APPENDIX D-1

PENNSYLVANIA NONROAD SOURCE EMISSIONS ESTIMATION METHODOLOGY

Bureau of Air Quality

Department of Environmental Protection

Division of Air Information 

  Methodology for estimating nonroad emissions

I.	INTRODUCTION

This following methodology provides a description of the procedures used
to generate 2002, 2004, 2009, and 2018 county-level pollutant emission
estimates for nonroad mobile engines included in the United States
Environmental Protection Agency’s (EPA’s) NONROAD2005 model, as well
as locomotive engines and aircraft operations.  For the NONROAD2005
model engines, emission estimates were calculated for volatile organic
compounds (VOCs), oxides of nitrogen (NOx), and carbon monoxide (CO). 
Revised geographic allocation files for NONROAD model option files and
revised housing unit data used for the model runs are also included.

II.	2002 NONROAD MODEL SOURCE CATEGORY EMISSIONS

  SEQ CHAPTER \h \r 1 The Department used EPA’s Final NONROAD2005
Model to generate 2002, 2004, 2009, and 2018 summer work weekday
emissions for 12-counties in Pennsylvania.  The inventory was prepared
for Columbia, Crawford, Juniata, Lawrence, Northumberland, Pike,
Schuylkill, Snyder, Somerset, Susquehanna, Warren and Wayne Counties. 
These counties are designated attainment for the eight-hour ozone
standard but were designated nonattainment for the former one-hour ozone
standard and never had an approved maintenance plan.  The Department
prepared NONROAD2005 model option files that account for temperatures
and gasoline Reid vapor pressure (RVP) values representative for these
counties for summer weekdays.  Pennsylvania was separated into four
climate zones for the Maintenance Plans:  East North, East South, West
North, and West South for the inventories for all maintenance plans. 
Three of the four geographic regions were represented.  The summertime
RVP value used for each region was 9.0.  Minimum, maximum, and average
temperatures for July for each region were obtained from the
Pennsylvania State Climatologist website, Pennsylvania State
Climatologist, Penn State University, 2002 Temperature Data by Weather
Station which is available at   HYPERLINK
"http://pasc.met.psu.edu/PA_Climatologist/cityform.html" 
http://pasc.met.psu.edu/PA_Climatologist/cityform.html .  The RVP and
temperature inputs were applied to all equipment categories to obtain
both summer day and annual emissions.  

Table 1 lists the counties included in each of the three pertinent
regions and the weather station where the temperature data were obtained
for each of the regions.  Table 2a and 2b presents the RVP and
temperature data used in the model runs for each region of Pennsylvania.

  SEQ CHAPTER \h \r 1 Table 1.  Regions of Pennsylvania for the
12-County Maintenance Areas







Region	Weather Station	Counties in Region	FIPSST	FIPSCNTY

East North	Scranton	Columbia County 	42	037



Northumberland County	42	097



Pike County	42	103



Schuylkill County	42	107



Susquehanna County	42	115



Wayne County	42	127

West North	Erie	Crawford County 	42	039



Warren County	42	123

West South	Altoona	Juniata	42	067

West South

Lawrence	42	073



Snyder	42	109



Somerset	42	111



  SEQ CHAPTER \h \r 1 Table 2a.  Summer Day NONROAD Model Temperature
and RVP Inputs



Temperature*

	Region	Season	Maximum 	Minimum 	Average 	RVP**

East North	Summer	83	60	72	9.0

West North	Summer	80	63	71	9.0

West South	Summer	82	60	71	9.0

*  Temperature in degrees Fahrenheit

** RVP in pounds per square inch (psi)

	

Table 2b.   Annual Average Day NONROAD Model Temperature and RVP Inputs

	Temperature*

	Region	Maximum 	Minimum 	Average 	RVP**

  East North	61	42	51	9.0

  West North	59	43	51	9.0

  West South	60	42	51	9.0

*  Temperature in degrees Fahrenheit

                                ** RVP in pounds per square inch (psi)

EPA-recommended diesel fuel sulfur levels for marine and land equipment
for all years were used as inputs to the model, as outlined in Diesel
Fuel Sulfur Inputs for the Draft NONROAD2004 Model used in the 2004
Nonroad Diesel Engine Fuel Rule, April 27, 2004.  

In past versions of the NONROAD model, state recreational marine vessels
populations were underestimated when compared to boat registrations
tracked by the Pennsylvania Fish and Boat Commission (PFBC).  EPA’s
population of recreational marine vessels in the NONROAD2005 model now
seem more representative of the number of boat registrations that the
PFBC tracks.  We used EPA’s default values in the model runs.  We also
examined geographic allocation factors for residential lawn and garden
equipment.  These improvements are discussed further in the next
section.  All other categories rely on default data included in the
model for population and activity estimates.

  SEQ CHAPTER \h \r 1 Residential Lawn and Garden Equipment

The EPA’s NONROAD2005 model uses 2003 U.S. Census data of all housing
units in Pennsylvania to allocate residential lawn and garden equipment,
even though EPA guidance states that emissions should be based only on
the number of single detached, single attached, and double housing
units.  EPA’s method in the NONROAD2005 model alters the allocation of
lawn and garden emissions in some Pennsylvania counties significantly. 
The Department will use data obtained by E.H. Pechan from the 2000
Census, updated to 2002, and used in the state’s 2002 inventory on the
number of single detached, single attached, and double housing units for
both the State and all counties in the state.  Table 3 presents the
Census data (Bureau of the Census, 2003), which can be found in 2000
County and State Housing Units by Unit Type, Census 2000,
http://factfinder.census.gov/servlet/.  The total number of housing
units was incorporated into the NONROAD2005 model geographic allocation
factor file, PA HOUSE.ALO, for use in allocating state-level lawn and
garden equipment populations to all Pennsylvania counties for 2002.

  SEQ CHAPTER \h \r 1 Table 3.  Number of Single and Double-Family
Housing Units from 2002 Census

County	# 1-Unit Detached

Housing Units	# 1-Unit Attached 

Housing Units	# 2-Unit 

Housing Units	Total # of 

Housing Units

Adams	24,549	2,206	1,490	28,245

Allegheny	345,479	46,899	29,002	421,380

Armstrong	22,268	824	1,014	24,106

Beaver	54,418	2,312	2,863	59,593

Bedford	14,684	248	501	15,433

Berks	78,946	32,377	5,803	117,126

Blair	36,919	1,844	2,668	41,431

Bradford	16,861	232	1,224	18,317

Bucks	141,951	30,506	5,425	177,882

Butler	46,271	2,523	2,215	51,009

Cambria	44,453	3,795	2,882	51,130

Cameron	1,749	35	176	1,960

Carbon	14,431	5,104	990	20,525

Centre	27,786	2,691	1,749	32,226

Chester	99,549	25,911	3,155	128,615

Clarion	11,635	118	471	12,224

Clearfield	24,829	412	1,064	26,305

Clinton	10,141	662	711	11,514

Columbia	16,856	1,328	1,388	19,572

Crawford	24,430	397	1,933	26,760

Cumberland	51,934	10,450	2,792	65,176

Dauphin	52,961	20,195	3,848	77,004

Delaware	93,642	64,529	9,361	167,532

Elk	11,355	79	807	12,241

Erie	70,504	2,955	9,504	82,963

Fayette	41,679	3,094	2,473	47,246

Forest	1,660	8	18	1,686

Franklin	34,720	4,292	2,073	41,085

Fulton	4,084	56	133	4,273

Greene	10,387	481	416	11,284

Huntingdon	12,463	331	686	13,480

Indiana	23,215	825	1,232	25,272

Jefferson	14,276	237	729	15,242

Juniata	6,455	355	166	6,976

Lackawanna	53,357	3,328	12,626	69,311

Lancaster	98,364	32,122	7,370	137,856

Lawrence	28,316	799	1,489	30,604

Lebanon	27,272	8,647	2,225	38,144

Lehigh	59,753	29,474	5,118	94,345

Luzerne	82,363	15,404	9,435	107,202

Lycoming	31,568	2,812	2,998	37,378

McKean	13,794	158	972	14,924

Mercer	34,859	735	1,817	37,411

Mifflin	12,327	1,788	966	15,081

Monroe	40,696	1,726	1,457	43,879

Montgomery	163,211	53,370	9,599	226,180

Montour	4,769	645	346	5,760

Northampton	60,344	19,729	4,755	84,828

Northumberland	21,955	9,280	1,657	32,892

Perry	12,209	733	398	13,340

Philadelphia	48,724	359,877	46,425	455,026

Pike	15,501	395	299	16,195

Potter	5,263	62	281	5,606

Schuylkill	32,695	17,989	2,092	52,776

Snyder	10,263	644	526	11,433

Somerset	22,159	1,236	1,312	24,707

Sullivan	2,165	18	84	2,267

Susquehanna	12,139	180	711	13,030

Tioga	11,076	150	753	11,979

Union	9,341	652	527	10,520

Venango	17,197	227	1,080	18,504

Warren	13,031	239	930	14,200

Washington	60,711	3,891	3,187	67,789

Wayne	14,311	249	750	15,310

Westmoreland	113,694	4,839	5,997	124,530

Wyoming	7,858	159	412	8,429

York	95,921	20,218	6,102	122,241

Total	2,724,746	860,086	235,658	3,820,490



  SEQ CHAPTER \h \r 1 After the model runs, model outputs were processed
to develop summer work weekday emissions inventories for NOx, VOC, and
CO.  Nonroad equipment refueling, either by portable container or at the
gasoline pump, is being accounted for under Pennsylvania’s area source
inventory.  As such, spillage and vapor displacement VOC emission
estimates were subtracted from the total VOC emission estimates for all
NONROAD2005 model emissions.  Therefore, only exhaust, crankcase, and
evaporative diurnal components are included in these VOC estimates.

Emissions from nonroad equipment were tabulated in both source
classification code and category format.  Immaterial rounding errors may
exist when comparing the two formats due to different arithmetic
operations performed inside and outside the NONROAD2005 model for the
two formats.

III.	2002 LOCOMOTIVE EMISSIONS

Much of the locomotive emissions were captured from a 1999 survey
conducted by the Department included hydrocarbon (HC) and NOx for the
following locomotive source categories:

2285002006 :	Railroad Equipment, Diesel, Line Haul Locomotives: Class I
Operations

2285002007:	Railroad Equipment, Diesel, Line Haul Locomotives: Class
II/III Operations

2285002008:   Railroad Equipment, Diesel, Line Haul Locomotives:
Passenger Trains (Amtrak)

2285002010:  Railroad Equipment, Diesel, Yard Locomotives

All line haul locomotive emissions were grouped into one SCC category in
the appendix, 2285002005.

Norfolk Southern and CSX Corporations purchased Conrail.  The takeover
of Conrail’s assets occurred in June 1999.  For that reason, it was a
very bad time to develop a representative emission inventory for these
railroads.  Both Conrail and Norfolk Southern suffered major gridlock in
Pennsylvania and beyond during 1999.  Consequently, fuel consumption and
air emissions for these two railroads were greatly reduced in 1999.  The
Department requested and received 2002 fuel usage from these railroad
companies and developed a 2002 emissions inventory for them.  Fuel
consumption increased 60 percent from 1999 to 2002.  Clearly, this was
not due to normal economic growth.  All other emissions from railroad
companies operating in Pennsylvania in 1999 were grown with a growth
factor to obtain 2002 emissions.

To estimate 2004, 2009, and 2018 locomotive emissions, the Department
projected the 2002 inventory to 2004 and beyond using national fuel
consumption information supplied to the Department by the Association of
American Railroads in combination with emissions factors developed by
EPA and presented on the EPA website in the Emissions Factors for
Locomotives, EPA420-F-97-051, December 1997, Table 9, Fleet Average
Emission Factors For All Locomotives.  According to the Association of
American Railroads, national railroad annual fuel consumption has grown
consistently at about 1.6 percent over the last 15 years.  We used the
following normalized emission growth factors for locomotive emissions. 
These numbers compare well with the EPA Economic Growth Analysis System
(EGAS) 5.0 in the near-term.  The only differences are that EGAS 5.0
forecasts a slightly larger reduction of NOx emissions in 2018 and a
much larger VOC reduction in some future years.  VOC emissions from
locomotives are typically very small.  EGAS 5.0 may be downloaded from
http://www.epa.gov/ttn/ecas/egas5.htm.

Table 4.  Normalized Growth Factors for Locomotives



Year	Fuel Use Growth	NOx Emission Factors	NOx Emission Growth (Fuel use
growth * emission factor)	HC/VOC Emission Factors	HC/VOC Emission Growth
(Fuel use growth * emission factor)

2002	1.0000	1.0000	1.0000	1.0000	1.0000

2004	1.0323	0.8766	0.9049	1.0000	1.0323

2009	1.1175	0.6765	0.7560	0.8785	0.9817

2018	1.2891	0.5804	0.6553	0.7664	0.9880



  

In the Regulatory Support Document (RSD) for locomotive emission
standards, national emissions account for future, phased-in controls
that will primarily reduce NOx and HC emissions as well (EPA, 1997). 
Emission reductions, which include rule effectiveness and rule
penetration, are estimated based on the percent change in emissions from
the base year to a given projection year.  The Department reduced or
increased the 2002 locomotive emissions for NOx and VOC by the factors
shown in Table 4.   

  SEQ CHAPTER \h \r 1 To estimate VOC emissions from HC, the Department
applied a VOC/HC conversion factor of 1.005 to the HC emissions.  This
conversion factor was obtained from EPA’s Documentation for Aircraft,
Commercial Marine Vessel, Locomotive, and Other Nonroad Components of
the National Emission Inventory, Volume I: Methodology (EPA, 2002).

Estimated annual emissions were divided by 365 to obtain a daily
emission estimate which was assumed to be a good estimate for emissions
during an average summer day.

IV.	Aircraft Emissions

 

Emissions from air carriers for 2002 are estimated using the Emissions &
Dispersion Modeling System (EDMS) 4.20.  Very few of the aircraft
operations in these particular 12 counties are considered to be air
carrier operations (an aircraft that can seat more than 60 passengers). 
Air carrier aircraft operations were insignificant at airports in these
12 counties.  Emissions were not modeled with the EDMS model directly. 
A description of EDMS calculation methods is included because some
information from the model is used in estimating emissions from the
smaller airports in the county.    

Commercial airport operations data.  Airport specific data on operations
were found at   HYPERLINK "http://www.transtats.bts.gov" 
www.transtats.bts.gov  and also the FAA’s Terminal Area Forecast found
at http://www.apo.data.faa.gov. Operations data on all significantly
large regional airports in Pennsylvania could be found at this website,
although some of the airports modeled supported very few commercial
flights.  We used default values in the EDMS model for aircraft engines
and service equipment for each aircraft type.  These emissions covered
all air carrier and air taxi service at these airports. 

Mixing height in EDMS.  It was determined that a better mixing height
than the model’s default value could be used in EDMS.  Upper air
meteorological data available from Sterling Virginia in combination with
surface data measurements taken at the Philadelphia International
Airport generated 1-hr mixing heights in the meteorological preprocessor
model PCRAMMET, EPA, PCRAMMET (software), Research Triangle Park, NC,
June 1999.  All mixing heights between 10 a.m. and 6 p.m. were not
considered when generating these averages because an extremely small
percentage of flight operations occur between those hours.  The average
summer mixing height was 4,428 feet for airports in the Eastern
Pennsylvania.  The default value of 3000 feet was used for all other
airports.

Air taxi emission estimation methodology.  We used emission factors from
EDMS for a common aircraft used in air taxi service to calculate
emissions from air taxi operations.  Air taxi ground support equipment
emission estimates produced by the NONROAD model were used.  

Small airport emission estimation methodology. Small aircraft emissions
were calculated by using small airport operation statistics, which can
be found at   HYPERLINK "http://www.airnav.com"  www.airnav.com .  An
emissions factor for a typical air general aviation single engine,
multi-engine, and jet engine aircraft were derived by averaging the
emissions factors from a basket of emission factors for common aircraft
of each of the three types of aircraft.  Emission factors and
operational characteristics contained in EDMS were used.  The proportion
of operations between the three groups of aircraft was determined by
examining the number of each aircraft type based at each airport.  For
military operations at small airports, the type of aircraft and its
emission factors are sometimes identifiable.  If not, emission factors
calculated to represent an “average” military aircraft are used. 
Growth was estimated using estimates of small airport activity from
Federal Aviation Administration’s APO Terminal Area Forecast Detailed
Report.  The FAA Terminal Area Forecast predicts growth for most
airports in the 12-county area.  The results are in the table below:

County	2002-2004 Normalized Growth Estimate	2002-2009 Normalized Growth
Estimate	2002-2018 Normalized Growth Estimate

Columbia	0.98	1.06	1.25

Crawford	0.63	0.62	0.56

Juniata	1.00	1.00	1.00

Lawrence	0.74	0.75	0.79

Northumberland	1.00	1.08	1.27

Pike*	0.00	0.00	0.00

Schuylkill	0.94	0.97	1.03

Snyder	0.97	1.07	1.26

Susquehanna*	0.00	0.00	0.00

Somerset	1.00	1.00	1.00

Warren*	0.00	0.00	0.00

Wayne	1.00	1.00	1.00

		*0.00 growth indicates that no airports are located in those counties.

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