ERG No.: 0245.03.402.001
Contract No.: EP-D-07-097



### Documentation for Aircraft Compone nt of the National Emissions

Inventory Methodology

Prepared by:

Eastern Research Group
1600 Perimeter Park Drive Morrisville, North Carolina 27560

Under Contract to: E.H. Pechan & Associates, Inc. 3622 Lyckan Parkway
Suite 2002 Durham, North Carolina 27707

For Submittal to:

Laurel Driver Emissions, Monitoring and Analysis Division U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27711

January 27, 2011i TABLE OF CONTENTS

Section Page No.

1.0 INTRODUCTION ........................................................................................................... 1-1
1.1 What is the National Em ission Inventory? .......................................................... 1-1

1.2 Why Did the EPA Create the NEI? ...................................................................... 1-1

1.3 How is the EPA Going to Use This Version of the NEI? .................................... 1-1

1.4 Report Organization ............................................................................................. 1-2

2.0 DEVELOPMENT OF THE AIRCRAFT COMPONENT FOR THE NEI ..................... 2-1
2.1 How does this aircraft study fit into the NEI? ..................................................... 2-1

2.2 What are Aircraft Sources? ................................................................................ 2-11

2.3 What Pollutants are Included in th e National Emission Estimates for

Aircraft? ............................................................................................................. 2-11

2.4 How Were the Aircraft Emissions Estimated? .................................................. 2-12

2.5 How Were Emissions Allocated? ...................................................................... 2-17

2.6 QA/QC ............................................................................................................... 2-17

2.7 What are the Results?......................................................................................... 2-17

2.8 Aircraft References ............................................................................................ 2-20

Appendix A – Generic Airc raft Emission Factors

Appendix B – Calculating Piston- Engine Aircraft Airport Inve ntories for Lead for the 2008 National Emissions Inventoryii LIST OF TABLES AND FIGURES

Tables Page No.

Table 2-1a. Methods Used to Develop Emission Estimates for Onroad Vehicle Sources .......... 2-2 Table 2-1b. Methods Used to Develop A nnual Emission Estimates for Nonroad
Mobile Sources ................................................................................................................ ............ 2-4
Table 2-2. Aircraft Pollutant List ............................................................................................ ... 2-12
Table 2-3. National-Scale GSE Engine Distribution ................................................................. 2-14
Table 2-4. Aircraft Criteria Emissi on Estimates 2008 (tons per year) ...................................... 2-18
Table 2-5. Aircraft HAP Emission Es timates 2008 (tons per year) ........................................... 2-18

Figures Page No.

Figure 2-1. Procedures for Estimating Emissi ons from Commercial Air Carriers .................... 2-14 Figure 2-2. Procedures for Estimating Emissions from Commercial Ai r Taxis and General
Aviation....................................................................................................................... ............... 2-151-1 

### 1.0 INTRODUCTION

1.1 What is the National Emission Inventory?

The National Emission Inventory (NEI) is a comprehensive i nventory covering all anthropogenic sources of criteria pollutants and hazardous air pollutants (HAPs) for all areas of the United States. The NEI was created by the U.S. Environmental Protection Agency’s Emission Inventory and Analysis Group (EIAG) in Research Triangle Park, North Carolina. The NEI will be used to support air quality modeli ng and other activities. To this end, the EPA established a goal to compile comprehensive emissi ons data in the NEI for criteria and HAPs for mobile, point, and nonpoint sources. This report presents an overview of how emission estimates for the aircraft component of the NEI were compiled.

1.2 Why Did the EPA Create the NEI?

The Clean Air Act (CAA), as amended in 1990, includes mandates for the EPA related to criteria and hazardous air polluta nts. The CAA defines criteria pollutants as being one of the following air pollutants:

 Carbon monoxide (CO);

 Sulfur oxides (SO
x );

 Nitrogen oxides (NO
x );

 Ozone; and

 Particulate matter (PM).

Hazardous air pollutants are also delineated in the CAA, see http://www.epa.gov/ttn/atw/188polls.html for a complete list of re gulated pollutants and their chemical abstract service [CAS] numbers.

The CAA requires the EPA to identify emi ssion sources of these pollutants, quantify emissions, develop regulations for the identified source categories, and assess the public health and environmental impacts after th e regulations are put into effect . The NEI is a tool that EPA
can use to meet the CAA mandates. In this re port, criteria and HAP emission estimates are
discussed for aircraft sources.

1.3 How is the EPA Going to Use This Version of the NEI?

It is anticipated that the emission inventory developed from this effort will have multiple end uses. The data have been formatted according to protocols established for the EPA’s NEI
submittals. The common data structure on which th e NEI platform is based will allow the NEI emission data to be transferred to multiple end-users for a variety of purposes.1-2 The criteria and HAP emission estimates devel oped for the NEI will be used to evaluate air pollution trends, air quality modeling anal ysis, and impacts of potential regulations.

1.4 Report Organization

Following this introduction, Section 2.0 provide s information on how the national aircraft emission estimates were develope d. This inventory effort was c oordinated by the EPA’s Office of Transportation and Air Quality (OTAQ) and EIAG. The appendixes were created to provide the supporting references from OTAQ.2-1 

### 2.0 DEVELOPMENT OF THE AIRC RAFT COMPONENT FOR THE
NEI

2.1 How does this aircraft study fit into the NEI?

The NEI was developed to include all point, nonpoint (sometimes referenced as “area”), and mobile sources. The approaches used in the point and nonpoint s ource categories are documented in other reports. Table 2-1 summarizes the approaches used to estimate emissions from all nonroad sources included in the NEI pr ogram. Those source categories and years that are included in this report are noted in bold.

The scope of this inventory component of the NEI was to compile criteria and HAP emissions data for aircraft operating in United Stat es air space. In this effort, national emission estimates were often developed as point sources for each airport. The methodologies used to estimate emissions are discussed in this report.

The target inventory area includes every st ate in the United States and every county within a state, including Wash ington, DC, Puerto Rico, and US Virgin Islands. There are no boundary limitations pertaining to traditional cr iteria pollutant nonattainment areas or to designated urban areas. The pollutants inventorie d included all criteria pollutants (and the
188 HAPs identified in Sec tion 112(b) of the CAA).

In addition to numerous specific chem ical compounds, the list of 188 HAPs includes several compound groups [e.g., individual metals and their compounds, polycyclic organic matter (POM)]; the NEI includes emission esti mates for the individual compounds wherever possible. Many of the uses of the NEI depend up on data (e.g., toxicity) for individual compounds within these groups rather than aggreg ated data on each group as a whole.

The intent in presenting the following em ission inventory approach is to provide sufficient and transparent documentation such th at states and local agencies can use these approaches, in conjunction with th eir specific local activity data to develop more accurate and comparable emission estimates in future submittals.

This documentation is not meant to provide an exhaustive analysis on the derivation of all the inputs. For example, an emission factor used for a national estimate may be given in the appendix, but the source test data that were evaluated to obtain th is factor may not be presented or discussed. The goal of the documentation provid ed is to show in a brief and concise manner how a given estimate was derived.2-2Table 2-1a. Methods Used to Develop Emission Estimates for Onroad Vehicle Sources(Years addressed in this report are noted in bold print)Base Year(s)Pollutant(s)Geographic AreaEmission Estimation Method2008 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed using EPA’s National MobileInventory Model (NMIM), which uses MOBILE6 (specifically,M6203ChcOxFixNMIM.exe) to calculateonroad emission factors. Where Statesprovided alternate onroad MOBILE6 inputsor VMT, these data replaced EPA defaultinputs. Default VMT is based on FHWA 2008 data and 2008 Census populationestimates.2005 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed using EPA’s NMIM,which usesMOBILE6 to calculate onroad emission factors. Where Statesprovided alternateonroad MOBILE6 inputs or VMT, these data replaced EPA default inputs. DefaultVMT is based on FHWA 2005 data and 2005 Census population estimates.2002 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed using EPA’s NMIM,which usesMOBILE6 to calculate onroad emission factors. Where Statesprovided alternateonroad MOBILE6 inputs or VMT, these data replaced EPA default inputs. Californiasupplied emissions data which replaced defaultEPA emission estimates for this state.Default VMT is based on FHWA 2002 data and population data from 2000 Census.2001VOC, NOx, CO, SO2, PM10,PM2.5California Emissions and VMT provided by California at county/vehicle type level; Stateprovided emissions expanded to county/SCC level by EPA.2001NH3California Calculated at State/county/SCC level by month using MOBILE6 emission factors withState-provided VMT data.2001All CriteriaAL; CO; ME; MA; MS; OR; UT; VA;WV; Maricopa County, AZ; HamiltonCounty, TNState-provided VMT grown to 2001; emissions calculated by EPA using MOBILE6emission factors.2001All CriteriaRest of US Calculated at State/county/SCC level by month using MOBILE6 and FHWA-basedVMT.1999All CriteriaAL; ME; MA; MS; UT; VA; WV;Maricopa County, AZ; HamiltonCounty, TNCalculated at State/county/SCC level by month using MOBILE6; State-providedVMT data used.1999VOC, NOx, CO, SO2, PM10,PM2.5California Emissions and VMT provided by California at county/vehicle type level; Stateprovided emissions expanded to county/SCC level by EPA.1999NH3California Calculated at State/county/SCC level by month using MOBILE6 emission factors withState-provided VMT data.1999PM10ExhaustColorado PM10emissions and VMT provided by State.2-3Table 2-1a. Methods Used to Develop Emission Estimates for Onroad Vehicle Sources(Years addressed in this report are noted in bold print)Base Year(s)Pollutant(s)Geographic AreaEmission Estimation Method1999VOC, NOx, CO, SO2, PM10brake and tire wear, PM2.5,NH3Colorado Calculated at State/county/SCC level by month using MOBILE6; State-providedVMT data used.1999All CriteriaOregon Emissions and VMT provided by Oregon at county/vehicle type level; State-providedemissions expanded to county/SCC level by EPA.1999All CriteriaRest of US, Puerto Rico, and USVirgin IslandsCalculated at State/county/SCC level by month using MOBILE6 and FHWA-basedVMT.1999HAPsCalifornia HAP emissions and VMT provided by California at county/vehicle type level;emissions allocated to SCC level by EPA.1999HAPsRest of US, Puerto Rico, and USVirgin IslandsMOBILE6 emission factors calculated at State/county/SCC level by season; applied toFHWA-based VMT.1997-1998All CriteriaUS 2-step linear interpolation at State/count/SCC level based on 1996 and 1999State/count/SCC level data.1990, 1996HAPsUS MOBILE6 emission factors calculated at State/county/SCC level by season; applied toFederal Highway Administration (FHWA)-based vehicle miles traveled (VMT).1991-1995All CriteriaUS Linear interpolation at State/count/SCC level based on 1990 and 1996State/count/SCC level data.1988-1989All CriteriaUS Linear interpolation at State/count/SCC level based on 1987 and 1990State/count/SCC level data.1979-1986All CriteriaUS Linear interpolation at State/count/SCC level based on 1978 and 1987State/count/SCC level data.1978, 1987,1990, 1996,2000All CriteriaUS Calculated at State/county/source classification code (SCC) level by month usingMOBILE6, no State data incorporated.1970, 1975All CriteriaUS Linear extrapolation at national vehicle type level based on 1978 and 1987 nationaldata.2-4Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*NONROAD CategoriesNonroad Gasoline,Diesel, LPG,CNG2008 VOC, NOx, CO, SO2,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines weredeveloped using EPA’s National Mobile InventoryModel (NMIM), which incorporates NONROAD2008.Where states providedalternate NMIM nonroadinputs, these data replaced EPA default inputs.2005 VOC, NOx, CO, SO2, ,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines were developed using EPA’s NMIM, which incorporatesNONROAD2005. Where States providedalternate nonroad inputs, these data replaced EPA default inputs.2002 VOC, NOx, CO, SO2,PM10, PM2.5, NH3, &HAPsEmission estimates for NONROAD model engines were developed using EPA’s NMIM, which incorporatesNONROAD2004. Where states provided alternate nonroad inputs, these data replaced EPA default inputs.State-supplied emissions data also replaced default EPA emission estimates.1999 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROADmodel; and 2) an updated 1999 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated fromthe Lockdown C model. Replaced State-submitted datafor California for all NONROAD model categories; Pennsylvania for recreational marine and aircraft groundsupport equipment, and Texas forselect equipment categories.1996, 1997,1998, 2000 &2001VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated year-specific national andCalifornia inventories, based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the1996 county-level emission estimates, seasonal and daily county-to-national ratios and California county-tostate ratios were then developed for application to updated national estimates per season estimated from theLockdown C model. California results replace the diesel equipment emissions generated from priorapplication of county-to-national ratios.2-5Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Nonroad Gasoline,Diesel, LPG, andCNG(Continued)1991-1995 VOC, NOx, CO, SO2,PM10, PM2.5, NH3Using 1990 and 1996 county-level emissions inventories, estimated emissions using linear interpolation ofnational emissions between 1990 and 1996. From these emissions, calculated the average annual growth ratefor each pollutant/SCC combination for each year, and thenapplied the growth factors to 1990 county-levelemissions to estimate 1991-1995 emissions.1990 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1990 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated from the Lockdown C model.1986, 1988, &1989VOC, NOx, CO, SO2,PM10, PM2.5, NH3Using 1985 and 1990 county-level emissions inventories, estimated emissions using linear interpolation ofnational emissions between 1985 and 1990. From these emissions, calculated the average annual growth ratefor each pollutant/SCC combination for each year, and thenapplied the growth factors to 1985 county-levelemissions to estimate 1986-1989 emissions.1987 VOC, NOx, CO, SO2,PM10, PM2.5Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated nationalemissions for 1987 by running 4 seasonal NONROAD model runs to estimate annual criteria pollutantemissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.1985 VOC, NOx, CO, SO2,PM10, PM2.5Using emission estimates from two emission inventories including: 1) a 1996 county-level inventory,developed using EPA’s October 2001 draft NONROAD model; and 2) updated 1985 national inventory,based on EPA’s draft Lockdown C NONROAD model (dated May 2002). Using the 1996 county-levelemission estimates, seasonal and daily county-to-national ratios were then developed for application toupdated national estimates per season estimated from the Lockdown C model.1970, 1975,1978, & 1980VOC, NOx, CO, SO2,PM10, PM2.5Using EPA’s draft Lockdown C NONROAD model (dated May 2002), developed updated nationalemissions for all years by running 4 seasonal NONROAD model runs to estimate annual criteria pollutantemissions. Also performed national NONROAD model runs to estimate typical summer weekday emissions.2-6Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Nonroad Gasoline,Diesel, LPG, andCNG(Continued)1996, 1997,1998, 1999,2000, & 2001NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying byNH3emission factors, and distributing to counties using 1996 inventory, based on October 2001 draftNONROAD. NH3emissions for California were also recalculated using updated diesel fuel consumptionvalues generated for California-specific runs, and assuming the 1996 county-level distribution.1985 & 1990 NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model, multiplying byNH3emission factors, and distributing to counties using 1996 inventory, based on October 2001 draftNONROAD.1987 NH3Obtaining 1987 national fuel consumption estimates from Lockdown C NONROAD model and multiplyingby NH3emission factors.1970, 1975,1978, & 1980NH3Obtaining national fuel consumption estimates from the Lockdown C NONROAD model and multiplying byNH3emission factors.1990, 1996, &1999HAPs Speciation profiles applied to county VOC and PM estimates. Metal HAPs were calculated using fuel andactivity-based emission factors. Some state data were provided and replacednational estimates. (2003)AircraftCommercialAircraft2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System (EDMS) - Version5.1.was run using BTS T-100 LTO data. (2009)2002 and 2005 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion and Modeling System (EDMS) was runfor criteria pollutants, VOC and PM emissions were speciated into HAP components. (2004)1990, 1996,1999, 2000,2001VOC, NOx, CO, SOxInput landing and take-off (LTO) data into FAA EDMS. National emissions were assigned to airports basedon airport specific LTO data and BTS GIS data.State data replaced national estimates. (2003)1970-1998 VOC, NOx, CO, SOxEstimated emissions for interim years using linearinterpolation between available base years. (2003)1990, 1996,1999HAPs Speciation profiles were applied to VOC estimates to get national HAP estimates. State data replacednational estimates. (2003)General Aviation,Air Taxis2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System (EDMS) - Version5.1.was run using BTS T-100 LTO for aircraft identified as Air taxis. (2010)Used FAA LTO data from TAF and OTAQ provided activity data for smaller airports derived fromFAA 5010 master plans. EPA approved generic emission factors for criteria estimates. Speciationprofiles were applied to VOC and PM estimates to get national HAP estimates. (2010)2-7Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*General Aviation,Air Taxis(Continued)2005 VOC, NOx, CO, SO2,PM10, PM2.52002 emissions for approximately 4,000 largest airports were calculated via EDMS and SIP guidance andincluded in the 2005 NEI as point sources. Only airports in FAA’s T100 and TAF databases were included.State point source submittals were incorporated.1978, 1987,1990, 1996,1999, 2000,2001, & 2002VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data and EPA approved emission factors for criteria estimates. Speciation profiles wereapplied to VOC estimates to get national HAP estimates. State data replaced national estimates. (2004)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999, & 2002HAPs Used FAA LTO data and EPA approved emission factors for criteria estimates. Speciation profiles wereapplied to VOC estimates to develop national HAP estimates. (2004)1990, 1996,1999, & 2002Pb Used Department of Energy (DOE) aviation gasoline usage data with lead concentration of aviation gasoline.(2004)1996 NH3Applied NH3emissions factors to 1996 national jet fuel and aviation gasoline consumption estimates.Military Aircraft2008 VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data as reported in TAF and EPAapproved emission factors for criteria estimates.Representative HAP profiles were not readily available, therefore HAP estimates were not developed.(2010)2005 VOC, NOx, CO, SO2,PM10, PM2.52002 emissions were included in the 2005 NEI as point sources similar to other TAF reported data.1978, 1987,1990, 1996,1999, 2000,2001, 2002,2008VOC, NOx, CO, SO2,PM10, PM2.5Used FAA LTO data as reported in TAF and EPA approved emission factors for criteria estimates.Representative HAP profiles were not readily available, therefore HAP estimates were not developed.1970-1998 VOC, NOx, CO, SOX,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)Auxiliary PowerUnits and GroundSupportEquipment2008 VOC, NOx, CO, SO2,PM10, PM2.5, HAPsFederal Aviation Administration (FAA) Emissions and Dispersion and Modeling System (EDMS) -Version 5.1.was run using BTS T-100 LTO data. (2009)2002 and 2005 VOC, NOx, CO, SO2,PM10, PM2.5, HAPsComputed via NONROAD2005 model runs.1985-2001 VOC, NOx, CO, SO2,PM10, PM2.5Grew 1996 emissions to each year using LTO operations data from the FAA. Estimation methods prior to1996 reported in EPA, 1998.2-8Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Unpaved Airstrips11985-2001 PM10, PM2.5Grew 1996 emissions to each year using SIC 45-Air Transportation growth factors, consistent with thecurrent draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998.Aircraft Refueling11985-2001 VOC Grew 1996 emissions to each year using SIC 45-Air Transportation growth factors, consistent with thecurrent draft version of EGAS. Estimation methods prior to 1996 reported in EPA, 1998.Commercial Marine Vessel (CMV)All CMV Categories 2008 VOC, NOx, CO, SO2,PM10, PM2.5OTAQ provided CAP emission estimates for all CMV categories. Note that the SCCs for this category havechanged such that the Diesel category refers to smaller vessels (Category 1 and 2) using distillate fuels andthe Residual category refers to larger (Category 3) vessels using a blend of residual fuels. Emissions wereallocated to segments using GIS shapefiles and adjusted based on limited state data (2010)2008 HAPs OTAQ’s 2008 estimates were speciated into HAP components using SEPA profiles (2009)CMV Diesel 2002 and2005VOC, NOx, CO, SO2,PM10, PM2.52001 Estimates carried over. Usedstate data when provided. (2004)HAPs 1999 Estimates carried over. Used state data when provided. (2004)1978, 1987,1990, 1996,1999, 2000, &2001VOC, NOx, CO, SOx,PM10, & PM2.5Used criteria emission estimates in the background document for marine diesel regulations for 2000.Adjusted 2000 criteria emission estimates for other used based on fuel usage. Emissions were disaggregatedinto port traffic and underway activities. Port emissions were assignedto specific ports based on amount ofcargo handled. Underway emissions were allocated based on Army Corp of Engineering waterway data.State data replaced national estimates. (2003)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999HAPs VOC and PM emission estimateswere speciated into HAP components. State data replaced nationalestimates. (2003)1996 NH3Applied NH3emissions factors to 1996 distillate and residualfuel oil estimates (i.e., as reported in EIA,1996).1990-1995 NH3Estimation methods reported in EPA, 1998.2-9Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*CMV SteamPowered2005 VOC, NOx, CO, SOx,PM10, & PM2.5,HAPs2002 estimates grown to 2005 (2008).2002 VOC, NOx, CO, SOx,PM10, & PM2.5,HAPs2002 based estimates were developed for port and underway category 3 (C3) vessels aspart of a rulemakingeffort. Emissions were developed separately for near port and underway emissions. For near port emissions,inventories for 2002 were developed for 89 deep water and 28 Great Lake ports in the U.S. The WaterwayNetwork Ship Traffic, Energy, and EnvironmentalModel (STEEM) was used to provide emissions fromships traveling in shipping lanes between and near individual ports (2008)1978, 1987,1990, 1996,1999, 2000, &2001VOC, NOx, CO, SOx,PM10, & PM2.5Calculated criteria emissions based on EPA SIP guidance. Emissions were disaggregated into port trafficand under way activities. Port emissions were assignedto specific ports based onamount of cargo handled.Underway emissions were allocated based on Army Corpof Engineering waterway data. State data replacednational estimates. (2003)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996, &1999HAPs VOC and PM emission estimateswere speciated into HAP components. State data replaced nationalestimates. (2003)Military Marine 1997-2001 VOC, NOx, CO, SO2,PM10, PM2.5Applied EGAS growth factors to 1996emissions estimates for this category.CMV Coal,2CMV,Steam powered,CMV Gasoline21997-1998 VOC, NOx, CO, SO2,PM10, PM2.5Applied EGAS growth factors to 1996emissions estimates for this category.CM Coal, CMV,Steam powered,CMV Gasoline,Military Marine1991-1995 VOC, NOx, CO, SO2,PM10, PM2.5Estimation methods reported in EPA, 1998.LocomotivesClass I, II, III andYard operations2008 VOC, NOx, CO, PM10,PM2.5,SOx& HAPsCriteria emission estimates were provided to EPA by ERTAC. These data were assigned to individualrailway segments using DOT shapefiles and guidance from ERTAC. HAP emissions were calculated byapplying speciation profiles to VOC and PM estimates. (2010)2-10Table 2-1b. Methods Used to Develop Annual Emission Estimates forNonroad Mobile Sources (Continued)(Categories included in this report are noted in bold print)CategoryBase YearPollutant(s)Estimation Method*Class I, Class II,Commuter,Passenger, and YardLocomotives1978, 1987,1990, 1996,1999, 2000,2000, 2002, &2005VOC, NOx, CO, PM10,PM2.5Criteria pollutants were estimated by using locomotive fuel use data from DOE EIA and available emissionfactors. County-level estimates wereobtained by scaling the national estimates with the rail GIS data fromDOT. State data replaced national estimates. (2004)1978, 1987,1990, 1996,1999, 2000,2001, 2002, &2005SO2SOxemissions were calculated by using locomotive fuel use and fuel sulfur concentration data from EIA.County-level estimates were obtained by scaling the national estimates with the county level rail activitydata from DOT. State data replaced national estimates. (2004)1970-1998 VOC, NOx, CO, SOx,PM10, PM2.5Estimated emissions for interim years using linear interpolation between available base years. (2003)1990, 1996,1999, & 2002HAPs HAP emissions were calculatedby applying speciation profiles toVOC and PM estimates. County-levelestimates were obtained by scaling the national estimates with the county level rail activity from DOT. Statedata replaced national estimates. (2004)1997-1998 NH3Grew 1996 base year emissions using EGAS growth indicators.1996 NH3Applied NH3emissions factors to diesel consumption estimates for 1996.1990-1995 NH3Estimation methods reported in EPA, 1998.Notes:*Dates included at the end of Estimation Method represent the year that the section was revised.1 Emission estimates for unpaved airstrips and aircraft refueling are included in the area source NEI, since they represent non-engine emissions.2 National Emission estimates for CMV Coal and CMV Gasoline were not developed though states and local agencies may have submitted estimates for thesesource categories.EPA, 1998. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Emission Factors and Inventory Group, National AirPollutant Emission Trends, Procedures Document, 1900–1996, EPA-454/R-98-008. May 1998.2-11 2.2 What are Aircraft Sources?

The aircraft source category includes all ai rcraft types used for public, private, and military purposes. This includes four types of ai rcraft (EPA, 1992): 1) Commercial; 2) Air Taxis; 3) General Aviation; and 4) Military.

Commercial aircraft include those used fo r transporting passengers, freight, or both.
Commercial aircraft tend to be larger aircraft powered with jet engines. Air Taxis (AT) carry passengers, freight, or both, but us ually are smaller aircraft and operate on a more limited basis
than the commercial carriers. General Aviation (GA) includes most other aircraft used for recreational flying and personal tr ansportation. Aircraft that su pport business travel, usually on an unscheduled basis, are included in the category of general aviation.

The national AT and GA fleet includes both je t and piston-powered aircraft. Most of the AT and GA fleet are made up of piston powered airc raft, though smaller business jets can also be found in these categories. According to a 2008 Federal Aviation Administration GA and AT Activity Survey, 66% of all GA and AT activit y are powered by piston- powered aircraft and 34% are jet (or turbine) driven. EPA has used th is estimate as a national-scale default value in recently published studies investigating lead em issions from aviation sources (EPA, 2008). The piston powered aircraft tend to have higher VOC, PM, and CO emissions and lower NO X emissions than larger jet-powered aircraft (EPA, 1992). Military ai rcraft cover a wide range of aircraft types such as training aircraft, fighter jets, helicopters, and jet- and a small number of piston powered planes of varying sizes.

It should be noted that this inventory effort also include s criteria and Hazardous Air Pollutants (HAP) emission estimates for aircraft Auxiliary Power Units (APU) and aircraft Ground Support Equipment (GSE) typical ly found at airports, such as aircraft refueling vehicles, baggage handling vehicles, and equipment, ai rcraft towing vehicles, and passenger buses.

2.3 What Pollutants are Included in the Nati onal Emission Estimates for Aircraft?

Emissions estimates were developed for all cr iteria pollutants includ ing volatile organic compounds (VOC), nitrogen oxides (NO
x ), carbon monoxide (CO), sulfur oxides (SO
x ), particulate matter less than 10 microns (PM 10 ), particulate matter less than 2.5 microns (PM 2.5 ) and hazardous air pollutants (HAP) (Cook, 1997; Cook, 1998; EPA/FAA, 2009). The HAPs that are included in the national aircraft inventory ar e shown in Table 2-2 and are based on available test data and accepted emission estimation procedures.2-12 Table 2-2. Aircraft Pollutant List

1,3-Butadiene Carbon Dioxide Naphthalene

1-Methylnaphthalene* Carbon Monoxide Nitrogen Oxides

2,2,4-Trimethylpentane Chrysene* O-xylene*

2-Methylnaphthalene* Cumene* Phenanthrene*

Acenaphthene* Dibenzo[a,h]Anthracene* Phenol

Acenaphthylene* Ethyl Benzene PM 10 Primary
Acetaldehyde Fluoranthene* PM 2.5 Primary

Acrolein Fluorene* Propionaldehyde

Anthracene* Formaldehyde Pyrene*

Benz[a]Anthracene* Hexane* Styrene

Benzene Indeno[1,2,3-c,d]Pyrene* Sulfur Dioxide

Benzo[a]Pyrene* Lead Toluene

Benzo[b]Fluoranthene* Methane* VOCs

Benzo[g,h,i,]Perylene* Methanol* Xylene

Benzo[k]Fluoranthene* M-xylene*

* Added to 2008 Inventory

2.4 How Were the Aircraft Emissions Estimated?

EPA has developed guidance for inventorying aircraft emissions associated with an aircraft’s landing and takeoff (LTO) cycle. The cycle begins when the aircraft approaches the airport on its descent from cruisi ng altitude, lands, taxis to th e gate, and idles during passenger deplaning. It continues as the aircraft idles du ring passenger boarding, taxis back out onto the runway for subsequent takeoff, and ascent (climb out) to cruising altitude. Thus, the five specific operating modes in an LTO are (EPA, 1992): 1) A pproach; 2) Taxi/idle-in; 3) Taxi/idle-out; 4) Takeoff; and 5) Climbout.

The LTO cycle provides a basis for calculati ng aircraft emissions. During each mode of operation, an aircraft engine operates at a fairly standard power setting for a given aircraft category. Emissions for one complete cycle ar e calculated using emission factors for each operating mode for each specific aircraft engine combined with the typical period of time the aircraft is in the operating mode.

On March 20, 2009, the EPA posted preliminar y LTO data intended to be will use to calculate emissions for review prio r to developing the aircraft i nventory. State and local agencies were encouraged to review the materials posted at ftp://ftp.epa.gov/Emis Inventory/2008_nei/ and provide comments on any necessary corrections to:2-13  Airport names and locations for approximate ly 20,000 airports to be included in the Emission Inventory System (EIS) facility inventory;

 Landing and Takeoff (LTO) information that will be used to estimate emissions for each airport;

 Aircraft/engine combinations to link to F AA LTO data including default assumptions and AircraftEngineCodeTypes for EIS submittals; and

 Lead estimates and lead estimation methodology.

This preliminary review by state, local, and trib al groups provided information that EPA used to improve EPA’s work. EPA received comments fro m four states (i.e., Minnesota Pollution Control Agency - Environmental Analysis and Ou tcomes Division; New Jersey Department of Environmental Protection; Bureau of Air Management, Connecticut Department of Environmental Protection; and Wisconsin Departme nt of Natural Resources (specifically related to Volk Field Air National Guard Base (VOK) in Juneau County Wittman Regional Airport (OSH)) and three local agencies (i.e., Mecklenburg County No rth Carolina; Ventura County
California Air Pollution Control District (Specifically related to Oxnard (OXR), Camarillo (CMA) and Santa Paula (SZP); and - Regiona l Air Pollution Control Agency (Dayton and Montgomery County Ohio)).

Criteria emission estimates are presented here for four different aircraft types: commercial air carrier, air taxis, general avia tion, and military. HAP emission estimates were developed for all aircraft types.

Emissions for commercial air carriers for whic h detailed aircraft-s pecific activity data were available, were calculated differently than the other three aircraft categories (See Figure 2- 1). Criteria and HAP emissions were estimated fo r commercial aircraft by applying aircraft make and model (e.g., Boeing 747-200 series) sp ecific LTO activity data from FAA’s Form 41, Schedules T100 and T100(f) Air Carrier Data to the FAA’s Emissions and Dispersion Modeling System (EDMS), Version 5.1 (DOT, 2008). It should be noted that due to the reporting requirements of T-100, only commercial activities are included in the dataset, and therefore does not include activity data for non- air carrier applications such as general aviation and military.
This distinction lead to a revisi on to EPA’s original aircraft cro sswalk table, also known as the aircraft engine type code, used to match airc raft to EDMS aircraft and to account for double counting between the T-100 data and the TAF data. In the revised crosswal k, aircraft that were previously considered general aviation and military based on aircraft model were changed to air
taxi and commercial air car rier aircraft types base d on the definition of air taxis (i.e., any aircraft
that was not considered an air taxi was classified as an air carrier airc raft). The FAA reviewed the cross walk tables and made additional changes that moved some of the larger air taxis to the commercial air carrier category and some of the smaller commercial air carriers to the air taxi category. The revised crosswalk tabl e is provided in an electronic f ile as supporting data for this study.2-14 Emissions were calculated for each airport individually using airport specific mixing height. The national-scale defau lt values for taxi in and out are seven and nineteen minutes, respectfully. It should be noted that EDMS inco rporates the latest ai rcraft engine emission
factors from the International Civil Aviation Or ganization Engine Exhaust Emissions Data Bank. The EDMS output includes organic HAPs, but not metals.

Figure 2-1. Procedures for Estimating Emissions from Commercial Air Carriers

Emissions for GSE and APU associated with commercial air carriers and air taxis for
which T-100 data were available were estimate d by EDMS, using the assumptions and defaults incorporated in the model. This is significant change from previous NEI year’s emissions where
GSE estimates came from the NONROAD model and APUs were not included in EPA’s estimates. With EDMS, GSE that are assigned to an aircraft are given times (minutes per arrival, minutes per departure) based upon the type of servi ce. For example, a fuel truck servicing a large
commercial aircraft will have a different operating time than the same fuel truck servicing a
commuter aircraft. All EDMS defaults for GSE durat ion and type (e.g., fuel truck, cabin service truck, baggage belt loader) were used. GSE emission factors used by EDMS are derived from
EPA’s NONROAD2005 model and are based on the fo llowing variables: fuel, brake horsepower and load factor. GSE engines burn gasoline, dies el, compressed natural gas (CNG), and liquefied petroleum gas (LPG). EPA has used a national-scal e value to characterize engines type. The GSE engine distribution is shown below in Table 2- 3. Like GSE, APU emissions are the product of operating time. The purpose of an aircraft APU is to provide power to start the main engines and run the heating, cooling, and ventilation sy stems prior to starting the main engines.

Table 2-3. National-Scale GSE Engine Distribution

GSE Engines Type Percent of
Total

Gasoline Fired, 4-Stroke 16.9

Liquefied Petroleum Gas (LPG) Fired 1.65

Compressed Natural Gas (CNG) Fired 1.25

Diesel Fired 80.2

Emissions of criteria pollutants for air taxis, general aviation, and military aircraft were calculated by combining aircraft operations data from FAA’s Terminal Area Forecasts (TAF)
and 5010 Forms. To avoid double counting between the T-100 data set and the TAF/5010 data,2-15 LTOs by airport and aircraft type were summed in the T-100 data and compared with data in the
TAF/5010 data. If the TAF/5010 LTO estimates were larger than the T-100 estimates for a specified aircraft type then th e T-100 values were subtracted from the TAF/5010 values. If the T-100 values were larger than the TAF values, then the TAF values were set to zero. A data set of adjusted TAF/5010 LTOs were provided to OTAQ where additional adjustments were made
to address older data in the TAF and 5010 datasets and to incorporate ot her insights provided by
FAA reviewers.

The TAF/5010 LTO data were dividing into jet and piston powered fractions based on the national observation that 66 percent of all general aviati on and air taxi activities are associated with piston powered aircraft and the remaini ng 34 percent of general aviation and air taxi activities are associated with je t powered aircraft. The adjusted and split TAF/5010 activity data were applied to emission factors as appropriate (See Fi gure 2-2). It should be noted that EDMS calculates organic HAP emissions in the model (metal HAPs are currently not included in the EDMS output). HAP emission estimates for air taxi s, general aviation, and military aircraft were estimated by applying specia tion profiles to VOC or PM 10 emissions estimates. The following equation was used (emission factor are included as Appendix A).

E ixj = LTO i × FR pro-i × EF ij

Where:

E ixj = Emission estimate for aircraft t ype i equipped with engine type x and pollutant j (lbs/year)
LTO i = Annual count of LTO cycl es for aircraft type i

FR
x = Fraction of LTOs equipped with engine type x

EF ij = Generic emission factor for airc raft type i equipped with engine type x and pollutant j (lbs/LTO) i = Aircraft type (i.e., air ta xi, general aviation, and military) x = Engine type (i.e., jet or turboprop, and piston engine) j = Criteria pollutant j

Figure 2-2. Procedures for Estimating Em issions from Commercial Air Taxis and
General Aviation Split into: Jet-Propelled and

Piston-Driven
Aircraft FAA LTO Data

for Air Taxis
and General

Aviation

(5010 and TAF) Apply Criteria and

HAP Pollutant
Emission Factors Apportion
Emissions Based on Airport Activity
for Air Taxis and
General Aviation Split into: Jet-Propelled and

Piston-Driven
Aircraft FAA LTO Data

for Air Taxis
and General

Aviation

(5010 and TAF) Apply Criteria and

HAP Pollutant
Emission Factors Apportion
Emissions Based on Airport Activity
for Air Taxis and
General Aviation2-16 Lead emission estimates were handled differe ntly. Lead emissions are associated with leaded aviation fuel used in piston driven ai rcraft associated with general aviation. Lead emissions per LTO are calculate d using the following equation:

Pb(tons) = (piston-engine LTO) ( 7.34 g Pb/LTO) (0.95) / 907,180 (g/ton)

Where the lead content of aviation gasoline is assumed to be 0.56 grams per liter or 2.12 grams per gallon.

In flight lead emissions were calculate ba sed on national aviation gasoline consumption and similar assumptions noted above about lead fu el content and retention rates. Lead emissions associated with airport LTO activities were s ubtracted from the national fuel based lead emissions to approximate in flight lead emissi ons which were allocated to individual counties
and noted with the code 777.

For additional details on EPA lead emissi on calculation procedures see Calculating Piston-Engine Aircraft Airport Inventories for Lead for the 2008 National Emissions Inventory (included in Appendix B).

HAP Emission Estimates

As noted earlier, EDMS calculate s organic HAP emissions for ai rcraft activity reported in the T-100 dataset. Representative HAP speciation profiles were used to estimate the individual chemical species for each aircraft type includ ed in the TAF/5010 dataset. Profiles are used to split (or speciate) organic gases, hydrocarbons, a nd particulate matter emissions estimates into more individual HAP compounds using the following equation:

E ixj = LTO ix × SP ixj

Where:

E ixj = Emission estimate for aircraft t ype i equipped with engine type x and pollutant j (tons/year)
LTO ix = Annual count of LTO cycles for ai rcraft type i a nd engine type x
SP ixj = Generic speciation profiles for ai rcraft type i equipped with engine type x and pollutant j (tons/LTO) i = Aircraft type (i.e., air ta xi, general aviation, and military) x = Engine type (i.e., jet or turboprop, and piston engine) j = Pollutant j

Appendix A contains the HAP profiles converted to emissions factors used for this 2008 inventory. In this version of the NEI aircraft em issions inventory the foll owing corrections to the
HAP emission estimates were made:

 Acenpthylene was removed from this inventory for SCC 2275050012.2-17  To avoid double counting tota l xylene emissions were removed if speciated xylene
factors were also available.

2.5 How Were Emissions Allocated?

For the 2008 inventory, emissions were indi vidually estimated for each airport. A GIS database obtained from the Bureau of Transporta tion Statistics (BTS) contai ned airport level data with latitude and longitude coordinates.

2.6 QA/QC

Given the significant methodological changes ov er previous inventory efforts, several quality checks were implemented to ensure that these data were developed and allocated in a clear and reproducible manner. So me of the quality checks impl emented include the following:

Emissions allocations and estimations

 All original data importations and transc riptions into the da tabase were doublechecked for errors.

 All calculation methods and approaches we re evaluated for t echnical soundness.

 All unit conversions and equations used to generate results were double-checked for

errors.

 All sources of original data are referenced in the spreadsheet.

 Emission factors were compiled from a va riety of sources. Each emission factor development methodologies were evaluated to identify the most accurate emission factor for use in this inventory effort.

 Emission sums were evaluate d across activity types (e.g., Ai rcraft, APU, and GSE) to ensure they consistently mirror LTO activity levels.

 2008 pollutants and emissions were checked against the 2005 inventory to identify any missing pollutants or major changes compared to previous inventories. Discrepancies were investigated a nd revisions were made as needed.

 The validity of SCC codes, FIP county code s, and pollutant codes were confirmed.

 The validity of Airport and plane id entification codes were confirmed.

2.7 What are the Results?

Table 2-4 summarizes the emission estimates for Aircraft, ground support equipment and APUs for criteria pollutants. Table 2-5 summari zes the emission estimates for individual HAPs. Both tables aggregate the data for all states, in cluding the District of Columbia. Note that the
2008 estimates do not include state submitted emissions data.2-18Table 2-4. Aircraft Criteria Emission Estimates 2008 (tons per year)Pollutant2008Military(2275001000)Commercial(2275020000)GA, Piston(2275050011)GA, Turbine(2275050012)AT, Piston(2275060011)AT, Turbine(2275060012)GSE, Gas(2265008005)GSE, LPG(2267008005)GSE, CNG(2268008005)GSE, Diesel(2270008005)APU(2275070000)CO33,161.20 75,463.61 192,510.69 56,532.07 19,116.38 10,180.90 18,005.13 1,768.69 1,398.67 85,607.61 4,072.84NOX284.92 102,561.46 1,041.55 1,911.11 465.64 2,274.10 1,927.90 189.38 149.76 9,166.44 2,841.72PM10-PRI709.12 1,782.43 3,792.85 1,397.21 242.12 797.03 55.87 5.49 4.34 265.62 457.11PM2.5-PRI92.60 1,776.37 493.07 181.64 44.81 103.65 53.63 5.27 4.17 254.97 457.11SO227.32 10,179.67 160.24 434.33 53.76 439.43 53.21 5.23 4.13 252.99 443.04VOC1,652.02 13,608.67 2,399.79 3,223.93 310.48 2,610.94 615.80 60.49 47.84 2,927.89 313.72Table 2-5. Aircraft HAP EmissionEstimates 2008 (tons per year)Pollutant2008Military(2275001000)Commercial(2275020000)GA, Piston(2275050011)GA, Turbine(2275050012)AT, Piston(2275060011)AT, Turbine(2275060012)GSE, Gas(2265008005)GSE, LPG(2267008005)GSE, CNG(2268008005)GSE, Diesel(2270008005)APU(2275070000)1,3-Butadiene0.87 184.14 29.75 61.04 5.01 44.44 5.321-Methylnaphthalene0.13 26.96 8.94 0.23 6.20 0.782,2,4-Trimethylpentane0.69 1.09 1.55 0.03 0.51 8.95 0.88 0.69 42.542-methylnaphthalene0.11 22.48 7.45 0.20 5.17 0.65Acenaphthene0.36 0.17Acenaphthylene2.03 0.93Acetaldehyde2.21 466.29 18.82 154.57 11.97 113.00 2.43 0.24 0.19 11.57 13.47Acrolein0.02 37.70 1.82 88.61 0.04 32.72Anthracene0.42 6.16E-04 0.19 3.52E-04Benz[a]Anthracene6.09E-04 0.05 9.33E-05 0.02 5.32E-05Benzene0.87 183.48 122.97 60.82 7.58 44.59 10.44 1.03 0.81 49.62 5.30Benzo[a]Pyrene4.52E-04 0.05 5.11E-05 0.02 2.91E-05Benzo[b]Fluoranthene8.89E-04 0.06 0.03Benzo[g,h,i,]Perylene8.11E-06 0.13 8.47E-06 0.06 4.83E-06Benzo[k]Fluoranthene8.89E-04 0.06 0.03Chrysene6.17E-04 0.05 8.69E-05 0.02 4.96E-052-19Table 2-5. Aircraft HAP Emission Estimates 2008 (tons per year) (Continued)Pollutant2008Military(2275001000)Commercial(2275020000)GA, Piston(2275050011)GA, Turbine(2275050012)AT, Piston(2275060011)AT, Turbine(2275060012)GSE, Gas(2265008005)GSE, LPG(2267008005)GSE, CNG(2268008005)GSE, Diesel(2270008005)APU(2275070000)Cumene2.68E-05 0.05 0.11 0.04Ethyl Benzene1.55E-03 2.68 44.63 6.30 1.05 2.32Fluoranthene1.17E-03 0.45 1.29E-03 0.21 7.35E-04Fluorene0.74 0.34Formaldehyde6.36 1,343.45 81.67 445.41 38.06 327.87 7.20 0.71 0.56 34.23 38.82Hexane21.25 0.50Indeno[1,2,3-c,d]Pyrene0.00 0.04 0.02Lead **245.48 8.97Methane0.01 18.96 14.79 14.61 1.44 1.14 69.47Methanol0.02 27.78 65.31 24.11m-Xylene0.14 26.44 0.36 1.58E-04 0.88 3.66 11.09 1.09 0.86 52.74 0.89Naphthalene0.28 54.17 21.11 20.42 5.05 13.86 1.71O-xylene0.08 15.56 2.03 9.30E-05 1.40 2.19 5.43 0.53 0.42 25.80 0.52Phenanthrene0.01 1.25 0.01 0.58 3.27E-03Phenol0.01 11.17 26.27 9.70Propionaldehyde0.38 79.35 1.82 26.30 2.29 19.45 1.48 0.15 0.11 7.04 2.29Pyrene1.42E-03 0.61 1.58E-03 0.28 8.99E-04Styrene0.16 33.73 10.32 11.18 1.18 8.25 0.97Toluene0.33 70.07 315.76 23.23 8.87 16.77 17.77 1.75 1.38 84.50 2.02Xylenes (MixedIsomers)4.85 177.92 19.04 4.18 6.21**The lead estimated provided above represent emissions at individual airports, for 2008, there is an additional 296 tons of leademitted associated with thecombustion of leaded aviation gasoline during in flight operations which is not attributed to airports.2-20 2.8 Aircraft References

Cook, Rich. Memorandum entitled Guidance on Mobile Source Emi ssion Estimates in the 1996 National Toxics Inventory , to Laurel Driver and Anne Pope, U.S. EPA Office of Air Quality Planning and Standards. U.S. EPA Office of Mobile Source s. Ann Arbor, MI. June 9, 1998.

Cook, Rich. Memorandum entitled Source Identification and Base Year 1990 Emission Inventory Guidance for Mobile Source HAPs on th e OAQPS List of 40 Priority HAPs , to Laurel Driver and Anne Pope, U.S. EPA Office of Air Quality Pl anning and Standards ( OAQPS). U.S. EPA Office of Mobile Sources. Ann Arbor, MI. June 11, 1997.

Billings, Richard and Roger Chang, Eastern Research Group, Inc. Memorandum entitled Revised HAP Speciation Profiles for Commercial Aircra ft, to Laurel Driver and Rich Cook, U.S. Environmental Protection Agency. October 25, 2004.

Federal Aviation Administration. General Avia tion and Part 135 Activity Survey - Calendar Year 2008. Downloaded from the following Internet site: http://www.faa.gov/data_res earch/aviation_data_statist ics/general_aviation/.

Federal Aviation Administration. Emissions and Dispersion Modeling System (EDMS), Version 5.1 released September 2008. Downloaded from the following Internet site: http://www.faa.gov/about/office_org/headqua rters_offices/aep/models/edms_model/.

U.S. Department of Transportation. Emissions and Dispersion M odeling System, Version 5.1. Federal Aviation Administration. September 2008. Do wnloaded from the following Internet site: http://www.faa.gov/about/office_org/headqua rters_offices/aep/models/edms_model/.

U.S. Department of Transportation. Terminal Area Forecast System . Federal Aviation Administration, Aviation Policy and Plans. Down loaded from the following Internet Site: http//www.apo.data.faa.gov/.

U.S. Department of Transportation. T-100 Segmen t (All Carriers). Bureau of Transportation Statistics. Downloaded from the following Internet site: http ://transtats.bts.gov/.

U.S. Environmental Protection Agency and Federal Aviation Administration. Recommended Best Practice for Quantifying Speciat ed Organic Gas Emissions from Aircraft Equipped with Turbofan, Turbojet, and Turboprop Engines - Version 1.0 . EPA-420-R-09-901. Assessment and Standards Division, Office of Transportation a nd Air Quality, U.S. Environmental Protection Agency in collaboration with the AEE-300 - Em issions Division, Office of Environment and Energy, Federal Aviation Administration. May 2009.

U.S. Environmental Protection Agency. Lead Emissions from the Use of Leaded Aviation
Gasoline in the United States - Technical Support Document . EPA-420-R-08-020. Assessment and Standards Division, Office of Trans portation and Air Quality. October 2008.

U.S. Environmental Protection Agency. Calculating Aviation Gasoline Lead Emissions in the Draft 2008 NEI . Assessment and Standards Division, Offi ce of Transportation and Air Quality.
December 2009.2-21 U.S. Environmental Protection Agency. Procedures for Emission Inve ntory Preparation, Volume
IV: Mobile Sources . EPA-450/4-81-026d (Revised). Office of Air and Radiation. Research Triangle Park, NC, and Ann Arbor, MI. 1992.

### Appendix A

Generic Aircraft Emission Factors/ Speciation ProfilesA-1 Commercial Aircraft Emission Factors

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)
THC 2.680E-03
VOC 2.934E-03
TOG 3.276E-03
NO
x 9.288E-03
CO 1.119E-02
SO
x 8.910E-04

PM 10 5.385E-04

PM 2.5 5.256E-04 Acetaldehyde 75070 CAA 1.400E-04
Acetone 67641 1.025E-05 Acetylene 74862 1.290E-04
Acrolein 107028 CAA 8.023E-05 Benzaldehyde 100527 IRIS 1.540E-05

Benzene 71432 CAA 5.507E-05 Benzo(a)anthracene 56553 1.297E-09 Benzo(a)pyrene 50328 9.621E-10 Benzo(b)fluoranthene 205992 1.892E-09 Benzo(ghi)perylene 191242 1.726E-11 Benzo(k)fluoranthene 207089 1.892E-09 1,3-Butadiene 101314 CAA 5.527E-05
1-Butene 101389 5.746E-05 Butyraldehyde 123728 3.899E-06
C14-Alkane No CAS 6.094E-06
C15-Alkane No CAS 5.799E-06
C16 Branched Alkane No CAS 4.783E-06
C18-Alkane No CAS 6.552E-08
C4-Benzene + C3-Aroald No CAS 2.149E-05
C5-Benzene+C4-Aroald No CAS 1.061E-05 Chrysene 218019 1.313E-09
Cis-2-Butene 514181 6.880E-06
Cis-2-Pentene 627203 9.042E-06 Crotonaldehyde 4170303 3.384E-05
1-Decene 872059 6.061E-06 Dibenzo(ah)anthracene 53703 2.551E-09 Dimethylnapthalenes 28804888 2.949E-06

Ethane 74840 1.707E-05 Ethylbenzene 100414 CAA 5.701E-06 Ethylene 74851 5.065E-04

Fluoranthene 206440 2.492E-09A-2 Commercial Aircraft Emission Factors

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO) Formaldehyde 50000 CAA 4.033E-04 Glyoxal 107222 5.950E-05 Heptene 25339564 1.435E-05

Hexadecane 544763 1.605E-06
1-Hexene 592416 2.411E-05 Indeno(1,2,3-cd)pyrene 193395 2.050E-09 Isopropylbenzene 98828 CAA 9.829E-08 Isovaleraldehyde 514863 1.048E-06
Methacrolein 78853 1.405E-05

Methanol 67561 CAA 5.913E-05 Methyl Glyoxal 78988 4.924E-05 1-Methyl Naphthalene 14120 8.092E-06 2-Methyl Naphthalene 91576 IRIS 6.749E-06 3-Methyl-1-Butene 563451 3.669E-06 4-Methyl-1-Pentene 131372 4.259E-07 2-Methyl-1-Butene 563462 4.587E-06 2-Methyl-2-Butene 513359 6.061E-06 2-Methylpentane 107835 1.337E-05 2-Methyl-1-Pentene 763291 1.114E-06 M-Ethyltoluene 620144 5.045E-06 M-Tolualdehyde 620235 9.108E-06 Naphthalene (gas phase) 91203 CAA 6.084E-06 Naphthalene (solid phase) 91203 CAA 1.260E-06 Napthalene 91203 CAA 1.772E-05

N-Decane 124185 1.048E-05

N-Dodecane 112403 1.514E-05 N-Heptadecane 629787 2.949E-07 N-Heptane 142825 2.097E-06

N-Nonane 111842 2.031E-06
N-Octane 111659 2.031E-06
1-Nonene 124118 8.059E-06

N-Pentadecane 629629 5.668E-06

N-Pentane 109660 6.487E-06 N-Propylbenzene 103651 1.736E-06

N-Tetradecane 629594 1.363E-05
N-Tridecane 629505 1.753E-05

N-Undecane 1120214 1.455E-05
Octene 111660 9.042E-06 O-Ethyltoluene 611143 2.130E-06A-3 Commercial Aircraft Emission Factors

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO) O-Tolualdehyde 529204 7.535E-06
1-Pentene 109671 2.542E-05 P-Ethyltoluene 622968 2.097E-06

Phenanthrene 85018 1.112E-08

Phenol 108952 CAA 2.378E-05 Propane 74986 2.555E-06 Propionaldehyde 123386 CAA 2.382E-05 Propylene 115071 1.485E-04 P-Tolualdehyde 104870 1.573E-06 Pyrene 121400 3.028E-09 Styrene 100425 CAA 1.012E-05

Toluene 108883 CAA 2.103E-05
Trans-2-Hexene 4050457 9.829E-07
Trans-2-Pentene 646048 1.176E-05 1,2,3-Trimethylbenzene 526738 3.473E-06 1,2,4-Trimethylbenzene 95636 1.147E-05 1,3,5-Trimethylbenzene 108678 1.769E-06 2,2,4-Trimethylpentane 540841 CAA 1.466E-06 Valeraldehyde 110623 8.027E-06 Xylene 1330207 CAA 1.032E-05A-4 Air Taxi Emission Factors - Jet

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)
THC 4.37E-04
VOC 5.03E-04
TOG 5.06E-04
NO
x 3.88E-04
CO 1.81E-03
SO
x 8.12E-05

PM 10 3.017E-04

PM 2.5 3.922E-05 Acetaldehyde 75070 CAA 2.160E-05
Acetone 67641 1.583E-06 Acetylene 74862 1.992E-05
Acrolein 107028 CAA 1.238E-05
Anthracene 120127 1.331E-10 Benzaldehyde 100527 IRIS 2.377E-06

Benzene 71432 CAA 8.500E-06 Benzo(a)anthracene 56553 2.014E-11 Benzo(a)pyrene 50328 1.103E-11 Benzo(ghi)perylene 191242 1.829E-12 1,3-Butadiene 101314 CAA 8.531E-06
1-Butene 101389 8.869E-06 Butyraldehyde 123728 6.017E-07
C14-Alkane No CAS 9.405E-07
C15-Alkane No CAS 8.950E-07
C16 Branched Alkane No CAS 7.383E-07
C18-Alkane No CAS 1.011E-08
C4-Benzene + C3-Aroald No CAS 3.317E-06
C5-Benzene+C4-Aroald No CAS 1.638E-06 Chrysene 218019 1.876E-11
Cis-2-Butene 514181 1.062E-06
Cis-2-Pentene 627203 1.396E-06 Crotonaldehyde 4170303 5.224E-06
1-Decene 872059 9.355E-07 Dimethylnapthalenes 28804888 4.551E-07

Ethane 74840 2.635E-06 Ethylbenzene 100414 CAA 8.799E-07 Ethylene 74851 7.818E-05

Fluoranthene 206440 2.784E-10 Formaldehyde 50000 CAA 6.225E-05 Glyoxal 107222 9.183E-06A-5 Air Taxi Emission Factors - Jet

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO) Heptene 25339564 2.215E-06

Hexadecane 544763 2.478E-07
1-Hexene 592416 3.722E-06 Isopropylbenzene 98828 CAA 1.517E-08 Isovaleraldehyde 514863 1.618E-07
Methacrolein 78853 2.169E-06

Methanol 67561 CAA 9.127E-06 Methyl Glyoxal 78988 7.600E-06 1-Methyl Naphthalene 14120 1.249E-06 2-Methyl Naphthalene 91576 IRIS 1.042E-06 3-Methyl-1-Butene 563451 5.663E-07 4-Methyl-1-Pentene 131372 6.574E-08 2-Methyl-1-Butene 563462 7.079E-07 2-Methyl-2-Butene 513359 9.355E-07 2-Methylpentane 107835 2.063E-06 2-Methyl-1-Pentene 763291 1.719E-07 M-Ethyltoluene 620144 7.787E-07 M-Tolualdehyde 620235 1.406E-06 Napthalene 91203 CAA 2.736E-06

N-Decane 124185 1.618E-06

N-Dodecane 112403 2.336E-06 N-Heptadecane 629787 4.551E-08 N-Heptane 142825 3.236E-07

N-Nonane 111842 3.135E-07
N-Octane 111659 3.135E-07
1-Nonene 124118 1.244E-06

N-Pentadecane 629629 8.748E-07

N-Pentane 109660 1.001E-06 N-Propylbenzene 103651 2.680E-07

N-Tetradecane 629594 2.104E-06
N-Tridecane 629505 2.705E-06

N-Undecane 1120214 2.245E-06
Octene 111660 1.396E-06 O-Ethyltoluene 611143 3.287E-07 O-Tolualdehyde 529204 1.163E-06
1-Pentene 109671 3.924E-06 P-Ethyltoluene 622968 3.236E-07

Phenanthrene 85018 1.238E-09

Phenol 108952 CAA 3.671E-06A-6 Air Taxi Emission Factors - Jet

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO) Propane 74986 3.944E-07 Propionaldehyde 123386 CAA 3.676E-06 Propylene 115071 2.293E-05 P-Tolualdehyde 104870 2.427E-07 Pyrene 121400 3.401E-10 Styrene 100425 CAA 1.563E-06

Toluene 108883 CAA 3.246E-06
Trans-2-Hexene 4050457 1.517E-07
Trans-2-Pentene 646048 1.815E-06 1,2,3-Trimethylbenzene 526738 5.360E-07 1,2,4-Trimethylbenzene 95636 1.770E-06 1,3,5-Trimethylbenzene 108678 2.731E-07 2,2,4-Trimethylpentane 540841 CAA 1.915E-07 Valeraldehyde 110623 1.239E-06 Xylene 1330207 CAA 2.352E-06A-7 Air Taxi Emission Factors - Piston

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)
THC 7.750E-05
VOC 8.484E-05
TOG 9.474E-05
NO
x 7.900E-05
CO 1.407E-02
SO
x 7.500E-06

PM 10 3.015E-04

PM 2.5 3.920E-05 Acenaphthene 83329 2.201E-07 Acenaphthylene 208968 1.242E-06 Acetaldehyde 75070 CAA 5.874E-07
Acrolein 107028 CAA 5.684E-08
Anthracene 120127 2.563E-07

Benzene 71432 CAA 3.837E-06 Benzo(a)anthracene 56553 3.015E-08 Benzo(a)pyrene 50328 3.015E-08 Benzo(b)fluoranthene 205992 3.618E-08 Benzo(ghi)perylene 191242 7.839E-08 Benzo(k)fluoranthene 207089 3.618E-08 1,3-Butadiene 101314 CAA 9.285E-07 Chrysene 218019 3.015E-08 Ethylbenzene 100414 CAA 1.393E-06

Fluoranthene 206440 2.744E-07

Fluorene 86737 4.553E-07 Formaldehyde 50000 CAA 2.548E-06 Indeno(1,2,3-cd)pyrene 193395 2.412E-08 M-Xylene and P-Xylene 108383 CAA 2.201E-07 Naphthalene (gas phase) 91203 CAA 4.327E-07 Naphthalene (solid phase) 91203 CAA 4.432E-06

N-Hexane 110543 6.632E-07 O-Xylene 95476 CAA 1.242E-06

Phenanthrene 85018 7.658E-07 Propionaldehyde 123386 CAA 5.684E-08 Pyrene 121400 3.739E-07 Styrene 100425 CAA 3.221E-07

Toluene 108883 CAA 9.853E-06 2,2,4-Trimethylpentane 540841 CAA 3.394E-08A-8 General Aviation Emission Factors - Jet

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)
THC 3.00E-04
VOC 2.73E-04
TOG 3.06E-04
NO
x 1.62E-04
CO 4.79E-03
SO
x 3.68E-05

PM 10 1.184E-04

PM 2.5 1.539E-05 Acetaldehyde 75070 CAA 1.309E-05
Acetone 67641 9.593E-07 Acetylene 74862 1.207E-05
Acrolein 107028 CAA 7.506E-06
Anthracene 120127 5.221E-11 Benzaldehyde 100527 IRIS 1.440E-06

Benzene 71432 CAA 5.152E-06 Benzo(a)anthracene 56553 7.903E-12 Benzo(a)pyrene 50328 4.327E-12 Benzo(ghi)perylene 191242 7.178E-13 1,3-Butadiene 101314 CAA 5.170E-06
1-Butene 101389 5.376E-06 Butyraldehyde 123728 3.647E-07
C14-Alkane No CAS 5.700E-07
C15-Alkane No CAS 5.425E-07
C16 Branched Alkane No CAS 4.475E-07
C18-Alkane No CAS 6.130E-09
C4-Benzene + C3-Aroald No CAS 2.010E-06
C5-Benzene+C4-Aroald No CAS 9.930E-07 Chrysene 218019 7.359E-12
Cis-2-Butene 514181 6.436E-07
Cis-2-Pentene 627203 8.459E-07 Crotonaldehyde 4170303 3.166E-06
1-Decene 872059 5.670E-07 Dimethylnapthalenes 28804888 2.758E-07

Ethane 74840 1.597E-06 Ethylbenzene 100414 CAA 5.333E-07 Ethylene 74851 4.738E-05

Fluoranthene 206440 1.092E-10 Formaldehyde 50000 CAA 3.773E-05 Glyoxal 107222 5.566E-06A-9 General Aviation Emission Factors - Jet

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO) Heptene 25339564 1.342E-06

Hexadecane 544763 1.502E-07
1-Hexene 592416 2.256E-06 Isopropylbenzene 98828 CAA 9.194E-09 Isovaleraldehyde 514863 9.807E-08
Methacrolein 78853 1.315E-06

Methanol 67561 CAA 5.532E-06 Methyl Glyoxal 78988 4.606E-06 1-Methyl Naphthalene 14120 7.570E-07 2-Methyl Naphthalene 91576 IRIS 6.313E-07 3-Methyl-1-Butene 563451 3.433E-07 4-Methyl-1-Pentene 131372 3.984E-08 2-Methyl-1-Butene 563462 4.291E-07 2-Methyl-2-Butene 513359 5.670E-07 2-Methylpentane 107835 1.250E-06 2-Methyl-1-Pentene 763291 1.042E-07 M-Ethyltoluene 620144 4.720E-07 M-Tolualdehyde 620235 8.520E-07 Naphthalene (gas phase) 91203 CAA 1.674E-06 Naphthalene (solid phase) 91203 CAA 5.571E-08 Napthalene 91203 CAA 1.658E-06

N-Decane 124185 9.807E-07

N-Dodecane 112403 1.416E-06 N-Heptadecane 629787 2.758E-08 N-Heptane 142825 1.961E-07

N-Nonane 111842 1.900E-07
N-Octane 111659 1.900E-07
1-Nonene 124118 7.539E-07

N-Pentadecane 629629 5.302E-07

N-Pentane 109660 6.068E-07 N-Propylbenzene 103651 1.624E-07

N-Tetradecane 629594 1.275E-06
N-Tridecane 629505 1.640E-06

N-Undecane 1120214 1.361E-06
Octene 111660 8.459E-07 O-Ethyltoluene 611143 1.992E-07 O-Tolualdehyde 529204 7.049E-07
1-Pentene 109671 2.378E-06 P-Ethyltoluene 622968 1.961E-07

Phenanthrene 85018 4.858E-10A-10 General Aviation Emission Factors - Jet

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)

Phenol 108952 CAA 2.225E-06 Propane 74986 2.391E-07 Propionaldehyde 123386 CAA 2.228E-06 Propylene 115071 1.390E-05 P-Tolualdehyde 104870 1.471E-07 Pyrene 121400 1.334E-10 Styrene 100425 CAA 9.470E-07

Toluene 108883 CAA 1.968E-06
Trans-2-Hexene 4050457 9.194E-08
Trans-2-Pentene 646048 1.100E-06 1,2,3-Trimethylbenzene 526738 3.249E-07 1,2,4-Trimethylbenzene 95636 1.073E-06 1,3,5-Trimethylbenzene 108678 1.655E-07 2,2,4-Trimethylpentane 540841 CAA 1.313E-07 Valeraldehyde 110623 7.509E-07 Xylene 1330207 CAA 1.612E-06A-11 General Aviation Emissi on Factors - Piston

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)
THC 7.750E-05
VOC 7.524E-05
TOG 8.537E-05
NO
x 3.250E-05
CO 6.007E-03
SO
x 5.000E-06

PM 10 1.184E-04

PM 2.5 1.539E-05 Acenaphthene 83329 1.123E-08 Acenaphthylene 208968 6.339E-08 Acetaldehyde 75070 CAA 5.874E-07
Acrolein 107028 CAA 5.684E-08
Anthracene 120127 1.308E-08

Benzene 71432 CAA 3.837E-06 Benzo(a)anthracene 56553 1.539E-09 Benzo(a)pyrene 50328 1.539E-09 Benzo(b)fluoranthene 205992 1.846E-09 Benzo(ghi)perylene 191242 4.000E-09 Benzo(k)fluoranthene 207089 1.846E-09 1,3-Butadiene 101314 CAA 9.285E-07 Chrysene 218019 1.539E-09 Ethylbenzene 100414 CAA 1.393E-06

Fluoranthene 206440 1.400E-08

Fluorene 86737 2.323E-08 Formaldehyde 50000 CAA 2.548E-06 Indeno(1,2,3-cd)pyrene 193395 1.231E-09 M-Xylene and P-Xylene 108383 CAA 1.123E-08 Naphthalene (gas phase) 91203 CAA 4.327E-07 Naphthalene (solid phase) 91203 CAA 2.262E-07

N-Hexane 110543 6.632E-07 O-Xylene 95476 CAA 6.339E-08

Phenanthrene 85018 3.908E-08 Propionaldehyde 123386 CAA 5.684E-08 Pyrene 121400 1.908E-08 Styrene 100425 CAA 3.221E-07

Toluene 108883 CAA 9.853E-06 2,2,4-Trimethylpentane 540841 CAA 3.394E-08A-12 Military Emission Factor

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)
THC 6.170E-04
VOC 6.815E-04
TOG 7.597E-04
NO
x 7.900E-05
CO 1.407E-02
SO
x 7.500E-06

PM 10 3.017E-04

PM 2.5 3.922E-05 Acetaldehyde 75070 CAA 3.245E-05
Acetone 67641 2.378E-06 Acetylene 74862 2.993E-05
Acrolein 107028 CAA 1.861E-05 Benzaldehyde 100527 IRIS 3.571E-06

Benzene 71432 CAA 1.277E-05 1,3-Butadiene 101314 CAA 1.282E-05
1-Butene 101389 1.333E-05 Butyraldehyde 123728 9.041E-07
C14-Alkane No CAS 1.413E-06
C15-Alkane No CAS 1.345E-06
C16 Branched Alkane No CAS 1.109E-06
C18-Alkane No CAS 1.519E-08
C4-Benzene + C3-Aroald No CAS 4.984E-06
C5-Benzene+C4-Aroald No CAS 2.461E-06
Cis-2-Butene 514181 1.595E-06
Cis-2-Pentene 627203 2.097E-06 Crotonaldehyde 4170303 7.848E-06
1-Decene 872059 1.405E-06 Dimethylnapthalenes 28804888 6.837E-07

Ethane 74840 3.958E-06 Ethylbenzene 100414 CAA 1.322E-06 Ethylene 74851 1.175E-04 Formaldehyde 50000 CAA 9.352E-05 Glyoxal 107222 1.380E-05 Heptene 25339564 3.328E-06

Hexadecane 544763 3.723E-07
1-Hexene 592416 5.591E-06 Isopropylbenzene 98828 CAA 2.279E-08 Isovaleraldehyde 514863 2.431E-07
Methacrolein 78853 3.259E-06A-13 Military Emission Factor

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO)

Methanol 67561 CAA 1.371E-05 Methyl Glyoxal 78988 1.142E-05 1-Methyl Naphthalene 14120 1.876E-06 2-Methyl Naphthalene 91576 IRIS 1.565E-06 3-Methyl-1-Butene 563451 8.509E-07 4-Methyl-1-Pentene 131372 9.876E-08 2-Methyl-1-Butene 563462 1.064E-06 2-Methyl-2-Butene 513359 1.405E-06 2-Methylpentane 107835 3.100E-06 2-Methyl-1-Pentene 763291 2.583E-07 M-Ethyltoluene 620144 1.170E-06 M-Tolualdehyde 620235 2.112E-06 Napthalene 91203 CAA 4.110E-06

N-Decane 124185 2.431E-06

N-Dodecane 112403 3.510E-06 N-Heptadecane 629787 6.837E-08 N-Heptane 142825 4.862E-07

N-Nonane 111842 4.710E-07
N-Octane 111659 4.710E-07
1-Nonene 124118 1.869E-06

N-Pentadecane 629629 1.314E-06

N-Pentane 109660 1.504E-06 N-Propylbenzene 103651 4.026E-07

N-Tetradecane 629594 3.160E-06
N-Tridecane 629505 4.064E-06

N-Undecane 1120214 3.373E-06
Octene 111660 2.097E-06 O-Ethyltoluene 611143 4.938E-07 O-Tolualdehyde 529204 1.747E-06
1-Pentene 109671 5.895E-06 P-Ethyltoluene 622968 4.862E-07

Phenol 108952 CAA 5.515E-06 Propane 74986 5.926E-07 Propionaldehyde 123386 CAA 5.523E-06 Propylene 115071 3.445E-05 P-Tolualdehyde 104870 3.647E-07 Styrene 100425 CAA 2.348E-06

Toluene 108883 CAA 4.877E-06
Trans-2-Hexene 4050457 2.279E-07
Trans-2-Pentene 646048 2.727E-06A-14 Military Emission Factor

Pollutant CAS No. CAA
"187"
or IRIS
HAP? Emission
Factors (tons/LTO) 1,2,3-Trimethylbenzene 526738 8.053E-07 1,2,4-Trimethylbenzene 95636 2.659E-06 1,3,5-Trimethylbenzene 108678 4.102E-07 Valeraldehyde 110623 1.861E-06

### Appendix B

Calculating Piston-Engine Aircraft Ai rport Inventories for Lead for the 2008 National Emissions InventoryB-1 Calculating Piston-Engine Aircraft Airport Inventories for Lead for the 2008 National Emissions Inventory
December 2010

Section 1. Introduction

The main purpose of this doc ument is to describe the methods the Environmental Protection Agency (EPA) used to calculate airport lead (Pb) inventories for the 2008 National Emissions Inventory (NEI). 1 These methods focus on the development of approaches to estimate piston-e ngine aircraft activity at airports in the U.S. since the activity of this fleet is reported to the Fe deral Aviation Administra tion (FAA) as general aviation (GA) or air taxi (AT) activity – categ ories that also include jet-engine aircraft activity. The methods described here reflect improvements to th e methods used in developing the airport-specific pi ston-engine aircraft inventori es in the 2002 NEI and the
2005 NEI.

Background information regarding the use of leaded aviation gasoline (avgas) in piston-engine powered aircraft is available in other documents. 2,3 Briefly, most pistonengine aircraft ope rations fall into the ca tegories of either GA or AT. Aircraft used in
GA and AT activities include a diverse set of aircraft types and en gine models and are
used in a wide vari ety of applications. 4 Lead emissions associated with GA and AT
aircraft stem from the use of one hundred octane low lead (100LL) avgas. The lead is
added to the fuel in the form of tetraethyl lead (T EL). This lead additive helps boost fuel octane, prevent engine knock, and prevent valve seat recession and subsequent loss of compression for engines wit hout hardened valves. Today, 100LL is the most commonly available type of aviation gasoline in the United States. 5 Lead is not added to jet fuel that is used in commercial aircraft, most militar y aircraft, or other tu rbine-engine powered
aircraft. Lead emissions from the use of leaded avgas comprised 45% of the national inventory for emissions of lead in 2002. 6

1 In this document ‘2008 NEI’ refers to 200 8 NEI version 1 (January 2011), available at http://www.epa.gov/ttn/chief/net/2008inventory.html

2 EPA (2007) Review of the National Ambient Air Qu ality Standards for Lead: Policy Assessment of Scientific and Technical Information. OAQPS Staff Paper. EPA-452/R-07-013 November 2007. pp 2-8 and
2-9.

3 FAA William J. Hughes Technical Center http://www.tc.faa.gov /act4/insidethefenc e/2006/0609_06_AvFuels.htm

4 Commercial aircraft include those used for scheduled service transporting passen gers, freight, or both. Air taxis fly scheduled and for-hire service carrying passengers, frei ght or both, but they usually are smaller aircraft than those operated by commercial air carrier s. General aviation includes most other aircraft (fixed and rotary wing) used for personal transportation, business, instructional flying, and aerial application.

5 ChevronTexaco (2005) Aviation Fu els Technical Re view. FTR-3. http://www.chevronglobalaviation.co m/docs/aviation_tech_review.pdf

6 U.S. Environmental Protection Agency (2008) EPA’ s Report on the Environment EPA/600/R-07/045F.
Available at: http://www.epa.gov/roeB-2 This document is or ganized into eight sections. Se ction 2 describes the data we
use to calculate the national inventory for the amount of lead re leased to the air from the combustion of leaded avgas. S ection 3 describes the landing and takeoff data we use to calculate airport-specific i nventories for lead. Section 4 describes how we estimate landing and takeoff data for the airport facilities that do not report it to the FAA. Section 5 describes the estimate of landing and takeoff activity occurring at heliports in the
U.S. Section 6 describes the me thods used to calculate the ai rport-specific inventories for
lead. Section 7 describes data that would be needed to improve the estimates of airportspecific inventories for lead and Section 8 desc ribes the estimates of the amount of lead emitted in-flight that are in the 2008 NEI.

In this document, units of tons (i.e., U.S. short tons) are used when discussing the national and airport-specific lead inventory in order to be consistent with the manner in which the NEI reports inventorie s for lead and other pollutants. The unit of grams is used in describing the concentration of lead in avgas and in describing emission factors. Conversion factors are provided for clarity.

Section 2. Calculating the National Avgas Lead Inventory

Because lead is a persistent pollutant and accumulates in th e environment, we include all lead emissions from piston-engi ne aircraft in the NEI – emissions occurring during the landing and take-off cycle at airports as well as emissions occurring at
altitude. 7 To calculate the national avgas lead inventory, we use information provided by the U.S. Department of Tr ansportation’s (DOT’s) Federa l Aviation Administration (FAA) regarding the volume of leaded avgas consumed in the U.S. in 2008. 8 The U.S. Department of Energy’s (DOE’s) Energy In formation Administration (EIA) provides information regarding the volume of leaded avgas produced in a given year. EPA has historically used the DOE EIA avgas fuel volume produced to calculate national lead inventories from the consumption of leaded avgas. However, since EPA uses DOT airport activity and aircraft data, we are us ing the DOT fuel volume data in the 2008 NEI to calculate the national lead inventory in order to use a consistent data source. In this document, when we refer to avgas fuel volume data it is data supplied by DOT, except
where noted.

As demonstrated in the equation below, to calculate the annual emission of lead from the consumption of leaded avgas, we multiply the volume of avgas used by the
concentration of lead in the a vgas, minus the small amount of lead that is retained in the engine, engine oil and/or exhaust system. Th e volume of avgas used in the U.S. in 2008

7 U.S. EPA, 2006. Air Quality: Criteria for Lead: 2006; EPA/600/R-5/144aF; U.S. Government Printing Office, Washington, DC, October, 2006.

8 U.S. Department of Tr ansportation Federal Aviation Administration Aviation Policy and Plans. FAA Aerospace Forecast Fiscal Years 2010-2030. p.99. Available at: http://www.faa.gov/data_research/a viation/aerospace_forecasts/2010- 2030/media/2010%20Forecast%20Doc.pdf This documen t provides historical data for 2000-2008 as well
as forecast data.B-3 was 248,100,000 gallons. 9 The concentration of lead in avgas ([Pb] in the equation below) can be one of four levels (ranging fro m 0.14 to 1.12 grams of lead per liter) as specified by the American Society for Tes ting and Materials (ASTM). By far the most common avgas supplied is “100 Low L ead” or 100LL. 10,11 The maximum lead concentration specified by AS TM for 100LL is 0.56 grams pe r liter or 2. 12 grams per gallon. 12 A fraction of lead is retained in the engine, engine oil and/or exhaust system which we currently estimate at 5%. 13

For the 2008 NEI, the national estimate of lead emissions from the consumption of avgas was 551 tons (see equation below).

(248,100,000 gal)(2 .12 g Pb/gal)(0.95)
= 551 tons Pb 907,180 g/ton

As described above, DOE’s EIA also provides estimates of the annual volume of leaded avgas produced in a given year. For 2008, the volum e of avgas produced in the U.S. was 5,603 thousand ba rrels or 235,326,000 gallons. 14 Consumption of this volume of avgas equates to a national lead emission s estimate for this source of 522 short tons.

Section 3. Landing and Takeoff Data Sources and Uses

Airport-specific inventories require in formation regarding landing and takeoff (LTO) activity by aircraft type. 15 According to FAA records, there are approximately 20,000 airport facilities in the U.S., the vast majority of which are expected to have activity by piston-engine aircraft that operate on leaded avgas. Of these facilities, EPA’s NEI has in the past, reported emissions of lead (and other criteria pollutants and

9 U.S. Department of Transporta tion Federal Aviation Administration Aviation Policy and Plans. FAA Aerospace Forecast Fiscal Years 2010-2030. p.99. Available at: http://www.faa.gov/data_research/a viation/aerospace_forecasts/2010- 2030/media/2010%20Forecast%20Doc.pdf This documen t provides historical data for 2000-2008 as well
as forecast data.

10

ChevronTexaco (2005) Aviation Fuels Technical Review. FTR-3.

11 The 2008 General Aviation Sta tistical Databook & Industry Ou tlook report by General Aviation
Manufactures Associ ation (GAMA) found that over 90% of avgas is 100LL.

12

ASTM International (2005) Annu al Book of ASTM Standards S ection 5: Petroleum Products, Lubricants, and Fossil Fuels Volume 05.01 Petrol eum Products and Lubricants (I): D 56 – D 3230.

13 The information used to develop this estimate is from the following references : (a) Todd L. Petersen, Petersen Aviation, Inc, Aviation Oil Lead Content Analysis , Report # EPA 1-2008, January 2, 2008, available at William J. Hughes Technical Center Technical Reference and Research Library at http://actlibrary.tc.fa a.gov/ and (b) E-mail from Theo Rindlisbach er of Switzerland Federal Office of Civil Aviation to Bryan Manning of U.S. EPA, regard ing lead retained in engine, September 28, 2007.

14

DOE Energy Information Administration. Fuel production volume data obtained from http://tonto.eia.doe.gov/dnav/pet/hist/mgaupus1A.htm accessed November 2006.

15 An aircraft operation is defined as any landing or takeoff event, therefore, to calculate LTOs, operations are divided by two. Most data sour ces from FAA report aircraft activity in numbers of operations which, for the purposes of calculating lead emissions using the method described in th is document, need to be
converted to LTO events.B-4 hazardous air pollutants) at 3,410 airports. 16 While the 3,410 airport facilities are among
the most active in the U.S ., they comprise on ly a small fraction of the total airport facilities where leaded avgas is used.

FAA’s Office of Air Traffic provides a co mplete listing of operational airport facilities in the National Airspace System Resources (NASR) data base. The electronic NASR data report, referred to here as the 50 10 airport data report, can be generated from
the NASR database and is available for download from the FAA website. 17 This report is updated every 56 days. EPA ob tains airport information (i ncluding operations) for a
subset of the facilities in the NASR databa se from FAA’s Terminal Area Forecast (TAF) database that is prepared by FAA’s Office of Aviation Policy and Plans. 18 The TAF database currently includes information for ai rports in FAA’s National Plan of Integrated Airport Systems (NPIAS), whic h identifies airports that are significant to national air transportation. Approximately 500 of the airports that are in the TAF database have
either an FAA air traffic control tower or an FAA contract tower where controllers count operations. The operations data from the cont rol towers is reported to The Operations Network (OPSNET) 19 which is publically available in the Air Traffic Activity System (ATADS) database. 20 The operations data for the towered airports that is reported in OPSNET and ATADS is then reported to the TAF database. The operations data for the airports in the TAF database that do not ha ve control towers represent estimates. 21 The operations supplied in the 5010 airport data report for facilities not repo rted in the TAF may be self-reported by airport operators through da ta collection accomplished by airport inspectors who work for the State Aviation Agency, or operations data can be obtained through other means. 22

The 5010 airport data report supplies the date that the associated operations data
represents. 23 Because airports that are not in the TAF database submit data voluntarily to FAA for the 5010 data report, many of the air ports have operations data that represent data for years earlier than 2008. Nationally, GA and AT pist on-engine operations have
decreased in recent years, 24 therefore EPA did not use operations data from years prior to 2008 as it is reported. Instead , EPA multiplied the older GA and AT piston- engine data (Section 6 describes the method EPA used to calculate the number of piston-engine

16

These 3,410 facilities are the facilit ies for which the FAA’s Terminal Area Forecast (TAF) database provides information regarding aircraft activity. Th e TAF database is prepared by FAA’s Office of Aviation Policy and Plans and includes information for th e airports in FAA’s Nati onal Plan of Integrated Airport Systems (NPIAS). One of the goals of the NPIAS is to identify airports that are significant to national air transportation.

17 http://www.faa.gov/airports_airtraffic/ai rports/airport_safety/airportdata_5010/

18 http://aspm.faa.gov/main/taf.asp

19 http://aspm.faa.gov/opsnet/sys/

20 http://aspm.faa.gov/opsnet/sys/Airport.asp

21 FAA’s Terminal Area Forecast Summary (Fis cal Years 2009 – 2030), Appendix A (page 28) http://www.faa.gov/data_r esearch/aviation/taf_reports/media/ TAF%20Summary%20Report%20FY%2020 09%20-%202030.pdf

22

In the absence of updated information from States, local authorities or Tribes, we are using the LTO data provided in the FAA database.

23 The 12-month ending date on which annual operations data in the report is based.

24 http://www.faa.gov/data_r esearch/aviation_data_stat istics/general_aviation/B-5 operations from total GA and AT activity data) by sc aling factors that we re calculated by dividing the 2008 national amount of avgas pr oduced by the national amount of avgas produced in the year the ope rations data represents. 25 A table with the scaling factors is provided in Appendix A. The national volu me of avgas produced data comes from the DOE, EIA website and is av ailable for 1981 – 2009. 26 For operations data older than 1981, EPA divided the 2008 national amount of avgas produced by the average of the national amount of avgas produced from 19 81 – 1989. Jet engines do not use avgas, therefore EPA did not apply scaling factors to the turbine operations for data from years prior to 2008.

EPA also obtains operations data from the T-100 segment data from the Bureau of Transportation Statistics (BTS). The aircraft in the T-100 data are ma tched to aircraft in the FAA’s Emission and Dispersion Modeling System (EDMS) using the crosswalk table developed for earlier versions of the NEI. Generally the T-100 data covers commercial air carrier operations, but some AT activitie s are included in the data set that would
double count with th e TAF data at the sa me airport. To correct for possible double counting, first the AT LTOs included in the T-100 data were compiled using the aircraft type data included in the ai rcraft make/models crosswalk. 27 The resulting aggregated LTOs were compared with the reported TAF LTOs for airports where there were overlaps. The T-100 AT LTOs were then subt racted from the TAF AT data to ensure that double counting was minimized. Note that if the T-100 AT value was larger than the TAF value, the TAF value was set to zero to eliminate the possibility of negative LTOs in
the dataset.

The 2008 draft NEI was developed using the January 15, 2009 version of the 5010 airport data report. In that version of th e report there were 19,925 airport facilities
in the U.S. that had submitt ed data to the F AA. Among these 19,9 25 facilities, 99 facilities were not relevant for the purposes of estimating lead emissions because they were either listed as closed (85) or they were balloonports (14). 28 Therefore, lead
inventories were needed for 19,826 facilities. In the Janua ry 15, 2009 version of the 5010 airport data report th ere were 5,654 airport facilities for which operations data were provided (many of which are facilities in FAA’s TAF database). 29 There were 14,172 facilities in the 5010 airport data report for which there were no operations data. 30 As a

25 The FAA General Aviation and Air Taxi (Part 135) Activity Surveys (source ofnational level pistonengine operations data) are only av ailable annually, starti ng in 1999. Because ther e are airports with operations data older than 1999, EPA used avgas product supplied data as a surrogate for piston-engine operations to estimate the change in piston-engine activity over the last three decades.

26 http://tonto.eia.doe.gov/dnav/pet/hist /LeafHandler.ashx?n=PET&s=mgaupus1&f=A. DOT recently changed the way they estimate fuel consumption data, so while EPA used DOT data to determine the 2008 national avgas lead inventory, for the purpose of calculating these scali ng factors EPA used DOE’s data in
order to have historical fuel data that is calculated in a consistent manner.

27 The T-100 data does not specify that the operations data is ai r taxi in nature; however, in discussions with FAA, EPA determined that these flig hts are air taxi in nature and has assigned them in the 2008 NEI as
such.

28 Balloon craft do not use avgas

29

Either Commuter, GA I tinerant, GA Local, or Air Taxi operations data, as these operations can be performed by piston- engine aircraft.

30

No Commuter, GA Itinerant, GA Local, or Air Taxi operations data.B-6 part of the review process fo r the draft 2008 NEI, EPA receiv ed updated airport data from
states and also looked at more recent versions of the 5010 airport data report to update the status of airports, so the number of airports for which EPA estimated activity is slightly lower in the 2008 NEI than in the draft 2008 NEI. The following section of this
document describes the method EPA used to estimate operations for the 14,132 airport facilities in the 2008 NEI that do not have reported activity data.

As described in Section 1, most piston-engine aircraft fall into the categories of either GA or AT. Some GA and AT activity is conducted by turboprop and turbojet aircraft which do not used leaded avgas. There are no national databases that provide airport-specific LTO activity da ta for piston-engine aircraft separately from turbojet and turboprop aircraft. The databases described above report total GA and AT activity conducted by both piston-engine and jet-engine aircraft. Part (a) in Section 6 describes how we estimate piston-engine LTOs at airports in the 2008 NEI.

Section 4. Estimating LTOs at the 14,132 Airport Facilities with No LTO Data

FAA has used regression mo dels to estimate operations at facilities where operations data are not available. 31,32 In this work and othe r work, FAA identified characteristics of small towered airports fo r which there were statistically significant relationships with operati ons at these airports. 33 Regression models based on the airport
characteristics were then used to estimate general aviation operations for a set of nontowered airports. The airport characteristics identified by FAA and used to estimate general aviation operations at small airports include: the nu mber of aircraft based at a facility (termed ‘based aircraft ’), population in the vi cinity of the airpor t, airport regional prominence, per capita income, region, and th e presence of certificated flight schools.

In the 2000 report titled ‘Model for Estimating Genera l Aviation Operations at Non-towered Airports,’ a model of GA annual activity was developed using information from small towered airports to explain GA activ ity at towered and non-towered airports. The model explained GA activity at the towered airports well (R 2 of 0.75) but produced higher estimates than state-supp lied estimates for non-towered airports. 34

The relevant data available in the 5010 airport data report for the purposes of estimating airport operations include: facility type (airport, balloonport, seaplane base, gliderport, heliport, stolport, 35 ultralight); number of GA aircraft based at each airport by

31 Federal Aviation Administration, Office of Aviation Policy and Plans, Statistics and Forecast Branch. July 2001. Model for Estimating General Aviation Op erations at Non-towered Airports Using Towered
and Non-towered Ai rport Data. Prepared by GRA, Inc.

32

Mark Hoekstra, “Model for Estimating General Avia tion Operations at Non-Towered Airports” prepared for FAA Office of Aviation Policy and Plans, April 2000.

33 GRA, Inc. “Review of TAF Methods,” Final Report, prepared for FAA Office of Aviation Policy and Plans under Work Order 45, Contract No. DTFA01-93-C-00066, February 25, 1998.

34

The mean absolute difference between the model operations estimate and the state operations estimate was 16,940 operations.

35 Stolport is an airport designed with STOL (Short Take-Off and Landing) opera tions in mind, normally having a short single runway.B-7 type (glider, helicopter, jet engine, military, multi-engine, single engine, ultralight); operations data (air taxi , commercial, commuter, GA iti nerant, GA local, military) 36 ; and operations date (12-month ending date on which annual operations data is based). Census data was also merged with the 5010 ai rport data report to give population data for each airport’s county.

Using the FAA work referenced above, we explored relationships among the airport data variables that best predicted ai rcraft activity (LTOs). We found that based aircraft was a highly significan t and positive regressor to LTOs. Table 1 shows that for facilities that did not have LTO data in the January 15, 2009 version of the 5010 airport data report, 7,856 had based airc raft data while 6,316 did not have based aircraft data. 37, 38 Therefore, as described below, LTO estimat es were derived usi ng different methods depending on data availability.

Table 1: Contingency ta ble describing the number s of airport facilities that have or do
not have LTO data and/or based aircraft data for airport faci lities in the Ja nuary 15, 2009 version of the 5010 airport data report



### HAVE LTO DATA

YES NO

YES 4,872 7,856 12,728

NO 782 6,316 7,098

5,654 14,172 19,826

36

As explained in footnote 15, an aircraft operation is defined as a ny landing or takeoff event, therefore, to calculate LTOs, operations are divided by two. The 5 010 airport data report fr om FAA reports aircraft activity in numbers of operations which, for the purposes of calcula ting Pb emissions using the method described in the TSD, are converted to LTO events.

37 As described in Section 3, the number of facilities with no LTO data changed slightly from the draft 2008 NEI to the 2008 NEI. In the 2008 NEI, of the facilities that did not have reported activity data, 7,837 facilities reported based aircraft data and 6,295 did not report based aircraft data.

38

These numbers include data for the following types of facilities: ai rports, balloonports, seaplane bases, gliderports, heliports, stol ports, and ultralights. 

### HAVE
BASED
AIRCRAFT
DATAB-8 (a) Estimating LTOs at Facilities with Ba sed Aircraft Data, but No LTO Data:

There are 6,414 facilities in the 2008 NE I (not including heliports) for which the 5010 airport data report supplies the number of based aircraft 39 but not activity data to which the regression equation (based aircra ft vs. LTOs) could be applied. Using the 4,872 airports for which both LTO and aircra ft data is known, th e initial relationship
found between based aircraft and LTOs was:

Equation 1:
LTOs = 2494 + 208*aircraft R 2 = 0.55

The FAA models found population to be another significant regressor. We used the population of the county in which the airport is located as the population variable. Adding county population to the model gave the following relationship:

Equation 2:
LTOs = 2204 + 194*aircraft + 0.0038*county population R 2 = 0.56

EPA received numerous comments to th e docket on its Advance Notice of Proposed Rulemaking on Lead Emissions from Piston-Engine Aircraft Using Leaded
Aviation Gasoline 40 indicating that aviation in Alaska is differ ent than it is in the continental U.S. Commenters pointed out that in Alaska, 82% of communities are not accessible by road and rely on air transpor t for life sustaining goods and services. 41

Commenters also noted that Alaskans travel by air eight times more often per capita than
those in the continental U.S. For those reas ons, we added a dummy variable in equation 3 to identify whether or not an airport is located in Alas ka. Because the relationship between based aircraft and LTOs is likely di fferent for Alaskan airports than it is for airports that aren’t in Alaska, we also added an interaction term to equation 3 (interaction of an airport being in Alaska and its sum of based aircraft).

Equation 3:
LTOs = 1937 + 205*aircraft + 0.00 38*county population + 566*Alaska – 108*(AlaskaXaircraft)

R 2 = 0.58

After analyzing the data and plot for th e data underlying equation 3, we found many airport facilities identified as commerci al airports for which based aircraft was extremely low (i.e., less than 10), yet LTO s were quite high (i.e., anywhere from 100,000

39

Based aircraft for this purpose was limited to single- and multi-engine ai rcraft, helicopters, and ultralights since these aircraft types can use leaded avgas.

40

U.S. Environmental Protection Agency (2010) A dvance Notice of Proposed Rulemaking on Lead Emissions From Piston-Engine Ai rcraft Using Leaded Aviation Ga soline. 75 FR 22440 (April 28, 2010).

41 Comments to the docket on EPA’s Advance Noti ce of Proposed Rulemaking on Lead Emissions from Piston-Engine Airc raft Using Leaded Aviation Gasoline from the Alaska Air Carriers Association (dated 18 June 2010; comment number OAR-2007-0294-0323.1) an d Alaska Governor Parnell (dated 25 August 2010; comment number OAR-2007-0294-0403.1).B-9 to more than 200,000 LTOs/year). 42 These facilities were re moved from the regression analysis. Additionally, for reasons describe d below, heliports were also removed from the regression. The resu lting relationship was:

Equation 4: LTOs = 1293 + 203*aircraft + 0.0019*county population - 473*Alaska –
144*(AlaskaXa ircraft) R 2 = 0.65

When equation 4 was applied to the 6,414 airport facil ities that report based
aircraft data but not LTO ac tivity, the resulting sum of LTO s was almost 15 million.
EPA estimates that the number of LTOs at the airports that do not report activity data should approximate the number of LTOs from th e bottom of the distribution of the set of airports that report ac tivity data to the 5010 airport data report but th at are not in the TAF database. The average number of LTOs per year from airpor ts in the bottom 30% of the set of airports that report activi ty data to the 5010 airport da ta report but th at are not in the TAF database is ~63 LTOs/year. Multiply ing 63 by the number of airports that do not report activity data equals 549,050 LTOs. 43 Therefore, EPA us ed equation 4 to generate the distribution of LTOs at the individu al airports that report based aircraft data but not activity data and then applied a scali ng factor of 0.0356 to those LTOs to obtain the LTOs that are reported in the 2008 NEI. 44 The sum of the LTOs from this set of airports plus the sum of the LTOs at the airports that do not report either based aircraft or activity data (described below in section (b) ) sum to 549,050 LTOs. These LTOs are all assigned to the GA, piston-engine category since they are assigned to smaller general aviation airports that are assu med to have little to no air taxi or jet aircraft activity.

Equation 4 and the scaling factor were used to estimate LTO activity for the 2008 NEI at airport facilitie s that report based aircraft da ta but not activity data.

(b) Estimating LTOs at Facilities with Neith er Based-Aircraft Data nor LTO Data:

There are 2,260 facilities (not including heliports) for which the 5010 airport data report supplies neither the numb er of based aircraft nor acti vity data. In the absence of
data to establish a relationshi p to airport activity , we assign a defaul t value of LTOs to the GA, piston-engine category for each of these facilities.

42 From FAA’s website, “Addresses for Comme rcial Service Airports”, available at: http://www.faa.gov/airports _airtraffic/airports/planni ng_capacity/passenger_allcar go_stats/addresses/media /commercial_service_ai rports_addresses.xls

43 This rounded number is calculated by multiplying 63 .298 LTOs/year by 8,674, which is the number of airports that don’t report activity data (6,414 don’ t report activity data and 2,260 facilities don’t report activity or based aircraft data).

44

The scaling factor was calc ulated by dividing 528,710 LTOs by 14,862,767 LTOS; the 528,710 LTOs are equal to 549,050 LTOs minus 20,340 LTOs (20,340 LTOs represent the sum of LTOs assigned to the 2,260 facilities that don’t report either activity data or base d aircraft data - the derivation of LTO estimates for
these facilities is described in Section 4 (b) ). The 14,862,767 LTOs are the sum of LTOs that result from applying equation 4 to the 6,414 facilities wi th based aircraft data but no activity data.B-10 The default value was determined by evaluating GA LTOs that are reported at the set of 2,471 facilities th at report activity data to the 5010 airport data report but that are not in the TAF set of airports. The average number of LTOs reported to the bottom ten percent of these facilities (when sorted by to tal GA LTOs) was 9. These facilities are assumed to most closely approximate the set of 2,260 facilities that do not report any based aircraft or LTO data; therefore, we assigned 9 LTO s to the GA, piston-engine category for these airport facilities for pur poses of developing inventory estimates.

Section 5. Calculating LTOs at Heliports:

There were 5,559 heliport facilities in the January 15, 2009 FAA 5010 data report that were operational. Of thos e, only 92 (or 2%) reported LTO data, and of those, only 31 reported both based aircra ft and LTO data. Because of the limited information regarding activity at heliports, some munici palities have hired contractors to survey activity in their local area. 45, 46

The summary statistics for LTO data provided at the 92 operational heliports is presented in Table 2. These facilities report a wide range in activity from 3 LTOs/year to more than 18,000 LTOs/year. Some facilities clearly have significant helicopter traffic (i.e., thousands of LTOs/year) which is supported by the contractor su mmaries of heliport activity in the Washington Metropolitan area. Th e little data available to us suggests that the median helicopter activity is less than 200 LTOs/year. In the absence of more
information on which to base estimates of LTO activity, we assigned 141 LTOs (the median of the reported heliport LTOs) to the GA category at all of the heliports which do not report LTO data. The piston-engine fracti on developed in Section 6 is applied to the 141 LTOs resulting in 51 LT Os assigned to the GA, piston-engine category and 90 assigned to the GA, turbine-engine category. Th is is an area of significant uncertainty in the inventory and one for which EPA is seeking information from local agencies.

Table 2: Heliport LTO Data for those Reporting LTO Da ta in the Janua ry 15, 2009 Version of the 5010 Airport Data Report 18,250 Maximum LTOs

3 Minimum LTOs 1,123 Average LTOs

141 Median LTOs

50 Mode LTOs

45 Executive Summary: Region al Helicopter System Plan, Metropo litan Washington Area, prepared by Edwards and Kelcey for the Metropolitan Washington Counc il of Governments, 2005.

46

Alaska Aviation Emission Inventory, prepared by Sierra Research, Inc. for Western Regional Air Partnership, 2005.B-11 Section 6. Methodology for Estimating Airport

­ Specific Lead Emissions

In 2008, EPA developed a method to calcula te lead emissions at airports where piston-engine powered aircraft operate. 47 This method brings le ad inventories into alignment with the manner in which other cr iteria pollutants emitte d by aircraft are
calculated. This method is described here wi th changes that were made from previous methods (i.e., the method us ed to develop the 2002 invent ory) and applied in developing airport lead inventories for the 2008 NEI. In this section we first present the equation used to calculate lead emitted during the LTO cycle then we de scribe each of the components of th e input data: we describe how we calculate piston-engine LTOs from data available in FAA databases, we describe the derivation of the em ission factor for the amount of lead emitted during the LTO cycle, and we describe the estimate of the amount of lead retained in the engi ne and oil that we do not include in the amount of lead
released to the air.

Historically, where aircraft specific activ ity data are available (such as T-100), aircraft gaseous and particulate matter (PM) emissions have been calculated through the
FAA’s EDMS. 48 This modeling system was designed to develop emission inventories for the purpose of assessing potential air quali ty impacts of airport operations and proposed airport development pr ojects. However, EDMS has a limited number of pistonengine aircraft in its aircraft data and is cu rrently not set up to ca lculate metal emissions and thus, it is not a readily available tool fo r determining airport lead inventories related to aircraft operations. In developing this approach to determine pi ston-engine aircraft lead emissions, EPA relied upon the ba sic methodology employed in EDMS. This requires as input the ac tivity of piston-eng ine aircraft at a facility , fuel consumption rates by these aircraft during the various mode s of the LTO cycle and time in each mode (taxi/idle-out, takeoff, climb-ou t, approach, and taxi/idle-in), the concentration of lead in
the fuel and the retention of lead in the engine and oil. The equation used to calculate airport-specific lead emissions during the LTO cycle is below, follow ed by a description of each of the input parameters.

LTO Pb (tons) = (pisto n-engine LTO)(avgas Pb g/LTO)(1-Pb retention) 907,180 g/ton

(a) Calculating Piston-engine LTO:

Piston-engine LTOs are used to calculate emissions of le ad that are assigned to the airport facility where the aircraft operations occur. An aircraft operation is defined as any landing or takeoff event, ther efore, to calculate LTOs, ope rations are divided by two. Most data sources from FAA report aircraft activity in numbers of operations which, for the purposes of calculating lead emissions, need to be converted to LTO events. We

47

U.S. EPA (2008) Lead Emissions from the Use of Leaded Aviation Gasolin e in the United States, Technical Support Document. EPA420-R-08-020. Available at: www.epa.gov/otaq/aviation.htm.

48 EDMS available from http://www.faa.gov/ about/office_org/headquarters_o ffices/aep/models/edms_model/B-12 describe here the method used to estimate th e fraction of GA and AT LTOs at an airport that are conducted by piston-engine aircraft. These frac tions are calculated separately (one fraction for GA and one for AT). Th ese fractions are multiplied by total LTOs reported separately for GA and AT and then summed to arrive at the total LTOs conducted by piston-engine aircraft at an airport.

One use of the 2008 NEI is to identify s ources of lead, including airports, that have inventories of 0.50 tons per year or m ore for the purposes of identifying locations where lead monitoring may be required to evaluate compliance with the National Ambient Air Quality Standard for Lead. To calculate the most airport-specific inventories for airports that ma y potentially exceed this inve ntory threshold, we used a more airport-specific surrogat e for this subset of airports than the remainder of the airports where we applied national default averages described below.

We used the fraction of based aircraft at an airport that are single- or multi-engine
to calculate the number of GA LTOs at an airport that were conducted by piston-engine aircraft. The data regarding th e population of based aircraft at an airport is available for a subset of airports in the FAA 5010 master records data report described in Section 3. For example, if an airport reports 150 single-engine aircraft, 20 multi-engine aircraft and a
total of 180 aircraft based at that facility, then th e fraction of based aircraft we would use as a surrogate for piston-engine aircraft is 94% ((150+20)/1 80). We then multiply the total GA LTOs for that facility by 0.94 to calculate piston-engine LTOs.

We evaluated this surrogat e by comparing the results of using it with pistonengine aircraft operations reported for airpor ts that supply this information in master plans, airport layout plans, noise abatement studies and/or land use compatibility plans. We could rarely find data fro m the same year for comparison purposes; however, for the majority of airports, based aircraft and actu al observed piston-engine aircraft activity agreed within ten percent. 49

For the majority of airports in the 2008 NE I we used national average fractions of GA and AT LTOs conducted by piston-engine aircraft that were derived using FAA’s
General Aviation and Part 135 50 Activity Surveys – CY 2008 (GAATA). 51 Table 2.4 in the 2008 GAATA Survey re ports that approxim ately sixty-si x percent (66%) of all GA and AT LTOs are from piston-engine aircraft which use avgas, a nd about thirty-four

49 Documents used to evaluate the use of based aircraft in clude the following: Airport Master Plan Update Prescott Municipal Ai rport (Ernest A Love Field) (2009) Available at: www.cityof prescott .net/_d/amp_tablecontents.pdf Gillespie field Airport Layout Plan Upda te Narrative Report (2005) Available at: www.co.sandiego.ca.us/dpw/ airport s/powerpoints/pdalp.pdf Land Use Compatibility Pl an for the Grand Forks Internatio nal Airport (2006) Available at: www.gfk airport .com/authority/pdf/ land

_ use .pdf McClellan-Palomar Land Use Compatibility Plan (Amended March 4, 2010) Available at:
www.ci.oceanside.ca.us/.../ McClellan

- Palomar _ALUCP_03-4-10_amendment.pdf

50

On-demand (air taxi) and commuter operations not cove red by Part 121

51 The FAA GAATA is a database collected from surveys of pilots flying aircraft used for general aviation and air taxi activity. For more informa tion on the 2008 GAATA, see Appendix A at http://www.faa.gov/data_rese arch/aviation_data_statistic s/general_aviation/CY2008/B-13 percent (34%) are turboprop and turbojet powered which use jet fuel, such as Jet A. The
LTO data in Table 2.4 in the 2008 GAATA Survey does not distinguish LTOs as GA or AT, and thus does not allow us derive separate piston activity fractions for GA and AT.

We are using the number of hours flown by piston versus turboprop or turbojet aircraft (reported in Table 1.4 in the 2008 GAATA Survey) to allow us to make separate estimates of the fraction of GA activity conduc ted by piston aircraft and the fraction of AT activity conducted by piston aircraft. We ch ose to use the fraction of hours flown by piston-engine aircraft as a surrogate to calculate the fraction of LTOs flown by piston aircraft since the overall (i.e., for GA and AT combined) piston percent of hours flown (66.4%) is very close to the percent of LTOs that are piston (65.7%). Table 1.4 of the 2008 GAATA presents the total hours flow n by aircraft type an d separates GA from AT. Seventy-three percent (73%) of all GA hours fl own are by piston-engine aircraft while twenty-eight percent (28%) of all GA hours flown are by turboprop and turbojet powered
aircraft. 52 Twenty-three percent (23% ) of all AT hours flow n are by piston-engine aircraft while seventy-seven percent (77%) of all AT hours flown are by turboprop and turbojet powered aircraft. Approximately 5,000 of the total 20,000 airport facilities in the U.S. are heliports at which only helicopters (rotocraft) operate. Therefore, EPA also calculated the percent of rotocraft hours flown that are conduc ted by piston-engine aircraft. Thirty-six percent (36%) of all GA rotocraft hours flown are by piston-engine rotocraft while sixty-four percent (64%) of al l GA rotocraft hours flown are by turboprop and turbojet powered rotocraft. Two percent (2%) of all AT rotocraft hours flown are by piston-engine rotocraft while ninety-eight pe rcent (98%) of all AT rotocraft hours flown are by turboprop and turbojet po wered rotocraft. Table 3 iden tifies the piston and turbine
fractions that were used in th e absence of airport-specific information to calculate pistonengine operations at airports and heliports in the 2008 NEI.

Table 3: Piston and Turb ine Activity Fractions used in the 2008 NEI 

### Airports Heliports

GA AT GA AT
Piston
Powered 72.5% 23.1% 36.1% 2%

Turbine
Powered 27.5% 76.9% 63.9% 98%

52

Numbers in the text may not add to 100% due to r ounding; the percentages in Table 3 are the values we
used to calculate the 2008 NEI.B-14 (b) Calculating the Piston-engine Aircraft Emission Factor: Grams of Lead Emitted per
LTO:

Piston-engine aircraft can have either one or two engines. EDMS version 5.0.2 contains information on the amount of avga s used per LTO for so me single and twinengine aircraft. The proportion of piston-engineLTOs conducted by single- versus twinengine aircraft was taken from the FAA’s GAATA Survey for 2008 (90% of LTOs are conducted by aircraft having one engine and 10% of LTOs by aircraft having two engines). 53 Since twin-engine aircraft have higher fuel consump tion rates than those with single engines, a weighted-average LTO fuel usage rate was calculated to apply to the population of piston-engine aircraft as a w hole. For the single-engine aircraft, the average amount of fuel consumed per LTO was determined from the six types of single piston-engine aircra ft within EDMS. 54 This was calculated by averaging the singleengine EDMS outputs for fuel consumed per LTO using the EDMS scenario property of ICAO/USEPA Default - Times in Mode (TIM), with a 16 minute taxi-in/taxi-out time according to EPA’s Procedures for Emission Inventory Preparation, Volume IV: Mobile
Sources , 1992. 55 This gives a value of 16.96 pounds of fuel per LTO (lbs/LTO). The average single-engine fuel consumption rate was divided by the average density of 100LL avgas, 6 pounds per gall on (lbs/gal), producing an average fuel usage rate for single-engine piston aircraft of 2.83 gallon s per LTO (gal/LTO). This same calculation was performed for the two twin-engine pist on aircraft within EDMS, producing an average LTO fuel usage rate for twin-e ngine piston aircraft of 9.12 gal/LTO.

Using these single- and twin-engine piston aircraft fuel consumption rates, a weighted average fuel usage rate per LTO wa s computed by multiplying the average fuel usage rate for single-engine aircraft (2.83 gal/LTO) by the fleet percentage of singleengine aircraft LTOs (90%). Next, the twin-engi ne piston aircraft average fuel usage rate (9.12 gal/LTO) was mu ltiplied by the fleet percentage of twin-engine aircraft LTOs (10%). By summing the results of the single - and twin-engine aircra ft usage rates, the overall weighted-average fuel usage rate per LTO of 3.46 gal/LTO was obtained.

To calculate the emission factor, the concen tration of lead in fuel is multiplied by the fuel consumption per LTO. The maximum lead concentr ation specified by ASTM for 100LL is 0.56 grams per liter or 2.12 grams pe r gallon. This amount of lead is normally added to assure that the required lean and rich mixture knock values are achieved. Multiplying this lead concentr ation in avgas by the weighted average fuel usage rate produces an overall average valu e of 7.34 grams oflead per LTO (g Pb/LTO) for pistonengines: 3.46 gal/LTO x 2.12 g Pb/gal = 7.34 g Pb/LTO.

53 The LTOs from the categories of 1-e ngine fixed wing pi ston, piston rotocraft, experimental total, and light sport were summed to determine the total nu mber of single-engine piston aircraft LTOs.

54

EPA understands that EDMS 5.0.2 ha s a limited list of pi ston-engines, but these are currently the best
data available.

55 U.S. EPA, Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources , EPA-450/4- 81026d (Revised), 1992.B-15 (c) Retention of Lead in Engine and Oil (1-Pb Retention):

Data collected from aircraft piston-engines operating on leaded avgas suggests
that about 5% of the lead fr om the fuel is retained in the engine and engine oil. 56 Thus
the emitted fraction is 0.95. This information is used in calculating airport-specific lead
inventories and will be used to develop future natio nal estimates of lead emitted from the consumption of leaded avgas.

Applying these parameters in the equation above yields the following equation:

Pb(tons) = (piston-engine LTO) (7.34 g Pb/LTO) (0.95) 907,180 g/ton

which simplifies to:

Pb(tons) = (piston-engine LTO) (7.7 X 10 -6 )

Where piston-engine LTO 57 = (GA LTO x 0.725) + (AT LTO x 0.231)

(d) Estimating Lead Emissions from Piston-Engine Helicopters:

The emission factor for helicopters (g Pb/LTO) was determined in the same manner as described above for piston-engine fixed-wing aircraft. The concentration of lead in avgas (2.12 g/gal) was multiplied by the weighted aver age fuel usage rate for four types of Robinson helicopter engines. 58 This produced an overall average emission factor of 6.60 grams of lead per LTO (g Pb/ LTO) for piston-engine powered helicopters.

There are no national databases that prov ide heliport-specifi c LTO activity data for piston-engine powered helicopters se parately from turbine-engine powered helicopters. The 2008 FAA GA and Part 135 Activity (GAATA) Survey reports that approximately 36% of all GA he licopter hours flown are by pi ston-engine aircraft which use avgas, and about 64% are by turbine-engine powered which use jet fuel (which does

56 The information used to develop this estimate is from the following references : (a) Todd L. Petersen, Petersen Aviation, Inc, Aviation Oil Lead Content Analysis , Report # EPA 1-2008, January 2, 2008, available at William J. Hughes Technical Center Technical Reference and Research Library at http://actlibrary.tc.fa a.gov/ and (b) E-mail from Theo Rindlisbacher of Switzerland Federal Office of Civil Aviation to Bryan Manning of U.S. EPA, regardin g lead retained in engine, September 28, 2007.

57 This equation for piston-engine LTOs only applie s to non-heliport facilities. See the text immediately below for equations for calculating piston-engi ne LTOs and Pb emis sions at heliports.

58 This was done using the followi ng 4 engine types in EDMS 5.1: Robinson R22 IO-320-D1AD; Robinson R22 IO-360-B; Robinson R22 O- 320; Robinson R22 TSIO-360C. The fuel consumption rates were: Robinson R22 IO-320-D1AD – 5.546 g Pb/LTO; Robinson R22 IO-360-B – 5.973 g Pb/LTO; Robinson R22 O-320 – 6.276 g Pb/LTO; Robinson R22 TSIO-360C – 8.604 g Pb/LTO.B-16 not contain lead). 59 The 2008 FAA GAATA Su rvey reports that approximately 2% of all AT helicopter hours flown are by piston-engin e aircraft which use avgas, and about 98% are by turbine-engine powered rotocraft. We expect the fraction of helicopter activity conducted by piston -engines to vary by heliport with some facilities havi ng no pistonengine powered helicopter activity and some hosting mainly or only piston-engine powered helicopters. However, in the abse nce of heliport-specifi c data, the national
default estimates of 36% fo r GA and 2% for AT from th e GAATA Survey were used. Therefore, to calculate piston-engine airc raft LTO as input for this equation, the helicopter GA LTOs were mul tiplied by 0.36 and he licopter AT LTOs were multiplied by
0.02.

Lead emitted at the heliport facility wa s calculated for the 2008 NEI using either the LTO data provided in FAA databases or the es timate LTO activity in the following equation (i.e., 141 LTOs):

Pb(tons) = (piston-engine helic opter LTO) (6.60 g Pb/LTO) (0.95)

907,180 g/ton

which simplifies to:

Pb(tons) = (piston-engine helicopter LTO) (6.9 X 10 -6 )

Where piston-engine helicopter LTO = (Helicopter GA LTO x 0.36) + (Helicopter AT LTO x 0.02)

Section 7. Improving Airport

­ specific Lead Emissions Estimates

There are refinements to the methods described here that would improve airportspecific inventories, most of which involve acquiring airport- and aircraft-specific input
data. The following information describes data inputs that could be used to generate airport lead inventories tailored to specific airports or otherwise improve the estimates using currently available data . State and local authorities might have, or be able to collect, better information for so me of these key data inputs.

State and local agencies might have acce ss to airport-specific data that would improve the national estimates of lead emissions per LTO . These improvements largely involve replacing national average or default values with airport-specific data on the activity of piston-engine aircraft. Three key data inputs are:

59 The FAA GAATA is a database collected from surveys of pilots flying aircraft used for general aviation and air taxi activity. For more information on the GAATA, see Appendix A at http://www.faa.gov/data_statistics/avia tion_data_statistics/general_aviation/B-17 1) Airport-specific LTO activity for piston-powered aircraft, including the fraction of piston-engine activity c onducted by single- versus twin-engine aircraft. Some airport facilities collect this informati on and states may use these data to calculate airport-specific lead inventories. The activity data should be current and updated on a regular schedule so that the data represents the inventory year as closely as possible. 2) The time spent in each mode of the LTO cycle. EPA uses the EDMS scenario property of ICAO/USEPA Defa ult - Times in Mode, wi th a 16 mi nute taxiin/taxi-out time according to EPA’s Procedures for Emission Inventory Preparation, Volume IV: Mobile Source s, 1992. While some local authorities
have confirmed that these are the relevant times in mode at thei r airports for piston aircraft, the applicability of these times in mode will vary by airport. EPA has learned that one of the important factors in piston aircraft operation that is currently not included in the time in mode or emissions estimates is the time and fuel consumption during the pre-flight run-u p checks conducted by piston-engine aircraft prior to takeoff. 3) Other data inputs for the airport-specif ic lead inventory calculation for which
states or local authoritie s may provide airport-specific information include the concentration of lead in the avgas supplied at an airport, and the fraction of lead
in fuel that is retained in the engine and oil, and aircraft-specific fuel consumption rates by the piston-engine ai rcraft in specific modes of operation.

The accuracy of the based aircraft data on which equation 4 is modeled can be improved. FAA recogniz es the need to improve the inte grity of the 5010 data report based-aircraft counts for all of the GA airports and reliever airports in the NPIAS and is currently in the process of improving the data collection and submission methods to accomplish this task. 60

Section 8. Lead emitted in flight (i.e., outside the LTO cycle):

Lead emissions, especially those at al titude, undergo dispersion and eventually deposit to surfaces, and lead deposited to soil and water can remain available for uptake by plants, animals and humans for long periods of time. Because lead is a persistent pollutant, we are including all lead emissions – at airports and in-flight – in the NEI. 61

For inventory purposes, lead emitted outside the LTO cycl e occurs during aircraft cruise mode and portions of the climb-out and approach modes above the mixing height (typically 3,000 ft 62 ). This part of an aircraft operation emits lead at various altitudes as well as close to and away from airports. B ecause the precise area of lead emission and deposition is not known for these flights, EP A is using a simplistic approach to allocate

60 National Based Aircraft Inventory Program: http://www.basedaircraft.com/pub lic/FrequentlyAsk edQuestions.aspx, accessed 2/17/2009

61 U.S. EPA, 2006. Air Quality: Criteria for Lead: 2006; EPA/600/R-5/144aF; U.S. Government Printing Office, Washington, DC, October, 2006.

62

According to EPA’s Procedurees for Emission Inventory Preparation, Volume IV: Mobile Sources, 1992

.B-18 these emissions for the purposes of the 2008 NEI. A brief explanation of the nature of GA flights is provided here for context regarding emissions of lead in-flight.

FAA categorizes GA flights as either lo cal area or itinerant operations and this distinction plays a role in the area over which lead is emitted. Local operations are those activities performed by aircraft operating in the local traffic pa ttern or within sight of the airport, aircraft executing simulated instrumen t approaches or low passes at the airport, and/or aircraft operating to or from the ai rport in a designated practice area located
within a 20-mile radius of th e airport. Local operations are common for GA aircraft. This includes applications such as recreational, proficiency and instructional flying as well as many common general aerial support task s. Emissions during lo cal flying are more likely to influence air and soil co ncentrations of lead in the vi cinity of the airport because they occur near the airport, often at altitudes below the mixing height.

Itinerant operations are all operations othe r than those described above as local operations. An itinerant aircraft operation us ually is one in which the aircraft departs from one airport and lands at a different air port. Depending on air ti me and distance, an itinerant flight is much more likely to i nvolve departing the local flying area of the originating airport and climbing to altitude s above the mixing heig ht. It is reasonable then, to generally expect that lead emi tted outside the LTO cy cle during itinerant operations, in contrast with lo cal operations, will be more wi dely dispersed and at greater distances from the airport.

The portion of the national avgas lead emitted in flight (i.e., outside the LTO cycle) is calculated by subtracting the sum of airport facility lead inventories from the national avgas lead inventory. Even th ough FAA collects and reports information regarding the fraction of GA operations that are local and itinerant, there is no practical method to assign in-flight lead emissions to small geographic areas such as airports or
census tracts. And similar data is not availabl e for AT operations, a portion of which are conducted by piston-engine aircraft. Sinc e the average duration of a piston-engine aircraft flight is approximately an hour, an itinerant flight can traverse county lines. Therefore, given the current data available, the best approach is to assign the out-of-LTO cycle lead to the state where the flight originated.

In the 2008 NEI EPA allocated lead emissions that are calculated as being outside the LTO cycle to states based on the state-specific fraction ofnational GA and AT pistonengine LTO activity. The state-specific fr actions were calculate d by multiplying the percent of GA and AT piston-eng ine LTO activity in each state by 296 tons, which is the amount of lead we currently estimate is emitted outside of the LTO cycle nationwide. Table 4 presents the total GA and AT piston- engine LTOs by state, the state-specific faction of national GA and AT piston-engine LTO activity, and the out-of-LTO lead emissions assigned to each state.B-19 Table 4: Out-of-LTO Lead Emissions by State

STATE Total GA and AT

Piston

LTOs Percent of
National GA
and AT Piston LTOs (by state) Out of LTO
Pb emissions (tons)

A K 660,133 2.0% 5.86 AL 671,026 2.0% 5.96 AR 638,875 1.9% 5.68 AZ 1,430,302 4.3% 12.71 CA 3,881,357 11.6% 34.48 CO 780,426 2.3% 6.93 CT 226,807 0.7% 2.01 DC 28,833 0.1% 0.26 DE 84,617 0.3% 0.75 FL 2,751,015 8.3% 24.44 GA 750,876 2.3% 6.67 HI 138,432 0.4% 1.23 IA 281,961 0.8% 2.50 ID 430,812 1.3% 3.83 IL 920,908 2.8% 8.18 IN 566,583 1.7% 5.03 KS 459,720 1.4% 4.08 KY 280,378 0.8% 2.49 LA 622,011 1.9% 5.53 MA 714,159 2.1% 6.34 MD 436,861 1.3% 3.88 ME 228,302 0.7% 2.03 MI 880,818 2.6% 7.82 MN 647,876 1.9% 5.76 MO 389,551 1.2% 3.46 MS 461,383 1.4% 4.10 MT 270,311 0.8% 2.40 NC 743,004 2.2% 6.60 ND 214,139 0.6% 1.90 NE 221,681 0.7% 1.97 NH 173,355 0.5% 1.54 NJ 466,961 1.4% 4.15 NM 309,657 0.9% 2.75 NV 298,712 0.9% 2.65 NY 999,738 3.0% 8.88 OH 1,180,583 3.5% 10.49 OK 575,402 1.7% 5.11 OR 596,730 1.8% 5.30 PA 954,839 2.9% 8.48B-20 PR 80,728 0.2% 0.72 RI 45,348 0.1% 0.40 SC 506,650 1.5% 4.50 SD 228,198 0.7% 2.03 TN 535,913 1.6% 4.76 TX 2,422,722 7.3% 21.52 UT 299,471 0.9% 2.66 VA 502,559 1.5% 4.46 VI 25,763 0.1% 0.23 VT 88,318 0.3% 0.78 WA 1,189,142 3.6% 10.56 WI 778,320 2.3% 6.91 WV 143,393 0.4% 1.27 WY 106,190 0.3% 0.94

For additional information or if you have ques tions regarding the methods described in this document, please contact Meredith Pedde (pedde.meredith@epa.gov) or Marion Hoyer (hoyer.marion@epa.gov ).B-21 Supplemental Table 1

Table A-1: Scaling factors

Year U.S. Product Supplied
of Aviation Gasoline (Thousand Barrels) 63 Ratio of
2008 to
Year X

Before 1981 64 0.57

1981 11,147 0.50
1982 9,307 0.60
1983 9,444 0.59
1984 8,692 0.64
1985 9,969 0.56
1986 11,673 0.48
1987 9,041 0.62
1988 9,705 0.58
1989 9,427 0.59
1990 8,910 0.63
1991 8,265 0.68
1992 8,133 0.69
1993 7,606 0.74
1994 7,555 0.74
1995 7,841 0.71
1996 7,400 0.76
1997 7,864 0.71
1998 7,032 0.80
1999 7,760 0.72
2000 7,188 0.78
2001 6,921 0.81
2002 6,682 0.84
2003 5,987 0.94
2004 6,189 0.91
2005 7,006 0.80
2006 6,626 0.85
2007 6,258 0.90
2008 5,603 1.00

63 Data from the Energy Information Administration’ s (EIA’s) table, “U.S. Pr oduct Supplied of Aviation Gasoline (Thousand Barrels).” Available at: http://tonto.eia.doe .gov/dnav/pet/hist/LeafHandler .ashx?n=PET&s=mgaupus1&f=A Accessed August 25, 2010.

64

EIA does not have data for volumes of avgas produ ct supplied for years earlie r than 1981. To calculate the scaling factor to use for activity data from years before 1981, we used the r atio of 2008 avgas volume product supplied to the average avgas volume supplied from 1981 to 1989.