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Chapter 3 Contents

Chapter 3. Ambient Lead: Source to Concentration_____________________________________________________________ 3-1

3.1. Introduction _______________________________________________________________________________ 3-1

3.2. Sources of Atmospheric Lead _________________________________________________________________ 3-1

3.2.1. National Emissions Inventory _________________________________________________________ 3-2

Figure 3-1. Trends in Pb emissions (thousand tons) from stationary and mobile sources 

in the U.S., 1970-2008. ______________________________________________3-3

Figure 3-2. Trends in Pb emissions (thousand tons) from stationary and mobile sources 

in the U.S., 1990-2008. ______________________________________________3-3

Figure 3-3. Nationwide stationary source Pb emissions (tons/yr) in the U.S. by source 

sector in 2008._____________________________________________________3-4

Figure 3-4. County-level Pb emissions (tons) from stationary sources in the U.S. in 

2008. ____________________________________________________________3-5

Figure 3-5. Pb emissions (tons) at airports in the U.S. in 2008. The size of the symbol 

indicates the magnitude of Pb emissions at each airport. ____________________3-6

3.2.2. Anthropogenic Sources ______________________________________________________________ 3-6

3.2.2.1. Lead Emissions from Piston Engine Aircraft Operating on Leaded Aviation Gasoline 

and Other Non-Road Sources__________________________________________________ 3-6

3.2.2.2. Fugitive Emissions from Metals Processing and Mining _____________________________ 3-7

3.2.2.3. Fossil Fuel Combustion ______________________________________________________ 3-8

3.2.2.4. Other Industrial Sources ______________________________________________________ 3-9

3.2.2.5. Roadway-Related Sources ___________________________________________________ 3-10

3.2.2.6. Deposited Lead____________________________________________________________ 3-11

Figure 3-6. Total U.S. Pb additives in on-road gasoline used in on-road vehicles, 1927-

1995. ___________________________________________________________3-13

Figure 3-7. Estimated Pb aerosol inputs from on-road gasoline into 90 U.S. urbanized 

areas (UAs), from 1950 through 1982. _________________________________3-15

3.2.3. Source Attribution _________________________________________________________________ 3-15

3.2.3.1. Lead Speciation and Source Apportionment _____________________________________ 3-15

Table 3-1. Pb compounds observed in the environment _____________________________3-16

3.2.3.2. Lead Isotope Ratio Analysis__________________________________________________ 3-19

3.3. Fate and Transport of Lead __________________________________________________________________ 3-20

Figure 3-8. Fate of atmospheric lead. ___________________________________________3-21

3.3.1. Air _____________________________________________________________________________ 3-21

3.3.1.1. Transport ________________________________________________________________ 3-22

Figure 3-9. Scales of turbulence within an urban environment.________________________3-24

3.3.1.2. Deposition _______________________________________________________________ 3-25

3.3.1.3. Resuspension of Lead from Soil to Air after Lead Deposition________________________ 3-27

3.3.2. Water ___________________________________________________________________________ 3-28

3.3.2.1. Lead Transport in Water and Sediment _________________________________________ 3-29

3.3.2.2. Deposition of Lead within Bodies of Water and in Sediment_________________________ 3-30

Table 3-2. Surface sediment Pb concentrations for various continental shelves; see 

Fang et al. (2009) and references therein. ______________________________3-31

3.3.2.3. Flux of Lead from Sediments _________________________________________________ 3-32

3.3.2.4. Lead in Runoff ____________________________________________________________ 3-33

3.3.3. Soil_____________________________________________________________________________ 3-40

3.3.3.1. Deposition of Lead onto Soil from Air__________________________________________ 3-41

3.3.3.2. Sequestration of Lead from Water to Soil _______________________________________ 3-43

3.3.3.3. Movement of Lead within the Soil Column ______________________________________ 3-45
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Figure 3-10. Schematic model summarizing the estimated flux of Pb within a typical 

podzol profile from northern Sweden using data from Klaminder et al. 

(2006).__________________________________________________________3-47

Figure 3-11. Eh-pH diagram for Pb in shooting range soils, Jefferson National Forest, 

VA. ____________________________________________________________3-51

3.4. Monitoring of Ambient Lead _________________________________________________________________ 3-52

3.4.1. Ambient Measurement Techniques ____________________________________________________ 3-52

3.4.1.1. Size-Selective PM Monitoring for Lead Concentrations ____________________________ 3-52

3.4.1.2. Federal Reference Method and Federal Equivalence Method Evaluation _______________ 3-53

Table 3-3. Specifications for Pb monitoring ______________________________________3-54

3.4.1.3. Chemical Speciation Network, IMPROVE, and National Air Toxics Trends Network 

Monitors_________________________________________________________________ 3-55

3.4.1.4. Other Measurement Methods for Total Lead _____________________________________ 3-56

3.4.1.5. Sequential Extraction _______________________________________________________ 3-57

3.4.1.6. Speciation Techniques ______________________________________________________ 3-58

3.4.1.7. Continuous Lead Monitoring _________________________________________________ 3-60

3.4.2. Ambient Network Design____________________________________________________________ 3-60

3.4.2.1. Monitor Siting Requirements _________________________________________________ 3-62

3.4.2.2. Spatial and Temporal Coverage _______________________________________________ 3-63

Figure 3-12. Pb monitoring sites for SLAMS, CSN, NATTS, and IMPROVE networks, 

2007-2009. ______________________________________________________3-63

3.5. Ambient Air Lead Concentrations _____________________________________________________________ 3-64

3.5.1. Spatial Distribution of Air Lead _______________________________________________________ 3-64

3.5.1.1. Variability across the U.S. ___________________________________________________ 3-64

Table 3-4. Summary data for source oriented Pb monitors across the U.S. ______________3-65

Table 3-5. Summary data for sites at which source oriented statistics are at a maxima _____3-65

Figure 3-13. Highest county-level source oriented Pb-TSP concentrations (μg/m3), 

maximum 3-month average, 2007-2009. ________________________________3-66

Figure 3-14. Highest county-level Pb-PM10 concentrations (μg/m3), maximum 3-month 

average, 2007-2009. _______________________________________________3-67

Figure 3-15. Highest county-level Pb-PM2.5 concentrations (μg/m3), maximum 3-month 

average, 2007-2009. _______________________________________________3-68

3.5.1.2. Intra-urban Variability ______________________________________________________ 3-68

3.5.2. Temporal Variability _______________________________________________________________ 3-70

3.5.2.1. Multi-year Trends__________________________________________________________ 3-70

Figure 3-16. National trends in Pb concentration (μg/m3), all FRM monitors, 1980-2009. ____3-71

Figure 3-17. National trends in Pb concentration (μg/m3), source oriented FRM 

monitors, 1990-2009. ______________________________________________3-72

Figure 3-18. National trends in Pb concentration (μg/m3), non-source oriented FRM 

monitors, 1990-2009. ______________________________________________3-72

3.5.2.2. Seasonal Variations ________________________________________________________ 3-73

Figure 3-19. Monthly source oriented Pb-TSP average (μg/m3) over 12 months of the 

year, 2007-2009. __________________________________________________3-74

Figure 3-20. Monthly non-source oriented lead-TSP average (μg/m3) over 12 months of 

the year, 2007-2009. _______________________________________________3-75

Figure 3-21. Monthly lead-PM10 average (μg/m3) over 12 months of the year, 2007-2009. ____3-75

Figure 3-22. Monthly lead-PM2.5 average (μg/m3) over 12 months of the year, 2007-2009.____3-76

3.5.3. Size Distribution of Lead-Bearing PM__________________________________________________ 3-77

3.5.3.1. AQS Data Analysis ________________________________________________________ 3-77

Table 3-6. Summary of comparison data for co-located lead-TSP and lead-PM10

monitors. ________________________________________________________3-77

Table 3-7. Summary of comparison data for co-located Pb-TSP and Pb-PM2.5 monitors____3-78

Table 3-8. Summary of comparison data for co-located Pb-PM10 and Pb-PM2.5

monitors. ________________________________________________________3-78

3.5.3.2. Size Distribution Studies in the Literature _______________________________________ 3-79
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Figure 3-23. Comparison of urban background and near-road size fractions of leadbearing PM. _____________________________________________________3-81

3.5.4. Lead Concentrations in a Multipollutant Context__________________________________________ 3-82

Figure 3-24. Correlations of monitored Pb-TSP concentration with copollutant 

concentrations, 2007-2008.__________________________________________3-83

Figure 3-25. Correlations of monitored Pb-TSP concentration with co-pollutant 

concentrations, 2009. ______________________________________________3-84

Figure 3-26. Correlations of monitored lead-PM2.5 concentration with copollutant 

concentrations, 2007-2009.__________________________________________3-86

3.6. Ambient Lead Concentrations in Non-Air Media and Biota _________________________________________ 3-87

3.6.1. Soils ____________________________________________________________________________ 3-88

Table 3-9. Outdoor soil Pb levels in various cities within the U.S._____________________3-88

Figure 3-27. Map of median Pb content in soil in New Orleans. ________________________3-90

3.6.2. Sediments________________________________________________________________________ 3-92

Table 3-10. Sediment concentrations in various cities, prior to 2005____________________3-93

Figure 3-28. Sediment core data (1992-1994) for the lakes and reservoirs along the 

Apalachicola, Chattahoochee, and Flint River Basin (ACF), which feeds 

from north of the Atlanta, GA metropolitan area into the Gulf of Mexico at 

Apalachicola Bay in the Florida panhandle._____________________________3-94

Figure 3-29. Sediment core data (1975-1995) for the lakes and reservoirs along the 

Apalachicola, Chattahoochee, and Flint River Basin (ACF), which feeds 

from north of the Atlanta, GA metropolitan area into the Gulf of Mexico at 

Apalachicola Bay in the Florida panhandle._____________________________3-95

3.6.3. Rain ____________________________________________________________________________ 3-96

Figure 3-30. Trends in Pb concentration in precipitation from various sites in Norway 

over the period 1980-2005. __________________________________________3-97

3.6.4. Snowpack________________________________________________________________________ 3-97

3.6.5. Natural Waters ____________________________________________________________________ 3-99

3.6.6. Moss___________________________________________________________________________ 3-100

3.6.7. Grass, Foliage, and Tree Rings_______________________________________________________ 3-100

Figure 3-31. Trends in regional pollution near a copper smelter in Canada and Pb 

concentrations at the boundary of heartwood trees within roughly 75 km of 

the smelter. _____________________________________________________3-101

3.6.8. Aquatic Bivalves _________________________________________________________________ 3-101

3.7. Summary _______________________________________________________________________________ 3-102

3.7.1. Sources of Atmospheric Lead _______________________________________________________ 3-102

3.7.2. Fate and Transport of Lead _________________________________________________________ 3-102

3.7.3. Ambient Lead Monitoring __________________________________________________________ 3-104

3.7.4. Ambient Air Lead Concentrations ____________________________________________________ 3-104

3.7.5. Ambient Lead Concentrations in Non-Air Media and Biota ________________________________ 3-105

Chapter 3 References ____________________________________________________________________________ 3-107

Chapter 3 Appendix________________________________________________________________________________ 3-129

3.8. Variability across the U.S. __________________________________________________________________ 3-129

Table 3A-1. Distribution of 1-month average Pb-TSP concentrations (μg/m3) nationwide, 

source-oriented monitors, 2007-9. ___________________________________3-129

Table 3A-2. Distribution of 3-month moving average Pb-TSP concentrations (μg/m3) 

nationwide, source-oriented monitors, 2007-9. Sites listed in the bottom six 

rows of the table fall in the upper 90th percentile of the data pooled by site. ___3-130

Table 3A-3. Distribution of annual 1-month site maxima TSP Pb concentrations (μg/m3) 

nationwide, source-oriented monitors, 2007-2009. _______________________3-131

Table 3A-4. Distribution of annual 3-month site maxima Pb-TSP concentrations (μg/m3) 

nationwide, source-oriented monitors, 2007-2009. _______________________3-131

Table 3A-5. One-month average Pb-TSP for individual county concentrations 

nationwide (μg/m3

), non-source-oriented monitors, 2007-2009 _____________3-132
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Table 3A-6. Three-month moving average Pb-TSP for individual county concentrations 

(μg/m3

) nationwide, non-source-oriented monitors, 2007-2009 _____________3-133

3.8.1. Intra-urban Variability _____________________________________________________________ 3-133

Figure 3A-1. Pb TSP monitor and source locations within Los Angeles County, CA (06-

037), 2007-2009. _________________________________________________3-137

Figure 3A-2. Wind roses for Los Angeles County, CA, from meteorological data at the 

Los Angeles International Airport, 1961-1990.__________________________3-138

Figure 3A-3. Box plots of annual and seasonal Pb TSP concentrations (μg/m3) from 

source-oriented and non-source-oriented monitors within Los Angeles 

County, CA (06-037), 2007-2009. ____________________________________3-139

Table 3A-7. Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Los Angeles County, CA (06-037), 2007-

2009 __________________________________________________________3-140

Figure 3A-4. Pb TSP monitor locations within Hillsborough and Pinellas Counties, FL 

(12-057 and 12-103), 2007-2009. ____________________________________3-142

Figure 3A-5. Wind roses for Hillsborough/Pinellas Counties, FL, obtained from 

meteorological data at Tampa International Airport, 1961-1990.____________3-143

Figure 3A-6. Box plots of annual and seasonal Pb TSP concentrations (μg/m3) from 

source-oriented and non-source-oriented monitors within Hillsborough and 

Pinellas Counties, FL (12-057 and 12-103), 2007-2009. __________________3-144

Table 3A-8. Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Hillsborough and Pinellas Counties, FL 

(12-057 and 12-103), 2007-2009. ____________________________________3-145

Figure 3A-7. Pb TSP Monitor locations within Cook County, IL (17-031), 2007-2009.______3-148

Figure 3A-8. Wind roses for Cook County, IL, obtained from meteorological data at 

O’Hare International Airport, 1961-1990. _____________________________3-149

Figure 3A-9. Box plots of annual and seasonal Pb TSP concentrations (μg/m3) from 

source-oriented and non-source-oriented monitors within Cook County, IL 

(17-031), 2007-2009.______________________________________________3-150

Table 3A-9. Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Cook County, IL (17-031), 2007-2009. ______3-151

Figure 3A-10. Pb TSP Monitor locations within Jefferson County, MO (29-099), 2007-

2009. __________________________________________________________3-153

Figure 3A-11. Wind roses for Jefferson County, MO, obtained from meteorological 

data at St. Louis/Lambert International Airport, 1961-1990. _______________3-154

Figure 3A-12. Box plots of annual and seasonal Pb TSP concentrations (μg/m3) from 

source-oriented and non-source-oriented monitors within Jefferson County, 

MO (29-099), 2007-2009. __________________________________________3-155

Table 3A-10. Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Jefferson County, MO (29-099), 2007-2009 __3-156

Figure 3A-13. Pb TSP Monitor locations within Cuyahoga County, OH (39-035), 

2007-2009. _____________________________________________________3-158

Figure 3A-14. Wind roses for Cuyahoga County, OH, obtained from meteorological 

data at Cleveland/Hopkins International Airport, 1961-90. ________________3-159

Figure 3A-15. Box plots of annual and seasonal Pb TSP concentrations (μg/m3) from 

source-oriented and non-source-oriented monitors within Cuyahoga 

County, OH (39-035), 2007-2009.____________________________________3-160

Table 3A-11. Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Cuyahoga County, OH (39-035), 2007-

2009 __________________________________________________________3-161

Figure 3A-16. Pb TSP Monitor locations within Sullivan County, TN (47-163), 2007-

2009. __________________________________________________________3-163

Figure 3A-17. Wind roses for Sullivan County, TN, obtained from meteorological data 

at Bristol/Tri City Airport, 1961-90. __________________________________3-164

Figure 3A-18. Box plots of annual and seasonal Pb TSP concentrations (μg/m3) from 

source-oriented and non-source-oriented monitors within Sullivan County, 

TN (47-163), 2007-2009.___________________________________________3-165

Table 3A-12. Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Sullivan County, TN (47-163), 2007-2009 ____3-166
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3.8.2. Size Distribution of Pb-Bearing PM___________________________________________________ 3-166

Table 3A-13. Correlations and average of the concentration ratios for co-located 

monitors, TSP versus PM10, TSP versus PM2.5, and PM10 versus PM2.5. _______3-166

3.8.3. Lead Concentration in a Multipollutant Context _________________________________________ 3-169

Figure 3A-19a. Seasonal correlations of monitored Pb-TSP concentration with 

copollutant concentrations, 2007-2008. Top: winter; bottom: spring. ________3-169

Figure 3A-19b. Seasonal correlations of monitored Pb-TSP concentration with 

copollutant concentrations, 2007-2008. Top: summer; bottom: fall.__________3-170

Figure 3A-20a. Seasonal correlations of monitored Pb-TSPconcentration with 

copollutant concentrations, 2009. Top: winter; bottom: spring. _____________3-171

Figure 3A-20b. Seasonal correlations of monitored Pb-TSPconcentration with 

copollutant concentrations, 2009. Top: summer; bottom: fall. ______________3-172

Figure 3A-21a. Seasonal correlations of monitored Pb-PM2.5 concentration with 

copollutant concentrations, 2007-2009. Left: winter; right: spring. __________3-173

Figure 3A-21b. Seasonal correlations of monitored Pb-PM2.5 concentration with 

copollutant concentrations, 2007-2009. Left: summer; right: fall. ___________3-174

Table 3A-14. Copollutant exposures for various trace metal studies ____________________3-175
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Chapter 3. Ambient Lead: Source to 

Concentration

3.1. Introduction

1 This chapter reviews concepts and findings in atmospheric sciences that provide a foundation for 

2 the detailed presentation of evidence of Pb exposure and Pb-related health and ecological effects in 

3 subsequent chapters. Information in this chapter builds on previous Pb AQCDs using new data and 

4 studies. This includes new knowledge of Pb fate and transport, the latest developments in monitoring 

5 methodologies, and recent data describing Pb concentrations as a function of size range. Description of 

6 the chemical forms of Pb is not provided here, however, because this information is well established. The 

7 reader is referred to the 2006 Pb AQCD for a description of the chemical forms of Pb (U.S. EPA, 2006).

8 Section 3.2 provides an overview of the primary and secondary sources of air Pb. Section 3.3 

9 provides a description of the fate and transport of Pb in air, soil, and aqueous media. Descriptions of Pb 

10 measurement methods, monitor siting requirements, and monitor locations are presented in Section 3.4. 

11 Ambient Pb concentrations, their spatial and temporal variability, size distributions of Pb-bearing 

12 particulate matter (PM), and associations with copollutants are characterized in Section 3.5. 

13 Concentrations of Pb in non-air media and biota are described in Section 3.6.

3.2. Sources of Atmospheric Lead

14 The following section reviews updated National Emissions Inventory (NEI) data from 2008 (U.S. 

15 EPA, 2011), which is the most recently available quality-assured Pb emissions data. This section also 

16 reviews updated information from the peer-reviewed literature regarding sources of ambient Pb. Detailed 

17 information about processes for primary and secondary anthropogenic emissions and naturally-occurring 

18 emissions can be found in the 2006 Pb AQCD (U.S. EPA, 2006). The papers cited herein generally 

19 utilized PM sampling data, because ambient airborne Pb readily condenses to PM. The 2006 Pb AQCD 

20 (U.S. EPA, 2006) employed the 2002 NEI (U.S. EPA, 2008a) or source analysis and listed the largest 

21 sources to be (in order): industrial-commercial-institutional boilers and process heaters (17%), coal 

22 utilities boilers (12%), mobile sources (10%), iron and steel foundries (8%), and miscellaneous sources 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database (Health and Environmental 

Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used by U.S. EPA in the process of developing science 

assessments such as the Integrated Science Assessments (ISA) and the Integrated Risk Information System (IRIS).
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1 from industrial processes, incineration, and utilities, each contributing less than 5% (53%). Since that 

2 time, states have additional information to the inventory. The mobile source category included 

3 combustion products from organic Pb antiknock additives used in piston-engine aircraft (hereafter 

4 referred to piston aircraft emissions).

3.2.1. National Emissions Inventory

5 Emissions of Pb have dropped substantially over the past forty years, as shown in Figure 3-1 and 

6 Figure 3-2. The reduction before 1990 is largely due to the phase-out of Pb as an anti-knock agent in 

7 gasoline for on-road automobiles, as discussed in the 2006 Pb AQCD (U.S. EPA, 2006). This action 

8 resulted in a 98% reduction in Pb emissions from 1970-1990. Total Pb emissions over the period 1990-

9 2008 decreased an additional 77%, from 5,200 tons in 1990 to 1,200 tons in 2008. Subsequent emissions 

10 reductions are related to enhanced control of the metals processing industry. In 1990, metals processing 

11 accounted for 42% (2,200 tons) of total Pb emissions. By 2008, metals processing accounted for 12% 

12 (150 tons) of total emissions. This represented more than an order of magnitude decrease in Pb emissions 

13 from metals processing. At the same time, emissions from piston engine aircraft varied only slightly over 

14 this time period. In 1990, off-highway Pb emissions were 990 tons and represented 19% of total Pb 

15 emissions. In 2008, off-highway Pb emissions from piston engine aircraft were slightly lower at 590 tons, 

16 which comprised 49% of all Pb emissions. “Miscellaneous” emissions from other industrial processes, 

17 solvent utilization, agriculture, and construction comprised 20% of emissions (240 tons) in 2008. 
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Source: U. S. EPA (2011)

Figure 3-1. Trends in Pb emissions (thousand tons) from stationary and 

mobile sources in the U.S., 1970-2008.

Source: U. S. EPA (2011)

Figure 3-2. Trends in Pb emissions (thousand tons) from stationary and 

mobile sources in the U.S., 1990-2008. 
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1 Direct emissions of Pb into the atmosphere primarily come from piston engine aircraft, fuel 

2 combustion, and industrial activities. Direct Pb point source emissions estimated by the 2008 NEI are 

3 shown in Figure 3-3. Emissions from piston engine aircraft emissions comprised nearly half of all 

4 emissions (590 tons). Industrial fuel combustion contributed 220 tons (18%) of Pb emissions in 2008, 

5 followed by metal working and mining (12%), other industry (9%), dusts from construction (7%) and 

6 miscellaneous contributions from agriculture, solvent utilization, and operation of commercial marine 

7 vessels and locomotives (4%) (U.S. EPA, 2011). Pb emissions from the “metal working and mining”

8 category include the single primary Pb smelter in the U.S., the Doe Run facility in Herculaneum, MO; 

9 secondary Pb smelters, mostly designed to reclaim Pb for use in Pb-acid batteries; and smelters for other 

10 metals. 

Source: U. S. EPA (2011)

Figure 3-3. Nationwide stationary source Pb emissions (tons/yr) in the 

U.S. by source sector in 2008. 

11 There is substantial variability in Pb emissions from stationary sources across U.S. counties, as 

12 shown in Figure 3-4 for the continental U.S. The emissions levels, shown in units of tons, vary over 

13 several orders of magnitude. Ninety-four percent of U.S. counties had 2008 emissions below 1 ton, and 

14 50% of counties had 2008 emissions below 0.044 tons. The upper 0.1% of stationary emissions came 

15 from thirty-three counties. This category included all counties emitting more than 3.8 tons of Pb in 2008.

16 Jefferson County, MO was the highest emitting county, with over 21 tons of airborne Pb emissions in 
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1 2008. Jefferson County is home to the Doe Run primary Pb smelting facility, which is the only remaining 

2 operational primary Pb smelter in the U.S. 

Source: U.S. EPA (2011)

Figure 3-4. County-level Pb emissions (tons) from stationary sources in 

the U.S. in 2008. 

3 Pb emissions from piston engine aircraft operating on leaded fuel occur at approximately 20,000 

4 airports across the U.S. Figure 3-5 displays Pb emissions (tons) at airports around the continental U.S. 

5 The map illustrates that airport emissions tend to be elevated around highly populated metropolitan 

6 regions, which typically have multiple airports with varying activity levels. Clusters of airports around 

7 metropolitan areas and megapolitan regions (multiple contiguous metropolitan areas) are notable from 

8 Figure 3-5. Among these sites, piston aircraft emissions at airports within twenty-eight counties 

9 cumulatively emitted greater than one ton of Pb in 2008 U.S. EPA (2011). Additionally, within the 2008 

10 NEI, there were estimates of Pb emissions during flight from piston aircraft. These estimates are provided 

11 by state and cumulatively account for 296 tons in 2008. 
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Source: U.S. EPA (2011)

Figure 3-5. Pb emissions (tons) at airports in the U.S. in 2008. The size of 

the symbol indicates the magnitude of Pb emissions at each 

airport. 

3.2.2. Anthropogenic Sources

1 Anthropogenic Pb source categories are organized below in order of magnitude reported on the 

2 2008 NEI (U.S. EPA, 2011), with emissions from piston engine aircraft being the highest and resuspended 

3 dust from previously deposited Pb being substantially lower. 

3.2.2.1. Lead Emissions from Piston Engine Aircraft Operating on Leaded 

Aviation Gasoline and Other Non-Road Sources

4 The largest source of Pb in the NEI is from piston engine aircraft operating on leaded aviation 

5 gasoline emissions (U.S. EPA, 2011). Murphy et al. (2007) cited fuel consumption estimates provided by 

6 the U.S. Department of Energy indicating that 575,000 kg/yr of Pb is used in piston engine aircraft fuel, 

7 and based on the 1999 NEI, that 490,000 kg/yr (85%) become airborne upon combustion. Levin et al. 

8 (2008) point out that emissions from piston engine aircraft are exempt from reporting to the EPA Toxic 
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1 Release Inventory. Levin et al. (2008) summarized findings from environmental protection departments of 

2 the State of Illinois, the U.S., and Canada regarding ambient Pb concentrations at and near airports. The 

Canadian report noted average and maximum air Pb levels were 0.030 and 0.30 μg/m3 3 , respectively, 

compared with background levels of 0.007 and 0.018 μg/m3 4 (Conor Pacific Environmental Technologies 

5 Inc, 2000). The Illinois report noted that air Pb concentrations were elevated downwind of O’Hare airport 

6 compared with upwind levels (Illinois Environmental Protection Agency, 2002). Pb emission rates from 

7 piston aircraft vary with fuel consumption rates, which depend on the engine/airframe combination and 

8 the mode of operation of the aircraft. Fuel consumption rates can be obtained for some engine/aircraft 

9 combinations by running FAA’s Emissions and Dispersion Modeling System (FAA, 2011). The ASTM 

10 specification for the maximum Pb content is “100 Low Lead”, the most commonly used leaded avgas, is 

11 2.12 g of elemental Pb/gallon (ASTM, 2007).

12 Dynamometer testing has indicated that Pb emissions from piston engine aircraft fuel combustion 

13 can occur in the particulate and gaseous form. For example, Gidney et al. (2010) performed dynamometer 

14 testing on automobiles operating on standard gasoline and on gasoline with low levels of organometallic 

15 additives. Tetraethyl Pb was included since it is still used in avgas. The additives had trace levels of Pb 

16 that exist in gas phase when temperatures are higher than 650 C, below which they condense to 

17 particulate phase. Gidney et al. (2010) point out that, where tetraethyl Pb is used as an additive in piston 

18 engine aircraft fuel, the fuel also contains ethylene dibromide to act as a Pb “scavenging agent.” When 

19 ethylene dibromide reacts with Pb, it forms Pb bromide and Pb oxybromides, which are more volatile.

3.2.2.2. Fugitive Emissions from Metals Processing and Mining

20 Fugitive emissions from secondary Pb processing can be substantial over the course of a year, but 

21 they are difficult to estimate. Goyal et al. (2005) estimated fugitive emissions using concentration data 

22 obtained from samplers sited in close vicinity of secondary Pb recovery facilities and meteorological data 

23 from nearby weather monitoring stations. Regression modeling and Bayesian hierarchical modeling were 

24 both used to estimate fugitive and stack emissions from facilities in Florida, Texas, and New York. 

Depending on the model used, median fugitive emissions were estimated to be 1.0 × 10-6 to 4.4 × 10-5 25 g 

Pb/m2·sec at the Florida site, 9.4 × 10-7 to 2.0 × 10-6 g/m2·sec for the Texas site, and 8.8 x 10-7 to 1.1 × 10- 26

6 g/m2 27 ·sec at the New York site. Median stack emissions estimates varied widely among the models, with 

the Florida site median ranging from 1.4 × 10-6 to 1.4 × 10-1 28 g Pb/sec, the Texas site median ranging from 

8.4 × 10-2 to 8.6 × 10-2 g/sec, and the New York site ranging from 8.4 × 10-3 to 1.0 × 10-2 29 g/sec. 

30 Additionally, the Bayesian hierarchical model was used to estimate fugitive Pb emissions nationwide 

31 using concentration data as prior information. Nationwide median fugitive emissions were estimated to be 

9.4 × 10-7 to 3.3 × 10-6 g/m2 32 ·sec.
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1 Waste from current or defunct mines has been shown to present an additional fugitive source of Pb. 

2 For example, Zheng et al. (2009) applied source apportionment in three northeastern Oklahoma towns to 

3 identify the influence of “chat”, or waste piles from formerly operational Pb-Zn mines, on PM10-2.5 and 

4 PM2.5. They estimated that mine waste was responsible for 88% of Pb in PM10-2.5 samples and 40% of Pb 

5 in PM2.5 samples.

3.2.2.3. Fossil Fuel Combustion

6 Fossil fuel combustion accounts for roughly 12% of Pb emissions in the U.S. Murphy et al. (2007)

7 presented an estimated U.S. mass budget for Pb emitted from consumption of select fuels and crude oil. 

8 Fuel consumption estimates for 2005 were employed (Freme, 2004). Based on an annual consumption of 

1.0 × 109 9 tons coal with an average Pb concentration of 20 mg/kg (range: 5 to 35 mg/kg) and using an 

10 emission factor (airborne fraction) of approximately 0.01, coal contributed approximately 200 tons Pb/yr

11 to the atmosphere. There were no emission factors for crude oil or residual oil but these represent 

12 potentially large sources (up to 100-500 tons/yr and up to 25-700 tons/yr, respectively). The amounts of 

13 Pb emitted from these U.S. sources, however, are several orders magnitude smaller than those estimated 

14 to arise from coal combustion in China.

15 Coal combustion is considered to be a major source of Pb in the atmosphere now that leaded 

16 gasoline has been phased out for use in on-road vehicles (Diaz-Somoano et al., 2009). Global Pb 

17 estimates are considered here to inform understanding of U.S. Pb emissions from coal combustion. 

18 Globally, Pb emissions from stationary sources have been increasing and the north-south gradient in 

19 aerosol Pb concentrations over the Atlantic Ocean has disappeared as a result of industrialization of the 

20 southern hemisphere (J. M. Pacyna & Pacyna, 2001; Witt et al., 2006). The Pb isotope ratio values 

(mainly 206Pb/207 21 Pb) for coals from around the world have been compared with those for atmospheric 

22 aerosols. In most parts of the world, there has been a difference between the signature for aerosols and 

that for coal, where the atmospheric 206Pb/207 23 Pb ratio values are lower, indicative of additional 

24 contributions from other sources. 

25 Rauch and Pacyna (2009) constructed global metal cycles using anthropogenic data from 2000. 

26 They confirmed that the largest anthropogenic airborne Pb emissions arise from fossil fuel combustion, 

27 and they quantified Pb emissions at 85,000 tons/yr worldwide. Using a separate global model, Niisoe et 

28 al. (2010) calculated emissions of Pb from coal combustion in Japan during 2000 to be 900 tons/yr, based 

on 9 × 107 29 tons/yr coal combustion and an emission factor of 10 g Pb/ton. The equivalent value for Pb 

30 emissions from China was 56,000 tons Pb/yr. Calculated Pb concentrations in surface air for China agreed 

31 with this value within a factor of two, although there was a systematic underestimation suggesting an 

32 incomplete knowledge of the Pb emissions (Niisoe et al., 2010). It was notable, however, that the 
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1 calculated emissions from Chinese coal combustion make up a substantial proportion (~66%) of the total 

2 global Pb emissions from fossil fuels detailed in Rauch and Pacyna (2009).

3 Tan et al. (2006) compared several emissions sources in Shanghai, China. They estimated emission 

4 values for on-road exhaust from use of Pb-free gasoline (238 ± 5 mg/kg), vehicle exhaust from leaded on5 road gasoline (7,804 ± 160 mg/kg), coal combustion (1,788 ± 37 mg/kg), metallurgic dust (6,140 ±

6 130 mg/kg), soil (11.7 ± 0.3 mg/kg), and cement (103 ± 2 mg/kg). Pb-free automobile gasoline has been 

7 in use in Shanghai since 1997. The isotope ratios for each of these emission sources were determined. 

Based on the 4.4 × 107 8 tons of coal combusted annually in Shanghai, an average coal Pb concentration of 

9 13.6 ± 6.6 mg/kg, and an emission factor of 0.5, approximately 300 tons Pb was being emitted annually in 

10 association with fine PM. They concluded that a major priority should be to reduce Pb emissions from 

11 coal combustion now that the contribution from vehicle exhaust emissions has decreased.

12 Seasonal effects of the contributions of Pb emissions from coal combustion have been observed. 

13 For example, in Tianjin, northern China, the winter heating period starts in November, and the 

14 contribution from coal combustion to the Pb aerosol becomes high during the winter. This leads to both a 

high Pb content and a high 206Pb/207 15 Pb ratio. Coal consumption and Pb-bearing PM concentrations 

16 declined during the summer months, and Pb from other sources, mainly vehicle exhaust emissions, 

17 became relatively more pronounced (W. Wang et al., 2006). This seasonal relationship contrasts with 

18 observations for the U.S. described in the 2006 Pb AQCD (U.S. EPA, 2006) which indicated that for West 

19 Virginia, higher emissions from power stations occurred in summer months. The increased energy use in 

20 summer periods in the U.S. may be attributable to increased requirements for air-conditioning. 

3.2.2.4. Other Industrial Sources

21 Several Pb isotope studies have been used to distinguish contributions from industrial activities. 

22 For example, in northern China, Wang et al. (2006) noted that, in the response to decreasing atmospheric 

Pb concentrations in total suspended particles (TSP) samples collected from 1994 to 1998, the 206Pb/207 23 Pb 

24 isotope ratio showed a related trend with values of ~1.149 in 1994 increasing to ~1.161 in 1998. The Pb 

25 concentration and isotope ratio values then remained approximately constant from 1998 through to 2001. 

26 Although this was consistent with a decreasing contribution of Pb from on-road gasoline, the ratio values 

were still lower than those for Chinese coal [

206Pb/207 27 Pb ~1.18 in Mukai et al. (2001)], suggesting that 

local Pb ore sources typically have lower 206Pb/207 28 Pb ratios. The range for Chinese ores was 1.081 to 

29 1.176, with lower values corresponding to ores from northern China (Mukai et al., 2001). 

30 Novak et al. (2008) evaluated changes in the amounts and sources of Pb emissions in the U.K. and 

31 Czech Republic during the 19th and 20th centuries. Deconvolution of sources was attempted using Pb 

32 isotopes, but one major area of uncertainty was the amount and the isotope composition of Pb emanating 

33 from incineration plants, particularly in the U.K. The isotopic signature of Pb recycled into the 
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atmosphere by incineration of various industrial wastes could have shifted from relatively high 206Pb/207 1 Pb 

2 ratios consistent with local Variscan ores to lower values reflecting imported Precambrian ores. There 

3 have, however, been other environmental studies concerning incineration, and these give a highly 

4 consistent value for the Pb isotope ratio for European incineration sources. For example, Cloquet et al. 

5 (2006) showed that the Pb isotopic composition of urban waste incineration flue gases in northeastern 

6 France was ~1.155. de la Cruz et al. (2009) reported that waste incineration was an important source of 

Pb and showed that the 206Pb/207Pb and 208Pb/207 7 Pb ratios for waste incineration Pb emitted in European 

8 countries were 1.1427-1.1576 and 2.4260-2.4346, respectively, i.e., quite a narrow range (de la Cruz et

9 al., 2009 and references therein).

3.2.2.5. Roadway-Related Sources

Contemporaneous Emissions from Vehicle Parts

10 Contemporaneous Pb emissions from motor vehicles may occur because several vehicle parts still 

11 contain Pb. Wheel weights, used to balance tires, are clipped to the rims of every automobile in the U.S.

12 in order to balance the tires, and may become loose and fall off. Ambient air Pb concentrations near 

13 heavily trafficked areas may be related to use of Pb-based wheel weights that are prone to dislodgement. 

14 On pavement they may be ground into fine PM by the pounding forces of traffic (Root, 2000). For 

15 example, Schauer et al. (2006) measured Pb emissions in two traffic tunnels and found that the fraction of 

16 Pb in PM2.5 was no more than 17% of Pb measured in PM10. Schauer et al. (2006) suggested that 

17 enrichment in the coarse fraction may have been related to wheel weights. Additionally, Schauer et al. 

18 (2006) measured PM10 and PM2.5 composition from brake dust and found low but substantial quantities of 

19 Pb in PM10 (0.02 ± 0.01 mg/g) and PM2.5 (0.01 ± 0.00 mg/g) for semi-metallic brake pads and in PM10

20 (0.01 ± 0.00 mg/g) for low-metallic brake pads. Additionally, Hjortenkrans et al. (2007) used material 

21 metal concentrations, traffic volume, emissions factors, and sales data to estimate the quantity of Pb 

22 emitted from brake wear and tires in Stockholm, Sweden in 2005. They observed that 24 kg Pb were 

23 emitted from brake wear each year, compared with 2.6 kg of Pb from tire tread wear; an estimated 549 kg 

24 was estimated to have been emitted from brake wear in 1998. McKenzie et al. (2009) determined the 

25 composition of various vehicle components including tires and brakes and found that tires were a possible 

26 source of Pb in stormwater, but no identification of Pb-containing PM in stormwater was carried out. 

27 However, PM from tire abrasion are usually found in coarser size ranges (Chon et al., 2010), while those 

28 in the submicron range are more typically associated with combustion and incineration sources.
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Unleaded Fuel

1 Unleaded fuel contains Pb as an impurity within crude oil (E. G. Pacyna et al., 2007). Schauer et al. 

2 (2006) measured Pb in PM2.5 from tailpipe emissions and observed significant quantities in on-road 

3 gasoline emissions (83.5 ± 12.80 mg/kg) and higher but non-significant quantities in diesel emissions 

4 (137 ± 133 mg/kg). Hu et al. (2009) investigated the heavy metal content of diesel fuel and lubricating oil. 

5 They found <1-3 ppm Pb in samples of lubricating oil. Hu et al. (2009) also measured the size distribution 

6 of Pb emissions during dynamometer testing of heavy duty diesel vehicles with different driving patterns 

7 and control technologies. An urban dynamic driving schedule (UDDS) designed to mimic urban stop-go 

8 driving conditions, was simulated in two cases to produce 80 and 241 ng Pb/km driven, depending on the 

9 control technology used. Respectively, 54% and 33% of those emissions were smaller than 0.25 μm in 

10 MMAD. The Tan et al. (2006) study cited in Section 3.2.2.3 for Shanghai, China, where unleaded fuel has 

11 been in use since 1997, illustrated that Pb emissions from unleaded on-road gasoline were substantially 

12 lower than Pb emissions from coal combustion. Assuming that the natural Pb content of unleaded fuels in 

13 the U.S. is similar, it is unlikely that road vehicle combustion of unleaded on-road gasoline is currently a 

14 major contributor to total Pb emissions in the U.S.

3.2.2.6. Deposited Lead

15 Soil Pb can serve as a reservoir for deposited Pb. The following subsections describe studies of 

16 previously deposited Pb from industrial, historical leaded on-road emissions, and urban sources such as 

17 paint and building materials. The 2006 Pb AQCD (U.S. EPA, 2006) cited an estimate by Harris and 

18 Davidson (2005) that more than 90% of airborne Pb emissions in the South Coast Basin of California 

19 were from soil resuspension. Since publication of the 2006 Pb AQCD (U.S. EPA, 2006), further analysis 

20 of the Harris and Davidson (2005) paper has revealed that the contributions of Pb from piston engine 

21 aircraft were underestimated compared with the 2002 NEI. Assumptions of spatial uniformity incurred by 

22 the “continuously stirred reactor” mass balance model and for mixing layer height used by Harris and 

23 Davidson (2005) were also not valid because Pb concentrations are spatially heterogeneous at the urban 

24 scale; see Section 3.5. Therefore, the estimate of 90% of airborne Pb from resuspension is not employed 

25 in the current assessment. Currently, data are not available with sufficient spatial resolution to discern the 

26 specific contribution of soil Pb resuspension to air Pb concentration, but resuspended soil Pb cannot be 

27 eliminated as a potential source of airborne Pb.

Lead from Industrial Sites

28 Several studies have indicated elevated levels of Pb in soil exposed to industrial emissions, 

29 including brownfield sites (Deng & Jennings, 2006; Dermont et al., 2010; Hofer et al., 2010; Jennings & 
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1 Ma, 2007; Sriskandan et al., 2007; van Herwijnen et al., 2007; Verstraete & Van Meirvenne, 2008). It is 

2 possible that Pb in soil serves as a source of airborne Pb. Laidlaw and Filipelli (2008) reviewed the 

3 literature on Pb resuspension from soil and then analyzed IMPROVE data to explore conditions under 

4 which Pb may become resuspended. They observed a seasonal pattern in concentration of soil 

5 resuspended in the atmosphere, and they also found that 83% of the variability in concentrations of soil in 

6 the atmosphere was predicted by the variability in meteorology and soil moisture content. The authors 

7 concluded that seasonality and climate parameters could not be eliminated in relation to ambient Pb 

8 concentrations. Such mechanisms are described in more detail in Section 3.3.

Lead from Paint and Building Materials

9 Exterior painted structures have long been known to be a source of ambient Pb (U.S. EPA, 2006). 

10 Recent studies support older findings. Mielke and Gonzales (2008) sampled exterior paint chips from 25 

11 homes in New Orleans, LA, and they found elevated Pb levels in 24 of the 25 tested exterior paints 

12 (median: 36,000 mg/kg). Weiss et al. (2006) studied the distribution of Pb concentration in roadway grit 

13 in the vicinity of steel structures in New York City and contrasted those data with roadway grit 

14 concentration data where no steel structure was nearby. In each case, the comparison was significant (p 

15 <0.006 at one site and p <0.0001 at 4 other sites), with median Pb concentrations under the steel 

16 structures being between 2.5 to 11 times higher than median Pb concentrations not near a structure. 

17 The studies described above considered paint as a source of Pb dust through gradual abrasion of the 

18 painted surfaces. However, ambient conditions may also affect the availability of Pb in paints. Edwards et 

19 al. (2009) performed experiments to simulate one week of exposure of Pb-based paints to elevated levels 

20 of O3 (11.3 ± 0.8 ppm or 150 times the level of the 8-h NAAQS) and NO2 (11.6 ± 0.9 ppm, or 220 times 

21 the level of the annual NAAQS). Following NO2 exposure, the Pb availability in wipe samples increased 

22 by a median of 260% (p < 0.001), and following O3 exposure, the Pb availability increased by a median of 

23 32% (p = 0.004). Edwards et al. (2009) state that the high O3 and NO2 concentrations simulated in the 

24 chamber were equivalent of 4.3 and 3.7 years of exposure at 50 and 60 ppb, respectively.

25 Building demolition was listed as a source of urban Pb dust in the 2006 Pb AQCD (U.S. EPA, 

26 2006). In a follow-up study to previous work cited therein, Farfel et al. (2005) observed that Pb dust 

27 surface loadings increased by 200% in streets, by 138% in alleys, and by 26% in sidewalks immediately 

28 following demolition of an old building. One month later, Pb dust loadings were still elevated in alleys 

29 (18%) and sidewalks (18%), although they had decreased in streets by 29%. However, Farfel et al. (2005)

30 did not provide detailed time series samples from before or after demolition to judge whether the 

31 observations made one month following demolition were within the normal conditions of the urban area. 

32 These results suggest that building demolition may be a short-term source of Pb in the environment, but it 

33 is unclear if demolition is related to long-term Pb persistence in the environment.
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Lead from Historic Automobile Emissions

1 Historic Pb emissions, or Pb emitted from on-road vehicles prior to the ban on use of leaded 

2 automobile gasoline, deposited onto soil and still may be persistent in the environment as a potential 

3 source of airborne Pb. The historical combustion of leaded on-road gasoline has been estimated from 

4 documents submitted by Ethyl Corporation to the U.S. Senate ("Airborne Lead Reduction Act of 1984," 

5 1984) and a report by the U.S. Geological Survey (USGS, 2005); see Mielke et al. (2010b). These 

6 estimates are presented in Figure 3-6. The peak U.S. use of Pb additives occurred between 1968 and 1972 

7 with an annual amount of over 200,000 metric tons. According to Ethyl Corporation, the 1970 use of Pb 

8 additives was 211,000 metric tons. By 1980, the annual use of Pb additives to on-road gasoline decreased 

9 to about 91,000 metric tons or a 57% reduction from its 1970 peak. From 1970 to 1990 there was a 92% 

10 decline in Pb additive use. In 1990, the annual U.S. use of Pb additives decreased to 16,000 metric tons, a 

11 further 82% decline in Pb additive use from 1980. The final U.S. ban on the use of Pb additives for 

12 highway use in on-road gasoline occurred in 1996. After that time, Pb additives were only allowed in non13 highway applications, including piston engine aircraft fuel, racing fuels, farm tractors, snowmobiles, and 

14 boats.

Source: Used with permission from Pergamon Press, Mielke et al. (2010b).

Figure 3-6. Total U.S. Pb additives in on-road gasoline used in on-road 

vehicles, 1927-1995. Estimates were derived from the 

proceedings of the U.S. Senate hearings on the Airborne Pb 

Reduction Act of 1984, S. 2609 ("Airborne Lead Reduction Act 

of 1984," 1984) and the U.S. Geological Survey Pb end use 

statistics (USGS, 2005).

Lead Additives in U.S. Gasoline

0

50,000

100,000

150,000

200,000

250,000

192519301935194019451950195519601965197019751980198519901995

Year

Metric Tons
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1 The particle sizes of Pb emissions from on-road sources were estimated by the U.S. EPA (1986), 

2 which indicated that 75% of Pb additives were emitted as exhaust. The tonnages of relatively large 

3 >10 μm mass median aerodynamic diameter (MMAD) Pb-PM probably settled locally, especially in high 

4 traffic urbanized areas where soil Pb, from historic emissions as well as contemporaneous sources, are 

5 elevated adjacent to roadways and decrease with distance away from the roadway (Laidlaw & Filippelli, 

6 2008). EPA (1986) indicated that 35% of the PM were < 0.25 μm in MMAD. The majority of PM, by 

7 number, emitted from automobiles was in the ultrafine size range (Londahl et al., 2009). However, 

8 Londahl et al. (2009) did not include ethylene dibromide to the fuel in these experiments. As described in 

9 the Gidney et al. (2010) study referenced in Section 3.2.2.1, it was found that ethylene dibromide acted to 

10 scavenge Pb in PM to form more volatile Pb bromide and Pb oxybromide to produce gaseous Pb 

11 emissions.

12 The use of Pb additives also resulted in a national scale of influence. For example, various sized 

13 urbanized areas of the U.S. have different amounts of vehicle traffic associated with Pb (Mielke et al., 

14 2010a). Figure 3-7 illustrates the national scale of the estimated vehicle-derived Pb aerosol emissions. 

15 Note that the estimated 1950-1982 Pb aerosol emissions in the 90 cities below vary from 606 metric tons 

16 for Laredo, Texas, to nearly 150,000 metric tons for the Los Angeles-Long Beach-Santa Anna urbanized 

17 area. The implication of this figure is that the soil Pb concentration will be proportional to the magnitude 

18 of historic on-road emissions in each city. It is recognized that the amount of soil turnover since 1982 may 

19 have varied substantially among the cities illustrated in Figure 3-7, depending on the amount of highway 

20 construction in those cities. Hence, the map may overestimate potential amounts of Pb in soil, and 

21 consequently of airborne Pb from resuspended soil, in some of the cities illustrated.
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Source: Used with permission from Pergamon Press, Mielke et al. (2010b)

Figure 3-7. Estimated Pb aerosol inputs from on-road gasoline into 90 

U.S. urbanized areas (UAs), from 1950 through 1982.The 

numbers on the map are rankings of each UA. The size of each 

dot refers to the magnitude of motor vehicle gasoline-related 

emissions for each group of UAs. The extremes are, Los 

Angeles UA (ranked #1) and Laredo, Texas (ranked #90). Some 

of the UAs have been used as sites in soil Pb studies, as 

indicated in Table 3-9.

3.2.3. Source Attribution

3.2.3.1. Lead Speciation and Source Apportionment

1 The following section describes new findings with respect to speciation of Pb content in aerosols. 

2 Analytic techniques for speciation are explicated in Section 3.4. Forms of Pb commonly observed in the 

3 environment are presented in Table 3-1 to serve as a reference for the categories of Pb sources described 

4 in Sections 3.2.1 and 3.2.2. Detailed descriptions of the related chemistry were presented in the 2006 Pb 

5 AQCD (U.S. EPA, 2006).
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Table 3-1. Pb compounds observed in the environment 

Emission Source Observed Pb Compounds

Minerals PbS (Galena)

PbO (Litharge, Massicot)

Pb3O4 (Minimum or “Red Pb”)

PbSO4 (Anglesite)

Smelting Aerosols Pb0, PbS

PbSO4, PbO

PbCO3

Pb silicates

Coal Combustion Aerosols PbS

PbSe

Coal Combustion Flue Gases Pb0, PbO, PbO2 (Above 1150 K)

PbCl2 (Low rank coals, above 1150 K)

PbSO4 (Below 1150 K)

Wood Combustion PbCO3

Waste Incineration Aerosols PbCl2, PbO

Soils Near Mining Operations PbCO3

PbSO4

[PbFe6(SO4)4(OH)12]

[Pb5(PO4)3Cl]

[Pb4SO4(CO3)2(OH)3]

PbS-Bi2S3

Pb oxides, silicates

Motor Vehicle Exhaust (Combustion of Leaded Fuel)1 PbBrCl

PbBrCl-2NH4Cl

PbBrCl-NH4Cl

Roadside Dust PbSO4, Pb0, PbSO4(NH4)SO4, Pb3O4, PbO-PbSO4 and 2PbCO3-Pb(OH)2

Other mobile sources:

Brake wear, wheel weights Pb0

Racing vehicle emissions Pb halides

Aircraft Engine Wear Pb0

Lawn Mowers Pb halides (battery leakage)

Source: Biggins and Harrison (1979, 1980); U.S. EPA (2006).

1 Chemical speciation of Pb by source was reviewed in the 2006 Pb AQCD (U.S. EPA, 2006), and is 

2 fairly well understood and varies considerably between sources. Pb components from Pb smelters are 

mainly elemental Pb (Pb0 3 ), Pb sulfide (PbS), Pb sulfates (PbSO4, PbO-PbSO4), and Pb oxide (PbO), with 

4 Pb carbonate (PbCO3) and Pb silicates. Other smelters also produce Pb, mainly as Pb oxide (PbO). Pb in 

5 coal combustion emissions is mainly in the form of Pb sulfide (PbS) and Pb sulfate (PbSO4) with some Pb 

6 selenide (PbSe) as well as sulfates, oxides and chlorides. In wood combustion emissions PbCO3 and Pb 

7 oxides are important. Waste incineration produces mainly Pb chloride (PbCl2) and PbO. Resuspended 

8 mining soils were reported to be abundant in PbCO3 and PbSO4, as well as a variety of complex salts 

9 containing phosphates, hydroxides, chlorides, oxides, and silicates. On-road engine exhaust from leaded 

10 gasoline use contained mostly Pb bromide and Pb chloride salts, including PbBrCl, PbBrCl-NH4Cl, and 

PbBrCl-2NH4Cl. Road dust is rich in PbSO4, Pb0 11 , oxides, carbonates, and hydroxides. Motor vehicles also 

contribute Pb0 12 from brake wear and wheel weights.

13 The 2006 Pb AQCD (U.S. EPA, 2006) described the atmosphere as the major environmental 

14 transport pathway for Pb, with Pb primarily present in submicron aerosols. Although not directly 

15 addressed in the 2006 Pb AQCD (U.S. EPA, 2006), organolead vapor emissions were extensively 

16 discussed in the 1986 Pb AQCD (U.S. EPA, 1986) which concluded that they were primarily emitted 
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1 during manufacture, transport, and handling of leaded on-road gasoline. Organolead vapors contributed 

2 less than 10% of vehicular Pb tailpipe emissions when leaded on-road gasoline was still in use. Studies of 

3 Pb emissions within enclosed microenvironments where automobiles were the dominant Pb source cited 

4 within the 1986 Pb AQCD (U.S. EPA, 1986), reported that organic Pb vapors contributed less than 20% 

5 of total vehicular Pb emissions. More recent studies support this (Shotyk et al., 2002). The 20% estimate 

6 of organic Pb vapors from the previous studies of on-road Pb emissions may potentially provide an upper 

7 bound for organic Pb vapors from current piston engine aircraft emissions.

8 Several recent studies have used speciation techniques either simply to determine the chemical 

9 composition of emissions or for source attribution. In urban environments, airborne Pb concentrations are 

10 likely a mix of various sources. Ogulei et al. (2006) performed source apportionment of PM2.5 samples in 

11 Baltimore, MD and found multiple industrial, urban, and background influences. Sixty-three percent of 

12 the Pb was associated with incineration, while 20% was associated with a wildfire episode from which 

13 PM was transported from Quebec, 8% was associated with secondary nitrate, 6% was associated with 

14 operations at a steel plant, and 3% was associated with local gasoline traffic. Dillner et al. (2006)

15 analyzed the composition of PM2.5 and TSP samples in Beijing, China and found that Pb comprised 

16 roughly 0.2% of TSP and 1.4% of PM2.5 during industrial pollution events, 0.1% of TSP and 0.5% of 

17 PM2.5 during urban pollution events, and 0.05% of TSP and 0.4% of PM2.5 during dust storms. During 

18 industrial pollution events, the authors note that the amount of Pb in PM2.5 can be substantial. 

19 Speciation of emissions from a battery recycling facility indicated that PbS was most abundant, 

followed by Pb sulfates (PbSO4 and PbSO4-PbO), PbO and Pb0 20 (Uzu et al., 2009). Pb speciation 

21 emissions from a sintering plant, a major component of the steel making process, were reported for the 

22 first time, with cerussite, a Pb carbonate (PbCO3-2H2O), emerging as the most abundant species (Sammut 

23 et al., 2010). The predominance of carbonates as major Pb species in industrial emissions is unusual. 

24 Choel et al. (2006) confirmed that Pb was strongly associated with sulfur in smelter emission PM, and 

25 that Pb sulfates and Pb oxy-sulfates were the most abundant species, with important contributions from 

26 Pb oxides. Zhang et al. (2009) used single particle aerosol mass spectrometry (ATOFMS) to speciate Pb27 bearing PM in Shanghai, China in 2007. PM containing Pb along with OC and/or EC was attributed to 

28 coal combustion processes; this accounted for roughly 45% of Pb-bearing PM. PM producing high 

29 correlations between Cl and Pb were ascribed to waste incineration, while Pb-bearing PM with a strong 

30 phosphate signal was attributed to the phosphate industry.

31 A few recent studies have used speciation techniques to characterize Pb and other components of 

32 PM10, PM2.5, and PM1. Reinard et al. (2007) used a real-time single particle mass spectrometer to 

33 characterize the composition of PM1 collected in Wilmington, Delaware in 2005 and 2006. 

34 Approximately two-thirds of PM1 consisted of secondary aerosols, e.g. mainly sulfate, nitrate and 

35 primary/secondary organics. The remaining third included PM from biomass burning, fossil fuel 

36 combustion and various industrial sources. For the latter group, strong Pb-Zn-K-Na associations were 
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1 observed. Comparison with stack emissions revealed that a nearby steel manufacturing facility was an 

2 important source of Pb. Ambient PM classes containing only a subset of such elements, e.g., Zn only, Pb3 K only were non-specific and so could not be mapped to individual sources. Wojas and Almquist (2007)

4 used ICPMS to characterize trace metals in PM2.5, PM10, and TSP samples obtained in Oxford, OH. They 

5 observed that Pb was highly correlated with several other elements (Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Ni, 

6 Pb, Sb, Si, and Zn), suggesting that Pb and copollutants emanated from a variety of sources including 

7 road dust and fuel combustion. Similarly, a study by Moffet et al. (2008) found that Pb-Zn-Cl particles in 

8 PM2.5 samples collected from an industrial area in Mexico City represented as much as 73% of fine PM. 

9 These were mainly in the submicron size range and were typically mixed with elemental carbon (EC), 

10 suggesting a combustion source. The unique single particle chemical associations closely matched 

11 signatures indicative of waste incineration. A study of PM10 and PM2.5 collected in Shanghai, China and 

12 analyzed using extended X-ray absorption fine structure spectroscopy (EXAFS), found that the main 

13 chemical forms of Pb were PbCl2 (41 ± 4%), PbSO4 (37 ± 2%) and PbO (22 ± 3%) (Tan et al., 2006). 

14 There was no significant difference in the chemical forms of Pb between the PM10 and PM2.5 samples. 

15 The main sources of these forms of Pb, based on Pb isotopic composition, were coal combustion, 

16 metallurgic dust and vehicle exhaust emissions (none though from leaded on-road gasoline).

17 Approximately 83% Pb was in the <2.5 μm size range. Murphy et al. (2007) found that the volatility of 

18 Pb and its compounds such as PbO results in its presence at high concentration in the submicron fraction 

19 of PM emitted from coal emissions. PbSO4, also derived from coal combustion, has low solubility

20 (Barrett et al., 2010). Variations in the relative proportions of Pb-containing compounds may account for 

21 the difference in Pb solubility in aerosols (Fernández Espinosa & Ternero-Rodríguez, 2004; Tan et al., 

22 2006; von Schneidemesser et al., 2010).

23 Murphy et al. (2007) also carried out a detailed study of the distribution of Pb in single atmospheric 

24 particles. During the fifth Cloud and Aerosol Characterization Experiment in the Free Troposphere 

25 (CLACE 5) campaign conducted at the Jungfraujoch research station, Switzerland, about 5% of analyzed 

26 aerosol particles in PM1 contained Pb. Of these, 35% had a relative signal for Pb greater than 5% of the 

27 total mass spectrum measured by an aerosol time of flight mass spectrometer (ATOFMS). These “high 

28 Pb” particles also contained one or more positive ions (e.g., of Na, Mg, Al, K, Fe, Zn, Mo, Ag, Ba). 

29 Sulfate fragments were present in 99% of the negative ion spectra associated with high Pb particles and 

30 50% also contained nitrite and nitrate. About 80% contained positive and/or negative polarity organic 

31 fragments. The average aerodynamic diameter of the Pb-rich particles (500 nm) was larger than the 

32 background aerosol (350 nm) but none had a diameter less than 300 nm. For urban aerosols collected in 

33 the U.S., two types of Pb-PM were found; in the main class, Pb was found together with K and usually 

34 also Zn. There were also minor amounts of Na, EC and organic carbon (OC) including amines. The 

35 second, minor class contained Pb together with Na, K, Zn, smaller amounts of Fe, EC and OC. The size 

36 distribution of the first group of Pb-PM usually peaked around 200 nm.
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1 Sample solubility can inform speciation efforts. For example, a study involving weak acid leaching 

2 was carried out by Erel et al. (2006). The transport of anthropogenic pollution by desert dust in the eastern 

3 Mediterranean region was studied by determining major and trace element concentrations, organic 

4 pollutants, and Pb isotope ratios. PM10 samples were collected during 10 dust storms in 2001-2003. Most 

5 samples were polluted to some extent with pollutants released by weak acid (0.5 M HNO3) extraction 

6 (including carbonates, oxides and surface-bound fractions). From the Pb isotope data, most of the Pb 

7 came from recently north African emissions and from past Israeli emissions (Pb now residing in Israeli 

8 soils). 

3.2.3.2. Lead Isotope Ratio Analysis

9 Classifying Pb by its relative isotopic abundance has also proved useful for a variety of purposes, 

10 including the determination of its geochemical origins in natural samples and the relative contributions of 

11 coal burning, mining, smelting, and motor vehicle emissions in polluted samples (Farmer et al., 1996). 

Typically, isotopes of Pb (208Pb, 207Pb, 206Pb, and 204 12 Pb) are measured in a sample using mass 

spectrometry, and then ratios of the isotopes are calculated to obtain a “signature.” Isotopes of 208 13 Pb, 

207Pb, and 206Pb are substantially more abundant than 204 14 Pb, but they vary depending on the geologic 

15 conditions under which the ore was produced through decay of different isotopes of uranium and thorium 

16 (Cheng & Hu, 2010). Isotope ratio analysis was first applied to airborne PM in 1965 to identify the 

17 impact of motor vehicle exhaust on marine and terrestrial Pb deposition in the Los Angeles area (Chow & 

18 Johnstone, 1965). More recently, high resolution ICPMS has also proved to be a sensitive tool for isotope 

19 ratio analysis. High resolution ICPMS was first applied to geological samples (Walder & Freedman, 

20 1992), and has since been widely used for determination of Pb isotope ratios in airborne PM samples. Pb 

21 isotope ratios have been measured in a number of recent studies in a variety of locations to investigate the 

22 origin of airborne Pb (Hsu et al., 2006; Knowlton & Moran, 2010; Noble et al., 2008; Widory, 2006).

23 Shotyk and Krachler (2010) also used Pb isotopes to demonstrate that the fate of Pb from runoff can be 

24 different from Pb with different origins. They observed that humus PM impacted by leaded on-road 

25 gasoline that are derived from soil surfaces are likely to be more easily transferred to sediments than Pb of 

26 other origins, with substantial amounts retained by lakes. 

27 Recent studies have examined the use of Pb isotope ratios as a tool for source apportionment. 

28 Duzgoren-Aydin and Weiss (2008) provide caveats for using isotope ratio analyses. They point out that Pb 

29 isotope ratios may vary when Pb from several sources of different geological origins are introduced to the 

30 same location. Duzgoren-Aydin (2007) warned that the presence of a complex mixture of contaminants 

31 containing common Pb isotopes can lead to an overestimation of the contribution of one source (e.g., soil 

32 contaminated by Pb emissions from on-road gasoline) and an underestimate of another source, such as 

33 that from industry. For this reason, Cheng and Hu (2010) suggest that Pb isotope analysis only be used 
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1 when the investigators are confident that the isotopic signatures of various sources differ substantially. Pb 

2 recycling and international trading may cause more blending of Pb from various sources, so that there is 

3 less heterogeneity in the Pb isotopic signatures sampled. Additionally, Cheng and Hu (2010) point out that 

4 the isotopic signature of Pb in air or soil may change over time with changing source contributions, but 

5 historical Pb isotope data are lacking. Duzgoren-Aydin and Weiss (2008) suggest the use of GIS mapping 

6 of Pb isotopic information to help distinguish potential sources based on location of sources in addition to 

7 the sources’ isotopic signature. 

8 Gulson et al. (2007) examined the relationships between Pb isotope ratios and source 

9 apportionment metrics at urban and rural sites in New South Wales, Australia. In this study, Gulson et al. 

10 (2007) performed source apportionment with both principal component analysis (PCA) and a neural 

11 network technique called the self-organizing map (SOM) and compared results from each method with 

206Pb/204Pb, 207Pb/206Pb, and 208Pb/206Pb obtained from PM samples, although only 206Pb/204 12 Pb results were 

13 presented in detail. Wintertime “fingerprints” from both the PCA and SOM methods produced similarly 

linear relationships with 206Pb/204 14 Pb, with linearly decreasing relationships between the isotope ratios and 

15 the “secondary industry,” “smoke,” “soil,” and “seaspray” source categories. However, the relationships 

16 of the isotope ratios with the SOM fingerprints and PCA factors, respectively, were very similar. This 

17 finding may have been due to the presence of elements such as black carbon and sulfur in several SOM 

18 fingerprints and PCA factors. The authors suggest that this might be related to the presence of several 

19 sources, which in combination result in a weak atmospheric signal. Additionally, both PM2.5 and TSP 

20 samples were utilized for this study, and it was found that similar results were obtained for either size cut. 

At the urban site, they observed that the 206Pb/204 21 Pb ratio decreased over time with increasing 

22 contributions of industrial, soil, smoke, and sea spray sources. For the most part, these sources were not 

23 substantial contributions to Pb-PM2.5 for the rural site. As for the Tan et al. (2006) speciation study 

24 described above, no notable differences were observed between the size fractions with regard to isotopic 

25 signature. 

3.3. Fate and Transport of Lead

26 There are multiple routes of exposure to Pb, including direct exposure to atmospheric Pb, exposure 

27 to Pb deposited in other media after atmospheric transport, and exposure to Pb in other media that does 

28 not originate from atmospheric deposition. As a result, an understanding of transport within and between 

29 media such as air, surface water, soil, and sediment is necessary for understanding direct and indirect 

30 impacts of atmospheric Pb as well the contribution of atmospheric Pb to total Pb exposure. Figure 3-8 

31 describes relevant Pb transport pathways through environmental media discussed in this chapter and their 

32 relationship to key environmental exposure pathways for which some or all of the Pb is processed through 
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1 the atmosphere. This discussion includes new research on atmospheric transport of Pb, atmospheric 

2 deposition and resuspension of Pb, Pb transport in surface waters and sediments, and Pb transport in soil. 

Figure 3-8. Fate of atmospheric lead. Media through which Pb is 

transported and deposited are shown in bold.

3.3.1. Air

3 The 2006 Pb AQCD (U.S. EPA, 2006) concluded that Pb was primarily present in submicron 

4 aerosols, but that bimodal size distributions were frequently observed. Pb-PM in the fine fraction is 

5 transported long distances, found in remote areas, and can be modeled using Gaussian plume models and 

6 Lagrangian or Eulerian continental transport models as reported by several studies. Good agreement 

7 between measurements and these models have been reported. Historical records of atmospheric 

8 deposition to soil, sediments, peat, plants, snowpacks, and ice cores have provided valuable information 

9 on trends and characteristics of atmospheric Pb transport. Numerous studies using a variety of 

10 environmental media indicated a consistent pattern of Pb deposition peaking in the 1970s, followed by a 

11 more recent decline. These findings indicated that the elimination of leaded gasoline for motor vehicles 

12 has not only led to lower atmospheric concentrations in areas impacted by vehicles (Section 3.5), but a 

13 pervasive pattern of decreasing atmospheric Pb deposition and decreasing concentrations in other 

14 environmental media even at great distances from sources.

15 The 2006 Pb AQCD (U.S. EPA, 2006) documented that soluble Pb was mostly removed by wet 

16 deposition, and most of the insoluble Pb was mostly removed by dry deposition. As a result, dry 
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1 deposition was the major removal mechanism for Pb in coarse PM (which is mainly insoluble) and wet 

2 deposition as the most important removal mechanism for fine PM and Pb halides (which were more 

3 soluble). Numerous studies reported that Pb dry deposition velocities in the U.S. were mostly within a 

range of 0.05 to 1.0 cm/sec and dry deposition fluxes ranging from 0.04 to 4 mg/m2 4 ·yr. Precipitation 

5 concentrations ranged mostly from 0.5 to 60 μg/L, but with considerably lower concentrations in remote 

areas, and wet deposition fluxes in the United States ranged from 0.3 to 1.0 mg/m2 6 ·yr. Wet deposition was 

7 linked to precipitation intensity, with slow even rainfalls usually depositing more Pb than intense rain 

8 showers. Rain concentrations decreased dramatically between the early 1980s and the 1990s, reflecting 

9 the overall decreasing trend in Pb emissions due to elimination of leaded motor vehicle gasoline. A 

10 summary of studies investigating total deposition including both wet and dry deposition indicated typical 

deposition fluxes of 2-3 mg/m2 11 ·yr and dry to wet deposition ratios ranging from 0.25 to 2.5. Seasonal 

12 deposition patterns can be affected by both variations in local source emissions and vegetation cover, and 

13 as a result a consistent seasonal pattern across studies has not been observed, although there have been 

14 only a few investigations.

15 The 2006 Pb AQCD (U.S. EPA, 2006) concluded that resuspension by wind and traffic contribute 

16 to airborne Pb near sources. Pb in resuspended road dust exhibited a bimodal size distribution, but mass 

17 was predominantly associated with coarse PM. The Pb fraction in resuspended dust ranged from 0.002 to 

18 0.3%, with the highest fractions observed for paved road dust and lowest for agricultural soil.

3.3.1.1. Transport

19 New research on long range transport as well as transport of Pb in urban areas has advanced the 

20 understanding of Pb transport in the atmosphere. While the 2006 Pb AQCD described long range Pb 

21 transport as essentially a process of submicron PM transport (U.S. EPA, 2006), much of the recent 

22 research on Pb transport has focused on interactions between anthropogenic and coarser geogenic PM that 

23 leads to incorporation of Pb into coarse PM as well as subsequent transformation on exposure to mineral 

24 components of coarse PM. Using scanning electron microscopy (SEM), Schleicher et al. (2010) observed 

25 interactions of anthropogenic soot and fly ash particles on the surfaces of coarse geogenic mineral 

26 particles and concluded that toxic metals were often associated with coarse PM. Murphy et al. (2007)

27 found that PM released from wild fires and transported over long distances scavenged and accumulated

28 Pb and sulfate through coagulation with small Pb rich PM during transport and that Pb was associated 

29 with PM over a wide size range. Erel et al. (2006) also found that Pb enrichment factors calculated for 

30 PM from dust storms collected in Israel were much greater than those sampled at their north African 

31 source, suggesting that the dust samples had picked up pollutant Pb in transit between the Saharan desert 

32 and Israel. Marx et al. (2008) characterized dust samples collected from the surface of glaciers and in dust 
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1 traps on the remote west coast of New Zealand’s South Island and observed that most of the dust samples 

2 were enriched in metals, including Pb, compared with their source area sediments.

3 Pb accumulated on mineral dusts is also subject to atmospheric transformations. PbSO4 is one of 

4 the main constituents of Pb-containing aerosols resulting from coal combustion (Gieré et al., 2006) and it 

5 has been shown to react with calcite, CaCO3, a PM mineral component, to form Pb3(CO3)2(OH)2, Pb(CO3) 

6 and Ca(SO4)2·H2O on the surface of the calcite (Falgayrac et al., 2006). In laboratory experiments, 

7 (Ishizaka et al., 2009) also showed that PbSO4 could be converted to PbCO3 in the presence of water. 

8 Approximately 60-80% was converted after only 24 hours for test samples immersed in a water droplet. 

9 This compared with only 4% conversion for particles that had not been immersed. As a result of recent 

10 research, there is considerable evidence that appreciable amounts of Pb can accumulate on coarse PM 

11 during transport, and that the physical and chemical characteristics of Pb can be altered by this process 

12 due to accompanying transformations. 

Transport and Dispersion Mechanisms in Urban Environments

13 Several major U.S. sources of Pb emissions are located in urban areas. The urban environment can 

14 be considered unique because it has been highly modified by human activity, including above- and below15 ground infrastructure, buildings, and pavement, and a high density of motorized transportation. This 

16 section focuses on special features of urban environments and upon processes that influence the 

17 distribution and redistribution of Pb-bearing PM.
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Source: Used with permission from Annual Reviews, Fernando (2010)

Figure 3-9. Scales of turbulence within an urban environment.Top: 

multiple scales within the atmospheric boundary layer. 

Bottom: illustration of airflow recirculation within a single 

street canyon located in the urban canopy layer.
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1 As shown in Figure 3-9, urban turbulence occurs on several scales. Transport and dispersion of 

2 urban grit is subject to air movement within the urban canopy layer, where air movement is driven by air 

3 velocity within the urban boundary layer and urban topographical conditions such as building shape, 

4 building façade, and street canyon aspect ratio (Fernando, 2010). Within a street canyon, air circulates and 

5 tends to form counter-rotating eddies along the height of the canyon (see Figure 3-9), which result in 

6 lower mean components of air movement, higher turbulence components, and higher sheer stress within 

7 the canyon compared with open field conditions (Britter & Hanna, 2003; Kastner-Klein & Rotach, 2004). 

8 Recirculation around intersection corners and two-way traffic conditions can also enhance turbulence 

9 levels, while one-way traffic conditions increase air velocity along the street (Kastner-Klein et al., 2003; 

10 Kastner-Klein et al., 2001; Soulhac et al., 2009). All of these factors have the potential to influence human 

11 exposure to atmospheric Pb in urban areas with substantial Pb emissions.

3.3.1.2. Deposition

Wet Deposition

12 The 2006 Pb AQCD (U.S. EPA, 2006) documented that dry deposition was the major removal 

13 mechanism for Pb in coarse PM and wet deposition as the most important removal mechanism for fine 

14 PM. Which process is most important for atmospheric removal of metals by deposition is largely 

15 controlled by solubility in rain water. Metal solubility in natural waters is determined by a complex 

16 multicomponent equilibrium between metals and their soluble complexes and insoluble ionic solids 

17 formed with hydroxide, oxide, and carbonate ions. This equilibrium is strongly dependent on pH and 

18 ionic composition of the rain water. Recent research confirms the general trend described in the 2006 Pb 

19 AQCD (U.S. EPA, 2006) that Pb associated with fine PM is usually more soluble in rain water than Pb 

20 associated with coarse PM, leading to a relatively greater importance of wet deposition for fine Pb and of 

21 dry deposition for coarse Pb. This could also explain the greater importance of dry deposition near 

22 sources because coarse mode PM makes a greater contribution to PM mass. Although recent observations 

23 are consistent with these trends they also indicate considerable spatial and seasonal variability. Birmili et 

24 al. (2006) found that Pb solubility varied between the two main Pb-containing size fractions, <0.5 μm

25 (~40%) and 1.5-3.0 μm (~10%), indicative of a different chemical speciation. However, the observation 

26 that the amount of soluble Pb was higher in their U.K. samples than in an analytically identical study 

27 carried out in Seville, Spain (Fernandez Espinosa et al., 2004), led them to conclude that Pb solubility in 

28 fine PM may vary on a regional basis (Birmili et al., 2006). For PM10 from Antarctica, 90 to 100% of the 

29 Pb was insoluble at the beginning of the summer season (November), but by the end of the summer 

30 (January), approximately 50% was soluble. Most of the Pb was from long range transport (Annibaldi et 

31 al., 2007). These studies illustrate the variable nature of atmospheric Pb solubility.
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Dry Deposition

1 New measurements of Pb dry deposition fluxes are similar to those reported in the 2006 Pb AQCD 

2 (U.S. EPA, 2006), except in industrialized urban areas, where it is considerably greater. Yi et al. (2006)

3 calculated dry deposition fluxes for trace elements including Pb in New York-New Jersey harbor and 

4 observed much greater dry deposition fluxes for an urban industrial site than for New Brunswick. This is 

5 consistent with similar observations of dry deposition fluxes that were more than ten times greater in 

6 urban Chicago than in rural South Haven, Michigan (Paode et al., 1998). These results illustrate the 

7 strongly localized nature of atmospheric Pb deposition in source rich areas. Elements from anthropogenic 

8 sources, including Pb, were generally associated with fine PM. In a study of Tokyo Bay (Sakata & 

9 Asakura, 2008), reported an average dry deposition velocity of 1.06 cm/sec, which is at the upper end of 

10 dry deposition velocities reported in the 2006 AQCD (U.S. EPA, 2006). They also reported that dry 

deposition fluxes were greater in industrially impacted urban areas, ranging from 12-17 μg/m2 11 ·yr, more 

12 than 10 times the upper bound of the range reported in the 2006 Pb AQCD (U.S. EPA, 2006). 

13 Recent results also confirmed the trend of decreasing overall deposition fluxes after removal of Pb 

14 from on-road gasoline, as described in the 2006 Pb AQCD (U.S. EPA, 2006). Watmough and Dillon 

15 (2007) found that the bulk annual deposition of Pb in a central Ontario forested watershed during 2002-

2003 was 0.49 mg/m2·yr; this was lower than the value of 1.30-1.90 mg/m2 16 ·yr for 1989-91 and 

17 represented a 75% decline in Pb deposition. It was consistent with the decline more generally observed 

18 for the Northeastern U.S. as a consequence of the restrictions to alkyl-Pb additives in on-road gasoline. 

19 From previously published work, and in agreement with the precipitation data described above, most of 

20 the decline took place before the start of the Watmough and Dillon (2007) study.

21 Several important observations can be highlighted from the few studies of atmospheric Pb 

22 deposition carried out in the past several years. Deposition fluxes have greatly declined since the removal 

23 of Pb additives from on-road gasoline. However, new results in industrial areas indicate that local 

24 deposition fluxes there are much higher than under more typical conditions. In general, wet deposition 

25 appears to be more important for Pb in fine PM, which is relatively soluble; and dry deposition appears to 

26 be generally more important for Pb in coarse PM, which is relatively insoluble. However, the relative 

27 importance of wet and dry deposition is highly variable with respect to location and season, probably 

28 reflecting both variations in Pb speciation and variations in external factors such as pH and rain water 

29 composition. Although industrial Pb emissions are mainly associated with fine PM, and wet deposition is 

30 likely to be more important for this size range, a substantial amount of Pb is apparently removed near 

31 industrial sources.
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3.3.1.3. Resuspension of Lead from Soil to Air after Lead Deposition

1 As described in Section 3.2, the greatest Pb emissions in the United States occur in locations near 

2 major specific point sources, including airports, secondary smelters, and other industrial operations 

3 involving large scale metal processing or fuel combustion. However, in the absence of such sources and in 

4 the vicinity of previous major sources, the 2006 Pb AQCD (U.S. EPA, 2006) concluded that resuspension 

5 by wind and traffic can be a substantial source of airborne Pb above background levels near sources, with 

6 resuspended dust accounting for between 0.002 to 0.3% of PM mass. Since then, results from several 

7 studies have provided support for a substantial contribution from resuspension by indicating a smoothed 

8 soil Pb concentration profile that decreases with distance from various sources, including city centers

9 (Laidlaw & Filippelli, 2008), major freeways (Sabin, Lim, Venezia, et al., 2006), and steel structures with 

10 abrading paint (Weiss et al., 2006). The smoothed profile is consistent with continual Pb resuspension and 

11 deposition due to atmospheric turbulence. Recent Pb speciation results also indicate a substantial 

12 contribution from resuspended soils in areas with previous major emission sources, but without current 

13 major sources. Data from airborne PM in the vicinity of an inactive smelter in El Paso, TX were 

14 consistent with Pb-humate as the major form of Pb in airborne PM, suggestive of soil resuspension since 

15 the local near-surface soils had high humic content (Pingitore et al., 2009).

16 Recent research on urban PM transport is also highly relevant to Pb transport and dispersion 

17 because Pb is most prevalently particle-bound. Relevant results for Pb exposure in these areas include 

18 observations that PM concentration peaks dissipate more rapidly on wider streets than in narrow street 

19 canyons (Buonanno et al., 2011); concentrations are typically low next to a building because either less 

20 source material is available or less material penetrates the boundary layer of the building (Buonanno et 

21 al., 2011); and there are stronger inverse relationship between mean wind speed and PM concentration 

22 fluctuation intensities at middle sections of urban street blocks compared with intersections (Hahn et al., 

23 2009). Patra et al. (2008) conducted experiments in London, U.K. in which a “tracer” grit was applied to a 

24 road and then the grit’s dispersion by traffic was measured over time to simulate resuspension and 

25 transport of a trace metal such as Pb. During the experiments, 0.039% of the tracer grit was measured to 

26 move down the road with each passing vehicle, 0.0050% was estimated to be swept across the road with 

27 each passing vehicle, and 0.031% was estimated to become airborne when a vehicle passed. 

28 New resuspension studies complement previous research indicating street dust half-lives on the 

29 order of one-hundred days (Allott et al., 1989), with resuspension and street run-off as major sinks 

30 (Vermette et al., 1991) as well as observations of a strong influence of street surface pollution on 

31 resuspension (Bukowiecki et al., 2010), observations of greater resuspension of smaller PM than coarser 

32 PM (Lara-Cazenave et al., 1994), leading to enrichment of metal concentrations in resuspended PM 

33 relative to street dust (Wong et al., 2006) and observations of wind speed, wind direction, vehicular 

34 traffic, pedestrian traffic, agricultural activities, street sweeping and construction operations as important 
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1 factors determining resuspension. Together these results demonstrate that under in the vicinity of previous 

2 major emission sources and the absence of current major sources, resuspension can make a substantial 

3 contribution to atmospheric Pb concentrations.

3.3.2. Water

4 As described in the 2006 Pb AQCD (U.S. EPA, 2006), atmospheric deposition has been identified 

5 as the largest source of Pb in surface waters, but urban runoff and industrial discharge are also important. 

6 Water columns have been described as transient reservoirs with Pb residence times in lakes typically 

7 several months long, and shorter residence times expected in turbulent waterways. Because dispersal in 

8 waterways is a relatively rapid process, concentrations in surface waters are highest near sources of 

9 pollution before substantial Pb by flushing, evaporation and sedimentation. Transport in surface water is 

10 largely controlled by exchange with sediments, and the cycling of Pb between water and sediments is 

11 governed by chemical, biological, and mechanical processes that are affected by many factors, including 

12 salinity, organic complexation, oxidation-reduction potential, and pH. As described in the 2006 Pb AQCD 

13 (U.S. EPA, 2006), metals in waterways are transported primarily as soluble chelates and ions, or adsorbed 

14 on colloidal surfaces, including secondary clay minerals, iron and manganese oxides or hydroxides, and 

15 organic matter, and adsorption on organic or inorganic colloids is particularly important for Pb. The extent 

16 of sorption is strongly depends on particle size as smaller particles have larger collective surface areas. 

17 Aqueous Pb concentrations also increase with increasing salinity. Pb is found predominantly as PbO or 

18 PbCO3 in aqueous ecosystems. Pb is relatively stable in sediments, with long residence times and limited 

19 mobility. However, Pb-containing sediment particles can be remobilized into the water column. As a 

20 result trends in sediment concentration tend to follow those in overlying waters. Fe and Mn oxides are 

21 especially susceptible to recycling with the overlying water column. Although resuspension of sediments 

22 into overlying waters is generally small compared to sedimentation, resuspension of contaminated 

23 sediments is often a more important source than atmospheric deposition. Organic matter (OM) in 

24 sediments has a high capacity for accumulating trace elements. In an anoxic environmental removal by 

25 sulfides is particularly important. 

26 Although atmospheric deposition was identified as the largest source of Pb in surface waters in the 

27 2006 Pb AQCD (U.S. EPA, 2006), runoff from storms was also identified as an important source. A 

28 substantial portion of Pb susceptible to runoff is originates from atmospheric deposition. The 2006 Pb 

29 AQCD (U.S. EPA, 2006) concluded that important contributors to Pb in dust on roadways included 

30 vehicle wear, vehicle emissions, road wear, fluid leakage, and atmospheric deposition. Runoff from 

31 buildings due to paint, gutters, roofing materials and other housing materials were also identified as major 

32 contributors to Pb in runoff waters. Investigations of building material contributions indicated runoff 

33 concentrations ranging from 2 to 88 mg/L, with the highest concentrations observed from more than 10-
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1 year-old paint and the lowest concentrations from residential roofs. There was some indication that Pb 

2 from roofing materials, siding, and piping could be due to dissolution of Pb carbonate (cerussite) or 

3 related compounds. In several studies Pb in runoff was consistently mostly PM, with a relatively small 

4 dissolved fraction. Runoff release was dependent on storm intensity and length of dry periods between 

5 rain events, with greater runoff of Pb associated with more intense storms and with longer periods 

6 between rain events. Several studies indicated a “first flush effect,” with highest runoff concentrations 

7 observed at the beginning of a rain event.

3.3.2.1. Lead Transport in Water and Sediment

8 Recent publications provide additional detail regarding Pb adsorption on iron rich and organic rich 

9 colloids. Correlation between Pb concentration in unfiltered water with total Fe was observed (Hassellov 

10 & von der Kammer, 2008), which is consistent with previous research using cross flow filtration 

11 (Pokrovsky & Schott, 2002; Ross & Sherrell, 1999) and SEM examination of single particles (Taillefert et 

12 al., 2000).

13 Two distinct colloidal phases, one organic-rich (0.5-3 nm in diameter) and the other Fe-rich (>3 nm 

14 in diameter), have been observed to coexist in both soil isolates and river water (Stolpe & Hassellov, 

15 2007). Pb was observed to be predominantly associated with Fe-oxide PM in river water but also 

16 associated with the organic colloids in the soil isolates (Hassellov & von der Kammer, 2008). 

17 Investigation of Pb binding onto ferrihydrite showed Pb binding data were consistent with Pb being held 

18 at the surface by sorption processes, rather than enclosed within the particle structure (Hassellov & von 

19 der Kammer, 2008).

20 Observations in boreal rivers and soil pore waters in permafrost dominated areas of Central Siberia

21 indicated that Pb was transported with colloids in Fe-rich waters. Trace elements that normally exhibited 

22 limited mobility (including Pb) had 40-80% of their annual flux in the nominal dissolved phase, 

23 operationally defined as material that passes through a 0.45 μm pore-size filter, and that these metals had 

24 a higher affinity for organo-mineral Fe-Al colloids (Pokrovsky et al., 2006). Pokrovsky et al. (2006)

25 postulated that during the summer, rainwater interacts with degrading plant litter in the top soil leading to

26 the formation of Fe-Al-organic colloids with incorporated trace elements. Migration of trace element-Fe27 Al-OM colloids may result in export of Pb and other elements to riverine systems. Most of the transport 

28 occurred after thawing had commenced. This contrasts with permafrost free areas where trace elements 

29 such as Pb are incorporated into iron colloids during OM-stabilized Fe-oxyhydroxide formation at the 

30 redox boundary of Fe(II)-rich waters and surficial DOC-rich horizons. Similarly, during a spring flood 

31 (May) that exported 30-60% of total annual dissolved and suspended flux of elements including Pb, Pb 

32 was mainly in the nominal dissolved phase, operationally defined as material that passes through a 

33 0.45 μm pore-size filter (Pokrovsky et al., 2010). This was likely due to the presence of organic-bound 
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1 colloids smaller than 0.45 μm rather than true Pb dissolution (Pokrovsky et al., 2010). Pb adsorbed on 

2 colloidal surfaces rather than incorporated into particle structure is likely to be more readily dissolved 

3 because dissolution of the entire particle is not required.

4 Recent research on retention of Pb in water bodies and sediments has focused on the estuarine and 

5 marine environment, where considerable retention of Pb was observed in estuarine sediments. For a large 

6 riparian system, the Trinity River, Texas, Warnken and Santschi (2009) found that 80% of riverine Pb was 

7 retained in Lake Livingston, an estuarine region, while an additional 16% was removed to estuarine 

8 sediments, and only about 4% eventually reached the ocean. Geochemical (sorption by Fe 

9 oxyhydroxides), biological (seasonal uptake by sinking algae in Lake Livingston) and hydrological 

10 (dilution effects by increasing flow rates) processes were mainly responsible for controlling dissolved 

11 trace metal concentrations rather than pollution sources. 

12 Overall, recent research on Pb transport in aquatic systems has provided a large body of 

13 observations confirming that Pb transport is dominated by iron and organic rich colloids. In addition, new 

14 results indicated that although the 2006 Pb AQCD (U.S. EPA, 2006) described rivers and lakes as 

15 temporary reservoirs with Pb lifetimes of months or less, estuaries can present a substantial barrier to 

16 transport into the open ocean.

3.3.2.2. Deposition of Lead within Bodies of Water and in Sediment

17 As described in the 2006 Pb AQCD (U.S. EPA, 2006), in general Pb is relatively stable in 

18 sediments, with long residence times and limited mobility. As described in previous sections, Pb enters 

19 and is distributed in bodies of water largely in PM form. In rivers, particle-bound metals can often 

20 account for ≥ 75% of the total load, e.g. (Horowitz & Stephens, 2008). Urbanized areas tend to have 

21 greater aquatic Pb loads, as several studies have shown the strong positive correlation between population 

22 density and river or lake sediment Pb concentrations (Chalmers et al., 2007; Horowitz et al., 2008). 

23 Indeed, Chalmers et al. (2007) revealed that in river and lake sediments in New England, there was an 

24 order of magnitude difference between Pb sediment concentrations in rural versus urbanized areas. 

25 The fate of Pb in the water column is determined by the chemical and physical properties of the 

26 water (pH, salinity, oxidation status, flow rate and the suspended sediment load and its constituents, etc). 

27 Desorption, dissolution, precipitation, sorption and complexation processes can all occur concurrently and 

28 continuously, leading to transformations and redistribution of Pb. The pH of water is of primary 

29 importance in determining the likely chemical fate of Pb in terms of solubility, precipitation or organic 

30 complexation. In peatland areas, such as those in upland areas of the U.K., organic acids draining from 

31 the surrounding peatlands can lower stream water pH to below 4. Under these conditions, Pb-PM can be 

32 desorbed and released into solution, leading to elevated dissolved Pb concentrations (Rothwell et al., 

33 2008). At the other end of the pH scale, Pb tends to remain or become complexed, precipitated or sorbed 
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1 to TSP, as observed by Das et al. (2008) who studied trace metal geochemistry in a South African lake 

2 with water pH of 9. They also found marked differences in Pb concentrations associated with increasing 

3 depth in the water column [e.g., the surface Pb-PM concentration of 2 μg/L increased to 60 μg/L at depth 

4 and the Pb concentration in the <0.45 μm fraction increased from 2 μg/L at the surface to 19 μg/L at 

5 depth (Das et al., 2008)]. This is suggestive of a settlement process in action. 

6 In estuarine and wider marine environments the processes may be more complex because of the 

7 additional perturbation caused by tidal action and the strong effects of salinity. Again, PM forms of Pb are 

8 important in determining Pb distribution and behavior. Li et al. (2010) reported that PM Pb accounted for 

9 85 ± 15% and 50 ± 22% in Boston Harbor and Massachusetts Bay, respectively, while Lai et al. (2008)

10 reported a solid (acid soluble):dissolved Pb ratio of 2.6 for areas of the Australian sector of the Southern 

11 Ocean. 

12 The accurate modeling of Pb behavior in marine waters (including estuaries) requires consideration 

13 of many parameters such as hydrodynamics, salinity, pH, suspended PM, fluxes between PM and 

14 dissolved phases (Hartnett & Berry, 2010). Several new advances in the study of Pb cycling in these 

15 complex environments have been described in recent publications. Li et al. (2010) used particle organic 

16 carbon (POC) as a surrogate for the primary sorption phase in the water column to describe and model the 

17 partitioning of Pb between PM and dissolved forms. Huang and Conte (2009) observed that considerable 

18 change in the composition of PM occurs as they sink in the marine environment of the Sargasso Sea, with 

19 mineralization of OM resulting in increased PM-Pb concentration with increased depth. As a result of this 

20 depletion of OM in sinking particles, geochemical behavior at depth was dominated by inorganic 

21 processes, e.g. adsorption onto surfaces, which were largely independent of Pb source. Sinking rates in 

22 marine environments can vary, but a rate approximating 1 m/day has been used in some models of Pb 

23 transport and distribution in aquatic-sediment systems (L. Li et al., 2010). Surface sediment Pb 

24 concentrations for various continental shelves were collated and compared by Fang et al. (2009); see 

25 Table 3-2.

Table 3-2. Surface sediment Pb concentrations for various continental shelves; see 

Fang et al. (2009) and references therein.

Location Digestion solution Pb (mg/kg)

East China Sea HCl/HNO3/HF 10-49 (27)a

Mediterranean, Israel coast HNO3 9.9-20

Aegean Sea HCl/HNO3/HF 21-44 (34)

Banc d’Arguin, Mauritania HCl/HNO3/HF 2.8-8.9

Campeche shelf, Gulf of Mexico HCl/HNO3 0.22-20 (4.3)

Laptev Sea, Siberia HCl/HNO3/HF 12-22

Pechora Sea, Russia Not reported 9.0-22 (14)

a

Values in parentheses are the average, where calculable
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3.3.2.3. Flux of Lead from Sediments

1 Sediments can be either a source or a sink for metals in the aquatic environment. Release can be via 

2 re-suspension of the sediment bed via wind, wave and tidal action or by dissolution from sediment to the 

3 water column. When external Pb inputs to bodies of water are decreased by environmental improvement 

4 actions or regulations, contributions of Pb to the water column from the existing sediments can become an 

5 increasingly important source. (J. L. Roulier et al., 2010) determined that Pb flux from sediments 

6 originated mostly from organic fractions, but also partially from Mn and Fe components undergoing 

7 reductive dissolution. The rate of release was controlled by OM content, particle size, clay type and 

8 content, and silt fraction (J. L. Roulier et al., 2010). The importance of sediment particle size, OM content 

9 and acid volatile sulfide concentration in relation to metal release was similarly identified (Cantwell et al., 

10 2008). The effect of pH change on Pb release from lake sediments has also been examined, revealing that 

1.8 protons (H+ 11 ) were exchanged per divalent metal cation released (G. Lee et al., 2008). Processes 

12 governing Pb release from lake sediments, including microbial reductive dissolution of Fe, biogenic 

13 sulfide production and metal sorption-desorption, have been investigated and results indicated that release 

14 of Pb from sub-oxic and anoxic zones of the sediment act as a Pb source to the overlying water of the lake

15 (Sengor et al., 2007). 

16 Sediment resuspension from marine environments is similarly important, with disturbance of bed 

17 sediments by tidal action in estuarine areas resulting in a general greater capacity for re-suspension of 

18 PM. Benthic fluxes of dissolved metals released from sediments measured in Boston Bay were calculated 

19 as strong enough that in the absence of Pb inputs such benthic flux would reduce sediment Pb 

20 concentrations in Boston Bay to background levels in 30-60 years (L. Li et al., 2010). In a related way, a 

21 half-life for sediment Pb (considering benthic flux alone as the loss mechanism) of 5.3 years was 

22 estimated for marine sediments off the Belgian coast (Gao et al., 2009). 

23 Radakovitch et al. (2008) investigated the riverine transport of PM including Pb to the Gulf of 

24 Lion, France, and also concluded that a major part of annual fluxes could be delivered over a short time 

25 period. From budget calculations, riverine inputs were more important than atmospheric deposition and 

26 Pb concentrations in the prodelta sediments showed a strong correlation with OM content. These 

27 sediments, however, were not considered to be a permanent sink, as resuspension in these shallow areas 

28 was an important process. OM, Pb and other metals were enriched in resuspended PM compared with the 

29 sediment. 

30 Birch and O’Hea (2007) reported higher total suspended solids, turbidity and total water metal 

31 concentration in surface compared with bottom water as well as a difference in suspended PM metal 

32 concentrations between surface water and bottom sediments, demonstrating that stormwater discharge 

33 was the dominant process of metal transfer during high rainfall events. Total suspended sediments (and 

34 total water metals) in bottom water were higher than in the surface water plume, indicating that 
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1 resuspension of bottom sediment is a greater contributor of total suspended sediments than stormwater 

2 during such events, especially in shallower regions of the bay. Soto-Jimenez and Páez-Osuna (2010)

3 determined diffusive and advective fluxes, geochemical partitioning of Pb and Pb-isotopic signatures in a 

4 study of mobility and behavior of Pb in hypersaline salt marsh sediments. They determined that sulfides 

5 were the main scavengers for Pb that was diagenetically released Pb.

6 Overall, recent research on Pb flux from sediments in natural waters provided greater detail on 

7 resuspension processes than was available in the 2006 Pb AQCD (U.S. EPA, 2006), and has demonstrated 

8 that resuspended Pb is largely associated with OM or Fe and Mn particles, but that anoxic or depleted 

9 oxygen environments in sediments play an important role in Pb cycling. This newer research indicated 

10 that resuspension and release from sediments largely occurs during discrete events related to storms. It 

11 has also confirmed that resuspension is an important process that strongly influences the lifetime of Pb in 

12 bodies of water. Finally, there have been important advances in understanding and modeling of Pb 

13 partitioning in complex aquatic environments.

3.3.2.4. Lead in Runoff

14 Runoff is a major source of Pb in surface waters. This complicates any evaluation of the 

15 contribution of atmospheric Pb to surfaces waters, which must take into account direct atmospheric 

16 deposition, runoff of atmospherically deposited Pb, and runoff of Pb from sources such as mine tailings or 

17 paint chips that are deposited from the atmosphere. The 2006 Pb AQCD (U.S. EPA, 2006) identified

18 important contributors to Pb pollution in dust associated with roadways, such as vehicle wear, vehicle 

19 emissions, road wear, fluid leakage, and atmospheric deposition That review identified contributors to 

20 runoff from buildings, such as paint, gutters, roofing materials and other housing materials. The 2006 Pb 

21 AQCD (U.S. EPA, 2006) also concluded that runoff was consistently mostly PM, with a relatively small 

22 dissolved fraction, and that dissolution of carbonate and related compounds were important contributors 

23 to Pb pollution in runoff waters. It also described runoff Pb release into runoff as dependent on storm 

24 intensity and length of dry periods between rain events, and a “first flush effect,” with highest runoff 

25 concentrations observed at the beginning of a rain event. Subsequent research has provided considerable 

26 new information about roadway and urban runoff and snow melt.

27 Severe contamination due to export of anthropogenic Pb to adjacent ecosystems via sewage 

28 systems (urban runoff and domestic wastewater) and to a lesser extent by direct atmospheric deposition

29 has been documented (Soto-Jiménez & Flegal, 2009). Recent investigations also confirm roof runoff as an 

30 important contributor to Pb pollution. Huston et al. (2009) measured Pb concentrations in water from 

31 urban rainwater tanks and found Pb concentrations in bulk deposition were consistently lower than in

32 water in the rainwater tanks, but that sludge in the tanks had a high Pb content, indicating that not all 

33 major sources of Pb are from atmospheric deposition. Pb levels frequently exceeded drinking water 
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1 standards. Pb flashing on the roofs was implicated as the source of Pb in the rainwater tanks although 

2 other possible sources include old paint and Pb stabilized PVC drain pipes (Al-Malack, 2001; Lasheen et 

3 al., 2008; Weiss et al., 2006). 

4 New research has improved the understanding of suspended PM size ranges, speciation, and 

5 impacts of Pb runoff from urban soil and road dust. Soil and road dust have been identified as major 

6 sources of Pb pollution to near-coastal waters, leading to high Pb concentrations in stormwater runoff that 

7 became associated with dissolved and suspended PM phases as well as bedload, material moved by 

8 rolling, sliding, and saltating along the bottom of a stream (Birch & McCready, 2009). 

9 Several new studies reported that the size distribution of PM transported in runoff is relatively 

10 uniform. Characterization of the roadside dust in Australia showed that Pb in PM was approximately 

11 uniformly distributed among PM size fractions of up to 250 μm. The Pb-containing particles had the 

12 potential to be dispersed to some distance into sensitive ecosystems (Pratt & Lottermoser, 2007). Pb in 

13 roadside dusts in Thessaloniki, Greece was characterized by Ewen et al. (2009) and no difference in Pb 

14 concentration was found between <75 μm and 75-125 μm PM size ranges, although a difference in the 

15 chemical form of Pb between slightly versus highly contaminated areas was observed. 

16 Ewen et al. (2009) reported that Pb was mainly in a more exchangeable form (similar to that in an 

17 old auto-catalyst reference material) in small particles, but in the residual, or least mobile fraction in 

18 larger particles. In urban road dust from Manchester U.K., Pb-bearing Fe-oxides were observed to be 

19 dominant in most of the size fractions, and PbCrO4 comprised 8-34% of total Pb with the highest 

20 concentrations being found in the largest and smallest size fractions. Pb(CO3)2 and Pb(OH)2 were 

21 measured in the two middle size fractions whilst PbO and PbSO4 were present in the largest and smallest 

22 size fractions (Barrett et al., 2010). 

23 Murakami et al. (2007) also emphasized the importance of PbCrO4 as an important species of Pb 

24 from road surfaces using , identified individual particles containing high levels of Pb and Cr (≥ 0.2%), 

25 most likely from the yellow road line markings. The identified PM constituted 46% of Cr and Pb in heavy 

26 traffic dust and 7-28% in dust from residential areas and soakaway sediments. The presence of such 

27 particles in soakaway sediments is consistent with their low environmental solubility.

28 Recent research also continues to document the first flush effect described in the 2006 Pb AQCD. 

29 Flint and Davis (2007) reported that in 13% of runoff events, more than 50% of Pb was flushed in the first 

30 25% of event water. A second flush occurred less frequently (4% of runoff events for Pb). In agreement 

31 with the 2006 Pb AQCD (U.S. EPA, 2006), most recent studies have concluded that, during storm events, 

32 Pb is transported together with large PM. Some studies, however, found that Pb was concentrated in the 

33 fine PM fraction and, occasionally, Pb was found predominantly in the dissolved fraction. Tuccillo (2006)

34 found that Pb was almost entirely in the >5 μm size range and, indeed, may be associated with PM larger 

35 than 20 μm. (J. Sansalone et al., 2010) compared Pb-containing PM size distributions from New Orleans,

36 LA; Little Rock, AR; North Little Rock, AR; and Cincinnati, OH and found no common distribution 
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1 pattern. Pb was associated with Cincinnati PM mainly in the <75 μm fractions, at Baton Rouge and Little 

2 Rock Pb mainly in the 75-425 μm PM fractions, and at North Little Rock Pb predominantly in the 

3 >425 μm PM fractions. New Orleans Pb was almost uniformly distributed among the smaller size PM 

4 fractions. McKenzie et al. (2008) found that Pb was enriched in the finest PM (0.1-0.3 μm) in stormwater 

5 samples collected in California, particularly for storms that occurred during and after an extended dry 

6 period. 

7 Guo et al. (2006) investigated the effect of engineered partial exfiltration reactor (PER) systems on 

8 the partitioning and speciation of Pb in rainfall-runoff at the upstream end of an urban source area 

9 catchment that is part of the much larger urbanized and industrial Mill Creek watershed in Hamilton 

10 County, Ohio. The catchment is paved to a large extent with asphalt and is used for transportation. Guo et 

11 al. (2006) investigated a catchment that drained towards a wide grassy area and found that Pb was mainly 

12 associated with dissolved organic matter (DOM). The study suggested that interaction of the rainfall13 runoff with the grassy area may have resulted in removal of PM-bound Pb and hence in the association of 

14 Pb with DOM. PM amount and size can also be influenced by the runoff surface. Guo et al. (2006) found 

15 that Pb entering the engineered PER system was mainly in the dissolved fraction with ~76%. 

16 There were several recent observations of a relationship between road traffic volume and runoff Pb 

17 concentration, although a clear relationship was not always observed. At a relatively clean location, Desta 

18 et al. (2007) studied highway runoff characteristics in Ireland and found that although as expected, Pb was 

19 strongly correlated with TSP, no relationship between total suspended solids and rainfall, rain intensity, 

20 antecedent dry days or runoff event duration were observed, and traffic volume also did not appear to 

21 have an effect They concluded that runoff composition from site to site could be highly variable. Most 

22 other studies, however, did find a relationship between traffic volume and Pb concentration. A California 

23 study of highway runoff by Kayhanian et al. (2007) reported that 70-80% Pb was in PM form for both 

24 non-urban and urban highways, and that the concentration of Pb in runoff from low traffic flow (30,000-

25 100,000 vehicles/day) urban highways was 50% higher than that from non-urban highways (mean =

26 16.6 μg/L). Additionally, the concentrations in runoff from high traffic flow (>100,000 vehicles/day) 

27 urban areas were five times higher than those from non-urban highways. Helmreich et al. (2010)

28 characterized road runoff in Munich, Germany, with an average daily traffic load of 57,000 vehicles. The 

29 mean Pb concentration, 56 μg/L (maximum value = 405 μg/L), lay in between the values for low traffic 

30 flow and high traffic flow runoff from urban areas in California, i.e., there was good agreement with

31 Kayhanian et al. (2007). There was no detectable dissolved Pb, i.e. 100% in PM form. Seasonal effects of 

32 highway runoff have also been observed recently. Hallberg et al. (2007) found that summer Pb 

33 concentrations in runoff water in Stockholm ranged from 1.37-47.5 μg/L while, in winter, the range was 

34 1.06-~296 μg/L. There was a strong correlation between Pb (and most other elements) and total 

suspended solids (R2 35 = 0.89). Helmreich et al. (2010) also found higher metal concentrations during cold 

36 seasons in Stockholm but Pb concentrations increased only slightly during the snowmelt season. There 
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1 was no change in the distribution of Pb between dissolved and PM forms for the rain and snowmelt 

2 periods. Runoff from urban snowmelt has been intensively investigated since the 2006 Pb AQCD was 

3 published (U.S. EPA, 2006). The relocation of snow means that the area receiving the snowmelt is not 

4 necessarily the same area that which received the snowfall. Magill and Sansalone (2010) also noted that 

5 plowed snowbanks alongside roadways form a temporary linear reservoir for traffic generated 

6 constituents such as metals and PM. Snowmelt concentrations of metals such as Pb can therefore be 

7 several orders of magnitude higher than those in rainfall runoff (J. J. Sansalone & Buchberger, 1996). The 

8 melt process usually occurs in a sequence: pavement melt, followed by roadside (impervious) and finally 

9 pervious area melt. As part of this sequence, rain-on-snow can transport high loads of PM-associated 

10 pollutants (Oberts, 2000). Westerlund and Viklander (2006) investigated differences in PM and Pb 

11 concentrations between rainfall events occurring during snowmelt and rain periods. Runoff events 

12 occurring during the snowmelt period (i.e. rain-on-snow) had about five times higher numbers of particles 

13 (in the size range 4 to 120 μm)/liter of runoff. The first rain-on-snow event was characterized by an 

14 increase in the number of particles in the 4 to 25 μm size range. The rain-on-snow gave a “flush” through 

15 the snow but this was still not sufficient to transport the larger sized particles. Only the highest energy 

16 rain-on-snow events increased transport of PM across the entire size spectrum. There was no difference in 

17 particle size distributions between snowmelt and rain on snow events, although more was transported 

18 during snowmelt. Pb concentrations were most strongly associated with the smaller PM size fractions.

19 Overall, there was a significant difference between the melt period and the rain period in terms of 

20 concentrations, loads, transportation and association of heavy metals with particles in different size 

21 fractions (Westerlund & Viklander, 2006). Over a 4-year period, Magill and Sansalone (2010) analyzed 

22 the distribution of metal in snow plowed to the edge of roads in the Lake Tahoe catchment in Nevada, and 

23 concluded that metals including Pb were mainly associated with coarser PM (179-542 μm). The PM24 associated metal could be readily separated from runoff water (e.g., in urban drainage systems), but there 

25 is potential for leaching of metals from the PM within storage basins (Ying & Sansalone, 2008). For 

26 adsorbed species that form outer sphere complexes, a decrease in adsorption and an increase in aqueous 

27 complexes for pollutant metals is a likely consequence of higher deicing salt concentrations. If metals 

28 form inner-sphere complexes directly coordinated to adsorbent surfaces, background deicing salt ions 

29 would have less impact. It is thought that physical and outer-sphere complexes predominate for coarse 

30 PM, as was the case in Nevada, and so leaching would be likely to cause an increase in dissolved phase 

31 Pb concentrations.

32 Rural runoff has also been extensively studied since publication of the 2006 Pb AQCD (U.S. EPA, 

33 2006), including several recent publications on a forested watershed (Lake Plastic) in central Ontario

34 (Landre et al., 2009, 2010; Watmough & Dillon, 2007) and nearby Kawagama Lake, Canada (Shotyk & 

Krachler, 2010). Results indicated that bulk deposition substantially decreased to 0.49 mg/m2 35 in 2002 

from 1.30-1.90 mg/m2 36 in 1989-91. The upland soils retained >95% of the Pb in bulk deposition, i.e. 
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1 leaching losses to stream water were small. The wetland area was, however, a net source of Pb with 

2 annual Pb concentrations in stream water ranging from 0.38 to 0.77 μg/L. Lake sediments were efficient 

3 sinks for atmospherically deposited Pb with 80-91% of the Pb input being retained. Up to 68% of the Pb 

4 entering the lake was derived from the terrestrial catchment. Overall, the watershed effectively retained

5 atmospherically deposited Pb, but some Pb was then redistributed from the catchment to the lake 

6 sediments; and the Pb in the near-surface lake sediments reflected terrestrially transported soil material,

7 rather Pb being deposited from the atmosphere. The highest concentrations of dissolved organic carbon

8 (DOC), Fe and Pb in the wetland draining stream occurred in summer when it frequently exceeded 1 μg/L 

9 (Landre et al., 2009).

10 Graham et al. (2006) observed two temporally separated mechanisms occurring during storm 

11 events in a rural organic rich upland catchment. At the beginning of an event, Pb was transported together 

12 with large particles in the >25 μm size range, but after several hours Pb was mainly transported with 

13 colloidal or DOM (<0.45 μm), and the remaining 30-40% of storm related Pb was transported in this 

14 form. This indicated that rapid overland flow rapidly transported Pb-PM into the receiving streams at the 

15 very beginning of the event, and this was followed within a few hours by transport of organic-colloidal Pb 

16 via near-surface throughflow. The authors used a conservative estimate of Pb removal, based on their 

17 observations that the catchment was continuing to act as a sink for Pb. These observations about the 

18 transport and fate of Pb agree well with those of Watmough and Dillon (2007) and Shotyk et al. (2010).

19 Soil type was also found to have a strong influence on runoff contributions. Dawson et al. (2010)

20 found that for organic-rich soils, Pb was mobilized from near-surface soils together with DOC but for 

21 more minerogenic soils, percolation of water allowed Pb, bound to DOC, to be retained in mineral 

22 horizons and combine with other groundwater sources. The resulting Pb in stream water that had been 

23 transported from throughout the soil profile and had a more geogenic signature (Dawson et al., 2010). The 

24 findings of both Graham et al. (2006) and Dawson et al. (2010) were important because the provenance 

25 and transport mechanisms of Pb may greatly affect the net export to receiving waters, particularly since 

26 higher concentrations of previously deposited anthropogenic Pb are usually found in the near-surface 

27 sections of upland U.K. soils (e.g., (Farmer et al., 2005)).

28 In another study Rothwell et al. (2007) observed stormflow Pb concentrations almost three times 

29 higher than those reported by Graham et al. (2006) for northeastern Scotland. The generally high 

30 dissolved Pb stores and high stream water DOC concentrations (Rothwell, Evans, Daniels, et al., 2007). 

31 In a separate study, Rothwell et al. (2007) showed that OM was the main vector for Pb transport in the 

32 fluvial system. Some seasonal variability was observed: declining Pb concentrations in autumn stormflow 

33 may indicate the exhaustion of DOC from the acrotelm (the hydrologically active upper layer of peat 

34 which is subject to a fluctuating water table and is generally aerobic) or a dilution effect from an 

35 increasing importance of overland flow. 
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1 Erosion of agricultural soils and the effects of different types of storm events on soil particle and Pb 

2 losses from these soils was characterized by Quinton and Catt (2007). A close link between metal 

3 concentration and the silt, or clay and organic content of stream sediments was consistent with enrichment 

4 of metals as a consequence of small erosion events. They also noted that short intense events could 

5 produce the same amount of sediment as longer low-intensity events. More intense events, however, 

6 could mobilize a wider range of particle sizes whereas low intensity events mobilized finer but more 

7 metal-rich material. Smaller events accounted for 52% of Pb losses from the agricultural soil.

8 The Tinto River in Spain drains one of the largest polymetallic massive sulfide regions in the 

9 world: the Iberian Pyrite Belt. Evaporitic sulfate salts, formed as a result of acid mine drainage processes, 

10 are considered to be a temporary sink for many heavy metals. Upon the arrival of rainfall, however, they 

11 rapidly dissolve, releasing acidity and contaminant metals into receiving waters. Thus rivers in semi-arid 

12 climate regions such as the Tinto River which alternate between long periods of drought and short but 

13 intense rainfall events, can experience quick acidification and increases in metal concentration. In a study 

14 of such events, Cánovas et al. (2010) found that while many element concentrations decreased during 

15 events, the concentrations of Fe, Cr, Pb and As increased. This was attributed to the redissolution and 

16 transformation of Fe oxyhydroxysulfates and/or desorption processes. 

17 Several investigators considered a Pb isotope study by Dunlap et al. (2008) of a large 

(>160,000 km2 18 ) riparian system (the Sacramento River, CA), which showed that the present day flux of 

19 Pb was dominated by Pb from historical anthropogenic sources, which included a mixture of high-ratio 

20 hydraulic Au mining-derived Pb and persistent historically-derived Pb from leaded on-road gasoline. 

21 Outside of the mining region, 57-67% Pb was derived from past on-road gasoline emissions and 33-43% 

22 was from hydraulic Au mining sediment. The flow into the Sacramento River from these sources is an 

23 ongoing process. Periods of high surface runoff, however, mobilize additional fluxes of Pb from these two 

24 sources and carry them into the river. These pulses of Pb, driven by rainfall events, suggest a direct link 

25 between local climate change and transport of toxic metals in surface waters (Dunlap et al., 2008).

26 Rothwell et al. (2007) commented that although there have been substantial reductions in sulfur 

27 deposition to U.K. uplands over the last few decades (Fowler et al., 2005), anthropogenic acidification of 

28 upland waters is likely to continue due to nitrogen leaching from the surrounding catchment and this may 

29 increase with nitrogen saturation (Curtis et al., 2005). Rothwell et al. (2007) predicted that if an increase 

30 in surface water acidification is coupled with further increases in DOC export from organic-rich 

31 catchments, metal export from peatland systems will increase. The deterioration of peat soils by erosion is 

32 considered to be exacerbated by climatic change. Rothwell et al. (2010) used digital terrain analysis to 

33 model suspended Pb concentrations in contaminated peatland catchments. The peat soils of the Peak 

34 District are characterized by extensive eroding gullies and so they were combined in an empirical 

35 relationship between sediment-associated Pb concentrations and mean upslope gully depth with fine-
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1 resolution mapping of the gully areas. This model will enable prediction of metal contamination in

2 receiving waters.

3 Klaminder et al. (2010) investigated the environmental recovery of sub-arctic lakes in response to 

4 reduced atmospheric deposition over the last few decades. They found that there had been no 

5 improvement in surface sediments and indeed the reduction in Pb contamination had been much less than 

the 90% reduction in emissions over the last four decades. The weak improvement in the 206Pb/

207 6 Pb ratio 

7 together with the Pb contaminant concentrations suggests that catchment export processes of previously8 deposited atmospheric contaminants have had a considerable impact on the recent contaminant burden of 

9 sub-arctic lakes. In Arctic regions, soil export of contaminants to surface waters may dramatically 

10 increase in response to climate change if it triggers thawing of frozen soil layers. It is thought that 

11 thawing may generate accelerated soil erosion, altered hydrological flow paths, increased runoff and 

12 exposure of soluble compounds that had previously been in the frozen layers. At this stage, however, the 

13 links between catchment export and climate change have not yet been clearly established.

14 Coynel et al. (2007) also considered the effects of climate change on heavy metal transport. In this 

15 case, the scenario of flood-related transport of PM in the Garonne-Gironde fluvial-estuarine system was 

16 investigated. Export of suspended PM during a five-day flood in December 2003 was estimated at 

17 ~440,000 tons, accounting for ~75% of the annual suspended PM fluxes. Sediment remobilization 

18 accounted for ~42% of the total SPM flux during the flood event (~185,000 tons suspended PM) and 

19 accounted for 61% of the 51 tons Pb that was exported. Coynel et al. (2007) postulate that flood hazards 

20 and transport of highly polluted sediment may increase as a result of climate change and/or other 

21 anthropogenic impacts (flood management, reservoir removal).

22 In heavily contaminated catchments (e.g., that of the Litavka River, Czech Republic (Zak et al., 

23 2009)), the flux of heavy metals to the river during storm events can be substantial. Even during a minor 

24 4-day event, 2,954 kg of Pb was transported, and the majority was associated with suspended PM. For the 

25 Adour River in a mountainous area of France, Pb pollution predominantly originated from mining 

26 activities, and Point et al. (2007) showed that 75% of annual soil fluxes into the river were transported in 

27 30-40 days. 

28 The consequences of flood management (dam flushing) practices on suspended PM and heavy 

29 metal fluxes in a fluvial-estuarine system (Garonne-Gironde, France) were considered by Coynel et al. 

30 (2007). Dam flushing enhanced mobilization of up to 30-year-old polluted sediment from reservoir lakes. 

31 Sediment remobilization accounted for ~42% of the total suspended PM fluxes during the flood and 

32 strongly contributed to PM-bound metal transport (61% for Pb). They concluded that flood management 

33 will need to be taken into consideration in future models for erosion and pollutant transport.

34 Bur et al. (2009) investigated the associations of Pb in stream-bed sediments of the French 

35 Gascony region. They found that Pb enrichment in stream sediments was positively correlated with 

36 catchment cover and increasing organic content whereas Pb concentration was strongly linked with Fe-
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1 oxide content in cultivated catchments. For the low-OM, anthropogenic Pb was associated with 

2 carbonates and Fe-oxides (preferentially, the amorphous fraction). Fe-oxides became the most efficient 

3 anthropogenic Pb trapping component as soon as the carbonate content is reduced. They noted, however, 

4 that OM was always weakly involved. N’Guessan et al. (2009) also studied trace elements in stream-bed 

5 sediments of the French Gascony region. They used enrichment factors to show that only ~20-22% of Pb 

6 was from anthropogenic sources with the remainder originating from natural weathering processes.

7 Overall, research results from the last several years have greatly expanded the extent of the

8 knowledge concerning Pb from runoff. Substantial Pb input to estuarine and marine ecosystems has been

9 well documented. More detail concerning the origin of Pb from roof runoff has led to the conclusion that 

10 roof flashing could be especially important. Research on road runoff has provided valuable insight into 

11 PM size and composition, indicating that size distributions for Pb-containing PM in runoff water varies 

12 from study to study and from location to location, and that Pb is frequently associated with chromate near 

13 roads, probably from paint used to mark road lines. Recent studies confirmed the “first flush” effect, 

14 releasing more Pb at the beginning of rainfall than subsequently, and documented size distributions of Pb15 containing PM also vary considerably when water from the first flush is isolated. Influence of road traffic 

16 volume on runoff has also been more fully documented in recent years. The role of urban snowmelt and 

17 rain-on-snow events is also better understood, and it has been observed that greater runoff occurs from 

18 snowmelt and in rain on snow events than when snow is not present, and that metals, including Pb, are 

19 often associated with coarse PM under these circumstances. Runoff in rural areas is strongly controlled by 

20 soil type and the presence of vegetation, with less runoff and greater retention in mineral soils or when 

21 grass is present, and more runoff for soils high in OM. Runoff also follows a two-step process of transport 

22 of larger particles at the beginning of an event, followed within hours by transport of finer colloidal 

23 material. Some initial research on the effects of climate change on runoff has focused on documenting the 

24 association between increased runoff and more intense rain events and greater thawing. Overall, recent 

25 research has provided greater detail on amounts, particle size distributions, composition, and important 

26 processes involving Pb transport, and the understanding of Pb runoff has become more complete since 

27 publication of the 2006 Pb AQCD (U.S. EPA, 2006).

3.3.3. Soil

28 The 2006 Pb AQCD (U.S. EPA, 2006) summarized that Pb has a relatively long retention time in 

29 the organic soil horizon, although its movement through the soil column also suggests potential for 

30 contamination of groundwater. Leaching was consistently observed to be a slower process for Pb than for 

31 other contaminants because Pb was only weakly soluble in pore water, but anthropogenic Pb is more 

32 available for leaching than natural Pb in soil. Pb can bind to many different surfaces and Pb sorption 

33 capacity is influenced by hydraulic conductivity, solid composition, OM content, clay mineral content, 
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1 microbial activity, plant root channels, animal holes, and geochemical reactions. As a result of Pb binding 

2 to soil components, leaching is retarded by partitioning to soils, which is not only influenced by sorption 

3 capacity, but leaching also increases with proximity to source, increasing pH, and increasing metal 

4 concentrations. Leaching is also strongly influenced by pore water flow rates, with more complete 

5 sorption contributing to slower leaching at lighter flows. Leaching rates are especially high in soils with a 

6 high Cl content, but typically the most labile Pb fraction is adsorbed to colloidal particles that include 

7 OM, clay, and carbonates. Transport through soils is enhanced by increasing amount of colloidal 

8 suspensions, increasing colloidal surface charge, increasing organic content of colloids, increasing 

9 colloidal macroporosity, and decreasing colloidal size. Acidity and alkalinity have a more complex 

10 influence, with sorption maximized at neutral pH between pH = 5 and pH = 8.2, and greater mobility at 

11 higher and lower pH. High Pb levels have been observed in leachates from some contaminated soils, but 

12 this effect appears to be pH dependent. In several studies of contaminated soils a substantial fraction of Pb 

13 was associated was associated with Mn and Fe oxides or carbonate. 

3.3.3.1. Deposition of Lead onto Soil from Air

14 As described in the 2006 Pb AQCD (U.S. EPA, 2006), a considerable amount of Pb has been 

15 deposited from air onto soils in urban areas and near stationary sources and mines, and soil Pb 

16 concentrations can reach several thousand mg/kg. Major sources in urban soil were identified as 

17 automotive traffic (prior to when leaded on-road gasoline was phased out), and deteriorating Pb-based 

18 paint, with the highest Pb concentrations observed where traffic and population density were the greatest. 

19 Highest concentrations were found in city centers and near roadways, and several studies reported 

20 concentrations falling off rapidly with distance and depth of soil layers near roads. High Pb soil 

21 concentrations were also observed near stationary sources such as smelters and battery disposal 

22 operations, also decreasing rapidly with distance from the source. Several recent studies continue to 

23 document high concentrations of Pb in soil. A study of soil Pb concentrations in Queensland, Australia 

24 described atmospheric transport and deposition of Pb in urban soils due to ongoing emissions from nearby 

25 mining and smelting activities are continuing to impact on the urban environment (Taylor et al., 2010) . 

26 Similarly, sediment cores from four remote Canadian Shield headwater lakes located along a transect 

27 extending 300 km from a non-ferrous metal smelter generated useful information about distance of Pb 

28 transport from the smelter prior to deposition (Gallon et al., 2006). Shotyk and Krachler (2010) postulated 

29 that long-range transport of Pb from a smelter at Rouyn-Noranda may still contribute to deposition on

30 these lakes. Recent measurements of deposition fluxes to soil in rural and remote areas have ranged from 

approximately 0.5 mg/m2·yr to about 3 mg/m2 31 ·yr with fair agreement between locations in Canada, 

32 Scandinavia, and Scotland and showed a substantial decrease compared to when leaded on-road gasoline 
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1 was in widespread use (Fowler et al., 2006; Graham et al., 2006; Shotbolt et al., 2008; Watmough & 

2 Dillon, 2007).

3 Differences between throughfall and litterfall in forested areas have also been investigated in 

4 forested areas, and the combined input of Pb to the forest floor from throughfall and litterfall was 

5 approximately twice that measured in bulk deposition (Landre et al., 2010). The difference was attributed 

6 to a substantial contribution from internal forest cycling and indicates that bulk deposition collectors may 

7 underestimate the amount of Pb reaching the forest floor by about 50% (Landre et al., 2010).

8 There has been considerable interest in the response of soils to the decreasing aerosol Pb 

9 concentrations and Pb deposition rates that have been recorded in recent years. Kaste et al. (2006)

10 resampled soils at 26 locations in the Northeast U.S. (during a 2001-2002 survey of soil sites originally 

11 sampled in 1980), and found no significant change in the amount of Pb in the O-horizon at high altitude 

12 sites. However, the amount of Pb in the O-horizon had decreased at some locations in the southern part of 

13 the survey region (Connecticut, New York, Pennsylvania), where the forest soils have typically thinner 

14 O-horizons, the reasons for which are discussed further in Section 3.3.3.2. Higher Pb concentrations at 

15 greater altitudes were also found in Japan, especially above 600 m (Takamatsu et al., 2010). 

16 There is wide agreement that atmospheric deposition due to long-range transport from industrial 

17 areas has been the major source of Pb to remote surface soils over the past decades, e.g. (Steinnes et al., 

18 2005). However, another hypothesis proposes that the gradual increase in Pb content in O-horizon soil 

19 with changing latitude is attributable to “plant pumping and organic binding” rather than to atmospheric 

20 deposition (Rasmussen, 1997; Reimann et al., 2008; Reimann et al., 2001). 

21 Further support for the use of mosses as bioindicators or monitors for atmospheric Pb inputs to peat 

22 bogs have recently been published by Kempter et al. (2010) who found that high moss productivity did 

23 not cause a dilution of Pb concentrations, and that productive plants were able to accumulate more 

24 particles from the air and that rates of net Pb accumulation by the mosses were in excellent agreement 

25 with the fluxes obtained by direct atmospheric measurements at nearby monitoring stations. In addition, 

26 Bindler et al. (2008) used Pb isotopes to compare the distribution of Pb in the forest soils with that of lake 

27 sediments where no “plant pumping” processes could be invoked, and used Pb isotope ratios to 

28 demonstrate that observations were consistent with anthropogenic Pb deposition to the soils rather than 

29 intermixing of natural Pb from underlying mineral soil horizons. 

30 Overall, recent studies provided deposition data that was consistent with deposition fluxes reported 

31 in the 2006 Pb AQCD (U.S. EPA, 2006), and demonstrated consistently that Pb deposition to soils has 

32 decreased since the phase-out of leaded on-road gasoline. Additional research highlighted the importance 

33 of taking forest cycling and litter throughput account in estimating input by deposition. Follow-up studies 

34 in several locations indicated little change in soil Pb concentrations since the phase-out of leaded on-road 

35 gasoline, consistent with the high retention reported for Pb in soils. Finally, although there has been 

36 considerable discussion of plant pumping as an alternative hypothesis for explaining the increases in soil 
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1 concentrations, much evidence is more consistent with atmospheric deposition as the explanation for 

2 observed increases in soil Pb concentration.

3.3.3.2. Sequestration of Lead from Water to Soil

3 The 2006 Pb AQCD described Pb as being more strongly retained in soil than other metals because 

4 of its weak solubility in pore water, but that anthropogenic Pb was more available for leaching than 

5 natural Pb (U.S. EPA, 2006). It also described a complex variety of factors that influence Pb retention, 

6 including hydraulic conductivity, solid composition, OM content, clay mineral content, microbial activity, 

7 plant root channels, geochemical reactions, colloid amounts, colloidal surface charge, and pH. 

8 Recent research in this area has provided more insight into the details of the Pb sequestration 

9 process. Importance of leaf litter was further investigated, and it was observed that the absolute Pb 

10 content can be substantial because rain events cause splashing of the leaf litter with soil thus placing the 

11 litter in direct contact with soil metals. The resulting increase in leaf litter metal concentrations suggests

12 that the litter can act as a temporary sink for metals from the soil around and below leaves on the ground. 

13 The low solubility of Pb in the leaf litter indicates that the Pb is tightly bound to the decomposing litter, 

14 making the decomposing leaves act as an efficient metal storage pool (Scheid et al., 2009).

15 New research has also provided details about the complexity of Pb sequestration during soil OM 

16 decomposition. Schroth et al. (2008) investigated Pb sequestration in the surface layer of forest soils and 

17 the transformation of Pb speciation during soil OM decomposition. The pH range for forest floor soils in 

18 the Northeast U.S. is typically 3.5-5 and, under these conditions, dissolved Pb would adsorb strongly to 

19 soluble OM and to Fe/Al/Mn oxides and oxyhydroxides. It had been thought that the high affinity of Pb 

20 for organic ligands meant that sequestered atmospheric Pb would be preferentially bound to soluble OM. 

21 As a consequence, decomposition of OM would lead to Pb migration to the underlying mineral layers 

22 where it would be precipitated with the dissolved OC or adsorbed to pedogenic mineral phases. However, 

23 recent research has revealed a more complicated picture of gasoline-derived Pb associations in the forest 

24 floor. More recent research indicates that, as decomposition progresses, Pb and Fe become more 

25 concentrated in “hotspots” and Pb likely becomes increasingly distributed on surfaces associated with Fe 

26 and Mn (and to some extent Ca). It was postulated that Pb was initially bound to labile organic but, 

27 following decomposition, the Pb was adsorbed at reactive sites on pedogenic mineral phases (Schroth et 

28 al., 2008). Differences in litter types were also reported, with more rapid decomposition of OM in high 

29 quality deciduous litter mobilizing more Pb initially bound to labile OM than coniferous litter, and 

30 producing more pedogenic minerals that could readily sequester the released Pb (Schroth et al., 2008). In 

31 the next stage of the study, the speciation of Pb in the O-horizon soils of Northern Hardwood, Norway 

32 spruce and red pine forest soils were compared. In general there was good agreement between the Pb 

33 speciation results for the soils and those for the laboratory decomposition experiments. Specifically, for 
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1 the Northern Hardwood forest soil, a little more than 60% of the Pb was bound to SOM and this 

2 percentage increased to ~70% and ~80% for the Norway spruce and red pine soils, respectively. In all 

3 three cases, however, most of the remainder of the Pb was bound to ferrihydrite rather than to birnessite. 

4 This was not considered to be surprising because of the well-known leaching and cycling behavior of Mn 

5 that would be expected in the natural system. Thus the prevalence of Mn phases in the field based 

6 samples would be lessened (Schroth et al., 2008). 

7 More generally, other studies have observed Pb sorption to Mn and Fe phases in soils. For example, 

8 Boonfueng et al. (2006) investigated Pb sequestration on Mn oxide-coated montmorillonite. Pb formed 

9 bidentate corner-sharing complexes. It was found that Pb sorption to MnO2 occurred even when MnO2

10 was present as a coating on other minerals, e.g., montmorillonite. Although their importance in the near11 surface phases has clearly been demonstrated by Schroth et al. (2008), ferrihydrite surfaces may not be a 

12 long-term sink for Pb since reductive dissolution of this Fe(III) phase may release the surface-bound Pb 

13 into the soil solution. Sturm et al. (2008) explored the fate of Pb during dissimilatory Fe reduction. Pb 

14 was indeed released but was then incorporated into less reactive phases. These phases could not, however, 

15 be identified. Even so, it was asserted that Pb should be largely immobile under Fe-reducing conditions 

16 due to its incorporation into refractory secondary minerals. 

17 Kaste et al. (2006) found that Pb species currently in the O soil horizons in the Northeast U.S. 

18 differed considerably from those that were originally deposited from fossil fuel combustion (including on19 road gasoline). PbSO4 was considered to be the main form of Pb that had been delivered from the 

20 atmosphere to the surface of the Earth and it was postulated that the presence of sulfate may have 

21 facilitated the adsorption of Pb to colloidal Fe phases within the organic-rich horizons. 

22 Altogether, these new results enhance the understanding of Pb sequestration in forest soils. First, 

23 the role of leaf litter as a major Pb reservoir is better understood. Second, the effect of decomposition on 

24 Pb distribution and sequestration on minerals during OM decomposition has been further characterized, 

25 and finally, the relative importance of Mn and Fe in sequestration is better understood.

26 Recent research also addressed roadsides soils. Jensen et al. (2006) found that Pb was retained by 

27 an organic-rich blackish deposit with a high OM content and elevated soil Pb concentrations, originating 

28 from total suspended solids in road runoff and from aerial deposition. Hossain et al. (2007) observed that 

29 after long dry periods, OM oxidation may potentially result in the release of Pb. Microbial activity may 

30 also breakdown OM and have similar consequences (i.e., Pb release). Bouvet et al. (2007) investigated the 

31 effect of pH on retention of Pb by roadside soils where municipal solid waste incineration (MSWI) 

32 bottom ash had been used for road construction. They found that the Pb that had leached from the road 

33 construction materials was retained by the proximal soils under the prevailing environmental conditions 

34 (at pH = 7, <2% was released, but at pH = 4, slightly more Pb (4-47%) was released) and the authors 

35 speculated that the phase from which Pb had been released may have been Pb(CO3)2(OH)2, indicating that 
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1 sequestration of Pb via formation of oxycarbonate minerals is only effective at near-neutral to alkaline pH 

2 values (Figure 3-10 in Section 3.3.3.3). 

3 Other recent research on Pb sequestration focused on microbial impacts and soil amendments. 

4 There have been few if any previous observations of microbial sequestration of Pb in soil. Perdrial et al. 

5 (2008) observed bacterial Pb sequestration and proposed a mechanism of Pb complexation by 

6 polyphosphate. They also postulated that bacterial transport of Pb could be important in sub-surface soil 

7 environments. Wu et al. (2006) also and concluded that Pb adsorption to the bacterial cell walls may be 

8 important with respect to Pb transport in soils. This new area of research provides important evidence that 

9 bacteria can play an important role in both sequestration and transport of Pb. Phosphate addition to 

10 immobilize Pb-contaminated soils has often been used to immobilize Pb in situ through the formation of 

11 Pb phosphate minerals such as chloropyromorphite. Recent research investigated factors affecting the

12 long-term stability of such products, which depends on the equilibrium solubility and the dissolution rate 

13 of the mineral, trace impurities, such as Pb(OH)2, the presence of complexing agents, and pH (Xie & 

14 Giammar, 2007). Overall, in agreement with the 2006 Pb AQCD (U.S. EPA, 2006), the addition of 

15 phosphate can enhance immobilization of Pb under certain conditions in the field but may cause 

16 desorption and mobilization of anionic species of As, Cr and Se.

3.3.3.3. Movement of Lead within the Soil Column

17 The 2006 Pb AQCD summarized studies that demonstrated that Pb has a long retention time in the 

18 organic soil horizon, it also has some capacity to leach through the soil column and contaminate 

19 groundwater more than other contaminants do, because Pb is only weakly soluble in pore water (U.S. 

20 EPA, 2006). The fate of any metal transport in soil is in response to a complex set of parameters including 

21 soil texture, mineralogy, pH and redox potential, hydraulic conductivity, abundance of OM and 

22 oxyhydroxides of Al, Fe, and Mn, in addition to climate, situation and nature of the parent material. As a 

23 consequence, it is impossible to make general conclusions about the final fate of anthropogenic Pb in 

24 soils. Indeed, Shotyk and LeRoux (2005) contend that the fate of Pb in soils may have to be evaluated on 

25 the basis of soil type. Some generalizations are, however, possible: Pb migration is likely to be greater 

26 under acidic soil conditions (Shotyk & Le Roux, 2005). In this respect, it would be expected that there 

27 should be considerable mobility of Pb in the surface layers of certain types of forest soils. This section 

28 reviews recent research on movement of Pb through soil types by first focusing on forest soils, followed 

29 by a broader treatment of a more diverse range of soils.

Forest Soils and Wetlands

30 Several studies confirmed the slow downward movement of Pb within the soil column. Kaste et al. 

31 (2006) found that the amount of Pb in O-horizon soils had remained constant at 15 of 26 sites in remote 
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1 forested areas of the Northeast U.S. that had been re-sampled after a 21-year time period had elapsed, but 

2 that measured soil Pb concentrations were lower than predicted concentrations from total deposition, 

3 strongly suggesting that the O-horizon had not retained all of the atmospheric Pb, and that a proportion of 

4 the atmospheric deposition must have leached into the underlying mineral layers. At some sites, mainly 

5 those at the southern latitudes and lower altitude sites, the proportion of Pb that had been leached 

6 downward from the O-horizon was quite considerable. Relative retention of Pb was influenced by the rate 

7 of OM decomposition, depth of soil O-horizon, and pH. For soils where Pb was strongly retained by the 

8 O-horizon, a relationship between Pb and Fe-rich phase was observed, but Pb was also significantly 

9 correlated with other metals. XANES data suggested a possible interaction with an amorphous Fe oxide, 

10 but spectra were not entirely explained by Fe and oxygen and an additional spectral feature suggested the 

11 presence of a S or P atom, which could result if OM functional groups were binding to Pb. Kaste et al. 

12 (2006) concluded that a substantial fraction of Pb was associated with amorphous Fe-hydroxides. The 

13 strong binding of Pb coupled with the low solubility of Fe phases under oxic conditions, helped to explain 

14 the relatively long residence time of gasoline-derived Pb in forest floors which had thick O-horizons and 

15 were well-drained. In the situations where Pb was leached downward to a large extent, mobility was 

16 likely governed by OM decomposition and colloidal transport of Pb associated with colloidal Fe and OM. 

17 Klaminder et al. (2006) also considered the transfer of Pb from the O-horizon to the underlying 

18 mineral horizons (including the C-horizon). They concluded that atmospheric pollution-derived Pb 

19 migrated at a rate about 10-1,000 times slower than water. They assumed that Pb was mainly transported 

20 by dissolved OM and so the mean residence time of Pb in the O-horizon depended on OM transport and 

21 turnover. The retardation rate was a reflection of the slow mineralization and slow downward transport 

22 rates of organic-Pb complexes, due to sorption and desorption reactions involving mineral surfaces.

23 In a study involving stable Pb isotopes, Bindler et al. (2008) showed that Pb with a different 

24 isotopic composition could be detected in the soil down to a depth of at least 30 cm and sometimes down 

25 to 80 cm in Swedish soils. In comparison, in North American podzols, pollution Pb is typically only 

26 identified to a depth of 10-20 cm (even with the aid of isotopes). This difference is attributed to the longer 

27 history of metal pollution in Europe (as has been traced using lake sediments).

28 Several research groups have attempted to determine the mean residence time of Pb in the 

29 O-horizon of forest soils. Klaminder et al. (2006) used three independent methods to estimate a mean 

30 residence time of about 250 years for Pb in the O-horizon of boreal forests in Sweden, indicating that 

31 deposited atmospheric Pb pollution is stored in the near-surface layers for a considerable period and, 

32 consequently, will respond only slowly to the reduction in atmospheric inputs. It should be noted, 

33 however, the OM in the upper parts of the O-horizon is continually being replaced by fresh litter and the 

34 mean residence time of Pb in these horizons is only 1-2 years. Thus, the uppermost layer will respond 

35 more quickly than the rest of the O-horizon to the decreases in Pb inputs.
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1 Klaminder et al. (2008) considered the biogeochemical behavior of atmospherically derived Pb in 

2 boreal forest soils in Sweden (Figure 3-10). The estimated annual losses via percolating soil water were 

~2 mg/m2 3 ·yr (Klaminder, Bindler, & Renberg, 2008) and so the annual loss, assumed to be from the mor 

layer, was greater than the atmospheric input of ~0.5 mg/m2 4 ·yr. The upward transport of Pb did not 

5 compensate for the losses either. In contrast, the amount of Pb being stored in the mineral soil layers was 

6 increasing. The mean residence time of Pb in the mor layer was estimated to be ~300 years, in reasonable 

7 agreement with their earlier work (Klaminder, Bindler, Emteryd, et al., 2006). These values were greater 

8 than the values of 2-150 years determined for U.S. forest soils, e.g. (J. Kaste et al., 2003; Watmough et 

9 al., 2004) but the difference was attributed to the lower decomposition rates of OM within the northern 

10 boreal forests of Sweden. They concluded that more research was needed to determine the processes 

11 occurring within the mor layer that control the release of Pb from this horizon.

Figure 3-10. Schematic model summarizing the estimated flux of Pb within 

a typical podzol profile from northern Sweden using data from 

Klaminder et al. (2006).The atmospheric deposition rate is 

from (Klaminder, Bindler, Emteryd, et al., 2006), the plant 

uptake rates from (Klaminder et al., 2005) and estimated soilwater fluxes from (Klaminder, Bindler, Laudon, et al., 2006).
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1 Klaminder et al. (2008) investigated in more detail the distribution and isotopic signature of Pb 

2 persisted within the O-horizon (mor layer) of boreal forest soils. They found that the mor layer preserved 

3 a record of past Pb emissions from a nearby smelter. Minimal animal burrowing activity and low leaching 

4 rates observed at the sampling location were important factors contributing to the preservation of this 

5 record. They concluded that temporal changes in atmospheric fallout in addition to adsorption processes 

6 need to be considered when interpreting Pb concentrations changes within the mor layer.

7 Significantly higher O-horizon Pb concentrations have been observed in coniferous than deciduous 

8 forest soils (McGee et al., 2007). Steinnes et al. (2005) noted evidence for downward migration of Pb 

9 from the O-horizon to the E-horizon of most soils and in some cases the upper B horizon. They found that 

10 the downward transport of Pb differed considerably between the sites, e.g., from almost no anthropogenic 

11 Pb in the B-horizon at some sites to ~70% at other sites. The greater downwards transport in some 

12 locations was attributed to climatic variations, with more extensive leaching and possibly a greater 

13 turnover of OM at sites where higher mean annual temperatures were experienced. Higher atmospheric 

14 deposition of acidifying substances in these locations was considered the most important factor in Pb 

15 transport, causing release of Pb from exchange sites in the humus layer and promoting downward 

16 leaching. 

17 Seasonal variation in Pb mobility has also been observed in forest soil. Other research indicated

18 that Pb concentrations correlated with DOC concentrations in the soil solution from the O-horizon, and

19 were lower during late winter and spring compared with summer months (Landre et al., 2009). The 

20 degradation of OM in the O-horizon produced high DOC concentrations in the soil solution. It was also 

21 shown that Pb was associated with the DOC, and concluded that DOC production is a primary factor 

22 enhancing metal mobility in this horizon. In the underlying mineral horizons, DOC concentrations 

23 declined due to adsorption and cation exchange processes. The B-horizon retained most of the DOC

24 leached from the O-horizon and it has also been observed that Pb is similarly retained. 

Non-forested Soils

25 In contrast with forest soils, most non-forested soils are less acidic and so most studies of Pb 

26 behavior in non-forested soils have focused on Pb immobility. However, there are acid soils in some 

27 locations that are not forested. For these soils, as for forest soils, Pb mobility is weak but correlated with 

28 OM. For example, Schwab et al. (2008) observed that low molecular weight organic acids added to soil

29 enhanced Pb movement only slightly. Citric acid and tartaric acid enhanced Pb transport to the greatest 

30 degree but the extent of mobilization was only slightly higher than that attained using deionized water 

31 even at high concentrations. While the formation of stable solution complexes and more acidic conditions 

32 favored mobilization of Zn and Cd, Pb remained strongly sorbed to soil particles and so the presence of 

33 complexing agents and low pH (2.8-3.8) did not substantially enhance Pb mobility. Similarly, limited 
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1 penetration and leaching was observed in an extremely complex temperate soil profile, with highest 

2 concentrations of Pb (~80 mg/kg) found in the top 0-5 cm section of soil. For this uppermost soil section, 

3 there was a strong correlation between Pb concentration and OC content, both for the total soil fraction 

4 and the acid-extractable fraction. The Pb migration rate was calculated to be 0.01 cm/yr and it was 

5 estimated that Pb would be retained in the soil column for 20,000 years, with no evidence of rapid 

6 movement of anthropogenic Pb from the top 0-5 cm soil section into the soil profile Kylander et al. 

7 (2008). 

8 Other recent studies also reported strong retention on non-forest soils and enhanced mobility on Fe 

9 and OM colloids. Pb was strongly retained on acidic Mediterranean soil columns, with association of Pb 

10 with the exchangeable, OM and crystalline Fe oxide fractions appearing to favor mobility while 

11 association with Mn oxides and amorphous Fe oxides was linked with semi-irreversible retention of Pb in 

12 the solid phase (Garrido et al., 2008). Pedrot et al. (2008) studied colloid-mediated trace element release 

13 at the soil/water interface and showed that Pb was mobilized by Fe nanoparticles that were bound to 

14 humic acids. 

15 Soil pH value is probably the single most important factor affecting solubility, mobility and 

16 phytoavailability but reducing conditions also results in increased Pb mobility, with the release of Pb into 

17 an anoxic soil solution due to the combined effect of Fe(III) reductive dissolution and dissolved OM

18 release. Dissolved OM is more important than Fe oxyhydroxides in determining Pb mobility. Under oxic 

19 conditions, Fe-Mn-hydroxides often play an important role in the sorption of Pb to the solid phase soil 

20 (Schulz-Zunkel & Krueger, 2009). In an agricultural soil, fate of Pb in soils is related to agricultural 

21 management. Although Pb was found to be strongly sorbed to the soil, downward migration was observed

22 and the movement of Pb to deeper soils was due to the soil mixing activities of earthworms (Fernandez et 

23 al., 2007). Thus in relatively unpolluted non-forested soils, as in forested soils, colloidal Fe and OM, pH, 

24 and biophysical transport all enhance Pb mobility in soil. Pb transport in more highly contaminated soils 

25 has also been the subject of recent research. In a vegetated roadside soil, Pb was leached from the upper 

26 50 cm of the soil even though the pH was 7.2. Pb was transported on mobile particles and colloids in the 

27 soil solution. Some of the colloids may have formed from OM produced by roots and decaying shoots. 

28 The transport process was enhanced by preferential flow triggered by intense rainfall events. This study 

29 suggested that the value of the effective sorption coefficient estimated under dynamic conditions was 

30 unrelated to values measured in conventional batch studies. This indicates that the use of batch studies to 

31 derive input values for sorption coefficients in transport models requires caution. It was concluded that 

32 the primary control of Pb transport in the long term was the degree of preferential flow in the system (S. 

33 Roulier et al., 2008).

34 Other studies also noted similarly low Pb mobility, but with substantial variation between soil types 

35 and locations. A decline in O-horizon Pb concentrations and Pb accumulation in mineral horizons was 

36 also observed for forest soils by Watmough and Dillon (2007), but did not hold for nearby wetland areas 
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1 from which a large amount of DOC is exported, with approximately 10 times more Pb being associated 

2 with a given amount of DOC in the leachate from the LFH-horizonof the wetland soil than with the DOC

3 in the stream water draining the wetland. This may reflect greater retention of Pb by the wetland and/or a 

4 change in structure of DOC leading to a change in complexing capacity possibly because of changes in 

5 pH or competition with Al and Fe. 

6 Williams et al. (2006) characterized Pb speciation in a mine waste-derived fertilizer, ironite. It was 

7 thought that PbS would be the main form of Pb, but instead was the predominant form was PbSO4, which 

8 may move more easily through soil and enter proximal waters. In contrast, Courtin-Nomade et al. (2008)

9 showed that Pb was incorporated into barite rather than goethite in waste rock pile materials. The high10 stability phase formed was an anglesite-barite solid solution.

11 In weathering flotation residues of a Zn-Pb sulfide mine were more Pb was mobile in weathered 

12 topsoil than in the unweathered subsoil. The topsoil had a very high OM content and the Pb enrichment 

13 was attributed to an interaction with soil OM. Overall, the results contrast strongly with most other 

14 studies but the interpretation was supported by the sequential extraction results which showed that there 

15 was a very large exchangeable Pb component in these surface soils (Schuwirth et al., 2007). Scheetz and 

16 Rimstidt (2009) characterized shooting range soils in Jefferson National Forest, VA, in which the metallic 

17 Pb shot rapidly became corroded and developed a coating of hydrocerussite, which dissolved at the pH 

18 values of 8-9; see Figure 3-11, which shows an Eh-pH diagram indicating the solubility, equilibrium, and 

19 stability of these corroded Pb molecules in terms of the activity of hydrogen ions (pH) versus the activity 

20 of electrons (Eh [in volts]). The solubilized Pb was largely re-adsorbed by the Fe and Mn oxides and 

21 carbonate soil fractions. The minimum solubility of hydrocerussite lies in the pH range 8-9 but solubility 

22 increases by several orders of magnitude at pH below 6 (Scheetz & Rimstidt, 2009).
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Source: Used with permission from Elsevier Publishing, Scheetz and Rimstidt (2009)

Figure 3-11. Eh-pH diagram for Pb in shooting range soils, Jefferson 

National Forest, VA.

1 Rooney et al. (2007) also investigated the controls on Pb solubility in soils contaminated with Pb 

2 shot. Again, corrosion crusts were found to develop on Pb pellets. The concentrations of Pb in the soil 

3 solution were, however, much lower than if they were controlled by the solubility of the dominant crustal 

4 Pb compounds (mainly hydrocerussite). Instead it was suggested that the concentrations were being 

5 controlled by sorption of Pb by the soil solid phase. The pH range in this study was 4.5-6.5 and so again 

6 dissolution of hydrocerussite would be expected. Sorption to solid phases in the soil is also consistent 

7 with the findings of Scheetz and Rimstidt (2009). Overall, in contrast to less polluted forested and non8 forested soils, considerable mobility was often, but not always observed in soils near roadways and mines 

9 and on shooting ranges, with colloid transport and soil pH playing an important role in Pb mobility. 

10 Although there have been steep declines in Pb deposition, surface soils in have been slow to recover 

11 (Bindler et al., 2008; J. M. Kaste et al., 2006). As was concluded in the 2006 Pb AQCD (U.S. EPA, 2006), 

12 soils continue to act as a predominant sink for Pb. 

13 While in some studies the flux of Pb, from the soil through aquatic ecosystems to lakes has peaked 

14 and declined. In other studies, no recovery of lake sediments in response to emission reductions was 

15 observed (Norton, 2007). For example, Klaminder et al. (2010) has shown that the Pb concentrations in 

16 sub-Arctic lake sediments remain unchanged in recent years, with the lack of recovery linked to the 

17 effects of soil warming, which affect Pb-OM transport from soil to the receiving lake systems. Shotyk and 

18 Krachler (2010) also reported a disconnect between atmospheric deposition and recent changes in Pb 

19 concentration and isotope ratios in the lake sediments. Simulations of future metal behavior suggest that 
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1 the more strongly sorbing metals such as Pb will respond to changes in metal inputs or acidification status 

2 only over centuries to millennia (Tipping et al., 2006).

3 Overall, recent research confirms the generally low mobility of Pb in soil. This limited mobility is 

4 strongly dependent on both colloid amount and composition, as well as pH, and may be greater in some 

5 contaminated soils. Mobility is so low that soils continue to act as a sink for atmospheric Pb even though 

6 atmospheric Pb concentrations peaked several decades ago. 

3.4. Monitoring of Ambient Lead

3.4.1. Ambient Measurement Techniques

3.4.1.1. Size-Selective PM Monitoring for Lead Concentrations

7 Ambient Pb is present in the atmosphere as PM and distributed over a wide range of PM sizes. In 

8 recognition of the role of all PM sizes in ambient air Pb exposures, including the ingestion of PM 

9 deposited onto surfaces, the indicator for the Pb NAAQS is Pb in TSP. As described in Chapter 4, 

10 ingestion of deposited Pb can be a substantial contributor to total Pb exposure. Additionally, a substantial 

11 fraction of atmospheric Pb may be associated with PM larger than 10 μm (ultracoarse PM). However, the 

12 variability of capture efficiency for TSP using current TSP samplers is considerably greater than the 

13 capture efficiency for PM10 using current PM10 samplers. For example, the symmetrical design of Federal 

14 Reference Method (FRM) samplers for PM10 makes their collection efficiency independent of wind 

15 direction, and collection efficiency is independent of wind speed under typical sampling conditions. 

16 While the collection efficiency of TSP samplers is nearly 100% for fine PM up to 5μm diameter, there is 

17 much greater variability associated with collection of larger PM (Wedding et al., 1977). For example, 

18 using the FRM for TSP, a directional difference of 45 degrees can result in a nearly two-fold difference in 

19 15 μm particle collection efficiency and a nearly five-fold difference in 50 μm particle collection 

20 efficiency (Rodes & Evans, 1985). Effective D50 (size at 50% efficiency) was observed to decrease from 

21 50 μm at a 2 km/h wind speed to 22 μm at 24 km/h (Wedding et al., 1977).

22 Recognizing the variability in capture efficiency associated with TSP samplers and the potential 

23 benefit of an indicator with lower measurement variability, the last NAAQS review considered whether 

24 the indicator for the Pb NAAQS should be revised from one based on Pb-TSP to one based on Pb-PM10. 

25 The final decision in the review was to retain the Pb-TSP indicator. The rationale for this decision 

26 included recognition of exposure due to Pb-TSP that would not be captured by PM10 sampling, the 

27 paucity of information documenting the relationship between Pb-PM10 and Pb-TSP at the broad range of 

28 Pb sources in the U.S., and uncertainty regarding the effectiveness of a Pb-PM10-based NAAQS in 

29 controlling ultracoarse Pb-PM near sources where Pb concentrations are highest (73 FR 66991). Changes 
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1 were made to the monitoring and data handling provisions, however, to allow for the siting of Pb-PM10

2 monitors for compliance purposes in locations remote from sources, where the evidence indicates that 

3 airborne Pb is predominantly in the PM10 size fraction (73 FR 66964). For Pb-PM10 monitoring to be 

4 allowed under these regulations, the maximum three-month average Pb concentration at a site must not 

exceed 0.10 μg/m3 5 over a three-year time period. Additionally, if a Pb-PM10 monitor is sited near a source, 

6 the majority of the particle-bound Pb must be smaller than 10 μm (40 CFR Part 58).

3.4.1.2. Federal Reference Method and Federal Equivalence Method Evaluation

7 For enforcement of the air quality standards set forth under the Clean Air Act, EPA has established 

8 provisions in the Code of Federal Regulations under which analytical methods can be designated as FRM 

9 or federal equivalence methods (FEM). Measurements for determinations of NAAQS compliance must be 

10 made with FRMs or FEMs. As of August 2010, 1 manual reference method and 24 manual equivalent 

11 methods had been approved for Pb (http://www.epa.gov/ttn/amtic/criteria.html). The FRM for Pb was 

12 promulgated in 1979 and is based on flame atomic absorption spectroscopy (AAS) (40 CFR Part 50). The 

13 FRM provides for collection of PM by high volume sampling and analysis of the PM for Pb by atomic 

14 absorption spectrometry. Ambient air suspended in PM is collected on a glass fiber filter for 24 hours 

15 using a high volume air sampler. The analysis of the 24-hour samples may be performed for either 

16 individual samples or composites of the samples collected over a calendar month or quarter. Pb in PM is 

17 then solubilized by extraction with nitric acid (HNO3), facilitated by heat, or by a mixture of HNO3 and 

18 hydrochloric acid (HCl) facilitated by ultrasonication. The Pb content of the sample is analyzed by atomic 

19 absorption spectrometry using an air-acetylene flame, using the 283.3 or 217.0 nm Pb absorption line, and 

20 the optimum instrumental conditions recommended by the manufacturer. Inductively-coupled plasma 

21 mass spectrometry (ICPMS) is under consideration as the new FRM for Pb-TSP.

22 PM10 monitoring can be used in limited circumstances to measure Pb concentration. (40 CFR 58). 

23 The proposed method is based on sampling requirements for an existing Federal Reference Method for 

24 the Determination of Coarse PM as PM10 – PM2.5 ("Reference Method for the Determination of Coarse 

25 Particulate Matter as PM10-2.5 in the Atmosphere," 2010), which requires a specially approved PM10C

26 sampler that meets more demanding performance requirements than conventional PM10 samplers. 

27 Ambient air is drawn through an inertial particle size separator for collection on a polytetrafluoroethylene 

28 (PTFE) filter. The analysis method for the FRM is based on x-ray fluorescence spectrometry. In addition, 

29 several FEM have been approved based on a variety of principles of operation have been approved, 

30 including: inductively coupled plasma optical emission spectrometry, or ICPMS. Specifications for Pb 

31 monitoring are designed to help states demonstrate whether they have met compliance criteria. 

32 Operational parameters required under Appendix G of 40 CFR Part 50 are listed in Table 3-3.
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Table 3-3. Specifications for Pb monitoring

Parameter Specificationa

Range 0.7-7.5 μg Pb/m3

Sensitivity 0.2-0.5 μg Pb/mL for 1% change in absorbance

Lower Detectable Limit 0.07 μg Pb/m3

a

Assumes sample volume of 2,400 m3.

Atomic Absorption Spectrometry

1 AAS is the basis for the existing FRM. Atomic absorption spectrometry was first developed in the 

2 19th century, and became widely used in the 1950s. More than 70 elements can be analyzed by AAS. 

3 Typically a liquid sample is nebulized into a flame with sufficient heat for elements to be atomized. The 

4 liquid specified by the FRM is a nitric acid extract of a glass fiber filter used for collection of suspended

5 PM with a high volume sampler. The atomized sample is then irradiated with visible light at a specific 

6 wavelength to promote an electronic transition to a short-lived excited state, resulting in absorption of the 

7 light. Elemental selectivity is achieved because light absorption is specific to a particular electronic 

8 transition in a particular element. As a result, absorption of light at a given wavelength generally 

9 corresponds to only one element. The flame is irradiated with a known quantity of light and intensity of 

10 light is measured on the other side of the flame to determine the extent of light absorption in the flame. 

11 Using the Beer-Lambert law the concentration of the element is determined from the decrease in light 

12 intensity due to sample absorption.

13 A more sensitive variation of atomic absorption spectrometry for most elements is graphite furnace 

14 atomic absorption spectrometry (GFAAS). Instead of introducing the sample into a flame, the liquid 

15 sample is deposited in a graphite tube that is then heated to vaporize and atomize the sample.

Inductively-Coupled Plasma Mass Spectrometry

16 Inductively coupled plasma mass spectrometry (ICPMS) is a sensitive method of elemental 

17 analysis developed in the late 1980s. Argon (Ar) plasma (ionized gas) is produced by transmitting radio 

18 frequency electromagnetic radiation into hot argon gas with a coupling coil. Temperatures on the order of 

19 10,000 K are achieved, which is sufficient for ionization of elements. Liquid samples can be introduced 

20 into the plasma by extracting samples in an acid solution or water, and nebulizing dissolved elements. 

21 Resulting ions are then separated by their mass to charge ratio with a quadrupole and signals are 

22 quantified by comparison to calibration standards. While solid samples can be introduced by laser 

23 ablation, nebulization of liquid extracts of PM collected on Teflon filters is more typical. One major 

24 advantage of ICPMS over AAS is the ability to analyze a suite of elements simultaneously. An additional 

25 advantage is low detection limits of 50-100 parts/trillion for Pb.
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Inductively-Coupled Atomic Emission Spectroscopy

1 Inductively coupled atomic emission spectroscopy (ICP-AES) also generates ions from elements 

2 with a hot Ar plasma, similar to ICPMS. Excited atoms and ions are produced, and these emit 

3 electromagnetic radiation with frequencies characteristic of a particular element. Intensity of emission is 

4 used to determine the concentration of an element in the sample. Elements are extracted from filter 

5 samples and nebulized into the plasma.

Energy Dispersive X-ray Fluorescence

6 In energy dispersive X-ray fluorescence spectrometry a beam of X-ray photons from an external 

7 excitation source is applied to a sample, causing ejection of inner shell electrons from elements in the 

8 sample. Because inner shell electrons have higher electron binding energies than outer shell electrons, the 

9 ejection of the inner shell electron induces an energetically favorable electronic transition of an outer shell 

10 electron to replace the ejected electron. The energy released as a result of this transition is in the form of 

11 electromagnetic radiation, corresponding to the difference in electronic binding energies before and after 

12 the transition. The energy released is typically in the X-ray portion of the electromagnetic spectrum. The 

13 release of electromagnetic radiation as a result of an electronic transition is defined as fluorescence. 

14 Fluorescence energies associated with electronic transitions depend on atomic structure, and vary between 

15 elements. As a result, X-ray fluorescence energy is uniquely characteristic of an element, and X-ray 

16 intensity at a given energy provides a quantitative measurement of elemental concentration in the sample. 

17 The X-rays are detected by passing them through a semiconductor material, resulting in an electrical 

18 current that depends on the energy of the X-ray.

3.4.1.3. Chemical Speciation Network, IMPROVE, and National Air Toxics 

Trends Network Monitors

19 In addition to being monitored for regulatory purposes in the SLAMS network, Pb is also 

20 monitored in three other sampling networks. Pb is monitored at 53 monitoring sites as a part of the 

21 Chemical Speciation Network. Participating monitoring agencies responsible for site operation are given 

22 flexibility in sampler design, with filter collection media best-suited for the analysis of specific 

23 components (U.S. EPA, 1999a). Several samplers are approved for CSN monitoring, all of which collect 

24 bulk PM species with multiple channels containing different types of filters appropriate for speciation 

25 sampling. Pb is one of 33 elements in PM2.5 collected on Teflon filters every third day and analyzed by 

26 energy dispersive X-ray fluorescence spectrometry.

27 Pb is also monitored at 110 aerosol visibility-monitoring sites as a part of the Interagency 

28 Monitoring of Protected Visual Environments (IMPROVE) program. An additional 59 aerosol samplers 

29 that are not directly operated through the program are operated following IMPROVE protocols. 
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1 IMPROVE is a cooperative effort by Federal and state organizations to protect visibility in 156 national 

2 parks and wilderness areas as described in the 1977 amendments to the Clean Air Act. Objectives are: (1) 

3 to establish current visibility and aerosol conditions in high priority (class I) areas for visibility protection; 

4 (2) to identify chemical species and emission sources responsible for existing man made visibility 

5 impairment (3) to document long-term trends for assessing progress towards visibility goals; and (4) to 

6 provide regional haze monitoring representing protected federal areas in accordance with the regional 

7 haze rule. The IMPROVE sampler operates with four sampling modules, three for PM2.5 and one for 

8 PM10. Pb is not measured in PM10, but one of the three PM2.5 modules contains a Teflon filter used for 

9 determination of gravimetric mass, absorbance, and elemental analysis by Particle Induced X-Ray 

10 Emission (PIXE) and XRF. A total of 9 elements are determined by XRF, including Pb (University of 

11 California Davis, 1995).

12 Pb in PM10 is also monitored in the National Air Toxics Trends Station (NATTS) network (ERG, 

13 2009). PM is collected either by high volume sampling with a quartz fiber filter or low volume sampling 

14 with a PTFE filter following EPA Compendium Method IO-3.5 (U.S. EPA, 1999b). Pb is one of seven 

15 core metals collected on Teflon filters and analyzed by ICPMS. The NATTS network was developed to 

16 fulfill the need for consistent data quality of long-term monitoring data on hazardous air pollutants of 

17 consistent data quality, for use in assessing trends and emission reduction program effectiveness, 

18 assessing and verifying air quality models, exposure assessments, emission control strategies, and as 

19 direct input for receptor modeling. As of December 2009, the network consisted of 27 monitoring 

20 stations, including 20 urban and 7 rural stations operating on a one in six day sampling frequency. 

21 Typically more than 100 pollutants are measured at each site, and monitoring is required for nineteen 

22 species, including Pb. Pb monitoring is also required for PM2.5 samples at NCore monitoring sites 

23 beginning no later than January 1, 2011, and monitoring of Pb in coarse PM (PM10-PM2.5) is also likely to 

24 be included (U.S. EPA, 2006). 

3.4.1.4. Other Measurement Methods for Total Lead

25 Several other methods that have not been designated as FRM or FEM methods have also been 

26 frequently used to obtain atmospheric Pb measurements. These include proton induced x-ray emission 

27 (PIXE), X-ray photoelectron spectroscopy (XPS), and other methods

PIXE

28 Proton-induced X-ray emission (PIXE) spectroscopy has been widely used to measure Pb in 

29 atmospheric PM. It is the method used for Pb analysis in the IMPROVE network. In PIXE, a high-energy 

30 proton beam passes through the sample, causing electrons to be excited from inner shells. The x-rays 

31 emitted when electronic transition occur to replace the inner shell electrons are characteristic of an 
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1 element and can be used to identify it. Development of PIXE for analysis of airborne PM was reviewed 

2 by Cahill et al. (1981). Numerous applications of PIXE to analysis of airborne Pb-PM have been reported 

3 in the past five years (Ariola et al., 2006; Chan et al., 2008; Cong et al., 2007; Johnson et al., 2006; 

4 Johnson et al., 2008; Sanchez-Ccoyllo et al., 2009; Wåhlin et al., 2006) (Cohen et al., 2010; Waheed et 

5 al., 2010).

XPS

6 X-ray photoelectron spectroscopy (XPS), also called electron spectroscopy for chemical analysis 

7 (ESCA) has been used to determine Pb concentrations on materials surfaces, including atmospheric PM 

8 (Finlayson-Pitts & Pitts, 2000). A fixed frequency X-ray beam causes inner shell electrons to be emitted 

9 and kinetic energy of ejected electrons is measured. Binding energy characteristic of an element can be 

10 calculated from the measured kinetic energy, allowing identification of the element. XPS can also provide 

11 information about an element’s chemical environment or oxidation states because of chemical shifts in 

12 binding energy caused by differences in chemical environment. There have been some recent applications 

13 of XPS to airborne PM, concluding that Pb was mostly in the form in of Pb sulfate (Qi et al., 2006). XPS 

14 analysis is a surface technique that is suitable only to a depth of 20-50Å. 

Other Total Lead Methods

15 Anodic stripping voltammetry, atomic emission spectroscopy, and colorimetry have also been used 

16 for measurement of atmospheric Pb (Finlayson-Pitts & Pitts, 2000). In anodic stripping voltammetry, 

17 metal ions are reduced to metallic form and concentrated as an amalgam on a suitable electrode (e.g. a 

18 mercury amalgam on a mercury electrode). This is followed by re-oxidation in solution, which requires 

19 “stripping” the reduced metal from the electrode. Emission spectroscopy can be compared to the existing 

20 FRM for Pb based on AAS. In atomic absorption spectroscopy radiation absorbed by non-excited atoms 

21 in the vapor state is measured. In emission spectroscopy, radiation due to the transition of the electron 

22 back to ground state after absorption is measured, and the energy of the transition is used to uniquely 

23 identify an element in a sample. Colorimetric methods are wet chemical methods based on addition of 

24 reagents to a Pb containing solution to generate measurable light absorbing products. These methods are 

25 less sensitive than ICPMS, XRF, and PIXE and their use is declining as more sensitive methods become 

26 more widely used, but have advantages regarding simplicity and cost.

3.4.1.5. Sequential Extraction

27 Sequential extraction has been widely used to further classify Pb for various purposes, including 

28 bioavailability, mobility, and chemical speciation. In general the more easily extractable Pb is considered 
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1 more mobile in soil and is more bioavailable to organisms. This approach has also been used widely in 

2 characterization of airborne PM. In its original application (Tessier et al., 1979) metals extraction solvents 

3 were selected to correspond to common species present in soil, and metals were classified as 

4 exchangeable, bound to carbonates, bound to iron and manganese oxides, bound to OM, and residual. 

5 Extraction was carried out with successively stronger solutions, starting with magnesium chloride for 

6 removal of exchangeable metals and ending with hydrofluoric and perchloric acids for removal of 

7 residual metals. Pb was one of the elements originally studied by Tessier et al. (1979) as well as one the 

8 elements analyzed when Tessier’s scheme was first applied to airborne PM (Fraser & Lum, 1983).

9 Tessier’s scheme was modified and optimized for airborne PM over time (Fernandez Espinosa et 

10 al., 2002) and additional extraction schemes were also developed (Chester et al., 1989), including the 

11 simplest case of two fractions corresponding to soluble and insoluble fractions (Canepari et al., 2006; 

12 Falta et al., 2008; Voutsa & Samara, 2002). The variety of methods in current use was recently thoroughly 

13 reviewed by Smichowski et al. (2005). With the recognition that biological processes involving deposited 

14 PM metals were related to their solubility (U.S. EPA, 2009), sequential extraction methods or simpler 

15 schemes to divide metals into water and acid soluble fractions were increasingly applied to PM samples to 

16 obtain data not just on total metal concentration but also on water soluble concentration (Graney et al., 

17 2004; Kyotani & Iwatsuki, 2002; Wang et al., 2002). Compared to other elements, a large fraction of total 

18 Pb is soluble (Graney et al., 2004). Recent advances in this area have included application to size 

19 fractionated PM (Birmili et al., 2006; Dos Santos et al., 2009), time resolved measurements (Perrino et 

20 al., 2010), and an extensive comparison of different fractionation schemes (Canepari et al., 2010). 

21 Sequential extraction with two or more fractions is becoming more widely used for characterization of 

22 Pb-PM in a variety of sources (Canepari et al., 2008; Poykio et al., 2007; Sillanpaa et al., 2005; 

23 Smichowski et al., 2008) and locations (Al-Masri et al., 2006; Annibaldi et al., 2007; Canepari et al., 

24 2006; Cizmecioglu & Muezzinoglu, 2008; Dahl et al., 2008; Dos Santos et al., 2009; Fujiwara et al., 

25 2006; Gutierrez-Castillo et al., 2005; Heal et al., 2005; Perrino et al., 2010; Richter et al., 2007; Sato et 

26 al., 2008; W. Wang et al., 2006; Yadav & Rajamani, 2006), leading to a better understanding of mobility 

27 characteristics of Pb in airborne PM.

3.4.1.6. Speciation Techniques

XAFS

28 There have been few attempts to speciate Pb in atmospheric PM into individual species. However, 

29 recently X-ray absorption fine structure (XAFS) has been applied to PM and road dust to obtain Pb 

30 speciation data from direct analysis of particle surfaces. In XAFS the absolute position of the absorption 

31 edge can be used to determine the oxidation state of the absorbing atom, and scattering events that 
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1 dominate in the near edge region provide data on vacant orbital energies, electronic configurations, and 

2 site symmetry of the absorbing atom that can be used to determine the geometry of the atoms surrounding 

3 the absorbing atom. XAFS can be divided into two spectral regions. X-ray absorption near edge structure 

4 (XANES) is the region of the x-ray absorption spectrum up to 50 eV above the absorption edge observed 

5 when an inner shell electron is electronically excited into unoccupied states, and Extended X-ray 

6 Absorption Fine Structure (EXAFS) up to 1 keV above the absorption edge. Both have been applied 

7 recently to Pb in PM. XANES spectra of Pb coordination complexes with a wide range of 

8 environmentally relevant ligands have been reported (Swarbrick et al., 2009). XANES has been used to 

9 show that several different Pb species are probably present in urban airborne PM (Funasaka et al., 2008)

10 and urban road dust (Barrett et al., 2010). XANES has been used to differentiate between Pb chromate, 

11 Pb-sorbed minerals, Pb chloride, Pb oxide, Pb carbonate, Pb sulfide and Pb sulfate are probably present in 

12 urban PM and road dust samples (Barrett et al., 2010; Funasaka et al., 2008; Tan et al., 2006). XANES 

13 has also been used to quantify Pb complexed with humic substances from soil in road dust (Pingitore et 

14 al., 2009) and to investigate the speciation of atmospheric Pb in soil after deposition (X. Y. Guo et al., 

15 2006). EXAFS has been applied to emission sources to show Pb from a sinter plant was mainly carbonate 

16 (Sammut et al., 2010). XAFS has only been applied to airborne PM very recently and shows promise for 

17 chemical speciation of airborne metals, including Pb.

GC- and HPLC-ICPMS

18 Environmental analytical methods for organolead compounds prior to 2000 were generally time 

19 consuming and costly, requiring extraction, derivatization, and detection (Quevauviller, 2000). These have 

20 been thoroughly reviewed (Pyrzyńska, 1996) and method intercomparison studies have been conducted 

21 (Quevauviller, 2000). More recently, speciation of organometallic compounds in environmental samples 

22 has usually carried out by coupling a chromatographic separation step with a mass spectrometry-based 

23 multi-element detection systems capable of analyzing a wide range of elements along with Pb, and these 

24 approaches have also been recently reviewed (Hirner, 2006). Chromatographic systems in common use 

25 are gas chromatography and high performance liquid chromatography. Detection systems most commonly 

26 used are ICPMS, electron impact ionization mass spectrometry (EI-MS), and electrospray ionization mass 

27 spectrometry (ESI-MS) (Hirner, 2006). Using these techniques, organometallic species are separated from 

28 each other based on differences in retention times on chromatographic columns, and elemental Pb is 

29 determined by the ICPMS used as a detector downstream of the column to measure elemental Pb in the 

30 pure compounds after chromatographic separation. Pb speciation analysis has benefited from the 

31 development of HPLC-ICPMS in particular (Quevauviller, 2000). Recent advances in metal speciation 

32 analysis in environmental samples by HPLC-ICPMS have been extensively reviewed (Popp et al., 2010). 

33 HPLC-ICPMS has been used for analysis of Pb complexes with humic substances (Vogl & Heumann, 
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1 1997), which could be relevant for resuspended soil and road dust. GC-ICPMS has been more widely 

2 used for separation and analysis of methyl and ethyl Pb species in atmospheric PM (Jitaru et al., 2004; 

3 Leal-Granadillo et al., 2000; Poperechna & Heumann, 2005). 

3.4.1.7. Continuous Lead Monitoring

4 Development of high time resolution measurement capabilities has advantages for determining 

5 peak exposure concentrations and diurnal exposure trends. High time resolution samplers suitable for 

6 analysis after sampling by XRF and ICPMS have been developed and applied. The eight-stage Davis 

7 Rotating Unit for Monitoring (DRUM) impactor (T. A. Cahill et al., 1987; Raabe et al., 1988) collects PM 

8 samples with a cascade impactor on Mylar film substrate on a slowly rotating drum, with samples 

9 analyzed by XRF. It has been used to measure size and time resolved Pb and other elements with a time 

10 resolution of less than 6 hours using x-ray fluorescence (Bench et al., 2002; C. F. Cahill, 2003). The 

11 University of Maryland Semi-continuous Elements in Aerosol Sampler (Kidwell & Ondov, 2001, 2004)

12 uses direct steam injection into promote condensational growth of sampled at a high flow rate, and 

13 accumulates resulting droplets in a slurry by impaction. It has been successfully applied to measurement 

14 of Pb and other elements by AAS (Pancras et al., 2006; Pancras et al., 2005) with a 30-minute time 

15 resolution. This approach is also suitable for ICPMS analysis. A gas converter apparatus has also been 

16 developed to improve transfer of ions to the ICPMS, including Pb, and successfully tested with outdoor 

17 air (Nishiguchi et al., 2008). Other high time resolution methods suitable for Pb analysis in PM are under 

18 development, including near real-time XRF analysis.

19 Much of the recent progress in ambient aerosol instrumentation has been related to the 

20 development and improvement of single particle mass spectrometry (Prather et al., 1994). This technique 

21 can also be considered as an effective method for real time Pb measurement in PM (Silva & Prather, 

22 1997). Progress has continued in the development of single particle mass spectrometry to quantify 

23 elements and organic ion fragments and a number of recent applications that included (Bein et al., 2007; 

24 Johnson et al., 2008; Pekney et al., 2006; Reinard et al., 2007; Snyder et al., 2009) or specifically targeted 

25 (Moffet, de Foy, et al., 2008; Murphy et al., 2007; Salcedo et al., 2010) Pb measurements.

3.4.2. Ambient Network Design

26 Ambient air Pb concentration is detected by FRM monitors at state and local monitoring stations 

27 (SLAMS) reporting data used for NAAQS compliance to the Air Quality System (AQS). Monitoring 

28 requirements for Pb have evolved over the past ten years. Monitoring for ambient Pb levels has been 

29 required for all major urban areas where ambient air Pb measurements have been elevated near or beyond 

30 the level of the NAAQS. Alternately, state and local agencies have located Pb monitoring stations in 

31 proximity to Pb point source emissions. Prior to 2006, monitoring sites were established where sources 
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1 emitted 5 or more tons/yr or where smaller stationary sources were located in proximity to populated 

2 neighborhoods. 

3 Pb monitoring requirements have experienced several changes since publication of the last Pb 

4 AQCD (U.S. EPA, 2006). In 2008 revisions for the Pb NAAQS were announced, and new monitoring 

5 requirements to support NAAQS revision called for expanded monitoring at sources that emit Pb at a rate 

6 of 1.0 or more tons/yr and non-source oriented monitoring at each Core Based Statistical Area (CBSA) 

7 with a population of 500,000 or more ("National Ambient Air Quality Standards for Lead (final rule)," 

8 2008). This corresponded to approximately 100 non-source oriented monitors. Some of the new monitors 

9 were required to become operational by January 1, 2010, with the remainder operational by January 1, 

10 2011. Subsequent revisions to these requirements have been promulgated, including reduction of the 

11 source oriented monitoring threshold from 1.0 tons/yr to 0.5 tons/yr and replacing the requirement for 

12 population-based CBSA monitoring with a requirement for non-source oriented Pb monitoring at National 

13 Core multipollutant monitoring network (NCore) sites in CBSA’s with a population of 500,000 or more 

14 (75 FR 81126). NCore is a new network of multipollutant monitoring stations intended to meet multiple 

15 monitoring objectives. The NCore stations are a subset of the SLAMS network are intended to support 

16 long-term trends analysis, model evaluation, health and ecosystem studies, as well as NAAQS 

17 compliance. The complete NCore network consists of approximately 60 urban and 20 rural stations, 

18 including some existing SLAMS sites that have been modified for additional measurements. Each state 

19 will contain at least one NCore station, and 46 of the states plus Washington, DC, will have at least one 

20 urban station. 

21 Data used in this chapter are from the period 2007-2009. The number of source oriented and non22 source oriented monitors changed each analysis year because the monitoring requirements changed over 

23 this time. Monitors were designated to be source-oriented if they were designated in AQS as source 

24 oriented, or they were located within one mile of a 0.5 ton/yr or greater source, as noted in the 2005 NEI 

25 (U.S. EPA, 2008a). Non-source oriented monitors were those monitors not considered to be source 

26 oriented. This loosening of the restrictions was intended to accommodate the 2007-2008 data that were 

27 obtained before the latest monitor designation requirements were implemented.

28 In addition to FRM monitoring, Pb is also measured within the Chemical Speciation Network 

29 (CSN), Interagency Monitoring of Protected Visual Environments (IMPROVE), and the National Air 

30 Toxics Trends Station (NATTS) networks. While monitoring in multiple networks improves geographic 

31 coverage, measurements between networks are not directly comparable in all cases because different PM 

32 size ranges are sampled in different networks. Depending on the monitoring network, Pb is monitored 

33 either in TSP, PM10, or PM2.5.
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3.4.2.1. Monitor Siting Requirements

1 Spatial scales defined for Pb monitoring range from microscale to regional scale (40 CFR Part 58):

2  Microscale: Defines the concentrations in air volumes associated with area dimensions 

3 ranging from several meters up to about 100 m. This scale applies to areas in close proximity 

4 to Pb point sources. 

5  Middle Scale: Defines the concentration typical of areas up to several city blocks in size with 

6 dimensions ranging from about 100 m to 0.5 km. This scale generally represents Pb air 

7 quality levels in areas up to several city blocks.

8  Neighborhood Scale: Defines concentrations within some extended area of the city that has 

9 relatively uniform land use with dimensions in the 0.5 to 4.0 km range. Where a 

10 neighborhood site is located away from immediate Pb sources, the site may be very useful in 

11 representing typical air quality values for a larger residential area, and therefore suitable for 

12 population exposure and trends analyses.

13  Urban Scale: Defines concentrations within area of city-like dimensions on the order of 4 to 

14 50 km. Such stations would be used to present ambient Pb concentrations over an entire 

15 metropolitan area with dimensions in the 4 to 50 km range. An urban scale station would be 

16 useful for assessing trends in citywide air quality and the effectiveness of larger scale air 

17 pollution control strategies.

18  Regional Scale: Defines usually an area of reasonably homogeneous geography without 

19 larges sources, and extends from tens to hundreds of kilometers. This large scale of 

20 representativeness has not been used widely for Pb monitoring, but provides important 

21 information on background air quality and inter-regional pollutant transport.

22 Since the majority of Pb emissions mass comes from point sources, such as metals processing 

23 facilities, waste disposal and recycling, and fuel combustion, the SLAMS network is primarily used to 

24 assess the air quality impacts of Pb point sources. A second purpose of the SLAMS network is to 

25 determine the broad population exposure from any Pb source. The most important spatial scales to 

26 characterize the emissions from point sources are the micro, middle, and neighborhood scales. 

27 Background information such as point source emissions inventories, climatological summaries, and 

28 local geographical characteristics are used to identify areas where monitoring is necessary. After siting 

29 each Pb station, specific siting criteria must be fulfilled for Pb monitoring in the SLAMS network. Micro 

30 and middle scale monitors must be 2-7 m above ground. All other scale monitors must be 2-15 m above 

31 ground. Monitors must be more than 2 m from supporting structures. Monitors must be more than 10 m

32 from trees. Microscale monitors designed for monitoring traffic related Pb must be 2-10 m from 
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1 roadways. Distance from roadways for other scales depends on the purpose and scale of the monitor and 

2 the level of traffic on the roadway. 

3.4.2.2. Spatial and Temporal Coverage

Figure 3-12. Pb monitoring sites for SLAMS, CSN, NATTS, and IMPROVE 

networks, 2007-2009.

3 Figure 3-12 shows Pb monitoring sites for all networks. The top left map shows the SLAMS 

4 monitors reporting to the AQS system from 2007 to 2009. Monitors are indicated as Pb-TSP source 
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1 oriented, Pb-TSP non-source oriented, and PM10 non-source oriented. Source and non-source designations 

2 used in the data analysis in Section 3.5 are indicated on this map. The top right map shows PM2.5 monitors 

3 from the CSN. The bottom left map shows National Air Toxics Trend Networks sites, and the bottom right 

4 map shows IMPROVE monitoring sites. There is a high density of FRM monitors in some cities 

5 containing Pb sources, including Los Angeles, St. Louis, Pittsburgh, and Minneapolis. As a result, 

6 population coverage varies across cities, with those cities with major Pb sources having greater coverage. 

7 Coverage for PM2.5 in the CSN and IMPROVE network is geographically comprehensive. In comparison,

8 the FRM sites are more representative of source effects. NATTS sites have less extensive national 

9 coverage.

3.5. Ambient Air Lead Concentrations

10 The following section summarizes data on ambient air Pb concentrations during the years 2007-

11 2009. The section begins with a description of Pb concentrations observed in TSP, PM10, and PM2.5 at 

12 source oriented and non-source oriented monitors across the U.S. Next, seasonal patterns and multi-year 

13 trends of Pb concentration are presented for the U.S. It is notable that Pb concentrations have declined 

14 substantially over the past 40 years; this is described further in Section 3.5.2. An examination of AQS 

15 data and the peer-reviewed literature is provided to evaluate the size distribution of Pb-bearing airborne 

16 PM under varied ambient conditions. Finally, the relationship between Pb concentration and 

17 concentrations of copollutants are presented. Summary information is presented within this section, and 

18 detailed data are included in an Appendix to this chapter.

3.5.1. Spatial Distribution of Air Lead

3.5.1.1. Variability across the U.S. 

19 This section presents nationwide Pb concentration data measured using source oriented and non20 source oriented TSP FRM monitors, PM10 monitors, and PM2.5 monitors from the CSN for 2007-2009. 

21 This information is useful to develop a sense of variability in Pb concentrations at a national scale. For 

22 this analysis, source oriented monitors encompassed all those listed as “source oriented” in the AQS, 

23 based on state agency reporting, plus those within one mile of a facility emitting 0.5 ton/yr or more. Non24 source oriented monitors were those monitors in the system not designated to be source oriented (Figures 

25 3-13 though 3-16), the majority of U.S. counties do not have a Pb monitor. 
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Concentrations of Pb Measured using TSP Monitors

1 Source oriented maximum 3-month average Pb data were obtained for 22 counties across the U.S. 

2 during the period 2007-2009. Figure 3-13 illustrates that the level of the NAAQS was exceeded in 

3 fourteen counties where source oriented monitoring was performed. Summary data are presented below in 

4 Table 3-4, and detailed data for the one-month and three-month average and maxima source oriented Pb5 TSP concentrations are provided in Tables 3A-1 through 3A-4 in the Appendix. The mean was skewed 

6 towards the 75th percentile of the distribution for both the monthly and three-month data sets. The 

7 primary difference between the one-month average and three-month rolling average data sets occurs at the 

8 upper tails of the distribution. Data for sites at which national maxima were reached for 2007-2009 are 

9 presented in Table 3-5. The highest monthly and three-month average concentrations occurred at the same 

10 sites: Herculaneum, MO followed by Los Angeles, CA. The highest annual site max 1-month value 

11 occurred in Cook County, IL in 2008, followed by Iron County, MO in 2008 and Hillsborough County, FL 

12 in 2007. The Herculaneum and Los Angeles sites were also above the 90th percentile annual 3-month site 

13 max Pb concentrations. The highest annual site max 3-month concentrations occurred in Herculaneum in 

14 2008, Los Angeles in 2008, and Iron County, MO in 2008. The majority of data were below the level of 

15 the NAAQS over the 3-year period, but high values at a subset of source oriented monitoring locations 

16 tended to skew the nationwide distribution of Pb concentration data upwards.

Table 3-4. Summary data for source oriented Pb monitors across the U.S.

Mean, μg/m3 Median, μg/m3 95th%, μg/m3 99th%, μg/m3 Max, μg/m3

Monthly 0.24 0.070 0.98 2.1 4.4

3-mo rolling avg 0.24 0.080 0.98 1.9 2.9

Table 3-5. Summary data for sites at which source oriented statistics are at a maxima

County AQS Highest Monthly 

Mean, μg/m3 Highest 3-mo 

Mean, μg/m3

Highest Monthly 

Annual Site Max, 

μg/m3 (Year)

Highest 3-mo

Annual Site Max, μg/m3 (Year)

Jefferson, MO 290990015 1.3 1.3 2.9 (2008)

Jefferson, MO 290990004 1.1 1.1

Los Angeles, CA 060371405 0.86 0.93 2.5 (2008)

Chicago, IL 180350009 4.4 (2008)

Iron, MO 290930016 4.2 (2008) 2.5 (2008)

Hillsborough, FL 120571066 3.6 (2007)
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Figure 3-13. Highest county-level source oriented Pb-TSP concentrations

(μg/m3

), maximum 3-month average, 2007-2009.

1 Non-source oriented maximum 3-month average Pb concentration data were obtained with TSP 

2 monitors for 36 counties across the U.S. during the period 2007-2009; non-source PM10 monitoring data 

3 are not included here because they were obtained at select sites in 2009 only. The median for monthly and 

3-month rolling average data was 0.010 μg/m3 4 . Detailed data for site-specific Pb-TSP concentrations are 

5 provided in Tables 3A-5 and 3A-6 in the Appendix to this chapter. Nationwide, the mean monthly average 

6 non-source oriented Pb-TSP concentration for 2007-2009 was more than an order of magnitude lower 

7 than the source-oriented data. Collectively, these data indicate that non-source oriented monitors tend to 

8 measure concentrations an order of magnitude lower than the level of the NAAQS.

Concentrations of Pb Measured using PM10 Monitors

9 Figure 3-14 displays maximum 3-month average county-level data for Pb in PM10 concentrations 

10 for 36 counties in which measurements were obtained. The data presented here are not compared to the 

11 level of the NAAQS because PM10 monitors were not incorporated into the non-source oriented 

12 monitoring network until 2009. Among the 36 counties in which PM10 monitoring was conducted, only 

one county, Gila County, AZ, reported concentrations above 0.076 μg/m3 13 . Three other counties reported 
May 2011 3-67 DRAFT – DO NOT CITE OR QUOTE

concentrations greater than 0.016 μg/m3 1 : Wayne County, MI, Boyd County, KY, and the county of St. 

2 Louis City, MO. 

Figure 3-14. Highest county-level Pb-PM10 concentrations (μg/m3

), 

maximum 3-month average, 2007-2009.

3 Figure 3-15 displays maximum 3-month average county-level data for Pb in PM2.5 concentrations 

4 for 323 counties in which PM2.5 measurements were obtained for speciation in the CSN and IMPROVE 

5 networks. The data presented here are not compared to the level of the NAAQS because PM2.5 monitors 

6 are not deployed for that purpose. Among the 323 counties in which PM2.5 monitoring was conducted, 

only eleven counties reported concentrations greater than 0.016 μg/m3 7 : Jefferson, AL, San Bernardino, 

8 CA, Imperial, CA, Wayne, MI, Jefferson, MO, Erie, NY, Lorain, OH, Allegheny, PA, Berks, PA, 

9 Davidson, TN, and El Paso, TX. 
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Figure 3-15. Highest county-level Pb-PM2.5 concentrations (μg/m3

), 

maximum 3-month average, 2007-2009.

3.5.1.2. Intra-urban Variability

1 Intra-urban variability is defined as the variation in Pb concentration across an urban area. Because 

2 the source characteristics and size distribution of particle-bound Pb can vary considerably, spatial 

3 variability of Pb concentrations in urban areas may also be high. Such variability may not be detected if

4 one or a small number of central site monitors is in use, so cities with multiple monitors can be used to 

5 characterize intra-urban variability. Intra-urban variability in Pb concentrations reported to AQS at the 

6 individual county level was described in detail in the Appendix in Section 3A.2. County-level data were 

7 used because PM-bound airborne Pb tends to settle over short distances to produce large spatiotemporal 

8 variability, as described in Section 3.3.1 and revisited in Section 3.5.3. Los Angeles County, CA (Los 

9 Angeles), Hillsborough and Pinellas Counties, FL (Tampa), Cook County, IL (Chicago), Jefferson County, 

10 MO (Herculaneum), Cuyahoga County, OH (Cleveland), and Sullivan County, TN (Bristol) were selected 

11 for this assessment to illustrate the variability in Pb concentrations measured across different metropolitan 

12 regions with varying combinations of source and urban contributions of Pb. Maps and wind roses are 

13 presented in the Appendix for each of the six urban areas. Additionally, annual and seasonal box plots of 

14 the Pb concentration distributions and intra-monitor correlation tables are presented to illustrate the level 

15 of variability throughout each urban area. 
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1 When collectively reviewing the data from the six counties, it became apparent that spatial and 

2 temporal variability of Pb concentrations were commonly high. Variability was high for areas that 

3 included a Pb source, with high concentrations downwind of the sources and low concentrations at areas 

4 far from sources. When no large sources of Pb were present, variability of Pb concentrations were lower, 

5 and more data were observed to lie below the MDL. For example, the Los Angeles County, CA data 

6 illustrated very high concentrations adjacent to a Pb recycling facility, but non-source oriented 

7 concentrations were well below the level of the NAAQS at all times. As described in Section 3.3, PM size 

8 distribution influences how far the particle will travel upon initial emission or resuspension before being 

9 deposited. Meteorology, nature of the sources, distance from sources, and positioning of sources with 

10 respect to the monitors all appeared to influence the level of concentration variability across time and 

11 space for the monitoring data analyzed in the Appendix. Additionally, resuspension of wheel weights and 

12 soils, emission of trace Pb during on-road gasoline combustion, and urban background levels of Pb are 

13 uncertain influential factors in ambient Pb concentrations. This is consistent with field studies to 

14 characterize Pb concentrations that are described in the literature. 

15 A number of studies have characterized how Pb-bearing PM is distributed over the neighborhood 

16 scale in the air. Martuzevicius et al. (2004) examined the spatial variability of PM2.5 samples obtained in 

17 the greater Cincinnati, OH area at 6 urban, 4 suburban, and 1 rural site and found that Pb concentration in 

18 PM2.5 had a coefficient of variation (CV, defined as the standard deviation of site measurements divided 

19 by the average) of 33.8%, compared with a CV for PM2.5 of 11.3% over all sites. Average Pb-PM2.5

concentration among the sites varied from 1.79-28.4 ng/m3 20 . Martuzevicius et al. (2004) suggested that 

21 differences between mass and Pb spatial variability implied that Pb originated primarily from local 

22 sources. Sabin et al. (2006) measured Pb-PM with an upper cutpoint of 29 μm and found that urban 

concentrations ranged from 2.2 to 7.4 ng/m3 23 with a CV of 40%. In contrast, a rural location had a 

concentration of 0.62 ng/m3 24 . Sabin et al. (2006) also reported deposition flux at the same sites, which 

ranged from 8.3 to 29 μg/m2·day at the rural sites, with a CV of 48%, and was 1.4 ng/m3 25 at the rural site.

26 Han et al. (2007) found that Pb concentrations within resuspended road dust were higher at an inner-city 

27 ring road and an industrial site compared with residential or construction sites. Li et al. (2009) observed 

28 that Pb concentration in PM2.5 samples was 2.3-3.0 times higher near a bus depot than next to a rural29 suburban road. Ondov et al. (2006) measured Pb-PM2.5 concentration at three Baltimore sites, one of 

30 which was industrial and the other two of which were considered “receptor” sites. Average Pb-PM2.5

concentrations at the different sites were 8.3 ng/m3 at the industrial site and 1.9 ng/m3 and 7.2 ng/m3 31 at the 

32 receptor sites. As a group, these studies support the analysis of intra-urban AQS data by illustrating that 

33 intra-urban variability is most strongly related to type, strength, and location of sources.
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3.5.2. Temporal Variability

1 The following section presents data for multi-year trends and seasonal variability of Pb 

2 concentrations on a nationwide basis. The data presented here provide information on the success of Pb 

3 reduction efforts over past decades as well as on areas for continued attention with respect to Pb 

4 monitoring. The multi-year trends illustrate changes in air Pb concentrations resulting from the phase-out 

5 of leaded gasoline for automobiles and smaller reductions of industrial Pb usage. The seasonal variability 

6 plots demonstrate changes in concentration within a given year, potentially related to climate or source 

7 variation. 

3.5.2.1. Multi-year Trends

8 Figure 3-16 illustrates the trend in ambient air TSP-Pb concentrations during the years 1980-2009. 

Over this time period, average air Pb concentrations have declined by 91% from 1.3 μg/m3 9 (in 1980) to 

0.12 μg/m3 (in 2009). The median concentrations have declined by 97% from 0.87 μg/m3 10 (in 1980) to 

0.025 μg/m3 11 (in 2009). While the sharpest drop in Pb concentration occurred during 1980-1990 as a result 

12 of the phase-out of Pb antiknock agents in on-road fuel, a declining trend can also be observed between 

13 1990 and 2009 following reductions in industrial use and processing of Pb, as described in Section 3.2.1. 

In 1990, the median Pb concentration was 0.19 μg/m3 and the average Pb concentration was 0.55 μg/m3 14 to 

15 yield 87% and 78% reductions, respectively, from 1990 to 2009. Average concentrations in these 

16 calculations and in Figure 3-16, are heavily influenced by the source oriented monitors in the network. 

17 New Pb concentration data from expansion of the source oriented portion of the network in 2010 will 

18 allow for greater assessment of changes of Pb concentrations on nationwide statistics and trends.
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Figure 3-16. National trends in Pb concentration (μg/m3

), all FRM monitors, 

1980-2009.Average concentration is shown by the solid black 

line, median concentration is shown by the solid blue line, and 

10th and 90th percentiles are plotted with dashed lines. The 

red lines on the plot illustrate former and current levels of the 

Pb NAAQS.

1 Figure 3-17 and Figure 3-18 show ambient Pb concentrations from 1990 to 2009 for source 

2 oriented monitors and non-source oriented monitors, respectively. In both cases concentration data are 

3 consistent with a downward trend, and concentrations were considerably lower at the end of the period 

4 than at the beginning of the period.

0

0.5

1

1.5

2

2.5

3

3.5

4

TSP Concentration (μg/m3)

1978-2008 Level of the NAAQS

2009 Level of the NAAQS
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Figure 3-17. National trends in Pb concentration (μg/m3

), source oriented 

FRM monitors, 1990-2009.Average concentration is shown by 

the solid line, and the 10th and 90th percentiles are shown by 

the dashed lines. 

Figure 3-18. National trends in Pb concentration (μg/m3

), non-source 

oriented FRM monitors, 1990-2009. Average concentration is 

shown by the solid line, and the 10th and 90th percentiles are 

shown by the dashed lines.

0

0.5

1

1.5

2

2.5

3

TSP Pb Concentration (μg/m3)

1978-2008 Level of the NAAQS

2009 Level of the NAAQS

0

0.1

0.2

0.3

0.4

0.5

0.6

TSP Pb Concentration (μg/m3)

2009 Level of the NAAQS
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For source oriented monitors, average concentrations decreased from 0.93 μg/m3 to 0.23 μg/m3 1

(75% decline) and upper 90th percentile concentrations decreased from 2.5 μg/m3 to 0.54 μg/m3 2 (78% 

3 decline) over the 20-year period. A portion of the decrease can be attributed to reductions in emissions 

4 from the Herculaneum, MO smelter between 2001 and 2002 (U.S. EPA, 2010). An abrupt decrease in 

5 average concentrations between these years is evident in Figure 3-17. Note that the number of monitors 

6 contributing to these statistics increased from 29 during 1990-1999 to 47 for 2000-2009.

For non-source oriented monitors, average concentrations decreased from 0.18 μg/m3 7 to 

0.020 μg/m3 8 (88% decline) and upper 90th percentile concentrations decreased from approximately 0.49 

μg/m3 to approximately 0.05 μg/m3 9 (87% decline) over the 20-year period. Average concentrations near 

10 stationary sources were 5 to 12 times typical concentrations from non-source oriented monitoring 

11 locations between 1990 and 1999; during the subsequent decade, average source oriented Pb 

12 concentrations were 8 to 22 times higher than non-source concentrations (U.S. EPA, 2010). This 

13 differential likely reflects the absence of Pb emissions from automobiles during 2000-2009. The number 

14 of monitors contributing to these statistics increased from 29 during 1990-1999 to 53 for 2000-2009.

15 When both source oriented and non-source oriented monitoring sites are considered, average Pb 

16 concentrations decreased by 73% between 2001 and 2008 for maximum 3-month average concentrations 

17 at 24 sites that are near large stationary sources and 101 sites that are not near stationary sources (U.S. 

18 EPA, 2010).

3.5.2.2. Seasonal Variations 

19 This section outlines seasonal variability among Pb monitors on a nationwide basis. Seasonal 

20 variation may provide insight related to differential influences of sources and climate throughout a year. 

21 Additionally, the magnitude of concentrations within the monthly data distributions and of variations 

22 between months sheds light on the influence of season as well as on differences between source oriented, 

23 non-source oriented, PM10, and PM2.5 data.

24 The average of Pb concentrations over all monitoring sites is higher in fall and lower in winter than 

25 other seasons. Monthly average Pb concentrations averaged over multiple sites and over 3 years from 

26 2007-2009 are shown in for Pb-TSP from source oriented monitors (Figure 3-19), Pb-TSP from non27 source oriented monitors (Figure 3-20), Pb-PM10 (Figure 3-21), and Pb-PM2.5 (Figure 3-22). For source 

28 oriented Pb-TSP (Figure 3-19), monthly average concentrations were determined from between 146 and 

29 154 samples in each month. The highest monthly average concentrations were observed in March, April, 

and November, and exceeded 0.26 μg/m3 30 . For non-source oriented TSP (Figure 3-20), monthly average 

31 concentrations were determined from between 141 and 151 samples in each month. A winter minimum 

32 was observed with December, January, and February exhibiting the three lowest monthly average 
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concentrations, each of which were below 0.015 μg/m3 1 , but concentrations were similar between spring, 

2 summer and fall months.

Figure 3-19. Monthly source oriented Pb-TSP average (μg/m3

) over 12

months of the year, 2007-2009.Box and whisker plots are used 

for each month, with the box comprising the interquartile

range of the data and the whiskers comprising the range 

within the 5th to 95th percentiles. The median is noted by the 

red line, and the blue star denotes the mean.

concentration (μg/m3)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

Month

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

           
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Figure 3-20. Monthly non-source oriented lead-TSP average (μg/m3

) over 12 

months of the year, 2007-2009.Box and whisker plots are used 

for each month, with the box comprising the interquartile 

range of the data and the whiskers comprising the range 

within the 5th to 95th percentiles. The median is noted by the 

red line, and the blue star denotes the mean.

Figure 3-21. Monthly lead-PM10 average (μg/m3

) over 12 months of the year, 

2007-2009.Box and whisker plots are used for each month, 

with the box comprising the interquartile range of data and the 

whiskers comprising the range from 5th to 95th percentiles. 

The median is noted by the red line, and the blue star denotes 

the mean.

concentration (μg/m3)

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Month

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

          



concentration (μg/m3)

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.020

0.022

0.024

0.026

0.028

Month

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

       



 


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Figure 3-22. Monthly lead-PM2.5 average (μg/m3

) over 12 months of the year, 

2007-2009.Box and whisker plots are used for each month, 

with the box comprising the interquartile range of the data and 

whiskers comprising the range from 5th to 95th percentiles. 

The median is noted by the red line, and the blue star denotes 

the mean.

1 For both Pb-PM10 (Figure 3-21) and Pb-PM2.5, (Figure 3-22) monthly average concentrations are 

2 considerably higher in the fall than in other seasons, with lowest the three highest monthly average 

3 concentrations observed in September, October, and November, and the average September concentration 

4 more than double the average December concentration. Pb-PM10 monthly average concentrations were 

5 determined from between 100 and 109 samples and Pb-PM2.5 from between 866 and 1,034 samples each 

6 month. Some of the Pb-PM2.5 concentrations were below Method Detection Limits and the absolute 

difference in monthly average concentrations between fall and other seasons for Pb-PM2.5 of 0.001 μg/m3 7

8 is extremely small. In spite of this the observed trends for PM2.5 are consistent with the PM10

9 observations. Whether the seasonal trend for Pb-PM10 and Pb-PM2.5 differs from trends for both source 

10 oriented and non-source oriented Pb-TSP because of the difference in source proximity, sampling 

11 locations or difference in size range sampled is not clear.

12 Although details of the seasonal trends varied with PM size range and source proximity, the data as 

13 a whole indicate that average monthly concentrations in the fall were consistently higher than the lowest 

14 average monthly concentrations, and that average monthly concentrations in the winter were consistently 

15 lower than the highest average monthly concentration regardless of PM size range or source proximity. 

16 Overall, there this indicates a clear tendency toward higher fall concentrations and lower winter 

17 concentrations. These results are consistent with observations at a single location by Melaku et al. (2008) concentration (μg/m3)

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

Month

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

         




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1 that atmospheric Pb concentrations in fall were higher than in winter in an intensive study of urban 

2 Washington DC, but not consistent with their observations of higher summer concentrations than fall.

3.5.3. Size Distribution of Lead-Bearing PM

3 Size-selective monitoring data from AQS and the literature is examined in this section to improve 

4 understanding of the size distribution of Pb-bearing PM. This information informs monitoring strategies 

5 because high content or correlation of PM10 with TSP may allow for expanded usage of PM10 within the 

6 FRM monitoring network. Additionally, size distribution data enhances understanding of the relationship 

7 between sources and characteristics of airborne Pb-bearing PM.

3.5.3.1. AQS Data Analysis

8 This section employs AQS data for Pb concentrations from co-located TSP, PM10, and/or PM2.5

9 FRM monitors to analyze correlations and ratios of concentrations obtained from the different monitors. 

10 These data were used because relationships among the monitors provide information about the nature of 

11 Pb-bearing PM at different locations (e.g., whether the mode is in the fine or coarse fraction). Correlations 

12 indicate the extent to which the size fractions vary together in time, and the ratios signify the average 

13 proportion of the smaller fraction to the larger fraction (e.g., the ratio of PM2.5 to PM10 concentrations). 

14 Estimation of the size distribution of Pb-bearing PM is possible at a limited number of monitoring 

15 sites where monitors having different size-selective cut-points are co-located. Data for correlations 

16 between monitors and average concentration ratios are available per collocation site in Table 3A-13 in the 

17 Appendix. For the comparison between Pb-TSP and Pb-PM10, 27 sites were available for analysis. A 

18 summary of these data are provided in Table 3-6. Overall, the average correlation, ρ, was moderate, 

19 although the wide range across monitors indicates suggests site-to-site variability. The average ratio of 

20 Pb-PM10 to Pb-TSP concentrations was relatively high at 0.88. When broken down by land type, the 

21 average ρ went up slightly for urban and city center land use, with a lower average ratio of concentrations. 

22 For suburban sites, the average ρ was reduced, but the average ratio of concentrations was near unity. 

23 Average ratio of concentrations greater than one suggest that some portion of the TSP was not collected 

24 due to instrument biases, as discussed in Section 3.4.

Table 3-6. Summary of comparison data for co-located lead-TSP and lead-PM10 monitors.

Monitors

Correlation Average Ratio PM10:TSP

Average Standard 

Deviation Range Average Standard Deviation Range

Overall 0.65 0.30 0.00-0.99 0.88 0.51 0.33-2.60

Urban and City 

Center 

0.73 0.25 0.29-0.99 0.73 0.19 0.54-1.10

Suburban 0.55 0.33 0.00-0.98 0.99 0.74 0.33-2.60

Rural - - - - - -
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1 Forty-five sites were available for analysis to compare Pb-TSP with Pb-PM2.5. A summary of these 

2 data are provided in Table 3-7. Overall, the average ρ was moderate. As for the TSP to PM10 comparison, 

3 a wide range of correlations suggests that the tracking of the TSP and PM2.5 time series was quite variable 

4 between sites and source influences. The average ratio of Pb-PM2.5 to Pb-TSP concentrations was 

5 somewhat high, but with several monitors having ratios above one, sampler bias may have influenced 

6 these statistics. When broken down by land type, the average ρ was somewhat reduced for urban and city 

7 center land use. For suburban sites the average ratio of concentrations was lower, with some of the same 

8 sampling bias issues. For rural sites, the average ρ was much higher. Correlation between PM2.5 and TSP 

9 may suggest commonality of sources or processes influencing both size fractions at the same time.

Table 3-7. Summary of comparison data for co-located Pb-TSP and Pb-PM2.5 monitors

Monitors

Correlation Average Ratio PM2.5:TSP

Average Standard 

Deviation Range Average Standard Deviation Range

Overall 0.50 0.25 0.03-0.95 0.79 0.49 0.11-2.34

Urban and City 

Center 

0.43 0.26 0.03-0.90 0.75 0.54 0.11-2.34

Suburban 0.55 0.23 0.16-0.95 0.66 0.29 0.36-1.57

Rural 0.71 0.24 0.37-0.90 1.36 0.39 0.83-1.76

10 Pb-PM10 and Pb-PM2.5 data were compared for 50 sites. A summary of these data are provided in 

11 Table 3-8. Overall, the average ρ was moderately high, with perfect correlation at a Providence, RI site 

12 (AQS ID: 440070022) and very high correlation at several other sites. The average ratio of Pb-PM2.5 to 

13 Pb-PM10 concentrations was 1.01, suggesting that some bias existed in the data so that PM2.5 was often 

14 higher than PM10 concentration. Data for urban and city center and suburban sites were similar for 

15 correlations and average ratios of concentration. For rural sites, the average ρ was slightly lower, and the 

16 range of ratios of concentrations showed that PM2.5 concentrations were almost always higher than PM10

17 concentrations, suggesting bias among the rural monitors. 

Table 3-8. Summary of comparison data for co-located Pb-PM10 and Pb-PM2.5 monitors.

Monitors

Correlation Average Ratio PM2.5: PM10

Average Standard 

Deviation Range Average Standard Deviation Range

Overall 0.76 0.22 0.15-1.00 1.01 0.37 0.45-2.15

Urban and City 

Center 

0.72 0.24 0.15-1.00 0.85 0.38 0.45-2.15

Suburban 0.81 0.17 0.34-0.98 1.08 0.35 0.61-1.89

Rural 0.66 0.28 0.22-0.99 1.23 0.29 0.97-1.63

18 In a few cases, Pb-TSP, Pb-PM10, and Pb-PM2.5 monitors were co-located simultaneously, so that 

19 more information regarding size distribution can be discerned. For example, in urban Jefferson County, 

20 AL (AQS: 010730023), the average ratio of PM2.5 to TSP was 0.84, while the average ratio of PM10 to 

21 TSP was 0.80 for the years 2005-2006. These reported values suggested that most of the PM was in the 
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1 fine mode. But, the data also indicated instrumentation bias with either the PM2.5 or PM10 monitors or 

2 both, because the average concentration ratio was greater than one. In a suburban portion of Cook County, 

3 IL (AQS: 170314201), the PM2.5 to TSP average ratio was reported to be 0.36, and the PM10 to TSP 

4 average ratio was reported to be 0.39. This suggested that the majority of the sample mass was from 

5 particles larger than 10 μm, but that the distribution might have been bimodal since there was little 

6 difference between PM2.5 and PM10. Note that only some of the years reported for all three monitors 

7 overlapped. In suburban Wayne, MI (AQS: 261630033), the PM2.5 to TSP average ratio was reported to 

8 be 0.49, and the reported PM10 to TSP ratio was reported to be 0.84. This suggests a smoother distribution 

9 with one mode likely in the large fine or small coarse region of the distribution. Note that the PM2.5 to 

10 TSP collocation includes one year of data more than the PM10 to TSP collocation. Taken together, these 

11 findings imply that the Pb-bearing PM size distribution varies substantially by location.

3.5.3.2. Size Distribution Studies in the Literature

12 Several studies in the literature have been designed to characterize the size distribution of Pb 

13 concentrations in the vicinity of sources. The following section describes studies that have measured more 

14 than one size fraction of Pb-bearing PM in the vicinity of industrial, urban, and/or traffic-related sources. 

15 Some discussion of the variability of size distribution over space and time is also provided.

16 Size distributions of Pb-bearing PM have been measured near several industrial sites. For example, 

17 Bein et al. (2006) measured the size distribution of Pb in PM from the Pittsburgh superfund site using 

18 rapid single particle mass spectrometry and a Multi-Orifice Uniform Deposit Impactor (MOUDI). The 

19 Pittsburgh, PA, superfund site had seventeen major PM sources within a 24-km radius. Bein et al.’s 

20 (2006) measurements yielded different results on different days, with a bimodal distribution with modes 

21 around 140 nm and 750 nm during an October, 2001 measurement and a single dominant mode around 

22 800 nm during a March, 2002 measurement. Differences in the size distributions could have been related 

23 to differences among wind speed, wind direction, and source contributions on the respective dates. Singh 

24 et al. (2002) measured the mass distribution of Pb-PM in the coarse and fine PM size ranges for the 

25 Downey industrial site along the Alameda industrial corridor in Los Angeles and a site approximately 

26 90 km downwind in Riverside, CA. At the industrial site, the Pb-PM size distribution was unimodal with 

27 a concentration peak in the 100-350 nm size range with 34% of the particles in this size bin. At the 

28 downwind site, a bimodal distribution was observed with peaks in the 2.5-10 μm bin and the 350 nm-1 

29 μm bin, comprising 42% and 26% of the mass measured as PM10, respectively. Pb in the fine range only 

30 comprised 13% of the particles in the 100-350 nm bin. The authors suggested that higher wind speeds in 

31 Riverside compared with the Downey site are effective in resuspending larger particles from the ground to 

32 create a peak in the coarse mode of the distribution.
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1 Industrial operations associated with Pb emissions include metal works and incineration. Dall’Osto 

2 et al. (2008) measured the size distribution of Pb emissions from a steel works facility in a coastal town 

3 within the United Kingdom (U.K.). A MOUDI was employed to measure concentrations in the coarse to 

4 fine PM size range. The size distribution was multimodal with a primary mode around 1 μm, a secondary 

5 mode around 300 nm, and a very small additional mode around 5 μm. This multimodal distribution was 

6 thought to be associated with sintering and steel working processes, from which Pb was emitted. 

7 Weitkamp et al. (2005) measured Pb-bearing PM2.5 concentrations across the river from a coke plant in 

8 the Pittsburgh, PA area. Pb was measured to comprise 0.088% of the PM2.5 mass, and background9 corrected Pb mass concentration was reasonably correlated with background-corrected PM2.5 mass 

concentration (R2 10 = 0.55). Pekey et al. (2010) measured PM2.5 and PM10 concentrations in a heavily 

industrialized area of Kocaeli City, Turkey and obtained an average PM2.5 concentration of 47 ng/m3 11

during summer and 72 ng/m3 during winter. Average PM10 concentration was 78 ng/m3 12 during summer 

and 159 ng/m3 13 during winter, to produce PM2.5/PM10 ratios of 0.60 during summer and 0.45 during winter.

14 Traffic can be a source of resuspension of Pb from deposited contemporaneous wheel weights or 

15 industrial emissions or historic sources via traffic-induced turbulence. Sabin et al. (2006) compared the 

16 size distribution of coarse Pb-PM captured at an urban background site and at a location 10 m from the I17 405 Freeway in the southern California air basin; data from Sabin et al. (2006) are displayed in Figure 3-

18 23. For both the urban background and near-road sites, the largest fraction was from PM sampled below 

19 the 6 μm cut point, but the near-road Pb-PM distribution appeared bimodal with a mode in the largest size 

fraction. Over all size fractions, the near-road site had a Pb concentration of 17 ng/m3 20 , compared with an 

urban background concentration of 9.7 ng/m3 21 . Sabin et al. (2006) point out that the freeway tends to be a 

22 source of very large particles that are dispersed via the turbulent motion of the vehicular traffic. In a near23 road study conducted in Raleigh, NC, Hays et al. (2011) note that the concentration of Pb in ultrafine, 

24 fine, and coarse size ranges was roughly constant at 50 mg/kg. The Pb samples from Hays et al. (2011)

25 were highly correlated with As samples (ρ = 0.7, p < 0.0001); both Pb and As are found in wheel weights. 

26 Likewise, the Pb samples were not well correlated with crustal elements in the coarse size distribution, so 

27 it is more likely that resuspended Pb originated from wheel weights rather than historic Pb on-road 

28 gasoline emissions. Pb dust was shown by Bukowiecki et al. (2010) to be significantly higher at roadside 

29 samples compared with urban background when the PM was in the coarse mode, measured as PM10-2.5, 

30 but not for fine modes measured as PM2.5-1 and PM1-0.1. Chen et al. (2010) measured Pb in PM10, PM2.5, 

31 and PM0.1 at a roadside location and in a tunnel in Taipei, Taiwan in 2008. While roadside and tunnel 

32 concentrations of PM10 and PM2.5 were roughly equivalent, Pb in PM0.1 was approximately 15 times 

33 higher than by the roadside. The authors suggest that particle-bound Pb was emitted from on-road 

34 gasoline and diesel engines. This could possibly be attributed to residual Pb in unleaded gasoline.
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0

10

20

30

40

50

60

70

80

< 6 μm 6-11 μm 11-20 μm 20-29 μm > 29 μm

Percent of Total Pb-PM Sampled

Urban Background Near-Road

Source: Adapted, with permission from Elsevier Publishing, from Sabin et al. (2006).

Figure 3-23. Comparison of urban background and near-road size fractions 

of lead-bearing PM.

1 Several studies have suggested that near-road ambient air Pb samples are derived from non-road 

2 sources. Harrison et al. (2003) measured the distribution of Pb in PM10 at a roadside sampler in 

3 Birmingham, U.K.. The size distribution was unimodal with approximately 2% of the Pb mass 

(0.5 ng/m3) above the 10 μm cut point, 12% (3 ng/m3) in the 2-10 μm bin, 9% (2 ng/m3 4 ) in the 1-2 μm 

bin, 53% of the Pb mass (14 ng/m3) in the 0.2-1.0 μm bin, and 24% (7 ng/m3 5 ) collected below the 0.2 μm 

6 cut point. Regression analysis against NOX concentration in the Harrison et al. (2003) paper provided a 

weak indication that Pb-PM0.2 was associated with traffic (β = 0.067, R2 7 = 0.38) as well as PM10 (β = 0.26, 

R2 8 = 0.35). Brüggemann et al. (2009) observed a unimodal Pb size distribution with 51% of the mass in 

9 the 0.42-1.2 μm size bin. During winter, Pb concentrations were twice as high as during the summer, and 

10 they were also higher when winds blew from the east. Brüggemann et al. (2009) suggested that this 

11 finding reflected coal burning sources rather than road dust resuspension. Wang et al. (2006) observed a 

12 bimodal Pb distribution in a heavily trafficked area of Kanazawa, Japan with incineration and generation 

13 facilities also nearby. They observed a bimodal distribution with modes at the 0.65-1.1 μm and the 3.3-4.7 

14 μm size bins. Wang et al.’s (2006) source apportionment work in this study suggested that the fine mode 

15 derives from incineration and combustion of oil and coal.

16 Spatial and temporal concentration variability is also reflected in varying Pb-PM size distributions 

17 within and between cities. Martuzevicius et al. (2004) measured the size distribution of Pb in Cincinnati, 

18 OH at the city center site using a MOUDI and showed it to be bimodal with a primary peak at 0.56 μm 
May 2011 3-82 DRAFT – DO NOT CITE OR QUOTE

1 and a slightly smaller secondary peak at 5.6 μm. Moreno et al. (2008) measured Pb concentrations in 

2 PM2.5 and PM10 at urban, suburban, and rural sites around Mexico City, Mexico to illustrate differences 

among the land use categories. At the urban site, average Pb-PM2.5 concentration was 30 ng/m3 3 during the 

day and 92 ng/m3 at night, and average Pb-PM10 concentration was 59 ng/m3 4 during the day and 

162 ng/m3 5 at night, to yield PM2.5/PM10 ratios of 0.51 during the day and 0.57 at night. At the suburban 

site, average Pb-PM2.5 concentration was 15 ng/m3 during the day and 34 ng/m3 6 at night, and average PbPM10 concentration was 24 ng/m3 during the day and 42 ng/m3 7 at night, to yield PM2.5/PM10 ratios of 0.63 

during the day and 0.81 at night. Rural measurements were only made for Pb-PM10 and averaged 6 ng/m3 8

during the day and 5 ng/m3 9 at night. Goforth et al. (2006) measured TSP and PM2.5 in rural Georgia and 

observed a PM2.5 concentration of 6 ng/m3 and a TSP concentration of 15 ng/m3 10 . Makkonen et al. (2010)

11 measured concentrations of Pb in PM1, PM2.5, and PM10 during a spate of wildfires in rural southeastern 

12 Finland. They found that the ratio of PM1/PM10 varied substantially from day to day (examples provided 

13 of 64% on 8/14/07 and 35% on 8/25/07, with PM2.5/PM10 ratio of 51% on 8/25/07), and they attributed the 

14 highest concentrations to long-range transport of wildfire emissions via southerly winds; variability in 

15 concentration and ratios was related to shifting wind conditions. Birmili et al. (2006) compared 

16 concentrations of Pb in PM at various traffic and background sites in Birmingham, U.K.. captured at the 

17 stage below a 0.5 μm cutpoint and on the 1.5-3.0 μm stage for near-road, in a traffic tunnel, and remote 

and urban background sites. The highest concentrations were measured in the tunnel, at 3.3 ng/m3 18 for PbPM0.5 and 10 ng/m3 19 for Pb-PM1.5-3.0. Roadside concentrations were low. During the day, Birmili et al. 

(2006) measured 0.4 ng/m3 for Pb-PM0.5 and 1.2 ng/m3 20 for Pb-PM1.5-3.0. At night, roadside concentrations 

reduced to 0.17 ng/m3 for Pb-PM0.5 and 0.6 ng/m3 21 for Pb-PM1.5-3.0. In contrast, urban background was 

more enriched in the finer size fraction, with concentrations of 5.4 ng/m3 for Pb-PM0.5 and 0.84 ng/m3 22 for 

Pb-PM1.5-3.0. Remote background concentrations were on 0.16 ng/m3 for Pb-PM0.5 and 0.03 ng/m3 23 for Pb24 PM1.5-3.0. Brüggemann et al. (2009) measured roadside distribution of Pb in PM in Dresden, Germany to 

25 analyze the effect of season and direction of the air mass. For all data combined as well as for data broken 

26 down by season or by wind direction, it was found that the data followed a unimodal distribution with a 

27 peak at the 0.42-1.0 μm size bin. The distribution of data along the curves did not change substantially 

28 under the different conditions examined. When winds came from the east, the total concentration was 

approximately 22 ng/m3, compared with a concentration of approximately 13 ng/m3 29 when winds came 

from the west. Total winter concentrations of Pb were approximately 26 ng/m3 30 , while summertime 

concentrations were roughly 11 ng/m3 31 .

3.5.4. Lead Concentrations in a Multipollutant Context

32 The correlations between Pb and copollutant concentrations were investigated because correlation 

33 may indicate commonality of sources among the pollutants. For example, correlation between Pb and SO2
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US Overall

Spearman Correlation Coefficient

-1.0 -0.5 0.0 0.5 1.0

1 may suggest common industrial sources. Correlation between Pb and NO2 or CO may suggest roadway 

2 sources, such as trace Pb in unleaded on-road gasoline or resuspension of Pb wheel weights or 

3 contaminated soil. Additionally, seasonality can influence correlations, potentially from differences 

4 among sources or the contaminants’ responses to climate differences.

5 Pb concentrations exhibit varying degrees of association with other criteria pollutant 

6 concentrations. Spearman correlations of monitored TSP-Pb concentrations with concentrations of other 

7 criteria pollutants are summarized in Figure 3-24 for 2007-2008 data from 129 monitoring sites, and in 

8 Figure 3-25 for 2009 data from 16 monitoring sites. At most sites, Pb monitors are co-located with 

9 monitors for other criteria pollutants, but monitoring the full suite of criteria pollutants at a single 

10 monitoring site is rare. As a result the number of observations for each copollutant varies, ranging from 

11 44 non-source oriented sites for the association of Pb with SO2 to 81 sites for the association of Pb with 

12 PM10. In Figure 3-24, and fewer for each copollutant in Figure 3-25. Each of these figures illustrates co13 pollutant correlations across the U.S. Additionally, seasonal correlations between Pb and co-pollutants are 

14 provided in Figures 3A-19 through 3A-21 in the Chapter 3 Appendix, with seasonal co-pollutant 

15 measurement data from the literature (Table 3A-14). As evident in each figure, there were considerably 

16 fewer source-oriented sites available for co-located comparisons.

Source, SO2

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Source, PM10

Non-Source, PM10

Source, O3

Non-Source, O3

Source, NO2

Non-Source, NO2

Source, CO

Non-Source, CO

Figure 3-24. Correlations of monitored Pb-TSP concentration with 

copollutant concentrations, 2007-2008.
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US Overall

Spearman Correlation Coefficient

-1.0 -0.5 0.0 0.5 1.0

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Non-Source, PM10

Non-Source, O3

Non-Source, NO2

Non-Source, CO

Figure 3-25. Correlations of monitored Pb-TSP concentration with copollutant concentrations, 2009.

1 Overall, Pb was most strongly associated with PM2.5, PM10 and NO2 (median R = 0.38 to 0.41), 

2 with positive Spearman correlation coefficients observed at nearly all sites. However, Pb was just as 

3 strongly associated with CO in fall and winter (median R = 0.48 to 0.58). Such correlations may suggest 

4 common sources affecting the pollutants. Overall correlation coefficients between Pb and SO2 and 

5 between Pb and CO were also positive at most sites, but associations were generally weaker (median R = 

6 0.29 for CO, 0.17 for SO2). The poorest associations were observed between Pb and O3 (median R = 

7 0.00). Although the overall associations of Pb concentration with PM10 and PM2.5 concentrations were 

8 similar, the association with PM10 was stronger in the spring and the association with PM2.5 stronger in 

9 summer and fall. The strongest associations between Pb and other criteria pollutants were observed in fall 

10 and winter, and the weakest in summer.

11 The relationship between Pb and other species in PM2.5 is explored in Figure 3-26, which describes 

12 data from 3 years of CSN results. These data provide a national perspective on relationships between the 

13 various bulk and elemental species monitored in the CSN network. The strongest association was with Zn 

14 (median R = 0.51). Br, Cu, and K concentrations also exhibited moderately strong associations with Pb 

15 concentrations (median R = 0.40 to 0.41). Such correlations may suggest some common sources affecting 

16 the pollutants. Other species more useful for as diagnostic indicators of crustal, general combustion, 

17 industrial emission, and coal combustion processes exhibited weaker, but still remarkable associations 

18 with Pb, including crustal elements (median R = 0.32), EC (median R = 0.32), Mn and Fe (median R = 

19 0.32 and 0.34, respectively), S (median R = 0.27), and Se (median R = 0.27). Except for S, in summer 
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1 associations with each of these species were much weaker than in other seasons, with a Spearman 

2 Correlation Coefficient greater than R = 0.3 observed only for Zn (median R = 0.37). The weakest 

3 associations were with As, Cl, Hg, Ni, NO3, and Na (median R = -0.03 to 0.10).
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US Overall

Spearman Correlation Coefficient

-1.0 -0.5 0.0 0.5 1.0

r

r

Zinc

Volatile Nitrate

Vanadium

Titanium

Sulfur

Sulfate

Sodium Ion

Sodium

Silicon

Selenium

Potassium Ion

Potassium

Organic Carbon, Blank Adjusted

Non-Volatile Nitrate

Nitrate

Nickel

Mercury

Manganese

Magnesium

Iron

Elemental Carbon

Crustal

Copper

Chromium

Chlorine

Carbonate Carbon

Calcium

Cadmium

Bromine

Arsenic

Ammonium

Aluminum

Figure 3-26. Correlations of monitored lead-PM2.5 concentration with 

copollutant concentrations, 2007-2009.
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3.6. Ambient Lead Concentrations in Non-Air 

Media and Biota

1 There have been some major recent research efforts to characterize geographic and temporal trends 

2 in Pb concentrations in across a variety of environmental media and biota. In general these concentrations 

3 reflect the decreases observed in atmospheric Pb concentrations due to reduced on-road Pb emissions. 

4 The 2006 Pb AQCD (U.S. EPA, 2006) describes several studies showing higher Pb concentrations 

5 in plants grown in Pb contaminated soil related to mine spoils, smelting operations, sludge amendment, 

6 contaminated irrigation water, and Pb containing agro-chemicals. Pb accumulation occurs more readily 

7 for Pb salts applied to soils than for sewage sludge or fly ash. Root uptake is the dominant means of 

8 accumulation, and it is strongly influenced by pH. Root vegetables are the most strongly affected, and 

9 fruits and grains are the least susceptible. More Pb is also generally found in roots than in other parts of 

10 the plant.

11 The 2006 Pb AQCD (U.S. EPA, 2006) identified ingestion and water intake as major routes of Pb 

12 exposure for aquatic organisms, and it identified food, drinking water, and inhalation as major routes of 

13 exposure for livestock and terrestrial wildlife. The 2006 Pb AQCD (U.S. EPA, 2006) reports data from the 

14 U.S. Geologic Service National Water-Quality Assessment (NAWQA), which are updated every ten years. 

15 In the NAWQA survey, maxima concentrations in surface waters, sediments, and fish tissues were 

16 30 μg/L, 12,000 mg/kg, and 23 mg/kg, respectively, compared with median values of 0.50 μg/L, 

17 28 mg/kg, and 0.59 mg/kg. Some of the highest levels of Pb contamination occur near major sources, like 

18 smelters, and fatal doses have been measured in tissue from sheep and horses near sources. High levels in 

19 cattle have also been observed. Wildlife in urban areas tend to contain higher Pb concentrations than in 

20 rural areas, and higher Pb accumulations have been observed for aquatic organisms living in polluted 

21 coastal zones than in the open sea. Ingestion of deposited Pb-PM on plant surfaces was consistently 

22 observed to be more important than Pb accumulated from soil. Some important variations between 

23 animals have been observed, and ruminants appear to be less susceptible to Pb uptake than other animals. 

24 Uptake of Pb by lowest trophic levels, including invertebrates, phytoplankton, krill, were described as the 

25 most important means of introduction into food chains. Elevated Pb levels have been observed in aquatic 

26 organisms that feed from sediments when the sediments contain appreciable Pb. In shrimp, a substantial 

27 fraction of Pb can be absorbed from prey, and considerably more accumulated Pb from food has been 

28 observed to be irreversibly retained than is the case for dissolved Pb from water. These examples all 

29 illustrated that substantial Pb uptake by livestock and wildlife readily occurs in Pb contaminated 

30 environments.
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3.6.1. Soils

1 Several studies suggest that soil can act as a reservoir for contemporaneous and historical Pb 

2 emissions. In a recent review of soil data collected from 90 U.S. cities, Mielke et al. (2010b) cited studies, 

3 some of which were 35 years old but many from the last 15 years, reporting that median soil Pb 

4 concentrations ranged from 16 to 262 mg/kg, with maximum levels ranging from 461 to 348,000 mg/kg 

5 (see Table 3-9). Soil Pb was thought to originate from present-day sources, such as industry, debrided 

6 paint, and piston engine aircraft fuel, as well as historic sources, such as on-road gasoline emissions, as 

7 described in Section 3.2. 

8 Emissions trends have shown that industrial activities are now one of the largest sources of Pb 

9 following phase out of Pb in on-road gasoline. Pruvot et al. (2006) compared urban and agricultural soils 

10 near a closed Pb smelter with soils in similar environments not exposed to smelter emissions in northern 

11 France. For samples near the smelter, Pruvot et al. (2006) observed that median soil Pb levels in lawns 

12 were roughly 2 times higher, while kitchen garden soil Pb concentrations were 10 times higher and 

13 agricultural soil Pb was almost 15 times higher than soil not exposed to smelter emissions. In soil samples 

14 obtained near a defunct smelter in El Paso, TX, in 1999 and 2005, Pingatore et al. (2009) found that TSP 

15 concentration was predicted strongly by concentrations of Pb-humate, which is created by sorption of Pb 

16 onto humic substances in soil. Spalinger et al. (2007) compared soil Pb samples from surrounding towns 

17 with those from the Bunker Hill Superfund remediation site in Idaho. Median background soil Pb 

18 concentrations was 48 mg/kg, while the median soil Pb concentration at Bunker Hill was 245 mg/kg.

Table 3-9. Outdoor soil Pb levels in various cities within the U.S.

Study Year n Mina Meda Maxa

Background soil Pb, U.S. 2001 1,319 16.5

City-State

Los Angeles, California 2010 550 9 216,174

Los Angeles, California 1995 343

Chicago Illinois 2008 57

Chicago Illinois 1987 667

Chicago-Urban Parks 1986 255 12 262 1,312

Chicago-Suburban Parks 1986 245 12 87 1,637

Illinois, Rural Parks 1986 177 12 37 937

Detroit, Michigan 2003 59 13 189 1,345

Detroit-Suburbs, Michigan 2003 76 4 16 810

Pontiac, Michigan 2003 38 15 86 495

Oakland, California 1995 358 7 347,900

Alameda, California 1993 138 22 3,187

Boston, Massachusetts 1988 195 7 13,240

Miami, Florida 2004 240 2 1,060

Seattle, Washington 1991 51 150 74,000

Washington, D.C. 1995 240 12 6,015

Minneapolis/St. Paul, Minnesota 1984 90 5 7,650

Minneapolis, Minnesota 1988 898 1 230 20,136

St. Paul, Minnesota 1988 832 1 170 7,994

Duluth, Minnesota 1988 229 1 144 11,110

St. Cloud, Minnesota 1988 124 1 41 1,952

Rochester, Minnesota 1988 165 1 25 1,930

Outstate farms Minnesota 1988 781 1 31 7,111

Cleveland, Ohio 2006 50 19 811

Baltimore, Maryland 2008 122 0.01 5,620
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Study Year n Mina Meda Maxa

Baltimore, Maryland 1983 422 1 100 10,900

Indianapolis, Indiana 2005 116 46 565

Milwaukee, Wisconsin summary 

data

1994 372 1 160 880

Milwaukee, Wisconsin cent city + 

North and South Side

1994 256 1 240 7,220

Milwaukee, Wisconsin suburbs 1994 122 1 50 1,780

Cincinnati, Ohio 1990 60 2 3,166

Cincinnati, Ohio-Childcare centers 2008 69 17 4,636

Cincinnati, Ohio 1990 60

Sacramento, California 1995 232 57 229 320,834

Tampa, Florida 1994 146 <1 100 9,160

New Orleans, Louisiana Survey 1 2005 4,026 18 134 183,588

New Orleans, Louisiana Survey 2 2005 5,467 3 100 52,798

Louisiana Orleans Parish 1997 ~1,540 <25 >200 <1,000

Louisiana Lafourche Parish 1997 ~190 <25

Albuquerque, New Mexico 1981 43 3 5,280

Omaha, Nebraska 1979 176

Dayton, Ohio 1983 22 22 461

El Paso, Texas 2009 94 <20 8700

Honolulu, Hawaii 1988 18

Charleston, South Carolina 1975 164 9 7,890

New Haven, Connecticut 1982 487 30 7,000

Corpus Christi, Texas 1987 485 21 2,969

Pueblo, Colorado 2006 33

Connecticut 2008 174 <10 2,200

Gainesville, Florida 2004 202 2.13 1,091

Champaign Illinois 1976 116 20 1,061

Louisiana and Minnesota 1993 6,342 Urban-rural comparisons

Southeastern. Michigan 2004 171 3 7,400

Mt. Pleasant, Michigan 1992 189 100 16,839

Syracuse, New York 2009 2,998 45

Syracuse, New York 2002 162

Syracuse, New York 2002 194 80 (GM)

Lubbock, Texas 2008 52 35

Maine urban soils 1989 100

a

Minimum, median, and maximum values are reported in units of mg/kg for individual cities cited in the review paper.

Source: Used with permission from Elsevier Publishing, Mielke et al. (Mielke et al., 2010b). 

1 Several studies explore the relationship between soil Pb concentration and land use. For example, 

2 the Mielke et al. (2010b) review also found that soil Pb concentrations tended to be higher within inner3 city communities compared with neighborhoods surrounding city outskirts. Laidlaw and Filippelli (2008)

4 displayed data for Indianapolis, IN showing the Pb concentration at the soil surface had a smoothed 

5 “bull’s eye” pattern, which suggested that the Pb in soil is continually resuspended and deposited within 

6 the urban area so that smooth air and soil concentration gradients emanating from the city center could be 

7 created over time. Cities generally have a similar pattern consisting of larger quantities of Pb accumulated 

8 within the inner city and smaller quantities of Pb in outer cities (i.e. near the outskirts or suburban areas) 

9 (Filippelli & Laidlaw, 2010). Similarly, Filippelli et al. (2005) reported soil Pb concentration distribution 

10 to have a maximum at the center of Indianapolis, IN, around the location where two interstate highways 

11 intersect, and to decrease with distance away from the center. However, the spatial distribution of Pb was 

12 presumed to be smoothed over time from resuspension and deposition with contributions from historic 

13 sources of on-road gasoline and Pb paint. In this paper, soil Pb concentrations were also shown to 

14 decrease with distance from roadways, but the levels were roughly four times higher in urban areas 

15 compared with suburban areas. This is also illustrated for urban scale Pb accumulation in New Orleans, 
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1 LA in Figure 3-27. Brown et al. (2008) also measured soil Pb concentration along three transects of 

2 Lubbock, TX and observed that soil Pb decreased with increasing distance from the city center, which 

3 was the oldest part of the city. 

Source: Used with permission from Elsevier Publishing, Mielke et al. (2007)

Figure 3-27. Map of median Pb content in soil in New Orleans.At the urban 

scale, Pb quantities are largest within the inner-city residential 

communities that surround the Central Business District 

where pavement and concrete cover the soil. Note the several 

orders of magnitude difference between the interior and the 

exterior areas of the city.

4 The amount of Pb within the inner-city is likely not from a single source but instead composed of 

5 all modern and historic sources of Pb dust that have been released in the city including Pb from several 

6 local industries, Pb dust from pulverized wheel weights, deteriorated Pb-based paint, Pb additives to on7 road gasoline, and defunct incinerators that once dotted New Orleans prior to being shut down by EPA in 

8 the early 1970’s. Similarly, Mielke et al. (2008) compared soil Pb concentrations for public and private 

9 housing at the center and outer sections of New Orleans and found that median and maximum soil Pb 

10 concentrations were substantially higher in the city center compared with the outer portions of the city. 

11 This study also found that private residences had higher soil Pb compared with public housing. In a 

12 separate study to examine surface soil Pb loading and concentration on 25 properties in New Orleans, 

13 Mielke et al. (2007) observed median and maxima deposition values of roughly 25,000 and 
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265,000 μg/m2 1 , respectively. Median and maxima surface soil Pb concentrations were observed to be 

2 1,000 and 20,000 mg/kg, respectively. Clark et al. (2006) performed isotopic analysis on urban garden 

3 soils in Boston, MA and estimated that 60% of the soil Pb could be attributed to historic Pb on-road 

4 gasoline emissions in an urban area of the city while 14% could be attributed to historic Pb on-road 

5 gasoline emissions in a suburban area. The remainder of the Pb was attributed to paint degradation. 

6 Several studies have examined the effects of roadways on Pb content in roadside dust. In an 

7 analysis of the relationship between land use parameters and Pb concentration in soil in Los Angeles, Wu 

8 et al. (2010) observed that soil Pb concentration was higher near freeways and major traffic arteries 

9 compared with other locations. The age of the land parcel (square-root transformed), length of highway 

10 within a 1,000 m buffer, and length of local road within a 20 m buffer in which the sample was obtained 

11 were significant predictors of Pb. Home age within 30 m of a soil sample and road length within 3,000 m 

12 of a road sample were also shown to be significant predictors of soil Pb concentration in areas not 

13 designated to be near a freeway or major traffic artery. Wu et al. (2010) concluded that both historical 

14 traffic and leaded paint contributed to Pb contamination in soils. Amato et al. (2009) observed that 

15 deposited PM10 onto roadways, measured as dust samples, in Barcelona, Spain was differentially enriched 

16 with Pb. Pb concentration in PM10 was highest at ring roads (229 ppm) and in the city center (225 ppm), 

17 followed by demolition and construction sites (177 ppm) and near a harbor (100 ppm). Joshi et al. (2008)

18 also observed Pb dust concentrations to be highest at industrial sites followed by commercial and 

19 residential sites in Singapore. 

20 Two recent studies focused on Pb from paint degradation by examining Pb dust loading to hard 

21 surfaces located along transects of each of the five boroughs of New York City (Caravanos et al., 2006; 

22 Weiss et al., 2006). Caravanos et al. (2006) used GIS to examined Pb dust loadings on top of pedestrian 

23 traffic signals and observed “hot spots,” defined by the authors as at least twice the Pb dust loading at

24 adjacent samples near major elevated bridges in upper Manhattan, the Bronx, and Queens. In Brooklyn 

25 and Staten Island, areas with high dust loading were not clearly attributed to a source. “Low spots,” 

26 defined by the authors as at least two times lower Pb dust loading compared with adjacent samples were 

27 observed in lower Manhattan, were thought to correspond with intensive cleaning efforts that followed 

28 the September 11, 2001 World Trade Center attack. Weiss et al. (2006) studied Pb concentrations of grit 

29 (granules of mixed composition found to accumulate alongside street curbs) along the transects and found 

30 that median Pb concentrations in grit under the elevated steel structures were 2.5-11.5 times higher than 

31 those obtained away from steel structures; 90th percentile values were up to 30 times higher near steel 

32 structures compared with those further from these structures.

33 Outdoor Pb dust has been also associated with demolition activities. Farfel et al. (2003, 2005)

34 measured Pb dust within 100 m of a demolition site before, immediately after, and 1 month following the 

35 demolition. They found that the rate of Pb dust fall increased by a factor of more than 40 during 

36 demolition (Farfel et al., 2003). Immediately after demolition, one demolition site had dust loadings 
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increase by a factor of 200% for streets (87,000 μg/m2), 138% for alleys (65,000 μg/m2 1 ), and 26% for 

sidewalks (23,000 μg/m2 2 ) compared with pre-demolition Pb dust levels. At another demolition site, 

smaller increases were observed: 29% for streets (29,000 μg/m2), 18% for alleys (19,000 μg/m2 3 ) and 18% 

for sidewalks (22,000 μg/m2 4 ) (Farfel et al., 2005). 

5 Pb can be present in soils located where ammunition is used for military or hunting purposes. In a 

6 study of Pb content in sand used to cover a firing range, Lewis et al. (2010) found that 93% of bullet mass 

7 was recovered in the top 0.3 m of the sand, and 6.4% was recovered at a depth of 0.3-0.45 m. Pb oxides 

8 were observed to be the dominant species in the contaminated sand. Berthelot et al. (2008) studied soil Pb 

9 concentrations in grounds used for testing military tanks and munitions and measured soil Pb levels to 

10 range from 250 to 2,000 mg/kg. 

11 Soil Pb variability depends on the strength and prevalence of nearby sources. Griffith et al. (2002)

12 investigated spatial autocorrelation of soil Pb concentration at three sites: urban Syracuse, NY, rural Geul 

13 River, The Netherlands, and an abandoned Pb Superfund site in Murray, UT. In both Syracuse and Geul 

14 River, the soil Pb concentrations were not strongly correlated in space, with the exception of soil obtained 

15 near roads, which exhibited less variability. The smelting and shooting areas of the Superfund site were

16 both demonstrated to have spatial clusters that were well correlated. These results suggest that soil Pb 

17 concentration tends to be spatially heterogeneous in the absence of a source. Later work on the spatial 

18 distribution of metals in Syracuse produced similar results for that city (Griffith et al., 2009). These 

19 studies did not adjust for age of housing, although Griffith et al. (2009) did find that housing age and Pb 

20 co-vary. An association between housing age and soil Pb would likely be enhanced by such co-variation.

3.6.2. Sediments

21 The recently completed Western Airborne Contaminants Assessment Project (WACAP) is the most 

22 comprehensive database, to date, on contaminant transport and depositional effects on sensitive 

23 ecosystems in the U.S. (Landers et al., 2010). The transport, fate, and ecological impacts of semi-volatile 

24 compounds and metals from atmospheric sources were assessed on ecosystem components collected from 

25 2002-2007 in watersheds of eight core national parks (Landers et al., 2008). The goals of the study were 

26 to assess where these contaminants were accumulating in remote ecosystems in the Western U.S., identify 

27 ecological receptors for the pollutants, and to determine the source of the air masses most likely to have 

28 transported the contaminants to the parks. Although, Pb was measured in snow, water, sediment, lichen 

29 and fish during the multiyear project, this metal was not quantified in air samples.

30 In the WACAP study, bioaccumulation of airborne contaminants was demonstrated on a regional 

31 scale in remote ecosystems in the Western U.S. Contaminants were shown to accumulate geographically 

32 based on proximity to individual sources or source areas, primarily agriculture and industry. This finding 
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1 was counter to the original working hypothesis that most of the contaminants found in western parks 

2 would originate from eastern Europe and Asia. 

3 Pb concentrations in sediments from all lakes in which Pb was measured in the conterminous 48 

4 states exhibited higher Pb concentrations near the surface relative to preindustrial Pb levels measured at 

5 greater depth. This was not the case for other metals measured, except for cadmium (Cd) and mercury 

6 (Hg). Sediments in most lakes exhibited maximum concentrations between 1960 and 1980, followed by a 

7 decrease. A clear decline in Pb concentrations in sediments after the discontinued use of leaded on-road 

8 gasoline was observed at almost all WACAP locations in the for nearly all WACAP sites in the 

9 conterminous 48 states. Pb concentrations in sediments were much lower in Alaska, and no such decline 

10 was observed. Pb in sediments was mainly attributed to on-road gasoline use, but for some lakes a strong 

11 influence from other local sources of Pb to lake sediments was shown to be important, including Pb 

12 mining, smelting, logging, and other industrial activities. Pb was also consistently observed in WACAP 

13 fish and wildlife samples. 

14 Data from select regions of the U.S. illustrate that Pb concentrations in surface waters and sediment 

15 are likely to be higher in urbanized areas compared with rural locations. Table 3-10 presents data from 

16 seven metropolitan areas (Cobb et al., 2006). Differences among the intraurban concentration ranges 

17 illustrate a high level of spatial variability within individual cities as well as high interurban variability. 

18 The rural New Orleans site reported relatively low Pb sediment concentrations, and the highest Pb 

19 sediment concentrations were reported for the city of New Orleans. Figure 3-28 and Figure 3-29 illustrate 

20 such variability within a single watershed for the Apalachicola, Chattahoochee, and Flint River Basin, 

21 which runs south from north of the greater Atlanta, GA metropolitan area and drains into the Gulf of 

22 Mexico at the Apalachicola Bay in the Florida panhandle. Sediment concentrations peaked near the 

23 Atlanta area and diminished as distance from the Apalachicola Bay decreased. This observation suggests 

24 that rural areas have lower Pb sediment levels compared with urban areas. The data also illustrated that Pb 

25 concentrations in sediment have declined in the U.S. since 1975 (Figure 3-29), prior to the phase-out of 

26 on-road leaded gasoline.

Table 3-10. Sediment concentrations in various cities, prior to 2005 

City Avg Pb Concentration (mg/kg)a Pb Concentration Range (mg/kg)a

Baltimore, MD 1-10,900

Miami, FL 275 25-1612

Mt. Pleasant, MI 320 100-840

New Orleans, LA 784 31.7-5195

New Orleans, LA (rural outskirts) 11 4.8-17.3

St. Louis, MO 427 35-1860

Syracuse, NY 80 20-800

a

Dry weight basis.

Source: Used with permission from the American Chemical Society, Cobb et al. (2006).
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Source: Used with permission from the American Chemical Society, Callender and Rice (2000).

Figure 3-28. Sediment core data (1992-1994) for the lakes and reservoirs 

along the Apalachicola, Chattahoochee, and Flint River Basin 

(ACF), which feeds from north of the Atlanta, GA metropolitan 

area into the Gulf of Mexico at Apalachicola Bay in the Florida 

panhandle.Note that background refers to concentrations from 

undeveloped geographic regions and baseline samples are 

obtained from the bottom of the sediment core to minimize 

anthropogenic effects on the sample.
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Source: Used with permission from the American Chemical Society, Callender and Rice (2000).

Figure 3-29. Sediment core data (1975-1995) for the lakes and reservoirs 

along the Apalachicola, Chattahoochee, and Flint River Basin 

(ACF), which feeds from north of the Atlanta, GA metropolitan 

area into the Gulf of Mexico at Apalachicola Bay in the Florida 

panhandle.Note that background refers to concentrations from 

undeveloped geographic regions and baseline samples are 

obtained from the bottom of the sediment core to minimize 

anthropogenic effects on the sample.

1 Many recent studies have illustrated the effects of natural disasters on Pb concentrations in surface 

2 water and sediment in the wake of Hurricane Katrina, which made landfall on August 29, 2005 in New 

3 Orleans, LA, and Hurricane Rita, which made landfall west of New Orleans on September 23, 2005. 

4 Pardue et al. (2005) sampled floodwaters on September 3 and September 7, 2005 following the hurricanes 

5 and observed that elevated concentrations of Pb along with other trace elements and contaminants were 

6 not irregular for stormwater but were important because human exposure to the stormwater was more 

7 substantial for Hurricane Katrina than for a typical storm. Floodwater samples obtained throughout the

8 city on September 18, 2005 and analyzed for Pb by Presley et al. (2006) were below the limit of detection. 

9 Likewise, Hou et al. (2006) measured trace metal concentration in the water column of Lake 

10 Pontchartrain and at various locations within New Orleans during the period September 19 through 

11 October 9, 2005 and found that almost all Pb concentrations were below the limit of detection. However, 
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1 several studies noted no appreciable increase in Pb concentration within Lake Pontchartrain soils and 

2 sediments (Abel et al., 2010; Abel et al., 2007; Cobb et al., 2006; Presley et al., 2006; K. J. Schwab et al., 

3 2007). Shi et al. (2010) analyzed Lake Pontchartrain sediment samples using a factored approach and 

4 found that most Pb was sequestered in carbonate-rich, iron oxide-rich, and magnesium oxide-rich 

5 sediments in which it can be more readily mobilized and potentially more bioaccessible. Zahran et al. 

6 (2010) and Presley et al. (2010) noted that soil Pb samples obtained outside schools also tended to 

7 decrease in the wake of Hurricanes Katrina and Rita, with some sites observing substantial increases and 

8 others noting dramatic reductions. These studies suggest that floodwaters can change the spatial 

9 distribution of Pb in soil and sediments to result in increased or reduced concentrations.

3.6.3. Rain

10 Recent results from locations outside the United States were consistent with decreasing rain water 

11 concentrations described in the 2006 Pb AQCD, reflecting the elimination of Pb from on-road gasoline in 

12 most countries. From the 2006 Pb AQCD (U.S. EPA, 2006), volume weighted Pb concentrations in 

13 precipitation collected in 1993-94 from Lake Superior, Lake Michigan and Lake Erie ranged from ~0.7 to 

14 ~1.1 μg/L (Sweet et al., 1998). These values fit well with the temporal trend reported in Watmough and 

15 Dillon (2007), who calculated annual volume-weighted Pb concentrations to be 2.12, 1.17 and 0.58 μg/L

16 for 1989-90, 1990-91 and 2002-03, respectively, in precipitation from a central Ontario, Canada, forested 

17 watershed. A similar value of 0.41 μg/L for 2002-03 for Plastic Lake, Ontario, was reported in Landre et 

18 al. (2009). For the nearby Kawagama Lake, Shotyk and Krachler (2010) gave Pb concentrations in 

19 unfiltered rainwater collected in 2008. For August and September 2008, the values were 0.45 and 

20 0.22 μg/L, respectively, and so there had been little discernible change over the post-2000 period. In 

21 support, Pb concentrations in snow pit samples collected in 2005 and 2009 collected 45 km northeast of 

22 Kawagama Lake had not changed to any noticeable extent (0.13, 0.17, and 0.28 μg/L in 2005; 0.15 and

23 0.26 μg/L in 2009) (Shotyk & Krachler, 2010).

24 There have also been a few recently published, long-term European studies of Pb concentration in 

25 precipitation including Berg et al. (2008) and Farmer et al. (2010). Berg et al. (2008) compared the trends 

26 in Pb concentration in precipitation at Norwegian background sites in relation to the decreasing European 

27 emissions of Pb over the period 1980-2005. The Birkenes site at the southern tip of Norway is most 

28 affected by long-range transport of Pb from mainland Europe but there had been a 97% reduction in the 

29 concentration of Pb in precipitation over the 26-year time period. This was similar to the reductions of 

30 95% and 92% found for the more northerly sites, Karvatn and Jergul/Karasjok, respectively (Figure 3-30). 

31 A decline of ~95% in Pb concentrations in moss (often used as a biomonitor of Pb pollution) from the 

32 southernmost part of Norway, collected every 5 years over the period 1977-2005, agreed well with the 

33 Birkenes precipitation results (Berg et al., 2008). The reductions in Pb concentration in both precipitation 
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1 and moss appear to agree well with the reductions in emissions in Europe (~85%) and Norway (~99%). 

2 However, similarly to the situation in the U.S., the greatest reductions occurred by the late 1990s and only 

3 relatively minor reductions have occurred thereafter; see Figure 3-30.

Source: Used with permission from Pergamon Press, Berg et al. (2008)

Figure 3-30. Trends in Pb concentration in precipitation from various sites 

in Norway over the period 1980-2005. 

4 Farmer et al. (2010) showed the trends in concentration of Pb in precipitation collected in a remote 

5 part of northeastern Scotland over the period 1989-2007. The 2.6- and 3.0-fold decline in mean 

6 concentration from 4.92 μg/L (1989-1991) to 1.88 μg/L (1999) and then to 0.63 μg/L (2006-2007) is 

7 qualitatively but not quantitatively in line with the sixfold decline in annual total U.K. emissions of Pb to 

8 the atmosphere over each of these time periods. Since the outright ban on the use of leaded on-road 

9 gasoline in 2000, however, the ratio of Pb concentrations in rainwater to U.K. Pb emissions (metric tons) 

10 appears to have stabilized to a near-constant value of 0.009 μg/L per metric ton. The concentrations in 

11 precipitation reported in these studies are all at the lower end of the range reported in the 2006 Pb AQCD 

12 (U.S. EPA, 2006), and similar to concentrations reported for those studies conducted after the removal of 

13 Pb from on-road gasoline. Overall, recent studies of wet deposition tended to confirm the conclusions of 

14 the 2006 Pb AQCD (U.S. EPA, 2006) that wet deposition fluxes have greatly decreased since the removal 

15 of Pb from on-road gasoline.

3.6.4. Snowpack

16 The location of Pb deposition impacts its further environmental transport. For example, Pb

17 deposited to some types of soil may be relatively immobile, while Pb deposited to snow is likely to 
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1 undergo further transport more easily when snow melts. Deposition to snow was investigated in several 

2 studies. Seasonal patterns of heavy metal deposition to snow on Lambert Glacier basin, east Antarctica, 

3 were determined by Hur et al. (2007). The snow pit samples covered the period from austral spring 1998 

4 to summer 2002 and Pb concentrations ranged from 1.29-9.6 pg/g with a mean value of 4.0 pg/g. This 

5 was similar to a mean value of 4.7 pg/g (1965-1986) obtained by Planchon et al. (2003) for Coats Land, 

6 northwest Antarctica. Estimated contributions to the Pb in Lambert Glacier basin snow were ~1% from 

7 rock and soil dust (based on Al concentrations) and ~4.6% from volcanoes (based on the concentrations 

8 of nss-sulfate). There was almost negligible contribution from seaspray (based on Na concentrations), and 

9 so it was suggested that a substantial part of the measured Pb concentration must originate from 

10 anthropogenic sources. Highest Pb concentrations were generally observed in spring/summer with an 

11 occasional peak in winter. This contrasts with data for the Antarctic Peninsula, where highest 

12 concentrations occurred during autumn/winter, and again with Coats Land, where high concentrations 

13 were observed throughout the winter. These differences were attributed to spatial changes in input 

14 mechanism of Pb aerosols arriving at different sites over Antarctica, which could be due to their different 

15 source areas and transport pathways. Hur et al. (2007), however, suggested that the good correlation 

16 between Pb and crustal metals in snow samples shows that Pb pollutants and crustal PM are transported 

17 and deposited in Lambert Glacier basin snow in a similar manner. 

18 Lee et al. (2008) collected 42 snow samples during the period autumn 2004-summer 2005 from a 

19 2.1 m snow pit at a high-altitude site on the northeast slope of Mount Everest, Himalayas. Pb 

20 concentrations ranged from 5-530 pg/g with a mean value of 77 pg/g. The mean value is clearly higher 

21 than the Hur et al. (2007) value for Antarctica but is substantially lower than a mean concentration of 573 

22 pg/g for snow from Mont Blanc, France (1990-1991) (collated in 2008). The mean Pb concentration for 

23 Mount Everest snow was lower during the monsoon (28 pg/g) compared with the non-monsoon periods 

24 (137 pg/g). From calculated enrichment factors (Pb/Alsnow:Pb/Alcrust), anthropogenic inputs of Pb were 

25 partly important but soil and rock dust also contributed. The low Pb concentrations during monsoon 

26 periods are thought to be attributable to low levels of atmospheric loadings of crustal dusts. K. Lee et al.

27 (2008) noted that their conclusions differ from those in Kang et al. (2007), who stated that anthropogenic 

28 contributions of Pb to Mount Everest snow were negligible because the Everest concentrations were 

29 similar to those in Antarctica. Kang et al. (2007) did not take account of the difference in accumulation 

30 rates at the two sites and had also used Pb concentrations for Antarctic snow from a study by Ikegawa et 

31 al. (1999). Lee et al. (2008) suggested that these Pb concentrations were much higher than expected and 

32 that their snow samples may have suffered from contamination during sampling and analysis.
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3.6.5. Natural Waters

1 Shotyk and Krachler (2007) measured Pb concentrations in six artesian flows in Simcoe County, 

2 near Elmvale, Ontario, Canada. The values ranged from 0.9 to 18 ng/L with a median (n = 18) of 

3 5.1 ng/L. These are comparable with reports of a range of 0.3-8 ng/L for Lake Superior water samples

4 (Field & Sherrell, 2003). Shotyk and Krachler (2007) also commented that such low concentrations for 

5 ground and surface waters are not significantly different from those (5.1 ± 1.4 ng/L) reported for Arctic 

6 ice from Devon Island, Canada, dating from 4,000-6,000 years ago. In a separate study, Shotyk and 

7 Krachler (2009) reported concentrations of Pb in groundwater (from two locations, Johnson and Parnell), 

8 surface water (Kawagama Lake) and contemporary snow (Johnson and Parnell). The lowest mean 

9 dissolved Pb concentrations were found for groundwater: 5.9 (Johnson, n = 11) and 3.4 (Parnell, n =

10 12) ng/L. For lake water the mean Pb concentration was 57 (Kawagama Lake, n = 12) ng/L and that for 

11 contemporary snow was 672 (Johnson, n = 6; Parnell, n = 3) ng/L. Shotyk et al. (2010) gave additional 

12 values for Pb in contemporary snow samples and these were again higher than for ground and surface 

13 waters. Luther Bog and Sifton Bog snow had mean Pb concentrations of 747 and 798 ng/L, respectively. 

14 The relatively high concentrations in snow were attributed to contamination with predominantly 

15 anthropogenic Pb, although it was noted that the extent of contamination was considerably lower than in 

16 past decades. The extremely low concentrations of Pb in the groundwaters were attributed to natural 

17 removal processes. Specifically, at the sampling location in Canada, there is an abundance of clay 

18 minerals with high surface area and high cation exchange capacity and these, combined with the elevated 

19 pH values (pH=8.0) resulting from flow through a terrain rich in limestone and dolostone, provide 

20 optimal circumstances for the removal of trace elements such as Pb from groundwater. Although such 

21 removal mechanisms have not been demonstrated, the vast difference between Pb concentration in snow 

22 and that in the groundwaters indicate that the removal process is very effective. Shotyk and Krachler 

23 (2010) speculate that even at these very low Pb concentrations, much if not most of the Pb is likely to be 

24 colloidal, as suggested by the 2006 Pb AQCD (U.S. EPA, 2006). Finally, Shotyk et al. (2010) suggest that 

25 the pristine groundwaters from Simcoe County, Canada, provide a useful reference level against which 

26 other water samples can be compared. 

27 Although Pb concentrations in Kawagama Lake water were approaching “natural values,” the 

206

Pb/207 28 Pb ratios for the samples that had the lowest dissolved Pb concentrations of 10, 10 and 6 ng/L

29 were 1.16, 1.15 and 1.16, respectively. These values are far from those expected for natural Pb (the clay 

30 fraction from the lake sediments dating from the pre-industrial period had values of 1.19-1.21) and it was 

31 concluded that most of the dissolved Pb in the lake water was of industrial origin. Shotyk and Krachler 

32 (2010) found that the full range of isotope ratios for Kawagama Lake water samples (Ontario, Canada) 

33 was 1.09 to 1.15; this was not only much lower than the stream water values entering the lake but also 

34 lower than the values attributed to leaded on-road gasoline in Canada (~1.15). The streamwater ratio 
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1 values were ~1.16 to 1.17 whilst those for rainwater were as low as 1.09, in good agreement with the 

2 lower lake water values. This means that there must be an additional atmospheric source of Pb, which has 

a lower 206Pb/207 3 Pb ratio than leaded on-road gasoline. Supporting evidence came from contemporary 

4 samples such as near surface peat, rainwater and snow, all of which confirmed a trend away from natural 

Pb (1.191 to 1.201) to lower 206Pb/207 5 Pb ratios. The local smelting activities (Sudbury) were unlikely to be 

the source of anthropogenic Pb as Sudbury-derived emissions exhibit a typical 206Pb/207 6 Pb ratio of ~1.15, 

7 similar to leaded on-road gasoline. Instead, it was suggested that long-range transport of Pb from the 

8 smelter at Rouyn-Noranda (known as the “Capital of Metal,” NW Quebec) may still be impacting on 

9 Kawagama Lake but no Pb isotope data was quoted to support this supposition.

3.6.6. Moss

10 Mosses can be used effectively for monitoring trends in Pb deposition as demonstrated in many 

11 studies (Harmens et al., 2008; Harmens et al., 2010). For example, Harmens et al. (2008) showed that a 

12 52% decrease in deposited Pb concentrations corresponded to a 57% decrease in Pb concentrations in 

moss. Farmer et al. (2010) showed that there was good agreement between the 206Pb/207 13 Pb ratio for 

14 precipitation and mosses collected in northeast Scotland. A study in the Vosges mountains also found a 

15 ratio value of 1.158 for a moss sample and a surface soil litter value of 1.167 and concluded that 1.158 to 

16 1.167 represented the current atmospheric baseline (Geagea et al., 2008). For rural northeast Scotland, a 

combination of sources is giving rise to a 206Pb/207 17 Pb ratio of ~1.15 in recent precipitation and mosses 

18 (Farmer et al., 2010). Clearly, sources with a lower ratio than coal (~1.20) must be contributing 

19 substantially to the overall emissions. Pb from waste incineration has been implicated as a possible 

current source (cf. typical 206Pb/207 20 Pb ratios for Pb from European incineration plants are ~1.14 to 1.15 (de 

21 la Cruz et al. (2009) and references therein).

3.6.7. Grass, Foliage, and Tree Rings

22 Trends in Pb concentration among flora have decreased in recent years. For example, Franzaring et 

23 al. (2010) evaluated data from a 20-year biological monitoring study of Pb concentration in permanent 

24 forest and grassland plots in Baden-Württemberg, southwest Germany. Grassland and tree foliage samples 

25 were collected from 1985-2006. The samples were not washed and so atmospheric deposition rather than 

26 uptake from the soil probably predominates. For all foliage (beech and spruce), Pb concentrations have 

27 shown large reductions over time, particularly in the early 1990s. The Pb concentrations in the grassland 

28 vegetation also decreased from the late 1980s to the early 1990s but the trend thereafter was found to be 

29 statistically non-significant. The reduction corresponded to the phase-out of leaded on-road gasoline in 

30 Germany. Similarly, Aznar et al. (2008) observed that the decline in Pb concentrations in the outer level of 

31 tree rings corresponded with the decline in Cu smelter emissions in Gaspé Peninsula in Canada; see 
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1 Figure 3-31. Both Pb concentrations and Pb isotope ratios declined with distance from the smelter (Aznar, 

2 Richer-Lafleche, et al., 2008; Aznar, Richer-Laflèche, et al., 2008).

Source: Used with permission from Elsevier Publishing, Aznar et al. (2008)

Figure 3-31. Trends in regional pollution near a copper smelter in Canada 

and Pb concentrations at the boundary of heartwood trees 

within roughly 75 km of the smelter. 

3.6.8. Aquatic Bivalves

3 Data from invertebrate waterborne populations can serve as in indicator of Pb contamination 

4 because animals such as mussels and oysters take in contaminants during filter feeding. Kimbrough et al. 

5 (2008) surveyed Pb concentrations in mussels, zebra mussels, and oysters along the coastlines of the 

6 continental U.S. In general, they observed the highest concentrations of Pb in the vicinity of urban and 

7 industrial areas. Company et al. (2008) measured Pb concentrations and Pb isotope ratios in bivalves 

8 along the Guadiana River separating Spain and Portugal. Analysis of Pb isotope ratio data suggested that 

9 high Pb concentrations were related to historical mining activities in the region. Elevated Pb 
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1 concentrations were also observed by Company et al. (2008) in the vicinity of more populated areas. 

2 Couture et al. (2010) report data from a survey of the isotopic ratios of Pb in Mytilus edulis blue mussel, 

3 collected off the coast of France from 1985-2005. The results indicated that the likely source of Pb in 

4 mussel tissue is from resuspension of contaminated sediments enriched with Pb runoff from wastewater 

5 treatment plants, municipal waste incinerators, smelters and refineries rather than from atmospheric 

6 deposition (Couture et al., 2010). 

3.7. Summary

3.7.1. Sources of Atmospheric Lead

7 The 2006 Pb AQCD (U.S. EPA, 2006) documented the decline in ambient air Pb emissions 

8 following the ban on alkyl-Pb additives for on-road gasoline. Pb emissions declined by 98% from 1970 to 

9 1990 and then by an additional 77% from 1990 to 2008, at which time emissions were 1,200 tons/yr. 

10 Industrial processes, including metals processing and industrial fuel combustion, had replaced mobile 

11 sources as the primary source of Pb to the atmosphere by the 2006 Pb AQCD (U.S. EPA, 2006). More 

12 recent data from the 2008 NEI (U.S. EPA, 2011) illustrate that piston engine aircraft emissions now 

13 comprise the largest share (~49%) of total atmospheric Pb emissions; the 2008 NEI (U.S. EPA, 2011)

14 estimated that 590 tons of Pb were emitted from aircraft point sources. Other sources of ambient air Pb, in 

15 approximate order of importance, include metals processing, fossil fuel combustion, other industrial 

16 sources, roadway related sources, and historic Pb.

17 Chemical speciation of Pb had been fairly well characterized in the 2006 Pb AQCD (U.S. EPA, 

18 2006). Estimates from the 1986 Pb AQCD (U.S. EPA, 1986) for organic on-road Pb emissions provides 

19 an upper bound for organic vapor emissions of 20% of total Pb dibromide and Pb bromide emissions from 

20 piston engine aircraft. Recent speciation studies of smelting and battery recycling operations have shown 

21 that PbS and Pb sulfates are abundant within the emissions mixture for such industrial operations. 

3.7.2. Fate and Transport of Lead

22 The atmosphere is the main environmental transport pathway for Pb, and on a global scale 

23 atmospheric Pb is primarily associated with fine PM. On a global scale, Pb associated with fine PM is 

24 transported long distances and found in remote areas. Global atmospheric Pb deposition peaked in the 

25 1970s, followed by a more recent decline. On a local scale, Pb concentrations in soils (including urban 

26 areas where historic use was widespread) can be substantial, and coarse Pb-bearing PM experiences 

27 cycles of deposition and resuspension that serve to distribute it. Both wet and dry deposition are important 

28 removal mechanisms for atmospheric Pb. Because Pb in fine PM is typically fairly soluble, wet 
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1 deposition is more important for fine Pb. In contrast, Pb associated with coarse PM is usually insoluble, 

2 and removed by dry deposition. However, local deposition fluxes are much higher near local industrial 

3 sources, and a substantial amount of emitted Pb is deposited near sources, leading to high soil Pb 

4 concentrations. Resuspension by wind and traffic can be an important source of airborne Pb near sources

5 where Pb occurs in substantial amounts in surface dust.

6 In water, Pb is transported as free ions, soluble chelates, or on surfaces of iron and organic rich 

7 colloids, and water columns behave as important reservoirs of Pb. In surface waters, atmospheric 

8 deposition is the largest source of Pb, but urban runoff and industrial discharge are also considerable. A 

9 substantial portion of Pb in runoff ultimately originates from atmospheric deposition, but substantial 

10 amounts of Pb from vehicle wear and building materials can also be transported by runoff waters without 

11 becoming airborne. Often a disproportionate amount of Pb is removed by runoff at the beginning of a 

12 rainfall event. Pb is rapidly dispersed in water, and highest concentrations of Pb are observed near sources 

13 where Pb is deposited.

14 Transport in surface waters is largely controlled by exchange with sediments. The cycling of Pb 

15 between water and sediments is governed by chemical, biological, and mechanical processes, which are 

16 affected by many factors. Organic matter in sediments has a high capacity for accumulating trace 

17 elements like Pb. In anoxic sediments removal by sulfides is particularly important. Pb is relatively stable 

18 in sediments, with long residence times and limited mobility. However, Pb containing sediment particles 

19 can be remobilized into the water column, and sediment concentrations tend to follow those in overlying 

20 waters. Resuspended Pb is largely associated with OM or iron and manganese particles. This resuspension 

21 of contaminated sediments strongly influences the lifetime of Pb in water bodies and can be a more 

22 important Pb source than atmospheric deposition. Resuspension and release from sediments largely 

23 occurs during discrete events related to storms.

24 A complex variety of factors that influence Pb retention in soil, including hydraulic conductivity, 

25 solid composition, OM content, clay mineral content, microbial activity, plant root channels, animal 

26 holes, geochemical reactions, colloid amounts, colloidal surface charge, and pH. Leaf litter can be an 

27 important temporary sink for metals from the soil around and below leaves, and decomposition of leaf 

28 litter can reintroduce substantial amounts of Pb into soil “hot spots,” where re-adsorption of Pb is favored. 

A small fraction of Pb in soil is present as the free Pb2+ 29 ion. The fraction of Pb in this form is strongly 

30 dependent on soil pH.

31 In summary, environmental distribution of Pb occurs mainly through the atmosphere, from where it 

32 is deposited into surface waters and soil. Pb associated with coarse PM deposits to a great extent near 

33 sources, leading to high soil concentrations in those locations, while fine Pb-PM can be transported long 

34 distances, leading to contamination of remote areas. Surface waters act as an important reservoir, with Pb 

35 lifetimes largely controlled by deposition and resuspension of Pb in sediments. Pb retention in soil 

36 depends on Pb speciation and a variety of factors intrinsic to the soil.
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3.7.3. Ambient Lead Monitoring

1 In recognition of the role of all PM sizes in ambient air Pb exposures, including the ingestion of 

2 particles deposited onto surfaces, the indicator for the Pb NAAQS is Pb in Pb-TSP. Although there is a 

3 lower rate of error in estimating ambient Pb from Pb-PM10 monitoring than from Pb-TSP monitoring, the 

4 Pb-TSP indicator was retained in 2008 because ingestion after deposition in the upper respiratory tract 

5 was considered an important component of Pb exposure. A new FRM for Pb-PM10 has been implemented 

6 in which ambient air is drawn through an inertial PM size separator for collection on a PTFE filter. 

7 Several FEMs have also been approved. The FRM is based on flame AAS. ICPMS is under consideration 

8 as a new FRM for Pb-TSP.

9 Monitoring for ambient Pb levels is required for all areas where Pb levels have been shown or are 

expected to contribute to maximum concentrations of 0.10 μg/m3 10 or greater over a three-year time period. 

11 Pb is monitored routinely at SLAMS that report data used for NAAQS compliance to the AQS database. 

12 Pb monitoring requirements have experienced several changes since publication of the 2006 Pb AQCD 

13 (U.S. EPA, 2006). In addition to FRM monitoring, Pb is also routinely measured in smaller PM fractions 

14 in the CSN, IMPROVE, and the NATTS networks, and is planned for the NCore network. While 

15 monitoring in multiple networks provides extensive geographic coverage, measurements between 

16 networks are not directly comparable in all cases because different PM size ranges are sampled in 

17 different networks. Depending on monitoring network, Pb is monitored in TSP, PM10, or PM2.5. Monitors 

18 reporting to the AQS were considered for the purpose of this ISA to be source oriented if they were 

19 designated in AQS as source oriented, or they were located within 1 mile of a 0.5 ton/yr or greater source, 

20 as noted in the 2005 NEI (U.S. EPA, 2008a). Non-source oriented monitors were those monitors not 

21 considered to be source oriented based on these two criteria. 

3.7.4. Ambient Air Lead Concentrations

22 Ambient air Pb concentrations have declined drastically over the period 1980-2009. The median 

annual concentrations for all monitors have dropped by 97% from 0.87 μg/m3 in 1980 to 0.025 μg/m3 23 in 

24 2009. While the sharpest drop in Pb concentration occurred during 1980-1990, a declining trend was 

25 observed between 1990 and 2009. A smaller reduction was observable among source oriented Pb 

26 concentration (56%) and non-source oriented Pb data (51%) for 2000-2009.

27 AQS data for source oriented and non-source oriented monitoring were analyzed for 2007-2009. 

28 For source oriented monitoring, the 3-month rolling average was measured to be above the level of the 

29 NAAQS in 14 counties across the U.S. Fourteen monitoring sites had maximum 3-month rolling average 

30 values that exceeded the level of the NAAQS. The maximum 3-month rolling average concentrations 

ranged from 0.17-2.9 μg/m3 31 . 
May 2011 3-105 DRAFT – DO NOT CITE OR QUOTE

1 Pb concentrations, seasonal variations, inter-monitor correlations, and wind data were analyzed for 

2 six counties: Los Angeles County, CA, Hillsborough County, FL, Cook County, IL, Jefferson County, 

3 MO, Cuyahoga County, OH, and Sullivan County, TN. These sites were selected for analysis because 

4 they contained a mix of source oriented and non-source oriented monitors in urban areas. Spatial and 

5 temporal variability of Pb concentrations in each county were commonly high. Meteorology, distance 

6 from sources with respect to the monitors, and source strength all appeared to influence the level of 

7 concentration variability across time and space. PM size distribution also influenced how far the particle 

8 will travel upon initial emission or resuspension before being deposited. 

9 Size distribution of Pb-bearing PM was demonstrated to vary substantially for several studies 

10 presented, depending on the nature of Pb sources and proximity of the monitors to the Pb sources. AQS 

11 data were also used to estimate the size distribution of Pb-bearing PM at several sites with co-located Pb 

12 monitors. On average, Pb-TSP and Pb-PM10 were moderately correlated, but the correlation improved for 

13 urban and city center land use types compared with all data. When comparing Pb-TSP with Pb-PM2.5, 

14 correlations were lower in urban and city center areas compared with suburban and rural sites. A 

15 relationship between land use type and correlation was less obvious when comparing Pb-PM10 with Pb16 PM2.5. For urban and city center types, average ρ was fairly high. Average ρ increased for suburban sites 

17 but decreased for rural sites. Variation in correlation of size-fractionated Pb samples among different land 

18 use types may reflect differences among sources among land use types.

19 Pb concentrations exhibit varying degrees of association with other criteria pollutant 

20 concentrations. Overall, Pb was moderately associated with PM2.5, PM10 and NO2, with positive 

21 Spearman correlation coefficients observed at nearly all sites. However, Pb was just as strongly associated 

22 with CO in fall and winter The poorest associations were observed between Pb and O3. Among trace 

23 metals, the strongest association was with Zn. Br, Cu, and K concentrations also exhibited moderate 

24 associations with Pb concentrations. Such correlations may suggest some common sources affecting the 

25 pollutants.

3.7.5. Ambient Lead Concentrations in Non-Air Media and 

Biota

26 Atmospheric deposition has led to measurable Pb concentrations observed in rain, snowpack, soil, 

27 surface waters, sediments, agricultural plants, livestock, and wildlife across the world, with highest 

28 concentrations near Pb sources, such as metal smelters. After the phase-out of Pb from on-road gasoline, 

29 concentrations in these media decreased to varying degrees. In rain, snowpack, and surface waters, Pb 

30 concentrations have decreased considerably following elimination of leaded on-road gasoline. Declining 

31 Pb concentrations in tree foliage, trunk sections, and grasses have also been observed. In contrast, Pb is 

32 retained in soils and sediments, where it provides a historical record of deposition and associated ambient 
May 2011 3-106 DRAFT – DO NOT CITE OR QUOTE

1 concentrations. In remote lakes, sediment profiles indicate higher Pb concentrations in near surface 

2 sediment as compared to pre-industrial era sediment from greater depth and indicate peak concentrations 

3 between 1960 and 1980, when leaded on-road gasoline was at peak use. Concentrations of moss, lichens, 

4 peat, and aquatic bivalves have been used to understand spatial and temporal distribution patterns of air 

5 Pb concentrations. Ingestion and water intake are the major routes of Pb exposure for aquatic organisms, 

6 and food, drinking water, and inhalation are major routes of exposure for livestock and terrestrial wildlife. 

7 Overall, Pb concentrations have decreased substantially in media through which Pb is rapidly transported, 

8 such as air and water. Substantial Pb remains in soil and sediment sinks. Although in areas less affected 

9 by major local sources, the highest concentrations are below the surface layers and reflect the phase-out 

10 of Pb from on-road gasoline and emissions reductions from other sources. 
May 2011 3-107 DRAFT – DO NOT CITE OR QUOTE

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Chapter 3 Appendix

3.8. Variability across the U.S.

Table 3A-1.Distribution of 1-month average Pb-TSP concentrations (μg/m3) nationwide, 

source-oriented monitors, 2007-9.Sites listed in the bottom six rows of the 

table fall in the upper 90th percentile of the data pooled by site.

Year Season State/

County State County 

name Site ID

N 

monthly 

means

N 

sites Mean Min 1 5 10 25 50 75 90 95 99 max

Nationwide statistics

2007-

2009 1,802 0.2353 0 0 0.007 0.012 0.028 0.070 0.254 0.670 0.976 2.061 4.440

2007 554 0.2500 0 0 0.008 0.012 0.028 0.070 0.290 0.706 1.085 1.982 3.620

2008 622 0.2803 0 0 0.008 0.013 0.034 0.080 0.300 0.741 1.164 2.501 4.440

2009 626 0.1774 0 0 0.006 0.010 0.023 0.063 0.194 0.535 0.787 1.280 2.438

Winter 443 0.2324 0 0 0.006 0.010 0.025 0.064 0.224 0.575 1.111 2.440 3.103

Spring 447 0.2695 0 0 0.008 0.013 0.031 0.077 0.333 0.794 1.085 2.035 3.123

Summer 458 0.2142 0 0 0.008 0.013 0.032 0.074 0.265 0.652 0.852 1.384 4.440

Fall 454 0.2260 0 0 0.007 0.012 0.026 0.064 0.226 0.670 1.006 1.565 4.225

Nationwide statistics, pooled by site

2007-

2009 56 0.2384 0.001 0.001 0.010 0.014 0.031 0.098 0.350 0.730 0.862 1.306 1.306

2007 48 0.2547 0.000 0.000 0.010 0.014 0.031 0.090 0.323 0.783 1.048 1.520 1.520

2008 53 0.2848 0.001 0.001 0.011 0.021 0.032 0.121 0.344 0.818 1.226 1.542 1.542

2009 53 0.1779 0.000 0.000 0.007 0.011 0.029 0.075 0.219 0.453 0.718 0.917 0.917

Winter 56 0.2353 0.001 0.001 0.008 0.010 0.033 0.088 0.290 0.654 1.205 1.389 1.389

Spring 56 0.2759 0.000 0.000 0.008 0.017 0.035 0.093 0.425 0.863 1.119 1.605 1.605

Summer 56 0.2136 0.000 0.000 0.008 0.016 0.034 0.095 0.289 0.654 0.802 1.170 1.170

Fall 55 0.2286 0.001 0.001 0.012 0.017 0.029 0.071 0.389 0.651 1.031 1.243 1.243

Statistics for individual counties (2007-2009)

01109 AL Pike 44 2 0.5110 0.070 0.070 0.083 0.094 0.190 0.355 0.710 1.277 1.356 1.434 1.434

06037 CA Los Angeles 108 5 0.2425 0.002 0.002 0.008 0.012 0.037 0.073 0.188 0.698 0.942 2.501 2.880

12057 FL Hillsborough 62 2 0.2939 0.014 0.014 0.020 0.040 0.080 0.139 0.333 0.600 0.840 3.620 3.620

17031 IL Cook 144 4 0.0241 0.010 0.010 0.010 0.010 0.014 0.022 0.030 0.040 0.046 0.070 0.084

17119 IL Madison 36 1 0.1088 0.022 0.022 0.024 0.028 0.037 0.058 0.138 0.300 0.325 0.454 0.454

17163 IL Saint Clair 36 1 0.0246 0.010 0.010 0.010 0.013 0.015 0.023 0.030 0.045 0.054 0.058 0.058

18035 IN Delaware 72 2 0.3318 0.034 0.034 0.045 0.056 0.094 0.202 0.341 0.639 0.980 4.440 4.440

18089 IN Lake 36 1 0.0297 0.004 0.004 0.006 0.007 0.017 0.025 0.045 0.060 0.063 0.065 0.065

18097 IN Marion 71 2 0.0198 0.003 0.003 0.005 0.007 0.010 0.016 0.028 0.040 0.046 0.057 0.057

27037 MN Dakota 35 1 0.2872 0.062 0.062 0.072 0.098 0.134 0.232 0.412 0.620 0.670 0.730 0.730

27163 MN Washington 31 1 0.0006 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.003 0.003 0.004 0.004

29093 MO Iron 144 4 0.4060 0.007 0.010 0.021 0.029 0.045 0.094 0.658 0.971 1.437 2.557 4.225

29099 MO Jefferson 296 10 0.6096 0.011 0.019 0.071 0.124 0.212 0.454 0.798 1.353 1.764 2.440 3.123

29189 MO Saint Louis 36 1 0.0361 0.005 0.005 0.005 0.005 0.008 0.050 0.050 0.050 0.050 0.066 0.066

34023 NJ Middlesex 12 1 0.0101 0.007 0.007 0.007 0.007 0.008 0.008 0.008 0.010 0.034 0.034 0.034

36071 NY Orange 106 3 0.0271 0.003 0.003 0.004 0.005 0.007 0.020 0.037 0.058 0.079 0.103 0.134

39035 OH Cuyahoga 108 3 0.0473 0.004 0.004 0.007 0.008 0.013 0.024 0.060 0.130 0.190 0.210 0.220

39051 OH Fulton 33 1 0.2434 0.015 0.015 0.055 0.066 0.093 0.190 0.360 0.510 0.620 0.690 0.690

39091 OH Logan 68 2 0.0763 0.020 0.020 0.020 0.030 0.040 0.070 0.090 0.120 0.190 0.290 0.290

42007 PA Beaver 32 1 0.1090 0.045 0.045 0.054 0.063 0.070 0.100 0.132 0.173 0.195 0.284 0.284

42011 PA Berks 108 3 0.1053 0.030 0.033 0.037 0.040 0.050 0.073 0.131 0.242 0.302 0.360 0.542

47163 TN Sullivan 108 3 0.0754 0.030 0.030 0.032 0.036 0.042 0.062 0.087 0.145 0.178 0.254 0.341

48085 TX Collin 108 3 0.2910 0.007 0.009 0.030 0.052 0.102 0.186 0.389 0.673 0.904 1.121 1.564

Statistics for individual sites where overall average monthly mean ≥ national 90th percentile (2007-2009)

060371405 24 0.8623 0.242 0.242 0.283 0.284 0.321 0.606 0.923 2.277 2.501 2.880 2.880

290930016 36 0.7302 0.166 0.166 0.186 0.235 0.347 0.545 0.837 1.295 2.435 4.225 4.225

290930021 36 0.7970 0.084 0.084 0.093 0.099 0.409 0.696 0.967 1.453 2.438 2.557 2.557

290990004 36 1.1177 0.242 0.242 0.285 0.518 0.764 1.005 1.519 1.905 2.101 2.416 2.416

290990015 34 1.3060 0.155 0.155 0.339 0.421 0.834 1.185 1.577 2.319 3.103 3.123 3.123

290990021 33 0.7498 0.084 0.084 0.141 0.423 0.550 0.681 0.901 1.164 1.553 2.162 2.162
May 2011 3-130 DRAFT – DO NOT CITE OR QUOTE

Table 3A-2.Distribution of 3-month moving average Pb-TSP concentrations (μg/m3) 

nationwide, source-oriented monitors, 2007-9. Sites listed in the bottom six 

rows of the table fall in the upper 90th percentile of the data pooled by site.

Year Season State/

County State County 

name Site ID

N 

monthly 

means

N 

sites Mean Min 1 5 10 25 50 75 90 95 99 max

Nationwide statistics

20079 1,737 0.2366 0.000 0.000 0.010 0.010 0.030 0.080 0.270 0.680 0.980 1.870 2.890

2007 507 0.2421 0.000 0.000 0.010 0.020 0.030 0.080 0.270 0.720 1.070 1.640 1.740

2008 612 0.2834 0.000 0.000 0.010 0.010 0.040 0.090 0.320 0.800 1.150 2.290 2.890

2009 618 0.1859 0.000 0.000 0.010 0.010 0.030 0.070 0.240 0.550 0.760 1.150 2.070

Winter 417 0.2434 0.000 0.000 0.010 0.010 0.030 0.070 0.270 0.660 1.120 2.080 2.620

Spring 436 0.2638 0.000 0.000 0.010 0.010 0.030 0.080 0.330 0.740 1.080 2.140 2.890

Summer 448 0.2269 0.000 0.000 0.010 0.020 0.030 0.080 0.290 0.670 0.900 1.730 2.140

Fall 436 0.2131 0.000 0.000 0.010 0.020 0.030 0.080 0.240 0.650 0.940 1.320 2.460

Nationwide statistics, pooled by site

20079 56 0.2386 0.000 0.000 0.011 0.017 0.032 0.099 0.333 0.733 0.930 1.332 1.332

2007 45 0.2435 0.003 0.003 0.016 0.019 0.033 0.084 0.277 0.687 0.831 1.524 1.524

2008 53 0.2903 0.000 0.000 0.010 0.022 0.034 0.119 0.383 0.806 1.301 1.641 1.641

2009 53 0.1848 0.000 0.000 0.009 0.014 0.029 0.075 0.229 0.617 0.855 0.863 0.863

Winter 56 0.2482 0.000 0.000 0.010 0.015 0.041 0.104 0.316 0.683 1.150 1.308 1.308

Spring 56 0.2736 0.000 0.000 0.010 0.014 0.032 0.096 0.369 0.820 1.320 1.679 1.679

Summer 56 0.2243 0.000 0.000 0.010 0.012 0.034 0.093 0.287 0.707 0.900 1.232 1.232

Fall 55 0.2132 0.000 0.000 0.011 0.017 0.032 0.085 0.341 0.592 0.960 1.164 1.164

Statistics for individual counties (2007-2009)

01109 AL Pike 44 2 0.5080 0.100 0.100 0.120 0.230 0.275 0.325 0.685 1.050 1.150 1.350 1.350

06037 CA Los Angeles 108 5 0.2594 0.010 0.010 0.010 0.010 0.045 0.075 0.185 0.710 1.260 2.450 2.490

12057 FL Hillsborough 48 2 0.2248 0.040 0.040 0.040 0.040 0.095 0.135 0.250 0.490 0.580 1.770 1.770

17031 IL Cook 144 4 0.0244 0.010 0.010 0.010 0.010 0.020 0.030 0.030 0.040 0.040 0.050 0.050

17119 IL Madison 36 1 0.1144 0.040 0.040 0.040 0.040 0.060 0.105 0.155 0.210 0.230 0.280 0.280

17163 IL Saint Clair 36 1 0.0250 0.010 0.010 0.010 0.020 0.020 0.020 0.030 0.040 0.040 0.050 0.050

18035 IN Delaware 72 2 0.3422 0.050 0.050 0.070 0.080 0.120 0.210 0.430 0.710 0.930 2.140 2.140

18089 IN Lake 36 1 0.0314 0.010 0.010 0.010 0.010 0.020 0.030 0.040 0.050 0.050 0.060 0.060

18097 IN Marion 69 2 0.0199 0.000 0.000 0.010 0.010 0.010 0.020 0.030 0.030 0.040 0.050 0.050

27037 MN Dakota 33 1 0.2742 0.100 0.100 0.120 0.140 0.210 0.240 0.350 0.400 0.470 0.570 0.570

27163 MN Washington 24 1 0.0000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

29093 MO Iron 144 4 0.4142 0.020 0.020 0.020 0.030 0.050 0.170 0.735 1.010 1.210 2.080 2.460

29099 MO Jefferson 280 10 0.6211 0.040 0.070 0.120 0.155 0.280 0.475 0.835 1.250 1.655 2.620 2.890

29189 MO Saint Louis 36 1 0.0383 0.010 0.010 0.010 0.010 0.010 0.050 0.050 0.050 0.050 0.060 0.060

34023 NJ Middlesex 12 1 0.0192 0.010 0.010 0.010 0.010 0.010 0.010 0.020 0.050 0.060 0.060 0.060

36071 NY Orange 102 3 0.0273 0.000 0.000 0.000 0.010 0.010 0.030 0.030 0.060 0.070 0.080 0.090

39035 OH Cuyahoga 102 3 0.0483 0.010 0.010 0.010 0.010 0.020 0.030 0.070 0.120 0.140 0.160 0.170

39051 OH Fulton 25 1 0.2420 0.050 0.050 0.050 0.080 0.130 0.240 0.320 0.450 0.520 0.570 0.570

39091 OH Logan 68 2 0.0809 0.030 0.030 0.030 0.030 0.050 0.070 0.090 0.160 0.190 0.260 0.260

42007 PA Beaver 32 1 0.1115 0.060 0.060 0.070 0.080 0.090 0.110 0.120 0.160 0.170 0.170 0.170

42011 PA Berks 108 3 0.1099 0.040 0.040 0.040 0.050 0.060 0.085 0.150 0.210 0.250 0.350 0.360

47163 TN Sullivan 102 3 0.0769 0.030 0.030 0.040 0.040 0.050 0.060 0.090 0.130 0.180 0.210 0.260

48085 TX Collin 108 3 0.2873 0.010 0.030 0.060 0.070 0.110 0.205 0.430 0.590 0.650 1.190 1.260

Statistics for individual sites where overall average monthly mean ≥ national 90th percentile (2007-2009)

060371405 24 0.9304 0.280 0.280 0.310 0.330 0.470 0.665 1.045 2.290 2.450 2.490 2.490

290930016 36 0.7328 0.210 0.210 0.260 0.380 0.445 0.570 0.770 1.170 2.080 2.460 2.460

290930021 36 0.8258 0.220 0.220 0.220 0.300 0.545 0.880 1.005 1.210 1.270 1.940 1.940

290990004 36 1.1383 0.630 0.630 0.680 0.700 0.810 1.085 1.340 1.710 2.130 2.140 2.140

290990015 34 1.3318 0.610 0.610 0.640 0.730 0.940 1.195 1.710 2.020 2.630 2.890 2.890

290990021 33 0.7682 0.430 0.430 0.440 0.520 0.610 0.750 0.900 1.090 1.310 1.320 1.320
May 2011 3-131 DRAFT – DO NOT CITE OR QUOTE

Table 3A-3.Distribution of annual 1-month site maxima TSP Pb concentrations (μg/m3) 

nationwide, source-oriented monitors, 2007-2009.Sites listed in the bottom 

eight rows of the table fall in the upper 90th percentile of the data 

pooled by site.

Year Site ID – year N (sites) Mean Min 1 5 10 25 50 75 90 95 99 max

Nationwide statistics

2007-2009 56 0.7961 0.004 0.004 0.025 0.040 0.076 0.289 0.747 2.557 3.620 4.440 4.440

2007 48 0.5517 0.003 0.003 0.025 0.035 0.054 0.192 0.735 1.565 2.162 3.620 3.620

2008 53 0.7157 0.004 0.004 0.014 0.039 0.059 0.247 0.754 2.416 3.123 4.440 4.440

2009 53 0.3758 0.003 0.003 0.016 0.019 0.065 0.141 0.536 1.124 1.357 2.438 2.438

Annual site max 3-month means >= national 90th percentile (2007-2009)

180350009-2008 4.4400

290930016-2008 4.2252

120571066-2007 3.6200

290990015-2008 3.1228

060371405-2008 2.8800

290930021-2008 2.5566

180350009-2008 4.4400

290930016-2008 4.2252

Table 3A-4.Distribution of annual 3-month site maxima Pb-TSP concentrations (μg/m3) 

nationwide, source-oriented monitors, 2007-2009.Sites listed in the bottom 

nine rows of the table fall in the upper 90th percentile of the data 

pooled by site.

Year Site ID – year N (sites) Mean Min 1 5 10 25 50 75 90 95 99 max

Nationwide statistics

2007-2009 56 0.5409 0.000 0.000 0.020 0.030 0.060 0.215 0.590 1.940 2.460 2.890 2.890

2007 45 0.3616 0.010 0.010 0.030 0.030 0.050 0.130 0.520 1.210 1.350 1.740 1.740

2008 53 0.5177 0.000 0.000 0.010 0.030 0.050 0.170 0.530 1.770 2.460 2.890 2.890

2009 53 0.3123 0.000 0.000 0.010 0.020 0.040 0.110 0.390 0.940 1.240 2.070 2.070

Annual site max 3-month means >= national 90th percentile (2007-2009)

060371405-2008 2.4900

180350009-2008 2.1400

290930016-2008 2.4600

290930016-2009 2.0700

290930021-2009 1.9400

290990004-2008 2.1400

290990015-2008 2.8900

060371405-2008 2.4900
May 2011 3-132 DRAFT – DO NOT CITE OR QUOTE

Table 3A-5.One-month average Pb-TSP for individual county concentrations nationwide 

(μg/m3), non-source-oriented monitors, 2007-2009

Stcou State County name

N 

monthly 

means

N 

sites Mean Min 1 5 10 25 50 75 90 95 99 max

Statistics for individual counties (2007-2009)

06025 CA Imperial 33 1 0.0218 0.009 0.009 0.010 0.011 0.013 0.019 0.029 0.036 0.041 0.041 0.041

06037 CA Los Angeles 117 5 0.0107 0.000 0.000 0.000 0.002 0.006 0.010 0.015 0.020 0.024 0.032 0.038

06065 CA Riverside 48 2 0.0090 0.000 0.000 0.002 0.003 0.008 0.010 0.010 0.016 0.018 0.022 0.022

06071 CA San Bernardino 47 2 0.0112 0.000 0.000 0.002 0.003 0.008 0.010 0.014 0.020 0.022 0.036 0.036

12103 FL Pinellas 12 1 0.0000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

17031 IL Cook 143 4 0.0144 0.010 0.010 0.010 0.010 0.010 0.014 0.017 0.020 0.024 0.028 0.032

17117 IL Macoupin 36 1 0.0102 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.013 0.014 0.014

17119 IL Madison 35 1 0.0187 0.010 0.010 0.010 0.010 0.010 0.015 0.022 0.030 0.038 0.066 0.066

17143 IL Peoria 36 1 0.0113 0.010 0.010 0.010 0.010 0.010 0.010 0.012 0.014 0.015 0.018 0.018

18097 IN Marion 35 1 0.0071 0.002 0.002 0.002 0.003 0.004 0.006 0.009 0.012 0.012 0.033 0.033

18163 IN Vanderburgh 21 2 0.0048 0.001 0.001 0.002 0.002 0.004 0.005 0.005 0.006 0.010 0.010 0.010

25025 MA Suffolk 24 1 0.0089 0.000 0.000 0.000 0.003 0.007 0.009 0.011 0.015 0.016 0.020 0.020

26163 MI Wayne 24 1 0.0187 0.007 0.007 0.009 0.012 0.013 0.018 0.022 0.027 0.032 0.045 0.045

27037 MN Dakota 129 4 0.0039 0.000 0.000 0.000 0.000 0.000 0.003 0.006 0.008 0.010 0.018 0.036

27053 MN Hennepin 128 4 0.0034 0.000 0.000 0.000 0.000 0.002 0.003 0.005 0.008 0.008 0.010 0.010

27123 MN Ramsey 71 3 0.0071 0.000 0.000 0.000 0.000 0.004 0.006 0.010 0.015 0.020 0.028 0.028

27137 MN Saint Louis 70 2 0.0017 0.000 0.000 0.000 0.000 0.000 0.002 0.003 0.005 0.006 0.010 0.010

27163 MN Washington 36 1 0.0035 0.000 0.000 0.000 0.000 0.003 0.004 0.004 0.006 0.006 0.008 0.008

36047 NY Kings 36 1 0.0142 0.010 0.010 0.010 0.010 0.011 0.013 0.016 0.020 0.021 0.026 0.026

39017 OH Butler 34 1 0.0052 0.000 0.000 0.000 0.003 0.004 0.005 0.007 0.008 0.009 0.009 0.009

39029 OH Columbiana 107 3 0.0145 0.000 0.000 0.004 0.006 0.008 0.012 0.019 0.031 0.034 0.045 0.050

39035 OH Cuyahoga 70 2 0.0138 0.004 0.004 0.006 0.006 0.009 0.013 0.016 0.022 0.028 0.041 0.041

39049 OH Franklin 36 1 0.0088 0.004 0.004 0.004 0.005 0.007 0.008 0.011 0.014 0.014 0.016 0.016

39143 OH Sandusky 12 1 0.0048 0.003 0.003 0.003 0.003 0.004 0.005 0.006 0.006 0.007 0.007 0.007

39167 OH Washington 43 2 0.0041 0.002 0.002 0.002 0.002 0.003 0.004 0.005 0.006 0.007 0.010 0.010

42003 PA Allegheny 36 1 0.0067 0.000 0.000 0.000 0.000 0.000 0.004 0.012 0.016 0.021 0.053 0.053

42045 PA Delaware 20 1 0.0400 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040

42129 PA Westmoreland 36 1 0.0410 0.034 0.034 0.037 0.040 0.040 0.040 0.040 0.044 0.050 0.053 0.053

48061 TX Cameron 35 1 0.0038 0.002 0.002 0.002 0.002 0.003 0.003 0.005 0.006 0.007 0.009 0.009

48141 TX El Paso 22 2 0.0229 0.014 0.014 0.015 0.016 0.018 0.019 0.019 0.041 0.056 0.057 0.057

48201 TX Harris 31 1 0.0054 0.003 0.003 0.004 0.004 0.005 0.005 0.006 0.007 0.009 0.010 0.010

48479 TX Webb 31 1 0.0103 0.004 0.004 0.005 0.006 0.007 0.008 0.010 0.024 0.025 0.026 0.026
May 2011 3-133 DRAFT – DO NOT CITE OR QUOTE

Table 3A-6.Three-month moving average Pb-TSP for individual county concentrations 

(μg/m3) nationwide, non-source-oriented monitors, 2007-2009

Stcou State County name

N 

monthly 

means

N 

sites Mean Min 1 5 10 25 50 75 90 95 99 max

Statistics for individual counties (2007-2009)

06025 CA Imperial 33 1 0.0216 0.010 0.010 0.010 0.020 0.020 0.020 0.030 0.030 0.030 0.030 0.030

06037 CA Los Angeles 117 5 0.0113 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.020 0.020 0.030 0.030

06065 CA Riverside 48 2 0.0102 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.020 0.020

06071 CA San Bernardino 47 2 0.0115 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.020 0.020 0.020 0.020

12103 FL Pinellas 12 1 0.0000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

17031 IL Cook 143 4 0.0139 0.010 0.010 0.010 0.010 0.010 0.010 0.020 0.020 0.020 0.020 0.020

17117 IL Macoupin 36 1 0.0100 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010

17119 IL Madison 35 1 0.0182 0.010 0.010 0.010 0.010 0.010 0.020 0.020 0.030 0.040 0.040 0.040

17143 IL Peoria 36 1 0.0100 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010

18097 IN Marion 35 1 0.0076 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.020 0.020 0.020

18163 IN Vanderburgh 21 2 0.0037 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010 0.010

25025 MA Suffolk 24 1 0.0092 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010 0.020 0.020 0.020

26163 MI Wayne 24 1 0.0196 0.010 0.010 0.010 0.010 0.020 0.020 0.020 0.020 0.030 0.030 0.030

27037 MN Dakota 129 4 0.0029 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010 0.010

27053 MN Hennepin 128 4 0.0024 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010

27123 MN Ramsey 71 3 0.0071 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.020 0.020 0.020

27137 MN Saint Louis 70 2 0.0000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

27163 MN Washington 36 1 0.0011 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010

36047 NY Kings 36 1 0.0128 0.010 0.010 0.010 0.010 0.010 0.010 0.020 0.020 0.020 0.020 0.020

39017 OH Butler 34 1 0.0061 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010 0.010 0.010

39029 OH Columbiana 107 3 0.0151 0.010 0.010 0.010 0.010 0.010 0.010 0.020 0.020 0.030 0.030 0.030

39035 OH Cuyahoga 70 2 0.0142 0.000 0.000 0.010 0.010 0.010 0.010 0.020 0.020 0.020 0.030 0.030

39049 OH Franklin 36 1 0.0094 0.000 0.000 0.000 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010

39143 OH Sandusky 12 1 0.0060 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010 0.010 0.010

39167 OH Washington 43 2 0.0008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010

42003 PA Allegheny 36 1 0.0058 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.020 0.030 0.030

42045 PA Delaware 20 1 0.0400 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.040

42129 PA Westmoreland 36 1 0.0414 0.040 0.040 0.040 0.040 0.040 0.040 0.040 0.050 0.050 0.050 0.050

48061 TX Cameron 35 1 0.0024 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010

48141 TX El Paso 22 2 0.0256 0.020 0.020 0.020 0.020 0.020 0.020 0.030 0.040 0.040 0.040 0.040

48201 TX Harris 31 1 0.0063 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.010 0.010 0.010 0.010

48479 TX Webb 31 1 0.0100 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010

3.8.1. Intra-urban Variability

1 Maps of six areas (Los Angeles County, CA; Hillsborough/Pinellas Counties, FL; Cook County, IL; 

2 Jefferson County, MO; Cuyahoga County, OH; and Sullivan County, TN) are shown to illustrate the 

3 location of all Pb monitors meeting the inclusion criteria. Wind roses for each season are also provided to 

4 help put the source concentration data in context. Letters on the maps identify the individual monitor 

5 locations and correspond with the letters provided in the accompanying concentration box plots and pair6 wise monitor comparison tables. The box plots for each monitor include the annual and seasonal 

7 concentration median and interquartile range with whiskers extending from the 5th to the 95th percentile. 
May 2011 3-134 DRAFT – DO NOT CITE OR QUOTE

1 Data from 2007-2009 were used to generate the box plots, which are stratified by season as follows: 

2 1 = winter (December-February), 2 = spring (March-May), 3 = summer (June-August), and 4 = fall 

3 (September-November). The comparison tables include the Pearson correlation coefficient (r), the 90th 

4 percentile of the absolute difference in concentrations (P90) in ppm, the coefficient of divergence (COD) 

5 and the straight-line distance between monitor pairs (d) in km. The COD provides an indication of the 

6 variability across the monitoring sites within each county and is defined as follows:

Equation 3A-1

7 where Xij and Xik represent the observed hourly concentrations for time period i at sites j and k, and p is 

8 the number of paired hourly observations. A COD of 0 indicates there are no differences between 

9 concentrations at paired sites (spatial homogeneity), while a COD approaching 1 indicates extreme 

10 spatial heterogeneity. 

11 In certain cases, the information contained in these figures and tables should be used with some 

12 caution since many of the reported concentrations for the years 2007-2009 are near or below the analysis 

13 method’s stated method detection limit (MDL). The MDL is generally taken as 0.01 because it is the 

14 upper value of the range of MDLs reported for AA and Emissions Spectra ICAP methods, which were the 

15 two methods reported in the AQS to have been used for analysis of FRM samples (Rice, 2007). Generally, 

16 data are reported to the hundredth place, so this assumption is reasonable. The approximate percentage of 

17 data below the MDL (to the nearest 5%) is provided for each site along with box plots of seasonal Pb 

18 concentration at monitors within each urban area studied.

19 Figure 3A-1 illustrates Pb monitor locations within Los Angeles County, CA. Ten monitors are 

20 located within Los Angeles County, five of which were source-oriented and the other five were non21 source-oriented monitors. Monitor A was located immediately downwind of the Quemetco battery 

22 recycling facility in the City of Industry, CA. This source was estimated to produce 0.32 tons of Pb/yr 

23 (U.S. EPA, 2008b). Monitor C was sited in a street canyon just upwind of the Exide Pb recycling facility, 

24 which was estimated to produce 2.0 tons of Pb/yr (U.S. EPA, 2008b). Monitor D was situated slightly 

25 northwest of the same Pb recycling facility. It is still in relatively close proximity but not downwind on 

26 most occasions. Monitor B was located 12 km downwind of the Exide facility. Monitor E was located 

27 nearby the Trojan Battery recycling facility, which emitted 0.79 tons Pb/yr (U.S. EPA, 2008b). Location 

28 of the non-source-oriented monitors varied. Monitor F was positioned on a roof top 60 meters away from 

29 a 4-lane arterial road and 100 m from of a railroad. Monitor G was located on a rooftop approximately 20 

30 m from an 8-lane arterial road, and monitor H was positioned at the curbside of a four-lane road roughly 

31 650 m north of that road’s junction with I-405. Monitor I was sited in a parking lot roughly 80 m from a 

2

1

1

∑= 















+

− =

p

i ij ik

ij ik

jk X X

X X

p

COD
May 2011 3-135 DRAFT – DO NOT CITE OR QUOTE

1 four-lane road, and monitor J was located approximately 130 m south of a 4-lane highway. Figure 3A-2 

2 displays seasonal wind roses for Los Angeles County. In spring, summer, and fall, the predominant winds 

3 come from the west-southwest. During winter, wind direction varies with a portion from the west4 southwest and the remainder from the east. The highest winds during winter come more frequently from 

5 the west-southwest.

6 The maps shown in Figure 3A-1 for source-oriented monitors A-E illustrate the different conditions 

7 captured by the monitors; this informs analysis of the seasonal and year-round concentrations reported in 

Figure 3A-3. The average annual concentration at monitor A was 0.074 μg/m3 8 . The 95th percentile 

exceeded the level of the NAAQS in the spring (0.16 μg/m3) and summer (0.18 μg/m3 9 ). Monitor C 

reported the highest concentrations in Los Angeles County, with a year-round mean of 0.68 μg/m3 10 . Given 

11 the position of this monitor with respect to the Exide facility, there is the potential for recirculation of 

12 fugitive Pb emissions in the air sampled by that monitor. The average annual Pb concentration at monitor 

D was 0.12 μg/m3 13 , and the 75th percentile of year-round data exceeded the level of the NAAQS; in 

spring, the 70th percentile exceeded 0.15 μg/m3 14 . Monitor B reported the lowest values among the sourceoriented monitors with an average annual concentration of 0.013 μg/m3 15 . Note that 75% of reported values 

16 were below the MDL for this site, and no data from this site exceeded the level of the NAAQS. The 

annual average concentration at monitor E was 0.068 μg/m3 17 , and the 95th percentile of concentration was 

0.17 μg/m3 18 .

19 The non-source-oriented monitors located at sites F-J all recorded low concentrations, with average 

values ranging from 0.004 to 0.018 μg/m3 20 (Figure 3A-3). The highest average year-round concentrations 

were recorded at site F. The 95th percentiles at these sites ranged from 0.01 to 0.04 μg/m3 21 . There is much 

22 less certainty in the data recorded at the non-source-oriented sites, because 45-95% of the data from these 

23 monitors were below the MDL. Additionally, only one of the non-source-oriented monitors (monitor H)

24 was positioned at roadside, and none of the non-source-oriented monitors were located at the side of a 

25 major highway.

26 Intersampler correlations (Table 3A-7), illustrate that Pb has high intra-urban spatial variability. For 

27 the source-oriented monitors, the highest correlation ρ = 0.57, occurred for monitors C and D, which 

28 covered the same site. Because monitor D was slightly farther from the Exide source and slightly 

29 upstream of the predominant wind direction, the signal it received from the source site was 

30 correspondingly lower. Hence, the correlation between these sites was moderate despite their relatively 

31 close proximity. In general, low or even negative correlations were observed between the source-oriented 

32 and non-source-oriented monitors. The exception to this was the correlation between source-oriented 

33 monitor B and non-source-oriented monitor F, with ρ = 0.74. Monitors B and F are roughly 16 km apart, 

34 whereas monitor B is only 12 km from monitors D and C, 8 km from monitor E, and 6 km from monitor 

35 A. It is possible that monitors B and F both captured a source that was either longer in range or more 

36 ubiquitous and so would have been obscured by the stronger source signals at sites A, C, D, and E.
May 2011 3-136 DRAFT – DO NOT CITE OR QUOTE

1 Comparisons between the non-source-oriented monitors revealed moderate correlation between sites (G 

2 to J [ρ = 0.37 to 0.65]). Sites G, H, I and J are all located in the southwestern quadrant of Los Angeles. It 

3 is possible that they are also exposed to a ubiquitous source that produces a common signal at these four 

4 sites.
May 2011 3-137 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-1. Pb TSP monitor and source locations within Los Angeles 

County, CA (06-037), 2007-2009.Note that monitor locations 

are denoted by green markers, and source locations are 

denoted by red markers. Top: view of all Pb FRM monitors in 

Los Angeles County. Bottom left: Close up of the industrial 

site near monitors C and D. Bottom right: Close up of the 

populated area captured by monitor F.
May 2011 3-138 DRAFT – DO NOT CITE OR QUOTE

Source: NRCS (2011).

Figure 3A-2. Wind roses for Los Angeles County, CA, from meteorological 

data at the Los Angeles International Airport, 1961-

1990.Clockwise from top left: January, April, July, and October.

Note that the wind percentages vary from month to month. 
May 2011 3-139 DRAFT – DO NOT CITE OR QUOTE

Site A B C D E F G H I J

SITE ID 06-037-

1404

06-037-

1602

06-037-

1405

06-037-

1406

06-037-

1403

06-037-

1103

06-037-

1301

06-037-

4002

06-037-

4004

06-037-

5005

MEAN 0.074 0.013 0.68 0.12 0.068 0.018 0.015 0.0083 0.0087 0.0040

SD 0.040 0.017 1.0 0.092 0.052 0.011 0.012 0.0068 0.0069 0.0064

OBS 66 112 617 242 128 121 108 120 117 109

% 

BELOW 

MDL

0 75 0 0 0 45 65 85 85 95

Source 

orientation Source Source Source Source Source Nonsource

NonsourceNonsourceNonsourceNonsource

Figure 3A-3. Box plots of annual and seasonal Pb TSP concentrations

(μg/m3

) from source-oriented and non-source-oriented 

monitors within Los Angeles County, CA (06-037), 2007-2009.
May 2011 3-140 DRAFT – DO NOT CITE OR QUOTE

Table 3A-7.Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Los Angeles County, CA (06-037), 2007-2009

A B C D E F G H I J

Source Source Source Source Source

Non- SourceNon- SourceNon- SourceNon- Source

Non- Source

A Source 1.00 0.16 0.10 0.08 0.27 -0.15 0.00 0.14 -0.02 -0.09

0.00 0.08 0.49 0.10 0.10 0.08 0.06 0.08 0.08 0.08

0.00 0.63 0.64 0.31 0.34 0.57 0.57 0.79 0.77 0.85

B Source 1.00 0.05 0.05 0.07 0.74 0.12 0.28 0.11 0.10

0.00 3.59 0.25 0.10 0.02 0.02 0.01 0.02 0.02

0.00 0.96 0.84 0.71 0.46 0.48 0.61 0.60 0.81

C Source 1.00 0.57 0.03 -0.08 0.26 0.28 0.20 0.13

0.00 1.76 2.14 3.59 4.22 3.59 3.59 3.92

0.00 0.68 0.77 0.95 0.96 0.98 0.98 0.99

D Source 1.00 0.12 0.17 0.11 0.24 0.21 0.07

0.00 0.17 0.24 0.25 0.25 0.25 0.25

0.00 0.42 0.78 0.80 0.89 0.89 0.95

E Source 1.00 0.13 0.06 0.24 0.07 0.18

0.00 0.10 0.10 0.11 0.11 0.11

Legend

ρ

P90

COD

0.00 0.61 0.64 0.78 0.79 0.90

F Non-Source 1.00 0.02 0.19 0.09 0.09

0.00 0.02 0.02 0.02 0.02

0.00 0.39 0.61 0.58 0.82

G Non-Source 1.00 0.65 0.39 0.38

0.00 0.01 0.02 0.02

0.00 0.54 0.61 0.85

H Non-Source 1.00 0.51 0.40

0.00 0.01 0.01

0.00 0.55 0.77

I Non-Source 1.00 0.37

0.00 0.01

0.00 0.78

J Non-Source 1.00

0.00

0.00

1 Figure 3A-4 illustrates Pb monitor locations within Hillsborough and Pinellas Counties in FL, 

2 which comprise the greater Tampa-St. Petersburg metropolitan area. Two source-oriented monitors (A and 

3 B) were located within Hillsborough County, and one non-source-oriented monitor (C) was located in 

4 Pinellas County. Monitor A was located 360 m north-northeast of the EnviroFocus Technologies battery 

5 recycling facility, which produced 1.3 tons/yr (U.S. EPA, 2008c), and monitor B was located 320 m

6 southwest of the same facility. Monitor C was located next to a two-lane road in Pinellas Park, FL.

7 Figure 3A-5 displays seasonal wind roses for the Tampa-St. Petersburg metropolitan area. These 

8 wind roses suggest shifting wind directions throughout the winter, spring, and summer. During the winter, 
May 2011 3-141 DRAFT – DO NOT CITE OR QUOTE

1 the highest winds came from the north and northeast with little influence from the west and southwest.

2 During spring and summer, easterly and westerly winds were evident from the wind rose, with winds 

3 from the west being slightly higher in wind speed. During autumn, winds came predominantly from the 

4 northeast with little signal from the west or south.

5 Seasonal and year-round concentrations are reported for Hillsborough and Pinellas Counties in 

Figure 3A-6. The average annual concentration at monitor A was 0.15 μg/m3 6 , and the 95th percentile was 

0.70 μg/m3 7 . During winter, the 60th percentile of the data met the level of the NAAQS. At this site, the 

8 highest concentrations occurred during summer, which corresponded to the time when westerly winds 

were stronger. Concentration data at monitor B were much higher, with an annual average of 0.45 μg/m3 9

and a 95th percentile of 1.9 μg/m3 10 . Annually, the 55th percentile exceeded the level of the NAAQS, and in 

11 autumn the 45th percentile exceeded the NAAQS. The highest concentrations occurred in autumn, 

12 coinciding with the time when winds blew from the northeast, when monitor B was most often downwind 

13 of the battery recycling facility. The non-source-oriented monitor C always reported concentrations of 0.0 

μg/m3 14 . This is likely related to its location next to a quiet road in a small city. 

15 Intersampler correlations, shown in Table 3A-8, illustrate that Pb has high intra-urban spatial 

16 variability. The source oriented monitors were anticorrelated (ρ = -0.08). This was likely related to the 

17 fact that they were designated to monitor the same source and were downwind of the source at different 

18 times.
May 2011 3-142 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-4. Pb TSP monitor locations within Hillsborough and Pinellas 

Counties, FL (12-057 and 12-103), 2007-2009.Top: view of all 

Pb FRM monitors in Hillsborough and Pinellas Counties. 

Bottom: Close up of industrial site around monitors A and B.
May 2011 3-143 DRAFT – DO NOT CITE OR QUOTE

Source: NRCS (2011).

Figure 3A-5. Wind roses for Hillsborough/Pinellas Counties, FL, obtained 

from meteorological data at Tampa International Airport, 1961-

1990.Clockwise from top left: January, April, July, and October.

Note that wind percentages vary from month to month.
May 2011 3-144 DRAFT – DO NOT CITE OR QUOTE

Site A B C

SITE ID 12-057-1073 12-057-1066 12-103-3005

MEAN 0.15 0.45 0.00

SD 0.27 1.08 0.00

OBS 154 155 58

% BELOW MDL 20 5 95

Source orientation Source Source Non-source

Figure 3A-6. Box plots of annual and seasonal Pb TSP concentrations

(μg/m3

) from source-oriented and non-source-oriented 

monitors within Hillsborough and Pinellas Counties, FL (12-

057 and 12-103), 2007-2009.
May 2011 3-145 DRAFT – DO NOT CITE OR QUOTE

Table 3A-8.Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Hillsborough and Pinellas Counties, FL (12-

057 and 12-103), 2007-2009.

A B C

Source Source Non-source

A Source 1.00 -0.08

0.00 1.20 0.50

0.00 0.71 1.00

B Source 1.00

0.00 2.20

Legend 0.00 1.00

C Non-source ρ 1.00

P90 0.00

COD 0.00

1 Figure 3A-7 illustrates Pb monitor locations within Cook County, IL. Eight monitors were located 

2 within Cook County, four of which were designated by the Illinois Environmental Protection Agency 

3 (IEPA) in data reported to the AQS as source-oriented and the other four were non-source-oriented 

4 monitors. Monitor A was situated within 10 km of 6 sources ranging in emissions from 0.14 to 1.08 

5 tons/yr (U.S. EPA, 2008a). Monitor A was also sited in the median of I-90/I-94. Monitor B was located on 

6 the northern roadside of I-290 and was within 10 km of 2 Pb sources (0.41 and 1.08 tons/yr) (U.S. EPA, 

7 2008a). Monitor C was also located within 10 km of 6 sources in Cook County and Lake County, IN; the 

8 largest of those sources was 2.99 tons/yr and was located 8 km southeast of monitor C (U.S. EPA, 2008a).

9 Monitor C was placed on the roof of a high school. Monitor D was located roughly 60 m west of I-294 

10 and adjacent to O’Hare International Airport. Monitor E was located on the rooftop of a building rented 

11 for government offices in Alsip, IL, a suburb south of Chicago. This location was roughly 1 km north of I12 294 but not located on an arterial road; it was 9 km southeast of a 0.56 tons/yr source (U.S. EPA, 2008a). 

13 Monitor F was sited in the parking lot of a water pumping station, 100 m north of I-90 and 300 m

14 northwest of the junction between I-90 and I-94. This site was 2 km north-northwest of a 0.10 tons/yr 

15 source (U.S. EPA, 2008a). Monitor G was situated atop an elementary school in a residential 

16 neighborhood on the south side of Chicago, roughly 100 m south of a rail line and over 300 m west of the 

17 closest arterial road. Although not designated as a source monitor, monitor G was located 2 km southwest 

18 of facilities emitting 0.30 and 0.41 tons/yr (U.S. EPA, 2008a). Monitor H was sited on the grounds of the 

19 Northbrook Water Plant. I-94 curves around this site and was approximately 700 m from the monitor to 

20 the east and around to the north. Figure 3A-8 displays seasonal wind roses for Cook County. Wind 

21 patterns were quite variable during each season for this area. During the winter, winds mostly came from 
May 2011 3-146 DRAFT – DO NOT CITE OR QUOTE

1 the west, with smaller contributions from the northwest, southwest, and south. In spring, measurable 

2 winds were omni-directional, with the highest winds coming from the south and northeast. Winds 

3 originated predominantly from the southwest and south during the summer, with measurable contributions 

4 from the northeast as well. In autumn, wind flow was predominantly from the south, but smaller 

5 contributions also came from the southwest, west, and northwest.

6 Figure 3A-9 presents seasonal box plots of Pb concentration at the eight monitors located within 

Cook County. The maximum 95th percentile concentration on this plot was 0.14 μg/m3 7 , so the scale of 

8 this box plot makes the variability in these data appear wider than the data presented for Los Angeles 

9 County and Hillsborough/Pinellas Counties.

10 Monitor C was in closest proximity to the industrial steel facilities located in Lake County, IN. The 

average of concentrations measured at monitor C was 0.031 μg/m3, with a median of 0.02 μg/m3 11 and a 

maximum concentration of 0.31 μg/m3. In winter, the 95th percentile of data was 0.14 μg/m3 12 . The higher 

13 values could potentially be attributed to transport of emissions; winds blow from the southeast roughly 

14 10-15% of the time throughout the year. No other monitors in Cook County reported values above the 

15 level of the NAAQS.

16 Three “near-road” monitors, A, B, and D can be compared with the other monitors to consider the 

17 possibility of roadside resuspension of Pb dust from contemporaneous sources, as discussed in Section 

18 3.2.2.5. It would be expected that resuspension would diminish with distance from the road. The 2

roadside monitors, A and B, reported average concentrations of 0.030 μg/m3 and 0.024 μg/m3 19 , 

respectively. The median concentrations for monitors A and B were 0.02 μg/m3 20 . Fifteen percent of data 

21 were below the MDL for monitor A, and 25% were below the MDL for monitor B. Note that data 

22 obtained from monitor A may reflect industrial emissions as well. Monitor D was located roughly 60 m

23 from the closest interstate and 570 m from the closest runway at O’Hare International Airport. However, 

the average concentration at this site was 0.012 μg/m3 24 , and 85% of data were below the MDL. In contrast, 

non-source monitors, E, F, G, and H had average concentrations of 0.011-0.017 μg/m3 25 . It is possible that 

26 the difference between Pb concentrations at monitors A and B and Pb concentrations at the other monitors 

27 was related to proximity to the roadway, although this cannot be stated with certainty without source 

28 apportionment data to confirm or refute the influence of industrial plumes from Lake County, IN or local 

29 sources at each of the monitors.

30 Comparison among the monitor data demonstrates a high degree of spatial variability (Table 3A-9). 

31 None of the source-oriented monitors were well correlated with each other. The highest correlation 

32 between source-oriented monitors occurred for monitors (A and B [ρ = 0.26]). This might have reflected 

33 more substantial differences related to the additional influence of industrial sources nearby monitor A.

34 Monitors (C and D) were uncorrelated with each other and with monitors (A and B), likely because their 

35 exposure to sources was substantially different. The source-oriented and non-source-oriented monitors 

36 were generally not well correlated. The highest correlation occurred between monitors (D and H [ρ = 
May 2011 3-147 DRAFT – DO NOT CITE OR QUOTE

1 0.53]). Both were located on the north side of Cook County, but monitor H was roughly 20 km northeast 

2 of monitor D. Winds blew from the southwest roughly 20-30% of the time throughout the year and from 

3 the northeast 20-25% of the time between the months of March and July, so the correlation may have 

4 been related to a common signal transported across both sites. Monitors (B and F [ρ = 0.46]) were also 

5 moderately correlated. Monitor F is roughly 12 km northeast of monitor B, so the same common wind 

6 influence for monitors D and H may have also caused the moderate correlation between monitors (B and 

7 F). Monitor F was also moderately correlated with the other 3 non-source monitors (ρ = 0.36 to 0.45), and 

8 the correlation between monitors (E and G) was ρ = 0.40. The data from monitor H did not correlate well 

9 with those from monitors E and G. The non-source monitors were oriented from north to south over a 

10 distance of roughly 50 km in the following order: monitor H, monitor F, monitor G, and monitor E. The 

11 correlation pattern may have been related to distance between samplers. H was located in the suburb of 

12 Northbrook, monitors F and G were sited within the Chicago city limits, and monitor E was situated in a 

13 town near the south side of Chicago. Differences among land use may have been related to the lack of 

14 correlation of the monitor H data with those from monitors E and G. It is likely that data from monitor F 

15 was at times better correlated with monitors E and G and at other times with monitor H, since it had 

16 moderate correlation with all three other non-source monitors.
May 2011 3-148 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-7. Pb TSP Monitor locations within Cook County, IL (17-031),

2007-2009.Top: view of all Pb FRM monitors in Cook County.

Bottom left: Close up of the high traffic site around monitor A.

Bottom right: Close up of O’Hare International Airport adjacent 

to monitor D.
May 2011 3-149 DRAFT – DO NOT CITE OR QUOTE

Source: NRCS (2011)

Figure 3A-8. Wind roses for Cook County, IL, obtained from meteorological 

data at O’Hare International Airport, 1961-1990.Clockwise from 

the top left: January, April, July, and October. Note that the 

wind percentages vary from month to month. 
May 2011 3-150 DRAFT – DO NOT CITE OR QUOTE

Site A B C D E F G H

SITE ID 17-031-

0026

17-031-

6003

17-031-

0022

17-031-

3103

17-031-

0001

17-031-

0052

17-031-

3301

17-031-

4201

MEAN 0.030 0.024 0.031 0.012 0.013 0.017 0.017 0.011

SD 0.020 0.013 0.036 0.0062 0.0078 0.0098 0.0097 0.0031

OBS 179 175 177 168 177 175 171 168

% BELOW 

MDL 15 25 25 85 75 55 50 95

Source 

orientation Source Source Source Source Nonsource

NonsourceNonsourceNonsource

Figure 3A-9. Box plots of annual and seasonal Pb TSP concentrations 

(μg/m3

) from source-oriented and non-source-oriented 

monitors within Cook County, IL (17-031), 2007-2009.
May 2011 3-151 DRAFT – DO NOT CITE OR QUOTE

Table 3A-9.Correlations between Pb TSP concentrations from source-oriented and nonsource-oriented monitors within Cook County, IL (17-031), 2007-2009.

A B C D E F G H

Source Source Source Source NonSource

NonSourceNonSource

NonSource

A Source 1.00 0.26 -0.01 0.08 0.06 0.32 0.18 0.06

0.00 0.03 0.06 0.04 0.04 0.03 0.03 0.04

0.00 0.29 0.38 0.43 0.41 0.36 0.36 0.45

B Source 1.00 0.05 0.10 0.32 0.46 0.35 -0.01

0.00 0.04 0.03 0.03 0.02 0.02 0.03

0.00 0.33 0.36 0.34 0.29 0.30 0.40

C Source 1.00 0.04 0.16 0.10 0.17 0.06

0.00 0.05 0.05 0.04 0.05 0.05

0.00 0.40 0.39 0.35 0.35 0.42

D Source 1.00 0.21 0.37 0.07 0.53

0.00 0.01 0.01 0.02 0.01

0.00 0.19 0.24 0.28 0.15

E Non-Source 1.00 0.36 0.40 0.07

0.00 0.02 0.01 0.01

Legend 0.00 0.24 0.24 0.20

F Non-Source ρ 1.00 0.41 0.45

P90 0.00 0.01 0.02

COD 0.00 0.24 0.26

G Non-Source 1.00 0.05

0.00 0.02

0.00 0.27

H Non-Source 1.00

0.00

0.00

1 Figure 3A-10 illustrates Pb monitor locations with Jefferson County, MO. Ten source-oriented 

2 monitors surrounded the Doe Run primary Pb smelter in Herculaneum, MO on the west and northwestern 

3 sides. The largest distance between these monitors was approximately 1.5 km. Monitor E located on the 

4 Doe Run facility roughly 20 m west of the nearest building. Monitors A, B, C, D, F, G, and H were all 

5 located approximately 200 m west of the facility. Monitors D, E, and H were situated alongside service 

6 roads to the facility. Monitor I was sited 100 m north of the smelter, and monitor J was located 

7 approximately 600 m northwest of the facility. The Doe Run smelter was the only active primary smelter 

8 in the U.S. at the time of this review (2007-2009), and the facility was estimated to have emitted 

9 41.1 tons Pb/yr (U.S. EPA, 2008d). Figure 3A-11 displays seasonal wind roses for Jefferson County.

10 During winter, predominant winds originated from the northwest, with a smaller fraction of calmer winds 

11 originating in the south-southeast. During the spring, the south-southeasterly winds became more 

12 prevalent with a measurable fraction of stronger winds still originating in the north-northwest. In the 
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1 summer, winds were omni-directional and generally calmer. A slightly larger percentage came from the 

2 south compared with other wind directions. Autumn winds were most predominantly south-southeastern, 

3 with a smaller fraction from the west and northwest.

4 Figure 3A-12 illustrates the seasonal distribution of concentrations at monitors A-J in Jefferson 

County. The annual average concentrations ranged from 0.18 to 1.36 μg/m3 5 across the monitors. The 

maximum concentration was measured at monitor C to be 21.6 μg/m3 6 , which was 144 times higher than 

7 the level of the standard. For this monitor, the 25th percentile of the data was at the level of the standard.

8 In general, median and 75th percentile concentrations were highest during the springtime and second 

9 highest during the fall. These seasons coincide with periods when the southeastern winds were stronger 

10 and more prevalent. Because the Doe Run facility had two 30-meter stacks (Bennett, 2007), it is possible 

11 that the emissions measured at the closer monitors were due to either fugitive emissions from the plant or, 

12 for the case where ground equipment or vehicles are operated nearby, that previously deposited emissions 

13 from the plant were resuspended.

14 Spatial variability among the monitors is lower than at many sites, because the monitors are 

15 relatively close together and are located on one side of the same source (Table 3A-10). Correlations range 

16 from ρ = -0.04 to 0.96. High correlations (ρ ≥ 0.75) occurred for monitors (A and C), (A and D), (C and 

17 D), (D and F), (E and F), (G and H), and (I and J). Monitors (A and C), (A and D), (C and D), (D and F), 

18 (E and F), and (G and H) are all within 250 m of each other. For the highest correlation (ρ = 0.96, for 

19 monitors (E and F), monitor F is 250 m directly east of monitor E. Low correlation (ρ ≤ 0.25) generally 

20 occurred when monitors B, I, and J were compared with monitors A, C, D, E, F, G, and H. Monitors B, I, 

21 and J were on the outskirts of the measurement area and so were likely oriented such that the 

22 southeasterly winds did not carry pollutant to these sites concurrently with the signal recorded by the 

23 other monitors.
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Figure 3A-10. Pb TSP Monitor locations within Jefferson County, MO (29-

099), 2007-2009.Note that all monitors surround the Doe Run 

industrial facility. Top: Map view of all monitors in Jefferson 

County. Bottom: Satellite view of the monitors and the Doe 

Run facility.
May 2011 3-154 DRAFT – DO NOT CITE OR QUOTE

Source: NRCS (2011)

Figure 3A-11. Wind roses for Jefferson County, MO, obtained from 

meteorological data at St. Louis/Lambert International Airport, 

1961-1990.Clockwise from top left: January, April, July, and 

October. Note wind percentages vary from month to month.
May 2011 3-155 DRAFT – DO NOT CITE OR QUOTE

Site A B C D E F G H I J

SITE ID 29-099-

0022

29-099-

0024

29-099-

0015

29-099-

0023

29-099-

0004

29-099-

0020

29-099-

0021

29-099-

0005

29-099-

0011

29-099-

0013

MEAN 0.43 0.36 1.36 0.39 1.12 0.69 0.75 0.29 0.34 0.18

SD 0.54 0.49 1.97 0.54 1.67 1.01 1.25 0.59 0.85 0.33

OBS 622 209 1E3 632 1E3 575 953 351 366 177

% BELOW 

MDL 0 5 0 0 5 0 5 25 5 15

Source 

orientation Source Source Source Source Source Source Source Source Source Source

Figure 3A-12. Box plots of annual and seasonal Pb TSP concentrations 

(μg/m3

) from source-oriented and non-source-oriented 

monitors within Jefferson County, MO (29-099), 2007-2009.
May 2011 3-156 DRAFT – DO NOT CITE OR QUOTE

Table 3A-10. Correlations between Pb TSP concentrations from source-oriented and 

non-source-oriented monitors within Jefferson County, MO (29-099), 2007-

2009

A B C D E F G H I J

Source Source Source Source Source Source Source Source Source Source

A Source 1.00 0.59 0.80 0.83 0.57 0.64 0.33 0.35 0.07 0.05

0.00 0.71 1.55 0.42 1.93 1.14 1.41 0.74 0.92 0.78

0.00 0.46 0.48 0.30 0.55 0.45 0.57 0.64 0.67 0.69

B Source 1.00 0.53 0.43 0.10 0.14 0.07 0.22 0.10 0.09

0.00 1.86 0.87 2.77 1.96 2.08 0.94 1.04 0.91

0.00 0.58 0.51 0.69 0.62 0.68 0.68 0.65 0.65

C Source 1.00 0.86 0.59 0.72 0.26 0.27 -0.04 0.04

0.00 1.56 2.26 1.26 2.94 2.65 3.18 2.60

0.00 0.50 0.50 0.46 0.60 0.74 0.73 0.73

D Source 1.00 0.71 0.80 0.41 0.56 0.14 0.18

0.00 1.83 1.02 1.38 0.76 0.88 0.70

0.00 0.50 0.36 0.53 0.61 0.63 0.66

E Source 1.00 0.96 0.54 0.46 0.06 0.16

0.00 0.86 2.16 2.50 3.09 2.57

Legend 0.00 0.35 0.49 0.66 0.70 0.72

F Source ρ 1.00 0.56 0.54 0.10 0.19

P90 0.00 1.13 1.51 1.74 1.40

COD 0.00 0.47 0.63 0.65 0.70

G Source 1.00 0.87 0.28 0.38

0.00 1.53 2.10 2.08

0.00 0.61 0.63 0.66

H Source 1.00 0.20 0.30

0.00 0.89 0.56

0.00 0.67 0.65

I Source 1.00 0.79

0.00 0.62

0.00 0.48

J Source 1.00

0.00

0.00

1 Figure 3A-13 illustrates Pb monitor locations with Cuyahoga County, OH. Five monitors are 

2 located within Cuyahoga County, three of which were designated by the Ohio EPA (OEPA) as source3 oriented and the other two were non-source-oriented monitors. Monitors A, B, and C were all located 

4 within 1-10 km of six 0.1 tons/yr source facilities and one 0.2 tons/yr source (U.S. EPA, 2008e).

5 Additionally, monitor B was located 30 m north of the Ferro Corporation headquarters. This facility was 

6 stated in the 2005 NEI to have no emissions, but it was thought by the OEPA to be the source of 

7 exceedances at this monitor (U.S. EPA, 2008e). Monitor A was sited roughly 300 m south of the Ferro 

8 Corporation facility. Monitor C was located 2.2 km west-northwest of the 0.5 ton/yr Victory White Metal 
May 2011 3-157 DRAFT – DO NOT CITE OR QUOTE

1 Co. facility. Monitor C was also roughly 250 m southeast of I-490. Monitors D and E were designated as 

2 non-source-oriented monitors, although monitor D was just 600 m further from the Victory White Metal 

3 facility than was monitor C. Monitor D was sited on a residential street located 50 m north of I-490.

4 Monitor E was located on the rooftop of a building within 20 m of a four-lane arterial road. Figure 3A-14 

5 displays seasonal wind roses for Cuyahoga County. During winter, summer, and autumn, the predominant 

6 winds were from the southwest, with stronger winds recorded during the winter. In the spring, the 

7 strongest winds still emanated from the south-southwest, but measurable winds were also scattered from 

8 the northeast to the northwest.

9 Figure 3A-15 illustrates the seasonal distribution of Pb concentration data at the five monitoring 

10 sites. The influence of southern winds, along with close proximity to a potentially-emitting facility, could 

have caused the elevated concentrations observed at monitor B (average: 0.10 μg/m3 11 ). The 80th percentile 

12 of data was at the level of the NAAQS at this monitor, and during autumn the 60th percentile of data met 

13 the level of the NAAQS. The maximum concentration during fall and for the monitor year-round was 

0.22 μg/m3 14 . Concentration data from all other monitors were below the level of the NAAQS. For monitor 

A, the average concentration was 0.025 μg/m3, and the median reached 0.04 μg/m3 15 during the summer.

Maximum concentration at this monitor was 0.07 μg/m3 16 . Concentrations at monitor C averaged 0.017 

μg/m3, and those at monitors D and E averaged 0.014 μg/m3 and 0.013 μg/m3 17 , respectively. Maximum 

concentrations reached 0.04 μg/m3 18 at all three monitors.

19 The level of spatial variability is illustrated by the intersampler correlations presented in Table 3A20 11. Monitors A and B appear to be anticorrelated (ρ = -0.13). If the Ferro site was the dominant source in 

21 this area, then the anticorrelation was likely caused by the positioning of monitors A and B on opposite 

22 sides of that facility. At any given time, potential emissions from the Ferro plant may have affected 

23 monitors A and B at distinct times. Monitors C, D, and E correlated well with each other (ρ = 0.67 to 

24 0.77). Given that all 3 monitors are separated by roughly 2.8 km, it is possible that the relatively high 

25 correlations related to common sources, as suggested in the previous paragraph. Little correlation was 

26 observed between the source-oriented and non-source-oriented monitors.
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Figure 3A-13. Pb TSP Monitor locations within Cuyahoga County, OH (39-

035), 2007-2009.Top: view of all Pb FRM monitors in Cuyahoga 

County. Bottom left: Close up of industrial site around 

monitors A and B. Bottom right: Close up of monitor D north 

of I-490.
May 2011 3-159 DRAFT – DO NOT CITE OR QUOTE

Source: NRCS (2011)

Figure 3A-14. Wind roses for Cuyahoga County, OH, obtained from 

meteorological data at Cleveland/Hopkins International 

Airport, 1961-90.Clockwise from top left: Jan, April, July, and 

October. Note wind percentages vary from month to month.
May 2011 3-160 DRAFT – DO NOT CITE OR QUOTE

Site A B C D E

SITE ID 39-035-0050 39-035-0049 39-035-0061 39-035-0038 39-035-0042

MEAN 0.025 0.10 0.017 0.014 0.013

SD 0.018 0.060 0.010 0.0072 0.0076

OBS 36 36 36 35 36

% BELOW MDL 20 0 30 45 45

Source orientation Source Source Source Non-source Non-source

Figure 3A-15. Box plots of annual and seasonal Pb TSP concentrations 

(μg/m3

) from source-oriented and non-source-oriented 

monitors within Cuyahoga County, OH (39-035), 2007-2009.
May 2011 3-161 DRAFT – DO NOT CITE OR QUOTE

Table 3A-11. Correlations between Pb TSP concentrations from source-oriented and 

non-source-oriented monitors within Cuyahoga County, OH (39-035), 2007-

2009

A B C D E

Source Source Source Non-Source Non-Source

A Source 1.00 -0.13 0.24 0.19 0.21

0.00 0.18 0.05 0.04 0.05

0.00 0.64 0.33 0.35 0.37

B Source 1.00 0.31 0.24 0.34

0.00 0.18 0.19 0.19

0.00 0.69 0.71 0.73

C Source 1.00 0.77 0.67

0.00 0.01 0.01

Legend 0.00 0.17 0.18

D Non-Source ρ 1.00 0.67

P90 0.00 0.01

COD 0.00 0.17

E Non-Source 1.00

0.00

0.00

1 Figure 3A-16 illustrates Pb monitor locations within Sullivan County, TN. Three source-oriented 

2 monitors were situated around an Exide Pb recycling facility emitting 0.78 tons/yr (U.S. EPA, 2008f).

3 Monitors A and C are positioned along the facility’s service road and are approximately 100 m and 200 m

4 away from the facility, respectively. Monitor A is directly next to the road, and monitor C is roughly 15 m

5 from the road. Monitor B is located in the facility’s parking lot roughly 50 m from the closest building. 

6 The facility and all three monitors are approximately 1.5 km northwest of the Bristol Motor Speedway 

7 and Dragway racetracks, which hosts a variety of auto races each year, including NASCAR, KART, and 

8 drag racing. Although the NASCAR circuit no longer uses tetraethyl Pb as an anti-knock agent in its fuel, 

9 some of the smaller racing circuits continue to do so. However, the speedway is rarely upwind of the 

10 monitoring sites and so likely had minimal influence on the reported concentrations. Figure 3A-17 

11 displays seasonal wind roses for Sullivan County. During winter and spring, the predominant winds come 

12 from the southwest and west. In the summer, the percentage of wind coming from the west and southwest 

13 is roughly equal to that for wind coming from the east and northeast, although the easterly winds are 

14 calmer. During autumn, winds come predominantly from the northeast and east, although these winds 

15 tend to be calmer than those originating from the southwest and west.

16 The data presented in Figure 3A-18 illustrates that concentrations above the level of the NAAQS 

occurred frequently at the monitors. The average concentrations at monitors A, B, and C were 0.11 μg/m3 17 , 

0.051 μg/m3, and 0.059 μg/m3, respectively. Median concentrations were 0.08 μg/m3, 0.03 μg/m3 18 , and 

0.04 μg/m3, respectively. The 75th 19 percentile of year-round data at monitor A was at the level of the 
May 2011 3-162 DRAFT – DO NOT CITE OR QUOTE

1 NAAQS, while the 95th percentile of data were below the NAAQS level for monitors B and C. The 

maxima at each monitor were 0.76 μg/m3, 0.26 μg/m3, and 0.43 μg/m3 2 for monitors A, B, and C. It was 

3 surprising that the concentrations measured at monitor A tended to be higher because the predominant and 

4 stronger winds came from the southwest, so in many cases monitor A was upwind of the facility. It is 

5 possible that Pb that had either deposited or was stored in waste piles became readily resuspended by 

6 traffic-related turbulence and was measured at monitor A since that monitor was closest to the road. The 

7 slightly higher concentrations at monitor C compared with those from monitor C are consistent with the 

8 southwestern winds.

9 Not surprisingly, the correlations of monitor A with monitors B and C were quite low (Table 3A10 12). The correlation between monitors B and C was ρ = 0.45. It makes sense that the correlation for these 

11 monitors would be somewhat higher because they are both oriented to the east of the Pb recycling facility, 

12 although monitor C is to the northeast and monitor B to the east-southeast.
May 2011 3-163 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-16. Pb TSP Monitor locations within Sullivan County, TN (47-163), 

2007-2009.Top: Map, bottom: Satellite image. Monitors A, B, 

and C surround the Exide Pb recycling facility. Just to the 

southeast is the Bristol motor speedway.
May 2011 3-164 DRAFT – DO NOT CITE OR QUOTE

Source: NRCS (2011)

Figure 3A-17. Wind roses for Sullivan County, TN, obtained from 

meteorological data at Bristol/Tri City Airport, 1961-

90.Clockwise from top left: January, April, July, and October.

Note that the wind percentages vary from month to month.
May 2011 3-165 DRAFT – DO NOT CITE OR QUOTE

Site A B C

SITE ID 47-163-3001 47-163-3002 47-163-3003

MEAN 0.11 0.051 0.059

SD 0.11 0.036 0.047

OBS 334 362 345

% BELOW MDL 0 0 0

Source orientation Source Source Source

Figure 3A-18. Box plots of annual and seasonal Pb TSP concentrations 

(μg/m3

) from source-oriented and non-source-oriented 

monitors within Sullivan County, TN (47-163), 2007-2009.
May 2011 3-166 DRAFT – DO NOT CITE OR QUOTE

Table 3A-12. Correlations between Pb TSP concentrations from source-oriented and 

non-source-oriented monitors within Sullivan County, TN (47-163), 2007-2009

A B C

Source Source Source

A Source 1.00 -0.04 0.13

0.00 0.21 0.19

0.00 0.47 0.43

B Source 1.00 0.45

0.00 0.06

Legend 0.00 0.23

C Source ρ 1.00

P90 0.00

COD 0.00

3.8.2. Size Distribution of Pb-Bearing PM

Table 3A-13. Correlations and average of the concentration ratios for co-located 

monitors, TSP versus PM10, TSP versus PM2.5, and PM10 versus PM2.5.Data are 

bolded for sites where the TSP, PM10, and PM2.5 monitors were colocated for at least one sampling year.

Site County Land Type Years Corr Avg

Ratio Years Corr AvgRatio Years Corr Avg

Ratio

PM10:TSP PM2.5:TSP PM2.5: PM10

010730023 Jefferson, AL Urban and 

center city 2005-2006 0.87 0.80 2005-2006 0.74 0.84 2005-2006 0.81 1.02

040139997 Maricopa, AZ Urban and 

center city 2006-2009 0.40 0.59

0600110

01 Alameda, CA Suburban 1994-1998 0.00 2.31

060130002 Contra Costa, CA Suburban 1994-1998 0.27 2.60

060130003 Contra Costa, CA Suburban 1994-1997 0.31 1.04

060190008 Fresno, CA Suburban 1995-2001 0.92 0.92 2000-2009 0.58 0.66 2000-2001 0.83 1.16

060250005 Imperial, CA Suburban 1996-2001 0.77 0.91 2002-2009 0.95 0.74

060290014 Kern, CA Urban and 

center city 1995-2000 0.92 0.76 2001-2009 0.22 0.72

060371103 Los Angeles, CA Urban and 

center city 2002-2009 0.22 0.28

060374002 Los Angeles, CA Suburban 1995-2000 0.72 0.39

060550003 Napa, CA Urban and 

center city 1994-1994 0.42 0.93

060658001 Riverside, CA Suburban 1995-1997 0.27 0.39 2001-2009 0.59 0.40

060730003 San Diego, CA Suburban 2001-2009 0.35 0.48

060750005 San Francisco, CA Urban and 

center city 1994-1998 0.29 0.98

060771002 San Joaquin, CA Urban and 

center city 1995-2000 0.73 0.82

060850004 Santa Clara, CA Urban and 

center city 1994-2000 0.32 0.95 2000-2002 0.63 0.63

060850004 Santa Clara, CA Urban and 

center city 2002-2009 0.11 0.78 2008-2009 0.76 1.41

060853001 Santa Clara, CA Suburban 1994-1998 0.16 1.00

060990002 Stanislaus, CA Urban and 

center city 1995-1998 0.94 0.82

060990005 Stanislaus, CA Urban and 

center city 1998-2000 0.79 1.02

061112002 Ventura, CA Suburban 2001-2009 0.47 0.74
May 2011 3-167 DRAFT – DO NOT CITE OR QUOTE

Site County Land Type Years Corr Avg

Ratio Years Corr AvgRatio Years Corr Avg

Ratio

PM10:TSP PM2.5:TSP PM2.5: PM10

080010006 Adams, CO Suburban 2001-2006 0.16 0.43

080410011 El Paso, CO Urban and 

center city 2001-2006 0.03 0.39

080770017 Mesa, CO Urban and 

center city 2004-2008 0.42 0.87

100032004 New Castle, DE Urban and 

center city 2003-2007 0.47 0.44

110010043 District of Columbia, DC Urban and 

center city 2004-2009 0.47 0.73

120571075 Hillsborough, FL Urban and 

center city 2001-2003 0.83 1.86

120573002 Hillsborough, FL Rural 2004-2009 0.66 1.55

121030026 Pinellas, FL Suburban 2004-2009 0.56 1.89

130690002 Coffee, GA Rural 2003-2009 0.82 1.46

130890002 DeKalb, GA Suburban 2003-2009 0.92 1.69

150032004 Honolulu, HI Urban and 

center city 2003-2009 0.77 2.34

170314201 Cook, IL Suburban 2006-2009 0.53 0.39 2002-2009 0.25 0.36 2005-2009 0.65 1.01

180970078 Marion, IN Suburban 2002-2009 0.75 0.78

201731012 Sedgwick, KS Suburban 1993-1997 0.63 0.33

202090015 Wyandotte, KS Urban and 

center city 1993-1997 0.66 0.55

202090020 Wyandotte, KS Urban and 

center city 1993-1997 0.99 0.56

210430500 Carter, KY Rural 2008-2009 0.22 1.39

211930003 Perry, KY Suburban 2003-2008 0.76 1.47

220511001 Jefferson, LA Suburban 2005-2006 0.96 0.79

220710010 Orleans, LA Urban and 

center city 2005-2006 0.94 0.64

220710012 Orleans, LA Urban and 

center city 2005-2006 0.91 0.53

220718105 Orleans, LA Urban and 

center city 2005-2006 0.98 0.80

220718401 Orleans, LA Urban and 

center city 2005-2006 0.89 0.45

220758400 Plaquemines, LA Urban and 

center city 2005-2005 0.98 0.83

220870004 St. Bernard, LA Suburban 2005-2006 0.94 0.78

220878103 St. Bernard, LA Urban and 

center city 2005-2006 0.90 0.66

250250042 Suffolk, MA Urban and 

center city 2009-2009 0.43 0.37 2003-2009 0.38 0.78

260770905 Kalamazoo, MI Urban and 

center city 1993-1996 0.98 0.77

260810020 Kent, MI Urban and 

center city 2005-2007 0.58 0.70

261130001 Missaukee, MI Rural 2002-2007 0.73 1.38

261250010 Oakland, MI Urban and 

center city 2001-2002 0.40 1.60

261390009 Ottawa, MI Urban and 

center city 2000-2001 0.90 0.67

261610008 Washtenaw, MI Urban and 

center city 2003-2007 0.58 0.71

261630001 Wayne, MI Suburban 2001-2007 0.68 0.58

261630019 Wayne, MI Suburban 2001-2002 0.45 0.51

261630033 Wayne, MI Suburban 2003-2009 0.87 0.84 2002-2009 0.84 0.49 2003-2009 0.86 0.61

270530053 Hennepin, MN Urban and 

center city 1996-2001 0.47 0.55

270530963 Hennepin, MN Urban and 

center city 2002-2009 0.64 0.42

280458104 Hancock, MS Suburban 2005-2006 0.93 1.51

280458105 Hancock, MS Rural 2005-2006 0.99 1.02

280458201 Hancock, MS Suburban 2005-2006 0.94 1.05

280470008 Harrison, MS Rural 2005-2006 0.87 0.99

280478101 Harrison, MS Suburban 2005-2006 0.98 0.99

280478102 Harrison, MS Suburban 2005-2006 0.80 1.10

280478103 Harrison, MS Suburban 2005-2006 0.93 1.09

280590006 Jackson, MS Urban and 

center city 2005-2006 0.97 0.78

295100085 St. Louis City, MO Urban and 

center city 2004-2004 0.96 1.10 2004-2004 0.26 1.08 2003-2009 0.76 0.76

330110020 Hillsborough, NH Urban and 

center city 2002-2005 0.42 0.81
May 2011 3-168 DRAFT – DO NOT CITE OR QUOTE

Site County Land Type Years Corr Avg

Ratio Years Corr AvgRatio Years Corr Avg

Ratio

PM10:TSP PM2.5:TSP PM2.5: PM10

330150014 Rockingham, NH Urban and 

center city 2003-2005 0.80 0.72

350010023 Bernalillo, NM Urban and 

center city 2004-2009 0.04 0.73

360050110 Bronx, NY Urban and 

center city 2007-2009 0.80 0.60

360551007 Monroe, NY Urban and 

center city 2007-2009 0.77 1.30

360610062 New York, NY Urban and 

center city 2005-2005 0.96 0.57

360632008 Niagara, NY Suburban 2005-2005 0.74 0.84

401091037 Oklahoma, OK Suburban 2009-2009 0.25 1.57

401431127 Tulsa, OK Urban and 

center city 2009-2009 0.34 0.74

410390060 Lane, OR Urban and 

center city 2002-2004 0.33 1.65

410510246 Multnomah, OR Urban and 

center city 2002-2003 0.90 0.90

410290133 Jackson, OR Urban and 

center city 2009-2009 0.54 1.10

410390060 Lane, OR Urban and 

center city 2004-2009 0.76 2.15

410510246 Multnomah, OR Urban and 

center city 2003-2006 0.98 0.99

410610119 Union, OR Urban and 

center city 2004-2007 0.15 1.60

420450002 Delaware, PA Urban and 

center city 2002-2008 0.04 0.11

420710007 Lancaster, PA Suburban 2004-2007 0.78 0.80

421010004 Philadelphia, PA Urban and 

center city 2000-2007 0.37 0.38

421010055 Philadelphia, PA Urban and 

center city 2005-2007 0.36 0.32

421010136 Philadelphia, PA Urban and 

center city 2004-2005 0.75 0.38

440070022 Providence, RI Urban and 

center city 2001-2002 0.78 0.54 2002-2009 1.00 0.70

440071010 Providence, RI Suburban 2001-2002 0.98 0.71

450250001 Chesterfield, SC Rural 2002-2009 0.37 1.76 2004-2009 0.41 1.63

450790019 Richland, SC Urban and 

center city 2001-2006 0.74 0.58

470370023 Davidson, TN Urban and 

center city 2003-2004 0.39 0.83

482011034 Harris, TX Urban and 

center city 2002-2005 0.41 0.40

482011039 Harris, TX Suburban 2000-2009 0.34 0.63

490110004 Davis, UT Suburban 2003-2009 0.68 0.91

500070007 Chittenden, VT Rural 2004-2009 0.89 0.97

510870014 Henrico, VA Suburban 2004-2008 0.54 0.79 2008-2009 0.91 1.08

530330038 King, WA Suburban 2001-2002 0.64 0.53

530330080 King, WA Urban and 

center city 2003-2009 0.91 0.81

530630016 Spokane, WA Suburban 2005-2005 0.77 0.91

550270007 Dodge, WI Rural 2004-2005 0.90 0.83 2005-2009 0.59 1.02

1
May 2011 3-169 DRAFT – DO NOT CITE OR QUOTE

3.8.3. Lead Concentration in a Multipollutant Context

Source, SO2

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Source, PM10

Non-Source, PM10

Source, O3

Non-Source, O3

Source, NO2

Non-Source, NO2

Source, CO

Non-Source, CO

Source, SO2

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Source, PM10

Non-Source, PM10

Source, O3

Non-Source, O3

Source, NO2

Non-Source, NO2

Source, CO

Non-Source, CO

Figure 3A-19a. Seasonal correlations of monitored Pb-TSP concentration 

with copollutant concentrations, 2007-2008. Top: winter; 

bottom: spring.
May 2011 3-170 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-19b. Seasonal correlations of monitored Pb-TSP concentration 

with copollutant concentrations, 2007-2008. Top: summer; 

bottom: fall.

Source, SO2

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Source, PM10

Non-Source, PM10

Source, O3

Non-Source, O3

Source, NO2

Non-Source, NO2

Source, CO

Non-Source, CO

Source, SO2

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Source, PM10

Non-Source, PM10

Source, O3

Non-Source, O3

Source, NO2

Non-Source, NO2

Source, CO

Non-Source, CO
May 2011 3-171 DRAFT – DO NOT CITE OR QUOTE

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Non-Source, PM10

Non-Source, O3

Non-Source, NO2

Non-Source, CO

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Non-Source, PM10

Non-Source, O3

Non-Source, NO2

Non-Source, CO

Figure 3A-20a. Seasonal correlations of monitored Pb-TSP concentration 

with copollutant concentrations, 2009. Top: winter; bottom: 

spring.

US Winter

Spearman Correlation Coefficient

-1.0 -0.5 0.0 0.5 1.0

 e

 e

 e

 e

 e

 e

 e
May 2011 3-172 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-20b. Seasonal correlations of monitored Pb-TSP concentration 

with copollutant concentrations, 2009. Top: summer; 

bottom: fall.

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Non-Source, PM10

Non-Source, O3

Non-Source, NO2

Non-Source, CO

Non-Source, SO2

Source, PM2.5

Non-Source, PM2.5

Non-Source, PM10

Non-Source, O3

Non-Source, NO2

Non-Source, CO
May 2011 3-173 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-21a. Seasonal correlations of monitored Pb-PM2.5 concentration 

with copollutant concentrations, 2007-2009. Left: winter; 

right: spring.

Zinc

Volatile Nitrate

Vanadium

Titanium

Sulfur

Sulfate

Sodium Ion

Sodium

Silicon

Selenium

Potassium Ion

Potassium

Organic Carbon, Blank Adjusted

Non-Volatile Nitrate

Nitrate

Nickel

Mercury

Manganese

Magnesium

Iron

Elemental Carbon

Crustal

Copper

Chromium

Chlorine

Carbonate Carbon

Calcium

Cadmium

Bromine

Arsenic

Ammonium

Aluminum

Zinc

Volatile Nitrate

Vanadium

Titanium

Sulfur

Sulfate

Sodium Ion

Sodium

Silicon

Selenium

Potassium Ion

Potassium

Organic Carbon, Blank Adjusted

Non-Volatile Nitrate

Nitrate

Nickel

Mercury

Manganese

Magnesium

Iron

Elemental Carbon

Crustal

Copper

Chromium

Chlorine

Carbonate Carbon

Calcium

Cadmium

Bromine

Arsenic

Ammonium

Aluminum
May 2011 3-174 DRAFT – DO NOT CITE OR QUOTE

Figure 3A-21b. Seasonal correlations of monitored Pb-PM2.5 concentration 

with copollutant concentrations, 2007-2009. Left: summer; 

right: fall.

Zinc

Volatile Nitrate

Vanadium

Titanium

Sulfur

Sulfate

Sodium Ion

Sodium

Silicon

Selenium

Potassium Ion

Potassium

Organic Carbon, Blank Adjusted

Non-Volatile Nitrate

Nitrate

Nickel

Mercury

Manganese

Magnesium

Iron

Elemental Carbon

Crustal

Copper

Chromium

Chlorine

Carbonate Carbon

Calcium

Cadmium

Bromine

Arsenic

Ammonium

Aluminum

Zinc

Volatile Nitrate

Vanadium

Titanium

Sulfur

Sulfate

Sodium Ion

Sodium

Silicon

Selenium

Potassium Ion

Potassium

Organic Carbon, Blank Adjusted

Non-Volatile Nitrate

Nitrate

Nickel

Mercury

Manganese

Magnesium

Iron

Elemental Carbon

Crustal

Copper

Chromium

Chlorine

Carbonate Carbon

Calcium

Cadmium

Bromine

Arsenic

Ammonium

Aluminum
May 2011 3-175 DRAFT – DO NOT CITE OR QUOTE

Table 3A-14. Copollutant exposures for various trace metal studies

Adgate et al. (2007) Riediker et al. (2003) Pekey et al. 

(2010) Molnar et al. (2007)

I-R (med)a,b Personal 

(median)c Vehicle 

(range)c Roadside (range)c I –near industry (range)a I-R (median)a,b I-School (median)a

I-Pre-School 

(median)a

Location Minnesota New Jersey Kocaeli, Turkey Stockholm, Sweden

PM2.5 24,000 31,579 24,400-29,800

Pb 1.5 3.2 2-3 4-6 34-85 2.8 2.5 1.7

S 272.1 351.6 905-1592 1416-2231 435-489 330 290 220

Ca 85.0 174.1 31-44 18-40 309-452 70 110 58

Al 23.3 58.6 53-60

Na 20.6 31.9

Fe 43.1 78.6 307-332 82-163 44-58 57 100 71

Mg 16.3 27.5

K 38.4 47.5 6-75 23-57 160-215 120 96 67

Ti 0.8 1.4 9-10 6-10 29-39 8.0 13 8.7

Zn 6.5 9.6 5-10 14-17 51-88 14 17 11

Cu 1.-0.15 4.9 18-32 8-16 21-58 9.3 1.7 2.1

Ni 2.4 1.8 0 0 2-3 0.99 1.0 0.72

Mn 0.21 2.3 3-4 3 28-32 2.2 2.5 2.1

Sb 0.12 0.30

Cd 0.12 0.14 4-6 4-7

V 0.05 0.16 1 1 3-5 2.5 2.7 1.8

La 0.00 0.11

Cs 0.00 0.00

Th 0.00 0.00

Sc 0.00 0.01

Ag 0.07 0.08

Co 0.02 0.07

Cr 1.2 2.6 2 1 3-8 <1.1 1.3 1.1

Si 198-464 338-672 387-401

Cl 7-32 3-9

Se 1 1-2

Rb 1 1

Sr 5-28 1

As 1 1 1-2

Mo

Br 2.1 1.3 1.3

a

I: Indoor; Units: ng/m3

b

R: Residential; Units: ng/m3

c

Units: ng/m3