ERG No.: 0245.03.402.001 

Contract No.: EP-D-07-097 

Documentation for Aircraft Component 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, 2011 
i 

TABLE OF CONTENTS 

Section Page No. 

1.0 INTRODUCTION ........................................................................................................... 1-1

1.1 What is the National Emission 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 the 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 Aircraft Emission Factors 

Appendix B – Calculating Piston-Engine Aircraft Airport Inventories for Lead for the 2008 

National Emissions Inventory 
ii 

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 Annual 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 Emission Estimates 2008 (tons per year) ...................................... 2-18

Table 2-5. Aircraft HAP Emission Estimates 2008 (tons per year) ........................................... 2-18

Figures Page No. 

Figure 2-1. Procedures for Estimating Emissions from Commercial Air Carriers .................... 2-14

Figure 2-2. Procedures for Estimating Emissions from Commercial Air Taxis and General 

Aviation...................................................................................................................................... 2-15
1-1 

1.0 INTRODUCTION 

1.1 What is the National Emission Inventory? 

 The National Emission Inventory (NEI) is a comprehensive inventory 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 modeling and other activities. To this end, the EPA 

established a goal to compile comprehensive emissions 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 pollutants. The CAA defines criteria pollutants as being one of the 

following air pollutants: 

 Carbon monoxide (CO); 

 Sulfur oxides (SOx); 

 Nitrogen oxides (NOx); 

 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 regulated pollutants and their 

chemical abstract service [CAS] numbers. 

 The CAA requires the EPA to identify emission sources of these pollutants, quantify 

emissions, develop regulations for the identified source categories, and assess the public health 

and environmental impacts after the regulations are put into effect. The NEI is a tool that EPA 

can use to meet the CAA mandates. In this report, 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 the 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 developed for the NEI will be used to evaluate 

air pollution trends, air quality modeling analysis, and impacts of potential regulations. 

1.4 Report Organization 

 Following this introduction, Section 2.0 provides information on how the national aircraft 

emission estimates were developed. This inventory effort was coordinated 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 AIRCRAFT 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 source categories are 

documented in other reports. Table 2-1 summarizes the approaches used to estimate emissions 

from all nonroad sources included in the NEI program. 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 States 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 state in the United States and every county 

within a state, including Washington, DC, Puerto Rico, and US Virgin Islands. There are no 

boundary limitations pertaining to traditional criteria pollutant nonattainment areas or to 

designated urban areas. The pollutants inventoried included all criteria pollutants (and the 

188 HAPs identified in Section 112(b) of the CAA). 

 In addition to numerous specific chemical 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 estimates for the individual compounds wherever 

possible. Many of the uses of the NEI depend upon data (e.g., toxicity) for individual compounds 

within these groups rather than aggregated data on each group as a whole. 

 The intent in presenting the following emission inventory approach is to provide 

sufficient and transparent documentation such that states and local agencies can use these 

approaches, in conjunction with their 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 this factor may not be presented 

or discussed. The goal of the documentation provided is to show in a brief and concise manner 

how a given estimate was derived. 
2-2 

Table 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 Area Emission Estimation Method 

2008 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed usi

Inventory Model (NMIM), which uses MOBILE6 (specM6203ChcOxFixNMIM.exe) to calculate onroad emissiprovided alternate onroad MOBILE6 inputs or VMT, thinputs. Default VMT is based on FHWA 2008 data and estimates. 

2005 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed usi

MOBILE6 to calculate onroad emission factors. Where 

onroad MOBILE6 inputs or VMT, these data replaced EVMT is based on FHWA 2005 data and 2005 Census po

2002 All Criteria, HAPs US, Puerto Rico, Virgin Islands Emission estimates for all pollutants were developed usi

MOBILE6 to calculate onroad emission factors. Where 

onroad MOBILE6 inputs or VMT, these data replaced Esupplied emissions data which replaced default EPA em

Default VMT is based on FHWA 2002 data and populat

2001 VOC, NOx, CO, SO2, PM10, 

PM2.5

California Emissions and VMT provided by California at county/v

provided emissions expanded to county/SCC level by E

2001 NH3 California Calculated at State/county/SCC level by month using M

State-provided VMT data. 

2001 All Criteria AL; CO; ME; MA; MS; OR; UT; VA; 

WV; Maricopa County, AZ; Hamilton 

County, TN 

State-provided VMT grown to 2001; emissions calculatemission factors. 

2001 All Criteria Rest of US Calculated at State/county/SCC level by month using M

VMT. 

1999 All Criteria AL; ME; MA; MS; UT; VA; WV; 

Maricopa County, AZ; Hamilton 

County, TN 

Calculated at State/county/SCC level by month using MVMT data used. 

1999 VOC, NOx, CO, SO2, PM10, 

PM2.5

California Emissions and VMT provided by California at county/v

provided emissions expanded to county/SCC level by E

1999 NH3 California Calculated at State/county/SCC level by month using M

State-provided VMT data. 

1999 PM10 Exhaust Colorado PM10 emissions and VMT provided by State. 
2-3 

Table 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 Area Emission Estimation Method 

1999 VOC, NOx, CO, SO2, PM10

brake and tire wear, PM2.5, 

NH3

Colorado Calculated at State/county/SCC level by month using M

VMT data used. 

1999 All Criteria Oregon Emissions and VMT provided by Oregon at county/vehi

emissions expanded to county/SCC level by EPA. 

1999 All Criteria Rest of US, Puerto Rico, and US 

Virgin Islands 

Calculated at State/county/SCC level by month using MVMT. 

1999 HAPs California HAP emissions and VMT provided by California at cou

emissions allocated to SCC level by EPA. 

1999 HAPs Rest of US, Puerto Rico, and US 

Virgin Islands 

MOBILE6 emission factors calculated at State/county/SFHWA-based VMT. 

1997-1998 All Criteria US 2-step linear interpolation at State/count/SCC level base

State/count/SCC level data. 

1990, 1996 HAPs US MOBILE6 emission factors calculated at State/county/S

Federal Highway Administration (FHWA)-based vehicl

1991-1995 All Criteria US Linear interpolation at State/count/SCC level based on 1

State/count/SCC level data. 

1988-1989 All Criteria US Linear interpolation at State/count/SCC level based on 1

State/count/SCC level data. 

1979-1986 All Criteria US Linear interpolation at State/count/SCC level based on 1

State/count/SCC level data. 

1978, 1987, 1990, 1996, 

2000 

All Criteria US Calculated at State/county/source classification code (SC

MOBILE6, no State data incorporated. 

1970, 1975 All Criteria US Linear extrapolation at national vehicle type level based 

data. 
2-4 

Table 2-1b. Methods Used to Develop Annual Emission Estimates for 

Nonroad Mobile Sources 

(Categories included in this report are noted in bold print) 

Category Base Year Pollutant(s) Estimation Method* 

NONROAD CategoriesNonroad Gasoline, 

Diesel, LPG, CNG 

2008 VOC, NOx, CO, SO2, 

PM10, PM2.5, NH3, & 

HAPs 

Emission estimates for NONROAD model engines were developed using EPAModel (NMIM), which incorporates NONROAD2008. Where states provided 

inputs, these data replaced EPA default inputs. 

2005 VOC, NOx, CO, SO2, , 

PM10, PM2.5, NH3, & 

HAPs 

Emission estimates for NONROAD model engines were developed using EPANONROAD2005. Where States provided alternate nonroad inputs, these data 

2002 VOC, NOx, CO, SO2, 

PM10, PM2.5, NH3, & 

HAPs 

Emission estimates for NONROAD model engines were developed using EPANONROAD2004. Where states provided alternate nonroad inputs, these data rState-supplied emissions data also replaced default EPA emission estimates. 

 1999 VOC, NOx, CO, SO2, 

PM10, PM2.5

Using emission estimates from two emission inventories including: 1) a 1996 developed using EPA’s October 2001 draft NONROAD model; and 2) an updbased on EPA’s draft Lockdown C NONROAD model (dated May 2002). Usiemission estimates, seasonal and daily county-to-national ratios were then devupdated national estimates per season estimated from the Lockdown C model. 

for California for all NONROAD model categories; Pennsylvania for recreatiosupport equipment, and Texas for select equipment categories. 

 1996, 1997, 

1998, 2000 & 2001 

VOC, NOx, CO, SO2, 

PM10, PM2.5

Using emission estimates from two emission inventories including: 1) a 1996 developed using EPA’s October 2001 draft NONROAD model; and 2) updateCalifornia inventories, based on EPA’s draft Lockdown C NONROAD model 1996 county-level emission estimates, seasonal and daily county-to-national rastate ratios were then developed for application to updated national estimates pLockdown C model. California results replace the diesel equipment emissions application of county-to-national ratios. 
2-5 

Table 2-1b. Methods Used to Develop Annual Emission Estimates for 

Nonroad Mobile Sources (Continued)

(Categories included in this report are noted in bold print) 

Category Base Year Pollutant(s) Estimation Method*

Nonroad Gasoline, 

Diesel, LPG, and CNG (Continued) 

1991-1995 VOC, NOx, CO, SO2, 

PM10, PM2.5, NH3

Using 1990 and 1996 county-level emissions inventories, estimated emissions national emissions between 1990 and 1996. From these emissions, calculated tfor each pollutant/SCC combination for each year, and then applied the growth 

emissions to estimate 1991-1995 emissions. 

 1990 VOC, NOx, CO, SO2, 

PM10, PM2.5

Using emission estimates from two emission inventories including: 1) a 1996 developed using EPA’s October 2001 draft NONROAD model; and 2) updatebased on EPA’s draft Lockdown C NONROAD model (dated May 2002). Usiemission estimates, seasonal and daily county-to-national ratios were then devupdated national estimates per season estimated from the Lockdown C model. 

 1986, 1988, & 

1989 

VOC, NOx, CO, SO2, 

PM10, PM2.5, NH3

Using 1985 and 1990 county-level emissions inventories, estimated emissions national emissions between 1985 and 1990. From these emissions, calculated tfor each pollutant/SCC combination for each year, and then applied the growth 

emissions to estimate 1986-1989 emissions. 

 1987 VOC, NOx, CO, SO2, 

PM10, PM2.5

Using EPA’s draft Lockdown C NONROAD model (dated May 2002), develoemissions for 1987 by running 4 seasonal NONROAD model runs to estimate emissions. Also performed national NONROAD model runs to estimate typica

1985 VOC, NOx, CO, SO2, 

PM10, PM2.5

Using emission estimates from two emission inventories including: 1) a 1996 developed using EPA’s October 2001 draft NONROAD model; and 2) updatebased on EPA’s draft Lockdown C NONROAD model (dated May 2002). Usiemission estimates, seasonal and daily county-to-national ratios were then devupdated national estimates per season estimated from the Lockdown C model. 

 1970, 1975, 

1978, & 1980 

VOC, NOx, CO, SO2, 

PM10, PM2.5

Using EPA’s draft Lockdown C NONROAD model (dated May 2002), develoemissions for all years by running 4 seasonal NONROAD model runs to estimemissions. Also performed national NONROAD model runs to estimate typica
2-6 

Table 2-1b. Methods Used to Develop Annual Emission Estimates for 

Nonroad Mobile Sources (Continued)

(Categories included in this report are noted in bold print) 

Category Base Year Pollutant(s) Estimation Method*

Nonroad Gasoline, 

Diesel, LPG, and CNG (Continued) 

1996, 1997, 1998, 1999, 2000, & 2001 

NH3 Obtaining national fuel consumption estimates from the Lockdown C NONRO

NH3 emission factors, and distributing to counties using 1996 inventory, based 

NONROAD. NH3 emissions for California were also recalculated using updat

values generated for California-specific runs, and assuming the 1996 county-le

1985 & 1990 NH3 Obtaining national fuel consumption estimates from the Lockdown C NONRO

NH3 emission factors, and distributing to counties using 1996 inventory, based 

NONROAD. 

1987 NH3 Obtaining 1987 national fuel consumption estimates from Lockdown C NONR

by NH3 emission factors. 

1970, 1975, 1978, & 1980 

NH3 Obtaining national fuel consumption estimates from the Lockdown C NONRO

NH3 emission factors. 

 1990, 1996, & 

1999 

HAPs Speciation profiles applied to county VOC and PM estimates. Metal HAPs we

activity-based emission factors. Some state data were provided and replaced n

AircraftCommercial Aircraft 

2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeli

5.1.was run using BTS T-100 LTO data. (2009) 

2002 and 2005 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion and Modeli

for criteria pollutants, VOC and PM emissions were speciated into HAP comp

1990, 1996, 1999, 2000, 2001 

VOC, NOx, CO, SOx Input landing and take-off (LTO) data into FAA EDMS. National emissions w

on airport specific LTO data and BTS GIS data. State data replaced national es

1970-1998 VOC, NOx, CO, SOx Estimated emissions for interim years using linear interpolation between avail1990, 1996, 1999 

HAPs Speciation profiles were applied to VOC estimates to get national HAP estima

national estimates. (2003) 

General Aviation, Air Taxis 

2008 Criteria and HAPs Federal Aviation Administration (FAA) Emissions and Dispersion Modeli

5.1.was run using BTS T-100 LTO for aircraft identified as Air taxis. (201

Used FAA LTO data from TAF and OTAQ provided activity data for smFAA 5010 master plans. EPA approved generic emission factors for criterprofiles were applied to VOC and PM estimates to get national HAP estim
2-7 

Table 2-1b. Methods Used to Develop Annual Emission Estimates for 

Nonroad Mobile Sources (Continued)

(Categories included in this report are noted in bold print) 

Category Base Year Pollutant(s) Estimation Method*

General Aviation, Air Taxis (Continued) 

2005 VOC, NOx, CO, SO2, 

PM10, PM2.5

2002 emissions for approximately 4,000 largest airports were calculated via EDincluded in the 2005 NEI as point sources. Only airports in FAA’s T100 and TState point source submittals were incorporated. 

1978, 1987, 1990, 1996, 1999, 2000, 2001, & 2002 

VOC, NOx, CO, SO2, 

PM10, PM2.5

Used FAA LTO data and EPA approved emission factors for criteria estimatesapplied to VOC estimates to get national HAP estimates. State data replaced n

 1970-1998 VOC, NOx, CO, SOx, 

PM10, PM2.5

Estimated emissions for interim years using linear interpolation between avail

 1990, 1996, 

1999, & 2002 

HAPs Used FAA LTO data and EPA approved emission factors for criteria estimates

applied to VOC estimates to develop national HAP estimates. (2004) 

 1990, 1996, 

1999, & 2002 

Pb Used Department of Energy (DOE) aviation gasoline usage data with lead con

(2004) 

 1996 NH3 Applied NH3 emissions factors to 1996 national jet fuel and aviation gasoline Military Aircraft 2008 VOC, NOx, CO, SO2, 

PM10, PM2.5

Used FAA LTO data as reported in TAF and EPA approved emission facRepresentative HAP profiles were not readily available, therefore HAP es(2010) 

2005 VOC, NOx, CO, SO2, 

PM10, PM2.5

2002 emissions were included in the 2005 NEI as point sources similar to othe

1978, 1987, 1990, 1996, 1999, 2000, 2001, 2002, 2008 

VOC, NOx, CO, SO2, 

PM10, PM2.5

Used FAA LTO data as reported in TAF and EPA approved emission factors fRepresentative HAP profiles were not readily available, therefore HAP estima

 1970-1998 VOC, NOx, CO, SOX, 

PM10, PM2.5

Estimated emissions for interim years using linear interpolation between avail

Auxiliary Power Units and Ground Support Equipment 

2008 VOC, NOx, CO, SO2, 

PM10, PM2.5, HAPs 

Federal Aviation Administration (FAA) Emissions and Dispersion and MVersion 5.1.was run using BTS T-100 LTO data. (2009) 

2002 and 2005 VOC, NOx, CO, SO2, 

PM10, PM2.5, HAPs 

Computed via NONROAD2005 model runs. 

1985-2001 VOC, NOx, CO, SO2, 

PM10, PM2.5

Grew 1996 emissions to each year using LTO operations data from the FAA. E1996 reported in EPA, 1998. 
2-8 

Table 2-1b. Methods Used to Develop Annual Emission Estimates for 

Nonroad Mobile Sources (Continued)

(Categories included in this report are noted in bold print) 

Category Base Year Pollutant(s) Estimation Method*

Unpaved Airstrips1 1985-2001 PM10, PM2.5 Grew 1996 emissions to each year using SIC 45-Air Transportation growth fa

current draft version of EGAS. Estimation methods prior to 1996 reported in E

Aircraft Refueling1 1985-2001 VOC Grew 1996 emissions to each year using SIC 45-Air Transportation growth fa

current draft version of EGAS. Estimation methods prior to 1996 reported in E

Commercial Marine Vessel (CMV)All CMV Categories 2008 VOC, NOx, CO, SO2, 

PM10, PM2.5

OTAQ provided CAP emission estimates for all CMV categories. Note that thchanged such that the Diesel category refers to smaller vessels (Category 1 anthe Residual category refers to larger (Category 3) vessels using a blend of resallocated to segments using GIS shapefiles and adjusted based on limited state 

 2008 HAPs OTAQ’s 2008 estimates were speciated into HAP components using SEPA pr

CMV Diesel 2002 and 

2005 

VOC, NOx, CO, SO2, 

PM10, PM2.5

2001 Estimates carried over. Used state data when provided. (2004) 

HAPs 1999 Estimates carried over. Used state data when provided. (2004) 

1978, 1987, 1990, 1996, 1999, 2000, & 2001 

VOC, NOx, CO, SOx, 

PM10, & PM2.5

Used criteria emission estimates in the background document for marine dieseAdjusted 2000 criteria emission estimates for other used based on fuel usage. into port traffic and underway activities. Port emissions were assigned to spec

cargo handled. Underway emissions were allocated based on Army Corp of EState data replaced national estimates. (2003) 

 1970-1998 VOC, NOx, CO, SOx, 

PM10, PM2.5

Estimated emissions for interim years using linear interpolation between avail

 1990, 1996, 

1999 

HAPs VOC and PM emission estimates were speciated into HAP components. State 

estimates. (2003) 

 1996 NH3 Applied NH3 emissions factors to 1996 distillate and residual fuel oil estimate

1996). 

 1990-1995 NH3 Estimation methods reported in EPA, 1998. 
2-9 

Table 2-1b. Methods Used to Develop Annual Emission Estimates for 

Nonroad Mobile Sources (Continued)

(Categories included in this report are noted in bold print) 

Category Base Year Pollutant(s) Estimation Method*

CMV Steam Powered 

2005 VOC, NOx, CO, SOx, 

PM10, & PM2.5, HAPs 

2002 estimates grown to 2005 (2008). 

2002 VOC, NOx, CO, SOx, 

PM10, & PM2.5, HAPs 

2002 based estimates were developed for port and underway category 3 (C3) v

effort. Emissions were developed separately for near port and underway emisinventories for 2002 were developed for 89 deep water and 28 Great Lake porNetwork Ship Traffic, Energy, and Environmental Model (STEEM) was used ships traveling in shipping lanes between and near individual ports (2008) 

1978, 1987, 1990, 1996, 1999, 2000, & 2001 

VOC, NOx, CO, SOx, 

PM10, & PM2.5

Calculated criteria emissions based on EPA SIP guidance. Emissions were disand under way activities. Port emissions were assigned to specific ports based 

Underway emissions were allocated based on Army Corp of Engineering watenational estimates. (2003) 

 1970-1998 VOC, NOx, CO, SOx, 

PM10, PM2.5

Estimated emissions for interim years using linear interpolation between avail

 1990, 1996, & 

1999 

HAPs VOC and PM emission estimates were speciated into HAP components. State 

estimates. (2003) 

Military Marine 1997-2001 VOC, NOx, CO, SO2, 

PM10, PM2.5

Applied EGAS growth factors to 1996 emissions estimates for this category. 

CMV Coal,2 CMV, 

Steam powered, CMV Gasoline2

1997-1998 VOC, NOx, CO, SO2, 

PM10, PM2.5

Applied EGAS growth factors to 1996 emissions estimates for this category. 

CM Coal, CMV, Steam powered, CMV Gasoline, Military Marine 

1991-1995 VOC, NOx, CO, SO2, 

PM10, PM2.5

Estimation methods reported in EPA, 1998. 

LocomotivesClass I, II, III and Yard operations 

2008 VOC, NOx, CO, PM10, 

PM2.5,SOx & HAPs 

Criteria emission estimates were provided to EPA by ERTAC. These data werrailway segments using DOT shapefiles and guidance from ERTAC. HAP emapplying speciation profiles to VOC and PM estimates. (2010) 
2-10 

Table 2-1b. Methods Used to Develop Annual Emission Estimates for 

Nonroad Mobile Sources (Continued)

(Categories included in this report are noted in bold print) 

Category Base Year Pollutant(s) Estimation Method*

Class I, Class II, Commuter, Passenger, and Yard Locomotives 

1978, 1987, 1990, 1996, 1999, 2000, 2000, 2002, & 2005 

VOC, NOx, CO, PM10, 

PM2.5

Criteria pollutants were estimated by using locomotive fuel use data from DOfactors. County-level estimates were obtained by scaling the national estimateDOT. State data replaced national estimates. (2004) 

1978, 1987, 1990, 1996, 1999, 2000, 2001, 2002, & 2005 

SO2 SOx emissions were calculated by using locomotive fuel use and fuel sulfur co

County-level estimates were obtained by scaling the national estimates with thdata from DOT. State data replaced national estimates. (2004) 

1970-1998 VOC, NOx, CO, SOx, 

PM10, PM2.5

Estimated emissions for interim years using linear interpolation between avail

1990, 1996, 1999, & 2002 

HAPs HAP emissions were calculated by applying speciation profiles to VOC and P

estimates were obtained by scaling the national estimates with the county levedata replaced national estimates. (2004) 

 1997-1998 NH3 Grew 1996 base year emissions using EGAS growth indicators. 

 1996 NH3 Applied NH3 emissions factors to diesel consumption estimates for 1996.  1990-1995 NH3 Estimation 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 e

2 National Emission estimates for CMV Coal and CMV Gasoline were not developed though states and local agencies may have subm

source categories. EPA, 1998. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Emission Factors and Inventory GPollutant 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 aircraft types used for public, private, and 

military purposes. This includes four types of aircraft (EPA, 1992): 1) Commercial; 2) Air Taxis; 

3) General Aviation; and 4) Military. 

Commercial aircraft include those used for 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 usually 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 transportation. Aircraft that support business travel, usually on 

an unscheduled basis, are included in the category of general aviation. 

The national AT and GA fleet includes both jet and piston-powered aircraft. Most of the 

AT and GA fleet are made up of piston powered aircraft, 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 activity are powered by piston-powered aircraft and 

34% are jet (or turbine) driven. EPA has used this estimate as a national-scale default value in 

recently published studies investigating lead emissions from aviation sources (EPA, 2008). The 

piston powered aircraft tend to have higher VOC, PM, and CO emissions and lower NOX

emissions than larger jet-powered aircraft (EPA, 1992). Military aircraft 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 includes criteria and Hazardous Air 

Pollutants (HAP) emission estimates for aircraft Auxiliary Power Units (APU) and aircraft 

Ground Support Equipment (GSE) typically found at airports, such as aircraft refueling vehicles, 

baggage handling vehicles, and equipment, aircraft towing vehicles, and passenger buses. 

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

Emissions estimates were developed for all criteria pollutants including volatile organic 

compounds (VOC), nitrogen oxides (NOx), carbon monoxide (CO), sulfur oxides (SOx), 

particulate matter less than 10 microns (PM10), particulate matter less than 2.5 microns (PM2.5) 

and hazardous air pollutants (HAP) (Cook, 1997; Cook, 1998; EPA/FAA, 2009). The HAPs that 

are included in the national aircraft inventory are 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 PM10 Primary 

Acetaldehyde Fluoranthene* PM2.5 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 cruising altitude, lands, taxis to the gate, and idles during passenger 

deplaning. It continues as the aircraft idles during passenger boarding, taxis back out onto the 

runway for subsequent takeoff, and ascent (climbout) to cruising altitude. Thus, the five specific 

operating modes in an LTO are (EPA, 1992): 1) Approach; 2) Taxi/idle-in; 3) Taxi/idle-out; 

4) Takeoff; and 5) Climbout. 

The LTO cycle provides a basis for calculating 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 are 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 preliminary LTO data intended to be will use to 

calculate emissions for review prior to developing the aircraft inventory. State and local agencies 

were encouraged to review the materials posted at ftp://ftp.epa.gov/EmisInventory/2008_nei/ and 

provide comments on any necessary corrections to: 
2-13 

 Airport names and locations for approximately 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 FAA LTO data including default assumptions 

and AircraftEngineCodeTypes for EIS submittals; and 

 Lead estimates and lead estimation methodology. 

This preliminary review by state, local, and tribal groups provided information that EPA used to 

improve EPA’s work. EPA received comments from four states (i.e., Minnesota Pollution 

Control Agency - Environmental Analysis and Outcomes Division; New Jersey Department of 

Environmental Protection; Bureau of Air Management, Connecticut Department of 

Environmental Protection; and Wisconsin Department 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 North Carolina; Ventura County 

California Air Pollution Control District (Specifically related to Oxnard (OXR), Camarillo 

(CMA) and Santa Paula (SZP); and - Regional 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 aviation, and military. HAP emission estimates were 

developed for all aircraft types. 

Emissions for commercial air carriers for which detailed aircraft-specific activity data 

were available, were calculated differently than the other three aircraft categories (See Figure 2-

1). Criteria and HAP emissions were estimated for commercial aircraft by applying aircraft make 

and model (e.g., Boeing 747-200 series) specific 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 revision to EPA’s original aircraft crosswalk table, also known as the 

aircraft engine type code, used to match aircraft to EDMS aircraft and to account for double 

counting between the T-100 data and the TAF data. In the revised crosswalk, aircraft that were 

previously considered general aviation and military based on aircraft model were changed to air 

taxi and commercial air carrier aircraft types based on the definition of air taxis (i.e., any aircraft 

that was not considered an air taxi was classified as an air carrier aircraft). 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 table is provided in an electronic file as supporting data for this 

study. 
2-14 

Emissions were calculated for each airport individually using airport specific mixing 

height. The national-scale default values for taxi in and out are seven and nineteen minutes, 

respectfully. It should be noted that EDMS incorporates the latest aircraft engine emission 

factors from the International Civil Aviation Organization 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 estimated 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 service. 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 duration 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 following variables: fuel, brake horsepower 

and load factor. GSE engines burn gasoline, diesel, compressed natural gas (CNG), and liquefied 

petroleum gas (LPG). EPA has used a national-scale 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 systems 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 the 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 other 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 aviation and air taxi activities are associated 

with piston powered aircraft and the remaining 34 percent of general aviation and air taxi 

activities are associated with jet powered aircraft. The adjusted and split TAF/5010 activity data 

were applied to emission factors as appropriate (See Figure 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 taxis, general aviation, and military aircraft were 

estimated by applying speciation profiles to VOC or PM10 emissions estimates. The following 

equation was used (emission factor are included as Appendix A). 

Eixj = LTOi × FRpro-i × EFij

Where: 

Eixj = Emission estimate for aircraft type i equipped with engine type x 

and pollutant j (lbs/year) 

LTOi = Annual count of LTO cycles for aircraft type i 

FRx = Fraction of LTOs equipped with engine type x 

EFij = Generic emission factor for aircraft type i equipped with engine 

type x and pollutant j (lbs/LTO) 

i = Aircraft type (i.e., air taxi, 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 Emissions 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 Aviation
2-16 

Lead emission estimates were handled differently. Lead emissions are associated with 

leaded aviation fuel used in piston driven aircraft associated with general aviation. Lead 

emissions per LTO are calculated 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 based on national aviation gasoline consumption 

and similar assumptions noted above about lead fuel content and retention rates. Lead emissions 

associated with airport LTO activities were subtracted from the national fuel based lead 

emissions to approximate in flight lead emissions which were allocated to individual counties 

and noted with the code 777. 

For additional details on EPA lead emission 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 calculates organic HAP emissions for aircraft activity reported in 

the T-100 dataset. Representative HAP speciation profiles were used to estimate the individual 

chemical species for each aircraft type included in the TAF/5010 dataset. Profiles are used to 

split (or speciate) organic gases, hydrocarbons, and particulate matter emissions estimates into 

more individual HAP compounds using the following equation: 

Eixj = LTOix × SPixj

Where: 

Eixj = Emission estimate for aircraft type i equipped with engine type x 

and pollutant j (tons/year) 

LTOix = Annual count of LTO cycles for aircraft type i and engine type x 

SPixj = Generic speciation profiles for aircraft type i equipped with engine 

type x and pollutant j (tons/LTO) 

i = Aircraft type (i.e., air taxi, 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 emissions inventory the following corrections to the 

HAP emission estimates were made: 

 Acenpthylene was removed from this inventory for SCC 2275050012. 
2-17 

 To avoid double counting total xylene emissions were removed if speciated xylene 

factors were also available. 

2.5 How Were Emissions Allocated? 

For the 2008 inventory, emissions were individually estimated for each airport. A GIS 

database obtained from the Bureau of Transportation Statistics (BTS) contained airport level data 

with latitude and longitude coordinates. 

2.6 QA/QC 

Given the significant methodological changes over previous inventory efforts, several 

quality checks were implemented to ensure that these data were developed and allocated in a 

clear and reproducible manner. Some of the quality checks implemented include the following: 

Emissions allocations and estimations 

 All original data importations and transcriptions into the database were doublechecked for errors. 

 All calculation methods and approaches were evaluated for technical 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 variety 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 evaluated across activity types (e.g., Aircraft, 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 and revisions were made as needed. 

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

 The validity of Airport and plane identification 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 summarizes the emission estimates for individual HAPs. 

Both tables aggregate the data for all states, including the District of Columbia. Note that the 

2008 estimates do not include state submitted emissions data. 
2-18 

Table 2-4. Aircraft Criteria Emission Estimates 2008 (tons per year) 

Pollutant 

2008 

Military 

(2275001000) 

Commercial 

(2275020000) 

GA, Piston 

(2275050011)

GA, Turbine

(2275050012)

AT, Piston 

(2275060011)

AT, Turbine

(2275060012)

GSE, Gas 

(2265008005)

GSE, LPG 

(2267008005)

GSE, C

(226800

CO 33,161.20 75,463.61 192,510.69 56,532.07 19,116.38 10,180.90 18,005.13 1,768.69 1NOX 284.92 102,561.46 1,041.55 1,911.11 465.64 2,274.10 1,927.90 189.38 PM10-PRI 709.12 1,782.43 3,792.85 1,397.21 242.12 797.03 55.87 5.49 PM2.5-PRI 92.60 1,776.37 493.07 181.64 44.81 103.65 53.63 5.27 SO2 27.32 10,179.67 160.24 434.33 53.76 439.43 53.21 5.23 VOC 1,652.02 13,608.67 2,399.79 3,223.93 310.48 2,610.94 615.80 60.49 

Table 2-5. Aircraft HAP Emission Estimates 2008 (tons per year) 

Pollutant 

2008 

Military 

(2275001000) 

Commercial 

(2275020000) 

GA, Piston 

(2275050011)

GA, Turbine 

(2275050012) 

AT, Piston 

(2275060011) 

AT, Turbine 

(2275060012) 

GSE, Gas 

(2265008005) 

GSE, LPG 

(2267008005)

GSE, 

(22680

1,3-Butadiene 0.87 184.14 29.75 61.04 5.01 44.44 1-Methylnaphthalene 0.13 26.96 8.94 0.23 6.20 2,2,4-Trimethylpentane 0.69 1.09 1.55 0.03 0.51 8.95 0.88 2-methylnaphthalene 0.11 22.48 7.45 0.20 5.17 Acenaphthene 0.36 0.17 Acenaphthylene 2.03 0.93 Acetaldehyde 2.21 466.29 18.82 154.57 11.97 113.00 2.43 0.24 Acrolein 0.02 37.70 1.82 88.61 0.04 32.72 Anthracene 0.42 6.16E-04 0.19 3.52E-04 Benz[a]Anthracene 6.09E-04 0.05 9.33E-05 0.02 5.32E-05 Benzene 0.87 183.48 122.97 60.82 7.58 44.59 10.44 1.03 Benzo[a]Pyrene 4.52E-04 0.05 5.11E-05 0.02 2.91E-05 Benzo[b]Fluoranthene 8.89E-04 0.06 0.03 Benzo[g,h,i,]Perylene 8.11E-06 0.13 8.47E-06 0.06 4.83E-06 Benzo[k]Fluoranthene 8.89E-04 0.06 0.03 Chrysene 6.17E-04 0.05 8.69E-05 0.02 4.96E-05 
2-19 

Table 2-5. Aircraft HAP Emission Estimates 2008 (tons per year) (Continued) 

Pollutant 

2008 

Military 

(2275001000) 

Commercial 

(2275020000) 

GA, Piston 

(2275050011)

GA, Turbine 

(2275050012) 

AT, Piston 

(2275060011) 

AT, Turbine 

(2275060012) 

GSE, Gas 

(2265008005) 

GSE, LPG 

(2267008005)

GSE, 

(22680

Cumene 2.68E-05 0.05 0.11 0.04 Ethyl Benzene 1.55E-03 2.68 44.63 6.30 1.05 2.32 Fluoranthene 1.17E-03 0.45 1.29E-03 0.21 7.35E-04 Fluorene 0.74 0.34 Formaldehyde 6.36 1,343.45 81.67 445.41 38.06 327.87 7.20 0.71 Hexane 21.25 0.50 Indeno[1,2,3-c,d]Pyrene 0.00 0.04 0.02 Lead ** 245.48 8.97 Methane 0.01 18.96 14.79 14.61 1.44 Methanol 0.02 27.78 65.31 24.11 m-Xylene 0.14 26.44 0.36 1.58E-04 0.88 3.66 11.09 1.09 Naphthalene 0.28 54.17 21.11 20.42 5.05 13.86 O-xylene 0.08 15.56 2.03 9.30E-05 1.40 2.19 5.43 0.53 Phenanthrene 0.01 1.25 0.01 0.58 3.27E-03 Phenol 0.01 11.17 26.27 9.70 Propionaldehyde 0.38 79.35 1.82 26.30 2.29 19.45 1.48 0.15 Pyrene 1.42E-03 0.61 1.58E-03 0.28 8.99E-04 Styrene 0.16 33.73 10.32 11.18 1.18 8.25 Toluene 0.33 70.07 315.76 23.23 8.87 16.77 17.77 1.75 Xylenes (Mixed Isomers) 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 lead emitted as

combustion 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 Emission 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 Sources. Ann Arbor, MI. June 9, 1998. 

Cook, Rich. Memorandum entitled Source Identification and Base Year 1990 Emission Inventory 

Guidance for Mobile Source HAPs on the OAQPS List of 40 Priority HAPs, to Laurel Driver and 

Anne Pope, U.S. EPA Office of Air Quality Planning 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 Aircraft, to Laurel Driver and Rich Cook, U.S. 

Environmental Protection Agency. October 25, 2004. 

Federal Aviation Administration. General Aviation and Part 135 Activity Survey - Calendar 

Year 2008. Downloaded from the following Internet site: 

http://www.faa.gov/data_research/aviation_data_statistics/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/headquarters_offices/aep/models/edms_model/. 

U.S. Department of Transportation. Emissions and Dispersion Modeling System, Version 5.1. 

Federal Aviation Administration. September 2008. Downloaded from the following Internet site: 

http://www.faa.gov/about/office_org/headquarters_offices/aep/models/edms_model/. 

U.S. Department of Transportation. Terminal Area Forecast System. Federal Aviation 

Administration, Aviation Policy and Plans. Downloaded from the following Internet Site: 

http//www.apo.data.faa.gov/. 

U.S. Department of Transportation. T-100 Segment (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 Speciated 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 and Air Quality, U.S. Environmental Protection 

Agency in collaboration with the AEE-300 - Emissions 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 Transportation and Air Quality. October 2008. 

U.S. Environmental Protection Agency. Calculating Aviation Gasoline Lead Emissions in the 

Draft 2008 NEI. Assessment and Standards Division, Office of Transportation and Air Quality. 

December 2009. 
2-21 

U.S. Environmental Protection Agency. Procedures for Emission Inventory 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 Profiles 
A-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 

NOx 9.288E-03 

CO 1.119E-02 

SOx 8.910E-04 

PM10 5.385E-04 

PM2.5 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-09 
A-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-06 

 
A-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-05 

 
A-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 

NOx 3.88E-04 

CO 1.81E-03 

SOx 8.12E-05 

PM10 3.017E-04 

PM2.5 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-06 

 
A-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-06 

 
A-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-06 

 
A-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 

NOx 7.900E-05 

CO 1.407E-02 

SOx 7.500E-06 

PM10 3.015E-04 

PM2.5 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-08 

 
A-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 

NOx 1.62E-04 

CO 4.79E-03 

SOx 3.68E-05 

PM10 1.184E-04 

PM2.5 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-06 
A-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-10 
A-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-06 

 
A-11 

General Aviation Emission 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 

NOx 3.250E-05 

CO 6.007E-03 

SOx 5.000E-06 

PM10 1.184E-04 

PM2.5 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-08 

 
A-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 

NOx 7.900E-05 

CO 1.407E-02 

SOx 7.500E-06 

PM10 3.017E-04 

PM2.5 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-06 
A-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-06 
A-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 Airport Inventories for Lead for the 2008 

National Emissions Inventory 
B-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 document 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-engine aircraft activity at airports in the U.S. since the 

activity of this fleet is reported to the Federal Aviation Administration (FAA) as general 

aviation (GA) or air taxi (AT) activity – categories that also include jet-engine aircraft 

activity. The methods described here reflect improvements to the methods used in 

developing the airport-specific piston-engine aircraft inventories 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 operations fall into the categories of either GA or AT. Aircraft used in 

GA and AT activities include a diverse set of aircraft types and engine models and are 

used in a wide variety 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 (TEL). This lead additive helps boost fuel 

octane, prevent engine knock, and prevent valve seat recession and subsequent loss of 

compression for engines without 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 military aircraft, or other turbine-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 2008 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 Quality 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/insidethefence/2006/0609_06_AvFuels.htm 4

 Commercial aircraft include those used for scheduled service transporting passengers, freight, or both. 

Air taxis fly scheduled and for-hire service carrying passengers, freight or both, but they usually are smaller 

aircraft than those operated by commercial air carriers. General aviation includes most other aircraft (fixed 

and rotary wing) used for personal transportation, business, instructional flying, and aerial application. 5

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

http://www.chevronglobalaviation.com/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/roe
B-2 

This document is organized into eight sections. Section 2 describes the data we 

use to calculate the national inventory for the amount of lead released to the air from the 

combustion of leaded avgas. Section 3 describes the landing and takeoff data we use to 

calculate airport-specific inventories 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 methods used to calculate the airport-specific inventories for 

lead. Section 7 describes data that would be needed to improve the estimates of airportspecific inventories for lead and Section 8 describes 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 inventories 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 the environment, we 

include all lead emissions from piston-engine 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 Transportation’s (DOT’s) Federal 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 Information 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 using 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 avgas, minus the small amount of lead that is retained in the 

engine, engine oil and/or exhaust system. The 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 Transportation Federal Aviation Administration Aviation Policy and Plans. FAA 

Aerospace Forecast Fiscal Years 2010-2030. p.99. Available at: 

http://www.faa.gov/data_research/aviation/aerospace_forecasts/2010-

2030/media/2010%20Forecast%20Doc.pdf This document 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 from 0.14 to 1.12 grams of lead per liter) as 

specified by the American Society for Testing and Materials (ASTM). By far the most 

common avgas supplied is “100 Low Lead” or 100LL.10,11 The maximum lead 

concentration specified by ASTM for 100LL is 0.56 grams per 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 volume of avgas produced in the 

U.S. was 5,603 thousand barrels or 235,326,000 gallons.14 Consumption of this volume 

of avgas equates to a national lead emissions estimate for this source of 522 short tons. 

Section 3. Landing and Takeoff Data Sources and Uses

Airport-specific inventories require information 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 Transportation Federal Aviation Administration Aviation Policy and Plans. FAA

Aerospace Forecast Fiscal Years 2010-2030. p.99. Available at: 

http://www.faa.gov/data_research/aviation/aerospace_forecasts/2010-

2030/media/2010%20Forecast%20Doc.pdf This document 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 Statistical Databook & Industry Outlook report by General Aviation

Manufactures Association (GAMA) found that over 90% of avgas is 100LL. 12 ASTM International (2005) Annual Book of ASTM Standards Section 5: Petroleum Products,

Lubricants, and Fossil Fuels Volume 05.01 Petroleum 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.faa.gov/ and (b) E-mail from Theo Rindlisbacher of Switzerland Federal Office of Civil

Aviation to Bryan Manning of U.S. EPA, regarding 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 sources from FAA report aircraft activity in numbers of operations which,

for the purposes of calculating lead emissions using the method described in this 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 only a small fraction of the total airport 

facilities where leaded avgas is used. 

FAA’s Office of Air Traffic provides a complete listing of operational airport 

facilities in the National Airspace System Resources (NASR) database. The electronic 

NASR data report, referred to here as the 5010 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 obtains airport information (including operations) for a 

subset of the facilities in the NASR database 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 airports in FAA’s National Plan of Integrated 

Airport Systems (NPIAS), which 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 control 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 have control towers represent estimates.21 The 

operations supplied in the 5010 airport data report for facilities not reported in the TAF 

may be self-reported by airport operators through data 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 airports have operations data that represent 

data for years earlier than 2008. Nationally, GA and AT piston-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 facilities for which the FAA’s Terminal Area Forecast (TAF) database 

provides information regarding aircraft activity. The TAF database is prepared by FAA’s Office of 

Aviation Policy and Plans and includes information for the airports in FAA’s National 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/airports/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 (Fiscal Years 2009 – 2030), Appendix A (page 28) 

http://www.faa.gov/data_research/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_research/aviation_data_statistics/general_aviation/
B-5 

operations from total GA and AT activity data) by scaling factors that were calculated by 

dividing the 2008 national amount of avgas produced by the national amount of avgas 

produced in the year the operations data represents.25 A table with the scaling factors is 

provided in Appendix A. The national volume of avgas produced data comes from the 

DOE, EIA website and is available 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 1981 – 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 matched 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 activities are included in the data set that would 

double count with the TAF data at the same 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 aircraft 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 subtracted 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 the report there were 19,925 airport facilities 

in the U.S. that had submitted data to the FAA. Among these 19,925 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 January 15, 2009 version of the 5010 

airport data report there 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 of national level pistonengine operations data) are only available annually, starting in 1999. Because there 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 scaling 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 air taxi in nature; however, in discussions with 

FAA, EPA determined that these flights 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 Itinerant, 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 for the draft 2008 NEI, EPA received 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 data 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 models to estimate operations at facilities where 

operations data are not available.31,32 In this work and other work, FAA identified 

characteristics of small towered airports for which there were statistically significant 

relationships with operations 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 number of aircraft based at a 

facility (termed ‘based aircraft’), population in the vicinity of the airport, airport regional 

prominence, per capita income, region, and the presence of certificated flight schools. 

In the 2000 report titled ‘Model for Estimating General Aviation Operations at 

Non-towered Airports,’ a model of GA annual activity was developed using information 

from small towered airports to explain GA activity at towered and non-towered airports. 

The model explained GA activity at the towered airports well (R2

 of 0.75) but produced 

higher estimates than state-supplied 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 Operations at Non-towered Airports Using Towered 

and Non-towered Airport Data. Prepared by GRA, Inc. 32 Mark Hoekstra, “Model for Estimating General Aviation 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) operations in mind, normally 

having a short single runway.
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type (glider, helicopter, jet engine, military, multi-engine, single engine, ultralight); 

operations data (air taxi, commercial, commuter, GA itinerant, 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 airport 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 aircraft activity (LTOs). We found that based 

aircraft was a highly significant 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 aircraft data while 6,316 did not have based aircraft data.37, 38 

Therefore, as described below, LTO estimates were derived using different methods 

depending on data availability. 

Table 1: Contingency table describing the numbers of airport facilities that have or do 

not have LTO data and/or based aircraft data for airport facilities in the January 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 any landing or takeoff event, therefore, to 

calculate LTOs, operations are divided by two. The 5010 airport data report from FAA reports aircraft 

activity in numbers of operations which, for the purposes of calculating 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: airports, balloonports, seaplane bases, 

gliderports, heliports, stolports, and ultralights. 

HAVE

BASED 

AIRCRAFT

DATA
B-8 

(a) Estimating LTOs at Facilities with Based Aircraft Data, but No LTO Data: 

There are 6,414 facilities in the 2008 NEI (not including heliports) for which the 

5010 airport data report supplies the number of based aircraft39 but not activity data to 

which the regression equation (based aircraft vs. LTOs) could be applied. Using the 

4,872 airports for which both LTO and aircraft data is known, the initial relationship 

found between based aircraft and LTOs was: 

Equation 1: 

LTOs = 2494 + 208*aircraft R2 = 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 R2 = 0.56

EPA received numerous comments to the docket on its Advance Notice of 

Proposed Rulemaking on Lead Emissions from Piston-Engine Aircraft Using Leaded 

Aviation Gasoline40 indicating that aviation in Alaska is different 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 transport 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 reasons, we added a dummy variable in equation 

3 to identify whether or not an airport is located in Alaska. Because the relationship 

between based aircraft and LTOs is likely different 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 + 0.0038*county population + 566*Alaska –

108*(AlaskaXaircraft)

R2 = 0.58 

After analyzing the data and plot for the data underlying equation 3, we found 

many airport facilities identified as commercial airports for which based aircraft was 

extremely low (i.e., less than 10), yet LTOs were quite high (i.e., anywhere from 100,000 

39 Based aircraft for this purpose was limited to single- and multi-engine aircraft, helicopters, and 

ultralights since these aircraft types can use leaded avgas. 40 U.S. Environmental Protection Agency (2010) Advance Notice of Proposed Rulemaking on Lead 

Emissions From Piston-Engine Aircraft Using Leaded Aviation Gasoline. 75 FR 22440 (April 28, 2010). 41 Comments to the docket on EPA’s Advance Notice of Proposed Rulemaking on Lead Emissions from 

Piston-Engine Aircraft Using Leaded Aviation Gasoline from the Alaska Air Carriers Association (dated 18 

June 2010; comment number OAR-2007-0294-0323.1) and 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 removed from the regression

analysis. Additionally, for reasons described below, heliports were also removed from

the regression. The resulting relationship was:

Equation 4: 

LTOs = 1293 + 203*aircraft + 0.0019*county population - 473*Alaska –

144*(AlaskaXaircraft) R2 = 0.65 

When equation 4 was applied to the 6,414 airport facilities that report based 

aircraft data but not LTO activity, the resulting sum of LTOs 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 the bottom of the distribution of the set of 

airports that report activity data to the 5010 airport data report but that are not in the TAF 

database. The average number of LTOs per year from airports in the bottom 30% of the 

set of airports that report activity data to the 5010 airport data report but that are not in 

the TAF database is ~63 LTOs/year. Multiplying 63 by the number of airports that do 

not report activity data equals 549,050 LTOs.43 Therefore, EPA used equation 4 to 

generate the distribution of LTOs at the individual airports that report based aircraft data 

but not activity data and then applied a scaling 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 assumed 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 facilities that report based aircraft data but not activity data. 

(b) Estimating LTOs at Facilities with Neither Based-Aircraft Data nor LTO Data: 

There are 2,260 facilities (not including heliports) for which the 5010 airport data 

report supplies neither the number of based aircraft nor activity data. In the absence of 

data to establish a relationship to airport activity, we assign a default value of LTOs to 

the GA, piston-engine category for each of these facilities. 

42 From FAA’s website, “Addresses for Commercial Service Airports”, available at: 

http://www.faa.gov/airports_airtraffic/airports/planning_capacity/passenger_allcargo_stats/addresses/media 

/commercial_service_airports_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 calculated 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 based 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 with 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 that 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 total 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 LTOs to the GA, piston-engine 

category for these airport facilities for purposes 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 those, only 92 (or 2%) reported LTO data, and of those, only 

31 reported both based aircraft and LTO data. Because of the limited information 

regarding activity at heliports, some municipalities 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 summaries of heliport 

activity in the Washington Metropolitan area. The 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 fraction developed in Section 6 is applied to the 

141 LTOs resulting in 51 LTOs assigned to the GA, piston-engine category and 90 

assigned to the GA, turbine-engine category. This 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 Data in the January 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: Regional Helicopter System Plan, Metropolitan Washington Area, prepared by

Edwards and Kelcey for the Metropolitan Washington Council 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 Airport­Specific Lead Emissions

In 2008, EPA developed a method to calculate lead emissions at airports where 

piston-engine powered aircraft operate. 47 This method brings lead inventories into 

alignment with the manner in which other criteria pollutants emitted by aircraft are 

calculated. This method is described here with changes that were made from previous 

methods (i.e., the method used to develop the 2002 inventory) 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 describe each of the 

components of the input data: we describe how we calculate piston-engine LTOs from 

data available in FAA databases, we describe the derivation of the emission factor for the 

amount of lead emitted during the LTO cycle, and we describe the estimate of the amount 

of lead retained in the engine and oil that we do not include in the amount of lead 

released to the air. 

Historically, where aircraft specific activity 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 quality impacts of airport operations and 

proposed airport development projects. However, EDMS has a limited number of pistonengine aircraft in its aircraft data and is currently not set up to calculate metal emissions 

and thus, it is not a readily available tool for determining airport lead inventories related 

to aircraft operations. In developing this approach to determine piston-engine aircraft 

lead emissions, EPA relied upon the basic methodology employed in EDMS. This 

requires as input the activity of piston-engine aircraft at a facility, fuel consumption rates 

by these aircraft during the various modes of the LTO cycle and time in each mode 

(taxi/idle-out, takeoff, climb-out, 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, followed by a description 

of each of the input parameters. 

LTO Pb (tons) = (piston-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 lead that are assigned to 

the airport facility where the aircraft operations occur. An aircraft operation is defined as 

any landing or takeoff event, therefore, to calculate LTOs, operations 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 Gasoline 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_offices/aep/models/edms_model/ 
B-12 

describe here the method used to estimate the fraction of GA and AT LTOs at an airport 

that are conducted by piston-engine aircraft. These fractions are calculated separately 

(one fraction for GA and one for AT). These 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 sources of lead, including airports, that 

have inventories of 0.50 tons per year or more 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 may potentially exceed this inventory threshold, we used a 

more airport-specific surrogate 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 the 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 the fraction of based aircraft we would use 

as a surrogate for piston-engine aircraft is 94% ((150+20)/180). We then multiply the 

total GA LTOs for that facility by 0.94 to calculate piston-engine LTOs. 

We evaluated this surrogate by comparing the results of using it with pistonengine aircraft operations reported for airports that supply this information in master 

plans, airport layout plans, noise abatement studies and/or land use compatibility plans. 

We could rarely find data from the same year for comparison purposes; however, for the 

majority of airports, based aircraft and actual observed piston-engine aircraft activity 

agreed within ten percent.49

For the majority of airports in the 2008 NEI 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 13550 Activity Surveys – CY 2008 (GAATA).51 Table 2.4 in 

the 2008 GAATA Survey reports that approximately sixty-six percent (66%) of all GA 

and AT LTOs are from piston-engine aircraft which use avgas, and about thirty-four 

49 Documents used to evaluate the use of based aircraft include the following:

Airport Master Plan Update Prescott Municipal Airport (Ernest A Love Field) (2009) Available at: 

www.cityofprescott.net/_d/amp_tablecontents.pdf

Gillespie field Airport Layout Plan Update Narrative Report (2005) Available at: www.co.sandiego.ca.us/dpw/airports/powerpoints/pdalp.pdf

Land Use Compatibility Plan for the Grand Forks International Airport (2006) Available at:

www.gfkairport.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 covered 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 information on the 2008 GAATA, see Appendix A at 

http://www.faa.gov/data_research/aviation_data_statistics/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 conducted by piston aircraft and the fraction of 

AT activity conducted by piston aircraft. We chose 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 flown by aircraft type and separates GA from AT. 

Seventy-three percent (73%) of all GA hours flown 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 flown 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 conducted 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 all 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 percent (98%) of all AT rotocraft hours flown 

are by turboprop and turbojet powered rotocraft. Table 3 identifies the piston and turbine 

fractions that were used in the absence of airport-specific information to calculate pistonengine operations at airports and heliports in the 2008 NEI. 

Table 3: Piston and Turbine 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 rounding; the percentages in Table 3 are the values we 

used to calculate the 2008 NEI. 
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(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 avgas used per LTO for some single and twinengine aircraft. The proportion of piston-engine LTOs 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 consumption 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 whole. For the single-engine aircraft, the 

average amount of fuel consumed per LTO was determined from the six types of single 

piston-engine aircraft 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 gallon (lbs/gal), producing an average fuel usage rate for 

single-engine piston aircraft of 2.83 gallons per LTO (gal/LTO). This same calculation 

was performed for the two twin-engine piston aircraft within EDMS, producing an 

average LTO fuel usage rate for twin-engine 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 was 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-engine piston aircraft average fuel usage rate 

(9.12 gal/LTO) was multiplied by the fleet percentage of twin-engine aircraft LTOs 

(10%). By summing the results of the single- and twin-engine aircraft usage rates, the 

overall weighted-average fuel usage rate per LTO of 3.46 gal/LTO was obtained. 

To calculate the emission factor, the concentration of lead in fuel is multiplied by 

the fuel consumption per LTO. The maximum lead concentration specified by ASTM for 

100LL is 0.56 grams per liter or 2.12 grams per gallon. This amount of lead is normally 

added to assure that the required lean and rich mixture knock values are achieved. 

Multiplying this lead concentration in avgas by the weighted average fuel usage rate 

produces an overall average value of 7.34 grams of lead 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-engine fixed wing piston, piston rotocraft, experimental total, and

light sport were summed to determine the total number of single-engine piston aircraft LTOs. 54 EPA understands that EDMS 5.0.2 has a limited list of piston-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.
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(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 from 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 national 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 LTO57 = (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 average 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 provide heliport-specific LTO activity data 

for piston-engine powered helicopters separately from turbine-engine powered 

helicopters. The 2008 FAA GA and Part 135 Activity (GAATA) Survey reports that 

approximately 36% of all GA helicopter hours flown are by piston-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.faa.gov/ and (b) E-mail from Theo Rindlisbacher of Switzerland Federal Office of Civil 

Aviation to Bryan Manning of U.S. EPA, regarding lead retained in engine, September 28, 2007. 57 This equation for piston-engine LTOs only applies to non-heliport facilities. See the text immediately 

below for equations for calculating piston-engine LTOs and Pb emissions at heliports. 58 This was done using the following 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. 
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not contain lead).59 The 2008 FAA GAATA Survey reports that approximately 2% of all 

AT helicopter hours flown are by piston-engine 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 having no pistonengine powered helicopter activity and some hosting mainly or only piston-engine 

powered helicopters. However, in the absence of heliport-specific data, the national 

default estimates of 36% for GA and 2% for AT from the GAATA Survey were used. 

Therefore, to calculate piston-engine aircraft LTO as input for this equation, the 

helicopter GA LTOs were multiplied by 0.36 and helicopter AT LTOs were multiplied by 

0.02. 

Lead emitted at the heliport facility was calculated for the 2008 NEI using either 

the LTO data provided in FAA databases or the estimate LTO activity in the following 

equation (i.e., 141 LTOs): 

Pb(tons) = (piston-engine helicopter 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 Airport­specific 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 some of these key data inputs. 

State and local agencies might have access 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/aviation_data_statistics/general_aviation/
B-17 

1) Airport-specific LTO activity for piston-powered aircraft, including the fraction 

of piston-engine activity conducted by single- versus twin-engine aircraft. Some 

airport facilities collect this information 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 Default - Times in Mode, with a 16 minute taxiin/taxi-out time according to EPA’s Procedures for Emission Inventory 

Preparation, Volume IV: Mobile Sources, 1992. While some local authorities 

have confirmed that these are the relevant times in mode at their 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-up checks conducted by piston-engine 

aircraft prior to takeoff. 

3) Other data inputs for the airport-specific lead inventory calculation for which 

states or local authorities 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 aircraft in specific modes of operation. 

The accuracy of the based aircraft data on which equation 4 is modeled can be 

improved. FAA recognizes the need to improve the integrity 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 altitude, 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 cycle occurs during aircraft 

cruise mode and portions of the climb-out and approach modes above the mixing height 

(typically 3,000 ft62 ). This part of an aircraft operation emits lead at various altitudes as 

well as close to and away from airports. Because the precise area of lead emission and 

deposition is not known for these flights, EPA is using a simplistic approach to allocate 

60 National Based Aircraft Inventory Program: 

http://www.basedaircraft.com/public/FrequentlyAskedQuestions.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.
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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 local 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 pattern or within sight of the 

airport, aircraft executing simulated instrument approaches or low passes at the airport, 

and/or aircraft operating to or from the airport in a designated practice area located 

within a 20-mile radius of the 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 tasks. Emissions during local flying are more 

likely to influence air and soil concentrations of lead in the vicinity of the airport because 

they occur near the airport, often at altitudes below the mixing height. 

Itinerant operations are all operations other than those described above as local 

operations. An itinerant aircraft operation usually is one in which the aircraft departs 

from one airport and lands at a different airport. Depending on air time and distance, an 

itinerant flight is much more likely to involve departing the local flying area of the 

originating airport and climbing to altitudes above the mixing height. It is reasonable 

then, to generally expect that lead emitted outside the LTO cycle during itinerant 

operations, in contrast with local operations, will be more widely 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 though 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 available for AT operations, a portion of which are 

conducted by piston-engine aircraft. Since 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 of national GA and AT pistonengine LTO activity. The state-specific fractions were calculated by multiplying the 

percent of GA and AT piston-engine 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. 
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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) 

AK 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% 8.48 
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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 questions regarding the methods described in 

this document, please contact Meredith Pedde (pedde.meredith@epa.gov) or Marion 

Hoyer (hoyer.marion@epa.gov). 
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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 

198164 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. Product 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 product supplied for years earlier than 1981. To calculate the scaling 

factor to use for activity data from years before 1981, we used the ratio of 2008 avgas volume product supplied to the 

average avgas volume supplied from 1981 to 1989.