S

- 1 

# Development and Evaluation of an Air Quality Modeling Approach for Lead Emissions from

Piston

- e ngine Aircraft Operating on Leaded

Aviation Gasoline

EDWARD CARR *† 

### , MARK LEE ‡ 

### , KRISTEN MARIN ‡ 

### , CHRIS TOPHER HOLDER ‡



### , MARION HOYER § 

### , MEREDITH PEDDE § 

### , RICH COOK §



### , AND JAWAD TOUMA !!

† ICF International, 101 Lucas Valley Road, Suite 260, San Rafael, CA 94903; ‡ ICF International;
§ Environmental Protection Agency Office of Transportation and Air Quality; !! Environmental Protection Agency, Office of Research and Development.



## Supportin g Information

Prepared for Atmospheric Environment

Pages:

Figures: 18

Tables: 9

* Corr esponding author phone (415) 507

- 7186; fax (415) 507

- 7105; e

- mail: ecarr@icfi.com

† ICF International San Rafael, CA
‡ ICF International Durham, NC

§ Office of Transportation and Air Quality, National Vehicle Fuels Emission Laboratory

!! Office of Researc h and Development, Atmospheric Modeling and Analysis DivisionSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

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- 2 

### Aircraft Activity Data (Supports 3.1 Aircraft Emissions)

Two sets of aircraft activity data were needed for this analysis: an annual activity dataset and activity data

for the two periods in which ambient monitoring data were collected). The Airport only maintains records of the number of total operations * , jet operations, and helicopter operations. Piston

- engine aircraft activity

was assumed to be the difference between the total operations less the jet and helicopter operations.

Daily records of one year of aviation activity were provided by Santa Monica Airport’s Operations Manager, Stelios Makrides. At the time of the analysis, only January 2008 through November 2008 was available. When analyzing the three

- month seasonal averages for 2008, the winter season consisted of only January and February since December 2008 data were unavailable.

For the 2009 model

- to

- monitor comparisons, Mr. Makrides provided day

- specific counts for the periods:

March 12 th

– March 17 th , March 26 th

– March 31 st , and July 25 th

– July 31 st , as shown in Table S

- 1 . These observed activity data were used in the model

- to

- monitor comparisons and are typical activity levels, with the exception of July 26, 2009 (see explanation in Table S

- 1).

Supporting T able S

- 1. Daily Aircraft Operations at Santa Monica Airport

DATE Total Operations Jets Helicopter Propeller

3/12/09 251 34 5 212

3/13/09 352 48 8 296

3/14/09 238 22 2 214

3/15/09 319 34 2 283

3/16/09 337 36 6 295

3/17/09 464 48 2 414

3/26/09 295 34 6 255

3/27/09 453 54 18 381

3/28/09 448 30 8 410

3/29/09 347 42 1 304

3/30/09 349 26 8 315

3/31/09 422 36 8 378

7/25/09 238 32 3 203

7/26/09 1 153 50 7 96

7/27/09 216 38 4 174

7/28/09 409 32 6 371

7/29/09 297 44 10 243

* “Operations” are the number of landings plus takeoffs.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- 3 Supporting T able S

- 1. Daily Aircraft Operations at Santa Monica Airport

DATE Total Operations Jets Helicopter Propeller

7/30/09 251 30 20 201

7/31/09 329 50 14 265

1 These anomalously low activity data for a Sunday were cross checked with the FAA’s ATADS Airport Operations database, which reported a total of 288 operations for the same day, of whi ch 7 were helicopters. These values

were used in the monitor

- to

- model comparison assuming the typical jet aircraft fraction determined from other weekend days of 15% or 43 jets, 7 helicopters, and 238 fixed wing aircraft.

For the 2008 annual modeling sc enario, the average daily activity data are summarized by season and weekday/weekend, as shown in Table S

- 2. Propeller operations (i.e., piston

- engine aircraft operations) are lowest in winter and there are only slight differences between weekdays and week ends.

Supporting Table S

- 2. Average Daily Aircraft Counts at Santa Monica Airport for 2008

Season Total

Operations Helicopter

Operations Jet

Operations Propeller

Operations

Weekday

Dec

- Feb 296.59 7.95 46.59 242.05

Mar

- May 364.80 10.41 53.14 301.25

J un

- Aug 373.94 12.72 48.06 313.16

Sep

- Nov 368.52 7.57 44.77 316.18

Weekend

Dec

- Feb 279.32 5.42 34.89 239.00

Mar

- May 355.36 7.46 39.82 308.07

Jun

- Aug 330.39 8.68 34.71 287.00

Sep

- Nov 287.60 7.00 35.93 244.67

Based on interviews with Airport operatio nal personnel, hourly activity levels were not well known. It was determined that this information could best be established by conducting an on

- site survey focusing on activity levels for piston

- engine aircraft. A similar study, but focused on jet aircraf t, had been led a few years earlier at Santa Monica Airport ( SMO ) by Professor Keith Mew, Department of Aviation and Administration, California State University, Los Angeles. Based on experience from his previous study, Dr. Mew led his team of graduate stu dents in conducting a survey of piston

- engine aircraft activity during two weekend periods in March 2009. A sample survey was performed for six days: March 13, 14 and 15, and March 27, 28 and 29 for three periods: morning (8 a.m. and 10 a.m.), midday (10:3 0 a.m. and 1:30 p.m.), and afternoon (2 p.m. and 4 p.m.). These periods were selected based on discussions with SMOSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

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- 4 personnel, who indicated that these times typically covered the most active periods for piston

- engine

aircraft.

The survey collected informa tion on the number of takeoffs and landings as well as the time durations of the activities. For departure, data were collected for the following activities: apron to runway end, engine

run

- up, take

- off roll, and climb

- out. For arrival, data were collected for: approach, landing, and taxi to apron (taxi

- in). In addition, the following aircraft identification data were collected for each aircraft: tail fin number and number of engines (either single or multiple).

The survey’s data on the temporal distributi on based on activity level were the basis for establishing the diurnal activity level for aircraft emissions. However, because the survey did not cover all hours of the day, the diurnal profile estimated by SMO personnel was used to estimate the distributi on for the remainder of the hours. Thus, the intraday activity levels were estimated by a combination of survey data and professional judgment.

Figure S

- 1 shows the piston

- engine activity data collected on each survey day, the estimated distribution

from an interview with SMO staff and the final smoothed distribution used in the analysis (dark black line). This figure shows both a late morning peak and a secondary late afternoon peak in activity. This temporal profile was used in the modeling for the model

- to

- monitor comparison for the July 2009 period and for the annual modeling. For the March model

- to

- monitor comparison, the hourly surveyed data were

used.

Supporting Figure S

- 1 . Hourly activity for piston

- engine aircraft at SM O

.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- 5 

### The following sections support 3.2 Other Emission Sources

On

- road Sources

Gasoline and diesel fuel contain small quantities of naturally occurring Pb (~ 0.00005 g/L in gasoline 1
[EPA 2006]). To accurately include these emissions in the air modeling i mpact assessment, roadways in close proximity to the airport were explicitly modeled. Other on

- road mobile source emissions (e.g., resuspended road dust) were included as general area source emissions. The Pb emissions from gasoline

and diesel vehicles for the three major arterials surrounding the airport that were explicitly included in the analysis are shown in Figure S

- 2 , and are described as follows:

23 rd Street (from Ocean Park Blvd. to Rose St.); Ocean Park Blvd. (from 30 th St. to South Bundy Dr.); a nd Bundy Dr. (from Ocean Park Blvd. to Airport Ave.).

Daily traffic counts with hourly resolution for Ocean Park Blvd. and 23 rd Street were provided by the City

of Santa Monica. The most recent traffic counts for these two roads were made in 2003. We used U.S. census population data 2 from 2000 to 2007 to project traffic changes for 2008 assuming traffic growth increased linearly with population growth. The population in Santa Monica between 2000 and 2007 only increased by 3,000 people, or 3.6%. Traffic dat a for South Bundy came from the 2001

- 2008 Traffic Volume Book, City of Los Angeles 3 as this roadway is just outside the Santa Monica city limits. The most recent traffic counts available for South Bundy Dr. were for National Blvd. at South Bundy and were

c ollected on November 18, 2003. As with the other two roadways, the traffic data were linearly scaled with Santa Monica population † to estimate traffic volumes in 2008. Table S

- 3 provides the statistics on each road, including length, area, traffic count, a nd the year the traffic counts were collected.

The traffic counts did not include estimates on the fleet traffic mix (light duty automobiles, trucks and buses). An estimate of these fractions was obtained as follows. Bus data were retrieved from Santa

Mon ica’s Big Blue Bus system which provides information on the system maps, bus routes and schedules and fleet composition 4 The system

- wide map of bus routes was reviewed and only buses that travel on Ocean Park Blvd., South Bundy Dr., and 23 rd St. were analy zed. Only bus routes 6, 8, and 14 travel on either Ocean Park Blvd., South Bundy Dr. or both. No buses were found to travel on 23 rd St. The bus schedules were reviewed to estimate the number of buses per hour that traveled on each road. Santa

Monica has a large fraction (43%) of buses operating with liquefied petroleum gas (LPG) that do not emit Pb. It was assumed that 43% of the buses traveling along Bundy and Ocean Park were fueled with LPG.

Table S

- 4 lists the total number of daily bus trips operating on Bundy and Ocean Park per weekday and weekend. An additional 5% of the traffic operating on these major arterials was assumed to be diesel

fueled trucks.

† Santa Monica population data was used as the change in traffic along this roadway is more affected by Santa Monica population chang es than the City of Los Angels which encompasses a population spread over an area of 470 square miles.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

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- 6 Source: GoogleEarth. Supporting Figure S

- 2 . Major roadways in close proximity to SMO explicitly modeled in AERMOD.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- 7 Supporting Table S

- 3 . Traffic Counts for the Three Major Roadways near SMO

Street Length of

Road (m) Area of

Road (m 2 ) Daily

Count Year of

Count

23rd St. 1,046 11,842 23,958 2003

Ocean Boulevard 853 17,343 31,295 1998

Bundy D r. 821 16,803 17,700 2003

Supporting Table S

- 4 . Daily Bus Trips on Major Roadways

near SMO

Street Weekday Saturday Sunday

Bundy Dr. 68 46 32

Ocean Park Blvd. 74 39 39

Emission Calculations
Each roadway source’s emissions were determined as follows:



### Where:

Count08 VehType = The 2008 total traffic count for vehicle type, VehType

Veh% VehType = Fraction of vehicle count comprised of vehicle type, VehType

.

Diesel trucks accounted for 5% of vehicles. The percentage of

vehicles tha t were diesel buses depended on the street, and was calculated by dividing the daily total vehicle count (Table S

- 3 ) by the daily total bus count (in Table S

- 4 ) assuming 57% were diesel fueled. The percentage of vehicles that were gasoline fueled

vehicles was determined by (100%

- 5% trucks

- X% buses).

Len = Length of roadway (mile)

EF VehType = Emission factor, in mg Pb per mile of roadway, for vehicle type,

VehType . The hot stabilized summer emission factor of 0.002 mg of Pb/mile was used for gasoline vehicles 1, 5 from dynamometer testing of in

- use, light

- duty vehicles model years 1991

- 1996). The emission factor for diesel fueled truck and bus engines was 0.00724 mg/mile 1

, 6

HrFrac = The fraction of daily traffic activity per hour of the day, averaged

a cross all three roads. These fractions are shown graphically inSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

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- 8

Figure S

- 2 . An average distribution was used to lessen the bias from the single day of sampling.

Area = The area of each roadway (square meters).

Supporting Figure S

- 2 . Hourly distributio n of traffic on three major roadways surrounding SMO

.



### Area Source Emissions

The area source emission inventory for non

- aircraft sources was developed based on the emission inventory previously prepared by SCAQMD and the California Air Resources Board (CA RB) for the Multiple Air Toxics Exposure Study III (MATES

- III) (SCAQMD, 2008). These emissions include all mobile source emissions not discussed in the preceding sections (e .g., brake and tire wear, re

- entrained road dust), and all other types of non

- road sources (e.g., construction dust, locomotives, fuel combustion, cooking). MATES

- III started with a 2002 baseline emissions (as used in the 2007 Air Quality Management Plan [ AQMP]) and was updated to 2005, which was the central year analyzed in MATES

III. Emissions specific to source categories (or Source Classification Codes, SCCs) and to distinct 2x2

- km grids were developed for the following criteria pollutants and for total organic and total suspended particulates pollutant groups speciation were based on the CARB speciation profiles :

Carbon monoxide; Nitrogen oxides; Sulfur oxides; Total organic gases;

Total su spended particulates; Particulate matter, 10 micrometers and smaller (PM 10 ); and Particulate matter, 2.5 micrometers and smaller (PM 2.5 ).

The source categories and source classification codes (SCCs) analyzed were part of three larger groups of

area sources : non

- mobile area sources, on

- road mobile sources (in two groups: heavy

- duty vehicles and light

- and medium

- duty vehicles), and off

- road mobile sources. For each of the non

- mobile categories, a
category

- specific methodology was used by SCAQMD to derive the criteria pollutant emissions. For on

-Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- 9 road mobile sources, emission factors from CARB’s EMFAC2007 (v2.3) were coupled with traffic activity data from the regional transportation modeling performed by the Southern California Association

of Governments (SCAG). The coupling of emission factors (g/mile) and traffic activity data (vehicle miles traveled) was done using the Caltrans Dir ect Travel Impact Model (DTIM) to generate hourly gridded emissions. For off

- road mobile sources, we used CARB’s OFF

- ROAD model , which incorporates regulations, technology types, seasonal cond itions, equipment population, equipment activity, horsepower and load factors, and emissions factors to produce annual emissions. The annual emissions were scaled to seasonal emissions using spatial and temporal features of the various area grids. This ana lysis excluded from the SCAQMD area source inventory the off

- road emissions from aircraft using leaded aviation fuel, as these emissions were already developed as described in the previous sections.

Nine 2x2

- km area source grids from the SCAQMD air emissi on inventory centered approximately on the Santa Monica Airport were used to estimate the area source emissions in the vicinity of Santa Monica Airport. The SCAQMD 2x2 km emission inventory of annual PM 10 emissions was then used for each
source category or source classification code within each grid in combination with speciation profiles to estimate the area source Pb emissions. Speciation profiles were based on several sources as shown in

Table S

- 5

. The paved road dust and engine exhaust, are to a small d egree, a double counting of the on

road emissions as included for 23 rd Street, Ocean Blvd and Bundy, however the emissions here are distributed over an area of 4 square kilometers and the three additional streets explicitly included represent an increase o f less than 0.1 in Pb emissions.

Supporting Table S

- 5 . Pb Emission Factors For Selected Area Sources

Source Type Weight Percent of PM 10 Weight Percent of PM 2.5
Unpaved road dust 1 0.013 0.013

Cooking 1 0.0015 0.0014

Construction dust 1 0.07 0.083

Paved road dust 0.0077 0.0077

Gasoline engine exhaust 3 0.016 0.016

Diesel engine exhaust 3 0.016 0.016

Locomotive 4 0.03 0.03

Commercial Ships 4 0.03 0.03

1 General speciation profiles 7

2 Site

- specific road

- side soil samples measured in July 2009 at the nort hern corner of the airport (Bundy Dr. and Ocean Park Boulevard)

3 Health Effects Institute (HEI) Tunnel Study 8

4 EPA supplied information

SCAQMD also provided cycle codes to partition the annual emissions to either: (1) each month, day of the week, and hour of the day (for non

- mobile and off

- road sources), or (2) each hour of the day (for on

road emissions). The SCAQMD SCC code for the entrained road dust category for paved roadway indicated a flat diurnal profile. This profile was replaced with the diu rnal profile for light

- and medium

duty vehicles as entrained road dust from paved roadways is expected to be closely related to vehicle activity levels.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

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- 10 All area source categories combined accounted for approximately 67 kg/year of Pb across all nine area source grid cells. The total Pb emissions across all area source types (except piston

- fired aircraft) for each Level 1 and Level 2 source classification code are presented in Table S

- 6 . Entrained road dust sources

dominates the collective area source emis sions when piston

- fired aircraft are excluded, with a total of 41 kg/year of Pb spread over the 36 square kilometer area. By comparison, the Santa Monica airport piston

fired aircraft emissions (exclusive of climb

- out and approach) total about 53 kg/year o ver an area of just one square kilometer. The following three groups of categories together account for another 26% of the

total area source Pb emissions:

Dust from construction and demolition activities accounts for about 6.6 kg/year of Pb (about 10%

of t he total area source Pb emissions);

Diesel and gasoline PM from exhaust emissions from on

- road vehicles account for about 5.7 kg/year of Pb (about 9% of the total area source Pb emissions); and

Cooking activities account for about 5.2 kg/year of Pb (abou t 7% of the total area source Pb emissions).

Supporting Table S

- 6 . Total Area Source Pb Emissions, Across All Nine Area Source Grids

Source Classification Code Level 1 Description Source Classification Code Level 2 Description Total Pb

Emissions (kg/year )

Paved Road Travel Entrained Road Dust 38.5

Cooking Commercial Charbroiling 4.22

Construction And

Demolition Building Construction Dust

- Commercial 3.40

Paved Road Travel Diesel PM [tailpipe exhaust emissions] 3.18

Unpaved Road Travel Entrained Road Dust 2.70

Paved Road Travel Gasoline PM [tailpipe exhaust emissions] 2.49

Construction And

Demolition Construction And Mining Equipment 1.93

Construction And

Demolition Building Construction Dust

- Institutional 1.79

Paved Road Travel All Brake Wear 1. 39

Construction And

Demolition Building Construction Dust

- Residential 1.39

Cooking Cooking (Unspecified) 1.02

Paved Road Travel All Tire Wear 9.84E

- 01

Construction And

Demolition Building Construction Dust

- Industrial 5.40E

- 01

Service And Commercial Other 3.02E

- 01

Service And Commercial Transport Refrigeration Units 2.91E

- 01Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- 11 Supporting Table S

- 6 . Total Area Source Pb Emissions, Across All Nine Area Source Grids

Source Classification Code Level 1 Description Source Classification Code Level 2 Description Total Pb

Emissions (kg/year )

Service And Commercial Road Construction Dust 2.85E

- 01

Service And Commercial Production 2.77E

- 01

Mineral Processes Grinding/Crushing 1.91E

- 01

Mineral Processes Fuel Combust ion

- Water Heating 1.82E

- 01

Mineral Processes Fuel Combustion

- Space Heating 1.81E

- 01

Mineral Processes Commercial 9.62E

- 02

Unplanned Fires Automobile Fires 9.53E

- 02

Trains Locomotives 7.30E

- 02

Trains Other 7.08E

- 02

Trains Lawn And Garden (Commerc ial) 6.99E

- 02

Trains Other 6.67E

- 02

Other (Fuel Combustion) I.C. Reciprocating Engines 5.58E

- 02

Other (Fuel Combustion) Lawn And Garden (Residential) 5.08E

- 02

Other (Fuel Combustion) Dust From Unpaved Roads And Associated Areas 4.81E

- 02

Other (Fuel Co mbustion) Structural Fires 4.49E

- 02

Other (Fuel Combustion) Commercial (Residential) 3.73E

- 02

Residential Fuel Combustion Fuel Combustion

- Cooking 3.73E

- 02

Residential Fuel Combustion Lawn And Garden (Other) 3.52E

- 02

Residential Fuel Combustion Manufa cturing 3.12E

- 02

Residential Fuel Combustion Space Heating 3.05E

- 02

Residential Fuel Combustion Water Heating 2.93E

- 02

Residential Fuel Combustion Surface Blasting 2.82E

- 02

Fugitive Windblown Dust Dust From Pasture Lands 2.10E

- 02

Metal Processes Secon dary Production 1.21E

- 02

Manufacturing And

Industrial I.C. Reciprocating Engines 1.21E

- 02

Manufacturing And

Industrial Sand And Gravel Excavation And Processing 8.48E

- 03

Manufacturing And

Industrial Metrolink 5.81E

- 03Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- 12 Supporting Table S

- 6 . Total Area Source Pb Emissions, Across All Nine Area Source Grids

Source Classification Code Level 1 Description Source Classification Code Level 2 Description Total Pb

Emissions (kg/year )

Manufacturing And

Industrial Othe r 5.72E

- 03

Manufacturing And

Industrial Other 4.72E

- 03

Manufacturing And

Industrial Commercial (Other) 4.01E

- 03

Off

- Road Equipment Airport Ground Support Equipment 3.13E

- 03

Fuel Combustion Other 1.83E

- 03

Fuel Combustion Trains 1.26E

- 03

Fuel Combusti on Military Tactical Support Equipment 1.04E

- 03

Fuel Combustion Other 2.53E

- 04

Fuel Combustion Resource Recovery 3.93E

- 05

Fuel Combustion Entertainment 2.81E

- 05



### Point Source Emissions

Point sources of Pb include ‡ sources such as Pb battery recyclers a nd battery manufacturers, Pb smelters, waste incineration, metal industries and glass manufacturers. The SCAQMD maintains an emission inventory based on a permit inventory for point source facilities throughout the district. SCAQMD provided the location, s ource code, operation frequencies, and Pb emissions information for 566 point source facilities within the South Coast Air Basin. These point source locations and emissions are representative of the year 2006, and it was assumed that these data were also r epresentative of 2008. Pb emissions for each facility were provided by SCAQMD at the source category code (SCC) level. Some facilities reported multiple SCCs associated with Pb emissions.

Initially, we proposed modeling all point sources within a 20 km ra dius of SMO. The 86 Pb

- emitting point source facilities within 20 km of the airport emitted a total of 27.5 kg/year of Pb. However, a number of facilities emitting relatively large amounts of Pb were located just outside this radius. These

additional facil ities emitted a total 1,877.8 kg/year of Pb (see Figure S

- 3 ) and were dominated by a single facility (Exide Technologies

– a Pb

- acid battery recycling plant as shown on Figure S

- 3 ) that emitted 1,813.5 kg/year Pb. In order to include these substantial Pb

‡ Many other source types are located at fixed locations, but are not significant enough in terms of emissions that they are listed as point sources.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

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- 13 Supporting Figure S

- 3 . Point source facilities emitting Pb near SMO

. ( Larger circles and warmer
colors reflect greater Pb emissions .)

emissions in the model, all 144 Pb

- emitting point sources within a 25 km radius of the airport were

included in the air quality modeling. The Exide Technologies facility and the seven other facilities that together make up 99.5% of the point

- source Pb emissions within 25 km of the airport are shown in

Table S

- 7

.

Data on physical stack parameters (stack height, diameter , exit gas temperature, and exit gas velocity) are needed to model each Pb emissions point source. While SCAQMD was not able to provide any physical stack parameters as part of their permit inventory, point source facilities can voluntarily report emission s, stack, and process information at the pollutant

- level to the EPA’s National Emissions Inventory (NEI)

. However, some of the facilities provided by SCAQMD could not be found in the NEI. In these cas es, emissions data from SCAQMD were used and physical stack parameters were estimated based on parameters provided in the NEI for similar facilities and processes.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

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- 14 Supporting Table S

- 7 . Facilities that Comprise 99.5% of Point Source Pb Emissions Within 25 km

of SMO

Facility Name Facility City Facility

Average

Latitude (UTM 11N) Facility

Average Longitude (UTM 11N) Lead

Emissions (kg/year) Cumulative

Percentage

Lead

Emissions (lbs/year)

Exide Technologies Los Angeles 3763256 389792 1,813.5 95.2%

Owens

- B rockway Glass

Container Inc Vernon 3761510 388230 27.7 96.6%

Liberty Mfg Inc Los Angeles 3764900 386169 19.1 97.6%

Chevron Products Co. El Segundo 3753601 368842 10.4 98.2%

Glendale City, Glendale

Water & Power Glendale 3780120 382110 10.3 98.7%

Chevro n Products Co. El Segundo 3753601 368842 8.1 99.1%

The Strelitz Co Inc Los Angeles 3761559 382680 3.9 99.4%

U S Radiator Corporation Vernon 3762592 389333 2.8 99.5%

The facilities provided by SCAQMD were manually cross

- referenced to the facilities cont ained in the 2002 EPA National Emissions Inventory (NEI) Version 3. Though the 2005 NEI is the most current NEI available, it wa s in its early stages of development at the time of analysis (early 2009) and evolving quickly. The 2002 NEI was selected because it was likely a more quality

- assured and stable dataset. In order to account for possible geographic coordinate discrepancies between facilities in both the SCAQMD and the NEI, all Pb

- emitting facilities in the 2002 NEI Version 3 that were within 27 km of the airport were manually matched to the facilities provided by SCAQMD that were within 25 km of the airport. The facility mat ching was based on facility coordinates, facility name, and facility address.

Among the 144 SCAQMD Pb

- emitting facilities within 25 km of the airport, 22 facilities were matched to facilities in the NEI. Some of the 117 SCAQMD facilities not matched to th e NEI may actually be in the NEI, but the facility data presented in each database were not consistent enough to make a match

without further information. For each of the 22 Pb

- emitting point source facilities provided by SCAQMD that were manually matched to the Pb

- emitting point source facilities in the NEI, the physical stack parameters of all Pb

- emitting sources at the facility were averaged together. § These facility

- level averaged physical stack parameters were then used in the air quality modeling.

Fo r facilities not matched to the NEI, each SCC associated with Pb emissions at a facility was cross

referenced to the “Stack Parameters SCC” table within the 2002 NEI Version 3 Stack Parameter Default

database . This stack parameter default database provides averages of the physical stack parameters per

SCC based on all data in the 2002 NEI Version 3. This SCC match was succes sful for all but one data

§ The 22 SCAQMD matched facilities were matched to 20 facilities in the NEI: 13 of the NEI facilities had only one

Pb

- emitting stack; 2 had 2 stacks with different stack parameters; 2 had 3 stacks (for one, 2 stacks were the same; for the other, all 3 stack s were the same); 1 had 4 stacks (3 were the same); 1 had 9 stacks (all different); and 1 had 27 stacks (26 were the same).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

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- 15 record (a record at the SCAQMD Facility ID 800016). For this one data record that was not assigned estimated physical stack parameters based on NEI facility data or on NEI SCC data, the record’s source industrial classification (S IC) was cross

- referenced to the “Stack Parameters SIC” table within the stack parameter default database. Appendix B shows the physical stack parameters assigned to each SCC

associated with Pb emissions at each of the 144 Pb

- emitting point source facilitie s within 25 km of the airport.

In addition to Pb emissions, SCAQMD also provided operating schedules for the Pb

- emitting point source facilities. The following operating schedule data were provided for each source location:

Number of operating hours per da y; Number of operating days per week; and Number of operating weeks per year.

All of the facilities were in operation at least 5 days per week and at least 48 weeks per year in 2006, but without more detailed information about which weeks a facility was no n

- operational, it was assumed that every facility was in operation for every week of the year. Also, all facilities operating 5 days per week were assumed to operate Monday through Friday. Since information was available on the number of operating hours pe r day, hourly emissions were developed for three day

- of

- week groups: week day (Monday through Friday), Saturday, and Sunday. For example, if a facility was reported to operate 6 days of the week it was assumed to operate Monday through Saturday (see Append ix B for the hourly and daily operation schedules). For hourly operations, the SCAQMD inventory provided the number of hours per day that the facility operated. It was assumed that this hourly activity was centered on 1300 Local Time (LT), though we perfor med some rounding in order to obtain emission amounts for whole hours

rather than half

- hours. For example, if a facility operated 13 hours of the day, it was assumed to mean the facility operated 0630 LT to 1930 LT. However, in order for emissions data to occupy whole hours, it was first rounded up to the closing time of 2000 LT (i.e., operating through the 1900 LT hour). This rounding forced the opening time to be 0700 LT (2000 LT

- 13 hours). Thus, a facility that operated 13 hours of the day would have e mission estimates for the hours of 0700 LT through 1900 LT.

Ninety facilities were reported to operate 24 hours a day, 7 days a week. Of the 54 facilities that did not operate every hour of every day of the week, 37 operated only during 5 days of the week and 11 operated during 6 days of the week. Independent of the number of operating days per week, 25 facilities operated only 8 hours of the day, 7 operated 10 hours, 5 operated 12 hours, 1 each operated 13 and 14 hours, 8 operated 16 hours, and 3 operated 18 hours.



### The following sections support 3.4 Runway Configuration and Aircraft Wake Turbulence

Fixed

- wing Aircraft

Vertical (sigma z) and horizontal (sigma y) dispersion parameters were developed for moving (dynamic) sources following a mixing zone resid ence time approach

. Sigma y parameters were developed by dividing the source separation distance by a standard deviation of 2.15; this is the standard methodology

used in AERMOD

. For initial sigma z, we used the mixing zone residence as defined in CALINE3 model by the following equation:Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 16 Where:

SZI = initial vertical dispersion (m)

W2 = half width of the runway or taxiway (m)

U = average wind speed (m/s) over the modeling period

This equation accounts for the longer time an a ir parcel spends in the turbulent mixing zone and hence greater initial vertical dispersion

. Initial sigma y and initial sigma z were developed for each mode of aircraft operation as described below:

Taxi

Initial sigma z

Width of taxiway = 80 feet (24.4m ) or W2 = 12.2 m; then apply equation above to estimate initial sigma z using the period average wind speed, U.

Initial sigma y

The horizontal separation distance between source centers is 50 m, thus the initial sigma

- y = 50/2.15 or 23.8 m.

Takeoff/Appro ach/Landing/Climb

- out (all treated the same)

Initial sigma z

Width = 35 feet 9 (average aircraft wingspan) or W2 = 5.34 m, using the equation above using the period average wind speed, U.

Initial sigma y

The horizontal separation distance between source c enters is 50 m, thus the initial sigma

- y = 50/2.15 or 23.8 m.

For the in

- flight segment for fixed

- wing aircraft, an additional consideration was made to account for the wake turbulence created by the forces that lift the aircraft. High pressure air from t he lower surface of the wings flows around the wing tips to the lower pressure region above the wings. A pair of counter

- rotating vortices is shed from the wings where the right and left wing vortices rotate. It is within this region of rotating air behind the aircraft where wake turbulence occurs. To account for this effect, the effective emission height was adjusted for the angle of climb (takeoff) and glide slope angle for landing. This adjustment lowers the effective emission height to approximate the m aximum downward extent of the aircraft’s trailing wake. For SMO, this resulted in an angle of climb out for takeoff of approximately 4.8 degrees, while for landing this was 2.8 degrees.

Run

- up

Initial sigma zSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 17 Initial sigma z (total) is a total combinatio n of:



### Where:

Height above ground = 1.0 m (typical tailpipe height on piston engine aircraft)

Exhaust buoyancy = 0.65 m **
Wind flow over stationary aircraft = Typically two aircraft undergo run

- up testing in staging area (tot al area with safe separation distance 100 feet)

thus W = 30.48 m or W2 = 15.24 m. Then the initial sigma z equation (SZI = (1.8 + 0.11* (W2 / U)) * (60/30) 0.2 ) is used to determine contribution from wind

flow over aircraft.

Then sum these three terms usi ng the period average wind speed, U, to estimate the initial sigma

z

Initial sigma y

Initial sigma

- y is a total combination of:



### Where:

Wingspan wake = typically has two wing spans over run

- up area (100 feet) or W=30.48 m, thu s the initial sigma

- y from wingspan wake =

30.48/2.15 or 14.18 m

Horizontal momentum = 0.6 m ††

Propeller turbulence wake = 0.85 m ‡‡

Total initial sigma

- y during run

- up = (14.18+0.60+ 0.85) m = 15.63 m

Rotorcraft (Helicopters)

For rotorcraft, initial si gma z during idle was based on the typical piston

- engine helicopter source height of 2.0 m divided by 2.15, or 0.93 m. Initial sigma y was based on the typical helicopter rotor width of 10 m divided by 4.13, or 2.33 m. For take

- off and climb

- out, the fligh t pathway was based on what was used

for the fixed

- wing aircraft because Santa Monica’s noise mitigation program asks that helicopters operate in the same flight path as fixed

- wing aircraft. 10 For landing, the rotorcraft are asked to approach from the

north or south, perpendicular to the runway, and then descending in a circular motion through 270 degrees onto the taxiway with a descent rate of 3 m/s starting at about 275 m (900 feet). The wake turbulence also occurs for rotorcraft as high pressure air on th e lower surface of the rotor blades flows around the tips to

** Based on sensitivity test with SCREEN3 with and without exhaust temp of 573K.
†† Based on a sensitivity test with SCREEN3 with an d without typical exhaust flow of 100 ft 3 per minute
‡‡ Base d on a typical 6

- foot propeller size or 1.83 m; thus initial sigma

- y equal s 1.83m/2.15 or 0.85 mSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 18 the lower pressure region above the blades. Consequently, air is forced in a downward trend below the main rotor. This combination of actions results in an angle of descent for rotorcraft of 3.7 degrees.



### Winter Program Monitoring Results

Individual Monitoring Results

Table S

- 8 summarizes the ambient Pb air monitoring data collected during the winter monitoring program at the Santa Monica Airport. The table shows the location of the monitor, the starting date, starting time and duration, day of the week in which the sample was collected, the type of monitor used to collect the data, and a description of any problems or invalid measurements in the “Comments” column).

Supporting Table S

- 8 . Pb Air C oncentrations from Winter Monitoring Program at SMO

Sample

ID Site Start

Date Start

Time Duration (hh:mm) Day of

Week Pb (ng/m 3 ) Type Comments

09

- Q46 E.Tarmac 3/12/2009 12:00 07:45 Thursday 24.6 HiVol

09

- T1041 E.Tarmac 3/12/2009 12:06 07:30 Thu rsday 15.6 MiniVol

09

- T1042 E.Tarmac 3/12/2009 12:08 07:19 Thursday 16.6 MiniVol

09

- T1043 E.Tarmac 3/12/2009 12:05 Unknown Thursday MiniVol Accidentally turned off, not used in analysis

09

- T1045 E.Tarmac 3/12/2009 12:00 07:30 Thursday 13.8 MiniVol

09

- T1060 E.Tarmac 3/12/2009 12:00 07:19 Thursday 11.0 MiniVol

09

- Q47 E.Tarmac 3/13/2009 8:04 24:41 Friday 45.6 HiVol

09

- T1048 W.Tarmac 3/13/2009 8:23 24:53 Friday 10.7 MiniVol

09

- T1052 E.Tarmac 3/13/2009 7:22 24:56 Friday 3 3.6 MiniVol

09

- T1 055 Clarkson 3/13/2009 8:46 24:59 Friday 40 .1 MiniVol

09

- T1058 E.Tarmac 3/13/2009 7:19 15: 41 Friday 48 .2 MiniVol 11 p.m. shutoff

09

- T1059 E.Tarmac 3/13/2009 7:29 25:08 Friday 25 .3 MiniVol

09

- Q48 E.Tarmac 3/14/2009 9:00 23:38 Saturday 5 2.6 HiVol

09

- T1044 E.Tarmac 3/14/2009 8:24 23:53 Saturday 3 5.5 MiniVol

09

- T1046 Clarkson 3/14/2009 9:43 23:53 Saturday 2 8. 9 MiniVol

09

- T1050 W.Tarmac 3/14/2009 9:23 23:40 Saturday 1.8 MiniVol Accidentally turned off, not

used use in the analysis

09

- T1051 E.Ta

rmac 3/14/2009 8:35 14:25 Saturday 53 .1 MiniVol 11 p.m. shutoffSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 19 Supporting Table S

- 8 . Pb Air C oncentrations from Winter Monitoring Program at SMO

Sample

ID Site Start

Date Start

Time Duration (hh:mm) Day of

Week Pb (ng/m 3 ) Type Comments

09

- T1040 E.Tarmac 3/15/2009 9:25 23:52 Sunday 4 5.9 MiniVol Not used in the analysis

– lo

cation of sample

measurement
uncertain

09

- Q49 E.Tarmac 3/15/2009 8:48 23:54 Sunday 7 6. 7 HiVol

09

- T1047 W.Tarmac 3/15/2009 9:09 24:03 Sunday 6 .3 MiniVol

09

- T1049 E.Tarmac 3/15/2009 8:33 14:27 Sunday 98.7 MiniVol 11 p.m. shutoff

09

- T1054 Clarkson 3/15/2009 9:43 23:47 Sunday 50 .1 MiniVol

09

- T1057 Clarkson 3/15/2009 9:32 23:54 Sunday 3 7.5 MiniVol

09

- T1061 W.Tarmac 3/15/2009 8:23 24:07 Sunday <detec

tion

limit MiniVol below minimum

detection limit

– which is 3.2 ng/m 3 at 68%

confidence level

09

- Q51 E.Tarmac 3/27/2009 8:00 25:02 Friday 8 2.8 HiVol

09

- T1062 E.Tarmac 3/27/2009 7:32 25:07 Friday 4 8.6 MiniVol

09

- T1063 E.Tarmac 3/27/2009 7:40 15:20 Friday 8 7.6. MiniVol 11 p.m. shutoff

09

- T1064 E.Tarmac 3/27/2009 7:45 25:10 Friday 7 2.5 MiniVol

09

- T1065 W.Tarmac 3/27/2009 8:22 25:08 Friday 8 .3 MiniVol

09

- T1066 Clarkson 3/27/2009 8:38 25:14 F riday 46 .0 MiniVol

09

- Q52 E.Tarmac 3/28/2009 9:12 23:39 Saturday 39 .3 HiVol

09

- T1067 E.Tarmac 3/28/2009 8:45 23:49 Saturday 29.6 MiniVol

09

- T1068 E.Tarmac 3/28/2009 8:52 14:08 Saturday 46 .0 MiniVol 11 p.m. shutoff

09

- T1069 W.Tarmac 3/28/2009 9:28 23:53 Saturday <detec

tion

limit MiniVol below minimum

detection limit, which is 3.2 ng/

m 3 at 68%

confidence level

09

- T1070 W.Tarmac 3/28/2009 9:35 23:37 Saturday 5 .0 MiniVol

09

- T1071 Clarkson 3/28/2009 9:55 23:46 Saturday MiniVol torn filter

09

- Q 53 E.Tarmac 3/29/2009 9:00 24:44 Sunday 70.6 HiVol

09

- T1072 E.Tarmac 3/29/2009 8:39 24:32 Sunday 59 .3 MiniVolSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 20 Supporting Table S

- 8 . Pb Air C oncentrations from Winter Monitoring Program at SMO

Sample

ID Site Start

Date Start

Time Duration (hh:mm) Day of

Week Pb (ng/m 3 ) Type Comments

09

- T1073 E.Tarmac 3/29/2009 8:47 14:13 Sunday 8 7.6 MiniVol 11 p.m. shutoff

09

- T1074 W.Tarmac 3/29/2009 9:17 23:18 Sunday <detec

tion

limit MiniVol below minimum

detection limit,

which here is 3.2 ng/ m 3 at 68%

confidence level

09

- T1075 Clarkson 3/29/2009 9:38 23:13 Sunday 2 7.6 MiniVol

09

- T1076 Clarkson 3/29/2009 9:38 23:16 Sunday 3 6.5 MiniVol

09

- Q54 E.Tarmac 3/30/2009 9:51 23:25 Monday 4 3.8 HiVol

09

- T1077 E.Tarmac 3/30/2009 9:18 23:34 Monday 3 1.7 MiniVol

09

- T1078 E.Tarmac 3/30/2009 9:27 13:33 Monday 4 4.6 MiniVol 11 p.m. shutoff

09

- T1079 E.Tarmac 3/30/2009 9:31 23:28 Monday 2 5.5 MiniVol

09

- T1080 E.Tarmac 3/30/2009 9:34 23:28 Mo nday 2 5.5 MiniVol

09

- T1081 E.Tarmac 3/30/2009 9:37 23:26 Monday 3 3.8 MiniVol

A total of 43 valid data samples were collected over a total of 8 different days. Most samples were measured using the MiniVols and in most cases were well above the detect ion limit. Only the West Tarmac location was frequently below the detection limit. Valid data from this study were used in the subsequent model

- to

- monitor comparison.



### Summer Program Monitoring Results

Individual Monitoring Results

Table S

- 9 summarizes t he ambient Pb air monitoring data collected during the summer monitoring program at Santa Monica Airport. The table shows the location of the monitor, the starting date, starting time and ending time, day of the week in which the sample was first collected , the type of monitor used to collect the data, and a description of any problems or invalid measurements (in the “Comments” column).

A total of 28 valid data samples were collected over a total of 7 days. All samples were measured using HiVol samplers an d in most cases were well above the detection limit. Only the Maintenance Shed location (which is located in the predominant upwind direction) showed concentrations below the detection limit. The highest monitored concentration was 79 ng/m 3 measured Reside n t 1 on July 26 th

. Valid data from this study were used in the subsequent model

- to

- monitor comparison.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 21 Supporting Table S

- 9 . Pb Air Concentrations from Summer Monitoring Program at SMO

Sample

ID Site Start Date Start

Time Duration (hh:mm) Day of

Week Pb

(ng/m 3 ) Comment

09

- Q539 East Tarmac 7/25/2009 8:16 24:29 Saturday 38 .4

09

- Q540 Maint.Shed 7/25/2009 8:30 24:40 Saturday 1.5 Just above detection limit of 1.4 ng/m 3 at 68% confidence

09

- Q541 Resident 1 7/25/2009 7:55 23:40 Saturday 44 .4

09

- Q542 Re sident 2 7/25/2009 8:02 18:28 Saturday 29.6 Shutoff at 2:30 a.m.

09

- Q543 East Tarmac 7/26/2009 8:53 23:07 Sunday 5 7.7

09

- Q544 Maint. Shed 7/26/2009 9:20 23:00 Sunday 3.6

09

- Q545 Resident 1 7/26/2009 7:40 15:20 Sunday 79 .1 Shutoff at 11 p.m.

09

- Q54 6 Resident 2 7/26/2009 8:27 14:33 Sunday 4 4.7 Shutoff at 11 p.m.

09

- Q547 East Tarmac 7/27/2009 8:06 23:05 Monday 53 .1

09

- Q548 Maint. Shed 7/27/2009 8:30 23:25 Monday 3.5

09

- Q549 Resident 1 7/27/2009 7:22 15:38 Monday 51.9 Shutoff at 11 p.m.

09

- Q550 Resident 2 7/27/2009 7:40 15:20 Monday 32 .4 Shutoff at 11 p.m.

09

- Q551 East Tarmac 7/28/2009 7:20 24:25 Tuesday 62 .2

09

- Q552 Maint. Shed 7/28/2009 8:05 23:20 Tuesday 3.5

09

- Q553 Resident 1 7/28/2009 6:42 16:18 Tuesday 7 5.7 Shutoff at 11 p.m.

09

- Q5 54 Resident 2 7/28/2009 7:00 Unknown Tuesday 50 .4 Unknown sample duration

- power lost

09

- Q555 East Tarmac 7/29/2009 7:52 23:28 Wednesday 55 .1

09

- Q556 Maint. Shed 7/29/2009 7:30 24:10 Wednesday 6 .2

09

- Q557 Resident 1 7/29/2009 6:47 23:57 Wednesday 32 .0

09

- Q558 Resident 2 7/29/2009 7:08 23:53 Wednesday 2 2.5

09

- Q559 East Tarmac 7/30/2009 7:25 23:51 Thursday 3 3.8

09

- Q560 Maint. Shed 7/30/2009 7:46 24:51 Thursday < detec

tion limit below detection limit of 1.4

ng/m 3 at 68% confidence

09

- Q561 R esident 1 7/30/2009 6:50 23:50 Thursday 2 6.9

09

- Q562 Resident 2 7/30/2009 7:06 16:09 Thursday 36 .4 Shutoff at 11 p.m.

09

- Q563 East Tarmac 7/31/2009 7:24 24:55 Friday 45 .3

09

- Q564 Maint. Shed 7/31/2009 7:45 24:18 Friday 3 .3

09

- Q565 Resident 1 7/31 /2009 6:46 24:49 Friday 3 8. 9

09

- Q566 Resident 2 7/31/2009 7:04 16:04 Friday 4 1.9 Shutoff at 11 p.m.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 22 

## Winter 2009 Model

- to

- Monitor Results

Supporting Figure S

- 4

. Clarkson site

– March 14 lead concentration by source.Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 23 Supporting Figure S

- 5

. Eas t Tarmac site

– March 14 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 24 Supporting Figure S

- 6

. Clarkson site

– March 28 lead concentrations by source (ng/m 3 ). Clarkson

- March 28 Lead Concentrations by Source (ng/m3)

0 100 200 300 400 500 600

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8

Time of Day Lead Concentration (ng/m3)

S Runup

Area

S Taxi S

S Takeoff

S Landing

S Climb

S Approach

Point

Offroad

M Approach

M Taxi S

M Taxi N

M Takeoff

M Runup

M Landing

M Climb

Light

Heavy

H Taxi S

H Taxi N

H Lan ding S

H Landing N

H Climb

BackgroundSupporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 25 Supporting Figure S

- 7

. East Tarmac site

– March 28 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 26 Supporting Figure S

- 8

. Clarkson site

– March 29 lead concentrations by source (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 27 Supporting Figure S

- 9

. East Tarmac site

– March 29 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 28 

## Summer 2009 Model

- to

- Monitor Results

Supporting Figure S

- 10

. East tar mac

– July 26, 2009 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 29 Supporting Figure S

- 11

. East tarmac

– July 27, 2009 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 30 Supporting Figure S

- 12

. East tarmac

– July 29, 2009 concentrations by source (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 31 Supporting Figure S

- 13

. Re sident 1

– July 26, 2009 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 32 Supporting Figure S

- 14

. Resident 1

– July 27, 2009 lead concentrations by source (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 33 Supporting Figure S

- 15

. Resident 1

– July 28, 2009 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 34 Supporting Figure S

- 16

. Resident 2

– July 26, 2009 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 35 Supporting Figure S

- 17

. Resident 2

– July 27, 2009 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 36 Supporting Figure S

- 18

. Resident 2

– July 28, 2009 lead concentrations (ng/m 3 ).Supporting Information Development and Evaluation of an Air Quality Modeling Approach f or Lead

Emissions from Piston

- Engine Aircraft Operating on Leaded Aviation Gasoline Carr, Lee, Marin, Holder, Hoyer, Pedde, Cook, And Touma

S

- 37 

### Literature Cited

1 Air Quality Criteria for Lead

- Volume 1 ; EPA/600/R

- 05/144aF ; National Center for Environmental

Assessment

- RTP Division Office of Research and Development, U.S. Environmental Protection Agency : Research Triangle Park, NC, October 2006

. 2 U.S. Census B ureau Population Trends: Santa Monica City, CA; http://factfinder.census.gov/servlet/SAFFPopulation?_eve nt=ChangeGeoContext&geo_id=16000US0670 000&_geoContext=01000US%7C04000US06%7C16000US0670000&_street=&_county=santa+monica %2C+CA&_cityTown=santa+monica%2C+CA&_state=&_zip=&_lang=en&_sse=on&ActiveGeoDiv=g eoSelect&_useEV=&pctxt=fph&pgsl=010&_submenuId=populati on_0&ds_name=null&_ci_nbr=null&q r_name=null®=null%3Anull&_keyword=&_industry =. (accessed March 23, 2008. )

3 2001

- 2008 Traffic Volume Book, Traffic Counts Conducted by City of Los Angeles Department of Transportation Traffic Survey Section
, http://ladot.lacity.org/tf_hist_auto_counts.htm

. 4 Santa Monica Big Blue Bus System, 2009. System map information obtained from http://www.b igbluebus.com/busroutes/index.asp ; information on bus routes and schedules from http://www.bigbluebus.com/busroutes/ ; information on fleet composition from http://www.bigbluebus.com/aboutus/index.asp

. 5 Cadle, S.H.; Mulawa, P.A.; Hunsanger, E.C.; Nelson, K.; Ragazzi, R.A.; Barrett, R.; Gallagher, G.L.; Lawson, D.R.; Knapp, K.T.; Snow, R. Composition of light

- duty motor vehicle exhaust parti culate matter in the Denver, Colorado area. Environ. Sci. Technol. 1999, 33: 2328

- 2339.

6 Lowenthal, D.H.; Zielinska, B.; Chow, J.C.; Watson, J.G.; Gautam, M.; Ferguson, D.H.; Neuroth, G.R.;
Stevens, K.D. Characterization of heavy

- duty diesel vehicle emissi ons. Atmos. Environ. 1994,

28: 731

- 743.

7 California Emission Inventory and Reporting System (CEIDARS), Particulate Matter Speciation Profile

. California Air Resource Board : September 2002

. 8 Characterization of Metals Emitted from Mobile Sources, Researc h Report Number 133

. Health Effects

Institute : March 2006

. 9 Montgomery, M.R., and Foster, G. A Field Guide to Airplanes, 3 rd Edition; Houghton Mifflin Company, NY, NY, 2006.

10 City of Santa Monica

– Requested Flight Paths (d) Helicopter ; http://www01.smgov.net/airport/n_flights.aspx

.