MARYLAND DEPARTMENT OF THE ENVIRONMENT

AIR AND RADIATION MANAGEMENT ADMINISTRATION

State Implementation Plan 

APPENDIX A-1 

2002 Base Year SIP Emissions 

Inventory Methodologies 

Prepared for: 

U.S. Environmental Protection Agency 

Prepared By: 

Maryland Department of the Environment 
Maryland Department of the Environment 

2002 Base Year Emissions Inventory Methodologies 

© Maryland Department of the Environment 

Air and Radiation Management Administration 

1800 Washington Boulevard, Suite 730 

Baltimore, Maryland 21230 

Phone 410.537.3240 • Fax 410.631.3202 
Table of Contents 

1.0 POINT SOURCES........................................................................................................................4

1.1 INTRODUCTION..........................................................................................................................4 

1.2 COMPILING THE POINT SOURCE LIST ..................................................................................4 

1.2.1 EMISSION CALCULATIONS..................................................................................................... 5 

1.2.1.1 Seasonal Adjustments.................................................................................................................6 

1.2.2 Consolidated Emissions Reporting Rule (CERR)......................................................................... 6 

2.0 QUASI - POINT SOURCES........................................................................................................7

2.1 INTRODUCTION..........................................................................................................................7 

2.2 ABERDEEN PROVING GROUNDS............................................................................................7 

2.3 ANDREWS AIR FORCE BASE .................................................................................................14 

2.4 BALTIMORE-WASHINGTON INTERNATIONAL AIRPORT (BWI) ...................................19 

3.0 AREAS SOURCES.....................................................................................................................23

3.1 EMISSION ESTIMATION METHOD BY CATEGORY ..........................................................23 

3.1.1 PETROLEUM DISTRIBUTION LOSSES................................................................................. 23 

3.1.1.1 Tank Truck Unloading .............................................................................................................24 

3.1.1.2 Stage II Refueling.....................................................................................................................29 

3.1.1.3 Underground Tank Breathing...................................................................................................31 

3.1.1.4 Gasoline Tank Trucks in Transit ..............................................................................................34 

3.1.1.5 Aircraft Refueling.....................................................................................................................37 

3.1.1.6 Petroleum Vessel Unloading Losses........................................................................................39 

3.1.1.7 Portable Fuel Containers ..........................................................................................................44 

3.1.2 STATIONARY SOURCE SOLVENT APPLICATION ............................................................ 50 

3.1.2.1 Dry Cleaners.............................................................................................................................50 

3.1.2.2 Surface Cleaning (Cold Cleaning Degreasing) ........................................................................50 

3.1.2.3 Architectural Surface Coating ..................................................................................................54 

3.1.2.4 Auto Refinishing ......................................................................................................................61 

3.1.2.5 Traffic Markings.......................................................................................................................64 

3.1.2.6 Industrial Surface Coating........................................................................................................68 

3.1.2.7 Industrial Adhesives and Sealants............................................................................................74 

3.1.2.8 Graphic Arts .............................................................................................................................75 

3.1.2.9 Asphalt Paving..........................................................................................................................79 

3.1.2.10 Synthetic Organic Chemical Storage Tanks.........................................................................81 

3.1.2.11 Pesticide Application............................................................................................................82 

3.1.2.12 Commercial/Consumer Solvent Use ....................................................................................87 

3.1.3 BIOPROCESS EMISSIONS SOURCES.................................................................................... 89 

3.1.3.1 Bakeries....................................................................................................................................89 

3.1.3.2 Breweries..................................................................................................................................92 

3.1.3.3 Wineries....................................................................................................................................94 
3.1.3.4 Distilleries.................................................................................................................................95 

3.1.4 CATASTROPHIC/ACCIDENTAL RELEASES ....................................................................... 96 

3.1.4.1 Oil Spills...................................................................................................................................96 

3.1.4.2 Leaking Underground Storage Tanks.......................................................................................98 

3.1.5 SOLID WASTE DISPOSAL, TREATMENT, AND RECOVERY......................................... 100 

3.1.5.1 On-site Incineration................................................................................................................100 

3.1.5.2 Publicly Owned Treatment Works (POTWs).........................................................................101 

3.1.5.3 Open Burning – Land Clearing Debris...................................................................................103 

3.1.5.4 Open Burning – Residential Municipal Solid Waste .............................................................106 

3.1.5.5 Open Burning – Residential Yard Waste ...............................................................................112 

3.1.5.6 Cremation – Animal and Human............................................................................................118 

3.1.5.7 Municipal Solid Waste Landfills............................................................................................121 

3.1.6 SMALL STATIONARY SOURCE FOSSIL FUEL USE ........................................................ 125 

3.1.6.1 Small Electric Utility Boilers .................................................................................................125 

3.1.6.2 Other Fuel Consumption ........................................................................................................125 

3.1.6.3 Fuel Oil Combustion ..............................................................................................................126 

3.1.6.4 Coal Combustion....................................................................................................................128 

3.1.6.5 Natural Gas Combustion ........................................................................................................135 

3.1.6.6 Liquified Petroleum Gas Combustion....................................................................................140 

3.1.6.7 Wood Combustion..................................................................................................................146 

3.1.7 FUGITIVE SOURCES.............................................................................................................. 153 

3.1.7.1 Residential Construction Activity ..........................................................................................153 

3.1.7.2 Heavy Construction Activity..................................................................................................157 

3.1.7.3 Road Construction Activity....................................................................................................160 

3.1.7.4 Agricultural Land Preparation................................................................................................163 

3.1.7.5 Paved Roads ...........................................................................................................................167 

3.1.7.6 Unpaved Roads.......................................................................................................................171 

3.1.8 FIRE SOURCES ....................................................................................................................... 172 

3.1.8.1 Vehicle Fires...........................................................................................................................172 

3.1.8.2 Forest Fires.............................................................................................................................174 

3.1.8.3 Slash/Prescribed Burning .......................................................................................................177 

3.1.8.4 Agricultural Burning ..............................................................................................................179 

3.1.8.5 Structure Fires ........................................................................................................................179 

3.1.8.6 Orchard Heaters......................................................................................................................182 

3.1.9 AMMONIA SOURCES ............................................................................................................ 183 

3.1.9.1 Cows (Milk Cows, Beef Cows, Heifers, and Steers) .............................................................184 

3.1.9.2 Hogs and Pigs.........................................................................................................................186 

3.1.9.3 Chickens (Pullets, Layers, and Broilers)................................................................................188 

3.1.9.4 Sheep ......................................................................................................................................190 

3.1.9.5 Goats (Angora and Milk)........................................................................................................192 

3.1.9.6 Horses.....................................................................................................................................194 

3.1.9.7 Ducks, Geese and Turkeys.....................................................................................................196 

3.1.9.8 Agricultural Fertilizer Application.........................................................................................198 

3.1.9.9 Human Breath and Perspiration..............................................................................................202 

4.0 NONROAD SOURCES............................................................................................................204

4.1 NONROAD VEHICLES/ENGINES..........................................................................................204 
4.2 NONROAD MODEL.................................................................................................................205 

4.2.1 NONROAD Model Equipment ................................................................................................. 207 

4.3 RAILROADS .............................................................................................................................209 

4.4 AIRCRAFT ................................................................................................................................214 

4.4.1 Commercial Aircraft.................................................................................................................. 216 

4.4.2 General Aviation ....................................................................................................................... 219 

4.4.3 Military Aircraft ........................................................................................................................ 221 

4.5 MARINE VESSELS ........................................................................................................................224 

5.0 ONROAD MOBILE SOURCES.............................................................................................228

5.1 INTRODUCTION......................................................................................................................228 

5.2 EMISSION FACTORS ..............................................................................................................230 

5.3 VEHICLE MILES TRAVELED................................................................................................230 

5.4 KEY TRAVEL DATA INPUTS................................................................................................230 

5.5 MOBILE INPUT PARAMETERS.............................................................................................234 

5.6 OTHER DATA INPUTS............................................................................................................235 

5.7 EMISSION PROCESS OUTPUTS............................................................................................236 

5.8 CONVERSION TO NIF FORMAT...........................................................................................237 

6.0 BIOGENIC EMISSIONS ........................................................................................................238

6.1 INTRODUCTION......................................................................................................................238 
4 

1.0 POINT SOURCES

1.1 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.”

1.2 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. 
5 

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. 

1.2.1 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. 

 
6 

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. 

1.2.1.1 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. 

1.2.2 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. 
2.0 QUASI - POINT SOURCES 

2.1 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. 

2.2 ABERDEEN PROVING GROUNDS 

Description

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. 

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. 

7 
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. 

Pollutants 

VOC, NOx, CO, PM, Toxics 

Emission

Source 

Categories 

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 

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 

8 

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 

Emission estimation methodologies varied by source category. A brief synopsis of the methodologies is 

presented below. 

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.

9 
10 

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)

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. 
11 

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. 

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. 

Spatial 

Spatial allocation of the emission estimates to specific areas within APG is not available. 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

12 
13 

Temporal 

Data for temporal allocation is not available for this source. 
2.3 ANDREWS AIR FORCE BASE 

Description

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: 

Pollutants 

Emission

Source 

Categories 

• Mobile On-Road Source Emissions 

o Mobile - LDGV 

o Mobile - LDGT12 

14 
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 

Emission estimation methodologies varied by source category. A brief synopsis of the 

methodologies is presented below. 

15 
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)

16 
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 

17 
Adjustment for 

Controls 

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. 

 

Spatial and 

Temporal 

Allocations

18 
19 

2.4 BALTIMORE-WASHINGTON INTERNATIONAL AIRPORT (BWI) 

Description

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: 

Pollutants 

Emission

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 
20 

• 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 

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 
21 

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 
22 

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
23 

3.0 AREAS SOURCES

3.1 EMISSION ESTIMATION METHOD BY CATEGORY 

3.1.1 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. 
24 

3.1.1.1 Tank Truck Unloading 

SCC: 25 01 060 053 

Description:

 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 EIIP1

, 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 

Pollutants 

Method and

Data Sources: 

 

1

 Emission Inventory Improvement Program
25 

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 expression2

: 

T

S P M LL* * =12.46*

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. 

( ) ( ) ⎭

⎬

⎫

⎩

⎨

⎧ ⎟ +

⎠

⎞ ⎜

⎝

⎛

+ − ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟ −

⎠

⎞ ⎜

⎝

⎛

+

+ ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛

+ − − ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛

+ = − 15.64459.6

8742 2.013 log 459.62416

459.6

1042 *log 1.854

459.6

413.0

exp 0.7553 10

0.5

10

0.5

T

RVP

T

S

T

S RVP

T

P

 

2

 AP42, Chapter 5.2: Transportation and Marketing of Petroleum Liquids 
26 

Proportioning the loading factors yields 

1* 2

2* 1

1

12.46* 1* 1* 1

2

12.46* 2* 2* 2

1

2

P T

P T

T

S P M

T

S P M

LL

LL = = 1* 2

2* 1 2 1*

P T

P T LL = LL

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 

0.2828

5.186 * 541.8

5.094 * 520 0.3*

1* 2

2 * 1 2 = 1* = = P T

P T LL LL

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 

Point Source 

Adjustments 

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. 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations
27 

Emissions 

Calculation 

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 20023

 = 2,570,356,195 gallons 

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration 

proportion: 

Carroll County vehicle registration4 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 

 

3

 Annual sales of gasoline from Maryland Comptroller of the Treasury, Gasoline Tax Division 4

 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program.
28 

 

[86,914,019.269 gallons of gasoline sold in Carroll County in 2002 x 91 percent5 filled by 

balanced submerged filling method x 0.2453 lbs.. VOC per 1000 gallons of gasoline6

 ] + 

[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 gasoline7

 ] = 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 

5

 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. 

6

 Emission factor for balanced submerged filling from AP-42 Volume I, Table 5.2-7. 7

 Emission factor for submerged filling from AP-42 Volume I, Table 5.2-7. 
29 

3.1.1.2 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 
30 

Point Source 

Adjustments 

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: 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

(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. 
31 

3.1.1.3 Underground Tank Breathing 

SCC: 25 01 060 201 

Description:

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 EIIP8

, 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. 

Pollutants 

Method and

Data Sources: 

 

8

 Emission Inventory Improvement Program
32 

Point Source 

Adjustments 

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: 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

(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 20029

 = 2,570,356,195 gallons 

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration 

proportion: 

 

9

 Annual sales of gasoline from Maryland Comptroller of the Treasury, Gasoline Tax Division 
33 

Carroll County vehicle registration10 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 gasoline11 ] = 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. 

 

 

10 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program. 

11 Emission factor from AP-42 Volume I, Table 5.2-7. 
34 

3.1.1.4 Gasoline Tank Trucks in Transit 

SCC: 25 05 030 120 

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. 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. 

Pollutants 

VOC 

The method used to calculate emissions (all VOC), is presented in EIIP12, 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. 

Method and

Data Sources 

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 

 

12 Emission Inventory Improvement Program
35 

/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 200213 = 2,570,356,195 gallons 

Allocate gallons of fuel sold to the county level by the 2002 county vehicle registration 

proportion: 

Carroll County vehicle registration14 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 gasoline15 ] = 6,518.55 lbs. VOC emitted. 

 

13 Annual sales of gasoline from Maryland Comptroller of the Treasury, Gasoline Tax Division 14 State of Maryland Motor Vehicle Administration and MDE Mobile Sources Control Program . 
36 

 

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. 

15 Emission factor from AP-42 Volume I, Table 5.2-7. 
37 

3.1.1.5 Aircraft Refueling 

SCC: 22 75 900 000 

Description

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. 

Pollutants 

Method and

Data Sources 

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 
38 

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 barrels16 = 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 14.8635817 = 256.721 lbs. VOC /year 

Emissions-GA Refueling Allegany = 256.721 ÷ (2000 x 365) = 0.0004 tons VOC /day 

 

16 From Department of Energy State Energy Data Report 

17 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, 
39 

3.1.1.6 Petroleum Vessel Unloading Losses 

SCC: 25 05 020 000 

Description

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 

Pollutants 
40 

Method and

Data Sources 

Activity 

The method used to calculate emissions (all VOC) is presented in EIIP18, 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: 

 

18 Emission Inventory Improvement Program
41 

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) 

Density19

(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) 

 

19 AP-42, Table 7.1-2 
42 

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 
43 

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 

 
44 

 

3.1.1.7 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: 

Description

• 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 CARB20 survey and

methodology adopted by OTC21. 

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 

Pollutants 

Method and

Data Sources 

20 ARB’s Mailout MSC 99-25, “Public Meeting to Consider Approval of CA’s Portable Gasoline-Container 

Emissions Inventory, “ (ARB, 199b) 21 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. 
45 

 

(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 businesses22 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). 

Point Source 

Adjustments 

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 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

22 Total 2002 employment and business establishments by 6 digit NAICS code and by county, County Business 

Patterns 
46 

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 
47 

 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 
48 

)

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) 
49 

 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 

 
50 

3.1.2 STATIONARY SOURCE SOLVENT APPLICATION 

3.1.2.1 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. 

3.1.2.2 Surface Cleaning (Cold Cleaning Degreasing) 

SCC: 24 15 300 000 

Description

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 

Pollutants 
51 

MDE staff used an alternative per capita emission estimation method documented in EIIP23, 

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:

Method and

Data Source

 

23 Emission Inventory Improvement Program
52 

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 4.6-124. 

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: 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

 

24 Nonmethane VOC Emissions from small cold cleaning degreasing operations 
53 

Equation:

[ ] CC CC CC PtSourceCC

j cc

CC CE RE RP E POP EF E −

⎭

⎬

⎫

⎩

⎨

⎧ = * 1− ( * * ) 2000*312

*

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)

(503,38825 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/year26 = 2,164,568 lbs. per person VOC emitted. 

Converting to tons per day: 2,164,568 / (312 operating days per year27 x 2000 pounds per ton) = 

3.469tons VOC per day emitted (there is no seasonal adjustment28). 

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 

 

25 Population data from the U.S. Bureau of Census, Population Estimates Branch 26 Emission factor from EIIP 27 6 days per week operation from EIIP 28 No seasonal adjustment from EIIP 
54 

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. 

3.1.2.3 Architectural Surface Coating 

SCC: 24 01 001 000 

Description

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 EIIP29, 

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 quantities30 for solvent- and water-based coatings by the U.S. population31 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: 

Pollutants 

Method and

Data Sources 

 

29 Emission Inventory Improvement Program 30 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. 31 Population data from the U.S. Bureau of the Census, Population Estimates Branch . 
55 

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 
56 

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 
57 

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 
58 

 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
59 

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:

Emissions 

Calculation 

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 efficiency32 for architectural surface coatings 

RE ASC = Rule effectiveness33 for architectural surface coatings 

RP ASC = Rule penetration for architectural surface coatings

Equation to calculate water-based emissions is:

E POPi x UF ASC - WB x EF ASC - WB x SAF ASC x [(1 – (CE ASC x RE ASC x RP ASC )] 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

 

32 A 20% reduction in emissions is due to EPA’s AIM regulation 33 EPA’s AIM regulation is a federal rule applying to architectural surface coatings 
60 

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 

 
61 

3.1.2.4 Auto Refinishing 

SCC: 24 01 005 000 

Description

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 

EIIP34, 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. 

Pollutants 

Method and

Data Sources 

 

34 Emission Inventory Improvement Program
62 

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: 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

EMP J x EF AR x [ 1- (RE x RP x CE)] E AR = 260 - E Point Source AR 
63 

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)

59435 x 0.385836 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 

 

35 Employee data from County Business Patterns - Maryland 

36 Emission factor from EIIP Chapter 13 – Auto Body Refinishing 
64 

3.1.2.5 Traffic Markings 

SCC: 24 01 008 000 - Traffic paints 

SCC: 24 01 008 999 - Traffic paint solvents 

Description

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. 

Pollutants 

Method and

Data Sources 
65 

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 
66 

(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 - October37 = 4,671 gallons 

Total VOC per gallon of yellow paint used38 = 0.78 lbs. VOC /gallon 

Total white gallons used April – October39 = 6,481 gallons 

Total VOC per gallon of white paint used40 = 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. 

 

37 Reported by Caroline County's Department of Public Works, Division of Highways 

38 MSDS from Caroline County's Department of Public Works, Division of Highways 

39 Reported by Caroline County's Department of Public Works, Division of Highways 

40 MSDS from Caroline County's Department of Public Works, Division of Highways 
67 

(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 
68 

3.1.2.6 Industrial Surface Coating 

Description

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 EIIP41, 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. 

Pollutants 

Method and

Data Sources 

 

41 Emission Inventory Improvement Program
69 

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 
70 

Point Source 

Adjustments 

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:

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

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 
71 

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): 7742

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

43

E MC-ADJ – Baltimore = 0.6727 – 0.00 

E MC-ADJ – Baltimore = 0.6635 tons VOC per day 

 

42 Table 8.5-1, EIIP Chapter 8 Industrial Surface Coatings 

43 Point Source Reduction from JCB Incorporated (SIC 3531) 
72 

 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
73 

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

503,38844 x 0.6 lbs. VOC/capita/year45 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 

 

44 2002 estimated population from U.S. Bureau of the Census, Population Estimation Branch . 

45 Emission factor from EIIP Industrial Surface Coating 
74 

 

3.1.2.7 Industrial Adhesives and Sealants 

SCC: 2440020000 

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.

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 Freedonia46 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)47. 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. 

Pollutants 

Method and

Data Sources 

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

47 National Paint and Coating Association (NP&CA) “Paints and Coatings ‘2000': Review

and Forecast” 
75 

3.1.2.8 Graphic Arts 

SCC: 24 25 000 000 

Description

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 EIIP48, 

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. 

Pollutants 

Method and

Data Sources 

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 

 

48 Emission Inventory Improvement Program
76 

Point Source 

Adjustments 

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. 

Adjustment for 

Controls 

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:

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

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) 
77 

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 
78 

2002 Example Calculation Graphic Arts (Anne Arundel County)

E GA = 503,38849 x 1.3 lbs. VOC/capita/year50 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 

 

49 2002 estimated population from U.S. Bureau of the Census, Population Estimation Branch . 

50 Emission factor from EIIP Chapter 7 Graphic Arts 
79 

3.1.2.9 Asphalt Paving 

SCC: 24 61 022 000 

Description

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

Pollutants 

Method and

Data Sources 

Point Source 

Adjustments 

Adjustment for 

Controls 
80 

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: 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

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 

503,38851 x 0.004 lbs. VOC/capita/year52 = 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

 

51 Population data from U.S. Bureau of the Census, Population Estimates Branch 52 Emission factor from the Short List of AMS SCCs and Emission Factors from EPA National Air Data Branch. 
81 

3.1.2.10 Synthetic Organic Chemical Storage Tanks 

This category is fully represented in the point source inventory. 
82 

3.1.2.11 Pesticide Application 

SCC: 24 61 800 000 

Description

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. 

Pollutants 

Method and

Data Source: 
83 

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
84 

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
85 

 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
86 

 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. 
87 

3.1.2.12 Commercial/Consumer Solvent Use 

SCC: 24 65 000 000 

Description

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. 

Pollutants 

Method and

Data Sources 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations
88 

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: 

Emissions 

Calculation 

[ 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)

[ (503,38853) x (7.84 54) ] - [ (503,388 x 3.955 ) x 

(0.20)56 E CC = ]

2000 x 365

E CC = 4.868 tons VOC per day

 

53 Population data from U.S. Bureau of Census, Population Estimates Branch 54 Emission factor from EIIP Chapter 5 Commercial and Consumer Solvent Use 55 EPA memo from John Sietz 56 EPA memo from John Sietz
89 

3.1.2.12.1 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. 

3.1.3 BIOPROCESS EMISSIONS SOURCES 

3.1.3.1 Bakeries 

SCC: 23 02 050 000 

Description

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 

Pollutants 

Method and

Data Sources 
90 

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: 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

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 
91 

Point Source Adjustments

E BAK-ADJ = E BAK - E BAK – Pt. Sources

57

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 

 

57 Point Source Reduction from MDE ARMA registration files 
 92

3.1.3.2 Breweries 

SCC: 23 02 070 001 

Description

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. 

Pollutants 

Method and

Data Sources 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations
 93

Temporal 

Data for temporal allocation is not available for this source. 

The equation used to estimate emissions from bakeries is: 

Emissions 

Calculation 

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 
 94

3.1.3.3 Wineries 

Description

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-4258, 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.

Pollutants 

Method and

Data Sources 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

 

58 AP42, Chapter 9.12.2: Food and Agricultural Industries, Beverages, Wines and Brandies 
 95

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. 

Emissions 

Calculation 

3.1.3.4 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. 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. 

Pollutants 

Method and

Data Sources 
 96

3.1.4 CATASTROPHIC/ACCIDENTAL RELEASES 

3.1.4.1 Oil Spills 

SCC: 28 30 000 000 

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 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. 

Pollutants 

Method and

Data Sources 

Point Source 

Adjustments 
 97

Adjustment for 

Controls 

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: 

 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

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 
 98

3.1.4.2 Leaking Underground Storage Tanks 

SCC: 26 60 000 000 

Description

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. 

Pollutants 

Method and

Data Sources 

Point Source 

Adjustments 

Adjustment for 

Controls 
 99

Spatial and 

Temporal 

Allocations

Spatial 

Data for spatial allocation is not available for this source. 

Temporal 

Data for temporal allocation is not available for this source. 

Emissions 

Calculation 

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 
 100

3.1.5 SOLID WASTE DISPOSAL, TREATMENT, AND RECOVERY 

3.1.5.1 On-site Incineration 

SCC: 26 01 000 000 

Description

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. 

Pollutants 

Method and

Data Sources 
 101

3.1.5.2 Publicly Owned Treatment Works (POTWs) 

SCC: 26 30 020 000 

Description

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.

Pollutants 

Method and

Data Sources 

Point Source 

Adjustments 

Adjustment for 

Controls 
 102

Spatial and 

Temporal 

Allocations

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: 

Emissions 

Calculation 

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 factor59 for POTWs 

SAF POTW = Seasonal adjustment factor60 for peak ozone season which is 1.4 

2002 Sample Calculation for POTW VOC Emissions (Anne Arundel County): 

Back River Sewage Treatment Plant statistics61: 

Average daily flow (MGD)62: 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 

 

59 Emission factor taken from Procedures, Section 3.5.1 60 Seasonal adjustment factor taken from Procedures, Table 5.8.1 61 Supplied by the Maryland Water Management Administration 62 MGD : Million Gallons per Day 
 103

3.1.5.3 Open Burning – Land Clearing Debris 

SCC: 26 10 000 500 

Description

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 EIIP63, 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. 

Pollutants 

Method and

Data Sources 

 

63 Emission Inventory Improvement Program
 104

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 64

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. 

 

64 Emissions factors for VOC NOx, CO, SO2, PM10 and PM2.5 were obtained from AP-42 Table 2.5-1. 
 105

Point Source 

Adjustments 

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 

Adjustments 

for Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

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 
 106

 

3.1.5.4 Open Burning – Residential Municipal Solid Waste 

SCC: 26 10 030 000 

Description

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.”65

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 

Pollutants 

Method and

Data Sources 

65 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. 
 107

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 burning66 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)] 

Point Source 

Adjustments 

Adjustments 

for Controls 

 

66 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. 
 108

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 
 109

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)

Spatial and 

Temporal 

Allocations

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 
 110

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 

Calculation 

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
 111

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 
 112

 

3.1.5.5 Open Burning – Residential Yard Waste 

 SCC: 26 10 000 100 (Leaf Debris) 

 SCC: 26 10 000 400 (Brush Debris) 

Description

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. 

Pollutants

VOC, NOx, SOx, CO, PM10, PM2.5, and Toxics

Method and

Data Sources 

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.”67

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 

67 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. 
 113

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 burning68 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 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

 

68 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. 
 114

Pennsylvania, unless a jurisdiction or county (e.g., Allegheny County) was determined via 

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 

survey to have a ban, it will be assumed that suburban and rural areas allow open burning. For 
 115

In determining annual emissions for those areas with a seasonal ban, Pechan adjusted the RP 

during this season, we assume that 2 percent of the summer season brush burning in August is 

Temporal 

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. 

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 

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 and 

Temporal 

Allocations

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). 

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)
 116

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 

Weekend Day Hour 

Temporal Allocation Profile Formats (daily; weekend day)

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 

Calculation 

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: 
 117

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 
 118

3.1.5.6 Cremation – Animal and Human 

 SCC: 31 502 102 

Description

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.

Pollutants 

Air Toxics (Criteria Pollutants were not calculated) 

Method and

Data Sources 

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.
 119

Emission Factors 

Emission factors these hazardous air pollutants, except formaldehyde, were taken from the 

State of California Air Resources Board Test Report No. C-90-00469. The emission factor 

used for formaldehyde was reported in the USEPA FIRE70 system database.

Emission factors were converted to a pound per ton basis using the procedure provided by 

the Emission Standards Division71. 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 America72 that 21.13 percent of bodies 

were cremated and that there were 2,322,265 deaths in the United States in 199673.

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

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

 

69 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 70 U.S. EPA. Factor Information Retrieval (FIRE) System Database, Version 5.1a. Research Triangle Park, NC. 

September 1995. 71 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. 72 Cremation Association of North America. 1996 Statistics as found on the Internet Cremation Society, Cremation 

Stats Nationwide webpage: www.cremation.org/stats.htm 73 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. 
 120

E CREM = Annual emissions from crematories 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

Spatial 

Data for spatial allocation is not available for this source. 

Temporal 

Data for temporal allocation is not available for this source. 

Emissions 

Calculation 

The equation for estimating emissions from crematories is: 

where:

TON cty = Tons cremated per year in county

EF = Emission Factor per pollutant (lbs/ton) 

2002 Sample Calculation (Harford County)

Arsenic Annual Emissions: 

EF = 0.0004 lbs Arsenic/Ton Cremated 

TON cty = 26

(26) x (0.0004) E CREM = (2000 lbs/ton) 

E CREM = 5.20E-06 tons Arsenic per Year 
 121

3.1.5.7 Municipal Solid Waste Landfills 

SCC: 26 20 030 000 

Description

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.

Pollutants 

VOC 

The method used to calculate emissions, is presented in AP-42, Chapter 2.4, Municipal Solid 

Waste Landfills and EIIP74, 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;

74 Emission Inventory Improvement Program

Method and

Data Sources 
 122

 The design capacity of the landfill, 

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 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: 
 123

Lo : 100.00 m3

 / Mg 

Landgem Model Parameters AP-42 Default Values 

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. 

Point Source 

Adjustments 

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: 

Adjustments for 

Controls 

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%) 
 124

Spatial and 

Temporal 

Allocations

Data for spatial and temporal allocation is not available for this source. 
 125

3.1.6 SMALL STATIONARY SOURCE FOSSIL FUEL USE 

3.1.6.1 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. 

3.1.6.2 Other Fuel Consumption 

Coke and process gas emissions will be inventoried as point sources. 
 126

3.1.6.3 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) 

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 

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. 

Pollutants

PM10, PM2.5, SOx, NOx, CO, VOC

Method and

Data Sources 

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 Energy75.

Emission Factors

Emission factors were obtained from AP-4276, 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

 

75 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". 76 Emission Factors from AP-42 Tables 1.3-1 and 1.3-3 
 127

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

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

Spatial

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). 

 

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 

EIIP77 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 

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).78

77 Emissions Inventory Improvement Program (EIIP) Area Source Method Abstract – Residential and

Commercial/Institutional Fuel Oil and Kerosene Combustion, dated April 2002 78 http://www.noaa.gov (home page) or http://www.ncdc.noaa.gov/ol/climate/climateproducts.html#PUBS (for a list 

of available data) 
 128

3.1.6.4 Coal Combustion 

SCC: 21 04 002 000 (Residential Coal) 

SCC: 21 03 002 000 (Commercial/Institutional Coal) 

Description

Residential 

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. 

Pollutants

PM10, PM2.5, SOx, NOx, CO, VOC

Method and

Data Sources 

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. 
 129

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 79

(lbs./kgal) 

Residential 9.10 275.00 10.00 6.20 62.00

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

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 EIIP80 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).81

79 MDE assumed an average sulfur content in coal of 2% 80 Emissions Inventory Improvement Program (EIIP) Area Source Method Abstract – Natural Gas and LPG

Combustion, dated April 2002 81 http://www.noaa.gov (home page) or http://www.ncdc.noaa.gov/ol/climate/climateproducts.html#PUBS (for a list 

of available data) 
 130

∑ =

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

Emissions 

Calculation 

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
 131

Ozone DAYS = Number of days in the ozone season: 214 Residential; 168 Commercial 

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 

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 
 132

HDD ANNUAL

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 

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 
 133

Activity 

Description – Commercial and Institutional Coal 

 

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.

Methods and 

Data Sources 

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. 

(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 82

(lbs./kgal) 

Commercial / 

Institutional 8.50 8.50 0.675 6.10 69

 

82 MDE assumed an average sulfur content in coal of 2%
 134

Adjustments 

for Controls 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

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. 

Emissions 

Calculation 
 135

(i) Number of Dwelling Units using Natural Gas 

3.1.6.5 Natural Gas Combustion 

SCC: 21 04 060 000 (Residential Natural Gas) 

SCC: 21 03 060 000 (Commercial/Institutional Natural Gas) 

Description

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. 

Pollutants

PM10, PM2.5, SOx, NOx, CO, VOC

Method and

Data Sources 

The following assumptions were made in the computation of the emissions from natural gas 

combustion. 

Activity 

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 
 136

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

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

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.
 137

= 

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: 
 138

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

NatGas i HotWaterApp J

CoAnnual

NatGas i SpaceHeat J CoOzSeason

NatGas

Ozone

EF NG

HDD

EF NG HDD

E

⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡

=

− − − −

2000

*

*

2000

( * )

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 

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

NG Hot water/App - J = Natural gas consumed for during ozone season by hot water and 

appliances in county j

Total Residential Natural Gas Consumption – Baltimore City83 14,483 M ft3

Percent natural gas used for cooking & appliances in the State of Maryland84

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 
 139

 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 Hot Water Fuel PERIOD Hot Water Fuel ANNUAL

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 

= 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. 

 
 140

SCC: 21 04 007 000 (Residential LPG) 

The following assumptions were made in the computation of the emissions from liquified 

petroleum gas (LPG) combustion. 

1. Number of Dwelling Units using LPG 

3.1.6.6 Liquified Petroleum Gas Combustion 

SCC: 21 03 007 000 (Commercial/Institutional LPG) 

Description

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). 

Pollutants

PM10, PM2.5, SOx, NOx, CO, VOC

Method and

Data Sources 

 

Activity 

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.

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. 

Residential and Commercial LPG Activity Consumption Data
 141

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). 

Emission Factors

LPG Emission Factors 

NOx 

(lbs./kgal) 

CO 

(lbs./kgal) 

PM 2.5 

(lbs./kgal) 

SOx 

(lbs./kgal) 

VOC PM 10 

(lbs./kgal) (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

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

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 EIIP85 in an Area Source 

Method Abstract for natural gas and LPG combustion. 

 

Spatial and 

Temporal 

Allocations

Spatial

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). 

85 Emissions Inventory Improvement Program (EIIP) Area Source Method Abstract – Natural Gas and LPG

Combustion, dated April 2002
 142

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).86

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 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). 

 

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 

 

86 http://www.noaa.gov (home page) or http://www.ncdc.noaa.gov/ol/climate/climateproducts.html#PUBS (for a list 

of available data) 
 143

= 

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: 

Residential Fuel ANNUAL HDD ANNUAL

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 = x

where:

Residential Fuel MONTH = Space heating fuel use for inventory month

Residential Fuel ANNUAL = Space heating fuel use for inventory year 

Emission Calculation

 HDD MONTH = Heating degree days for inventory month

 HDD ANNUAL = Heating degree days for inventory year

Emissions 

Calculation 

Ozone Season Daily Emissions

Equation:
 144

(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

 Residential LPG Hot water/App - J = 25% x LPG BALTIOMORE COUNTY 

LPG used for space heating in Baltimore County 

= 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 4,264.4 

 Residential LPG Hot water/App - J = 1,066.1 kilogallons 

 Residential LPG Space Heat - J = 4,264.4 – 1,066.1 

 Residential LPG Space Heat - J = 3,198.3 
 145

x 

LPG used for space heating in ozone season in Baltimore City 

HDD PERIOD Residential Space Heating Fuel PERIOD = Space Heating Fuel 

ANNUAL 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 
 146

PM10, SOx, NOx, CO, VOC, and Toxics 

 

3.1.6.7 Wood Combustion 

SCC: 21 04 008 000 (Residential Wood Combustion) 

Description

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).

Pollutants

Method and

Data Sources 

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.”87

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. 

87 Residential Wood Combustion Emission Inventory, Preparted by E.H. Pechan & Associates, Inc. for the MidAtlantic Regional Air Management Association, dated June 22, 2004. 
 147

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 
 148

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

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

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. 
 149

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. 

Monthly Temporal Allocation Files

Temporal 

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). 

FIPS 

ST 

FIPS 

CNTY May June Aug July 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
 150

Monthly Temporal Allocation Files

FIPS 

ST 

FIPS 

CNTY May June Aug July 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 0.12970 0.06266 0.19049 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
 151

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 
 152

Activity (tons/yr) = (HUs x UFs x As) + (HUo x UFo x A0) (equation 1) 

Emissions 

Calculation 

A sample calculation for annual activity is provided below for a specified census tract and SCC: 

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). 
 153

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: 

Description

3.1.7 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. 

3.1.7.1 Residential Construction Activity 

SCC: 23 11 010 000 

This source category covers fugitive dust emissions from residential construction activities. 

Pollutants

PM10 and PM2.5

Method and

Data Sources 

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. 

• 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. 
 154

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 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

Spatial 

Data for spatial allocation is not available for this source. 

Temporal 

Data for temporal allocation is not available for this source. 
 155

 E RC – MF = Emissions of pollutant i in tons per year from residential multi-family 

construction activity 

Emissions 

Calculation 

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

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
 156

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 
 157

3.1.7.2 Heavy Construction Activity 

SCC: 28 10 001 000 

Description

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 Census88. 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 Patterns89. 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 Patterns90 for the State of Maryland.

Pollutants

PM10 and PM2.5

Method and

Data Sources 

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 

 

88 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 89 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 90 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. 
 158

 PM 

adjusted so that the state total employment in a NAIC matched the sum of the number of 

employees reported per county.

Emission Factors 

10 PM 2.5

(tons/acre/month) (tons/acre/month)

Emissions 0.11 20% of PM 10

Duration of Project 11 months 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

Spatial 

Data for spatial allocation is not available for this source. 

Temporal 

Data for temporal allocation is not available for this source. 

Emissions 

Calculation 

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 
 159

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
 160

3.1.7.3 Road Construction Activity 

SCC: 28 10 001 000 

Description

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.

Pollutants

PM10 and PM25

Method and

Data Sources 

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 
 161

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..

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls

For construction emissions, a control efficiency of 50 percent is used for both PM10 and PM2.5

for PM nonattainment areas.

Spatial and 

Temporal 

Allocations

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. 
 162

Emissions 

Calculation 

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)

 
 163

3.1.7.4 Agricultural Land Preparation 

SCC: 28 01 000 003 

Description

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. 

Pollutants

PM10 and PM2.5

Method and

Data Sources 

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. 
 164

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-4291. 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 

 

91 U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission Factors, AP-42, Section 11.2.2, 

Fourth Edition. September 1985. 
 165

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.

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

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. 
 166

Emissions 

Calculation 

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 ALP PM2.5 = hay x AP hay) + (A soy x AP soy) + (A barley x AP barley) + (A tobacco x AP tobacco)]

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 
 167

3.1.7.5 Paved Roads 

SCC: 22 94 000 000 

Description

This source category covers fugitive dust emissions from activity on paved roads. 

Pollutants

PM10 and PM2.5

Method and

Data Sources 

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) 0.65x (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: 
 168

5,000 – 10,000 

Road Surface Silt 

Loading Constants 

ADTV 

 < 500 

ADTV 

500 - 5,000 

ADTV 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_ADTV 500 – 5000 = 

(3.18 / 3)1.5 ] – 0.2119 

(WEIGHT/3) 1.5 ] - C 

EF PAVED_ADTV >10000 = 

And Where: 

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

[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 

EF PAVED_ADTV 5000 – 10,000 = 0.603575 gram/mile 2

EF PAVED_ADTV >10000 = [PSDPVD x (PVSILT/2) 0.65 x 

EF PAVED_ADTV >10000 = [7.3 x (0.03 / 2) 0.65

 x (3.18 / 3)1.5 ] – 0.2119 

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 
 169

EF PAVED_ADTV >10,000 ADJ = CF RAIN

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_LOCAL x 

EF PAVED_ADTV >10,000 ADJ = 0.310239 x 0.928767 

EF PAVED_ADTV >10,000 ADJ = 0.285861 gram/mile 2
 170

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 
 171

3.1.7.6 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. 
 172

3.1.8 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. 

3.1.8.1 Vehicle Fires 

SCC: 28 10 001 000 

Description

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. 

Pollutants

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)92. 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)93. Maryland used a more conservative assumption based on a 2,000 pound 

average vehicle weight.

Pollutant Lbs/ton burned

 

92 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 93 CARB. 1995. Emission Inventory Procedural Manual, Vol. III: Methods for Assessing Area Source Emissions.

California Environmental Protection Agency: Air Resources Board. 

Method and

Data Sources 
 173

 VOC 32 

 NOx 4 

 CO 125 

PM10-PRI 100 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

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. 

Emissions 

Calculation 

2000 x 365 

VBj x FLF VF x EF VF i E VF, i = 

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

2000 x 365 E VF, i = 

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 
 174

3.1.8.2 Forest Fires 

SCC: 28 10 001 000 

Description

Forest fires in certain rural areas can produce very large, short term organic emissions. 

Pollutants

PM10 and PM2.5

Method and

Data Sources 

Activity

ARMA used data from the Maryland Forest, Park and Wildlife Service

94 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 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

No controls are available for this source category.

 

Adjustments 

for Controls 

94 Forest fire data collected from Mr. Bob Hartlove, Acting Fire Supervisor for the Maryland Forest Service 
 175

Temporal 

ABj x EF FF i

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. 

Data for temporal allocation is not available for this source. 

x FLF FF

2000 x 365 E FF I = 

where:

E FF,i = Emissions of pollutant i in tons per day from forest fires

FLF FF = Fuel loading factor (tons/acre burned) for forest fires (11.0)

AB J = Acres burned by wildfire in county j in 2002

EF FF i = Emissions factor in pounds per acre or pounds per ton for pollutant i 

2002 Sample Calculation Forest Fires (Anne Arundel County)

AB E j x EFf,i x FLF FF

 FF i = 2000 x 365 

where:

E FF i = (0.3 acres burned 95 x 11 tons per acre 96 x 24.0 lbs. VOC per ton) / (2000 x 365) 97

 

95 Number of acres burned by wildfire in Anne Arundel County in 2002 from Maryland Forest, Parks and Wildlife 

Service . 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 
 176

 

E FF i = 0.0001 tons per day of VOC emitted from forest fires in Anne Arundel County in 

 2002 

96 Fuel loading factor from AP-42, Table 13.1-1. 97 Emission factor from AP-42, Table 13.1-2. 
 177

3.1.8.3 Slash/Prescribed Burning 

SCC: 28 10 015 000 (prescribed burn) 

SCC: 28 10 005 000 (slash burn) 

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 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. 

Pollutants

PM10 and PM2.5

Method and

Data Sources 

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 
 178

Spatial 

Temporal 

ABj x EF PB i

No subtration of emissions from point sources is necessary. 

No controls are available for this source category.

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. 

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. 

x FLF J

2000 x 365 E PB i = 

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 = 

Point Source 

Adjustments 

Adjustments 

for Controls 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation 

0.016 tons VOC /day 

Slash burning calculations are done in a similar manner. 
 179

PM10 and PM2.5 

3.1.8.4 Agricultural Burning 

SCC: 21 01 500 000 

Description

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). 

Pollutants

Method and

Data Sources 

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. 

3.1.8.5 Structure Fires 

SCC: 28 10 030 000 

Description

Building fires produce short-term emissions of organic compounds. 

Pollutants

PM10 and PM2.5

Method and

Data Sources

MDE staff used emission factors, fuel loading factors and methodology documented in EIIP98, 

Structure Fires, dated July 1999.

Activity 

The Maryland State Fire Marshal's office provided the number of structure fires by county. 

 

98 Emission Inventory Improvement Program
 180

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 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

SFj x EF SF i

Spatial and 

Temporal 

Allocations

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. 

Emissions 

Calculation 

x FLF SF

2000 x 365 E SF i = 

where: 

SF J = Structure fires in county j in 2002 

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
 181

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 

238699 x 11 100 x 1.15 101

E SF i = 2000 x 365 

E SF i = 

 

0.0413 tons VOC / day 

99 Number of structure fires in Baltimore City in 2002 from Maryland State Fire Marshal's Office . 100 Emission factor from EIIP Structure Fires. 101 Fuel loading factor from EIIP Structure Fires 
3.1.8.6 Orchard Heaters 

SCC: 28 01 520 000 

Description

 182

In areas of the country where frost threatens orchards, heaters may be used in cold portions of the 

growing season. 

Pollutants

PM10 and PM2.5

Method and

Data Sources 

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. 
 183

This section contains the ammonia emission inventory for 

 

3.1.9 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 102 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. 

• Agricultural Livestock Production Operations 

• Agricultural Fertilizer Application, 

• Human activity. 

102 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). 
3.1.9.1 Cows (Milk Cows, Beef Cows, Heifers, and Steers) 

SCC: 28 05 020 000 (Cows Composite)

Description

These animals, and all livestock, are sources of ammonia emissions due to the biological 

decomposition of their waste products 

NH3

 184

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, 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 

 9.67 Kg/ heifer/ yea

39.72 Kg/ cow/ year Battye, et al. (1994) 

Heifers r Battye, et al. (1994) 

Steers 11.65 Kg/ steer/ year Battye, et al. (1994) 

No subtraction of emissions from point sources is necessary. 

Pollutants 

Point Source 

Adjustments 

Method and

Data Sources 

Adjustment for 

Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations
Spatial 

 185

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. 

Emissions 

Calculation

Equation:

1999 TPY ammonia emissions for cows in an individual county

1999 EMBC + 1999 EMMC + 1999 EMHF + 1999 EMST

 EMST = 1999 Uncontrolled emissions from steers 

(ACBC * EFBC) 

 ACST = Activity level (number) of steers 

 EFST = Emission factor for steers 

EM COWS-99 Total =

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

 Where:

EM BC =

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

 EFBC = Emission factor for beef cows

 EFMC = Emission factor for milk cows

 EFHF = Emission factor for heifers
3.1.9.2 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

 186

Factor 

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, et al. in 1994 and are 

presented in the table below:

Emission Factors and Source 

Livestock 

Category 

Emission 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 

Description

Pollutants 

Method and

Data Sources 

11.65 Kg/ steer/ year Battye, et al. (1994) 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

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. 

Temporal 

Data for temporal allocation is not available for this source. 

 187

Equation:

1999 TPY ammonia emissions for swine in an individual county

EM SWINE-99 Total = 

(ACPIGS * EFPIGS) 

Spatial and 

Temporal 

Allocations

Emissions 

Calculation

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 =

 Where:

 ACHOGS = Activity level (number) of hogs

 ACPIGS = Activity level (number) of pigs

 EFHOGS= Emission factor for hogs

 EFPIGS = Emission factor for pigs
3.1.9.3 Chickens (Pullets, Layers, and Broilers) 

SCC: 28 05 030 000 (Chickens Composite)

Description

These animals, and all livestock, are sources of ammonia emissions due to the biological 

decomposition of their waste products. 

Pollutants

NH3

Method and

Data Sources 

 188

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 levels were collected from the USDA Census of Agriculture data for 1997. 

Activity 

Emission Factors 

Emission factors were collected from a paper published by Battye, 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) 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

No controls are available for this source category.
Spatial and 

Temporal 

Allocations

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. 

Emissions 

Calculation

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

 189
3.1.9.4 Sheep 

 190

SCC: 28 05 040 000 (Sheep Composite)

Description

These animals, and all livestock, are sources of ammonia emissions due to the biological 

decomposition of their waste products. 

Pollutants

NH3

Method and

Data Sources 

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, 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) 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

No controls are available for this source category.
Spatial and 

Temporal 

Allocations

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. 

Emissions 

Calculation

Equation:

1999 TPY ammonia emissions for sheep in an individual county

EM SHEEP = Total NH3 emissions from sheep, all categories

EM SHEEP 

=

ACSHEEP * EFSHEEP

Where:

ACSHEEP = Activity level (number) of sheep

EFSHEEP = Emission factor for sheep

 191
192

3.1.9.5 Goats (Angora and Milk) 

SCC: 28 05 045 001(Goats Composite)

Description

These animals, and all livestock, are sources of ammonia emissions due to the biological 

decomposition of their waste products. 

Pollutants

NH3

Method and

Data Sources 

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, 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) 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

No controls are available for this source category.
Spatial and 

Temporal 

Allocations

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. 

Emissions 

Calculation

Equation:

1999 TPY ammonia emissions for goats in an individual county

 Where: 

 ACAG = Activity level (number) of angora goats 

 EFMG = Emission factor for milk goats 

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)

 ACMG = Activity level (number) of milk goats

 EFAG = Emission factor for angora goats

193
3.1.9.6 Horses 

SCC: 28 05 035 000 (Horses)

Description

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, et al. in 1994 and are 

presented in the table below:

Pollutants

Method and

Data Sources 

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. 

Point Source 

Adjustments 

Adjustment for 

Controls 

Spatial and 

Temporal 

Allocations

194
Temporal 

Data for temporal allocation is not available for this source. 

Equation:

Emissions 

Calculation

1999 TPY ammonia emissions for horses in an individual county

ACHORSE = Activity level (number) of horses 

EM HORSE = ACHORSE * EFHORSE

Where:

EM HORSE = Total NH3 emissions from horses, all categories

EFHORSE = Emission factor for horses

195
3.1.9.7 Ducks, Geese and Turkeys 

SCC: 28 05 035 001 (Ducks) 

SCC: 28 05 035 002 (Turkeys) 

SCC: 28 05 035 003 (Geese)

Description

These animals, and all livestock, are sources of ammonia emissions due to the biological 

decomposition of their waste products. 

Pollutants

196

Activity 

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 levels were collected from the USDA Census of Agriculture data for 1997. 

Emission Factors 

Emission factors were collected from a paper published by Battye, et al. in 1994 and are 

presented in the table below:

Emission Factors and Source 

Livestock 

Category 

Method and

Data Sources 

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.

Point Source 

Adjustments 

Adjustment for 

Controls 
Spatial and 

Temporal 

Allocations

197

Temporal 

Equation:

Spatial 

The activity data was collected at a county-level. No other method to spatially profile the 

source category was used. 

Data for temporal allocation is not available for this source. 

Emissions 

Calculation

1999 TPY ammonia emissions for ducks in an individual county

EM DUCKS =

EM DUCKS = Total NH3 emissions from ducks, all categories

ACDUCKS * EFDUCKS

Where:

ACDUCKS = Activity level (number) of ducks

EFDUCKS = Emission factor for ducks
3.1.9.8 Agricultural Fertilizer Application

198

 

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. 

 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. 

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
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. 

199

Emission Factors 

Emission factors were collected from a paper published by Battye, et al. in 1994 and are 

presented in the table below: 

Emission Factor 

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 and Source 

Fertilizer Type

Per Cent NH3 Released to 

the Atmosphere

Source of 

Ammonium nitrate 0.01 Battye, et al. (1994) 

Ammonium sulfate 

Battye, et al. (1994) 

0.08 

Nitrogen solutions 

Battye, et al. (1994) 

Battye, et al. (1994) 

0.15 

0.04 

Potassium nitrate Battye, et al. (1994) 

Miscellaneous 

Potassium nitrate Battye, et al. (1994) 

Mix 

0.01 Battye, et al. (1994) 

Ammonium thiosulfate 0.02 

Calcium ammonium nitrate Battye, et al. (1994) 

0.025 Battye, et al. (1994) 

Urea 0.02 

Diammonium phosphate 0.08 

Monoammonium phosphate Battye, et al. (1994) 

Liquid ammonium polyphosphate Battye, et al. (1994) 

0.04 

0.04 Battye, et al. (1994) 

0.02 

Miscellaneous 0.15 Battye, et al. (1994) 

0.04 Battye, et al. (1994) 

Method and

Data Sources 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations
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. 

Emissions 

Calculation

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)

200
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

201
3.1.9.9 Human Breath and Perspiration 

SCC: 28 10 010 000 (Human Perspiration)

Description

Ammonia emissions from human breath and perspiration comprise a few percent of the national 

ammonia emission inventory.

Pollutants

NH3

Method and

Data Sources 

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, 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) 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

Spatial 

The activity data was collected at a county-level. No other method to spatially profile the 

source category was used. 

202
Temporal 

Data for temporal allocation is not available for this source. 

Emissions 

Calculation

Equation:

1999 TPY ammonia emissions from human breathe and perspiration in an individual county

ACHUMAN = Activity level (number) of people per county 

EM HUMAN B&P = ACHUMAN * EFHUMAN B&P

Where:

EM HUMAN B&P = Total NH3 emissions from human breathe and perspiration

EFHUMAN B&P = Emission factor for human breathe and perspiration

203
4.0 NONROAD SOURCES

4.1 NONROAD VEHICLES/ENGINES 

204

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:

• construction equipment 

• general aviation 

 

• lawn and garden equipment 

• airport service equipment 

• logging equipment 

• recreational marine equipment 

• light commercial equipment 

• industrial equipment 

• agricultural or farm equipment 

• recreational land vehicles or equipment 

• railroads 

• commercial aviation 

• air taxis 

• 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 Model103. In a memorandum104, 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.

103 NONROAD2005 104 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. 
4.2 NONROAD MODEL 

205

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).

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: 

Parameters: 2002 

BNAA-MD

Min. Temp. 65.55 

Max. Temp. 87.6 

Avg. Temp. 76.8 

RVP 6.6

O2 % 2 

Gas Sulfur % 0.0162 

LPG/CNG Sulfur % 0.003 

Diesel Sulfur% 0.2283 

Marine Diesel Sulfur % 0.2638 

Stage II Control % 0 

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. 

206
4.2.1 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) 

Description

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. 

Pollutants

PM10, PM2.5, SOx, NOx, CO, VOC

Method and

Data Sources

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. 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

The NONROAD model automatically applies controls, when applicable, for a given year. 

207
Spatial and 

Temporal 

Allocations

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. 

208

 

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-015105, dated March 31, 1999.

Emissions 

Calculation 

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. 

105 Nonroad Engine Emission Modeling Team, Assessment and Modeling Division, EPA, Office of Mobile Sources 
4.3 RAILROADS 

 SCC: 22 85 002 005 (Line Haul) 

 SCC: 22 85 002 010 (Yard Engines) 

Description

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. 

209

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. 

7. Maryland Midland Railway, Incorporated 

11. Winchester and Western Railroad Company 

Pollutants 

PM, SOx, NOx, CO, VOC 

Method and

Data Sources: 

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 

8. Norfolk and Southern Railway Company 

9. Patapsco & Back Rivers Railroad Company 

10. Western Maryland Scenic Railroad 

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. 
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. 

210

Line Haul Yard

VOC 0.0213 lbs/gal VOC 0.0509 lbs/gal 

NOx 

Spatial 

Temporal 

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. 

Point Source 

Adjustments 

No subtration of emissions from point sources is necessary. 

Adjustments 

for Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

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. 

Data for temporal allocation is not available for this source. 
Emissions 

Calculation 

211

G CTY = 

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

M ST

* G ST

 G CTY = amount of total fuel used in gallons by the company in the county 

 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

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
212

Sample Calculations:

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 used by CSX Transportation line haul locomotives in 

Montgomery County: 

514.97 track miles in the state for CSX 

2002 Montgomery County Emissions 

Line Haul Emission Estimate 

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) 

36.37 track miles in Montgomery Co. for CSX Gcty4 = 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 

EMVOC = (2000 lbs. per ton) * (365 days 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 = 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) 

EMCO = 

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

(2000 lbs. per ton) * (365 days per year) 

EMCO = 0.0933 tons CO / day
Yard Locomotives Emission Estimate 

CSX operated 2 yard locomotives in Montgomery County: 

213

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 CO Emissions for Montgomery county: 

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

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
4.4 AIRCRAFT 

 SCC: 22 75 020 000 (Commercial Aircraft) 

 SCC: 22 75 050 000 (General Aviation) 

 SCC: 22 75 001 000 (Military Aviation) 

Description:

214

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. 

1) 

Pollutants

PM10, PM2.5, SOx, NOx, CO, VOC

Method and

Data Sources 

ARMA used a variety of sources for data and emission calculation methods as follows: 

Data sources

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.
215

3) 

 

For commercial aviation ARMA used FAA’s EDMS106 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. 

Point Source 

Adjustments 

No subtraction of emissions from point sources is necessary. 

Adjustment for 

Controls 

No controls are available for this source category.

Spatial and 

Temporal 

Allocations

Spatial 

Data for spatial allocation is not available for this source. 

Temporal 

Data for temporal allocation is not available for this source. 

106 Emissions & Dispersion Modeling System (EDMS) Version 3.2 for Windows from CSSI, Inc. 
4.4.1 Commercial Aircraft 

216

(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. 

Emissions 

Calculation 

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
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

HC107

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

217

 

107 Requires a Hydrocarbon to VOC conversion factor of 1.0947. 
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. 

218
4.4.2 General Aviation 

SCC: 22 75 050 000 

Emission

Calculation 

219

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. 

 EF(AT)xx = Emission factors 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

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
220

EmissSO2 = 0.0030 Tons SO2 / Day 

EmissNOx = 0.0019 Tons NOx / Day

EmissSO2 = [21,569 LTOs / Year * 0.100 (lbs. SO2 / LTO)]

EmissSO2 = 2,156.900 lbs. of SO2 / Year

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
221

4.4.3 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. 

Method and

Data Sources

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

Emissions 

Calculation 

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
EmissSO2 = [63,852 LTOs / Year * 1.430 (lbs. SO2 / LTO)]

222

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
223
4.5 Marine Vessels 

 SCC: 22 80 002 010 (diesel marine vessels) 

Description 

224

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. 

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. 

Pollutants

PM, SO2, NOx, CO, HC, CO2

Method and

Data Sources 

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. 
• The time spent, by ship type, in each of four operating modes defines as: normal cruise, 

slow cruise, maneuvering, and hoteling. 

Emission Factors 

225

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 0.3211

0.2633 

0.2784 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 0.2784 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 
226

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 

28.6027 41.1704 

32.7919

CO 

(gr/kw-hr) 

2.3937

HC 

(gr/kw-hr) 

Bulk Carriers & Tankers 0.2637 2.1092

0.7457

0.4059

0.2637 0.7457 2.1092 

CO2 

(gr/kw-hr) 

Bulk Carriers & Tankers 869.1 1,089.60

General Cargo

703.725 1,530.60

No controls are available for this source category.

Point Source 

Adjustments 

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 32.7919

General Cargo 26.5081 29.2012 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) 

Bulk Carriers & Tankers 1.0473 2.0945 4.189 8.378 

General Cargo 1.0473 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) 

0.0932 0.7457

General Cargo 0.0932 0.3221 0.7457 2.1092

Passenger 0.0932 2.1092 5.9658

Container/ RORO/ Reefer/Auto Carrier 0.0932 1.1481 3.2474

All non-oceangoing 0.0932 

CO2 

(gr/kw-hr) 

CO2 

(gr/kw-hr)

CO2 

(gr/kw-hr) 

703.725 758.85

703.725 774.6 869.1 1,089.60

Passenger 869.1 1,089.60

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.

Adjustment for 

Controls 
Spatial and 

Temporal 

Allocations

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. 

Emissions 

Calculation 

227

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. 
5.0 ONROAD MOBILE SOURCES

5.1 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) 

228

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. 

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. 

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. 

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) 

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.
229

 PPSUITE Emission Modeling Process 

SHA Prepared Data 

2002 Highway Data 

UNIV02 Database

(128,379 Statewide 

Records) 

Based on Highway

County Number 

- 

Location Reference System 

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 
5.2 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. 

5.3 VEHICLE MILES TRAVELED 

230

• Compiles vehicle miles of travel (VMT) and vehicle type mix data 

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 nontravel 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 

• 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. 

5.4 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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For input to the emission calculation process, all the vehicle classes were grouped into 4 categories

• Vehicle Type 2 = Light-duty vehicles 

• Vehicle Type 3 = Buses 

• Vehicle Type 4 = Heavy-duty vehicles 

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. 
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. 

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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 
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months by calculating an average factor for 3 weekdays, Tuesday, Wednesday and Thursday. The 

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.

 

5.5 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. 

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. 

There are other files required by PPSUITE that are used for all analysis year runs. These files are 

illustrated in following table. 

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. 

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. 

 

5.6 OTHER DATA INPUTS

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 

county-level totals report type option is selected. 

Used for the output emission reports. It relates the coded facility

and area type numbers to text names. This file is used when the 

county-rural/urban totals report type option is selected. 

NAME_RURURB.DBF

Contains the impacts of truck percentages on roadway capacity. As 

a result, the amount of trucks can have an impact on calculated 

congested speeds. 

VEHFC2_02SHA.DAT 

For each facility type, area type, and lane combination, this file 

contains: 

• Free flow speeds SPEEDCAP.DBF 

• Free flow capacities 

• BPR Parameters (relationship between speed and 

congestion) 
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 

• Determine free-flow speeds for links without

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: 

 coded speed limits 

• Determine speed/congestion relationships (BPR coefficients) 

• Determine link “ideal” capacity 

• Determine signal densities and characteristics 

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. 

5.7 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 

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will not 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. 

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5.8 CONVERSION TO NIF FORMAT 

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 

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: 

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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6.0 BIOGENIC EMISSIONS 

6.1 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 BEIS3108

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

108 BEIS 3.12 can be downloaded from an EPA website at: http://www.epa.gov/asmdnerl/biogen.html
• ETH: Ethane group from CB-IV chemical mechanism

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• OLE: Olefin group from CB-IV chemical mechanism

• Total VOC: The sum of ALD2, ETH, FORM, ISOP, NR, OLE, PAR, XYL, and 

TOL 

• FORM: Formaldehyde group from CB-IV chemical mechanism

• ISOP: Isoprene 

• NR: Nonreactive VOC 

• PAR: Parafin group from CB-IV chemical mechanism

• XYL: Xylene group from CB-IV chemical mechanism

• TOL: Toluene group from CB-IV chemical mechanism

• 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).