 0.0005
0.0004 0.0013 0.0016 0.0018 0.0059 0.0000 0.0000 0.0055

Auto-Access 0.5095 0.0813 0.2706 0.0910 0.0419 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0057

0.5016 0.0826 0.2748 0.0926 0.0426 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0058

0.4939 0.0840 0.2795 0.0939 0.0431 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0056

D1-462002 VMT Mix Fractions – City of Alexandria

Network
0.4597 0.0758 0.2523 0.0876 0.0403 0.0239 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0279 0.0000 0.0000 0.0050

0.4520 0.0770 0.2564 0.0892 0.0410 0.0239 0.0024 0.0021
0.0016 0.0061 0.0072 0.0081 0.0280 0.0000 0.0000 0.0050

0.4454 0.0781 0.2600 0.0904 0.0416 0.0239 0.0025 0.0021
0.0016 0.0061 0.0072 0.0081 0.0281 0.0000 0.0000 0.0049

Local
0.4907 0.0809 0.2693 0.0935 0.0430 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0061 0.0000 0.0000 0.0053

0.4824 0.0822 0.2737 0.0952 0.0438 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0061 0.0000 0.0000 0.0054

0.4755 0.0834 0.2776 0.0965 0.0444 0.0052 0.0005 0.0005
0.0003 0.0013 0.0016 0.0018 0.0062 0.0000 0.0000 0.0052

Auto-Access 0.4993 0.0823 0.2740 0.0952 0.0438 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0054

0.4909 0.0837 0.2785 0.0969 0.0446 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0054

0.4839 0.0849 0.2826 0.0982 0.0451 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0053

D1-472002 VMT Mix Fractions For School Bus and Transit Bus Analysis

VMT Mix Fractions Vehicle

Type School Bus Transit Bus

LDV 0.0000 0.0000 LDT1 0.0000 0.0000 LDT2 0.0000 0.0000 LDT3 0.0000 0.0000 LDT4 0.0000 0.0000 HDV2B 0.0000 0.0000 HDV3 0.0000 0.0000 HDV4 0.0000 0.0000 HDV5 0.0000 0.0000 HDV6 0.0000 0.0000 HDV7 0.0000 0.0000 HDV8A 0.0000 0.0000 HDV8B 0.0000 0.0000 HDBS 1.0000 0.0000 HDBT 0.0000 1.0000 MC 0.0000 0.0000

D1-481 DATE: December 11, 2007

To: Fine Particulate Matter (PM2.5) State Implementation Plan SIP Files

FROM: Eulalie G. Lucas
Daivamani Sivasailam Anant Choudhary Departm ent of Transportation Planning

SUBJECT: Procedures and Results of C onversion of 2002 W ashington, DC-MD-VA Mobile Source Emissions Inventories to National Emission Inventory Input Format (NIF): Direct PM 2.5 and PM 10 , SO 2 , NH 3 , NO X and VOC.

I. INTRODUCTION

This memo documents the procedures applied and results obtained for converting the 2002
annual m obile source emissions used to establish baseline conditions for PM2.5 SIP planning from a traditional transportation planning format to a format compatible with the Environmental Protection Agency’s (EPA) NIF3.0 format. Mobile6-based emissions originally prepared by transportation component, i.e., network emissions by trip start, running portion, and destination or hot soak, and off-network elements, were translated into estimates reflecting NIF requirements: exhaust vs. evaporative, facility type, county including rural and urban portions, and vehicle type.

II. REQUIREMENTS

A. Description of Mobile Inventories in Transportation Planning Format

Whereas some emissions inventories reflect the simple product of VMT data and aggregate running em issions factors, the COG emissions invent ories represent a disaggregate set of data in which separate emissions estimates are calculated by component of the trip cycle, e.g., startup, running, hot soak, diurnal and resting loss. See Exhibits 1 – 6 for year 2002 mobile source emissions inventory estimates of annual direct PM 2.5 , PM 10 , SO 2 , NH 3 , NO X , and VOC by jurisdiction and trip cycle. Exhibit 7 is an overview of the analysis structure used to create each component. The technical methods employed in generating Mobile source inventories are contained in the Air Quality Conformity Determination of the 2006 Constrained Long Range Plan and the FY 2007-2012 TIP, October 18, 2006 amended on June 20, 2007. While the TPB’s travel simulations provide the lion’s share of the transportation data (network travel), offline2 calculations are also required to prepare a comprehensive inventory. For example, as seen in Exhibit 6, this includes diurnal em issions which are a function of the number of gasoline fueled vehicles (or the number of gastanks) in the region, not VMT per se. In addition, off-network travel elements (not modeled explicitly in the TPB travel forecasting process), such as school and transit bus emissions (based on reported VMT), auto access to transit, and local street VMT, are separately analyzed for travel and emissions purposes.

B. NIF Format

EPA’s requirements for input into NIF format include data distributions by: exhaust / evaporative; facility type; vehicle type; and urban / rural designations within a county. Accordingly, the objective of this work effort was to translate these disaggregate transportation

em issions into the categories required for NIF processing. An overview of the approach for converting the existing COG emissions inventory categories into the NIF categories is shown in Exhibit 8. This overview chart shows that some conversions are readily achieved. For example, under emissions by vehicle type, school and trans it bus are computed directly from bus VMT data for each case and thus equate exactly with emissions by such vehicle types. Others are not so readily available. For example, under emissions by facility type, since diurnal emissions primarily occur while vehicles are parked, some assumptions need to be made as to where the parked vehicles are located. If parked in a gara ge, emissions would be ‘off the street system’ and therefore attributed to the local road system ; if parked on the street, emissions would be attributed to the facility type on which the vehicle is parked. The exhibit either directly classifies each component according to the NIF requirements or provides an approach to doing so. The specifics of converting each element in the transportation inventories are contained in the following section.

III. DATA TRANSLATION

The first step involved review of each existi ng inventory com ponent in light of the NIF requirements to determine the best means of translating it from one format to the other. Each NIF category is discussed in turn below.

A. Exhaust / Evaporative

Exhaust emissions occur when the engine is operating, and most often are tailpipe related, however, a sm all percentage of emissions occurs through what is know as ‘running loss’. These emissions may appear from numerous locations on a vehicle such as the evaporative canister, the fuel inlet or broken hoses or pipes in other parts of the engine. Exhaust emissions are calculated as grams per mile and are VMT dependent. There are some exhaust emissions associated with the start or origin component of the trip cycle; these emissions are calculated in grams per trip. All six pollutants, direct PM 2.5 , PM 10 , SO 2 , NH 3 , NO X , and VOC are present in exhaust
emissions.3 Evaporative emissions are associated with three characteristics of (gasoline-fueled) vehicles: ‘hot soaks’ or trip end, diurnal, and resting loss and running loss. Diurnal and resting loss

em issions are present regardless of vehicle activity and are calculated as grams per vehicle. Hot soak emissions are calculated as grams per trip. Only VOC are present in evaporative emissions.

Exhibit 8 shows that all components can be directly categorized as either being exhaust or evaporative. Such classifications are shown with an ‘x’ in the appropriate colum n.

B. Facility Type

As noted above, in some cases assumptions are needed to enable translation of data in existing transportation categories into the required NIF f acility type estimates. Each of the categories is
addressed in turn below.

1. Network Start Emissions

Cold starting vehicles will likely traverse several different facility types in the course of warming up to stabilized operating conditions. Since longer trips generally occur on freeways, i.e., freeways would have generally lower percentages of cold starting vehicles. Rather than use aggregate VMT distributions as a basis for this translation it is m ore appropriate to consider a supply side variable. For this reason we selected lane miles by facility type to provide a reasonable indicator of this distribution. In other words, the likelihood of cold starting vehicles being on a given class of facilities is proportional to the attractiveness or availability of that class of facilities. Data on lane miles by facility type were readily available for the three states (District of Columbia, Maryland, and Virginia) and broken down by rural and urban in the Federal Highway Administration’s Highway Statistics document (Table HM-20 miles by functional system). Exhibit 8 identifies this se t of assumptions between cold starts and lane miles; Exhibit 9 shows the actual percentages used for the jurisdictions. The percentages were renormalized if a jurisdiction does not have any interstate highway (Loudoun County, Calvert County) or rural highways (Arlington County, Fairfax County).

2. Network Running Emissions/Running Loss

These emissions equate with actual usage by facility type seen in each county, so a direct translation is perf ormed. The percentages for all the facility types except local streets, and broken up as rural and urban, are shown in Exhibit 9. The regional travel demand model uses a highway network which shows all facility types except local streets. The running emissions for local streets are therefore estimated by using base year 2000 HPMS-supplied local street VMT information by jurisdiction, which is growth-factored to represent the analysis year. The factor is based on the growth in VMT as estimated by the regional model.4 Running Loss

These emissions occur while the engine is in stabilized mode, but are not associated with tailpipe exhaust em issions and are considered evaporative. Unlike other evaporative type emission such as diurnal that occur when the engine is turned off and were distributed on local streets only, these emissions were distributed on all facility types and were associated with gas-operated vehicles only.

3. Network Hot Soak Emissions

These emissions occur at the conclusion of a vehicle trip. The facility type associated with the

em issions therefore relates to where the vehicle is parked. These parked vehicles, again, should relate to parking supply; however, since parking is not permitted on freeways, percentages of facility lane miles in each county were computed excluding freeway and expressway lane miles. Data on lane miles by facility type were readily available for the three states (District of Columbia, Maryland, and Virginia) and broken down by rural and urban in the Federal Highway Administration’s Highway Statistics document (Table HM-20 miles by functional system). See Exhibit 8 for the format mapping and Exhibit 9 for actual percentages used in the calculations for all the jurisdictions.

4. Diurnal Emissions

These emissions also equate to parking availability; as with hot soaks, lane miles excluding freeways are used for the translation.

5. Resting Loss

These emissions are handled consistent with diurnals and hot soaks.

6. Auto Access Emissions

This component of travel addresses transit trips which use autos to access the transit system, e.g., a transit tripm aker who drives to, and parks at, a Metro station. Transit assignments are not routinely performed in executing the travel demand estimates used to develop mobile inventories, therefore, these vehicles are not included in the transportation network analysis. Since these vehicle trips do produce emissions, however, they are addressed through offline analysis. Such trips incur start, running, and soak emissions and translation into the NIF5 components is the same as with the network analysis approach.

7A. School Bus Emissions

These emissions relate directly to VMT data obt ained from each jurisdiction in the region. Staff prepared estimates of travel by facility type in urban and rural jurisdictions based upon inspection of route maps in Montgomery, Calvert, Arlington, Fairfax and Prince William counties. These percentages are shown in Exhibit 9 and were used to allocate school bus emissions into the appropriate facility type categories.

7B. Transit Bus Emissions

These emissions relate directly to VMT data obtained from each transit provider in the region. Staff prepared estim ates of travel by facility type through inspection of route maps for each transit operator. The resulting percentages are shown in Exhibit 9 and were used to allocate the bus emissions into the appropriate facility type categories.

8. Local Road Emissions

By definition, all of these emissions occur on the local roads in each jurisdiction.

C. Vehicle Type

The Mobile6 model utilizes up to 28 different vehicle (and fuel) types in its calculations and a
‘VMT m ix’ (for each jurisdiction) results from the model’s application. COG’s modeling procedures tailor the analysis to represent further disaggregation of travel categories for specific applications: traffic stream, commuter, and vehicl e-specific. ‘Vehicle-specific’ refers to the separate analysis of school bus and transit bus emissions in which only the bus VMT associated with each category is considered. For example, school bus emissions = school bus VMT x emissions factors specific to school buses (i.e., at a 100% school bus VMT mix). Consistent with this approach, the ‘traffic stream’ VMT mix refers to all other traveling vehicles, and VMT mix percentages reflect the general traffic stream (minus the bus VMT shares).

Similarly, vehicles used for commuting travel purposes, such as those considered in the auto

access com ponent, have a somewhat different VM T mix, e.g., tractor trailers and other heavy duty truck types are not used for commuting and are excluded when developing this component of the emissions inventory. The resulting emissions , which are computed using specific vehicle type data for VMT mix, therefore needed to be considered separately (maintaining consistency regarding the input vehicle mix) in the translation to the NIF vehicle type categories, as seen in Exhibit 8. Note also that evaporative emissions result from gas vehicles only, so further refinements are made to associate evaporative emissions with only these vehicles.6 D. Urban / Rural Designation Within Each County

A number of counties in the Washington area contain portions which are classified as rural. Since the NIF requirem ents include a separate listing of such emissions, staff translated the total county emissions into separate urban / rural components. HPMS disaggregations for each county provided the data source for this work.

IV. APPLICATION / RESULTS

Following the specification of all of the ‘translation percentages’ for each required data element staff prepared a series of spreadsheets to conve rt each inventory com ponent into the more fine grained disaggregations. Specifically, each transportation component was split into its component parts (exhaust / evaporative, urban / rural, facility type, and vehicle type) and then summarized to produce the tables shown in the attachment. Because emissions rates vary by pollutant it was necessary to develop a weighted rate for each pollutant to estimate emissions by vehicle type. The first step involved multiplying the VMT mix percentage developed by the mobile model by the emissions rate for each vehicle type. The product is then renormalized to obtain the weighted VMT mix for each pollutant and is shown as Exhibit 10

. The following paragraph highlights emission results of the 2002 NIF.

The products of the disaggregation for each pollutant type (direct PM 2.5 , PM 10 , SO 2 , NH 3 , NO X , and VOC) are individual tables providing emissions by vehicle type and facility type, urban and rural (see Exhibits 11-16). A similar disaggregate table for VMT was also prepared and is shown as Exhibit 17. Vehicle type distributions for these exhibits are in the NIF format as shown in Exhibit 18. Emissions may not be identical with COG\TPB emission summaries shown in Exhibits 1-6 due to rounding. Summaries of emissions and VMT by jurisdictions are available upon request for the twenty-eight vehicle types and facility types used in the Mobile model and were also transmitted via e-mail to Sunil Kumar on December 11, 2007.

Following:

Exhibits 1 - 18

cc: Mike Clifford
Joan Rohlfs
Erin Morrow
Mobile Source SIP FileMOBILE SOURCE EMISSIONSBY JURISDICTION AND TRIP CYCLEPM 2.5 SIP BASE YEAR 2002DIRECT PM2.5(TONS PER YEAR)JURIS RUNNING TOTALCYCLENETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESSDC119.92 11.01 22.982.160.20 156.27MONTG 278.18 10.92 18.45 14.680.43 322.65PG305.76 10.34 15.37 16.220.89 348.59CHAS35.95 2.190.483.050.05 41.73FRED116.66 4.871.604.940.15 128.21ARL61.43 1.955.130.440.13 69.07FFX373.80 17.12 14.62 14.060.66 420.26LDN67.49 5.962.344.710.07 80.58PR W103.06 7.422.595.330.29 118.69ALEX29.41 3.415.380.340.11 38.65TOTAL 1,491.66 75.18 88.93 65.962.97 1,724.69TOTALEMISSIONS1,724.69VEHICLE RELATEDEMISSIONSEXHIBIT 1MOBILE SOURCE EMISSIONSBY JURISDICTION AND TRIP CYCLEPM 2.5 SIP BASE YEAR 2002DIRECT PM10(TONS PER YEAR)JURIS RUNNING TOTALCYCLENETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESSDC176.11 19.47 25.28 2.3900.37 223.62MONTG 405.28 18.89 20.30 16.2210.80 461.49PG 441.96 17.43 16.91 17.928 1.68 495.90CHAS 51.13 3.65 0.53 3.372 0.09 58.78FRED 168.31 8.40 1.76 5.464 0.27 184.20ARL 90.06 3.29 5.64 0.488 0.24 99.71FFX 540.84 29.38 16.08 15.538 1.24 603.08LDN 98.85 10.13 2.58 5.208 0.13 116.90PR W 151.08 12.68 2.85 5.891 0.54 173.04ALEX 43.13 5.84 5.92 0.381 0.20 55.47TOTAL 2166.750 129.15 97.84 72.88 5.57 2472.19TOTALEMISSIONS2472.186VEHICLE RELATEDEMISSIONSEXHIBIT 2MOBILE SOURCE EMISSIONSBY JURISDICTION AND TRIP CYCLEPM 2.5 SIP BASE YEAR 2002SO2(TONS PER YEAR)JURIS RUNNING TOTALCYCLENETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESSDC242.43 30.32 15.211.210.71 289.88MONTG 619.01 35.11 12.218.181.54 676.06PG650.47 31.65 10.179.043.23 704.57CHAS72.93 6.500.321.700.18 81.63FRED253.10 15.191.062.760.53 272.63ARL130.82 6.143.390.250.46 141.06FFX 803.39 53.07 9.68 7.84 2.38 876.35LDN 146.85 18.07 1.55 2.63 0.26 169.36PR W 221.69 22.48 1.71 2.97 1.05 249.90ALEX 63.51 10.90 3.56 0.19 0.39 78.56TOTAL 3,204.20 229.42 58.88 36.75 10.73 3,539.98TOTALEMISSIONS3,539.98VEHICLE RELATEDEMISSIONSEXHIBIT 3MOBILE SOURCE EMISSIONSBY JURISDICTION AND TRIP CYCLEPM 2.5 SIP BASE YEAR 2002NH3(TONS PER YEAR)JURIS RUNNING TOTALCYCLENETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESSDC323.85 57.500.700.081.24 383.37MONTG 734.18 54.910.560.552.68 792.88PG774.80 49.280.470.615.61 830.77CHAS84.63 9.890.010.110.31 94.96FRED291.96 23.490.050.180.91 316.59ARL164.86 9.800.160.020.80 175.63FFX947.79 81.680.440.524.13 1,034.57LDN 179.55 28.39 0.07 0.18 0.45 208.63PR W 273.68 35.23 0.08 0.20 1.82 311.00ALEX 79.13 17.25 0.16 0.01 0.67 97.22TOTAL 3,854.43 367.41 2.70 2.46 18.62 4,245.63TOTALEMISSIONS4,245.63VEHICLE RELATEDEMISSIONSEXHIBIT 4MOBILE SOURCE EMISSIONSBY JURISDICTION AND TRIP CYCLEPM 2.5 SIP BASE YEAR 2002Precursor NOx (TONS PER YEAR)JURIS ORIGINRUNNINGTOTALCYCLENETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESSDC709.72 6,845.55 637.17 561.17 43.6030.16 8,827.37MONTG 1,302.36 15,293.89 590.44 450.55 227.1065.13 17,929.47PG1,131.19 17,310.28 567.29 375.29 251.01 136.53 19,771.59CHAS187.44 1,636.39 126.08 11.83 47.217.62 2,016.57FRED343.31 7,146.16 295.35 38.99 76.5022.22 7,922.53ARL 331.39 3,552.73 105.35 125.19 7.15 19.58 4,141.39FFX 1,493.67 20,271.62 876.94 357.05 217.54 100.56 23,317.38LDN 279.92 3,734.78 326.59 57.17 72.91 10.91 4,482.29PR W 406.32 5,994.37 414.87 63.20 82.47 44.24 7,005.48ALEX 199.20 1,631.63 177.08 131.49 5.58 16.26 2,161.24TOTAL 6,384.52 83,417.40 4,117.16 2,171.94 1,031.07 453.21 97,575.31TOTALEMISSIONS97,575.31VEHICLE RELATEDEMISSIONSEXHIBIT 5MOBILE SOURCE EMISSIONSBY JURISDICTION AND TRIP CYCLEPM 2.5 SIP BASE YEAR 2002VOC (TONS PER YEAR)JURIS ORIGINRUNNING DESTINATIONVEHICLE RELATEDTOTALEMISSIONSCYCLENETWORK LOCALDIURNAL REST. LOSS TRANSIT BUS SCHOOL BUS AUTO ACCESSDC1,598.91 1,982.21 535.52 400.91 40.22 292.34 32.634.04 26.47 4,913.24MONTG 2,768.96 3,548.04 441.90 702.70 83.93 537.87 26.2016.54 57.16 8,183.30PG2,500.29 3,947.74 473.88 639.91 88.71 597.39 21.8217.25 119.83 8,406.81CHAS427.74 442.64 80.12 99.73 19.34 128.070.693.246.69 1,208.25FRED772.46 1,299.28 188.63 172.01 30.68 206.662.275.26 19.50 2,696.75ARL728.60 817.87 85.75 194.53 18.65 121.847.280.55 17.18 1,992.25FFX3,237.07 4,440.10 679.56 857.97 100.08 637.58 20.7614.95 88.26 10,076.33LDN639.24 841.81 204.75 157.53 24.83 158.533.325.019.57 2,044.61PR W916.80 1,275.60 293.43 236.46 46.24 304.433.685.67 38.83 3,121.13ALEX435.17 419.44 137.77 117.07 17.48 111.967.650.43 14.27 1,261.24TOTAL 14,025.24 19,014.73 3,121.31 3,578.82 470.15 3,096.67 126.3172.92 397.76 43,903.91TOTALEMISSIONS43,903.91EXHIBIT 6

## EXHIBIT 7

Analysis Structure for On-Road Mobile Source Emissions

Transportation Emission Component X Factor = Emissions

A. Network 1. Trip origins Cold start rate Startup (g/trip)

2. VMT Stabilized rate Running (g/mile)

3. Trip destinations Hot soak Hot soak (g/trip)

B. Off-Network 4. Number of vehicles Diurnal rate Diurnal (gasoline fueled) (g/day) evaporative

5. Number of vehicles Resting loss Resting loss (gasoline fueled) (g/day)

6. Auto access to transit Travel components Startup, running, (above) hot soak

7. School & transit bus VMT (HDDV) Stabilized rate Running (g/mile)

8. Local Road VMT Stabilized Rate (g/mile) RunningwExhibit 8Summary Table of Emissions Inventory Components(Facility Type and Vehicle Type Percentages Vary by Jurisdiction)2002 Baseline Inventories (AnnualDirect PM2.5, PM10,SO2,NH3,NOX,VOC)COG INVENTORY DATANIF REQUIREMENTSCategoryTransportationExhaustEvaporativeFacility TypeVehicle TypeEmissions TypeComponentHPMSLane miles w/fwyLane miles wo/fSchoolTransitTraffic StreamCommuterVehicleANetwork'Parking'DistrictService AreaSpecific1. StartTrip OriginsXXX2. RunningVMTXXXX3. Hot SoakTrip DestinationsXXX(gas)BOff-Network4. DiurnalNumber of VehiclesXXX(gas)5. Resting LossNumber of VehiclesXXX(gas)6. Auto Access to TransitStartTrip OriginsXXXRunningRunning VMTXXXX(gas)Hot SoaksTrip DestinationsXXX(gas)7a. School BusVMTXX7b. Transit BusVMTXXXX8. LocalVMTXXXExhibit 9 A Percentages forEmissions Distribution by Facility Typ e HPMS Lane w/fwy Lane wo/fwy Sch.Dist Tran.Serv. Facility Type % VMT % VMT (start ) % VMT (soak) % VMT % VMT
DC

Urban
Interstate 0.14 0.01 0.01 Other Frwy & Expwy 0.14 0.01 0.02 Other Principal Arterial 0.34 0.06 0.06 0.23 0.02
Minor Arterial 0.28 0.11 0.12 0.13 0.40
Collector 0.10 0.10 0.10 0.13 0.50 Local (see footnote) 0.71 0.72 0.51 0.05

Montg.Co. Facility Type

Rural
Interstate 0.03 0.01 0.05
Other Prin. Art. 0.00 0.03 0.03 0.20
Minor Arterial 0.03 0.06 0.06 0.23 0.20 Major Collector 0.03 0.11 0.12 0.13 0.25
Minor Collector 0.01 0.12 0.12 0.13 0.25 Local (see footnote) (se e 0.00 0.66 0.67 0.51 0.05

Urban
Interstate 0.35 0.02 0.02 Other Frwy & Expwy 0.02 0.02 0.03 Other Principal Arterial 0.29 0.06 0.06 0.23 0.20
Minor Arterial 0.17 0.08 0.09 0.13 0.20 Collector 0.08 0.09 0.09 0.13 0.50 Local (see footnote) 0.74 0.76 0.51 0.07

Prince George's Facility Type

Rural
Interstate 0.00 0.01 0.05 Other Prin. Art. 0.04 0.03 0.03 0.20
Minor Arterial 0.00 0.06 0.06 0.23 0.20 Major Collector 0.01 0.11 0.12 0.13 0.25 Minor Collector 0.00 0.12 0.12 0.13 0.25 Local (see footnote) (se e 0.00 0.66 0.67 0.51 0.05

Urban
Interstate 0.36 0.02 0.02 Other Frwy & Expwy 0.18 0.02 0.03 Other Principal Arterial 0.21 0.06 0.06 0.23 0.20
Minor Arterial 0.12 0.08 0.09 0.13 0.20 Collector 0.06 0.09 0.09 0.13 0.50 Local (see footnote) 0.74 0.76 0.51 0.07Exhibit 9 B Percentages forEmissions Distribution by Facility Typ e HPMS Lane w/fwy Lane wo/fwy Sch.Dist Tran.Serv. Facility Type % VMT % VMT (start ) % VMT (soak) % VMT % VMT

Frederick Facility Type

Rural
Interstate 0.32 0.01 0.05 Other Prin. Art. 0.18 0.03 0.03 0.20
Minor Arterial 0.06 0.06 0.06 0.23 0.20 Major Collector 0.12 0.11 0.12 0.13 0.25 Minor Collector 0.05 0.12 0.12 0.13 0.25 Local (see footnote) (se e 0.66 0.67 0.51 0.05

Urban
Interstate 0.07 0.02 0.02 Other Frwy & Expwy 0.07 0.02 0.03 Other Principal Arterial 0.04 0.06 0.06 0.23 0.20
Minor Arterial 0.05 0.08 0.09 0.13 0.20 Collector 0.04 0.09 0.09 0.13 0.50 Local (see footnote) 0.74 0.76 0.51 0.07

Charles Facility Type

Rural
Interstate 0.00 0.00 Other Prin. Art. 0.37 0.03 0.03 0.21
Minor Arterial 0.10 0.06 0.06 0.23 0.21 Major Collector 0.16 0.12 0.12 0.13 0.26 Minor Collector 0.05 0.12 0.12 0.13 0.26 Local (see footnote) 0.67 0.67 0.51 0.05

Urban
Interstate 0.00 0.00 Other Frwy & Expwy 0.00 0.03 Other Principal Arterial 0.23 0.06 0.06 0.23 0.20
Minor Arterial 0.04 0.12 0.12 0.13 0.20 Collector 0.06 0.12 0.12 0.13 0.50 Local (see footnote) 0.70 0.70 0.51 0.07

Arlington Facility Type

Urban
Interstate 0.48 0.02 . 0.03 Other Frwy & Expwy 0.17 0.01 0.02 Other Principal Arterial 0.23 0.06 0.06 0.23 0.19
Minor Arterial 0.08 0.11 0.11 0.13 0.20 Collector 0.04 0.10 0.10 0.13 0.51 Local (see footnote) 0.71 0.73 0.51 0.05Exhibit 9 C Percentages forEmissions Distribution by Facility Typ e HPMS Lane w/fwy Lane wo/fwy Sch.Dist Tran.Serv. Facility Type % VMT % VMT (start ) % VMT (soak) % VMT % VMT

Alexandria Facility Type

Urban
Interstate 0.41 0.02 . 0.03 Other Frwy & Expwy 0.00 0.01 0.02 Other Principal Arterial 0.25 0.06 0.06 0.23 0.21
Minor Arterial 0.29 0.11 0.11 0.13 0.21
Collector 0.05 0.10 0.10 0.13 0.51 Local (see footnote) 0.71 0.73 0.51 0.05

Fairfax County Facility Type

Urban
Interstate 0.37 0.02 . 0.03 Other Frwy & Expwy 0.07 0.01 0.02 Other Principal Arterial 0.28 0.06 0.06 0.23 0.21
Minor Arterial 0.22 0.11 0.11 0.13 0.21
Collector 0.06 0.10 0.10 0.13 0.51 Local (see footnote) 0.71 0.73 0.51 0.05

Loudoun Facility Type

Rural
Interstate 0.00 0.00
Other Prin. Art. 0.30 0.03 0.03 0.05
Minor Arterial 0.13 0.07 0.07 0.23 0.40 Major Collector 0.17 0.19 0.19 0.13 0.25
Minor Collector 0.02 0.05 0.05 0.13 0.25 Local (see footnote) 0.00 0.66 0.66 0.51 0.05

Urban
Interstate 0.00 0.00 . 0.00 Other Frwy & Expwy 0.12 0.01 0.02 Other Principal Arterial 0.14 0.06 0.06 0.23 0.21
Minor Arterial 0.09 0.11 0.11 0.13 0.21
Collector 0.03 0.10 0.10 0.13 0.51 Local (see footnote) 0.73Exhibit 9 D Percentages forEmissions Distribution by Facility Typ e HPMS Lane w/fwy Lane wo/fwy Sch.Dist Tran.Serv. Facility Type % VMT % VMT (start ) % VMT (soak) % VMT % VMT

Prince William Facility Type

Rural
Interstate 0.24 0.01 Other Prin. Art. 0.09 0.03 0.03 0.05
Minor Arterial 0.08 0.07 0.07 0.23 0.40 Major Collector 0.08 0.19 0.19 0.13 0.25 Minor Collector 0.00 0.05 0.05 0.13 0.25 Local (see footnote) 0.00 0.65 0.66 0.51 0.05

Urban
Interstate 0.14 0.02 . 0.03 Other Frwy & Expwy 0.00 0.01 0.02 Other Principal Arterial 0.07 0.06 0.06 0.23 0.19
Minor Arterial 0.25 0.11 0.11 0.13 0.20 Collector 0.04 0.10 0.10 0.13 0.51 Local (see footnote) 0.71 0.73 0.51 0.05

Footnote: Local road VMT is taken directly from HPMS reports.Exhibit 10Steps used in the preparation of weighted VMT mix percentsRates illustrated are for the District of Columbia2002 NOX Emission RatesExhaust Emissions FactorLDGV LDGT12 LDGT34 LDGT HDGV LDDV LDDT HDDV MCAFreeway 0.786 0.841 1.07 0.899 4.928 1.291 1.333 16.906 0.85Art/Coll 0.757 0.803 1.036 0.863 4.572 1.1820 1.221 12.185 0.78Local 0.825 0.83 1.088 0.896 3.787 1.654 1.695 13.042 0.82VMT MixLDGV LDGT12 LDGT34 LDGT HDGV LDDV LDDT HDDV MCB network 0.4631 0.3349 0.1150 0.0222 0.0007 0.0017 0.0571 0.0053 0.0053 1.0local 0.4943 0.3575 0.12260.0056 0.001323 0.0008 0.016039 0.0018 1.0Weighted VMT mix percentsC=A*BFreeway 36.400 28.165 12.305 1.996 0.345 0.219 7.611 8.960 0.451 96.452Art/Coll 35.057 26.892 11.914 1.916 0.320 0.201 6.972 6.458 0.413 90.143Local 40.784 29.671 13.336 0.000 2.112 0.219 0.137 20.918 0.148 107.325Weighted VMT percents by vehicle type for exhaust emissionsD=Normalized C Freeway 0.377 0.292 0.128 0.021 0.004 0.002 0.079 0.093 0.005 1Art/Coll 0.389 0.298 0.132 0.021 0.004 0.002 0.077 0.072 0.005 1Local 0.380 0.276 0.124 0.000 0.020 0.002 0.001 0.195 0.001 1Vehicle Types are from the EPA Mobile Model outputLDGVLight-Duty Gasoline Vehicles (Passenger Cars)LDGT12Light-Duty Gasoline Trucks LT 6,000 lbsLDGT34Light-Duty Gasoline Trucks greater than 6,000 lbsLDGT(all)Light-Duty Gasoline TrucksHDGVAllweightsHeavy-DutyGasolineVehiclesMCMotorcycles (Gasoline)LDDVLight-Duty Diesel Vehicles (Passenger Cars)LDDTLight-Duty Diesel TrucksHDDVAll weights Heavy-Duty Diesel VehiclesEXHIBIT 11MOBILE SOURCE EMISSIONSBY VEHICLE AND FACILITY TYPEPM 2.5 SIP BASE YEAR 2002DIRECT PM2.5 EMISSIONS (TONS PER YEAR)Facility TypeEmissRuralLDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV BUSES HHDDVInterstate71 11 9 4 4 0 0 0 1 1 6 0 34Other Principal Arterial79 17 13 6 5 00 0 1 1 5 1 28Minor Arterial42 8 6 3 3 0 0 0 1 1 2 5 13Major Collector55 11 9 4 4 0 0 0 1 1 3 4 19Minor Collector15 3 2 1 1 0 0 0 0 0 1 4 4Local22 5 4 2 0 0 0 0 0 0 0 7 2UrbanInterstate426 77 63 29 25 10 2 6 6 28 2 186Other Frwy & Expwy133 30 23 11 9 00 0 2 2 8 2 46Other Principal Arterial367 77 61 28 22 10 1 5 5 21 24 122Minor Arterial281 57 45 21 16 10 1 4 3 15 28 90Collector141 21 17 8 6 00 0 1 1 6 48 33Local92 23 17 8 1 00 0 0 0 2 318Total1,725 342 270 125 96 42 6 22 21 96 155 586% Emissions19.82% 15.65% 7.26% 5.57% 0.22% 0.10% 0.36% 1.30% 1.22% 5.54% 8.98% 33.97%Emissions by Vehicle TypeEXHIBIT 12MOBILE SOURCE EMISSIONSBY VEHICLE AND FACILITY TYPEPM 2.5 SIP BASE YEAR 2002DIRECT PM10 EMISSIONS (TONS PER YEAR)Facility TypeEmissRuralLDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV BUSES HHDDVInterstate104 17 13 6 6 0012 28049Other Principal Arterial114 25 20 9 8 0012 27141Minor Arterial60 12 9 4 4 0001 13620Major Collector79 16 13 6 5 0001 15427Minor Collector21 43 1 1 0 0 0 0 0 1 4 6Local32 97 3 0 0 0 0 0 0 1 8 3UrbanInterstate618 113 91 42 36 2129 9 412271Other Frwy & Expwy192 43 34 16 12 0013 3 11267Other Principal Arterial526 112 89 41 33 1127 7 30 26178Minor Arterial399 83 65 31 24 1015 5 22 31131Collector188 31 24 11 9 0002 28 5348Local139 40 30 14 2 0011 13 3513Total2,472 505 398 185 140 639 33 31 139 171854% Emissions20.42% 16.11% 7.48% 5.66% 0.23% 0.11% 0.37% 1.32% 1.24% 5.64% 6.91% 34.53%Emissions by Vehicle TypeEXHIBIT 13MOBILE SOURCE EMISSIONSBY VEHICLE AND FACILITY TYPEPM 2.5 SIP BASE YEAR 2002SO2EMISSIONS (TONS PER YEAR)Facility TypeEmissRuralLDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV BUSES HHDDVInterstate97 16 13 6 5 00 1 2 2 8 0 46Other Principal Arterial200 44 34 16 14 00 1 3 3 12 1 72Minor Arterial90 19 15 7 6 00 0 1 1 5 3 32Major Collector121 26 20 9 8 00 1 2 2 7 2 43Minor Collector28 6 4 2 2 0 0 0 0 0 2 2 9Local47 16 12 6 1 00 0 0 0 1 46UrbanInterstate904 165 134 61 53 21 3 13 13 60 1 396Other Frwy & Expwy268 61 48 22 17 10 1 4 4 16 1 94Other Principal Arterial786 173 137 64 51 21 3 11 10 46 15 274Minor Arterial560 122 96 45 35 11 2 8 7 32 18 193Collector235 46 36 17 13 00 1 3 3 12 31 73Local204 72 53 25 3 10 1 1 1 5 18 24Total3,540 765 602 280 209 94 14 48 45 206 96 1,262% Emissions21.62% 17.02% 7.90% 5.91% 0.24% 0.11% 0.39% 1.37% 1.28% 5.82% 2.70% 35.64%Emissions by Vehicle TypeEXHIBIT 14MOBILE SOURCE EMISSIONSBY VEHICLE AND FACILITY TYPEPM 2.5 SIP BASE YEAR 2002NH3EMISSIONS (TONS PER YEAR)Facility TypeEmissRuralLDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV BUSES HHDDVInterstate183 30 24 11 10 00 1 3 3 14 0 87Other Principal Arterial198 43 34 16 14 00 1 3 3 12 0 71Minor Arterial97 21 17 8 7 00 0 1 1 6 0 35Major Collector134 29 23 11 9 00 1 2 2 8 0 48Minor Collector30 7 5 2 2 0 0 0 0 0 2 0 11Local68 26 19 9 1 00 1 0 0 2 09UrbanInterstate1,099 202 163 75 65 31 4 16 15 73 0 482Other Frwy & Expwy338 77 61 28 22 10 1 5 4 20 0 119Other Principal Arterial893 201 159 74 58 21 3 13 12 53 1 317Minor Arterial661 149 117 55 43 21 2 9 9 39 1 234Collector244 55 43 20 16 10 1 3 3 14 1 86Local301 115 85 40 6 11 2 2 2 8 1 38Total4,246 955 750 349 251 115 17 59 55 252 5 1,536% Emissions22.50% 17.68% 8.21% 5.92% 0.25% 0.12% 0.41% 1.39% 1.30% 5.93% 0.12% 36.17%Emissions by Vehicle TypeEXHIBIT 15MOBILE SOURCE EMISSIONSBY VEHICLE AND FACILITY TYPEPM 2.5 SIP BASE YEAR 2002Precursor NOXEMISSIONS (TONS PER YEAR)Facility TypeEmissRuralLDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV BUSES HHDDVInterstate4,249 688 555 252 226 115 24 76 71 331 5 2,004Other Principal Arterial4,403 962 761 353 302 114 21 64 59 267 25 1,574Minor Arterial2,250 469 374 175 147 52 10 32 29 132 98 776Major Collector3,142 671 534 249 211 83 14 45 42 188 71 1,106Minor Collector830 167 133 60 53 21 3 11 10 46 71 272Local1,567 451 339 161 59 42 12 15 14 61 118 332UrbanInterstate23,800 4,361 3,535 1,618 1,396 59 28 86 354 332 1,572 40 10,418Other Frwy & Expwy7,521 1,711 1,337 614 487 187 24 106 99 440 44 2,634Other Principal Arterial19,860 4,370 3,445 1,605 1,263 46 21 65 276 258 1,154 477 6,882Minor Arterial15,315 3,318 2,610 1,224 950 35 16 53 209 196 876 617 5,210Collector6,851 1,302 1,024 474 374 146 19 82 76 341 1,107 2,033Local7,788 2,171 1,645 771 316 19 12 39 77 73 323 531 1,811Total97,575 20,642 16,291 7,557 5,785 232 107 370 1,346 1,260 5,731 3,203 35,052% Emissions21.15% 16.70% 7.75% 5.93% 0.24% 0.11% 0.38% 1.38% 1.29% 5.87% 3.28% 35.92%Emissions by Vehicle TypeEXHIBIT 16MOBILE SOURCE EMISSIONSBY VEHICLE AND FACILITY TYPEPM 2.5 SIP BASE YEAR 2002VOC EMISSIONS (TONS PER YEAR)Facility TypeEmissRuralLDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV BUSES HHDDVInterstate317 161 82 47 11 60 1 0 0 2 07Other Principal Arterial42 21 11 6 1 10 0 0 0 0 10Minor Arterial411 209 106 62 15 60 1 0 0 2 28Major Collector505 259 131 77 18 70 1 1 0 2 28Minor Collector235 121 61 36 8 30 0 0 0 1 22Local964 504 259 151 31 140 1 0 0 0 31UrbanInterstate5,341 2,725 1,411 783 175 762 10 7 6 29 1 115Other Frwy & Expwy1,597 809 442 224 47 231 3 2 2 9 1 33Other Principal Arterial7,138 3,623 1,910 1,024 223 1193 13 9 8 36 29 141Minor Arterial6,087 3,103 1,647 867 182 1032 9 6 6 24 43 95Collector3,814 1,950 1,031 545 115 651 4 3 2 10 50 40Local17,453 9,151 4,856 2,567 476 3112 7 1 1 3 65 14Total43,904 22,636 11,946 6,388 1,303 732 12 49 29 27 119 199 465% Emissions51.56% 27.21% 14.55% 2.97% 1.67% 0.03% 0.11% 0.07% 0.06% 0.27% 0.45% 1.06%Emissions by Vehicle TypeEXHIBIT 17VEHICLE MILES OF TRAVELBY VEHICLE AND FACILITY TYPEBASE YEAR 2002 (Annual Miles 000,000.s )Vehicle Miles Of TravelFacility TypeVMTVEHICLE TYPERuralLDGV LDGT12 LDGT34 HDGV MC LDDV LDDT1234 HDDV2B HDDV345 HDDV67 HDDVBSInterstate1,134 181 146 68 60 327 2119 89 538Other Principal Arterial2,288 499 393 182 161 6210 3431 140 831Minor Arterial1,005 217 173 81 70 215 1514 62 365Major Collector1,365 296 235 109 95 316 2019 84 496Minor Collector293 64 51 23 21 10144 18 107Local633 242 177 85 12 21744 17 81UrbanInterstate10,440 1,901 1,542 707 616 26 1237 156 147 694 4,601Other Frwy & Expwy3,122 710 556 256 204 7310 4441 185 1,106Other Principal Arterial8,965 2,011 1,584 737 589 21930 128 120 536 3,200Minor Arterial6,348 1,425 1,121 526 413 15723 9185 380 2,262Collector2,381 536 422 195 156 628 3432 142 848Local2,778 1,067 787 371 51 8621 1817 76 355Total40,752 9,151 7,187 3,339 2,448 101 48165 570 533 2,423 14,789% Emissions22.46% 17.63% 8.19% 6.01% 0.25% 0.12% 0.41% 1.40% 1.31% 5.95% 36.29%Travel data from the Amended Air Quality Conformity of the 2006 CLRP and the FY 2007-202 TIP June 20,2007Exhibit 18Correspondence Between the 28 MOBILE6 Vehicle Classes and the 12 Vehicle Classes Used in the NIF covnersion28MOBILE6VehicleCode12 NIFVehicleCodesDescription1LDGVLDGVLight-Duty Gasoline Vehicles (Passenger Cars)2LDGT1LDGT1Light-Duty Gasoline Trucks 1 (0-6,000 lbs. GVWR, 0-3750 lbs. LVW)LDGT2LDGT1Light-Duty Gasoline Trucks 2 (0-6,000 lbs. GVWR, 3751-5750 lbs. LVW)LDGT3LDGT2Light-Duty Gasoline Trucks 3 (6,001-8,500 lbs. GVWR, 0-5750 lbs. ALVW)3LDGT4LDGT2Light-Duty Gasoline Trucks 4 (6,001-8,500 lbs. GVWR, 5751 lbs. and greater ALVW)4HDGV2BHDGVClass 2b Heavy-Duty Gasoline Vehicles (8501-10,000 lbs. GVWR)HDGV3HDGVClass 3 Heavy-Duty Gasoline Vehicles (10,001-14,000 lbs. GVWR)HDGV4HDGVClass 4 Heavy-Duty Gasoline Vehicles (14,001-16,000 lbs. GVWR)HDGV5HDGVClass 5 Heavy-Duty Gasoline Vehicles (16,001-19,500 lbs. GVWR)HDGV6HDGVClass 6 Heavy-Duty Gasoline Vehicles (19,501-26,000 lbs. GVWR)HDGV7HDGVClass 7 Heavy-Duty Gasoline Vehicles (26,001-33,000 lbs. GVWR)HDGV8AHDGVClass 8a Heavy-Duty Gasoline Vehicles (33,001-60,000 lbs. GVWR)HDGV8BHDGVClass 8b Heavy-Duty Gasoline Vehicles (>60,000 lbs. GVWR)HDGBHDGVGasoline Buses (School, Transit and Urban)5MCMCMotorcycles (Gasoline)6LDDVLDDVLight-Duty Diesel Vehicles (Passenger Cars)LDDT12LDDTLight-Duty Diesel Trucks 1 and 2 (0-6,000 lbs. GVWR)7LDDT34LDDTLight-Duty Diesel Trucks 3 and 4 (6,001-8,500 lbs. GVWR)8HDDV2B2BHDDVClass 2b Heavy-Duty Diesel Vehicles (8501-10,000 lbs. GVWR)HDDV3LHDDVClass 3 Heavy-Duty Diesel Vehicles (10,001-14,000 lbs. GVWR)9HDDV4LHDDVClass 4 Heavy-Duty Diesel Vehicles (14,001-16,000 lbs. GVWR)HDDV5LHDDVClass 5 Heavy-Duty Diesel Vehicles (16,001-19,500 lbs. GVWR)10HDDV6MHDDVClass 6 Heavy-Duty Diesel Vehicles (19,501-26,000 lbs. GVWR)HDDV7MHDDVClass 7 Heavy-Duty Diesel Vehicles (26,001-33,000 lbs. GVWR)11HDDV8AHHDDVClass 8a Heavy-Duty Diesel Vehicles (33,001-60,000 lbs. GVWR)HDDV8BHHDDVClass 8b Heavy-Duty Diesel Vehicles (>60,000 lbs. GVWR)12HDDBTBUSESDiesel Transit and Urban BusesHDDBSBUSESDiesel School Buses