P.1 

OAR Box 1111 

Prepped by Ryan Dugan 

Document Number: 

-ne) II-A-9 

Docket Number: 

A-83-22 

Printed 4/15/2008 1:25:18 PM Sheet 118 of 118 
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A - i 3 - 2 2-

REVIEW OF THE NATIONAL AMBIENT AIR QUALITY STANDARDS FOR LEAD: 

EXPOSURE ANALYSIS METHODOLOGY AND VALIDATION 

DRAFT REPORT 

Air Quality Management Division 

Office of Air Quality Planniny and Standards 

U.S. Environmental Protection Ayency 

Research Trianyle Park, N.C. 27711 

August 1988 
P.3 

This document is an OAQPS staff draft that is being circulated 

for technical review and comment. I t has not been fully 

reviewed within EPA and does not represent Agency policy. 
P.4 

TABLE OF CONTENTS 

Page 

List of Figures ii i 

List of Tables ii i 

I. Introduction I-l 

II. Lead Exposure: Multimedia Considerations .. . II-l 

A. Airborne Lead 11-3 

B. Lead in Soil 11-6 

C. Lead in Dust 11-8 

D. Lead in the Diet 

E. Lead in Water 

F. Lead in Paint 

III. Estimating Lead Exposures and Blood Lead Levels 

A. Alternative Modeling Approaches 

B. Calculating Blood Lead Distributions Around Predicted 

Means 

1-11 

1-12 

1-13 

II-l 

II-l 

II-2 

IV. Integrated Lead Uptake/Biokinetic Model IV-1 

A. Estimates of Lead Uptake IV-3 

B. Uptake and Blood Lead Concentrations IV-5 

V. Statistical Relationships Between Blood Lead and Airborne 

Lead: Use in Disaggregate and Aggregate Models V-l 

A. Disaggregate Model V-3 

B. Aggregate Model V-13 

VI. Validation of Integrated Lead Uptake/Biokinetic Exposure 

Model VI-1 

A. Validation Using East Helena Data VI-2 

B. Application of Uptake/Biokinetic Model to Other Data 

C Sets VI-11 . Conclusions VI-16 
P.5 

11 

TABLE OF CONTENTS (Continued) 

Page 

VII. Application of Lead Exposure Modeling VII-1 

Appendix A. Estimates of Lead Uptake A-l 

Appendix B. Estimation of the Relationship Between Soil, Dust, 

and Ambient Lead B-l 

Appendix C. Estimating 1990 Baseline Blood Lead Averages C-1 

References 
Number 

iii 

LIST OF FIGURES 

Title 

1 ' 1 

Page 

P.6 

2-1 Principal Pathways of Human Exposure to Lead 11-2 

2-2 Trends in Maximum Quarterly Lead Concentrations for 11-5 

Various Monitor Types 

4-1 Summary of Relationships Between Daily Lead Uptake IV-14 

and Blood Lead for Different Age Groups 

5-2 Summary of Epidemiological Studies on Lead Exposed Children V-15 

5-3 Blood Lead/Air Lead Slopes in Children for Different Age V-17 

and Exposures 

6-1 Comparison of Distribution of Measured Blood Lead Levels VI-7 

in Children, 1-5 years of Age, Living Within 2.25 miles 

of E.Helena Smelter vs. Levels Predicted by Uptake/Biokinetic 

Model (Run B). 

6-2 Comparison of Distribution of Measured Blood Lead Levels VI-8 

in Children, 1-5 years of Age, Living Within 2.25 miles 

of E.Helena Smelter vs. Levels Predicted by Uptake/Biokinetic 

Model (Run C). 

LIST OF TABLES 

Number Title Page 

2-1 Typical Lead Concentrations in Various Exposure Media II-2 

2-2 Frequency Distributions of Maximum Quarterly Lead 

Concentrations by Type of Site . 11-5 

3-1 Comparison of Estimated GSDs Across Several Studies 111-5 

3-2 Illustrative Blood Lead Distributions Assuming Different 111-8 

Mean Blood Leads and Geometric Standard Deviations 

4-1 Estimated 1990 Average Lead Intake and Uptake in 2-Year IV-4 

Children Under Average Air Lead Levels 
P.7 

IV 

4-2 Predicted Equilibrated Blood Lead Levels Over Time Among ' IV-12 

Children with Constant Lead Uptakes 

5-1 Disaggregate Model of Contributions from Various Media V-8 

to 1990 Median Blood Lead Levels of U.S. Children 

(2 Years of Age): Background Levels and Incremental 

Contributions from Air 

6-1 Comparison of Integrated Lead Uptake/Biokinetic Model VI-6 

Predictions to 1983 Measurements in East Helena 

6-2 Children's Blood Lead Levels Measured in Omaha, 1971-1977 VI-13 

Vs. Integrated Uptake/Biokinetic Model Predictions 

6-3 Children's Blood Lead Levels Measured in Silver Valley, VI-15 

Montana 1974-1975 Vs. Integrated Uptake/Biokinetic Model 

Predictions 

A-l Age-Specific Estimate of Total Dietary Lead Intake for A-5 

1990-1996 

A-4 Long-Term Relationships Between Dust, Soil and Ambient Lead 

A-5 Estimating Short-Term Responses in Equilibrium Soil and 

Dust Lead Levels from Changes in Ambient Lead 

B-l Environmental Lead Concentrations in Omaha, Nebraska 

B-2 Linear Model Parameter Estimates for Air, Soil and Dust 

Lead Relationships 

C-1 Selected 1978 Blood Lead Levels from NHANES I I 

C-2 Predicted Changes in Average Blood Lead Levels Associated 

with Gasoline Lead Trend 

C-3 Trends in Dietary Lead Intake: Total Intake (and 

Atmospheric Contributions) 

C-4 Adjustments to 1978 Mean Blood Lead Levels for Dietary 

Lead Reductions 

C-5 Derivation of 1990 "Baseline" Average Blood Lead Levels 

C-6 Maternal:Child Blood Lead Concentrations and Ratios 

A-12 

A-12 

B-5 

B-8 

C-2 

C-6 

C-8 

C-12 

C-15 

C-17 
P.8 

REVIEW OF THE NATIONAL AMBIENT AIR QUALITY STANDARDS FUR LEAD: 

Exposure Analysis Methodology and Validation 

I . INTRODUCTION 

EPA i s assessing health risks associated with lead exposure, especially 

near stationary sources of atmospheric lead emissions (e.y. , lead smelters), 

under alternative regulatory scenarios for it s review of the National 

Ambient Air Quality Standards (NAAQS) for lead. The scientifi c and 

technical information on lead has been reviewed in EPA's "Air Quality 

Criteri a for Lead" (EPA, 1986). A "staff paper", in final preparation, 

wil l evaluate and interpret the most relevant of that information to help 

the Administrator in selecting the averayiny times, forms, and levels for 

the primary and secondary standards.* A critica l element in thi s process 

wil l be an exposure analysis whereby blood lead levels are estimated 

among populations exposed under alternative lead regulations in the 

future. (An exposure analysis of four lead sources, i.e. , four "case studies", 

i s currently being prepared using methodologies documented in thi s report.) 

This report summarizes relevant information on lead exposure and 

presents the modeling methodoloyies that the staff believes should be considered for the lead NAAQS exposure analysis. Results of validatiny one 

of these methodologies are also presented. 

Normally, such descriptions would be incorporated into the staff 

paper. Due to the complex nature of lead exposure analysis, we chose to 

separate thi s report to achieve a more thorouyh review and also to make 

i t easier for yeneral use in lead exposure analysis unrelated to the 

NAAQS review. This report should then be considered as a supplement to 

*The current primary standard for lead (to protect public health) i s 1.5 

micrograms per cubic meter (py/nr), maximum arithmetic mean averaged over 

a calendar quarter. The secondary standard (to protect public welfare) 

is identical to the primary standard. 
P.9 

1-2 

the OAQPS staff paper. I t i s intended for those readers familiar with 

the technical information contained in the criteri a document (hereafter 

referred to as "CO"). This report does not discuss health effects associated 

with lead or the implications of differen t levels of lead exposure. That 

information i s reviewed in the criteri a document and wil l be inteyrated 

in the staff paper with results of the exposure analysis. Both thi s 

paper and the staff paper wil l be circulated for review by the Clean Air 

Science Advisory Committee and the public. 

The approach used in thi s paper i s to assess and inteyrate exposurerelated information derived from the criteri a document review that the 

staff believes should be considered in the review of the primary lead 

NAAQS. Section I I presents relevant features of human exposure to 

atmospheric and non-atmospheric sources of lead throuyh various pathways. 

Section II I introduces different approaches to estimate the impact of 

alternative, ai r lead levels on lead body burdens amony different populations. 

Section IV and V discuss the methodoloyies of these different approaches 

in detail . Section VI presents results of validation exercises usiny the 

uptake/biokinetic model. Section VII presents some applications of the 

modeling approaches described in thi s report in addition to their role in 

the review of the lead NAAQS. 
P.10 

I I . LEAD EXPOSURE: MULTIMEDIA CONSIDERATIONS 

In order to assess the risks associated with alternative lead NAAQS, 

i t i s necessary to understand the influence exerted by atmospheric lead on 

the total lead exposure of the population(s) of concern through various 

exposure pathways. Relevant data on these pathways and the relationships 

between air lead and lead in other media are summarized in thi s section. 

The sources and pathways of human lead exposure are diagrammed in 

Figure 2-1 and typical levels of lead in differen t media to which U.S. 

populations are exposed are presented in Table 2-1 . Human exposure to lead 

can be traced primarily to lead in paint piyments, solder in canned foods and 

plumbing, as well as to atmospheric lead. Although airborne lead i s a 

principal starting point of environmental contamination, oral intake of 

deposited atmospheric lead i s often the primary identifiabl e factor predicting 

the blood lead of young children. High correlations have been found between 

children's blood lead and the lead content of household dust, playground 

dust, mouthing behavior, lead on children's hands and household cleanliness 

(Sayre et al. , 1974; Baker et al. , 1977; Charney et al. , 1980; Roels et 

al. , 1980, Yankel et al. , 1977; Angle et al. , 1979; Walter et al. , 1980; 

Brunekreef et al. , 1981; Quah et al. , 1982; Bellinger et al. , 1986; 

Bornschein et al. , 1986). Large scale isotopic studies provide strong 

evidence that air lead has a rapid and measurable effect on ingested lead, 

even in adult populations at low levels of air lead (Facchetti et al. , 

1985). I t i s necessary, therefore, to attempt to quantify how atmospheric 

anissions can influence human exposure not only throuyh direc t inhalation 

of lead-containing particles but through ingestion of lead which deposits 

onto soil , dusts, vegetation, and other environmental surfaces. 
P.11 

ri-2 

SURFACE ANO 

QROUNO WATER 

DRINKING 

WATER 

MAN 

FIGURE 2-1. PRINCIPAL PATHWAYS OF HUMAN EXPOSURE TO LEAD. HEAVY ARROWS ARE THOSE 

PATHWAYS DISCUSSED IN GREATEST DETAIL. FROM CD, FIGURE 7-1. 

TABLE 2-1. TYPICAL LEAD CONCENTRATIONS IN VARIOUS EXPOSURE MEDIA 

Medium 

Ambient A1r (pg/m3)b 

Indoor A1r (pg/m3) 

Soil (ppm) 

Street Oust (ppm)d 

House Oust (ppm)d 

Typical Foods (ppm) 

Water (yg/l) 

Painte 

Rural Area 

U.l 

0.03 - U.08 

5-3 0 

80 - 130 

(90) 

50 - 500 

(300) 

0.002 - 0.8 

5-7 5 M9/L 

<1 - >5 mg/cm2 

Urban Area 

0.1 - U.3 

0.03 - 0.2 

30 - 4500 

100 - 5,000 

(1500) 

50 - 3,000 

(1000) 

Same 

Same 

Same 

Near Point Source(s)a 

0.3 - 3.0 

0.2 - 2.4 

150 - 15,000 

(25,000) 

100 - 20,000 

(10,000) 

Same 

Same 

Same 

References 

Faoro, 1988 

See Footnote c 

CO, Table 7-11; Mlelke 

et al. ; 1983; See Table 

B-3 

Nriagu, 1978; CO, 

Table 7-26 

U.S. EPA, 1977; 

Landrigan et al. , 1975; 

Morse et al. , 1979; 

Angle and Mclntlre (1979) 

Flegel et al . 

(1988) 

BMskln, 1988 

Billick and Gray, 1978 

aW1thin 2-5 km of sources including primary and secondary lead smelters, battery plants. 

Represents quarterly averages monitored in 1986. 

cRange of indoor/outdoor ratios used (0.3 - 0.8) from CO, Table 7-6 except near point sources where large particles predominate and infiltration into homes is low, ratio appears to be closer to 0.3 (Cohen and Conen, 1980). 

aValues in parentheses represent estimates provided in CD (Tables 7-18 and 7-20) as typical averages. 

eS1nce there may be several layers of lead-based paint on a given surface, absolute concentration of lead is less 

useful than mg/cm2. Surveys by HUD in Pittsburgh showed that more than 70X of pre-1940 dwe^lr;; units and 20X of post1960 units had at least one surface with more than 1.5 mg/cm2

 lead paint (NAS, 1980). 
P.12 

II-3 

Unti l recently, between 85-90% of airborne lead in the U.S. originated 

from gasoline combustion, with most of the remainder from stationary industrial 

processes such as primary and secondary lead smelting, battery plants, and 

combustion of oil , coal, waste oi l and municipal waste. Because of the 

accelerated reduction of the lead content in gasoline, concern regarding 

lead emissions into the ambient air i s shiftin g almost exclusively to 

relativel y confined areas surroundiny significant stationary sources of 

lead and thi s paper's focus wil l be on estimating exposures and risks in 

those locales. 

A. Airborne Lead 

1 . Physical, Chemical and Spatial Characteristics 

Ambient air lead levels result from current industrial emissions, 

lead-contaminated road and wind-blown dust, and automotive exhaust. The 

industrial contribution includes point, fugitiv e process, and materials 

handling emissions from lead mininy, smelting, and recovery operations. 

Current contributions of road and other fugitiv e dust vary, with location 

and the influence of historicall y contaminated soil . 

In general, about 50% of automotive lead emissions deposits within a 

few hundred meters of major roadways (Daines et al. , 1970; Huntzicker et 

al. , 1975; Inyalls and Garbe, 1982) while the ranaininy particles are small 

enouyh to remain airborne and can travel hundreds or thousands of kilometers. 

This likel y accounts for the surface contamination of polar glaciers , 

oceans, and other remote locations around the globe (Settle and Patterson, 

1982). 

In contrast to automobile exhaust, atmospheric lead emissions from 

industrial plants that process lead and it s products have contributed littl e 

to the overall pollution load across large, regional areas although fallou t 
P.13 

II-4 

from these sources can be severe on a local scale. The trajectories "of 

atmospheric emissions from industrial sources vary with wind speed and 

direction . High concentrations around lead smelters and other major 

emitters result mainly from fugitiv e emissions, predominately made up of 

large (>7 micrometers (pm)) lead particles resulting from materials 

handliny, furnace upsets, and furnace charying and tapping operations 

(Landrigan et al. , 1975; Jennett et al. , 1977; Battye et al. , 1985). 

Beyond the immediate area ( * 2 km) of lead stationary sources, process 

emissions from stacks, predominately as lead sulfates and oxides with a 

size range between 1 and 10 pm, become the major source of lead in soils 

and air (Dorn et al. , 1976; Roels et al. , 1980; Davidson and Osborn, 1984). 

2. Ambient Concentrations 

As indicated in the CD (Section 7.2.1), lead levels in urban areas 

and near point sources have been markedly reduced since 1977 by the use 

of unleaded gasoline in new cars equipped with catalyti c converters, the 

lead-in-gasoline phasedown program, and steady reductions in anissions 

from stationary sources as a result of the 1978 lead NAAQS. Recent (1980-1983) 

air quality data for stationary source sites , micro-scale roadside sites , 

middle scale roadside sites , neighborhood scale roadside sites , and other 

non-classified sites are summarized in Table 2-2 (Battye, 1984). The 

monitoring sites located near stationary sources reported the majority of 

quarterly average concentrations over 1.5 pg/nP. 

Trends in maximum quarterly averages between 1980 and 1983 are 

illustrate d in Figure 2-2. These trends data are generally based on a 

limited number of available monitoring sites that remained in service since 

1980 (e.g. , 27 stationary source sites , 9 neighborhood scale sites). 
P.14 

II- 5 

TABLE 2-2 . FREQUENCY DISTRIBUTIONS OF MAXIMUM QUARTERLY LEAD CONCENTRATIONS 

- BY TYPE CF SITE* 

Site type/time frame 

1980 through 1983 

All monitors0 

Stationary source 

Microscale roadside3 

Middle scale 

Neighborhood scale 

1983 only 

All monitors0 

Stationary source 

Microscale roads1ded 

Middle scale 

Neighborhood scale 

Percent 

<0.5 

69 

62 

17 

39 

61 

71 

53 

16 

53 

72 

of site 

0.5-1.0 

22 

16 

40 

42 

32 

19 

24 

47 

33 

28 

years in concentration 

1.0-1.5 1.5-2.0 

5 

8 

27 

18 

5 

5 

9 

32 

13 

0 

2 

3 

13 

0 

0 

1 

2 

5 

0 

0 

ranges0 

>2.0 

2 

11 

3 

0 

2 

3 

11 

0 

0 

0 

Mean 

0.53 

0.95 

0.99 

0.68 

0.51 

0.51 

0.88 

0.83 

0.60 

0.40 

Total 

siteyears 

1189 

159 

30 

33 

62 

360 

45 

19 

15 

29 

Total 

number 

of sites 

414 

56 

18 

15 

29 

360 

45 

19 

15 

29 

dData are from the SAROAD system and represent the numbers of site-years for which the maximum quarterly concentrations 

fal l within the designated concentration ranges. To be included, a site-year must have four valid quarters of data. 

^Concentration ranges are in units of ug/m3. 

c

Includes sites previously classified into categories (e.g. , urban) that do not meet any of the current definitions. 

dM1croscale sites are within 5-15 meters from a major roadway and 2-7 meters above the ground. 

Source:Battye, 1984 

K!-

til 

LJ 

12 

LU 

2.0 

1 .9 

1 .8 

1 .7 

1 .6 

1 .5 

1 .4-

1 .3 

1 -2 H 

1 . ! 

1 .0 

0.9 

0.8 

0.7 

0.6 

0.5 

0.4 

0.3 

0.2 

O.1. 

0 . 0 

MICROSCALE 

"v 

* ^ \ STATIONARY SOURCES 

•M 

\ 

--K 

MoSEPSBtiSlS?0 SCALE 

ALL MONITORS 

^ss S 

"^a 

1980 1981 1982 1983 

Year 

FIGURE 2-2. TRENDS IN MAXIMUM QUARTERLY LEAD CONCENTRATION FOR VARIOUS 

MONITOR TYPES. SOURCE: BATTYE, 1984. 
P.15 

II-6 

Despite the new sitin g guidelines implemented in 1982 that added sites 

closer to traffi c emissions, microscale readings have been declining, 

corresponding to the phasedown of the lead content i n gasoline and reductions 

in leaded gasoline usage due to the yradual phase-out of older cars 

burning leaded gasoline. Similarly , annual and maximum quarterly averaye 

lead levels near point sources have also decreased since 1980, partly due 

to increased controls by lead-emitting sources in compliance with state 

implementation plans as well as to decreased industrial production at 

lead-enitting facilitie s (Silvasi , 1985). By September 1988, the information 

presented here wil l be updated to include data up through 1987. 

B. Lead in Soil 

The natural occurrence of lead in the earth's crust averages 

5-50 pg lead/g soi l in various soils * (CD, p. 7-28). Much of the lead in 

the atmosphere deposits on terrestria l surfaces where i t i s retained in 

organic complexes near the soi l surface (CD, p. 7-31). The abilit y of 

soi l to immobilize lead largely depends on soi l pH and organic content 

(i.e. , fulvi c and humic substances). Many U.S. soils appear to have a 

large capacity to bind lead with only a small fraction dissolved in soi l 

moisture where i t i s available for plant uptake. The environmental 

impact of lead on the biota of terrestria l and aquatic ecosystems is 

discussed in Chapter 6 of the CD. 

The upper layer of roadside soil s may contain deposited atmospheric 

lead in concentrations of 30 to 2000 ppm in excess of natural levels within 

25 meters of the roadbed, beyond which concentrations decline abruptly in 

''One pg/g i s equivalent to one part per millio n or 1 ppm. 
P.16 

II- 7 

relation to traffi c density and vehicle speed (Paye and Ganje, 1970; Quarles 

et al , 1974; Wheeler and Rolfe, 1979; Pierson and Brachaczek, ly76). 

Topsoil lead concentrations around various lead point sources generally 

decrease exponentially within a 3-10 km radius from 100-60,000 ppm down to 

background levels (Yankel et al. , 1977; Schmitt et al. , 1979; Roels et al. , 

1978; Diemel et al. , 1981; Fugas, 1977). However, elevated soi l lead 

levels have even been found at distances exceeding 20-25 km from some 

smelters (Wixson, 1978). Limited data indicate that lead in soi l near 

primary and secondary lead smelters occurs as lead oxides, sulfide , sulfate , 

and elemental lead (Olson and Skogerboe, 1975; Corrin and Natusch, 1977). 

Urban soil s are contaminated by lead from a combination of automotive 

and point source deposition as well as from lead in paint on indoor and 

outdoor surfaces. Elevated soi l lead concentrations (as high as 2000 ppm) 

have been found within 10 feet of wood frame houses painted with lead-based 

paint (Ter Haar and Aronow, 1974). Accumulations of lead in soils (and 

dusts) around brick or stone structures have also been found, and can be 

partiall y attributed to washoff lead collected on roofs, ledges, and exterior 

walls (Wheeler and Rolfe, 1979), and possibly to an aerodynamic effect of 

the structures on deposition of lead from nearby sources. Vegetable garden 

soi l samples collected in a 30-mile radius of downtown Baltimore had lead 

levels up to 10,900 ppm with a median value of 100 ppm (Mielke et al. , 

1983). Much of thi s lead was attributed to automotive exhaust and industrial 

emissions because of the near absence of lead painted houses and the clustered 

pattern of lead levels around downtown. Soil lead concentrations in a sample 

of cit y parks have also been reported to be high, ranging from 200 to 

3300 ppm (Chow et al. , 1975; Zimdahl and Hassett, 1977). 
P.17 

II-8 

Improvements in air quality do not necessarily involve reductions in 

soi l lead at the same rate. The decontamination of the environment i s a 

very complex and slow process, particularl y for soi l lead which has been 

shown to remain at elevated levels several years after lead manufacturing 

plants have ceased operating (Prpic-Majic et al. , 1984). While lead in 

soi l i s relativel y immobile, i t stil l may enter the food chain, be ingested 

directly , or may be redispersed into the air and resuspended into water by 

wind scattering of soi l particles and dust. Consequently, populations 

livin g in areas with historical accumulations of lead in soi l may continue 

to be exposed to lead for indefinit e periods despite effective controls of 

atmospheric emissions. 

C. Lead in Dust 

Oust i s a normal component of the home (i.e. , "house dust") as well as 

the outdoor environment where i t can be found on sidewalks, playgrounds, 

driveways, and other h-ard surfaces. Anthropogenic materials deposited on 

these outdoor surfaces wil l be referred to as "street dusts". In addition, 

the very top layer of soils (including leaf litter ) to which people, particularl y 

children, come in direct contact, are considered in the criteri a document 

to be "soi l dusts". 

Both house dust and street/soi l dust contain lead from atmospheric 

deposition, "natural" soil , and paint chips. As with roadside soil , significant 

correlations between lead concentrations in street dust and the proximity 

and density of traffi c have been found (Rolfe et al. , 1977; Lau and Wong, 

1982). Concentrations of lead in dusts on playgrounds, streets , and soi l 

surfaces also increase with higher air lead concentrations and with proximity 

to stationary lead sources (Roels et al. , 1980; Brunekreef et al. , 1981; 

Yankel et al. , 1977). As summarized by Nriagu (1978), street dusts from 
P.18 

II-9 

differen t U.S. citie s contained between 300 and 18,000 ppm lead. A survey 

of street dusts in 77 midwestern citie s showed an average lead content of 

1,636 ppm in residential neighborhoods and 2,413 ppm in commercial and 

industrial areas (NAS, 1980). Limited chemical analyses of roadside soils 

and dusts from U.S. citie s found lead predominately as sulfate, along with 

minor amounts of oxide and halide salts (Olson and Skogerboe, 1975; Corrin 

and Natusch, 1977). Pavement dust, street dust, gutter debris, and household 

dust samples contain mostly large lead particles ranging between 40 and 

1000 pm (Pierson and Brachaczek, 1976; Sturges and Harrison, 1985; Duggan 

and Inskip, 1985). Higher lead concentrations are usually found in the 

smaller sized fractions ; the concentration in a sample of street dust 

sieved at 100 pm, for example, i s usually at least two to four times greater 

than that in the same sample sieved at 1,000 pm (Duggan and Inskip, 1985). 

Preliminary work indicates coarse particles laryer than a few hundred 

micrometers in diameter are.easily brushed off hands and clothing whereas 

only the smaller ones (<100-200 pm) readily adhere to fingers and are thus 

more likel y to be ingested (Duggan and Inskip 1985). 

Airborne lead deposited on streets , sidewalks and driveways i s highly 

mobile and subject to further distributio n by wind and water. Windblown 

particles associated with dust are apt to be redeposited within the urban 

environment because of the complex wind currents caused by buildings and 

street canyons. There i s some evidence on the persistence of lead in 

street dust. A survey of rainwashed areas in the U.K. and New Zealand 

concluded that the normal acidity of rain (pH between 4 and 5) was 

insufficien t to completely dissolve and transport lead particles , and that 

residue near streets poses a health hazard to children who are prone to 

ingest street dusts (Day et al. , 1979). However, Laxen and Harrison 
P.19 

11-10 

(1977) found that only a ligh t rainfal l (2 to 3 mm) i s sufficient to .remove 

90% of the lead from the road surface, mainly to surrounding soi l and to 

waterways. Furthermore, based on deposition fluxes around a major roadway 

over a year and concentrations of lead in the road drainage water, Harrison 

et al . (1985) estimated that removal of lead in runoff waters exceeds that 

deposited on the roadside verges. The rate of removal of lead from street 

dusts i s also dependent on the frequency and efficiency of street cleaning 

operations and i t appears reasonable to assume that with continuous input, 

lead concentrations in street, curb, and sidewalk dust wil l rise between 

precipitation and street cleaning episodes, and drop thereafter. 

Lead levels in house dust can also be expected to vary considerably 

depending on house cleaning practices, as demonstrated by Charney et al. , 

(1983), as well as on the presence and condition of lead-based painted 

surfaces, the presence of ciyarette smoke, the amount of dust and soi l 

blown into or carried into the house on clothiny and. shoes (especially on 

those occupationally exposed to lead), indoor sources of lead other than 

paint (e.g. , solderiny), the permeability of the home to outdoor air (which can 

vary with season), and outdoor concentrations of air lead. Surveys of 

a diverse set of homes indicate a wide ranye of house dust lead levels 

between 18 and 16,000 ppm (EPA, 1977; Harrison, 1979; Angle and Mclntire, 1979) 

and as high as 100,000 ppm within 2 km of smelter (Landrigan et al. , 1975). 

For present purposes, the important point to note i s that unlike lead 

that is incorporated into soil , lead in surface dusts, both indoors and 

outdoors, i s mobile and can be expected to respond over time to a much 

greater degree to changes in atmospheric lead anissions. This has been 

observed around point sources where, following the installatio n or 

supplementation of emission controls and significant improvements in air 
P.20 

11-11 

lead q'uality, siynificant drops in concentrations of lead in playyround 

dust, surface dust on soil , and in house dust have been observed within 1 

to 2 years (Morse et al. , 1979; Prpic-Majic et al. , 1984). This also suyyests 

that lead in surface dusts in non-point source areas should decline as a 

result of the lead phasedown in gasoline. 

To assess the impact of atmospheric lead on children's total exposure, 

i t is necessary to estimate the contributions of different air lead levels 

to outdoor and indoor soil/dust lead levels as well as the amount of dir t a 

child may ingest, both inadvertantly, and deliberately . These issues are 

addressed in the modeliny approaches presented in Sections IV and V. 

D. Lead in the Diet 

The inyestion of food i s a major component of most individuals ' 

total lead uptake, although the relative contribution i s a function of their 

aye, and the size and type of diet . The occurrence of lead in the diet may be 

a result of a) natural sources of lead; b) deposition of airborne lead particles 

onto crops, forage, feed, soils , and water; and c) the harvesting, processing, 

transportation, packaging, preparation, and storage of food during which lead 

can be introduced at every stage, either by atmospheric deposition or through 

metallic contamination, particularl y from solder in cans or in plumbing. 

Recent studies on lead content of various foods, both before and after 

processing, packaging, and preparation, and on food consumption patterns 

in the U.S., provide information on dietary lead intakes for different 

populations (Beloian and McDowell, 1981; Wolnik et al. , 1983; National Food 

Processors Associations, 1982; Pennington, 1983; U.S. FDA, 1983, 1984). 

Usiny these data for 1982-83, a "Multiple Source Food Model" was developed 

in the CD that apportions lead in "typical" child and adult diets to the 

followiny sources: natural soi l lead, direct atmospheric lead added to 
P.21 

11-12 

food crops before harvest and during processing, indirec t atmospheric" lead 

that has been incorporated in soils , lead in solder from food cans and 

drinking water, and lead whose origin cannot be determined at present 

(CD, Section 7.3.1.2). The model was validated using the same parameters 

along with more recent food data from 1984 and 1985 to successfully predict 

continuing declines in dietary lead intake. For example, dietary lead intake 

for a 2-year old child has dropped from about 45-50 pg/day in 1978 to an 

estimated 13.1 pg/day in 1985; comparable declines (from 45-50 pg/day to 

15-20 pg/day) have been seen in different adult populations since 1982 

(Flegel et al. , 1988.) These trends are attributable to the drastic reduction 

in gasoline lead emissions and the voluntary phaseout of lead-soldered cans 

by U.S. manufacturers since the late 1970's. This downward shif t is expected 

to continue up unti l the early 1990's as lead from both these sources drops 

further. The methods by which estimates of dietary lead intake from the 

Multiple Source Food Model are derived and applied to modeling total lead 

exposure are discussed in Appendix A and Section V. 

E. Lead in Water 

Lead i s a natural, usually minor, constituent of surface and ground 

waters. Atmospheric lead can enter aquatic systems through direc t 

fallou t or in surface runoff as suspended particles or adsorbed to soi l 

particles . Undermost conditions (pH, temperature, alkalinity) , lead forms 

insoluble salts and precipitates to sediments, which probably accounts for 

the low lead content of U.S. source water supplies; the average concentration 

ranging between 3 and 4 micrograms Pb per lite r water (pg/L) (NAS, 1980). 

In contrast, lead levels in household, school, or offic e building 

drinking water can be much hiyher due to plumbing corrosion and subsequent 

leaching of lead, ranging between 10 and 30 pg/1 on average. The combination 
P.22 

11-13 

of corrosive (i.e. , soft or acidic) water and lead pipes or lead soldered 

joint s in distributio n systems or houses creates localized zones of high 

lead concentrations up to 380 pg/1 (Worth et al. , 1981). In general, 

levels are highest in samples of hot and/or stagnant "firs t draw" water. 

Drinking water i s a major source of lead exposure among many infants 

while they are dependent on baby formulas during their firs t year, as well 

as young children. EPA's Office of Drinking Water wil l soon propose 

revising the existing lead standard of 50 pg/L to 5 pg/L, measured at the 

treatment plant, with a "no-action level" average of 10 pg/L, measured 

at the home tap. 

Estimated contributions that natural, atmospheric and solder lead make 

to total lead exposure via drinking water and total diet are addressed in 

the modeling approaches presented in Sections IV and V. 

F. Lead in Paint 

Ingestion of lead-containing paint i s considered to be the most 

frequent cause of severe lead intoxication among children (Chisolm, 1984; 

CDC, 1985). Significant correlations have been found between the quantity 

and condition of lead painted surfaces in homes and blood and fecal lead levels 

in inner cit y children (Urban, 1976; CD, pp. 11-156 to 11-160). Significant 

differences in blood lead levels have been found in relation to housing 

condition among children as young as nine months, with highest levels in 

children livin g in deteriorating pre-World War I I housing, intermediate 

levels in well-maintained and rehabilitated older housing, and lowest levels 

in children in public housing and newer units free of lead paint (Clark et 

al. , 1984). Other investigations indicate that in addition to peeling 

lead-based paints, "intact" lead-based paint contributes to elevated 

blood lead levels in children via chalkiny or weathering (Gilbert et al. , 
P.23 

11-14 

1979; Galke et al. , 1975). Further risks are associated with conventional 

paint removal techniques (i.e. , sanding, burning heat guns) which can 

generate concentrations of fine lead dust up to 100 pg/m3 (NIBS, 1988). 

Under the 1971 Lead-Based Paint Poisoning Prevention Act, which has 

since been amended, the Department of Housing and Urban Development has 

regulatory and research responsibilities for eliminating the hazards of 

lead-based paint poisoning in federally funded housing. In 1977, the 

Consumer Product Safety Commission banned as hazardous, household paint 

(including toy and furniture paint) containing more than 0.06% lead. This 

was an important step but i t does not affect hazards posed by lead-based 

paints already present on old housing surfaces. Prior to 1940, some interio r 

paints contained more than 50% (500,OOU ppm) lead. Use of lead piyment 

paints declined slowly between 1940 and the late. 196U's after which i t 

declined at a rapid rate (NAS, 1972). Pope (1986a) estimates that in 1980, 

the interio r and/or exterior surfaces of between 21.5 and 47.3 millio n 

households in the U.S., mostly buil t before 1960, contained greater than 

0.7 mg/cm^ lead in painted surfaces, a level considered hazardous to young 

children by the Centers for Disease Control (CDC). Between 6.2 and 13.6 

millio n children under the age of 7 are estimated to have resided in lead-based 

painted housing in 1980 (Pope, 1986a). Even i f coated with low level-leaded 

paint, the underlying layers of lead-based paint in older homes represent a 

large reservoir of lead exposure in children, particularl y i f there i s 

peeling paint, broken or cracked plaster, or holes in the walls . The 

number of lead-based painted homes with these deteriorating conditions 

(i.e. , "unsound") in 1980 i s estimated to have been between 800,000 to 2.9 

millio n with approximately 235,000 to 842,000 children under age 7 livin g 

in such homes (Pope, 1986a). 
P.24 

11-15 

Lead-based paint continues to be the major source of high-dose lead 

exposure and symptomatic lead poisoning for children in the U.S. (Chisolm, 

1971; CDC, 1985), and i t appears that exposure to lead-based paint wil l 

continue to be a problem for decades to come (Schneider and Lavenhar, 1986). 

Between 1973 and 1980, only 10% of pre-1940 housing units and 5% of 

housing units buil t in the 1940 's had been removed from our nation's housing 

stock by demolition, disaster, or by other means such as conversion to 

commercial space (Bureau of the Census, 1983). Less than half of these 

units removed from service were located in central cit y areas where lead 

poisoning i s most prevalent. In addition, poor urban families often have 

no choice but to liv e in poorly maintained older housiny because the vast 

majority of new housing units created from 1973 to 1980 i s located outside 

of central cit y areas, and acute shortages of modern and lead-free, low 

income rental units exist in many citie s (Farfel, 1985). 

High exposures to lead in children livin g in older housing with flaking 

or intac t paint wil l not be significantl y influenced by any changes in 

atmospheric lead emissions. Children with pica for paint chips or others 

livin g in deteriorating lead-based painted homes who are excessively exposed 

to paint lead-contaminated dust through normal hand to mouth activit y 

cannot be expected to be protected by any lead NAAQS no matter how stringent. 

For thi s reason and because exposure to paint lead i s so highly variable, 

no attempt wil l be made here to quantitatively estimate exposures of children 

who are excessively exposed to lead-based paint under various air lead 

levels , as i s done for other exposure media. I t i s clear that any exposures 

and blood lead levels predicted for children under various air lead levels 

using the approaches in Section II I wil l be siynificantl y higher for children 
P.25 

11-16 

with high paint lead exposure. Comprehensive plans for safe and effective 

removal of lead-based paints from old housing need to be developed and implemented, otherwise pediatric plumbism wil l persist until much of the present 

housing stock is completely rehabilitated or demolished (Chisolm, 1986). 

Preventing excessive exposure to existing sources of lead in and around 

housing must be addressed by an appropriate combination of legislation, 

housing code inspection and enforcement, financial incentives, parental 

education, and other programs. 
P.26 

'III . ESTIMATING LEAD EXPOSURES AND BLOOD LEAD LEVELS 

A. Alternative Modeling Approaches 

To assess the health risks associated with alternative air lead 

standards, i t i s necessary to estimate the blood lead (PbB) levels that 

would be distributed in the population(s) of concern under various air lead 

concentrations. [The amount of lead measured in whole blood i s an index of 

the rapidly diffusibl e fraction of the total body burden of absorbed lead 

and i s generally used as the dosage, or index of exposure, in investiyatiny 

the various human health effects associated with lead.] Lead exposure occurs 

throuyh multiple media but unfortunately, lonyitudinal assessments of 

simultaneous multi-media exposures have not yet been made. Potentially 

useful longitudinal analyses are now being carried out as part of the 

Cincinnati Lead Program Project (Clark et al. , 1987). Three approaches . 

are examined here that can be used to estimate or predict the impact of inhaled 

and ingested lead aerosols and compounds on the body burden of lead as indexed 

by blood lead. These approaches are presented in.detai l in Sections IV and 

V for consideration for using one, two, or al l three in assessing the 

protection provided by alternative lead NAAQS. 

The firs t approach, discussed in Section IV, i s to use measured rates 

of absorption, or "uptake" of lead through different pathways (e.g. , inhalation, 

ingestion) from experimental studies together with available mathematical 

("biokinetic") models from lead balance studies to project either total 

body burden or the amount of lead in any of the presumed "physiological" 

kinetic compartments (e.g. , blood, soft tissue, bone) at any time. 

The second approach, referred to as an "aggregate" model, i s to 

directl y apply a mathematical relationship between air lead and blood lead 

derived from community epidemiological studies that reflect s both direc t 
III-2 

inhalation exposure and indirec t exposures via secondary deposition processes. The thir d approach, referred to as a "disaggregate" model, i s a 

hybrid of the firs t two in which separate empirical relationships between 

blood lead and lead intake from lead in air , food, water, dust, soil , 

available from experimental exposure and epidemiological studies of differen t 

populations, are applied to lead concentration estimates in differen t 

media. The nature of the relationships detected between lead concentrations 

in blood and various environmental media, and the merits and limitations in 

using empirical relationships to represent lead exposure through multiple 

pathways in these latte r two approaches, wil l be discussed in Section V. 

B. Calculating Blood Lead Distributions Around Predicted Means 

Because most of the data input to these models are generally average 

estimates, al l three models estimate PbB levels in terms of population mean 

levels . The distributio n of PbB levels in U.S. children i s broad because 

there i s a distributio n of exposures those children face, a distributio n of 

behavior patterns that affect the uptake of that exposure, and a distributio n 

of biological absorption and excretion rates. For purposes of setting a 

lead NAAQS, i t i s necessary to determine the entire blood lead distributio n 

corresponding to a given mean PbB for differen t populations so that , for 

example, percentages of individuals exceeding PbB levels of concern can be 

ascertained. Determining such distributions i s an attempt to account for 

the significant behavioral and biological variabilit y within populations. 

I t i s the group of individuals with the potentiall y greatest adverse response 

to any given lead exposure that are of greatest concern in establishing a 

primary lead NAAQS. 

As noted for other metals in tissues of human populations, the 

distributio n of PbB levels for any relativel y homogeneous population closely 
P.28 

III- 3 

follows.a lognormal distribution (CD, Section 11.3.4). A lognormal distributio n 

is completely specified by it s geometric mean and geometric standard deviation. 

I t is possible, therefore, to calculate percentiles of a blood lead distribution 

(e.g. , median or 99 percentile) around a mean PbB level by using the geometric 

standard deviation (GSD) of that population's blood lead distribution . Several 

epidemiological studies have indicated that the log values of measured 

individual PbB levels in a uniformly exposed population are normally dis -

tributed with a variation, including analytical variation, ranging between 

1.3 and 1.4, when expressed as a GSD (Tepper and Levin, 1975; Azar et al. , 

1975; Billic k et al. , 1979). The NHANES I I study provides the best available 

data on nationwide blood lead levels in terms of qualit y control and sample 

size. In regression analyses of these data, Schwartz (1985a) estimated a 

GSD of 1.428 for young children after removing the variance in PbB levels 

attributable to air lead exposure by adjusting every individual' s PbB level 

to what i t would be at zero air lead, while allowing for variations in 

background non-air lead exposure. 

After excluding from the analysis children with PbB levels above 

40 pg/dl, who would not be expected to be substantially affected by changes 

in the lead NAAQS (for example, because of higher than average pica activit y 

or those exposed to excessively high concentrations of lead in paint), 

Schwartz (1985b) reapplied the same technique and calculated a GSD of 

1.419. Thus, a GSD without attribution of any source of lead exposure 

except gasoline lead and industrial air lead emissions may be taken as a 

rounded-off value of approximately 1.42 for the NHANES I I population of 

children (CD, p. 11-31). 

Given that the focus of thi s exposure analysis is on populations livin g 

near lead point sources where blood lead variabilit y may be different compared 
P.29 

III-4 

to the total mix of U.S. children, a separate assessment of blood lead 

GSD's for such populations i s presented here. Published statistic s of PbB 

samples near various lead point sources have been assembled and analyzed 

in Cohen (1986) and Marcus (1988a). The GSDs calculated from these pointsource/blood lead surveys are liste d in Table 3-1 , along with the NHANES I I 

GSD for children. To different degrees, the primary origin of non-biological 

variation in lead exposure for these point source populations was the smelter, 

especially in the Roels and Yankel studies conducted when smelter emissions 

were considerably higher. I t i s possible that children with exposure 

to a single, intense source of lead may have relativel y low variabilit y 

(essentially only due to intrinsi c biologic variability ) with a high 

mean blood lead. The most recent study indicates a larger variance at 

relativel y lower exposure levels near the Montana smelter surveyed in 1983, 

suggesting that multiple origins with separate variabilit y may be present 

rather than a single predominant source of variabilit y in lead exposure 

(Marcus, 1988a). 

The selection of a GSD value to model populations livin g near various 

lead point sources in the future depends on assumptions regarding variance in 

exposure in the future. Perhaps the most relevant data are from the 1983 

CDC E. Helena, Montana study since they reflec t the most contemporary 

conditions. I t can be expected that even for thi s population, however, total 

lead exposure wil l have dropped substantially by 1990. This i s attributable 

to recent and continuing downward trends in lead levels in canned foods, the 

nationwide ban on lead solder in new construction and plumbing repairs, the 

lead-in-gasoline phasedown, and perhaps increasing public awareness regarding 

the dangers of lead exposure and effective avoidance measures. Al l of these 

changes should result in not only lower mean baseline PbB levels , but perhaps 
P.30 

| : i 1 , 

II1-5 

TABLE 3-1 . COMPARISON OF ESTIMATED GSDs ACROSS SEVERAL STUDIES 

Mean PbB Estimated 

Population/Reference (pg/dl) GSDl 

NHANES I I - total mix of 16.0 1.42 

children 1-5 years old 

(Schwartz, 1986b) 

11-year olds livin g near Belgian 21.7 1.29 

primary lead smelter (Roels 

et al. , 1980) 

1-9 year olds livin y near Idaho 56.5 1.32 

primary lead smelter (Yankel et al. , 

1977) 

1-5 year olds, closest to 3 non-ferrous 15.6 1.39 

smelters i n U.S. (Hartwell et al. , (median) 

1983) 

1-5 year olds, livin g near Montana 9.4 1.53 

primary lead smelter (CDC, 1983) 

1-5 year olds livin y in 3 Missouri 16.2 1.57 

smelter towns (Baker et al. , 1977) 

!GSD calculations described in Cohen (1986) and in Marcus (1988a). 
P.31 

III-6 

more importantly, in fewer high level exposure situations and therefore less 

variance in PbB levels . Quantifying such an effect to estimate a future GSD 

value i s difficult . I t i s likely , however, that future reductions in baseline 

"non-point source" lead exposures wil l result in a reduction in exposure 

variance so that the blood lead GSD wil l be more reflectiv e of intrinsi c 

biologic variance, such as that found in the Roels and Yankel studies. Although 

these latte r studies were conducted during times of much higher exposures, 

the exposures were dominated by high smelter emissions and soil/dus t contamination, resulting in relativel y low PbB variability . For purposes of 

modeling future exposures among children livin g near differen t lead point 

sources, a range of GSD values can be considered: a lower bound of approximately 

1.30 derived from the Yankel et al . and Roels et al . studies and an upper 

bound GSD value of 1.53 derived from the 1983 CDC study of E. Helena, 

Montana children. The midpoint of thi s range i s 1.42, which coincidentally 

i s identical to the NHANES I I GSD estimate. Until additional data are 

available, a range of 1.30-1.53 wil l therefore be assumed for children livin g 

near lead point sources as a reasonable range of GSD values, and the midpoint 

of 1.42 wil l be assumed as a reasonable best estimate. 

Since blood lead estimates wil l also be made for pregnant women and 

middle-aged men, GSD values for adult blood lead distributions are needed. 

There i s littl e information on adult blood lead GSDs from point source 

studies. The most complete data base i s clearly from NHANES II , which has 

been analyzed in the CD to yiel d a range of GSD values, depending on race 

and place of residence, between 1.34 to 1.39 for adult women and 1.37 to 1.40 

for adult men (CD, Table 11-9). Given the uncertainties in extrapolating 

these ranges to adult populations livin g near point sources under future 

exposure scenarios, a midpoint value of 1.37 wil l be chosen as a reasonable 
P.32 

III-7 

estimate for both adult men and women. 

Analytical variation which exists in any measurement has an impact 

on the bias and precision of statistical estimates such as the GSDs derived 

from the studies discussed here. For this reason, it is important to 

recognize the magnitude of analytical variation in blood lead measurements 

due to measurement variation (i.e., between measurements run at the same 

time) and variation created by analyzing blood samples at different times 

(CD, p. 11-29). For example, correcting the GSDs for homogeneous subpopulations 

of children (1.34 - 1.39) for the overall estimate of analytical variation 

for the NHANES II study yields estimated GSDs in the range of 1.29 to 1.34. 

Using GSDs corrected in such a way, although providing a more accurate 

characterization of a given blood lead distribution, may not be appropriate 

for this assessment because the health effects studies that will be used to 

define dose-response relationships did not correct their PbB measurements 

for analytical variance. These studies, like NHANES II and the other point 

source epidemiological surveys, generally employed the best available 

measurement techniques and quality control. Using "corrected" GSDs on one 

hand to predict the distribution of children's PbB levels around a mean 

population PbB, and then matching those predicted PbB levels with "uncorrected" 

PbB levels derived from health studies in order to assess the risks associated 

with that population mean PbB, would result in a somewhat biased assessment. 

Therefore, the range of GSDs presented above that are not corrected for 

analytical variance will be used in further calculations. 

Table 3-2 presents blood lead distributions associated with example 

population mean PbB levels calculated using the GSD values derived above. 
P.33 

II1-8 

These distributions were calculated using the formula given to describe 

a lognormal distribution (Yankel et al., 1977): Mg • GSDn = Dn 

where: 

My = geometric mean PbB 

GSD = geometric standard deviation 

n = the number of standard deviations 

Dn = value of PbB at n standard deviations 

TABLE 3-2. ILLUSTRATIVE BLOOD LEAD DISTRIBUTIONS ASSUMING 

DIFFERENT MEAN BLOOD LEADS AND GEOMETRIC STANDARD DEVIATIONS 

GSD 

1.37 

1.42 

Geometric 

Mean 

PbB 

4 

5 

6 

7 

4 

5 

6 

7 

90th 

6.0 

7.5 

9.0 

10.5 

6.3 

7.8 

9.4 

11.0 

Percentil 

95th 

6.7 

8.4 

10.1 

11.7 

7.1 

8.9 

1U.7 

12.5 

e 

99th 

8.3 

10.4 

12.5 

14.6 

9.0 

11.3 

13.6 

15.8 

99.5th 

9.0 

11.3 

13.5 

15.8 

9.9 

12.3 

14.8 

17.3 
P.34 

,IV. INTEGRATED LEAD UPTAKE/BIOKINETIC MODEL 

The "uptake/biokinetic" modeling approach attempts to account for the 

following: a) the amount of lead in the body at any one time is the product 

of dynamic interactions of partiall y offsetting processes of absorption, 

distribution , storage, mobilization, and excretion; b) these processes vary 

with the route and rate of exposure, a person's age, nutritional and health 

status, and baseline exposure; c) uptake from al l sources by al l absorption 

routes can be separately modeled, thus providing an estimate of the relativ e 

importance of atmospheric lead exposure, either directl y or indirectly , to 

total body burden; and d) past and future trends in environmental lead 

levels due to different control effort s and regulations. 

There have been several studies measuring the intake, uptake, and 

metabolism of lead in adult male volunteers, from which balance schemes have 

been constructed (Kehoe, 1961; Chamberlain et al. , 1978, Rabinowitz et al. , 

1976, 1977). By making estimates about lead intakes and various metabolic 

factors , balance schemes can be constructed for different groups with 

different exposures to lead to assess the importance of specific exposure 

factors under variable conditions (e.g. , alternative lead NAAQS, phaseout 

of lead in soldered cans and in gasoline). Pre-school age children (<_ 6 

years old), pregnant women (as exposure surrogates for the fetus), and 

adult men (40-59 years of age) are specified in the CD as particularl y 

sensitive to lead. Of these groups, children between 2 and 3 years old 

experience, in general, the highest blood lead levels (Mahaffey et al. , 

1982; Billic k et al. , 1979), most likel y due to their greater hand-to-mouth 

activit y as well as to various metabolic processes (Harley and Kneip, 

1985). To predict exposure impacts of alternative air lead standards, 

model balance schemes have been devised for children aged 0-6 years and 

are discussed below. 
P.35 

IV-2 

A lack of adequate biokinetic data for pregnant females prevents such 

modeling for the fetus. In addition, accurate biokineti c modeling of the 

sensitive population of adult males would require at least 40 years of 

cumulative exposure inputs. Such uptake modeling would be difficul t given 

the great variabilit y in exposure histories among U.S. adults and the paucity 

of data. Exposure modeling for purposes of risk estimation for pregnant 

females and adult males, discussed in Section V.A., wil l rely on applying air: 

blood lead "disaggregated" relationships to estimated baseline "non-air" 

blood lead levels . 

A discussion of lead's absorption, excretion, retention, and distributio n 

within the body under different exposure and physiological conditions is 

necessary background to the uptake/biokinetic model, and i s provided in 

Chapter 10 of the CD. As wil l be further discussed, application of thi s 

or any lead exposure model must recognize the limitations of the available 

data and the significant variability , among populations in their behavioral, 

exposure, and physiological characteristics . For present purposes, the 

children to be considered in the model do not include the whole U.S. population; 

they comprise groups with differen t exposures to lead, some of them extreme, 

in order to illustrat e the variations in lead exposure and absorption 

around lead point sources under differen t scenarios. Section IV.A presents 

methodologies to estimate average dail y lead uptake from al l exposure 

sources under alternative air lead levels . Section IV.B presents methodologies 

to relate these estimates of lead uptake to average, steady-state blood 

lead levels . Although thi s approach predicts hypothetical outcomes and 

the absolute numbers should not be used uncritically , the model does striv e 

to use the available data, with al l it s limitations , to the fulles t extent 

possible to provide a useful tool in eventually distinguishing the health 

impacts of alternative lead NAAQS. 
P.36 

IV-3 

A. Estimates of Lead Uptake 

The method employed to estimate the deyree to which each environmental 

source of lead contributes to a child' s total dail y lead uptake is based 

on the distributio n of ambient air lead levels that would be allowable or 

expected under each standard considered, probable exposure conditions with 

respect to other exposure media such as food and dust, and average biological 

absorption rates for each exposure route. The method consists of a four-step 

process: 

1) definitio n of ambient concentrations of lead for major exposure 

sources (i.e. , air, food, water, soil , dust); 

2) determination of dail y lead intake according to the relationship: 

. I-i = C-j • [Pbj-j 

where I-j i s the dail y lead intake from source i , C-j i s the ingestion or 

inhalation (i.e. , consumption) per day of each lead source i and [Pb]-j is 

the concentration of lead in each source i-j; 

3) calculation of the amount of lead absorbed from each exposure 

source i : 

U

i = I i ' A i 

where U-j is lead uptake for each exposure source i , I-j i s the dail y lead 

intake from each source i , and A-j i s the percent absorption of lead, via 

the appropriate exposure route for the particular source; and 

4) calculation of the total lead uptake from al l sources, Uu: 

Uu = E (I i • A ^ 

The way daily lead uptake would be calculated i s illustrate d in Table 4-1 

for 2-year old children livin y near (within 2-5 km) a lead point source. 

Details of the model parameters and the line-by-lin e estimates, alony with 
TABLE 4-1 . ESTIMATED 1990 AVERAGE LEAD INTAKE AND UPTAKE IN 2-YEAR OLD CHILDREN 

UNDER AVERAGE AIR LEAD LEVELS1 

0.25 pg/m3 0.5 pg/m3 0.75 pg/m3 1.0 pg/m3 1.25 pg/m3 1.5 pg/m3 

1 . Outdoor air lead (pg/m 0.25 0.5 0.75 1.0 1.25 1.5 3) _..-

2. Indoor air lead (pg/m3) .08 0.15 0.23 0.3 0.38 0.45 

3. Time spent outdoors (hours/day) 2-4 2-4 2-4 2-4 2-4 2-4 

4. Time weighted average (pg/m3) .09-.11 .18-.21 .27-.32 .36-.42 .45-.54 .b4-.63 

5. Volume of air respired (m3/day) 4-5 4-5 4-5 4-5 4-5 4-5 

6. Lead Intake from air (pg/day) 0.4-0.6 0.7-1.1 1.1-1.6 1.4-2.1 1.8-2.7 2.2-3.2 

7. % deposition/absorption in lunys 42 42 42 42 42 42 

8. Total lead uptake from lungs 0.2-0.3 0.3-0.5 0.5-0.7 0.6-0.9 0.8-1.1 0.9-1.3 

(py/day) 

9. Dietary Lead Consumption (py/day) 

a) from solder or other metals 

b) atmospheric lead 

c) natural lead, indirect atmospheric, undetermined sources 

10. % absorption in yut 

1 1. Dietary lead uptake (py/day) 

12. Street dust/soi l lead (pg/g) 

13. Indoor dust lead (pg/g) 

14. Time weighted average (pg/g) 

15. Amount of dir t ingested (g/day) 

16. Lead intake from dir t (pg/day) 

17. %dir t lead absorption i n gut 

18. Lead uptake from dir t (pg/day) 

19. Total lead uptake from lung and 

yut (pg/day) 

Assumptions and calculations are described i n Appendix A by row number. Refers to children livin y near one or more lead 

point sources and unaffected by lead paint children livin g in typical urban or rural environments remote from lead point 

sources can be modeled usiny the same uptake calculations and substituting parameter values where differences are.noted 

i n Appendix A. 

4.0 

1.2 

3.6 

42-53 

3.7-4.7 

160-240 

250-360 

220-340 

.08-.135 

17.6-45.9 

25 

4.4-11.5 

8.3-16.5 

4.0 

1.2 

3.6 

42-53 

3.7-4.7 

250-470 

440-670 

377-637 

.08-.135 

30.1-86.0 

25 

7.5-21.5 

11.5-26.7 

4.0 

1.2 

3.6 

42-53 

3.7-4.7 

325-720 

615-1010 

518-962 

.08-.135 

41.5-129.8 

25 

10.4-32.5 

14.6-37.9 

4.0 

1.2 

3.6 

42-53 

3.7-4.7 

405-975 

785-1355 

658-1292 

.08-.135 

52.7-174.3 

25 

13.2-43.6 

17.5-49.2 

4.0 

1.2 

3.6 

42-53 

3.7-4.7 

500-1205 

950-1700 

800-1618 

.08-.135 

64.0-218.4 

25 

16.0-54.6 

20.5-60.4 

4.0 

1.2 

3.6 

42-53 

3.7-4.7 

570-1490 

1120-2050 

937-1957 

.08-.135 

74.9-264.2 

25 

18.7-66.0 

23.3-72.0 

M < | 

-P-
P.38 

IV-5 

limitations of the available data base, are discussed in Appendix A. For 

comparative purposes, children livin g in areas generally unaffected by 

stationary lead emissions can also be modeled using most of the same parameter 

values; exceptions (indoor/outdoor particled penetration rates, respiratory 

deposition rates) are noted in Appendix A. Dust and soi l lead levels 

associated with given air lead concentrations would diffe r substantially 

between point and non-point source areas; thi s too i s briefl y discussed 

in Appendix A. The following points are important to consider with regard 

to the uptake calculations in the table: 1) the calculations do not represent 

population-wide exposure scenarios under alternative standards, only exposure for 

the specified air lead concentrations. Ambient lead levels around a point 

source meeting a given lead NAAQS vary depending on distance, topography, 

wind speed and direction , plant operating parameters, emissions controls, 

particl e sizes and deposition rates, etc. Air quality dispersion modeling 

that accounts for these factors wil l be used in the actual case study analyses 

to assign air lead concentrations under alternative standards to differen t 

"receptor" points where people liv e around the lead point sources; 2) the 

estimates in the table apply to 2-year old children to illustrat e the period 

of maximum exposure. Blood lead levels estimated by the biokinetic model 

(discussed below) account for cumulative exposure throughout childhood, 

not jus t a single year.. I t i s necessary, therefore, to make age-specific 

exposure estimates that reflec t changes in behavior and metabolism as a 

child ages. Age-specific exposure estimates are also discussed in detai l 

in Appendix A; and 3) the general types of exposure environments considered 

here do not include older homes with lead-based paint hazards. Such conditions 

are discussed at the end of Appendix A to illustrat e the severity of lead-paint 

hazards compared to other exposures. 
P.39 

IV-6 

B. Uptake and Blood Lead Concentration 

To estimate blood lead (PbB) levels under differen t exposure scenarios, 

several different kinds of studies can be used to derive a relationship 

between absorbed lead (or lead uptake) and blood lead. Available studies 

include population surveys in which the blood lead concentration of 

individuals or groups i s correlated with measured lead concentrations in 

air, food, water, soil , or dust; experiments in which volunteers are exposed 

to controlled air lead concentrations and their PbB levels measured; and 

lead balance studies, of individuals with measured lead intakes. The most 

relevant experimental studies including those on adults for comparative 

purposes, are discussed here along with descriptions of the analyses used 

to derive uptake/PbB relationships. Relationship between blood lead and 

environmental lead concentrations from population surveys are discussed as 

part of the aggregate and disaggregate models in Section V. 

1. Dietary Lead Ingestion Studies in Infants 

Studies that have measured dietary lead intake concurrently with 

PbB levels among infants and toddlers are compared in the criteri a document 

(CD, Table 11-49). Although precise estimates of dietary lead consumption 

can not be made, these studies (U.K. Central Directorate, 1982; Lacey 

et al. , 1985; Sherlock et al. , 1982; Ryu et al. , 1983) have several advantages: 

1) careful control and analysis of dietary intake; 2) minimal lead exposure 

to sources other than the diet as the study population (infants) i s relativel y 

immobile; and 3) intake/blood lead relationships can be used to estimate 

the impact of total lead exposure (i.e. , from al l sources) on blood lead 

because tracer studies (Chamberlain et al. , 1978; Rabinowitz et al. , 1976) 

show no differences in the distributio n of lead to tissues whether taken up 

from lung or gut. 
P.40 

IV-7 

Both the U.K. Central Directorate and the Sherlock et al . studies 

involved infants with relativel y high PbB levels and high intakes. I t i s 

well documented that the relationship between PbB and lead uptake from any 

source i s approximately linear at low intake levels but "flattens out" at 

high intake levels (CD, Sections 11.2 and 11.3). Because the PbB levels 

(< 20 py/dl) and lead intakes of the Ryu infants are more relevant, the 

criteri a document concludes that the slope from thi s study (0.16 py/dl per 

py/day) i s the best available estimate (CD, p. 11-129). 

Since lead uptake/PbB relationships are of interest , thi s slope (0.16) 

wil l be combined with the range of gastrointestinal absorption rates (42-53%) 

cited for infants in the CD to illustrat e the range of uptake/PbB relationships 

at the end of thi s section. A baseline PbB of 4 pg/dl wil l be assumed, 

based on recent studies of PbB levels and lead intake in Boston and Cincinnati 

infants'(Rabinowitz et al. , 1985; Succop et al. , 1987). 

2. Dietary Intake Studies in Adults 

The relationship between blood lead and food and/or water lead levels 

has been examined for adults in both experimental studies in which controlled 

dietary supplements were administered to volunteers, and duplicate diet 

studies. Again, several studies indicate non-linear blood lead responses at 

high exposures but a linear relationship at relativel y low intake levels 

(< 100 py/day, or < 30 py/dl PbB). 

Two studies identified in Table 11-49 and 11-50 of the CD appear most 

useful in estimatiny a dietary lead/blood lead relationship chiefl y because 

of their sample sizes and control over confoundiny factors: Sherlock et al . 

(1982), a duplicate diet study of 31 mothers (and their children) from Ayr, 

Scotland; and Cools et al . (1976) in which 11 subjects and 10 controls 

were studied for blood lead response to oral dosages of lead acetate. 
P.41 

IV-8 

The latte r study was an extension of the Stuik (1974) experiment, results 

of which wil l not be used here because responses were not followed long 

enough for blood lead to equilibrate. The weighted mean of the slopes 

reported in the CD for the Sherlock and Cools studies is 0.032 pg/dl 

increase in blood lead per pg/day intake, which i s a factor of 5-6 

times lower than the comparable slope estimated for infants at low exposure 

levels . A gastrointestinal absorption factor of 0.15, cited in the CD for 

adults, wil l be applied to thi s intake slope to derive a blood lead/uptake 

relationship. A baseline PbB level of 4 pg/dl wil l be assumed for adults 

based on projections described in Appendix C. The same pattern of non-linear 

absorption seen in children wil l be assumed and a slope of .008 pg/dl per 

pg/day wil l be used for levels above 50 py/day in adults. 

3. Application of Chamberlain and Heard Analysis of Adult Exposure Data 

An attempt to relate blood lead and absorbed lead was made by Chamberlain 

and Heard (1981) using epidaniological and c.linical data on adult men 

(Williams et al. , 1969; Kehoe, 1961; Nordman, 1975; Zurlo and Griffini , 

1973.; Fugas and Saric, 1979). Total dietary and airborne lead uptake was 

estimated using calculations similar to those presented in the integrated 

lead uptake model in Section IV.A. The following assumptions given in 

Chamberlain et al. , (1978) were used: a) a fraction , 0.55, of the uptake 

becomes attached to red blood cells ; b) the biological half-lif e of lead in 

blood i s 18 days; c) a factor, 1.3, i s to be allowed for long-term resorption 

and re-entry into blood of some of the lead which i s stored in bone; and 

d) the mass of blood i s 5400 grams. With these assumptions, Chamberlain 

and Heard calculated the following relationship: 

A PbB = 0.55 x 18 x 1.3 = 0.34 pg/dl per pg/day 

A Uptake 54 x 0.693 
P.42 

IV-9 

Thi-s relationship is comparable to that derived from the Cools and 

Sherlock studies after gastrointestinal absorption is accounted for. Given 

uncertainties about some of the studies analyzed by Chamberlain and Heard 

regarding exposure levels and quality control, and because of the exposure 

levels, this slope is presented here only for comparative purposes and will 

not be used further. 

4. Lead Balance Studies: Compartmental Models 

To demonstrate a causal relationship between lead in the body and a 

biological change, it would be ideal to know the amount of lead present at 

the site and time of the effect. For instance, if lead is suspected to 

induce neuropsychological changes, a measure of the lead level present in 

nerve cells when the change occurred would be desirable. Living tissues 

can rarely be sampled, and data obtained at necropsy cannot reveal the 

variations in exposure throughout the individual's life. For analytical 

simplicity, these tissues can be grouped together on the basis of lead 

distribution characteristics and body burdens of lead represented as a 

limited number of distinct, homogenous, and well-mixed pools or physiological 

compartments with similar kinetic properties. Mathematical biokinetic 

models have been fitted to data obtained in long-term balance studies and to 

lead isotope tracer experiments that estimate the rates of input to, 

transfer between, and excretion from the different compartments (Rabinowitz 

et al., 1976, 1977; Batschelet et al., 1979; Bernard, 1977; Mallon 1983; 

Harley and Kneip, 1985; Marcus, 1985a,b,c). Differences in the predictive 

lead models have been discussed by Bernard (1977), Batschelet et al. (1979) 

and Hammond et al. (1981). Models are shown schematically in the CD 

(Figures 10-3 and 10-4). 
__________ P.43 

IV-10 

The choice of pools or level of aggregation in a model depends on the 

available experimental data, the appropriate time scale, and the predictiv e uses of the analysis, and is a compromise between accuracy and 

complexity. For example, blood can be broken down into plasma and erythrocytes 

and then further into plasma protein-bound lead, diffusibl e lead, extracellular 

flui d lead, and erythrocyte proteins. Soft tissues can be broken down into 

brain (hippocampus, medulla, etc.), kidneys, liver , hair, and so on. The 

hard tissue pools can be separated into compact (cortical) and cancellous 

(trabecular) bones, and teeth; within each of these, separate components 

may be needed to model distinc t diffusion time scales (Marcus, 1985a,c). 

Because the skeletal system in young children i s rapidly developing and i s 

both large and kineticall y active, i t i s especially important to model bone 

lead in children. Unti l such refinements are further tested, a relativel y 

simple 3- 5 pool model should provide a framework for predicting lead 

distributions i n children. 

These models are helpful in predicting total body burden or equilibrium 

levels of lead over time in any of the presumed kineti c compartments under 

different exposure conditions. The basic assumption of the models i s that 

the mass of lead in each of the compartments changes according to a system 

of coupled first-orde r linear differentia l equations with constant fractional 

transfer rates. Such models predict that when the lead intake chanyes from 

one constant level to another, there i s a directl y proportional chanye in 

the mass of lead in each compartment and the attainment of a new equilibrium. 

The rates and magnitudes of these changes are dependent upon the rates of 

lead flux in the tissues and can theoreticall y be calculated from a compartmental 

model of the appropriate parameters. Support for a firs t order kineti c model 

for lead metabolism is demonstrated by calculations, using firs t order models 
P.44 

IV-11 

of soft tissue and bone concentrations of lead, and other elements (calcium 

strontium, radium), that fi t human measurements as well as by using more 

complex models (Johnson and Myers, 1981; Mallon, 1983). 

A four-compartment biokinetic model of lead metabolism has been developed 

from data obtained in controlled single dose and chronic lead exposures of 

infant (9 months) and juvenile (22 months) baboons (Mallon, 1983; Kneip et 

al. , 1983). Dynamic blood measurements and steady state blood and organ 

lead measurements were accurately fitte d to predict concentrations of lead 

in blood, liver , and kidney, and bone (the four compartments in which 95% 

of total body lead is contained) (Heard and Chamberlain, 1984). Human 

metabolism and growth patterns were applied in a computer simulation of the 

model that was then successfully validated using human autopsy data. 

The model parameters were revised using measured metabolic data for 

each organ (e.g. , bone turnover rates) for children and were used to 

simulate lead organ burdens and concentrations in children with constant 

lead exposures from birt h (Harley and Kneip, 1985). Although complete 

model validation i s not possible, the revised model i s consistent with experimental data on blood lead accumulation following dietary lead uptake among 

infants (Ziegler et al. , 1978), and skeletal lead accumulation following 

controlled exposures in adults (Heard and Chamberlain, 1984). Thus, given 

the available data thi s model appears to provide the best estimates of PbB 

levels in children with continuous lead uptake over time. 

Table 4-2 presents PbB levels predicted by the model for male children 

under different exposures, or lead uptake levels . No differences were found 

between the sexes except at older ages, and predicted PbB levels were 

highest amony 2-3 year olds, consistent with results of NHANES I I and the 

New York City screening program (Billic k et al. , 1979). These results wil l 
P.45 

IV-12 

TABLE 4-2. 

PREDICTED EQUILIBRATED BLOOD LEAD LEVELS (py/dl) OVER TIME AMONG CHILDREN 

WITH CONSTANT LEAD UPTAKES3 

Lead Uptake (pg/day) 

Age 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

10 

3.0 

4.0 

3.7 

3.6 

3.5 

3.5 

3.3 

2.5 

2.3 

2.6 

20 

5.9 

8.1 

7.3 

7.3 

7.0 

6.9 

6.5 

5.0 

4.6 

5.2 

30 

8.9 

12.1 

11.0 

10.9 

10.5 

10.4 

9.8 

7.4 

6.9 

7.8 

40 

11.9 

16.2 

14.6 

14.5 

14.0 

13.8 

13.0 

9.9 

9.3 

10.4 

50 

14.8 

20.2 

18.3 

18.1 

17.5 

17.3 

16.3 

12.4 

11.6 

13.0 

60 

17.8 

24.2 

22.0 

21.8 

21.0 

20.7 

19.5 

14.9 

13.9 

15.6 

70 

2U.8 

28.3 

25.6 

25.4 

24.5 

24.2 

22.8 

17.4 

16.2 

18.2 

80 

23.8 

32.3 

29.3 

29.0 

28.0 

27.6 

26.0 

19.9 

18.5 

20.8 

a

From Harley and Kneip (1985). 
P.46 

IV-13 

6e applied to estimates of the integrated lead uptake model to estimate 

children's PbB levels under alternative air lead levels . I t is important 

to note that thi s equilibrium blood lead model i s linear in total lead 

uptake at each age. This i s a necessary consequence of the 

linear pharmacokinetic model assumed by Harley and Kneip (CD, Appendix 11-A). 

The uptake/biokinetic model i s thus logicall y consistent with aggregate 

and disaggregate linear total-uptake models discussed in the following sections. 

Figure 4-1 compares the relationships between lead uptake and blood lead 

derived from the various (1983) studies on infants and adults. Despite the 

diverse nature of the populations, study designs, and methodologies, 

there i s a fai r degree of consistency in the relationships. Each study 

found that a linear function provided as good a fit , i f not better, than 

other non-linear forms at the relativel y low exposure levels investigated. 

Some experimental and epidemiological evidence suggests however, that the 

relationship between lead concentrations in tissues and cumulative lead 

intake i s only approximately linear at low levels of intake, and that 

successive increments in intake or exposure result in progressively smaller 

contributions to blood lead concentrations (Azar et al. , 1975; Moore, 1977; 

Gross, 1981; Sherlock et al. , 1982). The curves drawn in 

Figure 4-1 for infants and adults do in fact include smaller slopes for 

lead uptake values above 50 pg/day. This curvilinear relationship may be 

due to increased renal clearance with higher blood lead (Gross, 1981), 

distributiona l non-linearities due to differences in lead binding sites in 

different tissues (Hammond et al. , 1981; Marcus, 1985b; Manton, 1985), 

and/or to a sizeable pool of mobile lead in bone maintained more or less 

independently of uptake (Rabinowitz et al. , 1977; Chamberlain, 1983). I t 

appears however, that none of the mechanisms introduce significant non-linearities 
BLOOD LEAD (ug/dl) 

35 

30 h 

25 

20 h 

15 -

10 

5 -

0 

10 20 30 40 50 

LEAD UPTAKE (ug/day) 

60 70 

RYU-A 

RYU-B 

SHERLOCK/COOLS 

HARLEY AND KNEIP 

< 

i 

BO 

FIGURE 4-1, SUMMARY OF RELATIONSHIPS BETWEEN DAILY LEAD UPTAKE AND BLOOD LEAD FOR DIFFERENT AGE GROUPS, DERIVED h*KUM: 

a) RYU ET AL. (1983) STUDY OF INFANTS -- TWO CURVES REFLECT RANGE OF GI LEAD ABSORPTION KATES 

(0.42 - 0.53); b) SHERLOCK ET AL. (1982) AND COOLS ET AL. (1976) STUDIES ON ADULTS; AND 

c) HARLEY AND KNEIP (198b) BIUKINETIC MODEL WITH ESTIMATES FOR 2-YEAR OLD CHILDREN ILLUSTRATED. 

^1 
P.48 

IV-15 

at blood lead levels below 30 pg/dl (Marcus, 1984, 1985a,c; Chamberlain, 1983) 

and that a linear mathematical model i s valid for relativel y low to moderate 

lead exposures (CD, p. 10-31, Appdx. 11A-2). As discussed above, at levels 

above 30-40 pg/dl, blood lead may be an inadequate index for tissue lead burdens 

in many children (Piomelli et al. , 1984) and linear models are likel y to lose 

their predictive power. For thi s reason, the relationships depicted in Fiyure 

4-1 are truncated at 30 py/dl . To estimate PbB levels above 30 pg/dl, which is 

now above the PbB level of health-related concern for children, use of non-linear 

models discussed in the criteri a document would be required (CD, Appendix 11.B). 

The compartmental biokinetic model of lead metabolism developed by Mallon 

(1983) and Kneip et al . (1983), and revised for children by Harley and Kneip 

(1985), relied on a broad array of experimental and observational measurements 

of mammalian metabolism and growth patterns, and has been successfully 

validated using available human experimental and autopsy data. As i s the 

case for any mathematical model, there are inherent limitations and associated 

uncertainties. Because thi s model is based on the most comprehensive data 

available and has been developed specificall y to predict organ lead concentrations over time in youny children with continuous lead uptake, i t appears 

that the outputs of the Harley and Kneip (1985) biokinetic model are the 

most appropriate to predict PbB levels in children usiny the inteyrated 

lead uptake estimate methodologies presented in Section IV.A and Appendix A. 

PbB levels calculated from the conjunction of the inteyrated lead uptake and 

biokinetic models wil l be presented in the staff paper (along with estimates 

using other modeling approaches that are discussed later) in order to estimate 

potential health impacts under alternative air lead levels . Methodologies to 

calculate children's and adult blood lead levels data under alternative standards 

using other data and other modeling approaches wil l be discussed in Section V. 
P.49 

V. STATISTICAL RELATIONSHIPS BETWEEN BLOOD LEAD AND AIRBORNE LEAD: 

USE IN DISAGGREGATE AND AGGREGATE MODELS 

This section addresses two other methods of determining the contribution 

of air lead to total exposure and the potential health impacts associated 

with alternative air lead levels . The previous section examined the relationships between blood lead in children and estimated levels of lead 

uptake from the air, housedust, outdoor soi l and dust, and diet . The two 

approaches presented here develop a direc t relationship between air lead 

and blood lead from various experimental and community or epidemiological 

studies: 1) a disaggregate model in which total exposure to air lead i s 

assessed by separately analyzing the relationship between blood lead and 

inhaled air lead, versus the associated changes in blood lead as a result 

of exposure to lead that has deposited onto soil , dust, food, and water; 

and 2) an aggregate model in which a single variable, air lead, serves 

as an index for lead exposure through other media affected by integrated 

atmospheric lead deposition. 

Experimental studies include those in which adult volunteers have 

been exposed to controlled levels of laboratory generated lead aerosols. 

Because intake of air lead throuyh the diet and dust was probably minimal 

for the adult subjects in these experiments, these studies underestimate 

the dose-response relationships that would be seen amony children with 

chanyes in air lead (Anyle et al. , 1985). Epidemiological (i.e. , community) 

studies provide correlations between air lead and blood lead in different 

populations of children and adults under varyiny conditions of lead, from 

current or previous atmospheric fallou t and other sources, and yield doseresponse estimates at more relevant levels . 
P.50 

V-2 

Because of the simultaneous presence of lead in multiple media 

with different time profiles , the assessment and use of these studies 

i s not always direct . As in any attempt to model lead exposure, possible 

confounding variables that influence PbB levels but which are not related 

to air lead measurements (e.g. , lead in paint, canned food and plumbing, 

socioeconomic status, parental care, housiny and play conditions, calcium 

intake) cannot always be disentangled. Control for confounders can be 

achieved by comparing populations that diffe r only in their exposure to 

airborne-derived lead, although identifying such groups has been difficult . 

Another possibilit y i s to perform a multivariate statistica l analysis in 

which adjustments are made for some or al l of the confounders before calculating 

the blood lead/air lead relationship. This requires information on the 

value of each confounder for each individual , which i s also difficul t to 

.estimate. In the case of lead, several confounders tend to work in the 

same direction as air lead, e.g. , elevated exposure and unfavorable social 

conditions often are both concentrated in central cities . Consequently, 

when statistica l adjustment i s incomplete, the relationship between air 

lead and blood lead wil l likel y be inflated . Adjustment for a 

confounding variable may result in al l of the shared variance between 

confounder and exposure variable attributed to the confounder; thi s can 

inevitably lead to underestimation of the "true" impact of the exposure 

variable (Rutter, 1983). In characteriziny yood studies of air lead/blood 

lead relationships, several reviewers (e.g. , Hammond et al. , 1981; Brunekreef, 

1984), as well as the CD, discuss key factors that should be considered. These 

include a well-defined study population, a good measure of individual 

exposure, measurement of blood lead with adequate quality control , a statistica l 

analysis model that is biologicall y plausible and consistent with the data, 
P.51 

V-3 

and control or measurement of important covariates (CD, p. 11-63). The 

studies identifie d in the CD, and highlighted here, address these factors 

sufficientl y to establish meaningful relationships. 

A. Disayyreyate Model 

1 . Ai r Lead/Blood Lead Relationships in Adults 

Because the relationship between blood lead and environmental exposure 

i s nonlinear across the range of potential exposure, but approximately linear 

at lower levels (CD, p. 11-65), the focus here i s on studies of adults without excessive occupational or personal exposure. Longitudinal studies in 

which changes in blood lead were measured in adult volunteers exposed to 

controlled levels of laboratory generated aerosols, in some cases with 

isotopic lead tracer, are summarized in Table 11-40 of the CD. Data from 

the most relevant studies have been reanalyzed in the CD to yield blood 

lead air lead ."slopes" (3), where 3 measures the change in blood lead 

expected for a unit change in air lead. 

As noted in the CD, the blood, lead inhalation slope estimates vary 

appreciably from one subject to another in the experimental studies, and 

from one study to another. The weighted slope and standard error estimates 

from the Griffi n study (1.75 +_0.35) were combined with those calculated 

similarl y for the Rabinowitz study (2.14 +_0.47), and the Kehoe study 

(1.25 +^0.35), yielding a pooled weighted slope estimate of 1.64 +_ 0.22 

(CD, pp. 11-99 to 11-102). Excluding the subjects in the Kehoe study exposed 

to very high air lead levels (up to 36 pg/m3), results in an average slope of 

approximately 1.9 pg/dl per pg/m3. 

Several deficiencies in the individual studies are discussed in the 

CD such as uncontrolled or unmeasured air lead exposures outside the 
P.52 

V-4 

chambers or difficultie s in determining non-inhalation blood lead baseline 

levels (CD, p. 11-101). Furthermore, these experimental inhalation studies 

may underestimate the overall impact of airborne lead (via deposition and 

incorporation over time into soils , dusts, water, food chain). This i s 

much less of a problem, however, in predicting changes in adult lead 

exposure in the future, compared to children. For example, althouyh small 

increases in adult blood lead levels have been observed in areas of hiyh 

lead contamination (Barltrop et al. , 1975; Gallacher et al. , 1984; Rabinowitz 

et al. , 1985), adults do not ingest significant amounts of dir t and certainl y 

do not absorb ingested lead at the same rate as children. 

The cross-sectional relationship between blood lead and air lead in 

adults has been examined in several population studies. Azar et al . (1975) 

studied fiv e groups of men (cab drivers and offic e workers) who carried 

pers.onal air lead monitors and whose non-air lead exposures (water, smoking) 

were also measured over a 24-hour period. Several alternative geometric 

mean regressions have been calculated, including linear and non-linear 

models assuming different non-air contributions to blood lead, and estimations 

of the effect of endogenous lead stored in the skeleton usiny aye as a 

surroyate measure of cumulative exposure. None of the fitte d models are 

siynificantl y different statisticall y (CD, p. 11-81) with a pooled slope 

estimate of 1.32 ^0.3 8 (CD, p. 11-105). Althouyh the other population 

studies typicall y used less accurate measures of individual exposures 

(e.g. , Tepper and Levin, 1975; Nordman, 1975; Johnson et al. , 1975), the 

range of slope estimates (1.0-2.0) is comparable to the Azar et al . and 

experimental inhalation results (Snee, 1981; see CD, p. 11-98). 
P.53 

V-5 

Although the studies differed in co-variables measured, populations, 

exposure conditions, etc. , the most reliable and relevant studies consistently 

yield inhalation slope values typicall y in the range of 1.3-2.0 pg/dl per 

pg/m3, with a weiyhted slope of 1.4. The above slope estimates are derived 

from studies in which exposure to air lead was assessed over days, weeks, 

or months and are based on the assumption that an equilibrium level of 

blood lead is achieved within a few months after exposure beyins. This i s 

only approximately true , since some of the absorbed lead that accumulates 

in the skeleton deposits in the sponyy trabecular bones (e.y. , rib , vertebrae) 

where i t may be resorbed into the blood stream. An additional factor 

therefore, should be allowed for possible re-entry of lead into the blood 

transferred from bone or other long-term storage (Chamberlain, 1983). 

Based on isotopic ratio and radiolabel tracer studies on adults, Chamberlain 

et al . (1978) estimated thi s factor to be 1.3. I t is likel y to be lower in 

children because of the rapid growth, high rate of turnover and smaller 

reservoir of lead in their skeletal systems. While no adjustment for bone 

resorption wil l be made for children's slopes, i t appears reasonable to 

apply thi s factor to the blood lead/air lead inhalation slope of 1.4 derived 

above for adults, yielding a slope estimate of about 1.8. 

2. Estimating Future Adult Blood Lead Averages 

Two adult populations require separate exposure predictions for the overa l l risk analysis: middle-aged males, 40-59 years of aye; and preynant women, 

as exposure surrogates for fetuses (see CD, Sections 13.7.2 and 13.7.3). 

Older women may also be at increased risk due to mobilization of bone lead 

after menopause which can exacerbate osteoporosis (Silbergeld and Schwartz, 

1987). Unlike children, who receive much of their lead from ingestion of 

lead contaminated soils and dusts, especially those livin g near point 

sources, the bulk of non-occupational adult lead exposure typicall y can be 
P.54 

V-6 

attributed to diet (e.g. , canned foods and drinking water contaminated by 

lead solder, deposition of atmospheric lead onto crops and other vegetation) 

(see CD, Table 7). Further, women of child-bearing aye and middle-ayed men 

have cumulative stores of lead, primarily in their bones, so that the 

short-term changes in lead exposure that wil l be assumed for 1990-96 under 

alternative lead NAAQS (the timeframe for which case study exposure analyses 

wil l be made) wil l have relativel y smaller impacts on total body burden and 

blood lead than in children. Although future changes in industrial lead 

emissions would not affect PbB levels among adult populations livin g near 

point sources to the extent as they would children, even small changes 

can be important, especially given the sensitivit y of the fetus to lead. 

Given a background or "baseline" blood lead estimate representing non-air 

lead adult exposures, and an average disaggregated blood lead: air lead 

relationship, the following simple equation can be used to predict olood 

lead means for different adult populations in our case studies: 

x"= y 0 + 1.8A 

where x = mean blood lead (py/dl) 

y 0 = non-air background blood lead (pg/dl), and 

A = average air lead (pg/m3) 

Estimates of non-air "background" blood lead level contributions for differen t 

adult populations that wil l be used in the 1990-96 case studies are derived 

in Appendix C. Issues involved i n estimating fetal PbB levels are also 

discussed there. 

3. Air Lead/Blood Lead Relationships in Children 

Three population studies of children livin g near lead point sources 

in which covariates were controlled (e.g. , age, sex, dust exposure) were 

extensively analyzed in the CD for the most useful and relevant estimates of 
P.55 

V-7 

inhalation slopes: Angle and Mclntire, 1979 (3 = 1.92 +_0.60); Roels et al. , 

1980(3 = 2.46 +_0.58); and Yankel et al , 1977/Walter et al , 1980 (3 = 1.63 

^0.084). The median slope of the three studies i s 1.97 (CD, p. 11-189); it s 

application for use in the disaggregate model i s discussed below. 

4. Estimating Children's Blood Lead Levels Using Disaggregate Model 

The relationship between blood lead and direc t inhalation of airborne 

lead provides information useful for changes in air lead on a time scale of 

only several months (CD, p. 11-189). Over time, suspended lead is deposited 

and incorporated into soil , dust, and water, and enters the food chain. 

Since prior and current atmospheric fallout directl y modify the daily 

burden of ingested lead, laryer chanyes in blood lead would be predicted i f 

the associated changes in the surface deposition of lead were accounted for, 

rather than simply inhaled air lead (Anyle et al. , 1984). To account for 

the simultaneous presence of lead in multiple environmental media,, the CD 

has analyzed the separate mathematical relationships between blood lead and 

dietary , soil , and dust lead, described in detai l in Chapter 11.4. Usiny 

representative values fo r lead concentrations in these media, these 

relationships were applied in a further analysis presented in the CD (CD, 

Table 13-6) as a way to estimate proportional inputs to total blood 

lead levels in U.S. children. A similar disaggregate model was developed 

by Angle and Mclntire (1979) and Angle et al . (1984) in forming an integrated 

lead exposure function from measurements of lead in air, soil , and house 

dust and relating that to PbB levels of children livin g in various areas of 

Omaha. 

The disaggregate model developed in the CD, intended to represent 

the then "current (i.e. , 1983-84) exposure picture," is adopted here in 

Table 5-1 for different air lead levels and background levels of lead in 
P.56 

V-8 

TABLE 5-1. DISAGGREGATE MODEL OF CONTRIBUTIONS FROM VARIOUS MEDIA 

TO 1990 MEDIAN BLOOD LEAD LEVELS (pg/dl) OF U.S. CHILDREN 

(2 YEARS OF AGE): BACKGROUND LEVELS AND INCREMENTAL 

CONTRIBUTIONS FROM AIR1' 

Source 

Background - nonair 

food and water^ 

Dust3 

Subtotal 

Background-Ai r 

Food and Water 

Ingested Dust (with 

Pb deposited from air) ^ 

Inhaled air 6 

Total 

0.25 

1.2 

0.1 

1.6 

0.2 

1.0 

0.5 

3.0 

0.5 

1.2 

0.1 

1.6 

0.2 

1.7 

1.0 

4.2 

Air Lead 

0.76 

1.2 

0.1 

1.6 

0.2 

2.5 

1.5 

5.5 

(pg/m3) 

1.0 

1.2 

0.1 

1.6 

0.2 

3.2 

2.0 

6.9 

1.2b 

1.2 

0.1 

1.6 

0.2 

4.0 

2.5 

8.0 

1.5 

1.2 

0.1 

1.6 

0.2 

4.7 

3.0 

9.2 

Adapted from Table 13-6 of CD. 

^Estimated dietary intake of non-air Pb in 1990 (from Cohen, 1988; Appendix A) 

7.6 pg/day x 0.16 pg/dl per pg/day (from Ryu et al., 1983). 

3From CD, Chapter 7, 1/10 dust not atmospheric. Using Anyle et al. (1984) 

"low area" for soil and house dust levels and median regression coefficients 

from Stark et al. (1982): (1/10) x (97 pg/g x 0.0022) + (324 pg/y x 0.0018). 

^As in 2 above, but using 1.2 pg/day for dietary intake of atmospheric lead. 

Derived for component of backyround Pb in food from past deposition from air 

_onto soil and into other media leadiny into human food chain. 

^Regression equations of Stark et al. (1982) used alony with levels of 

soil dust and house dust predicted by reyression analyses of collected point 

source environmental data, described in Appendix B. For example, the mean soil 

and house dust lead concentrations associated with 1.0 py/m3 in air are 

approximately 630 ppm and 1U35 ppm, respectively. 

The effect on blood lead would be: 

(630 x 0.0022) + (1035 x 0.0018) = 3.2 pg/dl per pg/m3. 

6Using the median inhalation slope of 1.97 pg/dl per pg/m3 from the CD, p. 11-189. 
P.57 

V-9 

food, .water, dust, and soil , expected in 1990. The estimates are mean 

PbB levels for 2-year old children; comparable analyses for other ayes of 

children can be done usiny the aye-specific estimates of dietary lead intake 

presented in Appendix A. Calculations and assumptions used in deriviny the 

estimates are summarized in footnotes to the table and are similar to those 

described in Table 13-6 of the CD. The following changes were made for the 

present analysis: 

1) Estimated levels of dietary lead intake for children in 1990 were 

substituted for the estimates for 1983-84 used in the CD. The 1990 projections , described in Appendix A, are based on the Multiple Source Food 

Model developed in the CD and uses more recent data on the downward 

trends in food and water; 

2) Soil and housedust lead concentrations associated with different 

air lead levels are estimated based on the long-term relationships derived 

from reyression analyses of data collected from concurrent measurements of 

air, soil , and/or dust lead concentrations at about 45 lead point source 

locations (see Table A-4). These same relationships are beiny used to 

estimate surface soi l and indoor dust lead levels in the uptake biokineti c 

model. In contrast, soi l and dust lead concentrations under differen t air 

lead levels were estimated in Table 13-6 of the CD by interpolation of data 

from the Angle et al . (1984) study. This study i s but one of many data 

sets included in the aforementioned regression analysis described in 

Appendix B. 

3) The soi l and dust/blood lead regression coefficients used to compute 

soi l and housedust contributions to blood lead are from the CD analysis 

of the Stark et al . (1982) study and. are described in the CD as the most 

reasonable median estimates (pp. 11-151, 11-191). The coefficient s used in 
P.58 

V-10 

Table 13-6 of the CD are from the Angle et al . (1984) study and represent 

upper bound values. 

I t must be emphasized that the blood lead estimates presented in Table 

5-1 represent population mean PbB levels and are illustrativ e only. In 

order to assess health risks associated with such air lead exposures, i t would 

be necessary to calculate PbB distributions around these mean levels , as 

discussed earlier in Section III.B . 

Since completion of the 1986 CD, several findings have become available 

that supplement previous conclusions. Unpublished analysis by Johnson and 

Wijnberg (1988) of the 1983 study of young children livin g near the East 

Helena smelter (CDC, 1983) estimate slopes for both blood lead-soi l lead 

and blood lead-dust lead of approximately 1.4 pg/dl per 1000 ppm. This 

analysis adopted modeling used by EPA in the CD to fi t other similar studies 

and adjusted for numerous covariates including children's age, air lead, 

dust and/or soi l lead depending on analysis, poor quality lead painted 

housing, smoking, and secondary occupational exposure. 

• As indicated in many of the studies, the dust lead slope i s similar to 

the soi l lead slope, suggesting that soi l may contribute both directl y and 

indirectl y to blood. Such hypotheses regarding cause-effect responses of 

blood lead to earlier exposures have been explored in recent longitudinal 

studies on blood lead and developmental indicators in Cincinnati (Bornschein 

et al. , 1985, 1986) and Boston (Rabinowitz et al. , 1985; Bellinger et al. , 

1987) children. The Cincinnati data set was analyzed by structural equation 

methods (Bentler, 1980) for relationships between exterior surface scrapings, 

dust lead, and blood lead. Unfortunately, the results are expressed as a 

linear equation in logarithms of the environmental variables, and the 

standardized regression coefficients are not directl y interpretable as 
P.59 

V-l l 

overall slopes for soi l or dust lead given the published information (Bornschein et al. , 1986). 

The analyses of the Boston data used a somewhat different technique--

randorn effects models for longitudinal data (Ware, 1985). Unfortunately, 

soi l lead data were not sampled longitudinally . There were repeat 

measuranents for blood, dust, air, water lead. The 18-month blood lead 

regression model reported by Rabinowitz et al . (1985) used the logarithm 

of the yard soi l lead measurement as a predictor, so that the reported slope 

i s not directl y comparable to those cited in the CD. However, the slopes at 

several concentrations are similar to those cited in the CD: 8 pg/dl per 

1000 ppm soi l lead when soi l lead = 100 ppm, 1.6 pg/dl per 1000 ppm soi l lead 

when soi l lead = 500 ppm, and 0.8 pg/dl per 1000 ppm when soi l lead = 1000 

ppm. 

5. Plausibilit y of Disaggregated Slopes: Comparison with Uptake/ 

Biokinetic Model 

The disaggregated air, soil , and dust lead "slopes" used Were are 

plausibly consistent with the uptake/biokinetic model parameters. To show 

this , we use the well-known relationship (e.g. , Rabinowitz et al. , 1976) between 

blood lead increments, dPbB, and lead intake increments, dPbl; 

dPbB = dPbl * (mean residence time i n blood pool)/ (volume of 

distributio n in blood pool) 

For a two-year old child , the Harley-Kneip model predicts a mean residence 

time in the blood pool of about 8 days, i.e. , a blood lead half lif e of 8 

* 0.693 = 5.6 days, consistent with Duggan's (1983) estimate of 4-6 

days. The blood lead pool i s much larger than the blood lead volume, 

including accessible parts of the soft tissues, bone and bone marrow, and 

extracellular fluid . Rabinowitz et al . (1976) estimates that the volume 

of thi s pool in adult volunteers was 76 - 108 dl , almost twice the adult 
P.60 

V-12 

blood volume. Since the blood volume in infants (about 12% of body weight) 

is proportionately greater than in adults (about 8% of body weight), we will 

assume the blood volume in 1-6 year old children is about 10% of body weiyht, 

adjusted for whole blood density of 1.06 kg/1. Thus, the volume of distribution in a 10 kg child (about 2 years old) is taken as about: 

2 * 0.10 * 10 kg/(1.06 kg/1) = 2 1 = 20 dl. 

In Table 4.1 , the total amount of dir t consumed, C, i s taken as about 

0.1 g/day, of which a fraction a = 0.25 i s absorbed. The leaded dir t i s 

partitioned as some fraction p of soi l and 1 - p of interio r house dust. Thus: 

dPbl = c * a * (p * PbS + (1 - p) * PbD) 

Assuming p = 0.5 i.e . equal soi l and dust access, 

dPbB = (0.1 g/d) * (0.25) * (0.5 PbS + 0.5 * PbD) * 8d/20 dl 

= 0.005 PbS +0.005 PbD 

Thus the soi l lead vs. blood lead and the dust lead vs. blood lead slopes 

are both predicted to be about 0.005 pg/dl per ppm. 

A variety of factors may be responsible for the somewhat smaller 

empirical slope estimates, typicall y about 0.002 (see above). Even 

though the individual household PbS and PbD levels are available i n 

some studies, these are not necessarily the exact exposure covariates, 

but only indirect surrogate measures of dir t lead exposure. I t i s well 

known that exposure measurement "error" tends to flatte n or attenuate 

regression slopes in dose-response studies (e.g. , Pickles, 1982; Fuller, 

1987; Brunekreef et al. , 1987). Of course, specification of the constants 

(e.g. , a < 0.25 or C < 100 mg/d) could also reduce the predicted slopes. 

The agreement i s nonetheless impressive. 

The air lead slope i s similarl y calculated. From Table 4.1 , the point 

source uptake at 1.0 pg/m3 is 0.6 - 0.9 pg/d, thus 
P.61 

V-13 

PbB = (0.6 - 0.9) * PbA * 8d/20 dl 

= (0.24 - 0.36) PbA 

The estimated direc t inhalation slope of 0.24 - 0.36 i s much smaller 

than has been cited for empirical disaggregate studies. These discrepancies 

have been previously noted in Marcus (1988b) in an analysis of East Helena 

data. The differences between the uptake/biokinetic model apparent 

PbD slope and the disaggregate regression slope (0.00341 vs. 0.00151), 

apparent PbS slopes (0.00199 vs. 0.00102), and apparent PbA slopes (0.63 

vs. 1.08) were in the same direction . I t i s possible that the empirical 

multiple regression studies have misallocated the variance in log(PbB), 

attributin g too littl e effect to soi l and dust inyestion. We cannot decide 

whether these are artifact s of the multiple reyression model or of the 

uptake/biokinetic simulation model. Nevertheless, the slope values used in 

the disayyregate model are in general consistent with the uptake/biokinetic 

model. 

B. Aggregate Model 

1 . Air Lead/Blood Lead Relationship 

In the disaggregate modeling approach, "inhalation" slopes are derived 

by statisticall y adjusting blood lead/air lead slopes by whatever indirec t 

air exposure variables (e.g. , house dust lead) that were measured in the 

individual epidemiological studies, and then combining separate slopes 

available for other exposure media (e.g. , dust, food, water) to 

arrive at an inteyrated lead exposure function. With the exception of 

Angle and Mclntire (1979), the community studies from which inhalation 

slopes have been derived have not simultaneously measured lead in more than 

two or three media and consequently, the integrated lead exposure function 

i s necessarily based on data from multiple studies involving differen t 

populations, exposure conditions, measurement techniques, etc. An alternative 
P.62 

V-14 

method of calculating the effect of changes in air lead on children's blood 

lead i s to analyze individual community studies in which reliable "unadjusted" 

blood lead/air lead relationships can be derived such that the impact of 

both direc t (inhaled) and indirec t (via dust, soil , etc.) contributions of 

air lead are combined, or aggregated, i n one variable (i.e. , air lead). 

To only use an "adjusted" blood lead/air lead slope (i.e. , inhalation 

slope) would result in an underestimation of the impact of atmospheric 

lead on children's total exposure since air lead levels , in general, are 

causally related to other important exposure variables such as hand and 

household dust lead (Brunekreef, 1984). 

The population studies with identifiabl e air monitoring methods and 

reliable blood lead data are summarized in Table 5-2. None of the studies 

included adult populations. Since adults do not typicall y ingest much 

deposited lead anyway, the aggregate modeling approach wil l be limited to 

young children. As i s the case for the data in each of the experimental 

studies, different statistica l analyses of these studies have resulted in a 

range of possible values for the blood lead/air lead relationship (3). 

Unadjusted (i.e. , aggregate) relationships are presented in addition to 

adjusted (i.e. , disaggregate) relationships derived from regression analyses, 

the latte r which refer to the blood lead/air lead relationships due to 

direct inhalation exposure. 

In Table 5-3, the calculated 3 values listed in Table 5-2 for each study 

are presented according to the blood lead levels , ages, and type of location 

of the investigated children. Relatively wide ranges of 3 values are 

observed for industrial and urban areas at low and high PbB levels and for 

al l ages of children. The apparent trend towards smaller slopes with increasiny 

PbB levels is consistent with findings within some studies (Angle and 
TABL E 5-2 . SUMMARY OF EPIDEMIOLOGICA L STUDIE S ON LEAD-EXPOSE D CHILDRE N 

Study Population3 

Air Lead0 

(ug/m3) 

Blood Lead 

(uq/dl) 

Statistical Model 

(Analyst) 

Covariates 

Measured 

Blood Lead/ 

Aip Lead Slope 

Roels et al., 

1976,1978,1980 

Yankel et al., 

1977; Walter 

et al., 198U 

<lkm: 10-15 yrs n=214 

2.5km: 10-13 yrs n=168 

Urban: 10-14 yrs n=55 

Rural: 10-13 yrs n=223 

Living near "lead smelter 

(Antwerp, Belgium) 

1-9 yrs n=1149 (1974) 

1-10 yrs n=781 (1975) 

living at varying 

distances from lead 

smelter (Kellogg) 

2.68-4.06 

0.54-1.00 

0.45-0.56 

0.29-0.37 

(9 month avgs; 

low volume sampler)0 

0-1.6km: 18.0 

1.6-4km: 14.0 

4-10km : 6.7 

10-24km: 3.1 

24-32km: 1.5 

- 75km: 1.2 

(monthly avgs.) 

24.6-30.1 

13.3-21.1 

10.4-12.7 

9.0-10.7 

65.9 

47.7 

33.8 

32.2 

27.5 

21.2 

21.2 

Multiple regressions: 

Roels et al., 1980 

(8 group means) 

CO (148 subjects) 

Age, drinking water, income 5.3 

plus hand dust Pb adjustment 0.UU7 

-plus hand dust Pb adjustment 2.46 

Multiple regressions: 

Yankel et al. (1977) 

Snee (1982b) 

Snee (1982a) 

CU (linear) 

CU (non-linear) 

Walter et al. (1980) 

Group comparisons 

(Brunekreef, 1984) 

Age, drinking water, paint, 

SES, house dust 

-plus soil & dust Pb 

occupation adjustment 

-plus soil Pb, occupation, 

cleanliness, pica adjustment 

-same as above 

-same as above 

-same as above 

No adjustment for soil 

or dust Pb 

At l.U uy/rn^, 

iy74 data 

1.1b 

1.13 

l.U/ 

1.52 

1.1b 

1.2b 

2.4-3.3 

depending on dy 

Angle and 1-18 yrs n=831 

Mclntire, living in industrial 

1979 urban, suburban 

areas of Omaha 

industrial: 0;37-1.66 24.8 

urban: 0.32-1.44 22.0 

suburban: 0.22-0.73 18.0 

(annual avgs. 1970-

1977) 

Regression Analyses: 

Angle and Mclntire 

(1979) (6-18yr. olds) 

CU (Table 11-33) 

(1-18 yr. olds) 

C0-(Table 11-33) 

Brunkreef, 1984; 

(all children) 

(1-5 yr. olds) 

(6-18 yr. olds) 

Age, drinkiny water, food 

-plus soil & house dust 

Pb adjustment 

-same as above 

-same as above 

No adjustment for 

soil or dust lead 

1.4 

U.b 

1.92 

4.4U 

U.bb 

2.63 

2.1U 

<c 

1 

1 — > 

Ol 

Brunekreef 

et al., 1981; 

Zielhuis et 

al., 1979 

1976:2-3 yrs n=108 

1977:1-7 yrs n=690 

1978:1-3 yrs n=95 

living <2km and 2-5km 

from secondary smelter 

(Arnheim) 

0.5-2.5(0.4km) 

0.4-1.6(0.4km) 

0.28-0.51(<lkm) 

(2 month avg.) 

11.8(2-5km)-19.7(.4-lkm) 

14.6(l-2km)-18.2(.4-lkm) 

16.1(.4-lkm) 

Group comparison 

(Brunekreef, 1984) 

Multiple regression 

(Brunekreef, 1984) 

Age, parental education 

and exposure, drinkiny water, 

food, age of home, mouthiny 

behavior/hand dirt, house dust 

- plus adjustment for parental 

..education 

4.0 (1976) 

3.6 (1977) 

3.6 (1976) 

Landrigan 1972:1-18 yrs n=259 (exposed) 

et al., 1975; 1977:1-18 yrs n=499 (control) 

Morse et al. 1-18 yrs n=140 (exposed) 

1977 living near primary 

smelter (El Paso) 

<.8km .8-1.6km 

6.0d 

<.8km .8-1.6km 

10.0 

5.5 3.Ud 

(4 month avg.) 

41.4 31 

17.7e zu 

Group comparison 

(Brunekreef, 1984) 

Age, drinkiny water, milk 

consumption, parental income, 

home paint status 

2.6 (1972) 

i.l (197/) 
TABL E 5-2 . SUMMARY OF EPIDEMIOLOGICA L STUDIE S ON LEAD-EXPOSE D CHILDRE N (continued ) 

Study Population3 

Air Lead0 

(ug/m3) 

Blood Lead 

(uy/dl) 

Statistical Model 

(Analyst) Covariates Measured 

blood Lead/ 

Air Lead blope 

Billick et al., U-6 yrs n=178,533 

1979, 1980; living in NYC 

Nathanson 4 

Nudleman, 1980 

0.8-2.5 

(quarterly averages, 

1970-1974) 

20-33 Regression analysis 

(Brunekreef, 1984) 

Season, location, plus 

adjustment for age S race 

2.9 

Brunekreef 

et al.. 1983 

4-6 yrs n=195 

living in city center 

or in suburban area 

(Rotterdam) 

.25 city 

.13 suburban 

(6-month avg., 

low volume sampler0) 

13.1 

8.2 

Group mean comparisons 

Regression analysis 

(Brunekreef, 1984) 

Regression analysis 

(Brunekreef et al., 

1983, 1984) 

Age, drinking water, house 

paint, SES, parental exposure, 

location 

-plus adjustment for Pb 

deposition outdoors, age of 

home, milk consumption, number 

of rooms, hand dirt, mouthing 

behavior, pets 

24.5 

18.b 

3.U-8.5 

aRefers to age of children sampled and sample sizes (n). 

°Represents average levels measured either at various locations specified in "population" column or at various 

distances from specified point sources. 

cAir lead levels sampled by low volume methods likely underestimated levels that would have been measured by hi-volume samplers used in other studies, especially near smelter where larger lead particles predominate. This could result in inflated blood/air lead ratios. 

i 

•—• 

c* 

•^Estimated by interpolation of air quality data presented. 

eBased on only 3 samples - blood/air lead slope for 1977 based on reduction of air and blood lead at 0.8-1.6km from 

source. 
Type of Location (Study) 

Blood Lead (ug/dl)/ 

Age (years) Urban Near Point Source(s) 

<25/l-7 8.5a»

b

 (Brunekreef et al. , 1983) 3.6-4.0a (Zielhuis et al. , 1979; Brunekreef 

et al. , 1981) 

<2b/l-18 0.6 (Angle and 0.66a (Brunekreef, 1984 

1.4a Mclntire; -2.63a from Angle and 

1.92 1979, CD) 2.10a and Mclntire-, 1979) 

4_!_U) 

<25/10-15 - 2.46 (CD from Roels et al . 1976) 

5.3a (Roels et al . 198U) 

« 5.9-9.8a»

b

 (Brunekreef, 1984 from Roels 

et al. , 1976, 1978, 1980) 

>25/0-9 2.9 (Billic k et al. , 1979, 1980; 1.07-1.52 (Yankel et al. , 1977; Walter et al. , 

Nathanson and Nudleman, 1980) 1980; Snee, 1982b; CD) 

2.4-3.3a (Brunekreef, 1984 from Yankel et al. , 

1977) 

>25/l-18 - 2.6-3.7a (Landrigan et al . 1975; Morse et al. , 

1977) 

4.6a (Brunekreef, 1984 from Roels et al. , 1976, 

. 1978, 1980) 

^Slopes are in units of pg lead/dl blood per pg lead/nP air. 

a

"Aggregate" slopes derived from group comparisons or multiple regression analyses that were unadjusted for soi l or 

dust lead, thereby attempting to account for influence of deposited atmospheric lead through these exposure routes. 

Remaining slopes represent relationships between blood lead and air lead due solely to direc t inhalation which have 

been calculated by adjusting for the influence of soi l and/or dust lead. 

bUse of low-volume particulate samplers likel y underestimated air lead exposures, and overestimated the 

3 value, especially near point source where large particles predominate. 

< i 
P.66 

V-18 

Mclntire, 1979; Roels et al. , 1980) and other observations of curvilinear 

blood lead/exposure relationships (Azar et al. , 1975; Moore et al. , 1977; 

Gross, 1981; Sherlock et al. , 1982; Hammond et al. , 1981). 

As discussed, the CD determined that the disaggregate inhalation 

slopes derived from the studies by Angle and Mclntire, Roels et al. , and 

Yankel et al . are the most reliable given their overall quality . I t i s 

important to note several additional studies and analyses that may provide 

equally relevant and useful information for purposes of estimating an 

aggregate blood lead/air lead slope. Tables 5-2 and 5-3 identif y surveys 

besides those of Angle and Mclntire and Roels et al . which studied children 

(0-10 yrs) whose blood lead levels were below 25 pg/dl . These studies 

(Brunekreef et al. , 1983; Zielhuis et al . 1979; Brunekreef et al. , 1981) 

reported well-defined study populations, employed available quality control 

procedures for blood lead analysis, and measured or controlled for important 

covariates (see Table 5-2). Several specific comments should be made 

regarding these studies: 

1 . The series of studies reported by Zielhuis et al . (1979) and 

Brunekreef et al . (1981) included many environmental measurements (lead in 

ambient and indoor air , lead in dustfal l indoors and outdoors, soil , 

streetdust, floordust, tapwater, and dustiness of homes) and regression 

analyses to determine the impact of differen t variables on PbB levels 

(i.e. , the above environmental indices as well as distance from the smelter, 

parental education, aye of the child , mouthing activity , cleanliness of the 

child). Venous blood lead samples were analyzed by standard techniques and 

although information on interlaboratory comparisons i s not given in the 

original study, quality control participation is reported by one of the 

investigators in a subsequent review (Brunekreef, 1984). Air lead was 
P.67 

V-19 

measured at two sites in 1976, and in 1977, 0.2 and 0.4 km from the smelter. 

The levels in Table 5-2 were taken from Brunekreef (1984) and represent 

those measured at 0.4 km from the smelter. Air lead was measured at 6 

sites continuously for 2 months in 1978. Brunekreef (1984) estimates 

3 = 4.0 for 1976 by assuming a difference of 2.0 pg/m^ in average 

a ir lead exposure levels between the 2-3 year old children with the highest 

and lowest PbB levels . After adjustment for parental education, the blood 

lead difference of about 8 ug/dl decreased to 7.2 ug/dl , resulting in 

a slightl y lower 3 estimate (3.6). For 1977, a difference of 1.0 ug/nP 

was assumed for air lead exposure levels between smelter and control children 

aged 2-3 years who had PbB levels of 18.2 and 14.6 ug/dl , respectively, again 

resulting in a 3 of 3.6. In 1978, only children livin g between U.4 and 1.0 

km of the smelter were sampled and air levels did not correlate with blood 

lead within thi s population. Thus, no direc t estimate of 3 can be derived, 

although soi l lead and indoor and outdoor dust lead, and therefore, accumulated 

lead deposition, accounted for a significant fraction of the variance in 

PbB levels (Brunekreef et al. , 1981). 

2. The more recent study by Brunekreef et al . (1983) on Dutch cit y and 

suburban children measured venous blood (which was analyzed as part of 

the European Community laboratory quality control program) and many 

environmental and social variables and potential confounders (lead in 

drinking water, soil , street and playground dust, hand dust, indoor dust, 

mouthing behavior, dietary intakes, parental education and occupation, age 

of home, etc). The very high 3 value (8.5) derived by Brunekreef (1984) 

even after adjustment in a multiple regression analysis for six of tne 

confounders, may be related to an underestimation of ambient air lead 

levels due to the fact that low volume Britis h Smoke air monitors were 
P.68 

V-20 

employed, in contrast to the hi-vol samplers used in most other studies. 

The extent of inflatio n in the estimated slope as a result of any underestimated 

air lead level i s uncertain. Brunekreef (1984) notes however that even i f 

thi s bias is accounted for, the difference in urban and suburban air lead 

levels was probably not larger than 0.2 ug/m-^. The contrast in lead 

deposition between the areas was significant (i.e. , 643 vs. 220 mg/m^/day), 

indicating that ongoing lead pollution accounted for a good deal of the 

differences in PbB levels , although variations in historical emissions can 

not be entirel y ruled out. The relativel y low PbB levels in thi s study 

(« 8-13 ug/dl) could be another partial explanation of the high 3 estimates, 

yiven that other studies used to derive 3 included children with PbB levels 

on average closer to , and above, 30 ug/dl , at which point the blood 

lead/lead intake relationship i s estimated to level off ; below 30 ug/dl , 

thi s relationship appears to be approximately linear (CD, p. 11-104). 

In addition to these studies, the available statistica l aggregate 

analyses on the criteri a document's three "key inhalation slope" studies 

on children require brie f discussion. 

3. The three inhalation 3 values (0.6, 1.92, and 4.40) attributed to 

regression analyses performed by Angle and Mclntire (1979) (CD, Table 

11-39) al l included adjustments for soi l and house dust lead. An unadjusted 

regression analysis found a 3 of 1.4 for 6-18 year olds (Angle and Mclntire, 

1979). Unadjusted coefficients of 0.66 (al l children), -2.63 (1-5 y r olds) 

and 2.10 (6-18 year olds) were obtained by Brunekreef (1984). The surprising 3 

for the 1-5 year olds could be due to the fact that thi s age group was only 

sampled during one year, whereas sampling of older children was performed 

over 6 years. Brunekreef's reanalysis illustrate s two points: 1) any slope 
P.69 

V-21 

derived for al l children in the study (1-18 yrs) likel y i s deflated by 

including the discrepant results of the 1-5 year olds; and 2) by adjusting 

for factors that covary with air lead (soi l and house dust lead) in the 

analysis, the slope for air lead decreased three-fold from 2.10 to 0.69 in 

the 6-18 year olds. 

4. The inhalation 3 value of 2.46 from Roels et al . (1976) was estimated 

in the CD by adjusting for dust lead levels measured on the children's 

hands. An unadjusted regression analysis by the authors of the combined 

data (1976 through 1980) yielded a 3 value of 5.3 (Roels et al. , 1980). 

Brunekreef (1984) segregated the data and compared groups with large differences 

in exposure (i.e. , <1 km from smelter vs. urban/rural; 3" 5.9) groups with 

small differences in exposure at high exposure levels (i.e. , <1 km vs. 2.5 

km from smelter; 3" 4.6) and groups with small differences in exposures 

at low levels (i.e. , 2.5 km from smelter/urban vs. urban/rural; 3= 13.7). 

The high estimate at the lower exposure level i s influenced by two extreme 

values; removing them leaves a slope of approximately 9.8. As in the 

Brunekreef et al . (1983) study, the use of low-volume samplers may have 

underestimated air lead exposures, and overestimated the 3 value, especially 

for those children near the smelter where large particles predominate. The 

slope may be underestimated for young children, however, since thi s study 

only sampled children older than 10 years of age. Given these different 

factors and analyses, i t i s difficul t to estimate a single aggreyate slope 

from Roels et al . (1976, 1980). I t is clear that a ranye of possible 

slopes for thi s study has been calculated that are dependent on exposure 

levels and adjustments for dust lead, and which are al l yreater than the 

slope for inhaled air lead alone (2.46) cited in the criteri a document. 
P.70 

V-22 

5. Analyses of the Yankel et al . (1977) data adjusted for soil'lead , 

cleanliness, dust, education, and/or pica have yielded inhalation 3 estimates 

ranging between 1.01 and 1.53 at an air lead level of 1..0 pg/m3 (Yankel et 

al. , 1977; Snee, 1982; Walter et al. , 1980; CD, Table 11-39). Brunekreef 

(1984) estimated 3 values between 2.4 and 3.3 depending on age after comparing 

the highest and lowest exposed children's unadjusted PbB levels based on 

the 1974 data. 

The remaining slopes liste d in Table 5-3 are based on data from children 

whose PbB levels , as some in Yankel et al . (1977), exceeded 25 pg/dl . As 

discussed in the CD, the relationship between lead uptake and PbB levels 

above about 30 pg/dl appears to be non-linear (CD, p. 10-31). Because PbB 

levels above 25-30 pg/dl exceed those where health-related concerns are 

triggered (see CD, Chapter 13), these slopes are less relevant to the 

present review. 

In summary, the analyses using the aggregate approach assume the 

same source for most lead in air, soil , and housedust, and that adjustment of 

PbB levels for soi l or dust lead that yields an inhalation slope underestimates the "true" impact of atmospheric lead on PbB levels . A range of 

values can be estimated from a) additional, and apparently relevant, studies 

not used to derive inhalation slopes in the CD (i.e. , Zielhuis et al. , 

1979; Brunekreef et al. , 1981, 1983) and b) aggregate analyses that include 

both direc t (inhalation) and indirec t (via soil , dust, etc.) air lead 

contributions in the key "inhalation slope" studies cited in the criteri a 

document. Although far from conclusive, these studies and analyses suggest 

a range of possible blood lead/air lead aggregate slopes in the range of 2 

to 10 for young, moderately exposed children with the most reliable slopes 

fallin g between 3 and 5 (CD, p. 11-104). 
V-23 

2. Predicting Children's Blood Lead Levels Using Aggregate Model 

To predict PbB levels associated with alternative air lead levels using 

tnese aggreyate slopes, i t is necessary to estimate the contribution to 

total lead exposure from emission sources not subject to control by 

implementiny an air quality standard, for example, lead-soldered food cans, 

lead plumbing, and lead-based paint. I t should be noted that by using 

measured lead concentrations in dust from a wide range of locations and 

conditions, the integrated uptake model discussed in the previous section 

implicitl y includes average contributions to total exposure from lead-based 

paint, but excludes from the analysis high level exposures associated with 

deteriorated lead-based painted housing. 

Several difficultie s arise in attempting to explicitl y estimate 

exposures from non-air sources of lead: 

1) With the exception of non-air lead in diet , few studies provide 

detailed information on the relative contribution of various sources to 

children's PbB levels in the U.S. Estimates must be made Dy inference 

from earlier survey data; and 

2) Because non-air contributions to PbB levels probably vary widely 

in space and time among children, a single estimate for the average case 

may result in a lead NAAQS that is not protective for al l children. [This 

can be expected, for example, for children who regularly ingest lead-based 

paint. ] Conversely, the air standard wil l be overprotective i n areas 

where lead from non-air sources i s below the average. 

In setting the 1978 lead NAAQS, the Agency estimated that non-air 

sources of lead contributed on average, 12 pg/dl to children's PbB levels . 

Since then, significant reductions in PbB levels have occurred, attributable 

not only to declines in atmospheric lead emissions but to the gradual 
P.72 

V-24 

conversion by manufacturers to non-lead soldered cans, in some cases'reduction 

in the number of old , lead-painted homes, cleaner working conditions, as well 

as effort s by parents and public health agencies to minimize children's lead 

exposure. Further declines in lead exposure can be expected by 1990 as these 

trends continue and lead exposure from drinking water drops, due not only to 

increased awareness as a result of widespread, mandated public notifications , 

but to the 1986 Safe Drinking Water Act banning the use of lead solder and 

pipes in new construction and plumbing repairs, and to reductions in water 

corrosivit y by public water suppliers as compliance with the revised national 

water regulations for lead begins. The most recent, and well-conducted, 

nationwide survey of children's PbB levels was the Second National Health and 

Nutrition Evaluation Survey (NHANES II ) of 1976 to 1980. Appendix C describes 

analyses that a) starts with the average PbB level for children from 1978, 

the midpoint of the NHANES I I survey, and b) estimates a 1990 PbB average by 

adjusting the 1978 value to account for the important changes, summarized 

below, in lead exposure that have recently occurred and that can be expected 

to continue: 

1. Use of lead in gasoline has declined by about 90 percent since 

1978; thi s trend wil l continue up through 1990-92 as compliance with the 

lead in gasoline standard i s completed and as the fleet of lead-burning 

cars shrinks. As observed during the NHANES I I survey period (see CD, 

Section 11.3.6), the continued dramatic decline in gasoline lead emissions 

is predicted to parallel a major shif t in PbB levels . 

2. A significant reduction in dietary lead intake has occurred since 

the late 1970's, and thi s trend wil l continue as atmospheric lead emissions 

and deposition, the use of lead-soldered cans, and lead levels in drinking 

water al l continue to decline. 
P.73 

V-25 

» 

The derived ranye of mean PbB levels for children expected in lyyu 

(3.0 - 4.7 py/dl) reflect s chanyes that have occurred since 1978, and that 

are expected to continue, in yasoline lead emissions and deposition and canned 

food technology. Any other changes that are more difficul t to quantify are 

also probably of lesser importance for the bulk of the population, for 

example, any changes in lead-painted housing has not been significant on 

any scale. This range of 1990 "baseline" average estimates represents the 

mean PbB levels that would be expected in 1990 in U.S. children not exposed 

to atmospheric lead from lead point sources directl y or indirectly , based 

on the data and assumptions presented above. 

Another method to estimate children's mean "non-air" PbB i s to use 

available data on typical background levels of lead in food, water, dust, 

and soi l ingested by U.S. children and the relationship between lead 

taken up through these media and children's PbB levels . Table 13-6 of 

the criteri a document uses such data in calculating a mean PbB of 4.42 

pg/dl to be expected at an air lead level of zero. Although thi s value was 

calculated based on 1983-84 FUA data on lead in food, i t i s interesting that 

i t is within the range described above. This range can be used in the 

aggregate model approach to estimate ranges of mean blood lead levels under 

alternative air lead exposures in the following equation: 

mean PbB = (3.0 - 4.7 pg/dl) + (3 - 5 pg/dl per pg/m3) Air Pb 

I t must be emphasized that these estimates for non-air contributions to 

average PbB levels represent average values. Many children may be at risk 

for significantl y higher lead exposures that cannot be prevented Dy atmospheric 

emission controls. In particular, these include children who liv e in 

deteriorated or recently resurfaced lead-painted housing who deliberately or 

inadvertently ingest paint dust through normal mouthing activities , children 
P.74 

V-26 

exposed to hiyh drinking water lead levels from eroding lead pipes or 

solders in distribution systems, children of parents who work in lead-related 

industries and are exposed to lead dust that is subsequently carried home 

on clothing, or children living near lead smelters and other point sources 

where historical accumulations of lead are excessive. It is important that 

other regulatory agencies and public health programs, includiny other EPA 

components, responsible for minimizing children's lead exposures from nonair sources, or from historical accumulations of atmospheric lead deposition, 

maintain or increase, where necessary, their efforts. 
P.75 

V I . VALIDATION OF INTEGRATED LEAD UPTAKE/BIOKINETIC EXPOSURE MODEL 

While al l three modeling approaches identifie d i n Section II I are 

useful in assessing the relative protection afforded by differen t 

lead NAAQS, the aggregate and disaggregate blood lead-air lead models are 

intended to be "equilibrium" models. However, we know that there i s a great 

deal of variation in past and present exposures to lead from various 

sources and pathways. Of the three, the uptake/biokinetic model can best 

estimate the changes over time of blood lead to changes in environmental 

lead in rapidly developing young children. 

A general description of the model i s provided i n Section IV and 

Appendix A. Average dail y uptake for young children i s calculated under 

conditions specified in terms of ambient air lead levels , soi l and dust 

lead levels that correspond to both historical and current atmospheric lead 

emissions, and dietary lead levels from both water and food. Additional 

exposures to paint lead or secondary occupational sources (e.g. , dust 

tracked into homes by workers) can be added. Blood lead (PbB) levels 

i n populations of young children, who are the most exposed and highly 

susceptible to lead, are estimated over time based on tota l dail y lead 

uptake using a biokineti c compartmental model. 

Parameters such as indoor air lead exposure, time spent indoors 

vs. outdoors, absorption rates through the lung or gastrointestinal tract , 

and amount of dir t children that typicall y ingest through hand-to-mouth 

activity , are estimated from available data in the literature , as summarized 

i n Appendix A. 

In thi s chapter, results of several validation exercises where predicted 

and observed blood leads were compared are presented. The most detailed 

analysis was performed with data gathered around a smelter in East Helena, 
P.76 

VI-2 

Montana. Two types of validation effort s were undertaken with thi s data 

set: 1) in the firs t effort , the best data regarding such model parameters 

as observed air, soil , and dust lead exposure estimates were used; 2) in the 

second validation effort , predicted levels of air, soi l and dust levels were 

used to estimate PbB levels . The latte r work was undertaken to determine 

how well the model behaved when actual measurements of necessary input data 

are not available. This was necessary so that the reliabilit y of the model 

could be assessed for policy analysis purposes when less than ful l information 

i s available to use with the model. Also, presented in thi s section are 

validation exercises using observed blood lead estimates in locations other 

than East Helena. While less effort was undertaken in these exercises, 

they nonetheless provide additional information on the reliabilit y of the 

model and provide insight regarding the sensitivit y of the model results 

to uncertainties in the input data. Given the many uncertainties in the 

input data and the biological variabilit y that cannot be incorporated, the 

results of the validation exercises presented below reveal, that the lead 

uptake/biokinetic model perform quite well in predicting mean blood lead 

concentrations in children livin g near point sources of lead. 

A. Validation Using 1983 East Helena Data 

The data set considered firs t i s based on a 1983 study in which the 

Montana Department of Health and Environmental Sciences (MDHES) and the 

Centers for Disease Control (CDC), in cooperation with EPA, measured 

blood lead levels in approximately 400 children ages 1-5 livin g around 

the ASARCO lead smelter in East Helena. The lead content of soi l and 

dusts around and in individual homes was measured. Airborne lead was 

measured before and during the survey at 8 sites . Three study areas were 

designated according to their distances from the smelter: Area 1 , within 
P.77 

VI-3 

1 mile- of the smelter; Area 2, 1-2.25 miles from the smelter; Area 3, 

more than 5 miles from the smelter. The validation exercises included 

children from Areas 1 and 2 only. 

In order to estimate 1983 PbB levels in the East Helena children so 

they could be matched against the measured PbB levels , exposure profiles 

were generated extending as far back as 1978, depending on the children's 

age in 1983 and their residential location. A five-year description of 

monthly ambient air lead concentrations throughout the study area was 

generated in two ways: (1) use of the Industrial Source Complex-Long-Term 

(ISC-LT) dispersion model based on air lead concentrations, source sampling 

data of smelter emissions, and local meteorological data, and accounted for 

dry atmospheric deposition. Area and year-specific estimates of background 

lead contributions (i.e. , mobile sources, re-entrained soil , local minor 

point sources) were also included to account for total ambient exposure; 

and (2)-empirical smooth interpolation of observed concentrations (Marcus, 

1988c). Only one site , about 1/4 mile from the smelter, provided sufficientl y 

complete air quality data over the period 1978-1983 that could be considered 

representative of population exposure in the vicinit y of the monitor 

although air lead data were available from monitors in ten other locations 

around East Helena. 

Estimates of soi l and dust lead concentrations were also obtained using 

two methodologies. In the firs t case, home-specific observed values for 

soi l and dust lead were used. In the second case, soi l and dust lead estimates 

were made using models developed by McLamb (1988) and Marcus (1988c) 

that describe soi l and dust lead as a function of ambient lead. (For a 

description of these models, see Appendix B). The latte r approach was 

deemed necessary to determine how well the model predicts when ful l 
P.78 

VI-4 

information on model inputs i s not available. (This i s indeed the usual ' 

situation when the model i s used to assess the impacts of alternative 

regulatory programs on mean blood leads of a population of children.) 

Age-specific exposure parameters used as input to' the uptake model 

are described in Appendix A. Estimates of dietary lead intake for differen t 

age groups between 1978 and 1983, liste d in Table A-2, were calculated 

through application of the Multiple Source Food Model developed in Chapter 7 

of the CD. The latte r model uses year-specific FDA data on food lead content 

(i.e. , market basket surveys) and age-specific data on dietary patterns 

throughout childhood and has since been validated using recent 1984-85 

data (Flegel et al. , 1988). The contribution of drinking water to dietary 

lead exposure was estimated for an average tap water lead concentration 

of 12 pg/1 , which was the level reported for the State of Montana i n 

1983. 

The criteri a for validation need to be carefully defined. There i s a great 

deal of individual variabilit y i n PbB levels , even with available estimates 

of lead concentrations in exposure pathways such as air, dust, and soil . 

The variabilit y i s attributable to individual biological variation , to 

unknown factors mediating exposure such as frequency of hand-mouth contact, 

and to other unattributed sources of lead. Even with good environmental data, 

the fraction of variance in the logarithm of blood lead that i s accounted 

for by an optimal total uptake regression model (multiple R2) rarely exceeds 

30%. For the East Helena data, R2 = 0.28 in the best fittin g models (Johnson 

and Wijnberg, 1988). Thus, i t does not seem fruitfu l to use the individual 

predicted PbB levels as a criterio n for model validation . We used the more 

realisti c goal of matching the geometric mean PbB for children in a large 

neighborhood that was moderately homogeneous with respect to exposure. 
P.79 

VI-5 

A,more global validation involves comparing the cumulative distributio n 

function of observed PbB with that of the individual PbB estimates from the 

uptake/biokinetic model. These comparisons from the differen t validation 

runs are presented in Table 6-1 and in Figures 6-1 and 6-2. 

The simulations were al l run at two levels , one with al l parameters 

set to the lower bounds for uptake parameters in Appendix A, and the second 

with al l parameters set to the upper bound levels in Appendix A. The 

midpoint of the all-lower and all-upper bound PbB estimates, i.e. , the 

simple mean was found to be the best predictor. 

In model run A, only observed values for air, soi l and dust input 

data were used. This data set was limited to the 28 observations near the 

smelter where an ambient monitor was within a few blocks of the homes. 

The second model run includes observations on 299 children. This expanded 

data set was obtained by using dispersion modeling techniques to estimate 

block specific ambient exposure estimates.* Comparisons between runs A and B 

illustrat e that accurate PbB reductions result from using either observed 

or estimated ambient air data. Run C, lik e run B, has 299 observations. 

However, in the latte r model run, observed measures of household-specific 

soi l and dust lead are replaced with estimates obtained from equations 

that explain soi l and dust lead levels as functions of ambient lead (see 

Appendix B). Also, while model run C uses dispersion model estimates 

of ambient concentrations, as does model run B, the source of meteorological 

1 A similar validation exercise was conducted previously where average 

PbB levels predicted by the uptake/biokinetic model for differen t census 

tract s were compared to measured PbB levels in 1-5 year olds livin g near 

two secondary lead smelters and in a reference area, in Dallas. Results 

were useful in indicating that greater refinement in the spatial scale 

would be necessary in accurately modeling high exposure situations . 

For the East Helena analysis, and in subsequent case-study modeling, 

the highest degree of spatial refinement possible (i.e. , cit y blocks or 

block groups) i s used. 
TABLE 6-1. COMPARISON OF INTEGRATED LEAD UPTAKE/BIOKINETIC MODEL PREDICTIONS 

TO 1983 MEASUREMENTS IN EAST HELENA 

Model 

Run Population3 Pb Air Quality Dust/Soil Lead 

Predicted vs. Measured 

Average Blood Leadb and GSDC 

A 28 children livin g in 

area 1 around single 

air monitor with 

valid data 

Measured at monitor 

approx. 1/4 mile from 

smelter 

Measured in and 

outside individual 

homes 

16.3 vs. 16.5 pg/dl* 

1.42 vs. 1.49 

89 Area 1 and 210 

Area 2 Children 

89 Area 1 and 210 

Area 2 Children 

Contribution from 

smelter enission 

estimated by dis -

persion model (local 

meteorology data) 

local background Pb 

levels (e.g.,' auto 

anissions, fugitiv e 

dusts) estimated 

from 1982 source 

apportionment study 

Same as for Run B 

except that di spersion modeling 

used meteorological 

data from a nearby 

ai rport 

Measured in and 

outside individual 

homes 

Estimated from 

generalized air: 

soil/dus t Pb 

relationships from 

regression analyses 

of available data in 

literatur e 

9.3 vs. 9.3 pg/dl* 

1.61 vs. 1.59 

i 

cr\ 

9.5 vs. 9.3 pg/dl* 

1.67 vs. 1.69 

Note: Dietary Pb exposure estimated for al l model runs based on year-specific analyses of 1980's FDA food 

concentration data and food consumption data from Penninyton (1983, 1986), and U.S.D.A. Nationwide Food 

Consumption Survey, 1977-78. 

aAreas as defined i n the text 

bGeometric means 

cGeometric Standard Deviation 

*A11 differences statisticall y insignificant ; t-test s of differences of means assuming lognormal blood lead 

distributio n and non-equal variances. 

lead 

oo 

o 
PM 

VI-7 

100 

90 -

UJ 

80 

70 

60 

| 50 

CC 

UJ 

Q. 

40 

30 

20 

10 

"I 1 L-.-4-* I 

O - MODEL ESTIMATE 

• - OBSERVED 

I _L J_ 

10 20 30 40 

BLOOD LEAD CONCENTFIATION, ng/dl 

50 60 

FIGURE 6-1. COMPARISON OF DISTRIBUTION OF MEASURED BLOOD LEAD LEVELS 

IN CHILDREN, 1-5 YEARS OF AGE, LIVING WITHIN 2.25 MILES OF E. HELENA 

LEAD SMELTER VS. LEVELS PREDICTED BY UPTAKE/BIOKINETIC MODEL. MEASURED 

SOIL AND DUST LEAD LEVELS WERE INCLUDED IN ESTIMATING UPTAKE LEVELS. 

(RUN B) 
P.82 

'•» • "• I Wf 

VI-8 

UJ 

100 

90 -

80 -

70 

60 

I-

| .50 

CC ' 

UJ 

Q. 

40 

30 

20 

10 -

_ » » m » * * ~ ~ ' ' 

O - MODEL ESTIMATE 

• - OBSERVED 

_L 

10 20 30 40 

BLOOD LEAD CONCENTRATION, Hg/dl 

50 60 

FIGURE 6-2. COMPARISON OF DISTRIBUTION OF MEASURED BLOOD LEAD LEVELS 

IN CHILDREN, 1-5 YEARS OF AGE, LIVING WITHIN 2.25 MILES OF E. HELENA 

LEAD SMELTER VS. LEVELS PREDICTED BY UPTAKE/RIOKINETIC MODEL. ESTIMATED 

SOIL AND DUST LEAD LEVELS FROM GENERALIZED RELATIONSHIPS WERE INCLUDED 

IN ESTIMATING UPTAKE LEVELS. (RUN C) 
P.83 

VI-9 

data i s different : Run B uses local meteorological data, and run C uses 

airport data. This difference allows runs B and C results to be compared 

to assess how sensitive blood lead estimates are to less location-specific 

meteorological data. 

In conclusion, generally satisfactory results were obtained for 

predictiny geometric means. Model run A can be considered a "pure" 

validation run that uses the best input data available to predict 

mean blood leads which can be compared to mean observed blood leads. 

Model runs B and C were necessary validations since exact population 

locations, local meteorology, and soi l and dust lead data wil l rarely be 

available for point source areas where the model wil l be used for policy 

analysis. Therefore, Run C can be considered a "generalized methodology" 

for "export" or application to other study areas. 

Although the differences between observed and predicted mean PbB levels 

are not statisticall y significant , post hoc calibration of the model to remove 

any differences was considered (Marcus and Holtzman, 1988). Both linear 

and nonlinear models were examined and i t was found that calibrated 

models (including age-dependent ones) improved predictive abilit y of the 

model only marginally. One alternative i s to simply subtract the difference 

between observed and predicted PbB levels in the generalized methodology 

Run C ( =0.2 pg/dl) or use a multiplicativ e factor (the latte r probably 

more appropriate given the lognormality of the PbB distribution). Such a 

calibration based on the results of a single, albeit large and detailed, 

validation may be inappropriate, especially considering the uncertainties 

inherent in such modeling exercises (e.g. , a "positive" calibration may 

be needed in a differen t location). Given these uncertainties, no post 

hoc calibration of case study exposure estimates i s currently being 

proposed althouyh such an adjustment could easily be accommodated i f 
P.84 

VI-10 

decided upon. 

Several sensitivit y runs were made in order to "fine-tune" various 

parameters for which data are incomplete such as age-specific dir t 

consumption rates and gut absorption rates for ingested lead. For example, 

in estimating the rate by which ingested lead i s absorbed, the criteri a 

document identifie s many factors that have to be considered, among them 

person's age, physiological status, medium for the lead (e.g. , food vs. 

paint or "dirt") , coincident ingestion of other elements in food (e.g. , 

calcium) which compete with lead for intestinal absorption sites , and the 

non-linear relationship between lead intake and blood lead (due for example 

to a saturable gut absorption pathway). Differences may also be attributable 

to physical or chemical differences in bioavailabilit y of deposition from 

smelter anissions, or to the higher rate of intake in these areas compared 

to typical situations . 

In fact , there are reasons to believe that such differences must exist 

in East Helena. The lead-bearing particles that are deposited near the 

smelter are probably larger particles from fugitiv e emissions (e.g. , erosion 

from tailing s piles , loading operations) whereas the more distant deposits 

are predominantly smaller particles from stack emissions. Yet another 

factor i s that parents of children who lived closer to the smelter (e.g. , 

Area 1) may have been more sensitized to lead exposure and thus tended 

to control access to leaded soi l and dust more than parents in Area 2). 

To test this , we ran the model with 20% gut absorption of dir t lead in Area 1 

and 30% absorption in Area 2. 

Two additional runs were made i n which the same absorption factor, 

either 25% or 30%, was used for both areas. Area-specific results of the 

20% (Area 1) / 30% (Area 2) model were not significantl y differen t from the 
P.85 

VI-11 

observed geometric means. Likewise, using a 25% absorption factor for both 

areas yielded no significant difference between predicted and observed 

geometric means for the overall study area. Results using the 3U% rate 

cited In the CD based on indirect chemical and animal experiments were 

not as concordant. Because of the programming complexities that would be 

introduced i f dual absorption rates were used in al l other applications 

of the model, a 25% absorption rate i s chosen for general use since i t 

yielded adequate overall results . 

As indicated in Section III , the model should be regarded as valid for 

estimating mean responses and i t does appear that with the correct range of 

soi l and dust lead inputs, the model adequately predicts the geometric mean 

of the observed distribution . Estimation of the hiyher percentiles of the 

PbB distributio n requires application, to the yeometric mean, of a GSU from, 

for example, NHANES I I or exposure surveys around differen t point sources. 

B. Application of Uptake/Biokinetic Model to Other Data Sets 

There are other published data to test the uptake/biokinetic 

model at other U.S. locations and times. One data set was collected in 

Omaha, Nebraska, from 1971 to 1977 (Angle and Mclntire, 1979; Angle et al. , 

1984). Another data set was collected throughout Silver Valley, Idaho, in 

1974-1975 and i s described in Yankel et al . (1977), and Walter et al . (1980) 

with additional information given in the CD. 

1. Omaha Data 

The Omaha study measured blood leads in 242 children ages 1-5 years 

and 832 children ages 6-18 years. The children were at 3 locations, denoted 

C (commercial area near a small battery plant), M (mixed residentialcommercial), and S (suburban). Air lead, soi l lead, and house dust lead 
P.86 

VI-12 

measured in each area are incorporated into the model to estimate average 

dail y lead uptake levels . These data are less satisfactory for 

testing the model than the East Helena data because the soi l and dust 

lead measurements are not specific to each household where blood leads 

were taken. Furthermore, the study was not designed for controlled 

geographic comparisons given the significant demographic difference 

between areas in SES, housing, and racial composition. Age-specific 

dietary lead intakes were estimated based on 1970's data from the FDA and 

Jelinek (1982) as re-analyzed in the CD. In Table 6-2, the observed 

geometric mean blood lead levels for 1-5 year olds are compared to predicted 

mean PbB levels for 2-year olds in the suburban and mixed areas (blood 

lead data for 1-5 year olds were not reported for the commercial area). 

The model appears adequate for the suburban site , while average blood 

lead estimated from reported soil , dust, and air lead concentrations i s 

significantl y underpredicted for the "mixed" site . 

There are several factors that may explain the contrast in PbB 

levels between the areas despite the apparent similaritie s in environmental 

lead levels , for example: 

1) Air lead levels in the mixed area were apparently much higher than 

the suburban sit e in years prior to 1972 when soil , dust, and blood lead 

measurements were taken (e.g. , 1.44 pg/m3 in mixed vs. 0.73 pg/m3 in 

suburban in 197U). Thus, the higher blood leads in the mixed area may 

reflec t higher historical exposure; 2) The population i n the mixed area 

was predominately black with a large percentage of substandard housing 

compared to the suburban area which was predominately white. Blood lead 

levels are highly dependent on demoyrapnic variables such as SES, race, 

housiny conditions, parental care and nutrition , al l of which were likel y 
TABLE 6-2. CHILDREN'S BLOOD LEAD LEVELS MEASURED IN OMAHA, 1971-1977 VS. INTEGRATED 

UPTAKE/BIOKINETIC MODEL PREDICTIONS 

Average Air Lead (pg/m3) 

Average Soil Lead (ppm) 

Average House Dust Lead (ppm) 

Observed Mean PbB (pg/dl) 

1-5 yr . olds 

Predicted Mean* PbB (pg/dl) 

2 yr . olds 

"Mixed" Site 

0.26 

213 

653 

25.6 

20.2 

Suburban Site 

0.37 

110 

567 

14.6 

15.1 

Estimated Dietary Lead Uptake (pg/day) for 

both sites during early 1970's (see text) 

0-1 yr. olds 

1-2 yr . olds 

2-3 yr. olds 

16.3 - 20.6 

20.2 - 25.6 

16.6 - 22.1 

< 

M 

I 

^Predicted mean PbB represents midpoint of lower and upper bound means estimated by model 
P.88 

VI-14 

to have had systanatic interactive influences in the Omaha study areas; 

3) Other unmeasured variables may have differed between the areas such as 

drinking water levels (older homes in mixed area may have had lead plumbing), 

paint lead, frequency of canned foods in diets ; 4) Possible measurement 

error related to the fact that most housedust samples were collected from 

vacuum cleaner bags. There may have been differences between areas in 

floor surfaces (carpet vs. wood) or frequency of vacuuming, for example. 

2. Silver Valley Data 

The Silver Valley study of 1974 and 1975 covered 860 children ages 

1-9 years livin g near the lead smelter in Kellogg, Idaho and surrounding 

regions. PbB levels were quite hign for children nearest the smelter. 

Household dustiness, soi l lead, and estimated or observed air lead concentrations 

were obtained for 9 zones around the smelter and used to calculate daily 

lead uptake levels . As for the Omaha comparison, dietary lead intakes 

were calculated from 1970's data analyzed in the criteri a document. The 

geometric mean values by zone are shown in Table 6-3, along with predicted 

mean PbB using the uptake/biokinetic model.- Results are generally adequate 

for the more distant areas with lower exposure levels . This i s the 

intended range of applicabilit y of the model. I t i s not surprising that 

blood leads are overpredicted i n areas I and I I located closest to the 

smelter. The Harley and Kneip compartmental model's presumption of linear 

kinetics in lead absorption, excretion, and accumulation, while appropriate 

at relativel y low to moderate exposures i s not applicable for such extraordinaril y nigh exposure levels as observed in these two areas. Some 

adjustment for the non-linear patterns of lead uptake would be necessary in 

order to reliabl y model PbB levels in locales with such extremely high 
TABLE 6-3. CHILDREN'S BLOOD LEAD LEVELS MEASURED IN SILVER VALLEY, MONTANA 1974-1975 VS. INTEGRATED 

UPTAKE/BIOKINETIC MODEL PREDICTIONS 

Average Air Lead (pg/m3) 

Average Soil Lead (ppm) 

Average House Dust Lead (ppm) 

Observed PbB (pg/dl) 

2-yr. olds 

Predicted Mean PbB* (py/dl) 

2-yr. olds 

Area I_ 

16.8 

7,470 

11.7U0 

II_ 

14.2 

3,300 

10,30U 

III 

6.6 

1,250 

2,400 

IV_ 

3.0 

1,400 

3,3U0 

y_ 

0.7 0 

2,300 

3,400 

yj_ 

0.5 

337 

1,800 

VII 

0.5 

700 

3,900 

72 

88.5 

51 

74.1 

36 

28.4 

36 

33.7 

35 

34.6 

26 

22.3 

35 

35.8 

Estimated Dietary Lead Uptake (pg/day) for 

al l sites during early 1970's (see text) 

0-1 yr . olds 

1-2 yr. olds 

2-3 yr. olds 

16.3 - 20.6 

20.2 - 25.6 

16.6 - 22.1 

< 

M 

I 

r— 

U l 

*Predicted mean PbB represents midpoint of lower and upper bound means estimated by model. 
P.90 

VI-16 

air, soil , and/or dust lead concentrations. 

3. Other Data 

Unpublished analyses by Phillips and Vornberg et al . (1986) for 

populations livin g near a large industrial lead source in Herculaneum, 

Missouri, and have similarl y provided fairl y good validation for the 

uptake/biokinetic model, especially when measured soi l and dust lead 

values were available. 

C. Conclusions 

The above discussion illustrate d several validation exercises that were 

undertaken to refine data inputs and to assess the reliabilit y of the blood 

lead uptake/biokinetic model. The East Helena analysis was by far the 

most intensive effort . The results of the analysis indicated that the model, 

usiny the best available and location-specific input data, predicted overall 

means essentially identical to the observed blood leads. When usiny less 

location-specific input data (that i s generally available for policy analyses), 

the model predicts mean PbB levels within 2 percent of observed. Other 

validation efforts , though undertaken with less effort , of data from 

Omaha and Silver Valley also support the hypothesis that the uptake/biokinetic 

model i s reasonable for estimating blood leads when actual observations 

are not available. Other independent validation effort s by TRC have also 

provided general support for the efficacy of the model . 
P.91 

VII . CONCLUSIONS AND APPLICATIONS OF LEAD EXPOSURE MODELING 

Because of the pervasiveness of lead in the environment, a larye number 

and variety of exposure situations require some understanding not only in 

terms of present risks but for predicting hazards under future regulatory/ 

abatement alternatives . More than perhaps any other environmental contaminant, a wealth of information has accumulated not only on lead toxicit y 

but on lead exposure as well . This report has attempted to utiliz e the most 

reliable of that information to develop multi-media exposure methodoloyies to 

assess risks associated with alternative lead NAAQS and which can be applicable 

to other lead exposure scenarios. For example, blood lead levels in children 

exposed to different drinking water concentrations have been estimated in 

EPA's recent review of the lead in drinking water regulation by adopting 

both the disaggregate and the uptake/biokinetic modeling approaches. 

Each of the three approaches described here has both advantages and 

uncertainties. The aggregate model, for example, allows for a straightforward conversion of air lead concentration changes to the range of expected 

impacts on children's blood lead levels through direc t and indirec t sources. 

However, projecting in thi s approach what contribution non-air sources of 

lead wil l make to future PbB levels requires fairl y good data on current 

exposures as well as trends in different exposure sources. Also, since soi l 

lead changes relativel y slowly in response to decreases in air lead, the 

change in blood lead calculated from the aggregate model may not be achieved 

for a very long time. The disaggregate model, with rapid change in dust 

lead and slower change in soi l lead, may be a more accurate predictor 

of near-term effects of air lead changes on blood lead levels . The uptake/ 

biokinetic model, as with the other approaches, also must rely on incomplete 
P.92 

VII-2 

data in some cases and because of it s assumptions of linear absorptibn and 

biokinetics , i s limited to predicting relativel y low level exposures (i.e. , 

< 25-30 pg/dl). The model's mathematical assumptions and numerical parameters, 

however, combine plausible biological hypotheses, animal experimental data, 

and results of observational studies. Further, i t allows explici t projections 

of future lead concentrations in various media and in turn estimations of 

the impacts of these different changes on different age groups of children. 

I t is thi s flexibilit y that makes the integrated uptake/biokinetic model 

adaptable for a wide range of predictive exposure assessments and why i t 

was the focus of the validation exercises described in Section VI . 

Results of the different validations indicate good concordance between 

observed and predicted average PbB levels in children livin g near lead point 

sources. The model can also be a useful tool in estimating PbB levels in 

children livin y with different lead hazards, such as heavily contaminated 

soils from historical deposition near major urban roadways or closed smelters 

or mines. Ongoing regulatory effort s by differen t components of EPA to 

control concentrations of lead in air, water and soi l have created a significant 

need to model blood lead concentrations that delineates specific routes of 

lead exposure. At present, only the uptake/biokinetic model provides such 

specificity . Furthermore, such a model must be capable of simulating blood 

lead levels under future as well as historicall y known exposure regimes. 

(The validation effort s described in the previous section used historical 

data to test and improve the predictive abilit y of the model.) In fact , an 

earlier but similar version of the uptake/biokinetic model has been applied 

to assessments of Boston soi l contamination (Beck and Tsai, 1987), exposures 

around the Herculaneum, Missouri smelter (Phillips and Vornbery et al. , 

1986) and historical contamination of soils near the Bunker Hil l smelter in 
P.93 

VII-3 

Kellogg, Idaho and as part of EPA's Integrated Environmental Management 

Program in their effort s to develop and apply methodologies to establish 

public health and environmental priorities . 

The uptake/biokinetic model i s stil l being assessed and validation 

tests wil l continue as new data are available. In particular, adjustments 

of dir t ingestion rate and dir t lead absorption may be desireable in 

calibrating the air, dust, and soi l lead slopes relative to observed regression 

models. The empirical multiple regression methods used in the disaggregate 

models may also need refinement, e.g. , by use of structural equation analyses 

that extend the statistica l methods used by the Cincinnati Lead Program 

Project (Clark et al. , 1987). 
P.94 

APPENDIX A. ESTIMATES OF LEAD UPTAKE 

For each of the numbered lines in Table 4-1 in the integrated lead uptake/ 

biokinetic model, the assumptions and estimates used in calculating average 

lead uptake for children from the various exposure pathways are discussed 

in the correspondingly numbered paragraphs below. Table 4-1 only illustrate s 

calculations for 2-year old children; in order to estimate exposures 

throughout childhood, age-specific exposure parameters are necessary in 

several cases. These are also described below. 

1. Outdoor air lead: In the case-study exposure analyses of alternative , 

future regulatory scenarios, ambient air lead concentrations wil l be assigned 

to populations livin g in different locations, or "receptor points." Locations 

wil l be defined as block group centroids - i.e. , subdivision of census tracts . 

Air lead levels wil l be yenerated around individual lead point sources through 

use of the Industrial Source Complex-Long-Term (ISC^-LT) dispersion model, 

based on site-specifi c operating parameters, emissions (both stack and fugitive) , 

and meteorological data. Background lead concentrations from mobile sources, 

re-entrained soil , and local , minor point sources wil l also be included. The 

air lead concentrations specified in Table 4-1 do not represent exposure 

scenarios for alternative lead NAAQS but starting points to illustrat e how 

dail y lead uptake estimates are made. 

2. Indoor air lead: The penetration of atmospheric lead into residential 

structures depends on the size of the lead particles , meteorological conditions, 

and the permeability of the windows, doors, and walls of the home. A range 

of indoor/outdoor ratios has been found (0.3-0.8) for different citie s and 

structures (CD, Table 7-6). Near point sources where large airborne particles 

are more prevalent and infiltratio n into homes i s low, the ratio appears to 

be closer to 0.3 (Cohen and Cohen, 1980). 
P.95 

A-2 

3. Time spent outdoors: The amount of time spent between indoor and 

outdoor environments varies among young children depending on their stage 

of development (i.e. , infant , toddler, pre-school), season, geographical 

location, and family behavior. A range of 2-4 hours per day spent outdoors 

(and therefore 20-22 hours spent indoors) is considered a reasonable average 

for a 2-year old . The following age-specific estimated ranges for hours spent 

outdoors were derived from informal surveying of parents: 

age (years): 0-1 1-2 2-3 3-7 

time spent ~L 173 tt 2^5 

outdoors 

(hrs/day): 

4 . Time weighted air lead concentrations for each level i s estimated 

by: [(outdoor concentration x time spent outdoors) + (indoor concentration 

x time spent indoors)] * 24 hours. 

5. The volume of air breathed each day i s dependent on age, body 

size, lung capacity, altitude , and activit y of the child . For instance, 

ventilatory volume can increase three-fold during strenuous exercise 

(Cotes, 1979). Phalen et al . (1985) determined average ventilation rates 

for males and females from birt h through age 18 from graphical fit s of 

published tabulated data (Altman and Dittmer, 1971, 1972). For example, 

a two-year old at "low activity " i s estimated to have a minute ventilation 

rate of 2.75 liters/minute, which corresponds to an average daily rate of 

approximately 4 m3/day while a three-year old i s estimated to have a dail y 

rate of 4.3 m3/day. Other estimates that appear in the literatur e are 

4.7 m3/day (ICRP, 1975) and 4 to 6 m3/day (Nutrition Foundation, 1982) for 

active one-year olds, and 4.7 m3/day for a three-year old (Nutrition 

Foundation, 1982). These values combined with those determined by Phalen 
P.96 

A-3 

et al'. , and scaling factors based on body size are used to construct tne 

following ranges for average aye-specific daily ventilation rates. 

Aye (years): 0-1 1-2 2-3 3-4 4-6 5-6 6-7 

Ventilation Rate 

(m3/day): 2-3 3-5 4-5 4-5 5-7 5-7 6-8 

6. The ranye of total lead intake by inhalation for each air lead 

level is computed by multiplyiny both the estimated upper and lower bound 

time-weighted average concentrations of air lead by upper and lower bound 

estimates of the volume of air respired per day. 

7. Respiratory deposition and absorption: Only a portion of inhaled 

lead i s deposited in the lungs and subsequently absorbed into the bloodstream. 

The deposition efficiency of lead particles depends primarily on their size 

and the physiology and rate of breathing of the individual. Available data 

on lead particl e size distributions , particle deposition patterns in the 

lung, and respiratory absorption of lead particles were used to estimate 

deposition efficiencies of airborne lead particles in youny children 

(Cohen, 1987). A respiratory deposition/absorption rate of 2b to 45% i s 

calculated for youny children livin y in non-point source areas, while a 

rate of 42% i s calculated for those livin y near point sources. 

8. Total lead uptake from the air i s the product of tota l intake 

and the lung deposition/absorption factor. 

9. Average dietary lead consumption: Given the wide spatial and temporal 

distributio n of food in thi s country, i t appears reasonable to assume that 

even people livin g near industrial lead sources receive roughly typical 

lead levels from their diet . Any variabilit y due to local contamination of 

garden crops or kitchens near point sources can be factored in separately. 
P.97 

A-4 

As noted in Section II.D. , the Multiple Source Food Model developed in the 

CD has been validated and updated using the most recent food data from 1984 

and 1985 (Flegel et al. , 1988). Further declines in dietary lead intake 

are expected as a result of continuing reductions of lead in canned foods, 

gasoline anissions, and lead in drinking water. Cohen (1988), uses available 

data on these downward trends and information from the Multiple Source 

Food Model on food consumption patterns, lead content of various foods, 

and source-specific contributions to project 1990-96 dietary lead intake 

estimates for differen t age groups of children. The age-specific estimates 

from Table 5 of Cohen (1988) shown below, as Table A-l wil l be incorporated 

into the integrated uptake model to predict 1990-96 PbB levels among children. 

Similar dietary lead intake estimates were made for 1978-83 for purposes of 

validating the uptake/biokinetic model (See Section VI). These are shown in 

Table A-2. 

10. Gut absorption of dietary lead: Only a portion of ingested lead 

i s absorbed into the bloodstream from the gastrointestinal (GI) tract , 

or gut, and i s dependent upon the composition of the diet and physiological 

status of the individual . Based on measurements, mainly among infants , of 

lead in the diet and excreta, a gut absorption rate for ingested dietary 

lead between 42-53% has been calculated (Alexander et al. , 1973; Ziegler 

et al. , 1978). Corresponding rates between 7 and 15% have been estimated 

from adult studies (Kehoe, 1961; Chamberlain et al. , 1978; Rabinowitz 

et al. , 1980). Following the approach used by Harley and Kneip (1985), 

these rates were assumed for infants and adults and smoothed to yiel d 

values for intermediate ages, as follows: 
P.98 

A-5 

TABLE A-l . AGE-SPECIFIC ESTIMATES OF TOTAL DIETARY LEAD INTAKE (pg/day) FOR 1990-1996 

Age (years) 

<1 

1 

2 

3 

4 

5 

6 

Metallic 

2.6 

3.0 

4.0 

4.0 

4.0 

4.1 

4.2 

Atmospheric 

0.8 

1.1 

1.2 

1.2 

1.1 

1.2 

1.3 

Other 

3.3 

3.8 

3.6 

3.7 

3.8 

4.0 

4.3 

Total 

6.7 

7.9 

8.8 

8.9 

8.9 

9.3 

9.8 

Source: Cohen (1988) 

TABLE A-2. TOTAL DIETARY LEAD INTAKE (pg/day) FOR 1978-1983 FOR FIVE AGE 

GROUPS OF CHILDREN3 

Age (years) 1978 1979 1980 1981 1982 1983 

1-2 

2-3 

3-4 

4-5 

5-6 

45.8 

52.9 

52.7 

52.7 

55.6 

41.2 

48.0 

47.8 

47.8 

50.3 

31.4 

36.9 

36.9 

36.9 

38.7 

28.8 

33.8 

33.7 

33.8 

35.5 

26.0 

30.6 

30.6 

30.7 

32.2 

19.3 

24.1 

23.0 

22.0 

23.2 

a

From Sledge (1986) -- calculated using year-specific FDA data on food lead 

content and Multiple Source Food Modeling methodology described in 

Chapter 7 of CD. Assumes average drinking water lead concentration at the 

tap of 12 pg/1 . Used in validation exercises described in Section VI . 
P.99 

A-6 

Age: 0-1 1-2 2-3 3-4 4-5 5-6 6-7 

Average GI 42-53 42-53 30-40 30-40 30-40 30-40 18-24 . 

Absorption Rate (%): 

These rates do not reflec t the wide degree of inter-subject variabilit y 

observed in the studies nor other factors that influence absorption in 

children. (Such variabilit y wil l be accounted for in calculating population 

distributions of PbB levels around estimated average PbB levels usiny 

empirically-derived geometric standard deviations). For example, absorption 

rates 2 to 4 times higher were observed in adults following fasting periods 

of 4 to 16 hours (Blake, 1976; Chamberlain et al. , 1978, Heard and Chamberlain, 

1982; Rabinowitz et al. , 1980). Such increases can be expected among children 

who skip meals, a particular problem among lower income groups (Koh and 

Caples, 1977). Regular eating patterns do not insure minimized dietary lead 

absorption, however. Based on several animal studies, clinica l investigations , 

and epidemiological surveys, children with diets deficient in calcium, iron , 

phosphate, zinc, copper, vitamin D, protein, lipids , or lactose can be expected 

to absorb and retain lead to a greater degree (CD, Table 10-4). 

This phenomenon may partiall y explain the enhanced neurotoxicity of 

lead in animals with nutritional deficit s (Mahaffey and Michaelson, 1980). 

The importance of nutritional interactions with lead absorption and possibly 

toxicit y is particularl y significant for young children because of their large 

fluxes in relative nutrient status. Althouyh nutritional deficiencies are 

more pronounced among lower income children, they exist in children of al l 

socio-economic strata (CD, p. 10-41). 

1 1 . Daily dietary lead uptake i s obtained by multiplying rows 10 and 9. 
P.1 

A-7 

12. and 13. Dust/soil concentrations: As discussed in Section II , the 

accumulation of lead in street and household dusts and soils appears to be 

directl y related to the volume of traffic , and inversely related to distance 

from neighborhood streets and roads, distance from lead based painted and brick 

houses and buildings , and distance from lead point sources. Predicting a 

relationship between differen t air lead levels and dust and soi l lead 

levels over time would require the inclusion of many complex variables such 

as deposition rates, chemical and physical characteristics of the lead particles 

and soils , topographic and meteorological conditions, frequency of street 

washings and precipitation , background dust concentrations, and information 

on transport of dust and soi l into homes and buildings. Given current data, 

there would be an extremely large amount of uncertainty surrounding any one 

of these variables for different locations. In order to predict outdoor and 

indoor dust concentrations under alternative air lead concentrations, reliance 

i s placed on available studies that include measurements of both air levels 

and dust and/or surface soi l concentrations (see Table A-3). 

Because of historical accumulations of relativel y large lead particles 

near primary and secondary lead smelters and other point sources, outdoor 

soi l and dust lead concentrations, and consequently potential exposures, 

are significantl y greater in these areas, regardless of ongoing emission 

controls. This i s the main reason why separate exposure estimates for individuals 

livin g near point sources under alternative air lead levels are required. 

Data collected near lead point sources where anissions were comparable to 

current situations are used to develop outdoor soil/dust lead levels for 

point sources meeting differen t air lead concentrations (see Appendix B). 

Several of the studies for which data are not used to develop relationships 

require comment: a) Barltrop et al . (1975) surveyed a rural distric t in 
P.2 

A-8 

TABLE A-3. SUMMARY OF ENVIRONMENTAL LEAD MEASUREMENTS FROM VARIOUS LOCATIONS 

Average 

Air Lead 

(pg/m3) 

Average Surface 

Soil/Outdoor 

Dust Lead3 

(U9/9) 

Average Housedust 

Lead 

(pg/g) Location/Reference 

0.20 

0.40 

0.29 

0.61 

0.28 

0.34 

1.6 - 2.0 

1.5 

43 

336 

416 

912 

518 

4,881 

1,200 

425 

1 

11 

70 

190 

-

565 

,803 

,000 

-

Various Sites in U.K. 

(DOE, 1983) 

Two English towns 

(Barltrop et al. , 1974) 

Derbyshire, U.K. (lead mining 

area) (Barltrop et al. , 1975) 

Hartford (Lepow et al. , 1975) 

Below elevated London roadway 

(Barltrop and Strehlow, 1976) 

0.73 

0.76 

1.11 

1.25 

1.76 

230 

452 

318 

386 

621 

Throughout Chicago suburbs with 

major roadways 

(Jansen et al., 1977) 

0.22 

0.04 

0.32 

0.46 

0.30 

0.45 

0.8 

3.67 

80 

91 

591 

260 

114 

112 

466 

2,560 

215 

162 

280 

470 

"Post-control" 0 (1973-ly76) 

measurements in Omaha 

neighborhoods: 

suburban 

mixed (battery plant in residential neighborhood) 

commerci al 

(Angle and Mclntire, 1979; 

Angle, 1985) 

"Post-control" 0 measurements (1976) 

in rural area, Brussels, and near 

lead smelter, Belgium (Roels et 

al. , 1980) 

0.41 

0.82 

3.01 

- 2.0C 

690 

240 

924 

2,416 

1,214 

698 

253 

(street dust) 

(soil) 

(<1.6 km) 

(1.6 - 3.2 km) 

(>3.2 km) 

1,239 

713 

1,550 

Near Arnheim secondary lead 

smelter, Holland (Brunkreef et 

al. , 1981; Diemel et al. , 1981) 

Near Toronto secondary lead smelters 

and in cit y (Roberts et al. , 1974) 

Various distances from a lead-zinc 

smelter in Britis h Columbia 

(Schmitt et al. , 1979) 
P.3 

TABLE A 

• 

Average 

Air Lead 

(ug/m3) 

0.13 

0.20 

0.30 

0.31 

0.14 

0.18 

0.09 

0.26 

0.09 

0.11 

0.19 

0.26 

0.36 

0.56 

0.13 

0.28 

1.3 

2.7° 

0.5 

0.5 

0.7 

3.0 

6.6 

14.2 

16.8 

0.3 

0.8 

1.9 

2.9 

3.6 

- 3 . SUMMARY OF 

Average Surfac 

Soil/Outdoor 

Dust Lead3 

(ug/g) 

35 

243 

829 

821 

75 

115 

294 

424 

58 

65 

77 

95 

532 

117 

326 

331 

427 

948^ 

337 

700 

2,300 

1,400 

1,250 

3,300 

7,470 

200 

158 

307 

1,345 

1,549 

A-y 1 ' 

ENVIRONMENTAL LEAD MEASUREMENTS FROM VARIOUS LOCATIONS 

(Continued) 

e 

Average Housedust 

Lead 

(ug/g) 

241 

409 

386 

441 

235 

164 

210 

398 

75 

60 

65 

116 

263 

201 

198 

438 

1,479 

8,623d 

1,800 

3,900 

3,400 

3,300 

2,400 

10,300 

11,700 

501 

398 

891 

1,585 

2,284 

aSurface soi l measurements represent top 0 - 2.5 cm. 

°"Post-control" 

controls at the 

control" refers 

refers to the p 

Location/Reference 

Distance range (km) from 

zinc or copper smelters in : 

(3.5 - 24.0) 

(1.3 - 3.7) Bartlesville , OK; 

(0.8 - 4.3) 

(0.8 - 1.5) 

(10.0 - 26.0) 

( 3.5 - 21.0) Anaconda, MT; 

( 2.0 - 11.0) 

( 2.0 - 3.5) 

( 3.4 - 68.0) 

( 1.0 - 6.4) Ajo, AZ; 

( 0.5 - 2.3) 

( 0.5 -. 1.3) 

(11.0 - 26.0) 

( 5.4 - 14.5) Palmerton, PA 

( 3.3 - 9.9) 

( 0.3 - 2.8) 

(Hartwell et al. , 1983) 

Near El Paso primary lead smelter 

"Post-control" 0 

"Pre-control" (Landrigan et al. , 

1975; Morse et al. , 1979) 

Near Silver Valley, Idaho, primary lead 

smelter; Pre-control ° (Yankel et al. , 

1977; Idaho Dept. Health and Welfare, 

1977) 

Near E. Helena primary lead smelter 

(CDC, 1983) 

eriod of time following the application or increase in emission 

lead point source(s) involved in the 

to the period 

cAnnual mean concentration repo 

dfior-Mnot- r-i r annua l moan nf ai r 1 

of time before the app' 

rted as an approximate 

oar) 1 owol c moacuroii wi 

particular study. Conversely, "preication or increase in emission controls . 

value 

L

h i n £* km nf cmolto r 

eGeometric mean of dust and soi l lead levels within 6.4 km of smelter 
P.4 

A-10 

England with minimal air pollution , but with high natural soi l lead levels as 

well as being contaminated by nearly 1900 years of mining activity . Thus, 

lead deposition on soi l surfaces had probably been low for some time, in 

contrast to the other studies in which surface contamination was ongoing or 

had been recently reduced; b) Eight of the ten homes sampled by Lepow et al . 

(1975) were buil t prior to 1940 and apparently had significant sources of 

leaded paint that had been "corrected" for previous to the study. In addition, 

some of the homes were located close to heavily trafficked roadways, where 

street level air concentrations ranged between 2.2 and 7.7 pg/m3, thus 

lending uncertainty to a dust/air relationship from thi s study based on 

annual average air lead levels measured at centrally located monitors 

distant from the dust sampling sites ; c) The smelter studied by Yankel et al . 

(1977) operated for several years with severely limited air pollution control 

capacity due to a baghouse fir e in 1973. The very high soi l and dust lead 

concentrations measured near the smelter would not be expected today with 

normally controlled emissions; d) The high indoor dust lead levels measured 

by Brunekreef et al . (1981) and Diemel et al . (1981) near the Belgian smelter 

were probably due, in part, to extremely high lead content (up to 40% by 

weight) in peeling paint in old houses (buil t around 1900; the children in 

these houses were excluded from analysis of blood lead levels); e) The 

relativel y high soi l and dust lead levels in relation to concurrent air lead 

concentration measured near the Bartlesvill e smelter by Hartwell et al . (1983) 

was probably due to a drastic reduction of total suspended particulate emissions, 

from 1600 tons/year to 15 tons/year, jus t prior to the onset of the study. 

With these exceptions, the studies listed in Table A-3 appear to have 

sampled a broad spectrum of homes (e.g. , both low and middle class, old and 

modern, with and without leaded paint--those with high paint lead levels were 
P.5 

A-l l 

excluded) and neighborhoods that can be considered fairl y representative of 

current U.S. conditions in urban and point source areas. Although far from 

conclusive, the available data from point source studies suggest the long-term 

equilibrium relationships between air lead and soil/dust lead concentrations 

shown in Table A-4. Appendix B contains a description of the derivation of 

these equations. 

Short-term (several months) departures from long run equilibrium 

levels of soi l and dust lead (from imposition of new alternative lead NAAQS, 

for example) are also estimated in Appendix B. The short-term relationships 

are shown in Table A-5. In general, a change in ambient lead wil l in the 

short term, only induce direc t changes in dust lead. In the long term, the 

relationships in Table A-4 are appropriate. Unfortunately, insufficien t 

longitudinal data exists to explicitl y estimate the temporal relationship 

between ambient, soil , and dust lead. 

14. I t is estimated that a young child typicall y sleeps about 12 hours 

a day (Pope, 1986b), leaving approximately 12 waking hours in which he or she 

i s capable of ingesting dirt . The time weighted concentration of lead in 

dust and soi l that a child i s exposed to i s thus computed by: [(outdoor 

soil/dust lead concentration x time spent outdoors) + (indoor dust lead 

concentration x time spent indoors)] * 12 hours. 

15. Amount of dir t ingested: Hand to mouth activit y (e.g. , thumb 

sucking and finger licking) and immature dietary habits (i.e. , the retrieval 

and subsequent consumption of food from dusty surfaces or soil) , which are 

normal behavorial characteristics of children up to fiv e years of age 

(Lin-Fu, 1972), make soi l and dust major sources of ingested lead for 

children (Charney et al. , 1983). Good information on the amount of dir t a 
P.6 

A-12 

Table A-4. LONG-TERM RELATIONSHIPS BETWEEN DUST, SOIL ANU AMBIENT LEAU 

Soil Lead = 50.1 + 579.0 (Ambient Lead) 

Dust Lead = 57.6 + 972.0 (Ambient Lead) 

Table A-5. ESTIMATING SHORT-TERM1 RESPONSES IN EQUILIBRIUM SOIL AND OUST 

LEAD LEVELS FROM CHANGES IN AMBIENT LEAD 

Change in Dust Lead = 582.0 (Change in Ambient Lead) 

Change in Soil Lead = No Change 

1

 Duration of several months or less. 
P.7 

A-13 

child eats in the normal course of a day i s needed for.an assessment of 

health risks associated with toxic materials in the environment. Based on 

a small number of direc t measurements, Day et al . (1975) estimated that 

under average urban conditions (and after 30 minutes of normal playground 

activity) , 5 to 50 mg of dir t transferred from a child' s hands to a typical 

"sticky sweet", and estimated that a dail y intake of 2-20 sweets would result 

in a dir t intake of 10-1000 mg. Lepow et al. , (1974) measured a mean of 

10 pg of dir t on the hands of 22 young children which would be ingested with 

each episode of hand-to-mouth activity . These authors estimated that a 

child puts it s hand into it s mouth ten times per day which would result in 

the ingestion of 100 mg (0.1 g) of dust and soi l per day. An average 

estimate of 100 mg of dir t ingested daily by young children has been used 

in several documents (Dril l et al. , 1979; NAS, 1980; CD, Table 7-23) to 

represent a probable value for a "typical" child . 

Recently, Binder et al . (1986) and Clausing et al . (1987). estimated 

children's intake of soi l by measuring relativel y non-absorbed elements 

with high concentrations in soi l as tracers . Levels of aluminum, titanium, 

and either silico n or acid insoluble residue were determined in soi l and 

children's feces and mass balance calculations were made to estimate 

soi l ingestion. In both studies, soi l ingestion estimates based on titanium 

were highly variable and in many cases, an order of magnitude greater than 

results using the other tracers . This suggests an additional source of 

titanium not accounted for in the studies (e.g. , paint, toothpaste, talc , 

laboratory contamination) and that the titanium-based, outlying estimate 

should be given less weight. 

For 59 children, ages 1 through 3 years, Binder et al . estimated 

mean daily soi l ingestion based on aluminum and silico n to be 181 and 184 
P.8 

A-14 

mg/day respectively; geometric means for the two elements were 128 and 130 

mg/day. The mean estimate based on titanium was 1834 mg/day. Of the various 

factors and assumptions used in thi s study that could have contributed to 

an inaccurate estimate of soi l ingestion (e.g. , assumption that the tracer 

element absorption i s negligible, and that there i s introduction or loss 

of tracer element during processing), the assumption with the most significant 

potential impact i s that dietary intake of the tracer elements is negligible . 

Binder et al . and Sedman (1987) cit e evidence that these elements do in fact 

occur in the diet . The study design used by Clausing et al . provides an 

indirec t control for such dietary intake; 18 nursery school children and 6 

hospitalized children, without soi l contact, ages 2-4, were sampled. The 

average of estimated soi l ingestions based on al l 3 tracers was 105 mg/day 

for the nursery school children and 49 mg/day for hospitalized children which 

was. significantl y different despite the small number of samples. I f as the 

authors assumed, al l of the "soi l ingestion" by hospitalized children is 

background due to dietary and other non-soil sources, correction of the 

nursery school average for thi s background would result in an estimated 

average soi l ingestion rate of 56 mg/day. I f the same background i s 

subtracted from the Binder et al . estimates to adjust for dietary sources of 

tracer elements, soi l ingestion rates of approximately 80-135 mg/day result . 

For children in the 1-4 year old age group studied by Binder and Clausing, 

a range of soi l ingestion between 80 and 135 mg/day wil l be assumed. 

As noted by Binder, Clausing, Sedman,. and colleagues, considerable 

uncertainty surround these estimates given for example, the small number 

of subjects studied and the lack of complete data on dietary intakes and 

gut absorption. Nevertheless, the range of the estimates i s narrow despite 

being derived from separate data sets and does suggest that they reasonably 
P.9 

A-15 

reflec t average soi l ingestion for thi s age group. Given that children eat a 

combination of soi l and dust, and that the studies did not distinguish 

between those two media, the estimates would be inaccurate i f concentrations 

of silico n and aluminum were different in house dust and soil . Until further 

data are available, i t wil l be assumed that soi l ingestion estimates from 

these studies reflec t total "dirt" consumption rates. 

In order to use the above estimates to determine dir t ingestion rates 

for other ages of children, data on age-related changes in blood lead (Yankel 

et al. , 1977; Annest and Mahaffey, 1984; Billick , 1982; Quah et al. , 1982) 

and the prevalence of mouthing behavior (Mi H i can et al. , 1962; Barltrop, 

1966) were used by Sedman (1987). Relative age-related changes in soi l 

ingestion calculated by Sedman were applied to the range derived above 

for the 1-4 year old age-group to yield the following estimates: 

Age (years) 0-1 1-2 2-3 3-4 4-5 5-6 6-7 

Dirt Ingestion 0-86 80-135 80-135 80-135 70-100 60-90 55-85 

(mg/day) 

The lower bound of zero for the youngest age group was chosen because contact 

with dirt y surfaces i s limited for the firs t 6 months or so unti l crawling 

begins. In informal discussions with clinicians and other researchers, 

including those who are involved in ongoing studies of soi l ingestion in 

children, there was general agreement that these estimated ranges are 

reasonable averages given the available data and associated uncertainties. 

Further research on thi s issue that includes specific examination of tracer 

element metabolism and dietary intake, and house dust ingestion, has been 

stimulated by the Binder and Clausing studies. Preliminary results from thi s 

ongoing research that can hopefully clarif y the estimates presented here 

are expected sometime in early 1990. 
P.10 

A-16 

The above ranges representing average exposure estimates are derived 

from studies that did not include children with pica. Dirt ingestion rates 

for many children can be much higher. For example, among young children 

hospitalized for asymptomatic lead poisoning and exposed to three play 

environments which differed in their stimulus complexity (e.g. , number and 

type of toys , availabilit y of playmate), significantl y more mouthing behavior 

occurred in the impoverished play setting (Madden et al. , 1980). In particular, 

children with pica who display patterns of repetitive hand-to-mouth 

activity , or who deliberately ingest paint, plaster, paper and other non-food 

items including dirt , may be exposed to considerable amounts of lead compared 

to children who only inadvertantly ingest foreign substances. Pica occurs 

to some degree in a substantial percentage of young children. Data from 

NHANES II.indicat e that the percent of children with a history of pica i s 

significantl y higher for those 6 months through 3 years old (11.0%) than 

for those 4 through 5 years old (3.2%) and for children livin g in households 

with annual family incomes < $10,000 (11.9%) than for those i n households 

with incomes > $10,000 (6.0%) (Mahaffey and Annest, 1985). Estimates for 

pica prevalence rates, based on more limited samples, range as high as 

approximately 10 to 30% in children 1 to b years old to 35-50% in those 1 

to 3 years old (Millican et al. , 1962; Barltrop, 1966). Children exhibiting 

pica for paint are of major concern because of the high levels of lead in 

some paints, with older painted surfaces containing lead in concentrations 

greater than 1 percent (10,000 ppm). [The allowable lead content of paint 

was set in 1978 by the Consumer Product Safety Commission at 0.06 percent 

lead (600 ppm)]. Pica for paint is believed to occur in episodes, possibly 

2 to 3 times per week (NAS, 1972). I t has been estimated that a child can 

consume somewhat greater than 1 gram within a 24 to 36 hour period, with 
P.11 

A-17 

cases reported of up to 20 grams within the same time period (Sachs, 1976) 

and that children with pica for paint may consume 1 to 3 grams per week 

(NAS, 1972). Although direc t data on pica children are not yet available, 

a reasonable "worst case" estimate of 1 gram/day for soi l ingestion in young 

children has been suggested (White, 1987). 

Estimates of daily lead uptake under alternative air lead levels are 

presented in Table 4-1 only for children without pica. In order to calculate 

the contribution of lead in paint to the total lead exposure of children 

with pica, a worst-case estimate of 1 gram of paint chips consumed per day 

could be used. Future reductions in airborne lead emissions are not likel y 

to significantl y alter pica exposure to lead over the next few years and 

other regulatory alternatives to protect these children must be considered. 

16. Lead intake from dust and soi l i s computed by multiplying the 

time weighted concentration of indoor and outdoor soil/dust concentrations 

by the estimated dir t ingestion rates listed above. 

17. Gut absorption of dirt : Animal experiments indicate that lead 

of variable chanical forms in soi l or dust i s as available for absorption as 

food lead (Dacre and Ter Haar, 1977) and in vitr o studies demonstrate that the 

acidity of the human stomach is adequate to extensively solubilize lead 

assimilated from soi l and dust (Day et al. , 1979; Harrison, 1979; Duggan and 

Williams, 1977). Based on these data and the fact that ingestion of such 

materials occurs other than at mealtimes, allowing for potentiall y enhanced 

absorption, the CD estimates that 30% of the lead ingested in dust and soi l 

i s absorbed in a child (CD, p. 10-10). 

As discussed in the CD, the relationship between blood lead and lead 

intake i s curvilinear across a broad range of blood lead values such that 

the relative change in blood lead becomes smaller as "baseline" blood lead or 
P.12 

A-18 

lead intake increases (CD, p. 10-53, section 11.4.3). In the lower "range 

of exposures, there is no significant difference between curvilinear and linear 

relationships (CD, p. 11-99, p. 11-134). A number of biological factors may 

explain the curvilinear relationships such as an increasing fraction of blood 

lead as circulating lead rises , with greater movement of plasma lead to tissues, 

including bone, and increased lead excretion. Another plausible basis i s 

gradual saturation of lead transport proteins in the GI trac t as lead 

intake rises (CD, p. 10-13). In fact , improved fit s of the uptake/ biokineti c 

model estimates to measured blood lead data from E. Helena resulted when 

GI absorption rates in children were differentiated based on proximity 

to the smelter which i s a surrogate for lead intake level . The best fit s 

resulted when a GI absorption rate of 0.3, equivalent to the average rate 

cited in the CD for children, was assumed for children livin g beyond a onemile radius from the smelter, and a rate of 0.2 was assumed for children 

livin g within one mile. A close fi t between observed and predicted blood 

lead levels also resulted when an average rate of 25% was used for the 

entire area (within 2.25 miles) of the smelter. I t i s of interest to note 

that a GI absorption factor of 0.17 has been estimated for paint chip 

ingestion in children (CD, p. 10-10). For children above 6 years old , a 

slightl y lower value i s needed to reflec t the fact that GI absorption 

efficiency generally i s much lower in adults. For children ages 6-7 years 

of age, a GI factor of 0.15 and 0.2 wil l be assumed depending, as discussed 

above for younger children, on their proximity to a lead point source. 

An inverse relationship was found between particl e size and gastrointestinal absorption of lead, especially in the range of 1-100 pm, such 

that a 6 pm dietary lead particl e was absorbed fiv e times as efficientl y 

as a 197 pm particl e (Barltrop and Meek, 1975). There i s littl e information 
P.13 

A-19 

to assess whether the conversion in the physical form of atmospheric leadcontaining particles once inside the complex geochemical matrix of soi l or 

as dust would affect their bioavailabilit y and, consequently, toxicity . 

Thus, atmospheric lead particles that have deposited wil l be considered to 

have absorption rates i f ingested, independent of particl e size. 

18. Total lead uptake from dust and soi l i s obtained by multiplying 

rows 16 and 17. 

19. Total lead uptake is the sum of rows 8, 11, and 18. 

Paint Lead Exposure Estimates 

No attempt has been made to separate lead paint hazards from generalized 

conditions in estimating soi l and dust lead concentrations associated with 

different air lead levels . The major reasons are that 1) any changes in 

the lead NAAQS wil l have minimal effects on children exposed to dusts and 

soil s contaminated by the flaking , peeling, weathering or "powdering" of 

lead-based paint and 2) data are not available to adequately estimate lead 

concentrations resulting from lead paint contamination given their high 

variabilit y depending on many factors including housing age, extent of 

deterioration, layers of paint, family behaviors, and climate. For purposes 

of simply illustratin g the magnitude of risks associated with lead-paint 

hazards in relation to generalized exposures around point sources or in 

other areas, one set of average estimates of lead levels in dusts and 

soils in and around homes with lead paint, presented in the CD, can be used. 

Based on studies of Hardy et al . (1971) and Ter Haar and Aronow (1974), 

the CD states that soi l lead and household dust lead concentrations around 

and in lead-painted homes can be expected to average 2000 ppm (p. 7-62). 

I f thi s soi l and dust lead level is entered into the exposure profil e for 

children in Table 4-1 , assuming an air lead level of 0.5 pg/m3, for example, 
P.14 

A-20 

and a gut absorption rate of 0.17 cited in the CD for paint chips (CD, 

p. 10-10), ranges of total lead uptake would increase from 11.5-26.7 pg/day 

to 31.2-51.1 pg/day. Even thi s large difference markedly underestimates 

leaded paint exposure for many children since children who eat flaking 

paint or gnaw lead-painted woodwork are not accounted for. Assuming pica 

behavior (1 gram/day ingested rate, see #15 above) in lead-painted housing 

conditions with soi l and dust lead levels of 2000 ppm, the dail y lead 

uptake estimates cited above increase to approximately 350 pg/day. 
P.15 

APPENDIX B. ESTIMATION OF THE RELATIONSHIPS BETWEEN SOIL, DUST 

AND AMBIENT LEAD 

A key assumption in regulation of atmospheric lead concentrations 

(PbA) i s that changes in PbA wil l be followed by corresponding changes in 

soi l lead concentration (PbS) and interio r house dust lead concentration 

(PbD) i n the same vicinity . Since ingestion of soi l and dust lead during 

normal hand-mouth activit y i s believed to be the major source of lead 

uptake in very young children (and worse when pica is present) i t i s 

important to make a quantitative estimate of the magnitude of the effects 

on these proximate causes of childhood lead exposure due to changes in PbA. 

1 . Mathematical Models for Soil and Dust Lead vs. Air Lead 

The relationships depend on many factors , including time (t) and 

physical or chemical properties of the atmospheric lead particulates 

such as particl e size and surface water solubilit y of the particulate 

lead matrix. We let x denote a generic set of particl e properties. The 

fraction of airborne particles deposited on soil , per day, denoted DF(x,t), 

i s in general a function of x and t . So i s the fractional rate of removal 

of surface soi l lead, denoted RF(x,t), by burial , runoff, resuspension, 

cleaning and other activities , and the influ x rate (pg/g per day surface 

PbS from non-air sources) denoted IF(x,t) . Finally , in order to calculate 

the Pb concentration in the atmospheric particulates , we also need the 

atmospheric particulate matter concentration in particl e class x at time 

t , denoted PM(x,t). A formal model for combining these quantities i s 

described next. 

A plausible mathematical model for the rate of change of PbS(x,t) 

can be expressed by a differentia l equation 

Rate of change = non-air influ x + atmospheric deposition - soi l removal 
P.16 

B-2 

or, symbolically, 

dPbS(x,t)/dt = IF(x.t) + [PbA(x,t)/PM(x,t)] DF(x,t) 

- PbS(x,t) RF(x,t) (Equation 1.1) 

An equilibrium model may be obtained by setting dPbS/dt = 0 and 

solving the resulting equation (suppressing dependence on t) , 

PbS(x) = AQ(X) + Ai(x) PbA(x) (Equation 1.2) 

where 

A0(x) = IF(x) / RF(x) (Equation 1.3) 

Ai(x) = DF(x) / [RF(x) PM(x)] (Equation 1.4) 

Note that thi s implies that when there i s more unleaded dust in the air 

(larger PM(x)), then the soi l lead vs. air lead slope A^ is lower. 

Likewise, a non-equilibrium model can be derived from equation 1.1. In 

the case when al l of the parameters are independent of time, we have a 

relativel y simple solution in terms of an exponential approach to the 

equilibrium concentration PbS(x) in Equation 1.2, 

PbS(x.t) = PbS(x,0) exp(-RF(x)t) + 

(1 - exp(-RF(x)t) PbS(x) (Equation 1.5) 

In the case where the parameters can very with time, the exponential 

solution is much more complicated, 

PbS(x,t) = PbS(x,0) exp [ - 6 RF(x,U) du] 

+ h [IF(x,u) + PbA(x,u) DF(x,u) / PM(x,u)] 

exp (- 6 RF(x,v) dv) du (Equation 1.6) 

There may be substantial variation in the apparent soi l lead-air lead 

"slope" where PbS nas not had sufficient time to reach near-equilibrium, 

say t < 3/RF(x). Thus the soi l lead removal time scale l/RF(x) i s a 

critica l parameter. 
P.17 

B-3 

Another consequence of thi s model is that particl e properties (x) 

may be a factor in producing an apparently nonlinear relationship between 

total soi l lead concentration PbS 

PbS = Ex PbS(x) 

and total air lead concentration PbA 

PbA = Zx PbA(x). 

From equation 1.2, the equilibrium relation i s 

PbS = £x AQ(X) + Zx Ai(x) PbA(x) (Equation 1.7) 

This produces an exactly linear relationship 

PbS = ay + ax PbA (Equation 1.8) 

when 

Ai(x) = DF(x) / [RF(x) PM(x)J = ai (Equation 1.9) 

a0 = ExIF(x) / RF(x) 

The assumption that Ai(x) i s a constant at each site , i.e. , does not depend 

on particl e properties x, i s plausible but untested. Empirically, the 

relationship between PbS and PbA i s nearly linear at low levels of PbA, 

but may be somewhat nonlinear at higher PbA (McLamb, 1988; Marcus 1988b) 

I t is more plausible that PbS(x) is linear with the average concentration 

of lead in the particles , as in Equation 1.4 so that a linear relation 

between PbS and PbA is , at best, an approximation, unless al l particles 

are in a single x class. 

Similar but more complex calculations may be used to derive a linear 

PbD vs. PbA relationship. 

2. Review of Data in The Literature 

A number of data sets were examined that could be used to assess the 

rate at which soi l lead (PbS) and/or house dust lead (PbD) concentrations 

change over time as a consequence of changes in air lead concentration (PbA). 
P.18 

B-4 

Most of the reported studies are of marginal value. We wil l firs t describe 

the data sets we found less useful. 

The Omaha studies by Angle et al . (1984) contain useful annual 

data, but the spatial and temporal averaging is at a very broad scale and 

much detai l i s lost . The lead dustfal l data (PbDF, mg/cm^) was available 

for most of the years in which PbA averages are given, but PbD and PbS 

were only measured at 37 locations in 1972. The data are shown in Table 

B-l . No relation between PbDF and PbA i s evident. 

The Roels et al . (1978, 1980) data also measured PbA for a number of 

years, but PbD only for 1976, so i s not useful for showing PbD changes. 

The El Paso smelter data (Morse et al. , 1979; Landrigan et al. , 

1975; Landrigan and Baker, 1981) measured PbA, PbD, and PbS at several 

locations in 1972 and 1977. In 1972 many of the most heavily lead-burdened 

children lived in the Smeltertown neighborhood adjacent to the smelter. 

By 1977 almost al l children had been evacuated to safer neighborhoods. 

In the intervening fiv e years the mean annual air lead levels (PbA) had 

declined from 10.0 to 5.5 pg/m3 at 0.4 km from the smelter. The dust 

samples in 1972 were collected in Smeltertown and other locations, with 

exceptionally high geometric mean PbD value of 22,191 ppm in the ring 0 

to 1.6 km from the smelter. The 1977 mean PbD was only 1,479 ppm i n thi s 

ring , and 1,461 ppm in the ring 0.8 to 1.6 km from the smelter. Likewise, 

the 1972 soi l lead mean was 1,791 ppm in the 0 - 1.6 km ring , and 427 ppm 

i n 1977. 

The decline in El Paso PbS and PbD i s proportionately much greater 

from 1972 to 1977 than the decline i n PbA. Several factors may play a 

role here. The firs t i s that the extensive publicit y given to lead as a 

health hazard probably caused much more extensive individual attention to 
P.19 

B-5 

TABLE B-l 

ENVIRONMENTAL LEAD CONCENTRATIONS IN 

OMAHA, NEBRASKA (ANGLE ET AL., 1984) 

Area Year PbA PbDF PbD PbS 

1970 

1972 

1973 

1974 

1976 

1977 

1970 

1972 

1973 

1974 

1976 

1977 

1970 

1972 

1973 

1974 

1976 

1977 

1.66 

0.37 

0.46 

0.04 

0.13 

0.78 

1.44 

0.32 

0.32 

-

0.16 

0.62 

0.73 

U.26 

0.22 

0.04 

-

-

-

-

26 

17 

5 

34 

_ 

-

11 

6 

1 

8 

_ 

-

7 

3 

-

-

479 262 

300 339 

211 81 
P.20 

B-6 

household cleanliness and to control of areas in which children could be 

exposed to leaded soi l (Landrigan, personal communication, Apri l 5, 1988). 

Secondly, we do not know i f the same locations were sampled in 1972 and 

1977. Interior household dust collection would have been negligible in 

Smeltertown in 1977 as only three children lived there. Finally , the air 

lead levels relevant to the highest PbD i n 1972 may have been much larger 

than 10.0 pg/rn3 in 1972. Landrigan et al . (1975) reported a mean PbA of 92 pg/m3 

at the air monitor closest to the smelter. A PbD deline from 22,191 to 

1,479 ppm (15-fold) i s better explained by a PbA decline from 92 to 5.5 pg/m3 

(17-fold). Access to unpublished data may clarif y this . 

The NEA source apportionment study (Cooper et al. , 1981) obtained a 

number of low-vol, high-vol, and dichotomous sampler TSP samples at 

locations in the vicinit y of the Kellogg, Idaho, smelter during 1980, 

when the smelter was stil l in operation. Samples were also obtained of 

"aerosolizable dust." These data are not directl y comparable to PbS 

values. The samples of soi l and road dust were sieved, aerosolized, and 

samples with a dichotomous sampler. This fine surface soi l fraction 

probably is more relevant to the exterior dusts that adhere to a child' s 

fingers and are eaten (Duggan and Inskip, 1985). Since a number of 

samples were obtained after the area had been covered by fine volcanic 

ash from the eruption of Mt. St. Helens on May 18, 1980, "Soil samples 

were collected after scraping away the overburden of ash which probably 

also removed the normal aerosolizable dust layer. Special care was 

exercised to ensure that the ash did not contaminate the underlying soi l 

when sampled. The top one or two centimeters of soi l were collected by 

scraping with a spatula..." (Copper et al. , 1981, pp. 114-115). This 

study appears to be of marginal relevance for studying time trends. 
P.21 

B-7 

3. Estimating Soil and Dust Lead Levels From Ambient Lead Levels 

The assumption in most analyses of data around existing lead point 

sources i s that the environmental lead emissions have been nearly 

constant for a sufficientl y long time that lead levels in soi l and dust 

are nearly in dynamic equilibrium. Thus, for some parameters ao, &\, bQ, 

t>l, t>2,

 c0» c l » w e nav e th e

 following linear relations for predicted 

geometric means: 

G.M. PbS = ao + ai PbA (Equation 3.1) 

G.M. PbD = bo + bi PbA + b2 PbS (Equation 3.2) 

G.M. PbD = c0 + ci PbA (Equation 3.3) 

Because these are predictions for geometric means and are fitte d after a 

log transformation, we know that c^ f (b\ + a\ b2). Note that c^ > b^ 

since i t includes the indirec t PbA --> PbS --> PbD pathway. The values 

shown in Table B-2 were obtained from two data sets. SPTA refers to the 

45 community averages from different lead point sources reported in Table 

A-3. EH i s based on a sample of households with youny children obtained 

in 1983 in East Helena, Montana, by the Centers for Disease Control and 

the Montana Department of Health and Environmental Sciences (CDC, 1983). 

The data on time scales for soi l and dust lead changes i s inconclusive. 

Our opinion is that lead in undisturbed soi l matrix persists for an 

extremely long time, but that soi l lead concentrations in disturbed 

(especially urban) environments wil l change, on average, over periods of 

a few years to reflec t changes in surface deposition. Interio r dust lead 

concentrations wil l likel y change over a period of weeks to months i n 

response to air lead changes, depending on interior-exterio r access and 

interio r recirculation or removal of dust. Thus the following strategy 

i s recommended. 
P.22 

B-8 

TABLE B-2 

LINEAR MODEL PARAMETER ESTIMATES FOR AIR: 

SOIL AND DUST LEAD RELATIONSHIPS* 

Data Set SPTA EH 

Parameter ao 

31 

°0 

°1 

°2 

^0 

*From (Marcus, 1988c) 

G.M. PbS = ao + ai PbA 

G.M. PbD = bo + bi PbA + b2 PbS 

G.M. PbD = CQ + ci PbA 

50.1 

579.0 

33.2 

582.0 

0.514 

57.6 

972.0 

88.1 

206.0 

184.0 

267.0 

0.894 

220.0 

551.U 
B-9 

Th'e estimation of changes in PbS and PbD from a change in PbA (brought 

about from a hypothetical change in the Pb NAAQS) can be estimated under 

two situations--short-tenn and long-term. In the long-term, equations 

to use in predicting equilibrium levels of PbS and PbD following a change 

in PbA are illustrate d by equations 3-1 and 3-3 above. Each predicts soi l 

or dust lead dependent only on air lead, which wil l generally be the only 

information available in applied policy analyses. When available, PbS 

in combination with PbA should prove far more predictive of PbD than PbA 

alone, since the indirec t pathway from PbA to PbD through PbS is probably 

a more important dust lead source (Rabinowitz et al. , 1985). 

The short-term changes in PbS and PbA, however, require further 

consideration. In time periods measured in terms of several months, we 

would expect to see littl e or no change in PbS from a change in PbA. 

Therefore, PbS would remain constant in the short-term. In contrast, 

dust lead, being a soiling phemonena, would be expected to change in the 

short-term as a result of changing ambient lead concentrations. There 

are, however, two components comprising the level of PbD. There i s 

direc t deposition from the atmosphere and secondary deposition caused by 

such factors as reentrainment from the soil . Therefore, the coefficient , 

b i , i n Equation 3.2 must be used to predict short-term changes in PbD 

(from equilibrium levels) from a change in PbA. 

The model i s intended to be used at many sites . Of the two data 

sets that were analyzed, the SBTA data set i s preferable because i t 

includes site-to-sit e differences in soi l and dust slopes. Slopes from 

any particular location such as East Helena reflec t local climate, soi l 

type, accessibilit y of lead soi l and air to the interio r of the house, 

and housecleaning practices related to awareness of lead hazards. Thus, 
P.24 

B-10 

a model based on the EH data set may not be as transportable to other 

sites and the relationships expressed in Appendix A are based on the S8TA 

analyses. 

4. Conclusions 

We have shown that the relation between soi l lead, dust lead, and 

air lead is expected to vary over time, even under near-equilibrium 

conditions. The various slopes can be expected to depend on site-specifi c 

properties such as the deposition rate, removal rate, total airborne 

suspended particulate concentration, and non-air lead influ x rate for 

lead-contaminated surface soils . There are almost no data that can be 

used to provide estimates of critica l kineti c parameters such as soi l or 

dust lead removal or turnover rates. 

We thus suggest calculating the expected changes in PbS and PbD from 

equilibrium relationships. In the short term (a few months) we expect 

littl e or no change in surface soi l Pb, but almost complete equilibration 

of the PbA (only) component of PbD and no change in the PbS component of PbD, 

In the long-term (e.g. , ten years after a PbA change) we can use the 

full y equilibrated PbD vs. PbA slope that includes the indirec t PbA --> 

PbS —> PbD pathway. 
P.25 

APPENDIX C. ESTIMATING 1990 BASELINE BLOOD LEAD AVERAGES 

1. Introduction 

In estimating PbB levels expected under alternative lead NAAQS, both 

the disaggregate model for adults and fetuses and the aggregate model for 

young children require estimates of the contributions to blood lead from 

sources that wil l be unaffected by changes in atmospheric lead related to 

change in the lead NAAQS. These sources include, for example, solder in 

canned foods and plumbing and historical deposition of gasoline lead. 

Blood lead contributions from non-air sources of lead are explicitl y 

accounted for in the disaggregate model for children, and in the integrated 

uptake/biokinetic model. This section describes methodology for, and results 

of, estimating average blood lead contributions from non-air sources, or 

"baseline" blood lead levels for children and different, adult populations 

livin g in 1990. 1990 i s the starting year for the various exposure 

analyses that wil l be conducted as part of the lead NAAQS review. 

2. Approach 

Ideally , we would know current PbB levels in pregnant women, middleaged men, and young children livin g near point sources. Known blood lead 

distributions could then be adjusted to account for the continuing downward 

trends in food, water, and air lead concentrations, described in Section II , 

in order to estimate baseline 1990 blood lead distributions . Because 

there have been no recent systematic surveys of PbB levels in the U.S., 

baseline blood lead estimates wil l have to be based on earlier data. 

The most recent, and well-conducted, nationwide survey of PbB levels 

was the Second National Health and Nutrition Evaluation Survey (NHANES II ) 

of 1976 to 1980. Since then, lead concentrations in different media have 

dropped substantially and have apparently, and predictably, been accompanied 
P.26 

C-2 

by significant reductions in lead exposure. The approach taken here wil l be: 

1) start with average PbB levels from 1978, the midpoint of the NHANES I I 

survey; and 2) estimate 1990 blood lead averages by adjusting the 1978 values 

for changes in gasoline emissions, and food and water lead concentrations, 

that have recently occurred and that can be expected to continue. 

The issue of fetal lead exposure wil l be addressed separately. 

3. 1978 Blood Lead Data 

Table C-1 list s mean PbB levels for selected population subyroups 

measured as part of NHANES I I in 1978, based on data provided to OAQPS 

by Joel Schwartz of EPA's Office of Policy, Planning and Evaluation. 

These levels wil l serve as starting points for adjustments to account for 

the exposure sources in flux , described above. 

TABLE C-1. SELECTED 1978 BLOOD LEAD LEVELS FROM NHANES I I 

Population (Age) Geometric Mean Blood Lead Level (pg/dl) 

Children 14.9 

(0.5 - 5 years) 

Females 10.8 

(15-44 years) 

White Males 15.4 

(40-59 years) 

Black Males 17.7 

(40-59 years) 
P.27 

C-3 

Black middle-aged men have not been identified in the CD as a separate 

sensitive group. White middle-aged men have been the focus of the two key 

population studies on lead-related blood pressure effects (Britis h 

Regional Heart Study and U.S. NHANES II ) in order to avoid the effects of 

confounding variables and because of less extensive data for non-whites. 

Given their high risk of cardiovascular disease, i t i s likel y that a 

similar, but possibly less apparent, blood lead/blood pressure relationship 

exists in black males and therefore, blood lead changes for thi s group wil l 

also be estimated. 

4 . Adjustment for Gasoline Lead Phasedown 

The strong correlation between gasoline lead consumption declines and 

the downward trend in NHANES I I PbB levels between 1976 and 1980 has been 

described in the 1985 Regulatory Impact Analysis for the fina l rule on 

lead in gasoline (EPA, 1985) and the CD (Section 11.3.6). Similar results 

were found with U.S. childhood lead-screening data (Schwartz et al. , 

1984) and in an Italia n isotope experiment where fairl y rapid changes in 

gasoline lead produced large changes in adult and children's blood lead 

(Facchetti, 1985; CD, p. 11-87). 

Gasoline lead accounted for an estimated 60 percent of the lead in the 

average American's blood i n the second half of the 1970's, and explained 

short-term seasonal increases in PbB levels from winter to summer as well 

as the long-term drop. Further, the accelerated rate of decline in yasoline 

lead after 1978 was paralleled by an accelerated decline in PbB levels . 

Additional support for a causal association between gasoline lead and blood 

lead i s seen in a) the blood lead trend, which was consistent throughout the 

entire distribution , and not only through truncation of the high blood lead 

levels (CD, p. 11-185); b) one-month lagged gasoline lead sales being the 
P.28 

C-4 

most significant predictor of blood lead, which matches the one month halflif e of lead in blood (EPA, 1985; p. 3-24) and i s consistent with results of 

Rabinowitz and Needleman (1982, 1983) who found that monthly changes in 

gasoline lead exposure were the probable cause of trends in umbilical cord 

PbB levels in Boston births (CU, p. 11-39); and c) the gasoline/blood lead 

relationship being stable across demographic and geographic boundaries and 

between the firs t and second halves of the NHANES I I survey, when gasoline 

lead levels were roughly 50% lower. 

Regression coefficients estimated from the NHANES I I analysis after 

controlling for age, race, sex, region of the country, season, income, 

degree of urbanization, and accounting for laboratory error, changes in 

dietary lead (including canned food) and lead-painted housing and other 

time-trends, have been used to predict changes in blood lead due to the 

gasoline lead phasedown (Annest et al. , 1983; Schwartz et al. , 1984). 

The phasedown wil l have continuing effects at least up to 1990-92 and 

earlier projections regarding blood lead changes can be extended using 

these regression coefficients . Joel Schwartz of EPA's Office of Policy 

Analysis provided the coefficients to OAQPS (personal communication to 

Jeff Cohen, May 9, 1988), derived from regressing natural-log blood lead 

values on gasoline values since the data best fitte d a loy-normal distrioution . 

Similar analysis by the Centers for Disease Control and tne National 

Center for Health Statistic s has been described oy Annest et al . (1983). 

The coefficients were derived from a period when gasoline lead 

consumption dropped significantl y and since then, the trend has continued 

to an even greater extent. As noted earlier, adults have large stores of 

skeletal lead accumlated over times of higher lead exposures. Some of 

thi s lead i s mobile and can be resorbed from bones into the bloodstream 

after reductions in exposure (Rabinowitz et al. , 1977). The extent of 
P.29 

C-5 

such bone lead resorption and the amount of time for re-establishing new 

steady-state PbB levels in response to declines i n gasoline lead emissions 

since NHANES I I i s difficul t to quantify. The only available direc t data 

on bone lead resorption come from excessively exposed people who may not 

have the same biokineti c rates as those with lower exposures. Similarly , 

other studies using isotopic lead tracers may not be relevant since 

isotopic exchange rates may diffe r from bone lead resorption rates. 

Nevertheless, workers exposed for periods up to 10 years (O'Flaherty et 

al. , 1982; Hryhorczuk et al. , 1985) and 20 years (Ahlyren et al. , 1987) 

in the lead industry, with PbB levels as hiyh as 70 pg/dl (and normal 

renal function) had blood lead half-live s between 20 and 700 days and 

showed significant blood lead reductions as quickly as 3 months to 2 

years. Every indication from the NHANES I I blood lead/gasoline lead 

analysis (e.g. , short time lags, seasonal parallels), and other studies 

(e.g. , Facchetti et al. , 1985) indicate that non-occupationally exposed 

adult blood lead levels respond quickly (e.g. , as quickly as one month) 

to fluctuations in gasoline lead. Given the fact that by 1990, the current 

phase of the gasoline phasedown regulation (i.e. , 0.10 grains of lead/leaded 

gallon—current levels are slightl y lower; D. Kortum, EPA's Office of Mobile 

Sources, personal communication) wil l have been in ful l effect for about 3 

years, whatever changes predicted based on the 1976-1980 NHANES results 

can reasonably be applied to estimating "baseline" 1990 blood lead levels . 

Table C-2 summarizes calculations using the regression coefficients 

from NHANES I I along with gasoline lead to estimate changes in average 

blood lead expected from changes in recent and future gasoline lead usage. 

The regression coefficients were similar for the different population groups. 

As observed in the NHANES I I analysis, the continued dramatic decline in 
P.30 

C-6 

TABLE C-2. PREDICTED CHANGES IN AVERAGE BLOOD LEAD LEVELS 

ASSOCIATED WITH GASOLINE LEAD TREND 

Children Women White Men Black Men 

(0.5-5 years) (15-44 years) (40-59 years) (40-59 years) 

1978 Geometric Mean 

PbB (pg/dl) 14.9 10.8 15.4 17.7 

Regression Coefficient 

(log PbB change/100 tons 

gasoline Pb change)3 .1220 .. .1558 .1216 .1216 

Reduction in Gasoline Pb 

Consumption, 1977-78 to 

1990 (tons/day) 0 435 435 435 435 

Predicted Reduction 

i n Gas/Lead Contribution 

to 1990 Mean PbB 

(pg/dl) -8.6 -5.5 -9.1 -10.5 

Calculated by Joel Schwartz. 

°Estimates liste d below, of gasoline lead usage provided by John Holley 

and Dave Kortum of EPA's Office of Mobile Sources, Field Operations and 

Support Division; 1990-92 projections based on Turner Mason and Company, 

1987 report on petroleum industry marketing: 

1977-78 1988 •1990 1992c 

Tons/day 438 4.8 2.9 1.4 

cDespite further decline i n 1992 in gas-lead consumption, no additional 

reduction in blood lead levels predicted by model. 
P.31 

C-7 

gasoline lead emissions i s predicted to parallel a major shif t in PbB 

levels . This decline wil l be used along with adjustments expected because 

of other lead exposure trends to estimate average 1990 baseline blood lead. 

5. Adjustment for Dietary Lead Reductions 

A significant reduction in dietary lead intake nas occurred since tne 

late 1970's, and thi s trend wil l continue as atmospheric lead emissions 

and deposition, the use of lead-soldered cans, and lead levels in drinking 

water al l continue to decline. Source contributions to children and adult 

diets are estimated in Chapter 7 of the CD, as described in Section II.D of thi s 

paper. Age-specific estimates of dietary lead intake in children for 1978-

1985 based on that information are detailed in Sledge (1986) and projections 

of future lead intakes, incorporating more recent data in Flegel (1988) 

have been estimated for children in 1990 (Cohen, 1988). Estimated differences in 

dietary lead intake between 1978 and 1990 are shown.in Table C-3. The 1982-

85 values are taken directl y from Flegel.et al . (1988), who showed that 

earlier predictions using the modeling approach developed in the CD were 

validated by actual data since made available by FDA. The 1978 estimates are 

•backward extrapolations of the 1982-95 data using the calculations in Sledge 

(1986). Among children, only 2-year olds are considered for simplicit y 

since other children would have roughly the same proportional decrease in 

dietary lead over thi s time period. Likewise, the 1978-1985 extrapolations 

for adults were calculated by assuming the same proportional declines that 

occurred in 6-year olds ' dietary lead intake, given that the sources of lead 

intake among older children are the same as for adults (confirmed by Rob 

Elias of EPA's Environmental Criteri a and Assessment Office; personal 

communication to Jeff Cohen, March 9, 1988). 

The dietary intake estimates for 1982, based on the CD analysis, were 

adjusted for the changes that have occurred and that are expected to continue, 
P.32 

C-8 

TABLE C-3. TRENDS IN DIETARY LEAD INTAKE (pg/day): TOTAL 

INTAKE (AND ATMOSPHERIC CONTRIBUTIONS) 

19783 1982d 1983 1984 1985 1990e 

2 year old 52.9 30.6 21.6 21.7 13.1 8.8 

children (27.0)° (1.2)f 

Adult Females 65.6 37.9 27.2 27.6 14.5 0.2 

(26.3)C (4.3)C 

Adult Males 91.5 55.2 36.3 42.5 19.8 14.1 

(39.0)C (6.1)C 

a

1978 values are extrapolations based on estimates in Sledge (1986), 

assuming a mean lead in drinking water of 12 pg/L. 

°Atmospheric contribution to 1978 dietary lead in children from Sledge (1986) 

based on Multiple Source Food Model developed in CD, Chapter 7. 

cAtmospheric contributions to 1978 and 1990 adult diet s derived by taking 

proportional contributions to 1982-1985 diets , as provided in Flegel et 

a l . (1988). 

d

1982-85 values are from Flegel et al . (1988). Exception i s 1982 value 

for children which i s derived in Cohen (1988) assuming a mean tap water 

lead level of 12 pg/L. 

e

1990 projections, described in Cohen (1988) derived by adjusting 1982 

values based on following assumptions: 1) switchover to lead-free cans 

wil l continue such-that by 1989, lead levels in canned foods wil l be 10% 

of 1982 values; 2) average lead level in drinking water wil l drop from 

12 pg/L to 8 pg/L by 1990 due a) to nationwide ban on lead solder and 

lead pipes and fitting s in new construction and repairs, b) public 

notificatio n requirements under 1986 SDWA, c) gradual replacement of old 

lead pipes in several large cities , and d) revised national standard for 

lead in drinking water. 

^Atmospheric contribution to 1990 children's diet derived in Cohen (1988) 

by multivariate regression analysis using CD Multiple Source Food Model, 

FDA data, and projected gasoline and ambient air lead data. 
P.33 

C-9 

due to the phaseout of lead-soldered cans, reductions of lead in drinking 

water, and reductions in atmospheric lead deposition onto crops and other 

vegetation, to yield 1990 dietary estimates. Again, the same proportional 

change in dietary lead intake for a 6-year old, estimated between 1982-

85 and 1990, can be assumed for adults since the sources of dietary lead 

in both diets are the same. 

Part of the reduction in dietary lead intakes i s attributable to 

reduced deposition of atmospheric lead particles , and although the NHANES 

I I regression coefficients used to adjust PbB levels for the gasoline 

phasedown represented total exposure, they probably did not capture much 

of the latte r pathway since i t takes some time (at least more than a 

month) for changes in gasoline lead usage to be reflected in different 

foods. The gasoline lead/blood lead coefficients would likel y have been 

higher had a longer timeframe been analyzed. 

Given the uncertainties of precisely how much dietary lead exposure 

i s in fact captured by the gasoline lead/blood lead coefficient,. a range 

of assumptions wil l be made. As a lower bound, we wil l assume that the 

adjustment described previously for gasoline lead reductions, based on 

1976 to 1980 data, wil l account for reductions in atmospheric lead 

contributions to dietary lead intake. In other words, the entire reduction 

in dietary intake estimated from 1978 to 1990 (52.9 pg/day - 8.8 pg/day = 

44.1 pg/day for children, for example) would be considered in addition to 

the adjustment for gasoline lead reductions. Alternatively , the contribution 

of atmospheric lead deposition wil l be "factored out" of the estimates of 

dietary lead intake for 1978 and 1990 to account for reductions in gasoline 

lead usage. Atmospheric contributions to children's dietary lead intake, 

for example, are estimated to have been 27.0 pg/day in 1978 (Sledge, 
P.34 

C-10 

1986) and to be 1.2 pg/day in 1990 (Cohen, 1988). Factoring out atmospheric 

lead deposition from the dietary lead intakes cited above yields 52.9-

27.0 = 26.9 pg/day for 1978 and 8.8-1.2 = 7.6 pg/day for 1990. The range 

of dietary lead intake reductions estimated between 1976 and 1990 for 

children i s therefore comprised of two values--25.9-7.6 = 18.3 py/day, and 

52.9-8.8 = 44.1 pg/day. Corresponding ranges for adult females and adule 

males are 33.4-55.4 pg/day and 44.5-77.4 pg/day, respectively. 

To estimate the impact on blood lead levels that changes in dietary 

lead have had, and wil l continue to have by 1990, dose-response relationships 

between PbB levels and lead levels in food and/or water can be used. Studies 

relating blood lead to dietary intake, measured by duplicate diets or 

fecal lead determinations, are summarized in the CD and the most relevant 

coefficients relating dietary lead, or "slopes" are cited in Section 

IV.B.l and IV.B.2 of thi s report. Most available studies are either on 

infants or adults; only one model has been developed specificall y from 

data on young children but that i s based on a study in which only kitchen 

water lead concentrations, and hot dietary lead levels , were measured 

(Laxen et al. , 1987). Slopes, in units of pg/dl PbB per pg dietary Pb 

intake/day, range from about .02 from adult studies to about U.U60 (U.K. 

Central Directorate, 1982; Sherlock et al. , 1982) and U.16 (Ryu et al. , 

1983) from infant studies. Lead intake in the Ryu et al . study was low 

and therefore the derived slope, which assumes a linear relationship, is 

probably an overestimate for the changes in dietary exposure levels being 

considered here. 

Lacey et at. , (1985) provide data to relate water lead concentration 

to blood lead. They suggested a linear relationship between blood lead 

and water lead with a slope of 0.062 pg/dl per pg/L. Reanalysis of 
P.35 

C-1 1 

these data indicated that a piecewise linear relationship fi t as well as 

non-linear models, with a slope of 0.25 pg/dl per pg/L for water lead 

concentrations below 20 ppm and a lower slope of 0.046 for water lead 

above 20 ppm (Holtzman and Marcus, 1988). Drinking water lead levels on 

a weight basis in thi s study correlated very well with tota l dietary lead 

concentration, which i s not unexpected since 8/9 of the mass of the infant 

diets was tap water. Because of thi s close correlation, Lacey et al . used 

water lead concentration as a surrogate for total dietary lead concentration. 

Thus, the relationship in Lacey et al . was derived to predict the 

contribution of total diet to blood lead. Results of the Lacey et al . 

analyses can be used to predict changes in blood lead by converting 

dietary lead intake values (in pg/day) to concentrations in terms of 

pg/kg, or ppb, as follows: 

Dietary Lead Intake (pg/day) x slope (pg/dl) 

Total Dietary Intake (Kg/day) (pg/Kg) 

where: reduction in dietary lead intake between 1978 and 1990 i s in the 

range of 18.3 to 44.1 pg/day; 

tota l dietary intake for a 2-year old child is estimated at 1.502 

kg/day (CD , Table 7-15); and 

slope from the Lacey et al . study i s estimated at 0.25 for lead 

levels below 20 ppb and 0.046 for levels above 20 ppb. 

Table C-4 presents results of the above calculations for children, 

along with adjustments for 1978 adult PbB levels derived from multiplying 

the slopes discussed in Section IV.B.2 by estimated reductions in dietary 

lead intakes. These adjustments wil l be combined with these made previously 

for the gasoline lead phasedown to yield 1990 average baseline PbB levels . 
P.36 

C-12 

TABLE C-4. ADJUSTMENTS TO 1978 MEAN BLOOD LEAD LEVELS FOR UIETARY 

LEAD REDUCTIONS 

Range of Di fferences 

Between 1978 and 1990 

Estimated Dietary Lead 

Intake (pg/day)a 

PbB Reduction Estimated 

By 1990 Due to Dietary 

Lead Reduction 

(-py/dl ) D 

Children 18.3-44.1 1.4-3.U 

Adult Females 33.4-55.4 1.1-1.8 

Middle-aged Men 44.5-77.4 1.4-2.6 

a

From Table C-3. Ranges reflec t uncertainty as to how much of the adjustment 

for gasoline lead reductions, using NHANES Il-derived coefficients , captures 

changes in atmospheric contributions to dietary lead intake. 

°Slope values used to convert dietary lead intake to average blood lead 

changes are from reanalysis by Holtzman and Marcus, 1988 of Lacey et al . 

(1985) for children (see text) ; and 0.032 pg/dl per pg Pb/day for adults 

(Sherlock et al. , 1982; Cools et al. , 1976; see Section IV.8.2). 
P.37 

C-13 

6. Adjustment to Children's PbB for Reductions in Maternal Exposure 

Since lead exposure has been, and wil l continue to be, reduced for 

women since the 1970's, PbB levels in children born since then can be 

expected to be lower as a result . Over the course of the NHANES I I 

survey, much of the reduction in gasoline lead emissions was probably 

reflected in lowered maternal, as well as newborn PbB levels . Thus, i t 

can be assumed that the adjustment to children's PbB already described 

for gasoline lead changes sufficientl y included any gasoline-attributable 

reductions maternal lead exposure. 

Reduction in maternal PbB attributable to changes in PbB dietary 

lead intake, however, i s not reflected in adjustments made previously. 

One method to account for thi s i s by using a kineti c model fi t to blood 

lead data collected longitudinally from young children from birt h to 27 

months (Succop et al. , 1987). This model provides a rate of blood lead 

change which can be applied to the amount of newborn blood lead affected 

by reductions in maternal dietary lead intake estimated between 1978 and 

19.90. As wil l be shown in Section C.8 below, the rati o between newborn 

PbB to maternal PbB i s on average around 0.8. Thus, the following equation 

i s derived to account for the propagation of PbB reductions in women, due 

to dietary changes (1.1 - 1.8 pg/dl), to 2-year olds: 

[(1.1 - 1.8 pg/dl) x 0.8] * e" a t = dPbBm 

where: the rate constant « = 0.072 (Succop et al. , 1987) 

t = 24 months 

d PbBrp = PbB reduction in 2-year olds expected in 1990 due to reductions 

in maternal dietary lead intake. 
P.38 

C-14 

The resulting range for dPbBm i s 0.2 - 0.3 pg/dl at age 2. This 

adjustment wil l be combined with the others for 2 year old children to 

yield an expected background mean PbB for 1990. 

7. Adjustment for Implementation of the Lead NAAQS 

The midpoint of the NHANES I I survey, 1978, was the year the current 

lead NAAQS was promulgated. Since then air lead levels have dropped 

dramatically throughout the country, mainly due to the gasoline phasedown, 

but also because of implementation of the air standard, especially in 

areas dominated by industrial point source emissions. Since the bulk of 

the NHANES I I sample lived in urban or rural areas, fairl y remote from 

major lead point sources, i t wil l be assumed that correcting for the 

gasoline lead phasedown wil l capture most of the reduction in air lead 

exposures that has occurred since implementation of the standard. 

8. Additive Adjustments to 1978 Blood Lead Level Averages 

Table C-5 summarizes the derivation of mean PbB levels estimated for 

four subpopulations in 1990. These averages reflec t changes that have 

occurred since 1978, and that are expected to continue, in gasoline lead 

emissions and deposition, canned food technology, and corrosion control 

for lead in drinking water. Any other changes not quantified were probably 

of lesser importance for the bulk of the NHANES I I population (e.g. , 

reductions in industrial point source emissions). The 1990 baseline 

averages can subsequently be used to model exposure changes expected 

under alternative lead NAAQS between 1990 and 1996 using the disaggregate 

model for adults and the aggregate model for children. The methodologies 

for these models are discussed in Section V. 
P.39 

C-15 

Table C-5. DERIVATION OF 1990 "BASELINE" AVERAGE BLOOD LEAD LEVELS 

Children Women White Men Black Men 

(2 years) (15-45 years) (40-59 years) 

1978 NHANES II 14.9 10.8 15.4 17.7 

Average (pg/dl)* 

Adjustment for 8.6 5.5 9.1 10.5 

Gasoline Pb 

Phasedown 

(-pg/dl) 

Adjustment for 1.4 - 3.0 1.1 - 1.8 1.4 - 2.5 1.4 - 2.5 

Dietary Lead 

Reductions 

(-pg/dl) 

Adjustment for 0.2 - 0.3 

Reductions in 

Maternal 

Exposures 

(- Pg/dl) 

Estimated 3.0 - 4.7 3.5 - 4.2 3.8 - 4.9 4.7 - 5.8 

1990 Average 

(pg/dl) 1 

^Geometric Mean Levels 
P.40 

C-16 

8. Estimating Fetal Exposures 

Different indices of prenatal and neonatal lead exposure have been found 

in longitudinal studies to correlate with delays in early mental and physical 

development. Lead readily crosses the placenta and accumulates in fetal 

tissues throughout development. The dynamics of lead exchange during 

pregnancy are complex and poorly understood (see CD Addendum). Ideally , 

serial measurements of maternal lead, or i f possible, embryonic lead, would 

have been taken in the studies and biokineti c models would exist that can 

estimate actual fetal exposures. In the absence of either, the question i s 

whether equilibrated PbB levels in pregnant women, as wil l be estimated 

in the disaggregate modeling described in Section V, are adequate surrogates 

for critica l fetal lead exposure, or i s there a better index. 

Umbilical cord blood lead, for example, which has been a key effects 

predictor in several studies, could be estimated by adjusting maternal PbB • 

predictions and applied to available dose-response relationships to assess 

risks . Table C-6 list s available data on paired mother/child PbB concentrations along with ratios between average maternal and cord PbB levels . 

The consistently high ratios (mean of 0.80 or 0.82, depending on the inclusion 

of one study with outlying results) indicates that the mature fetus absorbs 

a sizable fraction of circulating maternal lead. Cord blood lead, however, 

may not accurately reflec t individual circumstances or past exposure levels . 

In at least some pregnancies, there could be greater than normal transfer of 

lead from mother to the fetus . In addition, integrated exposure levels during 

the course of pregnancy may not be accurately indexed by blood lead levels at 

delivery or by single measurements during pregnancy. Average maternal PbB 

levels can fluctuate considerably during pregnancy (CD Addendum, p. A-45), 

while the equilibrium between blood and soft and skeletal tissues in the 
P.41 

C-17 

Table C-6. MATERNAL: CHILD BLOOD LEAD CONCENTRATIONS AND RATIOS 

Study/Location 

Number of Mean Blood Lead (pg/dl) Ratio of 

Subjects Maternal Cord Newborn Cord: Maternal PbB 

Barltrop (1968)/U.K. 

Harris and Holley 

29 13.9 10.8 

(1972)/U.S. 

Haas (1972)/Germany 

Zetterlund et al . 

(1977J/4 areas in 

Sweden 

A 

B 

C 

D 

Clark (1977)/Zambia 

- Control 

- Mine 

Hubermont et al . (1978)/ 

Belgium 

Buchet et al . (1978)/ 

Belgium 

Dragovic (1980)/ 

Yugoslavia 

-Smelter 

-Control 

Alexander and 

Delves (1981)/U.K. 

Moore et al . (1982)/ 

U.K. 

Winneke et al . (1985)/ 

FRG 

Ernhart et al . (1986)/ 

U.S. 

24 

294 

21 

173 

103 

37 

31 

122 

70 

474 

102 

45 

165 

236 

114 

118 

13.2 

16.9 

6.1 

9.2 

8.4 

9.4 

14.7 

41.2 

12.0 

10.4 

32.6 

18.6 

12.2 

14.0 

9.3 

6.5 

12.3 

14.9 

4.4 

8.0 

7.3 

6.8 

11.8 

37.0 

10.1 

8.3 

28.3 

17.3 

-

12.0 

8.2 

5.9 

11.0 

0.78 

0.93 

0.88 

0.72 

0.87 

0.87 

U.72 

0.80 

0.90 

0.84 

0.80 

0.87 

0.93 

10.0 

0.86 

0.88 

0.91 

McMichael et al . (1986)/ 

Australia 

Port Porie 519 

Other 172 

10.8 

7.7 

10.1 

6.2 

11.2 

7.5 

0.94 

0.81 
P.42 

C-18 

Table C-6. MATERNAL: CHILD BLOOD LEAD CONCENTRATIONS AND RATIOS 

(Continued) 

Roels and 

Lauweyrs (1987)/ 

Belgium 

474 

Dietrich et al . (1987)/ 305 

U.S. 

10.1 

8.0 

8.4 

6.3 4.6-

5.9 

0.83 

0.79 

Bellinger et al . 

(1986)/ U.S. 

216 6.5 6.2-

7.7 

Milman et al. (1988)/ 

Denmark 48 36 20 0.57 

Fahim et al . 

U.S. 

Region I 

Region I I 

(1976)/ 

240 

177 

13.1 

14.3 

4.3 

4.6 

Weighted Mean: 0.82 

0.33 

0.32 

Weighted Mean: 0.80 
P.43 

C-19 

mother i s displaced, and lead i s transferred to the placenta and fetal 

tissues; Alexander and Delves (1981) found an almost 20% drop in maternal 

PbB levels from 8 weeks unti l delivery . Mobilization of bone lead stores 

during pregnancy and lactation may be more substantial in some women, and 

iron and calcium deficiency, both common in pregnancy, enhances gastrointestinal absorption of lead (Rom, 1976). 

While there are significant uncertainties associated with predicting 

PbB levels among pregnant women under alternative regulatory scenarios, 

there are data sufficient to at least enable identificatio n and bounding 

of the uncertainties. Attempting predictions of actual fetal lead exposure 

i s highly uncertain and the chance of underpredicting exposures i s great. 

Therefore, for purposes of assessing risks associated with fetal lead 

exposures, PbB level estimates generated for pregnant mothers wil l be used as 

surrogates with no further adjustment. 
P.44 

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