United States
Environmental Protection
Agency
Region 5
77 W. Jackson Blvd.
Chicago, II 60604-3507
Illinois, Indiana
Michigan, Ohio
, Wisccnsn
Environmental Sciences
7 November 1992
905R92002
&EPA Project LEAP— Phase 1
Spatial And Numerical
Dimensions of Young
Minority Children Exposed
to Low-Level Environmental
Sources of Lead
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SPATIAL AND NUMERICAL DIMENSIONS OF
YOUNG MINORITY C}IILDREN EXPOSED TO LOW-LEVEL
ENVIRONMENTAL SOURCES OF LEAD
BY
WILLIAM H. SANDERS III
Director, Environmental Sciences Division
U.S.E.P.A. Region 5
United States Environmental Protection Agency
Region 5, Chicago
Environmental Sciences Division
Project LEAP (Lead Education and Abatement Program)
77 West Jackson Blvd, Chicago, Illinois 60604-3507
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ABSTRACT
SPATIAL AND NUMERICAL DIMENSIONS OF
YOUNG MINORITY CHILDREN EXPOSED TO LOW-LEVEL
ENVIRONMENTAL SOURCES OF LEAD
BY
William H. Sanders III, Director
Environmental Sciences Division
Region 5
United States Environmental Protection Agency
Chicago, Illinois
A population comparative risk algorithm was developed as a pilot study for the Agency’s Lead Strategy,
as a Region 5 Comparative Risk initiative, and as an environmental equity project. All known
environmental sources of lead in 83 cities in the Midwest were assessed to develop a population
comparative risk analysis for childhood exposure to leatL A secondary objective was to discern the
association of proximity of transportation corridors, to elevations in blood-lead levels. The selected at
risk population were African-American and Hispanic children under seven years of age. Measured and
postulated values were derived to approximate lead concentrations in air, drinking water, soi1 and dust.
Sources included in the analysis were major point sources of lead and lead compounds (from the Toxic
Release Inventory national data base), ambient air concentrations, reported drinking water concentrations,
municipal waste combusters, abandoned hazardous waste sites, and operating hazardous waste facilities.
Using concentrations specific to census tracts within each city, the EPA Uptake Biolcinetic Model was used
to estimate the pmbabiliiy distribution of blood-lead levels for each area, and to estimate the percent of
children expected to exceed a criterion value of 10 p.g/dL blood-leaS
Although considered to be conservative, the analysis concluded that in 1988 a total childhood
population of 154,000 Midwest children were expected to have blood-lead levels exceeding 10 g/dL,
including 55,000 Afri can-American and 12,000 Hispanic children. No association was found for proximity
of transportation corridors to elevated lead-blood levels, for the Minneapolis/St. Pau Minnesota, study
area.
This report constitutes Phase 1 of a three phase projecL The purpose of this phase is to screen
a large number of cities for future lead reduction efforts through the use of a comparative risk analysis.
Phase 2 will include testing in a small number of communities, as well as public education and outreach.
Phase 3 will be remediation of environmental sources of lead in one or more communities.
1
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ACKNOWLEDGMENTS
I am deeply grateful to the U.S. Environmental Protection Agency, particularly the Region 5 Regional
Administrator Vakias V. Adamkus and Deputy Regional Administrator Ralph Bauer, who provided
tremendous support in this endeavor, culminating in a sabbatical that provided the time to complete a
complex study.
l’his study relies heavily upon previously gathered data, by design, and I want to thank those too
numerous to mention that provided assistance and data for the analysis. Three individuals and
organizations are, however, particularly noteworthy: Mr. Douglas M. Benson, Coordinator, Lead Program,
Division of Environmental Health, Minnesota Department of Health, for graciously providing the blood-
lead database for the Minneapolis/St. Paul Blood-lead Survey; the Minnesota Pollution Control Agency
for providing the counterpart soil-lead data for the Twin Cities; and the U.S. Department of Housing and
Urban Development, for providing the raw database used for the National Housing Survey.
Finally, my deepest appreciation to a husband and wife team in the U.S. Environmental Protection
Agency, Environmental Sciences Division, Mr. Larry Lehrman and Mrs. Loretta Lehrman. The computer
support, both hardware and software, and technical/programming assistance proved invaluable for efficacy
in conducting the study. But, as important, their personal support and encouragement proved
indispensable to the spirit, as I struggled through to completion.
U
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TABLE OF CONTENTS
CHAPTER PAGE
EXECUTIVE SUMMARY
1. INTRODUCI’ION 1
2. UTERATURE REVIEW 4
2.1 Toxicological Profile 4
2.1.1 Internal Exposure 4
2.1.2 Encephalopathy/Lethality 7
2.1.3 Neurological Impairment 8
2.1.4 Developmental Toxicity 9
2.1.5 Aggregated Studies Analysis 14
2.1.6 Growth 14
2.1.7 Toxicological Summary 14
2.2 Adequacy of Studies 16
23 Biological Monitoring Techniques 17
2.4 Typically Encountered Environmental Levels 18
2.5 At-Risk Population
2.5.1 Spatial/Numerical Estimates of At Risk Population 24
2.5.2 Lead Screening Programs
2.6 At Risk Population Estimates by Sources/Routes of Exposure 29
2.6.1 Lead-Based Paint 29
2.6.2 Leaded Gasoline 34
2.6.3 Stationary Sources 35
2.6.4 Dust and Soils 36
2.6.5 Drinking Water 41
2.6.6 Lead in Food 43
2.7 Special Concern For Exposure of the Fetus 43
2.8 Special Emphasis: Ethnicity
2.9 Research Needs 47
3. STUDY OBJECI1VES 49
4. METHODOLOGY 50
4.1 Study Scope and Methodology Overview 50
4.2 Study Area 52
43 Contribution to Childhood Lead Levels Fmm Air Emissions 57
43.1. Industrial Source Complex Long Term Model 57
4.3.2. ISCLT Sensitivity Analysis 59
4.3.3. Ambient Air Data
4.3.4. Air Emissions 63
4.33. Municipal Waste Combusters
4.4 Drinking Water Data 64
4.5 Soil and Dust Contributions to Elevated Blood-lead Levels 64
4.5.1. RCRA and Operating Landfills 64
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TABLE OF CONTENTS (CONTINUED)
4.5.2. Abandoned Hazardous Waste Site Data .65
4.5.3. Derivation of Soil and Dust Values 65
4.6 Lead Uptake Biokinetic Model 67
4.6.1. UBK Sensitivity Analysis 72
4.7 Selected Area for Verification of Lead Screening Approach: MinneapolisISLP.aul 81
4.7.1 Minneapolis/St. Paul Demographic, Biological, and Soils Data 81
4.7.2 Minneapolis/St. Paul Statistical Analyses 82
4.8 Derivation of City ExceedanCe Estimates 83
5. RESULTS 85
5.1 Overview/Introduction to Results 85
5.2 Environmental Data Categorical Assessments 85
5.2.1 Ambient Air 85
5.2.2 Air Emissions 85
5.2.2.1. ISCLT Modeling Results
5.2.3 Municipal Waste Combusters 91
5.2.4 Drinking Water 94
5.2.5 RCRA and Operating Landfills 95
5.2.6 Abandoned Hazardous Waste Sites (Superfund) 99
5.2.7 Environmental Data Qualitative Summary 102
5.4 Chosen Cities 107
5.4.1 Minneapolis/St. Paul Environmental Sources of Lead 107
5.4.2 Blood-Lead DatalDefllOgraphics 109
5.4.3 Minneapolis/St. Paul Correlation Analysis 112
5.4.4 Minneapolis/St. Paul Regression Analysis 117
5.5 UBK City Results 121
6. DISCUSSION 131
6.1 Demographics 131
6.2 Environmental Data 133
6.3 Correlation Analysis 134
6.4 Regression Analysis 135
6.5 City Estimates of ExceedanCe 136
6.6 Uncertainties 137
7. CONCLUSIONS 140
8. RECOMMENDATIONS 143
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TABLE OF CONTENTS (CONTINUED)
CITED LITERATURE. 145
BIBLIOGRAPHY 153
COMPANION REPORTS:
•PROJECr LEAP—PHASE I APPENDIX
Appendix A Air Monitoring Summary for 1988
Appendix B Soil and Dust Values Based Upon
DHUD National Housing Survey Data
Appendix C Values for Uptake Biokinezic Model
Air Concentrations
Appendix D 1988 Toxic Release Inventory
Environmental Emissions in the Midwest
Appendix E 1988 Toxic Release Inventory
Environmental Emissions in MSA Cities
Appendix F 1988 TRI Sources in the Midwest
MSA Areas Exceeding 4000 Pounds/year
Appendix G Industrial Source Complex Model Results
Appendix H Municipal Waste Combuster Inventory
in the Midwest
Appendix I Drinking Water Supply Data
Summary for 1988 MSA Area Cities
Appendix J Resource Conservation and Recovery
Act Facilities in Midwest MSA Cities
Appendix K Toxic Release Inventory Reported
On-Site Disposal in Midwest MSA Cities
Appendix L Final and Proposed Sites in the
Midwest with Lead, November 1989
Appendix M Final and Proposed Sites in the
Midwest with Lead, November 1989 in MSA Cities
Appendix N Minneapolis/St. Paul Soil Lead
Concentrations by Census Tract
Appendix 0 Common Log of Blood-lead Values by Ethnicity
Appendix P Common Log of Blood-lead Levels by Census Tract
Appendix 0 Regression Results for Full Model
Appendix R Regression Results for Final Model
Appendix S Regression Results for Revised Final Model
Appendix T UBK Community Area Exceedance Results
•PROJECT LEAP— PHASE 1 GIS APPENDIX
.PROJECr LEAP— PHASE 1 SUMMARY REPORT
•FROYECTO “LW” RESUMER DEL INFORME
V
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LIST OF TABLES
TABLE PAGE
I HEALTH EFFECTS SUMMARY 15
II BLOOD-LEAD SCREENING PROGRAM RESULTS FOR CHILDREN IN
16 MIDWEST CITIES IN 1981
III CHILDREN UNDER 7 YEARS OF AGE IN THE MIDWEST
RESIDING IN UNSOUND LEAD-PAINTED HOUSING 32
IV METROPOLITAN STATISTICAL AREA CENTRAL CITY DEMOGRAPHICS ....53
V PARTICLE SIZE DISTRIBUTION INPUT TO INDUSTRIAL
SOURCE COMPLEX MODEL 58
VI UPPER AIR DATA ANALYSIS 61
VII INDUSTRIAL SOURCE COMPLEX LONG TERM MODEL
RUN COMPARATIVE ANALYSIS 61
VIII SOIL AND DUST CONCENTRATIONS FOR PB BASED
UPON DHUD NATIONAL HOUSING SURVEY DATA 66
IX UPTAKE BIOKINETIC MODEL DEFAULT VALUES 69
X MODEL DEFAULT BLOOD-LEAD AND LEAD UPTAKE 70
XI UPTAKE BIOKINETIC MODEL SENSITivITY ANALYSIS 75
XII SOURCES WITH TRI REPORTED TOTAL AIR EMISSIONS
EXCEEDING 4,000 POUNDS/YEAR IN 1988 87
XIII MAXIMUM CONCENTRATIONS OF LEAD FOR MODELED SOURCES 90
XIV MUNICIPAL WASTE COMBUSTER INVENTORY FOR
METROPOLITAN STATISTICAL AREA CITIES IN REGION.5 93
XV TOXIC RELEASE INVENTORY REPORTED ON-SITE DISPOSAL
IN 1988 FOR MSA CITIES 98
XVI NATIONAL PRIORITY LIST FACILITIES IN METROPOLITAN STATISTICAL
AREA CITIES WITH LEAD AS OF NOVEMBER 1989 101
XVII QUALITATIVE SUMMARY OF ENVIRONMENTAL EXPOSURES
FOR MSA CITIES IN 1988 103
XVIII CHILDREN UNDER 6 YEARS OF AGE WITH BLOOD-LEAD
LEVELS EXCEEDING 10 tGIDL BASED UPON 1986-1987 BLOOD-LEAD
SURVEY FOR MINNEAPOLIS AND ST. PAUL 110
XIX BLOOD-LEAD VALUES ( LGIDL) BY ETHNICITY FOR MINNEAPOLIS AND
ST. PAUL, MINNESOTA BLOOD-LEAD SURVEY IN 1986-1987 111
xx CORRELATION ANALYSIS OF MINNEAPOLIS/ST. PAUL 113
XXI SELECTED CENSUS TRACF DATA FROM MINNEAPOLIS/ST..L4UL 115
XXII CORRELATION ANALYSIS— CENSUS TRACF LEVEL 116
XXIII SUMMARY OF STEP WISE PROCEDURE FOR DEPENDENT VARIABLE
ACTUAL BLOOD-LEAD CONCENTRATION FOR MINNEAPOUSISE..PAIJL...119
xx iv NUMBERS OF CHILDREN UNDER 7 YEARS OF AGE IN THE MIDWEST
EXPECTED TO EXCEED 10 iG/DL BLOOD-LEAD LEVEL IN 1988 122
xxv TOp NKEI) CITIES BY PERCENTILE OF CHILDREN
EXCEEDING 10 &G/DL PB-B
xxvi Top p &N}(E1) CITIES BY NUMBER OF CHILDREN
EXCEEDING 10 1 &G/DL PB-B 129
vi
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UST OF FIGURES
FIGURE PAGE
1 Industrial Source Complex Long Term Point Source Grid 60
2 Uptake Biokinetic Model Default Concentration Curve 71
3 Select Drinking Water Concentrations 77
4 Select Soil and Dust Concentrations 78
5 Select Ambient Air Concentrations 79
6 Uptake Biokinetic Model Default Concentrations with
Geometric Standard Deviation of 1.8 80
7 Total Air Emissions 1988 Toxic Release Inventory 86
8 Major Air Emission Facilities 88
9 Municipal Waste Combusters In U.S. EPA Region 5 94
10 Major On-Site Disposal Facilities 97
11 Superfund NPL Sites 100
12 Scatter Plot of Modeled Blood-lead Vaules Vs. Actual Blood-lead Values 117
v i i
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EXECUTIVE SUMMARY
This research considers the known environmental sources of lead in 83 cities in the Midwest,
estimates the probability distribution of lead in African-American and Hispanic children (as well as the
total childhood population) under seven years of age in each of the cities, and compares the numbers of
children at risk. The approach thus developed is a population comparative risk screening methodology
for ranking geographic areas as to potential lead toxicity. This data analysis report is the first phase of
a three phase effort. Phase 2 will be to conduct sampling in a small number of communities, as well as
to begin public outreach and education on the dangers of environmental exposure to lead. Phase 3 will
be to conduct remediation of environmental sources of lead (e.g., soil and dust) in one or two
communities.
The objective of Phase 1 is to estimate relative blood-lead levels in childhood populations and to
compare geographic areas to ascertain the severity. For each metropolitan statistical central city area,
environmental data were obtained for the major sources of exposure. This included stationary source air
facilities, municipal waste combusters, ambient air quality measurements, drinking water supplies, and
operating as well as abandoned hazardous waste sites. Where available, actual concentrations were used.
Default values were established for each environmental medium where actual measurements had not been
taken. Major air emission sources were modeled to calculate associated air concentrations. The results
were used in a qualitative assessment of environmental exposure.
Demographic data were obtained from a geographic information systems application (provided by
the Geographic Information Systems Management Office, Region 5, U.S. EPA). That office provided data
at the census tract and community area (aggregation of census tracts) levels for each city. In general, a
census tract has a population of about 4,000 people. Environmental data (air, drinking waler, soil and dust
Prqfrct LEAP— Pha.. 1 viii
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concentrations) associated with each tract were obtained in order to calculate blood-lead level distributions
in affected populations.
Based upon these environmental concentrations for each census tract/community area, the Uptake
Biokinetic Model (described in Section 4.7) was run to calculate an expected percent exceedance for each
area. The percentage, applied against the population data for the tract, provided an estimate of the number
of children under seven yeais of age at risk of lead exposure. Further aggregations allowed for a city
total, as well as a numerical ranking of cities.
Data from a single geographical area, Minneapolis/St. Paul,Minnesota, was selected to test the
methodology. That area had available measured blood-lead levels, along with pertinent demographic
information. Two statistical procedures were performed. A simple correlation analysis was conducted
to ascertain whether modeled blood-lead levels, based primarily upon the environmental data for the area,
were associated with actual measured blood-lead levels. An association would indicate the viability of
the approach in comparing cities. The correlation analysis indicates a correlation coefficient of 0.3. It
is only statistically significant, however, at the 0.10 level.
The second statistical procedure was conducted so further analyze the contribution of
environmental pathways of exposure to elevations in blood-lead levels and, in particular, to ascertain
whether mobile sources (i.e., proximity to a major transportation corridor) could account for a portion of
the elevation in blood-lead levels. No association was found.
An analysis of environmental data indicates that a tremendous quantity of lead is still being
released into the environment, and that quite typically a small (relative) number of sources contribute most
of the contaminant. For the six Midwest states, industry released nearly 450,000 pounds of lead and lead
compounds into the air in 1988. Seventeen sources out of nearly 350 reporting facilities accounted for
almost one-half of the total emissions. Nevertheless, air quality, based upon measurements of the ambient
air, was excellent, with few exceedances of the primary air quality standard for lead. Point sources of
Prqj.ct LEAP— Phi.. 1 ix
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emissions, although many in number, generally do not cause concerns (a measurable increase in the
ambient air-lead concentration). The notable exceptions are a few high emitting industries. For those
industries, the increased ambient air-lead concentration, as modeled, is expected to occur near the source.
Although there is a large amount of lead emitted into the air, only a few sources emit lead and lead
compounds in sufficient amount to exceed the ambient air quality standard for air (refer to Section 5.5.2).
Only two of 17 modeled stationary sources of air-lead emissions had calculated maximum point downwind
air-lead concentration values projected to exceed the air quality standard of 1.5 tg/in 3 . Drinking water
supplies are also typically safe, although exposure does continue in some communities. Violations of the
drinking water standard are rare.
Exposure to lead through soil and dust, associated with operating and abandoned hazardous waste
sites, may occur in a few cities. The majority of sites, however, are located beyond the boundaries of the
central cities assessed and, consequently, do not generally pose a threat.
The research placed special emphasis on the risk posed by low-level environmental sources of lead
to African-American and Hispanic children. These populations are thought to be at particular risk (refer
to Section 2.8). For children residing in central cities of one million population or more, and annual
family income less than $6,000, 68 percent of African-American children are projected to have blood-lead
levels exceeding 15 t .g/dL For white children in the same socioeconomic strata, the percent projected
so exceed that value is much smaller, at 36 percent.
Seven cities in Region 5 are in the top 10 of the 83 cities assessed in the Midwest by virtue of
having both the highest percentages of children as well as the greatest numbers of children that may
exceed 10 g/dL blood-lead concentration. Those cities are Milwaukee, Wisconsin; Detroit, Michigan;
Minneapolis and St. Paul, Minnesota; and Cincinnati, Akron, and Cleveland, Ohio.
The analysis indicates that the States of Illinois and Michigan had the largest numbers of African-
American and Hispanic children under seven years of age calculated so exceed 10 &g/dL blood-lead level.
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This includes 28,000 and 16,000 minority children, in the respective states, due to environmental sources
of lead. Every Region 5 state has community areas where elevated blood-lead levels are of concern.
For the six Region 5 states, all cities combined, the total childhood population under seven years
of age was 1,359,000 in 1988. The findings indicate that 154,000 children, or 11 percent of the total,
would have blood-lead levels exceeding 10 igfdL. The predominant environmental sources are lead
contaminated soil and dust. This includes 55,000 African-American and 12,000 Hispanic children.
The cities with the highest potential for sizable numbers of African-American and Hispanic
children with blood-lead levels calculated as above 10 tg/dL are Chicago, illinois, 27,000; Detroit,
Michigan, 13,000; Milwaukee, Wisconsin, 5,000; aeveland, Ohio, 4,000-, Cincinnati, Ohio, 2,000; and
Indianapolis, Indiana, 2,000.
It is important to note that this methodology is for population screening purposes. It expands upon
the use of an Uptake Biokinetic Model for derivation of blood-lead levels. Such use of the model has not
been attempted before. The Uptake Biokinetic Model was developed specifically for application at
abandoned hazardous waste sites for which measured environmental lead concentrations are known. The
Uptake Biokinetic Model has only been validated at that spatial scale. This methodology applies it at a
much larger spatial scale. It includes both estimated and measured environmental concentrations, and uses
the model as part of a population risk screening approach. Consequently, the results may have no
practical value as a prediction of the actual number of children expected to have elevated blood-lead
levels. Nor was that the intent of the methodology. The value of the approach is in the comparison
between cities. It is specifically to locate areas within a city that may be expected to have higher rates
of lead exposed children than other areas. The intent of the population screening methodology is to use
the relative number to set priorities for intervention efforts within a city or region. The reader is
particularly cautioned that the numbers of children cited in this research are as derived by the
computerized methodology. The methodology is a screening tool. It is not a methodology to predict
PrqJ.ct LEAP— Phase I xi
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aetual nuthber,ofcliildrefl at risk.,
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1. INTRODUCFION
The insidious effects that lead causes on the health of children have received increased attention
in recent years. Due to mouthing behavior, increased uptake of lead compared to adults, nutrition and
other factors, children under seven years of age present a subpopulation at increased risk to the adverse
effects of lead exposure. Within this population subgroup, it has been well demonstrated that African-
Americans, particularly in lower socio-economic situations, are a subpopulation group at even greater risk.
Hispanic children may also be at higher risk. The reasons for a dissimilarity between white and African-
American children are unclear. It is clear, however, that the difference is seen at all socioeconomic levels.
Measurements and projections of blood-lead levels for African-American children consistently reflect
elevated blood-lead levels.
Reports from the second National Health and Nutrition Examination Survey, based upon data from
1976 to 1980, illustrates the substantial difference in blood-lead prevalence levels based upon ethnicity.
Among African-American children six months to five years of age, only 2.5 percent of African-American
children, compared to 14.5 percent of white children, had blood-lead levels less than 10 .tg/dL (Lin-Fu,
1992). For families with an annual family income < $6,000, 18.5 percent of African-American children,
contrasted to only 5.9 percent of white children, exceeded 30 tg/dL (children aged six months to five
years). The percentage was 10.9 percent exceeding 30 tg/dL for all races. For that same age group, the
geometric mean blood-lead level was 19.6 p.g/dL for African-American children, 14 p.tg/dL for white
children, and 14.9 p.g/dL for all races. Although complete data are not available for children of Hispanic
origin, the Agency for Toxic Substances Disease Registry (ATSDR, 1988) postulates that it is reasonable
to assume that the association between high blood-lead levels and lower socioeconomic income Status
would hold true for this population as well. Hispanic children, accordingly, may also be at elevated risk.
As research continues, the level of blood-lead concentration of concern continues to be lowered.
PrqJectLEAP—Pbase l 1
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More and more studies add to the weight of evidence for health effects in children at levels previously
thought to be safe. The fact that lead is a transplacental contaminant is even more alarming because
internal exposure can begin in the fetus. The exposure can continue to contribute to body tissue burden
of the young child if the child is subsequently brought into a lead-contaminated environment. A
significant evolving concern is that many of the effects of low-level lead exposure are not readily
observable in the individual child, unlike physical manifestations caused by acute lead poisoning. Acute
(observable) effects are usually associated with lead-based paint. Health effects are generally ascertained
not through clinical diagnosis of the individual patient, but rather through epidemiologic study of large
groups of children already suffering from the chronic effects of lead exposure. These chronic effects are
generally not observed in the individual child. Effects may include lower intelligence and other
neuropsychologic deficits, hearing impairment, stunted growth, reduction in attention span, and other
reported health impacts. Some studies suggest the lack of a threshold. This is extremely problematic.
Even though acute poisoning and exposure have been recognized, generally associated with lead-based
paint contamination, chronic exposure and effects caused by low-level lead exposure in the environment
are difficult to recognize.
This nation has experienced a tremendous reduction in lead emitted into the environment by the
phase down of lead in gasoline. The reduction has been paralleled by a significant concomitant reduction
of the average blood-lead levels in this Country. Lead, however, remains pervasive in our environment.
It is in the homes of tens of millions of families and serves as a continuous source of contamination and
exposure via lead paint. Lead remains in some sources of drinking water in the home. It remains in soil
and dust, caused potentially by both exterior and interior lead-based paint, as well as historical or ongoing
deposition from mobile sources of nearby industry. Even the nation’s food supply still contains some lead,
albeit in small quantity. The aggregate effect from multiple sources, in a specific geographic area, may
be sufficient to cause concern.
p J.ct LEAP— Phase 1 2
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The major objective of this research is to examine environmental sources of lead that may be
linked to chronic health effects in young children. In particular, such effects may be exacerbated by an
aggregation of low-level environmental exposures to lead and lead compounds that result from multiple
pathways of exposure. The research effort does not account for the direct effects of lead-based paint
consumption. The methodology does take into account the indirect contribution to exposure from lead-
based paint via lead-contaminated soil and dust. It is recognized, nevertheless, that lead-based paint
provides the largest contribution to elevated blood-lead levels. This is particularly the case for acute lead-
poisoning events. This effort, however, is to assess the extent to which low-level environmental sources
of lead may also contribute to elevated blood-lead levels. It constitutes the first phase of Project LEAP:
analysis of existing environmental data pursuant so a comparative risk analysis of childhood exposure to
lead for the study cities. The goal is to discern a logical direction for future lead reduction efforts. Phases
2 and 3 will follow, to address lead testing and remediation, respectively.
This report documents the development of a management tool to identify and prioritize geographic
areas having children with elevated environmental exposures to lead which may constitute a health risk
to young children. The methodology explores the application of an Uptake Biokinetic Model, developed
by the U.S. Environmental Protection Agency for site specific application, on a much larger scale than
its original design and intent.
Pruj.ct LEAP— Phase 1 3
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2. LITERATURE REVIEW
2.1. Toxicological Profile
“The EPA (1986a) and ATSDR (1988) are concerned that the emerging evidence of a
consternation of effects, including inhibition of AL4-D activity and pyrimidine-5 ‘-nucleotidase activity and
reductions in serum 1,25-dihydrooxyvitamin D levels, is indicative that low-level lead exposure has a far
reaching impact on fundamental enzymatic, energy transfer, and calcium homeostatic mechanisms in the
body, which are expressed through subtle effects on neurobehavioral indices, growth and blood
pressure “(ATSDR, 1990).
The evidence that low level lead exposure is a health concern, particularly for young children, has
emerged from a host of studies concomitant with the recognition that today, such exposure has become
pervasive in the United States. This is especially alarming as we gain a fuller understanding of the
aggregate effects of the multitude of (external) environmental exposures that contribute to internal
exposures. That internal exposure is typically assessed via ascertainment of the blood-lead (Pb-B) level,
a measure historically associated not with low level, chronic exposure, but rather with the acutes effect
caused by lead-in-paint poisoning.
2.1.1. Internal Exposure
For decades, scientists have recognized that high exposure to lead results in encephafopathy, colic,
anemia, nephropathy, and electrocardiographic abnormalities. High exposure can cause spontaneous
abortions in females, and decreased fertility in men (AThDR, 1990). McMichael c i al. (1986) reported
on miscarriage and still births among pregnant women. ATSDR (1990) notes that the primary source of
lead (Pb) in children is via the gastrointestinal tract. It is distributed in blood, soft tissue, and bone. In
human blood, 99 percent of the lead in blood in attached to erythrocytes (with over 50 percent of this pool
bound to hemoglobin) (ATSDR, 1990). The balance is deposited in blood plasma, and can be transported
to soft tissues. Lead in bones is found in two components, an inert pool with a half life of decades, and
PrqJ.ct LEAP— Pha.. 1 4
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a labile pool having the ability to exchange readily between bone and blood or soft tissue (ATSDR, 1990).
According to a model proposed by Rabinowitz et al. (1976), the blood component half life is 36 days, soft
tissue is 40 days, and bone is iO days (about 27 years). A number of age related differences exists
between lead distribution and body burden of children, in comparison to adults. In a controlled
expenment, Griffin et al. (1975) found that blood levels returned to near-normal after about two months
subsequent to termination of exposure to airborne lead. In contrast, the biological half life in two year
old children has been measured to be about 10 months, (Succop et al., 1987). Further, in adults, about
95 percent of the total body burden is in bones, while in children, the percentage is approximately 73
percent (ATSDR, 1990). It is noted that lead accumulation in most soft tissues (the kidney, brain, and
liver) is of much smaller proportion than lead which accumulates in bone. Blood-lead which is not
retained in one of these compartments is excreted by the kidney, or is excreted through biliary clearance
into the gastTointestinat tract (AThDR, 1990). It is also noted that the physiological stress of pregnancy
can mobilize lead from maternal bone. This creates additional exposure for the developing fetus,
resulting, consequently, in greater danger to the fetus. The transpiacental transfer of lead has been cited
in a number of studies over the years. In a Glasgow, Scotland, study of 236 mothers and infants, the
geometric mean blood-lead levels were found to be 14 ig/dL for mothers, and 12 p.g/dL for infants
(Moore Ct al., 1982). According to the Public Health Service (ATSDR, 1988), there is no metabolic
barrier to fetus uptake of lead; consequently, exposure of women during pregnancy results in lead uptake
by the fetus (i.e., physiological stress results in increased exposure of the fetus). Differential internal
exposure risk appears to continue after birth. Infants from birth to two years have been shown to retain
32 percent of the total amount of lead absorbed, according to a study by Ziegler ci al. (1978); whereas
a study by Rabinowitz et al. (1977) discerned a one percent retention rate in adults of the absorbed amount
of inspired lead, derived by ATSDR from the Rabinowitz et al. study data. The Rabinowitz et al. study
itself found that the average respired lead intake of 14 pg/day, inhaling air containing 2 pg/rn 3 lead,
Pr iject LEAP— Ph 1 5
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resulted in a calculated increase of 0.06 tgfgm in the blood-lead level.
The interaction of lead with other chemicals in the body has also been extensively studied, and
is a matter of concern. “In humans, the interactive behavior of lead and various nutritional factors is
appropriately viewed as particularly significant for children, since this age group is not only particularly
sensitive to the effects of lead, but also experiences the greatest changes in relative nutrient status”
(ATSDR, 1990). Data supporting this conclusion is available from a number of sources. Studies have
found that calcium intake is inversely correlated with increasing blood-lead levels (ATSDR, 1990).
Watson et al. (1980) reported that iron deficient adults absorbed lead two to three times greater than lead-
replete adults (thus 20 to 30 percent of dietary input, versus 10 percent). Studies have found increased
lead absorption with low dietary calcium, increased lead absorption and toxicity with iron deficiency, and
that low zinc in the diet increases lead absorption (ATSDR, 1990). Mahaffey (1990) found that lead
absorption and toxicity increased for subjects with diets low in calcium. He also found that long term iron
deficiency, as well, increased the absorption and retention of lead. Mahaffey concluded that longitudinal,
prospective studies are needed to evaluate the effectiveness of nutrition as a preventive strategy for lead
intoxication.
Lower-level exposures affect the synthesis of heme, and decreases the circulating levels of the
active form of vitamin D, 1,25-dihydroxyvitamin D, in children. “This form of vitamin D is largely
responsible for the maintenance of calcium homeostasis in the body” (ATSDR, 1990). In a study by
Rosen et al. (1980), the researchers found that lead-exposed children with Pb-B levels of 33 to 120 .tg/dL
had notable reductions in serum levels for both 1,25-dihydroxyvitamin D and Pb-B over the entire range
of blood-lead levels measured in the study. EPA (1986a) concludes that lead’s interference with heme
synthesis may be the basis for the effects on vitamin D metabolism.
Low-level lead exposures causes inhibition of erythrocyte ALA-D, down to the lowest observed
blood-load levels of approximately three to five g/dL (ATSDR, 1990). This has been confirmed
PrqJ.ct LEAP— Pba.. 1 6
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particularly for child studies by Secchi et al. (1974) (minimum subject Pb-B value of 16 .tWdL), Wada
et al. (1973), Hernberg and Nikkanen (1970), Chisolm c i al. (1985a), and Rods et at. (1976) (mimimum
subject Pb-B value of 4.7 .tg/dL). The lowest observed adverse effects level (LOAEL) for ALA-D and
heme synthesis is thought to occur below 10 tg/dL (ATSDR, 1990).
Based upon a review of studies by EPA (1986a), ATSDR (1988), and Grant and Davis (1989) the
threshold for accumulation of erythrocyte protoporphyrin (EP) or zinc protoporphyrin is approximately
15 ,.tg/dL, the presumed Lowest Observed Adverse Effects Level (LOAEL) for children. EPA (1986a)
concluded that inhibition of the enzyme erythrocyte pyrunidine-5’-nucleotidase may occur in workers at
Pb-B levels at or exceeding 44 tg/dL, and in children that inhibition of the enzyme is seen down through
the lowest blood-lead levels of approximately seven j.tg/dL, based upon data of Angle et at. (1978) and
Angle et al. (1982). The LOAEL for children consequently appears to occur at less than 10 tg/dL under
intermediate and chronic exposure scenarios. A study by Rosen et al. (1980) found strong indication of
an inverse correlation between Pb-B and serum 1,25-dihydroxyvitamin D, that was observed in children
over the blood-lead levels measured in the study, from 33 to 120 ptg/dL
2. 1.2.EncephalopathyfLethaljty
For the oral route of exposure, the range of blood-lead levels associated with encephalopathy in
children was about 90 to 700 or 800 .tg/dL, with a mean of approximately 330 .tg/dL (ATSDR, 1990).
The range associated with death is approximately 125 to 750 tg/dL, with a mean of 327 tg/dL For the
inhalation route of exposure in adults, lead encephalopathy is the most severe neurobehavioral effect
(ATSDR, 1990). Early symptoms include dullness, irritability, poor attention span, headache, muscular
tremor, loss of memory, and hallucinations. The condition can worsen to delirium, convulsions, paralysis,
coma, and, ultimately, death. This is generally not observed in adults until levels exceed 120 p.g/dL Such
studies of signs and symptoms indicate that the lowest observed-effect levels for overt signs and symptoms
of neurotoxicity is in the range of 40 to 60 tg/dL (ATSDR, 1990). In children, acute lead poisoning other
PrQJ.ct LEAP— Ph... 1 7
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than signs of encephalopathy have been observed at levels of approximately 60 to 450 tg/dL. Acute lead
poisoning in children causes death from Pb-B levels equal to or exceeding 125 ig/dL, as reported by NAS
(1972), based upon studies by Chisolm (1962) and Chisolm and Harrison (1956). Although the Chisoim
studies did not address lethality directly, the latter study noted four deaths, and estimated the total lead
in the soft tissues of the individuals to be 20 to 100 mg. Grant and Davis (1989) suggest that Pb-B levels
that can produce death are basically the same as those associated with acute encephalopathy. Such effects
are usually observed in children from approximately 100 tg/dL
2.1.3. Neurological Impairment
AThDR (1990) paraphased an EPA (1986a) report, that concluded “that the consistent pattern of
lower JO values and other neuropsychologic deficits among the higher lead exposure children in these
studies indicate that cognitive deficits occur in apparently asymptomatic children with markedly elevated
blood-lead levels (starting at 401060 lg/dL and ranging up to 70 to 80 p.g/dL).” EPA concluded that
approximately five JO decrement points is a reasonable estimate of the extent of JO decrements associated
with markedly elevated blood-lead levels (mean approximately 50 to 70 tg/dL) in children that do not
exhibit signs and symptoms of lead poisoning (EPA, 1986a). 10 deficits of approximately four points are
associated with blood-lead levels of 30 to 50 tg/dL (ATSDR, 1990). In studies reported in 1986 and
1987, Hawk et al. (1986) replicated the Study with a cohort of 75 African-American children, aged three
to seven yeara old. All were of low socioeconomic status. Using a backward stepwise multivariate
regression analysis statistical technique, they found a “highly significant linear relationship between the
Stanford-Benet 10 scores and contemporary blood-lead levels, over the entire range of 6 to 47 p.tg/dL”.
Hawk et a!. (1986) and Fulton et a!. (1987) reported a significantly inverse linear association between
cognitive ability and blood-lead levels. There was no evident threshold down to the lowest Pb-B of
approximately 6 tg/dL The LOAEL for JO effects is, consequently, thought to be less than 10 .tg/dL
(ATSDR, 1990).
PrqJ.ct LEAP— Ph ... 1 8
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A study by Robison ci al. (1985) of 75 African-American children aged three to seven years old.
The study determined that hearing decreased for the study group, and that the severity of hearing loss
increased linearly wIth historical blood-lead levels, in the range of 6.2 to 56.0 p.g/dL. Schwartz and
Otto’s (1987) logistic regression analysis of NHANES II (the second National Health and Nutrition
Examination Survey) data suggests the probability of elevated hearing thresholds with significant increases
across the entire range of blood-lead levels of < four ig/dL to > 50 p.g/dL. The study involved 4,519
children aged four to 19 years, and was controlled for several confounding variables available from the
data set. A study of the effects on peripheral nerve function suggests an increased susceptibility to lead
neumpathy, among children with sickle cell disease (Erenberg et al., 1974).
2.1.4. Developmental Toxicity
Developmental toxicity of lead has been assessed in several studies. A study in Boston by
Needleman et al. (1984) found an association between lead exposure and congenital abnormalities,
including undescended testicles (Hydrocele). Several epidemiological studies have also been conducted.
A Port Pine, South Australia study of 595 children was reported by Vimpani ci a!. (1989) as well as
Baghursi et al. (1987). These studies determined that the geometric mean values of Pb-B increased from
approximately 14 p.g/dL at six months of age, to approximately 21 p.tg/dL at 15 and 24 months of age.
Depressed Mental Development Index (MDI) scores were found to be significantly associated with higher
post-natal blood-lead levels, as well as with six month blood-lead levels, although such an association was
not found with pne-natal delivery or with cord Pb-B level. The study found a two point deficit in MDI
at age 24 months, for every 10 tg/dL increase in Pb-B at age six months. In a Bellinger et a!. (1985a,b,
1986a,b,1987) prospective study of 249 middle-to-upper-middle-class children in Boston, Massachusetts,
the researchers determined that the high-lead group (having a mean cord blood level of 14.6 jtg/dL)
demonstrated an average deficit of 4.8 points on a “covariate-adjusted” MDI score, when compared to the
low-lead group (having a mean of 1.8 tg/dL cord blood level). The difference was 5.8 points at six
PrQJ.ct LEAP— Phi.. 1 9
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months, and 7.3 points at 12 months.This inverse relationship held for ages six, 12, 18, and 24 months
of age. The Bellinger study (1985a) considered several variables, including demographics (race, parental
age, education, marital status, occupation), medical/reproductive history, index pregnancy, labor and
delivery, neonatal status (such as birth weight and infections), post natal status (such as hospitalizations
and temperature), postnatal environment (including HOME, maternal JO, family stress, and feeding
method), and cord-blood level as an ordinal categorical value (low, medium, or high). The HOME (Home
Observation for Measurement of the Environment) assesses the quality of the rearing environment. The
study found a statistically significant association of blood cord levels and MDI scores, when the MDI
scores were adjusted for length of gestation and total HOME score.
A further analysis by Bellinger et al. (1990) found that children with high (10 to 25 .tg/dL)
umbilical cord-blood levels achieved significantly lower MDI scores through two years of age, than infants
with low (c three g/dL) or medium (six to seven ptg/dL) cord blood levels. The cord blood level,
however, was found not to be significantly related to performance (using the McCarthy Scales of
Childrens’ Abilities) at age 57 months. The study found that delta Z a derived index for a child’s
“developmental trajectory” between 24 and 57 months of age, to be significantly related to higher HOME
scores, higher social class, and more intelligent, older mothers. It was not, however, significantly related
to gender or ethnicity. According to the report, “The associations between performance trajectory between
ages 24 and 57 months and several of these characteristics, including high social class, high HOME score,
and high maternal 10, are consistent with the hypothesis that environmental enrichment facilitates the rate
and extent of recovery on compensation” [ from lead associated cognitive deficit].
EPA (1986a), Davis and Svendsgaard (1987), Grant and Davis (1989), and ATSDR (1988)
concluded from several studies of neurobehavioral effects of pre-natal lead exposure (Ernhar* ci al., 1985;
Wolf et a!., 1985; Davis and Svendsgaaid, 1987; Winnede ci al.,1985a,b), that neurobehavioral effects,
indeed, are associated with prenatal internal exposure levels. Maternal or cord blood-lead concentrations
Project LFAP— Phi .. 1 10
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of 10 to 15 tg/dL, and possibly lower were found to be associated with such effects (ATSDR, 1990).
(The Ernhart 1985 study, however, for which cord Pb-B levels ranged from 2.6 ig/dL to 14.7 .tg/dL with
a mean of 5.8 JAg/dL, concluded that “... the results do not provide a reasonable level of support for the
hypothesis of adverse effects due to intrauterine low-level Pb exposure”.) ATSDR (1990) notes the
criticism of the flaws of the studies reviewed, that showed both positive and no effects at low blood-lead
levels. The ATSDR further notes that a 2 to 8 point deficit for an individual child may not be clinically
significant, but that a 4 point reduction in a normal distribution of MDI scores for a given population of
children, would result in an increase of 50 percent of the children scoring below 80, which the report
called “a grave consequence” (ATSDR, 1990).
The Cincinnati Lead Program Project continues to follow study subjects into their early school
years to discern whether early deficits (i.e., decrements in Bayley mental index scores) persist into later
life (that is, do the observed effects of low level lead exposure continued at the same magnitude over
time). Dietrich c i a!. (1990) reports on the relationship between prenatal and postnatal lead exposure and
development status of two-year-old infants. Families for the study were recruited from “lead-hazardous
areas” of Cincinnati, Ohio, based upon pediatric case histories of lead poisoning. A total of 297 infants,
with a mean blood-lead level of 17.45 tg/dL, participated. The sample was 86.2 percent African-
American. The mothers were predominantly from lower social classes, unmarried, and on some form of
public assistance.
Developmental assessments were conducted at ages three, six, 12, and 24 months. The three part
Bayley Scales of Infant Development were used: Mental Development Index (MDI), Psychomotor
Development Index (PD!), and Infant Behavior Record (IBR). The researchers collected social as well
as medical background data to test as potential confoundeis, including race, maternal age and tobacco use.
The study employed multiple regression analysis with backward elimination of nonsignificant covariates
and confounders (in the reduced model, while all variables were included in the multiple regression
Prq .ct I FAP- Ph... 1 11
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analysis). The lead variables were analyzed both in terms of tg/dL and of a transformation to their
natural logarithms.
The prenatal and neonatal blood-lead levels were found to be low, with a few subjects exceeding
25 tg/dL Most reached the highest blood-lead level during the second year. About 25 percent had at
least one serial blood-lead of 25 p.g/dL during the second year. Prenatal blood-lead was found to be
significantly related to six month MDI after statistical adjustment for 10 potential covariates and
confounders, at six months, but only for males. It was insignificant for females at this age. The study
did not provide reasons for the gender difference. The study also found, for Hollingshead socioeconomic
status scores below the sample median of 17, a covariate adjusted reduction of 0.757 MDI points for each
.tg/dL increase of neonatal blood-lead (p = 0.0316). This was statistically insignificant, however, for a
status score above 17. A two year follow-up determined that there was no statistically significant
relationships between prenatal or postnatal blood-lead level variables and Bayley MDI. The relationship
with Bayley IBR factor scores also had statistically insignificant results. Dietrich ci al. conclude that the
lack of inverse relationships suggests that those infants of mothers with higher prenatal blood-lead levels
may have overcome their early developmental deficits. The authors note that these results are inconsistent
with previous studies by Bellinger and the Port Pine Study of 1988, and cite as caveats the limitation of
Bayley scales of measurement. The authors also noted that the two other studies did find continuing
harmful effects at two years of age.
The documented toxic effects of lead on the human fetus include a lowering of the gestational age,
reduction in birth weight, and reduced mental development, all of which may occur at relatively low Pb-B
levels (ATSDR, 1990). McMichael et al. (1986) found that the risk of pre-term delivery increases about
four times as cord or maternal Pb-B increases from s eight so >14 tg/dL Dietrich et a!. (1986; 1987a)
reported a significant inverse association between prenatal Pb-B levels in the mother, and birth weight,
withtheeffectobscrvcddownto12to13 tg/dL.
Prqj.etLEAP—Pbe l 12
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A Bellinger et al. (1987a) study reported significant deficits of 4.8 points in the Bayley MDI at
ages six to 24 months of age, in children whose Pb-B at birth ranged from 10 to 25 ig/dL, contrasted to
children whose Pb-B level at birth was less than three WdL. Dietrich et a!. (1987a) also reported an
inverse correlation between prenatal or neonatal blood-lead levels and MDI, in the range of one to 25
.tg/dL
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2.1.5. Aggregated Studies Analysis
Needleman et a!. (1990a) performed what was termed a meta-analysis of 12 of 24 studies that used
multiple regression analysis to study the effect of childhood exposure to lead on 10. They found overall
evidence of a strong link between low-dose lead exposure and intellectual deficit in children. The analysis
concluded that even though the studies had significant variation in their individual power to find an effect,
11 of 12 of the studies reviewed reported an association between adverse health effects and lead exposure.
2.1.6. Growth
The effects of lead exposure upon growth in the young child have been recognized as far back
as 1929, when Nye (1929) reported on runting (stunted growth) and chronic nephritis in overtly lead-
poisoned children in Australia. (Nye, in turn, cites a report by A. Jefferis Turner of lead poisoned children
in Brisbane, in the year 1892.) Schwartz et al. (1986), based upon data for 2,695 children under seven
years of age from the second National Health and Nutrition Evaluation Survey (NHANES II) study,
provides even stronger evidence of this effect. Through the use of a stepwise multiple regression analysis
technique, the Schwartz group concluded that blood-lead levels for the range of five to 35 p.tg/dL, were
a “statistically significant predictor of children’s height (p.c.0001), weight (p<.OO1), and chest
circumference (p<.O 26 ), after controlling for age in months ... race, sex, and nutritional covariates.” The
strongest relationship found was between Pb-B and height, with regression models indicating no threshold
down to the lowest observed Pb-B of five jtg/dL There was no indication of a threshold within the study
range.
2.1.7. Toxicological Summary
These studies indicate that there are several effects of major concern regarding low-level exposure,
including neurobehavioral effects Mental Development Index (MDI) and Intelligence Quotient (10)
deficits, as well as elevated hearing thresholds, and growth retardation (for young children with pie-natal
exposure as well as for children suffering from post-natal exposure) (ATSDR, 1990). There appears to
Proj.ct LEAP— Phii. 1 14
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be no indication of a threshold down to the lowest level of internal exposure (Pb-B c 10 xg/dL) (ATSDR,
1990). Health impact are summarized in Table I.
:$wdy : :
TABLE I
Health Effects Summary
:
Neahh Etfea
14B VSut
Rosen et at., 1980
Interference with heme synthesis, decreased
level of 1,25-dehydroxyvisamin D
33 to 120
Secchi ci al.,1974; Wada et al., 1973;
Hernberg and Nikkenen, 1970; Chisolm et
aL,1985a; and Roels et at., 1976
Inhibition of erythrocyte ALA-D
<3 to 5
AThDR, 1990
Lowest observed adverse effect level
(LOAEL) for ALA-D and heme synthesis
<10
EPA, 1986a; Grant and Davis, 1989
Acrumulation of crythrocyte pyrinmidine
(LOAEL)
15
Angle et at., 1978; Angle et at., 1982
Inhibition of enzyme erythrocyte
pyrinmidine-5-nucteotidase
44
ATSDR, 1990
Encephalopachy in children
90 to 700
NAS, 1972; Chisolm, 1962; Chisolm and
Harrison, 1956
Death
.
125 to 750
Hawk et at., 1986; h ilton et at., 1987
Decreased IQ
6 to 47
AThDR, 1990; EPA 1986a
Decreased 10 of 4 points; of 5 points
30 to * 50 to 70
Robison et at., 1985; Schwn and Otto,
1987
Decreased hearing acuity
6.2 to 56M <4 to >50
Needleman ci at., 1984
Hydrate (undescended testide)
Not specified
Ernharrt et at., 1985; Wolf c i at., 1985;
Davis and Svendsgaard, 1987; Winnede ci
at., 1985a,b
Neurobehavjoraj effects
<10 to 15
McMichael ci at., 1986
Pm-term delivery risk
s8 to 14
Dietrich et at., 1986, 1987.
Decreased birth weight asaociatcd with
mother’a lb-B
12 to 13
Dietrich et at., 1987a
Mental Development Index deficit
1 to 25
Nyc, 1929
Stunted growth
Not specified
ScbwartzetaE,1986
Rcducdonlnheightandweight
c5to35
In a speech given on October 7, 1991, Health and Human Services Secretary Louis Sullivan cited
Pn J.d LEAP —Phase!
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an announcement by the Centers for Disease Control, for a lower “threshold of concern” for blood-lead
levels in children (Sullivan, 1991). The new threshold is 10 p.tg/dL, coupled with recommendations for
“...levels of action for intervention.” Dr. Sullivan called lead poisoning “...the number one environmental
threat to the health of children in the United States.”
2.2. Adequacy of Studies
The United States Congress, in Section 110(3) of the Superfund Amendments and Reauthorization
Act (SARA) of 1986, tasked the ATSDR with preparing a toxicological profile for each of 100 most
significant hazardous substances found at the Comprehensive Environmental Response, Compensation, and
Liability Act (CERCLA) National Priority List (NPL) sites, and for each profile to provide “An
examination, summary, and interpretation of available toxicological information and epidemiologic
evaluations on a hazardous substance in order to ascertain the levels of significant human exposure for
the substance and the associated acute, subacute, and chronic health effects” (ATSDR, 1990). The result
of that mandate has been the preparation of a very intensive and extensive review of the literature on the
human health effects of lead. l’his was presented in pertinent part in the preceding section. Congress also
required ATSDR to determine whether sufficient information existed to ascertain the levels of exposure
for a given chemical that posed endangerment to human health.
ATSDR categorized the sufficiency of data from human studies for specific health endpoints as
sufficient, some, or no information available to make a definitive determination for each endpoint, for both
cancer and noncancer (A1SDR, 1990). ATSDR judged, for combined oral and inhalation studies, that
some information exists for lethality, acute systemic toxicity, reproductive toxicity, and carcinogenicity.
Sufficient information is deemed to be available, based upon the extensive literature review, for
intermediate systemic toxicity, chronic systemic toxicity, and developmental toxicity. No information
(derived from human health studies) is available for the dermal route of exposure for any of the seven
health endpoinss reviewed.
PmJ.ct LEAP— Phas. 1 16
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Information is available, however, for animal data. There appears to be sufficient information
available on reproductive toxicity (oral), along with some evidence of carcinogenicity via the dermal
exposure route (ATSDR, 1990). It is noted that the Interagency Regulatory Assessment Group has rated
lead as a Group B-2 possible human carcinogen (1987), and that EPA (1991) has determined lead to be
a Class B-2 probable human carcinogen.
Noting the difficulties in ascertaining the length of exposures and that distinctions are somewhat
arbitrary, ATSDR recommends the joint consideration of intermediate and chronic systemic toxicity data
together (AThDR, 1990). ATSDR has determined that the data do not clearly indicate NOAELs for
humans, recognizing that the associations between blood-lead levels and neurobehavioral indices, blood
pressure, growth, and heme synthesis, occur over a wide range of Pb-B concentrations. Further, there are
no indications of threshold values through the lowest Pb-B levels. More than 100 ongoing federally
sponsored projects involving lead toxicity have been identified, including several prospective studies on
the effects of lead toxicity on neurobehavioral changes in childhood populations (ATSDR, 1990). The
existence of a large data base relating Pb-B levels to measured lead concentrations in air, diet, drinking
water, dust and soil, has also been noted (ATSDR, 1990). ATSDR, nonetheless, considers such measures
to be an imperfect measure of body tissue burden. The better measure is the level of lead in teeth and
bones, together with Pb-B, to better measure both past exposures and current body burden. ATSDR
specifically cites the EPA lead uptake biokinetic model (EPA, 1991a) for estimating blood-lead levels. The
model is based upon exposures, and has been validated by an investigation of young children living near
industrial lead sources that contribute to lead concentrations in ambient air, soil, and dust.
2.3. Biological Monitoring TechniQues
As noted, however, blood-lead measurement is the most common method of assessing exposure
to lead. The half life of lead in human blood is 28 to 36 days (ATSDR, 1990). It is noted that the
detection limit at most clinical laboratories is three to five &g/dL (ATSDR, 1990).
PruJ.ct LEAP— Pha.. 1 17
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The use of erythrocyte protoporphyrin (EP) measurement for screening asymptomatic children for
lead toxicity was recommended (CDC, 1985; American Academy of Pediatrics, 1987), recognizing that
elevated EP was otie of the earliest and most reliable indications of impairment of heme biosynthesis.
Further, EP is used because of the contamination problems in measuring blood-lead levels (ATSDR, 1990).
In humans, it is noteworthy that Pb-B values are distributed in a log-normal distribution. Accordingly,
researchers should use the geometric mean and the geometric standard deviation when analyzing the
distribution data (ASTDR, 1988).
2.4. Ty ica1ly Encountered Environmental Levels
EPA (1986a) found that the relationship of blood-lead levels to lead concentrations in air, food,
and water is curvilinear, such that the increase in Pb-B is less at high levels than at low exposure levels.
The clear implication is that concern is warranted when children, in particular, are subject to even low
levels of environmental exposure. The range of normal air concentrations is 0.1 to 2.0 pg/rn 3 (A1SDR,
1990). The median blood-lead-level/inhalation-concentration for children is approximately 1.92 p g/dL
blood per pg/rn 3 air, based upon three major studies (AThDR, 1990). Aggregate values, including indirect
blood-lead contribution from dust and soil, range from three to five pg/dL per pg/rn 3 air (Brunekreff,
1984). Angle et al. (1984) defines the value at four to five p.g/dL for indirect exposure, additive to the
direct inhalation contribution.
The Centers For Disease Control (1985) has determined that concentrations of lead in soil of 500
to 1,000 p.g/g result in Pb-B in children exceeding background levels of Pb-B. EPA’s (1985) estimate of
the contributions of blood-lead levels from various media have been provided based upon background
levels, and the resultant levels from the addition of incremental concentrations of lead in air (EPA 1986,
1986a). Mean background contributions for non-air sources are 2.37 pg/dL from food, water, and
beverages; 0.30 ig/dL from dust; and 1.65 pg/dL from air. The total background contribution is 4.32
pg/dL The background Pb-B range is 4.32 pg/dL to 16.72 pg/dL (including 9.40 pg/dL from ingested
PrqJect LEAP— Ph e 1 18
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dust, and 3.00 .tWdL from ingested air, at the upper value). EPA found the estimates to be higher than
predicted when compared to observations in children living in areas with measured lead in air
concentrations. By comparison, Piomelli et al. (1980), during an expedition ascending the Marsyandi
River in the Manang district of Nepal in the foothills of Annaparna and Dhaulagiri, sampled the blood of
local inhabitants. The geometric mean Pb-B concentration was 3.4 p.g/dL. Only 10 of 103 individuals
tested exceeded 10 p.gIdL.
In 1986, the U.S. production of refined lead from primary sources totaled 808 million pounds, and
from secondary sources totaled another 1,356 million pounds (ATSDR, 1990). It is noted that recycling
of old scrap metal supplies 45 percent of U.S. demand. In that year, consumption in the nation was 2,480
million pounds, including 319 million pounds of lead imported to this country (ATSDR, 1990).
Anthropogenic emissions constitute the primary source of lead in the environment, and as of 1984,
gasoline combustion, in particular, was responsible for approximately 90 percent of all anthropogenic
emissions (ATSDR, 1990). This percentage has been reduced dramatically, however, due to the phase
down of lead in gasoline. Atmospheric deposition is the largest source of lead found in both soils and
surface waters. The lead particles are removed from the atmosphere principally via wet and dry
deposition. ATSDR (1990) stales that soil and sediments appear to be important sinks. The average
residence time in the atmosphere is seven to 30 days, during which period lead can be transported up to
thousands of kilometers. According to EPA (1986a), natural emissions of lead from volcanoes and
windblown dust are thought to be of minor significance. EPA (1986a) has also estimated the
anthropogenic lead emissions into the atmosphere for the year 1984. The 1984 estimate for gasoline
production was 34,881 tons/year, or 89.4 percent of the total emissions of 39,016 tons/year. Based upon
a current gasoline standard of 0.1 g Pb/gallon-gasoline, the estimated 1988 lead emission would be 1,100
tons/year.
In the atmosphere, lead exists mostly in particulate form (ATSDR, 1990). Large size particles,
19
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particularly those with aerodynamic diameters exceeding 2 I.tm, settle out of the atmosphere fairly rapidly
and are deposited relatively proximate to the emission source. Smaller particles may travel thousands of
kilometers. In waters, at a pH > 5.4, the total solubilily of lead is about 30 ig/l in hard water, and 500
i.tgfl in soft water (ATSDR. 1990). The ratio of lead in suspended solids to lead in dissolved form has
been found to vary from four to one in rural streams, to 27 to one in urban streams (EPA, 1986a). it is
noted that lead does not appear to be biomagnified in the food chain, but may accumulate in flora and
fauna. In aquatic organisms, the lead concentrations are typically highest in benthic organisms , such as
algae, and are lowest in the upper-trophic predators (e.g., carnivorous fish) (ATSDR, 1990).
Most lead is retained strongly in soil, and very little is transported into surface or groundwater,
according to reports by EPA (1986a) and the Zimdahl and Hasseti (1977). In soils with a pH 5 having
more than five percent organic content, atmospheric lead is retained in the upper two to five cm of soil,
if it is left undisturbed. EPA (1986a) estimates that four to five million metric tons of lead from gasoline
combustion remain in the dust, soils, and sediments of the U.S. Although lead does have a high degree
of immobility in soil (Zimdahl and Hassett, 1977), wind action may induce mobilization to the atmosphere
and thus downwind transport. This soil entrainment may be of significance to the atmospheric burden
downwind from stationary sources, particularly smelters and superfund sites (ATSDR, 1990).
As noted previously, preschool age children, pregnant women, and their fetuses constitute the
population at highest risk. ATSDR also notes the increase risk to white males aged 40 to 59 years old
(AThDR, 1990). The health endpoint of concern for this latter risk group is hypertension.
ATSDR (1990) estimates the baseline intake for a two year old child to be 466 &g/day, and for
an adult female to be 37.5 .ig/day. Additional exposure results from residing in an urban environment,
proxunity to stationary lead sources, residences and other building structures containing lead-based paint,
pica (eating disorder of some younger children), both primary and secondary occupational exposure,
smoking (from tobacco products containing lead), and wine consumption (for wines containing lead)
Prqjsct hAP— Phs 1 20
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(ATSDR, 1990). In addition, proximity to a superfund site is thought to increase risk of exposure. At
the time of the A1SDR (1990) report, lead and lead compounds had been discovered at 635 of 1,177
National Priority List (NPL) sites.
The levels of lead in the ambient air range from 0.000076 tg/m 3 in remote areas, to over 10 tg/m 3
near stationary lead sources (ATSDR, 1990). Confined places (e.g., parking garages, tunnels, and toll
booths) may have unusually high concentrations of lead in air. In surface waters in the United States,
EPA (1986a) has found typical levels of five to 30 .tg/l. Sediments contain a considerably elevated
concentration of approximately 20 rig/kg (ATSDR, 1990). In ground water, the typical range is one to
100 p.gfl (EPA, 1986a).
EPA (1988b) estimates that 99 percent of 219 million people in the United States that utilize
public drinking water supplies, are exposed to water with levels of lead < 0.005 mg/i, and that about two
million consumers are exposed to drinking water exceeding this value. The range is, on average, 10 to
30 i.g/l in households, schools, and office building drinking water supplies, although corrosive water, lead
pipes, and lead solder joints can, singly or in combination, produce much higher concentrations (EPA,
1989b).
Soils adjacent to roads traveled since 1930 may have as much as 10,000 .tg/g lead (EPA, 1986a),
while soils near homes with exterior lead-based paint may have even higher soil-lead concentrations.
ATSDR (1990) draws upon studies conducted in Baltimore, Maryland, and Minnesota, to conclude that
the highest soil-lead levels generally occur in inner city areas, especially in areas where there has been
an historically high amount of traffic.
Lead is also found in dairy products, meat, fish, poultry, fruits, sugar, and beverages (EPA,
1986a). Canning processes, in particular, can increase the concentration of pre-canned foods from eight
to 10-fold. According to the Food and Drug Administration (Gunderson, 1988), the baseline intake via
food consumption for the years 1982 to 1984 was 23.0 tg/day for a two year old child, 29.6 pg/day for
Proj.et LEAP— Pha.. 1 21
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an adult female, and 40.9 ig.dL for an adult male. Elias (1985), based upon an analysis of food residues
and using the 1984 U.S. Food and Drug Administration’s Marketbasket Survey, postulates total food
consumption to be 25.8 .tgfPb/day (including 2.8 tg/day from water) for a two year old child. For a male
aged 25 to 30 years, Elias estimates a lead consumption of 54.7 jig/day. It is also noted (ATSDR, 1990)
that additional exposure through dietary exposure, from atmospheric dust, is experienced by those living
in an urban environment, at 91 .i day for children, and 28 jLg/day for adults.
Lead content of dusts can be a significant source of exposure, particularly for young children
(ATSDR, 1990). It is estimated that children ingest five times more dust particles than adults do (EPA
1986a). Lead-based paint confounds the problem for young children. EPA (1986a) has found
concentrations of 1,000 to 5,000 pg/cm 2 for lead-based paint chips. Chisolm (1986) estimates that
between 40 to 50 percent of the currently occupied housing in the United States may contain lead-based
paint on exposed surfaces.
Cigarette smoke is yet another source of lead exposure, with each cigarette containing
approximately 23 to 12.2 pg lead (ATSDR, 1990). From two to six percent of the lead may be inhaled
in the smoke. Consequently, given the greater propensity for lead uptake by children, secondary smoke
poses yet another threat to children under seven years of age, as well as to the developing fetus.
Additional exposure to children in the home, as well as to others, is also plausible via secondary
occupational exposure from workers in lead processing industries. Workers may bring home lead dusts
on their clothing.
Other sources of lead exposure, such as housing renovation activity, are also now being more fully
recognized. Marino et al. (1990) reported on an outbreak of severe lead-based paint poisoning in a family
that was exposed to lead dust and fumes generated during the removal of lead-based paint in the family’s
rural farm house. Multiple coats of lead-based paint were being removed over a 10 week period. The
removal methods were sanding, torching, and the use of heat guns. These methods produced wood
Proj.ct LW- Ph 1 22
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particles, fine dusts, and fumes that could be ingested or inhaled. Symptoms were first noticed in the
family dog, found by the veterinarian upon examination to be weak, dehydrated, and depressed. The
animal was determined to be lead-poisoned, and subsequently died. The mother of the family began
feeling weak and tired. The daughter complained of stomach aches in the mornings. The father suffered
severe nausea during weekends of renovation work. All were found to have elevated blood-lead levels.
EPA (1986a) concluded, appropriately, that “... lead is a pervasive environmental contaminant that
causes a wide variety of adverse health effects in humans. In short, lead is potentially toxic wherever it
is found, and it is found everywhere”.
2.5. At Risk Population
Section 118(t) of SARA requires the ATSDR to prepare a comprehensive study on lead poisoning
in children.
ATSDR (1988) noted that much of the data needed to prepare the report was not available in peer-
reviewed literature, and, consequently, was developed specifically for the report to Congress.
In a given year, A1SDR estimates that an estimated 400,000 fetuses are exposed to maternal Pb-B
> 10 g/dL, within Standard Metropolitan Statistical Areas (SMSAs). For other exposures, the estimation
problem is more problematic. AThDR (1988) found that “The actual number of children exposed to lead
in dust and soil at concentrations adequate to elevate Pb-B levels cannot be estimated with the data now
available.” The opinion expressed is that the regulatory actions of the 1970’s to address existing lead-
based paint in housing “have been a clear failure” (ASTDR, 1988). The current average Pb-B levels in
the United States today, in some segments of the population, are 15 to30 times higher than the theoretical
mean value of 0.5 tg/dL, calculated for pre-industrial humans (ASTDR, 1988).
ATSDR (1988) selected 1984 as the base year for estimating the number of children at or above
selected Pb-B levels, because all of the required enumerations were available for that year. The findings
from NHANES II were utilized to derive prevalences for demographic and socioeconomic strata within
Pr J.ct LEAP- Pb e 1 23
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the childhood population, in order to judge the numbers of exposed children. The method was to allocate
the total number in each Standard Metropolitan Statistical Area (SMSA) for selected strata of age, race,
income, and (where possible) urbanization categories. The various strata were then added to obtain
national totals for each strata. Each stratum population number was then multiplied by the prevalence for
the three selected Pb-B levels (using national prevalence rates), adjusting prevalence from 1978 to 1984
levels, to account for the reduction of lead in gasoline. It is noted that NHANES II did not report Pb-B
levels for specific geographic areas, but rather reported for socioeconomic, demographic, and ethnic strata
for the nation as a whole. Consequently, due to the lack of geographic specificity of data, the ATSDR
report considers SMSAs collectively, and not individually. The data (ATSDR, 1988) is further limited
to young white and African-American children, because NHANES II did not include sufficient numbers
of Hispanic and other-race children, in order to enumerate prevalences in those ethnic sub-populations.
The strata analyzed were African-American and white; 0.5- to two-year-old children, three- to five-year-old
children (although these age bands were subsequently merged to derive a 0.5- to five-year-old child age
band); urban status (central city, outside of central city); and family income. The size of SMSA (< or>
one million population) was also provided. It is noted with specificity that just as the ASTDR study
adjusted the 1978 prevalence rates to account for reductions in lead-in-gasoline and lead-in-food from
1978 to 1984, so too are these prevalence rate estimates now overly conservative, due to the further
reductions of lead-in-gasoline and food for today (recall in particular the significant reduction in leaded-
gasoline emissions to 1,100 metric tons by the year 1990).
2.5.1. Spatial/Numerical Estimate of At Risk Population
ASTDR (1988) Pb-B criteria values of 15, 20, and 25 1 tg/dL were as calculated from
NHANES data by EPA’s Office of Policy, Planning, and Evaluation (ASTDR, 1988), using logistic
regression analysis techniques to update prevalences to 1984. Tables are provided, separately for central
cities and outside central cities, on the projected percentages of children 0.5 to five years old that are
PmJ.ct [ ZAP— Ph. 1 24
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estimated to exceed selected Pb-B levels by family income, race, and urban status within SMSAs. The
range is from 36 percent> 15 .tg/dL for white children in populations centers one million and income
< $6,000, to 0.5 percent > 25 tg/dL for white children, with family income >$15,000. For African-
American children, in the same categories, the range is from 67.8 percent> 15 i.tg/dL, to 2.2 percent >25
.tgfdL Similar patterns are presented for children residing outside central cities.
Estimates of the numbers of children in the age band who are projected to exceed the three criteria
levels of Pb-B are provided by family income and race. For central cities, with SMSAs < one million
population, the projections are 301,100 children >15 p.g/dL, 93,800 > 20 .tg/dL, and 27,500 > 25 .tg/dL.
For central cities with SMSAs > one million population, the numbers are even greater, 901,800 children
> 15 tg/dL, 301,700 >20 p.g/dL, and 86,200 > 25 p.g/dL Overall, for the 1984 United States childhood
population of 13,840,000, 2,381,000 are expected to have Pb-B values >25 g/dL (ASTDR, 1988).
Specific concerns with the limitations on accuracy of these projections are noted in the ASTDR report.
In particular, the Hispanic child population is not included, and that population segment is experiencing
high birth and growth rates. Some of this population is associated with lower economic and central city
strata and, consequently, are expected to have higher predicted prevalence rates across the criteria Pb-B
levels. “The most important finding, however, is that no strata of these children are totally exempt from
risk of Pb-B levels high enough to represent a potentially adverse health impact” (ASTDR, 1988).
2.5.2. Lead Screenin2 Programs
Lead has a long history of use by man as well as harm to man, extending hundreds of years back
in time. In this country, not much public concern was evident in the early part of this century. In the
early 1930’s, however, the Baltimore Health Department became interested in lead poisoning (Lin-Fu,
1982). Not much attention was shown by health officials in other cities until the early 1950’s. At that
time, New York, Chicago, and Philadelphia began case finding as well as public education efforts. During
this period through the mid-1960’s, health officials found hundreds of cases of lead poisoning in several
PrqJ.ct LFAP- Phi.. 1 25
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large older cities (Lin-Fu, 1980). These included Baltimore, New York, Philadelphia, and Chicago.
Between 1959 and 1963, Cook County Hospital in Chicago treated 182 children for lead encephalopathy
(Lin-Fu, 1982). Of the cases, 51 died.
A mass of data on childhood lead poisoning was published in the 1950’s to early 1060’s (Lin-Fu,
1982). Most of the public was unaware of the problem. Many in the public health profession failed to
react. According to Lin-Fu (1982), the turmoil and awakening of social conscience of the mid-1960’s
brought a sudden realization of the magnitude of childhood lead poisoning in this country. It was during
this period that it was discovered that lead poisoning was epidemic in the inner city slums (Lin-Fu, 1980).
In 1966, Chicago began the first mass blood-lead screening program in the nation. New York and other
cities did the same. It was also during this decade that health officials unexpectedly discovered
asymptomatic children with elevated blood-lead levels. This discovery sounded an alarm that health care
workers needed to recognize lead absorption in preventing lead poisoning disease, and that subclinical
toxic effects of lead were a concern (Lin-Fu, 1980). The pervasive source of lead exposure in children,
from lead in dust and soil, also became apparent (Lin-Fu, 1992). Childhood screening programs
discovered a high prevalence of elevated blood-lead levels in children that could not be fully explained
by ingestion of lead contaminated paint chips.
The U.S. Surgeon General issued a statement in 1970 which effectively shifted the emphasis of
health care workers from case finding to lead poisoning prevention. He advocated mass screening to find
cases of elevated blood-lead levels (Lin-Fu, 1982). Shortly thereafter, the 1971 Lead-Based Paint
Poisoning Prevention Act became law. The Act provided funds for mass screenings. Mass screening
funded by the Act began in mid-1971. From January 1972 through December 1978, 2,485,320 children
were screened by federally funded projects (Lin-Fu, 1980). Of these, 170,738 children were found to have
elevated Pb-B or EP levels.
In fiscal year 1982, these lead screening programs, along with other public health protection
Pi LFAP- Ph . 1 26
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programs, were incorporated into the Maternal and Child Health (MCH) Block Grant Program (ASTDR,
1988). The screening programs are targeted primarily at case finding for children with Pb-B levels serious
enough to warrant medical intervention. The classification schemes have changed over the years.
Analysis for elevated EP has been the first step in screening, although it is recognized that some children
having elevated Pb-B will pass the EP test; accordingly, the EP screening test does produce false
negatives. Table II, based upon data presented in the ATSDR (1988) report, presents the results of
screening programs in 16 cities in the Midwest region of the country, for fiscal year 1981, using the 1978
Centers for Disease Control classification of lead toxicity of 30 p.g/dL Pb-B and 50 p.g/dL EP.
In 1988 Congress enacted the Lead Contamination Control Act. Among other provisions, the Act
authorized the Centers For Disease Control to Provide grants to States and local health agencies to fund
childhood lead poisoning prevention programs (DHHS, 1991c). The grants are to screen children for lead
poisoning; to ensure environmental as well as medical follow up for lead-poisoned children; and to provide
education about lead poisoning.
PrqJ.et LEAP-Ph...! 27
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TABLE II
Blood-Lead Screening Program Results for Children in 16 Midwest Cities in 19811
Piog ram tacation
,
Number
Screened
Number With
Elevated
‘
32,861
PbB
Chicago, IL
2,070
--
Kankakee, IL
2,464
56
Madison County, IL
2,288
105
Rockford, IL
2,341
30
Waukegan-Lake Col, 1L
3,570
35
Illinois (other programs)
5,184
145
FT. Wayne, IN
532
19
Detroit, MI
19,281
926
Grand Rapids, M I
688
19
Wayne Co., MI
1,818
75
St. Paul, MN
2,107
15
Akron, OH
4,637
149
Qncinnati, OH
9,085
191
Qeveland, OH
14,151
921
Beloit, WI
779
15
Milwaukee, WI
6,640
316
‘Elevated Blood-lead (Pb-B) is based upon the Caiters for Disease Control lead toxicity dasification of & 30 pgAlL Pb-B
and t 50 pgklL erythrocyte protoporphyrin.
Project LEAP— Phase 1
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ATSDR has also compiled the number of lead poisonings determined by screening programs for
fiscal year 1983 (ASTDR, 1988). The numbers of children screened and cases of confirmed lead toxicity,
by state are Illinois: 25,340 and 136; Indiana: 1,265 and 1; Michigan: 14,700 and 434; Minnesota: 1,816
and 18; Ohio: 19,543 and 416 (the number evaluated for lead toxicity did not necessarily include all those
screened who may have been lead poisoned); and Wisconsin: 4,322 and 187 (some of the 187 cases are
estimates by respondents, not necessarily the result of Pb-B testing) (ASTDR, 1988). The cases ranged
from 0.1 to 4.3 percent of the children screened. It appears that the rate of chronic lead poisoning in
young children is decreasing somewhat (ATSDR, 1988). The numbers of children with elevated blood-
lead levels, as well as the percentages of screened children that have lead toxicity, indicates that lead
poisoning is a continuing problem. That conclusion is supported by an analysis of lead-screening statistics
for the Chicago Department of Health from 1981 to 1985 (ASTDR, 1988). That analysis suggests that
there has been minimal change over these years in the percent of children screening positive for lead
poisoning. The prevalence of Pb-B levels above 30 tg/dL in young children sampled by NHANES II was
higher than that which would be predicted from the state and local screening data (ASTDR, 1988). It
would appear, consequently, that screening programs may not be addressing the totality of the at-risk
population.
2.6. At Risk Population Estimates By Sources/Routes Of Exposure
2.6.1. Lead-Based Paint
Qearly the greatest amount of attention and data in recent yeais has been on the contamination
and health problems caused by lead-based paint. A prospective study of inner-city children conducted by
Qark c i al. (1985), that found that children who have the highest Pb-B levels lived in the worst housing.
The housing-quality accounted for more than 50 percent of the Pb-B variability in 18 month-old children.
The study also found that children in public (versus private) housing, near a heavily used interstate
PrqJ.ct LEAP- Ph. 1 29
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highway, had the lowest Pb-B levels. This result indicates that, for the study, air-lead from highways had
only a very limited impact on blood-lead in children. Further, the study found that although rehabilitated
housing contained lower lead paint levels than public housing, children in rehabilitated housing had higher
blood-lead levels than those in public housing, suggesting to the authors that lead sources in the immediate
neighborhood of the rehabilitated housing may be a factor. A more plausible explanation, however, is the
probability of the inadequacy of rehabilitation. Performed incorrectly, such units pose substantial risks
of reexposure of children returned to the housing units.
Chisobn et al. (1985b) found, in a prospective study of children in Baltimore, that children
returned to homes subsequent to lead paint abatement/removal actions, experienced significantly higher
Pb-B levels than children returned to public housing that was free of leaded paint. ATSDR (1988) noted
a “great decline” in the number of very severe cases of lead poisoning in the U.S., but notes that “... the
basic epidemiological picture characterizing paint-lead associated toxicity has not materially changed for
chronic interaction.”
To derive the number of children at risk via this route of exposure, ATSDR’s (1988) method was
to use estimates of the ratio of children under seven years of age per 1,000 housing units, together with
estimates of categories and numbers of lead-painted houses with problems such as peeling paint, broken
or cracked plaster, or holes in walls. Problem dwellings were as defined by the American Housing Survey
of the U.S. Bureau of the Census (ASTDR, 1988). The fraction of total housing units to that of such
defined “problem” units was used to derive estimates of the total number of children in lead-painted
homes, and the number of children in lead-painted homes categorized as problem dwellings. The ATSDR
study used estimates and calculations by Pope (1986), whose efforts addressed four major areas of the
country, including the Midwest.
ATSDR (1988) also notes a comprehensive unit-by-unit study that was conducted in the city of
aiicago in 1978, that assessed the Pb-B levels and the presence of leaded paint in 80,000 individual
PruJsct LEAP— Pb 1 30
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housing units. In general, however, ATSDR found “a general dearth of nationwide studies that estimate
the number of children living in paint-containing homes who have elevated Pb-B levels...” The study
approach was to take the number of children living that the U.S. Census Bureau estimates to be living in
deteriorated housing having 100 percent lead paint, and then to approximate “the most logical” prevalence
for the stratum (as discussed earlier), that would be applicable to children in such housing (ASTDR, 1988).
The stratum chosen was inner city, dense population, and lowest income, with the further assumption that
many of the children in such areas would be African-Amencan.
Paint with a lead concentration 0.7 mg/cm 2 was chosen as the criterion value for distribution,
with an estimation that 99 percent of pre-1940 housing stock, 70 percent of houses built from 1940-59,
and 20 percent of the housing stock built during 1959-74, would exceed this value. Thus, for the U.S.
housing inventoly of 80, 390,000 (1983 Survey, U.S. Bureau of the Census), ATSDR estimates that 52
percent (41,964,000) of the units exceed the criterion value (ASTDR, 1988). Ii is further noted that the
0.7 mg/cm 2 criterion value is based upon a CDC (1985) statement. Pope’s method (Pope, 1986) was used
to classify housing for age groupa by unsound housing (i.e., deteriorating paint).
The study denved, via these considerations, a best national estimate of 1,772,000 children, and
a national upper bound estimate of 1,996,000 children under seven years of age living in unsound lead-
painted housing. For the Midwest region, the derived numbers are (derived from ATSDR, 1988):
Prujict LEAP— Phase 1 31
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TABLE III
Children Under 7 years of age in the Midwest Residing in Unsound Lead-Painted Housing 2
Age of Housing
tnnsr usr —
Housing with Peeling Paint
La —
Number of
———--
Pre-1940
264,000 -
J4 ,000
-
1940-1959
159,000
47,000
-
1960-1974
47,000
14,000
Pre-1980 -
470,000
1 39,000
For comparison purposes, the numbers for all four regions of the nation and all housing, are 1,840,000
housing units, and 520,000 children, it is noted that these estimates (based on Pope’s work) include non-
SMSA housing stock, and exclude potential exposures that may result from renovation of older urban
housing (the so-called urban gentrification phenomenon, as discussed previously, for example, in the study
by Marino et at. of a rural farm house renovation) (ASTDR, 1988), due to an inability to quantify such
units.
A recently released study, the Comprehensive and Workable Plan for the Abatement of Lead-
Based Paint in Privately Owned Housing (HUD, 1990), determined there to be no correlation between
lead-based paint and household income, and that more units have lead paint on the exterior walls than on
interior walls. The national survey estimated that 38 percent of all homes occupied by families with
young children have priority hazards, and notes that blood-lead screening programs reach only five percent
of the young children in the nation.
2 San: The Nature end Extent of Lead Poisoning in Children in the United Statet A Report to Conga AISDR, 1988.
PrqJ.et LEAF — the .. 1 32
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The objectives of the national housing survey were to determine the incidence of lead-in-dust in
dwelling units, as well as lead-in-soil in and around residences; and to define the characteristics of housing
with varying levels of potential lead hazard in order to determine priorities for abatement. The study
population was the United States population residing in pre-1980 housing stock. A statistically based
survey was derived for the nation. A sample size of 284 housing units was chosen to represent 77 million
housing units. The survey assessed interior and exterior paint (concentration and condition) by year built,
the type of housing, the threshold level of lead concentration, and the census region. The stratification
was on type (privately owned single-family and privately owned multifamily) and construction date (before
1940, 1940 to 1959, and 1960 to 1979). The sample units were geographically clustered in 30 counties
(of 3,000 in the nation). The researchers employed X-ray fluorescence (XRF) to test for lead paint
concentration, and also collected and analyzed dust and soil samples. Is is noted with particularity that
XRF does not distinguish between paint lead on the surface and lead beneath the surface (e.g., old paint
under a fresh cover, or lead pipes).
The national survey found that 57.4 million homes, representing 74 percent of the study population
(residing in 77 million homes), contained lead-based paint (LBP 3 ). This included 9.9 million homes
whose families have young children. The percent of LBP housing units by strata was determined to be
90 percent for pre-1940 housing, 80 percent for 1940-59 housing, and 62 percent for 1960-79 housing.
The Midwest census region had 76 percent LBP housing, compared to the 74 percent national value.
Distribution for the housing unit was determined to be 14 percent LBP interior only, 23 percent LBP
exterior only, and 37 percent LBP on both interior and exterior walls (for a total of 74 percent). Thus
lead-based paint was determined to be more common on the exterior of homes.
Nonintact paint was estimated to exist in 13.8 million (of 57.3 million) units containing LBP. Of
‘LBP is defined as greater than of equal to 1.0 mgk m 2 , measured by XRF, in a crdance with the Federal Standard for LBP
eatablisbed in Section 566, Houning and Community Development Act of 1987 (HUD, 1990).
PrqJ.ct LEAP— Ph... 1 33
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the 13.8 million, 5 percent are interior only, 11 percent are exterior only, and 2 percent are estimated to
be both interior and exterior surfaces. Thus, 18 percent of the total housing stock is estimated to contain
nomntact LBP, defined as exceeding five ft 2 of LBP in a dwelling being defective (HUD, 1990). Further,
the paint is estimated to be damaged in 21 percent of units with exterior LBP, and in 13 percent of the
units with interior LBP. Citing the interim guidelines developed by the Department of Housing and Urban
Development on clearance levels for dust, post abatement’, the authors note that fully 17 percent of the
occupied homes that contain LBP exceed the guidelines. Only four percent of the homes free of LBP,
in contrast, were determined to have excessive dust-lead. The chance of having excessive dust-lead if
lead-based paint exists versus no lead-based paint was thus calculated to be 17:4.
Surprisingly, the study found that the incidence of dust-lead is almost as low for homes with
interior LBP only, as for homes with no LBP, while the incidence is approximately the same for units with
interior or exterior LBP. The study concludes, consequently, that interior dust-lead-contamination is more
likely generated by exterior LBP than by interior LBP. The incidence was found to be highest for units
containing both interior and exterior LBP. Most dust was found to be located around windows.
2.6.2. Leaded Gasoline
Recent consumption of leaded gasoline in the United States alone shows that in the 10-year period
from 1975 to 1984, inclusive, this country consumed 654.6 X iO gallons of gasoline, resulting in the
dispersal of 1,087.8 X io metric tons of lead in the U.S. (ASTDR, 1988). “Gasoline lead makes a sizable
contribution (about 90 to 95 %) to the total atmospheric lead burden in developed countries such as the
United States” (ASTI)R, 1988). From 1975 to 1984, however, U.S. gasoline lead consumption decreased
by 73 percent. ASTDR states that studies and data indicate that past gasoline lead consumption resulted
in airborne lead that “added significantly to atmospheric and soil/dust/food burdens, and that via both
direct and indirect rouses, such input contributes 20 to 25% to Pb-B levels.” The pathway can be very
200 pgf& for floors, 500 g/ft 2 for window sills, and 800 ig/ft 2 for window wells (DHUD, 1990).
PrqJ.ct LEAP— Pb 1 34
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significant as a route of exposure for children, with elevated blood-lead to airborne lead concentration
ratios of five to six gIdL Pb-B rise for each p .g/m 3 increase in air-lead concentration. The NHANES II
data supports the high correlation between reduction in leaded-gasoline and the decrease in Pb-B levels
in the general population (ATSDR, 1988).
The methodology utilized for estimating numbers exposed was to restrict the enumeration to the
100 largest cities, where the highest exposures, due to mobile sources (including soil/dust routes of
exposure resulting from past deposition), were expected to occur. For the estimated 1984 population of
50,597,300 residents of these areas, 11 percent (5,565,700) are estimated to be children under seven years
of age (ASTDR, 1988). ATSDR, estimating the numbers of children falling below criteria Pb-B levels,
and then projecting to the year 1990, found that gasoline lead phase down alone, will not be sufficient to
reduce all Pb-B levels down to levels considered to be acceptable. The agency determined that, in the
year 1990, the numbers of children estimated to be below criteria Pb-B levels, as a result of lead in
gasoline phaseout, are 25 gIdL-119,000; 20 jtg/dL-400,000; and 15 p.g/dL-1,252,000 (ASTDR, 1988).
2.6.3. Stationary Sources
This nation has 11 lead mines, five primary smelters and refineries, 60 secondary smelters, and
132 plants, the latter for manufacture of lead-acid batteries (ASTDR, 1988). Soil and dust levels near
these sources range from 500 to 5,000 ppm, with exponential decreases with distance from the source.
A 1977 investigation by Yankel et al. (1977) of one- to nine-year-old children living near a smelter in
Silver Valley, Idaho, clearly demonstrates an association of airborne lead concentration as well as
(elevated) Pb-B levels with distances from the source. That study modeled the natural log of blood-lead,
house dust, soil, age, occupational factors, and air concentration. The researchers determined that 99
percent of the children adjacent (within 1.6 km) to a smelter had Pb-B levels exceeding 40 p.g/dL. Air
concentration alone accounted for 55 percent of the variance in Pb-B levels. A CDC study in two smelter
communities in Montana (CDC, 1986a) and Idaho (CDC, 1986b) found that the only significant
PmJ.ct LEAP— Ph . 1 35
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environmental source causing elevated blood-lead levels in children was lead in the soil and house dust,
resulting from smelter operations. Thus previous fallout remains a main contributor to elevated Pb-B
levels. It is also noted that blood-lead remains elevated even when airborne levels have been reduced to
low levels. Consequently, ATSDR (1988) recommends that closed facilities be included in studies, to
account for the impact of previous lead emissions and deposition.
Based upon previous studies, A1SDR estimates that between 1 and 26 percent of children living
near primary lead smelters would exceed the CDC criteria for lead toxicity of 25 p gIdL Pb-B and 35
p .g/dL EP. Four percent of children residing near secondary smelters would also exceed the criteria values
(ASTDR, 1988). The report quotes an estimate by the EPA Office of Air Quality Planning and Standards,
of 21,000 children exposed via primary lead smelters (within five km of the source), and 187,000 exposed
via secondary lead smelters (within two km of the source). Some 25,000 children are estimated to be
exposed from lead-acid battery plants (within a one km radius), for a total childhood exposure count of
233,000.
2.6.4. Dust and Soils
Brunekruf et al. (1983), in a study conducted in the Netherlands, determined that household dust-
lead concentration increases by 40010700 ppm for each pg/rn 3 rise in airborne lead. This was as reported
by A1SDR, apparently based upon data presented in the Brunekruf study. The Bruenekruf study found
a Pb-B to air-lead concentration of one to two p.g/dL per pg/m 3 . The outdoor measured air values ranged
from 0.10 to 0.27 pg/rn 3 . Soil-lead generally was found to be less than 500 ppm. Dust-lead ranged from
geometric mean values of 58 to 81 pg/rn 2 for two inner city areas studied, with a range of values from
22 to 740 ppm. EPA (1986a) also reviewed reports on the relationship of lead in soil and dust to Pb-B
levels. Generally, the review found that lead in soil and dust of 500 to 1,000 ppm begins to affect Pb-B
levels in children (Baker at al., 1977; Mielke et *1., 1984). The Mielke Twin Cities, Minnesota, study of
inner city areas found that 50 percent of the individuals with lead poisoning lived in housing containing
Prqj.ct LEAP— Pha.. 1
36
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soil-lead levels of 500 to 999 .tgfg, and that 40 percent lived in homes with values of >1,000 gIg. The
authors cite both house paint and leaded gasoline as contributors. The study also found, from right-of-way
soil samples, that lead levels low to high correspond to ligbt to heavy traffic (however, the report did not
indicate a p-value or other indication of statistical significance for this finding). Over half the Minneapolis
homes in the study had soil-lead levels exceeding 50 tg/g. The variability of measured soil-lead
concentrations, sometimes a 100-fold order of magnitude difference in concentrations between the front
and back entrance of the home, was noted as a precaution in interpretation of the soils data. Clark et aL
(1987) determined an increase of Pb-B by 6.2 p.Lg/dL for each 1,000 ppm increase in soil-lead
concentration. Studies (EPA, 1986a) show a range of values, from 0.6 to 6.8 1 tg/dL rise in Pb-B level
for 1,000 ppm incremental increases in soil-lead concentration.
Recognizing that soil/dust information was not available at the time of the report (beyond a limited
number of site specific studies), the (ATSDR, 1988) report authors recommend the use of multiple linear
regression analysis to account for different contributions to a child’s Pb-B level, preceded by a
representative sampling of dusts and soils from the urban and rural areas of each of the nation’s four major
regions. Because such a statistically based representative sampling program was not available at that time,
the report used an admitted overestimate of exposure by combining the major routes: paint lead in pre-
1940 housing with the highest lead content - 5.9 million children; gasoline lead in the 100 largest cities -
5.6 million; and stationary sources - 0.2 million, for a total of 11.7 million exposed children (ASTDR,
1988). A reliable method to apportion Pb-B values to primary contributors was called for by ATSDR.
That call was answered in part by the Comprehensive and Workable Plan (DHUD, 1990) that
derived soil/paint correlations, and speculated about the contributions to elevated blood-lead levels. From
multiple regression and pathway analyses, the HUD report determined that excessive dust-lead levels occur
more often in houses with LBP (intact or not) than in housing without LBP. Elevated blood-lead levels
were associated more often with housing with nonintact LBP on exterior walls, than with intact exterior
PrQJ.ct LEAP— Ph 1 37
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LBP. HUD concludes that young children in homes having nonintact LBP, or excessive dust-lead, are
at highest risk. Of 57 million occupied homes having LBP, less than 10 million are occupied by families
with children under the age of seven. Of these homes, 3.8 million units have high dust-lead levels or
nonintact paint.
According to the survey report, soil-lead is within the guidelines 5 of 500 ppm, 79 percent of the
time that LBP is present. The analysis estimated the numbers of occupied dwellings with soil-lead
associated with the presence and condition of exterior LBP. The percentages of homes exceeding the
guidelines by strata were estimated to be 6 percent for homes with no LBP, 21 percent for homes with
intact LBP, 48 percent for nonintact LBP, and 27 percent with homes containing any exterior LBP.
Overall, 18 percent of 63 million occupied housing units are estimated to have soil-lead exceeding 500
ppm. A strong statistical association was thus found between the presence of lead-based paint and lead-
contaminated soil. The probability of excessive soil-lead was derived as 4:1 for LBP exterior compared
to LBP-free exterior.
The report analyzed hypothesized pathways from paint to dust, by determining the correlation
coefficients between the natural logarithms of the pairs of survey measurements of lead associated with
a pathway. The correlation coefficients determined were paint-on-wall:dust-on-window-sill——0.25; dust-
on-window-sill :dust-in-window-well-—O.46; dust-in-window-wethsoil-at-drip-line-—O.42-O.45; and soil-at-
drip-linesoil-at-remote-location-—O.68. All of the correlations were found to be statistically significant
at or below 0.05, with some at the 0.001 level. Thus, if high lead concentrations were found at one
location, values tended to be high everywhere.
The regression of dust variables on paint variables support the conclusion that paint is one of the
sources of lead in dust. Derived R 2 values to discern the fraction of the dependent variable explained by
‘The DHUD report refers so an EPA interim gwddine having a range of values for i l land uinccnsratron of 500 to 1000
ProJ.ct LEAP— Pb... 1 38
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the independent variables yielded values ranging from 0.11 to 0.30. From the regression analysis, the
authors conclude that lead from exterior paint is brought inside the house, and that lead from interior paint
contaminates the soil outside the house. When the age of housing is added to the regression analysis, that
variable helped explain lead levels in most of the regressions. The older the dwelling, the higher the
estimated lead levels. The regression values ranged from 0.13 to 0.43. HUD postulates that age of the
home “merely proxies for lead-based paint”, and that age may measure other sources, such as auto
emissions. HUD notes, however, the difficulty in estimating the percent of lead in dust and soil that can
be attributed to LBP. From the regression analysis, approximately 20 to 25 percent of the variation in dust
and soil-lead is explained by paint variables (HUD notes that this could be low). Consequently, the source
of most of the lead in soil is not explained by the model.
Thorton c i al. (1990) studied lead in garden soils and household dusts in England, Scotland, and
Wales. They found that 10 percent of the floor dusts exceeded 2,000 .tg/g. The two-year-olds and their
home environs were sampled for inside dust, soil, road soil, wipes, food and water, and venous blood.
The intent of the study was to assess lead intake from dusts in relation to other sources. The study
reported a geometric mean for lead in the surface (zero to five cm) garden soils to be 266 p.g/g and for
house dust to be 561 tg/g. In London, the mean values were 654 Lg/g for soils, and 1010 j.i.g/g for dust.
A highly significant correlation between household dust and garden soil was determined (r= 0.531, p=
0.001, n=4512). Overall, the geometric means were determined to be 11.7 p.g/dL blood-lead; playroom
air 0.27 p.g/m 3 ; bedroom air 0.26 g/m 3 ; external air 0.43 p.g/m 3 ; dust soil 424 p.&g/g; soil 313 .tgfg; dust
loading 60 Lg/m 2 ; handwipes 5.7 ptg; food and beverage 161 p.tg/weelq and water 19 .tg/l. The study
found that the correlation of Pb-B levels with indoor air concentration to be virtually zero. The correlation
of blood-lead levels with dust-lead was determined to be r= 0.34, with water to be r= 0.39, and with soil-
lead to be r= 0.18. The association with dietary variables was found not to be statistically significant.
The researchers used multiple linear regression to assess the relative importance of various sources,
PrQJsct LEAP— Pha.. 1 39
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with the model log Pb-B ( .tg/100 dl) = 0.55 + 0.10 log xi + 0.14 log PbW ( .tg/l) + 0.07 S, where
Pb-B = blood-lead concentration
PbW = water lead concentration
xi = dust loading x rate of hands touching all objects, and
S = 0,1 depending upon whether parents smoked cigarettes or not.
The analysis determined that adding air-lead concentrations, soil-lead concentrations, or dietary-lead intake
gave nonsignificant regression coefficients, and only marginal improvements to the R 2 value. The study
concluded that the Birmingham study for the first time demonstrated a relationship between levels of
environmental lead within the home and blood-lead in a two-year-old child.
In this country, a comprehensive study was concluded in 1987 by the Minnesota Pollution Control
Agency (MPCA) and the Minnesota Department of Health (MPCA, 1987). The report “provides the
results of soil testing throughout Minnesota and blood-lead screening of children residing near sites in
Minneapolis and St. Paul identified by the MPCA as having at least 1,000 parts per million (ppm) of lead
in soil.” The study sampled soils in five major cities and 27 counties in Minnesota, including census
tracts in Minneapolis, St. Paul, Duluth, Rochester, and St. Cloud. A total of 2,485 soil samples were
taken. Overall, 85.8 percent of the samples were found to be <500 ppm 6 . Only 7 percent of the samples
were found to exceed 1,000 ppm. For areas designated as play areas, only five of 564 samples exceeded
500 ppm, and none exceeded 1,000 ppm. For foundation samples (defined as being within five ft of a
structure), however, 53 percent (of 413 samples) exceeded 500 ppm, and 31 percent exceeded 1,000 ppm.
Surprisingly, only 4 percent (22 samples) of the street side samples (generally, the parkway areas adjacent
to the street) exceeded 500 ppm, and only one of 593 samples exceeded 1,000 ppm. As expected, the
study found that samples taken from sites occupied by industrial point sources had very high lead
‘The study notes that sod lead levels om vary by >50 percent, depending upon the (laboratory) anal ydcal method used, and
also that sod samplea from the same yard may vary by a factor of 100. Comequently, the mean soil concentration values are
deemed to be of questionable value.
Pr LEAP- Phi..! 40
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concentrations.
The researchers performed a regression analysis and found a general tendency for streetside soil-
lead concentrations to increase with increasing traffic, but judged the relationship to be weak, with 29
percent of variation in streetside soil-lead concentration attributable to average daily traffic count. The
study also noted that the degree of contamination in the streetside samples, ostensively from vehicular
traffic, is far less than soil-lead concentration along foundations. Maximum soil-lead concentration
accounted for little variation (R 2 = 0.0541, p = 0.0060) of measured blood-lead. The average daily traffic
count accounted for some of the variation in street side lead concentration (R 2 = 0.2888, p= 0.0001). The
report concludes that the relationship between soil-lead and blood-lead appears to be weak.
The Minnesota Department of Health (MDH) also conducted a lead screening program for youths
aged 6 months to 6 years living near the sites with soil-lead concentrations exceeding 1,000 ppm. Of 743
children screened (742 EP test and 656 blood-lead tests), 13 were determined to have lead toxicity in
accordance with the CDC criteria of> 25 j.tg/dL blood-lead and 35 .tg/dL EP. Another 24 had elevated
blood-lead (>25 g/dL Pb-B but <35 &g/dL EP), and 65 were determined to have iron deficiency.
Twenty percent (134) of the inner city children tested had Pb-B equal to or exceeding 15 .tgIdL. The
Minnesota Department of Health noted that the children tested “live in older, poor, inner city
neighborhoods dominated by lead painted housing, high traffic density, and the highest residential soil-lead
concentrations found in the study.” The average blood-lead level of screened children was 10 p .g/dL,
which the study compared to the NHANES 1980 national average Pb-B of 16 p.g/dL for children under
five years old.
2.6.5. Drinkmnn Water
Most contamination via this source results from domestic plumbing and plumbing in public
buildings, including lead pipe connections, lead-based solder in copper plumbing, and corrosive water in
plumbing (ASTDR, 1988). Water fountains and drinking water coolers in schools and other public
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buildings are potentially important sources, as well. EPA (1986a; A1’SDR 1988) and ATSDR (1988) note
that lead is absorbed in the human body at 35 to 50 percent from water, compared to 10 to 15 percent
from food; consequently, lead in water poses a three to five multiple risk compared to food having the
same lead concentration. Lead absorption rates are even higher for children, resulting in even higher
increased risks of exposure. EPA (1986b) estimates that 42 million people in the U.S. may be exposed
to lead in drinking water exceeding 20 pg 1 at the lap. This is based upon 772 samples from a random
grab sampling program conducted in 580 cities in 47 states. Data from this survey indicate that 16 percent
of water from U.S. kitchen taps exceed 20 pg / I, noting also a problem of lead leaching from new water
connections, that was not considered in the swvey. In addition, the survey did not consider drinking water
from water coolers in séhools, another documented potential source of lead contamination.
ATSDR (1988) assessed exposure by age of housing stock, considering the use of lead pipes for
pre-1920 homes, iron pipes for homes built between 1920 and 1949, the use of lead solder during the
period 1950-1984, and that fresh solder may have been used during the two most recent years preceding
the ATSDR report, 1985-6. Using this approach, the estimated population at risk is set at 1.8 million
children in new housing, and 4.89 million in older housing (assuming 1\3 of the housing built before 1939,
or 10 percent of the housing stock) contained lead pipes. The effects of corrosivity are also noted. From
the 42 million people estimated to be exposed above 20 p.g/dL (thought to result in an increase in Pb-B
levels), 3,780,000 children (9 percent of 42 million) are estimated to be exposed. Levels in drinking water
can be high (up to 1,000 p.i.g/l) due to leaching of lead from lead pipe and leaded solder Joints (EPA,
1991a). The concentration varies with the amount of lead in the plumbing and with the comsiveness of
the water. Soft or acidic waters tend to be more corrosive, and consequently tend to contain higher
concentrations of dissolved lead. An analysis performed for the Environmental Protection Agency, which
included public water supply systems’ data for the States of Indiana, Michigan, and Minnesota, indicates
that these states have only 1.6 percent of the public water suppliers delivering highly corrosive water (EPA
PiuJsct LEAP— Phi.. 1 42
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1988). In general, water with a pH of eight or above and high alkalinity is less corrosive than water with
a pH < eight and low alkalinity (highly corrosive) (EPA, 1991b). EPA estimates the water from lead
service lines to be 10 gfl for water systems with highly corrosive water, and five g/l for systems with
moderately corrosive water (Memorandum, Cohan, 1991). In an EPA (1986b) analysis of the benefits of
reducing the lead in drinking water standard, EPA estimated that 241,000 children had blood-lead levels
exceeding 15 .tg/dL due to lead in drinking water (as a result of the action of corrosive water on aged
piping), including 11,000 having Pb-B levels exceeding 30 .tg/dL.
2.6.6. Lead in Food
Lead enters food processing mainly through lead-soldered cans, which practice was to be phased
out beginning in the late 1970s (ASTDR, 1988). Studies have found varying levels of lead intake in
children, based upon foods consumed. Recognizing the centralized food distribution in this country, that
all children (indeed the entire population) are exposed via this route, ATSDR estimates that 9 percent of
the 1985 population, or 21 million children, are exposed by food intake. By making a series of
assumptions and relying on the results of previous surveys, the report estimates that a maximum of 5
percent of children five months to six years of age are “at or approaching a dietary lead exposure that
pushes their body burden close to that associated with early toxicity if they are also exposed to other
typical lead sources” (ASTDR, 1988). The continual decline of lead in food, however, is noted, along
with a myriad of uncertainties associated with the five percent estimate. By excluding children zero to
five months of age, the population estimate of 21,405,000 (citing the World Almanac 1987) is reduced
to 19,474,000. A 5 percent exposure rate would then result in 973,000 children at risk, based upon an
Pb-B increase of 10 g/dL
2.7. Special Concern For Exposure Řf The Fetus
To estimate exposure of the yet-to-be-born, ATSDR considered women in SMSAS of childbearing
age for the year 1984, with four strata: white and African-American women, and age ranges 15-19 and
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20-44. Using estimated prevalence and logistic regression to extend NHANES II Pb-B levels in the
general population to the year 1984, the authors then applied the prevalence to the four strata for 1984.
The resultant geometric mean Pb-B levels were 3.4 j.tg/dL for white females 15-19 yeais of age; 5.2 tg/dL
for white females 20-44 years old; 5.1 xg/dL for African-American females 15-19 years old; and 7.3
ig/dL for African-American females 20-44 years of age. An estimated 41,300,000 females are thought
to be in the four strata. ATSDR estimates that 3,595,000 could be pregnant (in a given year), with
403,200 (at risk annually, for fetuses of white and African-American women living in SMSAs) having Pb-
B levels 10 .ig/dL; 69,400 15p.g/dL; 14,500 20 p.g/dL; and 3,800 25 g.tg/dL. The report
acknowledges both overestimation and underestimation errors due to the limitations of methodology, data
availability, and assumptions. Estimations were not calculated for individual SMSAs.
2.8. Special Emphasis: Ethnicity
A crucial finding of the ATSDR (1988) study is the substantial difference in estimated prevalence
of blood-lead levels based upon ethnicity. The Agency provided projected percentages of children 6
months to 5 years old expected to exceed 15, 20, and 25 pg/dL Pb-B, who live inside central cities of
Standard Metropolitan Statistical Areas with populations greater than one million. The starkest difference
is at the lower socioeconomic level with annual family incomes of less than $6,000. For African-
American children, an astounding 68 percent are projected to exceed 15 .ig/dL Pb-B, compared to 36
percent for white children. A difference is indicated across all socioeconomic strata. For annual family
income exceeding $15,000, 26.6 percent of African-American children are projected to exceed 15 p.tg/dL ,
contrasted to 7.1 percent for white children. This is compelling evidence of an increased exposure risk
for African-American children. Because the projections rely upon NHANES II data, a similar comparison
was not provided for Hispanic children. Data were not available from NHANES for such analyses. It
is plausible, however, given similar socioeconomic circumstances of the African-American and Hispanic
population, that Hispanic children could also be at increased risk of the harmful effects of low-level lead
PruJ.et IL P- Phiae 1 44
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exposure. There is, moreover, city specific analyses, based upon blood-lead screening programs, to
support this contention.
Evidence that suggests that elevated blood-lead values are a significant concern in the Hispanic
community as well as the African-American community is based upon screening programs, rather than
upon epidemiological studies. Fernadez et a!. (1990) studied the demographic patterns of 485 lead-
poisoned children in the City of Chicago. Ninety-four of the cases studied were minority. Their analysis
indicated that African-American and Hispanic children are disproportionately affected by lead poisoning.
The study found that 69 percent of the cases were African-American children, and that 25 percent of the
children were Hispanic. In contrast, chicago’s African-American population is 41 percent, and the
Hispanic population is 17 percent. The analysis found that even in community areas with a “fairly even
racial/ethnic composition”, African-American and Hispanic children suffered disproportionately from lead
poisoning. The authors noted limitations in the analysis. The sample data were not representative of the
entire population of the city. True incidence could not be calculated. Further, the data was sometimes
incomplete. The relationship to socioeconomic characteristics of the neighborhoods studied was also
noted.
Data from the Minnesota Department of Health 1986-87 Blood Lead Survey supports this
conclusion (Memoranda, Benson, 1991). The survey was conducted for 451 children in Minneapolis and
584 children in St. Paul. Data for St. Paul indicated an average blood-lead value of 9 g/dL for African-
American children, and 7 .i.g/dL for both Hispanic and white children. The population size for the latter,
however, was quite small at 7 children. For Minneapolis, the average values were 9 tg/dL for African-
American children also, but 8 .tg/dL for white children, and 12 p.g/dL for Hispanic children. Overall, for
five Minnesota cities including Minneapolis and St. Paul, the analysis determined the percent of those
screened exceeding 10. j tg/dL blood-lead. The percentages were 33.3 percent for African-American
children, 25.7 percent for white children, and 43.9 percent for all others (including Hispanic, but excluding
PraJ.ct LEAP— Phase 1 45
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American Indian children). The author notes also that the screened children are not necessarily
representative of the entire population of the cities.
The Public Health Service (PHS), in Healthy People 2000 (Health and Human Services, 1991a),
has set an objective to “Reduce the prevalence of blood-lead levels exceeding 15 p.g/dL and 25 p.tg/dL
among children aged six months through five years to no more than 500,000 and zero, respectively.” The
baseline for the objective is an estimated three million children with Pb-B levels exceeding 15 .tg/dL, and
234,000 children with Pb-B levels exceeding 25 tg/dL, in the year 1984. The 1984 baseline of inner-city
low-income African-American children (having an annual family income <$6,000 in 1984 dollars) was
234,900 exceeding 15 .tg/dL (with a year 2000 target objective of reduction to 75,000 children), and
36,000 children exceeding 25 g/dL (with the corresponding year 2000 target objective of a reduction to
no children). The Public Health Service refers to this as a special population target. Such a special
emphasis is supported by the findings of Danford et al. (1982a). Danford and her colleagues found, in
a study population consisting of mentally retarded individuals, that 30 percent of African-American
children aged one to six years have abnormal ingestion behavior, compared to 10-18 percent in the same
age strata for white children. Danford (1982b) notes, however, that interpretation of survey results on the
incidence of pica is complicated by several factors, including limitations on statistical methods used,
inconsistent definitions of pica, and (statistically) small numbers of subjects. Danford also cites a cultural
hypothesis for pica. In some African cultures, the consumption of soil during pregnancy is thought to
suppress nausea. She asserts that, “given the deeply ingrained geophagy of the African cultures that
supplied the bulk of slaves to the New World, it is not surprising that the practice persists in the black
subculture of the United States.” Consumption of lead-contaminated soil, as a conscquence of such
practices, would cause elevated blood-lead levels.
PHS further, in its Strategic Plan for the Elimination of Childhood Lead Poisoning (HHS, 1991),
asserts that “Poor, minority children in the inner cities, who arc already disadvantaged by inadequate
PrnJ.ct hAP- Phi.. 1 46
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nutrition and other factors, are particularly vulnerable to this [ lead poisoning] disease.” The Strategic Plan
focuses heavily upon lead poisoning because of its importance to public health protection.
Needleman (1990) speculates about the social cost of exposure, based upon his ongoing study of
a cohort of children followed into the 19th year of life. Needleman and David Bellinger had found, when
the cohort was in grade five, that the incidence of grade retention at that time was significantly higher in
the high (blood) lead group. Further, the attention span of the high lead group was disturbed. Needleman,
in retesting 132 of the children, found the relative risk for not graduating from high school, associated
with lead, to be 4.8. He asserts that the high lead group in adult years are clumsier, have poorer reading
scores, more depression, and higher rates of hard drug use (no statistical presentation, however, was
provided in the paper). Further study is to be done. Bellinger et al. (1990) add that “Children already
stressed by sociodemographic disadvantages may be less able to weather the additional stress of high
prenatal lead exposure.”
The Needleman analysis also indicates that lead is associated with increased risk for attention
deficit disorder (ADD) (attributable risk of 0.51), and that attention deficit disorder in turn is a risk factor
for antisocial behavior. Needleman determined the attributable risk for antisocial behavior, given ADD,
to be 0.58. Using these findings, he postulates a joint probability of delinquency, given lead exposure,
to be that 20 percent of (juvenile) delinquency is lead-associated. He is currently examining this
relationship.
2.9. Research Needs
The Public Health Service (HHS, 1991b) calls for research studies to determine the relative
contributions of various pathways of lead to children’s blood-lead levels, particularly from paint, dust, soil,
air, food, water, parental occupations, and hobbies. HHS notes particularly that the dietary contribution
of lead in calcium supplements, especially when consumed by pregnant women, should be assessed.
The ATSDR (1988) report aptly deScribes the current situation on lead exposure: “A: the same
P J.ct LEAP— Pha .. 1 47
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time that progress is being made to reduce some sources of lead toxicity, scientific determinations of what
constitute safe’ levels of lead exposure are concurrently declining even further. Thus, increasing
percentages of young children and pregnant women fall into the ‘at-risk’ category as permissible exposure
limits are revised downward Accompanying these increases is the growing dilemma of how to deal
effectively with such a widespread public health problem. Since hospitalization and medical treatment
of individuals with Pb-B levels below approximately 25 &g/dL is neither appropriate nor even feasible,
the only available option is to eliminate or reduce the lead in the environment” (emphasis added). In
concluding its report to Congress, ATSDR (1988) cites the need for comprehensive studies, at the regional
level, of the impact and geographic distribution of lead sources upon exposed populations.
The need to eliminate low-level environmental sources of lead is clear. Far too many children
are still exposed to concentrations of lead in dust and soil that cause unacceptable blood-lead levels. A
lessor number are exposed to excessive air-lead and lead in drinking water. The relatively higher risk that
confronts African-American and Hispanic children, compared to the general population, is also apparent.
It is uncertain, however, where these children are located, and in what numbers, due to such environmental
exposures. Gathering actual data for all environmental pathways of exposure for the entire population is
neither practical nor feasible. Even creasing such a data base for the much smaller minority childhood
population would be a daunting task. Consequently, as an alternative, a population screening methodology
So guide public health officials to geographic areas where children are at high risk, is needed.
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3. STUDY OBJECI1VES
Children under seven years of age having low blood-lead levels, resulting from environmental
exposures to lead from multiple pathways of exposure, experience a significant health threat. Further, the
danger posed to specific communities within the Midwest region of the nation, is oftentimes not detected
via either environmental monitoring of exposures to lead and lead compounds, or via biological
measurements such as ascertainment of blood-lead levels. Consequently, large numbers of children at risk
to low level exposure to lead are undetected and thus, unprotected.
OBJECTIVE 1: Develop a population comparative risk approach for estimating the number and location
of African-American and Hispanic children under seven years of age, at risk of exposure to lead with
blood-lead levels exceeding 10 tg/dL Include a “hot spot” selection scheme that accounts for all known
routes of environmental exposure to lead.
OBJECTIVE 2: Conduct an analysis to ascertain the predictive ability of the approach for selecting “hot
spot” areas, by comparing modeled blood-lead levels to measured blood-lead levels.
OBJECTIVE 3: For a selected city, examine the association of elevated blood-lead levels with proximity
of children to transportation corridors (lead exposure due to historical deposition of lead in gasoline and/or
current emissions from mobile sources).
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4. METHODOLOGY
4.1. Study Scope and Methodology Overview
In 1987 the USEPA published a document entitled ‘Unfinished Business”, which provided a best
professional judgment review of agency programs and environmental problems from the perspective of
comparative risk. Since that time, each individual medium program office at USEPA headquarters, as well
as each of the 10 regional offices, were tasked with development of a comparative risk analysis pertinent
to the program or geographic region of concern. The intent of the approach was to discern and prioritize
environmental problems affecting human health and the environment, to determine whether Agency
programs were adequately addressing the existing and emerging environmental concerns, and to assess
whether resource shifts (generally at the margin) could impact priority environmental problems that
otherwise would not be addressed. The Region 5 office’s comparative risk study was completed in the
summer of 1990. Several cross-cutting concerns were identified. Lead was identified by several program
areas as one of the multi-program pollutants of concern. The region selected lead as a priority area, and
tasked the program managers, and a project director, with development of a comprehensive strategy and
implementation plan to address and remediate lead contamination in the six state region.
The group recognized that lead poisoning in children is now considered to be a national epidemic
by many in the public health community. Lead exposures from exterior and interior residential paint, in
particular, as well as exposures from contaminated soils and dust in and around structures present in most
urban areas, drinking water, air emissions, food, occupational settings, and hobby activities, result in
multiple pathways of exposure. These exposures are responsible for a number of adverse health effects
in humans, especially in children. Because children are at elevated risk a targeted population has been
chosen to be children under seven years of age. Within this population group, African-American and
PrqJ.ct LEAP— Phi.. 1 50
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Hispanic children are particularly targeted in recognition of increased body burden susceptibility and thus
vulnerability to the uptake and effects of lead exposure.
Project LEAP is a multi-media and multi-program approach having four basic components: data
analysis and targeting; pollution prevention; education and intervention activities; and abatement activities.
The project is being implemented in three phases. It is a component of the Agency Lead Strategy. Project
LEAP Phase 1 focuses on data analysis, air modeling of major sources, prioritization of sources and areas
for targeting purposes, and selection of geographic areas for attention during the subsequent phases of the
Project. Phase 2 will focus upon specific geographic areas of concern with an emphasis upon on-site
measurement, e.g., of soil and dust concentrations. Phase 2 will also include continuation of pollution
prevention efforts, and initiation of public education and outreach efforts in coordination with other
agencies. Phase 3 is envisioned to be actual abatement activities for a selected communicity.
Lead exposures from exterior and intenor residential paint, in particular, as well as from
contaminated soils and dust in and around structures present in most urban areas, drinking water, air
emissions, food, occupational settings, and hobby activities, result in multiple pathways of exposure.
These exposures are responsible for a number of adverse health effects in humans, especially in children.
Because children are at elevated risk, a targeted population has been chosen to be children under seven
years of age, as well as the fetus. Within this population group, African-American and Hispanic children
are particularly targeted in recognition of the vulnerability of this population to the uptake and effects of
lead exposure.
The approach of this effort was to estimate the probability distribution of blood-lead in childhood
populations. Determination of severity for each city would then allow for comparisons of geographic
areas. For each metropolitan statistical area central city, environmental data were obtained for the major
sources/routes of exposure (i.e., point sources of air emissions, municipal waste combusters as a special
case categorical source of air emissions, ambient air quality measurements, drinking water supplies, and
PrQJ.ct LEAP— Ph... 1 51
-------
operating as well as abandoned hazardous waste sites). Where available, actual concentrations were used.
Default values were established for each environmental medium where actual measurements had not been
taken. Sensitivity analyses were conducted to assess the impact of assumed (default) values on the blood-
lead uptake estimate.
Demographic information was obtained from a geographic information systems application
(derived and provided by the Geographic Information Systems Management Office, Region 5, EPA).
Information was provided at the census tract or community area (aggregation of census tracts) levels for
each city. Environmental data (i.e., media concentrations) associated with each tract were provided in
order to calculate blood-lead level distributions in affected populations.
A single geographical area, Minneapolis, t. Paul, Minnesota, was selected to test the viability of
the approach. That area had measured blood-lead levels available, along with pertinent demographic
information. A simple correlation analysis was conducted to ascertain whether modeled blood-lead levels
were associated with actual measured blood-lead levels. An association would indicate the viability of
the approach in comparing cities.
Based upon environmental concentrations for each census tract/community area, the Uptake
Biokinetic Model (described in Section 5.5) was run to calculate an expected percent lead exceedance for
the pertinent area. The percentage, applied against the population data for the tract, provided an estimate
of the number of children under seven years of age at risk. Further aggregations of geographic areas
provided city totals.
4.2. Study Area
The Study area includes 83 cities located in 60 metropolitan statistical areas in the Midwest. These
cities represent the central cities in all of the metropolitan statistical areas in the States of Illinois, Indiana,
Minnesota, Wisconsin, Michigan, and Ohio. Each city is shown, along with selected demographic
information, in TABLE IV.
PrQJ.ct LEAP—Ph...! 52
-------
TABLE IV
Metropolitan Statistical Area Central City Demographi&
— :
I Whiic African. flispani Bittt
Rock Island 43,720
82.48
-
15.18
3.36
F
695
15.3 II
Moline 44,500
95.64
1.17
5.38
667
14.5
Chicago 3,005,072
49.59
39.83
14.05
53912
18.0
Kankakee 27,220
70.53
28.19
1.08
543
19.1
Peoria 110,290
81.49
16.69
1.39
1931
16.5
Bloomington 46,250
92.80
5.70
1.38
860
18 5
Normal 36,790
91.99
6.07
.79
368
9.8
Champaign 59,180
84.52
12.74
1.23
800
13.3
Urbana 35,770
84.08
9.99
1.76
560
16.4
Rantoul N/A 8
Springfield 100,290
88.04
10.79
.66
1817
17.9
E. St. Louis 49,470
4.16
95.56
.94
1474
28.7
Granite City 35,150
98.76
.20
1.61
560
15.7
Rockford 135,760
84.27
13.19
2.89
2294
16.8
Ibta1 $třte
otiUb a ř < >.
ij11.i .u
Gary 136,790
25.16
jj;j
.:•: .: . .
70.84
q
:.:• . .. . .. .. ... . . :.:... .
7.10
2574
.
18.0
Hammond 86,380
89.48
6.40
8.30
1224
13.7
E. Chicago 36,950
47.85
29.66
42.27
617
16.6
South Bcnd 107,190
79.50
18.29
2.36
1862
17.4
Mishawaka 41,400
97.93
1.08
.71
602
14.6
44,180
86.02
12.56
1.28
866
20J
Goshen N/A
‘Sour : County and City Data Book 1988 U.S. Department of Commen , Bureau of the Census.
‘N/A not available. Data w not attainable for theae cities.
II
I’
II
Pi j.ct LFAP— Ph.. 1
53
-------
I
Afr 1can ’ .
. Hi sp an ic
Bbth .
Amencan
1%4
• rate per
:1,000
.Po .
..
• .
Ft. Wayne
172,900
83.24
14.55
2.20
3166
19.1
La Fayette
44,240
97.14
1.63
1.14
848
19.2
Kotomo
45,610
90.57
—_85.65
8.11
1.41
843
18.6
Anderson
61,020
13.70
.63
828
13.4
Muncie
Indianapolis
72,600
719,820
89.47
77.10
9.54
21.78
.80
.88
969
12812
13.1
18.0
Terre Haute
57,920
90.11
8.49
.77
891
15.2
Bloomington
- 52,500
91.10
4.31
139
688
13.2
Evansville
129,480
90.36
8.83
.49
1954
15.0
New Albany
94.32
5.19
.61
566
14.9
Ibtait State N
of Ind iana .
5504 ,000
>
t1
US
tSP
$0084
t4 6
Saginaw
72,470
—
57.37
.
35.55
9.01
1557
21.1
Bay City
39,700
—__94.69
1.79
4.68
701
17.6
Midland
35,890
96.26
139
142
537
14.2
Muskegon
Grand Rapids
— 39,810
— 186,530
76.04
80.93
21.42
15.73
2.98
3.16
867
3937
21.9
213
Lanc ing
128,980
80.42
13.94
632
2566
20.1
East Lansing
— 48,120
90.31
5.22
1.80
404
- 8.6
Flint
— 145,590
56.17
—- 41.43
249
3129
21.0
Detroit
1,086,220
34.38
63.07
2.41
18523
17.0
Ann Arbor
107,810
85.10
- 9.33
2.08
1414
13.1
Battle Creek 54,080
75.00
22.79
1.90
948
17.4
Jackson 36,970
82.45
15.43
2.03
705
18.7
Kalamazoo — 77,230
81.40
15.60
1.87
1416
18.3
1
Prujiet LW— Phase 1
54
-------
City
.i•.. •
: •: i•
I
MOOrhead
:f ..
: .
••
Population
. : •• •
:• • ::
I I ;
28,360
e
I
97.80
%
Anie ican
---- - - -
.46
%
Daa
• .
— :
1.02
total Birth
B
1 4• . i,ocx
•
426 14.6
Duluth
82380
96.98
.83
.45
1298
15.2
St. Cloud
42,850
97.70
33
.44
718
17.1
Minneapolis
356,840
87.30
7.66
1.26
6301
17.6
St. Paul
263,680
90.01
4.92
2.91
5040
19.0
Rochester
lbt*t State
orMbrneaot
- 58,130
4075,970
97.37
96J6
.65
131
.71
.79
1297
71
22.3
16 0
Toledo
340,680
80.06
17.41
3.01
5594
163
Cleveland
535,822
53.55
43.80
3.10
10162
18.6
Akion
222,060
76.78
22.23
.65
3451
15.2
Lorain
72,210
79.44
11.89
14.36
1114
15.3
Canton
87,110
83.06
15.99
1.31
1508
16.9
Steubenville
23,580
84.72
14.25
.72
319
13.1
Wheeling
N/A
Marietta
N/A
Youngstown
104,690
64.43
33.34
332
1641
15.2
Warren
52,900
8112
1&13
.66
934
17.3
MansfIeld
51,340
83.08
16.05
1.11
955
18.4
Lima
45,990
78.72
20.41
1.10
881
19.1
Dayton
178,920
62.05
36.89
.86
3535
19.5
SpringfIeld
69,500
81.87
17.24
.73
1158
16.5
Columbus
566,030
76.24
22.11
.82
10406
1&4
Hamilton
65,050
91.75
7.16
.69
1208
18.9
Middletown
46,090
8&00
11.57
.46
818
18.7
Cln nn
369,750
65.15
33.85
.78
7312
19.7
PrqJ.ct LEAP— Pb. 1
55
-------
Eau c laire
54 ,580
9&66
.25
.38
793
14 3
Wan
3Z24 0
98.80
.07
.30
519
1 6 3
Green Bay
93 ,470
97 .25
.25
.68
1542
17.1
Oshkosh
51 ,190
98.35
. 5 9
32
741
14.8
Neenab
N/A
M i lwaukee
605,090
73.34
r io
4.10
11800
19.0
Racinc
82 ,440
81.91
14.74
.34
1642
19.7
Kenosba
74,960
93.89
3.62
4.00
1232
16.3
Madi son
175,830
94 .33
2.70
1.31
2580
15.1
Jancsville
51,790
98.95
.22
.71
901
17.5
Beloit
33 ,760
86.99
1130
1.00
583
17.1
LaGossc
47,650
98.75
.29
.48
710
14.9
Sheboygan
47,410
98.28
.12
1.60
812
17.0
App le ton •_ . — -
$%.)
ipt i ;
98 .27
: 3 .C
____________
.08 .55
cL . a
I
1 052 • 1&9
731$1
Png.ct LEAP— Pbs. 1
56
-------
4.3. Conthbution to Childhood Lead Levels From Air Emissions
4.3.1. Industrial Source Complex Long Term Model
Air-lead concentrations resulting from significant point sources were estimated using the Industrial Source
Complex Long Term (ISCLT) Model, Personal Computer Version. The model is an advanced Gaussian plume model
that uses the steady-state Gaussian plume equation for a continuous source to calculate concentrations for point
sources. The model uses statistical wind summaries to calculate seasonal or annual concentration values, and a wind-
profile exponent law to adjust the observed mean wind speed from the measurement height to the emission height
for plume rise and other parameters. Plume rise is calculated due to momentum and buoyancy as a function of
downwind distance for stack emissions. Pasquill’s method is used to account for buoyancy induced dispersion.
The ISCLT requires input data arrays of the joint frequency of occurrence of wind speed and direction for
each Pasquill stability category and season (when the season option is selected); an array of the mean ambient air
temperatures as a function of stability category and season; and an array of the median mixing layer heights as a
function of wind speed, stability category, and season. Source specific information needed includes emission release
rate, stack height and diameter, gas exit velocity, and gas exit temperature. The “regulatory default” option of the
model was selected for the analysis. The regulatory default option includes final plume rise at all receptor locations,
stack-tip downwash, buoyancy induced dispersion, default wind profile coefficients, default vertical potential
temperature gradients, and revised wake effect procedures.
The particle size distribution was added to the model, in accordance with Agency recommendations
(Rothblatt Memorandum, “Refined Metals Lead Modeling Analysis, December 8 1989), as shown in Table V. This
particle size distribution provides a better estimate of the actual particle sizes expected, in comparison to the default
particle size distribution In the ISCLT model
Project LEAP— Phase! 57
-------
TABLE V
Particle Size Distribution Input to
Industrial Source Complex Model
1
.
.. :.
..:
Mean Mass Diameter
..:: ....
.079
ScuIin Velocity
.000129
Setthn
.:.
.237
Reflection
Co
1.0
4.08
.00363
.157
1.0
11.1
.0262
.68
20.4
.0877
.20
.52
30.27
.194
.16
.26
40.19
.342
.12
0
50.15
.532
.08 —
0
60.11
.764
.04
0
Meteorological input arrays were obtained by the following process. Surface meteorological data
files were obtained from the National Climatologic Data Center weather monitoring stations closest to the
source to be modeled, along with upper air data files. A “STAR” (Stability Array) program was run on
each set of meteorological data in order to convert the data into the format used by the !SCLT model.
The STAR program converted the raw meteorological data into the proper format required by the ISCLT
model for the joint frequency of occurrence of wind speed and direction for each Pasquill stability
category A through F. A file of hourly temperatures was also created. The temperature and upper air data
files were further processed using a statistical analysis program to derive the mean air temperatures and
mixing layer heights, and to calculate the median mixing heights by stability and wind speed categories.
The statistical analysis program was used as a convenient method for calculating mean and median values,
and for sorting data for use by the ISCLT program. The three data arrays were incorporated into a single
file specific to each source.
PrqJ.ct LEAP— Ph. 1 58
-------
Emission rates are those reported in the Toxics Release Inventory data base for 1988 (raw data
was retrieved from the U.S. EPA national computer center). Steady-state emissions were assumed for the
source to calculate a gram per second emission rate from the annual loading.
The Aeorometric Information and Retrieval Facility Subsystem (AIRS-FS) was utilized as the data
source for facility specific information on physical properties of emission releases, that were required to
model emissions at 17 selected facilities. As an approximation, multiple stacks were combined into a
single stack by weight-averaging emissions. For modeling purposes, the derived stack height, stack
diameter, temperature of gas at release, and gas exit velocity were used, together with the Toxic Release
Inventory (TRJ) reported emission rate for the facility. The AIRS-FS also contained emission data for 532
sources of lead emissions. That information, however, was deemed inappropriate for use by the project.
Much of the data had been estimated. The estimation factors are currently being updated. The use of the
quantity of lead data in AIRS-FS, based upon the existing emission factors, would provide questionable
results. Consequently, quantity emission from the TRI data base was used. Stack height, stack diameter,
and stack gas exit temperature were obtained from the AIRS-FS data base for eight of the 17 sources:
LaClede Steel Co., Alton, Illinois; Chemetco, Inc., Hartford, Illinois; Refined Metals Corp., Beech Grove,
Illinois; Quemetco, Inc., Indianapolis, Indiana; Inland Steel Co., East Chicago, Indiana; Kohler Co.,
Kohier, Wisconsin; Gopher Smelting and Refining Co., Eagan, Minnesota; and North Star Steel, St. Paul,
Minnesota. The ISCLT model was run for these sources, and for the additional seven sources using
default values.
4.3.2. ISCLT Sensitivity Analysis
Recognizing that upper air data (used to discern mixing heights in the model) are available for a
very small number of weather stations (Flint, Michigan; Dayton, Ohio; Green Bay, Wisconsin; and St
Cloud, Minnesota) for 1988, the ISCLT model was run using each, and the resulting lead concentrations
compared at the four locations. The locations included x and y coordinates (-2000,2000), (0,2000),
Project LEAP— Pha.. 1 59
-------
(200,0), and (2000,2000) in meters (Figure 1). The Flint, Green Bay, and St. Cloud upper air stations
(resulting in three observations for each x,y coordinate location) provided extremely close air-lead
concentrations, as shown in Table VI. Running the ISCLT model with data for the three upper air stations
results in a mean value of 1.693 .tg/m 3 air-lead. The standard deviation of 0.004 is quite small.
Consequently, the choice of upper air station for inclusion in the modeling of air-lead concentiations is
basically irrelevant, especially given the other assumption made in order to run the model. Green Bay,
which provided values close to the mean values, was selected.
ISCLT Point Source Grid
Oist.aioa From Point Sour..
2 00C
1580
-
(-2000.2000)
-
(200,2000)
(2000,2000)
-
1000
.
._..... . ..
.
.
-2 -1 o (2OO,0) 2 3
Distance From Point Source (Thousands)
Rscsptor Ps$t
1801.1 I.dus*. Sour.. G,.u$sn Long Tirm)
Figure
Industrial Soune Complex Long Term Point Source Grid
PrqJsct LEAP— Ph e 1
60
-------
TABLE VI
Upper Air Data Analysis
Analysis Variable: Lead Concentration
Locat ion
of ;y
No of
Observations
Mtnzmwn
( j ig/tn ’)
Maximum
( j i g /rn 3 )
Mean
4tg1&)
Standa id
Deviation
coordinate
1
3
0.043570
0 .050765
0.047196
0.003630
2
3
0.111866
0.130074
0.120823
0.009107
3
3
1.693079
1.700655
1.697299
0.003861
4
3
0.033252
0.041245
0.037243
0.003996
A similar series of model runs were conducted with varying source specific inputs of exit gas
temperature, stack diameter, and stack height, recognizing that those parameters were not available for all
sources. A model default of stack temperature of 432 degrees Kelvin, stack diameter of 2.4 meters, stack
height of 35 meters, and stack gas exit velocity of 11.4 meters/second were compared to varying inputs
for a source at the same emission rate. The modeled lead concentrations, for a selected point -200,0
meters west of the source, are shown in Table VII.
TABLE VII
industrial Source Complex Long Term
Model Run Comparative Analysis
I
k
111k
I
Default
432
35
2.4
11.7
0.055
Runi
426
34
1.7
1L7
0.085
Run2
121
22
7.2
11.7
0.044
Run 3
432
35
2.4
35.1
0.023
Pn1frct LEAP—. Ph ... 1 61
-------
Decreasing the stack diameter from 2.4 to 1.7 metets, along with very minor changes to the exit
temperature and stack height, results in an increase above the “default” run from 0.055 tgIm 3 to 0.085
p .g/zn 3 at selected grid point (-200,0). Both values indicate that associated quarterly values would be well
below the ambient air quality standard of 1.5 .ig/rn quarterly average. A reduction in the stack gas
temperature from 432 degrees K to 121 degrees K, along with a lower stack height (35 m to 22 in) and
a larger stack diameter (2.4 in to 7.2 m) results in a slight decrease in the concentration from 0.055 p.glni 3
Pb to 0.044 p .g/m 3 . Tripling the gas exit velocity front 11.7 to 35.1 m/sec, while holding all other
parameters constant, results in a decrease in the concentration to 0.023 iWm 3 . Consequently, choosing the
default value for a source in place of a source specific exit velocity, where the actual exit velocity at the
source is greater, would result in a conservative (i.e. higher) estimate of air-lead concentrations.
4.3.3. Ambient Air Data
Lead concentrations in the ambient air are reported as part of the National Ambient Monitoring
SysterniState and Local Monitoring System (NAMSISLkMS). The network of monitoring stations is
administered by State and local agencies. Monitors are sited to ascertain compliance with criteria air
pollutant standards, including lead. Although the monitors are not strategically placed to be statistically
representative of a geographic area, the measured air quality at the stations do provide an indication of
overall air quality in an area. Many arc sited near point sources or in locations expected to experience
maximum spatial concentrations.
By nature of the siting criteria, many of the Metropolitan Statistical Area cities had actual
concentration data for lead. The data quality is excellent, because the EPA conducts a rigorous quality
assurance program for the NAMS,SLAJvfS system. Flagged data indicates that the data is of questionable
quality. The results of 1988 monitoring data were obtained for project analysis. Where monitored data
were available the annual average concentration was used to characterize air quality for a city. The
Prqj.ct LW- Phi.. 1 62
-------
program default of 0.20 iWm 3 was selected when actual monitoring data was not available. The ambient
data was provided to the EPA Geographic Infonnation Systems Management Office to create a spatial data
coverage for comparison to estimated concentrations derived from point source modeling.
A summary of the ambient air concentrations is contained in Appendix A.
4.3.4. Air Emissions
The Toxic Release Inventory (TRI) data base was utilized as a source of information for point
sources of lead emissions, particularly for air emissions. The national computer center was queried for
a listing of all releases in the Midwest of lead and lead compounds, and that data was subjected to further
analysis.
TRJ was chosen because it is the most comprehensive data base available on toxic releases into
the environment. The data is provided to the EPA and the states as required by the Emergency Planning
and Community Right-to-Know Act of 1986. According to the 1990 report, “Toxics in the Community
National and Local Perspectives” (EPA, 1990), an analysis of data quality and completeness found the data
to be quite accurate in the aggregate. On-site visits by Agency personnel determined that the total volume
of reported releases were just 2 percent lower than corrected figures. The audit found that almost 80
percent of all release estimates were without error. Ii is noted, however, that only two-thirds of the
companies nationwide that were required to report, did so. Further, not all manufacturing facilities must
report; consequently, the TRI data base does not account for all toxic emissions.
4.3.5. Municipal Waste Combusters
Municipal Waste Combusters (MWCs) were analyzed as a special category of potential air
emissions of lead. The sources, which are not required to report by the Emergency Planning and
Community R.iglit-to-Know Act of 1986, but could have substantially large emissions of lead due to the
incineration of lead in the municipal waste stream. The EPA Region 5 Municipal Waste Combuster
Coordinator provided a listing of MWCs in the six states. Further information on the facilities was
PrqJict LEAP— Phi.. 1
-------
obtained by direct written and verbal communication with State agency personnel and facility operators.
The sources were to be modeled to discern air concentrations resulting from operations, if a facility were
deemed to be an important source (i.e., operations would be expected to result in a measurable increase
in the ambient lead concentrations).
4.4. Drinking Water Data
The Federal Data Reporting System (FRDS), operated at the EPA National Computer Center, was
accessed for information on violations of the drinking water standard. FRDS tracks community water
supplies’ compliance with monitoring requirements, maximum contaminant level (MCL) exceedances,
variances, enforcement actions, and population.
State agency records were also obtained. Community water supplies are required to participate
in a quality assurance program, and to report the results of data analysis to the state agency. Data quality
is consequently considered to be excellent. The test results for a city was used, when available. When
a non-detect value is reported, one-half of that value was used, in accordance with EPA risk assessment
guidelines (EPA, 1989). Otherwise, a UBK program default value of 4.0 i .g/l was used. Corrosivity of
drinking water supplies was taken into account to recognize the contribution from lead pipe leads, by
assuming a higher value for drinking water in homes built prior to 1949. Housing age data was provided
only as prior to 1949. This was done as a substitution for homes built before 1920, which are more likely
to have lead-pipe leads).
4.5. Soil and Dust Contributions to Elevated Blood-lead Levels
4.5.1. RCRA and O eratin Landfills
There is no central data base to query for Resource Conservation and Recovery Act (RCRA)
facilities that currently treat, store, or dispose of lead and lead-based compounds. Consequently,
information on facilities operating in the MSA cities was obtained by contacting RCRA program personnel
at EPA and the stale agencies. In many cases, facility operators were contacted to obtain more specific
ProJ.ct LEAP— Pb... 1 64
-------
information. The TRI data base was accessed to find facilities disposing of lead and lead compounds on
site (designated operating landfills). Each site was then characterized as to the potential for human
exposure.
4.5.2. Abandoned Hazardous Waste Sites Data
A November 1989 listing, Final and Proposed NPL (National Priority List) Sites With Lead, was
used to identify NPL Sites in the six states that listed lead as a primary OT major constituent of concern.
Specific information on sites located in the MSA cities was obtained from summary sheets and from the
more comprehensive reports on file for each facility.
4.5.3. Derivation of Soil and Dust Values
Data developed and utilized by the Department of Housing and Urban Development to prepare
the Comprehensive And Workable Plan (DHUD, 1990) were obtained to derive values for soil and dust
concentrations. Although data were coded by region, which would allow assessing data specific to the
Midwest states, the national data base was selected to avoid weakening the representativeness of the
statistically based sample. The data were generated under a rigorous quality control regimen, and is of
good quality, except for dust concentrations reported in ppm. Problems with use of that information was
flagged by DHUI) due to problems in the laboratory. The weight of the filter, upon which dust was
collected, could not be accurately measured. Consequently, the values in the data base may not be
accurate. The calculated values, however, although flawed, are ordinate indications of dust concentrations,
in that lead-dust concentration increases with age of dwelling. The data were therefore judged to be
adequate for use when categorized by housing age bands. The validity of this judgement is assessed in
the UBK sensitivity section 4.7.1.
In order to calculate mean soil and dust concentrations from data in the DHUD data base, several
soil and dust sampling locations were selected for analysis. The locations were standard points of
reference from which DHUD obtained samples at each home. For example, soil concentrations were
Pr LEAP- Pb e 1
65
-------
determined at the front entrance and rear yard locations for each home. Selected locations included dust
mass concentrations in ppm at six locations, and dust sample results at six locations in sgfff. A statistical
program was run on these to obtain minimum, maximum, mean, and standard deviations of lead, by
housing age category. The calculated values from two locations for each home, one for dust and one for
soil, were used to characterize soil and dust concentration for each census tract. These values were used
for inclusion in the Uptake Biokinetic (IJBK) Model.
Results of a statistical analysis of selected variables from the National I-lousing Survey, including
derived variables used to calculate soil arithmetic means and geometric means for dust concentration
samples, are shown in Appendix B. Dust concentration in ppm at the common-entrance location (of all
the houses surveyed), and soil concentration at the dwelling-entrance location, were selected for use in the
study. Values are shown in Table VIII. These values, rounded and prorated to reflect actual housing
counts in each area, were used in the UBK model as the soil and dust concentrations associated with the
age of housing for each census area (see page 84).
Table VIII
Soil and Dust Concentrations For Pb Based Upon
DHUD National Housing Survey Data
.—
te At
t$ i J
thse
Prqj.et LEAP—. Pbs 1
66
-------
4.6. Lead Uptake Biokinetic Model
The Uptake Biokinetic Model was developed by the U.S. EPA and was validated using blood-lead
and associated environmental concentrations for individual children (e.g., soil and dust values for the
child’s home). The model has not been validated at the large scale as applied by the study methodology.
It is specifically emphasized that this research explores the application of the model on a scale much
different from the original design and intent of the model. The effort is to determine whether the UBK
model can be used as an effective risk management tool to suggest which areas might have
comparatively more children at risk to environmental sources of lead. Thus, previously the UBK model
has been used to predict site-specific distributions of blood-lead leveLs in childhood populations in the
vicinity of lead point sources. This alternative use is to compare modeled levels between cities and areas
within cities.
The model uses assumptions regarding behavioral and physiologic parameters that determine intake
and absorption of lead from air, soil, dust, drinking water, and lead point sources. Behavioral and
physiologic assumptions vary by age of child, and include time spent indoors and outdoors; time spent
sleeping; breathing volume; deposition efficiency in the respiratory tract; diet (based upon a national food
basket survey, and not specific to the Midwest or to individual cities); and absorption efficiency in the
gastrointestinal and respiratory tracts.
The Uptake Biokinetic Model PC Version 0.5 (EPA, 1991d) is thus a mathematical simplification
of lead exposure-effect relationships. The model uses estimates of exposures to predict the distribution
of blood-lead concentrations in populations, for user selectable age ranges of children. This analysis uses
the full age range of the model, 0 to 84 months of age, and 10 .i.g/dL as the cutoff point for exceedances.
Marcus’ study suggests that the default value Geometric Standard Deviation (GSD) of 1.42 used
by the UBK model, based upon the nationwide NHANES II study, may be too small (Marcus, 1991). In
U.S. communities having much lower blood-lead values, and where there are a diversity of lead sources,
Projict LEAP— Ph ... 1 67
-------
for some children in smelter and mining towns indicated a range of unadjusted GSD values from 1.67 to
1.79, in three very disparate types of communities (Marcus, 1991). The communities assessed were
Kellogg, Idaho; East Helena, Montana; Leadville, Colorado; Telluride, Colorado; and Midvale, Utah.
Marcus analysis calculated both raw and adjusted GSDs for these communities. He determined, for
purposes of his analysis, that a GSD value of “... 1.66 fits neatly between the maximal raw GSD and the
minimal adjusted GSD in all cases ...“. Although the default value for the geometric standard deviation
(GSD) of blood-lead values is 1.42, appropriate for point sources of lead, this analysis uses a standard
deviation of 1.7. The wider value is more appropriate for area sources of lead. In addition, the wider GSD
better reflects the uncertainty of the spread in blood-lead data values for a population.
Table IX provides the UBK model default values for indoor air concentration, diet (based upon
Food and Drug Administration National Food Basket Survey for 1988), soil and dust, and paint. The
UBK model Calculated Blood Pb and Pb Uptakes shown in Table X are those derived from the default
values shown. The associated Figure 2 displays the probability density function for the selected age range
of children, along with the percentage of the population expected to exceed the cutoff value. The
probability distribution function is a mathematical representation of how blood-lead levels would be
distributed in a given population. The impact of various assumptions regarding lead concentration of
environmental sources (air, water, soil, and dust), as well as selection of a GSD value, is assessed in the
following section.
Piidect LEAP-. Pha.. 1 68
-------
TABLE 1X 9
Uptake Biokinetic Model Default Values
I I ABSORPT ION METhODOLOGY bocar Absoq*wn
I - T r 4 9 I
I1i CONCEWiBATiON 0 .200 &g Pb/ms f agj . . . . . ... . . . :
I Indoor Air Pb conceu ttation: flU % of outdoor ; . . . : R ! . ‘ :
I Ot licr Ak ?ar*incta$: . . . : : . . :.
I s I . 1
U I I I -
0 -1 1.0 2.0
32 .0
1 -2 2.0 3.0
32.0
2 -3 3.0 5 .0
32.0
3 -4 4 .0 5 .0
32.0
4 -5 4.0 5.0
32.0
5 -6 4D 7.0
32.0
6 -7 4.0 7.0
32.0
r L L ‘J I jflY m I
L—
0 - 1 200.0
200.0
1 -2 200.0
200.0
2 -3 200.0
200.0
3 -4 200.0
200.0
•
4 -5 200.0
200.0
5•6 200.0
200.0
—
6 -7 200.0
.
200.0
II
II
II
II
I I
I
H
i i
I I
I I
11
I I
H
H
I I
I
H
0 Based upon program default va!ua in the U Bicidnefic Model
Piidnt LEAP— Pbs 1 69
-------
TABLE X
Model Default Blood-lead and Lead Uptake:
:..C fS
.
. :: . :: jSlO oO: ItWl
:{jAg?4.W
..::.:.:. 1 . 1 i.. : I . .::. ;::ô W4a Y ).:
•. •:; •. .. WnJtSUptJkt
03-1
3.30
9.38
— 6.00
1-2
3.01
10.03
- 6.00
2-3
2.98
10 .56
— 6.00
3-4
3.04
10.48
6.00
4 -5
3.12
10.41
— 6.00
54
3.15
10.72
— 6.00
6-7
—...
3.18
.......
11.11
. . . . . . . . . . . . . . . . .
6.00
—.
Uptake Y ear
: . . .:: :: i i?
DM Uptake
34
Water Uptake
;:ç. . .:::4 j !RM SJ )
Paw Uptake
: : . :f .: ($j /4 y )
Air
.:...
03-1
2.94
0.40
0.00
0.04
1-2
2.96
1.00
0.00
0.07
2-3
3.40
1.04
0.00
0.12
3-4
3.29
1.06
0.00
0.13
4-5
3.18
1.10
0.00
0.13
5-6
3.38
1.16
0.00
0.19
6-7
3.74
1.18
0.00
0.19
Based upon information pertinent to each medium pathway/source contribution, as discussed
previously, the model was run for subareas within each of 83 cities, at the community area level (an
aggregation of census tracts). The population age range for the model runs was zero to 84 months of age.
The “percent above” percentages were then used to calculate numbets of children expected to exceed 10
,LWdL Pb-B.
PnJ.et LEAP— Pbs. 1 70
-------
ii
IS 12 14
LI D OI4CV4TJIRT ION C ug.i’dL)
S to 54 Hon
FIGURE 2
Uptake Biokinetic Model Default Concentration Curve
Prq .ct LEAP— Ph 1
71
-------
4.6.1. UBK Sensitivity Analysis
A sensitivity analysis was conducted in order to ascertain the impact of various assumptions made
in conducting the study, and to provide a sense of how a range of environmental media concentrations
affects the blood-lead level outputs from the model. The analysis considered various concentration levels
for drinking water, soil and dust, and outdoor air, as well as different geometric standard deviation values.
For each model run, except for the parameter of concern, all other values were held constant at the model
default values.
Table X displays how varying environmental media concentrations affect mean blood-lead
concentrations. The model runs use a Geometric Standard Deviation (GSD) of 1.7. Associated Figures
3, 4, and 5 show the probability density functions for each medium. Table X I summarizes information
from the figures. The blood-lead levels vary only slightly when drinking water concentration is increased
from 0 pig/I to 4.0 pig/I. The latter is the model default value. Consequently, drinking water
concentrations in these ranges would be expected to contribute only a small amount, as an environmental
pathway, to the numbers of children expected to exceed 10 p&g/dL
Soil and dust, however, can contribute significantly. Particularly for housing built prior to 1949,
the concentrations of lead in soil and dust, due to historical deposition as well as lead-based-paint, can
result in high numbers of potentially exposed people. To assess the impact of using a value for dust-lead
concentration that may not be accurate, the model was run using the same soil concentration as dust
concentration. This was in order to compare an assumption of soils concentration equals dust
concentration, to the use of the calculated dust concentrations in combination with the calculated soils
concentration. Using the same soil as dust value versus the calculated dust value of 565 ppm does not
change the percent expected to exceed 10 ig/dL Pb-B. Therefore, for the oldest housing age category,
there is no impact of using 565 ppm versus 555 ppm soil-dust, each together with a soil lead concentration
of 555 ppm. For housing age category 1940 to 1959, using a 175 ppm dust value in place of the
PrqJuct LEAP— Phi.. 1 fl
-------
calculated dust-lead concentration of 55 ppm, results in an elevation in the percent expected to exceed 10
g/dL of less than 1 percent. For the newest housing age category, substituting a dust-lead concentration
of 90 ppm for the calculated dust-lead value of 20 ppm, results in virtually no change in the percent
estimate of exceedance. Thus the model is not sensitive to using the calculated dust-lead values.
Running the model for dust alone (with model default values for air, drinking water, and diet)
indicates that, except for the highest dust-lead concentration, there is minimal contribution to the percent
expected to exceed the criterion Pb-B value. For housing age category prior to 1940, the modeled percent
exceedance of 4.55 percent indicates an increase of slightly more than 3 percentage points associated with
increasing dust concentration from 200 ppm to 565 ppm. Compared to the model derived percent
exceedances when soil and dust values are both held at 0, essentially the full 4.55 percent is associated
with the dust concentration of 565 ppm.
Outdoor air, at low levels (generally expected, except where a significant point source is in the
vicinity of a population), is not expected to contribute greatly to an increase in Pb-B levels. When the
air quality standard is greatly exceeded, however, as may be caused by a point source or lead-contaminated
dust, the Pb-B levels of nearby residents (within one to two km) are expected to rise significantly. As
indicated in the table, an air concentration ten times the standard would result in a percent exceedance of
almost 13 percent.
The model is very sensitive to the choice of blood-lead GSD for the population. The GSD model
default value of 1.42, thought to be applicable to point sources of lead, as mentioned, results in a 0.05
percent exceedance of 10 p.g/dL A GSD of 1.7, selected as discussed earlier, results in a 1.44 percent
exceedance, while a GSD of 1.8 results in an even greater exceedance of 2.47 percent (Figure 6). At
higher input levels of environmental concentrations, the spread would be even more dramatic. When
applied to a population, for example of 1,000 children, the number of children expected to exceed 10
&g/dL for the model default concentrations would vary from 0 to 14 to 25 children at GSDs of 1.42, 1.70,
Project LEAP— Ph.. 1 73
-------
and 1.80, respectively. Consequently, the choice of a GSD value for the model has a significant effect
upon the estimated number of children at risk of elevated blood-lead.
PrQJsct LEAP— Phi.. 1 74
-------
TABLE X I
Uptake Biokinetic Model
Sensitivity Analysis 1 °
l r • ! ‘ ‘ ! “ ? “ ““ 1 r rrTn h 1i • : — : • . • . . : : • : • • • : • : : • : : I I 1 T I
Faramett i Gtomc t ic 4$ txceeduig tJBI( Remarks
Canctntmtioa Mean 10 .0 tgtdL Run
Value (sf1) Children aged No
..........
rinking Water
(pg/i)
0
2.92
0.98
1
23
3.09
1.29
2
For level of detection 5.0 pg/I
.
For level of detection 7.Opg,’l
44 )
319
E44
4
DelauliSk
15.0
3.94
3.81
5
New drinking water standard.
50.0
6.33
18.69
6
Old drinking water standard.
Soil& (Dust)
(pg lg)
0(0)
1.47
0.01
1
L 21D(200)
319
244
DefaultSue
500 (500)
5.78
14.56
3
Superfund lower range value.
1,000 (1,000)
10.10
49.00
4
Superfund upper range value.
555 (565)
6.3
17.56
5
Housing age prior to 1940
175 (55)
2.41
0.34
6
Housing age 1940-1959
90(20)
1 91
0.00
7
Housing age 1960-1979
555 (555)
6.25
17.56
Assumes soil conczntration = dust
concentration
175 (175)
3.02
1.15
90 (90)
2.29
0.25
0(565)
—
4.17
—
435
.
Dust concentration only
I
I I
11
Ii
I I
II
I I
It
I
‘° Mo le that the level of detection for lead in drinking water varies by state, either 5.0 pgfl a 7.0 pg4. The significance
of the soil and dust values is discussed in Sec t ion 44.6.
Prqj.ct LEAP- Pus. 1
75
-------
[ 0(55)
1.79 035
0 (20)
1.62 0.02
Outdoor Air
( g/m 3 )
0
3.16
0
1
0.20
1.50
319
3.41
144
2.13
2
3
Pth
Quart
u t
erly average standard.
15.0
5.63
12.86
4
Ten times standard
II
II
Prqj.ct LEAP—. Phe 1
76
-------
ii
H
S
3LOUD
LEW ON 4TJ T lOll C uQ/ )
S to SI MonThs
FIGURE 3
Select Drinking Water Concentrations
Prq .ct LEAP— Phase 1
77
-------
I!
Ii
S S IS IS
lICOD L HCD4TIIRT ION C ugldL)
S to S4 Nosiths
FIGURE 4
Select Soil and Dust Concentrations
PrqJ.ct LEAP— Pba.e 1
78
-------
S B 1 5 12 ii 10 15
3L005 LSVED ONcE1TJVVT ION C u d’dL)
S to S4 Month,
FIGURE 5
Select Ambient Air Concentrations
Prq .ct LEAP— Pha.. 1
79
-------
ii
I i
31.000 L CWICW4TT ION C ugtdL
0 to 04 NDntIn
FIGURE 6
UBK Default Concentrations with Geometric Standard Deviation of 1.8
PrqJ.ct LEAP— Ph... 1
80
-------
4.7. Selected Area for Verification of Lead Screening Approach: Minneapolis/St. Paul
4.7.1. Minneapolis/St. Paul Demographic. Biological, and Soils Data
Minneapolis/St. Paul MSA was selected for verification of the population screening approach
(Objective 2) and for analyzing the association of blood-lead level to mobile sources (Objective 3) because
its data were available in computerized format. The Minnesota Department of Health (MDH) conducted
blood-lead testing in the area during the years 1986 and 1987. Reports of the results of the Minnesota
Department of Health 1986-87 Blood-lead Survey were reported by memoranda from the Lead Program
Coordinator, Division of Environmental Health, MDH, (Douglas Benson, Office Memorandum, October
11, 1991). A total of 1,410 children were surveyed, mostly in the Twin Cities, to ascertain blood-lead
values and to find lead-poisoned children. The data collected in support of the survey were provided on
computer disk. The data base contained 1,034 records for Minnesota and St. Paul. Data included blood-
lead level, census tract of home, ethnicity, gender, birth date of child, years of education for the father and
mother, and year blood-lead sample was taken. It is important to note that the blood-lead survey was
conducted in geographic areas where soil-lead values had been previously determined to exceed 1,000
ppm.
Environmental and demographic data were added to each record. Blood-lead-modeled values were
calculated from the UBK model for the age and census tract location for each child/record. Environmental
concentrations ascertained for the census tract of residency for each child were included to account for
relevant routes of exposure. Most particularly, soils data for each census tract were obtained from the
Minnesota Department of Pollution Control. The data base was that used by the MDH to prepare the Soil
Lead Report to the Minnesota State Legislature (MPCA, 1987). Geometric mean soil-lead concentrations
were calculated from the raw data, for each census tract. The geometric mean was selected in order to
compare values with modeled blood-lead values. The UBK model assumes a lognormal distribution. The
Project LEAP— Pba.e 1 81
-------
model calculates a geometric mean.
A Geographic Information Systems applications was use to determine the distance from a
transportation corridor for each census tract. That distance was then included in the data set for each child.
The distance between the center of each census tract and the closest heavy duty transportation rn’
was determined for each census tract.
4.7.2 Minneapolis/St. Paul Statistical Analyses
Two statistical procedures were conducted. To gauge the predictive ability of the comparative risk
approach, the UBK model was run for each child’s data set, using the child’s age and the environmental
data (concentrations) pertinent to the census tract of residency. The geometric mean estimated blood-lead
levels were then compared to the measured blood-lead levels, using a simple correlation procedure. The
correlation analysis was then repeated, grouping the children by census tract. The mean Pb-B values for
each group was then compared to the UBK modeled Pb-B value for the census tract.
A multivariable regression analysis procedure was employed to discern the contributions of various
pathways of exposure. The procedure was limited by the lack of variation of some of the data. Neither
drinking water nor air concentrations varied (sufficiently) across geographic areas and, consequently, the
variables were not included in the regression analysis. The predominant housing age for each census tract
was assigned to each record. Housing age was included in the model to account for historic deposition
from mobile sources, both exterior and interior lead-based-paint, and deposition from point sources.
Insufficient information is available, in general as well as for this analysis, to distinguish between and
partition the contributions from these sources. For the remaining data/variables (full model on the
following page), a regression analysis using stepwise comparison/replacement of independent variables
was conducted. The decision point p-value for selecting a variable in the model was p = 0.05.
U lnt 3 , 94, 494, and 694
Prnj.ct LEAP— Phi.. 1
-------
The full model is of the form:
Log Pb-B, = + 1 Log Pb Bm + 2 HAC + I3 3 Dist + 4 AGE + 5 E 1 + + 7 E 1 + 8 GEN + p 9 FAT
+ ftOMOT + 11 Soil + 12 INC
Where
Pb-B 1 ,
Pb-B
HAC
= measured lead blood from survey (pg/dL)
= model estimate of lead blood level ( gIdL)
= 1 if house built before 1949
2 if house built 1950-59
3 if house built 1960-69
4 if house built 1970-79
= distance from centroid of census tract to nearest heavy duty highway (meters)
= Age of child (years)
= 1 if ethnicity is white, 0 otherwise
= 1 if ethnicity is African-American, 0 otherwise
= 1 if ethnicity is American Indian, 0 otherwise
= 1 if gender is female, 0 otherwise
= number of years of father’s education
= number of years of mother’s education
= soil lead concentration measured for census tract (ppm)
= family income for census tract (dollars)
DIST
AGE
El
E2
E3
GEN
FAT
MOT
SOIL
INC
4.8. Derivation of City Exceedance Estimates
To derive an estimate of exceedance of the 10 .i.g/dL blood-lead value for each group of census
tracts, the UBK model was run with data pertinent to the area. Ambient air concentrations for the city
(refer to Section 4.4.3.) and drinking water concentrations for the city (refer to Section 4.5) were used as
input. No data from the air quality modeling efforts were used in the city computations. The results of
the air quality modeling for the 17 sources were used in the qualitative analysis only.
Soil and dust concentrations were calculated as a weighted average of the actual number of houses
in each housing age category, for each census tract group, based upon the soil and dust concentration
values derived from HUD data (refer to Section 4.63.). To illustrate, consider a census tract with 200
homes built before 1940, 300 homes built between 1940 and 1959, and 100 homes built from 1960 to
1979. Calculation of soil and dust values for the census tract, for input into the model, would be as
follows:
PrqJ.ct LEAP— Phi.. 1
83
-------
Housing Age Number Calculated Soil Value Calculated Dust Value
of Homes ( ppm) ( ppm )
1960-1979 100 (100/600)090= 015.0 (100/600)020= 003.3
1940-1959 300 (300/600)175= 087.5 (300/600)055= 027.5
pre- 1940 200 (200/600)555= 185.0 (200/600)565= 188.3
Total/Ave. 600 287.5 219.1
Thus, the soil and dust concentrations for the census tract, for input into the UBK model, would
be 287.5 ppm and 219.1 ppm, respectively.
The percentage of population expected to exceed 10 tg/dL, derived from the UBK model, was
then multiplied by the total, African-American, and Hispanic childhood counts to derive the number of
children expected to exceed the criterion Pb-B value for the census group area. The numbers for all
census tract groups were then totaled to derive an exceedance number for each city.
The number of new borne by ethnic categoly was calculated by applying the city specific birth
rate to the total, African-American, and Hispanic populations. The UBK derived percentages were
multiplied by those numbers to derive an estimate of fetuses that would exceed 10 p.g/dL Pb-B. Census
tract groups were similarly aggregated to derive city totals.
It is important to note that this methodology is for population screening purposes. The results may
have no practical value as a prediction of the actual number of children expected to have elevated blood-
lead values. Nor was that the intent of the methodology. The value of the approach is in the comparison
between cities, and specifically to areas within a city that may be expected to have higher rates of lead
exposed children than other areas. The intent of the population screening methodology is to use that
indication to set priorities for intervention efforts within a city or region. The reader is particularly
cautioned that the numbers are as derived by the computerized methodology and therefore appear to be
precise. They are not.
Project LEAP- Phase 1 84
-------
5. RESULTS
5.1. Overview/Introduction to Results
Results are presented for each environmental category, along with the modeling results for 17 air
emission sources, soil and dust derivations, and a qualitative summary of the results for each city. An
environmental profile and the results of statistical analyses pertinent to Minneapolis and St. Paul,
Minnesota, are provided. Finally, the results of Pb-B modeling for each city, are presented.
5.2. Environmental Data Categorical Assessments
5.2.1. Ambient Air
During 1988, there were few exceedances of the air quality standard for lead (three month average
of 1.5 .tg.m 3 ). Most monitois reported in the tenths or hundreds of a Lg/m 3 The notable exception is
Eagan, Minnesota, with a single fourth-quarter exceedance of 1.8 g/m 3 .
The average lead concentrations utilized as the air concentration values in the UBK model are
listed in Appendix C. Cities for which a program default values were used are also listed.
5.2.2. Air Emissions
Tables showing total emissions in the six states and total emissions in the 83 cities are provided
as Appendices D and E, respectively, based upon the Toxic Release Inventory data base. Figure 7 shows
total air emissions of lead by state.
The inventory contains 497 facility emission reports. Total air releases from 342 sources reporting
release to air equals 449,304 pounds for calendar year 1988. Twenty-one sources, or 6.1 percent of the
total number of sources, release 261,051 pounds annually, or 58.1 percent of the total air emissions. In
the MSA areas, 226 sources account for 314,904 pounds annually. Seventeen sources with annual releases
to the air greater than 4,000 pounds release 216,459 pounds annually. This accounts for 48.2 percent of
total air emissions in the six states. These 17 sources are listed in Table X II. They constitute a mere 5
percent of the number of sources in the six states. Appendix F provides locational information.
Prqjset LEAP- Phase 1 85
-------
Total Air Emissions 1988
Toxic Release Inventory
200
N
U
m
b
a
r
150
P
0
U
100
0
f
S
0
U
r
C
a
a
150
50
I
100
0
200
(
T
h
0
U
a
a
n
d
S
)
R
a
a
a
a
d
No. —
Lbs —
50
Ohio I Michigan Indiana Illinois
169
166.1
81 87 110 15
I 49.561 66.369 70.644 30.02
0
FIGURE 7
Total Air-lead Emissions 1988
Prq .ct LEAP— Pb 1
86
-------
TABLE XII
Sources with TR.I Reported Total Air Emissions
Exceeding 4,000 Pounds/Year in 1988
Trr .... B
Location
A ir
Einisstcns
(Pounds)
Columbus, OH
61,300
Toledo, OH
6,711
Cleveland, OH
4,200
Warren, OH
Steels, Canton Works Canton, OH
4,600
Mansfield, OH
7,231
Products Division Dayton, OH
4,250
Beech Grove, IN
9,870
Indianapolis, IN
5,485
Division Ecoise, MI
11,590
Saint Johns, MI
5,740
Co. Eagan, MN
13,812
Hanford, IL
11,570
East Chicago, IN
17,900
Koh ler, WI
29,200
Saint Paul, MN
12,480
Aiton. IL
gr cjj 4J tA *44 s
4,677
t f l !
Prtdset LEAP— Pbs. 1 87
-------
Figure 8 shows the spatial distribution of the sources of lead and associated annual release
amounts.
Gopher
Major Air Emission
Facilities
pounds/year
FIGURE S
Major Mr-lead Emission Facilities
PrqJ.ct LEAP- Ph... 1
88
-------
5.2.2.1. ISCLT Modeling Results
Model run results for the seventeen major air emission facilities, included in Appendix G, were
provided to the GISMO for spatial representation and to relate to census tracts. The resultant
concentrations of air-lead were cross checked with ambient air data, where the latter was available.
Table XIII summarizes the concentrations of lead determined for each of the 17 sources at a
comparable grid point (200, 200) meters. This is generally the point of maximum concentration. Beyond
200 meters from the source, concentrations begin to decrease rapidly, generally to tens and hundredths of
a pg/rn 3 . At the extremities of the model grid, 2,000 meters from the source, concentrations were in the
thousandths of a pg/rn 3 , for all but the largest sources. All sources were less than hundredths of a
at the extreme points.
The maximum concentrations for the 17 sources varied from a low of 0.118 pg/rn 3 downwind from
Acussar Dayton Thermal Products Division in Dayton, Ohio, to the two highest maximum concentrations
values calculated at 1.792 pg/rn 3 for Kohler Co., Kohler, Wisconsin, and 1.693 pg/rn 3 for Ol-Neg TV
Products, Inc., Columbus, Ohio. Except for these two sources, all sources had annual concentrations of
less than unity.
PrqJect LEAP- Ph.. 1 89
-------
TABLE XIII
Maximum Concentrations of Lead
for Modeled Sources
Ftacskty Name
Locat ion
Estimated Concentration
:;..:::::
Ol-Neg TV Products, Inc.
....::..::.:::..:3 ..:: . ..
Columbus, OH
.. . . . ....
1 .693
DuPont Toledo Plant
Toledo, OH
0.138
Oatey Co.
Qeveland, OH
0.132
Copperweld Steel Co.
Warren, OH
0.151
Republic Engineered Steels, Canton Works
Canton, OH
0 .135
Empire Detroit Division
Mansfield, OH
0.229
Acustar Dayton Thermal Products Division
Dayton, OH
0.118
Refined Metals Corp.
Beech Grove, IN
0.584
Quemetco, Inc.
Indianapolis, IN
0.244
National Steel Great Lakes Division
Ecorse, MI
0.306
Federal-Mogul
Saint Johns, MI
0.136
Gopher Smelting & Refining Co.
Eagan, MN
0.179
Chemetco, Inc.
Hanford, IL
0.912
Inland Steel Co.
East Chicago, IN
0.527
Koh ler Co.
Kohler, WI
1.792
North Star Steel Minnesota
Saint Paul, MN
0302
LaClede Steel Co.
Alton, IL
0.146
P. J.et LEAP— Ph 1 90
-------
5.2.3. Municipal Waste Combusters
There are 32 municipal waste combusters in the Agency’s inventory, although three facilities are
not currently operating. The three are all outside the study area. A significant finding is thai estimated
emissions exceed actual emissions gathered by stack test emissions, generally by an order of magnitude
or more. Appendix H provides information on each of the facilities, including design capacity, estimated
emissions, stack test emissions, and comments pertinent to each facility.
The 32 facilities, when all were operating, had annual emissions of 62,288 pounds of lead, based
upon estimated emission factors and stack test emissions. Stack test emissions, available for 17 of the 32
sources, were utilized when available. Of the 32 sources, 15 are located in the project MSA cities. The
facilities are listed in Table IV. Figure 9 shows the location of the facilities.
An analysis of• the 17 sources with emissions data indicates the problem of using estimated
emission factors. For those sources, estimated emissions total 349.13 pounds/day, while emissions based
upon stack test information total only 46.78 pounds/day. Notably large differences for estimated and stack
test emissions, respectively, include the Indianapolis facility, 48.60 and 0.06 pounds/day; Detroit, 92.40
and 1.82 pounds/day; NSP-Red Wing (Minnesota), 27.00 and 0.34 pounds/day; and Columbus, Ohio,
56.00 and 7.60 pounds/day. Analysis of the seven facilities with stack data, located in the MSA cities,
shows a similar spread of 251.50 pounds/day estimated emission estimate, and 30.89 pounds/day stack test
emissions, for an aggregate annual (stack test) emission of 11,275 pounds for the seven sources. Several
sources, including the Chicago facility with estimated emissions of 35.20 pounds/day, appear to be
significant sources and to warrant modeling. No municipal waste coinbuster has been modeled, however,
due to the uncertainty of the estimated values, and as well as the significant differences between estimated
emissions and stack test emission results. Consequently, the lead emissions from this categorical source
was not incorporated into the study modeling and subsequent estimates of children exposed to lead. Large
Prqj.ct LEAP— Phase 1 91
-------
sources, nonetheless, may prove to be a concern, when actual stack test data is derived. The Chicago,
South Montgomery County (Ohio), and North Montgomery County (Ohio) facilities are planning or have
recently obtained stack test data. Stack test data for those facilities may indicate the need for additional
consideration.
P,oJ.ct 1W- Pb 1 92
-------
TABLE XIV
Municipal Waste Combuster Inventory
Metropolitan Statistical Area Cities in Region 5
1 on. WUSt D n
:•, :•. •..
-
1 atcd Air-Icad
.. m s
. .I
. . . . m n
c y
. . .
Da 1 )
..
Chi go, IL 1600
3520
N/A
East (licago, IN 450
9.90
N/A
Indianapolis, IN 2200
4840
0.06
Jackson, MI 200
4.40
N/A
Detroit, MI 3300
92.40
1 Ł2
Grand Rapic , MI 625
13.75
N/A
Duluth, MN 110
3.10
0.04
Rochester, MN 200
4.40
0.37
Rcs. Minneapolis, MN 1,000
22.00
0.06
Co. Dayton, OH 900
19.80
N/A
Co. Dayton, OH 900
19.80
N/A
Akmn, OH 900
25.20
20.94
Columbus, OH 2000
56.00
7.60
Shcboygan, WI 96
2.10
N/A
Madison, WI 75
2.10
N/A
...
- 14556
........... .............. ..
\ \ 3 $
-.
Pr j.et LEAP— Phase 1 93
-------
5.2.4. Drinking Water
The Federal Data Reporting System(FDRS) data base for 1988 indicated that there were no
violations of the (50 pg/ I) Maximum Contamination Level (MCL) for Pb for any of the study area cities.
Only exceedances of the MCL, however, are reported to the system. Consequently, the FRDS does not
contain information on actual measured concentrations less than the MCL State agency records indicate
actual values from sampling results. These are summarized in Appendix I, with test results, number of
PrnJ.ct LEAP— Phi.. 1 94
Municipal Waste
Combus ters
rand Rapids
FIGURE 9
Municipal Waste Combustera in U.S. EPA Region 5
-------
samples in each test, and the drinking water concentration value for modeling, for each city. Of the 83
cities, only 10 had test results above the level of detection, while 27 cities showed non-detect levels. The
drinking water suppliers for 46 cities did not report sample results in 1988. For the latter, 4.0 p g/l was
assumed. The largest values reported were for Wausau, Wisconsin at 1500 p.g/l (reported value is suspect
and was not used in the study) and 7 i.gfl ; Milwaukee, Wisconsin at 25.0 g/l; Youngstown, Ohio at 12.0
gfl; and Madison, Wisconsin at 10.2 g/l. Thus of all the cities sampled, only two would exceed a
standard of 15.0 tgfl.
5.2.5. RCRA and Operating Landfills
RCRA facilities as a category do not appear to present a significant risk of lead exposure. That
assessment is qualified, however, due to the difficulty in obtaining information about a particular
parameter, lead, at a given facility. Generally, the facilities may treat or otherwise process a limited
number to a wide variety of pollutants, depending upon the facility’s operating permit and type of
operation. A total of 27 RCRA facilities were assessed to determine whether lead was processed at the
facility, and a determination was made on potential exposure.
Appendix J lists the 27 RCRA facilities with comments on each and a T/F (true or false) notation
as to potential for exposure. No information was obtained for seven facilities. For the 20 facilities
assessed, only four appeared to have a potential for off-site exposure that could result in human exposure,
generally via the air pathway from lead-contaminated piles and wind blown dust. These are Saint Louis
Lead Recyclers, McLean Steel, Kemeto, and Olin, all located in Granite City, Illinois. Response action
is ongoing in Granite City, Illinois, at the NLdTaracorp Site, that will result in capping a 240,000 ton lead-
bearing waste pile situated adjacent to the former lead smelter, along with residential soil cleanup in a 55
square block area. Soils with lead concentration exceeding 500 ppm will be excavated and replaced with
clean soil. EPA (Superfund program) is currently preparing the remedial design for the project.
Granite City is also one of three study areas that is part of a tn-state lead study being conducted
PrqJ.ct LEAP— Phase 1 95
-------
jointly by EPA and the Agency for Toxic Substances Disease Registry. In addition to determination of
soil and dust contamination, the Illinois Department of Public Health has conducted extensive blood-lead
testing for the project. This ongoing area-wide study in the city, should elucidate the potential for human
exposure to lead from these facilities.
Operating facilities that dispose of lead on-site were obtained from the TRI data base. Sixteen
facilities in the MSA cities reported on-site disposal, ranging from a diminutive seven pounds annually
to 566,000 pounds annually, for a total of 2,138,048 pounds/year disposed of on-site in 1988. Figure 10
provides a spatial representation of the largest facilities, with annual amounts indicated for the facilities
shown.
PmJ.ct LEAP— Ph.. 1 96
-------
Appendix K contains information on facilities having on-site lead disposal, along with a
categorical judgement on the potential for off-site contamination. Of the 16 facilities, five appear to have
the potential for off-site lead-contamination, as described in Table XV. As is the case for RCRA facilities,
minimal data is available to characterize the concentration and spatial extent of lead-contamination that
may result from landfilhing/on-site disposal at the facilities.
In land
Major On-Site Disposal
Facilities
Co.: 320
240
pounda/year
FIGURE 10
Major On-Site Lead Disposal Facilities
Pivjuct LEAP— Phi.. 1
97
-------
TABLE XV
Toxic Release Inventory Reported On-Site
Disposal in 1988 for MSA Cities
Fac 1iIy
L ca&ioi
On4hc
Remarks
N fl
..:.•• . ::.:• :.: .: .:...:..
Dlsp a1
..: t djy:
: :: ::: .:. . ..: :. •:•.
Keystone
Steel & Wire
Co.
Peoria, IL
41,000
Ground water around the facility is contaminated with lead.
Facility is seeking closure. Arc furnace dust pile addressed
previously. Near residential area and Peoria State HospitaL
Potential dust source. 1-11gb level exposure to population.
Granite City
Steel
Granite City,
IL
45,000
Facility sends 15-20 different types of waste streams to
landfill, including blast furnace flue dust, settling pond sludge,
etc. Some potential for off-site contamination of residents
proximate to main street side of facility.
Inland Steel
East Qrn go,
IN
560,000
No information on-site disposal operations.
USX Gary
Gary, IN
7,400
Good potential for electric arc furnace dust to get off site.
Residential area.
Cooperweld
Steel Co.
Warren, OH
2,001
Main waste is arc furnace dust. State is handling the closure
wastc piles.
Prq .ct LEAP— Ph.. 1 98
-------
5.2.6. Abandoned Hazardous Waste Sites (Superfund )
The National Priority List (NPL) listing contained 95 sites in the six states that listed lead as a
major contaminant. Of these, 17 facilities are located in the MSA cities. These are indicated on the map,
Figure 11. Appendix L lists all sites in the six state area, with a designation of final or proposed
pertaining to designation status as an NPL site. Appendix M provides definitive information on the sites
Located in MSA cities.
The data base consists of sites that were both proposed for listing and final, at that time, so that
the extent of information about the sites vary greatly. In particular, the proposed sites tended to have
much less information on the extent of lead contamination. Of course, lead is just one of the pollutants
that could be on any given site, consequently, there is no requirement or particular reason for a file to
contain more extensive data on lead. The more extensive site investigation step, development of a
remedial investigation/feasibility study (to better characterize the extent of contamination and to develop
alternatives for abatement) had not been initiated at many of the sites. Extensive sampling results,
therefore, were not available. It is important to note, further, that the investigations are not undertaken
solely to determine lead concentrations. Lead is only one of a host of contaminants of concern, and is
most often not the prime pollutant being investigated.
Table XVI lists the 17 sites located in the MSA cities. Most of the sites are abandoned landfills,
many municipally owned and operated, and have been assessed primarily for potential groundwater
contamination both on and off site. Soil contamination investigations, at this stage of investigation of site
conditions, has almost exclusively focused upon on-site concentrations. Soil-lead contamination has been
documented on-site for most of the facilities, although the primary route of exposure appears to be through
contaminated groundwater. Information is, at best, sparse, particularly for those sites that have been
PmJ.ct LEAP— Pbs .. 1 99
-------
proposed for the National Priority List, as contrasted to final NPL sites. For the former, only preliminary
information, and few actual physical measurements of concentrations of groundwater, soil, or on site
materials (e.g., in barrels or sludge lagoons) had been taken. There are two sites that are notable
exceptions. The Barrels, Inc., site, in Lansing, Michigan, appears to have potential for off-site
contamination. The NL Industries/Taracorp Lead Smelter site in Granite City, Illinois, has well
documented and significant contamination in the residential area surrounding the Site and is, consequently,
currently being addressed by the EPA Superfund pmgram.
Janes
S.E. Rocklord Grna
Super fund NPL
Sites
ertima Ref
& arreie Inc
FIGURE 11
Superfund National Priority Ust Sites
with Lead Contamination
Pn J.ct LEAP— Ph ... 1
100
-------
TABLE XVI
National Priority List Facilities in Metropolitan Statistical Area Cities
with Lead as of November 1989
NL Industriestraraunp Lead Smelter
Granite City, II
Y
Southeast Rockford Groundwater Contamination
Rockford, II
N
MIDCOI
Gary , In
N
MIDCOII
Gary,In
N -
Tippecanoe Sanitary Landfill, Inc.
Lafayette, In
N
WhitfordSalcs&Service
SouthBend,In
N
Michigan Disposal (Cork Street Landfill)
Kalamazoo, Mi
N
Motor Wheel, Inc.
Lansing, Mi
N
11. Brown Co., Inc
Grand Rapids, Mi
N
Folkcrlsrna Refuse
Grand Rapids, Mi
N
Barrels, Inc.
Lansing. Mi
Y
Kaydon Corp.
Muskegon. Mi
N
Van Dale Junkyard
Marietta, Oh
N
ianesville Ash Beds
Janesville, Wi
N
Janesvllle Old Landfill
Janesvill; Wi
N
National Presto Industries, Inc.
Eau Claire, Wi
N
Fort Howard Paper Co. Lagoons
Green Bay, Wi
N
12 Potential for off4lte lead amatnaficm. Y Skates flat mtendal exists. N indicates flat no potential exists for off.site
lead amtaminntion.
PunJ.et LEAP— Pbs 1 101
-------
5.2.7. Environmental Data Qualitative Summary
Table XVII is presented as a qualitative summary of potential routes of exposure to lead from
environmental sources, for the 83 MSA cities. A positive indication for a categorical source for a
particular city does not imply violations of an environmental standard or that there is necessarily an urgent
public health concern caused by sources via the indicated medium. It does mean that, based upon current
information, the potential for a problem exists. More definitive conclusions, in most instances, can only
be drawn subsequent to on-site measurements.
The qualitative summary table is presented as a quick view method of understanding where
environmental sources of lead may exists in the 83 cities. The existence of a point source, RCRA facility,
landfill facility, or Superfund site does not necessarily indicate that there is an environmental problem.
Similarly, the cities shown with ambient air concentrations exceeding 0.2 p.g/m 3 and drinking water
exceeding 4 tg/l, may be well below the standards for air and drinking water, respectively. The
significance of the values in the table is merely to reflect the UBK default values. The table is presented
to account for known sources of lead that may be above the norm for the 83 cities. A check mark
indicates the existence of a facility, or measured air or water concentration above the concentrations shown
in the table.
Pr LEAP- Pb 1 102
-------
TABLE XVII
Qualitative Summary of Environmental Exposures’ 3
to Lead for MSA Cities in 1988
. ;: •:: ; •x:: •: : • :: :::
.
......,.
. ‘. . ‘••• • •
Rock Island
Moline
Chicago
1
/
Kankakee
Peoria
1
/
Bloomington
Normal
Champaign
Urbana
Rantoul
Springfield
E. St. Louis
1
/
GraniteOty
7
1 /1 /
p
/
/
Rockford
IUI!
________
Hammond
1
s .
E.Cbicago
3
/
S e
i
South Bend
.
Mishawaka
Elkhart
13 Air point sourc.t (in or proximate to city), RCRA facility, Landfill Facility, and Superfund facility numbers
Indicate facilities with potential to cause exposure to humans. Ambient air and drinking water exceedances pertain
to the UBK model default values.
PTOJ.ct ISA?— Pbs. 1 103
-------
C u y Total No
utAwa
H : Ot 1 &flS.
No of
Air Point
SoUttts
Woof
flA
‘ ffif
No of
Landfifl
:
Na of
Supcrftmd
:: I: : S itS
Ambient
Mr >
•: o wm ’
Dnnking
Water>
4 J
Gosben
,
Ft. Wayne
LaFayette
Kokomo
.-
An de r son
-
Muncie
I ndianap o l is
3
1/
1
Terre Haute
Bloom ington
Evansville
New Athany
tota iSs ,
: x : • : xx : • : ; : : c • : • : : : T : ’ : • : : :
a
1
2
: . x : ’ :. : .x . :.z N :: : : . : . : .: . :. :
3
: : : : : : : : . : : c . x 1 ; : : : : : . : ; : : : :
!t 10d Aa
Saginaw
)
BayCity
.
Midland
Muskegon
Grand Rapide
Lansing
1
‘
East Lansing
Flint
Detroit
1
1
Ann Athor
.
Battle Creek
Jackson
KMamnoo
Benton Hathor
* *
S
J :
*f
I !
!
PniJ.ct LEAP— Pbs 1 104
-------
City total No
No of
No of
No of
No of
Ambient
Mc
Drmking
Water>
ofAiea
Mr Point
R RA
UindtU
Su md
Concerns
M oOrhead
Sources
PSciIIUeS
PadlitS
&a
02 tgf&
4 flfJ
Duluth
St. Cloud
Minneapo lis
1
/
SLPauI
1
P
Rochester
Ibtai state
2
! ! MbOC$OW
Toledo
)
Cleveland
Akron
1
/
LotS
Canton
Steubenville
Wheeling
Marietta
Youngstown
1
/
Wairen
1
/
Mansfield
2
/
1’
Lima
Dayton
Springfield
Columbus
1
, ,
Hamilton
Middletown
Cincinnati
Ban Claire
i as
*i
im :
fW !
SM
Prqjet LEAP— Phee 1 105
-------
Pro [ ZAP— Phase 1 106
-------
5.4. Chosen Cities
5.4.1. Minneapolis/St. Paul Environmental Sources of Lead
Air quality monitoring data for NAMS stations located in Minneapolis and St. Paul indicate very
low values of lead. Annual average air-lead concentrations, from the quarterly monitoring data, were 0.06
tg/m 3 and 0.05 .tg/m 3 for Minneapolis and St. Paul, respectively.
Six sources in the Metropolitan Statistical Area reported air emissions to the Toxic Release
Inventory. These were Gopher Smelting and Refining Co., Eagan, with 13,812 pounds/year total air
emissions of lead and lead compounds; North Star Steel, St. Paul, at 12,480 pounds/year; American
National Can Co., St. Paul, at 551 pounds/year, Honeywell New Hope Facility, Minneapolis, at 500
pounds/year; Bureau of Engraving, Inc., Minneapolis, at 500 pounds/year, and Whir-Air-Flow,
Minneapolis, at 250 pounds/year. Both Gopher Smelting and Refining Co., and North Star Steel, were
modeled to estimate air concentrations resulting from emissions. The maximum downwind concentrations
were 0.18 g/m 3 for Gopher Smelting, and 0.30 .i.g/m 3 for North Star Steel. Both values were derived
in close proximity, 200 meters, to the emission source. The Eagan facility, consequently, would not
contribute to increased lead-air concentrations in either Minneapolis or St. Paul, due to the distance.
Generally, noting the relatively de mini nus maximum concentration value, the exposures are rather limited.
The Hennepin Energy Res. Municipal Waste Conibuster, located in Minneapolis, is the only other
point source of lead emissions reported in the MSA. The amount of emission, 0.06 pounds per day, based
upon stack test emissions, is quite small and, therefore, the source was not modeled to derive air
concentrations.
Drinking water test results were not required and therefore were not conducted for the drinking
water supplies for 1988 because supplies were sampled for lead every other year. There is no indication
of a problem with the source drinking water. Consequently, the model default value of four p.g l was
PrqJ.etLEAP—Phu.1 107
-------
assumed.
On-site disposal was reported in TRI only for the Gopher Smelting facility. As noted above, the
facility is far enough from the two central cities such that wind-blown lead contaminated soil and dust,
if there were any, would not impact/contribute to soil-lead and dust-lead concentrations in Minneapolis
or St. Paul.
Although the NPL Superfund sites with lead included in the data base, discussed earlier, did not
list any sites in either city, a further review of NPL site summary documents and files found three sites:
Union Scrap Iron and Metal Qmpany located in Minneapolis, Twin Cities Air Force Reserve Base (Small
Arms Range Landfill), also located in Minneapolis, and Pigs Eye Landfill, located in St. Paul. None of
the sites appear to pose a threat to residents via wind-blown off-site lead contaminated dust.
The Pigs Eye Landfill is a 307 acre site that served as the City’s municipal waste landfill and also
accepted industrial waste. The soil on-site is contaminated with lead and other constituents. The area
immediately surrounding the site is industrial. A residential area is located one-half mile east. Lead was
detected in high concentrations in one well, and in low concentrations in soil, indeed, soil samples taken
near the facility indicate soil-lead concentrations of less than 150 ppm. The potential route of exposure
is through contamination of 210 residential wells in the vicinity.
The Minneapolis sites are both small. Union Scrap Iron is an one-acre site used to crush lead
battery fragments. Reportedly, 30,000 Ions of lead-contaminated plaster and rubber fragments remain on-
site, partially covered by tarp. A soil contamination study was to be conducted. The three-acre Twin
Cities Air Force Base, Small Arms Range Landfill site, is located within and adjacent to the Minneapolis-
St. Paul International Airport. Periodic flooding of the site has resulted in the release of lead and other
contaminants into the Minnesota River. The primary potential for exposure is through contamination of
drinking water wells. A hydrogeological investigation has been initiated.
Three additional sites in the two cities are National Priority Last sites that do not cite lead as a
Pr J.ct LEAP- PhM. 1 108
-------
contaminant. The Whittaker Corp. property is a 10-acre site located in Minnesota. The General
Mills/Henkel Corp. site, also in the City of Minneapolis, poses a threat to the groundwater aquifer from
solvents disposed in a dry well. The 45-acre Koppers Coke site is located in St. Paul. The removal of
lead-contaminated coal tar waste and contaminated soil from the site has begun.
The Minnesota Pollution Control Agency provided the raw data base for soil sampling conducted
in Minneapolis and St. Paul, that provided a partial basis for the report to the Minnesota State Legislature
(MPCA and MDH, 1987). Geometric mean soil concentrations are shown, by census tract, in Appendix
N. Soil lead geometric mean values range from a low of 33 ppm to a high of 736 ppm. The geometric
mean values are deceptive, however, in that the values do not truly represent soil concentrations in a tract.
Indeed, a review of the individual samples taken for each census tract shows a wide range of values, with
the highest concentrations generally from soil samples taken near house foundations. Foundation sample
concentration values of 3,000 to 7,000 ppm are not uncommon, with the highest sample results in a single
census tract in Minneapolis showing a value > 20,000 ppm. The two highest values of 38,850 ppm and
166,780 ppm were determined near an industrial facility in St. Paul. (It should be noted that the blood-
lead counterpart data base contains no child blood-lead level measurements for that census tract).
Recognizing the wide range of sample values within each census tract, for purposes of deriving modeled
blood-lead values for each census tract, the foundation sample values were selected, where available, to
represent soil concentration values.
To assess the contribution to elevated Pb-B levels from mobile sources, the distance from the
centmid of each census tract was calculated using geographic information systems applications.
5.4.2. Blood-lead Data/Demographics
The Minneapolis and St. Paul blood-lead survey data contains the records of over a thousand
children under the age of six for whom blood-lead levels were measured in 1986 and 1987. Table XVIII
shows the number of children with elevated blood-lead levels by ethnicity. The dual heritage ethnic
Pr LEAP- Phue 1 109
-------
category refers to those children listed as white/African-American, Hispanic/American Indian, or other
races. Table XIX provides descriptive statistics for each ethnic group.
TABLE XVIII
Children Under Six Years of Age with
Blood-Lead Levels Exceeding 10 p.g/dL based upon
1986 - 1987 Blood-lead Survey for Minneapolis and St. Paul
2. :r :.:. !:. :. Z ;.5 ? ! ..!........x:;.;.x:x.xx.;. • :: : •f ! - . . . -
For white, African-American, and American Indian children (those ethnic groups greater than 100
children), arithmetic blood-lead levels are 7.7 zg/dL, 9.2 sg.dl, and 13.2 pg/dL, respectively.
Corresponding geometric mean blood-lead levels (Appendix P) are 5.8 pg/dL, 7.2 pg/dL, and 9.8 p.g/dL,
respectively. For the data set in total, blood-lead levels ranged from a minimum of 1.0 p.tg/dL to a
maximum of 65 Lg/dL, with a geometric mean of 6.6 g/dL and a geometric standard deviation (GSD)
of 2.2. Appendix 0 provides comparable data by census tract. Geometric mean blood-lead levels ranged
from 2.0 p.g/dl (14 observations) to 65 p.tg/dL (one observation), for the census tract
‘ 4 Other ethnic groups include cthlldxen of dual heritage ethnicity and children for whom ethnicity wn not rearded.
•Pr J.ct LEAP— Pb .. 1 110
ji i t i t
• : _
Number>
10&g/dL
2%
151
4
64
9
8
28
Total Number
1022
667
114
13
— 121
31
1 1
65
Percent
Exceeding
29.1
22.6
29.8
30.7
52.8
29.0
72.7
43.1
-------
TABLE XIX
Blood-lead Values (pgIdL) by Ethnicity for
Minneapolis and St. Paul, Minnesota Blood-lead Survey in 1986 - 1987
Btbrdcky
Na of
Miobnun
Mnnnum
OcometS
StaaSd
Not SpecifIed
14
:
3.0000
19.0000
7.2142
4.9017
White
667
1.0000
65.0000
7.6971
6.1447
African-AmerIcan
114
1.0000
37.0000
9.1666
6.6929
His p anic
13
3.0000
28.0000
8.8461
6.6061
American Indian
121
1.0000
39.0000
13.23%
92032
Asian
31
3.0000
36.0000
10.0967
7.9177
Other”
11
1.0000
44.0000
15.4545
12.1767
White/African-
American
30
2.0000
34.0000
12.6666
9.2263
White/Hispanic
8
3.0000
22.0000
10.2500
6.0886
White/
American Indian
8
1.0000
21.0000
11.3750
7.4630
White/Asian
3
1.0000
7.0000
4.0000
3.0000
White/Other
3
3.0000
5.0000
4.0000
1.0000
African-American/
Hispanic
8
3.0000
24.0000
15.1250
7.6613
African-American/
American Indian
1
8.0000
8.0000
8.0000
Hispanic/
American Indian
4
3.0000
20.0000
83000
8.0208
Age of housing for each census tract in the Twin Ofies was provided from census data via
geographic information systems. As counted by the 1980 census, housing in the two cities is
“(blidren for whom ethnicity wn not rearded.
PniJ .ctLEAP—Phaee l 111
-------
overwhelmingly built before 1949, with 78.9 percent of then-existing housing stock built prior to that year,
and 92.9 percent built prior to 1960. For the blood-lead data base, the housing stock reflects an even older
pattern (as a result primarily of the selection criteria for the blood-lead survey); consequently, there is very
little differentiation in housing age by census tract.
5.4.3. Minneapolis/St. Paul Correlation Analysis
A correlation analysis, using the Minneapolis/St. Paul blood-lead data and derived blood-lead
levels from the UBK qiodel, for each record, was performed to ascertain the validity of the methodology
for finding geographic areas where environmental exposures to lead would result in increased Pb-B levels.
Sources have been described earlier.
Selected zero-order correlations are shown in TABLE XX. The correlation of actual blood-lead
levels to the corresponding modeled blood-lead levels is small, at 0.05, with a p = 0.14; consequently, the
results indicate a failure to reject the null hypothesis of no correlation between the modeled and measured
blood-lead values. The conclusion from this analysis would be that the modeled blood-lead levels do not
predict the actual blood-lead levels at a statistically significant level. (Recognizing problems with the
approach, however, a second analysis as employed. This provided better results, as discussed below.)
The analysis also determined very small correlation coefficients for actual Pb-B levels with
housing age category, distance from an interstate highway, and soil-lead concentration.
The combined routes of exposure of air (due to ongoing emissions from mobile sources) and soils and dust
contamination, due to past deposition from mobile sources, do not appear to contribute appreciably to Pb-
B levels for the study population. Similarly, the expected finding of a strong correlation for soil with
housing age category, was not determined. The analysis did, however, find a weak correlation of soil
concentration with distance from a major highway (r= 0.13, p= 0.0001).
PrqJctLEAP—Pha..1 112
-------
TABLE XX
Correlation Analysis of Minneapolis/St. Paul
. I • • . i . • •i • . .
B -BA 1 L 0 .8198 ‘
I . .., . 1 .
03476 L L .L I 1 .8129
LPB-BM 901 0.9664
0.3013 870.7621 0.4941 3.86 46
HAC 1033 0.9990
0.1841 1032 0 3.0000
DIST 1033 1135
937.76 1 172375 0 5015
SOIL 1033 1863 2199 19244 15 0 11162
I I , . , ’ I . H ; . ; . . 1 . . I . . .
.- . . : 4 Vy ? ?. V • .: . : : • . • • : : : : ; • 1: : • . . . : : : v : •: : • • . • • : • • • • : .
P*atson thbtblt2an CoefflaenW PStlity > 01 , R1x n LV No of OSetvaUoas
1 I
• : ; i : : :. • : .. ‘ : IP&BA • • •
• ! ? . E 1.0 0 0 0 0.0487
0 01436
1033 901
I d
::. : • ; ; . . . : • d . : • s i
0.0095 -0 .0849
07593 00063
1033 1033
r
• : • .:. :
0.0795
00106
1033
:.
WBBM 0 0487 1 0000
01436 0
901 901
1_ 1 . i j
-0 03855 .0 0049
0.2477 08825
901 901
0 7248
00001
901
flAt, ° 00095 -00385
* 07593 02477
: 1033 901
L.U t 11
10000 00093
0 07637
1033 1033
00240
04408
1033
DIS1 .00849 -00049
‘ ••• 00063 0.8825
? 1033 901
00093 10000
07637 0
1033 1033
01318
00001
1033
r ( tYL ri ( A r
sot 00795 07248
1 I ’ V 00106 00001
•:• < 1033 901
00240 01318
04408 00001
1033 1033
10000
0
1033
1 whcrc LPBBA a ln uu blood-lead level (pg ,tH); LPBBM a modeled Wood-lead level (pgM l) HAC a housing age
ategoty (range of years for oath category), as &fiIICd in she rcgreaion model; DIST a distace from an interstate highway
(men); and SOIL a SO iWead conanntion (ppm).
Pm LEAP— PIa 1 113
-------
A significant problem with the correlation analysis was that different physical scales were being
compared. The actual blood-lead values were associated with soil-lead values at or near the home of the
individual child, and thus it was on a relatively small geographic scale. The modeled blood-lead values,
in contrast, depended upon a soil-lead concentration for the census tract where the child resided. This
much larger geographic area (scale) could result in a soil-lead concentration much different than the actual
exposure concentration. Recognizing this, a second correlation analysis was employed to compare the
geometric mean of the measured blood-lead levels to the geometric mean modeled blood-lead levels
calculated for each census tract. Only census tracts having nine or more observations were selected, as
displayed in Table XX I. The modeled values are higher particularly in that high soil lead values were
used for census tract modeling, than is thought to be the actual exposure of children living in a census
tract.
PrQJ.ct LEAP— Ph 1 114
-------
TABLE XXI
Selected Census Tract Data from Minneapolis/St. Paul
... . ..
$o+
Ř
CCSI
‘fl
m4atP
(Ř j )
t S R
j44 *
!....!.!..
No
OW
-x : -x :yy’ •: : • ’: ’: •
Cs*te
Trs*
Vb.R A *
(GM)
• - : • :xc • : • • ’ • : • : •
Pb B Mod
(Ok)
a
26
15
9.79
(GM)
18.33
a
73
6.63
5.35
14
16
7.76
7.12
32
79
8.12
46.15
28
18
338
8.55
3)
83
10.19
11.73
9
21
8.60
13.59
14
86
5.36
11.93
14
22
8.10
8.00
30
301
536
6.49
27
25
4.78
8.77
20
325
10.84
6.49
14
28
538
6.31
16
326
931
8.06
14
29
6.62
14.61
14
335
7.08
8.06
12
33
731
7.77
11
355
8.91
3.48
16
36
4.95
7.22
46
357
431
6.27
3)
50
6.85
630
19
368
536
14.38
18
61
8.79
20.24
36
370
4.35
4.90
15
66
7.98
3.30
27
371
6.80
17.27
46
—
72
. 832
18.25
Table XXII presents the results of a correlation analysis for modeled blood-lead and actual blood-
lead variables listed in the table. The correlation improved from 0.13 to 0.3. The results were not
statistically significant, with p 0.10. Given the constraints inherent in the methodology, however, the
approach works reasonably well. It is interesting to note that for the modeled Pb-B mean values, some
census tracts were quite close to the measured Pb-B mean values. The larger estimated values from the
model results in a small Pearson correlation coefficient.
“Geometric mean value of rne ured blood-lead level.
Geometric mean value of modeled blood-lead level.
Pmj.s LEAP— Pbs . 1 115
-------
TABLE XX I I
Correlation Analysis- M inneapolis/St . Paul Census Tract Level
L 1 snnP !&atLe& : :
VMi ilt Numbtt j Mean Stimd*d r I “ “ ‘
. . ; . ‘ . : ; : : : : : : c . . . : : : : :z ::: .. . . . : . :.. ;. . : . . . : . : : . .
;I • •! 23324 • 97 : F o io;o
Thin !!•• —
28 io ns 8 5733 299120 0 46150
.11T 1 LL...LLJ ’ 1I ’I 1 1t .. LL.LJLL I U. .J. I
•
J] . . t .
x.ooo 03167
o.o 0.1005
I 03167 1 1 100
* 01005 00
.
In particular, one outlier results in a skewing of the data which causes a smaller pearson
correlation coefficient and a smaller p-value. Figure 12 is a scatter plot of the 27 data points in Table
XXI, comparing the geometric mean modeled blood-lead levels with the actual blood-lead levels for
children in each of the 27 census tracts. As shown in the scatter plot 1 there appears to be a definite linear
association between the two variables, with modeled values generally increasing with increasing measured
blood-lead levels.
“where LPBBA s meuumd blood4ead level, and PBBM a modeled blood-lead level.
Prqj.ctLFM —Pks l 116
-------
MinneapoHs/St.Paut Census Tract Data
G.řm.tr Ic M.ari -B Val u.s (u /dL)
a
40 -
30 -
20
D D
D D
0 D
a
U a
a
D
I I I I I I I I I I I I
0 2 4 6 9 10 12 14
tust BIocd-I*ad C -B) Values
FIGURE 12
Scatter Plot of Modeled Blood-lead Values Vs. Actual Blood-lead Values
5.4.4. Minneapolis/St. Paul Regression Analysis
A second use of the blood-lead data was to partition the actual blood-lead levels found among
environmental sources. For the data set, distance from a major thoroughfare was added to each record
in order to ascertain whether lead from vehicle exhaust (thought to be primarily via lead-contaminated dust
PrqJSCtLEAP—PhM.1 117
-------
and soil from historic deposition from vehicles) would explain a portion of the variation. In addition,
housing age was added to each record (by category) to recognize the contribution of lead-based paint.
This would also account for historic deposition from area and point sources.
Results of the regression analysis yielded the following for the full model and the final model.
Regression analysis for the full model shows a very small R 2 value of only 0.08, although the result is
statistically significant (p= 0.0001). This is an expected result, given the minimal Peaison correlation
coefficients derived for selected variables. The results are tabulated as Appendix 0.
The final model was derived by using a stepwise regression procedure, with a criterion level of
significance of p= 0.05 for inclusion of an independent variable in the formula. Non-significant regression
coefficients were not carried forward from the full to the final model. The results are tabulated in full as
Appendix R, and in summary form as TABLE XXJII. The final model is
Log PbB =1.007 - 0.017 AGE - 0.092 El + 0.099 E3 + 0.001 FAT - 0.004 INC
Where
PbB , = Measured blood-lead level from survey ( g/dL)
AGE = Age of child (years)
El = 1 if ethnicity is white, 0 otherwise
E3 = 1 if ethnicity is American Indian, 0 otherwise
FAT = number of years of father’s education
INC = family income for census tract (thousands of dollars)
PrqJ.ct LEAP— Phi.. 1
118
-------
TABLE XXIII
Summary of Stepwise Procedure for Dependent Variable
Actual Blood-lead Concentration for Minneapolis/St. Paul
I
.... ..... . ........... ... .. . .. .. ..... .. ..
Regression 5
&49494 1 .69698 14.88 0.0001
Error II 10
2 .20900 0 .11420
Total It 900 11
0.70394
: : : : : : .
INTERCEP 1.00708 0 .0 5457 38.88745 34032 0.0001
AGE -0.01748 0.00657 0.80810 7.08 0.0800
El -0.091 68 0.02840 1. 18992 10.42 0.00 13
E3 0.09692 0.03969 0 .70 930 6.21 0.0129
FAT 0.00096 0.00048 0.45675 4.00 0.0458
INC .0.00454 0.00 191 0.64049 . 5.6 1 0.0181
aiwnsna ll*anniambet4.47Ia4 3OS I5U\ +
AU nthbó In S ixaS an nflcam a the IWOGIcS Not vwats met the*OflisŘflc*n 1* cl *t
sqyintothomScL
J’L I ( 1 11 wiLi ahr L i d J t L J * 4J.J . aJ 4 J.
Swumaty otS*p win rnted ntt uepnnSx YMIS LPb4IA
l litF Lt i N1 MJ %v L 1 Ifl}t # ’ i Y ’ t ’ ’ ( ( i 1 , r F
SIm 41* t4c + 1 1 t*ds1R* 4 >M dta t c® F
: 4 b$;bt lI L f c; $.‘4t tZ ‘t;
1 El 1 J 0 .048 5 0.485 30.7085 45.8441 0.0001
2 INC 2 0.0096
0.058 1 23.3882 9. 1 134 0.026
3 AGE 3 0.0080
0 .0 661 17.5747 7.6970 0.0056
4 E3 4 0 .006 5
0.0726 13.2208 62961 0.0123
S FAT 5 0.0041
0.0767 11. 1980 3.9996 0.0458
a wte AGE s age ofthild: El a dummy variable fat white cthnidty E3 a dummy vati t hle for Aimri n In an eththdty
FAT a number of yars of father’s cduation and INC a family inuxnc for a nct of nsidcn
21 V R I I IMe Enteted, Removed
Pt J.ct LEA.?—. fla 1 119
-------
Independent variables that did not improve the model were the model estimate of the blood-lead
level (PbBm ), housing age category (HAC), distance from a major highway (DIS1), African-American
ethnicity (E2 = 1), gender (GEN), number of years of mother’s education (MOT), and the measured soil-
lead concentration for the census tract (SOIL). The comparison population for ethnicity (El =E2=E3=0)
consists of all ethnic categories except white, African-American, and American Indian. Although the final
model is statistically significant (p 0.001), the R 2 value is small, indicating that the selected independent
variables do not explain much of the variation in the measured blood-lead levels.
With the exception of the number of years of father’s education, FAT, the signs of all regression
coefficients in the final model reflect intuitive expectations. The blood-level decreases with age. This
is as expected for the overall childhood population range, although within the age strata, blood-lead levels
are expected to peak at two and then decrease. The negative association with white ethnicity and
increasing family income is also as expected. A positive regression coefficient associated with American
Indian ethnicity merely reflects the higher mean blood-lead levels for this ethnic group as a whole.
Only the number of yeais of fathers education, indicating an increasing blood-lead level with
increasing education, is counter to expectations. Further, it would be more logical to have a significant
regression coefficient for the mother’s education attainment, not the father’s, as indicated in the final
regression model. Consequently, the inclusion of FAT in the model and the positive sign of the regression
coefficient is thought to be a spurious effect.
A change in the ethnicity dummy variable scheme was made to ascertain whether African-
American and Hispanic blood-lead values would be statistically significantly higher than values for white
children, while controlling for other variables. Variable El was changed from El= white to E1 Hispanic.
The change was made to make the comparison population (E1=E2=E3=0) to be white and a small number
of ethnic minority children. This comparison population thus excludes Hispanic, African-American, and
American Indian children. The final revised model results are provided as Appendix S. The revised final
Prqfrct LEAP— Pb ... 1 120
-------
model is:
Log PbB = 0.998 -0.0172 AGE + 0.151 E3 + 0.001 FAT - 0.006 INC
Where
PbB = Measured blood-lead level from survey ( .tg/dL)
AGE = Age of child (years)
E3 = 1 if ethnicity is American Indian, 0 otherwise
FAT = number of years of father’s education
INC = family income for census tract (thousands of dollars)
5.5. UBK City Results
Based upon the use of ambient air quality data for each city, measured drinking water
concentration for the city, and weight averaged soil and dust concentrations for each census tract group,
the UBK model was used and city exceedance number developed. Aggregate results are displayed in
Table XXIV. Appendix T, provides detailed information by census tract group area.
Prcij.ctLEAP—Pha.e1 121
-------
TABLE XXIV
Numbers of Children Under 7 Yeazs of Age in the Midwest
ExpectS to Exceed 10 pxg/dL Blood-Lead Level in 1988
City Cbi ldhood
Population
Total No
xceedth2
African
Amenan
1Th
Exceedzog
Rock Island
4,910
461
103
17
Moline
4,379
434
5
37
Ch i t go
321,585
40,370
18,712
7,888
Knnkqkec
3:e l
289
87
— 3
Peoria
13,368
1,306
354
24
!omi ton
4,362
330
21
5
Normal
2,430
26
2
0
Champaign
3,979
168
34
2
Urbana
2,359
154
10
3
Rantoul -
N/As
Springfle]d
9,716
554
76
4
E. St. Louis
8,127
798
768
8
(3raniteCity
3,726
273
4
5
Zaate ‘
-
rx 1%$S
I
, 1 44, $
S2J @ ) !
198
Y 40 3%
ThY
; A
Gary
2o,855
831
652
69
Hammond —
10,522
-
1,059
92
100
E.Qilcago
5,073
660
189
275
SouthBend
11,441
1,084
207
26
Mishawaka
4,149
225
2
2
N/A not available. Data was not available S these thin.
Percentage of total population. Numbers are based upon ambient air, drinking water and derived soil and dust
lead ccnrrations used in the Uptake Biokmnctic Model.
ProJ.ct LEAP— Pbs. 1 122
-------
Ci ty O ii ldhood
PopU lat ion
Tot al No 4
&C eed1P g
African -
E A m er i can
H i s p a n i c
Exceeding
Elkhart
• : • f:
4,616
:
464
Exo dfl
97
7
Goshen
Ft. Wayne
18,910
1,780
414
55
LaFayette
4,146
243
5
3
Kokomo
5,437
401
27
6
Anderson
6,707
502
110
3
Muncie
6,822
522
56
4
Indianapolis
73,868
5,223
1,740
52
Terre Haute
5,250
797
71
6
Bloomington
2,775
- 141
7
—
2
Evansville
12,444
1,248
135
7
New Albany
tttal$*te
ót ln4Utw
3,598
•• : .. -
t$ř
sa Y
258
‘ A 43
L
13
•flTfll . _
an ?
‘ .
2
614
—
Saginaw
9,943
935
348
92
Bay City
4,358
564
10
— 27
Midland
3,834
45
1
1
Muskegon
4,741
603
135
18
Grand Rapids
20,064
1,942
486
99
Lansing
15,251
955
128
75
East Lansing
2,531
115
7
—
2
flint
19,923
1,446
581
38
Detroit
134,680
19,142
12,409
555
Ann Arbor
7,819
381
38
9
Battle_Creek
4,150
569
129
12
Jackson
4,588
748
119
15
Kalamazoo •
7,323
• 181
v i
Benton Harbor
NIA
Pnd.ct LEAP s Pbs. 1 123
-------
Moorhead 2,401 61 0 1
Duluth 8,299 1,284 9 5
St.Cloud 3,577 206 1 1
Minneapolis 29,884 4,611 379 59
St. Paul 25,357 3,333 194 97
Rochester 5,774 237 1 2
rota! State 75,2W 9 ,732 584 165
!LMmAesota (13 %)
Toledo 38,143 4,515 1,157 182
Cleveland 61,289 9,396 4,022 360
Akron 23,644 3,161 694 20
Lorain 8,962 465 53 70
Canton 9,739
1,342 264 18
—
Steubenville 2,002 160 25 1
Wheeling N /A
-
Marietta N/A
Youngstown 11,968
1,884 673 64
—
Warren 5,742 437 69 3
Mansfield 7,180 688 7
Lima 5,972 550 116 6
Dayton 22,426 2,206 688 17
Springfield 7,745 914 175 7
Columbus 2,968 432 110 5
Hamilton 7,217 728 77 6
M lddletown 4,467 281 31 1
Cimati 38,829 5,415 1,939 41
I
I
I
I
Prqj.ct LEAP— Ph ... 1
124
-------
1
J blOWn I a i m
BauClaire
4,250
247
- :i
• 1
Wausau
3,017
224
0
1
Green Bay
9 ,058
483
1
4
Oshkash
3,992
388
2
2
Neenah
N /A
Milwaukee
67,871
13,878
4,225
781
Racinc
9,626
819
130
56
Kenosha
7,927
494
19
22
Mad ison
12,294
759
21
11
Janesvifle
5,655
263
0
1
Beloit
3,982
421
63
5
LaQ •ossc
3 ,341
404
1
2
Sheboygan
4,810
443
1
8 II
. .AP !1!t ?n . 6 ,2 5 1
286
0
— -ii
The highest percentages of children exceeding 10 pg/dL Pb-B in Ill inois were derived for Chicago,
where the majority of census areas were in double digit percentages, with many in the 15 to 19 percent
range. The maximum value was 19 percent. A majority of the total number of children exceeding 10
pWdL in many of the conimunitia were Mńcan-Arnerican and Hispanic, reflecting the racial makeup of
the neighborhoods. This factor also gives rise to the large number of children under seven years of age
at risk of exposure to lead. The high exposure potential reflects primarily soil and dust concentrations
Indict LEAP— Pbs 1 125
-------
(based upon housing stock age). Drinking water and air concentration values in the city were low.
Two areas in East St. Louis also had high numbeis of African-American children with expected
exceedances, although the percentages were not high at 11 and 12 percent (597 and 100 African-American
children, respectively). Granite City, an area with widespread soil and dust contamination resulting from
industrial operations in the city, had an average of 7 percent exceedances using the methodology. The
relative small numbers for African-American and Hispanic children reflect the low population
concentrations of these two ethnic groups in Granite City. It is clear that the study approach
underestimates the risk in Granite City, however, by not using the higher actual soil and dust
concentrations that are currently being determined. One area in Peoria is notable, with a 15 percent
exceedance estimate corresponding to 224 African-American and 13 Hispanic children. No other Illinois
city was notable for large numbers of African-American or Hispanic children under seven years of age,
expected to exceed 10 .tg/dL Pb-B.
Compared to other states in the Midwest, the community areas of most cities in Indiana have low
percentile values for expected exceedances, and low numbers of potentially exposed African-American and
Hispanic childhood populations. This is due to not only generally low derived-exceedance-percentages,
but also to smaller city populations and relatively low population density for both minority ethnic groups.
Five cities, East Chicago, Evansville, Ft. Wayne, Indianapolis, and Terre Haute, had community areas in
the 15 to 19 percent range. The largest numbers of African-American and Hispanic children with expected
exceedances of 10 tg/dL Pb-B were in Indianapolis, with 1,740 and 52 children, respectively, followed
in quantitative rank by Gary, with 652 and 69 children, respectively. This ranking is generally indicative
of the relatively large population size of these two cities. It is noted, in particular, that the community
area percentages for the City of Gary were all less than 10 percent.
Detroit closely resembles Chicago in having a number of areas with expected percentages ranging
from 15*020 percent, with corresponding high numbers of African-American and Hispanic children
PraJ.ct LEAP- Ph 1 126
-------
reflecting the ethnic makeup of the communities. A total of 19,142 children, including 12,409 African-
American and 556 Hispanic children, are the expected exceedance numbers. For other State of Michigan
cities, aside from Detroit, community areas in Ann Arbor, Battle Creek, Flint, Jackson, and Kalamazoo
had percentile values in the 15 to 19 percent range. None of these areas, however, had very high numbers
of African-American or Hispanic children with expected exceedances of 10 .tg/dL Pb-B.
As expected, for the State of Minnesota, both the highest percentages and the greatest number of
African-American and Hispanic children with exceedances were derived for Minneapolis and St. Paul.
The Twin Cities expected numbers of African-American and Hispanic children with exceedances were,
respectively, 379 and 59 for Minneapolis, and 194 and 97 for St. Paul. For the State of Minnesota, only
Duluth, aside from the Twin Cities, had community areas with percentile ranges of 15 to 18 percent.
The community area in Ohio with the largest expected exceedance percentile was located in the
City of Toledo, with a value of 20 percent, corresponding to 431 African-American and 45 Hispanic
children expected to exceed 10 .tg/dL Pb-B. For the city as a whole, 1,157 African-American and 182
Hispanic children are expected to exceed 10 .tg/dL Pb-B. Two cities in Ohio have higher numbers of
children with exceedances. Qeveland’s numbers are 4,022 African-American children and 360 Hispanic
children, and Cincinnati’s numbers are 1934 and 41, respectively. Although several other cities had
community areas with percentage values in the 15 to 19 percent xunge, the only other city with more than
1,000 children potentially exceeding the criterion value was Columbus, with 1,094.African-American and
33 Hispanic children. For the State of Ohio, the highest percentile of 23 percent was derived for a low
population density community area in Youngstown.
Wisconsin is set apart somewhat from the other states and community areas by having several
communities with levels of lead in drinking water at measured levels, above the level of detection. This
factor, combined with soil and dust concentrations associated with older housing stock, resulted in the
higher estimates of exceedance for four Wisconsin cities.
Prqjsct IZAP- Ph. 1 127
-------
On a community total basis, Milwaukee is high both in percentile (20 percent) and in numbers
(13,878 total, including 4,225 African-American and 781 Hispanic children). Several areas were in the
28 to 30 percent range, making the city the highest overall of all cities assessed, and resulting in large
estimated numbers of children with exceedances. Milwaukee’s drinking water concentration also measured
comparatively high, at 25 ppb for 1988. Aside from estimated percentages of 17 percent for areas in both
La Crosse and Racine, neither the percentiles nor the numbers of African-American and Hispanic children
exceedances were exceptional for all other communities in Wisconsin.
Seven cities are in the top 10 by virtue of both overall percent exceeding and number of children
exceeding 10 Itg/dL Those cities are Milwaukee, Wisconsin; Detroit, Michigan; Minneapolis and St. Paul,
Minnesota; and Cincinnati, Akron, and Cleveland, Ohio. The top 10 cities, by percentile and total number
of children, are shown in TABLES XXV and XXVI, respectively.
TABLE XXV
Top Ranked Cities by Percentile
of Children Exceeding 10 jsg/dL Pb-B
1 Milwauke WI 20.4
13,878 4,225 781
2 Jackson,MI 163
748 118 15
3 Duluth, MN 15.5
1,284 9 5
4 Minneapolis, MN 153
4,611 379 5 9
5 Cleveland, OH 153
96 4,022 360
6 Terre Haute, IN 15.2
797 71 6
7 Detroit,MI 14.2
19,142 12,409 556
8 Cincinnati, OH 13.9
5,415 1,934• 41
9 BattleCreek,MI 13.7
569 129 11
1 Akron, OH 13.4
0
3,161 694 20
Pn J.d LEAP- Ph .. 1 128
-------
TABLE XXVJ
Top Ranked Cities by Number of
Children Exceeding 10 pg/dL Pb-B
. ... . ...i..r - .
b BimectedibudNo E x pected f l o -o f ExxctedNoo l
. :..
. • .
:.
:r . r ::.ihIsS lSIW*W
Ve in
:.
baldi c aa
Lts,JJaIJa.
xenc7Years
I
1
i • —
Chicago, IL
13
C
i — • — a i
40,370
Old
a
18,712
O I L)
a S
7,888
2
Detroit, Ml
14
19,142
12,409
555
3
Milwaukee, WI
20
13,878
4,225
781
4
Cleveland, OH
15
9,396
4,022
- 360
S
Cincinnati, OH
13
5,415
1,939
- 41
6
Indianapolis, IN
7
5,223
1,740
52
I.
Minneapolis, MN
15
4,611
379
!.
8
Toledo OH
12
4,515
1,157
182
9
1
St. Paul, MN
Akron,OH
13
85
3,333
3,161
194
694
97
20
0
a
—
The six Midwest states ranged from 8 percent exceedance estimates in Indiana to 13 percent in
Minnesota, although it is noted that these percentages are not particularly meaningful at the stale level.
The States of Illinois and Michigan had the largest numbers of African-American and Hispanic children
under seven years of age expected to exceed 10 sg/dL Pb-B, including 28,000 and 16,000 minority
children, in the respective states. Every state has community areas where elevated blood-lead levels are
of concern.
For the six states, all cities combined, the total childhood population (children under seven yeafl
of age) was 1,359,000 in 1988. The analysis indicates that 154,000 children, or 11 percent of the total,
would have blood-lead levels exceeding 10 pgldL This includes 55,000 African-American and 12,000
Project LEAP— Pha. 1 iv
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Hispanic children. These numbers are presented for illustrative purposes, and are not a prediction of
numbers of children. It is noted, however, that these numbers are conservative compared to other
estimates (refer to Section 2.5).
PrqJ.ct LEAP— Pha.. 1. 130
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6. DISCUSSION
The population comparative risk methodology developed for this study contributes to the
understanding of the extent to which low-level environmental sources of lead add to elevated blood-lead
levels in childhood populations. The methodology provides an assessment of the relative numbers of
children at risk to the adverse health effects due to environmental lead exposure. Previous studies have
been at the national level. The methodology fills a gap in research efforts on the extent of childhood lead
poisoning. It provides city specific estimates to highlight possible areas of l igh numbers of children with
elevated blood-lead levels. Indeed, the methodology provides comparative numbers within cities.
A key value of the methodology is as a ranking tool to guide public health officials to cities and
areas within cities having the highest potential for childhood exposure to lead. More definitive data would
need to be obtained to confirm the initial characterization of areas as high risk. Rather than investing
resources in areas found in retrospect to be low risk areas, however, high risk areas could be targeted and
addressed on a priority basis. Further, the environmental pathways of exposure developed in this study,
provide a clear indication of whether to gather further information on air quality, drinking water quality,
or soil and dust concentrations in a given city. Such measured environmental data, together with any
blood-lead data available for a community, is a fundamental step towards primary intervention actions.
Removing lead from the environment will avoid the need for clinical interveetion for the individual child.
That is, of course, the desired outcome.
6.1. Demograřhics
Although the demographic and associated data (housing age, income) was obtained for each census
tract, there were inherent imprecision in the data. The results of the 1990 census was not yet available;
1988 data (estimated from the 1980 census) were utilized. The numbers derived from these estimated data
therefore have, inherently, the same level of inaccuracy.
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Beyond data estimation, a larger problem concerns how the data were categorized, as reported in
the census data base. Because the age categories did not match the study design (e.g., childhood age strata
were zero to five, six to 13 years, etc., while the Study design focused upon children less than seven years
of age), an approximation was derived to reflect the number of children in the study design strata.
A more problematic concern is that children in each age band were not totally disaggregated by
ethnicity. Derived numbers were thus underestimates of the actual numbers of minority children in an area
and, consequently, determined to exceed the criterion blood-lead value. This resulted from a procedure
that calculated the number of children in a census tract by a proration of the relevant ethnic group’s
portion of the total population. Such an approach is accurate only for mono- thnic populations. As ethnic
diversity increases, this method of estimation becomes more and more imprecise. In particular, it results
in an underestimate when the number of children in minority families (i.e., family size) exceed the number
of children for the community as a whole. Similarly, the demographic data obtained at the census tract
level did not include ethnicity-specific birth, rates. Because African-American and Hispanic birth rates are
often higher than the general population, application of a city’s overall birth rate to the ethnicity-specific
population, to estimate numbers of fetuses at risk, results in an underestimate of fetuses at risk.
Problems of matching housing age categories were similar. The census data provided strata
beginning with housing stock built prior to 1949. For purposes of the study, age strata for housing stock
built before 1920 and before 1940, associated with lead pipes and higher concentrations of lead-based
paint, respectively, would be more pertinent. Some precision in estimating soil and dust values, in
particular, was sacrificed by assuming houses built before 1949 were also expected to have lead-water
supply pipes and higher lead-based-paint concentrations.
A key finding, well into the study, was that the geographic information systems software platform
was not the most expedient in manipulation of demographic housing stock age, and other census bureau
obtained information. Indeed, extraction of relevant data (census tract information only for selected cities
PrQJ.ct IZAP— Phi.. 1 132
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within each of the six states) proceeded rapidly when processed using standard data base management
software on a personal computer platform.
6.2. Environmental Data
Several aspects of the usefulness, or lack thereof, of environmental data became readily apparent
as the study progressed. The air route of exposure was determined to be of minor consequence as a
contributor to the estimated blood-lead levels. The measured air-lead concentrations were found to be very
low in an overwhelming number of cases. Even the modeled major sources; for which air concentrations
were derived, proved to have little impact, beyond relative close proximity to the source. Consequently,
at the large scale for which the algorithm was applied (aggregations of census tracts), those concentrations
could not be included in the UBK model results, nor, consequently, accounted for in the estimated
numbers of childhood exceedances. It is also noted that many of the sources are located distant from the
central city populations of concern. Based upon these findings, it is apparent that the relatively small
numbers of children affected by such point sources, would not change the substantive results of the
comparative population (by city) risk analysis. Surprisingly, the Toxic Release Inventory data base proved
to be valuable in assessing the relative importance of point sources of emissions, while the Aerometric
Information and Retrieval System Facility Subsystem, which also provided emission information, was not
useful for the study. The only other category of air emissions, municipal waste combusters, appeared to
be of minor import as a source of exposure.
The results for abandoned hazardous waste sites were also unexpected, in that the great majority
(of lead contaminated sites) are located outside the central cities, and thus away from populations of
concern. As was the case for air stationary sources, contamination of soils and dusts at a site would be
a local phenomenon affecting only closely proximate populations. None were accounted for in the UBK
modeling. An assessment of sites, however, indicated the need for little concern for the category as a
whole, except as noted in the results section concerning Granite City, Illinois.
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Operating hazardous waste facilities proved to be the most difficult to assess. This was primarily
because there is no central data base for which to list Resource Conservation and Recovery Act facilities
that dispose of lead and lead compounds. Generally, for the facilities assessed, the categorical source was
•not deemed to be a factor in the study area cities.
Drinking water contamination was found generally to not be a problem, and, except for the cities
noted in the results section, the categorical source is not a major contributor to estimated elevated blood-
lead levels. It is noted, however, that brass plumbing fixtures and lead contamination associated with new
home construction is not addressed.
The procedure, utilization of the UBK model, did not include lead-based paint concentrations.
That was beyond the scope of the study, which addressed environmental sources of lead. There was also
a deanh of information upon which to estimate lead-based paint contribution, for purposes of this
methodology. The study focused upon environmental sources of lead to estimate chronic effects. Lead-
based paint, historically, has been associated more with acute effects. (This is because at high blood-lead
levels, signs and symptom are more readily discernable.) Consequently, soil and dust concentration
values, derived from age of housing stock, generally predominates as the source of estimated elevated
blood-lead levels. The percent exceedances and corresponding numbers of children exceeding the criterion
value are driven by housing age (dust and soil concentrations) with adjustments for drinking water and
air concentrations pertinent to each community assessed.
6.3 Correlation Analysis
The original correlation analysis for the Minneapolis and St. Paul areas, upon application, was
determined not to be adequate for testing the validity of the algorithm. A fundamental problem is in the
use of the UBIC model to derive modeled blood-lead values for comparison to actual values. The model
calculates a geometric mean blood-lead value for a population. The study data was of individual
measurements. An individual child, even having the same exposure concentrations used in the UBK
Project LEAP- Phase 1 134
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model run, could, of course, have a Pb-B level on either side of the mean value, and could very well be
two or more standard deviations from the mean. Consequently, the derived (mean) value cannot be
expected to correlate well with the actual (individual) value. Further, a different scale for the two values
was used. For the actual Pb-B value, data for the child was measured specific to the child and the home.
For the UBK model, information (soils data) was available only at the (much larger and consequently very
much more varied) census tract level. The great deal of variability in soil concentrations at residential
yards, as further varied by choice of sampling location, is also noted. Moreover, nothing in the model
could account for what was undoubtedly also occurring, i.e., potential for contaminated paint and dust
exposure, home habits (such as frequency of dusting), occupational exposure, cigarette smoking in the
home, and other factors. These factors are all known to affect Pb-B levels. Consequently, the procedure
was not deemed to be robust, in that statistical power was lost due to each of these factors.
A second derived approach, using the geometric mean values for all actual blood-lead values,
yielded a better result, although most of the same problems are inherent in that approach as well.
6.4 Renression Analysis
Distance from a major highway was not found to be associated with blood-lead levels. The
finding of statistical significance is not particularly relevant given the small R 2 value calculated for the
final model. The analysis failed to find an association between blood-lead levels and distance from either
an interstate highway, or with soil. The latter fmding is consistent with that of the State of Minnesota
study (MPCA and MDH, 1987) (i.e., the relationship between blood-lead levels and soil concentrations
is weak). Given that weakness, the lack of a relationship with distance from a highway is also an
expected result.
With the exception of the number of yeazs of father’s education, FAT, the signs of all regression
coefficients in the final model reflect intuitive expectations. The blood-level decreases with age. This
is as expected for the overall childhood population range, although within the age strata, blood-lead levels
Projsct LEAP— Ph ... 1 135
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are expected to peak at two and then decrease. The negative association with white ethnicity and
increasing family income are also as expected. A positive regression coefficient associated with American
Indian ethnicity merely reflects the higher mean blood-lead levels for this ethnic group as a whole. Thus
compared to minority children (other than African-American), white children have statistically significantly
lower blood-lead level. American Indian children, however, have statistically significantly higher blood-
lead levels.
Only the number of years of fathers education, indicating an increasing blood-lead level with
increasing education, is counter to expectations. Further, it would be more logical to have a significant
regression coefficient for the mother’s education attainment, not the father’s, as indicated in the final
regression model. Consequently, the inclusion of FAT in the model and the positive sign of the regression
coefficient is thought to be a spurious effect.
The revised final regression inodel, substituting Hispanic for white as dummy variable El, yielded
unexpected results. After controlling for other variables, neither variable El (Hispanic) nor E2 (African-
American) were associated with the actual blood-lead levels at statistically significant levels. Thus the
higher mean blood-lead levels for African-American and Hispanic children compared ton white children,
controlling for other variables, is not statistically significant. Compared to white children, American
Indian children have statistically significant higher mean blood-lead levels. Compared to (predominately)
white childhood population in the revised model, or other ethnic minorities as in the original regression
model, American Indian children have blood-lead Levels that are statistically significantly higher.
6.5 City Estimates of Exceedance
The derived values are thought to be minimal estimates for several reasons. As discussed under
demographics, the numbers of children estimated in the ethnicity categories of interest arc low. The
procedure, further, focuses upon chronic exposure from environmental sources, and does not account for
additional numbers of children due to exposures to contaminated paint, including any resultant acute
PrqJsd LEAP— Ph. 1 136
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exposures. The latter, in an area of deteriorating older housing stock, can greatly increase the numbers
of affected children.
Moreover, a significant concern in the procedure is that the UBK model does not account for
ethnicity or socioeconomic status (nor was it designed to do so). It is well documented that such factors
increase the relative risk for many in the study population. By point of comparison, for large numbers
of African-American children, ATSDR (1988) postulates that fully two-thirds in the lowest socio-economic
stratum would exceed 15 p.tg/dL blood-lead. This is well above the percentages derived from the
algorithm. Further, a 10 g/dL criterion level would result in greater than two-thirds of the pertinent
population exceeding the value.
6.6 Uncertainties
As with most screening methodologies, there are a number of areas in the methodology that
introduce uncertainty into the results. Due to the wide range of data that the methodology uses, mixing
actual data with postulated data and then using a model, it is impossible to calculate an uncertainty in the
traditional sense (derivation of a confidence interval with an associated level of statistical significance for
the numbers of children cited for each city). It is not the intent of the study, however, to predict numbers
of children exceeding 10 tg/dL blood-lead. Rather, it is to compare cities in order to make reasoned
judgements on which geographic areas appear to have children at highest risk of exposure to
environmental sources of lead. Actual measurements would then be necessary to ascertain childhood
exposure. Nonetheless, it is useful to discuss uncertainties in the methodology, discussed throughout this
document, in one section. That is the purpose of this discussion, to summarize uncertainties inherent in
this population comparative risk screening methodology.
The quality of ambient air quality data is judged to be excellent. The data is from an ongoing
ambient air quality network administered by each state agency under a rigorous quality assurance program.
The program is prescribed by U.S. EPA regulations. Monitors arc generally sited to ascertain peak spatial
Project LEAP— Phi.. 1 137
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concentrations, however, not to determine representativeness of air quality in a city, per se. It is,
nevertheless, often used for that purpose. Further, the limited numbers of monitors does raise concern
about how representative the data are.
Drinldng water data were taken from data generated by drinking water suppliers, as provided to
state agencies, under a quality assurance program prescribed by U.S. EPA regulation. A limited number
of samples, taken at the supply, is used to characterize exposure for the entire community serviced.
Variations in samples taken over a course of time during the year indicates that actual exposure, in some
instances, may be difficult to determine. There is no readily discernable pattern of variation, where lead
was found at detectable levels. It is also noted that most of the supplies consistently measured non-
detectable levels of lead.
The soil and dust values used in the UBK model were those estimated from the ages of housing
stock for each area. No measured values were used. Consequently, there is substantial uncertainty in the
derived concentrations. Further, the data base from which the estimates were derived, the National
Housing Survey Data discussed in Section 4.6.3., had a range of values for each housing age category.
For houses built between 1961) and 1979, dust-lead concentration values ranged from Oppm to 1520 ppm,
with a mean value of 20 ppm and a standard deviation of 145. For older homes, those built prior to 1940,
the range was even greater, from a minimum of 0 ppm dust-lead to a maximum of 33,130 ppm, with a
mean of 565 ppm and a standard deviation of 3,780. Comparable soil-lead concentrations for pre-1940
housing stock were a minimum soil-lead concentration of 1 ppm, a maximum of 6,260 ppm, a mean of
565 ppm, and a standard deviation of 1,060. Thus there is uncertainty in the values chosen to represent
soil and dust values in the UBK model, based upon age of the dwelling.
There are a number of routes for introduction of uncertainty via use of the UBK model. The
model uses assumptions regarding behavioral and physiological parameters that affect the results (discussed
in Section 4.7). Behavioral patterns assumed for each age group, for example, could miss the mark.
Prqfrct LEAP— Ph 1 138
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Section 4.7.1. discusses the high dependence of the model on the selection of the geometric standard
deviation (GSD) assumed to be applicable a modeled population. For a given set of concentrations,
changing the GSD from 1.42 to 1.8 results in an estimated percentage of childhood exceedance of 10
tg/dL of 0.05 percent for the lower GSD, to 2.47 percent for a GSD of 1.8. This, consequently, would
introduce a great amount of uncertainty, if the UBK model were being used as a predictive tool. It is not
being used for that purpose here. Consequently, because any uncertainty introduced by selection of a GSD
value is in the same direction for all cities, the uncertainty introduced via this mechanism is of less
concern (when comparing populations).
Additional uncertainty is introduced via this new use of the model. It has not been validated for
use at the census tract level. Rather, it was developed for use at specific sites, for which environmental
concentrations have been more readily obtainable.
Finally, the correlation analysis, comparing the mean values of blood-lead values for groups of
children in a census tract, to the UBK modeled values for the tract, resulted in a correlation coefficient
of 0.3 at p > 0.10. While this result indicates a relatively weak correlation, it appears to be quite
reasonable given the myriad of uncertainties associated with the methodology. In particular, it is
reasonable given the use of the methodology as a population comparative risk screening tool, as opposed
to as a predictive methodology.
PrqJ.ct LEAP— Pb. 1 139
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7. CONCLUSIONS
Central city residents, particularly African-American and Hispanic children, are subject to low-
level exposure of environmental sources of lead. Differential exposure exists amongst the cities. The
population screening methodology provides a viable method for estimating where the greatest numbers
of children at highest risk reside. Clearly soil and dust concentrations predominate as sources of lead
contamination. Drinking water quality contributes in a few cities.
The screening methodology is based upon using existing environmental and demographic
information. Consequently, not all desired information was attainable. Several assumptions were made
in order to proceed with the study. To test the impact of the assumptions (for example, the use of model
default concentrations when measured environmental data were unavailable), a sensitivity analysis was
conducted. l’hat analysis indicated that soil and dust concentrations, at higher concentrations,
predominated as contributing to higher blood-lead levels. The dust concentration value, however, was
unreliable. Nevertheless, the analysis indicated that use of the calculated dust concentration had minimum
effect upon the numbers of children calculated to exceed 10 p.g/dL Pb-B.
An inability to account for ethnicity and socioeconomic status resulted in an underestimate of the
at-risk population in lower socioeconomic minority communities. Nevertheless, the approach is considered
to be valid, even though there was only a weak cormlation between Pb-B modeled and Pb-B measured,
due to the factors discussed. A fundamental factor of the analysis is that the UBK model used to derive
modeled blood-lead levels is not, nor was it intended to be, applicable and appropriate for use to discern
a blood-lead level for an individual child. The model is only appropriate for estimating the affects on
populations of children. That is the use for which the methology uses the UBK model. Consequently, its
use in this population comparative risk analysis is thought to be appropriate. Accordingly, the
methodology should prove to be useful in identifying “hot spot” areas where there may be sizable numbers
of children at higher relative risk to environmental lead exposure. The study approach estimates that
Pmj.ct LEAP- Phi.. 1 140
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significant numbers of children under the age of seven years are exposed to environmental sources of lead
at levels exceeding 10 g/dL The population comparative risk number of children is 163,000 in 83 cities
in the six states assessed, including 56,000 African-American and 12,000 Hispanic children. The actual
numbers exceeding 10 ig/dL cannot be ascertained by the population screening methodology. Additional
blood-lead elevations due to lead-based paint exposure is not accounted for in the methodology.
Consequently, the calculated numbers are believed to be conservative.
Although soil and dust are the most important determinants of modeled Pb-B levels, there is a
paucity of information about the extent of lead-contamination caused by operating and abandoned
hazardous waste facilities that could cause such contamination. Generally, off-site soil, dust, and air
sampling for lead has not been conducted. Nonetheless, there may be a relatively small number of
residents potentially exposed. Except for Granite City, Iffinois and Lansing, Michigan, this category of
sources does not appear to warrant significant concern for most areas. Extensive sampling, however,
around each site, would be required to make a definitive fmding. Unless there is strong indication of
contamination, however, such sampling is not generally deemed to be prudent or cost effective.
Major air sources are of concern only for residences near emission sources. Municipal waste
combusters, as a whole, do not appear to constitute a serious concern. More information is required,
however, to make that judgement. Modeling of the air sources did not add value to the methodology,
aside from confirming the lack of wide-spread impact.
The ambient air, drinking water supply, and toxic release inventory data were useful in
development of the methodology and, for the former two data bases, for calculation of mean blood-lead
values.
One would expect to find a stronger correlation for distance from a major highway and the actual
blood-lead measurements only if there were a strong correlation for soil concentration and distance from
a major highway. That association, although statistically significant, was weak. The conclusion is that,
Pr .etLEAP—Pbu.s1 141
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for the population (recall that high soil-lead values were the criterion for sclection of tested children for
the blood-lead survey), the distance from a major highway does not correlate with actual blood-lead levels
(or soil concentrations). Consequently, other factors (e.g., lead-based paint) appear to contribute more to
the elevated Pb-B found, in the survey. It is noted, however, that the average distance from the center
of the census tracts to an interstate is greater than one km, and that the maximum distance exceeds five
km. Accordingly, most of the children appear to be too far distant to be exposed via the mobile source
route. These results are applicable only for the Minneapolis,St. Paul area studied, and can not be
generalized to the study area as a whole.
The majority of data analysis should be conducted on a personal computer, in lieu of manipulation
using geographic information systems. Data manipulation on the personal computer proceeds with relative
ease. The latter computer platform should be utilized to obtain the census bureau data, as well as to map
the results of the analysis.
The demographic and housing information was adequate for purposes of developing the
methodology and for estimating the spatial and numerical dimensions of minority children at risk for low-
level exposure from envimnnientaj sources of lead. Precise population and housing estimates for optimal
stratification were not available. Nevertheless, that factor was not deemed crucial to the study results, in
that estimated and representative environmental exposures were used. Further, the UBK model itself is
an approximation. Consequently, for population risk screening purposes, the data were satisfactory.
PreJ. * LEAP— Pb 1 142
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8. RECOMMENDATIONS
Repeat the derived methodology for other EPA regions and states, or for smaller geographic areas
where targeting is desired to rank, prioritize, and better characterize the numbers and extent of at risk
minority populations exposed to lead. The derived methodology recognizes the efforts that did not
contribute to the screening approach. For example, account for abandoned and operating waste sites,
municipal waste combusters, and stationary sources of air emissions spatially and qualitatively, with
follow-up if a facility is located within a high percentage exceedance area, as identified via the
methodology. It is not worthwhile, however, to include the modeled air-lead concentrations as input to
the UBK model.
Include the contribution of lead-based paint to elevated blood-lead levels by using procedures as
derived for soil- and dust-lead concentrations, based upon age of housing stock. This would better
estimate expected blood-lead values. Calculated values would be based upon better knowledge of the
association of lead-based paint contributions to daily intake, with housing age.
Select areas within the top 10 cities with the highest numbers of children at risk, for on-site
sampling and investigation, in order to determine the actual extent of residential lead contamination.
Develop and implement a public outreach and awareness strategy, pertinent to African-American and
Hispanic communities, in particular, but inclusive of any population at high risk of exposure, in selected
cities. Work with public health departments to coordinate outreach and education efforts to targeted
communities.
Determine if census tract level data are available from the Bureau of the Census, stratified by
ethnicity for children under seven years of age, for ethnicity specific birth rates, and housing age
categories more relevant to lead usage in residential areas.
Further investigate hazardous wastes sites in Granite Qty, East St. Louis, Lansing Michigan, and any city
PrqJ.ct LEAP-- 1 143
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where a site falls within an area with large numbers of children expected to exceed 10 .tg/dL blood-lead.
Complete the remedial design work for the NLTFaracorp Corp. site in Granite City, Illinois, pursuant to
on-site abatement and replacement of contaminated soil in the 55 square block residential area.
Review major sources with high (relatively) high modeled air values to ensure nearby residents
are not exposed to excessive air-lead concentrations. Obtain results of stack test information, when
available, for the Chicago, Illinois, North Montgomery County, Ohio, and South Montgomery County,
Ohio, municipal waste incinerators, to ensure that lead emissions do not pose an unacceptable risk to local
residents.
Ascertain the current drinking water lead concentrations for the Cities of Wausau, Milwaukee, and
Madison, Wisconsin, and Youngstown, Ohio, and consider whether additional education or other action
is warranted.
PrqJ.ct LEAP— Ph s 1 144
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