Appendix B 

Base Year 2002 Emissions Inventory 

and Documentation 

Appendix B - Page Number:

1
2002 BASE YEAR EMISSIONS INVENTORY 

FOR THE 

WASHINGTON DC-MD-VA 

PM2.5 NONATTAINMENT AREA 

Prepared by: 

District of Columbia Department 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 Committee 

Appendix B - Page Number:

2
TABLE 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 Year 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 II) 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-29 

 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-54 

Appendix B - Page Number:

3
 3.4.3.4 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 – Residential/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 Petroleum 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, Feedlots, 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-112 

Appendix B - Page Number:

4
5.0 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 Commercial 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 - NIF3.0 Format (Available on a CD on request) 

D1. BY 2002 Onroad Mobile Source Emissions Inventory and Documentation 

D2. BY 2002 Onroad Mobile Model Input & Output Files (Available on a CD on request) 

D3. BY 2002 Onroad Mobile Source Emissions - NIF3.0 Format (Available on a CD on request 

Appendix B - Page Number:

5
 B-1

Chapter 1 

Introduction 

Appendix B - Page Number:

6
 B-2

1.0 INTRODUCTION 

1.1 Overview and Background 

This document contains a detailed explanation of the 2002 base year SIP emissions 

inventory for stationary, area, nonroad and mobile anthropogenic sources and biogenic 

sources for nitrogen dioxide (NOx), volatile 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 designed to protect the public health and welfare 

from these six criteria pollutants. These standards are referred to as the National Ambient 

Air Quality Standards (NAAQS). 

The base year 2002 emissions inventory covers the Washington, DC-MD-VA PM2.5 

nonattainment area. The goal of a base year inventory 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 inventory document includes emissions from point sources, mobile sources, biogenic 

emissions, non-road mobile sources, and area sources. The Metropolitan 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 referred 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 separately. MWCOG developed the 2002 onroad 

mobile inventory using MOBILE6.2 model 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 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 emissions from all sources or the 

relevant pollutants or pollutants in such area . . .”. Regulatory agencies and industrial 

facilities rely on emission inventories on an ongoing basis as indicators of air quality 

changes and for setting permit requirements. 

Appendix B - Page Number:

7
 B-3

The end use of emission inventories requires that they be of the highest quality 

obtainable. They are the foundation of air quality decisions. Inventory quality is critical 

to defining realistic regulations and attainment strategies. Deficiencies and 

inconsistencies 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 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 following 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 (includes independent Fairfax and Falls Church cities) 

• Loudoun County, Virginia 

• Prince William County, Virginia (includes independent Manassas and Manassas 

Park cities) 

1.3 Temporal Resolution 

Another step of inventory development is the 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 sources 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. 

Appendix B - Page Number:

8
 B-4

1.4 Quality Assurance Policy and Objectives 

In order to provide data of sufficient quality for maintenance planning needs, quality 

assurance (QA) and quality control (QC) procedures are implemented as part of the 

inventory process. The procedures address 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, completeness, comparability, and representativeness 

are addressed to ensure an inventory of high quality. The target 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 ensuring 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 discrepancies (data outliers) greater 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 calculations wherever possible. 

1.5 Plan Information Sources 

This plan draws upon inventory, quality assurance, and emissions projections guidance 

available from state and federal agencies and partnerships. The effort will also draw upon 

experience gained with the 1990 base year 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 submitted 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 Tribal Association of the Southeast). 

1.6 Summary of the Base Year Emissions Inventory 

A summary of annual emissions 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, refer 

Appendix B - Page Number:

9
 B-5

to the beginning of the respective section. There 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 determining 2002 annual emissions 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 mobile emissions tables are presented in 

Attachments A1, C1, and D1 of this document. 

Appendix B - Page Number:

10
Chapter 2 

Point Sources 

B-6 Appendix B - Page Number:

11
2.0 POINT SOURCES 

2.1 Introduction 

This section documents the development of the Washington, DC-MD-VA nonattainment area 

stationary point source emissions inventory and serves to characterize the point source 

component of the emissions inventory by describing the 2002 annual emissions estimation 

techniques. The point source inventory 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 Quality, Maryland Department of Environment and 

the District of Columbia Department 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 Documentation of Point Source Emissions 

District Department of the Environment (DDOE), the Maryland Department of the Environment 

(MDE), and the Virginia Department of Environmental Quality (VDEQ) maintain substantial 

databases of both small and large air emission sources. The list of point sources in this inventory 

was developed by applying the appropriate thresholds to the emission levels in the database to 

differentiate between point and area 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 emissions 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 point source emissions for the 

Washington region. Detailed point source emissions are being provided separately in electronic 

format (NIF3.0) as Appendix A2 of this document.

2.3 Quasi-Point Source (Andrews 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 establishment 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 totaled 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-7 Appendix B - Page Number:

12
Emission Source Categories

MDE staff reviewed emission estimates prepared 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 gasoline engine, Gas-Fired Non-road vehicle-2-

stroke gasoline engine, Aircraft - All Aircraft Types and Operations, Emissions from 

military aviation aircraft landing and takeoff, Emissions from commercial aviation 

aircraft landing and takeoff, Diesel Generators, Off-highway Vehicle Gasoline, 2-Stroke 

Total without APUs, Off-highway Vehicle Gasoline, 4-Stroke Total without APUs, Offhighway Vehicle Gasoline, 4-Stroke APU emissions, 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 included emission estimates from emission 

certification reports prepared by Andrews 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 brief 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 natural gas-powered government-, and privately owned vehicles 

(POVs). POVs include vehicles owned by both daily employees and weekend personnel. 

The inventory contains the vehicle type, model year, number of vehicles, and annual onbase mileage. To distinguish leased General 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 vehicle 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, Volume II includes the emission factors for NOx, 

B-8 Appendix B - Page Number:

13
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 

factors from the latest version of EPA’s MOBILE 6.2.03 model, released in October 2002. 

Therefore, the emission factors for on-road vehicles were obtained by running the 

MOBILE 6.2.03 model. The MOBILE model DOHs not address compressed natural gas 

vehicles, so emission factors for these vehicles have been obtained 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 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 following equation to estimate annual emissions: 

E = V * F * C 

Where: 

E = Annual emissions of particular pollutant from each vehicle category (lb/yr) 

V = Vehicle miles traveled on-base per year 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 equipment, and towing equipment. The inventory 

contains the equipment name, model year, horsepower rating, number of vehicles, fuel 

type, engine cycle type, and operating hours for CY 2002. The inventory specifies whether 

the operating 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 Environment, Safety & Occupational Health Risk Analysis (IERA), 

January 2002, which includes the emission factors used in EPA’s NONROAD 2002a 

model. 

The Andrews AFB aircraft operations inventory consists of information 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 

revision of its SIP. The inventory contains the aircraft type and manufacturer, engine 

model and manufacturer, 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, 

B-9 Appendix B - Page Number:

14
B-10

the Andrews AFB Federal Aviation Administration (FAA) Liason, and Allan Holtzman, 

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 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. 

Appendix B - Page Number:

15
2.4 POINT SOURCE SUMMARY – BASE YEAR 2002 SIP EMISSION INVENTORY 

Point 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 

PM2.5-Direct 2397.62 665.53 45.73 388.42 220.42 19.25 303.22 2.82 126.53 34NOx 18979.26 1992.53 8573.23 16284.41 33.88 6315.35 2234.09 77.28 5494.36 40.69 1317.46 458SO2 71397.88 6734.09 34038.88 52613.21 5.95 16144.95 132.64 26.68 21078.23 11.79 2467.55 1647VOC 117.32 299.04 129.64 566.16 10.03 47.36 245.35 89.41 114.66 193.80 1.32 87.76 11NH3 22.33 3.00 0.00 11.13 PM10 3786.77 841.91 49.22 530.33 12.73 501.81 51.92 19.71 398.91 12.55 181.56 52

1 There is no PM2.5, NOx, SO2, VOC, NH3, and PM10 emissions for the Virginia Independent Cities of Falls Churc

Point source inventory of Prince George's county includes quasi- point source inventory from Andrews AFB (Refer 

Maryland Point Source Emissions). 

B-11

Appendix B - Page Number:16
Chapter 3 

Area and Nonroad Sources 

B-12 Appendix B - Page Number:

17
3.0 AREA AND NONROAD SOURCES 

3.1 Introduction and Scope 

This document contains a detailed explanation of how the 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 developed. The area source inventories for the 

entire year in 2002 were prepared by the state air agencies. The MWCOG staff compiled 

the states’ data for including in this SIP inventory document. Detailed area and nonNonroad model source emissions are being provided 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 "quasi" 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 airport activities, lawn and 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 agency 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 inputs for a computation, excluding the 

surrogate activity data, which is provided in the appendices. 

• Equation - enables the user to reproduce the estimates once all the necessary 

parameters are obtained. 

• Summary of jurisdictional estimates - provides a summary table listing emissions 

estimates for the source by county and pollutant. 

Jurisdictional estimates are provided for all six pollutants, where appropriate. 

Tables at the end of area source methods section 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-13 Appendix B - Page Number:

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B-14 

3.2.1 Source and Category Identification 

All of the area source categories contained in the EPA Procedures document1, 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 calculated using the recommended guidance in the 

EPA Procedures document. Exceptions to the recommended approaches, and selection of 

the approach, are detailed in the individual 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, SO2, 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 and planning studies for regional haze and 

visibility issues for southeastern and mid-Atlantic and northeastern states respectively. 

MWCOG staff collected all area and non-nonroad 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 categories for Virginia to include most updated 

emissions. While details on methodologies to calculate PM2.5, PM10, and SO2 

emissions for Virginia for different source categories 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 Regional Air Management Association, Inc 

(http://www.marama.org). Maryland has provided detailed documentation of emission 

estimation methods, emission factors, and data sources for its area and nonroad source 

VOC, NOx, PM2.5, PM10, SO2, and NH3 emissions in the following report: 

 2002 Base Year State Implementation Plan Emissions Inventory and Methodologies 

for PM2.5 and Precursors; Prepared for U.S. Environmental Protection Agency by 

Maryland Department of the Environment. 

Individuals are referred to this report for further details 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 source category and jurisdiction 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. 

Appendix B - Page Number:

19
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 than 10 tons VOC per year and therefore are 

generally inventoried using area source methods. One of the sources of such VOC 

emissions at gasoline dispensing outlets is the vapor lost during tank truck unloading into 

underground storage tanks. The amount of vapor lost is dependent 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 state 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. 

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 filling method, it was the only method for which 

control efficiency, rule penetration and rule effectiveness 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 Stationary Anthropogenic, Biogenic 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 Council of Governments dated September 22, 

1993, herein referred to as “1990 Inventory Document” for a detailed explanation of 

these calculations in Attachment A beginning on Page 3-5. 

B-15 Appendix B - Page Number:

20
Factors: 

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 Method Apportionment Factor 

FM2 Balanced Submerged Filling 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-16 Appendix B - Page Number:

21
Summary of Jurisdictional Estimates, 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-17 Appendix B - Page Number:

22
3.4.1.2 Vehicle Fueling (Stage II) and Underground Tank Breathing 

VOC emissions from gasoline dispensing outlets are typically less than 10 tons 

per year, and therefore are inventoried with area sources. Much of the VOC emissions at 

a gasoline dispensing outlet come from vehicle fueling and underground tank breathing. 

Vehicle fueling displaces vapors from the vehicle's tank into the atmosphere, and also 

results in drip and spit-back spillage. Tank breathing results when gasoline 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 breathing were calculated separately. 

Data for fuel sales were obtained from state 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. 

State regulations were consulted for data on tank breathing, refueling vapor displacement 

and refueling spillage, and information on control 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 breathing, 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 estimation 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-18 Appendix B - Page Number:

23
Equation: 

 

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-19 Appendix B - Page Number:

24
3.4.1.3 Losses from Gasoline Tank Trucks in Transit 

Description: 

Breathing losses from tank trucks during the 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 arises if a poorly sealed tank has been loaded with gasoline 

and pure air becomes saturated. During the vaporization process, pressure increases and 

venting occurs. 

Method and Data Sources: 

Staff followed the methods detailed in EIIP. 

Data for fuel sales were obtained from state 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 multiplied by 1.25, to reflect an EPA estimate 

(Procedures, Volume I, section 4.2.2.3) that nationally 25% of all 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 psi 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-20 Appendix B - Page Number:

25
Emission 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-21 Appendix B - Page Number:

26
3.4.1.4 Aircraft Refueling 

Description: 

Jet kerosene, jet naphtha and aviation gasoline 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 small for Virginia and so instead of using 

new 2002 survey data, inventories 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 computed 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 measured 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 Pi x Mi / 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-22 Appendix B - Page Number:

27
Equation: 

SFSa x (PTAc / STAc) x (CTAc / MTAc) x EFa x CF / AD = Ea

SFSb x (PTAd / STAd) x (CTAd / MTAd) x EFb x CF / AD = Eb

Ea – Eb = 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-23 Appendix B - Page Number:

28
3.4.1.5 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 from marine vessel operations. However, it 

was assumed that very little loading activity occurred in the region and that most 

emissions resulted from ballasting activities associated with fuel delivery. Ballasting 

emissions occur as vapors inside empty cargo 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 

EFi = 0.31 + (0.20 x Pi) + (0.01 x Pi 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-24 Appendix B - Page Number:

29
Vessel 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: 

(DCa X EFa x CPa) + (DCb x EFb x CFb) + (DCc x EFc x CFc) + (DCd x EFd x CFd)] 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-25 Appendix B - Page Number:

30
3.4.2 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 are negligible due to controls required since 

1990. These controls virtually eliminate perchloroethlyene emissions from dry cleaning 

machines by recapturing vapors. 

 Maryland’s inventory includes VOC emissions 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-26 Appendix B - Page Number:

31
3.4.2.2 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 automobile 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 solvents 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 activity period, a 312-day year was assumed. 

Employment figures for facilities included 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-27 Appendix B - Page Number:

32
Equation: 

{[(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-Line Cleaning Emissions Factor 

EF4 Automobile Repair and Manufacturing 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-28 Appendix B - Page Number:

33
3.4.2.3 Surface Coating 

Description: 

Surface coating includes paints, enamels, varnishes, lacquers and other product 

finishes. Same of those coatings contain a solvent-based liquid carrier; others use a waterbased liquid carrier but still contain a small portion of solvents. Solvents are also used to 

clean up painting equipment. 

The primary types of surface coating applications are architectural 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 included in the point source inventory were 

subtracted from the County Business Patterns employment figures for automobile 

refinishing and all manufacturing activities to prevent double-counting of emissions. 

A consumption-based emission factor was applied, using national consumption 

data from 1998 apportioned to the county level. 

B-29 Appendix B - Page Number:

34
Factors: 

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-30 Appendix B - Page Number:

35
Summary 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-31 Appendix B - Page Number:

36
3.4.2.4 Graphic Arts 

Description: 

Graphic arts include operations that are involved in the printing of newspapers, 

magazines, books and other printed materials. In 1989, nationwide graphic arts solvent 

consumption exceeded 550 million pounds; the majority 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 graphic 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 year was assumed. Total emissions from 

facilities included in the point source inventory with annual 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-32 Appendix B - Page Number:

37
Summary 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-33 Appendix B - Page Number:

38
3.4.2.5 Asphalt Paving 

Description: 

There are three basic types of asphalt used for paving and roofing. The first, 

cutback asphalt, is a liquefied road surface prepared by blending (or "cutting back") 

asphalt cement wit different petroleum distillates. The second type, emulsified asphalt, is 

also a liquefied road surface, but is prepared 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 construction 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 through 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 emission 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-34 Appendix B - Page Number:

39
Summary 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-35 Appendix B - Page Number:

40
3.4.2.6 Pesticide Application 

Description: 

Pesticides broadly include any substances used to kill 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 "inert'. Both the active and the inert ingredients 

of the pesticides are considered reactive in the formation of ozone. 

The pesticide usage can be broadly divided into agricultural 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 been included based on the presumption 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 residential (home and garden). The amount 

(pounds) of active ingredients applied per county was determined. The vapor pressure, 

percentage of inert ingredients, and application method were considered. 

As recommended in Procedures, active ingredient application 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 the 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-36 Appendix B - Page Number:

41
Factors: 

Organic Content Adjustment Factor 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 Use (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 Estimates, 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-37 Appendix B - Page Number:

42
3.4.2.7 Commercial/Consumer Solvent Use 

Description: 

Certain commercial/consumer uses of products containing volatile organics 

cannot easily be identified by usual inventory procedures yielding locale-specific 

emission estimates. This category includes the following commercial/consumer 

subcategories: household products, toiletries, aerosol products, rubbing compounds, 

windshield washing fluids, polishes and waxes, non-industrial adhesives, space 

deodorants, moth control, and laundry detergents and treatments. 

This category does not include the following subcategories: small cold cleaning 

degreasing operations; dry cleaning plants; auto refinishing shops; architectural surface 

coating applications; graphics arts plants; cutback asphalt 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 person 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 EFU x CF / AD) + (POP x EFC x CF x 0.20 / AD) = E 

POP Population 

EF Comm./Cons. Solvent Use Emissions Factor 

EFU Uncontrolled Comm./Cons. Solvent Use Emissions Factor 

B-38 Appendix B - Page Number:

43
EFC Controlled Comm./Cons. Solvent Use Emissions Factor 

CF Units Conversion Factor 

AD Activity Days Per Period 

E Total Emissions 

Summary of Jurisdictional Estimates, 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-39 Appendix B - Page Number:

44
3.4.2.8 Synthetic Organic Chemical Storage Tanks 

Description: 

Chemical manufacturers make organic chemicals for a variety of end-users. 

Manufacturers of such chemicals are generally located around industrialized areas, or 

anywhere else that base chemicals are readily available. End-users may be more 

concentrated in industrialized areas. The synthesized chemicals may be stored by the 

manufacturer before distribution, 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, and 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 more, they are inventoried as point sources. 

Method and Data Sources: 

It was determined that there are no synthetic organic chemical manufacturers in 

the Washington, DC MSA. It was also observed 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 Storage Tanks were not inventoried as an 

independent area source. 

B-40 Appendix B - Page Number:

45
3.4.2.9 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 contaminated, are cleaned only 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 point or below the freezing point of either the 

compound or the cleaning agent. Cleaning agents include water, steam, detergents, 

bases, adds and solvents. 

The cleaning of these transport vessels may 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 residues. 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 primarily 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-41 Appendix B - Page Number:

46
3.4.2.10 Industrial Adhesives and Sealants 

Description: 

Industrial adhesive and sealant surface coating is the application of a liquid or 

powder substance, such as solvent type paints, varnishes, and lacquers 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.

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 estimate overall emissions then subtracting out 

emissions due to point sources, waste management, and recycling. 

 EPA used the Freedonia2

 market research report on nonpoint solvents to obtain 

solvent utilization data for this source category. 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 Adhesives and Sealants. VOC emission estimates 

were then allocated to the state 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 Coatings ‘2000': Review 

and Forecast”

B-42 Appendix B - Page Number:

47
Summary 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-43 Appendix B - Page Number:

48
3.4.2.11 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 Emissions, which result when stored fuel vapors escape to the outside of 

a gas can through any possible openings while the gas can is subjected to daily 

cycle of increasing and decreasing ambient 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 (all VOC) for District is adopted from a 

CARB1

 survey and methodology adopted by OTC2 is being described below. Virginia 

used a different methodology, which is being described at the end of this section. 

 

Portable fuel container emissions are calculated by accounting for emissions from 

five different components related to gas container use: permeation, diurnal, transportspillage, refueling spillage and refueling vapor 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 residential portable fuel container 

population is developed using the number of residential housing units in 2002 by county. 

For commercial portable fuel containers, population 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 allocated to the local 

 

1

 ARB’s Mailout MSC 99-25, “Public Meeting to Consider Approval of CA’s Portable 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-44 Appendix B - Page Number:

49
area level based on commercial and industrial business location. For the residential PFC 

SCCs, the emissions were allocated based 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 emissions 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 developed for permeation, diurnal, transport and 

spillage emissions for PFC (both for commercial and residential PFCs). These emission 

factors were derived from CARB’s survey data (CARB, 1999). A weekly activity period 

of 7 days/week was used. 

Equation: 

The residential-gas-can population is calculated as follows: 

 

 PopR = (N)*(A)*(CountR) (Eq. 1) 

where: PopR = Statewide Residential-Gas-Can Population 

 N = Number of Occupied-Housing Units in OTC State 

 A = Percentage of Households with Gas Cans (46%) 

 CountR = Average Number of Residential-Gas Cans per Household 

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

 HCPR = Σ (PopR)*(S)*(EFP)*(BR)*(SizeR)*(Level)/CF (Eq. 2) 

where: HCPR = Permeation Emissions in tons per day (tpd) 

 PopR = Statewide Residential-Gas-Can Population 

 EFP = Appropriate Permeation-Emission Factor (g/gal-day) 

 S = Percentage of Gas Cans Stored with Fuel (70%) 

BR = Percentage of Cans Stored in Closed Condition with respect 

to Material (Plastic 53%; Metal 13%) 

 SizeR = 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-gas cans are calculated 

as follows: 

 HCDR = (PopR)*(S)*(EFD)*(BR)*(SizeR)*(Level) (Eq. 3) 

where: HCDR = Diurnal Emissions (tpd) for Residential-Gas Cans with 

respect to Storage Condition (Open or Closed) and Material 

(Plastic or Metal) 

B-45 Appendix B - Page Number:

50
 PopR = Statewide Residential-Gas-Can Population 

S = Percentage of Gas-Can Population Stored with Fuel (70%) 

 EFD = Appropriate Diurnal-Emission Factor with respect to 

Storage Condition and Material (g/gal-day or g/day) 

 BR = Percentage of Gas-Can Population with respect to Storage 

Condition and Material 

 SizeR = Weighted Average Capacity of Residential-Gas Cans 

(2.34 gal.) 

Level = Weighted Average Amount of Stored Fuel (49%) 

 CF = 908,105 g/ton 

 

Residential-transport-spillage emissions are determined as: 

 HCTR = (PopR)*(S)*(RefillR)*(EFT)*(BR) (Eq. 4) 

where: HCTR = Residential-Gas-Can-Transport-Spillage Emissions (tpd) 

 PopR = Statewide Residential-Gas-Can Population 

S = Percentage of Gas Cans Stored with Fuel (70%) 

 RefillR = Average Number of Residential-Gas-Cans-Pump-Refills 

per Day per Can (refill/day from survey) 

 EFT = Transport-Emission Factor with respect to Storage 

Condition (g/refill) 

 BR = Percentage of Gas Cans with respect to Storage Condition 

and Material 

 CF = 908,105 g/ton 

 

The commercial-gas-can population is calculated as follows: 

 

 PopC = (NC )*( CountC) (Eq. 5) 

where: PopC = Statewide Commercial-Gas-Can Population 

 NC = Number of Occupied Businesses in State 

 CountC = Average Number of Gas Cans per Business 

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

 HCPC = Σ (PopC)*(S)*(EFP)*(BC)*(SizeC)*(Level) (Eq. 6) 

where: HCPC = Permeation Emissions (tpd) 

 PopC = Statewide Commercial-Gas-Can Population 

 EFP = Appropriate Permeation-Emission Factor (g/gal-day) 

S = Percentage of Gas Cans Stored with Fuel (70% for 

Residential Survey) 

 BC = Percentage of Applicable Gas Cans Stored in Closed 

Condition 

B-46 Appendix B - Page Number:

51
 SizeC = 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 amount of diurnal emissions from both open- and closed-system commercial-gas 

cans is calculated as follows: 

 HCDC = (PopC)*(S)*(EFD)*(BC)*(SizeC)*(Level) (Eq. 7) 

where: HCDC = Diurnal Emissions (tpd) for Commercial-Gas Cans with 

respect to Storage Condition (Open or Closed) and Material 

(Plastic or Metal) 

 PopC = Statewide Commercial-Gas-Can Population 

 EFD = Appropriate Diurnal-Emission 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) 

 BC = Percentage of Gas Cans with respect to Storage Condition 

and Material 

 SizeC = 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: 

( )

( ) ( )() ⎢⎣ ⎥⎦ SIZ POP NON S C * *

Average Nu

= ⎢ ⎥ EREFILL

C

 (Eq. 8) 

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

PNO 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 

 SizeC = 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-47 Appendix B - Page Number:

52
 CF = 908,105 g/ton 

The commercial-transport-spillage emissions are determined as: 

here: TC tpd) 

 PopC = al-Gas-Can Population 

rvey) 

ondition 

 

Factor (g/refill) with respect 

to Storage Condition 

The tot ed as follows: 

PFC - A = HCPR+HCDR+HCTR+HCPC+HCDC+HCTC

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

Where

ty 

er day emission of pollutant 

ADF = Annual activity day factor (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). 

 

 HCTC = (PopC)*(S)*(BC)*(RefillC)*(EFTC) (Eq. 9) 

w HC = Commercial-Gas-Can-Transport-Spillage Emissions (

Statewide Commerci

S = Percentage of Gas Cans Stored with Fuel (70% from 

Residential Su

 BC = Percentage of Gas Cans with respect to Storage C

and Material 

 RefillC = Average Number of Gas-Cans Pump Refills per 

Day per Can 

 EFTC = Transport-Spillage Emission 

 CF = 908,105 g/ton 

al area source portable fuel container emissions are summ

E

E

: 

EPFC - A = (tons/yr) for an annual emission of pollutant by coun

EPFC - SD = (tons/day) for a typical summ

A

SAF = Seasonal adjustment factor 

Virginia used a methodology developed by the EPA, which is essentially a modified 

CARB approach. EPA’s methodology is described in detail in its report3

. EPA provided 

in this report state level annual emissions for the year 2005 for Virginia for differe

processes through which portable fuel containers 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 EPA’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-48 Appendix B - Page Number:

53
Summary of Jurisdict le Fuel Containers: 

VOC (TPY) 

ional Estimates, Portab

Jurisdiction 

District of Columbia 1,061.41

Charles County 321.32

Frederick County 668.02

Montgomery County 2,279.73

Prince George’s County 1,696.50

Arlington County 86.845

Alexandria City 88.952

Fairfax County 1046.161

Fairfax City 37.091

Falls Church City 22.422

Loudoun County 460.025

Prince William County 280.710

Manassas City 18.351

Manassas Park City 21.030

Region Total 8,088.57

B-49 Appendix B - Page Number:

54
3.4.3 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 are typically inventoried 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. District 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-50 Appendix B - Page Number:

55
Summary 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-51 Appendix B - Page Number:

56
3.4.3.2 Breweries 

Description: 

During the fermentation process, breweries will emit ethanol and other VOCs. Because 

of their relatively large emissions, large-scale commercial breweries will be inventoried 

as point sources. Microbreweries and brewpubs will emit lower levels of VOCs, 

however, and thus must be inventoried as area sources. 

Method and Data Sources: 

Staff followed guidance provided in a February 5, 1992 Memorandum from Lucy 

Adams at Radian. The guidance requires inquiries into a brewery's annual production and 

the types of brewing process 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-52 Appendix B - Page Number:

57
Summary 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-53 Appendix B - Page Number:

58
3.4.3.3 Wineries 

Description: 

Like beer, wine will emit ethanol during its fermentation. The emissions vary, 

depending upon the type of wine (red vs. white), the fermentation temperature and the 

sugar content of the grape(s) used. 

Method and Data Sources: 

Staff followed the methods detailed in the 3/10/92 Memorandum from Lucy 

Adams of Radian. The Memorandum requires inquiries into the gallons and types of wine 

produced at each winery (red vs. white), and 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 wineries 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: 

[(CWPa x EFa) + (CWPb X EFb)] 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-54 Appendix B - Page Number:

59
Summary 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-55 Appendix B - Page Number:

60
3.4.3.4 Distilleries 

Description: 

Ethanol emissions are the largest component of the VOCs emitted from 

distilleries. Distilleries produce both grain alcohol for industrial and fuel purposes, and 

distilled spirits such as whiskey and brandy for consumption purposes. The emissions 

points In the distilled spirits 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 the Washington, DC-MD-VA MSA during 2002. 

B-56 Appendix B - Page Number:

61
3.4.4 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 industrial contribution to 

POTW Influent. 

Method and Data Sources: 

The 1990 Inventory (refer to 1990 Inventory Document) relied upon the work of a 

contractor to inventory POTW emissions. The contractor first compared the accuracy of 

the Surface Impoundment Modeling System (SIMS) against estimates based on total 

industrial flow per POTW, multiplied by an EPA emissions factor. The SIMS method 

was found to be more accurate, as the emissions 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 source-specific data wherever possible, 

contacting each POTW in the area. When data could not be obtained directly from a 

POTW, average industrial contribution was applied, along with device parameters (or, 

treatments) from a typical POTW collection and treatment scheme, as described in AP42. The contractor also relied upon approximate impoundment surface areas found in 

EPA's Background Information Document for Industrial Wastewater (1990). 

Because of the direct relation between industrial influent and VOC emissions, and 

because the Washington, DC MSA is a relatively 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 grown using employment-based growth factors 

for developing the 2002 emissions for this category. 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 Memorandum1 (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-57 Appendix B - Page Number:

62
Summary of Jurisdictional Estimates, POTWs: 

Jurisdiction VOC (TPY) NH3 (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-58 Appendix B - Page Number:

63
3.4.4.2 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 assumption that emissions from industrial 

wastewater were included in the emissions from publicly owned treatment works. 

Therefore, there is no need to inventory this source separately. 

B-59 Appendix B - Page Number:

64
3.4.4.3 Hazardous Waste Treatment, Storage, and Disposal Facilities (TSDFs) 

In the 1990 Inventory (refer to 1990 Inventory Document), a list of TSDFs in the 

region was compiled from the RCRIS database. These facilities are primarily involved in 

temporary storage. Consequently, 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-60 Appendix B - Page Number:

65
3.4.4.4 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 decomposition of liquid and solid compounds into 

other chemical species. Volatilization is affected by partial pressure of the volatile 

substance, substance concentration at the air/liquid interface, temperature, and confining 

pressure. Chemical reaction is affected by temperature, waste composition, moisture 

content, and whether different 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, landfill age, and total refuse deposited in the 

study year. The model is more accurate if provided with the rate of refuse deposit, but it 

can generate that variable if needed. The model 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 atmospheric factors). There are 

no landfills in the District of Columbia. 

Summary of Jurisdictional Estimates, Municipal Solid Waste Landfills: 

Jurisdiction VOC(TPY) NOx (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-61 Appendix B - Page Number:

66
3.4.4.5 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 hospitals, nursing homes, veterinarians' offices, 

funeral homes, biomedical/biotechnological 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 year were included. Sources above 10 tons 

VOC per year will be included 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 held 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-62 Appendix B - Page Number:

67
Equation: 

Virginia

POP x [(ICa x EFa) + (ICb X EFb) + (ICc x EFc] 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) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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-63 Appendix B - Page Number:

68
B-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. Similarly, VA’s inventory 

does not include emissions associated with the open burning of land 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 followed the methods detailed in Procedures, 

section 4.6.2. Open burning permit issuance data were obtained from the county 

governments in each jurisdiction. Some jurisdictions also provided information on the 

materials and/or the acreage burned 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 Emissions 

Appendix B - Page Number:

69
B-65 

Summary of Jurisdictional Estimates, Open Burning: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) NH3 (TPY) PM10 (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

Appendix B - Page Number:

70
.3.4.5 Small Stationary Source – Residential/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 grades 1, 2 and 4. Diesel fuel and kerosene also 

can be considered distillate oils. Nationwide, residential and commercial/institutional 

sources are the largest consumers 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 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 industrial 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-66 Appendix B - Page Number:

71
Seasonal 

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: 

{[(((DFCi + OFCi) x (CP / SP)) – PDCi) x EF1i] + [((RFCi x (CP / SP)) - PRCi) x EF2i]} 

x SAFi x CF1 x CF2 / ADi = Ei

Ea + Eb + Ec = E 

DFC State Distillate Fuel Oil Consumption (Grades 1, 2, and 4) 

OFC State Diesel Fuel and Kerosene Consumption 

PDC Point Source Distillate, Diesel, 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-67 Appendix B - Page Number:

72
Summary of Jurisdictional Estimates, Fuel Oil Consumption: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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-68 Appendix B - Page Number:

73
3.4.5.2 Coal Consumption 

Description: 

Two types of coal are commonly used: anthracite, or hard coal; and bituminous, 

or soft coal. Anthracite is mined almost exclusively in Pennsylvania, and is consumed 

primarily in states within easy shipping distance of PA. Bituminous 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 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 industrial 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-69 Appendix B - Page Number:

74
Equation: 

{[(BCCi + ACCi) x (CP / SP)] - (PBC + PAC)} x EF x SAF x CF / AD = Ei

Ea + Eb + Ec = 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) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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-70 Appendix B - Page Number:

75
3.4.5.3 Natural Gas and Liquefied Petroleum Gas (LPG) Consumption 

Description: 

The LPG use contribution to total emissions 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 gallon 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 industrial consumption. Emissions factors were 

taken from AP-42, Table 1.4-2, 1.4-3, 1.5-1 (8/82), and 1.5-1 (Supplement E, 10/92). 

Emissions in the district were grown from the 1990 Inventory (refer to 1990 Inventory 

Document) using population growth 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 Gas1 94 7.3 

Liquid Petroleum Gas2 14 0.5 

b-Commercial 

Natural Gas1 100 5.8 – VA 

2.8 – DC 

Liquid Petroleum Gas2 14 0.5 

c-Industrial 

Natural Gas1 140 – VA 

100 – DC 

5.8 – VA 

2.8 – DC 

Liquid Petroleum Gas2 19 – VA 

14 – DC 

0.5 

1 - pounds per million cubic feet 

2 - pounds per kilo gallon 

B-71 Appendix B - Page Number:

76
Seasonal 

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: 

{[((NGCi x (CP / SP)) – PNCi ) x EF1i] + [((LPCi x (CP / SP)) – PLCi) x EF2i x CF1]} x 

SAFi x CF2 / AD = Ei

Ea + Eb + Ec = E 

NGC State Natural Gas Consumption 

LPC State Liquid Petroleum 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-72 Appendix B - Page Number:

77
Summary of Jurisdictional Estimates, Natural Gas and LPG Consumption: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) NH3 (TPY) PM10 (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-73 Appendix B - Page Number:

78
3.4.5.4 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 developed 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 burned) and to apportion activity between rural, 

urban, and suburban areas. Details on the methods, data sources, survey instrument, and 

calculation methods are provided in the report titled MANE-VU Residential Wood 

Combustion Emission Inventory1

. The MANE-VU inventory includes 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 Inventory Document), Virginia staff relied upon 

the work of their contractor to estimate wood-burning emissions. The contractor apportioned 

state wood fuel consumption to the county level 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 the temperature drops below 65 degrees 

Fahrenheit; one "heating degree day" is registered 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-74 Appendix B - Page Number:

79
Factors: 

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-75 Appendix B - Page Number:

80
Summary of Jurisdictional Estimates, Other Fuels Consumption (Residential Wood 

Burning; Indoor Equipment):1

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) NH3 (TPY) PM10 (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, Other Fuels Consumption (Residential Wood 

Burning; Outdoor Equipment):1

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) NH3 (TPY) PM10 (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-76 Appendix B - Page Number:

81
3.4.5.5 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-77 Appendix B - Page Number:

82
3.4.6 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 forests, and to remove brush that can serve as a host to destructive 

insects. Prescribed burning is used as a forest management practice to establish favorable 

seedbeds, remove competing underbrush, accelerate nutrient recycling, control tree pests and 

contribute other ecological benefits. 

Organic emissions from forest fires 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 burning emissions calculation 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 per fire, fuel loading, and types of wood burned per fire. The 

emissions from Slash/Prescribed and Forest burning were calculated separately. 

The National Park Service National Capital Region provided data on NPS parkland 

forest fires, including fuel type, in the District of Columbia and in the northern VA counties. 

Staff assumed that the National Park Service forest 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 NOX

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-78 Appendix B - Page Number:

83
Seasonal 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 Virginia was prepared using CMU ammonia model 

version 3.6. 

B-79 Appendix B - Page Number:

84
Summary of Jurisdictional Estimates: 

Forest Fires: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) NH3 (TPY) PM10 (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) PM2.5 (TPY) NOx (TPY) SO2 (TPY) NH3 (TPY) PM10 (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-80 Appendix B - Page Number:

85
3.4.6.2 Agricultural Burning 

Description: 

Agricultural burning is used to clear and/or prepare land for planting. Operations 

under this category include stubble burning, burning of agricultural 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 burning is also assumed not to be practiced in District. 

B-81 Appendix B - Page Number:

86
3.4.6.3 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 result 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 reported. 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 (refer to 1990 Inventory 

Document) using population as the growth surrogate. 

Emission factors from Procedures page 4-44 were used. 

Factors: 

Fires Per Capita (when actuals were unavailable) .006

Fuel Loading Factor 1.15 tons solid material/fire

Emissions 

- VOC 11 lbs/ton solid material burned

- NOX 1.4 lbs/ton solid material burned

Activity Day Per Period 365

Units Conversion Factor .0005 tons/lb

B-82 Appendix B - Page Number:

87
Equation: 

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) PM2.5 (TPY) NOx (TPY) PM10 (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-83 Appendix B - Page Number:

88
3.4.6.4 Orchard Heaters 

Description: 

Orchard heaters are used in certain climates to prevent frost damage in the colder 

months. Most heaters are combustion- powered, and thus will emit VOCs during operation. 

Method and Data Sources: 

Virginia Department of Agriculture both stated 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 irrelevant to the inventory. 

B-84 Appendix B - Page Number:

89
3.4.6.5 Leaking Underground Storage Tanks 

Description: 

Leaking Underground Storage Tanks (LUSTs) are environmentally important because 

they may result in the contamination of drinking 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 emissions are negligible until LUST remediation 

occurs. Upon remediation, the VOCs are vented into the atmosphere. 

Remediation of LUSTs may follow several methods, among them soil venting, air 

stripping of VOCs in ground water, excavation and soil aeration, product recover and carbon 

adsorption. Each of the respective jurisdictions in the MSA follows 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 Memorandum requires investigating the number of 

LUST remediations; each remediation is to be multiplied by an emission factor. 

Virginia applied an emission factor of 3 lbs VOC/remediation day to the number of leaking 

underground storage tanks reported by each county. 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 boundaries; it is all trucked to other jurisdictions for land farming 

or disposal. Because of this, staff assumed that 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-85 Appendix B - Page Number:

90
Summary 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-86 Appendix B - Page Number:

91
3.4.6.6 Oil Spills 

Description: 

Oil spills involve oil tanker accidents, 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 

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 recommended 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 reactive 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-87 Appendix B - Page Number:

92
Summary 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-88 Appendix B - Page Number:

93
3.4.6.7 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) 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. 

• 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. 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 ceramic stones, are sometimes used. This 

category includes broilers, grill charbroilers, flame broilers, and direct-fired 

barbecues. 

Method and Data Sources: 

 District’s inventory is taken 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 Memorandum2 (see Attachment B1).

 

2 U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Methods for 

Developing a National Emission Inventory for Commercial Cooking Processes: Technical Memorandum, 

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

B-89 Appendix B - Page Number:

94
Summary of Jurisdictional Estimates, Commercial Cooking:

Jurisdiction VOC (TPY) PM2.5 (TPY) PM10 (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-90 Appendix B - Page Number:

95
3.4.6.8 Composting 

Description: 

 Composting refers to the use of both aerobic and anaerobic microbial processes to 

degrade waste materials for beneficial reuse. Compostable wastes include biosolids (sewage 

sludge), manure, green waste (e.g., landscape 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 Miscellaneous Sources: Final Technical Memorandum1

(see Attachment B2). 

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

Summary of Jurisdictional Estimates, Composting:

Jurisdiction VOC (TPY) NH3 (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-91 Appendix B - Page Number:

96
3.4.6.9 Motor Vehicle Fires 

Description: 

 Maryland’s inventory includes VOC, NOx, PM2.5, and PM10 emissions associated 

with motor vehicle fires. Vehicles included are any commercial or private mode of 

transportation that is authorized 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) PM2.5 (TPY) NOx (TPY) PM10 (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-92 Appendix B - Page Number:

97
3.4.6.10 Construction 

Description: 

 This includes PM2.5 and PM10 emissions from residential, commercial, institutional, 

industrial, and road sectors 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 because 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 Sector (Feb 06 Version) National Emission 

Inventory For Criteria And Hazardous Air Pollutants”, July 2006. 

Summary of Jurisdictional Estimates, Construction:

Jurisdiction PM2.5 (TPY) PM10 (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-93 Appendix B - Page Number:

98
3.4.6.11 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 because 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 Sector (Feb 06 Version) National Emission 

Inventory For Criteria And Hazardous Air Pollutants”, July 2006. 

Summary of Jurisdictional Estimates, Mining & Querying: 

Jurisdiction PM2.5 (TPY) PM10 (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-94 Appendix B - Page Number:

99
3.4.6.12 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 because 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 Sector (Feb 06 Version) National Emission 

Inventory For Criteria And Hazardous Air Pollutants”, July 2006. 

Summary of Jurisdictional Estimates, Crop Tilling: 

Jurisdiction PM2.5 (TPY) PM10 (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-95 Appendix B - Page Number:

100
3.4.6.13 Livestock, Beef Cattle, Feedlots, Dust Kicked-up by Hooves 

Description: 

 This includes PM2.5 and PM10 emissions 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 because 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 Sector (Feb 06 Version) National Emission 

Inventory For Criteria And Hazardous Air Pollutants”, July 2006. 

Summary of Jurisdictional Estimates, Livestock, Beef Cattle, Feedlots, Dust Kicked-up 

by Hooves: 

Jurisdiction PM2.5 (TPY) PM10 (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-96 Appendix B - Page Number:

101
3.4.6.14 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 because 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 Sector (Feb 06 Version) National Emission 

Inventory For Criteria And Hazardous Air Pollutants”, July 2006. 

Summary of Fugitive Emissions – Paved and Unpaved Roads: 

Jurisdiction PM2.5 (TPY) PM10 (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-97 Appendix B - Page Number:

102
3.4.7 Non-Road Engines and Vehicles 

3.4.7.1 Commercial Aviation 

Description: 

There are two commercial airports in the study area: Ronald Reagan Washington 

National and Washington-Dulles International Airports. 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 airport 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, using 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 Ronald Reagan Washington National Airport for Calendar Years 

2002, 2008, 2009.1

 

Summary of Jurisdictional Estimates, Commercial Aviation: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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-98 Appendix B - Page Number:

103
3.4.7.2 General Aviation & Air Taxi 

Description: 

The Washington metropolitan area contains 12 public-use general 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 reported for the District of Columbia. 

Factors: 

Sector VOC NOX

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: 

[(LTOa x EFa) + (LTOb x EFb)] x UF / AD = E 

LTO Landing/Takeoff Cycle 

EF Emission Factor 

UF Units Conversion Factor 

AD Activity Days Per Period 

E Emissions 

B-99 Appendix B - Page Number:

104
Summary of Jurisdictional Estimates, General Aviation: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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-100 Appendix B - Page Number:

105
3.4.7.3 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 commercial 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 methods 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 reported for the District of Columbia. 

Factors: 

Emissions 

- VOC 1.234 

- NOX 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-101 Appendix B - Page Number:

106
Summary of Jurisdictional Estimates, Military Aviation: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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-102 Appendix B - Page Number:

107
3.4.7.4 Railroad Locomotives 

Description: 

Diesel-powered railroad locomotives generate emissions during fuel combustion and 

are inventoried as area sources. Electric locomotives are not inventoried under area sources, 

as they take their locomotive power from electricity supplied by power plants. 

Method and Data Sources: 

Two types of locomotive categories are inventoried: 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 the pollutant being inventoried. Where specific 

county-level fuel consumption data is unavailable, 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 calculated 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 instances, 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 were county-specific; for those data, the states 

estimated fuel consumption through one of the two methods above. District obtained the 

2002 data by direct inquiry to the railroad 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 NOX

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-103 Appendix B - Page Number:

108
Equation: 

[(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 VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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 0.000 0.00 0.00

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-104 Appendix B - Page Number:

109
3.4.7.5 Aircraft Auxiliary Power Units 

Description: 

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. 

Method and Data Sources: 

 

 The methods and data sources used to prepare the Virginia inventory for this category 

are documented in Air Pollution Emission Inventories for Washington Dulles International 

Airport and Ronald Reagan Washington National Airport for Calendar Years 2002, 2008, 

2009.1

 

Summary of Jurisdictional Estimates, Aircraft Auxiliary Power Units: 

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (TPY) SO2 (TPY) PM10 (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-105 Appendix B - Page Number:

110
3.4.7.6 Commercial Marine Vessels 

Description: 

Commercial Marine 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, which can exceed 1,000 feet in 

length. 

Method and Data Sources: 

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

B-106 Appendix B - Page Number:

111
3.4.8 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 saws, recreational equipment, farm equipment 

and construction equipment. Nonroad emissions result from the use of fuel in a diverse 

collection of vehicles and equipment, including vehicles and equipment in the following 

categories: 

• Recreational vehicles, such as all-terrain 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 version 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 geographical allocation data files updated until February 1, 2006 

was used by COG staff to calculate base year 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 types 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), NOX, carbon monoxide (CO), carbon dioxide (CO2), sulfur 

dioxides (SO2), and PM. For the purpose of base 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 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, 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 deterioration and/or new standards. 

The emissions are then temporally and geographically allocated using appropriate allocation 

factors. 

B-107 Appendix B - Page Number:

112
There are several input files that provide necessary information to calculate and allocate 

emissions estimates. These input files correspond to the basic data needed to provide the 

calculations: emission factors, base year equipment population, activity, load factor, average 

lifetime, scrappage function, growth estimates, 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. 

Details of this model can be found in its user guide named “User’s Guide for the Final 

NONROAD2005 Model” (EPA420-R-05-013; December 2005) available from the EPA. 

The NONROAD2005 model was run for the metropolitan 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 Autumn (September, October, and November). 

Model inputs (Temperature, fuel, and other parameters) were prepared 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-108 Appendix B - Page Number:

113
Maryland 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 model 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 National 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 (Sulfur percent in gas and diesel, fuel RVP, and 

oxygen weight percent) were provided 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 marine 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 Washington Airports Authority document (see Attachment B4). 

NONROAD2005 model generated GSE emission for Arlington and Loudoun counties were 

replaced by MWAA emissions. Since Dulles airport is spread across Fairfax and Loudoun 

counties, MWAA emission from Dulles airport were divide equally between Fairfax and 

Loudoun counties. 

B-109 Appendix B - Page Number:

114
B-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 format (NIF3.0) as Attachment C3 of this document.

Jurisdiction VOC (TPY) PM2.5 (TPY) NOx (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 2,439.53

Appendix B - Page Number:

115
 B-111

Chapter 4 

Onroad Mobile Sources 

Appendix B - Page Number:

116
 B-112

4.0 ONROAD MOBILE SOURCES 

4.1 Introduction 

This section describes the preparation of the base year 2002 onroad mobile source 

emissions for the Washington DC-MD-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 nonattainment area counties for the purpose of 

putting them in the NIF3.0 format, and emissions and VMT summaries allocated using 

this methodology, is presented in Appendix D1. Mobile6.2.03 input files, 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 Committee (MWAQC) staff is responsible for 

preparing mobile emission factors for the base year 2002. The National Capitol Region 

Transportation Planning Board (TPB) is the lead agency responsible for post-processing 

these mobile emission factors using a comprehensive travel demand modeling process 

and compiling on-road mobile source emissions. 

Except for updating the input data such as vehicle age distributions, diesel sales fraction, 

temperature, I/M programs, and vehicle miles traveled fractions data, the on-road mobile 

emissions analysis process is essentially the same as the one used for developing the 1990 

Base Year Emissions Inventories. A detailed description of travel demand modeling and 

emissions analysis process can be found in “1990 Base Year Emission Inventory for 

Stationary Anthropogenic, Biogenic Sources and Highway Vehicle Emissions of Ozone 

Precursors in the Washington, DC-MD-VA metropolitan Statistical Area, September 

1993”. 

4.2 Summary of Onroad Mobile Source Emissions 

The table below summarizes annual emissions in the nonattainment area for PM2.5-

Direct, NOx, SO2, VOC, NH3, and PM10. 

Appendix B - Page Number:

117
B-113

Onroad Mobile Source Emissions –Base Year 2002 Annual 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 Tl 

PM2.5-Direct 41.73 128.21 322.65 348.59 69.07 38.65 420.26 80.57 118.69 156.27 8NOx 2,016.57 7,922.53 17,929.45 19,771.57 4,141.40 2,161.24 23,317.38 4,482.29 7,005.51 8,827.37 476SO2 272.63 81.63 676.05 704.57 141.06 78.56 876.35 169.36 249.90 289.88 17VOC 2696.75 1208.25 8183.30 8406.81 1992.18 1261.24 10076.33 2044.61 3121.13 4913.24 204NH3 94.96 316.59 792.88 830.76 175.63 97.22 1,034.57 208.63 311.00 383.37 20PM10 58.78 184.20 461.49 495.90 99.71 55.47 603.08 116.89 173.05 223.62 12

1 Fairfax County emissions include onroad emissions from Fairfax City and Falls Church City. Prince William County emis

emissions from Manassas City and Manassas Park City. * Small discrepancies may result due to rounding 

Appendix B - Page Number:118
Chapter 5 

Quality Assurance Procedures 

 B-114 Appendix B - Page Number:

119
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. Staff involved in the inventory 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. 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 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 inventory efforts, particularly the 1990 base 

year inventory and the 1999 PEI. 

Limitations: 

None 

 B-115 Appendix B - Page Number:

120
5.2 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 PM10 and CO contributors. 

Limitations: 

Estimates calculated using computer models 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 have 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 determine where efforts should be concentrated. 

Limitations 

None 

 B-116 Appendix B - Page Number:

121
5.4 STANDARD RANGE CHECKS 

Definition 

Standard range checks address the data quality objective of comparability 

Benefit 

Identify the source categories that have the 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 (data outliers) greater than 20% involving 

sources that made up greater than 5% of the 1990 PM10, 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 year and a given projection year greater 

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 anticipation of emissions increasing 

or decreasing (e.g., decreases in the onroad sector due to fleet turnover). 

Limitations 

None. 

5.5 CORRECTIVE ACTION PLAN 

Corrective and follow-up actions identified during the quality checking process will be 

noted and referred to the appropriate staff. Both the corrective actions identified and 

results of actions taken in response will be documented. 

 B-117 Appendix B - Page Number:

122
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 staff not involved in the inventory calculations. 

Several quality assurance checks will be employed to address the data quality objectives: 

reality/peer review checks, sample calculations, 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 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 inventory efforts, particularly the 1990 base 

year inventory and the 1999 PEI. 

Limitations: 

None 

 B-118 Appendix B - Page Number:

123
5.2 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 PM10 and CO contributors. 

Limitations: 

Estimates calculated using computer models 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 have 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 determine where efforts should be concentrated. 

Limitations 

None 

 B-119 Appendix B - Page Number:

124
5.4 STANDARD RANGE CHECKS 

Definition 

Standard range checks address the data quality objective of comparability 

Benefit 

Identify the source categories that have the 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 (data outliers) greater than 20% involving 

sources that made up greater than 5% of the 1990 PM10, 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 year and a given projection year greater 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 anticipation of emissions increasing or 

decreasing (e.g., decreases in the onroad sector due to fleet turnover). 

Limitations 

None. 

5.5 CORRECTIVE ACTION PLAN 

Corrective and follow-up actions identified during the quality checking process will be 

noted and referred to the appropriate 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 discussions on inventory quality considerations for 

each major source category. It will summarize the results of the quality checking 

procedures 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.

 B-120 Appendix B - Page Number:

125
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 calculations. Several quality 

assurance checks will be employed to address the data quality objectives: reality/peer 

review checks, sample calculations, sensitivity 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 Plan, 2) reliance on reviewer expertise, and 3) comparison of 

emissions estimates to other previous inventory efforts, particularly the 1990 base year 

inventory and the 1999 PEI and other inventories developed by EPA, regional 

organizations, or other states. 

Limitations: 

None 

 B-121 Appendix B - Page Number:

126
5.2 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 emissions estimate. Priority is given to those categories identified 

as the largest emissions contributors. 

Limitations: 

Estimates calculated using computer models 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 have 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 where efforts should be concentrated. 

Limitations 

None 

 B-122 Appendix B - Page Number:

127
5.4 STANDARD RANGE CHECKS 

Definition 

Standard range checks address the data quality objective of comparability 

Benefit 

Identify the source categories that have the 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 greater than 5% of the 1990 PM10, 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 plus 10% and involving sources that made up 

greater than 5% of the 2002 or projection year daily inventories are investigated and 

either corrected (see Corrective Action Plan below) or justified. The justification includes 

whether there was a change in methodology (e.g., different emission factor, allocation 

method, activity data) or if there is a real anticipation of emissions increasing or 

decreasing (e.g., decreases in the onroad sector due to fleet turnover). 

Limitations 

None. 

5.5 CORRECTIVE ACTION PLAN 

Corrective and follow-up actions identified during the quality checking process are noted 

and referred to the appropriate staff. Both the corrective actions identified and results of 

actions taken in response are documented. 

 B-123 Appendix B - Page Number:

128
Attachment A1 

BY 2002 Point Source Emissions Summary 

Appendix B - Page Number:

129
2

Summary of Point Source Emissions: 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 11.13 181.56 

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3

Summary of Point Source Emissions: Virginia 

Point Sources 

(Virginia Portion of Washington 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 Services Inc - Fairfax 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 0.00 997.63 

Appendix B - Page Number:

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4

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 

Appendix B - Page Number:

132
Attachment B1 

Technical Memorandum on 

Commercial Cooking Emissions 

Appendix B - Page Number:

133
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

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PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

iii Cooking Processes: Technical Memorandum

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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

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PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

iv Cooking Processes: Technical Memorandum

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 . . . . . . . . . . . . . . . . . . . . . . . . 119

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

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

2. Comparison of Commercial Cooking PM Emissions to NEI 2001 PM Emissions . . . . 28 2.5 2.5

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 . . . . . 30

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Methods for Developing a NEI for Commercial

1 Cooking Processes: Technical Memorandum

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. 

Emissions from commercial cooking may contribute to exceedances of the Federal PM air 2.5

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

NH were identified). The most challenging aspect of the work was to identify appropriate 3

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

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

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

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

atmosphere with other air pollutants (e.g., nitrogen oxides or NO ). Commercial charbroiling x

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PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

2 Cooking Processes: Technical Memorandum

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.

Appendix B - Page Number:

139
PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

3 Cooking Processes: Technical Memorandum

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

other combustion products, such as NO , carbon monoxide (CO), or sulfur dioxide (SO ), which x 2

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),

however there appears to be some contribution from meat cooking. Emission rates for SO were 2

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.

Appendix B - Page Number:

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4

Table 1A. Summary of Commercial Cooking Test Results: Criteria Pollutants (g/kg)

Equipment Type (fuel) Meat/Food

Emission Factor (g/kg meat) 1

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

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

was thigh meat. SO analyzer malfunctioned, so no 2 

emissions data reported. CO and NO emissions x

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.

Appendix B - Page Number:

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5

Table 1B. Summary of Commercial Cooking Test Results: Criteria Pollutants (lb/ton)

Equipment Type (fuel) Meat/Food

Emission Factor (lb/ton meat) 1

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

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

was thigh meat. SO analyzer malfunctioned, so no 2 

emissions data reported. CO and NO emissions x

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.

Appendix B - Page Number:

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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.

Appendix B - Page Number:

143
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.

Appendix B - Page Number:

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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.

Appendix B - Page Number:

145
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.

Appendix B - Page Number:

146
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.

Appendix B - Page Number:

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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.

Appendix B - Page Number:

148
PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

12 Cooking Processes: Technical Memorandum

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

Criteria Pollutants: PM , PM , VOC 10 2.5 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).

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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 on

total 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: 

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• 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.

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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.

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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. 

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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.

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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.

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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 Type1

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 –

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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. 

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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.

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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):

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

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

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

N = ethnic, ufc 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):

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

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

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

least one under-fired charbroiler;

E = ethnic, ufc 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:

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

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

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

Efast,ufc = Total number of under-fired charbroilers at fast food restaurants;

Eseafood,ufc = Total number of under-fired charbroilers at seafood restaurants;

ES&B,ufc = Total number of under-fired charbroilers at steak & barbecue restaurants;

and

Eall,ufc = 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):

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E * m = M all,ufc steak,ufc steak,ufc

where: Eall,ufc = Total number of under-fired charbroilers at all restaurants

msteak,ufc = Average pounds per week of steak cooked on one under-fired charbroiler

Msteak,ufc = 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,

while those associated with PM were estimated using the PM CE. 10

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Table 12. HAP Pollutants and CE

Pollutant Pollutant Code CE Used

4-Nitrophenol 100027 PM10

Acenaphthene 83329 PM10

Acenaphthylene 208968 PM10

Acetaldehyde 75070 VOC

Acetophenone 98862 VOC

Anthracene 120127 PM10

Benz[a]Anthracene 56553 PM10

Benzene 71432 VOC

Benzo[a]Pyrene 50328 PM10

Benzo[g,h,i,]Perylene 191242 PM10

Biphenyl 92524 PM10

Dibutyl Phthalate 84742 PM10

Ethyl Benzene 100414 VOC

Ethylene Dichloride 107062 VOC

Fluoranthene 206440 PM10

Fluorene 86737 PM10

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

Phenanthrene 85018 PM10

Phenol 108952 VOC

Propionaldehyde 123386 VOC

Pyrene 129000 PM10

Styrene 100425 VOC

Toluene 108883 VOC

Total PAH 234 PM10

Appendix B - Page Number:

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PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

25 Cooking Processes: Technical Memorandum

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

PM10 85,515 8,460 60,304 15,679 1,073

PM2.5 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 10.4

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Methods for Developing a NEI for Commercial

26 Cooking Processes: Technical Memorandum

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

PM commercial cooking emissions were also compared to various source category PM 2.5 2.5

emissions obtained from EPA’s 2001 NEI (EPA, 2003a). Percent contributions, by source

category, to the total 2001 area source NEI PM emissions are summarized in Figure 2. 2.5

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.

Appendix B - Page Number:

163
27

1. PM2.5 Emissions by Commercial Cooking Source Category

Figure 1. PM2.5 Emissions by Commercial Cooking Source Catego

1%

Clamshell Griddle Frying

15%

Flat Griddle Frying

74%

Underfired-Charbroilers

10%

Conveyorized 

Charbroiling

Appendix B - Page Number:164
28

2. Comparison of Commercial Cooking PM2.5 Emissions to NEI 2001 PM2.5 Emissions

1. Agriculture & Forestry consists of agricultural crops and agricultural livestock.2. Stationary Source Fuel Combustion consists of electric utilities oil, gas,other, and internal combustion; industrial coal, oil, other, and internal combustion;commerci

combustion; 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 Emissions

to NEI 2001 PM2.5 Emissions

1%

Agricultur

& Kindred 

1%

Commercial C

Wood, Pulp 

1

Mineral 

2%

Industrial Gas Co

2%

Metals Proces

2%

On-Road Vehicles

4%

Non-Road

Engines &

Vehicles

5%

Residential

Wood 

Combustion

5%

Other

Combustion3

6%

Open Burning

6%

Stationary Source

Fuel Combustion2

7%

Electric Utilities 

Coal Combustion

8%

Forest

Wildfires

13%

Agriculture & Forestry1

Appendix B - Page Number:165
29

3. Total Polycyclic Aromatic Hydrocarbon (PAH) Emissions by Commercial Cooking Source Category

Figure 3. Total Polycyclic Aromatic Hydrocarbon (PAH) Emission

by Commercial Cooking Source Category

20%

Flat Griddle Frying

21%

Conveyorized 

Charbroiling

59%

Underfired-Charbroiling

Appendix B - Page Number:166
30

4. Comparison of Commercial Cooking PAH Emissions to NEI 1999 PAH Emissions

Figure 4. Comparison of Commercial Cooking PAH Emissions

to NEI 1999 PAH Emissions

3%

Surface Coating Solv

2%

Storage & Transpo

Sta

Sto

1%

Commercia

Storag

So

5%

Catastrophic/Accidental Releases

7%

Residential

Wood 

Combustion

22%

Other Combustion

55%

Nonindustrial Solvent 

Utilization

1. Not Elsewere Classified.

Appendix B - Page Number:167
PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

31 Cooking Processes: Technical Memorandum

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. 

Appendix B - Page Number:

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PECHAN September 30, 2003

Methods for Developing a NEI for Commercial

32 Cooking Processes: Technical Memorandum

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.

Appendix B - Page Number:

169
Attachment B2 

Technical Memorandum on 

Composting Emissions 

Appendix B - Page Number:

170
Appendix B2 

Technical Memorandum on 

Composting Emissions 

Appendix B - Page Number:

171
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 for 

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, 2004

Appendix B - Page Number:

172
PECHAN March 31, 2004 

A. INTRODUCTION 

E.H. Pechan & Associates, Inc. (Pechan) developed 2002 ammonia (NH3) emission estimates for 

several miscellaneous source categories for the Mid-Atlantic – Northeast Visibility Union 

(MANE-VU) Regional Planning Organization (RPO). The source categories are a part of four 

different source sectors: industrial refrigeration (Section B); cement plants (Section C); and 

publicly-owned treatment works (POTWs) and composting (Section D). For composting, 

Pechan developed 2002 emission estimates for volatile organic compounds (VOC) in addition to 

NH3. Methods and data sources for developing the 2002 inventory are described in the first three 

sections of this technical memorandum. Section E provides the results of this project. 

B. INDUSTRIAL REFRIGERATION 

In order to estimate NH3 emissions from industrial refrigeration sources for the 2002 MANE-VU 

Ammonia Inventory, Pechan attempted both top-down and bottom-up approaches as described in 

the work plan (Pechan, 2003a). The top-down approach was based on methods used to construct 

the South Coast Air Quality Management District’s (SCAQMD) inventory. For this inventory, 

NH3 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 three companies supplied nearly all of the NH3 (Chitjian et 

al, 2000). 

Pechan attempted to obtain data on NH3 purchases and the amount of NH3 lost by facilities using 

NH3 refrigeration systems. Pechan first tried to collect data from NH3 suppliers. This attempt 

was unsuccessful for two reasons. First, finding a comprehensive list of NH3 suppliers was 

difficult. Many of the companies listed as supplying NH3 in chemical supplier databases either 

did not sell NH3, sold NH3 in another form, or only sold small amounts of NH3for laboratory use. 

Second, few of the companies contacted responded to our request for sales data. 

Once it was determined that surveying suppliers would not yield sufficient data for inventory 

development, Pechan began collecting data directly from facilities operating NH3 refrigeration 

systems. Pechan’s starting point was EPA’s Risk Management Program (RMP) database (EPA, 

2003a). This information included data on the location of 188 RPO facilities that submitted 

RMPs to EPA with NH3 refrigeration systems. The threshold 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 NH3 refrigeration process at the facility (in a process 

field). Pechan attempted to obtain information 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 sensitive (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 NH3 typically lost by the refrigeration system in one year or the amount of 

NH3 purchases over the past few years to recharge the system; and 

 1 Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

Appendix B - Page Number:

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PECHAN March 31, 2004 

• The operating capacity of the system (in lbs of NH3). 

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 capacities 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 NH3 (±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 recharges during the previous year(s). 

For all of the surveyed facilities, Pechan estimated annual NH3 losses by multiplying the 

capacity by the 8% loss factor. This was done instead of using the values 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 survey period likely did not emit that amount of NH3 

during a single year. For the remaining RMP facilities 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 that 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 facility had more than one refrigeration system. Therefore, these 

potential duplicates were left in the database. The overall effect on the inventory estimates is 

small. 

The information described above should cover facilities with large NH3 refrigeration systems 

(>10,000 lb) based on the assumption that facilities required to report under the RMP program 

have done so. For facilities that have smaller refrigeration systems, Pechan requested data from 

the MANE-VU states from the Superfund Amendments and Reauthorization Act of 1986 (SARA) 

Tier II reporting requirements. Under these requirements, facilities subject to Section 311 of 

SARA must supply information on the type and amount of hazardous substances at their 

facilities each year. For NH3, the threshold quantity is 500 lb. 

Pechan again had difficulty obtaining 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 facilities from RI. Of these nine facilities, 

one was larger than the 10,000 RMP reporting threshold. Pechan also received Tier II data from 

NJ. Pennsylvania refused to provide Tier II data for this project and no other states provided 

data. After extracting data for facilities within the 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 available information for smaller capacity facilities 

 2 Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

Appendix B - Page Number:

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PECHAN March 31, 2004 

was not sufficient to develop estimates that could be extrapolated to the RPO. The data from RI 

and NJ were added to the database for larger facilities described above. 

In order to fill out the rest of the inventory for this source category, Pechan used an employeebased emission factor to be included in the Emission Inventory Improvement Program (EIIP) 

guidance to estimate total county-level refrigeration loss emissions (30 lb/employee-yr). This 

emission factor was derived from data in the SCAQMD 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). The Standard Industrial Classification (SIC) codes used to develop 

the county-level employment data are shown in Table 1 below (the North American Industrial 

Classification System codes 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 apply is for the State of 

Delaware. The DNREC contact feels that their coverage of industrial refrigeration sources is 

complete (Fees, 2004). It is interesting to note that the use of the emission factor above yields an 

estimate for DE that is about an order of magnitude higher than that developed through the DE 

survey data. While some smaller industrial refrigeration systems could be missing in DE’s 

survey data, the missing emissions are probably not 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 (NH3) Refrigeration Facilities 

SIC Code Description NAICS Code

2011 Meat Packing Plants 311611 

2013 Sausages/Other Prepared Meats 311612, 311613 

2015 Poultry Slaughtering/Processinga 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 “point-source” data from the facility database 

described above. There were no instances where the total county-level estimate from the facility 

database was more than the employment-based estimate. State-level results are provided in 

Section E. 

 3 Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

Appendix B - Page Number:

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PECHAN March 31, 2004 

C. 2002 CEMENT PLANT EMISSION ESTIMATES 

Pechan contacted Garth Hawkins of the Portland 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 PCA member facilities requesting 

that they provide this information to Pechan directly. Pechan did not receive any responses from 

facilities, and because Mr. Hawkins did not feel comfortable releasing member contact 

information, Pechan was unable to contact facilities directly. 

Since the attempt to collect activity data from facilities was not successful, Pechan turned to 

other sources of data. Actual 2002 throughput data for facilities in Maryland and New York 

were obtained from state agency contacts (Lang, 2004; King, 2004; Mancilla, 2004). For 

facilities in Pennsylvania and Maine, emissions were estimated using 2001 kiln clinker capacity, 

obtained from the PCA (Hawkins, 2003a). 

An NH3 emission factor of 0.145 lb/ton clinker based on data obtained from the PCA (Hawkins, 

2003b) was used to estimate emissions for all plants, 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 the source test, the emission factor for this plant 

was estimated to be 1.31 lb NH3/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 emission factors from cement plants). 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 NH3 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 result, the minimum, average, and maximum emission 

factors based on the PCA data vary over three orders of magnitude (0.002 to 1.29 lb NH3/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 NH3 EMISSIONS INVENTORY 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 Management (OWM; EPA, 2003b), Envirofacts (EPA, 2003c), 

BioCycle (2000), the New England Biosolids & Residuals Association (NEBRA, 2003), and the 

States of New Jersey (Pilawski, 2003) and Delaware (Fees, 2003). 

 4 Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

Appendix B - Page Number:

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PECHAN 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 wastewater collection and treatment facilities, 

facilities for control of sanitary sewer overflows (SSOs), combined sewer overflows (CSOs), 

storm water control activities, nonpoint sources, and programs designed to protect the nation's 

estuaries. Information obtained from the survey is maintained in the CWNS database. The 

collected data are used to produce a Report to Congress, which provides an estimate of clean 

water needs for the United States. 

The CWNS 2000 Survey database was augmented with 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 the MANE-VU database and is supplemented with 

the following data; 

• Envirofacts – Multiple environmental databases for facility information, including toxic 

chemical releases, water discharge permit compliance, latitude and longitude, hazardous 

waste handling processes, Superfund status, and air emission estimates; 

• State of New Jersey – Individual facility number, facility name, county, existing flow, 

biosolids generation, and breakdown of: incineration 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, facility name, county, existing flow, and 

farmland beneficial use. The updated flow rates substituted those provided in CWNS 

2000 Survey; 

• BioCycle – Year 2000 statewide biosolids generation, breakdown of land application, 

composting, lime stabilization, heat drying- pelletization, landfilling, incineration, surface 

disposal, lagoon storage and other; and 

• NEBRA – Biosolids generation of six New England states in 2000, breakdown of land 

application, compost, landfilling, and incineration disposal. This data set replaced six 

New England states biosolids production data reported in the CWNS 2000 Survey. 

For POTWs, Pechan developed emission estimates for wastewater treatment processes, biosolids 

processes at POTWs, and biosolids management practices (mainly at an off-site location). The 

emission factors were taken from draft EIIP guidance (Pechan, 2003b; estimated to be finalized 

in April 2004). The following sections describe the methods for assembling the activity data. 

 5 Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

Appendix B - Page Number:

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PECHAN 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 generation data were taken from the BioCycle 2000 Survey and 

NEBRA. In addition, NJ provided detailed facility-level biosolids production data (Pilawski, 

2003). In order to spatially-allocate NH3 emissions, facility-level biosolids production was 

allocated based on wastewater flows. Biosolids 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 (R2

 = 0.90) of wastewater flow rates and 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 for 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 other 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 statewide 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 regression equation mentioned previously. 

Except for NJ, year 2002 biosolids generation was grown from Year 2000 to Year 2002 based on 

the population for each state. For New Jersey, 2002 biosolids generation data were available at 

individual facilities (Pilawski, 2003). 

All reported biosolids production data are in units of dry tons per year. Since the available NH3

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 NH3 emission estimates, biosolids management practices are aggregated into: land 

application; composting; heat drying- pelletization; 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 factor contained in the 

upcoming EIIP guidance, and are not included in this inventory (estimates of landfill methane 

emissions are needed to estimate landfill NH3 emissions). For biosolids sent to landfills for use 

as daily cover, this activity is included in the land application estimates. Ammonia emissions 

associated with incineration are assumed to be negligible. For heat-drying – pelletization, no 

emissions data are available. Therefore, Pechan developed emission estimates for two biosolids 

management practices: land application and composting. 

 6 Ammonia Emissions Inventory for 

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Table 2 lists the fraction of biosolids applied to land including 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 differently from those listed in the BioCycle Year 2000 Survey. Land 

application fractions of biosolids were estimated 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 facility-specifica 

New York 0.52 

District of Columbia 1.00b

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 the county in which each POTW is located. This 

is an area requiring further study, since biosolids may be landfilled, composted, or land applied 

in different counties or states. The only instance where this allocation method changed was for 

DC-generated biosolids. Information from the District of Columbia Water and Sewer Authority 

(DCWASA, 2004) indicated that biosolids were land applied mainly to crop lands in Virginia 

and Maryland. DCWASA provided estimates that 96% of the biosolids were applied to Virginia 

crop lands with the remainder going to MD croplands. Pechan assumed that the counties in MD 

were those six MD counties surrounding DC. The fraction of biosolids applied to each MD 

county were derived based on harvested acreage in the 1997 Census of Agriculture (NASS, 

2004). The fractions are as follows: Charles – 0.17; Prince Georges – 0.14; Calvert – 0.09; 

Anne Arundel – 0.12; Howard – 0.16; and Montgomery – 0.32. 

Facility geographic coordinates (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 latitudes and longitudes were estimated based on the county centroids 

where the facilities were located. 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 

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d. Estimates of NH3 Emissions from POTWs 

Ammonia emissions from POTWs were assigned to the three source 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 treatment emission factor reflects recent testing in 

southern California that showed much lower NH3 emission levels than had previous been used 

(e.g. previous EPA guidance). For water treatment, much 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 (NH3) 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 

0.027 106

 gallons D; range is 0.004 

to 0.051. 

2630020020 Waste Disposal, Treatment 

and Recovery; 

Wastewater Treatment; 

Public Owned; 

Biosolids Processes Total 

0.142 106

 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 wastes include biosolids (sewage sludge), manure, 

green waste (e.g., landscape trimmings, grass clippings), 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 questions on the fraction of MSW 

recycled, including the amount composted. While recycle 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 and composting fractions. For those 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 close 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 

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for these states, the recycled yard trimmings quantities were used to represent total composting 

activity. 

An NH3 emission factor of 2.81 lb/ton of mixed waste composted was applied to estimate NH3

emissions (see Table 4). This emission factor was derived from SCAQMD test data of a 50:50 

mixture by weight of biosolids and green waste (Pechan, 2003b). Pechan believes that this 

emission factor represents the best match to the available data. The EIIP guidance will also 

contain a set of emission factors strictly for green waste (e.g., yard trimmings); however these 

emission factors should only be applied to green waste composting facilities. This is because 

NH3 emissions are much lower and VOC estimates are higher during green 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 facilities exist in the MANE-VU states; however, the 

BioCycle data did not report throughput data for these facilities. The only place where Pechan 

applied a different composting emission factor was for DC. Information from Biocycle and 

DCWASA indicated that only green waste was composted. Therefore, the emission factors for 

green waste were used to estimate emissions for 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 published in the November 2000 issue. The survey 

conducted in 1999 had only one third of the operating facilities returning questionnaires. In total, 

there were 115 biosolids composting facilities 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 NH3/wet 

ton was applied (see Table 4). Solids content was assumed to be 10% when adjusting dry 

biosolids to the moisture content of composted biosolids (BioCycle, 2000). A few facilities 

reported biosolids in units of cubic yards. For these facilities, a biosolids density of 1000 wet 

lb/cubic yard was applied to convert biosolids volume into mass (EPA, 1993). Table 4 provides 

the SCCs and emission factors for composting operations (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 NH3 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 

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The state-level composting activity data were grown from 1998 to 2002 using population data. 

The 2002 state-level composting activity was then allocated to the county-level using population 

data. As specified in the work plan, Pechan developed emission estimates for both NH3 and 

VOC for composting. 

E. RESULTS 

Table 5 provides a summary of 2002 NH3 emission estimates developed during this project. 

Table 6 provides facility-level emission estimates 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 density maps showing the distribution of RPO 

emissions for industrial refrigeration losses, POTWs and biosolids management, and composting, 

respectively. 

Figures 4 and 5 are pie charts showing NH3 emission estimates for the entire RPO and the New 

York City metropolitan (NYC metro) area, respectively. 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, Essex, Hudson, and Union counties). Also, the 

emission estimates underlying these figures are taken 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 levels, primary contributors are 

from the agricultural sector, although onroad sources are also significant contributors at the 

regional level (see Figure 4). As shown in Figure 5, most of the primary contributors at the 

urban scale are relatively unimportant at the regional to national level. The onroad sector 

dominates in the NYC metro area and other source sectors become more significant contributors. 

This has important implications for understanding fine PM formation in urban areas. 

Regarding cement plants, while these sources also do not appear to be large contributors at the 

regional level, they can be significant 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 - FINAL 

Appendix B - Page Number:

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11 

Table 5. Summary of 2002 Ammonia (NH3) Emission Estimates 

Emissions (tons/year)a 

SCC Description CT DC DE MA MD ME NH NJ NY PA 

2399010000 Industrial Processes;

Industrial 

Refrigeration; Refrigerant Losses; All Processes 

371 46 20.1 756 524 241 124 1051 1817 1629 

305006xx 305007xx 

Industrial Processes; Mineral 

Products; Cement Manufacturing; Kilns 

0.0 0.0 0.0 0.0 157 31.3 0.0 0.0 252 428 

2630020010 Waste Disposal,

Treatment and Recovery; 

Wastewater Treatment; Public Owned; 

Wastewater Treatment Processes Total 

1.9 1.7 0.5 3.9 2.3 0.7 0.4 4.9 39.1 7.4 

2630020020 Waste Disposal,

Treatment and Recovery; 

Wastewater Treatment; Public Owned; 

Biosolids Processes Total 

10.2 8.7 2.4 20.6 12.3 3.6 2.3 25.6 205 38.8 

2630050000 Waste Disposal,

Treatment and Recovery; 

Wastewater Treatment; Public Owned; Land 

Application – Digested Sludge 

0.0 0.0 23.1 179 138 11.7 2.2 107 206 184 

2680001000 Waste Disposal,

Treatment and Recovery; 

Composting; Biosolids, All Processes 

205 0.0 4.6 468 655 247 149 627 350 712 

2680002000 Waste Disposal,

Treatment and Recovery; 

Composting; Mixed Waste, All Processes 

248 0.83b 163 1289 924 98.2 31.7 710 2365 607 

Totals 836 57.2 214 2,716 2,412 634 310 2,526 5,234 3,606 

a Totals do not always add exactly due to rounding. b Reported under SCC 2680003000 (green waste composting). 

Appendix B - Page Number:183
12 

Table 6. 2002 Cement Kiln Emissions 

Facility 

Kiln 

Type State

Clinker 

(ton/yr) 

EF 

(lb/ton 

clinker) 

2002 

Emissions 

(tons) S

Lehigh Portland Cement preheater MD 1,291,628 0.145 93.6 Steve Lang, MDIndependent Cement/St. Lawrence long dry MD 569,993 0.145 41.3 Duane King, MDEssroc Cement Corp long wet MD 308,000 0.145 22.3 Duane King, MDDragon Products Company wet ME 432,180 0.145 31.3 Garth Hawkins, Norlite Corp dry NY 240,942 0.145 17.5 Carlos MancillaNortheast Solite Corporation dry NY 241,996 0.145 17.5 Carlos MancillaGlens Falls Lehigh Cement Company preheater NY 563,618 0.145 40.9 Carlos MancillaSt Lawrence Cement Company wet NY 622,091 0.145 45.1 Carlos MancillaGlens Falls Lehigh Cement Company wet NY 81,472 0.145 5.9 Carlos MancillaLafarge North America Inc. wet NY 1,727,241 0.145 125 Carlos MancillaAllentown Cement Co /Evansville dry PA 853,335 0.145 61.9 Garth Hawkins, Essroc/Bessemer wet PA 621,810 0.145 45.1 Garth Hawkins, Cemex Inc/Wampum Cement Plt dry PA 837,900 0.145 60.8 Garth Hawkins, Lafarge Corp/Whitehall Plt preheater PA 793,800 0.145 57.6 Garth Hawkins, Essroc/Nazareth Lower Cement Plt preheater PA 1,230,390 0.145 89.2 Garth Hawkins, Essroc/Nazareth Cement Plt long dry PA 572,198 0.145 41.5 Garth Hawkins, Hercules Cement Co/Stockertown preheater PA 999,968 0.145 72.5 Garth Hawkins, 

Totals 11,988,562 869

Appendix B - Page Number:184
13 

Table 7. Summary of 2002 VOC Emission Estimates 

Emissions (tons/year) 

SCC Description CT DC DE MA MD ME NH NJ NY PA 

2680010000 Waste Disposal,

Treatment and 

Recovery; Composting; Biosolids, All Processes 

106 0.0 2.4 243 339 128 77.4 325 181 369 

2680020000 Waste Disposal,

Treatment and 

Recovery; Composting; Mixed Waste, All Processes 

275 3.8a 181 1432 1025 110 35.2 788 2626 674 

Totals 381 3.8 183.4 1,675 1,364 238 112.6 1,113 2,807 1,043 

a Reported under SCC 2680030000 (green waste composting). 

Appendix B - Page Number:185
14 

Figure 1. MANE-VU RPO 2002 NH3 Emissions

Industrial 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. Ma

E.H. Pec6245 PleEl Dorad

Appendix B - Page Number:186
15 

Figure 2. MANE-VU RPO 2002 NH3 Emissions

POTWs 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. Ma

E.H. Pec6245 PleEl Dorad

Appendix B - Page Number:187
16 

Figure 3. MANE-VU RPO 2002 NH3 Emissions

Composting

<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. Ma

E.H. Pec6245 PleEl Dorad

Appendix B - Page Number:188
PECHAN March 31, 2004 

Figure 4. MANE-VU RPO NH3 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 NH3 use. “Other Point” includes nonindustrial point sources. It is not clear the degree of overlap between the point source inventory and industrial refrigeration 

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. 

 17 Technical Memorandum: MANE-VU 2002 

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Figure 5. NYC Metro Area NH3 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 NH3 use. “Other Point” includes nonindustrial point sources. It is not clear the degree of overlap between the point source inventory and industrial refrigeration 

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 NH3

emission estimates from NYC metro area landfills (e.g., Fresh Kills). 

 18 Technical Memorandum: MANE-VU 2002 

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Miscellaneous Sources - FINAL 

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E. REFERENCES 

BioCycle, 1999. “Biosolids Composting 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 and Sewer Authority, downloaded from 

http://www.dcwasa.com/education/biosolids_brochure.pdf, February 2004. 

EPA, 1993. Markets for Compost, U.S. EPA, EPA/530-SW-90-073A. 

EPA, 1998, Characterization of Municipal Solid Waste in the United States, U.S. EPA, EPA 

530-R-98-007. 

EPA, 1999. Biosolids Generation, Use, and Disposal 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 Preparedness 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/chief/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 - FINAL 

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PECHAN 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 Cement Association, 2001 kiln capacity personal 

communication with Cristina Mackay, E.H. Pechan & Associates, December 2004. 

Hawkins, 2003b. Garth Hawkins, Portland Cement 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 Holly Lindquist, E.H. Pechan & Associates, January 2004. 

Lang, 2004. Steve Lang, Maryland Department of the Environment, 2002 clinker throughput, 

personal communication with Holly Lindquist, E.H. Pechan & Associates, January 2004. 

Mancilla, 2004. Carlos Mancilla, New York State 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 Biosolids & Residuals Association, 

http://www.nebiosolids.org/savingsoil.html, accessed December 2003. 

Papalski, 2004. R. Papalski, New Jersey Department of Environmental Protection, personal 

communication with H. Lindquist, E.H. Pechan & Associates, Inc., January 2004. 

Pechan, 2004. Documentation for the 2002 Nonpoint Source National Emission Inventory for 

Criteria and Hazardous Air Pollutants, prepared for the U.S. EPA, Office of Air Quality 

Planning and Standards, Emissions, Monitoring and Analysis Division, Emission Factor 

and Inventory Group, prepared by E.H. Pechan & Associates, Inc., February 2004. 

Pechan, 2003a. Work Plan for Preparation of a 2002 Ammonia Emissions Inventory for 

Selected Source Categories for the Mid-Atlantic/Northeast Visibility Union (MANE-VU), 

prepared for the Mid-Atlantic Regional Air Management Association, prepared by E.H. 

Pechan & Associates, Inc., August 29, 2003. 

Pechan, 2003b. Estimating Ammonia Emissions from Anthropogenic Sources – Draft Report, 

prepared for the U.S. EPA, Emission Inventory Improvement Program, prepared by E.H. 

Pechan & Associates, Inc., September 2003.

 20 Technical Memorandum: MANE-VU 2002 

Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

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Pilawski, 2003. A. Pilawski, New Jersey Department 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 Cement, 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 

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Miscellaneous Sources - FINAL 

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Appendix A. Supporting Documentation 

 22 Technical Memorandum: MANE-VU 2002 

Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

Appendix B - Page Number:

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PECHAN March 31, 2004 

 23 Technical Memorandum: MANE-VU 2002 

Ammonia Emissions Inventory for 

Miscellaneous Sources - FINAL 

Appendix B - Page Number:

195
Attachment B3 

BY 2002 Emissions Inventory Document for 

Maryland 

(Maryland Department of the Environment) 

Appendix B - Page Number:

196
MARYLAND DEPARTMENT OF THE ENVIRONMENT

AIR AND RADIATION MANAGEMENT ADMINISTRATION

State Implementation Plan 

2002 Base Year 

State Implementation Plan 

Emissions Inventory and 

Methodologies for 

PM2.5 and Precursors

Prepared for: 

U.S. Environmental Protection Agency 

Prepared By: 

Maryland Department of the Environment 

Appendix B - Page Number:

197
Maryland Department of the Environment 

2002 Base Year State Implementation Plan Emissions Inventory and 

Methodologies for PM2.5 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 

Appendix B - Page Number:

198
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 O3, PM10 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................................................................................................... 12 

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 ........................................................................................46 

Appendix B - Page Number:

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4.1.1.7 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/ACCIDENTAL RELEASES ..................................................................... 103 

4.1.4.1 Oil Spills.................................................................................................................................103 

4.1.4.2 Leaking Underground Storage Tanks.....................................................................................105 

4.1.5 SOLID WASTE DISPOSAL, TREATMENT, 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 SOURCE 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 ....................................................................................147 

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...........................................................................................................................179 

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4.1.8.2 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 ................................................................................................. 215 

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 MARINE VESSELS ........................................................................................................................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 ...........................................................................248

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8.1 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 UPDATES (PLEASE DELETE) ........................................................................................................252 

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1.0 INTRODUCTION 

1.1 OVERVIEW AND BACKGROUND 

The 2002 Base Year State Implementation Plan Emissions Inventory and Methodologies for PM2.5 and 

Precursors (Base Year) is being prepared for the purpose 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 organic compounds (VOC) emissions 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) requires all areas of the nation to 

attain and maintain compliance with the federal ambient air quality standards. These federal standards are 

designed to protect the public health and welfare from these six criteria pollutants. These standards are 

referred to as the National Ambient Air Quality Standards (NAAQS). Areas that meet the NAAQS are 

referred to as “attainment areas”; those that do not are referred to as “nonattainment areas.” The Base 

Year will provide an outline for content and organization 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 Radiation 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 for developing emissions estimates. 

The final inventory document will include emissions from point sources, mobile sources, biogenic 

emissions, non-road mobile sources, and area sources. MDE-ARMA will use the Non-Road Mobile 

Emissions Model, NONROAD, for small engine emissions. MDE-ARMA will supply emissions for 

major point sources and area sources, and will accept 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 demonstrations, emissions trading, emissions 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 emissions from all sources or the relevant pollutants 

or pollutants in such area . . .”. Regulatory agencies and industrial facilities rely on emission inventories 

on an ongoing basis as indicators of air quality changes and for setting permit requirements. 

The end use of emission inventories requires that they be of the highest quality obtainable. They are the 

foundation of air quality decisions. Inventory quality is critical to defining realistic regulations and 

attainment strategies. Deficiencies and inconsistencies 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 quality of inventory data 

collection so that it is a reliable source of information for sound decision-making. 

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6 

1.2 GEOGRAPHIC AREA 

The area that will be inventoried includes the entire State of Maryland. The area can be divided into the 

distinct Non-attainment areas (NAA). Categories that will be inventoried are 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 (PM2.5) 

nonattainment areas in Maryland: 

TABLE 1.1 MARYLAND PM2.5 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, Somerset, St. Mary's, Talbot, 

Wicomico, Worcester 

Unclassifiable 

(Insufficient data to 

classify)1

N/A 

 

1

 Areas which are unclassified are not nonattainment areas. 

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7 

FIGURE 1-2: MARYLAND PM2.5 DESIGNATIONS 

1.3 TEMPORAL RESOLUTION 

Another step of inventory development is the 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 sources 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 particle matter is based on annual emissions. 

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1.4 QUALITY ASSURANCE POLICY AND OBJECTIVES 

In order to provide data of sufficient quality for maintenance planning needs, quality assurance (QA) and 

quality control (QC) procedures are implemented as part of the inventory process. The procedures address 

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, completeness, comparability, and representativeness are addressed to 

ensure an inventory of high quality. The target 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 ensuring 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 PM10 and 1999 

for CO. Any discrepancies (data outliers) greater than 20% involving sources that made up greater than 

5% of either the 1990 or the 2002 inventories for PM10, 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 calculations wherever possible. 

1.5 PLAN INFORMATION SOURCES 

This plan draws upon inventory, quality assurance, and 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 inventory 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: Quality Assurance Procedures. EPA-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 Standards. 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 Plans for O3/CO SIP Emission Inventories. EPA-450/4-88-023. 

December 1988. 

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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 projection year onroad mobile source emissions data and 

additional activity data to be used in estimating emissions for other source categories (paved and unpaved 

road dust). Finally, information from local sources, including Maryland Transportation Authority, 

Maryland Aviation Authority, Maryland Port Authority, university sources, and agricultural experts will 

be used to develop emission estimates for select source categories (as described in Chapter 6). 

1.6 INVENTORY DEVELOPMENT AND QUALITY CONTROL PROCEDURES 

An inventory of actual emissions will be developed for base year 2002. Annual and typical VOC, NOX, 

SO2, PM10 and CO season day emissions estimates will be made. A list of potential VOC, NOX, SO2, 

PM10 and CO sources was developed using the 1990 base year inventory, 1996/1999 periodic emission 

inventories, local knowledge, categories as defined in references, and the 2002 National Emissions 

Inventory (NEI) for VOC, NOX, SO2, PM10 and CO source categories. The source categories are listed in 

Appendix A. 

The inventory development process consists of several 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 effectiveness and rule penetration; 

• Corrective action; and 

• Documentation. 

1.7 ESTIMATION METHODS 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 checking for reasonableness of data obtained. General 

estimation methods and data sources anticipated for each source category are listed below. 

1.7.1 COMBINED APPROACH FOR O3, PM10 and CO BASE YEAR EMISSIONS 

This section of the Base Year document is an overview of MDE-ARMA’s proposed approach to 

preparing the 2002 emission estimates. This is followed by approaches specific to the source 

categories. 

For PM10, the top-emitting PM10 categories are point sources, residential wood combustion, open 

burning, paved and unpaved road fugitive dust. In addition, 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 agricultural 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 the NAA. MDE-ARMA does not intend to estimate 

these emissions. 

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10 

MDE-ARMA plans to focus most of its CO emission inventory and emissions projection effort on the 

top-emitting source categories in the area. For CO, the priority source categories are onroad mobile 

sources, point sources, residential wood combustion, open burning, and nonroad engines/vehicles. 

1.8 MISSING DATA 

Missing data will be identified by the inability to complete the calculations. If data are found to be 

missing, a reasonable effort will be made to acquire the data. If this is unsuccessful, estimates will be 

made based on past years' data or default information 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 the ability of a control device or regulation to achieve all the emission 

reductions that could be achieved by full compliance at all times. Rule penetration (RP) is a measure of 

the extent to which a regulation covers emissions from a source category. RE/RP has been the subject of 

ongoing discussion nationally and is the topic of a draft report by the Emissions Inventory Improvement 

Program (EPA/STAPPA/ALAPCO).9 Briefly, the report recognizes 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 the NAAs. Additionally, some point source emissions are estimated through 

source testing, and therefore do not use control efficiencies 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 results of actions taken in 

response will be documented and kept on file. 

Written documentation specifying inventory methodology 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 Committee Members. September 23, 1998. 

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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 inventory, including identification 

of sources, documenting the method used to calculate emissions from each source, and presenting the 

findings. In order to provide EPA with a written documentation of emissions 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 contractors employed by EPA to review the inventory are 

also subject to confidentiality provisions, or the EPA must remove the confidential material before 

submitting the document for review. This information does not appear in copies prepared public review. 

The Maryland stationary point source inventory is the result of efforts to characterize air emissions 

sources since the early 1970's. This section describes data collection, verification 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 industrial operations that emit 

more than 10 tons per year of volatile organic compounds (VOC); 100 tons per year of carbon monoxide 

(CO), sulfur oxides (SOx), particulate matter with an aerodynamic diameter less than 10 micrometers 

(PM10), and total suspended particulates (TSP); or 25 tons per year of oxides of nitrogen (NOx. In 

addition, stationary sources included in previous PEI submissions were included herein regardless of the 

amount of air pollutants emitted. These emissions criteria are more commonly referred to as “emissions 

thresholds” or simply, “thresholds.”

2.2 COMPILING THE POINT SOURCE LIST 

Maryland has a substantial database of both small and large air emission sources compiled over the last 

eighteen years. Since the thirteen 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 database of over 10,700 sources (both above and below the point source 

thresholds) is reasonably complete. The list of point sources in this inventory was developed by applying 

the appropriate thresholds to the emission levels in the database to differentiate between point and area 

stationary sources. Sources with emission levels greater than the threshold or sources previously included 

in PEI submittals are by definition point sources while sources with emissions levels less than the 

thresholds are by definition area sources. 

 

Several methods of source identification are used by ARMA to ensure the 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 sources though annual facility inspections and through 

investigations conducted in response to citizen complaints. 

The primary means of new source identification is the steady influx of permit applications and equipment 

registrations. Many sources are required by COMAR 26.11.02, Permits, Approvals and Registration, to 

register with ARMA. From 700 to 1,000 new sources are registered with the Department each year. 

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12 

Most of these sources are not considered to be point sources as defined 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 with the Department are tracked until the Department 

receives notification that the equipment or emission source has ceased operations. An emissions source or 

its equipment is not permanently deleted from the registration database until the installation is 

demolished. 

The Department has established a Small Business Assistance 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 Department 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 sources. During these inspections, 

unregistered equipment is sometimes discovered. Statewide response to the Air 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, visible emissions, etc., sighted elsewhere 

during the response. 

2.2.1 EMISSION CALCULATIONS 

The ARMA technical staff uses one of the following methodologies to calculate 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 inspectors 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 numbers 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. Therefore, these boiler emissions 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 category rather than in External 

Combustion Sources category. 

 

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13 

Emissions from specific subcategories of sources can be extracted from the inventory to estimate possible 

reductions from various control strategies. 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 Registration File. Therefore, subcategories of equipment emissions are not 

included in the inventory as separate line items for to do so would result in the double counting of those 

emissions. 

The estimates prepared by the facility inspectors following the annual inspection of each facility are 

compared to the annual emissions reported by each facility in its Annual Emissions 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 further certify that the emissions statement is accurate to the best of the 

owner/operator’s best knowledge. After the certified emissions statements are logged in, they are 

thoroughly reviewed by the assigned facility 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 any discrepancies between the two estimates with the 

owner/operator of the facility in question. When all discrepancies are resolved to the satisfaction of MDE, 

the final emissions estimates are then submitted as an update to ARMA’s Registration 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 ozone 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 and are included in the emissions summary tables, by 

county, at the end of this section: 

1) Annual emissions in pounds per year were converted into pounds per day emissions by dividing 

annual emissions by operating days, 

2) Pounds per day emissions were then multiplied 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 daily 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 inventory in order to satisfy EPA reporting 

requirements under the Consolidated Emissions Reporting Rule. This will be the primary resource 

for developing refined estimates of PM2.5 and NH3 emissions. 

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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. For each particular establishment, the 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, separated by the Bush River. The northern area is known 

as the Aberdeen Area, and the southern sector, formerly Edgewood Arsenal (established in November, 

1917 - as a chemical weapons research, development and 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 Engineering (RDECOM), U.S. Army Ordnance Center 

and Schools, U.S. Army Developmental Test Command, U.S. Army Aberdeen Test Center, U.S. Army 

Center for Health Promotion and Preventive Medicine, 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 testing, 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 Vehicle and Family of Stryker Vehicles of today. 

Known as the "Home of Ordnance," APG has been training Army ordnance personnel since 1918. The 

Army's ordnance training was consolidated at the proving ground during World 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 contributed to the defense and safety of American forces 

threatened by chemical weapons. 

Description 

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15 

More than 7,500 civilians work at Aberdeen Proving 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 the 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 employers in the state of Maryland. 

U.S. Army Garrison, Aberdeen Proving Ground, provides general, administrative and logistical support to 

the post's tenants and satellite activities, and is responsible for the management and operation of the entire 

installation, which in many ways is like a small city. 

Environmental stewardship is an essential 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 2004 APG spent a total of $31 million on environmental 

programs, installation programs and installation restoration activities. 

VOC, NOx, CO, PM, Toxics 

MDE staff reviewed emission estimates 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 & Garden Equip; Other Equipment 

o 4-Stroke Gas Eng; Recreational Equip; Golf Carts 

o 4-Stroke Gas Eng; Recreational Equip; Specialty Vehicles/Carts 

o 4-Stroke Gas Eng; Construction & Mining Equip; Off-Highway Trucks 

o 4-Stroke Gas Eng; Industrial 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 Equip; Rear Eng Riding Mowers 

Pollutants 

Emission 

Source 

Categories 

Appendix B - Page Number:

213
16 

o 4-Stroke Gas Eng; Lawn & Garden Equip; Front Mowers 

o 4-Stroke Gas Eng; Lawn & Garden Equip; Other Lawn & Garden Equip 

o 4-Stroke Gas Eng; Commercial 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 & Mining Equip; Off-highway Trucks 

o Diesel Eng; Construction & Mining Equip; Tractors/Loaders/Backhoes 

o Diesel Eng; Construction & Mining Equip; Other Construction Equip 

o Diesel Eng; Industrial Equip; Forklifts 

o Diesel Eng; Industrial Equip; Sweepers/Scrubbers 

o Diesel Eng; Lawn & Garden Equip; Front Mowers 

o Diesel Eng; Agricultural Equip; Agricultural Tractors 

o Diesel Eng; Commercial Equip; Generator Sets 

o Recreational marine 4-stroke 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 Landfills - 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 emission 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 category. A brief synopsis of the methodologies is 

presented below. 

Emission 

Estimation 

Methodologies 

Appendix B - Page Number:

214
17 

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 calculated 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 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, released in October 2002, which also includes emission factors for PM-10, PM-25, 

S02, and HAPS. Therefore, the emission factors for on-road vehicles were obtained by running the 

MOBILE 6.2.03 model.

 

APG government-owned vehicles were grouped into vehicle categories according 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 estimates 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 vehicles from other organizations 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 counted at each gate over 

both years was used to estimate the number of POVs 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 entered 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 the above-referenced vehicle categories.

Emissions of NOx, CO, VOC, PM-10, PM-2.5, and SO2 from daily employee POVs were estimated 

by multiplying the annual on-base mileage of each vehicle category with the emission factors 

obtained from the MOBILE 6.2.03. Since the model years of POVs traveling on the base would 

vary greatly, it is impractical to estimate the emissions 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 emission 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 pollutant from each vehicle category (lb/yr) 

V = Vehicle miles traveled on-base per year 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)

Appendix B - Page Number:

215
18 

The information on the vehicles tested and miles driven on unpaved test tracks at APG was obtained 

from 2002 logs for each track. The test vehicles were divided equally into the HDDV and HDGV 

vehicle classes. 

Mobile Nonroad Mobile Source Emissions 

APG gathered information about the number of vehicles, 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 hours were not readily available and 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 factors were obtained from Air Emissions Inventory Guidance Document 

for Mobile Sources at Air Force Installations, United 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. Emission 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 Vehicle Emission Study (NEVES), 

November 1991, as well as from the California Air Resources Board's off-road model, test results, 

and regulatory emission standards. These factors were used to estimate the emissions from non-road 

vehicles and equipment.

Emission factors for stationary internal combustion engines were used to estimate 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 calculated 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 towers 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 and 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 Airfield 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). Emissions from aircraft operations were estimated 

using the EDMS (version 4.4) model. 

Emissions of criteria pollutants for watercraft were calculated using factors provided in AP-42, 

Volume 11. Inboard emissions were calculated based on fuel consumption or operating time. 

Outboard emissions were calculated using factors related to fuel consumption. Fuel consumption 

was rarely known, so a generic fuel usage of 3 gallons per hour was used to calculate consumption 

from operating time. 

Appendix B - Page Number:

216
19 

The inventory of watercraft includes APG vessels, privately owned boats, and rental boats. The 

inventory included the size of vessels, whether the boat has an inboard 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 the limited information known about 

many of the watercraft. The number of memberships to the private boat clubs located at APG and 

number of permits to launch boats at APG was known, but no information as to the size and type of 

boats was, nor the time or distance they traveled within the boundaries of APG. All privately 

owned boats launched in the Aberdeen Area were considered outside of the APG boundary once in 

the water, so no emissions were counted from these boats. For privately owned watercraft it was 

assumed that 80% have outboard motors and 20% have inboard and that all are 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 rental 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 categories 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 for Michaelsville landfill using Landfill Gas Emissions Model 

(LandGEM) version 3.02 available through the EPA. LandGEM is based on a first-order 

decomposition rate equation for quantifying emissions 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 Emission Inventory Improvement Program (EIIP); AP-42, 

Volume 11, Fifth Edition; EPA's NON-ROAD 2002 model; EPA's MOBILE 5 model; and the 

Landfill Gas Emissions Model (LandGEM) version 3.02. 

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. 

Controls were applied when applicable to a particular source category. 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations 

Appendix B - Page Number:

217
20 

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. 

Appendix B - Page Number:

218
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. According 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 Airlift Wing which falls under Air Mobility 

Command. The primary mission at Andrews AFB is to transport the President of the 

United States. The base is also tasked, under 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 dignitaries. 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 transporting high-ranking VIPs, typically on foreign flights. The call 

sign prefix was constructed from the acronym SAM (Special Air Mission) and the initial 

F (Foreign), which at the time was represented by the phonetic word "Fox." 

Andrews is also the home of the 89th Communication Group, a unit that provides 

communications to military installations all over the world. The technical control facility 

is one of the largest in the world, and hosts a myriad of sophisticated 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 prepared for Andrews Air Force Base by a 

private contractor. These emission estimates included data for the following source 

categories: 

• Mobile On-Road Source Emissions 

o Mobile - LDGV 

o Mobile - LDGT12 

Description 

Pollutants 

Emission 

Source 

Categories 

Appendix B - Page Number:

219
22 

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 aviation 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 included emission estimates from emission 

certification reports prepared by Andrews 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 varied by source category. A brief synopsis of the 

methodologies is presented below. 

Emission 

Estimation 

Methodologies 

Appendix B - Page Number:

220
23 

Mobile On-Road Source Emissions 

The 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 vehicles 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 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, 

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 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, 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 factors from the latest version of EPA’s 

MOBILE 6.2.03 model, released in October 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 obtained 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 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 following equation to estimate annual 

emissions: 

E = V * F * C 

Where: 

E = Annual emissions of particular pollutant from each vehicle category (lb/yr) 

V = Vehicle miles traveled on-base per year 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)

Appendix B - Page Number:

221
24 

Mobile Nonroad Mobile Source Emissions 

The Andrews AFB non-road vehicle inventory consists of various equipment 

including forklifts, loaders, riding lawn care equipment, and towing equipment. 

The inventory contains the equipment name, model year, horsepower rating, 

number of vehicles, fuel type, engine cycle type, and operating hours for CY 2002. 

The inventory specifies whether the operating 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 Environment, 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 from EPA’s NONROAD 2002a model.

The Andrews AFB aircraft operations inventory consists of information 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 revision of its SIP. The inventory contains the aircraft type 

and manufacturer, engine model and manufacturer, 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, and Allan Holtzman, 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 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 

Adjustments 

Appendix B - Page Number:

222
25 

Controls were applied when applicable to a particular source category. 

Spatial 

Spatial allocation of the emission estimates 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 

Allocations 

Appendix B - Page Number:

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26 

3.4 BALTIMORE-WASHINGTON INTERNATIONAL 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 Route 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 Boulevard 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, aircraft ground support service equipment, motor 

vehicles (on roadways, in parking facilities, and at terminal curbsides), the heating plant, fuel 

storage and handling, and 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 for 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 diesel 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 

Categories 

Appendix B - Page Number:

224
27 

• Mobile Nonroad Source Construction Equipment Emissions 

o 2-Stroke Gas Eng; Construction & Mining Equip; Paving Equip 

o 4-Stroke Gas Eng; Construction & Mining Equip; Plate Compactors 

o 4-Stroke Gas Eng; Construction & Mining 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; Construction & Mining Equip; Signal 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 & Mining Equip; Off-highway Trucks 

o Diesel Eng; Construction & Mining Equip; Rubber Tire Loaders 

o Diesel Eng; Construction & Mining Equip; Tractors/Loaders/Backhoes 

o Diesel Eng; Construction & Mining Equip; Crawler Tractor/Dozers 

o Diesel Eng; Industrial Equip; Aerial Lifts 

o Diesel Eng; Industrial Equip; Forklifts 

o Diesel Eng; Industrial Equip; Sweepers/Scrubbers 

o Diesel Eng; Commercial Equip; Generator Sets 

o Diesel Eng; Commercial Equip; Air Compressors 

o Diesel Eng; Commercial Equip; Welders 

• Mobile Onroad Source Emissions 

o Firefighting Training 

• Point Source Emissions 

o MDE staff also reviewed and included 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 Modeling System (EDMS) Version 4.4 

• Aircraft 

Emission 

Estimation 

Methodologies 

Appendix B - Page Number:

225
28 

FAA’s EDMS computer program contains a database of aircraft engine emission factors 

based on engine make and model and four engine operation modes (taxi/idle, takeoff, 

climb out, and approach). EDMS also contains a database of emission 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 data 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 aircraft. 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 from parking facilities. 

• Training Fires 

FAA’s EDMS computer program contains a database 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 activities 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 were taken from EPA’s NONROAD program and 

MOBILE6.2. Emissions from several components of construction activities were calculated, 

specifically: onsite construction equipment (backhoes, bull dozers, graders, etc.), haul 

vehicles idling onsite (cement trucks, dump trucks, etc.), and haul vehicles and construction 

worker vehicles accessing the site. An industry-wide, representative mix of the number and 

types of construction equipment, average power rating (horse power), and equipment load 

factors was used in the analysis. Construction-related motor vehicles (dump trucks, pick-up 

Appendix B - Page Number:

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29 

trucks, etc.) were assumed to travel a round trip on-site distance 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 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. 

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 

Allocations 

Appendix B - Page Number:

227
30 

4.0 AREAS SOURCES

4.1 EMISSION ESTIMATION METHOD BY CATEGORY 

Sample calculations presented below are for illustrative purposes only and may not reflect actual 

emissions. 

4.1.1 PETROLEUM DISTRIBUTION LOSSES 

Evaporative emissions occur at all points in the gasoline distribution process. 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 inventoried 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 dispensing outlets result from vapor losses during tank truck 

unloading into underground storage tanks, vehicle fueling (boat fueling at marinas), and 

underground storage tank breathing. Evaporative losses from each activity in this source 

category have been tabulated separately so that various emission reduction control measures 

could be easily evaluated. 

Emissions from vehicle fueling, including spillage 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. 

Appendix B - Page Number:

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31 

4.1.1.1 Tank Truck Unloading 

SCC: 25 01 060 053 

 Emissions from tank truck unloading are affected by whether the service station tank is 

equipped for submerged, splash or balance filling. Therefore calculations were based on the 

filling method used and gallons sold. 

VOC 

The method used to calculate emissions (all VOC), is presented in EIIP10, Chapter 11, Gasoline 

Marketing, which extracts the emission factors from AP-42, Volume I, Table 5.2-7. 

Activity 

The Maryland Comptroller of the Treasury, Gasoline Tax Division provided annual 

gallons of gasoline and diesel fuel sold. This data includes taxable and non-taxed gasoline 

purchased by the U.S. Government. State and local government sales are included in the 

taxable sales data. The statewide total of gallons of fuel sold was allocated to the county 

level proportional to the number of registered vehicles within the county. Vehicle 

registration data was collected from the Maryland 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 tanks 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 tanks have eliminated splash-fill tanks in the state. A 

recent SSCD study determined that the rule effectiveness 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 gas stations. 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. This survey data was used to determine the 

penetration of each filling technology. The total fuel sales in the county were multiplied 

 

10 Emission Inventory Improvement Program 

Description: 

Pollutants 

Method and 

Data Sources: 

Appendix B - Page Number:

229
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 pressure and temperature. Emissions from 

loading petroleum liquid can be estimated (with a probable error of ±30 percent) using the 

following expression11: 

T

MPS LL** = *46.12

where: 

LL = loading loss, pounds per 1000 gallons (lb/103 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 loaded, pounds per square inch absolute (psia) 

 (see Figure 7.1-5, Figure 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 saturation factor (S) is a constant for a specific 

petroleum liquid, carrier and type of loading service 

The true vapor pressure (P) can be estimated 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 

( ) ( ) ⎭

⎬

⎫

⎩

⎨

⎧ ⎟ +

⎠

⎞ ⎜

⎝

⎛

+ − ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟ −

⎠

⎞ ⎜

⎝

⎛

+

+ ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛

+ −− ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛

+ = − 64.156.459

8742 log013.2 6.459

2416

6.459

1042 log* 854.1

6.459

0.413 7553.0exp 10

5.0

10

5.0

T

RVP

T

S

T

S RVP

T

P

Appendix B - Page Number:

230
33 

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

P T

TP = LLLL

The loading factor or emission factor is directly proportional to true vapor pressure and 

inversely proportional to temperature 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 and 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 = = P T

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 pressure 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 from 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 

Allocations 

Appendix B - Page Number:

231
34 

The equation for estimating emissions from tank truck unloading is: 

(Gi x Fi (fm) x EFfm) + (Gi x Fi (fm) x EFfm) Efj = 2000 x 365 Where: 

 Efj = Emissions of VOC in tons per day from tank truck unloading per county i 

 Gi = Gallons of gasoline sold in county i during 2002 

 Fi (fm) = Fraction of gasoline dispensed per county i per filling method (balanced 

submerged or submerged) during 2002 

 EFfm = Emission factor per filling method for 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 200212 = 2,570,356,195 gallons 

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration 

proportion: 

Carroll County vehicle registration13 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 Comptroller of the Treasury, Gasoline Tax Division 13 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program. 

Emissions 

Calculation 

Appendix B - Page Number:

232
35 

[86,914,019.269 gallons of gasoline sold in Carroll County in 2002 x 91 percent14 filled by 

balanced submerged filling method x 0.2453 lbs.. VOC per 1000 gallons of gasoline15 ] + 

[86,914,019.269 gallons of gasoline sold in Carroll County in 2002 x 9 percent filled by 

submerged filling method x 5.9691 lbs.. VOC per 1000 gallons of gasoline16 ] = 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. 

Appendix B - Page Number:

233
36 

4.1.1.2 Stage II Refueling 

SCC: 25 01 060 100 

Emissions from Stage II refueling are substantially less than those from Stage I because gasoline 

vapors that ordinarily might have escaped during vehicle fueling are recirculated by a special 

nozzle back into the pump. The start year for Stage II refueling in all Maryland ozone 

nonattainment areas was 1993. Gasoline stations were required to have Stage II nozzles installed 

by November of that year. Calculations were based on the filling method used and gallons sold. 

VOC 

EPA recommends that the MOBILE6 model be used to generate refueling (Stage II) emission 

factors for highway vehicle emission inventories (EPA, 1992b). The model, designed to support 

the evaluation of air pollution from gasoline- and diesel-fueled vehicles, 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 refueling emissions in units of grams per 

mile. These values are multiplied by fuel economy (in units of miles per gallon) and total 

gasoline sales (in units of gallons purchased/sold) 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 refueling emission factors, including sensitivity to 

temperature and Reid vapor pressure (RVP), and these have not yet been incorporated into 

published AP-42 factors for refueling. Additionally, 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 tank during refilling; and (2) gasoline spillage 

during refueling. The MOBILE user may request either a single emission factor that 

combines the two mechanisms or separate emission 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 Sources 

Appendix B - Page Number:

234
37 

No subtration of emissions from point sources is necessary. 

Controls for this source category include Stage 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: 

(Gi x EFStII x MPG x SAF) EStII = 2000 x 365 Where: 

 EStII = emissions of VOC in tons per day from stage II refueling 

 Gi = gallons of gasoline sold in county i during 2002 

 EFStII = 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 included 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 

Calculation 

Appendix B - Page Number:

235
38 

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 the tank evaporating gasoline and emitting vapors. 

VOC 

The method used to calculate emissions (all VOC), is presented in EIIP17, Chapter 11, Gasoline 

Marketing, which extracts the emission factors from AP-42, Volume I, Table 5.2-7. 

Activity 

The Maryland Comptroller of the Treasury, Gasoline Tax Division provided annual 

gallons of gasoline and diesel fuel sold. This data includes taxable and non-taxed gasoline 

purchased by the U.S. Government. State and local government sales are included in the 

taxable sales data. The statewide total of gallons of fuel sold was allocated to the county 

level proportional to the number of registered vehicles within the county. Vehicle 

registration data was collected from the Maryland 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 sales and car registration as in tank truck 

unloading. 

 

17 Emission Inventory Improvement Program 

Description: 

Pollutants 

Method and 

Data Sources: 

Appendix B - Page Number:

236
39 

No subtration of emissions from 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 emissions from underground tank breathing is: 

(Gi x EFutb) Eutb = 2000 x 365 Where: 

 Eutb = emissions of VOC in tons per day from underground tank breathing and 

emptying 

 Gi = gallons of gasoline sold in county i during 2002 

 EFutb = emission factor for underground 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 200218 = 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 Comptroller of the Treasury, Gasoline Tax Division 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

237
40 

Carroll County vehicle registration19 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 gasoline20 ] = 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. 

Appendix B - Page Number:

238
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 effects 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, pressure 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 other dispensing outlet, and 

• from empty tank trucks returning from service stations to bulk plant/terminals. 

VOC 

The method used to calculate emissions (all VOC), is presented in EIIP21, 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 document in Table 11.3-1. The AP-42 emission 

factors represent a typical range of values. EIIP averages the “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 and car registration as in tank truck unloading. 

MDE used the emission factors from EIIP, Volume 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 Sources 

Appendix B - Page Number:

239
42 

/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 retail sales and state retail sales times state 

fuel sales. MDE used the same sources for gasoline sales and car registration 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:

(Gi x 1.25 x EFtt) Ett = 2000 x 312 Where: 

 Ett = emissions of VOC in tons per day from tank trucks in transit 

 Gi = thousand gallons of fuel sold in county i 

 EFtt = 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 200222 = 2,570,356,195 gallons 

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration 

proportion: 

Carroll County vehicle registration23 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 gasoline24 ] = 6,518.55 lbs. VOC emitted. 

 

22 Annual sales of gasoline from Maryland Comptroller of the Treasury, Gasoline Tax Division 23 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program . 

Appendix B - Page Number:

240
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. 

Appendix B - Page Number:

241
44 

4.1.1.5 Aircraft Refueling 

SCC: 22 75 900 000 

Jet kerosene (used primarily by commercial turbojet and turboprop aircraft), jet naphtha (used 

primarily by military aircraft) and aviation gasoline (used by aviation reciprocating engines) are 

the three most common types of aircraft fuels used 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 activity 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 airport survey data and the Maryland Aviation 

Administration’s 2002 Operations Count for Public-Use Airports to obtain operational 

counts. A few airports, such as Andrews Air 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 loading 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 emissions at airports 

with large amounts of general aviation (piston engine 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 saturation factor: 1.45 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

242
45 

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 (REi) 

Fuel Type (lbs. VOC/kgal)

Jet Kerosene 0.03839 

Aviation Gasoline 14.86358 

Jet Naphtha 3.61340 

Emission Estimate Equation:

CAI Si x SAi

X REi Ear = 

2000 x 365 

where: 

 Si = 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 factor for fuel type i 

 Ear = Emissions from aircraft refueling in tons VOC per day 

2002 Sample Calculation for Aircraft Refueling- General Aviation (Allegany County)

Maryland aviation gasoline fuel sales = 105,000 barrels25 = 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 14.8635826 = 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, 

Appendix B - Page Number:

243
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 transport 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 barges carrying petroleum liquids result from 

loading losses, ballasting losses and transit losses. Petroleum 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 pipeline transport of petroleum products (AP-42, 

Section 5.2). 

Loading losses occur as organic vapors in “empty” cargo tanks are displaced to the atmosphere 

by the liquid being loaded into the tanks. These vapors are a composite of vapors formed in three 

ways: 

 Vapors which are formed in the “empty” tank by evaporation of residual product from 

previous loads; 

 Vapors transferred to the tank from 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 petroleum liquids at marine terminals and 

refinery loading docks. It is common 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. Ballasting 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 compartment 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 the liquid in the tank due to liquid expansion or 

contraction due to the temperature change. Some ships are equipped with controls for these 

losses. 

VOC 

Description 

Pollutants 

Appendix B - Page Number:

244
47 

Activity 

The method used to calculate emissions (all VOC) is presented in EIIP27, Chapter 12, 

Marine Vessel Loading, Ballasting and Transit, dated May 1998. 

A significant part of the emissions from this source are from the Eastern Shore of 

Maryland because petroleum products are delivered 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, Ballasting and Transit, Waterborne Commerce of the 

United States, Atlantic Region Freight Tables, Part 1, 1998, and AP-42, Table 7.1-2 and 

Section 5.2. Waterborne Commerce supplied tonnage and type of petroleum products 

delivered to the various ports in Maryland for the year 2001. Tonnages of petroleum 

delivered were converted into Kgal.s (1000 gallons) and then used to calculate emissions. 

 

Factors 

UNCONTROLLED VOC EMISSION FACTORS 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 convert units from 1,000 ton (Mtons) to Mgal. 

where: 

 

27 Emission Inventory Improvement Program 

Method and 

Data Sources 

Appendix B - Page Number:

245
48 

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 petroleum liquid; see Table 7.1-2 in AP-42 (lb/gallon) 

 Density28

 (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 control 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:

[(SOEFP x PPS,P) + (BREFP x PPB,P) + (BLEFP,U x 0.30 x PPBL,P) + (TREFP x PPT,P)] PVP = 2000 

Where: 

PVP : 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) 

SOEFP: Ship/ocean vessel loading emission factor (pounds VOC per 1,000 gallons 

transferred) 

PPS,P: Amount of petroleum liquid (p) loaded into ships and ocean vessels in the 

inventory region (1,000 gallons) 

BREFP: Barge vessel loading emission factor (pounds VOC per 1,000 gallons 

transferred) 

PPB,P: Amount of petroleum liquid (p) loaded into barges in the inventory region 

(1,000 gallons) 

 

28 AP-42, Table 7.1-2 

Appendix B - Page Number:

246
49 

BLEFP,U : Ballasting emission factor (pounds VOC per 1,000 gallons water ballasted) 

PPBL,P: Amount of petroleum liquid (p) unloaded from vessels that are ballasted 

(1,000 gallons) 

TREFP : Vessel transit emission factor (pounds VOC per week per 1,000 gallons 

transferred) 

PPT,P: Amount of petroleum liquid (p) transported by marine vessels in the inventory 

region (1,000 gallons) 

2002 Petroleum Vessel Unloading Losses Sample Calculation (Gasoline - Baltimore City)

Gallons (in Thousands) of Petroleum 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 (Kgal.s) and then used to calculate emissions. 

Vessel Loading Emissions

For vessel loading operations, 90 percent of the total throughput was loaded at terminals with a 

control system of 95 percent efficiency. According to the local port authorities, transit time in the 

inventory area is two days (2/7 of a week). Emissions for each 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/year 

Appendix B - Page Number:

247
50 

Note that the calculation for ballasting emissions in the equation includes a correction term of 

0.20. This correction term reflects 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 distillate oil at 60 deg. F: 0.0074 

 

Appendix B - Page Number:

248
51 

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 has been stored long enough in a 

can for fuel molecules to infiltrate 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 gas can is subjected to daily cycle of 

increasing and decreasing ambient 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. The SCCs for PFCs are also new and are 

shown above. 

VOC 

The method used to calculate emissions (all VOC), is adoped from a CARB29 survey and 

methodology adopted by OTC30. 

Portable fuel container emission are calculated by accounting for emissions from five different 

components related to gas container use: permeation, diurnal, transport-spillage, refueling 

spillage and refueling vapor displacement emissions. The permeation, diurnal emissions 

 

29 ARB’s Mailout MSC 99-25, “Public Meeting to Consider Approval of CA’s Portable 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 Sources 

Appendix B - Page Number:

249
52 

(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 

Activity 

The following input data is required to calculate emissions for this source category. 

1. Number of residential housing units in 2002 by county, N 

2. Number of commercial businesses31 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 commercial and residential PFCs). These emission factors 

were derived from CARB’s survey data (CARB, 1999). 

Because the application of architectural surface coating is defined as an area source, there is no 

need to subtract point source emissions from the total, 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 were allocated to the local area level based 

on commercial and industrial business location. 

Temporal 

For the residential PFC SCCs, the emissions were allocated based on the monthly and 

weekday/weekend day temporal profiles for residential 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 

Allocations 

Appendix B - Page Number:

250
53 

NONROAD model. For the commercial PFC SCCs, 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 population is calculated as follows: 

 

 PopR = (N)*(A)*(CountR) (Eq. 1) 

where: PopR = Statewide Residential-Gas-Can Population 

 N = Number of Occupied-Housing Units in OTC State 

 A = Percentage of Households with Gas Cans (46%) 

 CountR = Average Number of Residential-Gas Cans per Household 

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

 HCPR = Σ (PopR)*(S)*(EFP)*(BR)*(SizeR)*(Level)/CF (Eq. 2) 

where: HCPR = Permeation Emissions in tons per day (tpd) 

 PopR = Statewide Residential-Gas-Can Population 

 EFP = Appropriate Permeation-Emission Factor (g/gal-day) 

 S = Percentage of Gas Cans Stored with Fuel (70%) 

BR = Percentage of Cans Stored in Closed Condition with respect to 

Material (Plastic 53%; Metal 13%) 

 SizeR = 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-gas cans are calculated as 

follows: 

 HCDR = (PopR)*(S)*(EFD)*(BR)*(SizeR)*(Level) (Eq. 3) 

where: HCDR = Diurnal Emissions (tpd) for Residential-Gas Cans with respect to 

Storage Condition (Open or Closed) and Material (Plastic or 

Metal) 

 PopR = Statewide Residential-Gas-Can Population 

S = Percentage of Gas-Can Population Stored with Fuel (70%) 

 EFD = Appropriate Diurnal-Emission Factor with respect to Storage 

Condition and Material (g/gal-day or g/day) 

Emissions 

Calculation 

Appendix B - Page Number:

251
54 

 BR = Percentage of Gas-Can Population with respect to Storage 

Condition and Material 

 SizeR = Weighted Average Capacity of Residential-Gas Cans (2.34 gal.) 

Level = Weighted Average Amount of Stored Fuel (49%) 

 CF = 908,105 g/ton 

 

Residential-transport-spillage emissions are determined as: 

 HCTR = (PopR)*(S)*(RefillR)*(EFT)*(BR) (Eq. 4) 

where: HCTR = Residential-Gas-Can-Transport-Spillage Emissions (tpd) 

 PopR = Statewide Residential-Gas-Can Population 

S = Percentage of Gas Cans Stored with Fuel (70%) 

 RefillR = Average Number of Residential-Gas-Cans-Pump-Refills per Day 

per Can (refill/day from survey) 

 EFT = Transport-Emission Factor with respect to Storage Condition 

(g/refill) 

 BR = Percentage of Gas Cans with respect to Storage Condition and 

Material 

 CF = 908,105 g/ton 

 

The commercial-gas-can population is calculated as follows: 

 

 PopC = (NC )*( CountC) (Eq. 5) 

where: PopC = Statewide Commercial-Gas-Can Population 

 NC = Number of Occupied Businesses in State 

 CountC = Average Number of Gas Cans per Business 

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

 HCPC = Σ (PopC)*(S)*(EFP)*(BC)*(SizeC)*(Level) (Eq. 6) 

where: HCPC = Permeation Emissions (tpd) 

 PopC = Statewide Commercial-Gas-Can Population 

 EFP = Appropriate Permeation-Emission Factor (g/gal-day) 

 S = Percentage of Gas Cans Stored with Fuel (70% for Residential 

Survey) 

 BC = Percentage of Applicable Gas Cans Stored in Closed Condition 

 SizeC = 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 

Appendix B - Page Number:

252
55 

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

calculated as follows: 

 HCDC = (PopC)*(S)*(EFD)*(BC)*(SizeC)*(Level) (Eq. 7) 

where: HCDC = Diurnal Emissions (tpd) for Commercial-Gas Cans with respect to 

Storage Condition (Open or Closed) and Material (Plastic or 

Metal) 

 PopC = Statewide Commercial-Gas-Can Population 

 EFD = Appropriate Diurnal-Emission 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) 

 BC = Percentage of Gas Cans with respect to Storage Condition and 

Material 

 SizeC = 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: 

( )

( )( )()⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

= ∑

SIZE POP S

Fuel

REFILL

C NON

C * * (Eq. 8) 

where: RefillC = Average Number of Non-Lawn-and-Garden Equipment 

Commercial-Gas-Cans Pump Refills per Day per Can (refill/day) 

 Fuel = Non-Lawn-and-Garden Equipment Fuel Consumption (gal/day) for 

2000 

 SizeC = Weighted Average Capacity of Commercial-Gas Cans (3.43 

gal/can-refill) 

 POPNON = 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: 

 HCTC = (PopC)*(S)*(BC)*(RefillC)*(EFTC) (Eq. 9) 

where: HCTC = Commercial-Gas-Can-Transport-Spillage Emissions (tpd) 

Appendix B - Page Number:

253
56 

 PopC = Statewide Commercial-Gas-Can Population 

S = Percentage of Gas Cans Stored with Fuel (70% from Residential 

Survey) 

 BC = Percentage of Gas Cans with respect to Storage Condition and 

Material 

 RefillC = Average Number of Gas-Cans Pump Refills per 

 Day per Can 

 EFTC = Transport-Spillage Emission Factor (g/refill) with respect to 

Storage Condition 

 CF = 908,105 g/ton 

The total area source portable fuel container emissions are summed as follows: 

EPFC - A = HCPR+HCDR+HCTR+HCPC+HCDC+HCTC

EPFC - SD = EPFC - A *SAF//ADDF 

Where: 

EPFC - A = (tons/yr) for an annual emission of pollutant by county 

EPFC - SD = (tons/day) for a typical summer day emission of pollutant 

AADF = Annual activity day factor (WAF * 52 weeks/year) 

SAF = Seasonal adjustment factor 

 

Appendix B - Page Number:

254
57 

4.1.2 STATIONARY SOURCE SOLVENT 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, trifluorotrichloroethane and 

perchloroethylene. None of these solvents is on the VOC list. The latest 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 inventory of ozone precursors. 

Therefore this category has 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 stations or manufacturing facilities, where solvents 

at room temperature (or slightly warmed) are used to clean parts via immersion or rinsing. 

Cold cleaners are usually individually small emission sources and, because they are widely 

scattered and frequently used, they are most easily treated as area sources. If they are collocated 

at a major source, they may be included in the point source inventory and those emissions will 

need to be subtracted from the area source estimate. 

There are two basic types of cleaning machines: batch and in-line cleaning machines (also called 

continuous cleaning machines). Both of these equipment types are designed to use solvent to 

clean parts. The solvent is either used to clean in its non-vapor liquid form (at a temperature 

below the boiling point, referred to as cold cleaning), or heated to a temperature above its boiling 

point (referred to as vapor cleaning). Other solvent cleaning operations 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 counting of emissions. Additionally, emissions from 

solvent cleanup may be included as a part of an industry- or process-specific emission estimate. 

VOC 

Description 

Pollutants 

Appendix B - Page Number:

255
58 

MDE staff used an alternative per capita emission estimation method documented in EIIP32, 

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 inventory. 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). A 2002 reduction factor (Phase II Attainment Plan for the 

Baltimore Nonattainment Area and Cecil County) of 53.60% was applied to the calculated 

emissions. This factor combines reductions from technology rules and good housekeeping 

practices and the application of rule effectiveness as shown below: 

Reduction factor = (control 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 total emission factor of 4.3 lbs. VOC per capita 

per year for solvent cleaning operations. The emission 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

Ecc = 4.3 lbs VOC per capita per year for cold cleaning degreasers 

CEcc = 67% 

REcc = 80% 

RPcc = 100% 

Note:

 

32 Emission Inventory Improvement Program 

Method and 

Data Source 

Appendix B - Page Number:

256
59 

Emissions from this source category have increased because of a change in the emission factor 

and emission estimation methodology. In previous emission inventories, 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 subtracted from the area source inventory. MDE 

previously used an emission factor from AP-42, Section 4.6 – Solvent Degreasing, Table 4.6-133. 

This table reports a 4.0 lbs. VOC per capita emission 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 the calculated emissions (rule effectiveness was not applied). This factor 

combines reductions from technology rules and 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 degreasing 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 emissions 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 

Calculation 

Appendix B - Page Number:

257
60 

Equation:

[ ] CC CC CC PtSourceCC

ccj

CC ERPRECE EFPOP E −

⎭

⎬

⎫

⎩

⎨

⎧ = − )**(1* 312*2000

*

Where: 

 Ecc = Emissions of VOC in tons/day from cold cleaners 

 POPj = 2002 population of county j 

 EFcc = VOC emissions factor for cold cleaning degreasing 

 CEcc = Control efficiency for cold cleaning degreasing 

 REcc = Rule Effectiveness for cold cleaning degreasing 

 RPcc = Rule Penetration for cold cleaning degreasing 

E PtSourceCC = Point Source Emissions from cold cleaning degreasing 

2002 Sample Calculation for Cold Cleaning Degreasing (Anne Arundel County)

(503,38834 people x 4.3 lb/capita/year)/(2000 lbs./ton x 312 operating days/year) = 3.469 

tons/day. 

503,388 x 4.3 lbs. VOC/ person/year35 = 2,164,568 lbs. per person VOC emitted. 

Converting to tons per day: 2,164,568 / (312 operating days per year36 x 2000 pounds per ton) = 

3.469tons VOC per day emitted (there is no seasonal adjustment37). 

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 EIIP 

Appendix B - Page Number:

258
61 

3.3.2.3 Surface Coating

Surface coating includes paints, enamels, varnishes, lacquers and other product finishes. Some 

of those coatings contain a solvent-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 coating 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 EIIP38, 

Chapter 3, Architectural Surface Coating, dated November 1995. The document provides an 

outline for developing a per capita usage factor, and for using that usage factor and an emission 

factor to calculated a VOC emission estimate. 

Activity 

Determine the per capita usage factor by dividing the national total architectural surface 

coating quantities39 for solvent- and water-based coatings by the U.S. population40 for that 

year. 

Per Capita Usage Factor Development

The table below shows a portion of Table 2 from 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-based paints, except for the two types listed as 

Architectural Lacquers and Architectural Coatings N.S.K. These latter types of paints can 

be assumed to be entirely solvent-based coatings. 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 Sources 

Appendix B - Page Number:

259
62 

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 dividing 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 

= 2.044352 

Appendix B - Page Number:

260
63 

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-interior 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 47,994 

Appendix B - Page Number:

261
64 

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 insulation, 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 concentrates produced for packaging in 

Appendix B - Page Number:

262
65 

 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 surface 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 architectural surface coating is defined as an area source, there is no 

need to subtract point source emissions from the total, 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 

Allocations 

Appendix B - Page Number:

263
66 

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 solvent-based emissions is:

POPi 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 

POPi = 2002 population of county i 

UF ASC – SB = Usage factor for solvent-based 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 efficiency41 for architectural surface coatings 

RE ASC = Rule effectiveness42 for architectural surface coatings 

RP ASC = Rule penetration for architectural surface coatings 

Equation to calculate water-based emissions is:

POPi 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 

POPi = 2002 population of county i 

UF ASC – WB = Usage factor for water-based architectural surface coatings 

EF ASC – WB = VOC emission factor for water-based 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 

Calculation 

Appendix B - Page Number:

264
67 

2002 Example Calculation Architectural Surface Coating (Anne Arundel County)

Solvent-Based

503,3881

 x 0.442846 gal/capita x 3.87 lbs. VOC/gal/year2 = 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 1.33

 = 1.229 tons VOC per ozone season day emitted from solvent-based architectural 

surface coating 

Water-Based

503,3881

 x 2.044352 gal/capita x 0.74 lbs. VOC/gal/year2 = 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 1.33

 = 1.085 tons VOC per ozone season day emitted from water-based architectural 

surface coating 

 

Appendix B - Page Number:

265
68 

4.1.2.4 Auto Refinishing 

SCC: 24 01 005 000 

Automobile refinishing is the repainting of worn or damaged automobiles, 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 enamels 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. MDE adopted a regulation based upon 

federal guidance that requires the use of reformulated coatings and equipment with greater 

transfer efficiency in the application of coatings. 

VOC 

MDE staff used an alternative per employee emission estimation methodology documented in 

EIIP43, Chapter 13, Auto Body Refinishing, dated January 2000. The document provides an 

outline for developing a per employee emission factor 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 state 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 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. 

County Business Patterns lists employee data by Standard Industry Code (SIC). Many 

values are based on actual data. However, some county SICs list a range for the number of 

employees through a letter code. 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. 

 

43 Emission Inventory Improvement Program 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

266
69 

The autobody refinishing category does not include new car coating. Applicable point 

source emissions (those within the same SIC) taken from the MDE/ARMA registration 

files have been subtracted from the calculated emissions, and their emissions are separated 

from the totals presented below. Table 5.8-1 in Procedures shows that 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 reported 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 information 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 emissions 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 

Calculation 

Appendix B - Page Number:

267
70 

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)

59444 x 0.385845 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 Refinishing 

Appendix B - Page Number:

268
71 

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 majority 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 evaporation of organic solvents during and shortly 

after the application of the marking paint. All traffic paint emissions are included in the area 

source inventory. 

VOC 

MDE staff were not able to utilize 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 Administration (SHA) keeps data on gallons of traffic 

marking paint used by district and not by individual county. For emissions from SHA line 

painting, each county’s proportion of the total district’s lane miles was multiplied by total 

gallons painted in a district to get an estimated amount of gallons used for each county. In 

a few counties, SHA does all the line painting. Also, data was collected from the 

Maryland Aviation Addministration (MAA) and the Mass Transit Addministation (MTA). 

MDE was able to gather information on gallons 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 collect 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-borne) paints for traffic marking, and those 

areas already using latex paints have switched to using a latex 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 Sources 

Appendix B - Page Number:

269
72 

The following information was collected from all public agencies using traffic marking 

paint in Maryland: 

Gallons of yellow traffic paint and solvent used in 2002. 

Gallons of white traffic paint 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 apply coatings to road surfaces and transportation 

projects. MDE collected data on the gallons of paint applied and the VOC content of the paint. 

MDE made emission estimates based on this data and 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 

Calculation 

Appendix B - Page Number:

270
73 

(1) Calculate VOC emissions from yellow and white traffic paints for ozone season 

a. State Highway Administration (SHA) Traffic Paint Use

Total yellow gallons used April - October46 = 4,671 gallons 

Total VOC per gallon of yellow paint used47 = 0.78 lbs. VOC /gallon 

Total white gallons used April – October48 = 6,481 gallons 

Total VOC per gallon of white paint used49 = 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 paint in Caroline County. 

c. Maryland Transportation Administration (MTA) Traffic Paint Use

The MTA did not apply any paint in Caroline County. 

d. Local Jurisdiction Traffic Paint Use 

The Local Jurisdictions did not apply 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 Highways 

Appendix B - Page Number:

271
74 

(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 Administration (MTA) Solvent Use - None 

The MTA did not use any paint cleaning solvents in Caroline County. 

(3) Total VOC emissions from traffic paint use 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 = 0.0202 

Appendix B - Page Number:

272
75 

4.1.2.6 Industrial Surface Coating 

Industrial surface coatings are applied during the manufacture of a wide variety of products, 

including furniture, cans, automobiles, other transportation equipment, machinery, appliances, 

metal coil, flat wood, wire and other miscellaneous 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 EIIP50, Chapter 8, Industrial Surface 

Coatings, dated September 1997. Applicable point source emissions (those within the same 

NAICS) taken from the MDE/ARMA registration files 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 and per employee factors in categories where a 

choice of factors was offered was made based 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. However, some county NAICS list a range for the 

number of employees through a letter code. In this case the arithmetic average number of 

employees per letter code per county 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 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). 

Because the emission factors were developed based on NAICS employment data and 2001 

was the last year employment data was available per NAICS, MDE used the 2001 County 

Business Patterns as the source 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 Sources 

Appendix B - Page Number:

273
76 

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 EIIP SIC data could be used. EPA provided 

the correlation between NAICS and SIC. Emission 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 equation 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 County Business Patterns 2001- Maryland, MDE assumed no 

emissions were generated because these processes 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 794 

Appendix B - Page Number:

274
77 

Applicable point source emissions (those within the same SIC or NAICS) taken from the 

MDE/ARMA registration files have been subtracted from the calculated emissions, and their 

emissions are separated from the totals presented below. 

MDE surveyed the various state agenicies that apply coatings to road surfaces and transportation 

projects. MDE collected data on the gallons of paint applied and the VOC content of the paint. 

MDE made emission estimates based on this data and 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:

EMPi x EF FW E FW = 2000 x 260

Where: 

E FW = VOC emissions in tons per day from finished wood 

EMPi = 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 

Calculation 

Appendix B - Page Number:

275
78 

E FWR = emissions from factory finished wood sources in ARMA registration files that 

 emit more than 10 tons per year VOC 

CE = Control Efficiency 

RE = Rule Effectiveness 

RP = Rule Penetration

2002 Example Calculation Industrial Surface Coating – Machinery Coating (Baltimore County)

Number of employees in NAICS 33272 in Baltimore County 

(2001 County Business Patterns): 4543 

Emission factor for other transportation equipment (lbs. VOC/employee/year): 7751

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) 

Appendix B - Page Number:

276
79 

 Industrial Surface Coating- per Capita Emissions

The following sources had their emissions calculated 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:

POPi 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 

POPi = 2002 population of county i 

EF MFM = VOC emission factor for misc. finished metals (0.5 lbs. VOC per person per year) 

CE = Control Efficiency 

RE = Rule Effectiveness 

RP = Rule Penetration

Appendix B - Page Number:

277
80 

To adjust for Point Sources: 

E MFMA = (E MFM - Emfmar) 

Where: 

E MFMA = adjusted emissions from 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

503,38853 x 0.6 lbs. VOC/capita/year54 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 Coating 

Appendix B - Page Number:

278
81 

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 lacquers 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 Balance” methodology for estimating emissions from 

nonpoint solvents, which uses the total solvent production and sales for a particular source 

category to estimate overall emissions then subtracting out emissions due to point sources, waste 

management, and recycling. 

Activity 

EPA used the Freedonia55 market research report on nonpoint 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 and 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 (NP&CA) “Paints and Coatings ‘2000': Review 

and Forecast” 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

279
82 

4.1.2.8 Graphic Arts 

SCC: 24 25 000 000 

Graphic arts includes operations that are involved 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 EIIP57, 

Chapter 7, Graphic Arts, dated November 1996. The EIIP methodology recommended an 

emission factor of 1.3 lbs. VOC per capita per year emission factor (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 recommended in Table 5.8-1 in Procedures. Any point 

source graphic arts facility (SIC 275) in the ARMA registration 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 the total graphic arts emissions to specific 

printing types. Maryland has different regulations regarding specific types of printing 

operations and thus to calculate controlled emissions 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 Sources 

Appendix B - Page Number:

280
83 

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 regulations for each type of printing process and has 

been developed within technical support documents for the graphic arts printing regulations. 

Rule penetration has been defined as the estimated percentage that each type of printing 

operation. Rule effectiveness has been assigned 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:

POPi 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 

POPi = 2002 population of county i 

EF GA = VOC emission factor for graphic arts (1.3 lbs. VOC per person per year) 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

281
84 

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 registered premise files that emit more than 

 10 tons VOC /year 

Appendix B - Page Number:

282
85 

2002 Example Calculation Graphic Arts (Anne Arundel County)

E GA = 503,38858 x 1.3 lbs. VOC/capita/year59 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 Arts 

Appendix B - Page Number:

283
86 

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 different petroleum distillates. The 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 based on a per capita emission factor of 0.004 

pounds VOC per person per year for emulsified asphalt 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 level 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 evaporate 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 emulsified 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 

Controls 

Appendix B - Page Number:

284
87 

cutback asphalt application were not calculated. Cutback asphalt is made by blending asphalt 

cement with petroleum distillates that evaporate 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 estimate emissions from asphalt paving is: 

POPi x EF EA E EA = 2000 x 260 Where: 

E EA = VOC emissions in tons per day from emulsified asphalt 

POPi = 2002 population of county i 

EF EA = VOC emission factor for emulsified 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 

503,38860 x 0.004 lbs. VOC/capita/year61 = 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 

Calculation 

Appendix B - Page Number:

285
88 

4.1.2.10 Synthetic Organic Chemical Storage Tanks 

This category is fully represented in the point source inventory. 

Appendix B - Page Number:

286
89 

4.1.2.11 Pesticide Application 

SCC: 24 61 800 000 

Pesticides are substances or mixtures used to control plant and animal life for the purposes of: 

agricultural production, public health from pest-borne disease, reducing property damage due to 

pests, and improving the aesthetic quality of outdoor and indoor surroundings. Agriculture, 

homeowners, industry, and government agencies use pesticides. The largest usage of pesticides 

by weight is in agriculture. Agricultural pesticides control weeds, insects, mites, fungi, 

nematodes, and other threats to the yield, 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 formulations. Many pesticide formulations use solvents as carriers 

for more active organic or inorganic ingredients. In pesticide formulations, the organic or 

inorganic solute is the "active ingredient" (AI), while the solvent carrier is the "inert carrier." 

Thus, the terms "active" and "inert" in pesticide formulations refer to toxicological action, and 

are not indicators of photochemical activity. Both the active and inert ingredients in these 

formulations evaporate and contribute 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 ingredient for each Maryland county. Along with the 

pounds of AI applied, the document also listed the form of many pesticides and the formulation 

of some selected pesticides. From this, MDE 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 ingredient and inert carrier of the pesticide. This 

required assumptions and other references to collect the best information 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: 

Appendix B - Page Number:

287
90 

MDE slightly deviated from this method, since information was presented to MDE in pounds of 

active ingredient. With the active 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 Database 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 Pesticide Statistics for 2000. 

Also, the statistics listed some formulations, for example 80% inert, 20% AI. Most of the 

formulations were assumptions based on the information 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 for 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 % Inert 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 Factor

Appendix B - Page Number:

288
91 

where: 

AI = Active Ingredient ( lbs. / yr. ) 

EF AI = Emission Factor ( lbs. VOC / ton AI ) 

% inert = percentage of formulation 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 Pesticide Statistics for 2000 and 

The SCS/ARS/CES Pesticide Properties Database for Environmental Decision-Making: 

Table 3-26 

Allegany County Pesticide Information 

 VOC 

 V. Press Formulation Formula % VOC EF Alleg. Alleg. 

Pesticide mm Hg Application 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 11.429

Appendix B - Page Number:

289
92 

 VOC 

 V. Press Formulation Formula % VOC EF Alleg. Alleg. 

Pesticide mm Hg Application 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 9.450

Appendix B - Page Number:

290
93 

 VOC 

 V. Press Formulation Formula % VOC EF Alleg. Alleg. 

Pesticide mm Hg Application 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 active ingredient per county and then summed. 

Example calculation for the emissions from Pendimethalin 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 county are calculated in a similar manner. 

Results:

Since the EPA has released new guidance on the calculation of agricultural pesticide application, 

the new methodology vastly differs from the method 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 has been debated by different 

groups. General thoughts from scholars and private industry is the old methodology overpredicts 

the volatility of the organics in the pesticide. The new methodology, presented here, requires 

many assumptions and uses data that takes account for the different vapor pressures of individual 

active ingredients. This method, along with some general assumptions, estimated pesticide 

emissions at 8.7 tons per day for the state. The decrease is due to the change in method, along 

with a decline in pounds of pesticides applied in the state. 

Appendix B - Page Number:

291
94 

4.1.2.12 Commercial/Consumer Solvent Use 

SCC: 24 65 000 000 

Certain commercial/consumer uses of products containing volatile organics cannot easily be 

identified by questionnaires, surveys or other inventory procedures yielding locale-specific 

emission estimates. This category includes the 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, Preferred 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 

Allocations 

Appendix B - Page Number:

292
95 

Temporal 

Data for temporal allocation is not available for this source. 

The per capita equation used to estimate emissions from commercial and consumer solvents is: 

[ POPi x EF CC ] - [ (POPi 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 

POPi = 2002 population of county i 

EF CC = VOC emission factor for commercial 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/Consumer Solvent Use (Anne Arundel County)

[ (503,38862) x (7.84 63) ] - [ (503,388 x 3.964 ) 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 

Calculation 

Appendix B - Page Number:

293
96 

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 treatment 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 point 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 calculated on a per employee basis that are presented 

below. 

Activity 

Employee numbers were taken from County Business Patterns 2001 - Maryland, NAICS 

311812, Bakery Products and 311811, Retail Bakeries. Some county employment data is 

represented by a letter code indicating 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 Sources 

Appendix B - Page Number:

294
97 

Emission Factor 

An emission factor of 0.11 tons VOC per employee cited in an April 24, 1992 Technical 

Memorandum prepared by Radian Corporation for EPA was utilized. 

Bakery emissions from facilities identified as point sources (NAICS 311812 and 311811) were 

subtracted from the area source inventory 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 (less than 20 employees), bakeries in county j 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

295
98 

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 

E 0.11 x 256 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 files 

Appendix B - Page Number:

296
 99

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 VOCs 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 asked the brewing facilities to provide MDE/ARMA with the 

amount of barrels brewed per month for the calendar 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 calculated using an emission 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. One 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 

Allocations 

Appendix B - Page Number:

297
 100

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 Brewery VOC Emissions (Anne Arundel County): 

Number barrels produced by microbreweries 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 

Calculation 

Appendix B - Page Number:

298
 101

4.1.3.3 Wineries 

Ethanol emissions from wineries occur during the fermentation process. 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-4267, 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 area suggests that 64,233 

gallons of white and 57,303 gallons of red wine 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 

Allocations 

Appendix B - Page Number:

299
 102

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 decided 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 the VOCs emitted from distilleries. Distilleries 

produce both grain alcohol for industrial and fuel purposes, and distilled spirits such as whiskey 

and brandy for consumption purposes. The emissions points in the distilled spirits 

manufacturing process are likely to be the same as in breweries and wineries, with the aging 

process as an additional source of emissions. During 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 the 10 ton per year point source cutoff operated in 

the inventory area during 2002. Fugitive VOC emissions from the aging process at large 

distillery operations can be substantial and will be included in the point source inventory. 

Emissions 

Calculation 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

300
 103

4.1.4 CATASTROPHIC/ACCIDENTAL RELEASES 

4.1.4.1 Oil Spills 

SCC: 28 30 000 000 

Oil spills involve oil tanker accidents, 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 obtained from MDE's Hazardous Waste Emergency 

Response Department. They provided MDE/ARMA staff a monthly list of all oil spills that 

occurred in Maryland during 1999, by county. Gallons 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 recommended to the Metropolitan Washington Council 

of Governments by E.H. Pechan and Associates, 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 emissions 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 gallon of oil spilled. below. 

No point source adjustments were made. 

Description 

Pollutants 

Method and 

Data Sources 

Point Source 

Adjustments 

Appendix B - Page Number:

301
 104

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 Baltimore 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 

Calculation 

Appendix B - Page Number:

302
 105

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 piping 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 soils, 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 files, 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 category. 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 

Controls 

Appendix B - Page Number:

303
 106

Spatial 

Data for spatial allocation is not available for this source. 

Temporal 

Data for temporal allocation is not available for this source. 

RS1j + RS2j + RS3j .... E UST = 2000 

where: 

E UST = VOC emissions in tons per day from leaking underground storage tanks 

RS1j, RS2j = pounds VOC per day allowed from remediation site(s) in county j 

2002 Sample Calculation for Leaking Underground Storage Tanks (Anne Arundel County)

No seasonal variation assumed 

Annual VOC emissions in pounds per day: (from 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 underground storage tanks in Anne 

Arundel County 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

304
 107

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 confined 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 PM10

In Maryland incinerators 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 incinerators 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 all incinerators to obtain a permit to operate and any person 

who owns or operates an incinerator must obtain certification from MDE and renew the 

certification annually. 

MDE/ARMA maintains a registry of all incinerators within the State. Because of the 

requirements prohibiting single chamber incinerators, the requirement for a permit to operate, 

and the operator certification requirements, 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 NOx. Incinerators from the registry with 

emissions above these thresholds are included 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 Sources 

Appendix B - Page Number:

305
 108

4.1.5.2 Publicly Owned Treatment Works (POTWs) 

SCC: 26 30 020 000 

EPA Procedures mentions that research into VOC emissions from POTWs has found that in the 

event of "heavy chemical loading", 85% of volatile 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 contribution to POTWs as stated in Procedures, Page 3-14. 

VOC, NH3 

The emissions from these facilities were calculated 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 staff 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 discharged 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 discharged to a POTW. 

VOC stack emissions in the Air Management registration 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 

Controls 

Appendix B - Page Number:

306
 109

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 flow from POTW i in county j 

EF POTW = VOC emission factor68 for POTWs 

SAF POTW = Seasonal adjustment factor69 for peak ozone season which is 1.4 

2002 Sample Calculation for POTW VOC Emissions (Anne Arundel County): 

Back River Sewage Treatment Plant statistics70: 

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 

Calculation 

Appendix B - Page Number:

307
 110

4.1.5.3 Open Burning – Land Clearing Debris 

SCC: 26 10 000 500 

Open burning of land clearing debris 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 results 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 practiced by private individuals, corporations, and 

government agencies (e.g., highway construction department). There are no federal laws 

restricting the open burning of land clearing wastes, although state or local laws may exist.

Residential open burning without a permit is prohibited 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 lines, etc. In the more rural counties, areas 

with no available trash collection are more prevalent. MDE adopted a regulation that prohibits 

open burning during the peak ozone period (June to August). The seasonal prohibition only 

affects those counties that lie within serious and severe ozone nonattainment areas. Certain 

exemptions must be in place however so as not to adversely affect agriculture or restrict fire 

training and recreational activities. Commercial open burning without a permit is prohibited in 

Maryland. 

VOC, NOx, SOx, CO, PM10 and PM2.5

The method used to calculate emissions, is presented in EIIP72, Chapter 16, Open Burning 

(Revised Final 2001). 

Activity 

The number of acres disturbed by residential, non-residential and roadway construction are 

estimated and then these values are added together 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 Sources 

Appendix B - Page Number:

308
 111

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 type of vegetation class to the total land area for each county. 

The loading factors for slash hardwood and slash 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 LFAdj-HW) +(Acres SW-COi x LFAdj-SW) +(Acres GR-COi x LFAdj-GR) LF OB –LCD – COi Acres TOT-COi

LFOB –LCD – COi = Average Load Factor in County i 

Acres HW-COi = Acres of hardwood in County i from BELD database 

LFAdj-HW = Adjusted Load Factor for Hardwood 

Acres SW-COi = Acres of softwood in County i from BELD database 

LFAdj-SW = Adjusted Load Factor for Softwood 

Acres GR-COi = Acres of grasses in County i from BELD database 

LFAdj-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 

PM10 16 Lbs. PM10/ ton 

PM2.5 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, SO2, PM10 and PM2.5 were obtained from AP-42 Table 2.5-1. 

Appendix B - Page Number:

309
 112

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. 

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 Residential, 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 

Calculation 

Appendix B - Page Number:

310
 113

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 clearing debris, household waste, 

and agricultural crop waste. Household waste, often 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, leather, 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 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 lines, etc. In the more rural counties, areas 

with no available trash collection are more prevalent. MDE adopted a regulation that prohibits 

open burning during the peak ozone period (June to August). The seasonal prohibition only 

affects those counties that lie within serious and severe ozone nonattainment 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, PM10, PM2.5, and Toxics 

The method used to calculate emissions is presented 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 would form the basis of an improved open burning 

emission inventory for Mid-Atlantic/Northeast Visibility Union (MANE-VU) states and 

tribes for the year 2002. 

A rule effectiveness (RE) survey was also performed to estimate controlled emissions for 

areas that prohibit open burning. Household waste burning surveys were completed for 72 

respondents or jurisdictions, while yard waste surveys were conducted for 181 espondents. 

The respondents for this survey were typically 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 Sources 

Appendix B - Page Number:

311
 114

effectiveness surveys related to residential 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, suburban, 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 category 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 jurisdictions. For the non-surveyed areas, including tribal lands, 

the default activity data derived from all survey responses were applied. Households are 

defined as detached single-family unit dwellings 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 Refuse and from a 1997 EPA research paper on 

open burning75 are listed below: 

Pollutant Emission Factor 

Lb/ton total mass burned 

VOC 8.556 

NOx 6 

CO 85 

PM10 38 

PM2.5 34.8 

SO2 1.0 

No subtration of emissions from point sources is necessary. 

If an area has controls or prohibitions on residential burning, controlled emissions were 

calculated from uncontrolled emissions using the following equation: 

Ec = Euc * [(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 Controls 

Appendix B - Page Number:

312
 115

where: 

Ec = Controlled area source emissions 

Euc = 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 burning. Although one may expect that RE would be 

higher for urban than for suburban or rural areas, 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 distinct populations. Therefore, the final 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 perform open burning for areas in the region where 

there is no rule (i.e., # households x fraction of open burning households 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 those areas. Pechan did not develop statespecific 

RE values since we had no reason to believe that local jurisdictions in individual states 

implemented their rules differently than local jurisdictions 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 data 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 MSW and yard waste burning (Pechan, 2002b).

Control Efficiency and Rule Penetration 

For those areas identified to have a control, CE is assumed to be 100 percent (since the 

control is typically a ban on burning activity). For MSW burning, 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 state did not have a statewide ban on burning). In 

Pennsylvania, unless a jurisdiction 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 be 

Appendix B - Page Number:

313
 116

uncontrolled, unless the survey data or other statewide or local control information indicated 

otherwise. For municipal yard waste burning, areas were assumed to either perform this activity 

and have associated emissions, or did not conduct burns and therefore were assigned zero 

emissions. 

In determining annual emissions for those areas with 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 activity 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%; and Fall–28%. So, for an area that has a 

brush burning ban in the summer, although some percentage of burning is likely to be prevented 

during this season, we assume that 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 mentioned in the discussion of temporal allocation 

profiles, this also has an affect on the monthly activity profile. A summer RP value of 4 percent 

would result in a revised temporal allocation profile to be: Winter–20%; Spring–46%; Summer– 

4%; and Fall–30%. 

Spatial 

Pechan collected activity data and control information for areas classified as urban, 

suburban, and rural, or a combination of these 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 profiles to represent monthly, weekly, and daily 

activity profiles by SCC (see Tables II-2 through 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 

Allocations 

Appendix B - Page Number:

314
 117

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 calculation will not be presented here, however the 

equations for a particular census tract are presented 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 

Calculation 

Appendix B - Page Number:

315
 118

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 time period (Question 3, Part 2) 

M = Mass of waste per burn (Question 5, Part 3) 

Uncontrolled emissions were then calculated using the following equation: 

EUNC = Wt MSW * EF 

where: 

EUNC = Uncontrolled area source emissions 

Wt MSW = Mass of waste burned per time period 

EF = Emission factor per pollutant 

Controlled emissions were then calculated using the following equation: 

EC = EUNC * [(1-(CE)(RP)(RE)] 

where: 

EC = Controlled area source emissions 

EUNC = Uncontrolled area source emissions 

CE = % Control efficiency/100 

RP = % Rule penetration/100 

RE = % Rule effectiveness/100 

Appendix B - Page Number:

316
 119

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 clearing debris, household waste, 

and agricultural crop waste. Household waste, often 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, leather, 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 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 lines, etc. In the more rural counties, areas 

with no available trash collection are more prevalent. MDE adopted a regulation that prohibits 

open burning during the peak ozone period (June to August). The seasonal prohibition only 

affects those counties that lie within serious and severe ozone nonattainment 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, PM10, PM2.5, and Toxics 

The method used to calculate emissions is presented 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 would form the basis of an improved open burning 

emission inventory for Mid-Atlantic/Northeast Visibility Union (MANE-VU) states and 

tribes for the year 2002. 

A rule effectiveness (RE) survey was also performed to estimate controlled emissions for 

areas that prohibit open burning. Household 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 Sources 

Appendix B - Page Number:

317
 120

respondents or jurisdictions, while yard waste surveys were conducted for 181 

respondents. The respondents for this survey were typically local fire wardens or chiefs. 

Rule effectiveness surveys related to residential 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, suburban, 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 category 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 jurisdictions. For the non-surveyed areas, including tribal lands, 

the default activity data derived from all survey responses were applied. Households are 

defined as detached single-family unit dwellings 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 Refuse and from a 1997 EPA research paper on 

open burning77 are listed below: 

Pollutant Emission Factor 

Lb/ton total mass burned 

VOC 8.556 

NOx 6 

CO 85 

PM10 38 

PM2.5 34.8 

SO2 1.0 

No subtration of emissions from 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 Controls 

Appendix B - Page Number:

318
 121

If an area has controls or prohibitions on residential burning, controlled emissions were 

calculated from uncontrolled emissions using the following equation: 

Ec = Euc * [(1-(CE)(RP)(RE)] 

where: 

Ec = Controlled area source emissions 

Euc = 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 burning. Although one may expect that RE would be 

higher for urban than for suburban or rural areas, 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 distinct populations. Therefore, the final 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 perform open burning for areas in the region where 

there is no rule (i.e., # households x fraction of open burning households 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 those areas. Pechan did not develop statespecific 

RE values since we had no reason to believe that local jurisdictions in individual states 

implemented their rules differently than local jurisdictions 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 data 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 MSW and yard waste burning (Pechan, 2002b). 

Control Efficiency and Rule Penetration 

For those areas identified to have a control, CE is assumed to be 100 percent (since the 

control is typically a ban on burning activity). For MSW burning, 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 state did not have a statewide ban on burning). In 

Pennsylvania, unless a jurisdiction 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 

Appendix B - Page Number:

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 122

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 statewide or local control information indicated 

otherwise. For municipal yard waste burning, areas were assumed to either perform this activity 

and have associated emissions, or did not conduct burns and therefore were assigned zero 

emissions. 

In determining annual emissions for those areas with 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 activity 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%; and Fall–28%. So, for an area that has a 

brush burning ban in the summer, although some percentage of burning is likely to be prevented 

during this season, we assume that 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 mentioned in the discussion of temporal allocation 

profiles, this also has an affect on the monthly activity profile. A summer RP value of 4 percent 

would result in a revised temporal allocation profile to be: Winter–20%; Spring–46%; Summer– 

4%; and Fall–30%. 

Spatial 

Pechan collected activity data and control information for areas classified as urban, 

suburban, and rural, or a combination of these 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 profiles to represent monthly, weekly, and daily 

activity profiles by SCC (see Tables II-2 through 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 

Allocations 

Appendix B - Page Number:

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 123

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 calculation will not be presented here, however the 

equations for a particular census tract are presented 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 

Calculation 

Appendix B - Page Number:

321
 124

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 time period (Question 3, Part 2) 

M = Mass of waste per burn (Question 5, Part 3) 

Uncontrolled emissions were then calculated using the following equation: 

EUNC = Wt MSW * EF 

where: 

EUNC = Uncontrolled area source emissions 

Wt MSW = Mass of waste burned per time period 

EF = Emission factor per pollutant 

Controlled emissions were then calculated using the following equation: 

EC = EUNC * [(1-(CE)(RP)(RE)] 

where: 

EC = Controlled area source emissions 

EUNC = Uncontrolled area source emissions 

CE = % Control efficiency/100 

RP = % Rule penetration/100 

RE = % Rule effectiveness/100 

Appendix B - Page Number:

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 125

4.1.5.6 Cremation – Animal and Human 

 SCC: 31 502 102 

Propane-fired burners (afterburner and ignition) are typically used at cemeteries for human body 

and animal cremation. Burners are usually rated 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 ignition burner modulates to a low-fire mode that 

will reduce the Btu per hour usage. 

When the crematory reaches an operating temperature of 1,250 F (680 C) the body container is 

placed on the combustion chamber grate and the ignition burner is fired to attain a target 

combustion temperature sufficient for the proper 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 container is introduced into the combustion 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 Pollutants were not calculated) 

The method used to calculate emissions, is presented in “Documentation for the 1996 Base Year 

National Toxics Inventory for Area Sources” prepared 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 certification annually. 

MDE/ARMA maintains a registry of all crematories within the State. Because of the 

requirement for a permit to operate, and the operator 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 than 10 tons/VOC, 100 tons/yr CO and 50 tons 

per year NOx. 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

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 126

Emission Factors 

Emission factors these hazardous air pollutants, except formaldehyde, were taken from the 

State of California Air Resources Board Test Report No. C-90-00478. The emission factor 

used for formaldehyde was reported in the USEPA FIRE79 system database. 

Emission factors were converted to a pound per ton basis using the procedure provided by 

the Emission Standards Division80. 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 America81 that 21.13 percent of bodies 

were cremated and that there were 2,322,265 deaths in the United States in 199682. 

Animal and Human Cremation 

Pollutant Emission Factor 

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 from 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 Camellia 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 Animal 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 America. 1996 Statistics as found on the Internet Cremation Society, Cremation 

Stats Nationwide webpage: www.cremation.org/stats.htm 82 Ventura, S. et al. “Births and Deaths: United States, 1996.” 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 Controls 

Appendix B - Page Number:

324
 127

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 

Calculation 

Appendix B - Page Number:

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 128

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 and 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 hazardous air pollutants and reactive VOCs. 

VOC 

The method used to calculate emissions, is presented in AP-42, Chapter 2.4, Municipal Solid 

Waste Landfills and EIIP83, Volume III, Chapter 15, Landfills, dated September 1997. 

Emission estimation assumptions were also made using supporting documents Standards of 

Performance for New Stationary Sources (NARA, 1991a) and Emission Guidelines for Control 

of Existing Sources (NARA, 1997b). 

To estimate uncontrolled emissions of the various 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 conditions of the landfill; and (2) the 

characteristics of the refuse such as moisture content, age, and composition. Uncontrolled CH4

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 (LandGEM). The model equation is as follows:

QCH4 = LO R (e-kc - e-kt) (1) 

 

Where: 

QCH4= Methane generation rate at time t, m3/yr; 

 

83 Emission Inventory Improvement Program 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

326
 129

Lo = Methane generation potential, m3 CH4 / 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 landfill. Also, nondegradable refuse should be subtracted from the refuse 

in place to prevent over estimation of CH4 generation. The average annual acceptance rate 

should only be estimated by this method when there 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 methane and carbon dioxide in the gas (the default 

value is a 50/50 split), 

 The concentration of nonmethane organic compounds (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 operation (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 information is not known. The AP-42 default value for 

k (0.04/yr) was used for Maryland since it has normal or above normal precipitation, rather than 

the default value. This recommendation is based 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 values from landfills. The proposed regulatory 

default value for VOC concentration was developed for regulatory compliance purposes and to 

provide the most cost-effective default values on a national basis for 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 value of all VOC concentrations, 595 ppmv as 

hexane should be used. This was done for Maryland. The AP-42 default values used in the 

LandGEM to develop Maryland’s landfill inventory are shown in the table below: 

Appendix B - Page Number:

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 130

Landgem Model Parameters AP-42 Default Values 

Lo : 100.00 m3

 / 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 Landfill, Montgomery County RRF, and Newland 

Park Landfill are considered Point Sources. LandGEM model runs for these landfills are not 

included in the area source emission estimates for landfills. 

Emission reductions were calculated for landfills 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 – CEFF)} + {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 landfills (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 

Controls 

Appendix B - Page Number:

328
 131

Data for spatial and temporal allocation is not available for this source. 

Spatial and 

Temporal 

Allocations 

Appendix B - Page Number:

329
 132

4.1.6 SMALL STATIONARY SOURCE FOSSIL FUEL USE 

4.1.6.1 Small Electric Utility Boilers 

All small electric utility boilers are inventoried in the point source category. The list of small 

boilers from Inventory of Power Plants in the United States, DOE/EIA-0095(88) was obtained 

and indicated that all small electric boilers were included in the point source inventory. 

4.1.6.2 Other Fuel Consumption 

Coke and process gas emissions will be inventoried as point sources. 

Appendix B - Page Number:

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 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 (residential 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 distillate 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/institutional 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 industrial and commercial/institutional users may consume 

significant amounts. 

PM10, PM2.5, SOx, NOx, CO, VOC 

Activity 

Total sales statistics of kerosene, distillate oil, and residual oil in the State of Maryland 

were obtained from the Annual Report on Sales of Fuel Oil and Kerosene, 2002, published 

by Energy Information Administration, U.S. Department of Energy84. 

Emission Factors 

Emission factors were obtained from AP-4285, 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 Industrial 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 Sources 

Appendix B - Page Number:

331
 134

 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 from point sources is necessary. 

No controls are available for this source category. 

Spatial 

This information on total sales of kerosene, distillate oil and residual oil was broken down 

to the county level using a spatial allocation factor documented and recommended by 

EIIP86 in an Area Source Method Abstract for Residential and Commercial/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 used to indicate how cold it has been over a 

24-hour period. Daily heating-degree days are calculated as the difference 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/climateproducts.html#PUBS (for a list 

of available data) 

Point Source 

Adjustments 

Adjustments 

for Controls 

Spatial and 

Temporal 

Allocations 

Appendix B - Page Number:

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 135

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, represents the bulk of the coal used residentially for 

space heating in the State. Although mined nearby in Pennsylvania, readily available, and 

cleaner burning, anthracite coal is not used much in Maryland because of its expense. 

PM10, PM2.5, SOx, NOx, CO, VOC 

Activity 

The following assumptions were made in the computation of emissions from coal 

combustion from the residential sources. 

(i) Number of Dwelling Units using Coal 

The number of dwelling units using coal 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 authorized for construction between 1990 and 2002 was 

obtained from the Maryland Office of Planning – 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 fuel-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, Consumption 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 hand-fired residential coal sources in the State 

of Maryland. 

Description 

Residential 

Coal 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

333
 136

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 from 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 EIIP89 in an Area Source Method Abstract for 

natural gas and LPG combustion. Because the emission factor was specifically adjusted to 

reflect seasonal emissions through heating degree days, no further seasonal adjustment 

factor is necessary. 

A “heating-degree day” is a unit of measure used to indicate how cold it has been over a 

24-hour period. Daily heating-degree days are calculated as the difference 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).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/climateproducts.html#PUBS (for a list 

of available data) 

Point Source 

Adjustments 

Adjustments 

for Controls 

Spatial and 

Temporal 

Allocations 

Appendix B - Page Number:

334
 137

 ∑ =

AllCountiesInState

County County

InventoryCounty InventoryCounty

InventoryCounty

HDD CHU

HDD CHU 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 consumed in the inventory county 

Coal TOTAL STATE = Total Coal fuel consumed in the inventory county 

Temporal 

MDE assumed that all residential coal combustion is used for space heating purposes. The 

total coal consumed in the county can be allocated by month 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 days 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

E COAL = HDD Co Annual

 Ozone DAYS

Emissions 

Calculation 

Appendix B - Page Number:

335
 138

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 days in county for ozone season 

HDD Co Annual = Number of heating degree days in county in the calendar year 2002 

Ozone DAYS = Number of days in the ozone season: 214 Residential; 168 Commercial 

Residential Coal Combustion Sample Calculation (Allegany County) (tons / ozone season day)

Total Residential Coal Consumption – State of Maryland 8,360 tons 

To calculate spatial apportioning 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 = 0.045531 

Appendix B - Page Number:

336
 139

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 ) 

E (2000 x 214) COAL = 

(10.0 x 79.48804 ) E COAL = (2000 x 214) 

E COAL = 0.0019 tons VOC / Ozone season day 

Appendix B - Page Number:

337
 140

 

Commercial and Institutional sources of coal combustion above the point source threshold are 

included in the point source portion of the inventory. The following table lists area source 

emissions from commercial and institutional sources smaller than the threshold values. 

The following assumptions were made in the computation 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 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 authorized for construction between 1990 and 2002 was 

obtained from the Maryland Office of Planning – 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 fuel-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 Sources 

Appendix B - Page Number:

338
 141

No subtration of emissions from 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 

Calculation 

Appendix B - Page Number:

339
 142

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 heating units that are not inventoried as point 

sources. Residential and commercial sectors comprise housing units; wholesale and retail 

businesses; health institutions; social and educational 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 cooking and hot water heating. 

PM10, PM2.5, SOx, NOx, CO, VOC 

The following assumptions were made in the computation of the emissions from natural gas 

combustion. 

Activity 

(i) Number of Dwelling Units using Natural Gas 

The number of dwelling units using natural 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 authorized for construction between 1990 and 

2002 was obtained from the Maryland Office of Planning – New Residential Units 

Authorized for Construction by Building Permits (http://www.op.state.md.us). The total 

number of additional housing units constructed in the county was apportioned to type of 

home heating fuel by the same ratio as the 1990 Census figures. 

(ii) Residential and Commercial/Institutional Natural Gas Consumption Data 

Total residential and commercial/institutional natural 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 Energy Services (Maryland 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

340
 143

Division), Chesapeake Utilities Corporation, Columbia Gas of Maryland, Easton Utility 

Commission, and Elkton Gas Company. The companies provided natural gas sales 

statistics for the year 2002 in therms or cubic feet for all counties in their service area for 

the residential, commercial, and industrial categories. 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 commercial 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./106

 scf) 

CO 

(lbs./106 scf) 

VOC 

(lbs./106 scf) 

PM 10 

(lbs./106 scf) 

PM 2.5 

(lbs./106 scf) 

SOx 

(lbs./106 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 from point sources is necessary. 

No controls are available for this source category. 

Spatial 

The natural gas survey of suppliers provided 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 consumption 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 

Allocations 

Appendix B - Page Number:

341
 144

Temporal 

In addition to space heating, natural gas is often used for cooking and water heating. For 

ozone and other seasonal inventories, consumption 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 natural gas usage from cooking and water heating, 

MDE used data from the State Energy Data Report, Consumption Estimates, Energy 

Information Administration, Office of Energy Markets and End Use, U.S. Department of 

Energy. Specifically data was collected from Table 15 – Natural Gas Deliveries to 

Residential Customers, by State, 1998-2002. The residential deliveries for the month with 

the lowest deliveries can be assumed to be only for cooking and water heating. The 

percentage of residential natural gas consumption for cooking and water heating may then 

be calculated: 

Annual Non-Space 12 * Lowest Monthly Fuel Use 

Heating Percent = Annual Fuel Use * 100 

Annual Non-Space 12 * 1635 

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: 

Annual Non-Space 12 * Lowest Monthly Fuel Use 

Heating Percent = Annual Fuel Use * 100 

Annual Non-Space 12 * 2440 

Heating Percent = 65323 * 100 

Annual Non-Space 

Heating Percent = 44.823 % 

This percentage may be applied to the inventory area’s total residential and/or 

commercial/institutional natural gas consumption 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 heating, can be allocated by month or period 

using proportions of annual and monthly or period heating degree days. 

HDD MONTH Space Heat Fuel MONTH = Space Heat Fuel ANNUAL x HDD ANNUAL

Where: 

Appendix B - Page Number:

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 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 – Residential Ozone Season Daily Emissions

Equation:

Days

iNatGas HotWaterAp Jp

CoAnnual

iNatGas SpaceHeat J CoOzSeason

NatGas

Ozone

EF NG

HDD

EF NG HDD

E

⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡

=

− − − −

2000

*

*

2000

*( )

E NatGas = Ozone Season Daily emissions from natural gas combustion 

EF NatGas-i = Emission factor for natural 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 days in county in the calendar year 2002 

NG Hot water/App - J = Natural gas consumed for during 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 City92 14,483 M ft3

Percent natural gas used for cooking & appliances in the State of Maryland93

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 

Calculation 

Appendix B - Page Number:

343
 146

 Residential NG Hot water/App - J = 3,532.130 M ft3

 

Natural gas used for space heating in Baltimore County 

 Residential NG Space Heat - J = 14,483 – 3,532.130 M ft3

 Residential NG Space Heat - J = 10,951 M ft3

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 ft3

Natural gas used for hot water and appliances 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 ft3

Equation:

VOC Ozone Season Day Emission Calculation 

(EF NG i x NG Space Heat - J ) + (EF NG i x N Hot water/App - J ) 

E (2000 x 214) 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. 

 

Appendix B - Page Number:

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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 small boilers, furnaces, heaters and other heating 

units that are not inventoried as point sources. Residential and commercial sectors comprise 

housing units; wholesale and retail businesses; health institutions; social and educational 

institutions; and Federal, state and local government institutions (e.g., military installations, 

prisons, office buildings). 

PM10, PM2.5, SOx, NOx, CO, VOC 

 

The following assumptions were made in the computation of the emissions from liquified 

petroleum gas (LPG) combustion. 

Activity 

1. Number of Dwelling Units using LPG 

The number of dwelling units using LPG 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 authorized for construction between 1990 and 

2002 was obtained from the Maryland Office of Planning – New Residential Units 

Authorized for Construction by Building Permits (http://www.op.state.md.us). The total 

number of additional housing units constructed 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 consumption 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 Sources 

Appendix B - Page Number:

345
 148

Emission Factors 

Emission factors for combustion of LPG in commercial boilers are presented in Table 1.5-

1 of Section 1.5 of AP-42 (EPA, 1998a). The LPG emission factor 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 using the AP-42 emission factor and multiplied by 

the sulfur content of the 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 from 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 gas to spatially allocated liquid propane gas 

consumption. The method is documented and recommended by EIIP94 in an Area Source 

Method Abstract for natural gas and LPG combustion. 

A “heating degree day” is a unit of measure used to indicate how cold it has been over a 24-

hour period. Daily heating degree days are calculated as the difference between the base 

value of 65°F and the mean temperature for the 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 

Allocations 

Appendix B - Page Number:

346
 149

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).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 days 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 fuel 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, consumption 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 usage from cooking and water heating, MDE used data 

from the State Energy Data Report, Consumption Estimates, Energy Information 

Administration, Office of Energy Markets and End 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. Households 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 consumption 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/climateproducts.html#PUBS (for a list 

of available data) 

Appendix B - Page Number:

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 150

Also, 2002 residential LPG usage was estimated 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. 

Percent of LPG used for amount of LPG used for hot water and appliances 

cooking & appliances = total amount of LPG consumed 

(100 + 43) = 572 

 = 0.25 

Therefore 25 percent of the annual LPG consumed is used for non-space heating and an 

individual county’s residential LPG consumption 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 water and appliances in county j 

This percentage may be applied to the inventory area’s total residential liquid propane gas 

consumption to calculate the cooking and water heating portion of usage. This portion can be 

subtracted from the annual total, and the remaining consumption, which is being used for space 

heating, can be allocated by month 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 days for inventory month 

 HDD ANNUAL = Heating degree days for inventory year 

Emission Calculation

Ozone Season Daily Emissions 

Equation:

Emissions 

Calculation 

Appendix B - Page Number:

348
 151

(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 days 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 season 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 = 3,198.3 

Appendix B - Page Number:

349
 152

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 ) 

E (2000 x 214) LPG = 

(0.5 x 0.00 ) + (0.5 x 621.89) E LPG = (2000 x 214) 

E LPG = 0.00073 tons VOC / Ozone season day 

Appendix B - Page Number:

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 153

4.1.6.7 Wood Combustion 

 SCC: 21 04 008 000 (Residential Wood Combustion) 

This source category covers air emissions from wood combustion in the residential sectors 

primarily for space heating and aesthetics. This MANE-VU RWC inventory 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).

PM10, SOx, NOx, CO, VOC, and Toxics 

The method used to calculate emissions is presented in a study/survey conducted by the MidAtlantic Regional Air Management Association (MARAMA), titled “Residential Wood 

Combustion Emission Inventory.”96

Activity 

In order to improve the RWC inventory for 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 units, including 

mobile homes). In previous technical memoranda, 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 further 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 category. For indoor wood burning equipment, 

the survey was designed to obtain information on equipment type. Indoor equipment 

includes fireplaces, woodstoves (both conventional and certified), furnace/boilers and 

pellet stoves. However, due to concerns regarding 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 Sources 

Appendix B - Page Number:

351
 154

Emissions were estimated at a more general level: outdoor and indoor equipment. Outdoor 

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

During this project, Pechan prepared six technical 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 Combustion EI Project: Sample Frame 

Development – this TM described the development of the sample frame to be used 

during the project. Note that the sample frame 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 methods were not used since 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 Residential Wood Combustion Activity Survey – This 

TM provided statistical summaries of the survey results; 

• TM#5 - MANE-VU Residential Wood Combustion 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 variables to estimate emissions from indoor 

and outdoor equipment, and the emission factors to be applied. It was during the 

review of this TM that a different method was developed to estimate emissions for 

indoor equipment based on emission estimates constructed from each survey response 

(instead of estimating equipment level activity, which was originally envisioned for 

this project). This new method avoided the lowering of statistical precision (error) in 

the extrapolation of survey data, since individual responses were not divided into 

multiple equipment types. A description of the development of the general linear model 

for estimating emissions from indoor equipment 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 inventory constructed from the number of 

households in the 2000 Census (no adjustments to reflect 2002 housing changes were 

made) and the activity variables and emission factors documented in TM#5. During a 

Appendix B - Page Number:

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 155

review of the draft TM#6, reviewers questioned 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). Pechan reviewed the primary types of wood 

reported by the survey respondents. Oak/hickory 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 residential 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 factors were located for the combustion of 

wood for commercial consumption, emission factors for residential fireplaces were used to 

estimate commercial emissions. 

Residential Wood Combustion 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 from 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 profiles was used to go from group profiles to county profiles. 

Activity or emissions for each census tract were 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 give activity fractions. 

Point Source 

Adjustments 

Adjustments 

for Controls 

Spatial and 

Temporal 

Allocations 

Appendix B - Page Number:

353
 156

Temporal 

Temporal allocation profiles were also developed for this project using the residential 

wood survey data. Profiles were first developed 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., diurnal, 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 divided 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 morning activity to the hours of 

6 a.m. to 12 p.m. and 25% of the morning activity to the hours 12 midnight to 6 p.m. The 

hours of 6 p.m. to 12 noon were assigned 75% of the evening activity; and 25% of the 

evening activity went to the hours 12 midnight to 6 a.m. 

Once a fraction of the total activity was assigned 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.) The 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 0.0349

Appendix B - Page Number:

354
 157

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 0.19406

Appendix B - Page Number:

355
 158

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 0.37871 

Appendix B - Page Number:

356
 159

A sample calculation for annual activity is provided 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 fraction 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, during the analysis of survey data, Pechan finds a 

good correlation between wood consumption and annual HDD, the activity variable will take the 

form of tons/HDD-yr (where HDD are annual heating-degree days). The calculation of annual 

activity for a specified census tract and SCC would 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 days for the census tract; 

HUo = other housing units; 

UFo = other housing units user fraction for equipment type (SCC); and 

Ao = other housing units annual activity (tons/HDD-yr). 

Emissions 

Calculation 

Appendix B - Page Number:

357
 160

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 fugitive dust emissions from residential construction activities. 

PM10 and PM2.5

Activity 

For residential construction, housing permit data for single-family units, two-family units, 

and apartments were obtained at the county level from the U.S. Department of 

Commerce’s (DOC) Bureau of the Census. Adjusted county permit data to equal regional 

housing start data that was also obtained from the Bureau of the Census. 

Estimated the number of buildings in each category, and then estimated the total acres 

disturbed by construction by applying conversion 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 calculated 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 activity. The duration of construction activity for 

houses is assumed to be 6 months. 

Apartment construction emissions are calculated 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 Sources 

Appendix B - Page Number:

358
 161

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 square feet by an average basement depth of 8 

feet and adding in 10 percent of the cubic feet calculated for peripheral dirt removed 

produces an estimate of the cubic yards of earth moved during residential construction. The 

percentage of one-family houses with basements was obtained from the DOC. The 

percentage of houses per Census region (Northeast, Midwest, South, and West) that 

contain full or partial basements is applied to the housing start estimates for each of these 

respective regions. The best available control measures (BACM) Level 2 equation 

(emission factor of 0.011 tons PM10/acre/month plus 0.059 tons PM10/1000 cubic yards 

of on-site cut/fill) is applied once the number 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 PM10/acre/month ton PM10/acre/month ton PM10/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 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. 

Point Source 

Adjustments 

Adjustments 

for Controls 

Spatial and 

Temporal 

Allocations 

Appendix B - Page Number:

359
 162

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 residential construction activity 

 E RC - SFH = Emissions of pollutant i in tons per 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 residential single-family 

home construction activity of homes with basements 

E RC – SFH, w/o BM = Emissions of pollutant i in tons per year from residential single-family 

home construction activity of homes without basements 

HSSFH 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 per year from residential single-family 

home construction activity 

 HS SFH = Residential single-family housing starts 

 HS SFH, w BM = Percent of residential single-family housing starts with basements 

 AD RC - SFH = Acres disturbed per housing type (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 

Calculation 

Appendix B - Page Number:

360
 163

E RC – SFH, w BM = Emissions from residential construction + Emissions from basement excavation 

[HSSFH x HS SFH,w BM x (AD RC – SFH ) x (PD RC – SFH) x EF RC – SFH] + 

E [HSSFH x HS SFH,w BM x AHS RC – SFH x ABD RC – SFH x PDE RC – SFH x EF Acres-Disturb] RC – SFH, w BM = 

2000 

where: 

 E RC – SFH, w BM = Emissions of pollutant i in tons per year from residential single-family 

home construction activity 

 HS SFH = Residential single-family housing starts 

 HS SFH, w BM = Percent of residential single-family housing starts with basements 

 AD RC - SFH = Acres disturbed per housing type (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 ft2

) 

 ABD RC - SFH = Average basement depth for residential 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-family home construction in tons 

PM10/1000 cubic yards 

Appendix B - Page Number:

361
 164

4.1.7.2 Heavy Construction Activity 

SCC: 28 10 001 000 

Emissions produced from the construction of nonresidential buildings are estimated using the 

value of construction put in place. The national value of construction put in place is obtained 

from the Bureau of the Census97. The national value of construction put in place is allocated to 

the state level using non-residential building construction employment data within NAIC 2333 

obtained from 2002 County Business Patterns98. The state value of construction put in place is 

allocated to the county level using non-residential building construction employment data within 

NAIC 2333 obtained from the 2002 County Business Patterns99 for the State of Maryland. 

PM10 and PM2.5

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 using non-residential building construction employment data 

within NAIC 2333 obtained from 2002 County Business Patterns. 

A conversion factor of 1.6 acres/106

 dollars ($) is applied to the construction valuation 

data. This conversion factor is developed by adjusting the1992 value of 2 acres/$106

 to 

2002 and 2000 constant dollars using the Price and Cost Indices for Construction. The 

duration of construction activity for nonresidential construction is estimated to be 11 

months. 

Employee numbers were taken from County Business Patterns 2002 - Maryland, NAIC 

2333, Non-residential Building Construction. Some county employment data is 

represented by a letter code indicating 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 for 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 Patterns Economic Profile for 2002 – Repeat for each county. 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

362
 165

adjusted so that the state total employment in a NAIC matched 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 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. 

Number of Employees within 

Value of Construction NAIC 2333 in Maryland 

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 

Calculation 

Appendix B - Page Number:

363
 166

Number of Employees 

within NAIC 2333 in 

Maryland 

19,267 

Value of Construction 19,267 

Work in Maryland = $167,084,000,000.00 x 855,483 

Value of Construction 

Work in Maryland = $3,763,029,105 

HCj x CF HC x EF HC i x DC HC E HC i = 365 

where: 

E HC,i = Emissions of pollutant i in tons 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 per acre per month for pollutant i 

DC HC = Duration of construction activity (11 months) 

2002 Sample Calculation Heavy Construction (Anne Arundel County)

HCj 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 10

Appendix B - Page Number:

364
 167

4.1.7.3 Road Construction Activity 

SCC: 28 10 001 000 

This source category covers fugitive dust emissions from road construction activity. PM10

emissions produced by road construction are estimated using an emission factor for heavy 

construction and the State capital outlay for new road construction. 

PM10 and PM25

Activity 

To estimate the acres disturbed by road construction, the Federal Highway Administration 

(FHWA) State expenditure data for capital 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 (NCDOT) on the $/mile spent on various road 

construction projects. For interstate expenditures, used an average of $4 million/mile 

corresponding to freeways and interstate projects 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 freeways and interstate projects) listed for: 

1) new location; 2) widen existing 2-lane shoulder section; and 3) widen existing 4-lane 

w/ median. 

Miles are converted to acres for each of the 6 road types using the following estimates of 

acres disturbed per mile: 

• Interstate, urban and rural; Other 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 Sources 

Appendix B - Page Number:

365
 168

Emission Factors 

An PM10 emission factor of 0.42 tons/acre/month is used to account for the large amount 

of dirt moved during the construction of roadways. The duration of construction activity 

for road construction is estimated to be 12 months. 

PM25 emissions are estimated by applying a particle size multiplier of 0.20 to PM10

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-level dry silt values were applied to PM10 emissions 

for each county.. 

No subtration of emissions from point sources is necessary. 

For construction emissions, a control efficiency of 50 percent is used for both PM10 and PM2.5

for PM nonattainment areas. 

Spatial 

State-level estimates of acres disturbed are 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 

Allocations 

Appendix B - Page Number:

366
 169

Exp x MCi x ADi x EF RC i x DUR E RC, i = 2000 x 365 

where: 

E RC,i = Emissions of pollutant i in tons 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 

Calculation 

Appendix B - Page Number:

367
 170

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 methodology are discing, tilling, leveling, chiseling, plowing, and 

other mechanical operations used to prepare the soil. Dust emissions are produced by the 

mechanical disturbance of the soil by the implement 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 operations are computed by multiplying an emission 

factor (EF) by an activity factor. The agricultural tilling emission 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 need different operations to prepare the soil, each crop also has its 

own acre-pass value. Acre-passes are the number of passes, per acre, that are typically needed to 

prepare a field for planting a particular crop. By combining the crop acreage, crop specific acrepass data, and the agricultural tilling emission factor, we estimate the particulate matter produced 

by agricultural land preparation operations. 

Agricultural soil preparation particulate 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 summed to produce the county and statewide 

particulate matter (PM) and PM emission estimates. 

PM10 and PM2.5

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 Sources 

Appendix B - Page Number:

368
 171

In computing land preparation PM emissions, 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 include discing, tilling, land leveling, and other 

operations. Each crop is different in the type of soil operations performed and when they 

occur. MDE used acre-pass estimates compiled by the California Air Resources Board 

(CARB). For the crops that were not explicitly 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 agricultural land preparations 

is from U.S. EPA’s AP-42100. This emission factor was developed in 1981 based on test 

data measured in California and Kansas by Midwest Research Institute. Because of a lack 

of more detailed estimates, this single emission 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 interest (EPA default = 0.042 for PM2.5 or 0.21 for PM10) 

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 above 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. PM2.5 /acre-pass) (Lbs. PM10 /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 emissions are reduced when soil moisture is 

higher, California ARB staff has incorporated 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 for watering at construction sites and their best 

judgement. During December and March, California 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. 

Appendix B - Page Number:

369
 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 operations 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 from 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, California also collected detailed information on 

when agricultural operations occur. Using these 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 document includes detailed crop calendars for each 

crop with updated information. For all of the 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 

Allocations 

Appendix B - Page Number:

370
 173

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

E hay x AP hay) + (A soy x AP soy) + (A barley x AP barley) + (A tobacco x AP tobacco)] 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 PM2.5 

Emissions 

Calculation 

Appendix B - Page Number:

371
 174

4.1.7.5 Paved Roads 

SCC: 22 94 000 000 

This source category covers fugitive dust emissions from activity on paved roads. 

PM10 and PM2.5

Activity 

The basis for the activity data for fugitive dust emissions from paved roads is the statelevel vehicle miles traveled per paved road type and the state-level vehicle miles traveled 

per unpaved road per road type. 

Emission Factors 

The emission factor for paved roads is calculated 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 value = 7.3 grams PM 10 per mile) 

PVSILT Road surface silt loading factor in grams per square mile 

WEIGHT Average weight of all vehicle 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 Sources 

Appendix B - Page Number:

372
 175

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 factor (grams/mile) for paved roads 

CF RAIN = Correction Factor for Rain/Precipitation 

And Where: 

Appendix B - Page Number:

373
 176

CF RAIN = 1 - (P / 4N ) 

Where: 

CF RAIN = Correction Factor for Rain/Precipitation 

p = number of days in a given month with greater than 0.01 inches of rainfall 

(data collected from monthly 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 equation 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 2

Appendix B - Page Number:

374
 177

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 PM10 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% applied 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 

10 

Appendix B - Page Number:

375
 178

4.1.7.6 Unpaved Roads 

SCC: 22 96 000 000 

Description

This source category covers fugitive dust emissions from activity on unpaved roads. 

The activity data needed to calculate emissions from unpaved roads was not available. Methods 

are still being researched as to how to properly gather this data. MDE cannot submit any 

emissions for this source category at the present time. 

Appendix B - Page Number:

376
 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 emissions from accidental vehicle fires. Vehicles 

included are any commercial or private mode of transportation that is authorized for use on 

public roads. 

PM10, NOx, CO, VOC 

 

Activity 

Local data was collected from state or local fire marshals and public safety departments. 

See the spatial apportioning section 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 conservative assumption is that an average vehicle has 500 pounds of 

components that can burn in a fire, based 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--Volume 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 Sources 

Appendix B - Page Number:

377
 180

 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 fires 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. 

VBj 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 burned) for vehicle fires (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)

VBj x FLF VF x EFVF, 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 vehicle fires in Anne Arundel County in 20002 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

378
 181

4.1.8.2 Forest Fires 

SCC: 28 10 001 000 

Forest fires in certain rural areas can produce very large, short term organic emissions. 

PM10 and PM2.5

Activity 

ARMA used data from the Maryland Forest, Park and Wildlife Service103 on the number of 

fires and acreage burned per county. Emission 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 from 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 Controls 

Appendix B - Page Number:

379
 182

Spatial 

The activity data for forest fires 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. 

ABj 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)

ABj x EFf,i x FLF FF E FF i = 2000 x 365 

where: 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

380
 183

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. 

Appendix B - Page Number:

381
 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 controlled 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 forest management practice to establish favorable 

seedbeds, remove competing underbrush, accelerate nutrient cycling, control tree pests and 

contribute other ecological benefits. 

PM10 and PM2.5

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 was 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 Sources 

Appendix B - Page Number:

382
 185

No subtration of emissions from 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 different times of the year, ARMA used no seasonal 

adjustment factor. The activity level is seven days per week. 

ABj x EF PB i x FLF J E PB i = 2000 x 365 

where: 

E PB,i = Emissions of pollutant i in tons per day from prescribed burning 

FLF J = Fuel loading factor for type of material 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/Prescribed Burning (Worcester County)

ABj 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 are done in a similar manner. 

Point Source 

Adjustments 

Adjustments 

for Controls 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

383
 186

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 burning, burning of agricultural 

crop residues, and burning of standing field crops as part of harvesting (e.g., sugar cane). 

PM10 and PM2.5 

Emissions from this source were assigned to the open burning category because the county 

permits issued in 2002 did not require information 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. 

PM10 and PM2.5

MDE staff used emission factors, fuel loading factors and methodology documented in EIIP107, 

Structure Fires, dated July 1999. 

Activity 

The Maryland State Fire Marshal's office provided the number of structure fires by county. 

 

107 Emission Inventory Improvement Program 

Description 

Pollutants 

Method and 

Data Sources 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

384
 187

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 from 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. 

SFj 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 

Calculation 

Appendix B - Page Number:

385
 188

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 variation as given in Table 5.8-1 

in the EIIP document. 

2002 Sample Calculation Structure Fires (Baltimore City)

Equation:

SFj x EF SF i x FLF SF E SF i = 2000 x 365 

2386108 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 Fires 

Appendix B - Page Number:

386
 189

4.1.8.6 Orchard Heaters 

SCC: 28 01 520 000 

In areas of the country where frost threatens orchards, heaters may be used in cold portions of the 

growing season. 

PM10 and PM2.5

Calls to several orchards in Washington and Frederick Counties (where most of the orchards in 

Maryland are located), revealed that no heaters were used. One orchard used fans to move air on 

still nights when there would be danger of frost to fruit tree blossoms. Therefore, orchard heaters 

are not included in Maryland's 2002 baseline inventory. 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

387
 190

4.1.9 AMMONIA SOURCES 

Ammonia (NH3) is a pungent colorless gaseous compound of nitrogen and hydrogen that is very 

soluble in water and can be condensed into a liquid by cold and pressure. Ammonia gas reacts in 

the atmosphere with NOx or SOx to produce ammonium nitrate or ammonium sulfate, major 

PM2.5 components in the United States. 

In preparing an ammonia inventory, it is worthwhile to prioritize 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 lists of ammonia sources that can be used 

to evaluate which sources are present within a region. These sources may then be ranked in terms 

of priority for estimating emissions. 

Currently, there is a significant amount of uncertainty concerning the contribution of soil to 

ammonia emission levels. High quality emission factors for this category do not exist, and even 

the physics of ammonia-surface exchange is not well understood. Soils emit and uptake ammonia 

so it is difficult to evaluate the net contribution, emissions may be potentially significant in some 

regions if the uptake is not substantial. Indeed, the literature shows that 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 State of Maryland has decided not to include 

emissions from soils. 

This section contains the ammonia emission inventory for 

• Agricultural Livestock Production Operations 

• Agricultural Fertilizer Application, 

• Human activity. 

 

111 Battye, R., Battye, W., C. Overcash, 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). Appendix B - Page Number:

388
 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 

NH3

Conceptually, the method for estimating emissions from cattle is simple: count the number of 

animals, then multiply this by the average emissions per animal, and the resulting value 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 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/ year Battye, et al. (1994) 

Steers 11.65 Kg/ steer/ 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 

Controls 

Spatial and 

Temporal 

Allocations 

Appendix B - Page Number:

389
 192

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 EMBC + 1999 EMMC + 1999 EMHF + 1999 EMST

Where: 

EM COWS-99 Total = Total NH3 emissions from cows, all categories 

 EMBC = 1999 Uncontrolled emissions from beef cows 

 EMMC = 1999 Uncontrolled emissions from milk cows 

 EMHF = 1999 Uncontrolled emissions from heifers 

 EMST = 1999 Uncontrolled emissions from steers 

 Where: 

EM BC = (ACBC * EFBC) 

EM MC = (ACBC * EFMC) 

EM HF = (ACBC * EFHF) 

EM ST = (ACBC * EFST) 

 Where: 

 ACBC = Activity level (number) of beef cows 

 ACMC = Activity level (number) of milk cows 

 ACHF = Activity level (number) of heifers 

 ACST = Activity level (number) of steers 

 EFBC = Emission factor for beef cows 

 EFMC = Emission factor for milk cows 

 EFHF = Emission factor for heifers 

 EFST = Emission factor for steers 

Emissions 

Calculation 

Appendix B - Page Number:

390
 193

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. 

NH3

Conceptually, the method for estimating emissions from cattle is simple: count the number of 

animals, then multiply this by the average emissions per animal, and the resulting value 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 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/ 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 

Controls 

Appendix B - Page Number:

391
 194

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 EMHOGS + 1999 EMPIGS 

Where: 

EM SWINE-99 Total = Total NH3 emissions from swine, all categories 

EMHOGS = 1999 Uncontrolled emissions from hogs 

EMPIGS = 1999 Uncontrolled emissions from pigs 

 Where: 

EM HOGS = (ACHOGS * EFHOGS) 

EM PIGS = (ACPIGS * EFPIGS) 

 Where: 

 ACHOGS = Activity level (number) of hogs 

 ACPIGS = Activity level (number) of pigs 

 EFHOGS = Emission factor for hogs 

 EFPIGS = Emission factor for pigs 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

392
 195

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. 

NH3

Conceptually, the method for estimating emissions from cattle is simple: count the number of 

animals, then multiply this by the average emissions per animal, and the resulting value 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 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/ 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 

Controls 

Appendix B - Page Number:

393
 196

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 chickens in an individual county

EM CHICKENS-99 Total 

= 

1999 EMPULLET + 1999 EMLAYER + 1999 EMBROILER 

Where: 

EM CHICKENS-99 Total = Total NH3 emissions from chickens, all categories 

 EMPULLET = 1999 Uncontrolled emissions from pullets 

 EMLAYER = 1999 Uncontrolled emissions from layers 

 EMBROILER = 1999 Uncontrolled emissions from broilers 

 Where: 

EM PULLET = (ACPULLET * EFPULLET) 

EM LAYER = (ACLAYER * EFLAYER) 

EM BROILER 

= 

(ACBROILER * EFBROILER) 

 Where: 

 ACPULLET = Activity level (number) of pullet chickens 

 ACLAYER = Activity level (number) of layer chickens 

 ACBROILER = Activity level (number) of broiler chickens 

 EFPULLET = Emission factor for pullet chickens 

 EFLAYER = Emission factor for layer chickens 

 EFBROILER = Emission factor for broiler chickens 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

394
 197

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. 

NH3

Conceptually, the method for estimating emissions from cattle is simple: count the number of 

animals, then multiply this by the average emissions per animal, and the resulting value 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 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 

Controls 

Appendix B - Page Number:

395
 198

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 sheep in an individual county

EM SHEEP 

= 

ACSHEEP * EFSHEEP

Where: 

EM SHEEP = Total NH3 emissions from sheep, all categories 

ACSHEEP = Activity level (number) of sheep 

EFSHEEP = Emission factor for sheep 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

396
199

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. 

NH3

Conceptually, the method for estimating emissions from cattle is simple: count the number of 

animals, then multiply this by the average emissions per animal, and the resulting value 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 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 

Controls 

Appendix B - Page Number:

397
200

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 goats in an individual county

EM GOATS-99 Total 

= 

1999 EMAG + 1999 EMMG 

Where: 

EM GOATS-99 Total = Total NH3 emissions from goats, all categories 

 EMAG = 1999 Uncontrolled emissions from angora goats 

 EMMG = 1999 Uncontrolled emissions from milk goats 

 Where: 

EM AG = (ACAG * EFAG) 

EM MG 

= 

(ACAG * EFAG) 

 Where: 

 ACAG = Activity level (number) of angora goats 

 ACMG = Activity level (number) of milk goats 

 EFAG = Emission factor for angora goats 

 EFMG = Emission factor for milk goats 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

398
201

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. 

NH3

Conceptually, the method for estimating emissions from cattle is simple: count the number of 

animals, then multiply this by the average emissions per animal, and the resulting value 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 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 

Allocations 

Appendix B - Page Number:

399
202

Temporal 

Data for temporal allocation is not available for this source. 

Equation:

1999 TPY ammonia emissions for horses in an individual county

EM HORSE = ACHORSE * EFHORSE

Where: 

EM HORSE = Total NH3 emissions from horses, all categories 

ACHORSE = Activity level (number) of horses 

EFHORSE = Emission factor for horses 

Emissions 

Calculation 

Appendix B - Page Number:

400
203

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. 

NH3

Conceptually, the method for estimating emissions from cattle is simple: count the number of 

animals, then multiply this by the average emissions per animal, and the resulting value 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 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/ year 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 

Controls 

Appendix B - Page Number:

401
204

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 ducks in an individual county

EM DUCKS = ACDUCKS * EFDUCKS

Where: 

EM DUCKS = Total NH3 emissions from ducks, all categories 

ACDUCKS = Activity level (number) of ducks 

EFDUCKS = Emission factor for ducks 

Spatial and 

Temporal 

Allocations 

Emissions 

Calculation 

Appendix B - Page Number:

402
205

4.1.9.8 Agricultural Fertilizer Application 

 SCC: 28 01 700 001 (Fertilizer Composite) 

 

Fertilizer application is typically considered to be the second or third most important source on a 

national level, depending on whether the inventory includes soil emissions. Existing inventories 

usually estimate the contribution from fertilizer application 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 are for 1995 from the Association 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 inventories, which are based on sales of fertilizer 

to dealers rather than to farmers. The dealers may subsequently sell the fertilizer to farmers in 

other locations, resulting in an inaccurate spatial distribution of activity levels. A better 

approximation (in the absence of actual application data) is to use sales from dealers to farmers. 

The AAPFCO datasets contain county-level resolution for the top producing states for each crop 

(usually about 30 states), and state-level resolution for the other states. USGS also has countylevel records of fertilizer application for years 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 the 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 Asman 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 than 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 the spring and fall than in the summer and winter, 

corresponding to crop cycles. To improve temporal allocation, USDA data on crop planting 

times and fertilizer application times and rates were used to generate a monthly distribution of 

fertilizer application (USDA, 1997; USDA-ERS, 1991; USDA-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. 

NH3

Description: 

Pollutants 

Appendix B - Page Number:

403
206

Conceptually, the method for estimating emissions from mobile sources is simple: collect data on 

the amount of fertilizer sold to farmers in a specific county, then multiply this by the per cent of 

ammonia released per fertilizer application, and the resulting value 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 and Food Control Officials (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 NH3 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 

Allocations 

Appendix B - Page Number:

404
207

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 the spring and fall than in the summer and winter, 

corresponding to crop cycles. To improve temporal allocation, USDA data on crop planting 

times and fertilizer application times and rates were used to generate a monthly distribution of 

fertilizer application (USDA, 1997; USDA-ERS, 1991; USDA-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 for this category results in a 

substantial error for most months of the year. 

Equation:

1999 TPY ammonia emissions for agricultural fertilizer sources in an individual county

EM FERT-99 Total = 

EMAmmNit + EMAmmSul + EMAmmThio + EMCalAmmNit + EMNitSol + EMUrea

+ EMDiAmmPhos + EMMonoAmmPhos + EMLiqAmmPhos + EMPotNit + EMMisc + 

EMMix

Where: 

EM MOBILE-99 Total = Total NH3 emissions from agricultural fertilizer application, all categories 

EMAmmNit = Emissions from Ammonium Nitrate fertilizer 

EMAmmSul = Emissions from Ammonium Sulfate fertilizer 

EMAmmThio = Emissions from Ammonium Thiosulfate fertilizer 

EMCalAmmNit = Emissions from Calcium Ammonium Nitrate fertilizer 

EMNitSol = Emissions from Nitrogen Solutions fertilizer 

EMUrea = Emissions from Urea fertilizer 

EMDiAmmPhos = Emissions from Diammonium Phosphate fertilizer 

EMMonAmmPhos = Emissions from Monoammonium Phosphate fertilizer 

EMLiqAmmPhos = Emissions from Liquid Ammonium Polyphosphate fertilizer 

EMPotNit = Emissions from Potassium Nitrate fertilizer 

EMMisc = Emissions from Miscellaneous fertilizer 

EMMix = Emissions from Mixed fertilizer 

 Where: 

EM AmmNit = (ACAmmNit * Per Cent Released AmmNit) 

EMAmmSul = (ACAmmSul * Per Cent Released AmmSul) 

EMAmmThio (ACAmmThio * Per Cent Released AmmThio) 

EMCalAmmNit = (ACCalAmmNit * Per Cent Released CalAmmNit) 

EMNitSol = (ACNitSol * Per Cent Released NitSol) 

EMUrea (ACUrea * Per Cent Released Urea) 

Emissions 

Calculation 

Appendix B - Page Number:

405
208

EMDiAmmPhos = (ACDiAmmPhos * Per Cent Released DiAmmPhos) 

EMMonAmmPhos = (ACMonAmmPhos * Per Cent Released 

MonAmmPhos) 

EMLiqAmmPhos = (ACLiqAmmPhos * Per Cent Released LiqAmmPhos) 

EMPotNit = (ACPotNit * Per Cent Released PotNit) 

EMMisc (ACMisc * Per Cent Released Misc) 

EMMix = (ACMix * Per Cent Released Mix) 

 Where: 

 ACAmmNit = Activity level (amount of Ammonium Nitrate fertilizer 

applied per county) 

 Per Cent Released AmmNit = Per Cent of NH3 released during fertilizer application 

Appendix B - Page Number:

406
209

4.1.9.9 Human Breath and Perspiration 

SCC: 28 10 010 000 (Human Perspiration) 

Ammonia emissions from human breath and perspiration comprise a few percent of the national 

ammonia emission inventory.

NH3

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 approved 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 

Allocations 

Appendix B - Page Number:

407
210

Temporal 

Data for temporal allocation is not available for this source. 

Equation:

1999 TPY ammonia emissions from human breathe and perspiration in an individual county

EM HUMAN B&P = ACHUMAN * EFHUMAN B&P

Where: 

EM HUMAN B&P = Total NH3 emissions from human breathe and perspiration 

ACHUMAN = Activity level (number) of people per county 

EFHUMAN B&P = Emission factor for human breathe and perspiration 

Emissions 

Calculation 

Appendix B - Page Number:

408
211

5.0 NONROAD SOURCES

5.1 NONROAD VEHICLES/ENGINES 

This section contains the nonroad source emission inventory for volatile organic compounds 

(VOCs), nitrogen oxides (NOx), and carbon monoxide (CO) and if possible carbon dioxide 

(CO2), sulfur oxides (SOX), particulate matter (PM), ammonia (NH3), and toxic air pollutants. 

Nonroad mobile sources include motorized vehicles and equipment that are normally not 

operated on public roadways to provide transportation. 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 approved 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 Model112. In a memorandum113, dated June 

16, 2003, EPA allowed the use of the draft NONROAD Model and associated default inputs in 

the development of inventories supporting State Implementation Plans (SIPs). The second 

methodology entailed the use of EPA emission factors. 

Sample calculations presented below are for illustrative 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. Appendix B - Page Number:

409
212

5.2 NONROAD MODEL 

As stated previously, the 2002 emissions estimate 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 types by horsepower rating. Fuel types include gasoline, diesel, 

compressed natural gas (CNG), and liquefied petroleum gas (LPG). 

The NONROAD model consists of three separate 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 supplied 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 scenario. Once the model 

options are specified, the user can then run the Fortran core model from within the interface, 

and then can move directly to the reporting 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 core model can be operated as a stand-alone 

application; however, as a stand-alone application it requires 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 using Microsoft’s ACCESS database software, is used to create 

standardized reports using output data generated in the core model. 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 database application. Although the reporting utility 

is written in ACCESS, it is a stand-alone application, and you do not need to know how to use 

ACCESS to generate reports.

The NONROAD model estimates emissions for six exhaust pollutants: hydrocarbons (HC), 

NOx, carbon monoxide (CO), carbon dioxide (CO2), sulfur oxides (SOX), and PM. The user 

selects among five different types for reporting HC — as total hydrocarbons (THC), total 

organic gases (TOG), non-methane organic gases (NMOG), non-methane hydrocarbons 

(NMHC), or volatile organic compounds (VOC). Particulate matter can be reported as PM of 

10 microns or less (PM10) or PM of 2.5 microns or less (PM2.5). The model also estimates 

emissions of non-exhaust HC for four modes — diurnal, refueling spillage, vapor 

displacement, and crankcase emissions. All emissions are reported as short tons (i.e., 2000 

lbs). Ammonia (NH3) emissions from NONROAD Model equipment were post-processed 

outside of the actual model.

Appendix B - Page Number:

410
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, 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 deterioration and/or new standards. 

The emissions are then temporally and geographically allocated using appropriate allocation 

factors. 

There are several input files that provide necessary information to calculate and allocate 

emissions estimates. These input files correspond to the basic data needed to provide the 

calculations: emission factors, base year equipment population, activity, load factor, average 

lifetime, scrappage function, growth estimates, 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 national defaults are presented in Section 4.7 – 

NONROAD Model Appendices.’ 

Input parameters for the nonroad Model are listed below: 

2002 NONROAD MODEL INPUTS 

 

 Winter Spring Fall 

All Maryland Counties All Maryland 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 0 

 

Appendix B - Page Number:

411
214

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: Calvert, Charles, Frederick, Montgomery, Prince Georges 

The BNAA region includes the following counties: 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 NONROAD Model equipment were estimated by running the NR 

Model Reporting Tool for one county (Anne Arundel). The reporting tool provided the total 

fuel used per source classification 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 ratio was then applied to all the counties in 

Maryland to estimate ammonia emissions for the state. 

Appendix B - Page Number:

412
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 types 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), tillers (<5HP), lawn and garden tractors, wood 

splitters, snow blowers, chippers/stump grinders, commercial turf equipment, and other lawn and 

garden equipment. Emissions result from operation of the internal combustion engines that 

power the equipment. 

PM10, PM2.5, 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 International Corporation under EPA Contract No. 

DW47926801 dated December 2002. This report, EPA420-P-02-013, constitutes the 

User’s Guide to the NONROAD model. The report contains an overview of the 

model, equipment types, pollutants reported, 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 determining nonroad emissions, the Department ran 

the NONROAD model to determine the emission estimate for 2002. MDE-ARMA opted 

to choose seasonal (Spring, Summer, Fall, Winter) period totals as the output files from 

the model. These period totals were divided by the number of days in a season to reflect 

an average daily emission level for each season. 

No subtration of emissions from point sources is necessary. 

The NONROAD model automatically applies controls, when applicable, for a given year. 

Description 

Pollutants 

Method and 

Data Sources 

Point Source 

Adjustments 

Adjustments 

for Controls 

Appendix B - Page Number:

413
216

Spatial 

The NONROAD model spatially allocates equipment populations through the REGION 

data packet and the emissions through 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 identify the state where you are located. This 

step sets up the population and allocation factor data files for your state.

The ALLOC input file defines the spatial 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 fraction of annual activity 

occurring in the given month. For periods longer than a single month (e.g. season), the 

factors from each month spanned by the period are summed. The second, identified as 

/DAILY/, provides the day-of-the-week adjustments. 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 the NONROAD engine 

emissions modeling is further documented in Report No. NR-004, dated December 9, 

1997. The weekday and weekend day temporatl allocation of activity in the NONROAD 

model is further documented in Report No. NR-015114, 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 input 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 model 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 

Calculation 

Appendix B - Page Number:

414
217

5.3 RAILROADS 

 SCC: 22 85 002 005 (Line Haul) 

 SCC: 22 85 002 010 (Yard Engines) 

Railroad locomotives used in the United States are primarily of two types: electric and dieselelectric. Electric locomotives are powered by electricity generated at stationary power plants. 

Emissions are produced only at the electrical generation plant, which is considered a point source 

and therefore not included here. Diesel-electric locomotives, on the other hand, use a diesel 

engine and an alternator or generator to produce the electricity required to power its traction 

motors. Emissions produced by these diesel engines are of interest in emission inventory 

development. Other sources of emissions from railroad operations include the small gasoline 

and diesel engines used on refrigerated and heated rail cars. These engines are thermostatically 

controlled, working independently 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 Haul (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 responsible 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 distribution of the company's track mileage by Maryland 

County: 

1. AMTRAK (National Railroad 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: 

Appendix B - Page Number:

415
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 utilized in a county. 

Activity 

A survey of railroad petroleum consumption 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 

SO2 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 during this period) and consumes an average of 228 

gallons per day. 

No subtration of emissions from point sources is necessary. 

No controls are available for this source category. 

Spatial 

Emission estimates are based on fuel consumption. Company supplied state total fuel 

usage was allocated to the county level by the propotion 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 

Allocations 

Appendix B - Page Number:

416
219

When specific county information was not provided, 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 consumed by every railroad operating in the 

calculated county 

 Fuel CTY j = (Gcty1 + Gcty2 + ... + Gcty12) 

 EF LH = line haul locomotive emission factor for a given pollutant 

The following equation was used to calculate the 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 locomotives 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 = (Ncty1 + Ncty2 + ... + Ncty12) 

 EF YL = Yard locomotive emission factor for a given pollutant 

Emissions 

Calculation 

Appendix B - Page Number:

417
220

Sample Calculations:

2002 Montgomery County Emissions 

Line Haul Emission Estimate 

AMTRAK, CSX, and MARC operated line haul locomotives 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: 

Gcty1 = 25,463.8 gallons used in Montgomery Co. per year by AMTRAK 

 (information provided by AMTRAK) 

Amount of fuel used in gallons used by CSX Transportation line haul locomotives in 

Montgomery County: 

36.37 track miles in Montgomery Co. for CSX Gcty4 = 514.97 track miles in the state for CSX 

 x 10,512,431.53 gallons used in state per 

year 

Gcty4 = 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 Gcty12 = 156 track miles in the state for MARC x 1,782,750 gallons used in state per year 

Gcty12 = 319980.77 gallons used in Montgomery Co. per year by MARC 

VOC Emissions from line haul locomotives in Montgomery County: 

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.0213 lbs. VOC /gal EMVOC = (2000 lbs. per ton) * (365 days per year) 

EMVOC = 0.0316 tons VOC / day 

NOx Emissions from line haul locomotives in Montgomery County: 

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.4931 lbs. NOX /gal EMNOX = (2000 lbs. per ton) * (365 days per year) 

EMNOX = 0.7348 tons NOX / day 

CO Emissions from line haul locomotives in Montgomery County: 

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.0626 lbs. CO / gal EMCO = (2000 lbs. per ton) * (365 days per year) 

EMAppendix B - Page Number: CO = 0.0933 tons CO / day 418
221

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 engine per day * 0.0509 lbs. VOC / gallon) EMVOC = (2000 lbs. per ton) 

EMVOC = 0.0116 tons VOC / day 

NOx Emissions from yard locomotives in Montgomery County: 

(2 engine * 228 gallons per engine per day * 0.5044 lbs. NOX / gallon) EMNOX = (2000 lbs. per ton) 

EMNOX = 0.1150 tons NOX / day 

CO Emissions from yard locomotives in Montgomery County: 

(2 engine * 228 gallons per engine per day * 0.0894 lbs. CO / gallon) EMCO = (2000 lbs. per ton) 

EMCO = 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 added 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: 

EmisVOC = 0.0316 tons / day from line haul + 0.0116 tons / day from yard + 0.0013 tons VOC / 

day from EPA Non-Road Model. 

EmisVOC = 0.0445 tons VOC / day 

Total NOx Emissions for Montgomery county: 

EmisNOx = 0.7348 tons / day from line haul + 0.1150 tons / day from yard + 0.0005 tons NOx / 

day from EPA Non-Road Model. 

EmisNOx = 0.8503 tons NOx / day 

Total CO Emissions for Montgomery county: 

EmisCO = 0.0933 tons / day from line haul + 0.0204 tons / day from yard + 0.0518 tons CO / day 

from EPA Non-Road Model. 

EmisCO = 0.1655 tons CO / day 

Appendix B - Page Number:

419
222

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, which includes air taxis and commuter aviation, is 

used for recreational flying, business travel, personal transportation, and various other activities. 

Military aviation is the operation and activities of military aircraft at airports in Maryland. 

PM10, PM2.5, 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 departures 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 lists LTO cycles by aircraft 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 emission factors supplied in Procedures for 

Emission Inventory Preparation, Volume IV: Mobile Sources, EPA’s Office of 

Mobile Sources, 1992. This source provided emission factors for specific 

commercial engine types, and alternative fleet 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 specific aircraft data. 

ARMA also used this composite factor method in its 1990 baseline inventory. For 

the final 2002inventory ARMA has requested operation data from military aircraft by 

operation type from Maryland Army, Navy, and Air Force base environmental 

support offices. 

Description: 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

420
223

3) For commercial aviation ARMA used FAA’s EDMS115 emissions model and 

databases. EDMS is designed to assess the 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 aircraft engine emission 

factors from the International Civil Aviation Organization (ICAO) Engine Exhaust 

Emissions Data Bank, vehicle emission factors from EPA MOBILE 5a, and EPAvalidated dispersion algorithms. Aircraft activity includes landside and airside 

operations. EDMS defines four 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 default mixing height value of 3,000 feet above 

ground level. The mixing height is the layer of air where airplane emission affect 

ground level emission concentrations. Above 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 emissions from a particular airport to the 

county where that airport was located. We assumed no seasonal variation 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 

Allocations 

Appendix B - Page Number:

421
224

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 cycles 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 associate aircraft type with the number of engines, 

auxiliary power units and ground support equipment. The model also assigns 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, stationary 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 assigned to the aircraft, 

time for each mode of operation, annual LTO operations, 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 

Calculation 

Appendix B - Page Number:

422
225

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 the table below: 

NAME CO 

Tons/year 

HC116

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. Appendix B - Page Number:

423
226

A daily emission inventory was produced assuming an airport activity of 365 days per year. 

The model was run for all aircraft at BWI and all commercial aviation at Hagerstown Regional, 

Ocean City Municipal and military aircraft at Andrews Air Force Base. 

Appendix B - Page Number:

424
227

5.4.2 General Aviation 

SCC: 22 75 050 000 

A rough estimate of emissions were calculated after information on the LTO operations of 

aircraft operation type was obtained from Maryland’s airports. This method used the alternative 

fleet-average procedure of Section 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) EmissVOC = LTO (GA) * EF (GA)VOC

Where: 

LTO (GA) = LTOs for General Aviation 

 EF (GA)xx = Emission Factors for General Aviation 

2) EmissVOC = 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 Field in Talbot County. The airport had 21,569 

General Aviation LTOs over a twelve month period. Performing step 1 Equations (above) the 

calculations were: 

EmissVOC = [L(GA) * EF(GA)HC]* CF (VOC/HC) 

EmissVOC = [(21,569 LTOs / Year * 0.394 (lbs. HC / LTO)] * 0.9708 (lbs. VOC / lbs. HC)))) 

EmissVOC = 8,250.0390 lbs. VOC / Year 

EmissVOC = 0.0113 Tons VOC / Day 

EmissCO = [21,569 LTOs / Year * 12.014 (lbs. CO / LTO)] 

EmissCO = 259,129.966 lbs. of CO / Year 

EmissCO = 0.3550 Tons CO / Day 

EmissNOx = [21,569 LTOs / Year * 0.065 (lbs. NOx / LTO)] 

EmissNOx = 1,401.985 lbs. of NOx / Year 

Emission 

Calculation 

Appendix B - Page Number:

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228

EmissNOx = 0.0019 Tons NOx / Day 

EmissSO2 = [21,569 LTOs / Year * 0.100 (lbs. SO2 / LTO)] 

EmissSO2 = 2,156.900 lbs. of SO2 / Year 

EmissSO2 = 0.0030 Tons SO2 / Day 

EmissPM = [21,569 LTOs / Year * 0.020 (lbs. PM / LTO)] 

EmissPM = 431.380 lbs. of PM / Year 

EmissPM = 0.0006 Tons PM / Day 

Sample Calculation – Air Taxi: 

This calculation is for Easton Airport/Newman Field in Talbot County. The airport had 4,557 

Air Taxi Aviation LTOs over a twelve month period. Performing step 1 Equations (above) the 

calculations were: 

EmissVOC = [L(AT) * EF(AT)HC]* CF (VOC/HC) 

EmissVOC = [(4,557 LTOs / Year * 1.234 (lbs. HC / LTO)] * 0.9914 (lbs. VOC / lbs. HC)))) 

EmissVOC = 5,574.9773 lbs. VOC / Year 

EmissVOC = 0.0076 Tons VOC / Day 

EmissCO = [4,557 LTOs / Year * 28.130 (lbs. CO / LTO)] 

EmissCO = 128,188.410 lbs. of CO / Year 

EmissCO = 0.1756 Tons CO / Day 

EmissNOx = [4,557 LTOs / Year * 0.158 (lbs. NOx / LTO)] 

EmissNOx = 720.006 lbs. of NOx / Year 

EmissNOx = 0.0010 Tons NOx / Day 

EmissSO2 = [4,557 LTOs / Year * 0.015 (lbs. SO2 / LTO)] 

EmissSO2 = 68.355 lbs. of SO2 / Year 

EmissSO2 = 0.0001 Tons SO2 / Day 

EmissPM = [4,557 LTOs / Year * 0.020 (lbs. PM / LTO)] 

EmissPM = 91.14 lbs. of PM / Year 

EmissPM = 0.0001 Tons PM / Day 

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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 information by aircraft operation type, ARMA used 

composite emission factors from Procedures for 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 calculate emissions from Andrews Air 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) EmissVOC = 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 Equations (above) the calculations were: 

EmissVOC = [L(AT) * EF(MA)HC] 

EmissVOC = [(63,852 LTOs / Year * 27.10 (lbs. VOC / LTO)] 

EmissVOC = 1,730,389.200 lbs. VOC / Year 

EmissVOC = 2.3704 Tons VOC / Day 

EmissCO = [63,852 LTOs / Year * 48.80 (lbs. CO / LTO)] 

EmissCO = 3,115,977.60 lbs. of CO / Year 

EmissCO = 4.2685 Tons CO / Day 

EmissNOx = [63,852 LTOs / Year * 9.160 (lbs. NOx / LTO)] 

EmissNOx = 584,884.32 lbs. of NOx / Year 

EmissNOx = 0.8012 Tons NOx / Day 

Method and 

Data Sources 

Emissions 

Calculation 

Appendix B - Page Number:

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230

EmissSO2 = [63,852 LTOs / Year * 1.430 (lbs. SO2 / LTO)] 

EmissSO2 = 91,308.36 lbs. of SO2 / Year 

EmissSO2 = 0.1251 Tons SO2 / Day 

EmissPM = [63,852 LTOs / Year * 15.23 (lbs. PM / LTO)] 

EmissPM = 972,465.96 lbs. of PM / Year 

EmissPM = 1.3321 Tons PM / Day 

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Appendix B - Page Number:

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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, which can exceed 1,000 feet in length. 

PM, SO2, NOx, CO, HC, CO2

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 Baltimore non-attainment area. 

E&K used the marine emission inventory guidance method outlined in Analysis of Commercial 

Marine Vessels Emissions and Fuel Consumption Data (EPA-450-R-00-002), February 2000, to 

calculate emissions from commercial marine vessels. The methodology 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 marine engine emission 

factors have been historically specified. All of these calculations are made by vessel type and class, 

with the type specifying whether the vessel is a tanker, passenger liner, etc, and the class specifying 

either the weight or horsepower range. 

This new methodology considers new information collected on marine vessels. The time-in-mode is a 

function of the particular port area 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 concern. One reason for a detailed reconsideration 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 addition, both the EPA and ARB have recently sponsored 

studies to calculate marine vessel emissions in the South Coast Air 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 vessel class and deadweight tonnage. 

Description 

Pollutants 

Method and 

Data Sources 

Appendix B - Page Number:

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233

• The time spent, by ship type, in each of four operating modes defines 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 document 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 (SO2 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 algorithms are presented in the table 

below: 

Pollutant Exponent (x) Intercept (b) Coefficient (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 kilowatt-hour are presented in the table below: 

Vessel Type Cruise Slow Cruise 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 14.4183 

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Vessel Type Cruise Slow Cruise 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 subtracted from the area source inventory. 

No controls are available for this source category. 

Point Source 

Adjustments 

Adjustment for 

Controls 

Appendix B - Page Number:

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235

Spatial 

Data for spatial allocation is not available for this source. E&K emissions inventory focused on 

the City of Baltimore and allotted the 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, 

TIME VCC, DWT, MODE = 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, number of calls per vessel type, deadweight tons per vessel type, and 

time in each mode per vessel type using Baltimore 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 

Calculation 

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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 based on the highway traffic data obtained from the 

Maryland State Highway Administration (SHA) 

The official highway vehicle emission 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 modeling data and has been documented by that 

organization under separate cover. 

In accordance with the standard methodology for the development of highway vehicle emissions 

inventories, all of the emissions estimates documented herein are based on emission factors 

developed using the United States Environmental Protection Agency's (U.S. EPA's) latest version of 

the MOBILE6 emissions factor model and using appropriate activity levels i.e., vehicle miles 

traveled (VMT) estimates developed from the highway 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 vehicle 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 grams 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 requires the correct expertise and tools to produce 

emissions based on the federal and state requirements. MDE used the PPSuite system, a robust, 

systematic, and comprehensive software approach to develop the on-road emissions for the state. 

This new post-processor, PPSUITE was used for the first time in 2003 by MSCP for the 2005 Mobile 

Emission Budget effort. However this software system has been in use in Pennsylvania, Virginia, 

New Jersey, and the New York City Metropolitan Area, for previous inventory and conformity 

submissions. PPSUITE is also compatible with travel demand modeled activity data and as such used 

in the Baltimore Area’s for transportation conformity analysis. The following table provides a 

summary of the emission process and various data inputs. 

Appendix B - Page Number:

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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 

Lanes 

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 

Network 

MOBILE6 

Highway Network 

Data

POSTMOBILE 

Process M6

PEQUESTR 

Create Reports

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 

parameters, etc.,

IM Parameters 

Vehicle Age 

VMT Seasonal Adjustments 

Emission Calculation Scheme 

A

 B 

C

D 

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6.2 EMISSION FACTORS 

The heart of the highway vehicle emission’s calculation 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 emission factors as referred to in the previous section. 

The first MOBILE model was developed as MOBILE1 in the late 1970s. It has been periodically 

updated to reflect the collection and analysis of additional emission factor data over the years. It also 

has been upgraded to capture changes in vehicle/engine/emission control system technologies, and 

changes in applicable regulations, emission standards and test procedures, and improved 

understanding of in-use emission levels 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 factors 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 future, which will facilitate future 

updates to the process. The process utilizes the PPSUITE post processor 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 and actually runs MOBILE6 model 

• Calculates emission quantities from output MOBILE6 emission rates and accumulated 

highway VMT. 

The PPSuite process utilizes a number of programs and operations assembled into a chain of jobs and 

steps. The management of these model chains and their operations can be difficult. At the front end, 

an interfacing software package called CENTRAL is deployed, providing MDE with the ability to 

efficiently manage the emission calculation process. 

6.4 KEY TRAVEL DATA INPUTS 

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This section describes the SHA data inputs to the emission calculation 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 obtained directly from SHA and is referred 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 requires 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 operations on data fields such as addition, deletion, 

renaming and field value modifications 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 vehicle types. The vehicle mixes are input to PPSUITE 

as hourly distributions of vehicles by vehicle type. The mixes 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 vehicle classifications by functional class for the years 1998 

through 2003. 

The PPSUITE input 2002 SHA vehicle mix file was prepared based on 4 input vehicle groups: 

• Vehicle Type 1 = Motorcycle 

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• 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 classes 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 obtain the percentage autos. Class 4 was used for 

buses. Truck percentages were obtained by combining classes 5 to 13. The PPSUITE postprocessor automatically splits the four input vehicle categories to the required 16 MOBILE6 vehicle 

classes by using the MOBILE6 defaults, which 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 estimate the pattern by which roadway volume varies by 

hour of the day. The hourly pattern distributions are not only input directly to MOBILE6, but are 

also a key input file to PPSUITE for estimating hourly congested speeds. 

Hourly mixes of vehicles for each area and facility type combination are input to PPSUITE. These 

are used to determine the proportion of the daily volume 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 table with the factors is obtained. 

For the ozone daily emission calculation process, 2002 hourly pattern data for the 4 primary 

functional classes was used to create the PPSUITE input files. An average factor was calculated for 3 

months – June, July and August to derive hourly percentage of vehicles for a summer weekday. For 

the annual emission computation process, average factors were calculated 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 (differences 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. 

Appendix B - Page Number:

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The adjustment factors are obtained by dividing the 2002 HPMS VMT by the 2002 analysis run 

VMT for each county functional class grouping. These 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 description 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 for each roadway segment for each hour of the day. 

Seasonal Adjustments and Temporal Allocation 

Highway vehicles contribute significantly to air pollution, particularly to ground-level ozone in the 

summer months. Ozone is not created directly, but it is formed in sunlight from VOCs and NOx. 

Both VOCs and NOx are emitted largely from highway vehicles. 

Even though other pollutants such as CO, NH3, SO2, PM2.5, and PM10 contribute to air pollution 

during summer also, but their significance is much more during the winter months. This is in 

accordance with the EPA’s guidance on preparation 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 analyses. The seasonal and monthly VMT 

adjustment factors were developed 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 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 table with the traffic 

flow data is obtained. 

The AADT percentage is available for 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 factor was obtained for 12 months 

by calculating an average factor for 3 weekdays, Tuesday, Wednesday and Thursday. The 

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calculations were repeated for all the 4 functional classes. These functional class groups were then 

mapped to the 12 functional classes used within the emission process. 

Average monthly adjustment factors were developed 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 vehicle and environmental parameters 

including: 

• Vehicle Mixes 

• Vehicle age distributions and 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 significant impact on emission levels, are generated on 

the go by the PPSuite system using from all the traffic related data such as highway network data, 

vehicle pattern file, vehicle 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 registration 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, atmospheric pressure, etc., were also developed by 

MSCP tapping 2002 data from appropriate agencies. 

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MOBILE modeling assumptions include selection of appropriate 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 matrix 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 model is then invoked and after the specific 

number of runs, the PostMOBILE module takes care of the emission aggregation process. 

Finally the reporting routine comes in and formats the 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 generated 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 PPSUITE that are used for all analysis 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. This 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. This 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) 

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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 equivalency between each link and the fields 

used for pattern (hourly and vehicle mix) indexing and output emission indexes. The file is required 

by PPSUITE and relates to the equivalency keyword 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 names. 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 Information – Other PPSUITE Inputs 

The speed-lookup table is a key file that has a significant impact on calculated 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 relationships (BPR coefficients) 

This dataset was developed through a speed calibration analysis utilizing SHA 2002 speed 

monitoring data. 

The remaining two databases are used in the VMT Mix computations. 

6.7 EMISSION PROCESS OUTPUTS 

After MOBILE model has been run, PPSUITE processes the MOBILE output files and compiles the 

emission factors for each scenario. Using the MOBILE emission factors, PPSUITE calculates 

emission estimates by multiplying the emission factors by the aggregated VMT totals. PPSUITE 

then produces an emissions database summarizing VMT, VHT, VOC, and NOx emissions. The 

output files are automatically output to individual county subdirectories 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 not 

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have to utilize these files; however, they may be useful for investigating potential errors that may 

occur in the process. 

The summary results of all the summertime and 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 and 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 emissions for all counties in MD except for 

the MD counties under the jurisdiction of MWCOG. 

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7.0 BIOGENIC EMISSIONS 

7.1 INTRODUCTION 

Biogenic sources, a subset of natural sources, include only those sources that result from some sort of 

biological activity. Biogenic emissions represent a significant portion of the natural source 

emissions, and VOC, NOx, and the greenhouse gases can be emitted from biogenic sources. 

Vegetation is the predominant biogenic source of VOC and is typically the only source that is used to 

estimate biogenic VOC emissions. Microbial activity is responsible for the emission of NOx and the 

greenhouse gases of CO2, CH4, and N2O. Soil microbial activity is responsible for NOx and N2O 

emissions from agricultural lands and grasslands. CH4 is emitted through microbial action in 

waterlogged soils or in other anaerobic microenvironments. CO2 is released through the aerobic decay 

of biomass (EPA, 1993; EPA,1990a). 

Biogenic emissions is one category that MDE is unable to control directly, 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 BEIS3117 that 

utilized county land use data from EPA’s land use inventory and National Weather Service first-order 

station data of temperature and cloud cover. However, due to the large 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-total estimates of 2002 biogenic emissions based on 

the BEIS3.12 model. The purpose of this spreadsheet is to provide default 2002 estimates to the 

states for the purpose of biogenic emissions submittals by county required by the Consolidated 

Emissions Reporting Rule (CERR). These estimates 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 emissions from SMOKE, calculated from 36-km 

gridded emissions using the "land area" spatial surrogate. This means that when calculating 

the county-total numbers, the 36-km gridded emissions were assumed to be uniformly 

distributed over the grid cell for purposes of mapping to the counties. 

Monthly emission estimates were given for each county 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.html

Appendix B - Page Number:

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• 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 mass accounted for by TERPB is also included 

in VOC 

The daily emissions were calculated by summing the monthly emissions from June, July, and August 

and dividing by the number of days in those three months (92). 

 

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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 the sensitivity analysis and range checks) will be 

performed by staff not involved in the inventory calculations. Several quality assurance checks will 

be employed to address the data quality objectives: reality/peer review checks, sample calculations, 

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 process, the inventory 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, and 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 reviewer expertise, and 3) comparison of emissions 

estimates to other inventory efforts, 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: 

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Ensure calculations are done correctly 

Accuracy 

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 PM10 

and CO contributors. 

Estimates calculated using computer models 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. 

8.3 SENSITIVITY ANALYSIS 

Systematic study of how changes in parameters affect data 

Identify the parameters that have 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 

Definition 

Appendix B - Page Number:

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Identify the source categories that have the greatest 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 PM10, 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 year and a given projection year greater 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 anticipation 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 the quality checking process will be noted and 

referred to the appropriate staff. Both the corrective actions identified and results of actions taken in 

response will be documented. 

8.6 QUALITY ASSURANCE FINAL REPORT 

The final inventory report will include discussions on inventory quality considerations for each major 

source category. It will summarize the results of the quality checking procedures 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) 

Limitations 

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9.0 RESPONSIBILITY 

The inventory process will be a cooperative effort among MDE-ARMA Air Quality Policy and 

Planning Program, MDE-ARMA Air Quality Compliance Program, MDE-ARMA Air Quality 

Permits Program, MDE-ARMA Mobile Source Control Program, Baltimore 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), Maryland State Highway Administration (SHA), and 

Metropolitan Washington Council of Governments (MWCOG). 

Metropolitan Washington Council of Governments will provide estimates of actual 2002 and 

projected 2010 and 2015 emission estimates for onroad 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 emissions to 2010 and 2015. Planning will perform the final 

QA review of the inventories. Finally, Planning will prepare the inventory documentation. 

MSCP, Compliance, and Planning will review all inventory products. 

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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 Model Methodology Description 10-22-2007 

• Added Chapters 7 & 8 10-23-2007 

• Added Introduction specific to PM SIP 10-24-2007 

Appendix B - Page Number:

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Attachment B4 

Airport Emissions 

(Metropolitan Washington Airports Authority) 

Appendix B - Page Number:

451
AIR POLLUTION EMISSION INVENTORIES FOR

WASHINGTON DULLES INTERNATIONAL AIRPORT

AND

RONALD REAGAN WASHINGTON NATIONAL AIRPORT

FOR

CALENDAR YEARS 2002, 2008, AND 2009 

Prepared for: 

Metropolitan Washington Airports Authority 

Washington, DC 

Prepared by: 

URS Corporation

Tampa, FL 

MARCH 2006 

Appendix B - Page Number:

452
Air Pollutant Emission Inventories for Washington 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 Metropolitan Washington Airports Authority (MWAA) to 

provide aircraft operations, GSE, and motor vehicle data 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” (which requires using site specific “ozone season” 

mixing height and temperature data) were also requested. 

Historical data and available forecasts of future year activity 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 pollutants 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 organic 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 (SO2) 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 inventories are aircraft, Ground 

Support Equipment (GSE), aircraft Auxiliary Power Units (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 include emissions from vehicles idling and moving around 

inside the parking facilities. 

For these analyses, emissions were calculated using the latest version of the FAA approved program 

EDMS1

 (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.

1 Appendix B - Page Number:

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Aircraft

Historical data and available forecasts of future year aircraft operations at each airport were used as the 

basis for the emissions inventory calculations. The 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 Metropolitan Washington Airports Authority (MWAA)3

, and data 

for the 2009 analysis were derived from the Draft Part 150 Study4

 prepared for DCA. 

TABLE 1 

ANNUAL OPERATIONS, ENPLANEMENTS, AND TAXI TIMES 

2002 2008 2009 

Washington Dulles International 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 22.021 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 18.121 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 aircraft 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 base5

. For the IAD analysis for 2009, the 

taxi/idle times were derived from the SIMMOD airfield operational analysis combined with measurements 

of aircraft taxiing distances at the airport under the alternative improvement plans6

 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 assumed to remain unchanged between 2004 and 2009. 

 

2

 Final Environmental Impact Statement for New Runways, Terminal Facilities and Related Facilities at Washington Dulles 

International Airport, Department of Transportation, Federal Aviation Administration, Washington Airports District Office, Dulles, 

VA. August 2005. 3

 Supporting Data – 2002 Emissions Inventory, Aircraft and Ground Support Equipment, Ronald Reagan Washington National 

Airport, Metropolitan Washington Airports Authority, 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 Runways at Washington Dulles International Airport – Final Report. 

HNTB, February 2002. 

2 Appendix B - Page Number:

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Consistent with FAA guidelines7

, 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 fleet, fuel types and operating times were derived 

from in-the-field surveys performed at the airport in February 20048

. Wherever necessary, these data 

were supplemented with information contained in the 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 assignments 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 air9

. Also in both analyses, EDMS default assignments for deicer trucks 

were included with the time-in-mode set to 1.510 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 shuttles between the Main Terminal and the midfield 

concourse. Emission rates and activity levels for 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 Lounges at IAD for 2008 and 2009 would be the same as 

in 2002 because the Mobile Lounges will not be replaced by the Automated People Mover that will 

connect the terminals until the latter half of 2009. Therefore, 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 internal 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 Roads11 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. Washington, 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 Transportation, 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. 

3 Appendix B - Page Number:

455
IAD Airport Layout Plan (ALP). Traffic volumes on the roadways for the DCA analysis were derived from 

traffic count data for 2003 supplied by HNTB12 and adjusted based on enplanements. Roadway travel 

distances were derived from scaled drawings of the DCA ALP. 

The motor vehicle engine emission factors were derived from the EPA mobile source emissions model, 

MOBILE 6.213. For the IAD analysis, Fairfax County-specific motor vehicle operating characteristics (i.e., 

fleet mix, emission control programs, operating temperatures, 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 obtained 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 analysis 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 200415 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 parking facility for 2002 were provided by MWAA16; 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 enplanements between 2002 and 2009. Vehicle volumes for the 

employee parking facilities for 2002 were developed from data collected at DCA in 200217; employee 

vehicle volumes for 2009 were derived from vehicle 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 guidelines7

, the operational emissions inventories for IAD and DCA were initially prepared 

for annual average conditions. However, the SIP for the Washington DC-MD-VA area is based on the 

management and control of Ozone precursors (i.e., NOx 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 Corporation, to A. Goldman, URS Corporation, December 2005. 13 Approved final version of MOBILE6.2 computer 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, Director, Office of Air Quality Planning and 

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/Employee Parking and 

Rental Car Facilities, HNTB Corporation, December 2004. 

4 Appendix B - Page Number:

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characteristics, the operational emission inventory results were recalculated to reflect these “Ozone 

Season” conditions. “Ozone Day” emissions are derived 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 accomplished by factoring in the effects of the lower 

atmospheric mixing height and higher ambient temperatures that are characteristic of the O3 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 International 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 Corporation, 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 guidelines7

 recommend using “real 

world” data whenever it is available, as in this case. 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 2002, 2009, and 2008 are provided in the tables below. 

Aircraft emissions for 2008 were estimated by adjusting the aircraft emissions calculated for 2009 by the 

difference in forecasted aircraft operations for 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 airport 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 difference 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 for 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, 

5 Appendix B - Page Number:

457
2009, 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. 

6 Appendix B - Page Number:

458
TABLE 3 

WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) 

ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 20021 

Pollutant Source

CO VOCs NOx PM2.5 PM10 SO2

Annual Emissions in Tons Per Year (tpy)

Aircraft2 1,205.3 257.1 864.3 23.33 23.33 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 Lounges5 3.6 6.1 125.1 2.7 2.7 6.7 

Onsite Motor Vehicles6 411.9 30.2 103.4 1.8 2.8 2.0 

Parking Facilities7 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 

Daily8 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 version 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 for IAD was used in the inventory. 3

 Results calculated in EDMS 4.4 for jet aircraft using the 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 onsite 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 included in the EDMS data files. 6

 Onsite motor vehicles include all roads located on the airport property, except for the portions of Route 28 (Sully 

Road), Route 606 (Old Ox Road), and the Dulles Greenway 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. 

7 Appendix B - Page Number:

459
TABLE 4 

WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) 

ESTIMATED OZONE DAY1 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2002 

IN TONS PER DAY (TPD) 

Pollutant (tpd)

Source CO VOCs NOx PM2.5 PM10 SO2

Aircraft2 3.28 0.70 2.24 0.063 0.063 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 Lounges5 0.01 0.02 0.34 0.01 0.01 0.02 

Onsite Motor Vehicles6 1.31 0.09 0.28 <0.01 0.01 0.01 

Parking Facilities7 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 the “Ozone Season” mixing height and “Ozone Season” 

temperature to calculate the “Ozone Year” 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 for IAD was used in the inventory. 3

 Results calculated in EDMS 4.4 for jet aircraft using the FAA’s First Order Approximation (FOA) method. Results 

also include a contribution of 0.04 tpd 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 onsite 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 included in the EDMS data files. 6

 Onsite motor vehicles include all roads located on the airport property, except for the portions of Route 28 (Sully 

Road), Route 606 (Old Ox Road), and the Dulles Greenway 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). 

8 Appendix B - Page Number:

460
TABLE 5 

WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) 

ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 20091 

Pollutant Source

CO VOCs NOx PM2.5 PM10 SO2

Annual Emissions in Tons Per Year (tpy)

Aircraft2 2,109.8 410.7 1,471.2 26.83 26.83 125.0 

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 Lounges5 3.6 6.1 125.1 2.7 2.7 6.7 

Onsite Motor Vehicles6 332.9 26.1 66.7 1.6 2.8 0.7 

Parking Facilities7 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 

Daily8 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 Version 4.4 and the latest version 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 account for having the crosswind taxiways in place. 3

 Results calculated in EDMS 4.4 for jet aircraft using the 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 onsite 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 included in the EDMS data files. 6

 Onsite motor vehicles include all roads located on the airport property, except for the portions of Route 28 (Sully 

Road), Route 606 (Old Ox Road), and the Dulles Greenway located on Airport property, and do NOT include 

emissions from vehicles idling at curbside or parking facility emissions. MOBILE6.2 emission factors for 2009 

were derived from files obtained from MWCOG accounting 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 Lot, 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 difference 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). 

9 Appendix B - Page Number:

461
TABLE 6 

WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) 

ESTIMATED OZONE DAY1

 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2009 

IN TONS PER DAY (TPD) 

Pollutant (tpd)

Source CO VOCs NOx PM2.5 PM10 SO2

Aircraft2 5.75 1.12 3.81 0.073 0.073 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 Lounges5 0.01 0.02 0.34 0.01 0.01 0.02 

Onsite Motor Vehicles6 0.88 0.08 0.18 <0.01 0.01 <0.01 

Parking Facilities7 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 the “Ozone Season” mixing height and “Ozone Season” 

temperature to calculate the “Ozone Year” 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 the FAA’s First Order Approximation (FOA) method. Results 

also include a contribution of 0.03 tpd 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 onsite 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 included in the EDMS data files. 6

 Onsite motor vehicles include all roads located on the airport property, except for the portions of Route 28 (Sully 

Road), Route 606 (Old Ox Road), and the Dulles Greenway located on Airport property, and do NOT include 

emissions from vehicles idling at curbside or parking facility emissions. MOBILE6.2 emission factors for 2009 

were derived from files obtained from MWCOG. 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 Lot, 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 difference in aircraft enplanements between 2010 and 2009. 

Source: EDMS, Version 4.4 (URS Corporation, 2006). 

10 Appendix B - Page Number:

462
TABLE 7

WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) 

ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008 

Pollutant Source

CO VOCs NOx PM2.5 PM10 SO2

Annual Emissions in Tons Per Year (tpy)

Aircraft1 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 Lounges3 3.6 6.1 125.1 2.7 2.7 6.7 

Onsite Motor Vehicles4 324.9 26.1 70.3 1.6 2.8 0.6 

Parking Facilities5 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 

Daily8 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 estimated 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 adjusting 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 estimated 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” category of MOBILE6.2 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 IAD between 2009 and 2008, and the 

difference in the “All Vehicles” category of MOBILE6.2 emission 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). 

11 Appendix B - Page Number:

463
TABLE 8 

WASHINGTON DULLES INTERNATIONAL AIRPORT (IAD) 

ESTIMATED OZONE DAY1

 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008 

IN TONS PER DAY (TPD) 

Pollutant (tpd)

Source CO VOCs NOx PM2.5 PM10 SO2

Aircraft2 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 Lounges4 0.01 0.02 0.34 0.01 0.01 0.02 

Onsite Motor Vehicles5 0.87 0.08 0.18 <0.01 0.01 <0.01 

Parking Facilities6 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 estimated 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 adjusting 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 estimated 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” category of MOBILE6.2 emission 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” category of MOBILE6.2 emission factors for each pollutant between 2009 and 

2008. 

Source: EDMS, Version 4.4 (URS Corporation, 2006). 

 

12 Appendix B - Page Number:

464
TABLE 9 

RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) 

ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 20021 

Pollutant Source

CO VOCs NOx PM2.5 PM10 SO2

Annual Emissions in Tons Per Year (tpy)

Aircraft2 512.4 55.8 477.6 9.13 9.13 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 Vehicles5 144.2 14.8 36.2 0.8 1.2 0.8 

Parking Facilities6 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 

Daily7 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 Version 4.4 and the latest version of MOBILE6.2, using 

activity levels for DCA for 2002. 2 A total of 215,691 annual operations were modeled for 2002. 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 2002 for DCA was used in the inventory. 3

 Results calculated in EDMS 4.4 for jet aircraft using the 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-mode 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 most of an airport’s gates are electrified. 5 Onsite motor vehicles include 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 volumes 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). 

13 Appendix B - Page Number:

465
TABLE 10 

RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) 

ESTIMATED OZONE DAY1

 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2002 

IN TONS PER DAY (TPD) 

Pollutant (tpd)

Source CO VOCs NOx PM2.5 PM10 SO2

Aircraft2 1.39 0.15 1.25 0.023 0.023 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 Vehicles5 0.45 0.04 0.10 <0.01 <0.01 <0.01 

Parking Facilities6 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 the “Ozone Season” mixing height and “Ozone Season” 

temperature to calculate the “Ozone Year” emissions and then dividing by 365. 2 A total of 215,691 annual operations were modeled for 2002. 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 the FAA’s First Order Approximation (FOA) method. Results 

also include a contribution of 0.01 tpd 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-mode 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 most of an airport’s gates are electrified. 5 Onsite motor vehicles include 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 volumes 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). 

14 Appendix B - Page Number:

466
TABLE 11 

RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) 

ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 20091 

Pollutant Source

CO VOCs NOx PM2.5 PM10 SO2

Annual Emissions in Tons Per Year (tpy)

Aircraft2 716.6 80.3 636.3 9.73 9.73 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 Vehicles5 100.9 11.3 22.7 0.6 1.0 0.3 

Parking Facilities6 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 

Daily7 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 Version 4.4 and the latest version 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 the 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-mode 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 most of an airport’s gates are electrified. 5 Onsite motor vehicles include 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 volumes 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). 

15 Appendix B - Page Number:

467
TABLE 12 

RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) 

ESTIMATED OZONE DAY1

 2009 ESTIMATED AIRPORT-RELATED AIR POLLUTANT EMISSIONS 

IN TONS PER DAY (TPD) 

Pollutant (tpd)

Source CO VOCs NOx PM2.5 PM10 SO2

Aircraft2 1.95 0.22 1.66 0.033 0.033 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 Vehicles5 0.27 0.03 0.06 <0.01 <0.01 <0.01 

Parking Facilities6 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 the “Ozone Season” mixing height and “Ozone Season” 

temperature to calculate the “Ozone Year” 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 the FAA’s First Order Approximation (FOA) method. Results 

also include a contribution of 0.01 tpd 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-mode 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 most of an airport’s gates are electrified. 5 Onsite motor vehicles include 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 volumes 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). 

16 Appendix B - Page Number:

468
TABLE 13 

RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) 

ANNUAL AND DAILY AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008

Pollutant Source

CO VOCs NOx PM2.5 PM10 SO2

Annual Emissions in Tons Per Year (tpy)

Aircraft1 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 Vehicles3 105.7 12.1 25.4 0.7 1.1 0.3 

Parking Facilities4 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 

Daily7 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 estimated 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 emissions for 2008 were estimated by adjusting the GSE 

emissions calculated for 2009 by the difference in forecasted aircraft operations at DCA between 2009 and 2008. 3

 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 DCA between 2009 and 2008, and 

the difference in the “All Vehicles” category of MOBILE6.2 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 MOBILE6.2 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). 

17 Appendix B - Page Number:

469
TABLE 14 

RONALD REAGAN WASHINGTON NATIONAL AIRPORT (DCA) 

ESTIMATED OZONE DAY1 AIRPORT-RELATED AIR POLLUTANT EMISSIONS FOR 2008 

IN TONS PER DAY (TPD) 

Pollutant (tpd)

Source CO VOCs NOx PM2.5 PM10 SO2

Aircraft2 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 Vehicles4 0.29 0.03 0.07 <0.01 <0.01 <0.01 

Parking Facilities5 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 estimated 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 emissions 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 estimated 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 MOBILE6.2 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 MOBILE6.2 emission factors for each pollutant between 2009 and 

2008. 

Source: EDMS, Version 4.4 (URS Corporation, 2006). 

18 Appendix B - Page Number:

470
Attachment B5 

Portable Fuel Container Calculation 

Methodology for Virginia 

Appendix B - Page Number:

471
From: Barnard, Bill [mailto:WRBARNARD@mactec.com] 

Sent: Tuesday, December 19, 2006 9:27 AM 

To: Sunil Kumar 

Cc: Ballou,Thomas; Foster,Thomas; Joan 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 (hopefully) 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 inventory 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 decrease 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. Additionally, 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) and 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 would be substantially below that if controls were in 

place. Also the discussion in the second paragraph discusses the controls in the future (as if they weren't 

implemented in the 2005 values), we took that as further 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 equal to the 2005 estimates given in the EPA report. 

Also we did NOT include the two amounts in the Refueling Equipment (Vapor Displacement and Spillage) 

in our estimates since those were already 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 

Appendix B - Page Number:

472
Attachment B6 

PM2.5, PM10, and SO2 Emissions 

Calculation Methodology for Virginia 

Appendix B - Page Number:

473
BY 2002 PM2.5, PM10, and SO2 Emissions Calculation Methodology for Virginia

VISTAS used a factor (NOx / Pollutant) to calculate emissions 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 

Appendix B - Page Number:

474
Attachment C1 

BY 2002 Area and Nonroad Source 

Emissions Summary 

Appendix B - Page Number:

475
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

PM2.5

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Mana

Ci

Area Source

2102002000 Coal Consumption 213.62 21.66 13.59 106.06 1.01 2.17 34.42 21.46 2102004000 Fuel Oil Consumption 11.59 0.73 0.88 1.43 1.38 0.73 0.46 3.56 0.03 0.07 1.15 0.72 

2102005000 Fuel Oil Consumption 22.39 4.31 5.20 5.18 5.04 0.27 0.17 1.31 0.01 0.03 0.43 0.27 2102006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

184.71 18.73 11.76 91.71 0.87 1.87 29.76 18.56 

2102007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

18.98 1.92 1.21 9.43 0.09 0.19 3.06 1.91 

2103002000 Coal Consumption 26.30 8.80 2.04 4.08 6.12 2.04 0.51 0.30 1.72 0.06 0.05 0.25 0.26 2103004000 Fuel Oil Consumption 187.21 44.90 3.85 4.64 7.47 7.28 18.72 11.22 63.48 2.26 1.82 9.32 9.60 

2103005000 Fuel Oil Consumption 12.34 0.32 0.39 0.43 0.41 1.70 1.02 5.76 0.20 0.16 0.84 0.87 

2103006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

196.60 65.67

0.84 1.82 22.73 21.84

13.16 7.89 44.62 1.59 1.28 6.55 6.75 

2103007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

0.49

0.07 0.10 0.15 0.17

2103011000 Fuel Oil Consumption 1.66 0.28 0.33 0.53 0.51 2104002000 Coal Consumption 14.82 2.42 0.00 0.33 0.33 0.35 1.15 0.78 5.98 0.14 0.06 1.18 1.82 

2104004000 Fuel Oil Consumption 122.16 9.30 6.77 8.16 13.17 12.81 7.27 4.96 37.72 0.87 0.39 7.45 11.48 

2104006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

430.25 58.66

2.48 5.52 67.34 59.77

23.89 16.32 123.99 2.86 1.30 24.48 37.75 

2104007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

2.82 0.02

0.39 0.58 0.87 0.96

2104008001 Other Fuels Consumption (Residential 

Wood Burning)

301.44 13.14

18.73 42.61 61.73 91.62

14.31 2.00 36.47 2.20 1.16 4.82 9.44 

2104008002 Other Fuels Consumption (Residential 

Wood Burning)

711.00 39.36 73.57 10.30 398.33 11.32 5.95 52.56 103.14 

2104008003 Other Fuels Consumption (Residential 

Wood Burning)

28.22 1.56 2.92 0.41 15.81 0.45 0.24 2.09 4.09 

2104008004 Other Fuels Consumption (Residential 

Wood Burning)

11.86 0.66 1.23 0.17 6.64 0.19 0.10 0.88 1.72 

2104008010 Other Fuels Consumption (Residential 

Wood Burning)

1973.22 28.14

53.03 104.87 233.71 382.83

63.75 8.92 768.39 9.81 5.16 101.39 198.96 

2104008030 Other Fuels Consumption (Residential 

Wood Burning)

51.29 0.47

2.14 4.24 9.45 15.48

1.07 0.15 12.81 0.16 0.08 1.69 3.31 

2104008050 Other Fuels Consumption (Residential 

Wood Burning)

114.92 1.12

4.61 9.12 20.32 33.29

2.53 0.36 30.50 0.39 0.20 4.02 7.89 

2104008053

Other Fuels Consumption (Residential Wood Burning)

4.83

1.11 2.57 0.49 0.66

2104008060

Other Fuels Consumption (Residential Wood Burning)

25.77

5.94 13.85 2.54 3.44

2104008070 Other Fuels Consumption (Residential 

Wood Burning; Outdoor Equipment)

226.69

17.06 28.36 95.14 86.13

2104009000

Other Fuels Consumption (Residential Firelog)

30.00

2.62 5.95 8.63 12.80

2104011000 Fuel Oil Consumption 2.89 0.48 0.58 0.93 0.90 2199008000

Stationary Source Fuel Combustion (Wood Burning)

6.01

1.38 3.23 0.59 0.80

2294000000 Mobile: All Paved Roads - Total: 

Fugitives

854.01

135.54 144.27 128.61 78.22

18.13 14.59 154.37 3.25 0.84 91.36 78.70 

2296000000 Mobile: All Unpaved Roads - Total: 

Fugitives

353.56

2.50 12.18 6.95 6.17

73.41 98.67 153.69 

2302002100 Commercial Cooking 79.03 26.08 2.71 5.66 23.96 20.62 

2302002200 Commercial Cooking 547.50 188.69 18.39 34.75 173.54 132.14 2302003100

Industrial Processes (Commercial Cooking - Flat Griddle Frying)

72.49

3.70 7.25 35.36 26.17

2302003200

Industrial Processes (Commercial Cooking - Clamshell Griddle Frying)

5.94

0.29 0.57 2.67 2.40

2311010000 Total Residential Construction: SIC 15

- 17

112.75

6.10 6.40 15.73 10.81

0.55 3.27 17.47 0.25 0.01 39.92 11.23 

2311020000 Total 

Industrial/Commercial/Institutional Construction: SIC 15 - 17

833.09

6.77 28.98 253.12 145.05

21.53 20.99 195.51 7.56 14.15 108.73 13.72 

2311030000 Total Road Construction: SIC 15 - 17 1438.33 96.95 104.07 330.62 169.03 5.33 24.79 158.64 2.91 0.07 415.23 119.37 

2325000000 Industrial Processes: Mining and 

Quarrying: SIC 14 - All Processes

293.94 48.99 48.99 48.99 48.99 48.99 48.99 

2401001000 Surface Coating - Architectural 431.52 431.52 2401005000 Surface Coating - Automobile 

Refinishing

6.08 6.08 

2601000000 On-Site Incineration 25.95 0.00 11.90 12.50 1.55 2601010000 On-Site Incineration 41.04 4.16 2.61 20.40 0.18 0.41 6.61 4.13 2601020000 On-Site Incineration 95.03 9.60 6.55 49.83 1.15 0.52 9.84 15.17 

2610000100 Open Burning 24.76 4.72 8.23 4.89 0.17 6.75 

2610000400 Open Burning 14.80 3.14 5.47 3.25 0.00 2.94 

2610000500 Open Burning 6293.71 250.37 571.01 1632.54 613.17 67.48 125.17 1539.75 34.14 741.77 642.88 

C1-1

Appendix B - Page Number:476
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

PM2.5

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Mana

Ci

2610030000 Open Burning 33.40 10.98 18.02 4.40 0.00 

2801000003 Crops Tilling 575.47 62.28 233.25 81.31 28.08 3.11 150.94 16.51 2805001000 Livestock, beef cattle, feedlots, Dust 

Kicked-up by Hooves

60.00 5.06 45.51 9.43 

2810001000 Forest Fires 27.21 12.55 2.49 7.84 3.88 0.08 0.38 

2810015000 Slash/Prescribed Burning 117.65 0.00 1.77 0.00 0.00 0.65 0.01 0.01 32.41 42.14 40.60 

2810030000 Structure Fires 38.05 6.08 0.94 1.25 1.75 8.79 4.77 3.11 3.58 0.05 0.26 0.31 6.69 

2810050000 Motor Vehicle Fires 21.71 1.00 1.31 3.72 15.68 

2002 Area Source Total 17331.09 932.67 749.87 1444.49 3282.02 2003.10 449.64 342.07 4066.81 98.85 72.68 2096.12 1601.48 

Nonroad Model SourceAgricultural Equipment 59.09 0.00 4.67 24.86 9.04 3.54 0.00 0.00 0.41 0.00 0.00 13.21 3.36 Airport Equipment 21.52 0.00 0.00 0.00 0.01 0.00 10.30 0.00 5.60 0.00 0.00 5.60 0.00 

Commercial Equipment 102.03 8.78 1.97 6.06 22.81 17.42 2.46 3.18 26.30 1.50 0.49 5.15 3.99 

Construction and Mining Equipmen 1340.70 242.82 50.22 60.27 169.59 193.67 119.84 0.00 192.90 0.00 0.00 185.09 126.29 

Industrial Equipmen 116.61 13.81 2.78 8.97 23.90 20.14 3.37 3.06 23.85 0.58 0.33 6.68 6.56 Lawn and Garden Equipment (Com) 538.14 1.78 5.81 35.35 139.61 68.21 6.47 8.58 144.10 5.08 3.47 76.13 38.96 

Lawn and Garden Equipment (Res 74.42 11.32 1.94 3.23 14.33 12.83 3.81 2.77 15.45 0.32 0.20 3.08 4.48 

Logging Equipment 2.56 0.00 1.17 0.16 0.12 0.48 0.00 0.00 0.08 0.00 0.00 0.47 0.08 

Pleasure Craft 41.85 7.70 16.53 1.85 4.63 5.25 0.00 0.00 3.13 0.00 0.00 0.39 2.37 

Railroad Equipment 2.63 0.16 0.01 0.51 0.33 0.22 0.06 0.21 0.41 0.00 0.00 0.00 0.56 

Recreational Equipment 31.40 1.61 4.24 4.35 8.66 4.32 0.03 0.00 3.55 0.02 0.00 1.18 3.44 

Nonroad Model Source 2330.96 287.98 89.34 145.62 393.03 326.06 146.35 17.80 415.81 7.51 4.49 296.98 190.08 

Other Nonroad Sources

2275001000 Military Aviation 52.84 7.62 2.76 0.00 9.97 23.13 9.38 2275020000 Commercial Aviation 32.40 0.00 0.00 0.00 0.00 9.10 11.65 11.65 

2275050000 General Aviation 10.96 0.13 1.55 0.73 0.84 3.27 0.51 2275060000 Air Taxi 0.20 0.00 0.02 0.06 0.01 0.02 

2275070000 Aircraft Auxiliary Power Units 0.11 0.01 0.05 0.05 

2285002005 Railroad Locomotives 142.01 0.00 9.21 7.23 5.70 0.37 16.12 51.33 

2285002006 Railroad Locomotives 1.89 1.89 

2285002008 Railroad Locomotives 1.94 1.94 

2285002009 Railroad Locomotives 1.58 1.58 

2285002010 Railroad Locomotives 43.42 5.32 0.00 6.08 1.52 0.00 0.09 4.10 13.06 

Other Nonroad Sources Total 287.35 10.73 19.61 9.53 16.51 9.11 9.11 0.46 55.05 0.00 0.00 14.99 74.27 

2002 Nonroad Source Total 2618.31 298.71 108.95 155.15 409.54 335.17 155.46 18.26 470.86 7.51 4.49 311.97 264.36 

C1-2

Appendix B - Page Number:477
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Nitrogen Oxides (NOx)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City

Fairfax 

County

Fairfax 

City

Falls 

Church 

City

Loudoun 

County

Prince 

William 

County

Ma

Area Source

2102002000 Coal Consumption 1979.90 200.75 125.99 982.97 9.38 20.09 318.98 198.93 

2102004000 Fuel Oil Consumption 227.15 1.92 9.43 11.36 18.32 17.83 17.06 10.71 83.55 0.80 1.71 27.11 16.91 

2102005000 Fuel Oil Consumption 215.55 17.32 20.88 33.68 32.77 11.24 7.06 55.06 0.53 1.13 17.87 11.14 

2102006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

566.84 57.47 36.07 281.43 2.69 5.75 91.32 56.95 

2102007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

32.37 0.15 3.27 2.05 16.00 0.15 0.33 5.19 3.24 

2103002000 Coal Consumption 210.17 33.00 4.29 8.58 12.87 4.29 23.14 13.87 78.44 2.79 2.25 11.51 11.86 

2103004000 Fuel Oil Consumption 872.86 134.44 36.12 43.54 70.21 68.33 81.81 49.03 277.34 9.87 7.96 40.71 41.93 

2103005000 Fuel Oil Consumption 152.90 2.74 3.30 5.33 5.19 21.44 12.85 72.68 2.59 2.09 10.67 10.99 

2103006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

2534.53 650.64

10.33 22.54 281.13 270.16

204.39 122.50 692.90 24.67 19.89 101.71 104.76 

2103007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

77.25

1.74 2.59 3.88 4.28

10.18 6.10 34.52 1.23 0.99 5.07 5.22 

2103007005 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

0.15 0.15 

2103011000 Fuel Oil Consumption 15.53 2.57 3.10 5.00 4.86 

2104002000 Coal Consumption 17.40 4.55 0.00 0.62 0.62 0.67 1.10 0.75 5.74 0.13 0.06 1.13 1.75 

2104004000 Fuel Oil Consumption 999.49 136.79 57.24 69.00 111.28 108.29 52.21 35.66 270.98 6.27 2.83 53.52 82.51 

2104006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

3212.34 669.70

30.61 68.21 832.86 739.21

88.05 60.14 457.01 10.57 4.78 90.26 139.15 

2104007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

308.50 0.23

9.82 14.63 21.97 24.22

24.00 16.39 124.58 2.88 1.30 24.60 37.93 

2104008000 Other Fuels Consumption 

(Residential Wood Burning)

192.92 17.02 11.62 88.33 2.04 0.92 26.23 40.43 

2104008001 Other Fuels Consumption 

(Residential Wood Burning)

21.79 1.45

1.78 4.04 5.85 8.68

2104008002 Other Fuels Consumption 

(Residential Wood Burning)

3.60 3.60 

2104008004 Other Fuels Consumption 

(Residential Wood Burning)

0.06 0.06 

2104008010 Other Fuels Consumption 

(Residential Wood Burning)

61.23 2.57

4.02 7.94 17.70 29.00

2104008030 Other Fuels Consumption 

(Residential Wood Burning)

3.79 0.05

0.26 0.51 1.13 1.85

2104008050

Other Fuels Consumption (Residential Wood Burning)

10.22

0.70 1.38 3.08 5.05

2104008053

Other Fuels Consumption (Residential Wood Burning)

6.00

1.38 3.19 0.60 0.82

2104008060

Other Fuels Consumption (Residential Wood Burning)

1.94

0.45 1.04 0.19 0.26

2104008070 Other Fuels Consumption 

(Residential Wood Burning; Outdoor Equipment)

71.55 54.52

1.28 2.13 7.15 6.47

2104009000 Other Fuels Consumption 

(Residential Firelog)

4.02

0.35 0.80 1.16 1.72

2104011000 Fuel Oil Consumption 24.49 4.05 4.89 7.88 7.67 

2199008000

Stationary Source Fuel Combustion (Wood Burning)

0.40

0.09 0.22 0.04 0.05

2601000000 On-Site Incineration 961.45 0.26 5.78 937.51 17.90 2601010000 On-Site Incineration 23.02 2.33 1.46 11.43 0.11 0.23 3.71 2.31 

2601020000 On-Site Incineration 148.82 15.03 10.27 78.02 1.80 0.82 15.41 23.75 

2601030000 On-Site Incineration 7.63 0.77 0.53 4.00 0.09 0.04 0.79 1.22 2610000100 Open Burning 5.08 1.33 2.32 1.38 0.05 

2610000400 Open Burning 3.90 1.03 1.80 1.07 0.00 2610000500 Open Burning 73.64 73.64 2610020000 Open Burning 879.51 167.94 480.16 180.34 28.20 15.96 6.92 2610030000 Open Burning 3.85 3.85 2620030000 Municipal Solid Waste Landfills 8.03 6.32 1.54 0.00 0.17 2810001000 Forest Fires 6.42 2.95 0.59 1.85 0.91 0.02 0.10 2810015000 Slash/Prescribed Burning 0.36 0.00 0.00 0.00 0.00 0.00 0.04 0.32 2810030000 Structure Fires 6.42 0.87 0.13 0.18 0.25 1.25 0.92 0.60 0.70 0.01 0.05 0.07 1.29 

2810050000 Motor Vehicle Fires 0.95 0.04 0.06 0.16 0.69 

2002 Area Source Total 13954.02 1694.70 279.80 479.47 2865.86 1542.81 832.19 523.66 3643.91 78.61 73.22 862.01 799.62 Nonroad Model SourceAgricultural Equipment 501.93 0.00 39.68 211.20 76.82 30.03 0.00 0.00 3.50 0.00 0.00 112.17 28.53 

C1-3

Appendix B - Page Number:478
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Nitrogen Oxides (NOx)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City

Fairfax 

County

Fairfax 

City

Falls 

Church 

City

Loudoun 

County

Prince 

William 

County

Ma

Airport Equipment 467.78 0.00 0.00 0.05 0.10 0.01 134.00 0.00 166.75 0.00 0.00 166.75 0.00 Commercial Equipment 1288.28 109.31 24.87 76.56 288.26 220.21 31.11 40.27 332.67 18.99 6.22 65.16 50.42 

Construction and Mining Equipment 14147.82 2547.39 530.65 636.83 1791.96 2046.47 1266.24 0.00 2038.18 0.00 0.00 1955.68 1334.41 

Industrial Equipment 2442.55 271.98 48.43 259.69 515.00 401.35 41.68 58.46 465.85 12.51 8.21 168.95 109.67 

Lawn and Garden Equipment (Com) 2775.22 9.16 29.97 182.22 719.71 351.64 33.35 44.23 742.90 27.17 17.88 392.47 200.83 

Lawn and Garden Equipment (Res) 495.26 75.30 12.87 21.52 95.32 85.32 25.37 18.40 102.80 2.31 1.30 20.50 29.83 

Logging Equipment 27.06 0.00 12.33 1.73 1.32 5.02 0.00 0.00 0.84 0.00 0.00 5.00 0.82 

Pleasure Craft 219.35 43.41 112.10 5.97 14.93 16.92 0.00 0.00 13.54 0.00 0.00 1.36 11.13 Railroad Equipment 18.88 1.16 0.04 3.68 2.39 1.57 0.46 1.54 2.98 0.00 0.00 0.00 4.01 Recreational Equipment 77.07 8.49 6.28 9.90 18.71 8.81 1.08 0.00 11.65 0.72 0.00 3.76 7.67 Nonroad Model Source 22461.20 3066.20 817.22 1409.34 3524.52 3167.34 1533.29 162.89 3881.66 61.71 33.62 2891.80 1777.32 Other Nonroad Sources

2275001000 Military Aviation 50.69 4.58 1.66 6.00 26.82 11.64 

2275020000 Commercial Aviation 1341.90 477.60 432.15 432.15 

2275050000 General Aviation 14.67 0.41 5.02 2.36 2.73 1.76 0.27 

2275060000 Air Taxi 0.89 0.02 0.14 0.44 0.06 0.04 

2275070000 Aircraft Auxiliary Power Units 53.10 7.30 22.90 22.90 

2285002005 Railroad Locomotives 1861.54 341.60 268.22 211.36 3.18 139.99 445.42 2285002006 Railroad Locomotives 95.00 95.00 

2285002008 Railroad Locomotives 89.73 89.73 

2285002009 Railroad Locomotives 73.31 73.31 

2285002010 Railroad Locomotives 680.08 211.40 167.90 41.98 0.79 34.82 110.80 

Other Nonroad Sources Total 4260.91 469.44 5.00 516.32 313.00 220.14 484.90 3.97 656.68 0.00 0.00 456.84 568.12 

2002 Nonroad Source Total 26722.11 3535.64 822.23 1925.66 3837.51 3387.49 2018.19 166.87 4538.34 61.71 33.62 3348.65 2345.44 

C1-4

Appendix B - Page Number:479
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Sulfur Dioxide (SO2)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Ma

Area Source

2102002000 Coal Consumption 8159.05 20.36 24.54 39.58 38.52 814.80 511.35 3989.72 38.08 81.56 1294.69 807.43 

2102004000 Fuel Oil Consumption 423.15 100.17 120.74 97.36 94.75 1.03 0.64 5.03 0.05 0.10 1.63 1.02 

2102005000 Fuel Oil Consumption 146.37 14.84 9.31 72.69 0.69 1.48 23.58 14.71 

2102006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

4.47 0.45 0.28 2.22 0.02 0.05 0.72 0.45 

2103002000 Coal Consumption 892.14 114.00 34.83 69.66 104.49 34.83 84.03 50.36 284.86 10.14 8.18 41.82 43.07 2103004000 Fuel Oil Consumption 475.78 78.02 94.04 151.66 147.59 0.70 0.42 2.39 0.08 0.07 0.35 0.36 

2103005000 Fuel Oil Consumption 629.88 15.85 19.11 15.41 14.99 88.80 53.22 301.02 10.69 8.61 44.15 45.48 2103006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

15.57 3.90

0.07 0.14 1.79 1.72

1.25 0.75 4.23 0.15 0.12 0.62 0.64 

2103007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

0.02

0.00 0.00 0.01 0.01

2103011000 Fuel Oil Consumption 33.53 5.55 6.69 10.79 10.50 2104002000 Coal Consumption 29.70 15.50 0.00 4.24 4.24 4.54 0.12 0.08 0.62 0.01 0.01 0.12 0.19 

2104004000 Fuel Oil Consumption 1181.53 323.74 137.39 165.61 267.07 259.90 2.81 1.92 14.58 0.34 0.15 2.88 4.44 2104006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

20.16 4.27

0.20 0.44 5.32 4.72

0.53 0.36 2.74 0.06 0.03 0.54 0.83 

2104007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

0.11 0.00

0.01 0.02 0.03 0.04

2104008001 Other Fuels Consumption (Residential 

Wood Burning)

5.54 0.22 0.24 0.56 0.81 1.20 0.49 0.07 1.24 0.07 0.04 0.16 0.33 

2104008002 Other Fuels Consumption (Residential 

Wood Burning)

9.30 0.51 0.96 0.13 5.21 0.15 0.08 0.69 1.35 

2104008003 Other Fuels Consumption (Residential 

Wood Burning)

0.56 0.03 0.06 0.01 0.32 0.01 0.04 0.08 

2104008004 Other Fuels Consumption (Residential 

Wood Burning)

0.21 0.01 0.02 0.13 0.02 0.03 

2104008010 Other Fuels Consumption (Residential 

Wood Burning)

20.25 0.37 0.31 0.62 1.38 2.27 0.83 0.11 10.05 0.13 0.07 1.32 2.60 

2104008030 Other Fuels Consumption (Residential 

Wood Burning)

1.12 0.01 0.05 0.10 0.23 0.37 0.02 0.25 0.03 0.06 

2104008050 Other Fuels Consumption (Residential 

Wood Burning)

2.76 0.02 0.12 0.24 0.54 0.89 0.05 0.01 0.62 0.01 0.08 0.16 

2104008053 Residential Wood Combustion: NonCatalytic Woodstoves: Pellet Fired 0.50 0.12 0.27 0.05 0.07 

2104008060 Residential Wood Combustion - 

Outdoor Boilers & Furnaces

0.30 0.07 0.16 0.03 0.04 

2104009000 Residential Firelog: 'Total: All

Combustor Types

2.59 0.23 0.51 0.74 1.10 

2104008070 Other Fuels Consumption (Residential 

Wood Burning; Outdoor Equipment)

3.47 0.85 0.20 0.33 1.10 1.00 

2199008000 Total Area Source Fuel Combustion:

Wood - All Boiler Types

0.44

0.10 0.24 0.04 0.06

2104011000 Fuel Oil Consumption 58.77 9.73 11.73 18.91 18.40 2601000000 On-Site Incineration 88.96 0.18 2.96 84.26 1.56 2601010000 On-Site Incineration 20.50 2.08 1.30 10.19 0.09 0.21 3.30 2.06 2601020000 On-Site Incineration 104.42 10.55 7.20 54.76 1.26 0.57 10.81 16.67 

2610000100 Open Burning 0.62 0.16 0.28 0.17 0.01 

2610000400 Open Burning 1.29 0.34 0.60 0.35 0.00 

2610030000 Open Burning 1.96 0.64 1.06 0.26 0.00 

2810001000 Forest Fires 0.03 0.01 0.03 2810015000 Slash/Prescribed Burning 0.51 0.14 0.19 0.18 

2002 Area Source Total 12335.56 463.44 404.95 524.89 806.62 639.06 1024.42 637.52 4763.01 62.04 101.32 1427.74 942.17 

Nonroad Model SourceAgricultural Equipment 51.00 0.00 4.03 21.46 7.81 3.05 0.00 0.00 0.36 0.00 0.00 11.40 2.90 Airport Equipment 46.03 0.00 0.00 0.00 0.01 0.00 19.40 0.00 13.30 0.00 0.00 13.30 0.00 

Commercial Equipment 88.82 7.96 1.71 5.25 19.78 15.11 2.13 2.76 22.81 1.30 0.43 4.47 3.46 Construction and Mining Equipmen 1629.93 311.46 60.31 72.38 203.66 232.59 143.92 0.00 231.65 0.00 0.00 222.28 151.67 

Industrial Equipmen 142.42 17.83 3.36 10.94 28.96 24.37 4.05 3.71 28.91 0.70 0.41 8.12 7.91 Lawn and Garden Equipment (Com) 140.17 0.46 1.51 9.20 36.35 17.76 1.68 2.23 37.52 1.37 0.90 19.82 10.14 

Lawn and Garden Equipment (Res 14.01 1.91 0.37 0.62 2.75 2.46 0.73 0.53 2.96 0.07 0.04 0.59 0.86 Logging Equipment 3.41 0.00 1.55 0.22 0.17 0.63 0.00 0.00 0.11 0.00 0.00 0.63 0.10 

Pleasure Craft 14.35 2.84 7.49 0.37 0.93 1.05 0.00 0.00 0.87 0.00 0.00 0.09 0.72 

Railroad Equipment 1.87 0.12 0.00 0.36 0.24 0.15 0.05 0.15 0.29 0.00 0.00 0.00 0.39 

Recreational Equipment 3.61 0.52 0.36 0.45 0.88 0.43 0.03 0.00 0.44 0.02 0.00 0.14 0.34 Nonroad Model Source 2135.61 343.11 80.70 121.27 301.53 297.60 171.99 9.38 339.23 3.46 1.77 280.84 178.49 Other Nonroad Sources

2275001000 Military Aviation 49.74 0.72 0.26 0.00 0.94 4.70 43.13 

2275020000 Commercial Aviation 117.60 0.00 0.00 0.00 0.00 45.70 35.95 35.95 

2275050000 General Aviation 16.31 0.63 7.73 3.63 4.20 0.05 0.01 

2275060000 Air Taxi 0.12 0.00 0.01 0.04 0.01 0.01 

C1-5

Appendix B - Page Number:480
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Sulfur Dioxide (SO2)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Ma

2275070000 Aircraft Auxiliary Power Units 7.30 1.00 3.15 3.15 2285002005 Railroad Locomotives 395.69 0.00 24.94 19.58 15.43 1.03 45.17 143.74 2285002006 Railroad Locomotives 6.36 6.36 2285002008 Railroad Locomotives 6.55 6.55 2285002009 Railroad Locomotives 5.35 5.35 2285002010 Railroad Locomotives 92.47 15.09 0.00 11.98 3.00 0.00 0.19 8.40 26.72 

Other Nonroad Sources Total 697.49 33.35 1.34 44.92 26.25 20.57 46.70 1.22 97.37 0.00 0.00 39.16 213.60 

2002 Nonroad Source Total 2833.10 376.46 82.04 166.19 327.78 318.18 218.69 10.60 436.60 3.46 1.77 320.00 392.09 

C1-6

Appendix B - Page Number:481
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Volatile Organic Compounds (VOC)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City

Fairfax 

County

Fairfax 

City

Falls 

Church 

City

Loudoun 

County

Prince 

William 

County

Manas

Cit

Area Source

2102002000 Coal Consumption 157.23 15.94 10.00 78.06 0.75 1.60 25.33 15.80 

2102004000 Fuel Oil Consumption 2.26 0.02 0.09 0.11 0.18 0.18 0.17 0.11 0.84 0.01 0.02 0.27 0.17 2102005000 Fuel Oil Consumption 1.10 0.09 0.11 0.17 0.17 0.06 0.04 0.28 0.00 0.01 0.09 0.06 2102006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

11.27 1.14 0.72 5.60 0.05 0.11 1.82 1.13 

2102007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

0.85 0.01 0.09 0.05 0.42 0.00 0.01 0.14 0.09 

2103002000 Coal Consumption 22.67 0.15 0.34 0.68 1.02 0.34 3.17 1.90 10.73 0.38 0.31 1.58 1.62 

2103004000 Fuel Oil Consumption 14.18 1.63 0.61 0.74 1.19 1.16 1.39 0.83 4.71 0.17 0.14 0.69 0.71 2103005000 Fuel Oil Consumption 3.15 0.06 0.07 0.11 0.11 0.44 0.26 1.49 0.05 0.04 0.22 0.23 2103006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

119.72 35.79

0.60 1.32 16.45 15.81

7.82 4.69 26.52 0.94 0.76 3.89 4.01 

2103007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

2.76

0.06 0.09 0.14 0.15

0.36 0.22 1.23 0.04 0.04 0.18 0.19 

2103007005 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

0.01 0.01 

2103011000 Fuel Oil Consumption 0.25 0.04 0.05 0.08 0.08 

2104002000 Coal Consumption 19.12 5.00 0.00 0.68 0.68 0.73 1.21 0.83 6.30 0.15 0.07 1.24 1.92 

2104004000 Fuel Oil Consumption 39.59 5.42 2.27 2.73 4.41 4.29 2.07 1.41 10.73 0.25 0.11 2.12 3.27 2104006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

204.28 39.18

1.79 3.99 48.73 43.25

6.80 4.65 35.30 0.82 0.37 6.97 10.75 

2104007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

11.02 0.01

0.35 0.52 0.78 0.86

0.86 0.59 4.45 0.10 0.05 0.88 1.35 

2104008000 Other Fuels Consumption (Residential 

Wood Burning)

10074.87 888.65 607.03 4612.64 106.67 48.24 1369.57 2111.47 2

2104008001 Other Fuels Consumption (Residential 

Wood Burning)

259.78 127.46

11.55 26.26 38.05 56.47

2104008002 Other Fuels Consumption (Residential 

Wood Burning)

68.18 68.18 

2104008003 Other Fuels Consumption (Residential 

Wood Burning)

0.96 0.96 

2104008004 Other Fuels Consumption (Residential 

Wood Burning)

0.48 0.48 

2104008010 Other Fuels Consumption (Residential 

Wood Burning)

889.40 48.74

57.57 113.84 253.69 415.57

2104008030 Other Fuels Consumption (Residential 

Wood Burning)

32.53 0.34

2.20 4.36 9.71 15.91

2104008050 Other Fuels Consumption (Residential 

Wood Burning)

91.25 0.68

6.20 12.26 27.33 44.77

2104008053

Other Fuels Consumption (Residential Wood Burning)

0.06

0.01 0.03 0.01 0.01

2104008060

Other Fuels Consumption (Residential 

Wood Burning)

170.57

39.29 91.68 16.80 22.79

2104008070 Other Fuels Consumption (Residential 

Wood Burning; Outdoor Equipment)

1986.29 485.96

112.89 187.73 629.66 570.05

2104009000

Other Fuels Consumption (Residential Firelog)

21.04

1.84 4.18 6.05 8.98

2104011000 Fuel Oil Consumption 0.96 0.16 0.19 0.31 0.30 

2199008000

Stationary Source Fuel Combustion (Wood Burning)

2.55

0.59 1.37 0.25 0.34

2275900000 Aircraft Refueling 36.74 0.23 1.29 1.21 1.77 8.30 6.56 12.44 4.93 2302002100 Commercial Cooking 20.40 6.73 0.70 1.46 6.18 5.32 

2302002200 Commercial Cooking 67.94 23.41 2.28 4.31 21.53 16.40 

2302003000 Commercial Cooking 7.32 0.39 0.74 3.31 2.88 

2302003100

Industrial Processes (Commercial Cooking - Flat Griddle Frying)

5.72

0.29 0.57 2.79 2.06

2302003200

Industrial Processes (Commercial Cooking - Clamshell Griddle Frying)

0.25

0.01 0.02 0.11 0.10

2302050000 Bakeries 449.17 46.20 2.64 0.00 95.48 9.23 29.86 20.40 154.98 3.58 1.62 30.61 47.19 

2302070001 Breweries 1.22 0.10 0.00 1.04 0.06 0.01 0.00 

2302070005 Wineries 0.06 0.00 0.01 0.01 0.00 0.05 

2401001000 Surface Coating - Architectural 756.40 756.40 2401002000 Surface Coating - Architectural 2893.77 88.46 143.36 623.94 571.10 148.16 101.21 769.03 17.79 8.04 151.88 234.15 

2401003000 Surface Coating - Architectural 2297.50 78.09 126.55 550.76 504.12 104.84 71.61 544.17 12.58 5.69 107.47 165.68 

2401005000 Surface Coating - Automobile 

Refinishing

2725.29 82.96

55.36 79.85 267.59 212.58

163.66 216.58 635.86 107.35 75.45 305.92 386.62 

2401008000 Surface Coating - Traffic Paints 546.60 134.51 5.61 9.03 9.63 6.39 38.53 26.32 199.97 4.62 2.09 39.49 60.89 

2401015000 Surface Coating - Industrial 127.90 5.46 5.96 14.15 18.54 2.49 0.52 0.79 9.15 39.45 28.27 

2401020000 Surface Coating - Industrial 129.17 11.01 92.20 0.94 2.60 19.82 2401025000 Surface Coating - Industrial 541.79 31.72 11.33 8.97 139.71 220.90 11.01 92.20 0.94 2.60 19.82 

C1-7

Appendix B - Page Number:482
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Volatile Organic Compounds (VOC)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City

Fairfax 

County

Fairfax 

City

Falls 

Church 

City

Loudoun 

County

Prince 

William 

County

Manas

Cit

2401040000 Surface Coating - Industrial 1367.99 83.88 135.93 591.60 541.50 15.07 2401045000 Surface Coating - Industrial 34.04 8.63 12.95 2401050000 Surface Coating - Industrial 520.35 32.26 52.28 227.54 208.27 2401055000 Surface Coating - Industrial 145.66 0.21 3.50 44.08 29.53 25.29 3.94 1.24 18.04 7.51 12.27 

2401065000 Surface Coating - Industrial 2.08 2.08 2401070000 Surface Coating - Industrial 44.54 4.18 20.09 14.27 5.94 2401080000 Surface Coating - Industrial 3.85 0.00 0.00 0.77 3.08 

2401090000 Surface Coating - Industrial 1372.40 175.82 38.71 62.74 273.05 249.93 57.79 39.47 299.96 6.94 3.14 59.24 91.33 

2401100000 Surface Coating - Industrial 1463.89 187.54 41.29 66.92 291.25 266.59 61.64 42.11 319.95 7.40 3.35 63.19 97.42 

2401200000 Surface Coating - Special Industry 1463.89 187.54 41.29 66.92 291.25 266.59 61.64 42.11 319.95 7.40 3.35 63.19 97.42 

2401990000 Surface Coating - Industrial 13.44 0.00 5.95 0.68 6.81 

2415105000 Surface Cleaning 1.61 1.61 

2415120000 Surface Cleaning 3.55 3.55 

2415125000 Surface Cleaning 1.28 1.28 

2415130000 Surface Cleaning 2079.63 3.22 128.73 208.62 907.97 831.08 

2415135000 Surface Cleaning 0.66 0.66 

2415140000 Surface Cleaning 1.77 1.77 

2415145000 Surface Cleaning 4.71 4.71 

2415300000 Surface Cleaning 64.90 4.58 4.69 29.66 3.62 1.53 7.47 8.16 2415305000 Surface Cleaning 1.04 1.04 

2415320000 Surface Cleaning 1.03 1.03 

2415325000 Surface Cleaning 0.41 0.41 

2415330000 Surface Cleaning 21.49 0.54 1.03 0.08 7.35 0.08 0.18 3.71 0.25 

2415340000 Surface Cleaning 0.38 0.38 

2415345000 Surface Cleaning 71.31 3.57 2.30 1.16 37.84 0.11 0.15 11.54 6.01 

2415355000 Surface Cleaning 53.87 53.87 

2415360000 Surface Cleaning 1242.72 111.40 104.00 118.10 450.29 98.62 40.65 93.79 166.55 2420000370 Dry Cleaners 18.73 18.73 

2425000000 Graphic Arts 1295.57 127.48 30.12 53.08 187.20 140.05 71.13 52.69 400.34 9.26 4.19 79.06 121.89 

2440020000 Industrial Adhesives 1058.67 62.88 56.88 86.05 187.47 242.06 22.98 33.28 204.10 26.89 6.80 43.51 70.64 

2460100000 Commercial/Consumer Solvent Use 582.32 582.32 2460400000 Commercial/Consumer Solvent Use 353.39 353.39 2460500000 Commercial/Consumer Solvent Use 271.18 271.18 2460600000 Commercial/Consumer Solvent Use 149.20 149.20 2460800000 Pesticide Application 482.29 482.29 

2460900000 Commercial/Consumer Solvent Use 19.98 19.98 

2461020000 Asphalt Paving 1.17 1.17 

2461021000 Asphalt Paving 0.12 0.00 0.11 0.00 0.01 2461022000 Asphalt Paving 4.43 0.26 0.42 1.82 1.67 0.00 0.25 0.00 0.02 2461800000 Pesticide Application 2582.39 7.30 32.43 423.67 335.90 154.77 164.46 112.34 853.65 19.74 8.93 168.59 259.91 

2461850000 Pesticide Application 216.43 11.43 171.66 33.35 

2465000000 Commercial/Consumer Solvent Use 7347.36 455.51 738.21 3212.85 2940.79 

2465800000 Pesticide Application 545.19 49.66 27.66 319.99 7.64 3.97 38.11 84.48 

2465900000 Commercial/Consumer Solvent Use 6732.39 679.97 464.48 3529.47 81.62 36.91 697.04 1074.63 12501011011 Portable Fuel Containers 220.96 54.37 9.94 16.44 74.65 65.56 

2501011012 Portable Fuel Containers 1908.07 469.50 85.87 141.97 644.63 566.10 2501011016 Portable Fuel Containers 104.72 25.77 4.71 7.79 35.38 31.07 

2501012011 Portable Fuel Containers 17.92 2.42 1.04 2.37 7.21 4.89 

2501012012 Portable Fuel Containers 233.53 31.51 13.59 30.89 93.89 63.64 2501012016 Portable Fuel Containers 3541.80 477.85 206.16 468.56 1423.98 965.25 

2501060300 Portable Fuel Containers 2061.59 86.84 88.95 1046.16 37.09 22.42 460.02 280.71 

2501060053 Tank Truck Unloading (Stage I) 1244.10 75.34 27.24 46.42 170.86 143.78 77.80 54.77 372.30 28.76 13.75 71.16 132.71 

2501060100 Vehicle Fueling (Stage II) and 

Underground Tank Breathing

1282.41 235.41 62.84 143.81 383.04 457.31 

2501060103 Vehicle Fueling (Stage II) and 

Underground Tank Breathing

879.36 80.52 44.30 506.45 102.41 145.69 

2501060201 Vehicle Fueling (Stage II) and 

Underground Tank Breathing

919.28 79.86 29.29 49.91 183.73 154.71 42.05 29.60 201.20 15.54 7.43 38.45 71.72 

2501080050 Aircraft Refueling 1.17 1.17 

2501080100 Aircraft Refueling 0.07 0.07 

2505020000 Petroleum Vessel Loading and 

Unloading Losses

4.60 4.60 

2505020120 Petroleum Vessel Loading and 

Unloading Losses

52.27

52.27

2505020180 Petroleum Vessel Loading and 

Unloading Losses

0.02

0.02

2505030120 Losses from Gasoline Tank Trucks in 

Transit

54.48 5.27

2.47 4.31 15.77 13.25

1.34 0.94 6.40 0.49 0.24 1.22 2.28 

2601000000 On-Site Incineration 3.96 0.00 0.37 2.67 0.91 

2601010000 On-Site Incineration 59.05 5.99 3.76 29.32 0.28 0.60 9.51 5.93 2601020000 On-Site Incineration 305.88 30.89 21.10 160.36 3.71 1.68 31.67 48.82 

C1-8

Appendix B - Page Number:483
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Volatile Organic Compounds (VOC)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City

Fairfax 

County

Fairfax 

City

Falls 

Church 

City

Loudoun 

County

Prince 

William 

County

Manas

Cit

2601030000 On-Site Incineration 57.22 5.78 3.95 30.00 0.69 0.31 5.92 9.13 2610000100 Open Burning 22.92 6.01 10.47 6.22 0.22 

2610000400 Open Burning 14.81 3.92 6.83 4.06 0.00 

2610000500 Open Burning 2154.51 188.06 192.47 1077.96 696.02 

2610020000 Open Burning 242.59 133.93 75.81 32.85 

2610030000 Open Burning 8.21 2.70 4.43 1.08 0.00 

2620030000 Municipal Solid Waste Landfills 18.98 5.09 4.93 6.53 0.00 0.77 1.23 0.43 

2630020000 POTW 115.90 11.20 20.66 20.29 61.37 0.20 1.61 0.45 0.02 0.09 2660000000 Leaking Underground Storage Tanks 308.87 124.10 21.90 10.95 38.14 113.52 0.02 0.01 0.01 0.09 0.01 0.06 0.04 2680003000 Composting 3.80 3.80 

2810001000 Forest Fires 9.69 4.43 0.88 2.77 1.37 0.04 0.21 

2810015000 Slash/Prescribed Burning 2.24 0.00 1.52 0.56 0.02 0.14 

2810030000 Structure Fires 50.42 6.80 1.06 1.40 1.95 9.84 7.26 4.75 5.46 0.10 0.39 0.53 10.16 2810050000 Motor Vehicle Fires 7.63 0.35 0.46 1.31 5.51 

2830000000 Oil Spills 5.48 0.58 4.05 0.32 0.53 

2002 Area Source Total 72377.39 6313.88 2165.86 3959.60 13550.72 11991.53 3060.68 2285.40 16642.25 620.87 304.72 4427.44 5991.35 7

Nonroad Model Source

Agricultural Equipment 71.44 0.00 5.64 30.05 10.93 4.27 0.00 0.00 0.50 0.00 0.00 15.98 4.06 Airport Equipment 156.03 0.00 0.00 0.01 0.01 0.00 15.50 0.00 70.25 0.00 0.00 70.25 0.00 

Commercial Equipment 1851.27 156.98 35.65 109.77 413.30 315.72 44.81 58.02 479.27 27.36 8.96 93.87 72.64 Construction and Mining Equipment 2586.16 464.81 96.98 116.38 327.48 373.99 231.67 0.00 372.90 0.00 0.00 357.81 244.14 

Industrial Equipment 545.40 59.70 10.18 62.58 115.87 88.26 7.45 12.69 101.86 2.82 1.91 39.61 22.71 

Lawn and Garden Equipment (Com) 15633.42 51.63 168.76 1026.18 4053.00 1980.23 188.09 249.42 4189.70 145.94 100.86 2213.43 1132.61 

Lawn and Garden Equipment (Res) 5196.81 779.96 134.95 225.57 999.12 894.40 267.89 194.29 1085.61 23.19 13.72 216.52 315.01 

Logging Equipment 16.38 0.00 7.46 1.05 0.80 3.03 0.00 0.00 0.51 0.00 0.00 3.03 0.50 

Pleasure Craft 2519.84 460.16 989.98 112.51 281.27 318.78 0.00 0.00 190.19 0.00 0.00 23.48 143.47 

Railroad Equipment 4.77 0.30 0.01 0.92 0.60 0.39 0.12 0.39 0.75 0.00 0.00 0.00 1.01 Recreational Equipment 1105.56 49.75 142.45 153.11 303.02 149.91 3.21 0.00 134.61 2.14 0.00 44.51 122.84 Nonroad Model Source 29687.08 2023.30 1592.06 1838.12 6505.40 4128.99 758.74 514.82 6626.15 201.46 125.46 3078.50 2059.01 1

Other Nonroad Sources

2275001000 Military Aviation 264.23 13.55 4.91 17.74 200.68 27.36 

2275020000 Commercial Aviation 312.90 55.80 128.55 128.55 

2275050000 General Aviation 86.29 2.40 29.56 13.89 16.07 10.33 1.60 

2275060000 Air Taxi 6.86 0.12 1.05 3.43 0.43 0.29 2275070000 Aircraft Auxiliary Power Units 4.90 0.60 2.15 2.15 2285002005 Railroad Locomotives 74.21 14.76 11.59 9.13 0.12 5.21 16.58 2285002006 Railroad Locomotives 2.85 2.85 2285002008 Railroad Locomotives 3.88 3.88 2285002009 Railroad Locomotives 3.17 3.17 2285002010 Railroad Locomotives 45.89 9.64 16.93 4.23 0.05 2.03 6.46 

Other Nonroad Sources Total 805.18 19.54 16.07 67.20 33.14 43.38 56.40 0.16 338.62 0.00 0.00 141.31 52.00 

2002 Nonroad Source Total 30492.27 2042.83 1608.14 1905.32 6538.54 4172.36 815.14 514.98 6964.78 201.46 125.46 3219.81 2111.01 1

C1-9

Appendix B - Page Number:484
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Ammonia (NH3)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Ma

Area Source

2103006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption 5.14 5.14 

2104008001 Other Fuels Consumption (Residential 

Wood Burning) 12.66 1.10 2.51 3.64 5.40 

2104008010 Other Fuels Consumption (Residential 

Wood Burning) 38.95 2.67 5.27 11.75 19.25 

2104008030 Other Fuels Consumption (Residential 

Wood Burning) 1.68 0.12 0.23 0.51 0.83 

2104008050 Other Fuels Consumption (Residential 

Wood Burning) 4.04 0.28 0.55 1.22 1.99 

2104008053

Other Fuels Consumption (Residential Wood Burning) 0.47 0.11 0.25 0.05 0.06 

2104008060

Other Fuels Consumption (Residential Wood Burning) 1.34 0.31 0.72 0.13 0.18 

2104008070 Other Fuels Consumption (Residential 

Wood Burning; Outdoor Equipment)

15.61 3.82 0.89 1.48 4.95 4.48 

2104009000 Other Fuels Consumption (Residential 

Firelog) 0.002 0.00 0.00 0.00 0.00 

2199008000

Stationary Source Fuel Combustion (Wood Burning) 0.43 0.10 0.23 0.04 0.06 

2610000100 Open Burning 1.03 0.27 0.47 0.28 0.01 2610000400 Open Burning 0.98 0.26 0.45 0.27 0.00 2630020000 POTW 5.91 2.80 0.49 0.80 0.65 0.06 1.12 2680003000 Composting 16.49 0.83 15.66 

2801700001

Agriculture Production - Crops (Fertilizer Application) 0.66 0.13 0.13 0.13 0.27 

2801700002

Agriculture Production - Crops (Fertilizer Application) 4.57 0.00 4.57 0.00 0.00 

2801700003

Agriculture Production - Crops (Fertilizer Application) 607.07 17.89 555.59 0.01 13.10 0.12 1.70 17.31 1.36 

2801700004

Agriculture Production - Crops (Fertilizer Application) 283.69 5.08 215.86 6.60 22.61 10.16 1.30 13.04 1.52 4.15 

2801700005

Agriculture Production - Crops (Fertilizer Application) 5.39 0.15 0.04 0.04 0.41 0.02 0.10 4.57 0.03 

2801700006

Agriculture Production - Crops (Fertilizer Application) 34.08 0.14 32.63 0.05 0.26 0.00 0.15 0.82 0.00 0.01 0.00 0.01 

2801700007

Agriculture Production - Crops (Fertilizer Application) 19.60 0.00 0.00 0.00 0.00 0.00 19.58 

2801700010

Agriculture Production - Crops (Fertilizer Application) 126.21 7.29 11.68 30.01 25.08 0.80 2.54 29.31 6.22 0.58 0.04 8.33 

2801700011

Agriculture Production - Crops (Fertilizer Application) 0.00 0.00 0.00 0.00 0.00 

2801700012

Agriculture Production - Crops (Fertilizer Application) 0.25 0.00 0.01 0.00 0.24 

2801700013

Agriculture Production - Crops (Fertilizer Application) 37.75 0.00 32.06 0.00 0.04 0.54 0.29 4.82 

2801700014

Agriculture Production - Crops (Fertilizer Application) 1.63 0.00 0.65 0.00 0.00 0.98 

2801700015

Agriculture Production - Crops (Fertilizer Application) 4.44 0.00 4.40 0.00 0.00 0.02 0.00 0.02 

2801700099

Agriculture Production - Crops (Fertilizer Application) 20.90 1.35 4.06 2.53 3.91 1.41 0.31 2.49 0.09 0.00 0.36 4.28 

2805001100 Agriculture Production - Livestock 44.41 4.17 17.37 9.07 1.65 7.95 4.21 2805001200 Agriculture Production - Livestock 0.01 0.00 0.00 0.00 0.00 0.00 0.00 2805001300 Agriculture Production - Livestock 33.78 3.11 12.95 6.76 1.23 6.36 3.37 2805002000 Agriculture Production - Livestock 4.43 4.43 2805003100 Agriculture Production - Livestock 282.69 12.67 102.97 24.90 4.76 114.52 22.88 2805007100 Agriculture Production - Livestock 2.72 0.24 1.60 0.87 2805007300 Agriculture Production - Livestock 0.06 0.00 0.04 0.02 2805008100 Agriculture Production - Livestock 0.04 0.00 0.02 0.01 2805008200 Agriculture Production - Livestock 0.11 0.01 0.06 0.04 2805008300 Agriculture Production - Livestock 0.02 0.00 0.01 0.01 2805009100 Agriculture Production - Livestock 10.89 1.35 6.77 2.33 0.44 

2805009200 Agriculture Production - Livestock 2.99 0.22 1.10 0.42 1.25 2805009300 Agriculture Production - Livestock 8.56 1.09 5.45 1.90 0.12 2805010100 Agriculture Production - Livestock 74.88 74.82 0.05 0.01 2805010200 Agriculture Production - Livestock 12.14 12.13 0.01 0.00 2805010300 Agriculture Production - Livestock 60.20 60.16 0.04 0.01 2805018000 Agriculture Production - Livestock 12.90 5.11 6.34 1.45 

2805019100 Agriculture Production - Livestock 18.80 17.26 1.18 0.35 2805019200 Agriculture Production - Livestock 52.50 48.20 3.30 1.00 

C1-10

Appendix B - Page Number:485
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

Ammonia (NH3)

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Ma

2805019300 Agriculture Production - Livestock 5.08 4.66 0.32 0.09 

2805021100 Agriculture Production - Livestock 223.05 203.17 13.91 2.67 3.31 2805021200 Agriculture Production - Livestock 242.00 220.16 15.07 3.03 3.74 2805021300 Agriculture Production - Livestock 490.85 448.70 30.71 5.12 6.32 2805022100 Agriculture Production - Livestock 24.30 21.95 1.50 0.37 0.48 2805022200 Agriculture Production - Livestock 1.00 0.90 0.06 0.02 0.02 2805022300 Agriculture Production - Livestock 13.71 12.38 0.85 0.21 0.27 2805023100 Agriculture Production - Livestock 183.79 153.64 10.52 8.75 10.88 2805023200 Agriculture Production - Livestock 3.58 2.33 0.16 0.49 0.60 2805023300 Agriculture Production - Livestock 229.82 199.77 13.67 7.30 9.07 2805025000 Agriculture Production - Livestock 15.44 6.29 2.83 3.74 0.63 1.77 0.18 2805030000 Agriculture Production - Livestock 11.06 3.33 3.36 3.15 0.09 1.14 2805030007 Agriculture Production - Livestock 0.20 0.01 0.06 0.13 2805030008 Agriculture Production - Livestock 83.21 0.01 83.05 0.15 

2805035000 Agriculture Production - Livestock 221.48 18.77 76.33 59.76 29.93 8.20 9.32 19.17 

2805039100 Agriculture Production - Livestock 2.19 2.19 2805039200 Agriculture Production - Livestock 5.08 5.08 2805039300 Agriculture Production - Livestock 0.48 0.48 2805040000 Agriculture Production - Livestock 15.18 0.64 5.42 1.49 1.25 0.46 5.50 0.42 2805045000 Agriculture Production - Livestock 13.73 1.55 1.55 1.55 1.55 0.09 0.00 7.42 2805047100 Agriculture Production - Livestock 7.49 7.49 2805047300 Agriculture Production - Livestock 4.21 4.21 2805053100 Agriculture Production - Livestock 0.07 0.07 2810001000 Forest Fires 0.02 0.02 

2810015000 Slash/Prescribed Burning 0.06 0.01 0.05 

2002 Area Source Total 3670.14 12.59 93.78 2593.09 263.18 163.79 13.51 5.12 66.86 6.31 0.59 327.58 115.92 

Nonroad Model SourceAgricultural Equipment Airport Equipment 

Commercial Equipment Construction and Mining Equipmen Industrial Equipmen Lawn and Garden Equipment (Com) Lawn and Garden Equipment (Res Logging Equipment Pleasure Craft Railroad Equipment Recreational Equipment Nonroad Model Source 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

Other Nonroad Sources

2275001000 Military Aviation 0.00 

2275020000 Commercial Aviation 0.00 

2275050000 General Aviation 0.00 

2275060000 Air Taxi 0.00 

2275070000 Aircraft Auxiliary Power Units 0.00 

2280002010 Commercial Marine Vessels 0.00 

2285002005 Railroad Locomotives 0.00 

2285002006 Railroad Locomotives 0.00 

2285002008 Railroad Locomotives 0.00 

2285002009 Railroad Locomotives 0.00 

2285002010 Railroad Locomotives 0.00 

Other Nonroad Sources Total 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

2002 Nonroad Source Total 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

C1-11

Appendix B - Page Number:486
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

PM10

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Ma

Area Source

2102002000 Coal Consumption 937.07 95.01 59.63 465.24 4.44 9.51 150.97 94.15 

2102004000 Fuel Oil Consumption 16.42 1.08 1.31 2.12 2.05 1.00 0.63 4.89 0.05 0.10 1.59 0.99 

2102005000 Fuel Oil Consumption 34.48 6.36 7.68 7.46 7.26 0.58 0.36 2.84 0.03 0.06 0.92 0.57 

2102006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

225.18 22.83 14.33 111.81 1.06 2.28 36.28 22.63 

2102007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

18.98 1.92 1.21 9.43 0.09 0.19 3.06 1.91 

2103002000 Coal Consumption 41.91 13.32 3.60 7.21 10.81 3.60 0.53 0.32 1.80 0.06 0.05 0.26 0.27 

2103004000 Fuel Oil Consumption 208.99 50.15 4.30 5.18 8.35 8.13 20.90 12.52 70.86 2.52 2.03 10.40 10.71 

2103005000 Fuel Oil Consumption 26.03 0.74 0.90 0.90 0.87 3.56 2.13 12.06 0.43 0.35 1.77 1.82 2103006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

197.86 66.80

0.84 1.82 22.73 21.84

13.18 7.90 44.69 1.59 1.28 6.56 6.76 

2103007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

0.49

0.07 0.10 0.15 0.17

2103011000 Fuel Oil Consumption 1.85 0.31 0.37 0.59 0.57 

2104002000 Coal Consumption 28.12 3.62 0.00 0.50 0.50 0.53 2.32 1.58 12.08 0.27 0.13 2.38 3.67 2104004000 Fuel Oil Consumption 134.74 10.40 7.56 9.12 14.72 14.32 7.94 5.42 41.22 0.95 0.43 8.14 12.55 2104006000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

457.44 58.66

2.48 5.52 67.34 59.77

26.63 18.19 138.25 3.19 1.45 27.30 42.09 

2104007000 Natural Gas and Liquefied Petroleum 

Gas (LPG) Consumption

2.82 0.02

0.39 0.58 0.87 0.96

2104008001 Other Fuels Consumption (Residential 

Wood Burning)

301.44 13.14

18.73 42.61 61.73 91.62

14.31 2.00 36.47 2.20 1.16 4.82 9.44 

2104008002 Other Fuels Consumption (Residential 

Wood Burning)

711.00 39.36 73.57 10.30 398.33 11.32 5.95 52.56 103.14 

2104008003 Other Fuels Consumption (Residential 

Wood Burning)

28.22 1.56 2.92 0.41 15.81 0.45 0.24 2.09 4.09 

2104008004 Other Fuels Consumption (Residential 

Wood Burning)

11.86 0.66 1.23 0.17 6.64 0.19 0.10 0.88 1.72 

2104008010 Other Fuels Consumption (Residential 

Wood Burning)

1973.22 28.14

53.03 104.87 233.71 382.83

63.75 8.92 768.39 9.81 5.16 101.39 198.96 

2104008030 Other Fuels Consumption (Residential 

Wood Burning)

51.29 0.47

2.14 4.24 9.45 15.48

1.07 0.15 12.81 0.16 0.08 1.69 3.31 

2104008050 Other Fuels Consumption (Residential 

Wood Burning)

114.92 1.12

4.61 9.12 20.32 33.29

2.53 0.36 30.50 0.39 0.20 4.02 7.89 

2104008053

Other Fuels Consumption (Residential Wood Burning)

4.83

1.11 2.57 0.49 0.66

2104008060

Other Fuels Consumption (Residential Wood Burning)

25.77

5.94 13.85 2.54 3.44

2104008070 Other Fuels Consumption (Residential 

Wood Burning; Outdoor Equipment)

226.69

17.06 28.36 95.14 86.13

2104009000

Other Fuels Consumption (Residential Firelog)

30.00

2.62 5.95 8.63 12.80

2104011000 Fuel Oil Consumption 3.22 0.53 0.64 1.04 1.01 

2199008000

Stationary Source Fuel Combustion (Wood Burning)

6.01

1.38 3.23 0.59 0.80

2294000000 Mobile: All Paved Roads - Total: 

Fugitives

10960.55

1008.22 1005.07 1409.88 428.86

519.49 344.37 3622.12 63.92 16.53 1145.23 1303.70 

2296000000 Mobile: All Unpaved Roads - Total: 

Fugitives

3521.37

25.13 122.69 70.00 62.10

730.41 981.79 1529.25 

2302002100 Commercial Cooking 81.52 26.90 2.80 5.84 24.72 21.27 

2302002200 Commercial Cooking 566.37 195.19 19.02 35.94 179.52 136.69 

2302003100

Industrial Processes (Commercial Cooking - Flat Griddle Frying)

95.38

4.87 9.54 46.53 34.44

2302003201

Industrial Processes (Commercial Cooking - Clamshell Griddle Frying)

7.01

0.35 0.68 3.15 2.83

2311010000 Total Residential Construction: SIC 15

- 17

940.42

60.98 64.03 157.30 108.09

4.08 24.39 130.34 1.88 0.05 297.92 83.81 

2311020000 Total 

Industrial/Commercial/Institutional Construction: SIC 15 - 17

7385.89

67.75 289.77 2531.17 1450.46

160.68 156.65 1458.97 56.37 105.61 811.47 102.40 

2311030000 Total Road Construction: SIC 15 - 17 12443.84 969.49 1040.72 3306.16 1690.34 39.82 185.00 1183.87 21.68 0.55 3098.71 890.83 

2325000000 Industrial Processes: Mining and 

Quarrying: SIC 14 - All Processes

1469.76 244.96 244.96 244.96 244.96 244.96 244.96 

2401001000 Surface Coating - Architectural 2157.59 2157.59 

2401005000 Surface Coating - Automobile 

Refinishing

6.68 6.68 

2601000000 On-Site Incineration 25.95 0.00 11.90 12.50 1.55 

2601010000 On-Site Incineration 113.56 11.52 7.22 56.46 0.49 1.14 18.29 11.42 2601020000 On-Site Incineration 367.45 37.12 25.34 192.68 4.45 2.00 38.04 58.66 2610000100 Open Burning 24.76 4.72 8.23 4.89 0.17 6.75 

2610000400 Open Burning 18.32 4.07 7.09 4.22 0.00 2.94 

2610000500 Open Burning 6293.71 250.37 571.01 1632.54 613.17 67.48 125.17 1539.75 34.14 741.77 642.88 

C1-12

Appendix B - Page Number:487
 2002 Base Year Emission Inventory for the Metropolitan Washington Nonattainment Area

PM10

Area and Nonroad Source Emissions by Jurisdiction (tons/year)

SCC Code Category Name NAA Total

District of 

Columbia

Charles 

County

Frederick 

County

Montgomery 

County

Prince 

George's 

County

Arlington 

County

Alexandria 

City Fairfax County Fairfax City

Falls Church

City

Loudoun 

County

Prince 

William 

County

Ma

2610030000 Open Burning 36.47 11.98 19.68 4.80 0.00 

2801000003 Crops Tilling 2877.38 311.40 1166.24 406.54 140.39 15.55 754.68 82.58 2805001000 Livestock, beef cattle, feedlots, Dust 

Kicked-up by Hooves

426.74

12.55 2.49 7.84 3.88

33.72 303.41 62.85 

2810001000 Forest Fires 0.53 0.00 0.00 0.00 0.00 0.09 0.44 

2810015000 Slash/Prescribed Burning 130.44 0.01 1.77 0.00 0.00 0.65 0.01 0.01 36.01 46.82 45.11 

2810030000 Structure Fires 41.80 6.68 1.04 1.38 1.92 9.66 5.24 3.42 3.93 0.06 0.28 0.34 7.35 

2810050000 Motor Vehicle Fires 23.86 1.10 1.44 4.09 17.23 

2002 Area Source Total 55838.21 2680.45 2892.48 4619.47 10377.94 5469.94 1446.18 1263.06 11432.89 433.01 191.05 8910.29 5592.91 

Nonroad Model SourceAgricultural Equipment 60.93 0.00 4.82 25.64 9.32 3.65 0.00 0.00 0.42 0.00 0.00 13.62 3.46 Airport Equipment 22.22 0.00 0.00 0.00 0.01 0.00 10.60 0.00 5.80 0.00 0.00 5.80 0.00 

Commercial Equipment 106.28 9.15 2.05 6.31 23.76 18.15 2.56 3.32 27.40 1.56 0.51 5.37 4.15 

Construction and Mining Equipmen 1384.24 250.71 51.85 62.23 175.09 199.96 123.73 0.00 199.17 0.00 0.00 191.10 130.39 

Industrial Equipmen 120.07 14.22 2.87 9.23 24.61 20.74 3.47 3.15 24.57 0.59 0.34 6.87 6.75 Lawn and Garden Equipment (Com) 580.13 1.92 6.27 38.11 150.50 73.53 6.97 9.25 155.35 5.48 3.74 82.07 42.00 

Lawn and Garden Equipment (Res 80.89 12.30 2.10 3.52 15.57 13.94 4.14 3.01 16.80 0.35 0.21 3.35 4.87 Logging Equipment 2.68 0.00 1.22 0.17 0.13 0.50 0.00 0.00 0.08 0.00 0.00 0.50 0.08 

Pleasure Craft 45.36 8.34 17.90 2.01 5.03 5.70 0.00 0.00 3.40 0.00 0.00 0.42 2.57 Railroad Equipment 2.71 0.17 0.01 0.53 0.34 0.22 0.07 0.22 0.43 0.00 0.00 0.00 0.57 Recreational Equipment 34.02 1.72 4.60 4.71 9.39 4.68 0.03 0.00 3.86 0.02 0.00 1.28 3.73 Nonroad Model Source 2439.53 298.52 93.68 152.44 413.76 341.07 151.59 18.94 437.26 8.01 4.81 310.38 198.59 

Other Nonroad Sources

2275001000 Military Aviation 53.32 7.62 2.76 9.97 23.60 9.38 

2275020000 Commercial Aviation 32.40 9.10 11.65 11.65 

2275050000 General Aviation 11.12 0.13 1.55 0.73 0.84 3.34 0.52 

2275060000 Air Taxi 0.20 0.00 0.02 0.06 0.01 0.02 

2275070000 Aircraft Auxiliary Power Units 0.11 0.01 0.05 0.05 

2285002005 Railroad Locomotives 157.82 10.23 8.03 6.33 0.40 17.92 57.05 2285002006 Railroad Locomotives 2.05 2.05 

2285002008 Railroad Locomotives 2.11 2.11 

2285002009 Railroad Locomotives 1.72 1.72 

2285002010 Railroad Locomotives 48.15 5.78 6.75 1.69 0.10 4.56 14.53 

Other Nonroad Sources Total 309.00 11.66 7.74 21.30 10.50 17.15 9.11 0.50 57.78 0.00 0.00 15.06 81.48 

2002 Nonroad Source Total 2748.53 310.18 101.42 173.75 424.26 358.21 160.70 19.44 495.04 8.01 4.81 325.44 280.07 

C1-13

Appendix B - Page Number:488
Attachment D1 

BY 2002 Onroad Mobile Source Emissions 

Inventory and Documentation 

 D1-1

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489
On-Road Mobile Emissions Analysis – Metropolitan Washington, DC-MD-VA 

PM2.5 Nonattainment Area 

This appendix provides details of the MOBILE6.2.03 model input assumptions that were used to 

develop the base year 2002 annual onroad mobile 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 the 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 Emission Inventory (NEI) Input Format (NIF3.0). 

MOBILE6 input and output files used in the development of the base year 2002 annual onroad 

mobile emission analysis are available in an electronic format as Attachment D2. The NIF3.0 file is 

available in an electronic format as Attachment D3.

Separate sets of input files were created to model emission factors corresponding 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 these inputs is discussed separately below. 

A. MOBILE6 NETWORK AND LOCAL INPUT FILE SETUP 

The MOBILE6 input files representing the network and local roadway conditions include 

formatting commands, one-time inputs, and scenario data. The one-time inputs include countyspecific registration distributions by age, county-specific diesel sales fractions by model year, and 

inspection and maintenance (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, Charles County, Frederick County, Montgomery County, 

and Prince George’s County, MD; and Alexandria, Arlington County, Fairfax County, Loudoun 

County, and Prince William County, Stafford County, VA. Though MOBILE6 inputs files for 

Calvert and Stafford counties were prepared as they 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 

nonattainment 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 scenarios are modeled in a specified order. Table 3 

shows the order of the scenarios for modeling VOC and NOx emission 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 scenarios model the same ambient conditions 

(e.g., temperature, humidity, fuel parameters) for a given jurisdiction. The differences from one 

scenario to the next are the speeds, road types, operating modes, and, sometimes, the VMT mix 

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being modeled. As shown in Table 5, the scenarios for the annual inputs include three sets of 

seasonal inputs for each of the speeds, road types, and operating mode combinations that are 

modeled. Annual onroad mobile emissions were developed based 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 sets of seasonal inputs represent the differences 

in temperature, humidity, and fuel parameters associated with Winter, Summer, or Fall. The 

temperature and humidity inputs are the same regionwide, while the fuel input parameters vary by 

region. Table 5 summarizes the various input parameters and how they were matched by season in 

the annual input files. 

3. MWCOG Data Input Parameters 

The trip length distribution data 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 modeled with an operating mode input of either 

stabilized, hot start, or cold start. The inputs 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 and 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, gasoline Reid vapor pressure inputs, and gasoline oxygen 

content inputs. These fuel inputs except for diesel sulfur content are 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 inputs and ATP inputs in MOBILE6 format for 

2002. Table 15 shows the I/M program parameters for DC. As shown in this table, a separate 

cutpoint file is needed for the vehicles included in the IM240 test. This cutpoint file is shown in 

Table 16. The I/M program parameters for Maryland 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 distributions were used in the MOBILE6 input files. These 

distributions show the fraction of registered vehicles from ages 1 through 25 for each of 16 

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MOBILE6 vehicle types. The registration distribution inputs used for 2002 are provided in 

Attachment 1. Below is a detailed explanation of how these distributions 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 extracted 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 first 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 vehicles 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 beginning 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 vehicles were included with the 2002 model year 

as the first model year in the registration data. 

For each county in Virginia and Maryland, the 2002 registration data included counts of 

registered vehicles by the MOBILE5 vehicle categories. For use with MOBILE6, the LDGV and 

LDDV vehicle counts by model year were grouped together and the fraction by model year 

calculated. This was then used as the MOBILE6 LDV registration distribution. The LDGT1 and 

LDDT vehicle counts by model year were grouped together to create the MOBILE6 LDT1 and 

LDT2 registration distributions. The MOBILE5 LDGT2 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 create the registration distribution 

for the MOBILE HDV categories, except the MOBILE6 HDBT (transit bus) category. The 

MOBILE6 HDBT registration distribution 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 applied to obtain the MOBILE6 HDBT 

registration distribution. 

 c. Diesel Sales Fractions 

The diesel sales fractions input to MOBILE6 are specific to the calendar year being 

modeled. The MOBILE6 diesel sales fractions for 2002 are shown in Attachment 2. 

Diesel sales fractions were developed for each of the Maryland and Virginia counties based 

on 2002 year of analysis. The LDV diesel sales 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 model 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 for the District as well as for all of the heavy 

duty categories for Maryland and Virginia, since these sales fractions vary significantly by the 

MOBILE6 weight classes and the registration data for these States is not broken down by weight 

class. Appendix 2 shows the resulting diesel sales fractions, with the defaults shown for the 

District, and only the locally-derived LDV and LDT1/2 data shown for Maryland and Virginia. 

 

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d. 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 from COG’s travel demand model combined with 

county-specific registration distributions and diesel sales fractions and MOBILE6 default data on 

the VMT mix by vehicle type within the heavy and light-duty vehicle categories. The 2002 HDVs 

(excluding buses) account for 7.94 percent of the 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 road total VMT in 2002. 

A set of MOBILE6 input files was first prepared using each county’s registration 

distribution and the corresponding diesel 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 MOBILE6 and the database outputs for these inputs 

were obtained. The MOBILE6 database output format gives VMT fractions for each of the 28 

MOBILE6 vehicle types, based on the registration distribution and diesel sales fractions supplied in 

the input file, as well as the MOBILE6 default 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 MOBILE6 database output 

files were separately totaled. Following the MOBILE6 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 fraction. The HDV VMT fractions, excluding the bus fractions 

(which were multiplied by 0), were multiplied the ratio of COG’s estimated 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 each 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 created for use in off-network calculations of 

emissions resulting from auto access to transit. These input files were identical to the 

corresponding MOBILE6 network/local input files, with the exception of the VMT mixes used. 

The same procedure was used for developing the VMT mixes to represent auto access to transit. 

However, as this analysis pertains to vehicles accessing the transit 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 the LDV + MC accounting for 100 percent of the 

vehicles accessing the transit system. The resulting VMT mix fractions used for 2002 are reported 

in Attachment 3. 

The resulting MOBILE6 output files representing auto access to transit were post-processed. 

Running VOC emission factors by speed were estimated by averaging the total exhaust plus running 

loss plus crankcase VOC emission factors expressed in grams per mile over the 12 jurisdictions. 

Similarly, average NOx exhaust emission factors were estimated at each speed over the 12 

jurisdictions. The composite hot and cold start 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 

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grams per mile, combined with data from the MOBILE6 database output on the average daily miles 

driven by vehicle type, and the average trip starts made per day. Once 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 daily miles driven 

LDGV_T,..., MC_S = vehicle-specific average trip starts made per day 

C. MOBILE6 DIESEL SCHOOL BUS AND DIESEL TRANSIT BUS INPUT FILE 

SETUP 

Separate MOBILE6 files were set up to model diesel school bus and diesel transit bus 

emission factors. These input files were set up on a regional rather than county basis, with one 

input file per year for diesel school buses and one input file per year for diesel transit buses. Based 

on the October 10, 2002 memo prepared by COG 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 distribution and renormalizing these data over these 16 years (i.e., 

zeroing out years 17 through 25). The 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 provided in Attachment 1. For the 2002 school bus 

MOBILE6 input files, the VMT mix in all scenarios was set to 1 for the HDBS category and 0 for 

all other categories. For the 2002 transit bus MOBILE6 input files, the VMT 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 sales fractions for all 25 

years for the HDBS category were set to 1. The MOBILE6 default diesel sales fractions were used 

in the transit bus input file. These defaults are also 1 for the entire HDBT category. 

Each of the MOBILE6 bus input files was modeled 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 emission factors under these conditions are identical at 

the same speed.) Scenarios 196 through 198 model freeway ramps at a fixed speed of 34.6 mph for 

three seasons. Scenarios 199 through 201 model local roads at a fixed speed of 12.9 mph for three 

seasons. All scenario use the stabilized operating mode inputs and the same ambient and fuel 

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conditions as included in the network/local MOBILE6 input files. These scenarios 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 operating mode inputs and the same ambient and fuel 

conditions as included in the network/local MOBILE6 input files. These scenarios 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 the corresponding output files. No other emission 

factors from these output files were used. 

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Table 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 evaporative 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 Specifies 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.) 

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Table 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 similar in characteristics to Winter 2003 as compared to Winter 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 through 

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 files.

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Table 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 Season 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 

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Table 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 

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Table 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 

 D1-12

Appendix B - Page Number:

500
Table 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 

 D1-13

Appendix B - Page Number:

501
Table 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 

 D1-14

Appendix B - Page Number:

502
Table 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 Modeled 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 

 D1-15

Appendix B - Page Number:

503
Table 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 

 D1-16

Appendix B - Page Number:

504
Table 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 15.000 20.000 20.000 20.000 

20.000 20.000 30.000 30.000 30.000 30.000 30.000 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 20.000 60.000 60.000 60.000 

60.000 60.000 80.000 80.000 80.000 80.000 80.000 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 60.000 60.000 60.000 60.000 

60.000 60.000 80.000 80.000 80.000 80.000 80.000 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 60.000 60.000 60.000 60.000 

60.000 60.000 80.000 80.000 80.000 80.000 80.000 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 overrides 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.

 D1-17

Appendix B - Page Number:

505
Table 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 

 D1-18

Appendix B - Page Number:

506
Table 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. 

 D1-19

Appendix B - Page Number:

507
Table 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. 

 D1-20

Appendix B - Page Number:

508
Table 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 Analysis 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). 

 D1-21

Appendix B - Page Number:

509
Attachment 1 

Vehicle Registration 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 the 16 required vehicle classes used in MOBILE6, for each 

jurisdiction. For school and transit buses, the RDT reported were based on 2002 metropolitan Washington’s 

regional distribution. 

 D1-22

Appendix B - Page Number:

510
District 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

 D1-23

Appendix B - Page Number:

511
Charles 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 

 D1-24

Appendix B - Page Number:

512
Frederick 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

 D1-25

Appendix B - Page Number:

513
Montgomery 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

 D1-26

Appendix B - Page Number:

514
Prince 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

 D1-27

Appendix B - Page Number:

515
Alexandria, 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 

 D1-28

Appendix B - Page Number:

516
Arlington 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

 D1-29

Appendix B - Page Number:

517
Fairfax 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

 D1-30

Appendix B - Page Number:

518
Loudoun 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

 D1-31

Appendix B - Page Number:

519
Prince 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

 D1-32

Appendix B - Page Number:

520
2002 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 

 D1-33

Appendix B - Page Number:

521
Attachment 2 

Diesel Sales Fractions 

The diesel sales fractions are presented by vehicle, year-specific model year, and going back 25 model years. 

Maryland and Virginia use the defaults present for the District for all categories other than LDVs and LDT12 for 

network and off-network analyses. The diesel sales fractions 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 

 D1-34

Appendix B - Page Number:

522
Calvert County, MD—2002 Diesel 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 Diesel 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 

 D1-35

Appendix B - Page Number:

523
Arlington 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 Diesel 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 

 D1-36

Appendix B - Page Number:

524
Attachment 3 

VMT Mix Fractions (Network, Local, and Auto-Access to Transit) 

VMT mix fractions for network, local, and auto-access to transit analyses are being provided for the 

16 vehicle categories listed below. 

LDV LDT1 LDT2 LDT3 LDT4 HDV2B HDV3 HDV4 

HDV5 HDV6 HDV7 HDV8A HDV8B HDBS HDBT MC 

VMT fractions are arranged in the format below for network, local, and auto-access for each 

jurisdiction. Further details on the format for VMT fractions are available in the Mobile6 model 

user guide. 

Network 

Winter VMT Fractions (Arranged in blocks of 2 rows) 

Summer VMT Fractions (Arranged in blocks of 2 rows) 

Fall VMT Fractions (Arranged in blocks of 2 rows) 

Local 

Winter VMT Fractions (Arranged in blocks of 2 rows) 

Summer VMT Fractions (Arranged in blocks of 2 rows) 

Fall VMT Fractions (Arranged in blocks of 2 rows) 

Auto-Access 

Winter VMT Fractions (Arranged in blocks of 2 rows) 

Summer VMT Fractions (Arranged in blocks of 2 rows) 

Fall VMT Fractions (Arranged in blocks of 2 rows) 

 D1-37

Appendix B - Page Number:

525
2002 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 

 D1-38

Appendix B - Page Number:

526
2002 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 

 D1-39

Appendix B - Page Number:

527
2002 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 

 D1-40

Appendix B - Page Number:

528
2002 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 

 D1-41

Appendix B - Page Number:

529
2002 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 

 D1-42

Appendix B - Page Number:

530
2002 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 

 D1-43

Appendix B - Page Number:

531
2002 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 

 D1-44

Appendix B - Page Number:

532
2002 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 

 D1-45

Appendix B - Page Number:

533
2002 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 

 D1-46

Appendix B - Page Number:

534
2002 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 

 D1-47

Appendix B - Page Number:

535
2002 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 

 

 D1-48

Appendix B - Page Number:

536
1

DATE: December 11, 2007 

To: Fine Particulate Matter (PM2.5) State Implementation Plan SIP Files 

FROM: Eulalie G. Lucas 

 Daivamani Sivasailam 

 Anant Choudhary 

Department of Transportation Planning 

SUBJECT: Procedures and Results of Conversion of 2002 Washington, DC-MD-VA Mobile 

Source Emissions Inventories to National Emission Inventory Input Format 

(NIF): Direct PM2.5 and PM10, SO2, NH3, NOX and VOC. 

I. INTRODUCTION 

This memo documents the procedures applied and results obtained for converting the 2002 

annual mobile 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 emissions factors, the COG emissions inventories 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 PM2.5, PM10, SO2, NH3, NOX, 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), offline 

Appendix B - Page Number:

537
2

calculations are also required to prepare a comprehensive inventory. For example, as seen in 

Exhibit 6, this includes diurnal emissions 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 

emissions 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 transit 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 garage, 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 existing inventory component 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 small 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 PM2.5, PM10, SO2, NH3, NOX, and VOC are present in exhaust 

emissions. 

Appendix B - Page Number:

538
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 

emissions 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 column. 

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 facility 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 more 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 set 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 performed. 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. 

Appendix B - Page Number:

539
4

 Running Loss 

These emissions occur while the engine is in stabilized mode, but are not associated with tailpipe exhaust emissions 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 

emissions 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 tripmaker 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 NIF 

Appendix B - Page Number:

540
5

components is the same as with the network analysis approach. 

7A. School Bus Emissions 

These emissions relate directly to VMT data obtained 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 estimates 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 mix’ (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 vehicle-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 component, have a somewhat different VMT 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. 

Appendix B - Page Number:

541
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 requirements 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 convert each inventory component 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 PM2.5, PM10, SO2, NH3, NOX, 

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 File 

Appendix B - Page Number:

542
 MOBILE SOURCE EMISSIONS

BY JURISDICTION AND TRIP CYCLE

PM 2.5 SIP BASE YEAR 2002

DIRECT PM2.5 (TONS PER YEAR)

JURIS RUNNING TO

CY

NETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESS

 DC 119.92 11.01 22.98 2.16 0.20 

 MONTG 278.18 10.92 18.45 14.68 0.43  PG 305.76 10.34 15.37 16.22 0.89 

CHAS 35.95 2.19 0.48 3.05 0.05 

FRED 116.66 4.87 1.60 4.94 0.15  ARL 61.43 1.95 5.13 0.44 0.13 

FFX 373.80 17.12 14.62 14.06 0.66 

LDN 67.49 5.96 2.34 4.71 0.07 

PR W 103.06 7.42 2.59 5.33 0.29 

ALEX 29.41 3.41 5.38 0.34 0.11 

TOTAL 1,491.66 75.18 88.93 65.96 2.97 

TOTAL

EMISSIONS 

VEHICLE RELATED

EMISSIONS

EXHIBIT 1

Appendix B - Page Number:543
 MOBILE SOURCE EMISSIONS

BY JURISDICTION AND TRIP CYCLE

PM 2.5 SIP BASE YEAR 2002

DIRECT PM10 (TONS PER YEAR)

JURIS RUNNING TO

CY

NETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESS

 DC 176.11 19.47 25.28 2.390 0.37 

 MONTG 405.28 18.89 20.30 16.221 0.80  PG 441.96 17.43 16.91 17.928 1.68 CHAS 51.13 3.65 0.53 3.372 0.09 FRED 168.31 8.40 1.76 5.464 0.27  ARL 90.06 3.29 5.64 0.488 0.24 FFX 540.84 29.38 16.08 15.538 1.24 LDN 98.85 10.13 2.58 5.208 0.13 PR W 151.08 12.68 2.85 5.891 0.54 ALEX 43.13 5.84 5.92 0.381 0.20 TOTAL 2166.750 129.15 97.84 72.88 5.57 

TOTAL

EMISSIONS 2

VEHICLE RELATED

EMISSIONS

EXHIBIT 2

Appendix B - Page Number:544
 MOBILE SOURCE EMISSIONS

BY JURISDICTION AND TRIP CYCLE

PM 2.5 SIP BASE YEAR 2002

 SO2 (TONS PER YEAR)

JURIS RUNNING TO

CY

NETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESS

 DC 242.43 30.32 15.21 1.21 0.71 

 MONTG 619.01 35.11 12.21 8.18 1.54 

 PG 650.47 31.65 10.17 9.04 3.23 

CHAS 72.93 6.50 0.32 1.70 0.18 

FRED 253.10 15.19 1.06 2.76 0.53 

 ARL 130.82 6.14 3.39 0.25 0.46 FFX 803.39 53.07 9.68 7.84 2.38 LDN 146.85 18.07 1.55 2.63 0.26 PR W 221.69 22.48 1.71 2.97 1.05 ALEX 63.51 10.90 3.56 0.19 0.39 TOTAL 3,204.20 229.42 58.88 36.75 10.73 

TOTAL

EMISSIONS 

VEHICLE RELATED

EMISSIONS

EXHIBIT 3

Appendix B - Page Number:545
 MOBILE SOURCE EMISSIONS

BY JURISDICTION AND TRIP CYCLE

PM 2.5 SIP BASE YEAR 2002

 NH3 (TONS PER YEAR)

JURIS RUNNING TO

CY

NETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESS

 DC 323.85 57.50 0.70 0.08 1.24 

 MONTG 734.18 54.91 0.56 0.55 2.68 

 PG 774.80 49.28 0.47 0.61 5.61 

CHAS 84.63 9.89 0.01 0.11 0.31 

FRED 291.96 23.49 0.05 0.18 0.91 

 ARL 164.86 9.80 0.16 0.02 0.80 FFX 947.79 81.68 0.44 0.52 4.13 

LDN 179.55 28.39 0.07 0.18 0.45 PR W 273.68 35.23 0.08 0.20 1.82 ALEX 79.13 17.25 0.16 0.01 0.67 TOTAL 3,854.43 367.41 2.70 2.46 18.62 

TOTAL

EMISSIONS 

VEHICLE RELATED

EMISSIONS

EXHIBIT 4

Appendix B - Page Number:546
 MOBILE SOURCE EMISSIONS

BY JURISDICTION AND TRIP CYCLE

PM 2.5 SIP BASE YEAR 2002

Precursor NOx (TONS PER YEAR)

JURIS ORIGIN RUNNING T

C

NETWORK LOCAL TRANSIT BUS SCHOOL BUS AUTO ACCESS

 DC 709.72 6,845.55 637.17 561.17 43.60 30.16  MONTG 1,302.36 15,293.89 590.44 450.55 227.10 65.13  PG 1,131.19 17,310.28 567.29 375.29 251.01 136.53 CHAS 187.44 1,636.39 126.08 11.83 47.21 7.62 FRED 343.31 7,146.16 295.35 38.99 76.50 22.22  ARL 331.39 3,552.73 105.35 125.19 7.15 19.58 FFX 1,493.67 20,271.62 876.94 357.05 217.54 100.56 LDN 279.92 3,734.78 326.59 57.17 72.91 10.91 PR W 406.32 5,994.37 414.87 63.20 82.47 44.24 ALEX 199.20 1,631.63 177.08 131.49 5.58 16.26 TOTAL 6,384.52 83,417.40 4,117.16 2,171.94 1,031.07 453.21 

TOTAL

EMISSIONS 

VEHICLE RELATED

EMISSIONS

EXHIBIT 5

Appendix B - Page Number:547
MOBILE SOURCE EMISSIONS

BY JURISDICTION AND TRIP CYCLE

PM 2.5 SIP BASE YEAR 2002

VOC (TONS PER YEAR)

JURIS ORIGIN RUNNING DESTINATION VEHICLE RELATED 

EMISSIONS 

NETWORK LOCAL DIURNAL REST. LOSS TRANSIT BUS SCHOOL BUS 

 DC 1,598.91 1,982.21 535.52 400.91 40.22 292.34 32.63 4.04  MONTG 2,768.96 3,548.04 441.90 702.70 83.93 537.87 26.20 16.54  PG 2,500.29 3,947.74 473.88 639.91 88.71 597.39 21.82 17.25 CHAS 427.74 442.64 80.12 99.73 19.34 128.07 0.69 3.24 

FRED 772.46 1,299.28 188.63 172.01 30.68 206.66 2.27 5.26  ARL 728.60 817.87 85.75 194.53 18.65 121.84 7.28 0.55 FFX 3,237.07 4,440.10 679.56 857.97 100.08 637.58 20.76 14.95 LDN 639.24 841.81 204.75 157.53 24.83 158.53 3.32 5.01 

PR W 916.80 1,275.60 293.43 236.46 46.24 304.43 3.68 5.67 ALEX 435.17 419.44 137.77 117.07 17.48 111.96 7.65 0.43 TOTAL 14,025.24 19,014.73 3,121.31 3,578.82 470.15 3,096.67 126.31 72.92 

TOTAL

EMISSIONS 

EXHIBIT 6

Appendix B - Page Number:548
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) Running 

Appendix B - Page Number:

549
w

Exhibit 8

Summary Table of Emissions Inventory Components

(Facility Type and Vehicle Type Percentages Vary by Jurisdiction)

2002 Baseline Inventories (Annual 

Direct PM2.5, PM10,SO2,NH3,NOX,VOC)

COG INVENTORY DATA NIF REQUIREMENTS

Category Transportation Exhaust Evaporative Facility Type 

Emissions Type Component

HPMS Lane miles w/fwy Lane miles wo/f School Transit T

A Network 'Parking' District Service Area 

 1. Start Trip Origins X X 

 2. Running VMT X X X 

 3. Hot Soak Trip Destinations X X 

B Off-Network

 4. Diurnal Number of Vehicles X X 

 5. Resting Loss Number of Vehicles X X  6. Auto Access to Transit Start Trip Origins X X 

 Running Running VMT X X X  Hot Soaks Trip Destinations X X  7a. School Bus VMT X X

 7b. Transit Bus VMT X X  8. Local VMT X X 

Appendix B - Page Number:550
Exhibit 9 A

Percentages forEmissions Distribution by Facility Type

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) (see 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) (see 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 0.07

Appendix B - Page Number:

551
Exhibit 9 B

Percentages forEmissions Distribution by Facility Type

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) (see 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 0.05

Appendix B - Page Number:

552
Exhibit 9 C

Percentages forEmissions Distribution by Facility Type

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) 0.73 

Appendix B - Page Number:

553
Exhibit 9 D

Percentages forEmissions Distribution by Facility Type

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.

Appendix B - Page Number:

554
Exhibit 10

Steps used in the preparation of weighted VMT mix percents 

Rates illustrated are for the District of Columbia 

2002 NOX Emission Rates

Exhaust Emissions Factor

LDGV LDGT12 LDGT34 LDGT HDGV LDDV LDDT HDDV M

A Freeway 0.786 0.841 1.07 0.899 4.928 1.291 1.333 16.906 

Art/Coll 0.757 0.803 1.036 0.863 4.572 1.1820 1.221 12.185 Local 0.825 0.83 1.088 0.896 3.787 1.654 1.695 13.042 

VMT Mix

LDGV LDGT12 LDGT34 LDGT HDGV LDDV LDDT HDDV M

B network 0.4631 0.3349 0.1150 0.0222 0.0007 0.0017 0.0571 0.0053 

local 0.4943 0.3575 0.1226 0.0056 0.001323 0.0008 0.016039 

Weighted VMT mix percents

C=A*B Freeway 36.400 28.165 12.305 1.996 0.345 0.219 7.611 8.960 

Art/Coll 35.057 26.892 11.914 1.916 0.320 0.201 6.972 6.458 Local 40.784 29.671 13.336 0.000 2.112 0.219 0.137 20.918 

Weighted VMT percents by vehicle type for exhaust emissions

D=Normalized C Freeway 0.377 0.292 0.128 0.021 0.004 0.002 0.079 0.093 

Art/Coll 0.389 0.298 0.132 0.021 0.004 0.002 0.077 0.072 Local 0.380 0.276 0.124 0.000 0.020 0.002 0.001 0.195 Vehicle Types are from the EPA Mobile Model outputLDGV Light-Duty Gasoline Vehicles (Passenger Cars)LDGT12 Light-Duty Gasoline Trucks LT 6,000 lbsLDGT34 Light-Duty Gasoline Trucks greater than 6,000 lbsLDGT(all) Light-Duty Gasoline Trucks 

HDGV All weights Heavy-Duty Gasoline VehiclesMC Motorcycles (Gasoline)LDDV Light-Duty Diesel Vehicles (Passenger Cars)LDDT Light-Duty Diesel Trucks HDDV All weights Heavy-Duty Diesel Vehicles 

Appendix B - Page Number:555
EXHIBIT 11

 MOBILE SOURCE EMISSIONS

BY VEHICLE AND FACILITY TYPE

PM 2.5 SIP BASE YEAR 2002

DIRECT PM2.5 EMISSIONS (TONS PER YEAR)

Facility Type EmissRural LDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDInterstate 71 11 9 4 4 0 0 0 1 1 Other Principal Arterial 79 17 13 6 5 0 0 0 1 1 Minor Arterial 42 8 6 3 3 0 0 0 1 1 Major Collector 55 11 9 4 4 0 0 0 1 1 Minor Collector 15 3 2 1 1 0 0 0 0 0 Local 22 5 4 2 0 0 0 0 0 0 UrbanInterstate 426 77 63 29 25 1 0 2 6 6 Other Frwy & Expwy 133 30 23 11 9 0 0 0 2 2 Other Principal Arterial 367 77 61 28 22 1 0 1 5 5 Minor Arterial 281 57 45 21 16 1 0 1 4 3 Collector 141 21 17 8 6 0 0 0 1 1 Local 92 23 17 8 1 0 0 0 0 0 Total 1,725 342 270 125 96 4 2 6 22 21 

% Emissions 19.82% 15.65% 7.26% 5.57% 0.22% 0.10% 0.36% 1.30% 1.22% 5

Emissions by Vehicle Type

Appendix B - Page Number:556
EXHIBIT 12

 MOBILE SOURCE EMISSIONS

BY VEHICLE AND FACILITY TYPE

PM 2.5 SIP BASE YEAR 2002

DIRECT PM10 EMISSIONS (TONS PER YEAR)

Facility Type EmissRural LDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV Interstate 104 17 13 6 6 0 0 1 2 2 8 Other Principal Arterial 114 25 20 9 8 0 0 1 2 2 7 Minor Arterial 60 12 9 4 4 0 0 0 1 1 3 Major Collector 79 16 13 6 5 0 0 0 1 1 5 Minor Collector 21 43 1 1 0 0 0 0 0 1 Local 32 97 3 0 0 0 0 0 0 1 UrbanInterstate 618 113 91 42 36 2 1 2 9 9 41 Other Frwy & Expwy 192 43 34 16 12 0 0 1 3 3 11 Other Principal Arterial 526 112 89 41 33 1 1 2 7 7 30 Minor Arterial 399 83 65 31 24 1 0 1 5 5 22 Collector 188 31 24 11 9 0 0 0 2 2 8 Local 139 40 30 14 2 0 0 1 1 1 3 Total 2,472 505 398 185 140 6 3 9 33 31 139 

% Emissions 20.42% 16.11% 7.48% 5.66% 0.23% 0.11% 0.37% 1.32% 1.24% 5.64% 

Emissions by Vehicle Type

Appendix B - Page Number:557
EXHIBIT 13

 MOBILE SOURCE EMISSIONS

BY VEHICLE AND FACILITY TYPE

PM 2.5 SIP BASE YEAR 2002

 SO2 EMISSIONS (TONS PER YEAR)

Facility Type EmissRural LDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDInterstate 97 16 13 6 5 0 0 1 2 2 Other Principal Arterial 200 44 34 16 14 0 0 1 3 3 Minor Arterial 90 19 15 7 6 0 0 0 1 1 Major Collector 121 26 20 9 8 0 0 1 2 2 Minor Collector 28 6 4 2 2 0 0 0 0 0 Local 47 16 12 6 1 0 0 0 0 0 UrbanInterstate 904 165 134 61 53 2 1 3 13 13 Other Frwy & Expwy 268 61 48 22 17 1 0 1 4 4 Other Principal Arterial 786 173 137 64 51 2 1 3 11 10 Minor Arterial 560 122 96 45 35 1 1 2 8 7 Collector 235 46 36 17 13 0 0 1 3 3 Local 204 72 53 25 3 1 0 1 1 1 Total 3,540 765 602 280 209 9 4 14 48 45 

% Emissions 21.62% 17.02% 7.90% 5.91% 0.24% 0.11% 0.39% 1.37% 1.28% 5

Emissions by Vehicle Type

Appendix B - Page Number:558
EXHIBIT 14

 MOBILE SOURCE EMISSIONS

BY VEHICLE AND FACILITY TYPE

PM 2.5 SIP BASE YEAR 2002

NH3 EMISSIONS (TONS PER YEAR)

Facility Type EmissRural LDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDInterstate 183 30 24 11 10 0 0 1 3 3 Other Principal Arterial 198 43 34 16 14 0 0 1 3 3 Minor Arterial 97 21 17 8 7 0 0 0 1 1 Major Collector 134 29 23 11 9 0 0 1 2 2 Minor Collector 30 7 5 2 2 0 0 0 0 0 Local 68 26 19 9 1 0 0 1 0 0 UrbanInterstate 1,099 202 163 75 65 3 1 4 16 15 Other Frwy & Expwy 338 77 61 28 22 1 0 1 5 4 Other Principal Arterial 893 201 159 74 58 2 1 3 13 12 Minor Arterial 661 149 117 55 43 2 1 2 9 9 Collector 244 55 43 20 16 1 0 1 3 3 Local 301 115 85 40 6 1 1 2 2 2 Total 4,246 955 750 349 251 11 5 17 59 55 

% Emissions 22.50% 17.68% 8.21% 5.92% 0.25% 0.12% 0.41% 1.39% 1.30% 5

Emissions by Vehicle Type

Appendix B - Page Number:559
EXHIBIT 15

 MOBILE SOURCE EMISSIONS

BY VEHICLE AND FACILITY TYPE

PM 2.5 SIP BASE YEAR 2002

Precursor NOX EMISSIONS (TONS PER YEAR)

Facility Type EmissRural LDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDInterstate 4,249 688 555 252 226 11 5 24 76 71 Other Principal Arterial 4,403 962 761 353 302 11 4 21 64 59 Minor Arterial 2,250 469 374 175 147 5 2 10 32 29 Major Collector 3,142 671 534 249 211 8 3 14 45 42 Minor Collector 830 167 133 60 53 2 1 3 11 10 Local 1,567 451 339 161 59 4 2 12 15 14 UrbanInterstate 23,800 4,361 3,535 1,618 1,396 59 28 86 354 332 Other Frwy & Expwy 7,521 1,711 1,337 614 487 18 7 24 106 99 Other Principal Arterial 19,860 4,370 3,445 1,605 1,263 46 21 65 276 258 Minor Arterial 15,315 3,318 2,610 1,224 950 35 16 53 209 196 Collector 6,851 1,302 1,024 474 374 14 6 19 82 76 Local 7,788 2,171 1,645 771 316 19 12 39 77 73 Total 97,575 20,642 16,291 7,557 5,785 232 107 370 1,346 1,260 

% Emissions 21.15% 16.70% 7.75% 5.93% 0.24% 0.11% 0.38% 1.38% 1.29% 5

Emissions by Vehicle Type

Appendix B - Page Number:560
EXHIBIT 16

 MOBILE SOURCE EMISSIONS

BY VEHICLE AND FACILITY TYPE

PM 2.5 SIP BASE YEAR 2002

VOC EMISSIONS (TONS PER YEAR)

Facility Type EmissRural LDGV LDGT12 LDGT34 HDGV MC LDDV LDDT 2BHDDV LHDDV MHDDV Interstate 317 161 82 47 11 6 0 1 0 0 Other Principal Arterial 42 21 11 6 1 1 0 0 0 0 Minor Arterial 411 209 106 62 15 6 0 1 0 0 Major Collector 505 259 131 77 18 7 0 1 1 0 Minor Collector 235 121 61 36 8 3 0 0 0 0 Local 964 504 259 151 31 14 0 1 0 0 UrbanInterstate 5,341 2,725 1,411 783 175 76 2 10 7 6 Other Frwy & Expwy 1,597 809 442 224 47 23 1 3 2 2 Other Principal Arterial 7,138 3,623 1,910 1,024 223 119 3 13 9 8 Minor Arterial 6,087 3,103 1,647 867 182 103 2 9 6 6 Collector 3,814 1,950 1,031 545 115 65 1 4 3 2 Local 17,453 9,151 4,856 2,567 476 311 2 7 1 1 Total 43,904 22,636 11,946 6,388 1,303 732 12 49 29 27 1

% Emissions 51.56% 27.21% 14.55% 2.97% 1.67% 0.03% 0.11% 0.07% 0.06% 0.2

Emissions by Vehicle Type

Appendix B - Page Number:561
EXHIBIT 17

VEHICLE MILES OF TRAVEL

BY VEHICLE AND FACILITY TYPE

BASE YEAR 2002 (Annual Miles 000,000.s )

Vehicle Miles Of Travel

Facility Type VMT VEHICLE TYPERural LDGV LDGT12 LDGT34 HDGV MC LDDV LDDT1234 HDDV2B HDDV345 HDDInterstate 1,134 181 146 68 60 3 2 7 21 19 Other Principal Arterial 2,288 499 393 182 161 6 2 10 34 31 Minor Arterial 1,005 217 173 81 70 2 1 5 15 14 Major Collector 1,365 296 235 109 95 3 1 6 20 19 Minor Collector 293 64 51 23 21 1 0 1 4 4 Local 633 242 177 85 12 2 1 7 4 4 UrbanInterstate 10,440 1,901 1,542 707 616 26 12 37 156 147 Other Frwy & Expwy 3,122 710 556 256 204 7 3 10 44 41 Other Principal Arterial 8,965 2,011 1,584 737 589 21 9 30 128 120 Minor Arterial 6,348 1,425 1,121 526 413 15 7 23 91 85 Collector 2,381 536 422 195 156 6 2 8 34 32 Local 2,778 1,067 787 371 51 8 6 21 18 17 Total 40,752 9,151 7,187 3,339 2,448 101 48 165 570 533 

% Emissions 22.46% 17.63% 8.19% 6.01% 0.25% 0.12% 0.41% 1.40% 1.31% 

Travel data from the Amended Air Quality Conformity of the 2006 CLRP and the FY 2007-202 TIP June 20,2007

Appendix B - Page Number:562
Exhibit 18

Correspondence Between the 28 MOBILE6 Vehicle Classes and the 12 Vehicle Classes Used in the NIF covnersion

28 

MOBILE6 

Vehicle 

Code

12 NIF 

Vehicle 

Codes Description

1 LDGV LDGV Light-Duty Gasoline Vehicles (Passenger Cars)

2 LDGT1 LDGT1 Light-Duty Gasoline Trucks 1 (0-6,000 lbs. GVWR, 0-3750 lbs. LVW)

LDGT2 LDGT1 Light-Duty Gasoline Trucks 2 (0-6,000 lbs. GVWR, 3751-5750 lbs. LVW)LDGT3 LDGT2 Light-Duty Gasoline Trucks 3 (6,001-8,500 lbs. GVWR, 0-5750 lbs. ALVW)

3 LDGT4 LDGT2 Light-Duty Gasoline Trucks 4 (6,001-8,500 lbs. GVWR, 5751 lbs. and greater ALVW)4 HDGV2B HDGV Class 2b Heavy-Duty Gasoline Vehicles (8501-10,000 lbs. GVWR)

HDGV3 HDGV Class 3 Heavy-Duty Gasoline Vehicles (10,001-14,000 lbs. GVWR)

HDGV4 HDGV Class 4 Heavy-Duty Gasoline Vehicles (14,001-16,000 lbs. GVWR)

HDGV5 HDGV Class 5 Heavy-Duty Gasoline Vehicles (16,001-19,500 lbs. GVWR)

HDGV6 HDGV Class 6 Heavy-Duty Gasoline Vehicles (19,501-26,000 lbs. GVWR)

HDGV7 HDGV Class 7 Heavy-Duty Gasoline Vehicles (26,001-33,000 lbs. GVWR)

HDGV8A HDGV Class 8a Heavy-Duty Gasoline Vehicles (33,001-60,000 lbs. GVWR)

HDGV8B HDGV Class 8b Heavy-Duty Gasoline Vehicles (>60,000 lbs. GVWR)

HDGB HDGV Gasoline Buses (School, Transit and Urban)

5 MC MC Motorcycles (Gasoline)6 LDDV LDDV Light-Duty Diesel Vehicles (Passenger Cars)

LDDT12 LDDT Light-Duty Diesel Trucks 1 and 2 (0-6,000 lbs. GVWR)

7 LDDT34 LDDT Light-Duty Diesel Trucks 3 and 4 (6,001-8,500 lbs. GVWR)

8 HDDV2B 2BHDDV Class 2b Heavy-Duty Diesel Vehicles (8501-10,000 lbs. GVWR)

HDDV3 LHDDV Class 3 Heavy-Duty Diesel Vehicles (10,001-14,000 lbs. GVWR)

9 HDDV4 LHDDV Class 4 Heavy-Duty Diesel Vehicles (14,001-16,000 lbs. GVWR)

HDDV5 LHDDV Class 5 Heavy-Duty Diesel Vehicles (16,001-19,500 lbs. GVWR)

10 HDDV6 MHDDV Class 6 Heavy-Duty Diesel Vehicles (19,501-26,000 lbs. GVWR)

HDDV7 MHDDV Class 7 Heavy-Duty Diesel Vehicles (26,001-33,000 lbs. GVWR)

11 HDDV8A HHDDV Class 8a Heavy-Duty Diesel Vehicles (33,001-60,000 lbs. GVWR)

HDDV8B HHDDV Class 8b Heavy-Duty Diesel Vehicles (>60,000 lbs. GVWR)

12 HDDBT BUSES Diesel Transit and Urban Buses

HDDBS BUSES Diesel School Buses

Appendix B - Page Number:563