## M ARYL AND 

## D E P ARTM E NT OF THE 

## E NVIRONMENT



## A IR AND 

## R ADIATION 

## M ANAGEMENT 

## A DMINISTRATIONState 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 Methodol ogies

© M a r y land Depar t m e n t of t h e Envi ron m ent Ai r and R a d i ation M a nag e m e n t Ad m i n i st r a

t i o n 1800 W a shi ngton B oul ev ard, Suit e 730 B a ltim ore, M a ryl a nd 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

............................................................................................................................... .....943.1.3.4 Distilleries

............................................................................................................................... ..95 3.1.4 CATASTROPHIC/ACC IDENTAL RELEASES ....................................................................... 96 3.1.4.1 Oil Spills

............................................................................................................................... ....96 3.1.4.2 Leaking Underground Storage Tanks .......................................................................................98 3.1.5 SOLID WASTE DISPOSAL, TR EATMENT, 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 ..........................................................................................2044.2 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 M ARINE V ESSELS ........................................................................................................................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 ......................................................................................................................2384 

## 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 invent ory, including identification of sources, documenting the method used to calculat e emissions from each source, and presenting the findings. In order to provide EPA with a written documentation of emi ssions calculations for major point sources, confidential information was included in the documentation. It is included with the understanding that EPA is also bound to respect the confidentiality of the information, including appropriate storage of the information. Any contr actors employed by EPA to re view the inventory are also subject to confidentiality provisions, or the EPA must remove the confidential material before submitting the document for review. This information doe s not appear in copies prepared public review.

The Maryland stationary point source inventory is th e result of efforts to ch aracterize air emissions sources since the early 1970's. Th is section describes da ta collection, verificati on and emission estimation methods used to estimate point source emissions from stationary sources. For the 2002 Periodic Emissions Inventory, point sources are defined as stationary commercial or industria l operations that emit more than 10 tons per year of volatile organic compounds (VOC); 100 tons pe r year of carbon monoxide (CO), sulfur oxides (SO x ), particulate matter with an aerodynami c diameter less than 10 micrometers (PM 10 ), and total suspended particul ates (TSP); or 25 tons per year of oxides of nitrogen (NO x . In addition, stationary sources included in previous PEI submissions were included herein re gardless of the amount of air pollutants emitted. These emissions criter ia are more commonly referred to as “emissions thresholds” or simply, “thresholds.”

1.2 COMPILING THE POINT SOURCE LIST

Maryland has a substantial database of both small a nd large air emission sources compiled over the last eighteen years. Since the thirt een central counties of Maryland and Baltimore City have been nonattainment for ozone since before 1982 and 80% of the state's population and major industrial sources lie within these counties, the da tabase of over 10,700 sources (both a bove and below the point source thresholds) is reasonably complete. The list of point sources in this inventor y was developed by applying the appropriate thresholds to the em ission levels in the database to di fferentiate between point and area stationary sources. Sources with emi ssion levels greater than the thresh old or sources previously included in PEI submittals are by definition point sources wh ile sources with emissions levels less than the thresholds are by definition area sources.

Several methods of source identifica tion are used by ARMA to ensure th e point source inventory is as complete as possible. The primary data source is the Permitting Program, which overseas the registration requirements found in Title 26, Subtitle 11, Chapter 02, Code of Maryland Regulations (COMAR). The Compliance Program identifies other point source s though annual facility inspections and through investigations conducted in re sponse to citizen complaints.

The primary means of new source iden tification is the steady influx of permit applications and equipment registrations. Many sources are required by CO MAR 26.11.02, Permits, Approvals and Registration, to register with ARMA. From 700 to 1,000 new sources ar e registered with the Department each year.5 Most of these sources are not cons idered to be point sources as de fined for inventory purposes, even though they require permits. As an example, emissions from some sources can be less than one ton per year. However, all sources that are registered wi th the Department are tracked until the Department receives notification that the equipm ent or emission source has ceased operations. An emissions source or its equipment is not permanently deleted from th e registration database until the installation is demolished.

The Department has established a Small Business Assi stance Program as required by the Clean Air Act Amendments to acquaint the owners of potential sources with the State’s permitting requirements, including air quality permits. The De partment has also published a guidebook, Environmental Regulation: A Business Guide to the Maryland Depa rtment of the Environment's Permitting Process as part of its outreach program.

A secondary means of new source identification are the emission sources identified by Compliance Program staff during annual field inspections of major point sour ces. During these inspections, unregistered equipment is sometimes discovered. St atewide response to the Ai r Pollution Report and the Air Quality Complaint Hotline, has also led to the discovery of previously unidentified emissions sources. Sources discovered in this manner may be the result of the citizen complaints, or the result of further investigation of visual evidence such as buildings, storage yards, visibl e emissions, etc., sighted elsewhere during the response.

1.2.1 EMISSION CALCULATIONS

The ARMA technical staff uses one of the followi ng methodologies to calcul ate criteria pollutant emissions:

• EPA-supplied emission factors

• EPA-supplied emission models

• Material balances

• Emissions based on source test data

• Agency or company-generated emission factors

The Compliance Program facility insp ectors calculate annual emissions estimates following their annual facility inspections. The results are then entered into ARMA’s Registration Files for Facilities and Equipment, which lists facilities by premise numb ers and equipment by registration numbers under each facility. The emissions, both stack and fugitive, from all registered equipment at a specific facility are summed to yield the annual facility emissions estimate. This total facility estimate is used to determine whether the facility satisfies the criteria for classification of as a point source.

The estimation of emissions on a facility-wide basis can result in emissions from equipment in some subcategories, such as boilers, being obscured. For example, boiler emissions are included in the Amerada Hess Corporation’s total emissions. Ther efore, these boiler emi ssions are included with emissions from gasoline storage and handling operations and included in the Storage, Transportation and Marketing of Petroleum Products and Volatile Organic Liquids source cat egory rather than in External Combustion Sources category.6 Emissions from specific subcategories of sources can be extracted from the inventory to estimate possible reductions from various control st rategies. However, the emissions from specific equipment subcategories cannot be excluded from the facility -wide emissions because of the limitations of the software used to create the Regist ration File. Therefore, subcategor ies of equipment emissions are not included in the inventory as separa te line items for to do so would re sult in the double counting of those emissions.

The estimates prepared by the facility inspectors following the annual inspecti on of each facility are compared to the annual emissions reported by each facility in its Annual Em issions Certification. A person who owns or operates a major facility as defined in COMAR 26.11.01.05-1 must submit to the Department an emissions statement by April 1 of each year for the previous calendar year. The owner or operator of the facility must furthe r certify that the emissions statemen t is accurate to the best of the owner/operator’s best knowledge. Af ter the certified emissions statem ents are logged in, they are thoroughly reviewed by the assigned f acility inspectors. Each inspector compares their emissions estimate to that prepared by the respective company for consistency of methodology and final emissions estimate results. The facility inspectors resolve a ny discrepancies between the two estimates with the owner/operator of the facility in qu estion. When all discrepancies are reso lved to the satisfaction of MDE, the final emissions estimates are then submitted as an update to ARMA’s Regist ration File for Facilities and Equipment.

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 ozon e season, ozone season, or even monthly periods of activity was not collected in 2002. More specific information may be collected in the future.

In cases where the facilities did not provide peak ozone season emission estimates, the peak ozone season emissions were calculated by the following method a nd are included in the emissions summary tables, by county, at the end of this section: 1) Annual emissions in pounds per year were c onverted 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 i nventory in order to satisfy EPA reporting requirements under the Consolidated Emissions Repor ting Rule. This will be the primary resource for developing refined estimates of PM 2.5 and NH 3 emissions.

## 2.0 QU ASI - POINT SOUR CES

2.1 INTRODUCTION

The Maryland Department of the E nvironm ent Air and Radiation Managem e nt has identified several facilities that due to size and/or function are considered point sources . These estab l ish m ents contain a wide variety of air em ission source s, includ ing tr a d ition a l poin t source s, on -road m obile sources, of f -road mobile sources and area sources. Fo r each particular es tab lis hm ent, th e em issions from these sources are totaled under a single poin t source and summary docum ents include these “quasi-point” sources as point

sources.

2.2 ABERD EEN PR OV ING GR OU NDS

Description Aberdeen Proving Ground (APG) occupies m o re than 72,500 acres in Harford County, Md. Its northernm ost point is m a rked by the confluence of the Susquehanna River and the Chesapeake Bay. On the south the Gunpowder River borders it.
The installation com p rises two principal areas, sepa rated by the Bush River. The northern area is known as the Aberdeen Area, and the southern sector, fo rm erly Edgewood Arsenal (established in November, 1917 - as a chem ical weapons research, development a nd testing facility), is the Edgewood Area. The two areas were adm i nistratively com b ined in 1971. Aberdeen Proving Ground is hom e to 66 tenants and a host of satellite activities. Am ong the m a jor tenants are the U.S. Research, Developm ent and E ngineering (RDECOM ) , U.S. Ar my Ordnance Center and Schools, U.S. Ar m y Developm en tal Test Command, U.S. Ar m y Aber deen Test C e nter, U.S. Ar m y Center for Health P r om otion and Preventive Medici ne, Northeast Region Civilian Personnel Operations Center, U.S. Ar m y Medical Research Institute of Che m ical Defense, Program Manager for Che m ical Dem ilita riz a tion and m a jor elem ents of the Arm y Research L a borato r y. As a center for Arm y ma teriel testin g , laboratory research and m ilitary training, the po st is a k e y elem ent in the nation' s defense. All tanks and wheeled vehicles which have served U.S. forces for the past 50 years have been te sted f o r perf orm a nce and durability at APG - f r om the M4 Sherm a n tank of W o rld W a r II to the M1 tank and High Mobility Multipurpose W h eeled Ve hicle and Fam ily of Stryker Vehicles of today.

Known as the "Hom e of Ordnance," APG has been training Ar m y ordnance pe rsonnel since 1918. The Ar m y ' s ordnance training was consolidated at the proving ground during Worl d W a r II, and today the U.S. Ar m y Ordnance Center and School provides m echanical m a intenance training f o r m o re than 20,000 U.S. and for e ign person nel each y e ar. APG is the regim e ntal headquarters for the Army' s Chief of Ordnance.

APG' s Edge wood Area has been a center for chem ical warfare research and developm ent since it was estab lished. From the trenches of France and Belgium in W o r l d W a r I to the desert battlefields of Iraq nearly 80 years later, the work done at APG has contri buted to the defense and safety of Am erican forces threatened by chem ical weapons.

More than 7,500 civilians work at Aberdeen Prov ing Ground, and m o re than 5,000 military personnel are assigned there. In addition, there are nearly 3,000 contractors and pr ivate business em ployees working on the proving ground.

7There are 2, 148 m ilitary fa m ily m e mbers living o n th e post an d another 15 5 off post. The post supp orts more than 1 6,000 m ilitary retirees and retiree fam ily m e mbers. The post is Harford County' s largest

em ployer and one of the largest em pl oyers in the state of Maryland.

U.S. Ar m y Garrison, A b erdeen Prov ing Ground, provides general, adm i nist rative and logistical support to the post' s tenants and satellite activiti es, and is responsible for the m a na gem e nt and operation of the entire installation, which in m a ny wa ys is like a sm all city.

Environm ental stewardship is an es s e ntia l com p onent of all activ ity a t APG. The installa tion and its tenants are actively involved in a wide variety of environm ental com p liance, pollution prevention, conservation

, and resto r ation prog ram s . In FY 2 004 APG spent a to tal of $31 m illion on environ m ental
program s, installation program s and in sta lla tion r e stora tion ac tivitie s.

Pollutant s VOC, NOx, CO, PM, Toxics

Emission Source Categories

MDE staff reviewed em ission estim at es prepared for Aberdeen Proving Grounds by a private contractor. These em ission estim a tes includ ed d a ta for the f o llowing so urce categories:

• Mobile On-Road Source Em issions

o Mobile - LDGV E m issions

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 Exhau s t

o Mobile – H DDB

o Mobile - HD CNG Trucks

o Mobile - LD CNG Trucks

• Mobile Nonroad Source Em issions

o 2-Stroke Gas Eng; Lawn & Ga rden E quip; Other Equipm ent

o 4-Stroke Gas Eng; Recrea tional Equip; Golf Carts

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

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

o 4-Stroke Gas Eng; Indus trial Equip; Forklifts

o 4-Stroke Gas Eng; Lawn & Garden E quip; Chain Saws

o 4-Stroke Gas Eng; Lawn & Garden E quip; Leaf blowers/Vacuum s

o 4-Stroke Gas Eng; Lawn & Garden E quip; Rear E ng Riding Mowers

o 4-Stroke Gas Eng; Lawn & Ga rden E quip; Front Mowers

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

o 4-Stroke Gas Eng; Comm erci al Equip; Generator Sets

8 o LPG Eng; Construction & Mining Equip; Off-Highway Truckso Diesel Eng; Construction & Mining Equip; Rollers

o Diesel Eng; Construction & Mining Equip; Cranes

o Diesel Eng; Construction & Mining Equip; Graders

o Diesel Eng; Construction & Mi ning Equip; Off- highway Trucks

o Diesel Eng; Construction & Mini ng Equip; Tractors/Loaders/Backhoes

o Diesel Eng; Construction & Mini ng Equip; Other Construction Equip

o Diesel Eng; Industria l Equip; Forklifts

o Diesel Eng; Industrial E quip; Sweepers/Scrubbers

o Diesel Eng; Lawn & Gard en Equip; Front Mowers

o Diesel Eng; Agricultural E quip; Agricultu ral Tr a c tors

o Diesel Eng; Comm ercial Equip; Generator Sets

o Recreational m a rine 4-str oke gasoline equipm ent

o Recreational m a rine diesel com p ression ignition equipm ent

o Aircraft

• Area Source Em issions

o Em issions from aircraft refueling.

o Construction W e lding

o Solvent-b a s e d arch itectural su rface coating s

. o Water-bas ed architectural surface co atings.

o Cold clean in g solvents.

o Solvent Utilization - Miscellaneous

o Comm ercial/consum er solvents.

o Open Burning Detonation

o Landf ills - All Categor ies

o Munition s Detonation

o Firefighting Training

o Industrial Process - Miscellaneous

o Comm ercial/institu tional distillate o i l com bustion.

o Comm ercial/institu tional natural gas com bustion.

• Point Source Em issions

o MDE staff also rev i ewed and includ ed em ission estim ates from e m ission certification reports prep ared by Aberdeen Proving Grounds and subm itted on an ann u al bas i s to MDE’s Compliance an d Enforcement Program . These em ission es tim ates in clude m a jor

sources.

Emission Estimation Methodolog ies

Em ission estim a tion m e thodologies varied by source ca tegory. A brief synopsis of the m e thodologies is presented below.

Mobile On-Road Source Emissions Inform ation on the privately owned vehicles for APG was estim ated from a 2001 traffic study conducted f o r all gates at both Aberdeen and Edgewood.

910 Emissions for the on-road vehicles were calcula ted only for the estimated miles and hours of onbase vehicle operation. Miles traveled off the base were not included in the emission calculations. AP-42, Volume 11, Fifth Edition includes the emission factors for NOx, CO, and VOC, which were calculated using EPA's MOBILE 5 model for gasolin e and diesel operated ve hicles. AP-42 has not been updated with NOx, CO, and VOC emission fact ors from the latest version of EPA's MOBILE 6.2.03 model, released in Octobe r 2002, which also includes em ission factors for PM-10, PM-25, S02, and HAPS. Therefore, the emission factors fo r on-road vehicles were obtained by running the MOBILE 6.2.03 model.

APG government-owned vehicles were grouped into vehicle categories accor ding to vehicle type, gross vehicle weight (GVW), and fuel type. The CY 2002 mileage for each vehicle, if available, was provided by each organization, as were estimate s of on-base mileage or a percentage of the total miles per vehicle that were driven on the base . If the mileage data was not available, it was estimated based on mileage for similar types of vehi cles from other organiza tions or from estimates provided by organization personnel.

Emission estimates for privately owned vehicles (POVs) are based on traffic studies for CY 2000 and CY 2001. Each traffic study tracked incoming vehicles at all gates at both Aberdeen and Edgewood over a three-week period . The average number of vehicl es counted at each gate over both years was used to estimate the number of P OVs entering each day. The average values were 7,680 POVs per day at Aberdeen and 5,277 per day at Edgewood.

POV miles traveled were determined by using the distance from each gate to a central location at both Aberdeen and Edgewood. Each POV that entere d a specific gate was assumed to drive that distance each day. The daily on-base mileage was determined by multiplying the number of POVs by the round-trip distance to a specific gate. The POV vehicles from the traffic study were conservatively estimated to be in th e above-referenced vehicle categories.

Emissions of NOx, CO, VOC, PM-1 0, PM-2.5, and SO2 from daily employee POVs were estimated by multiplying the annual on-base mileage of eac h vehicle category with the emission factors obtained from the MOBILE 6.2.03. Since the model ye ars of POVs traveling on the base would vary greatly, it is impractical to estimate the emissi ons from each vehicle in that model year range. Instead the year 2000 was considered the average vehicle model year , and the emission factors for the 2000 model year vehicles were used. The emissi on factors were used in the following equation to estimate annual emissions:

1.1.1.1.1.1.1 E = V * F * C

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

### x 10 lb/g)

The information on the vehicles tested and miles driven on unpaved test tracks at APG was obtained from 2002 logs for each track. Th e test vehicles we re divided equally into the HDDV and HDGV vehicle classes.11 Mobile Nonroad Mobile Source Emissions

APG gathered information about the number of ve hicles, model year, horsepower rating, fuel type, engine cycle type, and estimated operating hours for CY 2002. In the majority of instances, horsepower ratings and operating hour s were not readily available a nd have been assumed based on the typical horsepower of similar types equipment. If data was not available for CY 2002, then data was obtained for the closest available year.

Criteria pollutant emission f actors were obtained from Air Emissions Inventory Guidance Document for Mobile Sources at Air Force Installations, Un ited States Air Force Institute for Environment, Safety & Occupational Health Risk Analysis (IERA), January 2002, which includes the emission factors used in EPA's NON-ROAD 2002 model. Emi ssion factors to estimate PM-2.5 from PM-10 emissions were obtained from EPA's NON-ROAD 2002a model. The Non-road model incorporates research results from U.S. EPA 's Non-road Engine and Vehi cle Emission Study (NEVES), November 1991, as well as from the California Air Resour ces Board's off-road model, test results, and regulatory emission standards. These factors we re used to estimate the emissions from non-road vehicles and equipment.

Emission factors for stationary internal combustion engines were used to es timate criteria pollutant emissions for the non-mobile equipment. These factors are found in Table 3.3-1, AP-42 Section 3.3, Gasoline and Diesel Industrial Engines. Emissions were calculated by multiplying the power output by the emission factors applicable to the type of fuel used by the non-mobile equipment, either gasoline or diesel. The power output was calculate d by multiplying the power of the equipment in horsepower times the estimated hours of operation. Net workdays were derived from the equipment rental records. It was assumed that the light to wers were used 8 hours per day and that all other equipment was used 10 hours per day.

The total emissions for all non-road vehicles a nd equipment were separated into emissions for Aberdeen and Edgewood. In cases were vehicles were used at both Aberdeen and Edgewood the total emissions were divided equally.

Aircraft operations are conducted at Phillips Airfie ld at Aberdeen and Weide Heliport at Edgewood. These operations include landings and takeoffs (LTOs), touch and go's (T&Gs), low approaches (LAs), and trim and power checks (T&Ps). Emi ssions from aircraft operations were estimated using the EDMS (version 4.4) model.

Emissions of criteria pollutants for watercra ft were calculated using factors provided in AP-42, Volume 11. Inboard emissions were calculated based on fuel consumption or operating time. Outboard emissions were calculat ed using factors related to fuel consumption. Fuel consumption was rarely known, so a generic fuel usage of 3 ga llons per hour was used to calculate consumption from operating time.

The inventory of watercraft includes APG vessels , privately owned boats, and rental boats. The inventory included the size of vesse ls, whether the boat has an inboa rd or outboard motor, whether the boat uses gasoline or diesel, on-site fuel usage, and on-site estimated usage.Many assumptions were necessary to calculate em issions from th e lim ited inform ation known about

m a ny of the watercraft. The num be r of m e m b erships to th e p r iva t e boat clubs located at APG and

num b er of perm its to launch boats at APG was know n, but no inform ation as to the size and type of boats was, nor the tim e or distan ce they traveled with in the boundaries of APG. All privately owned boats launched in the Aber deen Area were considered outsi de of the APG boundary once in the water, so no em issions were counted from th ese boats. For privately ow ned watercraft it was

assum e d that 80% have outboard m o tors and 20% have inboard and that all ar e gasoline fueled. An

assum p tion was m a de that privately owned watercraft were used 5 tim es per year and spent 2 hours on site each usage for a total of 10 ho urs each. Fo r re ntal ou tb oards it was assum e d that they were used 3 hours on-site per rental weekend and that there were 40 rentals in 2002.

Area Source Emissions

Em issions from the various area source categorie s were estimated using a variety of methods, including population based, fuel consum ption, and m a ss balance. Em ission factors were derived from the EPA docum ent titled ' E m i ssion Inventory Im provem e nt Program', and AP- 42. Landfill losses as VOC were calculated fo r Michae lsville landf ill using Landfill Gas Emissions Model (LandGEM ) version 3.02 available through the EPA. Land GEM is based on a first-order decom position rate equation for quantifying em i ssions from the decom position of waste in municipal s o lid waste la ndf ills. Activity

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

Emission F a

ctors Em ission factors were derived from the Em issi on Inventory Im prove m e nt Program (EIIP); AP-42, Volum e 11, Fifth Editio n; EP A' s NON-ROAD 2002 m odel; EPA' s MOBILE 5 m o del; and the Landfill Gas Em issions Model (Lan dGEM) vers ion 3.02.

Collecting all em issions estim ates un de r one facility effectively creates a single point source for all of the

em issions. No other point sources were subtract ed from the area source inventory to avoid double counting.

Controls were applied w h en applicab le to a particular source category.

Spatial Spatia l alloc a tion of the em ission estim a tes to sp ecific areas within APG is not av ailable. Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns

1213 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 hom e base of the U. S. presiden tial aircraft, Air Force One.

The base is located a few m iles southeast of W a s h ington, in Prince George' s County, Maryland near the town of Morningside. Acco rding to the United States C e nsus Bureau, the town has a total land area of 6.8 m i 2 and none of it is covered by water. There are two runways on the base; the western runway is 3,440 m e ters in length, and the eastern runway is 3,570 m e ters in length.

The host unit for Andrews AFB is the 89th Ai rlift W i ng which falls under Air Mobility Comm and. The prim ary m i ssion at Andrews AFB is to trans port the President of the United States. The base is also tasked, unde r what is known as "SAM FOX", to provide worldwide airlift for the vice president, the president' s Cabinet, m e m b ers of Congress,

m ilitary le ad ers and oth e r high rank ing dignita rie s . At one tim e , "SAM FOX", was used as a prefix to an aircraft tail num ber, during radio transm issions to identif y Air Force airc raft tha t were transp or ting high-ranking VIPs, typically on foreign flights. The call sign prefix was constructed from the acronym SAM (Special Air Missi on) and the initial F (Foreign), which at the tim e was re presented by the phonetic word "Fox."

Andrews is also the home of the 89th Communication Group, a unit that provides communications to m ilitary ins t allations all ov er the world. T h e techn i cal contro l f acility is one of the largest in the world, and hosts a m y riad of sophisticat ed telecomm unications equipm ent. One of the squadrons within the 89th Communications Group is the 789th Communications Squadron, whose CNCS re m o tely operates 15 HF Global radio stations from around the Globe. Other m a jor 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 em ission es tim ates pr ep ared for Andrews Air Force B a se by a private contractor. Thes e em ission estim at es included data for the following source catego r ies : Pollutant s

Emission Source Categories

• Mobile On-Road Source Em issions

o Mobile - LDGV

o Mobile - L DGT12

14o Mobile - L DGT34

o Mobile - HDGV / Buse s

o Mobile - MC

o Mobile - LDDV

o Mobile - L DDT

o Mobile - HDDBT

o Mobile - HDDV

o Mobile - HDDBS

o Mobile - Heavy Duty Trucks

o Mobile - Lig h t Duty Vehicle s

• Mobile Nonroad Source Em issions

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 N on-road vehicle- 4-stroke gasoline engine

o Gas-Fired N on-road vehicle- 2-stroke gasoline engine

o Aircraft - All Aircraft Types and Operations

o Em issions f r om m ilitary aviation airc raf t land ing and takeof f

. o Em issions from comm er cial aviatio n aircraft landing and takeoff.

o Diesel Generators

o Off-highway Vehicle G a soline, 2-Stroke Total without APUs

o Off-highway Vehicle G a soline, 4-Stroke Total without APUs

o Off-highway Vehicle G a soline, 4-Stroke APU em issions

o Off-highway Vehicle Diesel APU em issions

o Nonroad Mobile Aircraft Ground Equipm ent - All Gasoline Engines

o Nonroad Mobile Aircraft Ground Equipm ent - All JP-8 Engines

• Point Source Em issions

o MDE staff also rev i ewed and includ ed em ission estim ates from e m ission certif i cation reports prep ared by A ndrews Air For ce Base and subm itted on an annual basis to MDE’s Com p l i ance and E n forcem ent Program

. These em ission estim a tes includ e m a jor sources.

Emission Estimation Methodolog ies

Em ission estim a tion m e thodologies varied by source category. A brief synopsis of the

m e thodologies is presented below.

15Mobile On-Road Source Emissions The Andrews AFB on-road vehicle inventory consists of a m i x of light- and heavyduty gasoline-, diesel-, and natural gas- powered governm e nt-, and privately owned vehicles (P OVs). POVs include vehicl es owned by both daily em ployees and weekend personnel. The inventory contains the vehicle type, model year, num b er of vehicles, and annual on-base m ileage. To distinguish leased General Services Ad m i nistration (GSA) governm e nt-owned ve hicles (GOVs) from the regular fleet, vehicle tag num b ers are provided in cases where they are kno wn.

On the basis of inventory data prov ided by vehicle m a intenance personnel,
governm e nt-owned vehicles (GOVs) were grouped into eight vehicle categories accord ing to vehicle type, gross vehicle weight (GVW ), and fuel type. The 2002

m ileage for each vehicle was provided by ve hicle m a intenance personnel, as were estim ates of on-base m ileage or a p e rcentage of the total m iles per vehicle that were driven on the base.

Em issions were calculated only for th e estim a ted m iles and hours of on-base vehicle and equipm ent operation. Miles travel ed off the base were not included in the em ission calculations. The Fifth Ed ition of AP-42, Volum e II includes the

em ission factors for NOx, CO, and VOC, which were calculated using EP A’s MOBILE 5 model for gasoline and diesel operated vehicles. AP-42 has not been updated with NOx, CO, and VOC e m ission fact ors from the latest version of EPA’s MOBILE 6.2.03 m odel, released in Oct ober 2002, which also includes em ission factors for PM-10, PM-2.5, SO2, and HAPs. Therefore, the em ission factors for onroad vehicles were obtained by running the MOBILE 6.2.03 model. The MOBILE model does not address com p ressed natural gas vehicles, so em ission factors for these vehicles have been obtai ned from 40CFR86.1708-99, 40CFR88.105- 94, and 40CFR88.104.94.

Em ission estim a tes for privately owned vehicles (POVs) are based on traffic studies supplied by base personnel (89th AW Civil Engineering, July 2004). Andrews AFB has approxim a tely 61, 738 vehi cles traveling on base each workday. This num ber assum e s a working schedule of employees of 40 hours per week. In addition, 25% of the daily personnel ar e assum e d to be on the base on the weekends.

The em ission factors were used in th e following equation to estim ate ann u al

em issions:

E = V * F * C

Where: E = Annual em issions of particular po lluta nt from each vehicle catego r y (lb / yr) V = Vehicle m iles traveled on-base per ye ar for each vehicle catego r y (m i/yr) F = Average model year em ission factor in th e ap plicab le veh i cle catego ry (g/m i) C = Conversion factor (2.205 

### x 10 lb/g)

16Mobile No nroad Mo bi

le Source Emissions

The Andrews AFB non-road vehicle invent ory consists of various equipm ent including forklifts, loaders, riding lawn care equipm ent, and towing equipm ent. The inventory contains the equipm en t nam e , m o del year, horsepower rating,

num b er of vehicles, fuel type, engine cycle type, and operating hours for CY 2002. The inventory specifies whether the opera ting hours are a total operating tim e for CY 2002 for the num ber of units listed or an operating tim e for each un it.

Criteria pollutant and H A P e m ission factors were obtained from Air Emissions Inventory Guidance Document for Mobile Sources at Air Fo rce Installations, United States Air Force Institute for En vironment, Safe t y & Occupation a l Health Risk Analysis (IERA)

, Ja nuary 2002

, which inclu d es the em ission factors used in EPA’s NONROAD 2002a m odel. Em ission factors to estim ate PM-2.5 fromPM10 em issions were obtained fr o m EPA’s NONROAD 2002a model.

The Andrews AFB aircraft operations invent ory consists of info rm ation re lated 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 em issions invento r y because 200 2 is the b a seline ye ar se lected by the MDE f o r use in th e re visi on of its SIP. The inventory contains the aircraft type and m a nufacturer, engine m odel and m a nufacturer, the num ber of LTOs, T&Gs, LAs, and T&PCs. The calendar year 2002 inventory was generated using inform ation com p iled from the Aerial Port Squadron, the Andrews AFB Federal Aviation Adm i nistration (FAA) Liason, a nd Allan Holtzm a n, Andrews AFB Air Quality Pro g ram Manager. This inve ntor y will also be subm itted to MDE f o r incorpor atio n into ED MS (version 4.4).

Activity

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

Emission F a

ctors Em ission factors were derived from the EDMS Airport Em ission Model, Version 4.4; EPA's NON-ROAD 2002 m o d e l; and EPA's MOBILE 6.02.03 m o d e l.

Collecting all em issions estim ates under one f acility ef f ective l y crea tes a s i ngle po int source for all of the em issions. No other poin t so urces were s ubtracted from the area source inventory to avoid double counting. Point Source Adjustment s

17Adjustment for Controls Controls were applied w h en applicab le to a particular source category.

Spatial Spatia l alloc a tion of the em ission estim a te s to sp ecific areas within Andrews Air Force Base is not availab l e.
Temporal Data f o r temporal a lloc a tion is not available for this source. Spatial and Temporal Allocatio ns

1819 2

. 4 BALT I M ORE

- WAS H IN GT ON IN TERNATIONAL AIRPORT (BWI)

Description

Baltim ore-Washington Intern ational Airport (BW I) is located in Anne Arundel County, Maryland, approxim a tely 9 m iles so uth of the City of Baltimore and app r oxim a tely 30 m iles northeast of Washington, D.C. BWI Airport is generally bounded on the north, east, and west by Aviation Boulevard (MD Route 170 and MD Rout e 162) and on the south by Dorsey Road (MD Route 176). Interstate 1 95 (I-195 ) is a four-lan e divided h i gh way that serves as the p r im ary access po int to the airpo r t term inal area. Elm Road and Aviation Boulev ard provide secondary access to the term inal an d cargo facilities.

BW I is operated by the Maryland A v iation Administration, Maryland D e partm e nt of Transportation. BW I Ai rport encompasses 3,596 acres of land. The passenger term inal contains 1.4 m illion s quare feet; 4 concourses (3 dom estic, 1 internatio nal/swing ); 69 jet gates with 12 gates ded i ca ted to commuter a i rc raf t

.

The em ission sources at BW I include aircraft, ai rcraft ground support service equipm ent, m o tor vehicles (on roadways, in parking facilities, and at term inal curb sides), the heating plant, fuel storage and handling, an d training fires.

VOC, NOx, CO, PM, Toxics

MDE staff reviewed em ission es tim ates prep ared for BW I Air port by a private contractor. These

em ission estim a tes inclu d ed data fo r the following source categories: Pollutant s

Emission Source Categories

• Mobile Onroad Source Em issions

o Mobile - LDGV E m issions

o Mobile - Par k ing Facility Em issions

o Mobile - LDGT 1&2 Emissions

o Mobile - LDDT 1-4

o Mobile – HDDV

• Mobile Nonroad Source Em issions

o Em issions from airport service di esel com p ression ignition equipm ent

o Em issions f r om m ilitary airc raf t LTOs

o Em issions from comm er cial aircraft LTOs

o Em issions from general aviation aircraft LTOs

o Em issions from aircraft auxiliary pow er units20 • Mobile Nonroad Source Constr uction Equipm ent Em issions

o 2-Stroke Gas Eng; Constructi on & Mining Equip; Paving E quip

o 4-Stroke Gas Eng; Construction & Mining Equip; Plate Compactors

o 4-Stroke Gas Eng; Construction & Mi ning Equip; Concrete/Industrial S a ws

o Diesel Eng; Construction & Mining Equip; Pavers

o Diesel Eng; Construction & Mining Equip; Rollers

o Diesel Eng; Construction & Mining Equip; Scrapers

o Diesel Eng; Constructi on & Mining Equip; Sign al Boards/Light Plants

o Diesel Eng; Construction & Mining Equip; Trenchers

o Diesel Eng; Construction & Mining Equip; Excavators

o Diesel Eng; Construction & Mining Equip; Cranes

o Diesel Eng; Construction & Mining Equip; Graders

o Diesel Eng; Construction & Mi ning Equip; Off- highway Trucks

o Diesel Eng; Construction & Mi ning Equip; Rubber Tire Loaders

o Diesel Eng; Construction & Mini ng Equip; Tractors/Loaders/Backhoes

o Diesel Eng; Construction & Mini ng Equip; Crawler Tractor/Dozers

o Diesel Eng; Industrial Equip; Aerial Lifts

o Diesel Eng; Industria l Equip; Forklifts

o Diesel Eng; Industrial E quip; Sweepers/Scrubbers

o Diesel Eng; Comm ercial Equip; Generator Sets

o Diesel Eng; Comm ercial Equip; Air Com p ressors

o Diesel Eng; Comm erci al Equip; W e lders

• Mobile Onroad Source Em issions

o Firefighting Training

• Point Source Em issions

o MDE staff also rev i ewed and includ ed em ission estim ates from e m ission certif i cation reports prep ared by BW I and subm itted on an an nual bas i s to MDE’s Com p liance and Enforcem ent Program. These em ission estim a tes includ e m a jor

sources.

Emission Estimation Methodolog ies

Em ission estim a tion m e thodologies varied by source category. A brief synopsis of the

m e thodologies is presented below.

Emissions and Dispersion Mo deli ng System (EDMS) Version 4.4

• Aircraft21 FAA’s EDMS computer program contains a data base of aircraft e ngine emission factors based on engine make and model and four e ngine operation modes (t axi/idle, takeoff, climb out, and approach). EDMS also contai ns a database of em ission factors for an aircraft’s auxiliary power units (APUs). Time-in-mode data is also used as an input into the emission inventory. EDMS time-in-mode da ta include the time that aircraft spend in each of the four operating modes.

• Ground Support Equipment

FAA’s EDMS computer program contains a database of the ground support equipment (GSE) used to service specific types of aircra ft. Also included in the database are the emission factors for each piece of GSE, as well as the time that each piece of equipment spends servicing the aircraft.

• Roadways

FAA’s EDMS computer program uses EPA’ s MOBILE 6.2 model to estimate on-road mobile vehicle emissions.

• Parking Facilities

FAA’s EDMS computer program uses EPA’ s MOBILE 6.2 model to estimate on-road mobile vehicle emissions fr om parking facilities.

• Training Fires

FAA’s EDMS computer program contains a da tabase of emission factors for five fuel types (JP-4, JP-5, JP-8, Tekflame and Propane). Training fire emissions are estimated by choosing the fuel type and specifying the amount of fuel consumed in the training exercise.

Nonroad Mobile Source Emissions

• Construction Equipment

Emissions from construction ac tivities were estimated based on the construction activity schedule, including the number and types of construction vehicles and equipment units and their utilization rates. Emission rates we re taken from EPA’s NONROAD program and MOBILE6.2. Emissions from several components of construction activities were calculated, specifically: onsite construction equipment (back hoes, bull dozers, graders, etc.), haul vehicles idling onsite (cement trucks, dump truc ks, etc.), and haul ve hicles and construction worker vehicles accessing the site. An industr y-wide, representative mix of the number and types of construction equipment, average power rating (horse power), and equipment load factors was used in the analys is. Construction-related motor vehicles (dump trucks, pick-up22 trucks, etc.) were assumed to travel a round trip on-site di stance of 5 m iles while on the Airport con s truc tion s ite.

Activity

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

Emission F a

ctors Em ission factors were derived from FAA’ s EDMS com put er program (Version 4.4). Vehicular em ission factors contained in ED MS are obtained from the EPA' s M O BILE 6.2 model. Construction em ission factors were derived fro m EP A’s NONR OAD Model.

Collecting all em issions estim ates under one facility effectively cr eates a single point source for all of the em issions. No other point sources we re subtracted from the area source inv e n t ory to avoid double counting.

Controls were applied w h en applicab le to a particular source category.

Spatial Spatia l alloc a tion of the em ission estim a tes to sp ecific a r eas within Baltimore W a shington Intern ational Airport is n o t available.

Temporal Data f o r temporal a lloc a tion is not available for this source. Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns23 

## 3.0 AREAS SOURCES

3.1 EMISSION ESTIMATION METHOD BY CATEGORY

3.1.1 PETROLEUM DISTRIBUTION LOSSES

Evaporative emissions occur at all points in th e gasoline distribution pro cess. These operations, generally inventoried as area sources, are gasoline dispensing outlets and gasoline tank trucks in transit. Bulk terminals and gasoline bulk plants, which are intermediate distribution points between refineries and outlets, have been inventor ied as point sources. Most gasoline dispensing outlets emit less than 10 tons of VOC per year and therefore have been inventoried using area source methods.

VOC emissions from gasoline di spensing outlets result from vapor losses during tank truck unloading into underground storage tanks, vehicle fueling (boat fueling at marinas), and underground storage tank breathing. Evaporativ e losses from each activity in this source category have been tabulated separately so th at various emission reduction control measures could be easily evaluated.

Emissions from vehicle fueling, including spilla ge during fueling, were calculated with the MOBILE6 model and the methodology is described in Section 5.0 Mobile Sources. Tank truck unloading, underground tank breathing, tank trucks in transit and aircraft refueling were calculated using emissions factors from AP-42 and EIIP.24 3.1.1.1 Tank Truck Unloadin g SCC: 25 01 060 053

Description:

Em issions from tank truck unloading are aff ected by whether the service station tank is equipped for subm erged, splash or balance fil ling. Therefore calcu la tions were based on the filling m e thod used and gallons so ld.

VOC

The m e thod used to calculate em issions (all VOC), is presented in EIIP 1 , Chapter 11, Gasoline Marketing, which extracts the em ission factors f r om AP-42 , Volum e I, Table 5.2-7.

Activity

The Maryland Com p troller of the Treasur y, Gasoline T a x Divisi on provided annual gallons of gasoline and diesel fuel sold. This data includes taxable and non-taxed gasoline purchased by the U.S. Governm e nt . State an d local governm e nt sale s are included in the taxable sales data. The statewid e total of gallons of fuel so ld was allocated to the county level proportional to the num b er of regist ered vehicles within the county. Vehicle registration data was collected from the Ma ryland Department of Transportation, Motor Vehicle Adm i nistration that supplied the data to MDE’s Mobile Sources Control Program

. Diesel fuel powered vehicle totals were subtracted from the Maryland and county registration num b ers.

Percentages of subm erged, balanced subm erged and splash -f ill tanks were dete rm ined with the ass i stan ce of MDE W a ste Managem e nt. MDE staff reported no splash filling at Maryland service stations in 2002. All underground storage ta nks within the nonattainm ent areas of th e State of Maryland a r e required to use vapor-balance subm erged f illing

m e thods. Waste Managem e nt' s underground tank inspection program and regulations concerning underground storage ta nks have elim inated splash-fill tanks in the state. A

recen t SSCD study determ ined that the rule eff ectiv eness factor for vapor balance contro ls was 91%.

An activity level of 7 days per week was used, based on observations by MDE staff of unloading at Maryland retail ga s stations. A rule effectiveness of 91% was determ ined from a study of Stage I com p liance perform e d in Regions III and IV by the MDE/ARMA enforcem ent program in 1991. In the attainm e nt counties ou tside of Regions III and IV, a def a ult ru le ef f ectivenes s of 80 % was used. This survey data was used to determ ine the penetration of each fillin g technolog y. The tota l fuel sales in the county were m u ltiplied Pollutant s

Method and Data Sourc es:

1 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram25 by the fraction using each filling tech nology. The AP-42 tech nology-specific em ission f actors were then used to estim ate emissions f r om subm erged f illing and b a lanced subm erged filling. The em issions from each fillin g technolog y were summ ed to estim ate tota l em issions.

Filling Method Non-Attainment Area Transport Region Attainment Area

Subm e r g e d 9 % 9 % 2 0 % Balanced Subm erged 91% 91% 80% S p l a s h 0 % 0 % 0 %

Activity Days per Year 365

Emission F a

ctors Em ission factors are affected by true vapor pr essure and temperature. E m issions from loading petroleum liquid can be estim a te d (with a probable e rror of ±30 percent) using the following expression 2 :

T M P S L

L * * * 46

. 12 =

where: L L = loading loss, pounds per 1000 gallons (lb/10 3 gal) of liquid loaded (The load in g loss is equ i valen t to an em ission f actor) S = a saturation factor (see T a ble 5.2-1) P = true vapor pressure of liquid load ed, pounds per square inch absolute (psia) (see Figure 7.1-5, Figur e 7.1-6, and Table 7.1-2) M = molecular w e ight of vapors , pounds per pound-mole (lb/lb-mole) (see Tab l e 7

. 1-2) T = tem p erature of bulk liquid loaded, °R (°F + 460)

Table 5.2-1 from AP-42 shows that the saturati o n factor (S) is a constan t for a specific petroleum liquid, carrier and type of loading service

The true vapor pressure (P) can be estim a te d from the Reid vapor pressure using the f o llowing eq uation :

The m o lecular weight v a ries s ligh tly with tem p erature and pressure, how ever for th is analysis it is assum e d to be constant. ( ) ( ) ⎭ ⎬ ⎫ ⎩ ⎨ ⎧
+ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ − ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

− ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ + ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ − − ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

+ − = 64

. 15 6

. 459 8742 log 013

. 2 6

. 459 2416
6

. 459 1042 854

. 1 log * 6

. 459

0

. 413 7553

. 0 exp 10 5

. 0 10 5

. 0 T RVP T S T RVP S T P

2 AP 4 2 , C h a p t e r 5. 2: Tra n s p o r t a t i on an d M a r k et i n g o f Pet r o l eum Li qui ds26 Proportioning the loading factors yields

2 * 1 1

* 2

1 1 * 1 * 1 * 46

. 12 2 2 * 2 * 2 * 46

. 12

1 2
T P T P

T M P S T M P S

LL LL

= = 2 * 1 1

* 2 * 1 2 T P T P LL LL =

The loading factor or em ission factor is dir ectly proportional to true vapor pressure and inversely proportional to tem p erature in degrees Rankin.

LL1 = 0.3 at RVP of 10 and 60 F; this yields LL 1 =0.3; P =5.186; T=520 R

To calculate LL2 at RVP of 6.7 and 81.8 F or P = 5.094; T = 541.8 R

2828

. 0 8

. 541 * 186

. 5 520 * 094

. 5 * 3

. 0 2 * 1 1

* 2 * 1 2 = = = T P T P LL LL

Initial em ission factors of 0.3 lb VOC per 1000 gallons throughput for balanced subm erged f illing and 7

. 3 lb VOC per 1000 gallon s throughput for subm erged filling were used in all Maryland co unties. Thes e factors were then adjusted with county-specific monthly average temperature and true vapor pre ssure values using the above technique.

Filling Met hod Base Emission Factor Lb. VOC per 1,000 gallon Balanced Subm erged 0.3 Subm erged 7.3 Diesel Fuel Unloading 0.014

Point Source Adjustment s
No subtraction of e m issions fr om point sources is necessary.

Controls f o r this sou r ce c a tegory are reflected in the em ission factors.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

. Adjustment for Controls

Spatial and Temporal Allocatio ns27 Emission s Calculation The equation for estim ating em issions from tank truck unloading is:

(G i x F i (f m ) x E F fm ) + (G i x F i (f m ) x EF fm ) E fj = 2000 x 365 W h ere:

E fj = Em issions of VOC in tons per da y from tank truck unloading per county i

G i = Gallons of gasoline sold in county i during 2002

F i (f m ) = Fraction of gasoline dispensed per county i per filling m e thod (balanced subm erged or subm erged) during 2002

EF fm = Em ission factor per fill ing m e thod for tank truck unloading adjusted by RVP and
tem p erature: (0.3 lb. VOC/1000 gallon throughput or 7.3 lb. VOC/1000 gallon throughput )

Tank Truck Unloading Sam p le Calculation (Carroll County)

To calculate fuel usage for Carroll C ounty:

Filling Met hod Carroll County Adjusted Emission Factor Lb. VOC per 1,000 gallon Balanced Subm erged 0.2453 Subm erged 5.9691 Diesel Fuel Unloading 0.014

Total fuel sold in Maryland in 2002 3 = 2,570,356,195 gallons

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

Carroll County vehicle registration 4 138,645 Total MD vehicle registration = 4,100,225 = 0

. 0 3 3 8

2,570,356,195 x 0.0338 = 86,914,019.269 gallons sold in C a rroll County

3 An nu al sales of g a so lin e fro m Marylan d Com p tro ller o f the Treasu r y, Ga sol i n e Ta x Di v i si on 4 St at e o f M a ry l a nd M o t o r Ve h i cl e Adm i ni st rat i on a n d M D E M o bi l e So u r ces C o nt r o l Pr og ram

.28 [86,914,019.269 gallons of gasoline sold in Carroll County in 2002 x 91 percent 5 filled by balanced submerged filling method x 0.2453 lbs.. VOC per 1000 gallons of gasoline 6 ] + [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 gasoline 7 ] = 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

Em issions from Stage II refueling are substantiall y less than those from Stage I because gasoline vapors that ordinarily m i ght have escaped durin g vehicle fueling are recircu l ated by a special nozzle back into th e pump. Th e start year for Stage II re fueling in all Maryland ozone nonattainm e nt areas was 1993. Gasoline stations were required to have Stag e II nozzles installed by Nove m b er of that year. Calculations were ba sed on the filling m e thod used and gallons sold.

VOC

EPA recomm ends that the MOBILE6 m odel be used to gene rate ref u elin g (Stage II) em ission factors for highway vehicle em ission inventor ies (EPA, 1992b). The m o del, designed to support the evaluation of air pollution from gasoline- and diesel-fueled vehicl es, generates em ission factors for tailpipe em issions and refueling activities . A detailed discussion of using this m odel is available from EPA (EPA, 1994).

Activity The MOBILE6 m odel produces estim ates of re fueling em issions in units of gra m s per

m ile. These values are multiplied b y fuel ec onomy (in units of m iles per gallon) and total gasoline sales (in units of gallons purchased/so ld) in th e stu dy area resulting in ref u e l ing

em issions in term s of gram s. It should be noted that MOBILE m a kes use of i m proved predic tive e quations to c a lculate ref u eli ng em ission f actors, including s e n s itiv ity to
tem p erature and Reid vapor pre ssu re (RVP), and these hav e n o t yet be en incorpora t ed into published A P -42 factors for refueling. Additi onally, the user m a y provide inform ation on local S t age II em ission controls to develop an em ission factor for controlled em issions.

Refueling em issions have two m echanism s of introducing em issions to the environm ent: (1) vapor d i s p lacem ent from the vehicle fuel ta nk during refilling; and (2) gasolin e spillage during refueling. The MOBILE user m a y reque st either a s i ng le em ission factor that

com b ines the two m echanism s or separate em ission factors for displacem ent and spillage. Because both m echanism s should be taken into account when estim ating refueling

em issions, the preferred approach is to request the com b ined em ission factor.

Emission F a

ctors ARMA mobile sou r ces s t aff ran the MOBILE6 m odel to estim a te the ref u eling em iss i ons using the gram s per m ile (g/m ile) methodology described above. The em ission estim a tes were converted from gram s to tons. Description

Pollutant s

Method and Data Sourc es30 Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Controls for this source category include St age II Vapor Recovery System s and Onboard Refueling Vapor Recovery (ORVR) system s. The contro ls are reflected in the em ission estim ates produced by the MOBILE6 m odel.

Spatial The MOBILE6 m odel uses user -supplied county-level gasolin e sales d a ta to spatially alloc a te em ission es tim ates.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equation for estim ating em issions from tank truck unloading is: Adjustment for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

(G i x EF StII x MPG x SAF) E StII = 2000 x 365 W h ere:

E StII = em issions of VOC in tons pe r day from stage II refueling

G i = gallons of gasoline sold in county i during 2002

EF StII = em ission factor for stag e II refue ling f r om the MOBILE6 m o del (gr a m s /m ile)

MPG = average fuel econom y ( m iles/gallon)

SAF = seasonal adjustm e nt factor to reflect summer weekday em issions

Stage II Ref u eling Sam p le Calcu l atio n

Since all calculations are included in the MOBI LE6 m odel output, a sample calculation is not available for this sou r ce catego r y.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 pum p lines. Dur i n g this pro ces s air m oves into th e tank evapora ting gasolin e and em itting va pors.

VOC

The m e thod used to calculate em issions (all VOC), is presented in EIIP 8 , Chapter 11, Gasoline Marketing, which extracts the em ission factors f r om AP-42 , Volum e I, Table 5.2-7.

Activity The Maryland Com p troller of the Treasury, Gasoline T a x Divisi on provided annual gallons of gasoline and diesel fuel sold. This data includes taxable and non-taxed gasoline purchased by the U.S. Governm e nt . State an d local governm e nt sale s are included in the taxable sales data. The statewid e total of gallons of fuel so ld was allocated to the county level proportional to the num b er of register ed vehicles within the county. Vehicle registration data was collected from the Ma ryland Department of Transportation, Motor Vehicle Adm i nistration that supplied the data to MDE’s Mobile Sources Control Program

. Diesel fuel powered vehicle totals were subtracted from the Maryland and county registration num b ers.

An activity level of 7 days per week was used.

Activity Days per Year 365

Emission F a

ctors An e m ission factor of 1. 0 lbs. VOC per 1000 gallons throughput was used. The e m ission factor was taken from EIIP , Chapter 11, Gasoline Marketing

, which extracts the em ission factors from AP-42 , Volum e I, Table 5.2-7.

MDE used the sam e sources for gasolin e sa les and car registration as in tank truck unloading. Pollutant s

Method and Data Sourc es:

8 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram32 Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Controls f o r this sou r ce c a tegory are reflected in the em ission factors.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equation used to estim a te e m issi ons from underground tank breathing is: Adjustment for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

(G i x EF utb ) E utb = 2000 x 365 W h ere:

E utb = em issions of VOC in tons per day from underground tank breathing and

em ptying

G i = gallons of gasoline sold in county i during 2002

EF utb = em ission factor for underground tank breathing (1.0 lbs. VOC /1000 gallon throughput)

Underground Tank Breathing Sam p le Calculation (Carroll C ounty)

To calculate fuel usage for Carroll C ounty:

Total fuel sold in Maryland in 2002 9 = 2,570,356,195 gallons

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

9 An nu al sales of g a so lin e fro m Marylan d Com p tro ller o f the Treasu r y, Ga sol i n e Ta x Di v i si on33 Carroll County vehicle registration 10 138,645 Total MD vehicle registration = 4,100,225 = 0.0338

2,570,356,195 x 0.0338 = 86,914,019.269 gallons sold in Carroll County in 2002.

22,376,721 = gallons of gasoline sold in Carroll County during the summer of 2002.

[22,376,721 gallons of gasoline sold in Carroll County in 2002 x 0.000818 lbs. VOC per gallons of gasoline 11 ] = 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 T a nk 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, p r ess u re in the ta nks, and the r m a l ef f ect s on the vapor and on the liquid. A worst case situation arises if a poorly sealed tank has been loaded with gasoline and pure air becom e s saturated. D u ring the vaporization process, pres sure increases and venting occurs. E m issons from this source category include the evaporation of petroleum vapor from :

• loaded tank trucks during transportation of gasoline from the bulk plant/term i nal to the service station or othe r dispensing outlet, and

• from e m pty tank trucks returning from se rvice stations to bul k plant/terminals.

Pollutant s
VOC

The m e thod used to calculate em issi ons (all VOC), is presented in EIIP 12 , Chapter 11 , Gasolin e Marketing (Stage I & Stage II ), dated Septem ber 1997.

Activity

Emission F a

ctors EPA documents the em ission factors in AP-42, Table 5.2-5 and EIIP states the em ission factors within the above-referenced docum e nt in Table 11.3-1. The AP-42 em ission factors represent a typical range of values. EIIP averages th e “typical ran g e values ” within AP-42 and arrives at average em ission factor values of 0.055 and 0.005 lbs.. VOC per 1000- gallon gasoline, respectively for em issions from em pty tank trucks and em issions from full tank trucks. Method and Data Sourc es

Emission S o urce 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 Em pty Tank Trucks 0.055 0 - 0.11 Full Tank Trucks 0.005 0 - 0.01

MDE used the sam e sources for gaso line s a les an d car registration as in tank truck unloading.

MDE used the em ission factors from EIIP, Volum e I, Table 5.2-5, of 0.06 pounds VOC per 1000 gallons throughput (com bines 0.005 lb VOC /1000 gallon full tank truck delivery and 0.055 lb VOC

12 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram35 /1000 gallon empty tank return). MDE also used a bulk facility throughput adjustment factor of 1.25 and calculated throughput by a ratio of county re tail sales and state retail sales times state fuel sales. MDE used the same sources for gaso line sales and car 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:

(G i x 1.25 x EF tt ) E tt = 2000 x 312 Where:

E tt = emissions of VOC in tons per day from tank trucks in transit

G i = thousand gallons of fuel sold in county i

EF tt = Combined (full & empty) tank tr ucks in transit emission factor

2002 Gasoline Tank Trucks in Transit Sample Calculation (Carroll County)

To calculate fuel usage for Carroll County:

Total fuel sold in Maryland in 2002 13 = 2,570,356,195 gallons

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

Carroll County vehicle registration 14 138,645 Total MD vehicle registration = 4,100,225 = 0.0338

2,570,356,195 x 0.0338 = 86,914,019.269 gallons

[86,914,019.269 gallons of gasoline sold in Carroll County in 2002 x 1.25 x 0.06 lbs. VOC per 1000 gallons of gasoline 15 ] = 6,518.55 lbs. VOC emitted.

13 Annual sales of gasoline from Maryland Comp troller 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 prim a r ily by comm ercial turb ojet and turb opr op aircraft), jet naphtha (used prim arily by m ilita ry air c raf t ) and av iation gaso line (used by aviation re ciprocating en gines) a r e the th ree m o st comm on t ypes of aircraft fuels used in the United States. Em issions occur when vapor-laden air in a partially em pty fuel tank is d i splaced to the atm o sphere when the tank is ref illed.

VOC

MDE staff a pportioned state level fuel sale s to aircraft activity as suggested in Procedures

, Section 4.2.3.

Activity MDE used selected data from the Departm e nt of Energy’s State Energy Data System , to obtain fuel consum ption data. MDE used ai rport survey data and the Maryland Aviation Adm i nistration’s 2002 Operations Count for P ublic-Use Airports to obtain operational counts. A few airports, such as Andrews Ai r Force Base, provided their own operations
count. Pollutant s

Method and Data Sourc es

Fuel Type Fuel Consumption (1,000 Barrels) J e t K e r o s e n e 3,938.000 Aviation Gasoline 38.877 Jet Naphtha 39.380

Emission F a

ctors Em ission factors, splash loadi ng factor and physical properties of aviation fuel are taken fro m AP-42
, Tables 5.2-1, 5.2-5, 7.1-2, and are s u m m arized below. Note the r e la tiv ely high em ission factor for aviation gasoline which contributes to high em issions at airpo r ts with large amounts of ge neral aviation (piston e ngine aircraft).

Fuel Type Vapor Pressure (60 ° F) Molecu lar W e ight (at 60 ° F) Jet Kerosene 0.0085 130 Aviation Gasoline 6.9 62 Jet Naphtha 1.3 80

Splash load ing satu ration factor: 1.4538 Units conversion factor 42 gals/barrel Activity days per period 365 days/year Study Temperature 520 deg. R (unit used in Procedures )

Emission Factor Equation:

Refueling EF = 12.46 x splash loading

factor x true vapor pressure x molecular weight at the study temperature

Refueling EF (RE i ) Fuel Type (lbs. VOC/kgal) Jet Kerosene 0.03839 Aviation Gasoline 14.86358 Jet Naphtha 3.61340

Emission Estimate Equation:

CA I S i x SA i X RE i E ar = 2000 x 365

where: S i = State aircraft fuel sales for fuel type i CA i = County aircraft activity (LTO) for fuel type i SA i = State aircraft activity (LTO) for fuel type i RE i = Refueling emission factor for fuel type i E ar = Emissions from aircraft refueling in tons VOC per day

2002 Sample Calculation for Aircraft Refu eling- General Aviation (Allegany County)

Maryland aviation gasoline fuel sales = 105,000 barrels 16 = 1,632,826.86 gallons

Allegany County General Aviation LTOs 7650.5 Maryland general aviation LTOs = 723,256 = 0.010578

Gallons of AvGas used Allegany = 1,632,826.86 x 0.010578 = 17,271.81

Emissions-GA Refueling Allegany = 17,271.81 ÷ 1,000 x 14.86358 17 = 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 Petroleu m Vessel Unloading Losses SCC: 25 05 020 000

Description

Petroleum liquids are transported via ships and barges, and on-land transportation. T h e procedures discussed below relate to m a rine transpor t of petroleum liquids. This category does not include em issions from fuel consum ed by ve ssels while in trans it o r in port. Evaporative VOC em issions from ocean going sh ips and barg es carrying petro l eum liquids resu lt from loading losses, ballasting losses and transit losses. Pe troleum liquids are classified into groups which are represented by crude oil, g a solin e, je t n a ptha, 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 v a p o rs in “em pty” car go tan k s are displaced to th e atmosphere by the liquid being loaded into the tanks. These va pors are a com posite of vapors formed in three
ways:

 Vapors which are form ed in the “em p ty” ta nk by evaporation of residual product from previous loads;

 Vapors tran s f erred to the tank f r om a vapor balan ce 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 los s es are u s ually the larges t source of evaporative em issions from petroleum vessels (EPA, 1996).

Ballasting losses are ass o ciated with the unload i ng of pe troleum liquids at m a rine term inals and refinery loading docks. It is co mm on practice to load several cargo tank com p art m ents with sea water after the cargo has been unloaded. This water, ca lled “b alla st,” im proves the s t a b ility of the

em pty tanker during the subsequent voyage. Ballasti ng em issions occur as vapor-laden air in the

em pty cargo tank is d i splaced to the atm o sphere by ballast water being pu mped into th e tank.

Transit losses are s i m ilar to bre a th in g losses a sso ciated with petro l eum storage. Tran s it los s is the expulsion of vapor from a vessel com p art m ent through vapor contraction and expansion, which are th e result of changes in temperatur e and barom e tric pressure. This loss m a y be

accom p anied by sligh t changes in th e level of th e liqu i d in th e tank due to liquid exp a nsion or contraction due to the temperat ure change. Some ships are equi pped with controls for these losses.

VOC Pollutant s40 Method and Data Sourc es

Activity

The m e thod used to calculate em i ssions (all VOC) is presented in EIIP 18 , Chapter 12, Marine Vessel Loading, Ballasti ng and Transit, dated May 1998.

A significant part of the em issions from th is source are from the Eastern Shore of Maryland because petroleum products are deliver ed to this area by barge rather than by pipeline as in the res t of the state. To com p ile e m issions MDE used guidance in EIIP
, Chapter 12, Marine Vessel Load ing, Ballasting and Transit, Waterborne Comm erce of the United States, Atlantic R e gion Freight Tables, Part 1, 1998 , an d AP-42, Table 7.1-2 and Section 5.2. Waterborne Comm erce supplied tonnage and type of petroleum products delivered to the various ports in Maryla nd for the year 2001. Tonnages of petroleum delivered w e re converted into Kgal.s (1000 ga llons) and then used to calculate em issions.

Factors

UNCONTROLLED VOC EMISSION FACT ORS FOR PETROL E U M CARRYING MARINE VESSELS ( E PA, 1996)

Petroleu m Liquid Ship/Ocean Vessel Loading

(Lbs. VOC per 1,000 gallon s Transferred) Barge Loading (Lbs. VOC per 1,000 gallon s Transferred) Ballasting (Lbs. VOC per 1,000 gallon s Transferred) Transit (Lbs. VOC per 1,000 gallon s Transferre d)

Crude Oil 0.61 1 1.1 1.3 G a s o l i n e 1

. 8 3

. 4 0

. 8 2

. 7 Jet Naphtha / Other 0

. 5 1

. 2 N A 0

. 7

Distilla te Oil / Kerosene 0

. 0 0 5 0

. 0 1 2 N A 0

. 0 0 5

Residual Oil 4 x 10 -5 9 x 10 –5 NA 3 x 10 -5

Data obtained from sources such as the Waterbo r n e Commerce of the United States are typically provided in term s other than 1,000 gallons (Mgal) as is required in Equation 12.4-1 and m u st be converted. Equation 12.4-3 can be used to c onvert units from 1,000 ton (Mtons) to Mgal. where:

18 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram41 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; se e Table 7.1-2 in AP-42 (lb/gallon)

Density 19

(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:

[(SOEF P x PP S,P ) + (BREF P x PP B,P ) + (BLEF P,U x 0.30 x PP BL,P ) + (TREF P x PP T,P )] PV P = 2000

Where:

PV P : Total VOC emissions from petroleum vessel loading, ballasting, and transit for each of the petroleum liquids (p) transported: crude oil, gasoline, kerosene, distillate oil, and residual oil (tons) SOEF P : Ship/ocean vessel loading emission f actor (pounds VOC per 1,000 gallons transferred) PP S,P : Amount of petroleum liquid (p) loaded into ships and ocean vessels in the inventory region (1,000 gallons)
BREF P : Barge vessel loading emission fact or (pounds VOC per 1,000 gallons transferred) PP B,P : Amount of petroleum liquid (p) loaded into barges in the inventory region (1,000 gallons)

19 AP-42, Table 7.1-242 BLEF P,U : Ballasting emission factor (pounds VOC per 1,000 gallons water ballasted) PP BL,P : Amount of petroleum liquid (p) unload ed from vessels that are ballasted (1,000 gallons) TREF P : Vessel transit emission factor ( pounds VOC per week per 1,000 gallons transferred) PP T,P : Amount of petroleum liquid (p) transpor ted by marine vessels in the inventory region (1,000 gallons)

2002 Petroleum Vessel Unloading Losses Sample Calculation (Gasolin e - Baltimore City)

Gallons (in Thousands) of Petrol eum Shipped in Baltimore Harbor

Crude Oil Distillate Oil Gasoline Jet Naphtha Residual Oil Kerosene

Baltimore Harbor 0.00 1690.14 33214.29 625 56202.53 0.00

Tonnage of distillate oil shipped in Baltimore Harbor (from Waterborne Commerce of the U.S., 2001) were converted in thousands of gallons (Kga l.s) and then used to calculate emissions.

Vessel Loading Emissions For vessel loading operations, 90 percent of the to tal throughput was loaded at terminals with a control system of 95 percent efficiency. According to the local port authoriti es, transit time in the inventory area is two days (2/7 of a week). Emissions for eac h emission point are calculated using Equation 12.4-1 and the emission factors from Table 12.4-5. In this example, emissions for each emission point are calculated separately and then totaled. Note that CE is applied to vessel loading emissions, and transit emissions are apportioned to two days per week by multiplying emissions by 2/7.

Vessel Loading (gasoline) emissions are calculated: PV GAS = [(1.8 lbs VOC /Kgal) x (31785.71 Kgal/yr) x {0.10 + [0.9 ( 1 – 95/100)]}÷ 2,000 lb/ton PV GAS = 4.1480 tons/year

Barge Loading emissions are calculated: PV GAS = [(3.4 lbs VOC /Kgal) x ( 113928.57 Kgal/yr)] ÷ 2,000 lb/ton PV GAS = 193.6786 tons/year

Ballasting emissions are calculated: PV GAS = [(0.8 lbs VOC /Kgal) x (477857.14 Kgal/yr) x ( 0.20)] ÷ 2,000 lbs/ton PV GAS = 38.2286 tons/year43 Note that the calculation for ballasting emissions in the equation include s 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 distil late oil at 60 deg. F: 0.007444 3.1.1.7 Portable F u el Containers SCC: 25 01 011 011 (Residential – Perm ea tion) 25 01 011 012 (Residential – Diurnal) 25 01 011 016 (Residential – Transport) 25 01 012 011 (Comm e rcial – Perm e a tion) 25 01 012 012 (Comm e rcial – Diurnal) 25 01 012 016 (Comm e rcial – T r ansport)

Portable fuel containers (PFCs) store and transport fuel from gasolin e service s t ations to residen t ial h o m e s and businesses. Em issions from PFC use i n clude: Description

• Permeation Emissions , which are produced after fuel ha s been stored long enough in a can f o r f u el m o lecules to inf iltra te an d satura te th e can m a terial.

• Diurnal Emissions , which result when stored fu el vapors es cape to the o u tside of a g a s can through any possible openings while the ga s can is subjected to daily cycle of increasing and decreasin g am bient temperatur es. Diurnal em issions are dependent on the closed- or open-storage condition of a gas can.

• Transport Emissions arise when fuel escapes (e.g ., spil ls,etc.) from gas cans that are in
trans it.

• Equipment Refueling E miss i ons res u lts when fuel escapes (e.g., spillage, vapor displacem ent) during the refueling of nonroa d equipm ent; however these em issions are handled by EPA’s NONROAD m o d e l. Activ ity data from the NONR OAD m odel we re used to es tim a te these em issions (described b e lo w).

Both resid e n tial and comm ercial PFCs are in cluded. The SCCs for PFCs are also n e w and are shown above.

VOC

The m e thod used to calculate em issions (all V O C), is adoped from a CARB 20 survey and

m e thodology adopted by OTC 21

.

Portable fuel container em issi on are calculated by accounting for e m issions from five different

com ponents related to gas container use: perm eat ion, diurnal, transport-spillage, refueling spillage and refueling vapor displacem e nt e m issions. The perm eation, diurnal em issions Pollutant s

Method and Data Sourc es

20 ARB’s Mailou t MSC 9 9 -2 5, “Pub lic Meetin g to C o n s id e r Ap pr o v al of C A ’s P o rtable Gasoline-C o ntainer Emissio n s I n v e n t or y, “ ( A RB, 19 9b)
21 C o nt rol M eas ure De vel o pm ent S u p p o o r t A n al y s i s o f Ozo n e T r na sp ort C o m m i ssi on M o del R u l e s, E. H. Pecha n & A s so ciates, In c. 552 8- B H e mp stead W a y, Sp r i n g f i eld

, VA 2 215 1, Mar c h 3 1 , 2 001

.45 (associated with storage) and tr ansp ort-sp illage (associated with filling the can) em issions are included in the area source inven t ory

. The e quipm ent refueling spillage and refueling vapor displacem ent em issions are calculated from the non-road m o del and are included in the non-road inventory

Activity The following input data is re quired to calculate em issions for this source category.

1. Num b er of r e sidential ho using units in 2002 by county, N 2. Num b er of comm ercial b u sinesses 22 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, W A F = 7 days/week 4. Seasonal adjustm e nt factors, SAF = 1

Emission F a

ctors Separate emission factors were developed for perm eation, diurnal, transport and spillage

em issions for PFC (both for co mm ercial and res i dential PFC s). These em ission factors were derived from CARB’s survey data (CARB, 1999).

Point Source Adjustment s Because the application of archite ctu r al su rface coating is defined as an area source, th ere is no need to sub t ract po int so urce em issio n s from the to tal, and all em issions estim ated f o r this sourc e

are area sou r ce em issions

.

No controls are availab l e for this source category.

Spatial For the re sid e ntia l PFC SCCs, em issions were allocated to the local area level based on a housing surrogate. Comm ercial PFC em issions we re allocated to the local area level based on commercial and industria l business location.

Temporal For the re sid e ntia l PFC SCCs, the em issions were allocated based on the m onthly and weekday/weekend day temporal profiles for re sidential lawn and garden equipm ent in the Adjustment for Controls

Spatial and Temporal Allocatio ns

22 Tot a l 20 0 2 em pl oy m e nt and busi n ess est a bl i s hm ent s by 6 di gi t N A I C S c ode an d by c o u n t y , C o u n t y B u si ness Pattern s46 NONROAD m odel. For the comm er cial PFC S CCs, these em issions were allocated based
on tem poral profiles for the NONR OAD m odel e ngines used in comm ercial applications.

The equation used to estim a te e m issions from portable fuel containers is:

Equation:

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

Pop R = (N)*(A)*(Cou nt R ) (Eq. 1)

where: Pop R = Statewide R e sidential-G a s-Can Population N = Num b er of Occupied -H ousing Units in OTC State A = Percentage of House holds with Gas Cans (46%) Count R = Average Number of Res i dential-Gas Cans per Household

Statewide residential-gas

- can-p erm eation em issio n s are com puted as follo ws:

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

where: HC PR = Perm eation Em issions in tons per day (tpd) P o p R = Statewide R e sidential-G a s-Can Population E F P = Appropriate Perm eation-Em ission Fa ctor (g /ga l -d ay) S = Percentage of Gas Ca ns Stored with Fuel (70%) B R = Percentage of Cans Stored in Closed Condition with respe c t to Mater i a l (Plastic 53%; Meta l 13%) S i z e R = Weighted Average Capacity of Residential-Gas C a ns (2.34 gal.) Level = W e ighted Average Am ount of Stored Fuel (49%) CF = 908,105 g/ton

Diurnal em issions from both open- and closed-system

- residentia l-gas cans are calculated as f o llows:

HC DR = (Pop R )*(S)*(E F D )*(B R )*(S ize R )*(Leve l ) (Eq. 3)

where: HC DR = Diurnal Em issions (tpd) for Resi dential-Gas Cans with resp e c t to Storage Condition (Open or Closed ) and Mate ria l (Plastic o r Meta l) Pop R = Statewide R e sidential-G a s-Can Population S = Percentage of Gas-Can Popul ation Stored with Fuel (70%) EF D = Appropriate Diurnal-Em ission F acto r with respe c t to Storag e Condition and Material (g /gal-day or g/day) Emission s Calculation47 B R = Percentage of Gas-Can Popul ation with respect to Storage Condition and Material Size R = Weighted Average Capacity of Residential-Gas Cans (2.34 gal.) Level = Weighted Average Am ount of Stored Fuel (49%) CF = 908,105 g/ton

Residential-transport-spillage emissions are determined as:

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

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

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

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

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

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

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

where: HC PC = Permeation Emissions (tpd) Pop C = Statewide Commercial-Gas-Can Population EF P = Appropriate Permeation-Em ission Factor (g/gal-day) S = Percentage of Gas Cans Stored with Fuel (70% for Residential Survey) B C = Percentage of Applicable Gas Cans Stored in Closed Condition Size C = Weighted Average Capacity of Commercial-Gas Cans (3.43 gal) Level = Weighted Average Amount of Stored Fuel (49% from Residential Survey) CF = 908,105 g/ton48 

## ) The am ount of diurnal em issions from both open- and closed-system comm ercial-gas cans is calcu lated a s f o llows:

HC DC = (Pop C )*(S)*(E F D )*(B C )*(S ize C )*(Leve l ) (Eq. 7)

where: HC DC = Diurnal Em issions (t pd) for Comm er cial-Gas Cans with resp ect to Storage Condition (Open or Closed ) and Mate ria l (Plastic o r Meta l) Pop C = Statewide C o mm ercial-Gas-Can Population EF D = Appropriate Diurnal-Em ission F acto r with respe c t to Storag e Condition and Material (g /gal-day or g/day) S = Percentage of Gas Cans Stored with Fuel (70% f r om Residential Survey) B C = Percentage of Gas Cans with respect to Storage Condition and Material Size C = W e ighted Average Capacity of Comm ercial-Gas Cans (3.43 gal.) Level = Weighted Average Am ount of Stored Fuel (49% from Residential Survey) CF = 908,105 g/ton

The non-law n -and-garden-equipm ent commercial-gas- can refills at the pump is derived as f o llows: 

# ( ) ( ) ( ) ( ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡

= 

## ∑

S POP SIZE Fuel REFILL

NON C C * * (Eq. 8)

where: Refill C = Average Number of Non-Lawn-and-Garden Equipm ent Com m ercial-Gas-Cans P u m p Ref ills per Day per Can (ref ill/d ay) Fuel = Non-Lawn-and-Garden Equipm ent Fuel Consumption (gal/day) for 2000 Size C = W e ighted Average Capacity of Comm ercial-Gas Cans (3.43 gal/c an-r ef ill) POP NO N = Statewide C o mm ercial-Gas-Can Population with respect to NonLawn-and-Garden Busin e sses S = Percentage of Gas Cans Stored with Fuel (70% f r om Residen tia l Survey) CF = 908,105 g/ton

The commercial-transport-spillage em issions are determ ined as:

HC TC = (Pop C )*(S)*(B C )*(Ref ill C )*( E F TC ) (Eq. 9)

where: HC TC = Comm ercial-Gas-Can-Trans port-Spillage Em issions (tpd)49 Pop C = Statewide Commercial-Gas-Can Population S = Percentage of Gas Cans Stored with Fuel (70% from Residential Survey) B C = Percentage of Gas Cans with respect to Storage Condition and Material Refill C = Average Number of Gas-Cans Pump Refills per Day per Can EF TC = Transport-Spillage Emission Fact or (g/refill) with respect to Storage Condition CF = 908,105 g/ton

The total area source portable fuel cont ainer emissions are summed as follows:

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

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

Where: E PFC - A = (tons/yr) for an annual emission of pollutant by county E PFC - SD = (tons/day) for a typical summer day emission of pollutant AADF = Annual activity day fact or (WAF * 52 weeks/year) SAF = Seasonal adjustment factor50 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 reactiv e VOCs, it has been

rem oved from the inventory total. T a ble 4.3-3 in Procedures lists three compounds under halogenated solvents for dry cleaning: 1,1,1 tr ich l oroe thane, trif l uorotrichloroethane and perchloroethylene. None of these solvents is on the VOC list. The la test Em ission Inventory Im provem e nt Program guidance on d r y cle a ning (Vol. III, Cha p ter 4, Dry Cleaning Final Report , May 2002), also states that the synthetic solvents used in dry cleaning are not photochem i cally reactive and should not be included in a VOC inve ntory of ozone precursors. Therefore this category ha s been eliminated from the 2002 periodic inventory.

3.1.2.2 Surface Cleaning (Cold Cleaning Degreasing) SCC: 24 15 300 000

Description
Cold clean in g is seen p r im arily at auto repair st ations or m a nufacturing fa c ilitie s, wher e solven ts at room temperatu r e (o r slightly warm ed) are us ed to clean parts via imm e rsion or rinsing.

Cold cleaners are usually individu ally sm all em ission sources and, becau se they are widely scattered an d frequently used, they are m o st easil y treated as area sou r ces . If they are collocated
at a m a jor s ource, th ey m a y be included in the point source inventory a nd those em issions will need to be s ubtracted from the area source es tim ate.

There are tw o basic types of cl eaning m achines: b a tch and in-lin e cleaning m achines (also called continuous cleaning m achines). Both of these eq uipm ent types are designed to use solvent to clean parts. The solvent is either used to cl ean in its non-vapor liquid form (at a tem p erature below the b o iling po int, ref e rred to as cold c l ea ni ng), or heated to a temperatu r e abo v e its bo ilin g point (referred to as vapor cleaning). Other solv ent cleaning operations involve the use of solvent in wipe-cleaning and equipm ent cleanup. Em iss i ons from solvent cleaning m achines can also be considered to be point sources; therefore, the es tim ation pro cess for the source categ o ry m u st take th is in to account to prevent dou ble count ing of e m issions. Additionally, em ission s from solvent cleanup m a y be included as a part of an industry- or pro cess-specific em ission estim ate.

VOC Pollutant s51 MDE staff used an alternat ive per capita em ission estim ation m e thod doc um ented in EIIP 23

, Chapter 6, S o lvent Cleaning, dated S e ptem ber 1997.

Activity The U.S. Ce nsus Bureau reports population sta tis tics f o r the c ounties of M a ryland. Population statistics for 2002 for the counties of Maryland w e re collected from the U. S. Census Bureau Internet address ( http://www.census.gov ).

An activity level of 6 days a week with no seaso n al adju stm e nt factor was used as

recomm ended in the E I IP docum ent. Solvent s t o r age and recycling centers such as S a fety Kleen are in cluded in th e point sou r ce inve ntory. The U.S. Census Bureau reports population statistics for the counties of Mary land. Population statistics for 2002 for the countie s of Maryland w e re co llec t ed f

r om th e U.S. Census Bureau In tern et address ( http ://www.census.gov ). A 2002 reduction factor (Phase II Attainm e nt Plan for the Baltim ore Nonattainm e nt Area and C ecil County ) of 53.60% was applied to the calcu l ated

em issions. This factor com b ines reducti ons from technology rules and good housekeeping practices an d the applic a tion of rule ef f ectiv eness as shown below:

Reduction factor = (control effi ciency) x (ru l e effectiveness) x (rule p e n e tration )

Reduction factor = 0.67 x 0.80 x 1.00

Reduction factor = 0.5360

Emission F a

ctor Table 6.5-4 of the EIIP docum ent lists a tota l em ission factor of 4.3 lbs. VOC per capita per year for solvent cleaning operations. The em ission factor is a com posed of a total from f our categor ies; includ in g autom obile repa ir (2.5 lbs. VOC per capita), m a nufacturing (1.1 lbs. VOC per capita), electronics and electrical (0.2 1 lbs. VOC pe r capita), and other (0.49 lbs.

VOC per capita).

Factors

E cc = 4.3 lbs VOC per cap ita per year for cold clean ing d e greas ers CE cc = 67% RE cc = 80% RP cc = 100%

Note: Method and Data Sourc e

23 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram52 Em issions from this source category have increas ed because o f a change in the em ission factor and em ission estim ation m e thodology. In previo us em ission inventories, only cold cleaning degreasing operations were considered an area source and open top and conveyor degreasing operations were considered point s ources th at were lis ted in the MDE/ARMA registration files. No point source em issions were then subtract ed f r om the area source inv e ntory. MDE previous ly u s ed an em ission factor from AP-42 , Section 4.6 – Solvent Degreasing, T a ble 4.6-1 24

. This tab l e reports a 4.0 lbs. VOC per capita em i ssion factor that include s 25 percent non-reactive VOCs, yielding an effective em ission factor of 3.0 lbs. VOC per capita. A 1996 reduction factor of 0.70 was applied to th e calcu lated em issions (rule effectiven ess was not applied). T h is factor

com b ines reductions from technology rules a nd good housekeeping practices . In effect, MDE increased the em ission factor from 3.0 to 4.3.

Solvent cleaning em issions from facilities iden tifi ed as poin t s ources were subtracted from the area source inventory to avoid double counting.

Maryland has adopted a cold and vapor degrea sing regulation (COMAR 26.11.19.09). The regula tion m a ndates that all co ld degreasing m a terial m u st have a vapor pressure less than or equal to 1 m m Hg at 20 degrees centigrade after May 15, 1996. The regulation also requires that good operating practices be im ple m e n ted to m i ni m i ze VOC losses. MDE estim ates a 67 percent
contro l efficiency for th is contro l.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equatio n used to es tim a te em issi ons from cold cleaning/degreasing is: Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

24 N onm et hane VOC Em i ssi ons fr om sm al l col d cl ea ni n g de greasi n g o p e r at i ons53 Equation:



## [ ] PtSourceCC CC CC CC cc j CC E RP RE CE EF POP E

− ⎭ ⎬ ⎫ ⎩ ⎨ ⎧

− = ) * * ( 1 * 312 * 2000 *

W h ere:

E cc = Em issions o f VOC in tons/day from cold cleaners POP j = 2002 population of county j EF cc = VOC e m issions factor for cold cleaning degreasing CE cc = Control efficiency fo r cold cleaning degreasing RE cc = Rule Effectiveness for cold cleaning degreasing RP cc = Rule Penetr ation f o r co ld clean ing d e greas ing E PtSourceCC = Point Source Em issions from cold cleaning degreasing

2002 Sa m p le Calculation for Cold Cl eaning Degreasing (Anne Arundel County)

(503,388 25 people x 4.3 lb/capita/year)/(2000 lb s./ton x 312 operating days/year) = 3.469 tons/day. 503,388 x 4.3 lbs. VOC/ person/year 26 = 2,164,568 lbs. per person VOC e m i tted.

Converting to tons per day: 2,164,568 / (312 operating days per year 27 x 2000 pounds per ton) = 3.469tons VO C per day e m itted (ther e is no sea s o n al adju stm e nt 28 ).

To adjust fo r contro ls 3.469 x [1 – (0.67 x 0.80 x 1.00)] = 1.610 tons VOC / day em itted with 2002 controls applied

To adjust fo r point sou r ces 1.610 tons VO C / day – 0.076 tons VOC / day = 1.534 tons VOC / day

25 Popu latio n d a t a fro m th e U.S. Bu reau of Censu s , Po pu latio n Esti m a tes Bran ch
26 Em i ssi on fact or f

r om EIIP
27 6 day s per we ek ope rat i o n f r o m EIIP
28 No seas onal a d justm e nt from EIIP54 3.3.2.3 Surface Coatin g

Surface coating includes paints, enam els, varn ishes, lacquers and other pro duct finishes . Som e of those coatings contain a solv ent-based liquid carrier; others use a water-based liquid carrier but still contain a sm all portion of solvents. Solv ents are also used to clean up paintin g equipm ent. The prim ary types of surface coa ting application s are architectural co ating s , autom obile refinishing and traffic paints.

3.1.2.3 Architectural Surface Coating SCC: 24 01 001 000

Description
Architectural surface co ating is an area source th at occu rs fro m hom e owners and con t racto r s painting hom e s, buildings and signs.

VOC

MDE staff used an alternative per capita em ission estim ation m e thod doc um ented in EIIP 29

, Chapter 3, Architectural Surface Coating, da ted Nove m b er 1995. The docum ent provides an outlin e f o r developing a per cap ita us age f actor, a nd f o r using that us age f actor and an em ission factor to calculated a VOC em ission estim ate.

Activity

Determ ine the per cap ita usage factor by divi ding the national tota l arch ite c tura l surf ac e coating qu a n tities 30 for solvent- and water-based coatings by the U.S. population 31 for t h at year.

Per Capita Usage Facto r Development

The table below shows a portion of T a ble 2 fr om the U.S. Bureau of Census MA28F - Paint and Allied Produ cts. This sec t ion of the tab l e sum m arizes the m a rket inf o rm ation available on architectural coatings for the year of 2002. In the table, types of paints are identified as being either solvent- or water-b as ed paints, except for the tw o types listed as Architectural Lacquers and Arch ite ctural Coating s N.S.K. These la tte r typ e s of paints can be assum e d to be entirely solvent-based co atings . The calcu lation to obtain the num ber of gallons of so lvent ba sed paints tota ls the gallons f o r Exter i or Solvent Typ e , Inte rio r Solvent Typ e , Architectural Lacqu e rs and Architectural Coatings N.S.K: Pollutant s

Method and Data Sourc es

29 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram 30 To tal n a tio n a l co atin g usag e is co m p iled b y t h e B u reau o f th e Cen s us, Rep o rt MA28 F—Pain t and Allied Produ cts,

av ailab l e o n the Cen s u s B u reau B u lletin Board, (30 1 )4 57 -2 310

. 31 Po p u l a t i on dat a fr om t h e U. S. B u rea u o f t h e C e nsus , P o pul at i on Est i m at es B r anc h

.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 divi ding the total usage of solvent based paints by the U.S. population, and the total usage of water based paint by the U.S. population.

Gallons of Solvent Based Paints Per Capita Solvent Based Usage Factor = U. S. Population 127,703,000
= 288,368,698

= 0.442846

Gallons of Water Based Paints Per Capita Water Based Usage Factor = U. S. Population 589,527,000
= 288,368,698

= 2.04435256 Table 2. Quantity and Value of Shipments of Paint and Allied Products: 2002 Product

code Product description 2002 Quantity

325510 Paint and allied products 1/ 1,448,755

3255101 Architectural coatings 717,230 Exterior solvent-type 70,967 3255101111 Solvent thinned paints and tinting bases, including barn and roof paints 19,874 3255101115 Solvent thinned enamels and tinting bases, including exterior-int erior floor enamels 11,444 3255101119 Solvent thinned undercoaters and primers 9,184 3255101121 Solvent thinned clear finishes and sealers 5,701 3255101125 Solvent thinned stains, including shingle and shake 14,665 3255101129 Other exterior solvent thinned coatings, including bituminous paints 10,099 Exterior water-type 182,423 3255101131 Water thinned paints and tinting bases, including barn and roof paints 118,492 3255101135 Water thinned exterior-interior deck and floor enamels 4,186 3255101139 Water thinned undercoaters and primers 13,786 3255101141 Water thinned stains and sealers 16,773 3255101145 Other exterior water thinned coatings 29,186 Interior solvent-type 48,947 3255101211 Flat solvent thinned wall paint and tinting bases, including mill white paints 6,288 3255101215 Gloss and quick drying enamels and other gloss solvent thinned paints and enamels 4,164 3255101219 Semigloss, eggshell, satin solvent thinned paints and tinting bases 9,674 3255101221 Solvent thinned undercoaters and primers 11,602 3255101225 Solvent thinned clear finishes and sealers 7,429 3255101229 Solvent thinned stains 1,892 3255101231 Other interior solvent thinned coatings 7,898 Interior water-type 407,104 3255101235 Flat water thinned paints and tinting bases 162,810 3255101239 Semigloss, eggshell, satin, and other water thinned paints and tinting bases 164,419 3255101241 Water thinned undercoaters and primers 43,051 3255101245 Other interior water thinned coatings, stains, and sealers 36,824 3255101249 Architectural lacquers 5,808 3255101YWV Architectural coatings, n.s.k. 1,981

3255104 Product finishes for original equipment manufacturers (OEM), excluding marine coatings 414,943 3255104111 Automobile, light truck, van, and sport utility vehicle finishes 47,99457 3255104121 Automobile parts finishes 5,636 3255104131 Heavy duty truck, bus, and recreational vehicle finishes 12,481 3255104141 Other transportation equipment finishes, including aircraft and railroad 11,558 3255104211 Appliance, heating equipment, and air-conditioner finishes 7,329 3255104215 Wood furniture, cabinet, and fixture finishes 43,725 3255104219 Wood and composition board flat stock finishes 10,060 3255104221 Metal building product finishes (including coatings for aluminum extrusions and siding) 35,855 3255104225 Container and closure finishes 43,393 3255104229 Machinery and equipment finishes, including road building equipment and farm implement 18,865

3255104231 Nonwood furniture and fixture finishes, including business 38,842 equipment finishes 3255104235 Paper, paper board, film, and foil finishes, excluding pigment 14,241 binders 4,447 3255104239 Electrical insulating coatings 77,567 3255104241 Appliance powder coatings 2/ 11,889 3255104245 Automotive powder coatings 2/ 8,903 3255104249 Architectural powder coatings (such as aluminum extrusions) 2/ 2,062 3255104251 Lawn and garden powder coatings 2/ 2,434 3255104255 General metal finishing powder coatings 2/ 22,203 3255104259 Thermoset functional powder coatings (for pipe, rebar, electrical insula tion, etc.) 2/ (D) 3255104261 Thermoplastic powder coatings (all) 2/ (D) 3255104265 Other industrial product finishes 38,485 3255104YWV Product finishes for original equipment manufacturers (OEM), excluding marine coatings, n.s.k. 4,465

3255107 Special purpose coatings, including all marine coatings 174,114 Industrial new construction and maintenance paints (especially formulated coatings for special conditions of industrial plants and/or facilities requiring protection against extreme temperatures, funge, chemicals, fumes, etc.): 3255107011 Interior 23,370 3255107015 Exterior 34,207 3255107021 Traffic marking paints (all types; shelf goods and highway department) 39,397 3255107031 Automotive, other transportation and machinery refinish paints and enamels, including primers 45,979 3255107041 Marine paints, ship and off-shore facilities and shelf goods for both new construction and marine refinish and maintenance. Excludes spar varnish 13,565 3255107051 Marine paints for yacht and pleasure craft, new construction, refinish and maintenance (D) 3255107061 Aerosol - Paint concentrat es produced for packaging in58 ae ros o l c o ntainers (D ) 32 5 5 1 0 7 Y W V Speci al pu r p ose c o at i n gs, n

. s.k

. 4, 23 3

3 255 10A Miscellan e o u s allied p a in t p r od u c ts 1 4 2
, 46 8 32 5 5 1 0 A 0 1 1 Pai n t a n d va rni s h rem overs 6, 43 3 32 5 5 1 0 A 0 2 1 Thi nne rs fo r l acque rs a n d o t her s o l v e n t ba sed pai n t pr o d u ct s 31 ,3 8 6 3 255 10A 031 Pig m en t d i sp er si o n s 2 5 ,151 3 255 10A041 Oth e r m i scel lan e ou s allied p a in t p r od u c ts, in clud ing b r u s h cleane r s, ink vehicles, putty and glazing c o m pounds, etc. 78,512 3 255 10AYWV Miscellan e ou s allied p a in t p r od u c ts, n.s.k

. 9 8 6

To ta l So lv ent-Ba sed 12 7, 7 0 3 To ta l Wa ter-Ba sed 58 9, 5 2 7

Emission F a

ctor Use the em ission factors for architectural su rface coating s (EP A , 1993A), that are shown in Table 5-2 of the EIIP docum ent and reproduced below:

Coating Type VOC Content Lbs / gallon W a t e r

- b a s e d 0

. 7 4 S o l v e n t

- b a s e d 3

. 8 7 T o t a l 4

. 6 1

This activity occurs 7 days a week and is usually m o re common in the summer m ont hs as indicated by a seasonal adjustm e nt factor of 1.3 (see Table 5.8-1 in Procedures) . It sho u ld be noted th at 99% of solvents in thes e coatings are VOC.

Because the application of archite ctu r al su rface coating is defined as an area source, th ere is no need to sub t ract po int so urce em issio n s from the to tal, and all em issions estim ated f o r this sourc e

are area sou r ce em issions

.

EPA surface coating reg u lation prov ides a 20 percent reduction.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source. Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns59 Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equatio n used to es tim a te em issions from architectural su rface coatin gs is:

Equation to calcu late solv ent-based em issions is: Emission s Calculation

POP i x UF AS C - S B x EF ASC - SB x SA F ASC x [(1 – (CE ASC x RE ASC x RP ASC )] E ASC – SB = 2000 x 365

W h ere:

E ASC – SB = VOC em issions in tons p e r day from solvent-based architectural surface co atings POP i = 2002 population of county i UF ASC – SB = Usage factor for solvent-ba sed architectural su rface coatings EF ASC – SB = VOC em ission factor for solvent- bas e d arch itectural su rface coating s SAF AS C = Seasonal ad justm e nt factor for arch itectural su rface coatings CE ASC = Control efficiency 32 for architectural s u rface coatings RE ASC = Rule effectiveness 33 for architectural s u rface coatings RP ASC = Rule penetration for arch itectural surf ace coatings

Equation to calcu late wa ter-b ased e m issions is:

POP i x UF AS C - W B x EF ASC - WB x SA F ASC x [(1 – (CE ASC x RE ASC x RP ASC )] E ASC – WB

= 2000 x 365

W h ere:

E ASC – WB = VOC em issions in tons p e r day from water-b ased architectural surface coatings POP i = 2002 population of county i UF ASC – WB = Usage factor for water-b ased ar chite c tura l su rface coatings EF ASC – WB = VOC em ission factor for water-b as ed architectural surface co atings SAF AS C = Seasonal ad justm e nt factor for arch itectural su rface coatings CE ASC = Control efficiency for architectural s u rface coatings RE ASC = Rule effectiveness for architectural s u rface coatings RP ASC = Rule penetration for arch itectural surf ace coatings

32 A 20 % redu ctio n in em issio n s is du e t o EPA’s AIM regu latio n 33 EPA’s AIM re gulation is a fe deral rule appl ying to arc h itectural s u rface c o atings60 2002 Example Calculation Architectural Surface Coating (Anne Arundel County)

Solvent-Based 503,388 1 x 0.442846 gal/capita x 3.87 lbs. VOC /gal/year 2 = 862,713.4 lbs. VOC per person per yr

To adjust for controls 862,713.4 x [1 – (0.20 x 1.00 x 1.00)] = 690170.7 lbs. VOC / year with 2002 controls Converting to tons per day: 690,170.7 / (365 days per year x 2000 lbs. per ton) = 0.945439 tons VOC per average day

To seasonally adjust: 0.945439 x 1.3 3 = 1.229 tons VOC per ozone season day emitted from solvent-based architectural surface coating

Water-Based 503,388 1 x 2.044352 gal/capita x 0.74 lbs. VOC /gal/year 2 = 761,535.7 lbs. VOC per person per yr

To adjust for controls 761,535.7 x [1 – (0.20 x 1.00 x 1.00)] = 609,228.6 lbs. VOC / year with controls applied

Converting to tons per day: 609,228.6 / (365 days per year x 2000 lbs. per ton) = 0.83456 tons VOC per average day

To seasonally adjust: 0.83456 x 1.3 3 = 1.085 tons VOC per ozone season day emitted from water-based architectural surface coating61 3.1.2.4 Auto Refinishing SCC: 24 01 005 000

Description

Autom obile ref i nish ing is the re painting of worn or dam a ged auto m obiles, light trucks and other vehicles. Coating of new cars is not included in this category but falls under industrial coating. In autom obile refinishing, lacquers and enam els are usually applied with hand-operated spray guns. Because the veh i cles con t ain heat-sensitiv e plastics an d rubber, th e coating s are dried or cured in low-tem p erature ovens or at am bient conditions. MD E adopted a regulation based upon federal guidance that requires the use of refo r m ulated coating s and equip m ent with greater transfer efficiency in the application of coatings.

VOC

MDE staff used an alternative per em ploy ee em ission estim a tion m e thodology docum e n ted in EIIP 34 , Chapter 13, Auto Body Refinishing, date d January 2000. The docum ent provides an outlin e f o r developing a per em ployee em ission f actor us ing a nationa l VOC em ission estim ate and national em ploym e nt data.

Activity MDE calculated an em ission factor of 0.3858 tons VOC per employee per year by utilizing the national VOC e m ission estim ate found in the EIIP document (79,429.39 tons) and totaling all of the reported stat e em ploym e nt totals within SIC 7532 for the entire U. S. The national VOC e m iss i on estim a te of 79,429.39 tons per year has been developed using 1997 activity and 1998 and 1999 em ission rate inform ation and are thus controlled

em issions. An EPA me mo on auto body refinish ing allows a 37% reduction for the f e deral rule. Maryland’s auto body regulation is m o re stringent than the national rule, which allowed MD E to take an additional 8% reduction.

County Business Patterns lists em ployee data by Standard Industry Code (SIC). Many values are based on actual data. However, so m e county SICs list a range for the number of

em ployees through a letter code. In this cas e the arithm etic average num ber of em ployees per letter code per county was ad justed so tha t th e sta t e to tal em ploym e nt in a SIC m a tched the sum of t h e num ber of e m ployees reported per county. Pollutant s

Method and Data Sourc es

34 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram62 The autobody refinishing category does not in clude new car coating. Applicable point

source em issions (those within the sam e SIC) tak e n f r om the MDE/ARMA registratio n files have been subtracted from the calculate d em issions, and their em issions are separated from the totals presented below. Table 5.8-1 in Procedures shows th at th ere is no seasonal varia tion in this ca tegory and the ac tiv ity level is 5 days a wee k

.

Emission F a

ctor:

MDE calculated an em ission factor of 0.3858 tons VOC per employee per year by utilizing the national VOC e m ission estim ate found in the EIIP document (79,429.39 tons) and totaling all of the reporte d state em ploym e nt totals within SIC 7532 for the entire U. S.

0.3858 tons VOC per em ployee per year

Autobody refinishing em issions from facilities identified as point sources were subtracted from the area source inventory to avoid double counting.

The national VOC e m iss i on estim a te of 79,429.39 tons per year has been developed using 1997 activity and 1998 and 1999 em ission rate inform a ti on and are thus controlled em issions. An EPA m e mo 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 allow e d MDE to take an additional 8% reduction.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equatio n used to es tim a te em issi ons from autom obile refinishing is: Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

EMP J x EF AR x [ 1- (RE x RP x CE)] E AR = 260 - E Point Source A R63 Where:

E AR = VOC emissions in tons per day from auto refinishing

EMP J = Number of employees in county j for SIC 7532 (auto refinishing), from County Business Patterns

EF AR = VOC emission factor for auto refinishing

E Point Source AR = Point source emissions from auto body refinishing

2002 Example Calculation Auto Refinishing (Baltimore County)

594 35 x 0.3858 36 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 Refinishing64 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 m a rk pavem e nt, the majo r ity of which is us ed to create dividing lines for traffic lanes. These m a rkings are applied by state or lo cal highway mainten a nce crews or by contractors. VOC em issions resu lt from the evap oration of organic solv ents during and shortly af

ter the app lica tion of th e m a rking paint. Al l tr a f f i c paint em issions are included in the area source inventory.

VOC

MDE staff were not able to ut ilize E P A's recomm ended "pounds per lane-m ile painted" em ission f actor due to the f act th at severa l ju ris d ictions did not keep records on lane-m iles painted. Instead MDE surveyed agencies for gallons of paint used and the VOC content of the paint used.

Activity The Maryland State Hig h way Ad m i nistration (S HA) keeps data on gallons of traffic

m a rking paint used by district and not by indi vidual county. For em issions from SHA line painting, each county’s p r oportion of the to tal d i strict’s lane miles was m u ltiplied by to tal gallons p a in ted in a d i strict to get an estim at ed amount of gallons used for each coun ty. In a few counties, SHA does all th e line painting. Also, da ta was collected from the Maryland A v iation Addm inistration (MAA) a nd the Mass T r ansit Addm inista tion (M TA).

MDE was able to ga ther inf o rm ation on gall ons of traffic paint used during the ozone season and d u ring a year. The Material Safety Data Sheets an d Environmental Data S h eets were collected for each paint and solvent used by each local jurisdiction and State ag ency doing the striping. It was necessary to colle ct data on yellow and white paint separately because the am ount of VOCs per gallon is different for each type of paint.

The em ission tota ls ar e s lightly lowe r than in pre v ious inven t ories be caus e m a ny jurisd ic tions have switch e d to la tex ( w ater-b orne) paints for traffic m a rking, and those areas alread y using latex paints have switched to using a late x paint that is lower in V O C content than what was previously us ed. The widespread use o f latex pain ts m eans that there are no longer any em issions from the solvents used to clean painting equipm ent when oil based paints are used. Pollutant s

Method and Data Sourc es65 The f o llowing inf o rm ation was colle cted f r om all public ag en cies us ing traffic m a rking paint in Mar y land:

Gallons of yellow traffic pain t and solvent used in 2002. Gallons of white traffic pain t and solvent used in 2002.

The MSDS and Environ m ental Data Sheets per type of paint provided the following inf o rm ation:

• Percent vo la tile by weig ht

• Percent water by weight

• Percent volatile organic com pounds by weight

• Total VOC (lbs./ga l)

• VOC/gallon less wate r

Emission F a

ctor

No subtraction of e m issions from point sources is necessary.

MDE surveyed the various state agenicies that a pply coating s to road su rfaces and transportation projects. MDE collected data on the gallons of pa int app lie d and the VOC content of the paint. MDE m a de em ission estim a tes based on this data a nd therefore no controls are available for th is source category.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Traffic Paint Sa m p le Calculation (C aroline County) Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation66 (1) Calculate VOC emissions from yellow and white traffic paints for ozone season

a. State Highway Administrati on (SHA) Traffic Paint Use

Total yellow gallons used April - October 37 = 4,671 gallons Total VOC per gallon of yellow paint used 38 = 0.78 lbs. VOC /gallon Total white gallons us ed April – October 39 = 6,481 gallons Total VOC per gallon of white paint used 40 = 0.77 lbs. VOC /gallon

(4,671 gallons) x (0.78 lbs. VOC /gallon) E Yellow Paint = (2,000 lbs./ton) x (214 days / ozone season)

E Yellow Paint = 0.0085 tons / ozone day

(6,481 gallons) x (0.77 lbs. VOC /gallon) E White Paint = (2,000 lbs./ton) x (214 days / ozone season)

E White Paint = 0.0117 tons / ozone day

E Local Paint Total = E Yellow Paint + E White Paint

E Local Paint Total = 0.0085 + 0.0117

E Local Paint Total = 0.0202 tons / ozone day

b. Maryland Aviation Administration (MAA) Traffic Paint Use

The MAA did not apply any pa int in Caroline County.

c. Maryland Transportation Administ ration (MTA) Traffic Paint Use

The MTA did not apply any pa int in Caroline County.

d. Local Jurisdiction Traffic Paint Use

The Local Jurisdictions did not appl y any paint in Caroline County.

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 Highways67 (2) Calculate VOC emissions from paint cleaning solvent use for ozone season

a. Local Jurisdiction Traffic Paint Use

The Local Jurisdictions did not use any paint cleaning solvents in Caroline County.

b. State Highway Administration (SHA) Solvent Use - None

The SHA did not use any paint cleaning solvents in Caroline County.

c. Maryland Aviation Administration (MAA) Solvent Use - None

The MAA did not use any paint cleaning solvents in Caroline County.

d. Maryland Transportation Admini stration (MTA) Solvent Use - None

The MTA did not use any paint cleaning solvents in Caroline County.

(3) Total VOC emissions from traffic paint 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 = 0.020268 3.1.2.6 Industrial S u rface Coating

Description
Industrial su rface coatin gs are ap p lied during th e m a nufacture of a wide variety of pro ducts, includ ing f u rnitu re, can s , autom obiles, other tr ansportation equipm ent, machinery, ap pliances,

m e tal coil, flat wood, wire and other m i scellane ous products. In addition, coatings are used in

m a intenance operations at industrial facilities but these are considered paint sources.

VOC

MDE used the m e thods and procedures docum ented in EIIP 41 , Chapter 8, Industrial Su rface Coatings, dated Septem ber 1997. Applicable poi nt source emissions (those within the sam e NAICS) taken from the MDE/ARM A registration f iles have been subtracted from the em issions calcu lated o n a per cap ita and per employee bas i s that are presented b e lo w.

Activity The choice between using per cap ita factors an d per em ployee factors in catego r ies where a choice of factors was of fered was made based on the quality of data. County Business Patte rns lists em ployee data by North Am erican I ndustry Classification System (NAICS). Many values are based on actual data. Howeve r, som e county NAICS list a range for the

num b er of employees through a letter code. In th is case the arithm e tic average num ber of

em ployees per letter code per c oun ty was adjuste d so that the state total e m ploym e nt in a NAICS m a t c hed the sum of the number of e m ployees reported per county. For those catego r ies w h ere all or m o st of the employm e nt data was listed as a rang e, the per capita factor was assum e d to be m o re reliable and was used to calculate em issions. The U.S. Census Bureau reports populat ion statistics for the countie s of Maryland. Population statistics for 2002 for the counties of Maryla nd w e re collected from the U. S. Census Bureau Internet address ( http://www.census.gov ).

Because the em ission factors were d e velope d based on NAICS e m pl oym e nt data and 2001 was the last year em ploym ent data was av ailable per NAICS, MDE used the 2001 County Business Patterns as the sour ce for employm e nt figures.

Emission F a

ctor Per em ployee factors were used for the following SIC and NAICS because they are
genera lly m o re re liab l e (see Procedures , Table 4-10.1), and a com p arison with per capita

em issions in one county showed that for these SICs, the per capita factors led to a large overestim ation of e m issions. Pollutant s

Method and Data Sourc es

41 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram69 Industry SCC SIC NAICS

Factory Finished Wood 24 01 015 000 2426, 2427, 2428, 2429, 2430, 2440, 2450, 2493, 2499 32121

Metal Furniture and Fixtures 24 01 025 000 2500 33636, 33791, 33792, 337121, 337122, 337124, 337125, 337127, 337129, 337211, 337212, 337214, 337215, 339111, 339942 Machinery and Equipment 24 01 055 000 3500 33272 Other Transportation Equipment 24 01 990 000 3700 except 3711 and 3730 333924

Marine Coatings 24 01 080 000 3730 48839, 81149, 336611, 336612

NAICS were used that best corresponded to SIC for each source category so that emission factors that were generated from E IIP SIC data could be used. EPA provided the correlation between NAICS and SIC. Emi ssion factors are listed in Table 8.5-1 in the EIIP Industrial Surface Coating document and below. As an example, MDE has chosen finished wood for presentation of an equa tion and emissions by county. The EIIP document lists no seasonal adjustment factor and 5 days per week activity. For counties with no employees listed in County Business Patterns 2001- Maryland , MDE assumed no emissions were generated because these proce sses were not located in those counties.

Appliances (SIC 363) , and Electrical Insulation (SIC 3357,3612) , had no employees listed in County Business Patterns in Maryland, thus no emissions were calculated. Emissions from New Motor Vehicles (SIC 3711) , were assigned to the point source section of the inventory since they are all from the General Motors Truck and Bus Group in Baltimore City.

Industry VOC Emission Factor (lbs. VOC /employee/year) Factory Finished Wood 131 Metal Furniture and Fixtures 944 Machinery and Equipment 77 Other Transportation Equipment 35 Marine Coatings 308 Appliances 463 Electrical Insulation 290 New Motor Vehicles 79470 Point Source Adjustment s Applicable point source em i ssions (those within the sam e SIC or NAICS) taken from the MDE/ARMA registratio n files ha ve been subtracted from the calculated em issions, and their

em issions are separated f r om the totals presented below.

MDE surveyed the various state agenicies that a pply coating s to road su rfaces and transportation projects. MDE collected data on the gallons of pa int app lie d and the VOC content of the paint. MDE m a de em ission estim a tes based on this data a nd therefore no controls are available for th is source category.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Equation: Adjustment for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

EMP i x EF FW

E FW = 2000 x 260

W h ere: E FW = VOC e m issions in t ons per day from finished wood EMP i = employees in county i em ployed in N A ICS 32121. EF FW = VOC e m ission factor for finished wood which is 131 lbs. VOC per em ployee per year

To adjust fo r contro l efficiency, etc.:

E FWA = (E FW - E FW R ) x [1

- (CE x RE x RP)] where:

E FWA = finished woo d adjusted em issions71 E FWR = emissions from factory finished wood sources in ARMA re gistration files that emit more than 10 tons per year VOC

CE = Control Efficiency RE = Rule Effectiveness RP = Rule Penetration

2002 Example Calculation Industrial Surface Coa ting – Machinery Coating (Baltimore County)

Number of employees in NAI CS 33272 in Baltimore County (2001 County Business Patterns ): 4543

Emission factor for other transportation equipment (lbs. VOC/employee/year): 77 42

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 calc ulated by per capita emission factors because employment data was not definitive.

Industry VOC Emission Factor (lbs. VOC /person/year)
Metal Cans 1.3 Misc. Manufacturing 0.6 Industrial Maintenance 0.8 Other Special Purpose Coatings 0.8 Misc. Finished Metals 0.5

Equation:

POP i x EF MFM E MFM = 2000 x 260 x [1 – (CE x RE x RP)]

where: E MFM = VOC emissions in tons per day from miscellaneous finished metals POP i = 2002 population of county i EF MFM = VOC emission factor for mi sc. finished metals (0.5 lbs. VOC per person per year) CE = Control Efficiency RE = Rule Effectiveness RP = Rule Penetration73 To adjust for Point Sources: E MFMA = (E MFM - E mfmar )

Where: E MFMA = adjusted emissions fr om miscellaneous finished metals E MFMAR = emissions from miscellaneous finished metal coating facilities in ARMA registered premise files

2002 Per Capital Sample Calculation for Misc. Manufacturing Coating in Anne Arundel County

503,388 44 x 0.6 lbs. VOC/capita/year 45 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 Coating74 3.1.2.7 Industrial Adhesives and Sealants SCC: 2440020000

Description
Industrial adhesive and s ealant surface coating is the application of a liquid or powder substance, such as solv ent type p a ints, varn ishes, and l acqu e rs to a surface for deco rative or p r o t ective purposes. T h e substances can be applied by brushing, rolling, spraying, dipping or flow coating. VOCs are released into the air as the substance d r ies. Powder coating s are applied to a hot surface and then m e lted; VOCs are released as the powder m e l t s and dries.

VOC

MDE staff used EPA’s “Solvent Mass Bala nce” m e thodology for estim ating em issions from nonpoint solvents, which uses the total solven t production and sales fo r a particular source catego r y to estim ate overall em issions then subtr acting out em issions due to point sources, waste

m a nage m e nt , and recycling.

Activity

EPA used the Freedonia 46 m a rket research report on nonpoi nt solvents to obtain solvent utiliza tion d a ta f o r th is s ource ca tego ry. Som e solvent us age estim ates ca m e f r om a National Paint and Coating Association (NP&CA) 47 . A brakedown of the m e thods 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 em ission estim a tes were then allocated to the state and county levels a nd adopted by MDE for this source category. Pollutant s

Method and Data Sourc es

46 Dat a were est i m at ed fr om Freedo n i a Gr o u p , I n c. - Free d o n i a R e po rt s f r o m 1999 an d 2 0 04
47 Nation al Pain t an d Co ati n g Associatio n (N P&CA) “Pain t s an d Co atin gs ‘2000': Revie w

an d Fo recas t ”75 3.1.2.8 Graphic Arts SCC: 24 25 000 000

Description Graphic arts includes op erations th at are invo lv ed in the printing of newspapers, m a gazines, books and other printed m a terials. T h ere are six basic operations used in graphic arts: lithography, gravure, letterpress, flexography, screen printing and m e tal decorating. Lithography accounts for nearly half of all graphic arts operations.

VOC

MDE staff used an alternative per capita em ission estim ation m e thod doc um ented in EIIP 48

, Chapter 7, Graphic Arts, dated Novem b er 1996. The EIIP m e thodology recomm ended an

em ission factor of 1.3 lbs. VOC per capita per year em ission fact or (EPA, 1991) for graphic arts

sources em itting less than 100 tons VOC per year. An activity level of 5 days per week was used with no seasonal adjustm e nt factor as recomm e nded in Table 5.8-1 in Procedures . Any point source graphic arts facility (SIC 275) in the ARMA re gistration files that had 2002 em issions of between 10 and 100 tons VOC per year had its em issions subtracted from the area source inventory.

Activity The estim ated percen tag e of m a rket share, reported in Table 7.2-3 of the EIIP document and reproduced below, was used to allocate th e total g r aphic arts em issio n s to specific printing types. Maryland has different regu lations regarding specific types of printing operations and thus to calculate controlled em issions the es tim a ted percentage th at each type of printing operation contributes to the tota l had to be de term ined. Pollutant s

Method and Data Sourc es

Type of Printing Estimated Percentage of Product Market Share R o t o g r a v u r e 1 8 F l e x o g r a p h y 1 8 Offset Lithography 47 Lette rpres s 8 S c r e e n 3 P l a t e l e s s 3

Emission F a

ctor 1.3 lbs. VOC per cap ita per year

48 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram76 Point Source Adjustment s Graphic a r ts em issions f r om f

acilities identif i ed a s point sou r c e s were subtracted f r om the ar ea source inventory to avoid double counting.

Control efficiency is bas e d on Maryland regulati ons for each type of prin ting pro cess and has been developed within technica l support docum ents for the gra phic arts printing regulations. Rule penetration has been defined as the estim ated percen tage that each ty pe of printin g operation. Rule effectiveness has b een assi gned the EPA default value of 80 per cent. Adjustment for Controls

L i t h o g r a p h i c R o t o g r a v u r e F l e x o g r a p h i c S c r e e n Rule Ef f ectiveness (RE) 0.800 0.800 0.800 0.800 Rule Penetr ation (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 f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equation used to estim a te e m issions from graphic arts is:

Equation: Spatial and Temporal Allocatio ns

Emission s Calculation

POP i x EF GA E GA = 2000 x 260 x [ 1 - RF L – RF R – RF F – RF S ]

W h ere:

E GA = VOC e m issions in tons per day from graphic arts POP i = 2002 population of county i EF GA = VOC e m ission factor fo r graphic arts (1.3 lbs. VO C 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 re gistered premise files th at emit more than 10 tons VOC /year78 2002 Example Calculation Graphic Arts (Anne Arundel County)

E GA = 503,388 49 x 1.3 lbs. VOC /capita/year 50 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 Arts79 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

em ulsified asphalt. Cutb ack asphalt is a liqu e fied road surface prepared by blending (or "cutting back") asphalt cem e nt with diffe rent petroleum distillates. Th e second type, em ulsified asphalt, is also a liqu efied road s u rface, but is prepared with a water/s o ap m i xture instead of petroleum distillates. Cutback asp h alt em its m o re VOCs, and its use h a s been lim ited in Mary la nd to the non-ozone period of April 15 to October 15.

VOC

MDE calculated em issions from this category ba sed on a per capita em ission factor of 0.004 pounds VOC per person per year fo r em ulsified asphalt from the Short List of AMS SCCs and Em ission Factors prepa r ed by EPA' s National Air Data Branc h . All em issions f r om this source are reactive VOC. An activ ity le vel of 5 days a week and no seasonal v a riation were assum e d. State of Maryland Departm e nt of Environm ent regulations (COMAR 26.11.11.02B), prohibit use of cutback asphalt paving from April 15 to October 15 so ozone precursor em issions from cutback asp h alt app lication were not calcu lated. Cutback asphalt is m a de by blending asphalt

cem ent with petro l eum distillates that evapor ate when the ro ad surface is "cured" after applic ation. Em ulsif i ed a s phalt is asp h alt c e m e nt m i xed with a blend of water and an emulsifier, usually soap. The equations for calculating VOC e m issions from e m ulsifi ed asphalt paving are presented below.

Activity The U.S. Ce nsus Bureau reports population sta tis tics f o r the c ounties of M a ryland. Population statistics for 2002 for the counties of Maryland w e re collected from the U. S. Census Bureau Internet address ( http://www.census.gov ).

Emission F a

ctors: Em ulsified Asphalt 0.004 pounds VOC per person per year

No subtraction of e m issions from point sources is necessary.

State of Maryland Departm e nt of Environm ent regulations (COMAR 26.11.11.02B), prohibit use of cutback asphalt paving from April 15 to October 15 so ozone precursor em issions from Pollutant s

Method and Data Sourc es

Point Source Adjustment s

Adjustment for Controls80 cutback asp h alt app lication were not calcu lated. Cutback asphalt is m a de by blending asphalt

cem ent with petro l eum distillates that evapor ate when the ro ad surface is "cured" after applic ation. Em ulsif i ed a s phalt is asp h alt c e m e nt m i xed with a blend of water and an emulsifier, usually soap.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The per cap ita equation used to es tim a te e m issions from asphalt paving is: Spatial and Temporal Allocatio ns

Emission s Calculation

POP i x EF EA E EA = 2000 x 260 W h ere:

E EA = VOC e m issions in tons per day from em ulsified asphalt POP i = 2002 population of county i EF EA = VOC e m ission factor for em ul sified asphalt which is 0.004 lbs. VOC per person per yr

2002 Em ulsified Asphalt Sa m p le Calculations: A nne Arundel County

• No seasonal variation assum e d

• Activity of five days per week

• Em ission factor of 0.004 lbs. VOC/person/year

503,388 (2002 County Population) x 0.004 = 0.0039 tons VOC per day 2000 lbs. per ton x 260 days per year

503,388 51 x 0.004 lbs. VOC/capita/year 52 = 2,013.552 pounds per person VOC e m itted

Converting to tons per day: 2,013.552 / (260 days per year x 2000 lbs. per ton) = 0.0039 tons VOC per day em itted

51 Po p u l a t i on dat a fr om U.S. B u reau o f th e Censu s , Po pu latio n Esti m a tes Bran ch

52 Em i ssi on fact or f

r om t h e Sh ort Li st of AM S SC C s a n d E m i ssi on Fact o r s fr om EPA Na tional Ai r Data Branc h

.81 3.1.2.10 Synthetic Organic Chemical Storage Tanks

This category is fully represente d in the point source inventory.82 3.1.2.11 Pesticide Application SCC: 24 61 800 000

Description
Pestic ides a r e substanc es or m i xtures used to con t rol plant an d anim al lif e f o r the purp o ses of : agricultural production, public heal th from pest-borne disease, reducing property dam a ge due to pests, and improving the aesthet ic quality of outdoor and ind oor surroundings. Agriculture, hom e owners, industry, and governme nt agencies use pesticides. Th e largest usage of pesticides by weight is in agriculture. Agricultural pe sticides control weeds, insects, m ites, fungi,

nem a todes, and other threats to the yiel d, quality, or safety of food production.

Em issions arise from pesticide use b ecause of th e volatile n a ture of m a ny ingred ients, solvents, or other additives used in the fo rm ulations. Many pesticide form ul ations u s e solven ts as carriers for m o re active organic or inorga nic ingredients. In pesticid e for m ulations, the organic or inorgan i c so lute is the "a ctive ingred ient" (AI ) , wh ile the solv ent carrier is the "in e rt carrier." Thus, the term s "active" and "inert" in pesticide f o rm ulations refer to t oxicological action, and are not indicators of photochem i cal activity. Bo th the active and inert ingredients in these for m ulations evaporate and c ontribute to VOC em issions.

VOC

Maryland A g ricultural S t atistics service in cooperation with the Pesticide Regulation Section of the Maryland Departm e nt of Agriculture com p iled inform ation for Maryland's 2000 pesticide statistics do cum e nt. The docum ent, Maryland P e sticide Statistics f o r 20 00 , reported pesticide usage in pou nds used in a year by active ing r edient for each Maryland co unty. Along with the pounds of AI applied, the docum ent also listed th e for m of many pesticid es and the form ulation of

som e selected pes tic id es. From this, MD E used the EIIP’s em ission inventory reference docum ent titled Pesticid e s – Agricultural and No nagricu ltu ral , Decem ber 1997, Sectio n 9.2.2 to
genera te the VOC em issions f o r the a c tive ingred ie nt and in ert carrier of th e pesticide. This required assum p tions and other refere nces to collect th e best infor m ation used in th e c a lculation s

.

The EPA method for estim a ting pesticide em issions uses a six-step procedure, as follows: 1. Determ ine both the application m e thod and the quantity of pesticide product applied. 2. Determ ine the typ e of f

o rm ulation used. 3. Determ ine the spe c if ic AI(s) in th e for m ulation and their vapor pressure(s). 4. Determ ine the percentage of the AI (or each AI) present. 5. Determ ine the VOC content of the f o rm ulation

. 6. Calculate the em ission s. Pollutant s

Method and Data Source:83 MDE slightly deviated from this method, sin ce information was presented to MDE in pounds of active ingredient. With the activ e ingredient, the vapor pressure and general application method (surface application or soil incorporation) was determined from the EPA's AP-42 document or The SCS/ARS/CES Pesticide Properties Data base For Environmental Decision-Making , by R. D. Wauchope, et al. Then the form (i.e. wettable powder, emulsified concentrate, granule, etc.) of the most likely pesticide was determined from a list in the Maryland 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 inform ation provided with the form of the pesticide in the Maryland Pesticide Statistics for 2000

.

The table below lists the EIIP emissions factors taken from AP-42 (Table 9.2.2-4) used to calculate this category.

Uncontrolled Emission Factors fo r Pesticide Active Ingredients

Vapor Pressure Range Emission Factor

(mm Hg at 20 ° to 25 ° C) kg/Mg lbs./ton

Surface Application

1 x 10 -4 to 1 x 10 -6 350 700

> 1 x 10 -4 580 1160
Soil Incorporation

< 1 x 10 -6 2.7 5.4

1 x 10 -4 to 1 x 10 -6 21 42

> 1 x 10 -4 52 104

Equations:

E pest = VOC Emissions from Active Ingredient (AI) + VOC Emissions from the Inert Ingredients (Inert).

VOC Emissions Active Ingredients (AI) = (lbs AI / year) x (lbs VOC / lb AI )

VOC Emissions Inert Ingredients = [(lbs AI / year) / % AI] x % In ert Ingredients x % VOC INERT INGREDIENTS
(lbs AI/year) x EF AI in lbs VOC/ton AI (lbs AI/year) E pest = 2000 lbs. Per ton + (1 - % Inert) x (% Inert) x (% VOC in Inert)

Annual Emissions Daily Emissions = 312 days / year x Seasonal Adjustment Factor84 where: AI = Active Ingredient ( lbs. / yr. ) EF AI = Emission Factor ( lbs. VOC / ton AI ) % inert = percentage of formulati on that contains the Inert Carrier % VOC in the inert = percentage of VOCs in the Inert Carrier portion of the pesticide SAF = seasonal adjustment factor of 1.3 to adjust for the summer ozone season

MDE assumed six working days per week and 100% volatilization of the VOC portion of the inert carrier.

Sample Calculations:

The following information was compiled from The Maryland Pestic ide Statistics for 2000 and The SCS/ARS/CES Pesticide Properties Data base for Environmental Decision-Making :

Table 3-26 Allegany County Pesticide Information

VOC V. Press Formulation Formula % VOC EF Alleg. Alleg.

Pesticide mm Hg Applicatio n Type (% Inert) Inert lbs. VOC/ lbs. A.I. lbs of A.I. Lbs/yr

2,4-D 8E-06 foliar spray gas 0.8 0.29 0.35 2,058 3107.580 Acephate 1.7E-06 crop spray gas 0.8 0.29 0.35 62 93.620 Alachlor 1.4E-05 soil spray gas 0.15 0.29 0.35 19 7.622 Amitrole 4.40E-07 foliar spray gas 0.784 0.29 0.35 6 8.416 Atrazine 2.89E-07 soil surface wp 0.8 0.25 0.35 478 645.300 Azinphos-Methyl 2E-07 crop spray ec 0.35 0.56 0.35 33 21.501 Azoxystrobin crop spray gas 0.77 0.29 0.35 1 1.321 Bacillus thuringiensis neg crop spray gr 0.96 0.25 0.35 107 679.450 Benomyl 1E-10 crop spray wp 0.8 0.25 0.35 9 12.150 Bifenthrin 1.8E-07 crop spray gas 0.1 0.29 0.35 2 0.764 Boric Acid 0.0001 spray wp 0.1 0.25 0.35 4 1.511 Captan 8E-08 crop spray gas 0.5 0.29 0.35 727 465.280 Carbaryl 1.2E-06 crop spray gas 0.5 0.29 0.35 93 59.520 Carbofuran 6E-07 foliar spray fog 0.56 0.39 0.35 1 0.846 Chloroneb 0.003 spray wp 0.35 0.25 0.58 17 12.148 Chlorothalonil 1E-03 crop spray gas 0.8 0.29 0.58 368 640.320 Chlorpyrifos 1.7E-05 soil incorporation gas 0.15 0.29 0.021 36 2.598

Clomazone 1.4E-04 soil incorporation ec 0.3 0.56 0.052 3 0.876

Clopyralid 0 foliar spray gas 0.8 0.29 0.35 1 1.510 Cyanazine 1.6E-09 crop spray dust 0.8 0.21 0.35 31 36.890 Cyfluthrin 1.6E-08 crop spray wp 0.3 0.25 0.35 153 69.943 Cypermethrin 1.4E-09 crop spray wp 0.3 0.25 0.35 5 2.286 Diazinon 6E-05 crop spray pellet 0.143 0.27 0.35 21 8.296 Dicamba 0 spray gas 0.8 0.29 0.35 126 190.260 Dichlobenil 1E-03 crop spray wp 0.8 0.25 0.58 3 4.740 Dicofol 4E-07 crop spray wp 0.3 0.25 0.35 25 11.42985 VOC V. Press Formulation Formula % VOC EF Alleg. Alleg.

Pesticide mm Hg Applicatio n Type (% Inert) Inert lbs. VOC/ lbs. A.I. lbs of A.I. Lbs/yr

Diflubenzuron 9E-10 crop spray wp 0.25 0.25 0.35 80 34.667 Dimethenamid > 1.0 soil spray gas 0.468 0.29 0.35 5 3.026 Diuron 6.9E-08 soil surface wp 0.8 0.25 0.35 310 418.500 Endosulfan 1.7E-07 crop spray gas 0.5 0.29 0.35 2 1.280 Esfenvalerate 1.1E-08 crop spray dust 0.3 0.21 0.35 7 3.080 Fenarimol 2.2E-07 crop spray wp 0.3 0.25 0.35 1 0.457 Flumetsulam ND spray aq 0.18 0.21 0.35 12 4.753 Fluvalinate 1E-07 crop spray rtu 0.8 0.2 0.35 69 79.350 Fosamine Ammonium 4E-06 foliar spray aq 0.8 0.21 0.35 8 9.520 Glyphosate 0 foliar spray aq 0.8 0.21 0.35 2,610 3105.900 Hydroprene ? ? gr 0.09 0.25 2 0.049 Imidacloprid 1.50E-09 spray aq 0.786 0.21 0.35 1,426 1598.986 Iprodione 1E-07 crop spray wp 0.8 0.25 0.35 24 32.400 Lambda-cyhalothrin 1.50E-09 spray ec 0.87 0.56 0.35 8 32.782 MCPP 0 foliar spray aq 0.5 0.21 0.35 49 27.440 Malathion 8E-06 contact spray ec 0.3 0.56 0.35 7 4.130 Mancozeb 0 crop spray Fl aq conc 0.8 0.21 0.35 165 196.350 Maneb 0 crop spray wp 0.8 0.25 0.35 26 35.100 Metalaxyl 5.62E-06 soil spray wp 0.25 0.25 0.35 7 3.033 Metam-Sodium 20 soil spray aq 0.8 0.21 0.58 334 474.280 Methoprene 17.5 spray aq 0.8 0.21 0.58 26 36.920 Methoxychlor 0 spray wp 0.25 0.35 3 1.050 Methyl Bromide 1824 release of gas Fl aq conc 0.8 0.21 0.58 58 82.360 Metolachlor 3.135E-05 soil spray ec 0.3 0.56 0.35 488 287.920 Metribuzin 1E-05 soil surface Fl aq conc 0.75 0.21 0.35 3 2.940 Metsulfuron Methyl 2.5E-12 foliar spray gr 0.2 0.25 0.35 1 0.413 Nicosulfuron 1.20E-16 grass spray gr 0.162 0.25 0.35 2 0.797 Oryzalin 1E-08 soil spray wp 0.75 0.25 0.35 77 84.700 PCNB 1.1E-04 soil spray wp 0.6 0.25 0.58 88 84.040 Paclobutrazol 6.00E-10 spray wp 0.5 0.25 0.35 13 7.800 Paraquat 0 target spray aq 0.8 0.21 0.35 124 147.560 Pendimethalin 9.4E-06 soil spray ec 0.6 0.56 0.35 1,257 1495.830 Permethrin 1.3E-08 crop spray ec 0.3 0.56 0.35 9,455 5578.450 Petroleum Oils 1.0E-03 spray ec 0.56 0.58 1,503 871.740 Phosmet 4.9E-07 crop spray wp 0.5 0.25 0.35 26 15.600 Picloram Neg foliar spray aq 0.8 0.21 0.35 252 299.880 Primisulfuron-methyl 1.50E-05 crop spray gr 0.49 0.25 0.35 2 1.180 Propachlor 7.90E-05 spray gr 0.35 0.25 0.35 2 0.969 Propoxur 9.7E-06 crop spray ec 0.3 0.56 0.35 2 1.180 Quizalofop-ethyl 3E-07 foliar spray ec 0.2 0.56 0.35 1 0.490 Sethoxydim 1.6E-07 foliar spray ec 0.3 0.56 0.35 1 0.590 Simazine 2.21E-08 soil spray wp 0.8 0.25 0.35 776 1047.600 Sulfentrazone spray gr 0.25 0.25 0.56 1 0.643 Sulfometuron Methyl 6E-16 soil spray gr 0.2 0.25 0.35 7 2.888 Sulfur 0 dust dust 0.2 0.21 0 96 5.040 Terbacil 3.1E-07 soil spray wp 0.8 0.25 0.35 4 5.400 Thifensulfuron methyl 1.3E-10 foliar spray gr 0.2 0.25 0.35 1 0.413 Thiophanate-methyl 1E-07 crop spray wp 0.5 0.25 0.35 37 22.200 Triadimefon 1.5E-08 crop spray wp 0.8 0.25 0.35 7 9.45086 VOC V. Press Formulation Formula % VOC EF Alleg. Alleg.

Pesticide mm Hg Applicatio n Type (% Inert) Inert lbs. VOC/ lbs. A.I. lbs of A.I. Lbs/yr

Trichlorfon 2E-06 crop spray sp 0.8 0.12 0.35 36 29.880 Triclopyr 1.26E-06 foliar spray ec 0.8 0.56 0.35 454 1175.860 Trifluralin 1.1E-04 soil incorporation ec 0.015 0.56 0.052 3 0.182

Vinclozolin 120.0099 spray ec 0.5 0.56 0.58 16 18.240 Zinc Phosphide 0 powder pellet 0.8 0.27 0 1 1.080 County Total 24529 23472.544

Emissions are calculated for each pesticide ac tive ingredient per county and then summed.

Example calculation for the emissions from Pendi methalin pesticide use in Allegany county.

Lbs lbs. VOC 1257 Emis Pendimethalin 1257 year x 0
lbs. AI + (1-0.6) x 0.6 x 0.56

Emis Pendimethalin = 1495.83 lbs. VOC / year
Emis Pendimethalin = 1495.83 / 2000 = 0.7479 tons VOC / year
Emis Pendimethalin = (0.7479 tons VOC / year) * (1 year / 312 days) * (1.3)

Emis Pendimethalin = 0.0031 tons VOC / day

The remaining pesticides used in Allegany c ounty are calculated in a similar manner.

Results: Since the EPA has released new guidance on the calcu lation of agricultural pesticide application, the new methodology vastly differs from the 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 ha s been debated by different groups. General thoughts from scholars and priv ate industry is the ol d methodology overpredicts the volatility of the organics in the pesticid e. The new methodology, presented here, requires many assumptions and uses data that takes account for the different vapor pressures of individual active ingredients. Th is method, along with some genera l assumptions, estimated pesticide emissions at 8.7 tons per day for the state. Th e decrease is due to th e change in method, along with a decline in pounds of pes ticides applied in the state.87 3.1.2.12 Commercial/Consumer Solvent Use SCC: 24 65 000 000

Description
Certain comm ercial/consum er uses of products containing volatile organi cs cannot easily be identified by questionnaires, su rveys or other inventory proced ures yieldin g locale-specific

em ission estim a tes. This category includes th e following sources: househol d products, toiletries, aerosol products, rubbing com pounds, windshield washing fluid, polishes, waxes, non-industrial adhesives, space deodorants, m o th control agents and laundry deterg ents.

VOC

The recommended em ission factor that com b ines em issions from all these sources is 7.84 pounds VOC per person per year, from EIIP Volum e III , Area Sources, Preferre d and Alternate Methods (July, 1997). This em ission factor ex cludes non -reactive VOC and takes into account m o re

recen t vola t ility leve ls ba sed on prod uct reform ulation, than d o es AP-42 , Fif t h Editio n. MDE used an activity level of 7 days a week and no seasonal adjustm e nt factor as suggested in Table 5.8-1 in Procedures

. Activity The U.S. Ce nsus Bureau reports population sta tis tics f o r the c ounties of M a ryland. Population statistics for 2002 for the counties of Maryland w e re collected from the U. S. Census Bureau Internet address ( http://www.census.gov ).

Emission F a

ctors: Comm ercial and Consum er Products (All) 7.84 lbs. VOC /person / yea r

No subtraction of e m issions from point sources is necessary.

Federal regulations provide a 20 percent reduction in em issions from a 3.9 lbs. VOC /person subset of the total comm ercial and consum e r products category.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source. Pollutant s

Method and Data Sourc es

Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns88 Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The per cap ita equation used to es tim a te em issi ons f r om com m e rcial an d consum er solvents is : Emission s Calculation

[ POP i x EF CC ] - [ (PO P i x CS CC ) x CE CC ] E CC = 2000 x 365

W h ere:

E CC = VOC e m issions in tons per day from commercial and consumer solvents POP i = 2002 population of county i EF CC = VOC e m ission factor for commercia l and consumer solvents (7.84 lbs. VOC /person ) CS CC = Controlled subset of commercial and consum er solvents (3.9 lbs. VOC /person) CE CC = Control efficiency for controlled su bset of comm ercial and consum er solvents (20%)

2002 Sa m p le Calculation Comm ercial/Cons um er Solvent Use (Anne Arundel County)

[ (503,388 53 ) x (7.84 54 ) ] - [ (503,388 x 3.9 55 ) x (0.20) 56 ] E CC = 2000 x 365

E CC = 4.868 tons VOC per day

53 Po p u l a t i on dat a fr om U.S. B u reau o f Cen s us, Po pu latio n Esti m a tes Bran ch
54 Em i ssi on fact or f

r om EIIP C h apt e r 5 C o m m erci al and C o nsum er S o l v e n t Use
55 E P A me mo f r o m J o h n S i e t z 56 E P A me mo f r o m J o h n S i e t z89 3.1.2.12.1 Barge, Tank, Tank Truck, Rail C a r and Drum Cleaning

SCC: 24 61 160 000

The EPA explained to M D E staff that the agency has not developed an em ission factor for this category. The EPA also stated that most barge, tank truck, rail car and drum cleaning is done by
steam cleaning and the residue goes to industrial and public waste disposal treat m e nt plants. It is im possible to separa te th is category's portion of the treatm ent plant em issions. The EPA considers the em issions from this category to be insignificant. Em issions from this category are calcu lated f o r the app r o p riate facilities in the po int source in ventory.

3.1.3 BIOPROCESS EMISSIONS SOURCES

3.1.3.1 Bakeries SCC: 23 02 050 000

Description Bakeries emit VOC, prim arily ethanol form ed by yeast ferm entation of bread or dough, during the baking p r ocess. Eth a nol is em itted through a vent, along with com b ustion produ ct gases. Large commercial bakeries are inventoried as poin t sources. In-store and neighborhood bakeries have lower em issions, and thus are co nsidered area sources.

VOC

MDE staff followed m e thodology described in an EIIP Area S ource 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 em issions (those within the sam e NAICS) taken from the MDE/ARMA registration files have been subtracted from the em is sions calcul ated on a per em ployee basis th at are presen ted below.

Activity Em ployee num b ers were taken from County Business Patterns 2001 - Maryland , NAICS 311812, Bakery Products and 311811, Retail Bakeries. Som e county em ploym ent data is represented by a letter code i ndicating a range f o r the num ber of em ployees for that SIC. In this case the arithm etic average number of e m ployees per letter code per county was adjusted so that the state total em ploym ent in a SIC m a tched the sum of the num ber of

em ployees reported per county Pollutant s

Method and Data Sourc es90 Emission F a

ctor An e m ission factor of 0.11 tons VOC per em ployee cited in an April 24, 1992 Technical Mem o randum prepared by Radian Cor poration for EPA was utilized.

Bakery em issions from faciliti es identified as point source s (NAICS 311812 and 311811) were subtracted from the area source in ventory to avoid double counting.

No controls are availab l e for this source category.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equation used to estim a te e m issions from bakeries is:

Equation : Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

EF BAK x EMP j E BAK = 260

W h ere:

E BAK = VOC e m issions from s m all bakeries in tons per day EF BAK = per em ployee em ission factor for bakeries EMPj = num b er of employees at sm all (le ss than 20 em pl oyees), bakeries in county j91 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

0.11 x 256 E BAK = 260

E BAK = 0.108 tons VOC per day

Point Source Adjustment

E BAK – Pt. Sources (Prince George’s County) = 0.0728 tons VOC per day

E BAK-ADJ = E BAK - E BAK – Pt. Sources E BAK-ADJ = 0.1083 – 0.0728 E BAK-ADJ = 0.0355 tons VOC per day

57 Point Source Reduction from MDE ARMA registration files92 3.1.3.2 Brew eries SCC: 23 02 070 001

Description During the ferm entation process, breweries em it ethanol and other VOCs. Although large-scale commercial breweries have been inventoried as p o int sources, there are m i crobreweries and brewpubs that em it lower levels of VOCs and th erefore m u st be inventoried as area sources. These sm aller breweries em it m o st of their VOC s f r om the f e rm entation r o om , not the brew kettle as is the case with the large breweries.

VOC

MDE/ARM A staff surveyed sm all brewpubs and m i crobreweries in Maryland.

Activity The survey questionn aire aske d th e brewing f acilities to prov ide MDE/ARMA with the

am ount of barrels brewed per m onth for the cal endar year 2002. For those facilities that reported only annual production am ounts, an average m onthly value was used.

Emission F a

ctor Em issions from the sm al l breweries were calcu lated using an em issi on factor cited in a February 5, 1992 Technical Mem o randum prepared by Radian Corporation for EPA. This

em ission factor is 56.743 lbs. VOC per 1000 barrels produced. On e barrel equals 31 gallons.

No subtraction of e m issions from point sources is necessary.

No controls are availab l e for this source category.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source. Pollutant s

Method and Data Sourc es

Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns93 Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equation used to estim a te e m issions from bakeries is: Emission s Calculation

EF BREW x BPj E BREW = 2000 x 260

W h ere:

E BREW = VOC e m issions from s m all bakeries in tons per day EF BREW = em ission factor for sm all breweries BPj = 2002 beer production in barrels 260 = 5 days/week activity level

2002 Sa m p le Calculation for Sm all Brew ery VOC Em issions (Anne Arundel County) :

Num b er barrels produced by m i crobrewe ries in Anne Arundel County: 1470.25

0.05674 x 1506.40 E BREW = 2000 x 260

E BREW = 0.000164 lbs. VOC per day94 3.1.3.3 Wineries

Description
Ethanol em issions from wineries occur during the ferm entation pr ocess. The em issions vary, depending upon the type of wine (red vs. white), the ferm entation tem p erature and the sugar content of th e grapes us ed.

VOC

MDE used the m e thods and procedures docum ented in AP-42 58 , Chapter 12, Beverages, Section 2, W i nes and Brandies dated September 1995. AP42 Chapter 9.12.2

Activity State of Maryland Com p trollers Offi ce a nd the S t ate of Maryland Departm e nt of Agriculture inform ed M D E staff that in 2002 Maryland wineries produced approxim a tely 99,701 gallons of wine. An infor m al survey of wineries in the ar ea suggests that 64,233 gallons of white and 57,303 gallons of red wi ne yielding approxim a tely 121,536 gallons of wine was actually produced.

Emission F a

ctor Table 9.12.2-1 of AP-42 shows that ethanol em issions are 1.8 lbs. VOC per 1000 gallons of white wine ferm ented and 4.6 lbs. VO C per 1000 gallons of red wine ferm e n ted.

No subtraction of e m issions from point sources is necessary.

No controls are availab l e for this source category. Pollutant s

Method and Data Sourc es

Point Source Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns

58 A P 42 , C h ap ter 9

. 1 2 .2 : Food an d Agr i cu ltu ral I ndu str i es, B e v e r a g e s, W i nes and B r and i es95 Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Using the above figures, the production of wine by all Maryland wineries in 2002 resulted in the production of 379.2 pounds of ethanol. MDE has d ecided not to include this source in the periodic inventory due to the insignificance of the 2002 em issions. Emission s Calculation

3.1.3.4 Distilleries

Description
Ethanol em issions are th e larg est co mponent of th e VOCs e m itted from distilleries. Distilleries produce both grain alcohol for industrial and fuel purposes, and distilled sp irits such as whiskey and brandy for consum ption purposes. The em issions points in th e distilled spirits

m a nufacturing process are likely to b e the sam e as in brewerie s and wineries, with the aging process as an additional source of em issions. Du ring the aging process, ethanol and water seep through the wooden barrels used to age whiskey and evaporate into the air. Aging and barrel

em ptying are the m a jor sources of VOC e m issions from whi s key production.

VOC

MDE staf f indicated tha t no distiller i es below th e 10 ton per y ear poin t so urce cu toff operated in the inven t ory area du rin g 2002. Fugitive VOC em issions from the aging process at large distillery operations can be substa ntial and will be included in th e point source inventory. Pollutant s

Method and Data Sourc es96 3.1.4 CATASTROPHIC/ACCIDENTAL RELEASES

3.1.4.1 Oil Spills SCC: 28 30 000 000

Description Oil spills in volve oil tan k er acc idents, tanker tru c k accid e nts , and spills and blowouts from oil rigs or pipelines in coastal and inland areas. Because a wide range of fuel types m a y be spilled, the nature and quantity of e m issions can vary. E m issions are also influen ced by the clean-up procedure and by dispersion and weathering processes.

Oil spill evaporation produces loc a l VOC em issions. If spills catch fire, additional S O 2, CO, CO2, PM, NOx and VOC e m issions m a y result. Other potentially toxic chem ical compounds

m a y also be released as a result of chem ical clean up

VOC

Activity Data on oil s p ills in Maryland were obtai ned fro m MDE' s Hazardous W a ste Em ergency Response Departm e nt. They provided MDE/ARMA st aff a monthly list of all oil spills that occurred in Maryland during 1999, by county. Gall ons of oil spilled per ozone season were summed by county for the ozone season period of April 1 through October 31 (214 days).

Emission F a

ctor MDE staff used an em ission factor recomme nded to the Metropolitan W a shington Council of Governments by E.H. Pechan and Associat es, Inc., the con t racto r used by MW COG to prepare their 1990 base year inventory. This em ission factor was based on a California Air Resources B o ard (CARB), study of air em issi ons from large oil spills (o ver 10 m illion gallons of oil). Based on this study, a range of evaporation estim ates for reactiv e organ i c gases was found to be between 5,500 and 13,000 tons. Using this inform ation, an average

em ission factor was calculated to be 0.0000925 tons VOC pe r ga llon of oil spilled. below.

No point source adjustm e nts were m a de. Pollutant s

Method and Data Sourc es

Point Source Adjustment s97 Adjustment for Controls

No controls are availab l e for this source category.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equatio n used to es tim a te em issions f r om oil spills: Spatial and Temporal Allocatio ns

Emission s Calculation

EF Oil Spills x GOSj E Oil Spills = 2000 x 365

W h ere:

E Oil Spills = VOC em issions f r om oil spills in ton s VOC per day EF Oil Spills = em ission factor for sm all breweries GOSi = gallons of oil spilled in county I

2002 Sa m p le Calculatio n for Oil Spill VOC Em i ssions (Baltimore County) :

Annual Em i ssions: Num b er gallons oil spilled in Baltim ore County, 2002:

(0.0000925) x (Gal) E Oil Spills = 2000

E Oil Spills = tons VOC per year

Num b er gallons oil spilled in Ba ltim ore County, April-October, 2002

(0.0000925) x (Gal) E Oil Spills = 2000 x 214

E Oil Spills = tons VOC per ozone season day98 3.1.4.2 Leaking Underground Storage Tanks SCC: 26 60 000 000

Description Many underground storage tanks (U STs) are over 15 years old and are constructed of steel, which m a y r u st over tim e. The underground pipi ng connected to these tanks also has the potential to leak. Leakin g USTs are of concern b ecause they m a y result in the contam ination of drinking water, subsurface so ils, and ground and surface water, and m a y em it toxic an d/or explosive vapors. The contam inated soil and wa ter m a y also em it VOC.

VOC

Activity As suggested in section 4.8.6 of Procedures , MDE staff use d em issions from soil an d groundwater rem e diation to estim a te VOC e m issions from leaking underground storage tanks. From the MDE/ARMA registration file s, inventory staff obtained location of soil and ground water rem e diation sites and obtained fugitive VOC e m issions from each site in pounds per day. No seasonal variation was assum e d.

Emission F a

ctor VOC em issions are tho s e allowab l e in each rem e diation perm it- there are different allowable em issions for each perm it.

No point source adjustm e nts were m a de.

No controls are availab l e for this source cate gory. Because M D E staff used m a xim u m allowable

em issions f r om perm it inf o rm ation, MDE believ e s that Rule Effectivenes s, Control E fficiency, and Rule Pe netra tion a r e not applica b le to this so urce. Pollutant s

Method and Data Sourc es

Point Source Adjustment s

Adjustment for Controls99 Spatial and Temporal Allocatio ns Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s Calculation

RS1 j + RS2 j + RS3 j
.... E UST = 2000

where: E UST = VOC e m issions in tons per day from leaking underground storage tanks

RS1 j , RS2 j = pounds VOC per day allowed from rem e di ation site(s ) in coun ty j

2002 Sa m p le Calculation for Leaking Underg round Storage Tanks (Anne Arundel County)

No seasonal variation assum e d

Annual VOC e m issions in pounds per day: (f rom soil and groundwater rem e diation) Activity lev e l: 7 day s /w eek (se e tex t )

VOC e m issions in tons per day: pounds/day total from re gistration data: pounds/day/ 2000 = tons VOC per day from leaking underg round storage tanks in Anne Arundel County100 3.1.5 SOLID WASTE DISP OSAL, TREATMENT, AND RECOVERY

3.1.5.1 On-site Incineration SCC: 26 01 000 000

Description
On-site incineration is the conf in ed burning of waste on a s m all scale b y institution s such as hospitals, nursing hom es, veterinary offices, funeral hom es and laboratories. Large-scale incineration is included in the point source inventory.

VOC, NOx, SOx, CO, and PM 10

In Maryland incinera tors are regulated under COMAR 26. 11. 08. Maryland began regulating incine rato rs for control o f particu l ate s in the 197 0' s. In AQCRs III and IV single cha m ber incinerators, the type that would be used for on- site res i den tia l inc i nera tio n, were ban n ed. All such incinerators were rendered inoperative under the direction of the Maryland Departm e nt of the Environm ent (MDE). Over 1700 sm all incine rators were elim inated under this requirem e nt.

In the other Maryland counties included in the Washington, D.C. nonattainm e nt area, incineration of trash in on-site incinerators is prohibited except in areas w h ere public trash collection is not provided.

COMAR 26.11.08.09 now requires a ll in cine rato rs to obtain a pe rm it to operate and any person who owns or operates an inci nerato r must obtain certificat ion from MDE a nd renew the certification annually.

MDE/ARMA m a intains a regis t ry of all incine rators within th e State. Because of the requirem e nts prohibiting single cham ber incinerators, the requ irem ent for a perm it to o p erate, and the operator certification require m e nts, staff used the su m of the incinerato rs in the regis t ry as repr esen ting the to tal area sou r ce em issions f r om incinera tors of all typ e s em itting less than 10 tons/VOC, 100 tons/yr C O and 50 tons per year NO x . Incine rators from t h e regis t ry with

em issions above these thresholds are in cluded in the point source inventory.

No seasonality is applied. The em is sion factor is chosen by type of incin e rato r: was t e, patholog ical, hazardous, industrial, special m e dical, sewage sludge and municipal waste

com bustors. The burn rate is determ i n ed by stack test or AP-42. Hours of operation and tons of waste per day are supplied by the operator. Pollutant s

Method and Data Sourc es101 3.1.5.2 Publicly Owned Treatment Works (POTWs) SCC: 26 30 020 000

Description

EPA Procedures m e ntions that research into VOC e m i ssions from POTWs has found that in the event of "heavy chem ical load ing", 8 5 % of volatil e pollutan t s discharg ed to these facilities "are stripp ed to the am bient air" (Section 3.5.1). Also, VOC conce n tration in P O TW influent is directly proportional to the industrial cont ribution to POTW s as stated in Procedures , Page 3-14.

VOC, NH 3

The em issions from these facilities were calculated based on the m e thod described in Procedures

, Section 3.5.1.

Activity The percen t industrial flow for each POTW in Maryland was supplied by the Mary lan d W a ter Managem e nt Adm i nistration. MDE st aff multiplied this am ount by the em ission factor listed above to get VOC e m iss i ons from ea ch POTW . The individual POTW

em issions were then totaled by county. Som e counties are not listed in this table because their industrial effluent is discharg ed to a POTW in another county.

Emission F a

ctor This m e thod uses an em ission factor of 1.1 x 10 -4 pounds VOC em itted per gallon of industrial wastewater disc harged to a POTW

.

VOC stack em issions in the Air Managem e nt regi stration files from the Patapsco W a stewater Treatm e nt Plant in Baltim ore City were subtrac t e d f

r om the totals b e low.

No controls are availab l e for this source category. Pollutant s

Method and Data Sourc es

Point Source Adjustment s

Adjustment for Controls102 Spatial and Temporal Allocatio ns Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

The equatio n used to es tim a te em issions f r om POTW s is: Emission s Calculation

DF I J x PI F I J x EF PO TW x SAF POT W E POT W = 2000

W h ere: E POT W = VOC e m issions in tons VOC per day from POTWs DF I J = Daily flow into POTW i in county j PIF I J = Percent industrial fl ow from POTW i in county j EF PO TW = VOC e m ission factor 59 for POT W s SAF PO TW = Seasonal ad justm e nt factor 60 for peak ozone season which is 1.4

2002 Sa m p le Calculation for POTW VOC Emissions (Anne Arundel County) :

Back River Sewage Treatm ent Plant statistics 61 : 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 POT W = 2000

E POT W = 0.0639 tons VOC / day

59 Em i ssi on fact or t a ke n f r o m Pro ced ure s , Se ct i on 3. 5. 1
60 Seas onal a d ju stm e nt fact or t a ken f r om Pr o cedu r es, Ta bl e 5. 8. 1
61 Su p p l i e d by t h e M a ry l a nd Wat e r M a na gem e nt A d m i ni st rat i on 62 MGD : Millio n Gallo ns p e r Day103 3.1.5.3 Open Burning – Land Clearing Debris SCC: 26 10 000 500

Description Open burning of land clearing debr is ref e rs to the clea ring of land for new construction and the burning of organic m a terial (i.e., trees, shrubs and other vegetati on). The clearing of land for the construction of new buildings and highways often re sults in debris consisting of trees, shrubs, and brush. T h is debris may be burned in place but it is usually collected in piles for burning. The burning of land clearing wastes m a y be practi ced by private individua ls, corporations, and
governm e nt agencies (e.g., highway constructio n departm e nt). There are no federal laws restricting the open bur ning of land clearing wastes, although state or local laws m a y exist.

Residential open burning without a perm it is pr ohibited in Maryland, COMAR 26.11. 07, where trash and leaf collection is available. The basic d i fference between the reg u lation as it applies to counties in AQCRs III and IV and th e rest of th e state is the requirem e nts under which the burn takes p l ace, i.e., m i ni m u m setbacks from property lin es, etc. In the m o re rural counties, areas with no available trash collection are m o re preval ent. MDE adopted a regulation that prohibits open burning during the peak oz one period (June to August). The seasonal prohibition only affects those counties that lie within serious and severe ozone nonattain m e nt areas. Certain

exem ptions must be in p l ace however so as not to adversely affect agriculture or restrict fire training and recreational activitie s. C o mm ercial open burning w ithout a perm it is prohibited in Maryland.

VOC, NOx, SOx, CO, PM 10 and PM 2. 5

The m e thod used to calculate em issions, is presented in EIIP 63 , Chapter 16, Open Burning (Revised Final 2001).

Activity The num ber of acres disturbed by residential, non-residential and ro adway construction are estim ated and then these values are added togeth er to obtain a county- level estim ate of total acres disturbed by land-clearing. County-level em issions from land clearing debris are then calcu lated b y m u ltiply in g the to tal a c res disturb e d by constru c tion by a w e ighted load ing factor and em ission factor. Pollutant s

Method and Data Sourc es

63 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram104 The BELD database in BEIS was used to determine the number of acres of hardwoods, softwoods, and grasses in each county. Average loading factors were weighted according to the percent contribution of each t ype of vegetation class to the total land area for each county. The loading factors for slash hardwood and slas h softwood were further adjusted by a factor of 1.5 to account for the mass of tree that is below the soil surface that would also be subject to burning once the land is cleared.

Fuel loading factors are as follows:

Fuel Type Fuel Load Factor (tons/acre) Adjusted Load Factor (tons/acre) Hardwood 99 148.5 Softwood 57 85.5 Grass 4.5 4.5

Average fuel loading factors were calculated as follows:

(Acres HW-COi x LF Adj-HW ) +(Acres SW-COi x LF Adj-SW ) +(Acres GR-COi x LF Adj-GR ) LF OB –LCD – COi Acres TOT-COi

LF OB –LCD – COi = Average Load Factor in County i Acres HW-COi = Acres of hardwood in County i from BELD database LF Adj-HW = Adjusted Load Factor for Hardwood Acres SW-COi = Acres of softwood in County i from BELD database LF Adj-SW = Adjusted Load Factor for Softwood Acres GR-COi = Acres of grasses in Coun ty i from BELD database LF Adj-GR = Adjusted Load Factor for Grasses Acres TOT-COi = Total Land Acres in County i

Emission Factors 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 PM 10 16 Lbs. PM10 / ton PM 2.5 17 Lbs. PM2.5 / ton

Ozone Season Daily (OSD) emissions calculated by multiplying annual emissions by 0.25 then dividing by 92.

64 Emissions factors for VOC NOx, CO, SO 2 , PM 10 and PM 2.5 were obtained from AP-42 Table 2.5-1.105 Point Source Adjustment s
No subtraction of e m issions fr om point sources is necessary.

No controls are availab l e for this source category.

Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Annual Emissio n

s Adjustment s for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

AD R- N R

- R o a d x LF OB –L CD – COi x EF OB i E OB –L CD – Ann = 2000

E OB –L CD – Ann = Annual em issions from open burning of land clearing debris AD R- N R

- R o a d = Acres disturbed from Re sident ial, Non-residential and Roadway
construc tion in the coun ty LF OB –L CD – COi = Average Load Factor in County i FL HW

- S W- G = Fuel loading factor for hardwoods, softwoods, and grasses EF OB i = Open burning em ission factor f

o r po llutan t i in lb s. / ton

Ozone Season Daily Emissions

E OB –L CD – Ann E OB –L CD – Day = 4 x 92

E OB –L CD – Day = Ozone Season Daily emissions from open burning E OB –L CD – Ann = Annual em i ssions from open burning of land clearing debris 4 = Num b er of seasons in th e year 92 = Days in the season106 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 cl earing debris, household waste, and agricultural crop waste. Household waste, of ten referred to as residential m unicipal solid waste (MS W ), is a term for nonha zardous refuse produced by households (e.g., paper, plastics,

m e tals, wood, glass, rubber, leathe r, textiles, and food wastes).

Open burning without a perm it is prohibited in Maryland where trash and leaf collection is available, C O MAR 26.11.07. The basic differe nce between the regula tio n as it applie s to counties in AQCRs III and IV and th e rest of th e state is the requirem e nts under which the burn takes p l ace, i.e., m i ni m u m setbacks from property lin es, etc. In the m o re rural counties, areas with no available trash collection are m o re preval ent. MDE adopted a regulation that prohibits open burning during the peak oz one period (June to August). The seasonal prohibition only affects those counties that lie within serious and severe ozone nonattain m e nt areas. Certain

exem ptions must be in p l ace however so as not to adversely affect agriculture or restrict fire
tra i ning and recr eational activ ities.

VOC, NOx, SOx, CO, PM 10 , PM 2. 5 , and Toxics

The m e thod used to calculate em issions is pres ented in a study/survey conducted by the MidAtlantic/Nor theas t Visib i lity Union ( M ANE-VU), titled “Ope n Burning in Residential Areas Em issions Inventory Developm ent Report.” 65

Activity The purpose of the survey was to obtain data for developing activity estim a tes and control inform ation (e.g., bans on burning) that woul d form the basis of an im proved open burning

em ission inventory for Mid-Atlantic/Northeas t Visibility Union (MANE-VU) states and tribes for the year 2002.

A rule effectiveness (RE) survey was also pe rform e d to estim ate controlled em ission s for areas that prohibit open burning. Househol d waste burning surveys were com p leted for 72 respondents or jurisdictions, while yard wast e surveys were conducted for 181 espondents. The respondents for this survey were typi cally local fire wardens or chiefs. Rule Pollutant s

Method and Data Sourc es

65 O p en B u rni n g i n R e si de nt i a l Areas Em i ssi ons In ve nt o r y D e vel o pm ent R e prt , Pre p a r t e d by E. H. Pec h a n & Asso ciates, In c. fo r th e Mi d

- Atlan tic/No r th east Visib ility Un ion

, d a ted Janu ary 31
, 20 04

.107 effectiveness surveys related to residentia l MSW rules were conducted for 49 respondents, while RE surveys for yard waste burning rules were perform e d for 51 respondents. In obtain i ng su rvey respon s e s, Pechan collected ac tivity da ta an d contro l inf o rm ation f o r areas classified as urban, s uburban, and rural, or a com b ination of these designations (defined using data from the 2000 U.S. Census). Pechan also developed a control database for each open burning category that d e scrib e s th e recomm ended contro l efficiency (CE ) and rule penetration (RP) va lues by state and county, and by subcounty, where applicable.

Open burnin g activ ity estim a tes recorded from the survey were used directly to estim a te

em issions for the surveyed ju risdictions. For the non-surveyed areas, including tribal lands, the default activity data derive d from all survey responses w e re applied. Households are defined as detached single-fam ily unit dw ellings as provided by the 2000 U.S. Census.

Emission F a

ctors

Em ission f actors in lbs / ton tota l m a ss were taken from AP-42 Table 2.5-1, Em ission Factors for Open Burning of Municipal Re fuse and from a 1997 EPA research paper on open burning 66 are listed below:

Pollutan t Em ission Factor Lb/ton total m a ss burned V O C 8

. 5 5 6 N O x 6 C O 8 5 PM 10 38 PM 2. 5 3 4

. 8 SO 2 1.0

No subtration of e m issions fr om point sources is necessary.

If an area has controls or pr ohibitions on residential burning, controlled em issions were calculated from uncontrolled em ission s using the following equation:

E c = E uc * [(1-(CE)(RP)(RE)] Point Source Adjustment s

Adjustment s for Controls

66 EPA

. 19 9 7

. E v al uat i o n of E m i ssi ons f r o m t h e O p e n B u r n i ng O f H o use h ol d Wast e i n B a rrel s

. EP A

- 6 00/ R

- 9 7

- 13 4a. U

. S. E n i v i r onm ent a l Pr ot ect i on A g e n c y , C o nt rol Tec h n o l o gi es C e nt er. R e searc h T r i a n g l e Par k

, N o rt h Caro lin a.108 where: E c = Controlled area source emissions E uc = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100

The following sections describe how values for CE, RP and RE were derived from the
survey.

Rule Effectiveness Pechan evaluated differences in RE between rural/suburban and urban areas, as well as differences in RE for MSW and yard waste burni ng. Although one may expect that RE would be higher for urban than for suburban or rural ar eas, ANOVA of the survey results from these geographic subdivisions, as well as for the different open burning categories, did not show that RE values were drawn from dis tinct populations. Therefore, the fi nal selection of RE reflects a value for all areas and all burning categories.

There was a total of 26 RE survey responses that included information on the number of violating households. To calculate RE, Pechan used the number of households violating the rule, and the number of households expected to perf orm open burning for areas in the region where there is no rule (i.e., # househol ds x fraction of open burning hous eholds by region from survey).

The RE values obtained from the survey responses will be used for the specific State or jurisdiction surveyed. Non-surveyed areas could not be assigned a jurisdiction-specific RE, because no survey responses were obtained for t hose areas. Pechan did not develop statespecific RE values since we had no reason to believe th at local jurisdictions in individual states implemented their rules differently than local ju risdictions in the rest of the MANE-VU region. To estimate a default RE value for the remaining areas, the survey data were statistically analyzed. After evaluating the da ta using the Census 2000 data, a mean value of 96.8 percent reflected the best estimator of central tendency. As such, Pechan applied a rule effectiveness of 96.8 percent to all areas and for both MS W and yard waste burning (Pechan, 2002b).

Control Efficiency and Rule Penetration For those areas identified to have a control, CE is assume d to be 100 percent (since the control is typically a ban on burning activity). For MSW bur ning, with the exception of Pennsylvania, Pechan assigned 100 percent CE and 100 percent RP to urban and suburban areas in the MANE-VU region (i.e., even if the stat e did not have a statew ide ban on burning). In Pennsylvania, unless a jurisdic tion or county (e.g., Allegheny County) was determined via survey to have a ban, it will be assumed that suburban and rural areas allow open burning. For yard waste burning, Pechan assigned 100 percent CE and RP to all urban areas in the MANE-VU region. Yard waste emissions calculated for suburban and urban areas were assumed to be109 uncontrolled, unless the survey data or other st a t e w ide or loc a l control inf o rm ation indicated otherwise. F o r m unicipal yard waste burning, area s were assu m e d to either perf orm this activity and have associated em issions, or did not c onduct burns and therefore were assigned zero

em issions.

In determ ining annual em issions for those areas w ith a seasonal ban, Pechan adjusted the RP by the leng th of the seas onal ban r e lative to the entire year. The RP value also depends on how the tim e period of the ban overlaps w ith the activ ity profile for the specific category of burning. For exam ple, for brush waste burn i ng , the survey data revealed an averag e activ ity p r o f ile as follows: W i nter–20%; S p ring–46%; Summ er–6%; a nd Fall–28%. So, for an area that has a brush burning ban in the summer, although som e pe rcentage of burning is likely to be prevented during this season, we assum e th at 2 percent of the summ er se ason brush burning in August is delayed un til Septem ber when burnin g is perm itte d, resulting in an RP of 4 percen t to a pply to annual brush waste burning em issions. As m e ntione d in the discussion of tem poral allocation prof iles, this also has an af f ect on the m onthly activity profile. A summ er RP value of 4 percent would result in a revised tem poral allocati on profile to be: W i nt er–20%; S p ring–46%; Summ er– 4%; and Fall–30%.

Spatial Pechan colle c ted ac tiv ity data and co ntrol in formation for areas clas sified as urban, suburban, and rural, or a com b ination of thes e designations (defined using data from the 2000 U.S. Census).

Temporal Activity estim ates and associated em issions are calculated on an annual basis. Pechan proposes the following temporal allocation profile s to represent m onthly, weekly, and daily activity profiles by SCC (see Tables II-2 thr ough II-5). The m onthly activity profiles w e re developed based on data obtained from the survey. The weekly and week day/weeken d prof iles wer e developed based on en gineer ing ju dgm e nt. These prof iles w ill b e applie d to annual activity for all areas of MANE-VU (i.e., variations in regional, State, or tribal areas
are not acco unted for).

Tem poral Allocation Profile Form ats (m onthly) Spatial and Temporal Allocatio ns

Mont h

SCC Jan Feb Mar Ap r Ma y Jun Jul A ug Sep Oct No v Dec
261003000 0 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083
261000040 0 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067
261004040 0 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067
261000010 0 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.333 0.333 0.333 0.000

Tem poral Alloca tion Pr of ile Form ats (weekly)

Da y of We ek110 M o n T u e W e d T h u F r i S a t S u n
261003000 0 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 2 2 2 0

. 2 2 2
261000040 0 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 2 2 2 0

. 2 2 2
261004040 0 0

. 2 0 0 0

. 2 0 0 0

. 2 0 0 0

. 2 0 0 0

. 2 0 0 0

. 0 0 0 0

. 0 0 0
261000010 0 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 2 2 2 0

. 2 2 2

Tem poral Allocation Profile Form ats (daily; weekday)

Weekda y H our SCC 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200
261003000 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071
261000040 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071
261004040 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071
0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071 261000010 0

Weekda y H our 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 0000 SCC 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0 261003000 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0 261000040 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0 261004040 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0 261000010 0

Tem poral Allocation Profile Form ats (daily; weekend day)

Weekend Da y H our 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 SCC 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071 261003000 0 0 0 0 0 0.071 0.071 0.071 0 0 0.071 0.071 0.071 261000040 0 0 0 0 0.071 0 0 0 0.071 0.071 0.071 0.071 0.071 261004040 0 0 0 0 0 0.071 0 0 0.071 0.071 0.071 0.071 0.071 261000010 0

Weekend Da y H our 1300 1400 1500 1600 1700 2000 2300 1800 1900 2100 2200 0000 SCC
261003000 0 0.071 0.071 0 0 0.071 0.071 0.071 0.071 0.071 0.071 0 0
261000040 0 0.071 0.071 0.071 0.071 0 0.071 0.071 0.071 0.071 0 0 0
261004040 0 0.071 0.071 0.071 0.071 0 0 0 0.071 0.071 0.071 0.071 0
261000010 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

Emission s Calculation

Em issions were caculated at a census tract level and summed over a county for county level

em issions. A county level sam p le em ission calcu lation will not be pres ented here, h o wever the equations for a particular census tract are presente d below. All of the census tracts in a county would then be summ ed for county level em ission estim ates.

The equation for estim ating the m a ss of waste burned is:

PUT EQUATION HE R E111 Wt MSW = Mass of waste burned per time period HH = Number of households that burn (Question 1, Part 2 of survey) Bt = Number of burns per tim e period (Question 3, Part 2) M = Mass of waste per burn (Question 5, Part 3)

Uncontrolled emissions were then calculated using the following equation:

E UNC = Wt MSW * EF

where: E UNC = Uncontrolled area source emissions Wt MSW = Mass of waste burned per time period EF = Emission factor per pollutant

Controlled emissions were then calcu lated using the following equation:

E C = E UNC * [(1-(CE)(RP)(RE)]

where: E C = Controlled area source emissions E UNC = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100112 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 cl earing debris, household waste, and agricultural crop waste. Household waste, of ten referred to as residential m unicipal solid waste (MS W ), is a term for nonha zardous refuse produced by households (e.g., paper, plastics,

m e tals, wood, glass, rubber, leathe r, textiles, and food wastes).

Open burning without a perm it is prohibited in Maryland where trash and leaf collection is available, C O MAR 26.11.07. The basic differe nce between the regula tio n as it applie s to counties in AQCRs III and IV and th e rest of th e state is the requirem e nts under which the burn takes p l ace, i.e., m i ni m u m setbacks from property lin es, etc. In the m o re rural counties, areas with no available trash collection are m o re preval ent. MDE adopted a regulation that prohibits open burning during the peak oz one period (June to August). The seasonal prohibition only affects those counties that lie within serious and severe ozone nonattain m e nt areas. Certain

exem ptions must be in p l ace however so as not to adversely affect agriculture or restrict fire
tra i ning and recr eational activ ities.

Pollutant s VOC, NOx, SOx, CO, PM 10 , PM 2. 5 , a n d T o x i c s

Method and Data Sourc es

The m e thod used to calculate em issions is pres ented in a study/survey conducted by the MidAtlantic/Nor theas t Visib i lity Union ( M ANE-VU), titled “Ope n Burning in Residential Areas Em issions Inventory Developm ent Report.” 67

Activity The purpose of the survey was to obtain data for developing activity estim a tes and control inform ation (e.g., bans on burning) that woul d form the basis of an im proved open burning

em ission inventory for Mid-Atlantic/Northeas t Visibility Union (MANE-VU) states and tribes for the year 2002.

A rule effectiveness (RE) survey was also pe rform e d to estim ate controlled em ission s for areas that prohibit open burning. Househol d waste burning surveys were com p leted for 72

67 O p en B u rni n g i n R e si de nt i a l Areas Em i ssi ons In ve nt o r y D e vel o pm ent R e prt , Pre p a r t e d by E. H. Pec h a n & Asso ciates, In c. fo r th e Mi d

- Atlan tic/No r th east Visib ility Un ion

, d a ted Janu ary 31
, 20 04

.113 respondents or jurisdictions, while yard waste surveys were conducted for 181 respondents. The respondents for this survey we re typically local fire wardens or chiefs. Rule effectiveness surveys related to residential MSW rules were conducted for 49 respondents, while RE surveys for yard wa ste burning rules we re perform e d for 51 respondents. In obtaining surv ey responses, Pechan collected activity data and control inform ation for areas classified as urban, s uburban, and rural, or a com b ination of these designations (defined using data from the 2000 U.S. Census). Pechan also developed a control database for each open burning categor y that describes the recomm ended control efficiency (CE) and rule penetration (RP) values by state and county, and by subcounty, where applicable.

Open burnin g activ ity estim a tes recorded from the survey were used directly to estim a te

em issions for the surveyed ju risdictions. For the non-surveyed areas, including tribal lands, the default activity data derive d from all survey responses w e re applied. Households are defined as detached single-fam ily unit dw ellings as provided by the 2000 U.S. Census.

Emission F a

ctors

Em ission f actors in lbs / ton tota l m a ss were taken from AP-42 Table 2.5-1, Em ission Factors for Open Burning of Municipal Re fuse and from a 1997 EPA research paper on open burning 68 a r e l i s t e d b e l o w :

Pollutan t Em ission Factor Lb/ton total m a ss burned V O C 8

. 5 5 6 N O x 6 C O 8 5 PM 10 38 PM 2. 5 3 4

. 8 SO 2 1.0

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

68 EPA

. 19 9 7

. E v al uat i o n of E m i ssi ons f r o m t h e O p e n B u r n i ng O f H o use h ol d Wast e i n B a rrel s

. EP A

- 6 00/ R

- 9 7

- 13 4a. U

. S. E n i v i r onm ent a l Pr ot ect i on A g e n c y , C o nt rol Tec h n o l o gi es C e nt er. R e searc h T r i a n g l e Par k

, N o rt h Caro lin a.114 Pennsylvania, unless a jurisdic tion 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 emission s using the following equation:

E c = E uc * [(1-(CE)(RP)(RE)]

where: E c = Controlled area source emissions E uc = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100

The following sections describe how values for CE, RP and RE were derived from the
survey.

Rule Effectiveness Pechan evaluated differences in RE between rural/suburban and urban areas, as well as differences in RE for MSW and yard waste burni ng. Although one may expect that RE would be higher for urban than for suburban or rural ar eas, ANOVA of the survey results from these geographic subdivisions, as well as for the different open burning categories, did not show that RE values were drawn from dis tinct populations. Therefore, the fi nal selection of RE reflects a value for all areas and all burning categories.

There was a total of 26 RE survey responses that included information on the number of violating households. To calculate RE, Pechan used the number of households violating the rule, and the number of households expected to perf orm open burning for areas in the region where there is no rule (i.e., # househol ds x fraction of open burning hous eholds by region from survey).

The RE values obtained from the survey responses will be used for the specific State or jurisdiction surveyed. Non-surveyed areas could not be assigned a jurisdiction-specific RE, because no survey responses were obtained for t hose areas. Pechan did not develop statespecific RE values since we had no reason to believe th at local jurisdictions in individual states implemented their rules differently than local ju risdictions in the rest of the MANE-VU region. To estimate a default RE value for the remaining areas, the survey data were statistically analyzed. After evaluating the da ta using the Census 2000 data, a mean value of 96.8 percent reflected the best estimator of central tendency. As such, Pechan applied a rule effectiveness of 96.8 percent to all areas and for both MS W and yard waste burning (Pechan, 2002b).

Control Efficiency and Rule Penetration For those areas identified to have a control, CE is assume d to be 100 percent (since the control is typically a ban on burning activity). For MSW bur ning, with the exception of Pennsylvania, Pechan assigned 100 percent CE and 100 percent RP to urban and suburban areas in the MANE-VU region (i.e., even if the stat e did not have a statew ide ban on burning). In

survey to have a ban, it will be assumed that suburban and rural areas allow open burning. For115 In determ ining annual em issions for those areas w ith a seasonal ban, Pechan adjusted the RP

during this season, we assum e th at 2 percent of the summ er se ason 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 em issions calculated for suburban and urban areas were assum e d to be uncontrolled, unless the survey data or other st a t e w ide or loc a l control inf o rm ation indicated otherwise. F o r m unicipal yard waste burning, area s were assu m e d to either perf orm this activity and have associated em issions, or did not c onduct burns and therefore were assigned zero

em issions.

by the leng th of the seas onal ban r e lative to the entire year. The RP value also depends on how the tim e period of the ban overlaps w ith the activ ity profile for the specific category of burning. For exam ple, for brush waste burn i ng , the survey data revealed an averag e activ ity p r o f ile as follows: W i nter–20%; S p ring–46%; Summ er–6%; a nd Fall–28%. So, for an area that has a brush burning ban in the summer, although som e pe rcentage of burning is likely to be prevented

delayed un til Septem ber when burnin g is perm itte d, resulting in an RP of 4 percen t to a pply to annual brush waste burning em issions. As m e ntione d in the discussion of tem poral allocation prof iles, this also has an af f ect on the m onthly activity profile. A summ er RP value of 4 percent would result in a revised tem poral allocati on profile to be: W i nt er–20%; S p ring–46%; Summ er– 4%; and Fall–30%.

Spatial and Temporal Allocatio ns Spatial Pechan colle c ted ac tiv ity data and co ntrol in formation for areas clas sified as urban, suburban, and rural, or a com b ination of thes e designations (defined using data from the 2000 U.S. Census).

Activity estim ates and associated em issions are calculated on an annual basis. Pechan proposes the following temporal allocation profile s to represent m onthly, weekly, and daily activity profiles by SCC (see Tables II-2 thr ough II-5). The m onthly activity profiles w e re developed based on data obtained from the survey. The weekly and week day/weeken d prof iles wer e developed based on en gineer ing ju dgm e nt. These prof iles w ill b e applie d to annual activity for all areas of MANE-VU (i.e., variations in regional, State, or tribal areas
are not acco unted for).

Tem poral Allocation Profile Form ats (m onthly)

Mont h

SCC Jan Feb Mar Ap r Ma y Jun Jul A ug Sep Oct No v Dec
261003000 0 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083 0.083
261000040 0 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067
261004040 0 0.067 0.067 0.153 0.153 0.153 0.020 0.020 0.020 0.093 0.093 0.093 0.067
261000010 0 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.333 0.333 0.333 0.000

Tem poral Alloca tion Pr of ile Form ats (weekly)116 Da y of We ek SCC M o n T u e W e d T h u F r i S a t S u n
261003000 0 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 2 2 2 0

. 2 2 2
261000040 0 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 2 2 2 0

. 2 2 2
261004040 0 0

. 2 0 0 0

. 2 0 0 0.200 0

. 2 0 0 0

. 2 0 0 0

. 0 0 0 0

. 0 0 0
261000010 0 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 1 1 1 0

. 2 2 2 0

. 2 2 2

Tem poral Allocation Profile Form ats (daily; weekday)

Weekda y H our SCC 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200
261003000 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071
261000040 0 0 0.071 0.071 0 0 0 0 0 0.071 0.071 0.071 0.071
261004040 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

261000010 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

Weekda y H our SCC 1300 1400 1500 1600 1700 1800 2100 1900 2000 2200 2300 0000
261003000 0 0.071 0.071 0 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0
261000040 0 0.071 0.071 0.071 0.071 0 0.071 0.071 0.071 0.071 0 0 0
261004040 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

261000010 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

Weekend Da y H our Tem poral Allocation Profile Form ats (daily; weekend day)

SCC 0100 0800 0200 0300 0400 0500 0600 0700 0900 1000 1100 1200
261003000 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071
261000040 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071
261004040 0 0 0 0.071 0.071 0 0 0 0 0.071 0.071 0.071 0.071

261000010 0 0 0 0 0 0 0 0.071 0.071 0.071 0.071 0.071 0.071

Weekend Da y H our SCC 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 0000
261003000 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0
261000040 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0
261004040 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0
261000010 0 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0 0 0 0

Emission s Calculation

Em issions were caculated at a census tract level and summed over a county for county level

em issions. A county level sam p le em ission calcu lation will not be pres ented here, h o wever the equations for a particular census tract are presente d below. All of the census tracts in a county would then be summ ed for county level em ission estim ates.

The equation for estim ating the m a ss 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 tim e period (Question 3, Part 2) M = Mass of waste per burn (Question 5, Part 3)

Uncontrolled emissions were then calculated using the following equation:

E UNC = Wt MSW * EF

where: E UNC = Uncontrolled area source emissions Wt MSW = Mass of waste burned per time period EF = Emission factor per pollutant

Controlled emissions were then calcu lated using the following equation:

E C = E UNC * [(1-(CE)(RP)(RE)]

where: E C = Controlled area source emissions E UNC = Uncontrolled area source emissions CE = % Control efficiency/100 RP = % Rule penetration/100 RE = % Rule effectiveness/100118 3.1.5.6 Cremation – Animal and Human SCC: 31 502 102

Description

Propane-fired burners (afterburne r and ignition) are typically us ed at cemeteries for hum a n body and anim al crem ation. Burners are usually ra ted at 2,115,000 Btu per hour capacity. Newer units installed in thelate 1980' s are equ i pp ed with a modulating ig nition bu rner. W h en afte rburner
tem p eratures reach abou t 1800 F (98 0 C), the ign iti on bu rner modulates to a low-fire mode that will r e duce the Btu per h our usage.

When the crem atory reaches an operating tem p er ature of 1,250 F (680 C) the body container is placed on th e com bustion cham ber grate and the i gnition burner is fired to attain a target

com bustion tem p erature sufficient for the prop er reduction of hum a n rem a ins. The chamber preheat by the afterburner reaches 1,250 F (680 C) in about 30 to 45 m i nutes prior to ash

rem oval. When the body containe r is introdu ced into th e co m bus tion cham ber, and the burner is ignited, crem ation begins at about 1600 to 1800 F (870 to 980 C). Flam e im pinge m e nt on the body takes two to three m i nutes; crem ation occurs for about two hours. The rem a ins are then raked towards the ignition burner for about two m i nutes. Cooldown follows for 45 m i nutes to 1.5 hours.

Pollutant s Air Toxics (Crite ria Polluta nts were not calculated)

Method and Data Sourc es

The m e thod used to calculate em issions, is pres ented in “Docum entation f o r the 1996 Base Year National Toxics Inventory for Area Sources” prepar ed by E a stern Research Group, Inc. (May 31, 2001) and distributed by U.S. EPA Em issions, Monitoring and Analysis Division, E m ission Factor and Inventory Group.

Activity In Maryland crem atories are regulated under COMAR. COMAR now r e quires all

crem atories to obta i n a p e rm it to ope rate and any person who owns or operates an

crem atory must obtain certification from MDE and renew the cer tification annually.

MDE/ARMA m a intains a regis t ry of all c r em atories within the State. Because of the requirem e nt for a perm it to operate, and the ope r a tor ce rtif ication requ ire m ents, staf f used the sum of t h e crem atories in th e reg i stry as rep r esenting the total area so urce em issio n s from crem at ories of all types em ittin g less th an 1 0 tons/VOC, 100 tons/yr CO and 50 tons per year NO x .119 Emission F a

ctors

Em ission factors these h azardous air pollutants, except form aldehyde, were taken from the State of California Air Resources Board Test Report No. C-90-004 69 . The em ission factor used for form aldehyde was reported in the USEPA FIRE 70 system d a t a b a s e

.

Em ission factors were converted to a pound pe r ton basis using the procedure provided by the Em ission Standards Division 71 . Nationa l ac tiv ity was prov ided by the Em issions Standards D i vision based on an assum e d body weight of 150 pounds and infor m ation reported by the Crem ation Association of North Am erica 72 that 21.13 percent of bodies

were crem ated and that there were 2, 322,265 deaths in the United States in 1996 73

.

Ani m al and Hum a n Cre m ation Em ission Factor Pollutan t Lbs. pollutant / ton crem a t e d

a r s e n i c 4

. 0 0 E

- 0 4 beryllium 1

. 8 4 E

- 0 5 cadm i um 1

. 4 8 E

- 0 4 chrom i um 3

. 9 9 E

- 0 4 for m a l d e h y d e 2

. 8 9 E

- 0 9

n i c k e l 5

. 0 9 E

- 0 4 POM as 16-PAH 9.63E-04 POM as 7-PAH 1.03E-09 M e r c u r y 4

. 3 9 E

- 0 2

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

69 St at e o f C a l i f o r ni a Ai r R e s o u r ces B o ar d, En gi nee r i n g E v al uat i o n B r a n c h

, M oni t o ri n g a n d La b o rat o ry Di vi si o n

. “Ev a lu ation Test on Tw o Pr opan e Fi r e d Cr emato r ies at Ca m e llia Lawn C e m e tary.” Test Report No. C- 90- 0 04. Oct o ber 2 9
, 1 9 92
70 U.S. EPA. Facto r Info rm atio n Retriev a l (FIR E) System Dat a base, Ve rsi o n 5. 1a. R e sea r c h Tri a n g l e Pa rk

, NC

. Sep t em b e r 1995

. 71 C r um e, R i char d, U. S. E P A
, E m i ssi on St an da rds Di vi si o n

. Not e t o An ne Po pe, U. S. EP A/ Em i ssi ons M oni t o ri n g

an d An alysis D i v i sion . Co m m en ts on H u m a n an d An im al Crem a tio n inform at io n in the “Baseline Em ission In ve nt ory o f H A P Em i ssi ons fr om M A C T S o u r ces – I n t e ri m Fi nal R e port , ” Se pt em ber 1 8
, 1 9 9 8

. Oct o ber 3 0
, 1 9 9 8

. 72 Crem ation As sociation of Nort h Am eri ca. 1 996 Statistics as fo und o n th e Internet C r emation Society, Crem a tion Stats Nationwi d e webpa g e: ww w

. crem at i on. or g/ st at s.ht m 73 Ve ntura, S. et al. “Births a n d Deaths: United States, 1 996 .” Mo n t h l y Vital Statistics Rep o r t, Vo l. 64
, No

. 1
, Su

ppl em ent 2. Set p em ber 1 1
, 19 9 7

. U

. S. De part m e nt of He al t h an d Hum a n Se r v i ces, C e nt ers f o r Di ese a s C o nt r o l

an d Prev en tion, Nation a l Cen t er for Health an d Statistics.120 E CREM = Annual em issions from c r em atories No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s Calculation The equatio n for estim ating em issions from crematories is:

w h e r e :

TON ct y = Tons crem a t e d p e r y e a r i n c o u n t y EF = Em ission Factor per pollutant (lbs/ton)

2002 Sa m p le Calculation (Harford County)

Arsenic Ann u al Em issions:

EF = 0.0004 lbs Arsenic/Ton Crem ated TON ct y = 2 6

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

E CREM = 5.20E-06 tons Arsenic per Year121 3.1.5.7 Municipal Solid Waste Landfills SCC: 26 20 030 000

Description

Municip a l s o lid waste landfills receive household and commercial trash. VOC e m issions are produced from volatiliz ation, ch em i cal reaction a nd biolog ic al decom position of waste. Methan e and Carbon dioxide are the prim ary constitu ents o f landfill gas

, and are p r o duced durin g anaerob ic de com position of cellulos e and prote i n s in the land f illed waste. 98.7 perce n t of landfill em issions are m e thane and carbon dioxid e accord ing to the Volatile Organic C o m pounds Species Data Manual , an EPA publication. In addition to m e thane and carbon dioxide, nonm e thane organic carbons (NMOCs) are produced as a sm all fraction of the landfill g a s em issions (less than 1%). NMOCs include hazar dous air pollutants and reactive V O C s

.

Pollutant s
VOC

The m e thod used to calculate em issions, is presented in AP-42 , Chapter 2

. 4, Municip a l Solid W a ste Landf ills and EI I P 74 , Volum e III, Chapter 1 5 , La n d f i l l s , d a t e d S e p t e m b e r 1 9 9 7

.

Em ission estim a tion assumptions were also m a de using supporting documents Standards of Perform a nce for New Stationary Sources (NAR A, 1991a) and Em ission Guidelines for Control of Existing Sources (N ARA, 1997b).

To estim a te uncontrolled em issions of the va rious com pounds present in landfill gas, total landf ill g a s em issions m u st f i rst b e estim a ted. Em issions of landf ill gas depend on severa l factors inclu d ing: (1) the size, configuration, and operating conditi ons of the landfill; and (2) th e characteristics of the refuse such as moisture content, age, and com position. Uncontrolled CH 4
em issions m a y be estim ated f o r individua l la ndf ills by u s ing a theor e tic al f i r s t-o r der k i netic model of methane production developed by the EPA. A computer program that uses this m odel is known as the Landfill Gas Em issions Model (L a ndGEM). The m odel e quation is as follows:

Q CH4 = L O R (e -kc - e -kt ) ( 1 )

W h e r e : Q CH4 = Methane g e neration rate at tim e t, m 3 / y r ;

74 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram Method and Data Sourc es122  The design capacity of the landfill, L o = Methane generation potential, m 3 CH 4 / Mg (megagrams) refuse;
R = Average annual refuse acceptance rate during active life, Mg/yr; e = Base log, unitless;
k = Methane generation rate constant, yr -1;
c = Time since landfill closure, years (c = 0 for active landfills); and t = Time since the initial refuse placement, yrs. Site-specific landfill information is generally available for variables R, c, and t. When refuse acceptance rate information is scant or unknown, R can be estimated by dividing the refuse in place by the age of the landf ill. Also, nondegradable refuse should be subtracted from the refuse in place to prevent over estimation of CH 4 generation. The average annual acceptance rate should only be estimated by this method when ther e is inadequate information available on the actual annual acceptance rate.

The following LandGEM parameters are needed to estimate emissions from a landfill:

 The methane generation rate (k),

 The potential methane generation capacity (Lo),

 The number of years past closure that the model will estimate emissions,

 The estimated percentage composition of methan e and carbon dioxide in the gas (the default value is a 50/50 split),

 The concentration of nonmethane organic co mpounds (NMOC) found in the landfill gas,

 The concentrations of toxic air pollutants found in the landfill gas, and whether the landfill has been used for disposal of hazardous waste (co-disposal).

 The years the landfill has been in op eration (including the closure year),

The Landfill Gas Emissions Model has several different default values for k, Lo and NMOC concentration. The EIIP document recommends using AP-42 default values for k, Lo and NMOC concentration when site-specific informa tion is not known. The AP-42 default value for k (0.04/yr) was used for Maryland since it has normal or above nor mal precipitation, rather than the default value. This recommendation is ba sed on a comparison of gas-yield forecasts with landfill gas recovery data. The LandGEM contains a proposed regulatory default value for total VOCs of 595 ppmv expressed as hexane for non-codisposal and 2,420 ppmv for codisposal. However, there is a wide range for total VOC va lues from landfills. The proposed regulatory default value for VOC concentration was develope d for regulatory complia nce purposes and to provide the most cost-effective defa ult values on a national basis fo r the regulation. Therefore, if the landfill is known to contain only municipal solid waste or have very little organic commercial/industrial wastes, then the mean va lue of all VOC concentrations, 595 ppmv as hexane should be used. This was done for Mary land. The AP-42 default values used in the LandGEM to develop Maryland’s landfill inventory are shown in the table below:123 Lo : 100.00 m 3 / Mg Landgem Model Para meters AP-42 Default Values

Methane Ge neration Potentia l k : 0.0400 1/yr Decay Rate/Rate of Decom position NMOC : 595.00 ppm v Non- m e thane Concentration Methane : 50.00 % volum e Carbon Dioxide : 50..00 % volum e

Activity Data was obtained f r om MDE’s Solid W a ste Program and f r om the landf ill f a c ilites direc tly.

Emission F a

ctors All factors are incorparted in to the LandGEM itself.

Point Source Adjustment s

The Brown Station S ites A & B, Sandy Hill La nd fill, Montgo m e ry Count y RRF, and Newland Park Landf ill are conside r ed Point So urces. La ndGEM m odel runs for these landfills are not included in the area source em i ssion estim ates f o r landf ills.

Em ission reductions were calculated for landf ills that us ed co ntrol techno logy to reduce

em issions. Controlled e m issions f r om landf ills were calcula ted in the f o llowing m a nner: Adjustment s for Controls

Equation:

E CON- LF = {E UNC-L F x (1 – C EFF ) } + { E UNC-L F x C EFF x [1 – (D EFF x R E ) ] }

W h e r e : E CON- LF = Controlled e m issions f r om landf i l l s

E UNC- L F = Uncontrolled em issions from landfill s (generated from the LandGEM m o d e l )

C EFF = Landf ill collection ef f i ciency (EPA def a ult = 75 % )

D EFF = Control dev i ce destructio n e f f i c i e n c y ( 9 8 % )

RE = Rule effectiveness (EP A default 80%)124 Spatial and Temporal Allocatio ns
Data f o r spa tia l and tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.125 3.1.6 SMALL STATIONARY SO URCE FOSSIL FUEL USE

3.1.6.1 Small Electric Utility Boilers

All small electric utility boilers are inventoried in the point sour ce category. The list of small boilers from Inventory of Power Plants in the United States , DOE/EIA-0095(88) was obtained and indicated that all small electric boilers were included in the poi nt source inventory.

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 (co mmercial/in stitu tion a l k e rosene) SCC: 21 04 004 000 (reside ntial distillate oil) SCC: 21 03 004 000 (co mmercial/in stitu tion a l distillate oil) SCC: 21 02 004 000 (industrial distillate oil) SCC: 21 03 005 000 (co mmercial/in stitu tion a l residual o i l) SCC: 21 02 005 000 (industrial residual oil)

Description

Data collection for fuel oil consum ption covers the use of both distil late and residual oil. Distillate oil includes fuel oil grades 1,2 and 4. Diesel fuel an d kerosene also can be considered as distillate oils. Reside ntia l and co m m e rcial/in stitu tion a l s ources a r e th e larg est con s um ers of distillate o il, nationwide. Residual o i l include s f u el oil grades 5 and 6. In most areas residual oil is not used b y residen t ial sources, bu t industr ial and commercial/ins titu tio nal users m a y consum e significant amounts.

Pollutant s
PM 10 , PM 2. 5 , S O x , N O x , C O
, V O C

Method and Data Sourc es
A

c

t i v

i t y Total sa les s t atistics of kerosene, d i stillate o il, an d residua l oil in th e State of Marylan d were obtained from the Annual Report on Sale s of Fuel Oil and Kerosene, 2002, published by Energy Infor m ation Adm i nistrati on, U.S. De partm e nt of Energy 75

.

Emission F a

c

t o

r

s Em ission factors were obtained from AP-42 76

, T a b l e s 1

. 3

- 1 a n d 1

. 3

- 3 ( h a n d

- f e d u n i t s )

.

Uncontrollled Emission Factors – AP-42 T a ble s 1.3-1 an d 1

. 3-3 R e side n t i a l Comm e r c i a l Comm e r c i a l I ndustri a l I n d u s t r i a l Comm e r c i a l Industri a l

D i s t i l l a t e D i s t i l l a t e R e s i d u a l D i s t i l l a t e R e s i d u a l R e s i d u a l 1% S R esidual 1% S

75 To tal resid e n tial d i stillate o il u s e i n th e State of Maryland i n 2 002 fro m U.S Dep a rtm e n t o f En erg y , En erg y In fo rm at i on A d m i ni st rat i on, Of fi ce o f Oi l a n d Gas
, Pet r ol e u m M a rket i ng M ont hl y , "A n n u al R e p o rt o n Sal e s o f F u el Oi l an d Ker o se ne, 2 0 0 2 ".
76 Em i ssi on Fact ors f r om AP- 4 2 Ta bl es 1. 3- 1 and 1

. 3

- 3127 l b s / K g a l l b s / K g a l l b s / K g a l l b s / K g a l l b s / K g a l l b s / K g a l l b s / K g a l P M 1 0 1

. 0 8 0 1

. 0 8 0 1 3

. 4 9 4 1

. 0 0 0 1 8

. 7 1 4 7

. 7 0 3 1 0

. 6 8 3 P M 2

. 5 0

. 8 3 0 0

. 8 3 0 5

. 0 1 1 0

. 2 5 0 1 2

. 1 8 9 2

. 8 6 1 6

. 9 5 8

S O x 4 3

. 2 0 0 4 3

. 2 0 0 318.00 0 4 3

. 2 0 0 318.00 0 159.00 0 159.00 0 N O x 1 8

. 0 0 0 2 0

. 0 0 0 5 5

. 0 0 0 2 0

. 0 0 0 5 5

. 0 0 0 5 5

. 0 0 0 5 5

. 0 0 0 C O 5.000 5.000 5

. 0 0 0 5

. 0 0 0 5

. 0 0 0 5

. 0 0 0 5

. 0 0 0 V O C 0

. 7 1 3 0

. 3 4 0 1

. 1 3 0 0

. 2 0 0 0

. 2 8 0 1

. 1 3 0 0

. 2 8 0

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns
S

p

a

t i a

l

A “heating-degree day” is a unit of m easure us ed to indicate how cold it has been ov er a 24-hour period. Daily heating-degree days ar e calculated as the di fference between the base valu e o f 65°F and the m ean temperatu r e for the day (m ean of the hig h and low
tem p eratures for the day )

. This information on total sales of kerosene, di stillate oil and residual oil w a s broken down to the county level using a spatial allocation factor docum ented and recommended by EIIP 77 in an A r ea Source Method Abstract for Residential and Comm ercial/Institutional Fuel Oil and Kerosene com b u s t i o n

. 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 consum ption. The m e t hod is

Annual heating degree days are the sum of the daily heating degree days. Heating degree data is available from the National O ceanographic and Atm o s pheric Adm i nistration (NOAA). 78

77 Em issio n s In ven t or y I m p r ove m e n t Pro g r a m ( E I I P ) A r ea So ur ce Method A b st r act – Resid e n tial and Co mmercial/In s titu tio n a l Fu el Oil and Kero sen e C o m b u s tio n , d a ted April 2 002
78 h ttp ://www.noaa.go v (ho m e p a g e ) o r h ttp :// www.n c d c .n o a a. go v / o l/cli m a t e /cli m a tep r od uc ts.h tm l# PUBS (for a list of

avai l a bl e da t a )128 3.1.6.4 Coal Combustion SCC: 21 04 002 000 (Residential Coal) SCC: 21 03 002 000 (Comm e rcial/Institutional Coal)

Description Residenti a l Coal This source catego r y co vers air em issions from c o al com bustion in the residential sector. Bitum i nous coal, m i ned here in Maryland, represen ts the bulk of the coal used residentially for space heatin g in the State. Although m i ned n earby in Pennsylvania, readily availab l e, and cleaner burn i ng, anth racite coal is no t used m u ch in Maryland because of its expense.

Pollutant s
PM 10 , PM 2. 5 , S O x , N O x , C O
, V O C

Method and Data Sourc es

Activity The f o llowing assum p tions were m a de in th e computation of e m issions from coal

com bustion from the residential sources.

(i) Nu m b er of Dwelli ng Units using Coal

The num ber of dwelling units using coal fo r space heating for 2002 was obtained from 1990 Census Profile Series, S o cial and Econom i c Characteristics of Population and Housing. The

num b er of new housing units authorized for construction between 1990 and 2002 was obtained from the Maryland Office of Planni ng – New Residential Units Authorized f o r Construction by Building Perm its ( http://www.op.state.m d .u s) . MDE estim ated that no new housing units would be equipped to burn coal as a hom e h e a t i n g f u e l

. COMAR 26.11.09.04 prohibits the use of solid fu el-burning equipm ent that has a rated heat input of less than 35 m illion BTU per hour.

(ii) Residential Coal Activity Consum ption Data

The State E n ergy Data Report, Consum p tion Estim ates, by the Energy Infor m ation Adm i nistration, provided inform ation on estim ated coal consu m ption. The report ind i cates that in Maryland m o stly bitum i nous coal was used in 2002. It was assumed, therefore, that bitum i nous coal was consum ed by most of the ha nd-fired residential coal sources in the State of Maryland.129 Emission F a

ctors

Em ission factors were obtained from AP-42
, T a b l e s 1

. 1

- 3 a n d 1

. 1

- 1 9 ( h a n d

- f e d u n i t s )

.

Coal Emission Factors NOx (lbs./kgal) CO (lbs./kgal) VOC (lbs./kgal) PM 10 ( l b s . / k g a l ) SOx 79 (lbs./kgal) R e s i d e n t i a l 9

. 1 0 2 7 5

. 0 0 1 0

. 0 0 6

. 2 0 6 2

. 0 0

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns
S

p

a

t i a

l MDE developed an allocation factor from local and state totals of annual heating-degree days and housing units heating with coal to spatially a lloc a te d coal consu m ption. The

m e thod is docum ented and recomm e nded by EIIP 80 in an Area Source Method Abstract for natural gas and LPG combustion. Because the em i ssion factor was specifically ad justed to reflect seasonal em issions through heating de gree days, no further seasonal adjustm e nt factor is n e c e s s a r y

. A “heating-degree day” is a unit of m easure us ed to indicate how cold it has been ov er a 24-hour period. Daily heating-degree days ar e calculated as the di fference between the base valu e o f 65°F and the m ean temperatu r e for the day (m ean of the hig h and low
tem p eratures for the day )

. Annual heating-degree days are the sum of th e daily heating-degree days. Heating degree data is available from the National O ceanographic and Atm o s pheric Adm i nistration (NOAA). 81

79 MD E a s s u me d an av e r ag e su lfu r con t e n t in co a l of 2 %
80 Em issio n s In ven t or y I m p r ove m e n t Pro g r a m ( E I I P ) A r ea So ur ce Method A b st r act – N a t u r a l G a s and LPG C o m bust i on, d a t e d A p ri l 2 0 0 2
81 h ttp ://www.noaa.go v (ho m e p a g e ) o r h ttp :// www.n c d c .n o a a. go v / o l/cli m a t e /cli m a tep r od uc ts.h tm l# PUBS (for a list of

avai l a bl e da t a )130 

## ∑ =

sInState AllCountie County County ounty InventoryC ounty InventoryC ounty InventoryC CHU HDD CHU HDD SAF ) * ( *

W h e r e : SAF I NVE NTO R Y COUN TY = S p a t i a l a p p o r t i o n i n g f a c t o r f o r i n v e n t o r y c o u n t y HDD INV E NT ORY COU N TY = A n n u a l h e a t i n g d e g r e e d a y s f o r i n v e n t o r y c o u n t y CHU INV E NT ORY COU N TY = H o u s i n g u n i t s u s i n g c o a l i n i n v e n t o r y c o u n t y HDD COUNTY = Annual heating degree d a ys for each county in th e s t a t e CHU CO UNT Y = Housing units using co al for each co unty in th e s t a t e

The spatial apportioning factor is used to allocate the state fuel total to the county level using the f o llowin g equation :

Coal INVEN T O R Y COUN TY = SAF I NVE NTO R Y COUN TY x Coal TOTA L STAT E

W h e r e : Coal INVEN T O R Y COUN TY = Total Coal f u el consum e d i n t h e i n v e n t o r y c o u n t y Coal TOTA L S T AT E = Total Coal f u el consum e d i n t h e i n v e n t o r y c o u n t y
Temporal MDE assumed that all residential coal com bus tion is used for space heating purposes. The total coal consum ed in the county can be a llocated by m onth or peri od using proportions of annual and monthly (or period) heating-degree days.

HDD MON T H Residential Fuel MONTH = Residential Fuel ANNUAL x HDD ANNU A L

w h e r e : Residential Fuel MONTH = Space heatin g fuel use for inven t o r y m o n t h Residential Fuel ANNUAL = Space heatin g fuel use for inven t o r y y e a r HDD MON T H = Heating degree da y s f o r i n v e n t o r y m o n t h HDD ANNU A L = H e a t i n g d e g r e e d a y s f o r i n v e n t o r y y e a r

Emission s Calculation

O z o n e S e a s o n D a i l y E m i s s i o n s Equation:

(EF COAL i x Coal Space He at - J ) HDD Co Oz Se ason 2000 x HDD Co Annual E COAL = Ozone DAYS131 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 da ys in county for ozone season HDD Co Annual = Number of heating degree da ys in county in the calendar year 2002

Residential Coal Combustion Sample Calcula tion (Allegany County) (tons / ozone season day)

Total Residential Coal Consumpti on – State of Maryland 8,360 tons

To calculate spatial apportioni ng factor for Allegany County:

HDD INVENTORY COUNTY x CHU INVENTORY COUNTY SAF ALLEGANY COUNTY = ∑ ALL COUNTIES IN STATE (HDD COUNTY x CHU COUNTY )

SAF ALLEGANY COUNTY = 0.045531132 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 ) (2000 x 214) E COAL =

(10.0 x 79.48804 ) E COAL = (2000 x 214)

E COAL = 0.0019 tons VOC / Ozone season day133 Activity Description – Commerci a l and Insti t utional Coal

Comm ercial and Institutional sources of coal combustion above the point source threshold are included in the point source portion of the i nventory. The following table lists area source

em issions from comm er cial and ins t itution a l sou r ces sm aller than the th res hold values.

Methods an d Data Sourc es

The f o llowing assum p tions were m a de in the co mputation of e m issions from coal combustion f r om the com m e rcial an d institution a l sourc e s not included in the point source inventory.

(i) Coal Consumption Data

The State E n ergy Data Report (SE D R) estim ated that approxim a tely 68, 000 tons/year of total coal was used commerically by Maryland in 2002.

(ii) Nu m b er of Dwelli ng Units using Coal

The num ber of dwelling units using coal fo r space heating for 2002 was obtained from 1990 Census Profile Series, S o cial and Econom i c Characteristics of Population and Housing. The

num b er of new housing units authorized for construction between 1990 and 2002 was obtained from the Maryland Office of Planni ng – New Residential Units Authorized f o r Construction by Building Perm its ( http://www.op.state.m d .u s) . MDE estim ated that no new housing units would be equipped to burn coal as a hom e h e a t i n g f u e l

. COMAR 26.11.09.04 prohibits the use of solid fu el-burning equipm ent that has a rated heat input of less than 35 m illion BTU per hour. Emission F a

ctors

Em ission factors were obtained from AP-42 , Tables 1.1-3 and 1.1-19 (average of overfeed

a n d u n d e r f e e d s t o k e r )

.

Coal Emission Factors NOx (lbs./kgal) CO (lbs./kgal) VOC (lbs./kgal) PM 10 ( l b s . / k g a l ) SOx 82 (lbs./kgal) Comm ercial / Institutional 8

. 5 0 8

. 5 0 0

. 6 7 5 6

. 1 0 6 9

82 MD E a s s u me d an av e r ag e su lfu r con t e n t in co a l of 2 %134 Adjustment s for Controls Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial Spatia l and tem poral allo cation to th is source category were calculated in the sam e m a nner as the resid e ntial coal co mbustion category.

Temporal Spatia l and tem poral allo cation to th is source category were calculated in the sam e m a nner as the resid e ntial coal co mbustion category.

Emission s Calculation135 (i) Num b er of Dwelling Units us ing Natura l Gas 3.1.6.5 Natural Gas Combustion SCC: 21 04 060 000 (Residential Natural Gas) SCC: 21 03 060 000 (Comm e rcial/Institutional Natural Gas)

Description

This source catego r y co vers air em issions from natural gas combustion in the residential and commercial/institutional sectors for space heating

, water heating, and cooking. This category includes small bo ilers, furnaces, h e aters and o t her h eating units that are n o t inven t oried as point sources. Residential and commercial sectors co mprise housing units; wholesale and retail businesses; health institutions; social and educat ional institutions; and Federal, state and local
governm e nt institutions (e.g., m ilitary installations , prisons, office building s ). Natural gas is one of the m a jor fuels used throughout the country. It is used m a inly for power generation, for industrial process steam and heat production, and for dom e stic and commercial space heating. It is also used for dom e stic c ooking and hot water heating.

Pollutant s
PM 10 , PM 2. 5 , S O x , N O x , C O
, V O C

Method and Data Sourc es

The f o llowing assum p tions were m a de in the co m putation of the em issions from natural gas

com bustion.

Activity

The num ber of dwelling units using n a tura l gas fo r space h eating for 2002 was obtained from 1990 Census Profile Series, Social and Econom ic Characteristics of Population and Housing. The num ber of new housing units au thorized for construction between 1990 and 2002 was obtained from the Maryland Offi ce of Planning – New Residential Units Authorized f o r Construction by Building Perm its ( http ://www.op.state.m d .us) . The tota l

num b er of addition a l ho using units constructe d in the county was apportioned to type of hom e heating fuel by the sam e r a t i o a s t h e 1 9 9 0 C e n s u s f i g u r e s

. ( i i ) R e s i d e n t i a l and Comm e r cial/Inst itutional Natu ra l Gas Consum ption Data

Total r e side ntia l and co m m e rcial/in stitu tion a l n a tura l gas co nsum ption data in the State of Maryland for 2002 was obtained from surveying the following com p anies: Baltim ore Gas and Electric ( Constellation Energy Group ), W a shington Gas Ener gy Services (Maryland136 Division), C h esapeake U tilities Corp oration, Colum b ia Gas of Maryland, Easton Utility Comm ission, and Elkton Gas Co m p any. The com p anies pro v ided natu ra l gas sa les statistics for the year 2002 in therm s or cubi c f e e t f

o r all coun ties in the i r servic e ar ea f o r the res i den t ial, comm ercial, and indu strial cate go ries. Thes e statistics were then conv erted into m illion cubic feet us ing a conversion factor o f 1 therm equals 100 cub i c feet.

Emission F a

ctors (iii) Em ission Factors – Natural Gas

Em ission factors for combustion of natural gas in commercia l boilers are presen ted in Table 1.4-1 and 1.4-2 of Section 1.4 of AP-42 . The em ission factors for PM are as sumed to be less th an 1.0 m i crom eters in diam eter. Therefore the P M em isson facotrs p r es eneted

m a y be used to estim a te PM10, PM2.5 or PM1. Total PM is the sum of f

ilte rable and condensable PM. AP-42 Tables 1.4-1 - 1.4-2.

Natural Ga s Emission Factors N o x (lbs./10 6 s c f ) C O (lbs./10 6 s c f ) VOC (lbs./10 6 s c f ) P M 1 0 (lbs./10 6 s c f ) P M 2

. 5 (lbs./10 6 s c f ) S O x (lbs./10 6 s c f ) R e s i d e n t i a l 9 4 4 0 5

. 5 0 1

. 9 0 1

. 9 0 0

. 6 0 Comm e r c i a l 9 4 8 4 5

. 5 0 1

. 9 0 1

. 9 0 0

. 6 0

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial The natural gas survey of suppliers provide d MD E with county totals for natural gas

consum ption. Therefore MDE did not have to use an allocation facto r derived fro m local and state totals of annual heating degree days and housing units heating with natural gas to spatially allocated natural gas c onsumption to the county level.

1 The V O C em issi on fact or i s 11 .0 wi t h 3 4 % m e t h ane. The num ber l i s t e d i s t h e n onm et hane em i ssi on fa ct o r

. 2 The V O C em i ssi on fact o r i s 5. 80 wi t h 5 2 % m e t h ane. The num ber l i s t e d i s t h e n onm et hane em i ssi on fa ct o r

.137 = Temporal In addition to space heating, natural gas is of ten used for cooking and water heating. For ozone and other seasonal inventories, cons umption for cooking and water heating may be assumed to be constant through the year, but fuel used for space heating must be apportioned according to heating needs.

To separate residential space heating natura l gas usage from cooking and water heating, MDE used data from the State Energy Da ta Report, Consumption Estimates, Energy Information Administration, Office of Energy Markets and End Use, U.S. Department of Energy. Specifically data was collected fr om Table 15 – Natural Gas Deliveries to Residential Customers, by State, 1998-2002. Th e residential deliveries for the month with the lowest deliveries can be assumed to be only for cooking and water heating. The percentage of residential na tural gas consumption for cooking and water heating may then be calculated:

12 * Lowest Monthly Fuel Use Annual Non-Space Heating Percent Annual Fuel Use * 100

12 * 1635 Annual Non-Space Heating Percent 80,447 = * 100 Annual Non-Space Heating Percent = 24.389 %

The annual non-space heating percent can be calculated in a similar manner for commercial/institutional natural gas usage. The percentage of commercial/institutional natural gas consumption for non-space heating may then be calculated:

12 * Lowest Monthly Fuel Use Annual Non-Space Heating Percent = Annual Fuel Use * 100

12 * 2440 Annual Non-Space Heating Percent = 65323 * 100 Annual Non-Space Heating Percent = 44.823 %

This percentage may be applied to the i nventory area’s total residential and/or commercial/institutional natural gas consumpti on to calculate the non-space heating portion of usage. This portion can be subtracted from the annual total, and the remaining consumption, which is being used for space h eating, can be allocated by month or period using proportions of annual and mont hly or period heating degree days.

HDD MONTH Space Heat Fuel MONTH = Space Heat Fuel ANNUAL x HDD ANNUAL

Where:138 Space Heat Fuel MONTH = Space heatin g fuel use for inven t o r y m o n t h Space Heat Fuel ANNUAL = Space heatin g fuel use for inven t o r y y e a r HDD MON T H = Heating degree days f o r i n v e n t o r y m o n t h HDD ANNU A L = H e a t i n g d e g r e e d a y s f o r i n v e n t o r y y e a r

Em ission Calculation – Resident ial Ozone Season Daily Emissions

Equation:

Days J p HotWaterAp i NatGas

CoAnnual CoOzSeason J SpaceHeat i NatGas

NatGas Ozone NG EF
HDD HDD NG EF

E ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ + ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

= − − − − 2000 * * 2000 ) * (

HDD Co Annual = Num b er of heating degree da ys in county in the calendar year 2002

Ozone DAYS = Num b er of days in the ozone season: 214 Residential; 168 C o mm ercial E NatGas = Ozone Season Daily emissions from natural gas com b u s t i o n EF NatGas -i = Em ission factor for natu ral gas com b u s t i o n f o r p o l l u t a n t i NG Spac e He at - J = Natural g a s consum ed for space h e a t i n g i n c o u n t y j HDD Co Oz Se ason = Num b er of heating degree d a y s i n c o u n t y f o r o z o n e s e a s o n

NG Hot wate r/A pp - J = Natural gas consum ed for dur ing ozone season by hot water and

a p p l i a n c e s i n c o u n t y j

Total Resid e ntia l Natura l Gas Consum ption – Baltim ore City 83 14,483 M ft 3

Percent natural gas used for cooking & appliances in the State of Maryland 84

Total Natural Gas Delivered Low e st Monthly Deliv ery of Natural Gas Percent of Natural Ga s used for Cooking & Water Heating R e s C o m m R e s C o m m R e s C o m m State of Maryland 80,447 65323 1635 2440 24.389 % 44.823 %

Percent natural gas used for cooking & appliances in Baltim ore City

Residential NG Hot wate r/A pp - J = 24.389 % x NG BA LTI O M ORE COUN TY Residential NG Hot wate r/A pp - J = 2 4

. 3 8 9 % x 1 4
, 4 8 3

3 Nat u ral ga s c ons um pt i on da t a gat h e r ed f

r o m M D E sur v e y – B a l t i m o re C o u n t y dat a fr om B G E
4 Lowest su mmer m o n t h l y to tal is assu m e d to b e for co ok i n g and app liances. Emission s Calculation139 Residential NG Hot water/App - J = 3,532.130 M ft 3

Natural gas used for space heating in Baltimore County

Residential NG Space Heat - J = 14,483 – 3,532.130 M ft 3 Residential NG Space Heat - J = 10,951 M ft 3

Natural gas used for space heating in ozone season in Baltimore City

HDD PERIOD Residential Space Heating Fuel PERIOD = Space Heating Fuel ANNUAL x HDD ANNUAL 605

Residential 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 ft 3

Natural gas used for hot water and applia nces 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 ft 3

Equation:

VOC Ozone Season Day Emission Calculation

(EF NG i x NG Space Heat - J ) + (EF NG i x N Hot water/App - J ) (2000 x 214) E NatGas =

(5.5 x 1,705.807) + (5.5 x 2,060.409) E NatGas = (2000 x 214)

E NatGas = 0.0484 tons VOC / Ozone season day

The same equation and methodology can be used to estimate emission of various pollutants.140 SCC: 21 04 007 000 (Residential LPG)

The f o llowing assum p tions were m a de in the co mputation of the em issions from liquified petroleum gas (LPG) combustion.

1. Num b er of Dwelling Units using L P G 3.1.6.6 Liquified P e troleum Gas Combustion

SCC: 21 03 007 000 (Comm e rcial/Institutional LPG)

Description

This source catego r y co vers air em issions from liquefied petroleum gas (LPG) com b ustion in the residen t ial and commercial s ecto r s for space h eating, water heating, o r coo k ing. LPG includes propane, propylene, butane, and butylenes. The product used for dom e stic heating is com posed prim arily of propane. This catego r y in cludes sm all boilers, furnaces, heaters and other heating units that are not inventoried as point sources. Residential a nd comm er cial secto r s com p rise housing units; wholesale and retail businesses; health institutions; so cial and educational institutions; and Federal, state and local government institutions (e.g., m ilitary installations, prisons, office buildings).

Pollutant s
PM 10 , PM 2. 5 , S O x , N O x , C O
, V O C

Method and Data Sourc es

Activity

The num ber of dwelling units using LPG fo r spa ce heating for 2002 was obtained from 1990 Census Profile Series, Social and Ec onom i c Characteristics of Population and Housing. The num ber of new housing units au thorized for construc tion between 1990 and 2002 was obtained from the Maryland Offi ce of Planning – New Residential Units Authorized f o r Construction by Building Perm its ( http ://www.op.state.m d .us) . The tota l

num b er of addition a l ho using units constructe d in the county was apportioned to type of hom e heating fuel by the sam e r a t i o a s t h e 1 9 9 0 C e n s u s f i g u r e s

.

2

.

Total residential and co mmercial L P G consump tion data for space h eating in the State of Maryland (L PG ST ) for 2002 were obtained from State Energy Data Report, Consum ption Estim ates, Energy Inform ation Administration, Office of Energy Markets and End Use, U.S.Departm e nt of Energy. R e s i d e n t i a l and Comm e r cial LPG Activ ity Cons um p t i o n D a t a141 Em ission factors for combustion of LPG in comm ercial boilers are pres ented in Tab l e 1.5- 1 of Section 1.5 of AP-4 2 (EPA, 1998a). The LPG e m ission f actor for PM m a y be assum e d to represen t PM 10 em issions. Becaus e no em ission factors were located fo r the com bustion of

LPG f o r residen tia l consum ption, em ission factors for comm ercial boilers m a y be used for residen t ial em issions. PM 10 and SOx em ission factors listed below are averages of the commercial em ission factors for boilers that use propane and butane. The SOx e m ission f actors r e por ted below were ca lculate d usi ng the AP-42 em ission f actor a nd m u ltiplie d by the sulf ur co ntent of th e fuel (S = 0.18). Emission F a

c

t o

r

s

LPG Emission Factors NOx (lbs./kgal) CO (lbs./kgal) PM 2.5 (lbs./kgal) SOx (lbs./kgal) VOC PM 10 (lbs./kgal) (lbs./kgal) R e s i d e n t i a l 1 4 1

. 9 0

. 5 0

. 4 5 0

. 0 0.0171 Comm e r c i a l 14 1

. 9 0

. 5 0

. 4 5 0

. 0 0

. 0 1 7 1

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e 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 ga s to spatially alloca ted liquid propane gas

consum ption. The m e thod is documented and recommended by EIIP 85 in an Area Source Method Abstract for natura l gas and LPG com b ustion. Spatial and Temporal Allocatio ns
S

p

a

t i a

l

A “heating degree day” is a unit of measure us ed to indicate h o w cold it h a s been over a 24- hour period. Daily heating degree days are calc ulated as the difference between the base value of 65°F and the mean tem p erature for th e day (m ean of the high and low tem p e r atures for the day).

85 Em issio n s In ven t or y I m p r ove m e n t Pro g r a m ( E I I P ) A r ea So ur ce Method A b st r act – N a t u r a l G a s and LPG C o m bust i on, d a t e d A p ri l 2 0 0 2142 Annual heating degree days are the sum of the daily heating degree days. Heating degree data is available from the National Oceanographi c and Atmospheric Ad ministration (NOAA). 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 consum ption for cooking and water heating may then be calculated by developing a ratio between the amount of LPG used for hot water, appliances, and the total amount of LPG consumed (space heating + hot water + appliances). The spatial apportioning factor is used to allocate the state fu el total to the county level using the following equation:

LPG INVENTORY COUNTY = SAF INVENTORY COUNTY x LPG TOTAL STATE

Where: LPG INVENTORY COUNTY = Total LPG fuel consumed in the inventory county LPG TOTAL STATE = Total LPG fuel consumed in the inventory county

Temporal In addition to space heating, liquid propane gas is often used for cooking and water heating. For ozone and other seasonal inventories, cons umption for cooking and water heating may be assumed to be constant through the year, but fu el used for space heating must be apportioned according to heating needs.

To separate residential space heating usage fr om cooking and water heating, MDE used data from the State Energy Data Report, Consumption Estimates, Energy Information Administration, Office of Energy Markets and En d Use, U.S. Department of Energy. Data was obtained from the follow reports:

1. Water-Heating Energy Consumption in U.S. Households by South Census Region 2000 2. Appliances Energy Consumption in U. S. Households by South Census Region 2000 3. Total Energy Consumption in U.S. 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/climateproduc ts.html#PUBS (for a list of available data)143 = Also, 2002 residential LPG usage was estim a te d by taking the percent of new housing units constructed in 2000 and applying it to 2001 and 2002 new housing construction data from the Maryland D e partm e nt of Planning.

am ount of LPG used for hot water and appliances Percent of L P G used for cooking & appliances total am ount of LPG consum ed (100 + 43)
= 572

= 0

. 2 5

Therefore 2 5 percen t of the annual LPG consum e d is used for non-space h eating and an individual county’s residential LPG consum p tion total for hot water and appliances can be calcu lated as follows:

Residential Fuel ANNUAL HDD ANNU A L LPG Hot wate r/ App - J = 25% x LPG INV E N T ORY COUNT Y

W h e r e : LPG Hot wate r/ App - J = LPG consum ed for hot wate r a n d a p p l i a n c e s i n c o u n t y j

This percentage m a y be applied to the invent o r y area ’s to tal r e side ntial liquid propane gas

consum ption to calculate the cook ing and water heating portion of usage. This portion can be subtracted from the annual to tal, and the rem a in in g consum ption, which is being used for space heating, can be allocated by m onth or period using proportions of annual and m onthly or period heating degree days.

HDD MON T H Residential Fuel MONTH = x

w h e r e : Residential Fuel MONTH = Space heatin g fuel use for inven t o r y m o n t h Residential Fuel ANNUAL = Space heatin g fuel use for inven t ory year

Em ission Calcula tion HDD MON T H = Heating degree da y s f o r i n v e n t o ry m o n t h HDD ANNU A L = H e a t i n g d e g r e e d a y s f o r i n v e n t o r y y e a r

Emission s Calculation

O z o n e S e a s o n D a i l y E m i s s i o n s

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 da ys in county for ozone season HDD Co Annual = Number of heating degree days in county in the calendar year 2002 LPG Hot water/App - J = LPG consumed for during ozone se ason by hot water and appliances in county j Ozone DAYS = Number of days in the ozone season: 214 Residential; 168 Commercial

Residential LPG Combustion Sample Calculation (Baltimore City) (tons / ozone season day)

Total Residential LPG Consumption – State of Maryland 56,532 kgal

To calculate spatial apportioning factor for Baltimore City:

HDD INVENTORY COUNTY x NHU INVENTORY COUNTY SAF BALTIMORE CITY = ∑ ALL COUNTIES IN STATE (HDD COUNTY x NHU COUNTY )

SAF BALTIMORE CITY

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 = 3,198.3145 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 ) (2000 x 214) E LPG =

(0.5 x 0.00 ) + (0.5 x 621.89) E LPG = (2000 x 214)

E LPG = 0.00073 tons VOC / Ozone season day146 PM 10 , SOx, NOx, CO, VOC, and Toxics 3.1.6.7 Wood Combustion SCC: 21 04 008 000 (Residential W ood Combustion)

Description

This source category covers air em issions from wood com b ustion in th e residential sectors prim arily for space h eating and aesth etics. This MANE-VU RW C inve ntory includes em ission estim ates for indoor wood-burning equipm ent (e.g . fireplaces, woodstoves, pellet stoves, furnaces/bo i lers) and outdoor woodburning equ i p m ent (e.g. outdoor firep l aces, fire p i ts, woodfired barbecues, chim ineas).

Pollutant s

Method and Data Sourc es

The m e thod used to calculate em issions is pres ented in a study/survey conducted by the MidAtlantic Regional Air Managem e nt Associ ation (MARAMA), titled “Res idential W o od Com bustion Em ission Inventory.” 87

Activity In order to improve the RWC inventory fo r MANE-VU, a s u rvey was developed and im ple m ented in the region. The data sources u s ed to cons tr uct 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: sing lef a m ily units (includi ng both detached and attached units up to two units ) and multi-fam ily units (all other housing un its, including mobile homes). In p r evious techn i cal m e m o ra nda, Pechan described the developm ent of these data and the m e thods used to designate MANE-VU ce nsus tracts into one of three categories: urban, suburban, and rural. The rural category was furt her broken out into forested and non-forested categories.

The survey results were converted to em issions per survey response, and were then used to develop an em issions m o del for the source ca tegory. For indoor wood burning equipm ent, the survey w a s designed to obtain inform ation on equipm ent type. Indoor equipm ent includes fireplaces, woo d stoves (bo t h conventio nal and certified), furnace/boilers an d pellet stoves. However, due to concerns re ga rdin g the loss of statistica l pr ecis i on in estim ating e quipm ent level em ission s, estim ates at the equip m ent level were not m a de.

87 R e si dent i a l W o o d C o m bust i o n Em i ssi on I n v e nt o r y , P r epa r t e d by E. H. Pec h an & Ass o ci a t es, I n c. f o r t h e M i dAt l a nt i c R e gi o n al Ai r M a na g e m e nt Ass o ci at i on, dat e d J u ne 2 2
, 2 0 0 4

.147 Emissions were estimated at a more genera l level: outdoor and indoor equipment. Outdoor equipment includes barbeques, fireplaces, fire pits, and chimineas.

During this project, Pechan prepared six te chnical memoranda (TM) to document different phases of the project. The reader should consult these documents, located on the MidAtlantic/Northeast Visibility Union (MANE-VU) website www.mane-vu.org or on the Mid-Atlantic Regional Air Management Association’s (MARAMA’s) website
www.marama.org for details on each component of the project. The technical memoranda and important follow-up notes are as follows:

• TM#1- MANE-VU Residential Wood Combus tion EI Project: Sample Frame Development – this TM described the development of the sample frame to be used during the project. Note that the sample fr ame had incorrect values of the number of homes in the MANE-VU Region. This issue wa s resolved prior to data analysis and inventory development. The correct values are shown in Table 1 below. The total number of MANE-VU single- family households was 12,660,767 and the total number of multi-family units was 12,265,129;

• TM#2 - MANE-VU Residential Wood Combustion EI Project: Format for Activity Data in the Wood Consumption Model – This TM described the data formats for developing the wood consumption model from the survey data, including temporal profiles. Note that for indoor equipment, most of the me thods were not used si nce equipment-specific consumption estimates were not used to develop emission estimates (instead, the general linear model presented in TM#5 was used);

• TM#3 - MANE-VU Residential Wood Combustion EI Project: Pilot Survey and Final Survey Instrument – This TM provided the results of the pilot survey and the final survey instrument (questionnaire) for the survey);

• TM#4 - Results of MANE-VU Residentia l Wood Combustion Activity Survey – This TM provided statistical summaries of the survey results;

• TM#5 - MANE-VU Residential Wood 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 va riables to estimate emissions from indoor and outdoor equipment, and the emission fact ors to be applied. It was during the review of this TM that a different met hod was developed to estimate emissions for indoor equipment based on emission estimates constructed from each survey response (instead of estimating equipment level activ ity, which was originally envisioned for this project). This new method avoided the lowering of statistical precision (error) in the extrapolation of survey data, since i ndividual responses were not divided into multiple equipment types. A description of the development of the general linear model for estimating emissions from indoor equipm ent was incorporated into the final TM. Outdoor equipment emissions were estimated using a user fraction (UF) and annual consumption (AC) estimate developed from the survey data; and

• TM#6 - MANE-VU Residential Wood Combustion Emission Inventory – this TM provided the results of the emission inve ntory constructed from the number of households in the 2000 Census (no adjustme nts to reflect 2002 housing changes were made) and the activity variables and emi ssion factors documented in TM#5. During a148 review of the draft TM#6, reviewers que stioned the wood density value used by Pechan to co nstruc t the a c tiv ity va ria b les in TM#5 (2.1 tons/cord; based on the high end of the range reported for oak species). Pe chan reviewed the prim ary types of wood reported by the survey respondents. Oak/hic kory was the m o st popular choice provided in the survey and very little softwood (e.g., pine, hem l ock) was reported. The next m o st popular choice was “other hardwood”. Pechan developed a weighted estim ate of wood density from the survey responses of 1.8 tons /cord that was used to scale the em ission estim ates by a factor of 0.86 (1.8/2.1).

Emission F a

c

t o

r

s Em ission factors for wood com bustion in residen tial fireplaces are p r esented in Tab l e 1.9-1 Section 1.9 of AP-42 . The wood combustion em ission factor for PM may be assumed to
repres ent P M 10 em issions. Because no em ission factors were located for the com bustion of wood for commercial consum ption, em ission factor s for residential fireplaces were used to estim ate co mmercial em i s s i o n s

.

Residential Wood Combusti on Emission Factors NOx (lbs./ton) CO (lbs./ton) VOC (lbs./ton) PM 10 (lbs./ton) SOx (lbs./ton) R e s i d e n t i a l 2

. 6 2 5 2

. 6 2 2 9 3 4

. 6 0

. 4

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial To produce county-level tem poral profiles, the sam e process used to go from response level profiles to group-level prof iles was used to go from gr oup profiles to county profiles. Activity or em issions for each censu s tract we re assigned to each tem poral unit b a sed on the tract lev e l tem poral prof iles. The s e values we re then sum m e d across all trac ts in the county and norm a lized to gi ve activity fractions.149 Temporal allocation profiles were also devel oped for this project using the residential wood survey data. Profiles were first deve loped for each sample group. Activity (for outdoor equipment) or emissions (for indoor equipment) for each respondent was divided among the different temporal units (e.g., di urnal, weekly, monthly), based on their response to the temporal survey questions. For example, if a respondent reported only burning wood on weekdays, the activity value di vided by 5 was assigned to each weekday, with zero activity assigned to Saturday and Sunday. For the diurnal profiles, the survey data indicated whether respondents burned wood in the morning, evening, or both. Since it is unlikely that emissions take place only in the morning and evening hours, activity was allocated to the entire 24-hour period by assi gning 75% of morning ac tivity to the hours of 6 a.m. to 12 p.m. and 25% of the morning ac tivity to the hours 12 midnight to 6 p.m. The hours of 6 p.m. to 12 noon were assigned 75% of the evening activ ity; and 25% of the evening activity went to the hours 12 midnight to 6 a.m.

Monthly Temporal Allocation Files Temporal

Once a fraction of the total activity was assi gned to each temporal unit for each survey response, the temporal unit activity was summed across all respondents in that sample group. (i.e., survey frame cell; sample groups used for the temporal profiles are the same as those use to develop model parameters.) Th e resulting activity values were used to calculate activity fractions (i.e., activity for Monday was divided by the sum of activity for Monday through Sunday). The resulting profiles were then assigned to each census tract based on the sample group (survey frame cell).

FIPS ST FIPS CNTY May June Aug July Sept Oct Nov Dec Jan Feb March April

INDOOR EQUIPMENT

24 0.0059 001 0.0201 0.0061 0.0053 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 0.2263 0.1351 0.2086 0.1826 0.0954 0.0299

24 0.1868 005 0.0192 0.0051 0.0004 0.0004 0.0154 0.0676 0.1330 0.2111 0.2343 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 0.0015 013 0.0381 0.0096 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 0.1853 0.0062 0.0220 0.0718 0.1465 0.1953 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 0.0349150 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 0.1929 0.0735 0.1464 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 0.2232 0.0106 0.0548 0.1384 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 0.03449 0.00000 0.04004

24 0.16509 0.03363 0.03403 005 0.12837 0.19193 0.16790 0.12382 0.05275 0.02165 0.01721 0.00000 0.03996

24 009 0.11321 0.16773 0.02540 0.02731 0.21049 0.18790 0.13325 0.05402 0.01941 0.01934 0.00000 0.02486

24 011 0.10593 0.16687 0.20836 0.12970 0.06266 0.02514 0.19049 0.02771 0.02177 0.02134 0.00000 0.02094

24 013 0.20701 0.05428 0.01907 0.02840 0.11553 0.16720 0.18443 0.13134 0.02702 0.01995 0.00000 0.02736

24 015 0.20563 0.06069 0.02865 0.00000 0.11000 0.16659 0.18655 0.12881 0.02168 0.02057 0.02431 0.02673

24 017 0.11655 0.16681 0.12990 0.02820 0.01902 0.02896 0.20465 0.18238 0.05500 0.02045 0.00000 0.02871

24 019 0.10548 0.06400 0.02226 0.00000 0.16661 0.20714 0.18996 0.12868 0.02848 0.02157 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 0.02168 0.19017 0.12854 0.06444 0.02856 0.02237 0.00000 0.02076 0.02497

24 039 0.10571 0.16636 0.20580 0.02163 0.18898 0.12776 0.06475 0.02920 0.02262 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 0.19406151 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 0.19169 0.12332 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 0.12617 0.18458 029 0.12617 0.12617 0.12617 0.12617 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 0.19305 0.12278 0.12278 0.12278 0.12278 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 0.05066 0.37335 001 0.05066 0.05066 0.05066 0.05066 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 0.37871152 Activity (tons/yr) = (H Us x UFs x As) + (HUo x UFo x A0) (equation 1) Emission s Calculation

A sa m p le calculation for annual activity is provi ded below for a specified census tract and SCC:

W h ere: HUs = single-family housing units; UFs = single-family housing units user fraction for equipm ent type (SCC); As = single-family housing units annual activity (tons/yr); HUo = other housing units; UFo = other housing units user fract ion for equipm ent 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 coun ty or state levels using the FIPS code in Table 3a. If, durin g the analysis of survey data, Pechan finds a good correlation between w ood consum ption and annual HDD, the activity variable will take the for m of tons /HDD-yr (where HDD are annual he ating-degree days). Th e calculation of annual activ ity f o r a specif i ed c e n sus tra c t an d SCC woul d take the form shown in equation 2 below:

Activity (tons/yr) = [HUs x UFs x (As x HDD )] + [HUo x UFo x (A0 x HDD)] (equ ation 2)

W h ere: HUs = single-family housing units; UFs = single-family housing units user fraction for equipm ent type (SCC); As = single-family housing units annual activity (tons/HDD-yr); HDD = annual heating-degree da ys for the census tract; HUo = other housing units; UFo = other housing units user fract ion for equipm ent type (SCC); and Ao = other housing units annual activity (tons/HDD-yr).153 Estim ated th e num ber of buildings in each ca tegory, and then estim ated the total acres disturb e d by constructio n by applyin g conversio n factors to the housing start data for each catego r y as follows: Description 3.1.7 FUGITIVE SOURCES

Other area s ources in clu d e forest fires, slash and prescribed burning, agricultural burning, structure fires, orchard heaters, leaking underground storage tanks and natural organic sources. Although often interm ittent in nature, m a ny of these sources can produce large quantities of air pollutant em issions.

3.1.7.1 Residential Construction Activity SCC: 23 11 010 000

This source catego r y co vers fugiti ve dust em issions from resident ial con s truc tion ac tivities.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc es Activity For residential construction, housing perm it data for single-fam ily units, two-fa m ily units, and apartm e n ts were obtained at the count y level from the U. S. Departm e nt of Comm erce’s (DOC) Bureau of the Census. Adju sted county perm it data to equal regional housing start data that w a s also obtain ed from the Bureau of the Census.

• Single-fa mily 1⁄4 acre/building

• Two-f a m ily 1⁄3 acre/building

• Apart m ent 1⁄2 acre/build ing

Housing construction P M 10 em issions are calc ulated using an em ission factor of 0.032 tons PM10/acre/m onth, the num ber of housing units created, a units-to-acres conversion factor, and the duration of construction activ ity. The duration of c onstru c tion a c tiv ity f o r houses is assum e d to be 6 m onths.

Apartm ent construction em issions are calcu late d separately using an em ission factor of 0.11 tons PM10/acre/m onth. A duration of 12 months was assum e d for apartm ent construction.154 For areas in which basem e nts are constructed to estim ate the cubic yards of dirt m ove d per house, an average value of 2000 square feet is assum e d for both single fam ily and twof a m ily hom e s. Multiply ing the ave r a g e tota l s quare feet by an average basem e nt depth of 8 feet and adding in 10 percent of the cubic f eet calculated for peripheral dirt rem oved produces an estim ate of the cubic yards of ear th moved during resident ial construction. The percentage of one-fa m ily houses with ba sem e nts was obtained from the DOC. The percentage of houses per Census region (Nor theast, Midwest, South, and West) that contain full or partial basem e nts is applied to the housing start estim a tes for each of th ese respective regions. The b e st availab l e c ontrol m e a s ures (BACM) Level 2 equation (em i ssion factor of 0.011 tons PM10/acre/m onth plus 0.059 tons PM10/1000 cubic yards of

on-site cu t/f ill) is applied once the num b er of acres disturb e d due to the estim ated

num b er of houses built with basem e nts is determined.

Emission F a

ctors

Single-fa mily Construction Tw o-family Construction Multi-family Constructio n ton PM 10 /acre/m o n t h t o n PM 10 /acre/m o n t h t o n PM 10 /acre/m o n t h PM 10 Em ission F a c t o r 0

. 0 3 2 0

. 0 3 2 0

. 1 1

Duration of Activity 6 m onths 6 m onths 12 m onths

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.155 E RC – MF = Em issions o f pollutant i in tons pe r y ear f r om residentia l m u lti-f am ily
construc tion activ ity Emission s Calculation

E RC I = E RC – SFH + E RC – 2FAM + E RC – MF

w h e r e : E RC i = Em issions of pollutant i in tons per year from residentia l c o n s t r u c t i o n a c t i v i t y

E RC - SFH = Em issions of pollutant i in tons pe r y ear f r om residentia l sing le-f am ily hom e c o n s t r u c t i o n a c t i v i t y E RC – 2FAM = Em issions o f pollutant i in tons pe r y ear f r om residentia l two- f a m ily hom e construc tion activ i t y

and:

E RC – SFH = E RC – SFH, w BM + E RC – SFH , w/o BM

w h e r e : E RC – SFH, w BM = Em issions o f pollutant i in tons per year from resi dentia l sing le-f am ily hom e construction activity of hom e s with basem e n t s E RC – SFH, w/o BM = Em issions of pollutant i in tons pe r y ear f r om residentia l sing le-f am ily hom e construction activity of hom e s without basem e n t s

HS SFH x (1- HS SF H,w BM ) x (AD RC – SF H ) x (PD RC – SFH ) x EF RC – SFH E RC – SFH, w/o BM = 2000

w h e r e : E RC – SFH, w/o BM = Em issions of pollutant i in tons pe r y ear f r om residentia l sing le-f am ily hom e c o n s t r u c t i o n a c t i v i t y HS SF H = Residential single-fam ily housing s t a r t s HS SF H, w BM = Percent of residential single-f am ily housing starts with basem e n t s AD RC - SF H = Acres disturbed per housing t ype (residential single-fam i l y ) PD RC - SFH = Average project duration in m o n t h s EF RC – SFH i = Em issions factor in tons P M 1 0 / a c r e / m o n t h f o r p o l l u t a n t i156 E RC – SFH, w BM = Emissions from residential construction + Emissions from basement excavation

[HS SFH x HS SFH,w BM x (AD RC – SFH ) x (PD RC – SFH ) x EF RC – SFH ] + [HS SFH x HS SFH,w BM x AHS RC – SFH x ABD RC – SFH x PDE RC – SFH x EF Acres-Disturb ] E RC – SFH, w BM = 2000

where: E RC – SFH, w BM = Emissions of pollutant i in tons pe r year from residential single-family home construction activity HS SFH = Residential single-family housing starts HS SFH, w BM = Percent of residential single-f amily housing starts with basements AD RC - SFH = Acres disturbed per housing t ype (residential single-family) PD RC - SFH = Average project duration in months EF RC – SFH i = Emissions factor in tons PM10/acre/month for pollutant i AHS RC - SFH = Average residential single-family house size (national default = 2000 ft 2 ) ABD RC - SFH = Average basement depth for re sidential single-family homes (national default = 8 ft) PDE RC – SFH = Peripheral dirt excavated for residential single-family homes (national default = 10 percent) EF Acres-Disturb = Emissions factor for the acres disturbed during basement excavation activities during residential single-fa mily home construction in tons PM 10 /1000 cubic yards157 3.1.7.2 Heavy Construction Activity SCC: 28 10 001 000

Description

Em issions produced from the construction of nonr esiden tial buildings are estim a ted using the value of con s truction pu t in place. The nation a l value of construction pu t in place is obtained from the Bureau of the Census 88 . The nation a l value of construc tion pu t in place is allo cated to the state level using non-residential building construction em ploym ent data within NAIC 2333 obtained from 2002 County Business Patterns 89 . The state valu e of construction put in p l ace is allocated to the county level usi ng non-residential building constr uction em ploym e nt data within NAIC 2333 obtained from the 2002 County Business Patterns 90 f o r t h e S t a t e o f M a r y l a n d

.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc es Activity

ARMA used data from the U.S. Census Bureau on the national value of construction put in place. The national value of construction pu t in place is allo cated to the state level and then to the county level us ing non-residential building c onstruction em ploym e nt data within NAIC 2333 obtained from 2002 County Business Patterns.

A conversion factor of 1.6 acres/10 6 dolla rs ($) is applied to the constru c tion valua tio n data. This conversion factor is developed by adjusting the1992 value of 2 acres/$10 6 to 2002 and 2000 constant dollars using the Price and Cost Indices for Construction. The duration of construction activity for nonresidential construc tion is estim a ted to be 11

m o n t h s

.

Em ployee num b ers were taken from County Business Patterns 2002 - Maryland , NAIC 2333, Non-residential Building Construction. S o m e county em ploym e nt data is represented by a letter code i ndicating a range f o r the num ber of em ployees for that SIC. In this case the arithm etic average number of e m ployees per letter code per county was

88 Burea u of Census, Ta ble 1. Annual Value of Construction Put in Place i n the United States : 1997 – 2001; h ttp ://www.cen sus.g o v / con s t / c3 0 /tab1 01.tx t 89 U. S. C e ns us B u rea u , C o unt y B u si ness Pat t e r n s, 2 0 0 2 http://censtats.census. gov/cbpnaic/cbp naic.shtml Sele ct U.S

. then 2002 t h en Com p are fo r t h e “C onst r uct i on” I n dust r y t h en C o m p ary N A IC 2 3 3 3
90 U. S. C e ns us B u rea u , C o unt y B u si ness Pat t e r n s, 2 0 0 2 http://quickfacts.censu s. gov/qfd/states/24000.html Select county th en “B rowse m o re d a ta sets” th en Coun ty Bu sin e ss Patte rn s Econ o m ic Pr of ile fo r 20 02

– Rep eat fo r each co un ty.158 PM adjusted so that the state to ta l em ploym ent in a NAIC m a tc hed the sum of the num ber of

em p l o y e e s r e p o r t e d p e r c o u n t y

.

Emission F a

ctors

10 PM 2. 5 ( t o n s / a c r e / m o n t h ) ( t o n s / a c r e / m o n t h ) Em issions 0

. 1 1 20% of PM 10 Duration of Project 11 m onths

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s Calculation

Num b er of Em ployees within NAIC 2333 in Maryland Value of Construction W o rk in Maryland = Value of Construction W o rk in the U.S. x Num b er of Em ployees within NAIC 2333 in the U.S.

Value of Construction Work in the U.S. $167,084,000,000.00

Num b er of Em ployees within NAIC 2333 in the U.S. 855,483159 Number of Employees within NAIC 2333 in Maryland 19,267

19,267 Value of Construction Work in Maryland = $167,084,000,000.00 x 855,483 Value of Construction Work in Maryland = $3,763,029,105

HC j x CF HC x EF HC i x DC HC E HC i = 365

where: E HC,i = Emissions of pollutant i in t ons per day from heavy construction HC J = Value of heavy construction (million dollars) in county j in 2002 CF HC = Conversion factor (acres/million do llars) for heavy construction (1.6 ) EF HC i = Emissions factor in tons pe r acre per month for pollutant i DC HC = Duration of construc tion activity (11 months)

2002 Sample Calculation Heavy C onstruction (Anne Arundel County)

HC j x CF HC x EF HC i x DC HC E HC i = 365 196.68 x 1.6 x 0.11(PM 10) x 11 E HC i = 365

E HC i = 1.04 tons/day PM 10160 3.1.7.3 Road Const r uction Activity SCC: 28 10 001 000

Description This source category covers fugitive dust em issions from road c onstruc tion activ ity. PM 10
em issions produced by road construction are es tim a ted using an em ission factor for heavy construction and the State capital ou t l a y f o r n e w r o a d c o n s t r u c t i o n

.

Pollutant s
PM 10 and PM 25

Method and Data Sourc es Activity To estim ate the acres disturbed by road cons tru c tion, the Fed e ral Highway Adm i nistration (FHW A) St ate expend iture data for capit al outlay accord ing to the follow i ng six class i ficatio ns was obtained:

• Intersta te, urban;

• Intersta te, rural; • Other arterial, urban;

• Other arterial, rura l; • Collectors, urban; and

• Collectors, rural

Dollar expenditures are converted to m iles contructed using data obtained from the North Carolina Departm e nt of Transportation (NC DOT) on the $ / m ile sp ent on various road
construc tion projec ts. Fo r inters tate e xpenditu res, used an average of $4 million/m ile corresponding to freeways and interstate projec ts listed for: 1) new location; 2) widen existing 2-lane shoulder section; and 3) widen existing 4-lane w/ m e dian. For expenditu res on other a r teria l and co llecto r s, used an averag e of $1.9 m illion/m ile corresponding to all other projects (excluding fr eeways and interstate pr ojects) listed for: 1) new location; 2) widen existing 2-lane shou lder section; and 3) widen existing 4-lane w/ m e dian.

Miles are co nverted to acres fo r each of the 6 road types us in g the f o llowing estim ates of

a c r e s di s t ur be d pe r mi l e : • Interstate, urban and rural; Othe r arterial, urban - 15.2 acres/m ile

• Other arterial, rural - 1 2 .7 acres /m ile • Collectors, urban - 9.8 acres/m ile

• Collectors, rural - 7.9 a c res/m ile161 Emission F a

ctors

An PM 10 emission factor of 0.42 tons/acre/m onth is used to account for the large am ount of dirt m ove d during the construction of ro adways. The duration of construction activity for road construction is estim ated to be 12 m o n t h s

.

PM 25 em issions are es tim a ted by applying a pa rticle size m u ltiplier of 0.2 0 to PM 10
em i s s i o n s

.

Soil Mo istu r e Level To account for the so il m o isture lev e l, base em issions were m u ltip lied by 2 4 divided by the precip ita tion

- evapor ation (PE) value. Precip ita tion

- Evapora tio n (PE) value s were obta i ned from Thornthwaite’s PE Index. Average PE valu es for each State were estim ated bas e d on PE values for specific clim atic divisions within a State.

S i l t C o n t e n t To account for the s i lt co ntent, base em issions were m u ltiplied by percen t dry silt con t ent in soil divided by 9 percent. County-leve l dry silt values were applied to P M 10 em issions for each cou n ty

. .

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s f o r C o n t r o l s
For constru c tion em issio n s, a contro l efficiency o f 50 percent is used for b o th PM 10 and PM 2. 5 for PM nonattainm e n t a r e a s

.

Spatial and Temporal Allocatio ns Spatial

State-level estim ates of acres disturb e d ar e dis t rib u ted to coun ties accord in g to the housing starts per county, estim ated for the residential construction category.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.162 Emission s Calculation

Exp x MC i x ADi x EF RC i x D U R

E RC, i = 2000 x 365

where: E RC,i = Em issions o f pollutant i in t ons per day from r o a d c o n s t r u c t i o n Exp RC,i = E x p e n d i t u r e s p e r r o a d t y p e i MC RC,i = M i l e s c o n t r u c t e d p e r r o a d t y p e i AD i = A c r e s d i s t u r b e d p e r r o a d t y p e i EF RC i = Em issions factor (tons per a c r e p e r m o n t h f o r p o l l u t a n t i ) DUR = Duration of project (m o n t h s )163 3.1.7.4 Agricultural Land Preparation SCC: 28 01 000 003

Description

The land preparation sou r ce category includes estim a tes of the airborne soil particulate em issions produced during the preparation of agricu ltural lands for planting and after harvest activities. Operations included in this m e t hodology are discing, tilling, leve ling, chiseling, plowing, and other m echanical op erations used to prepar e the s o il. Dust em issions are p r oduced by the

m echanical disturb a nce of the soil b y the im plem ent used and the tractor pulling it. Soil
prepar ation activ ities ten d to be perf o r m e d in the early sp ring and f a ll m o nths.

Particula t e e m issions f r om land prep aration ope r a tions are co m puted by m u ltiply ing an em ission factor (EF) by an activity fact or. Th e agricultu ra l tilling em i ssion factor provided in the 4th edition of U.S. EPA’s AP-42 document is used to estim ate s o il preparation em issions. The activ ity factor is based o n the num be r of acres of each crop in production for each cou n ty in th e State. Becau se different crops n eed d i fferent operations to prepar e th e soil, each crop also has its own acre-pass value. Acre-pas ses ar e the num ber of passes, per acre, that are typically needed to prepare a field for planting a particular crop. By com b ining the crop acre age, crop sp ecific acrepass data, and the agricultural ti lling em ission factor, we estim ate the particulate m a tter produced by agricultural land pr eparation operations.

Agricultural soil preparation partic ulate dus t em issions are es tim ated for each crop in each county in Maryland using the following equation:

Em issions CROP = Em ission Factor x Acres CROP x Acre-pass e s/ac re CROP
The crop emissions for each county are summ ed t o produce the county and statewide particulate m a tter (PM) and PM emission estim ates.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc es Activity

The acreag es used for es tim ating soil preparation em issions were co llected from the Maryland C ooperative E x tension Service and the Maryland A g ricultural S t atistics Service. A summ ary of crop acreage harvested in 2002 from individual county agricultural

comm issioner repo rts w a s used to calculate em issions.164 In computing land preparation PM emissi ons, acre-passes are the number of passes typically performed to prepare a crop for planting. These operations may occur following harvest, or closer to planting, and can incl ude discing, tilling, land leveling, and other operations. Each crop is different in the type of soil operati ons performed and when they occur. MDE used acre-pass estimates compiled by the California Air Resources Board (CARB). For the crops that were not 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 agricultu ral land preparations is from U.S. EPA’s AP-42 91 . This emission factor was de veloped in 1981 based on test data measured in California and Kansas by Midw est Research Institute. Because of a lack of more detailed estimates, this single emissi on factor is used for all land preparation operations, all locations, and all seasons. The form of the emission factor is:

Emission Factor (lbs PM/acre-pass) = k (4.8) (s) 0.6

Where:

k = particle size fraction of inte rest (EPA default = 0.042 for PM 2.5 or 0.21 for PM 10 ) s = average percent soil silt content (EPA default = 18%)

For PM the value of ‘k’ used in California is 0.148. This is based on the EPA estimate that 33% of the total particulate entrained to the air during agricultural operations is 30 microns or less. Of this, analysis of California soil samples indicates that about 45% of the 30 micron or less sized particles are 10 microns or less in aerodynamic size (i.e., PM ). So, the California PM particle size multiplier is 0.148 (i.e., 0.33 x 0.45 = 0.148). Maryland decided to use the EPA default values listed 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. PM 2.5 /acre-pass) (Lbs. PM 10 /acre-pass) Emission Factor 1.141968254 5.709841268

The EPA emission factor does not include an association between soil moisture and emissions. Because it is known that dust emi ssions are reduced when soil moisture is higher, California ARB staff has incorporat ed an emission correction during the wettest months of the year. The correction was based on some limited agricultural dust source test data, as well as the control factor used fo r watering at constructi on sites and their best judgement. During December and March, Califo rnia ARB reduced the emission factor by

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 u n corrected v a lue. In January and February, often the wettest months, the em ission factor is reduced by 50% . This produces a seasonal em issions profile that is m o re consistent w ith Calif o rnia’s ac tual a m bient air d u st lev e ls, a nd also be tte r reflects that soil preparation ope ra tio ns typic a lly do not occur while the so il is exces siv e ly
wet or m uddy.

Precipitation data for calendar year 2002 in Maryland is presented in Section 3.4, Table 3.4-b 2002 Precipitatio n Data , since Maryland does not have a correlation between soil moisture an d em issions, the em issio n factors were not redacted.

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial Crop acreag es are collected on a cou n ty basis.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e in Maryland.

In collecting updated acre-pass data, Californi a also collected detailed inform ation on when agricu ltural operations occur. Using thes e data, it was possibl e to create detailed
tem poral pr of iles tha t h e lp to indica te when PM em issions from land preparations may be highest. The m o re detailed backgrou nd docum en t includes detailed crop calendars for each crop with updated inform ation. For all of th e acre-pass and crop calendar inform ation, the far m ers and other agricultural experts of the San Joaquin Valley were instrum e ntal in helping us to update our crop information.166 Emission s Calculation

EF AL P i x A I x AP I

E ALP i = 2000

w h e r e : E ALP = Annual PM em issions of pollutant i in tons per day from agricultural land preparation s

. EF AL P i = Em issions factor in pounds per ac re -pass for pollutan t i A i = A c r e s o f c r o p I h a r v e s t e d i n c o u n t y j i n 2 0 0 2 AP i = Acre-pass e s per ac r e s f o r c r o p i

2002 Sa m p le Calculation Agricultural Land Preparation (Anne Arundel County)

EF AL P P M 2.5 x [(A wheat x AP wheat ) + (A co rn -g r x AP co rn -g r ) + (A c o rn -silag e x AP co rn -silag e ) + (A

hay x AP hay ) + (A soy x AP soy ) + (A bar l ey x AP bar l ey ) + (A tobacco x AP tobacco ) ] E ALP PM2.5 = 2000
1

. 1 419 682 54 x [ ( 25 00 x 1 ) + (5 700 x 4) + (0 x 4) + ( 3 10 0 x 1) + ( 5 20 0 x 6) + ( 1 75 x 1) + ( 1 0 0 x 0)] E ALP PM2.5 = 2 000 1.141968254 x 60475 E ALP PM2.5 = 2000

E ALP PM2.5 = 34.530 tons per year of PM 2. 5167 3.1.7.5 Paved Roads SCC: 22 94 000 000

Description This source category covers fugitive dust em issions from activity on paved roads.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc es Activity The basis f o r the a c tiv ity data f o r f ugitiv e dust e m issions f r om paved roa d s is the sta t elevel vehicle m iles traveled per paved road t ype and the state-level vehicle m iles traveled per unpaved road per road type.

Emission F a

ctors

The em ission factor for paved roads is calcul ated from an empirical formula from AP-42 and then is a d justed f o r p r ecip ita tion.

AP-42 Paved Roads Emission Factor Formula

EF PAV E D RD = PSDP VD x (PVSILT/2) 0. 65 x (WEIGHT/3) 1. 5

w h e r e : EF PAV E D RD Paved road dust em ission factor for all veh i cle classes com b ined (gram s per m i l e ) PSDPVD Base em ission factor for particles of less than 10 m i crons in diam eter from paved road dust (d efault va lue = 7.3 gram s PM 10 per mile ) PVSILT Road surface silt load in g factor in g r am s per square m ile W E IGHT Average weight of all ve hicle types com b ined in tons

And where: PVSILT varies by road type and the average daily traffic volum e (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/Precipitation169 EF PAVED_ADTV >10,000 ADJ = CF RAIN CF RAIN = 1 - (P / 4 N )

Where: CF RAIN = Correction Factor for Rain/Precipitation p = number of days in a given month w ith greater than 0.01 inches of rainfall (data collected from mo nthly climatological data files from National Weather Service stations near or in the county of reference.) N

= number of days in the averaging period (e.g., 365 for annual, 91 for seasonal, 30 for monthly).

MDE altered the precipitation adjustment equati on by collecting data on the number of days in a given year that greater than 0.01 inches of rainfall fell and removing the x 12 from the equation.

CF RAIN = 1 – (104 / (4 x 365))

CF RAIN = 0.928767

Calculate Paved Roads Emission Factors Adjusted for Precipitation

EF PAVED-LOCAL < 500 ADJ = EF PAVED_LOCAL x CF RAIN
EF PAVED-LOCAL < 500 ADJ = 3.430692 x 0.928767

EF PAVED-LOCAL < 500 ADJ = 3.186314 gram/mile 2

EF PAVED_ADTV 500 - 5000 ADJ = EF PAVED_LOCAL x CF RAIN
EF PAVED_ADTV 500 - 5000 ADJ = 1.571635 x 0.928767

EF PAVED_ADTV 500 - 5000 ADJ = 1.459683 gram/mile 2

EF PAVED_ADTV 5000- 10,000 ADJ = EF PAVED_LOCAL x CF RAIN
EF PAVED_ADTV 5000- 10,000 ADJ = 0.603575 x 0.928767

EF PAVED_ADTV 5000- 10,000 ADJ = 0.560581 gram/mile 2

EF PAVED_LOCAL x

EF PAVED_ADTV >10,000 ADJ = 0.310239 x 0.928767

EF PAVED_ADTV >10,000 ADJ = 0.285861 gram/mile 2170 Equation:

EM PAVED RD, i = ∑ ( VMT ADTV, i x EF PAVED_ADTV ADJ, i x ( 1- CE x RE x RP) x 1.10231E-06 )

where:

EM PAVED RD ,i = Sum of PM 10 emissions in tons per year for paved roads in county i VMT ,i = VMT ( million miles of Vehicle Miles Traveled for county i ) EF PAVED_ADTV ADJ, i = Paved road emission factor adjusted for precipitation in county I (grams/mile)

CE = Control efficiency of 0% applied to Urban and Rural roads RE = Rule effectiveness of 100% applied to Urban and Rural roads RP = Rule penetration of 100% a pplied to Urban and Rural roads 1 gram = 1.10231E-06 tons

2002 Sample Calculation Paved Roads (Anne Arundel County)

EM PAVED RD, i = [( VMT _ADTV < 500, i x EF PAVED-LOCAL < 500 ADJ ) + ( VMT _ADTV 500 - 5000,i x EF

PAVED_ADTV 500 - 5000 ADJ ) + ( VMT _ADTV 5000 – 10,000, i x EF PAVED_ADTV 5000- 10,000 ADJ )

+ ( VMT _ADTV >10,000,i x EF PAVED_ADTV >10,000 ADJ )] x ( 1- CE x RE x RP) x 1.10231E-06

EM PAVED RD, i = [(355524175 x 3.186314) + (167099106 x 1.459683) + (279697255 x 0.560581) + (4.64E+09 x 0.285861)] x (1 – 0 x 1 x 1) x 1.10231E-06

EM PAVED RD, i = 3,152.509 tons per year of PM 10 or (3,152.509 / 365) = 8.64 tons per day of PM

10171 3.1.7.6 Unpaved Roads SCC: 22 96 000 000

Description

This source category covers fugitive dust em issions from activity on unpaved roads. The activity data needed to cal culate emissions from unpaved ro ads was not available. Methods are still being researched as to how to properly gather this data. MDE cannot submit any emissions for this source categ ory at the present time.172 3.1.8 FIRE SOURCES

Other area s ources in clu d e forest fires, slash and prescribed burning, agricultural burning, structure fires, orchard heaters, leaking underground storage tanks and natural organic sources. Although often interm ittent in nature, m a ny of these sources can produce large quantities of air pollutant em issions.

3.1.8.1 Vehicle Fires SCC: 28 10 001 000

Description

This em ission guidance report cov e rs air em ission s from accid e ntal v e hicle fires. Vehicles included are any comm e r cial or p r iv ate m ode of transpo r ta tio n that is authorized for use on public roads.

Pollutant s
PM 10 , N O x , C O
, V O C

Activity Local data was collected from state or local fire m a rshals and public safety departm e nts. See the spatial apportioning sect ion for available inform ation

sources.

Emission F a

c

t o

r

s Em ission factors are available for open bur ning of autom obile com ponents including upholstery, belts, hoses, and tires (A P-42, Section 2.5 Open Burning) (E PA, 1996) 92 . The

am ount of vehicle m a terial burned (the fuel load ing) in a vehicle fire m u st be estim a ted to use these factors. A conservative assum p tion is that an average vehicle has 500 pounds of

com ponents that can burn in a fire, ba sed on a 3,700 pound average vehicle weight (CARB, 1995) 93 . Maryland used a m o re conservative assum p tion based on a 2,000 pound
average v e hicle weigh t

.

P o l l u t a n t L b s / t o n burned

92 EPA. 1 996

. Co mp ila tion o f

Air Po llu t a n t Emission Fa cto r s--Vo l ume I: S t a tio na ry Po i n t a n d Area Sou rces. Fifth Ed itio n, AP-4 2. U. S. Env i ronmen tal Pro t ectio n Ag en cy, Office of Air Qu ality Plan n i ng an d Stand a rd s. (GPO 0 5 5

- 0 00- 002 51 -7)

. Resear ch Tr iang le Par k

, N o r t h Car o lin a 93 C A R B

. 1 9 9 5

. Em i ssi on I n ve nt o r y Pr oce d u r al M a nual

, V o l

. I II: M e t h o d s f o r

Asse ssi n g A r ea S o urce Em i ssi ons. Califo r n i a En viron m en tal Protectio n Ag en cy : Air Resou r ces Bo ard. Method and Data Sourc es173 VOC 32 NOx 4 CO 125 PM10-PRI 100

Point Source Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial The activity data for vehicle fi res was collected at a county- level. No other m e thod to spatially p r o f ile the veh i cle fire source category was used.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.
Emission s Calculation

2000 x 365 VB j x FLF VF x EF VF i E VF, i =

w h e r e : E VF,i = Em issions o f pollutant i in tons per day from v e h i c l e f i r e s VB J = V e h i c l e s b u r n e d i n c o u n t y j i n 2 0 0 2 FLF VF = Fuel loading factor (tons/vehicle bur ned) for vehicle fire s ( 5 0 0 l b s / 2 0 0 0 l b a u t o ) EF VF i = Em issions factor in pounds p e r t o n b u r n e d f o r p o l l u t a n t i

2002 Sa m p le Calculation Forest Fires (Anne Arundel County)

VB j x FLF VF x EF VF, 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 em itted from ve hicle fires in Anne Arundel County in 2000 2174 3.1.8.2 Forest Fires SCC: 28 10 001 000

Description

Forest fires in certain ru ral areas can produ ce very large, short term organic em issions.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc es
A

c

t i v

i t y ARMA used data f r om the Maryland Forest, Park and W ildlif e Servic e 94 on the num ber of fires and acreage burned per county. Em ission 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 ob tained 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 f i re data f r o m the Forest, Park and W ildlif e Service showed no apparen t incre a se in

num b er or size of forest fires in the ozone season, thus no seasonal adjustm e nt was us e d

.

Emission F a

ctors

VOC NOx C O P M TO T ( L b s . / t o n ) ( L b s . / t o n ) ( L b s . / t o n ) ( L b s . / t o n ) Em issions 24.0 4.0 140.0 17.0 Fuel load ing factor: 11.0 Tons/acre b u rned

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

No controls are availab l e for this source category. Adjustment s for Controls

94 Fo rest fire data collected fr o m Mr. Bo b Hartlo v e , Actin g Fire Sup e rv isor for th e Marylan d Fo rest Serv ice175 Temporal

AB j x EF FF i Spatial The activity data for forest fi res was collected at a county- level. No other m e thod to spatially p r o f ile the fores t fire source catego r y was used.

Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

x FLF FF 2000 x 365 E FF I =

w h e r e : E FF,i = Em issions o f pollutant i in tons per day from f o r e s t f i r e s FLF FF = Fuel load ing factor (tons/acre bu rned) for forest fires (11.0 ) AB J = A c r e s b u r n e d b y w i l d f i r e i n c o u n t y j i n 2 0 0 2 EF FF i = Em issions factor in pounds per acre or pounds per ton for pollutant i

2002 Sa m p le Calculation Forest Fires (Anne Arundel County)

AB E j x EF f, i x FLF FF

FF i = 2000 x 365

w h e r e : E FF i = (0.3 acres b u rned 95 x 11 tons per acre 96 x 24.0 lbs. VOC per ton) / (2000 x 365) 97

95 N u m b er o f ac r e s b u r n e d by w i l d fi re i n A n ne Ar un del C o u n t y i n 2 0 0 2 f r om M a ry l a nd F o r e st , Par k s an d W i l d l i f e Service . Spatial and Temporal Allocatio ns

Emission s Calculation176 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 controll ed conditions to reduce the potential fire hazard in forests and to rem ove brush that can s e rve as a ho st for destru ctive insects. Prescribed bu rn ing is used as a fo rest m a nagem e nt practice to establish favorable seedbeds, remove com p eting unde rbrush, accelerate nut rient cycling, control tree pests and contribute other ecological benefits.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc es Activity

Em issions from this source were calculated using data from the Maryland Forest Service for prescribed burning by county and type of m a te rial burned. Em ission and fuel loading factors for m a rsh grass was assum e d to be the s a m e as that for unspecified field crop s in AP-42 , Table 2.5-5, and the factor for pine wa s supplied by staff at the Maryland Forest S e r v i c e

.

Emission F a

ctor

V O C C O N O x P M TO T ( L b s . / t o n ) ( L b s . / t o n ) ( L b s . / t o n ) ( L b s . / t o n )

Ma r s h Gr a s s Em issions Factors 18.0 117.0 NA 21.0 Fuel loading factor 2.0 tons/acre

P i n e S l a s h Em ission factor 1 9

. 0 1 4 0

. 0 4

. 0 1 7

. 0 Fuel loading factor: 30.0 tons/acre178 Spatial

Temporal

AB j x EF PB i No subtration of e m issions fr om point sources is necessary.

No controls are availab l e for this source category.

The activity data for prescribed burning was collected at a county-level. N o other m e thod to spatially prof ile th e p r escr ibed burning source category was used.

Because prescribed bu rn ing is done at differe nt tim es of the year, ARMA used no seasonal adjustm e nt f actor. The a c tiv ity level is seven days per week.

x FLF J 2000 x 365 E PB i =

w h e r e : E PB,i = Em issions o f pollutant i in t ons per day from prescribed burning FLF J = Fuel load ing f actor f o r ty pe of m a teri al burned j (for m a rsh grass the factor is 2 tons per acre and for pine slash i t i s 3 0 t o n s p e r a c r e b u r n e d ) AB J = A c r e s b u rn e d i n c o u n t y j i n 2 0 0 2 EF PB,i = Em i s s i o n f a c t o r f o r p o l l u t a n t k

2002 Sa m p le Calculation Slash/Pres cribed Burning (W orcester County)

AB j x EF PB i x FLF J E PB i = 2000 x 365

(20 acres of pine slash burned x 19 lbs. VOC p e r t o n x 3 0 t o n s p e r a c r e b u rn e d ) E PB i = 2000 x 365

E PB i = Point Source Adjustment s

Adjustment s for Controls

Spatial and Temporal Allocatio ns

Emission s Calculation

0.016 tons VOC /day

Slash burning calculations ar e done in a sim ilar m a nner.179 PM 10 and PM 2. 5 3.1.8.4 Agricultural Burning SCC: 21 01 500 000

Description

This source catego r y co vers agricu ltural burn i ng practices u s ed to clear and/or prep are land for planting. Operations included under this categ ory are stubble burning, burning of agricultural crop residues, and burning of standing field crop s as part of harvesting (e.g., sugar cane).

Pollutant s

Method and Data Sourc es

Em issions from this source were assigned to the open burnin g catego r y b ecause the county
perm its issued in 2002 did not require inform a tion distinguishing the am ount of agricultural waste to be burned versus other m a terials.

3.1.8.5 Structure F i res SCC: 28 10 030 000

Description Building fires produce short-term em issions of organic compounds.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc e s
MDE staff used em ission factors, fuel lo ading factors and m e thodology docum e nted in EIIP 98

, S t r u c t u r e F i r e s , d a t e d J u l y 1 9 9 9

. Activity The Maryland State Fire Marshal's office provide d the num ber of structure fires by county.

98 Em i ssi on In ve nt o r y Im pro v e m ent Pr og ram180 Emission F a

ctors

V O C N O x C O P M TO T ( L b s . / t o n ) ( L b s . / t o n ) ( L b s . / t o n ) ( L b s . / t o n ) Em issions 1 0

. 8 1 1

. 0 1

. 4 6 0

. 0 Fuel loading factor: 1.15 Tons/fire

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

SF j x EF SF i Spatial and Temporal Allocatio ns Spatial The activity data for structure fires w a s collected at a county -level. No other m e thod to spatially p r o f ile the p r es cribed bu rning source category was u s ed.

Temporal Because stru cture fires o ccur at different tim es of the year, ARMA used no seasonal adjustm e nt f actor. The a c tiv ity level is seven days per week.

Emission s Calculation

x FLF SF 2000 x 365 E SF i =

where:

SF J = Structure fires in county j in 2002 E FF,i = Em issions o f pollutant i in tons per day from s t r u c t u r e f i r e s

FLF FF = Fuel load ing factor (tons/acre bu rned) for structu r e f i r e s181 EF SF,i = Emission factor for pollutant i in tons per day from structure fires

ARMA used an activity level of 7 days a week with no seasonal va riation as given in Table 5.8-1 in the EIIP document.

2002 Sample Calculation Struct ure Fires (Baltimore City)

Equation:

SF j x EF SF i x FLF SF E SF i = 2000 x 365 2386 99 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 Fires3.1.8.6 Orchard Heaters SCC: 28 01 520 000

Description

182 In areas of the country where frost threatens orchar ds, heaters m a y be us ed in cold portions of the growing season.

Pollutant s
PM 10 and PM 2. 5

Method and Data Sourc es

Calls to several orchards in W a shington and Fred erick Counties (where m o st of the orchards in Maryland are located), revealed that no heaters we re used. One orchard used fans to move air on still nights when there would be danger of frost to fruit tree blo ssom s . Therefore, orchard heaters are not included in Maryland' s 2002 baseline inventory.183 This section contains the a mmonia emission inventory for 3.1.9 AMMONIA SOURCES

Ammonia (NH 3 ) is a pungent colorless gaseous compound of nitrogen and hydrogen that is very soluble in water and can be condensed into a liqui d by cold and pressure. Ammonia gas reacts in the atmosphere with NOx or SOx to produce am monium nitrate or ammonium sulfate, major PM 2.5 components in the United States.

In preparing an ammonia inventor y, it is worthwhile to priori tize which of the many potential ammonia sources should rece ive attention. Previous studies conducted by Battye 102 and the State of California Air Resources Bureau (CARB), provide list s of ammonia sources that can be used to evaluate which sources are present within a re gion. These sources may then be ranked in terms of priority for estimating emissions.

Currently, there is a significan t amount of uncertainty concer ning 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 potentia lly significant in some regions if the uptake is not substantial. Indeed, th e literature shows th at a soil-plant canopy system can be a source of ammonia emissions under certain conditions and a sink under other conditions. Because of this uncertainty, the St ate of Maryland has decided not to include emissions from soils.

• Agricultural Livestock Production Operations

• Agricultural Fertilizer Application,

• Human activity.

102 Battye, R., Battye, W., C. Ov ercash, C., Fudge, S., 1994. Development and Selection of Ammonia Emission Factors, Final Report. EC/R Incorporated for U.S. EPA, EPA/ 600/R-94/190 (Prepared for William Benjey).3.1.9.1 Cow s (Milk Cow s , Beef Cow s , Heifers, and Steers) SCC: 28 05 020 000 (Cows Com p o s i t e )

Description

These anim als, and all livestock, are sources of ammonia e m issions due to the biological decom position of their waste products

NH 3

184 Conceptually, the m e thod for estim ating em issions from cattle is sim p le: count the nu mber of anim als, the n m u ltiply this by the av erage em issi ons per anim al, and the resulting va lue prov ides the em ission s. The CMU-NH3 Inventory (ve r sion 2.0) prog ram utilizes this app r oac h , a

m e thodology approved by the EPA for developing th e em issions inventory for other categories

Activity Activity levels were collected from the US DA Census of Agriculture data for 1997.

Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w :

Emission F a ctors and Source Livestock Category Em ission Factor Source of Em ission 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/ yea r Battye, et al. (1994)

No subtraction of e m issions from point sources is necessary. Pollutant s

Point Source Adjustment s Method and Data Sourc es

Adjustment for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio nsSpatial

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

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s C a l c u l a t i o n Equation:

1999 TPY a mmonia e m issions for cows in an individual county

1999 EM BC + 1999 EM MC + 1999 EM HF + 1999 EM ST

EM ST = 1999 Uncontrolled em issions from steers

(AC BC * EF BC )

A C ST = Activity level (num ber) of steers

E F ST = Em ission factor for steers EM COWS- 99 Total =

W h e r e : EM COWS- 99 Total = Total NH3 em issions f r om cows, all c a tego rie s EM BC = 1999 Uncontrolled em issions from b e e f c o w s EM MC = 1999 Uncontrolled em issions from m i l k c o w s EM HF = 1999 Uncontrolled em issions from h e i f e r s

W h e r e : EM BC = EM MC = (AC BC * EF MC ) EM HF = (AC BC * EF HF ) EM ST = (AC BC * EF ST )

W h e r e : A C BC = Activity level (num b e r ) o f b e e f c o w s A C MC = Activity level (num ber) of m i l k c o w s A C HF = Activity level (num b e r ) o f h e i f e r s

E F BC = Em i s s i o n f a c t o r f o r b e e f c o w s E F MC = Em ission factor for m i l k c o w s E F HF = Em i s s i o n f a c t o r f o r h e i f e r s3.1.9.2 Hogs and Pigs SCC: 28 05 025 000 (Swine Com p o s i t e )

These anim als, and all livestock, are sources of ammonia e m issions due to the biological decom position of their waste products.

NH 3

186 Factor Conceptually, the m e thod for estim ating em issions from cattle is sim p le: count the nu mber of anim als, the n m u ltiply this by the av erage em issi ons per anim al, and the resulting va lue prov ides the em ission s. The CMU-NH3 Inventory (ve r sion 2.0) prog ram utilizes this app r oac h , a

m e thodology approved by the EPA for developing th e em issions inventory for other categories

Activity Activity levels were collected from the US DA Census of Agriculture data for 1997.

Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w :

Emission F a ctors and Source Livestock Category Em ission Source of Em ission Factor Hogs 9.2 Kg/ hog/ year Battye, et al. (1994) Pigs 9.2 Kg/ pig/ year Battye, et al. (1994)

Steers Description

Pollutant s

Method and Data Sourc es

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

Point Source Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e 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 f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

187 Equation:

1999 TPY a mmonia e m issions for swine in an individual county

EM SWI N E- 99 T o tal =

(AC PIGS * EF PIGS )

Spatial and Temporal Allocatio ns

Emission s C a l c u l a t i o n

1999 EM HO GS + 1999 EM PIGS

W h e r e : EM SWI N E- 99 T o tal = Total NH3 em issions f r om swine, all c a tego rie s EM HOGS = 1999 Uncontrolled em issions from h o g s EM PIGS = 1999 Uncontrolled em issions from p i g s

W h e r e : EM HOGS = (AC HOGS * EF HOGS ) EM PIGS =

W h e r e : A C HO GS = Activity level (num b e r ) o f h o g s A C PI GS = Activity level (num b e r ) o f p i g s E F HOGS = Em i s s i o n f a c t o r f o r h o g s E F PIGS = Em i s s i o n f a c t o r f o r p i g s3.1.9.3 Chickens (Pullets, Layers, and Broilers) SCC: 28 05 030 000 (Chickens Com p o s i t e )

Description

These anim als, and all livestock, are sources of ammonia e m issions due to the biological decom position of their waste products.

Pollutant s
NH 3

Method and Data Sourc es

188 Conceptually, the m e thod for estim ating em issions from cattle is sim p le: count the nu mber of anim als, the n m u ltiply this by the av erage em issi ons per anim al, and the resulting va lue prov ides the em ission s. The CMU-NH3 Inventory (ve r sion 2.0) prog ram utilizes this app r oac h , a

m e thodology approved by the EPA for developing th e em issions inventory for other categories

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

Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w :

Emission F a ctors and Source Livestock Category Em ission Factor Source of Em ission Factor Pullets 0.269 Kg/ pullet/ year Battye, et al. (1994) Layers 0.598 Kg/ layer/ year Battye, et al. (1994) Broilers 0.167 Kg/ broiler/ yea r Battye, et al. (1994)

Point Source Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e for this source category.Spatial and Temporal Allocatio ns Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s C a l c u l a t i o n Equation:

1999 TPY a mmonia e m issions for chic kens in an individual county

EM CHICK E NS -9 9 To tal

= 1999 EM PUL LET + 1999 EM LAYER + 1999 EM BROILER

W h e r e : EM CHICK E NS -9 9 To tal = Total NH3 em issions f r om chickens, all categ o r i e s EM PULL ET = 1999 Uncontrolled em issions from p u l l e t s EM LAYER = 1999 Uncontrolled em issions from l a y e r s EM BROILER = 1999 Uncontrolled em issions from b r o i l e r s

W h e r e : EM P U LL ET = (AC P U LL ET * E F P U LL ET ) EM LAY E R = (AC LAY E R * EF LAY E R ) EM BROILER

= (AC BROILER * EF BROILER )

W h e r e : A C PU LL ET = Activity level (num b e r ) o f p u l l e t c h i c k e n s A C L AYER = Activity level (num b e r ) o f l a y e r c h i c k e n s A C BROILER = Activity level (num b e r ) o f b r o i l e r c h i c k e n s E F P U LL ET = Em ission factor f o r pu lle t chick e ns E F LAY E R = Em i s s i o n f a c t o r f o r l a y e r c h i c k e n s E F BROILER = Em ission factor fo r br oile r chick e n s

1893.1.9.4 Sheep

190 SCC: 28 05 040 000 (Sheep Com p o s i t e )

Description

These anim als, and all livestock, are sources of ammonia e m issions due to the biological decom position of their waste products.

Pollutant s
NH 3

Method and Data Sourc es Conceptually, the m e thod for estim ating em issions from cattle is sim p le: count the nu mber of anim als, the n m u ltiply this by the av erage em issi ons per anim al, and the resulting va lue prov ides the em ission s. The CMU-NH3 Inventory (ve r sion 2.0) prog ram utilizes this app r oac h , a

m e thodology approved by the EPA for developing th e em issions inventory for other categories

Activity Activity levels were collected from the US DA Census of Agriculture data for 1997.

Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w :

Emission F a ctors and Source Livestock Category Em ission Factor Source of Em ission Factor Sheep 3.37 Kg/ sheep/ year Battye, et al. (1994)

Point Source Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e for this source category.Spatial and Temporal Allocatio ns Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s C a l c u l a t i o n Equation:

1999 TPY a mmonia e m issions for sh eep in an individual county

EM SHE E P = Total NH3 em issions f r om sheep, all c a tego rie s EM SHE E P

= AC SH EEP * EF SHE E P

W h e r e :

AC SH EEP = Activity level (num b e r ) o f s h e e p EF SHE E P = Em ission factor for sh e e p

191192 3.1.9.5 Goats (Angora and Milk) SCC: 2 8 0 5 0 4 5 0 0 1 ( G o a t s C o m p o s i t e )

Description

These anim als, and all livestock, are sources of ammonia e m issions due to the biological decom position of their waste products.

Pollutant s
NH 3

Method and Data Sourc es Conceptually, the m e thod for estim ating em issions from cattle is sim p le: count the nu mber of anim als, the n m u ltiply this by the av erage em issi ons per anim al, and the resulting va lue prov ides the em ission s. The CMU-NH3 Inventory (ve r sion 2.0) prog ram utilizes this app r oac h , a

m e thodology approved by the EPA for developing th e em issions inventory for other categories

Activity Activity levels were collected from the US DA Census of Agriculture data for 1997.

Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w :

Emission F a ctors and Source Livestock Category Em ission Factor Source of Em ission 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 Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e for this source category.Spatial and Temporal Allocatio ns Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s C a l c u l a t i o n Equation:

1999 TPY a mmonia e m issions for go ats in an individual county

W h ere: A C AG = Activity level (num ber) of angora goats

E F MG = Em ission factor for m i lk goats EM GOA TS-9 9 To tal

= 1999 EM AG + 1999 EM MG

W h e r e : EM GOA TS-9 9 To tal = Total NH3 em issions f r om goats, all c a tego rie s EM AG = 1999 Uncontrolled em issions from a n g o r a g o a t s EM MG = 1999 Uncontrolled em issions from m i l k g o a t s

W h e r e : EM AG = (AC AG * EF AG ) EM MG

= (AC AG * EF AG )

A C MG = Activity level (num ber) of m i l k g o a t s E F AG = Em i s s i o n f a c t o r f o r a n g o r a g o a t s

1933.1.9.6 Horses SCC: 2 8 0 5 0 3 5 0 0 0 ( H o r s e s )

Description

These anim als, and all livestock, are sources of ammonia e m issions due to the biological decom position of their waste products.

NH 3

Conceptually, the m e thod for estim ating em issions from cattle is sim p le: count the nu mber of anim als, the n m u ltiply this by the av erage em issi ons per anim al, and the resulting va lue prov ides the em ission s. The CMU-NH3 Inventory (ve r sion 2.0) prog ram utilizes this app r oac h , a

m e thodology approved by the EPA for developing th e em issions inventory for other categories

Activity Activity levels were collected from the US DA Census of Agriculture data for 1997.

Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w : Pollutant s

Method and Data Sourc es

Emission F a ctors and Source Livestock Category Em ission Factor Source of Em ission Factor
Horses 12.2 Kg/ horse/ year Battye, et al. (1994)

No subtraction of e m issions from point sources is necessary.

No controls are availab l e 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 Adjustment s

Adjustment for Controls

Spatial and Temporal Allocatio ns

194Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Equation: Emission s C a l c u l a t i o n

1999 TPY a mmonia e m issions for ho rses in an individual county

AC HORS E = Activity level (num ber) of horses EM HORSE = AC HORS E * EF HORSE

W h e r e : EM HORSE = Total NH3 em issions f r om horses, all c a tego r i e s

EF HORSE = Em i s s i o n f a c t o r f o r h o r s e s

1953.1.9.7 Ducks, Geese and Turkeys SCC: 28 05 035 001 (Ducks) SCC: 28 05 035 002 (Turkeys) SCC: 2 8 0 5 0 3 5 0 0 3 ( G e e s e )

Description

These anim als, and all livestock, are sources of ammonia e m issions due to the biological decom position of their waste products.

Pollutant s

196 Activity NH 3

Conceptually, the m e thod for estim ating em issions from cattle is sim p le: count the nu mber of anim als, the n m u ltiply this by the av erage em issi ons per anim al, and the resulting va lue prov ides the em ission s. The CMU-NH3 Inventory (ve r sion 2.0) prog ram utilizes this app r oac h , a

m e thodology approved by the EPA for developing th e em issions inventory for other categories

Activity levels were collected from the US DA Census of Agriculture data for 1997.

Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w :

Emission F a ctors and Source Livestock Category Method and Data Sourc es

Em ission Factor Source of Em ission Factor Ducks 0.117 Kg/ duck/ year Battye, et al. (1994) Geese 0.890 Kg/ duck/ yea r Battye, et al. (1994) Turkeys 0.858 Kg/ duck/ year Battye, et al. (1994)

No subtraction of e m issions from point sources is necessary.

No controls are availab l e for this source category. Point Source Adjustment s

Adjustment for ControlsSpatial and Temporal Allocatio ns

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 f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s C a l c u l a t i o n

1999 TPY a mmonia e m issions for du cks in an individual county

EM DUCKS =

EM DUCKS = Total NH3 em issions f r om ducks, all c a tego rie s AC DUC KS * EF DUCKS

W h e r e :

AC DUC KS = Activity level (num b e r ) o f d u c k s EF DUCKS = Em i s s i o n f a c t o r f o r d u c k s3.1.9.8 Agricultura l Fertiliz er Application

198 Although there are alm o st 200 different comm er cial fertilizers used in th e United States, roughly 13 of them a ccount for th e m a jority o f fertilizer u s e. Em ission factors for these 13 were obtain e d from Battye et al. (1994) and As m a n et al. (1992). Quantities of the rest of the fertilizers have been com b ined into a ‘m iscellaneo u s’ category
, and assign ed an em ission factor eq ual to the
average em i ssion factor for all m a jor fertilizers. The am ount of fertilizer in the ‘m iscellaneou s’ catego r y is typically less th an 3-4% of the tota l. SCC: 28 01 700 001 (Fertilizer Com posite)

Fertilizer applicati on is typically considered to be the s econd or third m o s t im portant source on a national level, depending on whether the inventor y includes soil em issions. Existing inventories usually estim ate the contribu tion f r o m f e rtiliz er a pplic ation to be 10-20% of the natio nal to tal. Substantial progress was m a de in improving spatial and temporal resolution of em i ssions in this catego r y.

Activity level data for fertilizer application ar e for 1995 from the Associat ion of Am er ican Plant and Food Control Officials (AAPFCO), which reports fertilizer sales to farm ers at the county level. Th is is an im provem e nt on som e existing i nvento r ies, which are ba sed on sale s of f

e rtiliz er to dealers rather than to far m er s. The deale r s m a y subsequently sell the f e r tilize r to f a r

m ers in other locatio ns, resulting in an ina ccu rate sp atial d i str i bution o f activity lev e ls. A better approxim a tion (in the absence of act ual application data) is to use sales from dealers to farm ers. The AAPFCO datasets contain coun ty-level reso lution for the top producing states for each crop (usually about 30 states), and st ate-level resolution for the othe r states. US GS also has countylevel reco rd s of fertilizer a pplication for years up until 1991. For states where th e AAPFCO dataset only contained state-level resolution, the USGS dataset was used to allocate the AAPFCO st ate-level data to county-level.

Finally, ammonia em issions from fe rtilizer application have a strong temporal com ponent that has previou s ly been igno red; yearly averages have been used in existing inventories. Signif i cantly m o re f e rtilizer is app lie d in th e spring and fall than in the summer and winter, corresponding to crop cycles. To im prove tem poral allocation, USDA data on crop planting tim es and fertilizer app l ication tim es and rates we re used to generate a m o nthly distribution of fertilizer application (U SDA, 1997; USDA-ERS, 1991; US DA-ERS, 1996; USDA-ERS, 1996- 1997; USDA-NASS, 1992-1997a; U S DA- NASS, 1992-1997b; USDA-NASS, 1992-1997c; USDA-NASS, 1992-1997d; USDA- NASS, 1992- 1997a; USDA-NASS, 1995; USDA-NASS, 1997). Results show that assum i ng a yearly average for this category results in a substantial error for m o st m o nths of the year.

NH 3 Description:

Pollutant sConceptually, the m e thod for estim ating em issions fr om m obi le sources is sim p le: collect data on the am ount of fertilizer sold to fa rm ers in a specific county, then m u ltiply this by th e per cen t of ammonia released per fertilizer application, and the resulting va lue prov ides the em issions. The CMU-NH3 Inventory (v ersion 2.0 ) p r ogram u tilizes th is approach, a m e thodology app r oved by the EPA for developing the em issions inventory for other categories.

199 Emission F a

ctors

Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e below:

Em ission Factor Activity Activity lev e ls, am ount of fertilizer sold to farm ers per coun ty, were co llected from the Association of Am erican Plant a nd F ood Control Offi cials (AAPFCO).

Emission F a ctors and Source

Fertiliz er Ty p e Per Cent NH 3 Released to the Atm o s p h e r e 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 a mmonium 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 Sourc es

Point Source Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio nsSpatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

Temporal Finally, ammonia em issions from fe rtilizer application have a strong temporal com ponent that has previou s ly been igno red; yearly averages have been used in existing inventories. Signif i cantly m o re f e rtilizer is app lie d in th e spring and fall than in the summer and winter, corresponding to crop cycles. To im prove tem poral allocation, USDA data on crop planting tim es and fertilizer app l ication tim es and rates we re used to generate a m o nthly distribution of fertilizer application (USDA, 1997; US DA-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-NAS S, 1992-1997a; USDA-NASS, 1995; USDANASS, 1997). Results show that assum i ng a year ly average for this category results in a substantia l e rror for m o st m onths of the year.

Emission s C a l c u l a t i o n Equation:

1999 TPY a mmonia e m issions for agricultural fe rtilizer sources in an individual county

EM FE RT- 99 T o tal = EM Am m N i t + EM Am m S ul + EM Am m T hi o + EM CalAm m Nit + EM NitS ol + EM Ure a + EM DiAm m P hos + EM M onoAm m Phos + EM L i qAm m Phos + EM PotNit + EM Misc + EM Mix

W h e r e : EM MOBI LE -9 9 To tal = Total NH3 em issions f r om agricultura l f e rtiliz er applica tio n, all c a tego r i e s EM Am m N i t = Em issions f r om Am m onium Nitrate f e r t i l i z e r EM Am m S ul = Em issions from A mmoni um S u l f a t e f e r t i l i z e r EM Am m T hi o = Em issions f r om Am m onium Thiosulf ate f e rtilize r EM CalAm m Nit = Em issions f r om Calcium Am m onium Nitra t e f e rtilize r EM NitSol = Em issions f r om Nitrogen Solutions f e rtiliz e r EM Urea = Em issions f r om Urea f e r t i l i z e r EM DiAm m P hos = Em issions from Dia m m o nium P h o s p h a t e f e r t i l i z e r EM M onAm m Ph os = Em issions from Monoammonium P h o s p h a t e f e r t i l i z e r EM L i qAm m Phos = Em issions from Liquid Ammonium P o l y p h o s p h a t e f e r t i l i z e r EM PotNit = Em issions f r om Potassiu m Nitrate f e rtiliz e r EM Misc = Em issions from M i s c e l l a n e o u s f e r t i l i z e r EM Mix = Em issions from M i x e d f e r t i l i z e r

W h e r e : EM Am m N i t = (AC Am m N i t * Per Cent Released Am m N i t ) EM Am m S ul = (AC Am m S ul * Per Cent Released Am m S ul ) EM Am m T hi o (AC A mmTh i o * Per Cent Released Am m T hi o ) EM CalAm m Nit = (AC CalA m m Nit * Per Cent Released CalAm m Nit ) EM NitSol = (AC NitSol * Per Cent Released NitSol ) EM Urea (AC Urea * Per Cent Released Urea )

200EM DiAm m P hos = (AC DiA m m P ho s * Per Cent Released DiAmmPhos )

EM M onAm m Ph os = (AC M onAm m P hos * Per Cent Releas ed

M onAm m Phos ) EM L i qAm m Phos = (AC L i qA m m Ph os * Per Cent Released L i qAm m Phos ) EM PotNit = (AC PotNit * Per Cent Released PotNit ) EM Misc (AC Misc * Pe r Cent Released Misc ) EM Mix = ( A C Mix * Pe r Cent Released Mix )

W h e r e : A C Am m N i t = Activity level (am ount of Ammonium Nitrat e fertilizer

a p p l i e d p e r c o u n t y ) Per Cent Released Am m N i t = P e r C e n t o f N H 3 r e l e a s e d d u r i n g f e r t i l i z e r ap p l i c a t i o n

2013.1.9.9 Human Breath and Perspiration SCC: 28 10 010 000 (Hum a n P e r s p i r a t i o n )

Description
Ammonia em issions from hum a n br eath and perspiration comprise a few percent of the national ammonia em ission inventory.

Pollutant s
NH 3

Method and Data Sourc es Conceptually, the m e thod for estim ating em issions from hum a n breathe and perspiration is sim p le: count the num ber of people, then m u ltiply this by the average em i ssions per p e rson, and the resu lting value prov ides the em issions. The CMU-NH3 Inventory (version 1.2) program utilizes this approach, a m e thodology approve d by the EPA for developing the em issions inventory for other categories.

Activity The US Census (U.S. Census Bureau, 1999) was used to obtain activity level data for this catego r y.

Emission F a

ctors Em ission factors were collected from a paper published by Battye, et al. in 1994 and are presented in the tab l e b e l o w :

Emission F a ctors and Source

Em ission Category Em ission Factor Source of Em ission Factor
Hum a n Breathe and Perspiration 0.44 Kg / person/ year Battye, et al. (1994)

Point Source Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial The activity data was collected at a county-level. No other method to spatially profile the source category was used.

202Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s C a l c u l a t i o n Equation:

1999 TPY a mmonia e m issions from hum a n breathe and perspirati on in an individual county

AC HU MA N = Activity level (num ber) of people per county EM HUM AN B & P = AC HU MA N * EF HU MAN B & P

W h e r e : EM HUM AN B & P = Total NH3 em issions from hum a n b r e a t h e a n d p e r s p i r a t i o n

EF HU MAN B & P = Em ission factor for hum a n b r e a t h e a n d p e r s p i r a t i o n

203

## 4.0 NONR O AD SOUR CES

4.1 NONROAD VEHICLES/ENGINES

204 This section contains the nonroad source em i ssion inventory for volatile organic com p ounds (VOCs), nitrogen oxides (NOx), and carbon m o n oxide (CO) and if po ssible carbon dioxide (CO 2 ), sulfur oxides (SO X ), particulate m a tter (P M), amm oni a (NH3), and toxic air pollutants. Nonroad m o bile sources include m o torized ve hicles and equ i pm ent that are norm a lly not operated on public roadways to provide transporta tion. For nonroad m o bile sources, the source catego r ies o f interes t ar e airc raf t , loc o m o tives, m a rine v e sse ls and the sou r ce typ e s inc l uded in EPA’s NONROAD m o del. Nonroad mobile sources are brok en up into th e following catego r ies :

• construction equipm ent

• general aviation • lawn and garden equipm ent

• airport service equipm ent

• logging equipm ent

• recreational m a rine equipm ent

• light comm e r cial equipm ent

• industrial equipm ent

• agricu ltu ral or farm equipm ent

• recreational land vehicles or equipm ent

• railroads

• com m e rcial aviation

• air taxis

• m ilitary avia tion

• com m e rcial m a rine vessels

The Departm e nt used two m e thodologies a pproved by the E P A for developing the 2002

em issions inventory for nonroad categories. One of the m e t hodologies used consisted of

em ploying EPA’s NONROAD Em i ssion Inventory Model 103 . In a m e m o ra ndum 104 , dated June 16, 2003, EPA allowed the use of the draft NONRO AD Model and associated default inputs in the developm ent of inve ntories supporting St ate Im ple m entation Plans (S IPs). The second

m e thodology entailed the use of EPA e m i s s i o n f a c t o r s

.

103 N ONR OA D 2 00 5
104 USEPA Memo rand u m , d a ted Ju ne 1 6
, 2 003
, fro m Gen e Tiern e y o r th e Air Quality an d Mod e ling Cen t ery an d Lei l a H. C o o k of t h e T r a n sp o r t a t i on a n d R e gi o n al P r o g ra m s Di vi si on; t o R e gi o n al M o bi l e So u r ce P r og ram M a nage s and Staff.4.2 NONROAD MODEL

205 As stated previously, the 2002 em issions estim ate for all nonroad equipment categories listed above except comm ercial m a rine, railroad locomotives, and aviation em issions were determ ined by running EPA’s NO NROAD MOBILE Model, as suggested by EPA guidance. The m odel includes m o re than 80 basic and 260 specific types of nonroad equipm ent, and further stratifies equipment t ypes by horsepower rating. Fuel t ypes include gasoline, diesel,

com p ressed natural gas (CNG), and liquefied petroleum gas (LPG).

The NONROAD model consists of three separa te com ponen t s: a graphical user interface written in Visual Basic, the core m odel writte n in Fortran, and a repor ting utility wr itte n in Microsof t A CCESS. The insta ll u tility supplie d w ith th e m odel eas ily in sta lls a ll three

com ponents of the m odel onto a personal com puter.

The prim ary purpose of the user in terface is to p r ovide the u s er with an easy m e thod to specify the options for a model run. W ith si m p le W i ndows-type screens and pull-down

m e nus, the user can quickly set up, execute, and view a m ode ling sc enario. Once the model options are s p ecified, th e user can then run the Fo rtran core m odel from within the in terface, and then can m ove directly to th e rep o rti ng u t ility to view and sum m a rize the m odeling results.

The core m o del of NONROAD, written in For t ra n, contain s a ll of the a l go rithm s used by the model for calculating em issions estim ates. The co re m odel can be operated as a stand-alone application; however, as a st and-alone application it require s som e basic knowledge of the DOS operating system . Also, note that while th e user in terface runs the core m odel for one specified s e t of condition s , it cannot run m u ltiple runs in batch m ode. Multip le run s can be perform e d by creating and running a batch file in DOS or in a DOS window in a W i ndows 3.1 or 95 environm ent.

The repor tin g utility, wr itten us i ng Microsoft’s ACCESS database so ftware, is used to create standardized reports using output data generated in the core m odel. Like the graphical user interface, th e reporting u tility is a fully operation a l W i ndows program , wi th pull-down m e nus, designed as a separate m odule in order to take advantage of the m a ny reporting and for m atting options available when using a databa se application. Although the reporting utility is written in ACCESS, it is a st and-alone application, and you do not need to know how to use ACCESS to genera te rep o rts.

The NONROAD model estim ates em issions for si x exhaust pollutants: hydrocarbons (HC), NOx, carbon m onoxide (CO), carbon dioxide (CO 2 ), sulf ur o x ides (SO X ), and PM. The user selects am ong five different types for reporti ng HC — as total hydroc arbons (THC), total organic gases (TOG), non-m e thane organi c gases (NMOG), non-m e thane hydrocarbons (NMHC), or volatile organic com pounds (VOC). Pa rticulate m a tter can be reported as PM of 10 m i crons or less (PM 10 ) or PM of 2.5 m i crons or less (PM 2. 5 ). The m odel also estimates

em issions of non-exhaust HC for four m ode s — diurnal, refue ling spillage, vapor displacem ent, and crankcase em issions. All em i ssions are reported as short tons (i.e., 2000 lbs).

The NONROAD model estim ates em issions for each specific type of nonroad equipm ent by multiply ing the followin g input data estim ates:• Equipm ent population for base year (or base year population grown to a future year), distributed by age, power, fu el type, and application;

• Average load factor expressed as av erage fraction of available power;

• Available power in horsepower;

• Activity in hours of use per year; and

• Em ission factor with deterior ation and/or new standards.

The em issions are then tem porally and geograp h i cally allocated using appropriate allocation factors.

There are several input f iles that provide nece ssary inform ation to cal culate and allocate

em issions estim ates. These input files correspond to the basic data n eeded to provide the calculations: em ission factors, base year equi pm e n t population, activity, load factor, average lifetim e, scrappage function, growth estim at es, and geographic and tem p oral allocation. Default valu es are p r ovided for all input files. T h e user can replace the d e fault data files when bette r inf o r

m ation becom e s available, eith er f r o m EPA f o r nationa l def a

ults or f r om local sources for locality-specific data. The input files ar e also m odifiable to test control strategies. MDE input files that dif f er from the EPA na tional defaults are pres ented in Section 4.7 – NONROAD Model Appendices.’

Input parameters for the nonroa d Model are listed below:

Parameters: 2002 B NAA

- M D Min. Temp. 65.55 Max. Temp. 87.6 Avg. Temp. 76.8 R V P 6

. 6 O2 % 2 Gas Sulfu r % 0.0162 LPG/CNG Su lfur % 0.003 Die s el Sulfur% 0.2283 Marin e Die s el Sulfur % 0.2638 Stage II Control % 0

Details of this m odel can be found in its user guide nam e d “User’s Guide for the EPA Nonroad Em issions Model Draft NONROAD 2002” (EPA420-P-02-013 ; Decem ber 2002) available fro m the EPA.

2064.2.1 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 equ i pm ent inclu d es a variety of types of m achinery used in th e mainten a nce of lawns and gardens. E x am ples of t h e type s of equipm ent included in this category are trim m e rs/ed g ers/b r ush c u tte rs, lawn m o wers, lea f blowers, rear engine riding m o wers, front mowers, chainsaws (<4H P), shredders (<5HP), t illers (<5HP), lawn and garden tractors, wood splitters, snow blowers, chippers /stu m p grinders, com m e rcial turf equipment, and other lawn and garden equipm ent. Em issions result from opera tion of the internal com b ustion engines that power the equipm ent.

Pollutant s
PM 10 , PM 2. 5 , S O x , N O x , C O
, V O C

Method and Data Sourc e s

Data sources

A. " User’s Guide for the E P A Nonroa d Em issions Model Draft NONROAD 2002" prepared for EPA by ENVIRON Internationa l Corporation under EPA Contract No. DW 47926801 dated Decem ber 2002. This repo rt, EPA420-P-02-013, constitu tes th e User’s Guide to the NONROAD mo del. Th e report contains an overview of the model, equipm ent types, pollutants reporte d, geographic an tem poral coverage, the model com p onents, m o del inputs, and output options. The guide docum ents how to insta ll and r un the m odel and the ass o ciated repo rting u t ility.

B. http://www.epa.gov/om s/nonrdm dl.htm

Methods so urces Based upon EPA's requirem e nts for determ ining nonroad em issions, the D e partm e nt ran the NONROAD m odel to determ ine the em issi on estim ate for 2002. MDE-ARMA o p ted to choose seasonal (Spring, Summ er , Fall, W i nt er) period totals as th e output files from the m odel. These period totals were divide d by the num ber of days in a season to reflect
an averag e d a ily em issio n level for each season.

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

The NONR OAD model autom a tically applies cont rols, when applicable , for a given year.

207Spatial and Temporal Allocatio ns Spatial The NONROAD model spatially allocates equipm ent popula tions through the REGION data pack et and the em issions th rough the ALLOC data packet.

The REGION input file specifies the state or county to m odel. W h en you initially install the NONROAD m odel, you are prompted to iden tify the state where you are located. This step sets up the population and allocati on factor data files for your state.

The ALLOC input file defines the spatia l allocation files read by the m o del.

Temporal The NONR OAD model tem porally allocates activity to the differenent seasons through the SEASONALITY, MONTHLY, and DAILY data packets.

208 The first temporal allocation, identified by the p acket identifier /MONTHLY/, provides the monthly adjustm e nt factors used by the m odel to calculate the frac tion of annual activity occurring in the given m onth. For periods l ong er than a s i ngle m onth (e.g. season), the factors from each m onth spanned by the peri od are summ ed. The second, identified as /DAILY/, provides the day-of-the-week ad justments. The weekend and weekday allocations should sum to one for an entire week (i.e. 1 = 5 × weekday fraction + 2 × weekend fraction )

.

The seasonal and m onthly activity alloca tion fractions for th e NONROAD engine

em issions modeling is further do cumented in Rep o rt No. NR-004, dated Decem ber 9, 1997. The weekday and weekend day tem porat l allocation of activity in the NONROAD model is further docum ented in Report No. NR-015 105

, d a t e d M a r c h 3 1
, 1 9 9 9

.

Emission s Calculation The NONROAD calculations rely on em ission factors--estim ates of the am ount of p o llution

em itted by a particula r ty pe of equipm ent during a unit of use

. Typically, em ission f actors f o r nonroad sources are reported in gram s per horse power-hour (g/hp-hr), but they also may be reported in gram s per m ile, gram s per hour, and gram s per gallon. These em ission factors are stored in NONROAD’s data input files. NONROAD adjusts these em ission factors as necessary
to accoun t for the effects of fuel sulfur. Em ission changes with the age of the engin e , often called ‘dete r io ratio n ,’are also a pplied by th e m odel. The core m odel of NONROAD, writte n in Fortr a n, contain s all of the algorithm s used by the m odel for calculating em issions estim ates u s ing the input file listed above.

105 N o n r o a d En gi ne Em i ssi on M odel i n g Team , Assessm ent an d M o del i n g Di vi si o n , E P A
, O ffi ce of M o bi l e So ur ces4.3 RAILROADS SCC: 22 85 002 005 (Line Haul) SCC: 22 85 002 010 (Yard Engines)

Description
Railroad loc o m o tives us ed in the Un ited States a r e prim arily of two types: electric and dieselelectric. Electric locom o tives are po wered by elec tricity generated at sta tionary power plants. Em issions are produced only at the electrical generation plant, whic h is considered a point source and therefore not included here. Diesel-elect ric locom o tives, on the other hand, use a diesel engine and an alternator or ge nerator to produce the electricity required to power its traction motors. Emissions produced by these diesel e ngines are of interest in em i ssion inventory developm ent. Other sources of em issions from railroad oper a tions inclu d e the sm all gasolin e and diesel engines used on refriger ated and heated rail cars. Th ese engin e s are therm o statically controlled, working independent ly of train m o tive power, and fall in the category of nonroad equipm ent, addressed elsewhere in this docum ent.

209 Locom o tives can perform two differ e nt types of operations: Line Ha ul (SCC: 2285002005) and Yard (SCC: 2285002010). Line haul locom o tives, which perfor m the line haul operations,
genera lly tra v el between distan t loc a tions, such as f r om one city to ano t her

. Yard loco m o tives, which perform yard operations, are prim arily res ponsible for m oving railcar s within a particular railway yard.

7. Maryland Midland R a ilway, Incorporated

11. W i nchester and W e stern Railroad Com p any Pollutant s PM, SOx, NOx, CO, VOC

Method and Data Sourc es:
The f o llowing thir teen r a ilroad com p anies ope ra te in Maryland and were asked to provide the

am ount of fuel used in 2002, and the distribut ion of the com p any's track m ileage by Maryland County: 1. AMTRAK (National Railr oad Passenger Corporation) 2. Canton Railroad Company 3. W h eeling & Lake Erie Railway Com p any 4. CSX Tra n sportation, Incorporated 5. Eastern Shore Railro ad, Incorpo r ated 6. Marylan d & Delawa re Railroad Com p any

8. Norfolk and Southern Railway Com p any 9. Patapsco & Back Riv e rs Railroad Com p any 10. W e stern Maryland S cenic Railroad

12. MARC ( U nder the Maryland T r ansit Adm i nistration) 13. W a lkersville Southern Railroad

For CSX and Norfolk railroad operating statistics contained in R-1 reports obtained from the Surface Transportation Board under the Office of Econom i cs, Environm e n tal Analy s is and Adm i nistration were used to add in estim ating the am ount of fuel used within the state.MDE receiv e d fuel usag e and track m ileage data from all the railroads. F u el usage w a s proportioned to each co unty by the am ount of tr ack m iles each com p any utilized in a county.

Activity A survey of railroad petroleum consum ption and track m ileage was conducted.

Emission F a

ctor Em ission f actors wer e o b tained f r o m the EPA' s Procedures for Emission Inventor y 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

SO 2 em issio n s were calculated b a sed on a s u l f u r c o n t e n t o f 0

. 2 5 % b y w e i g h t

.

EPA estim ates tha t yard locom o tives operate 365 days per year (assum ing that when a yard engine is tak e n in for rep a irs it is rep l aced dur ing this period ) and consumes an averag e of 228 gallons per day.

Point Source Adjustment s
No subtration of e m issions fr om point sources is necessary.

Adjustment s for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns

Em ission estim a tes are based on fuel consum p tion. Com p any supplied s t ate to tal f u e l usage was allocated to the county level by the pr opotion of track m iles used in a particular county.

Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.Emission s Calculation

211 G CTY = When specific county inform ation was not provi ded, the following equations were used to

com pute the am ount of fuel consum ed by each railro a d in each Maryland County.

M CTY M ST * G ST

G CTY = am ount of total fuel used in gallons by the company in the county W h ere:

M CTY = m ileage of com p a n y t r a c k s i n t h e c o u n t y M ST = m ileage of com p any tracks in the s t a t e G ST = am ount of total fuel used in g a l l o n s b y t h e c o m p a n y i n t h e s t a t e

The following equation was used to calcu late the em issions for lin e haul locom o tives from each railroad com p any operating in a county.

Fuel CTY x EF LH E L H – i – C T Y j = 2000 x 365

W h ere:

E L H – i – C T Y j = Em issions from line haul railroad locom o tives for pollutant i in County j Fuel CTY j = Total am ount of fuel consum ed by every railroad operating in the

c a l c u l a t e d c o u n t y Fuel CTY j = (G cty1 + G ct y2 + ... + G cty12 ) EF LH = line hau l loc o m o tive em i s s i o n f a c t o r f o r a g i v e n p o l l u t a n t

The following equation was used to calcu late th e em issions for yard lo co motives fro m each railroad com p any operating in a county.

N YL – i – CT Y j x 228 x EF YL E YL – i – C T Y j = 2000 W h ere:

E YL – i – C T Y j = Em issions from yard locom o t i v e s f o r p o l l u t a n t i i n C o u n t y j N YL – i – CT Y j = num b er of yard locom o tives operated by each railroad com p any in

c o u n t y j N YL – i – CT Y j = (N cty1 + N ct y2 + ... + N cty12 ) EF YL = Yard locomotive em i s s i o n f a c t o r f o r a g i v e n p o l l u t a n t212 Sam p le Calc ulations:

AMTRAK, CSX, and M A RC operated line haul lo com o tives in the coun ty. AMTRAK also operated one yard (switcher) locomotive in the county.

Am ount of fuel used in gallons used by CS X Tra n sportation line haul locom o tives in Montgom ery County:

514.97 track m iles in the state for CSX 2002 Montgom e ry County Em issions

Line Haul Emission E s tima te

Am ount of fuel used in gallons by A M TRAK’s line haul locom o tives in Montgom ery County:

G cty1 = 25,463.8 gallons used in Montgom ery Co. per year by AMTRAK (inform a tion provided by AMTRAK)

36.37 track m iles in Montgom ery Co. for CSX G cty4 = x 10,512,431.53 gallons used in state per
year

G cty4 = 742,445.45 gallons used in Montgom e ry Co. pe r year by CS X

Am ount of fuel in gallons used by MARC line haul locom o tives in Montgom e ry county:

28 track m i les in Montgom e ry Co. for MARC G cty12 = 156 track m iles in the state for MARC x 1,782,750 gallons used in state per year

EM VOC = (2000 lbs. per ton) * (365 days per year)

G cty12 = 319980.77 gallons used in Montgomery Co. per year by MA RC

VOC Emissions from line haul lo comotives in Montgom ery County:

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.0213 lbs. VOC / g a l

0.0316 tons VOC / day EM VOC =

NOx Em issions from line haul lo comotives in Montgom ery County:

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.4931 lbs. NOX / g a l EM NOX = (2000 lbs. per ton) * (365 days per year)

EM CO = EM NOX = 0.7348 tons NOX / d a y

CO Em issions from line haul lo com o tives in Montgom ery County:

(25,463.8 gal / yr + 742,445.45 gal / yr + 319980.77 gal / yr ) * 0.0626 lbs. CO / g a l (2000 lbs. per ton) * (365 days per year)

EM CO = 0.0933 tons CO / d a yYard Loco motive s Emiss i on Estima te

CSX operated 2 yard locom o tives in Montgomery County:

213 VOC Emissions from yard locom o tives in Montgom e ry County:

(2 engine * 228 gallons per e ngine per day * 0.0509 lbs. VOC / g a l l o n ) EM VOC = (2000 lbs. per ton)

EM VOC = 0.0116 tons VOC / d a y

NOx Em issions from yard locom o tives in Montgom e ry County:

(2 engine * 228 gallons per e ngine per day * 0.5044 lbs. NOX / g a l l o n ) EM NOX = (2000 lbs. per ton)

EM NOX = 0.1150 tons NOX / d a y

CO Em issions from yard locom o tives in Montgom e ry Count y:

(2 engine * 228 gallons per e ngine per day * 0.0894 lbs. CO / gallon ) EM CO = (2000 lbs. per ton) EM CO = 0.0204 tons CO / d a y

Total Emissions

Em issions from m a intenance equipm ent used in the switching yards was calculated using the EPA’s Non-Road Model and then adde d for the appropriate county. Exam ple e m issions for Montgom ery county: 0.0013 tons VOC / day, 0.0005 tons NOx / day, 0.0518 tons CO / day

Total CO Em issions for Montgom ery county: Total VOC Em i s s i o n s f o r M o n t g o m e r y c o u n t y : Em is VOC = 0.0316 tons / day from line haul + 0.0116 tons / day from yard + 0.0013 tons VOC / day from EPA Non-Roa d M o d e l

. Em is VOC = 0.0445 t o n s V O C / d a y

Total NOx Em i s s i o n s f o r M o n t g o m e r y c o u n t y : Em is NOx = 0.7348 tons / day from line haul + 0.1150 tons / day from yard + 0.0005 tons NOx / day from EPA Non-Roa d M o d e l

. Em is NOx = 0.8503 t o n s N O x / d a y

Em is CO = 0.0933 tons / day from line haul + 0.0204 tons / day from yard + 0.0518 tons CO / day from E P A N o n

- R o a d M o d e l

. Em is CO = 0.1655 t o n s C O / d a y4.4 AIRCRAFT SCC: 22 75 020 000 (Comm e rcial Aircraft) SCC: 22 75 050 000 (General Aviation) SCC: 22 75 001 000 (Military Aviation)

Description:

214 This category includes three sub- cate gories identif ied as: com m e rcial air c r a f t , genera l aviation, and m ilitary airc raf t . Com m e rcial a i r c raf t ar e use d in regu lar l y scheduled f lights trans porting passengers, freight, or both. General aviation, w h ich includes air taxis and commuter aviation, is used for recreational flying, business travel, persona l transportation, and vari ous other activities. Milita ry aviation is the operation an d activ ities o f m ilitary a i r c raf t at airpo r ts in Mary land.

1) Pollutant s
PM 10 , PM 2. 5 , S O x , N O x , C O
, V O C

Method and Data Sourc es ARMA used a variety of sources for data and em ission calculation m e thods as follows:

D

a

t

a s o

u

r

c

e

s Airport Activity Sta tis tic s of Certif ic ated Route Air Carriers published by Federal Aviation Ad m i nistration for the 12 months endin g Decem ber 31,2002, pp 7-314 to 7- 3 2 0

. 2) This repor t lists tota l dep a rtures perform e d for commercia l air carriers and individu al
t ypes of commerci a l ai rcraft

. 3) Landing and takeoff cycle inform ation by airport for 1995/2002 from the Maryland

4) Aviation Adm i nistration and the Federa l Aviation Adm i nistration Airport L i cense Renewal Applica tions. The applic ations li sts LT O cycles by airc raft operation type f r om all gen e ral avia tion airpor ts, M a rtin State Airpor t which has gener a l, and Baltim ore/W a shington Intern ational Airport f o r the pas t 12 m onths.

Methods so u

r

c

e

s 1) For general aviation ARMA us ed em ission factors supplied in Procedures for Em ission Inventory Preparation, Volum e IV: Mobile Sour ce s , EPA’s Office of Mobile Sources, 1992. This source pr ovided em ission factors for specific commercial engine typ e s , and alternative flee t av erage facto r s for general aviation, air taxis, and co mmuter airc r a f t

. 2) For m ilitary airc raf t ARMA used a c o m posite f actor f r om section 5.2.5, Table 5-7 of Procedures f o r Em ission Inventory P r eparation, V o lum e IV: Mobile Sources , 1988. This m e thod required ARMA to collect LTO data rather than specifi c aircraft data. ARMA also used this com posite factor m e thod in its 1990 baseline inventory. For the f i nal 200 2invento r y ARMA has requested op eration data f r om m ilitar y airc raf t by operation type from Maryland Arm y , Navy, and Air Force base environm ental

s u p p o r t o f f i c e s

.215 3) For comm er cial aviation ARMA used FAA’s EDMS 106 em issions m odel and databases. E D MS is designed to assess th e air quality im pacts of airport em ission sources, particularly aviation sources, which consist of aircraft, auxiliary power units, and ground support equipm ent. EDMS features the latest aircra ft engine em ission f actors f r om the In terna t ional Civil Avia tion Organization (ICAO) Engine Exhaust Em issions Data Bank, vehicle em issi on factors from EPA M O BILE 5a, and EPAvalidated dispersion algorithm s . Aircraft activity includes landside and airside operations. EDMS defines four distinct m odes of aircraft operation based upon EPA and FAA guidance : appr oach, tax i/id le, tak e of f

, and clim b out. Together, these f our modes constitute one Landing and T a keoff ( LTO) cycle. EDMS calcu lates aircraft

em issions based on these four m o d e s

. 4) For all aircraft types, ARMA used a de fault m i xing height value of 3,000 feet above ground level. The m i xing height is the laye r of air where airplane em ission affect ground level em ission concentrations. A bove the m i xing level, pollutants are transpo r ted away accord ing to sectio ns 5.2. 2 of the 1992 Procedures. Because of the

m i xing height, ARMA assigned all aircraft em issions from a particular airport to the county where that airport was located. W e assumed no seasonal va riation and a seven day per wee k activ ity le vel.

Point Source Adjustment s
No subtraction of e m issions from point sources is necessary.

Adjustment for Controls

No controls are availab l e for this source category.

Spatial and Temporal Allocatio ns Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source.
Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

106 Em issio n s & D i sp er sion M o d e lin g System ( E D M S) V e rsio n 3.2 fo r W i nd ow s f r o m CSSI
, In c.4.4.1 Commercia l Aircra ft

216 (SCC: 22 75 020 000)

Steps in Creating and Airport Em ission Inventory in EDMS:

1) Open the EDMS m odel and create a new st udy for the airport in question. Enter the
param e ters (nam e, m i xing height, av erage yearly tem p erature, and units o f m easurement) that are specific to each airpo r t in to the study. 2) Provide EDMS with inform ation to com put e the em issions inventory. B e gin by m a tching engines with aircraft and assigni ng them to the study. Select th e aircraft to be used in the study (data that is collected from the airport) by picking the aircraft nam e from the m e nus. EDMS autom a tically as socia t es spe c if ic aircr a f t with cer tain engine typ e s. 3) For each a i rcraft fill in the yearly LTO cycles p r ovided by s u rveying the airport. 4) For each aircraft fill in the averag e annual ta x i tim e and queue tim e specific to the airp ort or use the EDMS provide default values. 5) Continue to add each aircraft/eng ine type, LTO cycle, taxi tim e and queue tim e to the study. 6) EDMS has tables bu ilt into the m odel tha t asso c i ate air c raf t type with the num b er of engines, auxiliary power units and ground support equipm ent. The model also a ssigns default values for Takeoff Tim e (typically 0.3 m i nutes), Clim bout Tim e (typically 5 m i nutes), and Approach Tim e (typically 6 m i nutes). 7) If e m issions from parking lots, roadways, st ationary sources, and training fires are also required, complete the dialog boxes associated w ith each of these subcategories. 8) Run the EDMS em ission inventor y program and view the results.

Emission s Calculation

The f o llowing calcu lation airc raf t o p erating at Baltim ore/W a shington Intern ational Airport in Anne Arundel County during 1998. Tabled below is the aircraft, engine a ssigned to the aircraft, tim e for each m ode of operation, an nual LTO ope rations, av erage annu al taxi tim e, and the
average ann u al queue tim e

.

Aircraft Nam e Aircraft Ty pe Eng i ne Assigned Appr oach Time (min) Climbout Time (min) Ta keo f f Time (min) Ann u al LTO T axi Time (min) Queue Time (min) Fal c on 1 0 0 GA TFE7 3 1

- 3 1. 60 0. 50 0. 40 18 2 5 10 .5 0 3

. 0 0 P-3 3 7 P Sky m ast e r GA TSI O

- 3 6 0 C 4. 50 2. 50 0. 50 94 9 0 10 .5 0 3

. 0 0
55 0 C i t a t i on GA JT1 5 D

- 4 (B ,C
, D ) 1. 60 0. 50 0. 40 21 9 0 10 .5 0 3

. 0 0 A3 2 0 C o m m C F M 5 6

- 5B 4 4. 00 2. 20 0. 70 25 5 5 10 .5 0 3

. 0 0 AH-1 M i l i t a r y T53

- L

- 1 1 D 6

. 8 0 6

. 8 0 0

. 0 0 1 825 1 0 .50 3 .0 0 ATR 4 2 C o m m P W 12 0 4. 50 2. 50 0. 50 21 9 0 10 .5 0 3

. 0 0
B 7 2 7

- 1 0 0 C o m m JT8 D

- 7 A 4. 00 2. 20 0. 70 80 3 0 10 .5 0 3

. 0 0
B 7 3 7

- 2 0 0 C o m m JT8 D

- 1 5 A 4. 00 2. 20 0. 70 21 9 0 0 10 .5 0 3

. 0 0
B 7 3 7

- 3 0 0 C o m m C F M 5 6

- 3B 4. 00 2. 20 0. 70 13 1 4 0 10 .5 0 3

. 0 0
B 7 3 7

- 4 0 0 C o m m C F M 5 6

- 3B 4. 00 2. 20 0. 70 36 5 0 10 .5 0 3

. 0 0
B 7 3 7

- 5 0 0 C o m m C F M 5 6

- 3B 4. 00 2. 20 0. 70 80 3 0 10 .5 0 3

. 0 0
B 7 3 7

- 7 0 0 C o m m C F M 5 6

- 3C

- 1 4. 00 2. 20 0. 70 73 0 10 .5 0 3

. 0 0
B 7 4 7

- 1 0 0 C o m m JT9 D

- 7 A 4. 00 2. 20 0. 70 18 3 10 .5 0 3

. 0 0
B 7 5 7

- 2 0 0 C o m m P W 20 3 7 4. 00 2. 20 0. 70 76 6 5 10 .5 0 3

. 0 0B 7 6 7

- 2 0 0 C o m m C F 6- 8 0 A ( A 1 ) 4. 00 2. 20 0. 70 10 9 5 10 .5 0 3

. 0 0
B A E ATP C o m m PT6 A

- 4 5 4. 00 2. 20 0. 70 25 5 5 10 .5 0 3

. 0 0
B H

- 1 9 0 0 C o m m PT6 A

- 6 5B 1. 60 0. 50 0. 40 32 8 5 10 .5 0 3

. 0 0 C-12 A / B / C M i l i t a r y PT6A-41 3

. 5 0 0

. 8 0 0

. 4 0 7 3 0 1 0 .50 3 .0 0 C-13 0 Hercu l es Military T56

- A-16 5

. 1 0 1

. 2 0 0

. 4 0 3 6 5 1 0 .50 3 .0 0 C

- 9 A M i l i t a r y JT8D-9 5

. 1 0 1

. 2 0 0

. 4 0 3 6 5 1 0 .50 3 .0 0 C a nadai r R e g

- 10 0 C o m m C F 34

- 3 A 1 4. 00 2. 20 0. 70 73 0 10 .5 0 3

. 0 0 C e ssna 1 50 GA O- 20 0 6. 00 5. 00 0. 30 51 1 0 10 .5 0 3

. 0 0 C o n v ai r l i n er C o m m R D A 10 4. 50 2. 50 0. 50 36 5 10 .5 0 3

. 0 0 DC 1 0

- 1 0 C o m m C F 6- 5 0 C 4. 00 2. 20 0. 70 73 0 10 .5 0 3

. 0 0 DC 9

- 1 0 C o m m JT8 D

- 7 A 4. 00 2. 20 0. 70 43 8 0 10 .5 0 3

. 0 0 DHC

- 8 C o m m P W 12 0 4. 50 2. 50 0. 50 36 5 0 10 .5 0 3

. 0 0 DHC -8 -4 0 0 C o m m P W 12 3 4. 50 2. 50 0. 50 18 2 5 0 10 .5 0 3

. 0 0 F-16 M i l i t a r y F10 0 -PW-10 0 3

. 5 0 0

. 8 0 0

. 4 0 1 8 3 1 0 .50 3 .0 0 F-27 Series Military RDa7 4

. 5 0 2

. 5 0 0

. 5 0 3 6 5 1 0 .50 3 .0 0
Fo kke r 1 00 GA TAY 6 50 4. 00 2. 20 0. 70 36 5 10 .5 0 3

. 0 0
H-4 6 Sea Kn igh t Military T58

- GE-8 F 6

. 8 0 6

. 8 0 0

. 0 0 1 8 3 1 0 .50 3 .0 0 Ki n g ai r B 2 0 0 GA PT6 A

- 4 1 1. 60 0. 50 0. 40 58 4 0 10 .5 0 3

. 0 0 Learjet 2 5 B GA C J 61 0- 6 1. 60 0. 50 0. 40 14 6 0 10 .5 0 3

. 0 0
M D

- 1 1 C o m m C F 6- 8 0 C 2 D1 F 4. 00 2. 20 0. 70 73 0 10 .5 0 3

. 0 0
M D

- 8 0 C o m m JT8 D

- 2 0 9 4. 00 2. 20 0. 70 45 6 3 10 .5 0 3

. 0 0
M D

- 8 0

- 8 8 C o m m JT8 D

- 2 1 7 4. 00 2. 20 0. 70 18 2 5 10 .5 0 3

. 0 0
M D

- 9 0

- 1 0 C o m m V2 5 2 5

- D 5 4. 00 2. 20 0. 70 36 5 10 .5 0 3

. 0 0
Po rter PC 6 / B2 Military PT6A-27 4

. 5 0 2

. 5 0 0

. 5 0 7 3 0 1 0 .50 3 .0 0 SF- 34 0

- A C o m m C T 7- 5 4. 50 2. 50 0. 50 73 0 10 .5 0 3

. 0 0 Swea ri n g en M e rl i n C o m m TPE3 3 1

- 3 4. 50 2. 50 0. 50 29 2 0 10 .5 0 3

. 0 0 Swea ri n g en M e rl i n C o m m TPE3 3 1

- 3 4. 50 2. 50 0. 50 36 5 10 .5 0 3

. 0 0 Once all of the data is en tered into th e m odel, the m odel produces an em ission inventory. Annual em ission inventory results are listed in th e table below:

NAME CO T o n s / y e a r HC 107 Tons/year NOX Tons/year SOX Tons/year PM10 Tons/year A i r c r a f t 7 6 7

. 8 8 6 128.821 905.493 41.586 GSE/AGE/ A P U 2 8 1 0

. 9 9 2 71.658 221.278 6.027 7

. 8 7 1 T o t a l 3 5 7 8

. 8 7 8 200.476 1126.771 47.613 7

. 8 7 1

The m odel will a l so pro duce an inve ntory spec ific to each aircraft type, w h ich allows the data to be separ a ted into typ e s ( c om m e rcial, genera l avia tion, and m ilita ry) of ope ration. For BW I the
separa tion r e sults in th e f o llowing:

NAME CO Tons/year HC Tons/year NOX Tons/year SOX Tons/year PM10 Tons/year Comm ercial 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 T o t a l 7 6 7

. 8 8 6 128.821 905.493 41.586 0

. 0

217 107 Requ ir es a H y d r o carbo n to VO C co nv ersion f actor o f 1.094 7.A daily em ission inventory was produced assum i ng an airport activity of 365 days per year.

The m odel was run for all a i rc raft a t BW I and a ll com m ercial avia tion a t Hagerstown Regional, Ocean City Municip a l a nd m ilita ry a i rc raft at An drews Air F o rce Base.

2184.4.2 General Aviation SCC: 22 75 050 000

Emission Calculation

219 A rough estim a te of e m i ssions were calculate d after inform ation on the L T O operations of aircraft operation type was obtaine d from Maryland’s airports. Th is m e thod used the alternative fleet-av e rag e procedu r e of Section 5.2.4.2 of Procedures , 1992. The composite em ission factors used are lis ted in the tab l e b e l o w

.

CO (lbs./LT O ) HC* (lbs./LT O ) NO x (lbs./LT O ) SO2 (lbs./LT O ) PM (lbs./LT O )

Gen e ral Av iatio n 12 .0 1 4 0. 39 4 0

. 06 5 0

. 10 0 0

. 02 0

Air Ta xis 28 .1 3 0 1. 23 4 0

. 15 8 0

. 01 5 0

. 02 0

* Requires Hydrocarbon to VO C conversion factor of 0.9708 for General Aviation and 0.9914 for Air Taxis.

EF(AT) xx = Em ission factors for Air Taxis 1) Em iss VOC = LTO (GA) * EF (GA) VOC

W h ere: LTO (GA) = L T O s f o r G e n e r a l A v i a t i o n EF (GA) xx = Em i s s i o n F a c t o r s f o r G e n e r a l A v i a t i o n

2) Em iss VOC = L(AT) * EF(AT) VOC

W h ere: L(AT) = L T O s f o r A i r T a x i s

Sample Calculation – General Aviation:

This calculation is for E a ston Airport/Newm a n Fi eld in Talbot County. The airport had 21,569 General Aviation LTOs over a twelve m onth period. Performing step 1 E quations (above) the calcu lations were:

Em iss VOC = [L(GA) * E F (GA) HC ] * C F ( V O C / H C ) Em iss VOC = [(21,569 LTOs / Year * 0.394 (lbs. HC / LTO)] * 0.9708 (lb s

. V O C / l b s

. H C ) ) ) ) Em iss VOC = 8
, 2 5 0

. 0 3 9 0 l b s

. V O C / Y e a r Em iss VOC = 0.0113 Tons VOC / Da y

Em iss CO = [21,569 LTOs / Year * 12.014 (lbs. C O / L T O ) ] Em iss CO = 2 5 9
, 1 2 9

. 9 6 6 l b s

. o f C O / Y e a r Em iss CO = 0

. 3 5 5 0 T o n s C O / D a y Em iss NOx = [21,569 LTOs / Year * 0.065 (lbs. NOx / LTO) ] Em iss NOx = 1
, 4 0 1

. 9 8 5 l b s

. o f N O x / Y e a r220 Em iss SO2 = 0.0030 Tons SO2 / Day Em iss NOx = 0

. 0 0 1 9 T o n s N O x / D a y

Em iss SO2 = [ 2 1
, 5 6 9 L T O s / Y e a r * 0

. 1 0 0 ( l b s

. S O 2 / L T O ) ] Em iss SO2 = 2
, 1 5 6

. 9 0 0 l b s

. o f S O 2 / Y e a r

Em iss PM = [21,569 LTOs / Year * 0.020 (lbs. P M / L T O ) ] Em iss PM = 4 3 1

. 3 8 0 l b s

. o f P M / Y e a r Em iss PM = 0

. 0 0 0 6 T o n s P M / D a y
Sample Calculation – Air Taxi:

This calculation is for E a ston Airport/Newm a n Fi eld in Talbot County. The airport had 4,557 Air Taxi Aviation LTOs over a twelve m onth peri od. Performing step 1 E quations (above) the calcu lations were:

Em iss VOC = [L(AT) * EF(AT) HC ] * CF (V O C /H C ) Em iss VOC = [(4,557 LTOs / Year * 1. 234 (lbs. H C / L T O ) ] * 0

. 9 9 1 4 ( l b s

. V O C / l b s

. H C ) ) ) ) Em iss VOC = 5
, 5 7 4

. 9 7 7 3 l b s

. V O C / Y e a r Em iss VOC = 0.0076 Tons VOC / Da y

Em iss CO = [4,557 LTOs / Year * 28.130 (lbs. C O / L T O ) ] Em iss CO = 1 2 8
, 1 8 8

. 4 1 0 l b s

. o f C O / Y e a r Em iss CO = 0

. 1 7 5 6 T o n s C O / D a y

Em iss NOx = [4,557 LTOs / Year * 0.158 (lbs. N O x / L T O ) ] Em iss NOx = 7 2 0

. 0 0 6 l b s

. o f N O x / Y e a r Em iss NOx = 0

. 0 0 1 0 T o n s N O x / D a y

Em iss SO2 = [4,557 LTOs / Year * 0

. 0 1 5 ( l b s

. S O 2 / L T O ) ] Em iss SO2 = 68.355 lbs. of SO2 / Ye a r Em iss SO2 = 0

. 0 0 0 1 T o n s S O 2 / D a y

Em iss PM = [4,557 LTOs / Year * 0

. 0 2 0 ( l b s

. P M / L T O ) ] Em iss PM = 9 1

. 1 4 l b s

. o f P M / Y e a r Em iss PM = 0

. 0 0 0 1 T o n s P M / D a y221 4.4.3 Military Aircraft SCC: 22 75 001 000

There ar e f i ve m ilitary a i rpor ts in M a ryland. Th ey are Andr ews Air For ce Base, For t Meade/T i pton, Aberdeen, Patuxent River Naval Air Station, and Martin State Airport. ARMA received LTO infor m ation from all airports. The Aberdeen Airport reported no activity in 2002. Most of the county airports also receive a sm all num b er of m i litary operations.

Method and Data Sourc e s
Since ARMA asked for and received LTO infor m ation by aircraft operation type, A R MA used

com posite em ission factors from Procedures for Em ission Invent ory Preparation, Volum e IV: Mobile Sources, 1988 for all airports except And r ews Air Force Base. Th e EDMS m o del (version 3.2) was used to calculate em issions from Andrews Air Force B a se. Otherw ise, th e

com posite em ission f actors are lis ted i n t h e t a b l e b e l o w

.

CO (lbs./LT O ) VOC (lbs./LT O ) NO x (lbs./LT O ) SO2 (lbs./LT O ) PM (lbs./LT O )

Military Aircraft 48 .8 0 2 7 .1 0 9

. 16 0 1

. 43 0 15 .2 3 0

Emission s Calculation 1) Em iss VOC = L(MA) * EF(MA) VOC

W h ere: L(MA) = LTOs for Milita r y A i r c r a f t EF(MA) xx = Em ission factors for M i lita ry Airc r a f t

This calcula tion is f o r P a tuxent Riv e r Naval Air Station in St. Mary’s county. The airport had 63,852 LTOs in 2002. Using step 1 from E quations (above) the calculations were:

Em iss VOC = [L(AT) * EF(MA) HC ] Em iss VOC = [(63,852 LTOs / Year * 2 7

. 1 0 ( l b s

. V O C / L T O ) ] Em iss VOC = 1
, 7 3 0
, 3 8 9

. 2 0 0 l b s

. V O C / Y e a r Em iss VOC = 2.3704 Tons VOC / Da y

Em iss CO = [ 6 3
, 8 5 2 L T O s / Y e a r * 4 8

. 8 0 ( l b s

. C O / L T O ) ] Em iss CO = 3
, 1 1 5
, 9 7 7

. 6 0 l b s

. o f C O / Y e a r Em iss CO = 4

. 2 6 8 5 T o n s C O / D a y

Em iss NOx = [63,852 LTOs / Year * 9.160 (lbs. NOx / LTO) ] Em iss NOx = 584,884.32 lbs. of NOx / Y e a r Em iss NOx = 0

. 8 0 1 2 T o n s N O x / D a yEm iss SO2 = [ 6 3
, 8 5 2 L T O s / Y e a r * 1

. 4 3 0 ( l b s

. S O 2 / L T O ) ]

222 Em iss SO2 = 9 1
, 3 0 8

. 3 6 l b s

. o f S O 2 / Y e a r Em iss SO2 = 0

. 1 2 5 1 T o n s S O 2 / D a y

Em iss PM = [ 6 3
, 8 5 2 L T O s / Y e a r * 1 5

. 2 3 ( l b s

. P M / L T O ) ] Em iss PM = 9 7 2
, 4 6 5

. 9 6 l b s

. o f P M / Y e a r Em iss PM = 1

. 3 3 2 1 T o n s P M / D a y2234.5 Mari ne Vessels SCC: 22 80 002 010 (diesel m a rine vessels)

Description

224 Comm ercial vessels include all bo ats and ships u s ed either d i rectly or ind i rectly for comm erce or

m ilitary ac tivity. These include v e ss els rang ing in size f r om 20-f oot char ter boa ts to the larg est tankers and m ilitary ves s els, whic h can exceed 1,000 feet in length.

MDE used the em ission inventory prepared for the Maryland Port Adm i nistration by E d wards and Kelcey (E&K). E&K analyzed the major catego ries of air em issions as sociated with sh ip and port operations and their relationship to air quality issues in the Ba ltim ore non-attainm e nt area. Pollutant s PM, SO 2 , NOx, CO, HC, CO 2

Method and Data Sourc es

E&K used the m a rine em ission inventory guid a n ce m e thod outlin ed in Analysis of Comm ercial Marine Vessels Em issions and Fuel Consum ption Data (EPA-450-R-00-002), February 2000, to calculate emissions from commerc ial m a rine vessels. The m e t hodology is based on a three-step calculation. The first step apportions the tim e spent by a vessel in a port area to different operating modes. The second calculates fuel consum ption in each operating m ode. The third step calcu lates

em issions using fuel consum ption specific em ission factors, which is how m a rine engine em ission factors have been historically specified. All of th ese calculati ons are m a de by vessel type and class, with the type specifying wheth e r the v e ssel is a tanker, passenger line r, etc, and the class

s p e c i f y i n g e i t h e r t h e w e i g h t o r h o r s e p o w e r r a n g e

. This new methodology considers new infor m ation co llected on m a rine vessels. The tim e -in-m o de is a function of the particular port area geography and was not considered in the report. The other factors used in the em ission estim ate com putati on are exam ined, with particular focus on the

em ission factors, for all pollutants of concern. O n e reason fo r a detailed reconsideration of the

em ission factors is that a num b er of large m a rine diesels have been tested for em issions and their
tests resu lts have become availabl e in the last few years. In add ition, both the EPA and ARB have

recen tly spo n sored stud ies to calculate m a rine vessel em issio n s in the So uth Coast Air Basin and in som e areas of Region IX, so that there is a body of new research avai lable to update em ission factors. Hen ce, the us e o f a larger an d newer da tabase on m a rine vessel em ission is exp ected to substantia lly im prove the quality of the derived em ission factors.

Activity The com put ation of em issions can be perform e d by ship type for a given port and requires the following inputs:

• The num ber of calls to the port by ve ssel class and deadweight tonnage.• The tim e spent, by ship type, in e ach of f

our operating m odes defines as: norm al cruise, slow cruise, m a neuvering, and hoteling. Emission F a

ctors

225 Em ission rates were calculated per pollutant (except SO2) per vessel type per m ode of operation within the guidance docum ent using the following form ula:

E (i) = a * (Fractional Lo ad) –x + b

W h e r e :

E (i) = Em ission rate of pollutant i in gram s p e r k i l o w a t t

- h o u r

a = Coefficient

x = Exponent b = Inte rcep t

Em ission ra tes were ca lc ulated p e r p o llutant (S O 2 only) per vessel type per m ode of operation within th e g u idance doc um ent using the f o llowin g f o rm ula:

E (SO2 ) = a * (Fuel Sulfur Flow in g/kW

- h r ) + b

The m a rine engine em ission factor and fuel consum ption algorith m s are presented in the tab l e below:

P o l l u t a n t E x p o n e n t ( x ) In tercept (b) Coe fficient (a)
PM 1. 5 0. 25 5 1 0. 00 5 9
N O x 1. 5 10 .4 4 96 0. 12 5 5 SO 2 1 0 2. 37 3 5 C O 1 0 0. 83 7 8 HC 1. 5 0 0. 06 6 7 C O 2 1 64 8. 6 44 .1

The m a rine engine em ission rates in gram s per k ilowatt-hour are presente d in the table below:

Vessel T y pe Cruise Slow Cr u i s e M a n e u v ering H o t e l i n g PM (gr/kw-hr) PM (gr/kw-hr) PM (gr/kw-hr) PM (gr/kw-hr)

B u l k C a rri ers & Ta nke r s 0. 26 3 3 0

. 32 1 1

0.2633 0

. 27 8 4 0

. 44 1 7

G e n e r a l C a r g o 0

. 2 633 0

. 2 836 0

. 3 211 0

. 4 417

Passeng er 0

. 2 633 0

. 3 211 0

. 4 417 0

. 7 828

C ont ai ne r/ R O R O / R eefer/ A u t o C a r r i e r 0. 26 3 3 0. 29 1 0. 35 6 7 0. 54 2 4 All non-oceangoi ng 0

. 2 7 8 4 0

. 3 2 1 1 0

. 4 4 1 7 NO x (gr/kw-hr) NO x (gr/kw-hr) NO x (gr/kw-hr) NO x (gr/kw-hr)

B u l k C a rri ers & Ta nke rs 10 .6 2 5 10 .9 4 57 11 .8 5 27 14 .4 1 83226 Vessel T y pe Cruise Slow Cr u i s e M a n e u v ering H o t e l i n g

Gene ral C a r g o 10 .6 2 5 11 .0 5 5 7 1 1 .8 5 2 7 1 4 .4 1 8 3

Passen g e r 10 .6 2 5 11 .8 5 2 7 1 4 .4 1 8 3 2 1 .6 7 4 7

C ont ai ne r/ R O R O / R eefer/ A u t o C a r r i e r 10 .6 2 5 11 .2 1 34 12 .6 0 99 16 .5 5 97 All non-oceangoi ng

2 8 .6 0 2 7 4 1 .1 7 04

3 2 .7 9 1 9

CO (gr/kw-hr)

2. 39 3 7

HC (gr/kw-hr)

B u l k C a rri ers & Ta nke rs 0

. 26 3 7 2

. 10 9 2

0

. 7 457

0. 40 5 9

0.2637 0.7457 2.1092 CO 2 (gr/kw-hr)

B u l k C a rri ers & Ta nke rs 86 9. 1 1, 08 9. 6 0

Gene ral C a r g o
7 0 3. 7 25 1, 53 0. 6 0

No controls are availab l e for this source category. Point Source Adjustment s 10.625 1 0

. 9 4 5 7 1 1

. 8 5 2 7 1 4

. 4 1 8 3 SO2 (gr/kw-hr) SO2 (gr/kw-hr) SO2 (gr/kw-hr) SO2 (gr/kw-hr)

B u l k C a rri ers & Ta nke r s 26 .5 0 8 1 3 2 .7 9 1 9

Gene ral C a r g o 26 .5 0 8 1 2 9 .2 0 1 2 4 1 .1 7 0 4

Passen g e r 26 .5 0 8 1 3 2 .7 9 1 9 4 1 .1 7 0 4 5 7 .9 2 7 3

C ont ai ne r/ R O R O / R eefer/ A u t o C a r r i e r 26 .5 0 81 29 .9 9 91 35 .5 8 47 46 .7 5 6 All non-oceangoi ng 26.5081 2 8

. 6 0 2 7 3 2

. 7 9 1 9 4 1

. 1 7 0 4 CO (gr/kw-hr) CO (gr/kw-hr) CO (gr/kw-hr)

B u l k C a rri ers & Ta nke rs 1. 04 7 3 2. 09 4 5 4. 18 9 8. 37 8

Gene ral C a r g o 1. 04 7 3 4. 18 9 8. 37 8

Passen g e r 1

. 04 7 3 4. 18 9 8. 37 8 16 .7 5 6

C ont ai ne r/ R O R O / R eefer/ A u t o C a r r i e r 1. 04 7 3 2. 79 2 7 5. 58 5 3 11 .1 7 07 All non-oceangoi ng 1.0473 2

. 0 9 4 5 4. 1 8 9 8

. 3 7 8 HC (gr/kw-hr) HC (gr/kw-hr) HC (gr/kw-hr)

0. 09 3 2 0

. 74 5 7

G e n e r a l C a r g o 0

. 0 932 0

. 3 221 0

. 7 457 2

. 1 092

Passeng er 0

. 0 932 2

. 1 092 5

. 9 658

C ont ai ne r/ R O R O / R eefer/ A u t o C a r r i e r 0. 09 3 2 1. 14 8 1 3. 24 7 4 All non-oceangoi ng 0.0932 CO 2 (gr/kw-hr) CO 2 (gr/kw-hr) CO 2 (gr/kw-hr)

70 3. 7 25 75 8. 8 5

70 3. 7 25 77 4. 6 86 9. 1 1, 08 9. 6 0

Passen g e r 86 9. 1 1, 08 9. 6 0

C ont ai ne r/ R O R O / R eefer/ A u t o C a r r i e r 70 3. 7 25 79 5. 6 94 2. 6 1, 23 6. 6 0 All non-oceangoi ng 703.725 7 5 8

. 8 5 8 6 9

. 1 1
, 0 8 9

. 6 0

No point source em issions were subtr acted from the area source inven t ory

. Adjustment for ControlsSpatial and Temporal Allocatio ns Spatial Data f o r spa tia l alloca tio n is not av ailable f o r this source. E& K em issions invento r y f o cused on the City of Baltim ore and allo tted the cru i se e m issions to the city.

Temporal Data f o r tem poral a lloc a tion is not av ailab l e f o r th is sourc e

.

Emission s Calculation

227 The equatio n used to es tim a te em issions f r om com m e rcial m a rine v e sse ls is:

CALLS VCC, DWT x LENGTH VCC, DWT x %TIME VCC, DW T,

MOD E TIME V CC, DW T, MO DE = 100

EMISSIONS VCC, DWT, M ODE = (EF)(LF MOD E ) x (HP) (DW T ) x LF MO DE x TIME VCC, DWT,

MOD E W h ere: VCC is the vessel c l ass (bulk ca rr ier

, tanker, container, general cargo, passenger, reefer, RORO, tug, vehicle carrier, or m i scellaneous)

DW T is the deadweight tons EF is the em issions f a c t o r LF is the m o de specific load factor

For the calculation, the TIME equation requires port specific inputs, while the guidance m e thod outlin ed in Analysis of Comm ercial Marine Ves s el s Em issions and Fuel Consum ption Data(EPA450-R-00-002), February 2000, provides t h e E F a n d H P r e l a t i o n s h i p s

. Data on the type of vessels, num be r of calls per vessel type, deadwe ight tons per vessel type, and tim e in each m ode per vessel type us ing Baltim or e port facilities cam e from the Maryland Port Adm i nistra tion (MPA).

In addition, the MPA provided data that trans l ated into app r oxim a tely 85 percen t of the vesse ls arriv i ng fro m the south (up the Ches apeake Bay) a nd 15 percent of the vessels arriving from the north (down from the Chesapeake an d Delaware Ca nal). The data a llowe d MDE to allocate slow cruising em issions to the appropria te counties to the north and south of the Port of Baltim ore. Em issions associated with "norm a l cruising" were assum e d by MDE not to have occurred while in the Mary lan d airshed.

All of the m a neuver i ng and hoteling em issions were assign ed to the City of Baltim ore.

## 5.0 ONR O AD MOBILE SOUR CES

5.1 INTRODUCTION

As detailed in the following sections, the offici al 2002 highway vehicle emissions estim ates for the 8-hour o z one SIP su bm ittal, h a v e been devel oped based on the high way traffic data obtained from the Maryland State Hi ghway Adm i nistration (SHA)

228 The official highway vehicle em ission inventory for the Mary land portion of the W a shington, D.C. Ozone Non-attainment Area (comprising th e countie s of Calvert, Cha r les, Fr eder ick, Montgom ery, and Prince George's) has been de veloped by the Metropolitan W a shington Council of Governments (MW C OG) based on the transp ortation dem a nd m odeling data and has been docum ented by that organization under separate cover.

The em ission m odeling com putations (expressed in tons per summ er weekday or tons per annum ) involve application of appropriate conversion an d seasonal adjustm e nt f actors on the two entities of the em ission equation – em ission factors in gram s per m ile and vehicle activity in VMT.

This new post-processor, PPSUITE was used f o r the first tim e in 2003 by MSCP for the 2005 Mobile Em ission Budget effort. However this softwa re system has been in use in Pennsylvania, Virginia, New Jersey, and the New York City Metropolitan Area, for previous inventory and confor m ity subm issions. PPSUITE is also com p atib le with travel demand m odele d activity data and as such used in th e Baltim ore Area’s for tr ansportation conform ity analysis. The following table provides a summ ar y of the em i ssion process and various data inputs. In acco rdan ce with th e standard m e thodology for the dev e lo pm ent of highway vehicle em issions invento r ies, all of the em issions estim ates docum ented herein are based on em ission factors developed using the United States E nvironm ental Protection Agency's (U.S. EPA' s) latest v e rs ion of the MOBILE6 em issions factor model and using appropriate activ ity le vels i. e., veh i cle m iles traveled (V MT) estim a tes developed from the highw ay traffic data obtained from the SHA of the Maryland D e partm e nt of Transportation (MDOT).

In its sim p lest form , highway vehicle em issions can be m ode led by aggregating the products of

em ission factors of various vehicle types and vehicl e travel activity on v a rious roadway classes, as illus t r a ted in the f o llowin g equation :

Em issions = (Em i ssion Factors) x (V ehicle Activity)

In the re al world, developm ent of highway vehicle em issions over a large network of roadways is

a com p licated and data intensive effort that re quires the correct expertise and tools to produce

em issions based on the federal and state requir em ents. MDE used the PPSuite system , a robust, system atic, and com p rehensive software approach to develop the on-road em issions for the state.229 PPSUITE Emission Modeling Process
SHA Prepared Data

2002 High w a y D a ta

UNIV02 Database

( 128, 379 Statewide Records) B a sed on Highway

County Number -

Location Reference System

L anes 2002 V e hicle Classific a tions
( S tatewide Avg. B y FC)

From SHA Traffic Monitorin g System Website

Percent of Fl eet by F HW A vehicle classes

Map to vehicle type 2002 S e asonal Facto r s (Statewide Averag e By FC Gr oup)

Based on SHA Traffic Trends System: F u nctional Class R e ports

Percent of A A DT f

o r monthly weekdays 2002 Hourly Pa t t ern Data
( S tatewide Avg. B y FC)

Based on SHA Traffic Trends System: F unctional Class R e

ports

Percent of volume in

each hour of d a y 

## A B C D

PPNET N e t wo rk

MOBILE6 H i g hw Ne tw or k ay Data

POSTMOBILE

Pr ocess M 6

PEQUESTR C r e at e R epo rt s PREMOBIL E

Prepare M 6 PPSUITE

PPSUITE Driver File Ve hi cl e M i x Fi le (V ol by ve hi cl e t y pe)

SHA Statew ide P a tte r n s

(LDV , H DV, BUS
, MC )

MPO Regional Pattern

(LDV , H DV, BUS
, MC ) p r ep a r ed b y

BMC, M W COG, etc.,

Hour ly P a tter n F i le
(Volume b y hou r of d a y )

Ve hi cl e F a ctor Fi le
(Veh i m pa ct on ca pacity)

Spe e d Capac i ty Lookup
Develop data set with fr ee flow speeds, lane capaci ties, def a ult signal spacing, BP R

p ara m et ers, etc. , IM Param e ter s

Vehicle Age

VMT Seasona l Adj u stm e nts 

### Emission Calculation Scheme


## A

B

C

D5.2 EMI S SIO N FACTO R S

The heart of the highway vehicle emission ’s ca lculation procedure is EP A’s highway vehicle

em ission factor m odel, MOBILE. This is a FO RTRAN program that calculates average in-us e fleet em ission factors for specific pollutants for each of twenty-e ight categories of vehicles under various conditions affecting in-u se em ission levels (e.g., am bient tem p eratures, av erag e traffic speeds, gaso line vo latility) as specified by the model user. MOBILE6 m o del does not produce
tota l em issions direc tly, but it g e nera tes em ission f

actors as referred to in th e previous section.

The first MOBILE m o del was developed as MOBILE1 in the late 1970s. It ha s been periodically updated to reflect th e co llection and analys is of a ddition a l em ission factor data over th e years. It also has been upgraded to capture changes in ve hicle/engine/em i ssion cont rol system technologies, and changes in applicable regulations, em issi on standards and test procedures, and im proved understanding of in-use em ission levels and the f actors that influence them . For this inventory effort, the latest MOBIL E m odel (MOBILE6.2 ve rsion 6.2.03 of 24-Sep-2003 - hitherto referred as MOBILE6) was utiliz ed in generating the em ission factors and in building the em ission inventories.

5.3 VEHICLE MILES TRAVELED

230 • Com p iles ve hicle m iles o f travel (VMT) and vehicle type m i x data The traf f i c d a ta sour ce is the key da ta item th at drives th e VMT and speed calcu lations. This process uses highway data and volum es obtaine d fromSHA. The objective was to utilize nontravel m odel data sources that will continue to b e m onitored a nd updated in the future, which will facilitate future updates to the process. The process utilizes the PPSU ITE post processor that consists of a set of program s that perfor m the following functions:

• Analyzes highway operating conditions

• Calculates highway speeds

• Prepares MOBILE6 input files a nd actually runs MOBILE6 m odel

• Calculates em ission quantities from output MOBILE6 em ission rates and accum u lated highway VMT.

The PPSuite process utilizes a num ber of programs and operations assem b led into a chain of jobs and steps. T h e m a nage ment of these model chains and their operations can be difficult. At the front end, an interfacing software package calle d CENTRAL is deployed, providing MDE with the ability to ef ficien tly m a nage the em ission calculation process.

5.4 KEY TRAVEL DATA INPUTS231 This section describes the SHA da ta inputs to the em ission calcula tion process. The inputs were prepared based on available 2002 data and include:

• Highway Data

• Vehicle Classifications

• Seasonal Factors / HPMS VMT Rec onciliation

• Hourly Patte r n Data

The rem a ining sections provide an overview of each of the key SHA data inputs.

Highw ay Data Inputs

The 2002 highway data set was obtained directly from SHA and is referred to as the “Universal” highway database . The file ob tained is nam e d HMIS.MDB ; it represents 2002 traffic data and

c o n t a i n s t h e f o l l o w i n g r o a d w a y v a r i a b l e s :

• Facility typ e and area ty pe class i fications

• Num b er of t r avel lanes

• Speed Lim its

• Average Annual Daily T r affic volumes

The PPSUI TE post processor require s a network database (in “DBF ” for m at) to support em ission calcu lation runs and exp ects specific data field s to be present. A roadway network was created using the table “ UNIV2002 ” in the S H A ACCESS database f i le HMIS.MDB. This table was f i rst saved as a separate database file. T h en som e sp ecific operations on data fi elds such as addition, deletion, renam i ng and fi eld value modificati ons were conducted usi ng the ACCESS database software. This is the key vehicle activ ity input to the em ission m odeling system

. Vehicle Mix Inputs

The vehicle m i x distribution file is another key input file that can have a significant impact on

em issions. The data is used in com b ination with diesel sales fractions by MOBILE6 to develop a

com posite em ission rate for all the 28 output ve h i cle types. T h e vehicle mixes are inpu t to PPSUITE as hourly distributions of vehicles by vehicle type. Th e m i xes are developed using 2002 data ava ilab l e f r om the Traffic Monitoring System section, from the SHA website that has a link

nam e d “ Vehicle Cla ssification by Functional Class ”. That lin k leads to a r e port f i le in PDF for m at, which reflects the percent of vehicle clas sifications by functional class for the years 1998 through 2003.

The PPSUI TE input 2002 SHA veh i cle m i x file wa s prepared based on 4 input vehicle groups:

• Vehicle Type 1 = Motorcycle232 For input to the em ission calculation process, all the vehicle classes were grouped into 4 categories • Vehicle Type 2 = Light-duty vehicles

• Vehicle Typ e 3 = Buses

• Vehicle Type 4 = Heavy-duty vehicles

for each functional class : Auto, Truck, Bus, and Motorcycle . Vehicle clas s 1 catego r y was used for motorcycles. Classes 2 and 3 were com b ined to obt ain the p e rcen tage au tos. Class 4 was used for buses. Truck percentages were obtained by com b i n ing classes 5 to 13. The PPSUITE p o stprocessor autom a tically splits the four input vehicle cate gories to the required 16 MO BILE6 vehicle classes by using the MOBILE6 defaults , which vary by the chosen analysis year.

H o u r l y P a t t e r n I n p u t s

Speeds and em issions vary depend ing on the tim e of day because of temperature v a riations an d congestion. Therefore, it is im portant to estim a te the pattern by which roadway volume varies by hour of the day. The hourly patte rn distributions are not only input directly to MOBILE6, but are also a key input file to P PSUITE fo r estim ating hourly congested speeds.

Hourly m i xes of vehicles for each area and facili ty type com b ination are input to PPSUITE. These are used to d e term ine the proportion of the daily volum e in each hour of the day, so separate hourly speeds can be prepared and input to MO BI LE6. Hourly pattern data was obtained from the Traffic Tr en ds System R e port Modu le 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 app ear with the type of group report, y e ar , 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 In te rsta te, Rural oth e r, Urban Interstate, U r ban other and summer seasonal. One functional class can be chosen at a tim e . Once these op tion s are se lec t e d and the view report bu tton c licked, the tab l e with the f acto r s is obta i ned

. For the ozone daily em ission calculation proces s, 2002 hourly pattern data for the 4 prim ary functional classes was used to cr eate the PPSUITE input files. An average factor was calculated for 3 m onths – June, July and August to derive hourly percentage of vehicles for a summer weekday. For the annual em issi on com putation process, average f acto r s were calculated for every month in the evaluation year 2002.

VMT Adjustments

The SHA ne twork link volum e s have been adjusted using the VMT adjustm e nt factors, to account f o r dif f e rences with th e HPMS VMT totals (dif f e rence s prim arily rela te d to m i ssing local VMT)

. The factors were developed upon completion of a 2002 analysis run (with no VMT adjustm e nts or seasonal factors enab led ) by com p aring the resu lts to the 200 2 HPMS VMT.The adjustm e nt factors are obtained by divi ding the 2002 HPMS VMT by the 2002 analysis run VMT for each county functional class grouping. Th ese calculated VMT adjustm e nt factors are provided as ASCII input files to PPSUITE and are applied to each of the roadway segm ent volum es (see seasonal factor section for descript ion of PPSUITE VMT adjustm e nt file for m at). These factors can be app lied to any future year runs. The VMT added or subtracted to the SHA databas e ass u m e s the sp eeds calculated using th e origin al volum es for each roadway s e gm ent for each hour of the day.

233 Seasonal Adjustments a nd Temporal Allocation

Highway vehicles contribute signif icantly to air pollution, particul arly to ground-level ozone in the

summer m o nths. Ozone is not created directly, bu t it is f o rm ed in sunlig ht f r om VOCs and NO x . Both VOCs and NO x are em itted larg ely f r om h i g h w a y v e h i c l e s

. Even though other pollutants such as CO, NH 3 , SO 2 , PM 2. 5 , and PM 10 con t ribu te to air pollution during summ er also, but their significance is m u ch m o re during the winter m onths. This is in accordan ce with the EP A’s guidance on preparati on and sub m ission of em i s s i o n i n v e n t o r i e s

. For annual inventories, MOBILE6 input param e ters such as average hourly tem p erature, hourly hum i dity and atm o spheric pressure , diesel sulfur content, RV P, etc., were developed f o r every month in the evaluation year 2002.

The seasonal factors are used to adjust the average annual day traffic (AADT) to represent the
average summ er weekday, which is n eeded for em ission an alyses. The seasonal and monthly VMT adjustm e nt factors were developed using th e traffic flo w data av ailable by day and m onth fro m ATR St ation Reports in the Traffic Trends System Report Module from the SHA website accessed. The above link leads to a screen with d i fferent Traffic Trends Reports Selection options. By clicking on the Group Reports section, a criteria screen wi ll appear with the type of group

r e p o r t , y e a r , a n d f u n c t i o n a l c l a s s t o b e c h o s e n

. To get the m onthly variation of traffic flow for the year 2002, the report type “ Traffic Flow by Day by Month by Group ” was selected. F actors are av ailab l e fo r 5 f unctional c l asses: Rur a l Inter s ta te, Rural other, Urban Interstate, Urban other and summer seasonal. One functional class can be chosen at a tim e . Once these options are selected and the view report button clicked, the table with the traf f i c f l ow data is o b tained.

The AADT percentage is available f o r each of the 7 days of the w eek for all the 12 months, which is divided by 100 to get a daily factor. An average m onthly weekday factor was obtained for 12234 months by calculating an average factor for 3 w eekdays, Tuesday, W e dnesday and Thursday. The calcu lations were repeated for a ll th e 4 f unctional classe s. The s e functional class groups were then

m a pped to the 12 functional classes us ed within the em ission p r o c e s s

. Average m o nthly adjustm e nt factors were de veloped for every m onth in 2002. The summer adjustm e nt factors were develope d, b y calcu latin g the averag e of the m o nthly facto r s 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 m onthly scenarios an d for the su mmer seasons. These files are s e lected through the Central m e nu screen depending upon what season the analysis is being run for. The adjustm e nt factors are ap plied by PP SUITE before the calcu lation of link

- leve l speed s

.

5.5 MOBILE INPU T PA RA METERS

The inputs to MOBILE that aff ect em issions include num erous vehicle and environm ental
param e ters including:

• Vehicle M i x e s

• Vehicle age distributions a nd diesel sales fractions

• Fuel param e ters

• Inspection/m a intenance program param e ters

• Other environm ental variables

MOBILE model allows the user to choose default values for input param e ters where da ta is no t locally available. User s upplied data is preferable in m o st cases.

VMT m i xes, a significant piece of data with a si g n if icant im pact on em ission leve ls, a r e gene rated on the go by the PPSuite system using fro m all the traffic related data such as highway network data, veh i cle patte rn f ile, ve hicle factor file, etc.,

The vehicle fleet age has a significan t im pact on regional em ission estim a tes and these were

com puted by MSCP from the 2002 Maryland vehi cle registration databa se. The diesel sales fractions als o cam e out of the sam e source.

The fuel param e ters such as , Reid Vapor Press u re diesel sulfur, etc., and environm ental variables such as hourly tem p eratures, hourly hum i dity, atm o spheric pressure, etc., were also developed by MSCP tapping 2002 data from appropriate agencies.235 MOBILE modeling assumptions in clude selection of appropria te m onth and season and the appropriate fuel program for the modeling dom ain. In case of areas with reform ulated gasoline requirem e nts, fuel program ‘4’ was modeled with the gasoline sulfur m a trix supplied by U.S EPA.

PPSuite generates several MOBILE inputs for each county by roadway class, based on the above
param e ters using the PreMOBILE module. MOBILE m odel is then invoked a nd after the specific

num b er of runs, the PostMOBILE module takes care of the em ission aggregation process.

There are other files req u ired by PP SUITE that are used for all an alys is year runs. T h ese files are illus t r a ted in f

o llowing ta ble. North East Low Em ission Vehicle (NLEV) program was selected for th e state of MD and for the NOx correction, the MO BILE parameter REBUILD EFFECTS was m o deled at a 11% value for 2002 for North East states, per U.S EPA.

Finally the reporting routine com e s in and for m ats the report based on the pre-selection: summ ary or detailed em issions for selected pollutants by county, by roadway type, by vehicle group.

All the above input/output data has been gene rated based on the current em ission inventory developm ent guidelines issued by the U.S EPA. Th ey are not included in this docum entation due to their s i ze and num ber and will be m a de available upon req u est.

5.6 OTH E R DAT A I N P U T S

Other PPS UITE Input Files

File Name File Descr i ption

Area eq ui val e n c i e s use d fo r i n put pat t e r n fi l e s an d o u t p ut ag gre g at i o n. EQ UI V

. DBF

NAME_C O UNTY. DBF Used for the output em i ssi on reports. It relates the co ded facility and area ty pe num bers to text nam e s. This file is used when the
count y

- level t o tals report t ype optio n is selected. Used for the output em i ssi on reports. It relates the co ded facility and area ty pe num bers to text nam e s. This file is used when the
count y -rural/ urban totals r e port t y pe o p t i on is selected. NAME_R U RURB. D BF

Contains the im p acts of truck percentage s on roadway capacity . As a result, the am ount of trucks can have an im pact on calculated congested speeds. VEHFC2_02 SHA.DAT

For each facil ity ty pe, area type, and lane com b ination, this file contains:

• Free flow spe e ds SPEEDCAP.DBF • Free flow cap acities

• BPR Parameters (relationship between speed and congestion)VEHP ATT_ 02SHA.DAT Contains the mix of VMT am ong the auto, truck, bus and

m o torcy c le vehicle groups. Files were d e veloped utili zing SHA vehicle class e s clas sificatio n.

Z o ne/Area Equivalency

The zone/area equivalen c y file is a file used to provide equi v a lency between each lin k and the fields used for pattern (hourly a nd vehicle m i x) indexing and output em ission indexes. The file is required by PPSUITE a nd relates to the equivale ncy keyword in the PPSUITE driver file.

Names Database File

• Determ ine free-flow speeds for links without The nam e s database file is used in the process of generating output em ission reports. It rela tes the coded facility and area type num ber s to text na m e s. The e m ission process has the f l exibility to generate tw o types of reports, one w ith county totals and the other with county rural/urban subtotals. T o produce the reports with county to tals, NAMES_COUNTY. D BF is used; for reports with county – rural/urban tota ls, 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 road way link. T h e file is u s ed for the following purposes:

coded speed limits

• Determ ine speed/congestion relatio nships (BPR coefficients) • Determ ine link “ideal” capacity

• Determ ine signal den s ities and cha r a c ter i stics

This dataset was developed through a speed calibration analysis u tilizing SHA 2002 speed monitoring data.

The rem a ining two databases are us ed in the V M T Mix computations.

5.7 EMI S SIO N PRO C ESS OUTPUTS

After MOBILE m odel has been run, PPSUITE pr o cesses the MOBILE ou tput files and com p iles the em ission factors for each scenario. Usi ng the MOBILE em ission factors, PPSUITE calculates

em ission estim a tes by multip lying th e em ission f actors by the aggregated VMT totals. PPSUITE then produces an em issions database summari zing VMT, VHT, VOC, and NOx e m is sions. The output files are autom a tically output to individual county s ubdirectories lo cated under the
autom a tically created “O UT” directory. Files will have hard-coded nam e s. The nam i ng is done using the first four digits of the county nam e and the 2 -digit analysis year. In m o st cases, the user

236will not h a v e to utilize these f iles ; h o wever, the y m a y be usef ul f o r inve stiga ting po tentia l er rors that m a y occur in th e pro cess.

The summary results of all the summ erti m e a nd annual runs for VOC, CO and NOx have been incorporated in Table 1-3 through 1-8.

237 5.8 CONVERSION TO NI F FO RM AT

1) A database for summ er da y VOC, CO and NOx em issions for all counties in MD except f o r the MD countie s und er the jur i sdiction of M W COG, and This is also an autom a ted process through use of a NIF Conversion Program . This m odul e basically reads the appr opriate VMT and E m ission databases and converts them into ACCESS databas e s in the NIF f o rm at. As such th ere are two tables in this subm ittal:

2) Another database for annual VOC, CO and NO x em issions for all coun ties in MD except f o r the MD countie s und er the jur i sdiction of M W COG.238 

## 6.0 BIOGENIC EMISSIONS

6.1 INTRODUCTION

Biogenic sources, a subset of natu ral sources, include only those sour ces th at resu lt fro m som e sort of biological activity. Biogenic em issions repr es ent a s i gnificant portion of the natural source

em issions, and VOC, NO x , and the greenhouse gases can b e em itted from biogenic s ources.
Vegetation is the predom inant biogenic source of VO C and is typically the only sou r ce th at is us ed to estim a te biogenic VOC e m issi ons. Microbial activity is respons ible for the em ission of NO x and the greenhouse gases of CO 2 , CH 4 , and N 2 O. Soil m i crobial activity is responsible for NO x and N 2 O e m issio n s from agricultu ra l lands and grasslands. CH 4 is e m itted throu gh m i crobia l action in waterlogg ed soils o r in o t her anaerobic m i croenvironm ents. CO 2 is released through the aerobic decay of bio m ass (EPA, 1993; EPA,1990a).

Biogenic em issions is one category th at MDE is unable to control dire ctly, therefore, a m a jority o f the resou r ces were directed towards o t her catego ries of air pollution wh ere direct contro l is feasible. For this reason, MDE used the data files created and m a de available by EPA (2002). These em issions were computed on an hourly basi s with a specially-m odi fied version of BEIS3 108 that utilized county land use da ta from EPA’s land use inventory and National W eather Service first-order station data of tem p erature and cloud cover. However, due to the large size of the hourly data files, only the m onthly data files were available when MD E gathered this inform a t i o n

. The data files EPA generated contained county- total estim ates of 2002 biogenic em issions based on the BEIS3.12 m odel. The purpose of this spr eadsheet is to provide default 2002 estim ates to the states for the purpose of biogenic em issions subm ittals by county requ ired by the C onsolidated Em issions Reporting Rule (CERR). These estima tes wer e cr eated us ing the f o llowing data: 1) 2001 annual m e teorology 2) BEIS3.12 model via the Spar se Matrix Operato r Kernel Em issions (SMO KE) m odeling system 3) Recently rev i sed BEIS3.12 em ission factors file (also prov ided as a separate file with this spreadsheet) 4) BELD3 land use data (1-km original data agg r egated to 36 -km grid). 5) Post processing summ ation of county-tota l em issions from SMOKE, calculated from 36- km gridded em issions using the "land ar ea " sp atia l sur r oga te. This m eans that when calculating the county-total num bers, the 36-km gridded em issions were assum e d to be uniform ly distributed over the grid cell for purposes of m a pping to the counties.

Monthly em ission estim ates were given for each c ounty in Maryland fo r the following pollutants:

• CO: Carbon monoxide (a new species output by B E IS3.12 not previously included in BEIS3.09)

• NO: Nitrogen oxide

• ALD2: Aldehyde group from CB-IV chem ical m e chanism

108 BEI S 3.12 can b e do wn lo ad ed f r o m an EPA w e b s ite at: h ttp ://www.ep a .go v / asm d n e rl/ b io g e n

. h t m l• ETH: Ethane group from CB-IV chem ical m echanism

239 • OLE: Olefin group from CB-IV chem ical m echanism

• Total VOC: The sum of ALD2, ETH, FO RM, IS OP, NR, OL E, PAR, XYL, and TOL • FORM: Form aldehyde group from CB-IV chem ical m echanism

• ISOP: Isoprene

• NR: Nonreactive VOC

• PAR: Parafin group from CB -IV chem ical m echanism

• XYL: Xylene group from CB-IV chem ical m echanism

• TOL: Toluene group from CB-IV chem ical m echanism

• TERPB: Terpenes (Note that the sam e m a ss accounted for by TERPB is also included in VOC

The daily em issions were calculated by summ in g the m onthly em issions from June, July, and August and dividing by the num ber of days in those three m o nths (92).