ggl ) PEI ASSOCIATES
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ESTIMATION OF DAILY LEAD
UPTAKE IN CHILDREN AND RESULTING
END-OF-MONTH BLOOD LEAD LEVELS
by
Ted Johnson and Roy Paul
PEI Associates, Inc.
505 South Duke Street, Suite 503
Durham, North Carolina 27701-3196
Contract No. 68-02-4309
Work Assignment No. 22
PN 3659-22
Richard B. Atherton, Project Officer
Jeff Cohen, Work Assignment Manager
STRATEGIES AND AIR STANDARDS DIVISION
U.S. ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711
February 1986
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DISCLAIMER
This report was prepared by PEI Associates, Inc., Cincinnati, Ohio,
under Contract No. 68-02-4309, Work Assignment No. 22. It has been reviewed
by the Strategies and Air Standards Division of the Office of Air Quality
Planning and Standards, U.S. Environmental Protection Agency and approved for
publication. Approval does not signify that the contents necessarily reflect
the views and policies of the U.S. Environmental Protection Agency. Mention
of trade names or commercial products is not intended to constitute endorse-
ment or recommendation for use.
ii
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CONTENTS
Figures iv
Tables iv
Acknowledgment v
1. Introduction 1
2. Estimation of Lead Uptake 3
Daily lead uptake from lungs 8
Daily lead uptake related to diet 10
Daily lead uptake related to dirt 11
The Multiyear Lead Uptake Program 12
3. User Prompting and Output Format of the Multiyear Lead
Uptake Program 13
4. Estimation of Blood Lead Levels 17
5. User Prompting and Output Format of the Biokinetics
Program 21
6. Sensitivity Analyses 25
References 30
Appendices
A. Estimates for selected parameter values 32
B. Multiyear Lead Uptake Program and sample outputs 37
C. Biokinetics Program and sample outputs 54
iii
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FIGURES
Number Page
1 User Prompting Statements of the Multiyear Lead Uptake
Program 14
2 Lead Pathways Considered in Harley-Kneip Integrated Metabolic
Model 18
3 Harley-Kneip Integrated Metabolic Model for Determining Lead
Levels in Four Body Compartments 19
4 User-Prompting Statements of the Biokinetics Program 22
TABLES
Number Page
1 Parameters in Lead Uptake Model 4
2 Estimates for Selected Parameters of Lead Uptake Model. ... 5
3 Year-Specific Estimates for VEHIC, INADIET, and INMISC
Parameters of Lead Uptake Model 6
4 Lower and Upper Bound Estimates for Lead Concentration in
Street Dust and Soil and in Indoor Dust 7
5 Parameter Values for the Biokinetics Program 20
6 Initial and Alternate Paremeter Values Used in Sensitivity
Analyses 25
7 Results of Sensitivity Analyses 28
iv
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ACKNOWLEDGMENT
This report was prepared for the U.S. Environmental Protection Agency
by PEI Associates, Inc., Cincinnati, Ohio. Mr. Jeff Cohen was the EPA Work
Assignment Manager and contributed material to Section 6 and Appendix A of
this report. Mr. David Dunbar served as the PEI Project Director. Mr. Ted
Johnson was the PEI Project Manager and the principal author of this report.
Mr. Roy Paul wrote the computer programs which implement the lead uptake and
biokinetic models. Ms. Alicia Ferdo assisted in compiling input data for the
programs and in executing the programs. The authors would like to thank
Mr. Jeff Cohen and Ms. Donna Sledge for their guidance and direction on this
work assignment.
v
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SECTION 1
INTRODUCTION
Under the Clean Air Act, the U.S. Environmental Protection Agency (EPA)
is responsible for establishing National Ambient Air Quality Standards
(NAAQS's) and for reviewing them periodically to determine their adequacies
on the basis of recent experience and research. In view of these responsi-
bilities, the Strategies and Air Standards Division (SASD) of the Office of
Air Quality Planning and Standards (OAQPS) is currently assessing health risks
associated with alternative NAAQS's for lead. A staff paper1 prepared by SASD
describes a model for estimating lead uptake in children based on estimates of
lead concentrations in air, food, and dirt; on estimates of the quantities of
air, food, and dirt consumed by children; and estimates of the absorption of
lead by the lungs and gut. PEI Associates, Inc. (PEI), has written a computer
program, Multiyaar Lead Uptake, which implements the SASD lead uptake model.
The program provides daily lead uptake estimates for children in user-specified
census tracts which may or may not be impacted by emissions from lead point
sources. Children are grouped into cohorts according to age in a user-specified
base year. The lead uptake estimates are month-specific and span the period
from the birth of each group through the base year.
Multiyear Lead Uptake creates an output file which can be directly accessed
by a second PEI program, Biokinetics, which determines end-of-the-month blood
lead levels for each cohort from birth through the base year. This program
2
is based on a four-compartment metabolic model developed by Harley and Kneip
which calculates lead concentrations in blood and selected organs based on
daily lead uptake.
Section 2 of this report provides the formulas used by the Multiyear Lead
Uptake Program to estimate lead uptake. The rationale behind these formulas
is discussed in the staff paper and in Appendix A. User prompting statements
and output format for this program are described in Section 3. Section 4
provides a brief description of the Biokinetics Program; Section 5 describes
1
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user prompting statements and program output. The results of a sensitivity
analysis to determine the effects of varying input parameter values on program
output are discussed in Section 6.
2
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SECTION 2
ESTIMATION OF LEAD UPTAKE
The lead uptake model is intended to be applied to a group of census
tracts specified by the user. These census tracts comprise the "study area."
Within the study area, the model provides estimates of the daily average lead
uptake of specific population cohorts. A cohort is defined as all children
with a set of user-defined characteristics that reside in a particular census
tract in a specified year and fall into one of seven age groups: 0 to 0.99
year, 1 to 1.99 years, 2 to 2.99 years, 3 to 3.99 years, 4 to 4.99 years,
5 to 5.99 years, and 6 to 6.99 years. Consequently, a study area with 100
census tracts would contain 700 cohorts.
The daily average lead uptake (TDLU) of each member of a particular
cohort is assumed to be identical. The value of TDLU is calculated by the
expression
TDLU = UPLUNG + UPDIET + UPDIRT, (1)
where UPLUNG is the daily average lead uptake from the lungs, UPDIET is the
daily average lead uptake related to diet, and UPDIRT is the daily average
lead uptake related to dirt ingestion. Sections 2.1, 2.2, and 2.3 discuss
how UPLUNG, UPDIET, and UPDIRT are estimated.
Table 1 lists the parameters which appear in the lead uptake model and
the units in which each should be expressed. Recoiranended values for many of
these variables are presented in Tables 2, 3, and 4 and in the text. A lower
bound estimate of TDLU is determined by using only lower bound parameter values
in the lead uptake model. An upper bound estimate of TDLU is determined by
using only upper bound parameter values. If bounds have not been determined
for a variable, a "best estimate" value is used in both cases.
Estimates of TDLU are determined on a monthly basis to reflect the
ambient air lead data used by the model. These data consist of 12 monthly
3
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TABLE 1. PARAMETERS IN LEAD UPTAKE MODEL
Parameter
ABSDIET
ABSD1RT
ABSLUNG
BACK
CRYAL
D1RTCDNS
XfTST DUGT&T
HOUT
INAD1ET
INAIR
INDIET
INDIRT
INMISC
IORATIO
MULT
OUTAQ
SOURCEAQ
TOLU
UPDIET
UPDIRT
UPLUNG
VEHIC
VRESP
WAQ
UDIRT
Units
ug/m
ug/m3
g/day
vg/g
P9/9
hours/day
vg/day
ug/day
ug/day
ug/day
ug/day
ug/m
3
ug/ra
ug/day
ug/day
ug/day
yg/day
ug/m3
m3/day
ug/m3
ug/g
Definition
Fraction of ingested diet-related lead which is
absorbed by gut
Fraction of ingested dirt-related lead which is
absorbed by gut
Fraction of inhaled lead which is absorbed
through the lungs into the bloodstream
Background air lead concentration
Critical outdoor air lead concentration
Quantity of dirt consumed
Lead concentration in indoor dust
Lead concentration in street dust and soil
Time spent outdoors
Lead intake related to atmospheric lead which
contaminates diet
Lead intake from air
Lead intake related to diet
Lead intake from dirt
Dietary lead intake related to solder and mis-
cellaneous sources (see text)
Ratio of indoor air lead concentration to out-
door air lead concentration
Multiplicative factor for adjusting SOURCEAQ
Outdoor air lead concentration
Air lead concentration related to point sources
Total daily lead uptake
Lead uptake related to diet
Lead uptake from dirt
Lead uptake from lungs
Air lead concentration related to motor vehicles
Volume of air respired
Time-weighted air lead concentration
Time-weighted concentration of lead in dirt
Dimension!ess.
4
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TABLE 2. ESTIMATES FOR SELECTED PARAMETERS OF LEAD UPTAKE MODEL
Ac
e, years
Parameter3
Location
Bound
0-0.99
1-1.99
2-2.99
3-3.99
4-4.99
5-5.99
6-6.99
ABSDIET
NA
Lower
Upper
0.42^
0.53
0.42J;
0.53
0.30
0.40
0.30
0.40
0.30
0.40
0.30
0.40
0.18
0.24
ABSDIRT
NA
b
0.3C
0.3
0.3
0.3
0.3
0.3
0.3
ABSLUNG
General
Lower
Upper
0.15J;
0.30
0.15^
0.30
0.15
0.30
0.15
0.30
0.15
0.30
0.15
0.30
0.15
0.30
PSd
Lower
Upper
0.40
0.70
0.40
0.55
0.35c
0.60
0.30
0.60
0.30
0.55
0.30
0.55
0.30
0.50
DIRTCONS
NA
b
0.1c
0.1
0.1
0.1
0.1
0.1
0.1
HOUT
NA
Lower
Upper
1.0
2.0
1.0
3.0
2.0
4.0
2.0
5.0
2.0
5.0
2.0
5.0
2.0
5.0
IORATIO
General
Lower
Upper
0.3^
0.8
0.3
0.8
0.3
0.8
0.3
0.8
0.3
0.8
0.3
0.8
0.3
0.8
PS
b
0.3C
0.3
0.3
0.3
0.3
0.3
0.3
VRESP
NA
Lower
Upper
2.0
3.0
3.0
5.0
4.0^
5.0
4.0C
5.0C
5.0
7.0
5.0
7.0
6.0
8.0
aDefined in Table 1 and text.
^Best estimate. Lower and upper bounds not specified.
cDerived directly from lead criteria document.3 Other values discussed in
Appendix A.
dPS = near point source.
5
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TABLE 3. YEAR-SPECIFIC ESTIMATES FOR VEMC, INADIET, AKD ItWISC
PARAMETERS OF LEAD UPTAKE MODEL
Year
VEHIC,a
ug/m3
1NAD1ET,3
uq/da.y
INMISC,®
uq/day
1974
1.28
30.9
19.6
1975
1.24
29.8
19.6
1976
1.20
28.9
19.6
1977
LIS
27.8
19.6
1978
L 04
25.1
19.6
1979
0.86
20.8
19.6
1980
0.53
12.9
17.8
1981
0.48
11.5
16.2
1982
0.42
10.3
14.8
1983
0.37
9.0
12.5
1984
0.27
5.5
12.0
1985
0.18
4.5
11.3
1986
0.02
0.55
10.6
1987
0.02
0.36
10.1
1988
0.02
0.36
9.3
1989
0.01
0.36
S.2
1990
0.01
0.36
7.1
1991
0.01
0.19
6.8
1992
0.01
0.19
6.4
1993
0.01
0.19
6.0
1994
0.01
0.19
5.7
1995
0.01
0.19
5.7
1996
0.01
0.19
5.7
1997
0.01
0.19
5.7
aDefined in Table 1 and text.
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TABLE 4. LOWER AND UPPER BOUND ESTIMATES FOR LEAD CONCENTRATION IN STREET
DUST AND SOIL AND IN INDOOR DUST
OUTAQ3
Bound''
Lead concentration, ua/q
Street dust and soil (DIRTST)
Indoor dust (DIRTIN)
General
Near point
source
General
Near point
source
0
L
5
20
5
20
U
30
300
30
100
0.2
L
40
80
70
70
150
550
200
400
0.3
L
60
125
100
250
250
600
250
600
0.4
L
100
200
200
300
350
700
300
650
0.5
L
150
350
250
450
450
800
400
700
0.6
L
200
450
300
550
600
1000
500
750
0.7
L
250
550
350
600
650
1150
600
800
0.8
L
300
650
450
650
950
1300
700
900
1.0
L
500
750
525
800
1150
1450
875
1150
1.25
L
600
850
625
1050
1250
1600
1000
1400
1.5
L
700
1000
750
1200
1400
1750
1150
1700
1.75
L
775
1075
800
1350
U
1450
1950
1200
1900
aOutdoor lead concentration, ug/m^.
^L = lower, U = upper.
7
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average (January through December) air lead concentration values for each
census tract. Section 2.4 describes a computer program developed by PEI that
calculates TDLU values based on an input file consisting of monthly average
air lead values spanning a user-specified 7-year exposure period.
2.1 DAILY LEAD UPTAKE FROM LUNGS
The daily average lead uptake from the lungs, UPLUNG, is estimated by
the formula
UPLUNG = (INAIR)(ABSLUNG) (2)
where INAIR is the average daily intake of air lead by respiration and ABSLUNG
is the fraction of respired air lead which is absorbed into the blood stream.
Table 2 lists lower and upper bound estimates of ABSLUNG recommended for use
with the lead uptake computer program. These estimates appear in the lead
1 4
staff paper and are based on analyses by Chan and Lippman, Davidson and
5 6
Osburn, and Phalen et al. ABSLUNG is assumed to increase near point sources
where large particles are more prevalent. Consequently, the bounds for point
source locations provided in Table 2 are larger than those for general urban
locations. A location is assumed to be near a point source whenever the
value of SOURCEAQ exceeds a specified critical value (CRVAL). SOURCEAQ is
discussed below.
INAIR is estimated by the formula
INAIR = (WAQ)(VRESP) (3)
where WAQ is the time-weighted air lead concentration and VRESP is the air
volume respired per day. Table 2 lists lower and upper bounds for VRESP for
7 8
the seven age groups as determined by Ferdo, ICRP, and the Nutrition Foun-
g
dation.
WAQ is estimated by the formula
WAQ = (1/24)[(HOUT)(OUTAQ) + (24 - HOUT)(I0RATI0)(OUTAQ)] (4)
8
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where OUTAQ is the average ambient (i.e., outdoor) air lead concentration
determined for the census tract for the specified month, and HOUT is the aver-
age number of hours spent outdoors per day. I0RATI0 .is the ratio of indoor
air lead concentration to outdoor air lead concentration. Table 2 lists val-
ues of HOUT by age group as determined by the lead staff * and by Pope.^ The
lower and upper bound values for I0RATI0 are 0.30 and 0.80, respectively, for
general urban/rural locations. These are the bounds suggested for indoor
3
microenvironments by the lead criteria document. For locations near point
sources where large particles are more prevalent and infiltration into homes
is lower, a single "best" estimate of 0.3 is considered appropriate for I0RATI0.
A location is assumed to be near a point source whenever the value of S0URCEAQ
exceeds CRVAL.
OUTAQ is estimated as
OUTAQ = (MULT)(S0URCEAQ) + BKGD. (5)
S0URCEAQ is the point-source-related component of the ambient lead concentra-
tion and is taken from a user-supplied input file specific to the point
source(s) being considered, the control scenario hypothesized, and the year.
Within this file, S0URCEAQ values are indexed by census tract and month.
MULT is a user-specified multiplicative factor by which S0URCEAQ values
can be adjusted to simulate regulatory impacts on point-source emissions.
MULT values are year-specific.
BKGD is estimated by the expression
BKGD = VEHIC + ADD. (6)
VEHIC represents the year-specific contribution of motor vehicles to ambient
lead concentrations. Table 3 lists recommended values for VEHIC. ADD is an
additive factor which can be used to account for background air lead concen-
trations not associated with point sources or motor vehicles. ADD values are
not year-specific.
In initial applications of the lead uptake model, the value of S0URCEAQ
was estimated for the geographic centroid of each census tract by the
Industrial Source Complex (ISC) dispersion model using emissions data for
9
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lead point sources and local meteorological data. Values of SOURCEAQ were
also calculated by the ISC model for receptor points on a radial grid sur-
rounding each point source. Use of these radial grids permitted estimates of
SOURCEAQ to be made at receptor points that were closer to the sources than
any of the census tract centroids.
Values for MULT were determined by dividing the maximum SOURCEAQ value
permitted under a given scenario by the largest "as is" or baseline SOURCEAQ
value determined by the ISC. The latter value was always associated with a
radial grid receptor point rather than with a geographic centroid. If, for
example, the maximum SOURCEAQ value permitted after certain emission controls
3
are implemented is 0.25 ug/m and the largest baseline SOURCEAQ value deter-
mined by ISC is 0.40 ug/m^, then MULT = 0.25/0.40 = 0.625. This MULT value
is then multiplied by the SOURCEAQ value for each census tract centroid as
indicated by Equation 5.
Where appropriate, the impacts on lead exposure of two or more point
sources can be considered simultaneously. In these cases, source-specific
MULT values can be used to adjust the baseline SOURCEAQ values associated
with each source. The resulting source-specific SOURCEAQ values can then be
added together to yield a SOURCEAQ value for each census tract representing
the combined contribution of all point sources.
2.2 DAILY LEAD UPTAKE RELATED TO DIET
The formula used to estimate UPDIET, the average daily lead uptake
related to diet, is
UPDIET = (INDIET)(ABSDIET) (7)
where INDIET is the average daily intake of lead from the diet and ABSDIET
is the fraction of lead consumed which is absorbed through the gut into
the bloodstream. Table 2 lists lower and upper bounds for ABSDIET by age
group as estimated in the staff paper. INDIET is estimated as
INDIET = INADIET + INMISC. (8)
INADIET is the average daily dietary lead intake related to the deposition of
atmospheric lead on food surfaces before and during processing. INMISC is the
10
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average daily dietary lead intake related to solder in canned foods, to water
distribution systems, to soil lead, and to undetermined sources. Table 3
lists year-specific "best estimates" for INADIET and INMISC which reflect the
downward trend expected in lead levels found in food and water (Appendix A).
2.3 DAILY LEAD UPTAKE RELATED TO DIRT
The average daily lead uptake related to dirt is estimated as
UPDIRT = (INDIRT)(ABSDIRT) (9)
where INDIRT is the average daily intake of lead through ingestion of dirt
and ABSDIRT is the fraction of ingested lead which is absorbed through the
gut into the blood stream. The staff paper estimates ABSDIRT to be 0.30.
INDIRT is estimated by the formula
INDIRT = (WDIRT)(DIRTCONS) (10)
where DIRTCONS is the average quantity of dirt consumed during the period each
day when a child is active. This period is assumed to have a duration of 12
hours. WDIRT is the time-weighted lead concentration of the dirt. The staff
paper recommends a value of 0.1 g/day for DIRTCONS.1 WDIRT is estimated by
the formula
WDIRT = (1/12)[(HOUT)(DIRTST) + (12 - HOUT)(DIRTIN)]. (11)
DIRTST is the lead concentration of street dust and soil. DIRTIN is the
lead concentration of indoor dust. DIRTST and DIRTIN vary with the ambient
air lead concentration (OUTAQ) and reflect whether or not the census tract is
considered to be significantly impacted by a point source. Point source impact
is assumed to occur if the value of SOURCEAQ exceeds CRVAL. Table 4 lists
values of DIRTST and DIRTIN for both nonimpacted and impacted census tracts
according to OUTAQ value. These estimates were also obtained from the lead
staff paper. Interpolation is used to determine DIRTST and DIRTIN values for
OUTAQ values not appearing in the table.
11
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2.4 THE MULTIYEAR LEAD UPTAKE PROGRAM
Sections 2.1 through 2.3 discuss how a TDLU valve is estimated for a
single cohort for a given month. The Multiyear Lead Uptake Program calculates
month-by-month TDLU values by cohort from birth through a user-specified last
year of exposure (LYOE). A separate output table presents estimates for each
individual census tract; the individual cohorts within each census tract are
identified according to age at the begining of the LYOE. The number of chil-
dren in each cohort is also indicated. These population data are obtained
from an input data file provided by the user. Section 3 discusses the user
prompting statements and output format of the Multiyear Uptake Program.
A second program, Biokinetics, uses the month-by-month daily lead uptake
estimates from the Multiyear program to calculate end-of-month blood lead
concentrations from birth through the LYOE for each cohort. The program
implements the model described in Section 4. Section 5 discusses the user
prompting statements and output format of the Biokinetics program. Section 6
discusses the results of a sensitivity analysis which evaluated the effects
on program output of varying program input values.
12
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SECTION 3
USER PROMPTING AND OUTPUT FORMAT OF THE
MULTIYEAR LEAD UPTAKE PROGRAM
Appendix B contains a listing of the Multiyear Lead Uptake Program. Fig-
ure 1 lists the series of prompting statements by which the program elicits
instructions, parameter values, and labeling information from the user.
The user first enters the name of the study area or principal point
source as a means of labeling the area to which the lead uptake estimates
apply. Next the user enters the name of the control scenario to which
the estimates apply. Responses to these two prompts are used solely to
label output tables.
The program next requests whether lower or upper bound estimates are to
be determined. The program then asks for information as to which population
subgroups are to be included in the uptake estimates. Note that the user can
include children from any of six demographic subgroups defined according to
presence of lead-based paint in housing (yes or no), housing condition (sound
or unsound), and potential for indirect or secondary occupation lead exposure
(yes or no). The program also asks if the population age groups are to be
further subdivided. If the answer is yes, the user can specify what fraction
of each age group should be included in the lead uptake determination. This
allows the user to focus on the effects of age-related factors (e.g., pica)
on lead uptake.
In response to the next prompting, the user enters the name of a user-cre-
ated file which contains values for all input parameters other than SOURCEAQ
and population. This file is referred to as the "Arrays" file. Section 2
contains recommended values for this file.
The user next enters the name of a user-created file which contains popu-
lation data for each of the six demographic groups by age group and census
tract for the study area under consideration. This file also must list 12 val-
ues (January through December) of SOURCEAQ for each census tract. These
SOURCEAQ values are the monthly average air lead concentration from sources in
13
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COHORT MULTI-YEAR LEAD UPTAKE PROGRAM
Calculates daily uptake by month over lifetime
For selected children aae 0-6 vears
01-06-1986
Strateaies and Air Standards Division
SPECIFICATIONS FOR THIS ANALYSIS:
Enter name o-f study area or principal point source (in CAPS):
Enter name o-f control scenario to be analysed (in CAPS):-
Lower(0) or uooer(1) bound estimate?
P'r=s5 (Shi-f t-F'rtSc) to print these speci -f i cat l ons.
Then press ENTER' to continue:
SPECIFICATIONS CONTINUED:
wnich o-f the -following population aroups should be included in thi =
a-3lvsis? I-f more than one. aroup populations will be added.
1 >Jote: LPH = lead-painted house; SOE = secondary occupational e:.po = ure)
Children in LPH\unsound. with SOE (Y/N)?
Children in LFH\unsound. no SOE (Y/N>?
Children in LPH\sound, with SOE (Y/N)?
Children in LFH'scund. no SOE (Y/N)?
Children in ncn-LF'H. with SOE (Y/N)?
Children in ncn-LF'H, no SOE (Y/N)?
I'.'OLia cm Id arouos be -further subdivided tor thiz anal /si s ¦. v • f;; ?
r 5 = s ¦ 3h i t t-F rtSc to print these specifications.
'•¦2r preii ENTER to conni nut?:
Figure 1. User prompting statements of the Multiyear Lead Uptake Program,
(continued)
14
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SPECIFICATIONS CONTINUED:
Enter name o-f input (Arravs) -file in DOS -format:
Enter name o-f inout (AQ) -file in DOS -format:
Enter name o-f output -file in DOS -format:
Enter last year o-f exposure
This procram uses a set o-f
Do vou want to substitute a
Year 1974 ?
rear 1975 ?
Year 1976 ?
Year 1977 ?
Year 197S ?
Year 1979 ?
Year 1980 ?
Should backaround values be used to
above which point source impact
Enter alternate AO critical value
(4 diaits): 1980
1974-1997 backaround values -for motor
set o-f rural backaround values (Y,'N)
/ehic1e=,
ooin:
source
Year
1974
Year
1975
Year
197 6
/ear
1977
i'ear
1°73
'r ear
1979
T-
Year
1980
indicate critical values
is assumed (Y/'N) ?
(ua/cu.m.) above which
assumed:
::rit =>r additive backaround factor (other than vehicles-1
Int~r multiplicative -factors to adjust AQ by vear:
't ear i
to adjust nU:
I i ! a
1 '7
1 = -=}
'T
mi •
cr:-:-
-:-rt:
:: -:th:
to print the;
:o ccntir.ua:
sj?c1 t 1C at 1Ci~ 3
Figure 1. User prompting statements of the Multiyear Lead Uptake Program.
15
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the study area during the base year. Paul has developed a program, MATCH-AQ,
which creates this file using population data from the Bureau of Census and
dispersion modeling estimates of lead air quality.** The program yields
separate data sets for 1980 and for each of two future years specified by the
user. The user of the lead uptake program specifies which data set to use by
entering the appropriate file name in response to a request for the "input
POPAQ file." The user also specifies the name of an output file which will
serve as input to the Biokinetics program.
The user next enters the last year of the seven-year exposure period for
which the program will calculate lead uptake values. The user is then given
a choice of 1) having BKGD represent urban locations by incorporating the val-
ues of VEHIC listed in Table 3 or 2) specifying an alternative set of BKGD val-
ues which better represent rural locations. If the user chooses the latter
option, the program requests a value for each year of the exposure period. The
program also asks whether the critical value (CRVAL) for each year should equal
the BKGD value specified for that year. If the answer is no, the user is asked
to specify a CRVAL for each year in the exposure period. The remaining prompt-
ings request that the user enter a single value for the additive background
factor (ADD) and seven year-specific values for MULT.
16
-------
SECTION 4
ESTIMATION OF BLOOD LEAD LEVELS
Harley and Kneip have developed an integrated metabolic model which esti-
mates day-by-day blood lead levels based on daily uptake of lead into the
2
bloodstream. The model assumes that most (over 95%) of the lead in the body
is contained in four compartments (bone, liver, kidney, and blood) and that
lead moves among these compartments in a predictable manner. Figure 2 shows
the various lead pathways considered in the Harley-Kneip model. Figure 3
presents the mathematical relationships which the model uses in an iterative
manner to estimate the total lead content in each compartment as the body
receives varying daily lead inputs. Harley and Kneip have incorporated these
relationships into a computer program for estimating blood lead concentrations
12
in children 1 to 6 years of age. PEI has adapted the Harley-Kneip program
to accept daily lead uptake values (i.e., TDLU) as estimated for a cohort by
the Multiyear Lead Uptake Program. The resulting Biokinetics Program tracks
a cohort from birth on January 1 of a user-specified calendar year through
the last day of a user-specified calendar year. A year is assumed to contain
12 months of 30 days. The cohort receives the same daily lead uptake for each
of the 30 days in a month. This value is the TDLU value estimated for that
month by the Multiyear Lead Uptake Model. The Biokinetics Program calculates
the resulting blood lead concentration on a daily basis but prints out only
end-of-the-month values. Thus, 360 sequential blood lead concentrations are
calculated for a given year, but only the 12 end-of-the-month values are
actually printed out.
Table 5 lists the parameter values used by Harley and Kneip in their
model.1 These have been incorporated into the Biokinetics Program. Note
that many of these values change with the age of the child. Section 5 presents
typical output from the Biokinetics Program.
17
-------
61
Trad
Liver
Bone
W ^CKb
Blood
ba
Figure 2. Lead pathways considered in Harley-Kneip
integrated metabolic model.
18
-------
dB/dt
- P -
Cb.
x B -
Ckb
x K
" Cbu
dS/dt
• cbs
x B
" csb
dL/dt
" cbl
x B
" clb
dK/dt
¦ cbk
x B
" ckb
Cbl * B - Cblt * B * Csb x S " clb x L
* B ~ F * Clg x L
x S
x L
x S
Cl% x L
Where P • dally Input to blood In ug/day
Cw. - blood to skeleton ricovtl rata (days~^)
skeleton to blood riaovil rata "
blood to liver raaoval rata "
liver to blood removal rata "
blood to kidney raaoval rata "
C,,k ¦ kidney to blood raaoval rata "
blood to uriaa removal rata "
livar to gastrointestinal tract
removal rata "
F • fractional uptake from gastrointestinal tract to
blood
8,S.L,K • total lead content in blood, skeleton, liver, kidney
( ug)
The organ burdens are calculated in an Iterative aanner using the
expressions
3 i t-l )-B(t) - d 3 / d *
S(fl)-S(t) ~ dS/dt
etc.
Figure 3. Harley-Kneip integrated metabolic model for determining
lead levels in four body compartments.2
19
-------
TABLE 5. PARAMETER VALUES FOR THE BIOKINETICS PROGRAM
Aqe, years
Parameter
Exploration
0-0.99
1-1.99
2-2.99
3-3.99
4-4.99
5-5.99
6-6.99
Cbs
Blood to bone.removal
rate, days"
0.300
0.300
0.134
0.134
0.134
0.134
0.134
Csb
Bone to blood.removal
rate, days"
2.65 * 10"4
2.65 x 10"4
2.65 x 10"4
2.65 x 10"4
2.65 x 10"4
2.65 x 10"4
2.65 x 10"4
Cb1
Blood to liver removal
rate, days"
0.0301
0.0301
0.0301
0.0301
0.0301
0.0301
0.0301
Clb
Liver to blood removal
rate, days"
0.0130
0.0130
0.0130
0.0130
0.0130
0.0130
0.0130
Cbk
Blood to kidney re;.
moval rate, days"
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
Ckb
Kidney to blood re-,
moval rate, days'
0.0301
0.0301
0.0301
0.0301
0.0301
0.0301
0.0301
Cbu
Blood to urine removal
rate, days"
0.0334
0.0334
0.0334
0.0334
0.0334
0.0301
0.0301
C'9
Liver to gastroin-
testinal tract re-
moval rate, days'
3
3
5
5
5
10
10
F
Fractional uptake from
gastrointestlonal
tract to blood
0.4
0.4
0.3
0.3
0.3
0.3
0.3
-------
SECTION 5
USER PROMPTING AND OUTPUT FORMAT
OF THE BIOKINETICS PROGRAM
Appendix C contains a listing of the Biokinetics Program. Figure 4 lists
the series of prompting statements by which the program elicits instructions,
parameter values, and labeling information from the user.
The user first enters the name of the study area or principal point source
as a means of labeling the area to which the program estimates apply. Next
the user enters the name of the control scenario to which the estimates apply.
Responses to the two prompts are used solely to label output tables.
The program next requests the calendar year which will be the last year of
the 7-year exposure period. The user should enter the same year previously
specified for the Multiyear Lead Uptake Program run which created the input
data file for the Biokinetics Program. The user then enters the name of this
file and indicates which estimates (lower or upper bound) the file contains.
The last prompting statement asks if the user wants the geometric mean of the
12 end-of-month blood lead values calculated for each cohort's sixth year of
exposure.
Appendix C contains printouts for "lower bound" and "upper bound" runs
of the program for the study area previously discussed in Section 3. Each
printout consists of a separate table for each census tract in the study area
and four tables which present results averaged across all census tracts.
Values tabulated in the census tract tables are end-of-the-month blood lead
concentrations from birth through the last year of the exposure period. The
format is similar to that of the Multiyear Lead Uptake Program in that esti-
mates are arranged according to the cohort's age in the last year.
The last two pages of each printout contain the four summary tables. These
tables pertain only to those cohorts whose seventh year of life is the last year
the 7-year exposure period. (If the last year of the exposure period year is
1980, for example, these would be those children born at the beginning of
1974.) Summary Table 1 presents month-by-month geometric means of the end-of-
the-month blood lead concentrations of all cohorts born on January 1 of the
21
-------
+¦
BIOKINETICS
Version 2.0
Calculates end-o-f-month blood lead
Concentrations -for chidren aae O-o vears
01-06-1986
Strategies and Air Standards Division
SPECIFICATIONS FOR THIS ANALYSIS:
Eniier name o-f study area or Drincioal point source (in CAPS):
Enter name ot control scenario to be anal yz ed (in CAPS):
Enter last vear or child exposure (4 diaitsi:
PROGRAM ONLY FOR 1900-1997
t'.De or uptake estimates — uooer (1) or lower (0) bounds"'
Lc< -CL'. want the aeometric mean blood concentrat 1 on for eacn census
t.-act durina the ne:;t to last year o-^ e:;oosureY/N) ?
Incuts complete. Press (Shi-f t-PrtSc) to print soeci i l cat l ens.
or ess ENTER' to continue:
"suse to initialize arravs o-f data in croaram. . .
calculations tor each cohort within census tracts:
Figure 4. User-prompting statements of the
Biokinetics Program.
2?.
-------
first year listed in the left-hand column. These values are calculated as
follows. Let be the end-of-the-month blood lead concentration for cohort
i in the year j and month k. Then y^, the blood lead concentration listed in
Summary Table 1 for month k of calendar year j, is calculated by the expression
yjk = exp[z(pi)(ln Xjji^/EPj 3 (12)
where p^ is the number of children in cohort i and the summations include all
cohorts in the study area which meet the stipulation stated above. Note that
yjk is a population-weighted geometric mean.
Summary Table 2 presents population-weighted geometric means of annual
average blood lead levels for the same cohorts considered in Summary Table 1.
The geometric mean for year j, y., is calculated as
J
y. s exp[i(pi)(ln mij)/zpi ] (13)
where m.. is the arithmetic mean of the 12 end-of-the-month blood lead con-
' J
centration values for cohort i in year j, p. is the number of children in
cohort i, and the summations include all cohorts meeting the previously stated
stipulation.
The seven values listed in the right-hand column of Summary Table 3 are
calculated as follows. Let h. . be the highest end-of-the-month blood lead
' w
concentration for cohort i in year j. Then y., the blood lead concentration
J
listed in the right-hand column of Summary Table 3 for calendar year j is
calculated by the expression
y^. = exp[E(pi)(ln hij)/Epi ] (14)
where p^ is the number of children in cohort i and the summations include all
cohorts in the study area which meet the stipulation stated above. Thus y-
v
is a population-weighted geometric mean of the highest end-of-month blood
lead concentration.
In developing Summary Table 4, the program first calculates a., the arith-
metic mean of the x. . values for the first four years of a cohort's life, and
bi, the arithmetic mean of the x^ values for the next three years of a cohort's
23
-------
life. The first value listed in the right-hand column of Summary Table 4 is
calculated as
wa = exp[E(pi)(ln ai)/zpi ] ; (15)
the second is calculated as
wfa = exp[z(pi)(1n b.)/zp.] (16)
The summations include all cohorts in the study area which meet the stated
stipulation. The quantities and are both population-weighted geometric
means.
24
-------
SECTION 6
SENSITIVITY ANALYSES
Multiple runs of the Multiyear Lead Uptake and Biokinetics program were
made to assess the effects on blood lead estimates of varying the values
assigned to selected input parameters. All runs used the same study area, a
set of census tracts surrounding a secondary smelter located in a relatively
densely populated area of a U.S. city. The parameters listed in Table 6 were
selected for the sensitivity analyses because of their apparently large in-
fluence on blood lead estimates relative to that of other parameters. Listed
in Table 6 is the initial value used for each parameter, an alternate value
substituted for the initial value, and the scenario being analyzed.
TABLE 6. INITIAL AND ALTERNATE PARAMETER VALUES USED IN SENSITIVITY ANALYSES
Parameter(s)
Initial
value
Alternate
value
Scenario analyzed
DIRTCONS
0.1 g/day
0.2 g/day
Baseline exposure
Lower and upper bound runs
INMISC
Year-specific
estimates (see
Table 3)
See text
Precontrol exposure and
post-control exposure (1.0
ug/m3 standard)
Lower and upper bound runs
DUSTIN
Lower bound
estimates9
Upper bound
estimates3
Baseline exposure
Lower bound run
DIRTST
Lower bound
estimates3
Upper bound
estimates3
Baseline exposure
Lower bound run
DUSTIN +
DIRTST
Lower bound
estimates3
Upper bound
estimates3
Baseline exposure
Lower bound run
DUSTIN +
DIRTST
Upper bound
estimates3
Lower bound
estimates3
Baseline exposure
Upper bound run
aLower and upper bound estimates used are values presented in Table 4 for
"near point source."
25
-------
The selection of alternative values for the sensitivity analyses was
based on the following considerations:
1. While the estimate of 0.1 g/day for the average daily consumption,
of dirt in young children is generally accepted (lead staff paper
and lead criteria document^), it is based on a limited amount of
data, and most likely is a conservative value. A doubled value of
0.2 g/day of dirt ingestion was arbitrarily chosen to assess how
sensitive the model was to this parameter.
2. INMISC represents the dietary lead intake due to lead from solder
in canned foods and water distribution systems, natural sources of
lead, indirect sources (i.e., historical accumulations of deposited
atmospheric lead), as well as sources of lead that have not yet been
determined according to the criteria document. Estimates of INMISC
are derived in the lead staff paper* from calculations presented in
the criteria document, which in turn are based on the most recent
available data on mean dietary lead intake (1982-1984), and on pro-
jections of future trends in the lead content of canned food and of
drinking water by the criteria document and EPA's Office of Drinking
Water, respectively. Because these projections involve various
assumptions on the economic and technologic feasibility of future
controls on lead exposure, it was of interest to test how sensitive
the model outputs were to these assumptions. Rather than assume
that the use of lead-soldered cans in the canning industry would con-
tinue to decline after 1983 (the most recent data of lead solder can
usage), it was simply assumed that no further controls would be
implemented in the canning industry. As a result, rather than a
steady decline in INMISC from 12.7 in 1983 to 5.7 ug/day in 1997,
there would be a decrease from 12.7 to 12.0 ug/day in 1997 (due solely
to expected improvements in lead drinking water quality).
3. Estimates of the lead concentrations in indoor dust, and in street
dust and soil associated with different,air lead concentrations
were obtained from the lead staff paper and were derived from
various studies which measured air lead levels and dust and/or
surface soil lead concentrations concurrently. Although the
studies sampled a broad spectrum of homes, none of the studies in-
cluded data from homes with reported lead paint hazards. Given
the complex variables involved in the air lead/dust soil lead rela-
tionship (e.g., deposition rates, chemical and physical character-
istics of the lead particles and soils, topographic and meteorologic
conditions, frequency of street washinqs and precipitation, trans-
port of dust and soil into homes, etc.), it is not surprising that
a range of soil and dust lead concentrations are estimated for any
given air lead concentration. To test the impact the ranges have
on the model outputs, three runs were made. The first used the
upper bound value of DUSTIN and lower bound value for DIRTST; the
second used the lower bound value of DUSTIN and the upper bound
value for DIRST; and the third used upper bound values for both
parameters.
26
-------
In general, the air quality (SOURCEAQ) throughout each census tract is
assumed to equal the air quality at the geographic center of the census
tract. In some cases, the geographic center may be a significant distance
from the population center of a census tract. Air quality at the two points
could be significantly different, with the air quality at the population
center being considered the more accurate indicator of exposure for the
children residing in the census tract. To determine the magnitude of the
discrepancy, alternative SOURCEAQ input files were developed using the ISC
dispersion model and two radial grids.
A series of runs were made to assess the effect of receptor point loca-
tion on blood lead estimates. In one run, the SOURCEAQ for each census tract
was determined using the geographic centroid of the census tract as the
receptor point for the ISC model. In another run, geographic centroids were
used for all but the two census tracts closest to the smelter. A radial grid
receptor point 1000 m from the smelter was used for the census tract nearest
the smelter; a receptor point 2000 m from the smelter was used for the
other census tract. These receptor points approximated the locations of the
population centroids of the two census tracts. In a third run, radial grid
receptor points 500 m from the smelter were used for both census tracts.
These locations were assumed to represent residential areas experiencing air
lead levels near the maximum levels expected in the two census tracts.
Results of the different sensitivity analyses are given in Table 7. To
illustrate the effects of the various adjustments, blood lead levels pre-
dicted by the model using parameter values given in Tables 2, 3, and 4 are
also shown for different scenarios. As noted previously, all of the sensi-
tivity analyses used the same U.S. secondary lead smelter. The results pre-
sented in Table 7 for runs without any adjustments apply to the same smelter.
Based on the results of the sensitivity analyses, the following conclu-
sions can be drawn.
1. Doubling the estimate for the average daily dirt ingestion rate
from 0.1 to 0.2 g/day significantly increased the blood lead esti-
mates. The marked sensitivity of the model to this parameter,
which is based on a limited amount of data in relation to the other
parameters, should be highlighted. Furthermore, none of the
analyses completed to date were intended to model children with
pica. Although no precise estimates are available, the amount of
dirt ingested by children with a high degree of pica is significantly
27
-------
TABLE 7. RESULTS OF SENSITIVITY ANALYSES
Blood lead levels3
Air lead scenario
Parameter(s) tested (value)
0-3 years
4-6 years
36th month
Baseline-lower bound
No adjustments
19.4
14.3
19.2
Baseline-upper bound
No adjustments
27.0
21.2
27.1
Baseline-lower bound
DUSTC0NS (0.2 g/day)
31.6
23.6
31.9
Baseline-upper bound
DUSTC0NS (0.2 g/day)
44.4
35.5
45.4
Baseline-lower bound
DUSTIN (upper bound estimates)
23.3
17.4
23.1
Baseline-lower bound
DIRTST (upper bound estimates)
20.4
15.5
20.6
Baseline-lower bound
DUSTIN + DIRTST (upper bounds)
24.3
18.6
24.5
Baseline-upper bound
DUSTIN + DIRTST (lower bounds)
21.4
15.9
21.3
Baseline-lower bound
Radial grid air quality valuesb substituted for
19.3
14.3
19.1
Baseline-upper bound
geographic centrold values at 1000 or 2000
26.9
21.1
27.0
meters only
Baseline-lower bound
Radial grid air quality values'5 substituted for
19.5
14.4
19.2
Baseline-upper bound
qeographic centroid values at 500 meters only
27.1
21.3
27.2
Precontrol-lower bound
No adjustments
5.2
2.4
4.4
Precontrol-upper bound
No adjustments
9.9
5.9
9.7
Precontrol-lower bound
INMISC (canned food lead constant post-1983)
5.3
2.6
4.5
Precontrol-upper bound
INMISC (canned food lead constant post-1983)
10.0
6.3
9.8
Post-control (1.0
ug/m3) - lower bound
No adjustments
1.4
1.1
1.3
Post-control (1.0
pg/m3) - upper bound
No adjustments
3.5
3.4
3.6
Post-control (1.0
wg/m3) - lower bound
INMISC (canned food lead constant post-1983)
2.0
1.6
1
Post-control (1.0
ua/m3) - uDDer bound
INMISC (canned food lead constant Dost-1983)
4.4
4,2
4.6
Blood lead levels presented represent average levels of the 7-year cohorts born to the beginning of the
time period analyzed (1974-1980, 1983-1989, or 1990-1996), at different periods 1n their life. These
levels are used in the risk assessment as Indicators of exposure for estimating the risks associated with
alternative lead NAAQS of various health effects.
^Blood lead results shown are averages across all census tracts surrounding point source. In contrast to
area averages, blood lead levels in individual census tracts that were reanalyzed indicate significant
differences from baseline run (see text).
-------
larger than for children who ingest dirt in the course of normal
hand-to-mouth behavior, which is what the estimate of 0.1 g/day is
intended to represent. It is clear from this analysis that the
exposure and blood lead estimates for children with a high degree
of pica would be significantly greater compared to those of other
children.
2. The use in the model of the upper bounds of the ranges of indoor dust
lead concentrations and outdoor soil/dust lead concentrations rather
than the lower bounds significantly affects the blood lead estimates
of the model. The results further indicate that indoor dust lead
exerts a significantly greater impact on exposure than does outdoor
soil/dust lead. As Equation 11 indicates, the contribution of
DIRTIN to WDIRT is greater than the contribution of DIRTST to WDIRT.
It should be emphasized that none of the runs completed to date were
intended to model children exposed to significant concentrations of
lead in paint. For those children living in homes with lead paint
hazards, it is clear that significantly higher lead exposures and
blood lead levels would be estimated due to the higher levels of
lead in indoor, and possibly, outdoor dust.
3. Using radial grid air quality values for receptors points at 1000
and 2000 meters that approximate the locations of the population
centroids of the two closest census tracts, rather than using geo-
graphic centroid air quality values for those tracts, did not
affect the results significantly. For one of the census tracts
(Census Tract A), the geographic centroid of the census tract was
actually closer to the source than the population centroid. Assign-
ing radial grid air lead concentrations at 500 meters for the two
closest census tracts did not significantly increase the blood lead
estimates when averaged across all census tracts surrounding the
point source (Table 7). The effects of altered air quality on blood
lead estimates for individual census tracts was more evident. For
example, an approximate 35 percent increase in blood lead estimates
for Census Tract A resulted when the radial grid estimates were
used for the upper bound run. For the other census tract, the use
of radial grid air quality values rather than geographic centroid
values did not significantly increase air lead exposure due to the
relatively closer proximity of the geographic centroid to the point
source. The resulting blood lead estimates for this census tract
are not significantly different. It is possible that for other
lead point sources, modeling with radial grid air lead concentrations
that approximate the population centroids, rather than geographic
centroid values, might better represent actual exposures and result
in significant differences in blood lead estimates.
4. The assumption that further reductions in canned food lead levels
will not occur in the future noticeably alters the blood lead esti-
mates only for the post-control 1990-1996 scenario. Estimates for
the precontrol 1983-1989 time period are not significantly affected.
Based on projections in the criteria document, it appears most
likely that further controls by can manufacturers will continue.
29
-------
REFERENCES
1. U.S. Environmental Protection Agency. Review of the National Ambient
Air Quality Standards for Lead: Assessment of Scientific and Technical
Information. Office of Air Quality Planr.ing and Standards, draft staff
paper. April 1985.
2. Harley, N. H., and T. H. Kneip. An Integrated Metabolic Model for Lead
in Humans of All Ages. U.S. Environmental Protection Agency, Contract
No. B44899 with New York University School of Medicine, Department of
Environmental Medicine. January 30, 1985.
3. U.S. Environmental Protection Agency. Air Quality Criteria for Lead.
Research Triangle Park, North Carolina. August 1984.
4. Chan, T. L., and M. Lippman. Experimental Measurements and Empirical
Modeling of the Regional Deposition of Inhaled Particles in Humans.
Am. Ind. Hyg. Assoc. J., 41:399-408, 1980.
5. Davidson, C. I., and J. F. Osborn. The Sizes of Airborne Trace Metal
Containing Particles. In: Toxic Metals in the Air. J. 0. Nriagu and
C. I. Davidson eds. New York, New York, 1984.
6. Phalen, R. F., M. J. Oldham, C. B. Beaucage, and T. T. Crocker. Postnatal
Enlargement of Human Tracheobronchial Airways and Implications for
Particle Deposition. Anatomical Record. Vol. 212, 1985.
7. Ferdo, A. M. Ventilation Rates for Testing Lead NEM. Memorandum from
PEI Associates, Inc., to Mr. Jeff Cohen, U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina. April 1985.
8. International Committee on Radiological Protection (ICRP). Report of
the Task Group on Reference Man: Report No. 23. Pregamon Press, New
York, 1975.
9. Nutrition Foundation, Inc. Assessment of the Safety of Lead and Lead
Salts in Food: A Report of the Nutrition Foundation's Expert Advisory
Committee, Washington, D.C. The Nutrition Center. 1982.
10. Pope, A. A. Development of Activity Patterns for Population Exposure to
Ozone. Memorandum from PEI Associates, Inc., to Mr. Tom McCrudy, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina.
June 1985.
30
-------
11. Paul, R. A. Demographic Data for Lead Exposure Analysis. Report from
PEI Associates, Inc., to Mr. Richard Atherton, U.S. Environmental Pro-
tection Agency, Research Triangle Park, North Carolina. January 1986.
12. Harley, N. H., and T. H. Kneip. A Metabolic Model to Calculate Blood
Lead and Concentrations in Selected Organs by Month for Children Ages 1
to 6. A Report from New York University School of Medicine, Department
of Environmental Medicine to the U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina. August 1985.
31
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APPENDIX A
ESTIMATES FOR SELECTED PARAMETER VALUES
Values for parameters of the lead uptake model given in Tables 2 and 3
of the main text that are not derived directly from the lead staff paper* are
discussed in this appendix.
1. ABSDIET represents the average fraction of ingested dietary lead
that is absorbed through the gastrointestinal tract into the bloodstream.
2 3
Lead balance studies in infants (Alexander and Ziegler ) report GI uptake
factors in the range of 42 to 53 percent based on measurements of lead in the
4-6
diet and excreta. Several studies have found that adults absorb a much
smaller fraction of ingested dietary lead with measurements ranging between
7 to 20 percent. For the present model, a range of 42 to 53 percent is used
for infants up to their third year of life, 18 to 24 percent for children
upon reaching their 7th year of life, and proportional, incremental values
in intermediate ages.
2. Table 3 describes past and future trends in average daily dietary
lead intake (INDIET) for 1974-1997. Year-specific estimates by Battye7 of the
mobile source contribution to ambient lead concentration in urban areas,
3
VEHIC pg/m , are used to estimate INADIET, the average daily lead intake
related to atmospheric lead deposition on food surfaces before and during
processing. Past trends in lead solder usage in canned foods,1 anticipated
future reductions in lead solder usage, and the anticipated impact of the
Q
expected revision of the lead drinking water standard were used to make year-
specific estimates of the contribution of these sources to average daily
dietary lead intake. The contributions of soil lead and undetermined sources
of lead remain constant in estimating average daily dietary lead intake be-
tween 1974-1997. The contribution of components of dietary lead intake, with
the exception of the INADIET component, are combined to yield year-specific
estimates of INMISC.
32
-------
3. ABSLUNG represents the fraction of inhaled lead that is deposited
into and subsequently absorbed through the lungs into the bloodstream. In
the staff paper, data on particle size distributions of airborne lead mass,
collected from various urban, rural, and industrial areas, are combined with
particle respiratory deposition and absorption data to calculate the absorp-
tion rate of inhaled lead particles for a 2-year old child living in generalized
urban/rural areas (15 to 30%) as well as near stationary lead sources (35 to
Q in
60%). Data were obtained from Landrigan et al., Dorn et al., Chan and
Lippmann,^ Davidson and Osborn,^ and Phalen et al.^
Age-related differences in deposition efficiencies estimated by Phalen
et al. are not large for the relatively small particle diameters that pre-
dominate in generalized urban/rural areas. Therefore, the range estimated
for a 2-year old is applied to all ages of young children (0 to 7 years)
living in those areas. Near point-sources, there is generally a greater
fraction of coarse-mode particles (>2.5 um) in the ambient air. Consequently,
the fraction of particle mass that deposit in the lungs of young children and
are absorbed is estimated to be larger than that of adults. Particle deposi-
tion efficiencies for 5 um particles were derived from Phalen et al. as a
function of age and ventilatory state (e.g., low activity, light exertion) to
calculate average daily deposition rates by age:
% deposition % deposition Average daily
Age at low activity at light exertion deposition rate
0
80
65
75
1
75
60
70
2
70
55
65
3
65
50
60
4
60
45
55
5
60
45
55
6
55
40
50
18
35
35
35
Average respiratory deposition/absorption rates for different ages living
near lead point sources were calculated using the equation
[(CRD5 - ARD5) x PbPSj Q] + ARDPS
33
-------
where CRDr is the average daily deposition rate of 5 gm particles for a child
13
between 0 and 6 years (50 to 75£, from Phalen et al. ); ARD^ is the average
daily deposition rate of 5 um particles for an 18-year old (35% from Phalen
et al.); PbPSj q is the average percentage of lead particle mass collected
near point sources that is comprised of particles that are larger than 1.0
9 ID
pm in diameter (50 to 70%, from Landrigan et al. and Dorn et al. ); and
ARDPS is the estimated respiratory deposition rate for adults living near lead
point sources (20 to 40%, estimated in the lead staff paper1).
The calculated ranges were rounded off to yield the rates listed in
Table 2. It should be noted that deposition efficiencies for 5 um particles
were combined with data on the percentage of lead particles larger than 1 ym
around point sources to calculate point source area respiratory deposition
rates. The available data related to particle size in the published literature
do not permit a more direct comparison and calculation.
4. H0UT represents the amount of time spent outdoors. Among young
children, this value varies depending on their stage of development (i.e.,
infant, tDddler, preschool), season, geographical location, and family
behavior. The values for a 2-year old child in Table 2 were obtained from the
1 14
lead staff paper. Estimates for other ages were developed by Pope, who
analyzed the time spent by children indoors, outdoors, and in motor vehicles,
with respect to season and day of week.
5. VRESP, the volume of air respired each day, is dependent on age, body
size, lung capacity, altitude, and activity of the child. The lead staff
paper1 estimates a range of 4 to 5 m^ day for 2- and 3-year old children
based on various sources (ICRP,^ Nutrition Foundation,*^ Phalen et al.^).
Phalen et al. determined average ventilation rates for males and females, at
different activity levels, from birth through age 18 from graphical fits of
17 lfl
published tabulated data (Altman and Ditmer ' ). The calculations for low
activity levels were used to construct the ranges of daily ventilation rates
in Table 2 for children 0 to 6 years.
34
-------
REFERENCES
1. U.S. Environmental Protection Agency. Review of the National Ambient
Air Quality Standards for Lead: Assessment of Scientific and Technical
Information. Office of Air Quality Planning and Standards, draft staff
paper. April 1985.
2. Alexander, F. W., H. T. Delves, and B. E. Clayton. The Uptake and
Excretion by Children of Lead and Other Contaminants. In: Environmental
Health Aspects of Lead Proceedings, International Symposium. D. Barth,
A. Berlin, R. Engel, P. Recht, and J. Smeets, eds. Amsterdam, The
Netherlands. Commission of the European Communities Center for Informa-
tion and Documentation. Luxemborg. October 1972.
3. Ziegler, E. E., B. B. Edwards, R. L. Jensen, R. R. Mahaffey, and S. J.
Fomon. Absorption and Retention of Lead by Infants. Pediatric Research,
12:29-34, 1978.
4. Kehoe, R. A. The Metabolism of Lead in Man in Health and Disease: The
Normal Metabolism of Lead. J. R. Inst. Public Health Hyg., 24:81-97,
1961.
5. Rabinowitz, M., G. W. Wetherill, and J. D. Kopple. Lead Metabolism in
the Normal Human: Stable Isotope Studies. Science, 1982:725-727, 1973.
6. Rabinowitz, M. B., J. D. Kopple, and G. W. Wetherill. Effect of Food
Intake and Fasting on Gastrointestinal Lead Absorption in Humans. Am.
J. Clin. Nutr., 33:1784-1788, 1980.
7. Battye, W. Predicted Mobile Source Lead Impact for 1990 and 1995.
Technical Memorandum from GCA Corporation, Technical Division to Mr. John
Haines and Mr. Jeff Cohen, U.S. Environmental Protection Agency, Research
Triangle Park, North Carolina. April 1985.
8. Personal communication between Mr. Jeff Cohen, U.S. Environmental Pro-
tection Agency, Research Triangle Park, North Carolina, and Mr. W.
Coniglio, U.S. Environmental Protection Agency, Office of Drinking
Water. Washington, D.C. November 14, 1985.
9. Landrigan, P. J., S. H. Geklbach, B. F. Rosenblum, J. M. Shoults, R. M.
Candelaria, W. F. Barthel, J. A. Liddle, A. L. Smrek, N. W. Staelhing, and
J. F. Sanders. Epidemic Lead Absorption Near and Ore Smelter: The Role
of Particulate Lead. N. Engl. J. Med., 292:123-129, 1975.
35
-------
10. Dorn, C. R., J. 0. Pierce, P. E. Phillips, and G. R. Chase. Airborne
Pb, Cd, Cu Concentration by Particle Size Near a Pb Smelter. Atmos.
Environ., 10:443-446, 1976.
11. Chan, T. L., and M. Lippman. Experimental Measurements and Empirical
Modeling of the Regional Deposition of Inhaled Particles in Humans.
Am. Ind. Hyg. Assoc. J., 41:399-408, 1980.
12. Davidson, C. I., and J. F. Osborn. The Sizes of Airborne Trace Metal
Containing Particles. In: Toxic Metals in the Air. J. 0. Nriagu and
C. I. Davidson eds. New York, New York, 1984.
13. Phalen, R. F., M. J. Oldham, C. B. Beaucage, and T. T. Crocker. Postnatal
Enlargement of Human Tracheobronchial Airways and Implications for
Particle Deposition. Anatomical Record. Vol. 212, 1985.
14. Pope, A. A. Development of Activity Patterns for Population Exposure to
Ozone. Memorandum from PEI Associates, Inc., to Mr. Tom McCurdy, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina.
June 1985.
15. International Committee on Radiological Protection (ICRP). Report of
the Task Group on Reference Man: Report No. 23. Pregamon Press, New
York, 1975.
16. Nutrition Foundation, Inc. Assessment of the Safety of Lead and Lead
Salts in Food: A Report of the Nutrition Foundation's Expert Advisory
Committee, Washington, D.C. The Nutrition Center. 1982.
17. Altman, P. L., and D. S. Dittmer, eds. Respiration and Circulation.
Federation of American Societies for Experimental Biology. Bethesda,
Maryland. 1971.
18. Altman, P. L., and D. S. Dittmer, Eds. Biology Data Book, 2nd Edition,
Volume 1. Federation of American Societies for Experimental Biology.
Bethesda, Maryland. 1972.
36
-------
APPENDIX B
MULTIYEAR LEAD UPTAKE PROGRAM
AND SAMPLE OUTPUTS
37
-------
REM ¦*•#**•*•¦**¦~***¦****** COHORT LEAD UF'TAKE PROGRAM
:EM
nEM Arrays accomodate aae arouDS 0-6, years o-f aae 0-6, subaroups 1-6,
REM calendar years 1974-97(0-23), upper & lower bounds(O-l), and
:EM una-f-fected or a-f-fected (0-1) by point source o-f lead.
_>IM PFRACT (6) , 10RAT10 (6,1,1) , H0UT(6,1)
DIM VRESP(6,1), ABSLUNG(6,1,1)
TIM ABSDIET(o,1), INDIET(6), INMISC(23)
)IM DUST 1(11,1,1), DUST2(11,1,1), INADIET(23)
DIM AIR(11), OUTAO(6,12), INAIR(6), BKGD(23), CRALT(6)
DIM DIRTCONS(6,1), ABSDIRT(6,1), INDIRT(6)
DIM GRP*(6), PREG(6), POP(6), MONTHS(12), MULT(6)
TODAY# = DATES: LF* = CHRSilO): CLS: LPRINT CHR*(12)
PRINT TAB(12) "+
PRINT TAB(12) "!
PRINT TAB(12) "!
PRINT TAB(12) "
PRINT TAB(12) "
PRINT TAB(12) "
PRINT TAB(12) "
PRINT TAB(12) "
PRINT TAB(12) "
COHORT MULT I-YEAR LEAD UPTAKE PROGRAM
Calculates daily uptake by month oyer lifetime
For selected children
aae 0-6 years
TAB(34)
PRINT TAB(12)
PRINT TAB(12)
TODAY* TAB(70)
Strategies and Air Standards Divisi.on
PRINT TAB(12) "1
NT TAB J 12) "+
FPIN7 LF-f: LF £; "SPECIFICATIONS FOR THIS ANALYSIS: 1
PRINT "Enter name of study area or principal point
INPUT SRC-f
source '.in CAP'S)
FF INT
INPUT
INPUT
rz r:- r \it
o+ control scenario to be analyzed (in CAPS):
"Enter name
CTRL-f
''Loner 0) or upper >, 1) bound estimate? BND
"Press '.2hi rt-Prt=c) to print these specifications."
IiiP'jT ''Then press 'ENTER' to continue: C-T
:L5: FRI.'IT LFS: "SPECIFICATIONS CONTINUED: "
F F IMT: PFINT "UJhich of the followina population arouos should b-i
lncIuded
_• _ i1
il /31 ='
If more than one. arouo populations will be added.
f * !7
i_PH = leid-painted house:
SOE = second.
occup-zz i on jl
•z :o-~
' .J I
* J "J"
' ¦_ T
•
' !JT
C!i l 1 u.-=n in LPH\unsound. with SuC >'(' Ni
Children in LFH'.uniounG. no SCE /N)^
Children in LF H\ sound . with 50E ' > / N > ?
Children in lFH'. scund . ~o 3C'E ¦ V. I'D ~
Cruldren • n non-LF'H. wi ^.h SOE '. ^ N_
" . bRr'.r v 1 i
' „ GRF' £ (2.'
' „ i^F'PI '. 3 .'
GPP-f • ->¦ ¦
GPFf'5•
CiMldrsn in non-LFH. no SOE •. 7-N' ? "jFF't .3.
'2. iou 1 -J child a .--.lids be t jr i'.r.cr suLidi i ded -or th l ;
, i -
: 11
-------
5S'"' PRINT LF-f: LF-P: : INFUT "Enter last year of exposure (4 diaits): YEAR
2: IF YEAR; 1980 OR YEAR>1997 THEN PRINT
PROGRAM ONLY FOR YEARS OF EXPOSURE ENDING IN 1930-1997": GOTO 530
bOO 3VP = 0 : IF YEAR :•= 1990 THEN BYR = 1
t PRINT "This Droaram uses a set o-f 1974-1997 backcround values -for motor
1 r as . "
z2''j INPUT "Do vou want to substitute a set o-f rural backaround values t'y'/N)
RURAL$
,5: IF RURAL-!1 = "N" OR RURAL#= "n" THEN GOTO 630
6-10 FOR V = 0 TO 6
0p- vv = YEAR - 6 + Y: Y2 = YY - 1974
a. PRINT " Year YY;: INPUT RURALB: BKGD(Y2) = RURALB
=;¦,) NEXT Y
iBfi PRINT "Should backaround values be used to indicate critical values"
INPUT " above which point source impact is assumed (Y/N) CV-f
~ . IF CVS = "v" OR CV* = "Y" THEN GOTO 720
~iC F!~. INT "Enter alternate AQ critical value (uq/cu.m.) above which
PRINT " point source impact should be assumed: "
FOF Y = 0 TO
714 YY = YEAR - 6 + Y
PRINT " Year "; YY:: INPUT CRALT(Y)
NEXT Y
"20 INPUT "Enter additive backaround -factor (other than vehicles.1 to adjust AG
' ,*• p, r*
HLu
PRINT "Enter multiplicative -factors to adjust AQ bv year: "
F'jR 1 = O TO 6
"50 YY = YEAR - o ¦+ Y
PRINT " Year YY;: INPUT MULT(Y)
. NEXT /
"20 PRINT "Press (.Shi -f t-PrtSc ) to print these spec i -f 1 cat i ons. "
~ INPUT "Then press 'ENTER'to continue: L-P
¦2' OPEN FILE3* FOR INPUT AS #3
2.0 RE: I - + + Names o-f inontns:
3" ' FOR MTH = 1 TO 12
_ Kci:-iD MGNTH-1" '.Ml H,1
2 ¦ y-I, T "1TH
. 7 7-'.TA " JANUAP. " , " FEBPUAR'i " . "MARCH" . "APRIL" . "MAY" . "JUNE" , "J'JlN " . ' AuSU'Z T" . " z EPT
I 2r ,"32 TIBER"-"NOVEMBER". 'DECEMBER"
I.. ~ZM Hours-diiv =usnt outdoors *-¦>-*¦
. irii'i.T #3- AFRAt'-P: PRINT LF* . LF-T . AF'F AV'X , LF-P
,T2"~ EE -- ¦.) TO i; I MRU" #3. --I0UT ;'Y. BO; : PFINT H2'JT ;• J2. t j
t 2
1 t OS corr'-sri ~o indoor r'-;; — -
- I-rLT L^3 . ^rPn-rJT; PRi;.T LF-T . LF-f . AF,RA'< -P . LF-P
. - i 1
1 . i f' • J T t: „ • L Crlri 1 I —J . . I" J - L'i.1 ; ! p - 1 i ; T J
: xe, t s :•
NE/T PS
ii:: ' ! ''
, . — ^-""i j e- Ti-.j.r, motor --ehic]e= r.dooJ tc
U"r !+3. A; -V : FF:InT LF-P . LF1". AF PA -P . LF-I
¦ F :!'.•= i - ~ i 1 1 t'-7
1, •.'2.11 - : Y2 = C. • 1 ¦" I
1 ",r .-".ur:. ,^.r= t he:: i 2i'2E ^'2>
: i~ .=¦ i- -=¦' . " 2." rL-r.'-iL./^" . ' \ 2
t?;! "jrcur.j
- i_r
-------
p.c.i i -t i-iu a<—•» u u x u-. i - i < N ' '
INPUT #3. ARRAY'S: PRINT LFS.LFS.ARRAYS.LFS
FOR Y = 0 TO 6
FOR PS = 0 TO 1
FOR BD = 0 TO 1
INPUT #3, ABSLUNG(Y,PS,ED) : PRINT ABSLUNG ( Y,FS,BD >
NEXT BD
.au NEXT FS
NEXT y
REM *** Pb intake -from undetermined sources **¦*
310 INPUT #3. ARRAYS: PRINT LFS . LFS , ARRAY* . LFS
FOR CY = 0 TO 23
INPUT #3, INMISC(CY): PRINT INMISC(CY):
NEXT CY
FEM **¦*¦ Pb dietarv intake related to air *•*•*
INPUT #3. ARRAYS: PRINT LFS,LFS,ARRAYS.LFS
FOR CY = 0 TO 23
400 INPUT #3, INADIET(CY): PRINT INADIET(CY):
NEXT CY
PEM **-* Absorption in aut o-f lead -from diet ***-
•150 INPUT #3. ARRAYS: PRINT LFS , LFS , ARRAYS, LFS
FOR Y = 0 TO o
FOR BD = 0 TO 1
INPUT #3, ABSDIET ( V , BD) : PRINT ABSDIET (Y , BD ;
J-O NEXT BD
NEXT Y
_..0 REM Ouantitv o-f dirt consumed **¦*¦
540 INPUT #3, ARRAYS: PRINT LFS.LFS,ARRAYS.LFS
0 FDR Y = 0 TO 6
.0 FOP BD = 0 TO 1
570 INPUT #3, DIRTCONS(Y,BD): PRINT DIPTCONS(Y,EL):
NEXT BD
¦I NEXT t
=' REil *¦*•->- Absorption in aut o-f Pb troin dirt *-*¦-
"I- iNrLT 1+3. ARRAY'S : FRINT LFS . LFS . AF:F:A r'S . LFS
FOR t = TG o
FGP BD = 0 TO i
INFUT #3. ABSDIRT (V . BD) : PR. NT AB"D I FT i '¦ , Lij;
:¦ ::E'.t e-d
. FZ/I —r-< Twei ,s discrete air Pb levels tcr mterool jticr.E
:i-..:,LT S3. AF'RA i S : PRINT LF £ , i_FS , AF RAY i". LF t
:E: = TC 11
it:. i-,rP'.P5;: "PINT AIk.PE)-
jncu'ni-.ratioR ct Fb in st.-eet dust
r-r - V.'S ; F R 11 -T lF$. i_F.r „ AF PA S . L.FS
: re i i
; = 0 TG L
DLSTl '.~B ,F3.Z:D' : FRfriT L'LM-Tl
-------
FOR CTRACT = 1 TO 9999
IF EOF(1) THEN GOTO 2510 ELSE GOSUB 2810: REM To aet tract data
IF BND = 0 THEN BD$ = "LOWER"
IF BND = 1 THEN BD* = "UPPER"
TI TLEf = SFC-f + " - " + CTRL-5
TL */. = 35 - LEN (TITLE-f) / 2
FOR BY. = 1 TO TL7.: TITLED = " " + TITLED: NEXT BY.
LPRINT CHR*(12): LPRINT" LPRINT" LPRINT TITLED
LPRINT TAB <11) BD$ " BOUND ESTIMATES OF DAILY LEAD UPTAKE BY MONTH"
LPRINT TAB(20) "FOR COHORTS IN CENSUS TRACT "; TRACT*
LPRINT " LPRINT" ": |_PRINT"=========================================
0 LPFINT " Aae Daily Lead Uptake iua/dav) bv Month
0 LPRINT YEAR " Pod rear 1 2 3 4 5 o 7 3 9 10 11
LPRINT"
•j
0
0
0
0
o
r)
rr
0
TO 0 STEP -1
: LPRINT" ":
FOR AG ~ 6>
LPRINT"
POP
\"; TRACT t;
AG;
POP(AG):
'; CY;
US ING"\
USING"###'
USING"#####":
USING"#####
1 TO 12
IF(OUTAO(Y,MO) ' CRVAL) THEN PS = 1 ELSE PS =
30SUE- 25o0: REM Dust Interpolations +
GGSUB 267' >: PEM Uptsl-e Calculations
:_FRINT US I NG "#£##": TDLU:
PPINT#2. USING "###&": TDLU;
-------
'0 IF i AC! .;¦= AIR(CHK)) AND (AG < AIR(CHK+1)) THEN 2640
ELSE NEXT CHK
2 . !> DUSTST = DUST 1 (CHK . F'S , BND) + (DUST 1 - DUST 1(CHK,PS,BND) )
* (AQ-AIP(CHK)) / (AIR(CHK+1)-AIR(CHK)>
I :> IUSTIN = DUST2 (CHK , PS . BND) + (DUST2(CHK+1.PS,BND> - DUET2(CHK,PS,BND))
* (AQ-AIR(CHK)) / (AIR(CHK+1)-AIR(CHK))
2660 F:ETUF:N
I -o REM
1 REM **-* Uptake Calc. -far Calendar Year(CY), Year a-f Aqe(AG), & Month (MO) **
2j-?0 REM
IY = CY - 1974: REM Convert cal . year to inde:; year
2 AQ = OUT AQ (Y , MO)
2._0 H = HOUT(Y.BND): 10 = IORATI0(Y,PS,BND)
2730 WAG = (H * AQ + (24—H) * 10 + AG) / 24
I UPLUNG = VRESP(Y.BND) * WAG * ABSLUNG (Y . PS , BND)
: :> UPDIET = (INMISC(IY) + INADIET ( IY) ) * ABSD IET (Y , BND >
27.a J WDIRT = (H * DUSTST + (12 - H) * DUSTIN) / 12
I ~j UPDIRT = DIRTCONS'.Y.BND) * WDIRT * ABSD IRT (Y . BND )
:: j TDLU = UPLUNG + UPDIET + UPDIRT
27 t'O RETURN
'»:¦ REM
;• REM -C++-***:****-***-***-* Census Tract Data Subroutine
• 0 REM
ICV, INPUT #1, TRACTf
I- REM Incut population data *-«--*
_ FOP GF' = 1 TO 6: INF'UT #1. F,F:EG(GF'): NEXT GF': REM ** Data not usea
PRINT LFX; "Census tract CTRACT " = TRACTS; " Child pops:";
r OR AO = U TO 6
POP (Ab) = 'J
INFUT #1, SAME*
- IF S AME-T/ TRACT $ THEN PRINT LF-T: "ERROR IN INPUT FILE. STOP PROGRAM":
GOTO 2520
_ :0 FOF GF' = 1 TO 6
Ii'lF'UT #1. GRF'POP
"i IF GPPi-'.GP) = "Y" OR GRPX(GP) = "V THEN FOP. AG) = FuP 1 AG .• + GrPc,QP
ne:."~ gp
- v i' i" 1 I— '-T = " y" lR PuF'-T — i i HEN FOF'*.AG^ = F'bP 1 m£ / rFF;.~iL7 'i-iG.'
:¦ print usImG pgp(ag/:
t ' j
"EM InoM.t t-uClu jl i tv uata *¦*<
r- »- — t T —. j —.
I * L i- l . \J — x I x
I . I " ¦ J I if L 1 riL! I r.f • riw! I N = flO I P-i / 1
i— i • '—'.j! i • " n^nocr arcs, cli«iTi« uo »tii cocjf~ rOTi3 cLi ¦ .11 • on- 1 nol-x.
rcw . 2 = o to o step - L
j 1 — < E.-tP — 1,'4) —+ V 2 j FEM t'-i loD • 1 !¦ or l'-,74-l -
OU"-, j ¦ ; 2. MO) - :iULT'f'2) * HCI!) Z-'M.-Z ¦ t ¦
";E - 7 ; 2
i..'£:«T r-ic
-------
juLFZ C-/L
DUST 1 ,2/U
lcu = r 1•. :
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cc
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t j _¦ V.1 - ¦ 1 7 i ) i : 2'v "r 3 . r*—rv 1 *r 2 £ ? >
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f- c; '97 7 It It 5c 5 c 5 6 5= 5 6 5= 56 55 55 5 6
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-------
APPENDIX C
BIOKINETICS PROGRAM
AND SAMPLE OUTPUTS
54
-------
BIOKINETICS
Version 2.0
Calculates end-o-f-month blood lead
Concentrations -for chidren aae O-o vears
" TAB(33) TODAY$ TAB(70) "I"
Strategies and Air Standards Division
0 KEivl ***¦»¦*-*¦****¦*•<¦***** BIOKINETICS Version 2 **¦****•#******¦*****¦#¦*¦*¦#•*¦*¦**
1 EM Calculate lead oraan burdens tor continuous exposure ot cohorts,
i r\EM F'roqram adapted -from Dr. N. Harley. NYU School o-f Medicine. 12/85.
0 DIM CBLBO(34).CBOBL(84).SCALE(34).FACTOR(34)
ii~ IM GU(6) . CLIGUT (6)
,< _ IM TB <6,84) , TC (84) , TBO (34) , TL (84) , TK (84) , WT (84)
0 DIM CBLUR(84),WTB(84),WTBO(34),GI(84).CLIGU(84),WTFAC(84)
iO IM UPTAKE(6,12), HIGH6(260,6), SUM12M(6). SUMYR(6), SUMM0(6,12)
'IM CGROUF' (6) , CPOF' (6) . SUMHI (6) . HIGHF'B (260 .6) , GE0M(6)
.<..0 DIM TRAVGQ (6) . TRAVG6(6). TRLVL3o(6)
.1C TODAYS = DATE-f: LF* = CHR$(10>: LF'RINT CHF:*(12): CLS
PRINT TAB (12) "+ :
. PRINT TAB (12)
140 PRINT TAB(12)
i: PRINT TAB (12)
L PRINT TAB (12)
170 PRINT TAB(12)
i." PRINT TAB (12)
L- PRINT TAB (12)
200 PRINT TAB(12)
Z"" PRINT TAB (12)
2 PRINT TAB(12)
PRINT TAB (12)
24.-1 PRINT LF-t:LF*: "SPECIFICATIONS FOR THIS ANALYSIS: "
2! FRINT "Enter name ot study area or principal point source (in CAFS):
INPUT SRC*
2=0 PRINT "Enter name ot control scenario to be analyzed (in CAFS): ":
INPUT CTRL*
I INPUT "Enter last year ot child exposure (4 diaits): YEAR
!¦=¦:¦ IF 7EAR-. 1980 GF: YEAR>1997 THEN PRINT "PROGRAM ONLY FOR 1930-1997": GOTO 3i.»
2" INPUT "Enter name ot mout tile in DOS -format: FILE*
7 INPUT "What type ot uptake estimates — uDoer(l) or lower iO! bounds": BUD
7-10 F'RINT "Do vou want tne aeometric mean blood concentration tor each census
7 " 2NFU7 "tr set durina the next to last vear o-f e :posure ( r .-N) "; Gfll"1-?
¦ ,-FINT LF-1": "Inputs comclste. Press •> Sh i -f t-PrtSc to print spec l l c at i on s. "
INP'JT "Thsn press ENTER' to continue: C-F
7~"' Fr-I.JT LFJ;LF.£; "F'ause to initialize arravs ot data in program..."; LF£
7 "EM *-* urinary excretion halt-times
G i-'i ! pi 9 . , v , v . v . 1 o , 1
770 FOF: I\ = 0 Tu o: READ SCALE NEXT I','.
7 FCR I";= 1 TO 84
- \ m.= T/.-l)\12
-.0 CBL'JR- i I'/.j = L0G'2K' SCALE (f'/i
- ~ i'IE *¦' ~ I
1 "£!•! -<•-** bone turnover scale
ui—:-i.''i2
CH'LBoi;• - . 3-factur •. j > /ss
) ¦¦ iE.^T I
15 .• -"'Eil boric removal hal-r-times
-f 1 ¦ D.-'- V-i 1 i 73 , 1 1 75 . 1 1 75 , 1 1 75 . i 1 35 , 1 1 35 , W 75
i; ¦ i- I".= •.! I l' o: IxmJj I-,-iL/-1. ! Jr'1 I: NE •'T I,.
~ ~ 1 r I\= 1 Tu S4
7s-"'. :¦ » i I \- i ¦ ¦ l 2
5~ " ["¦. ¦ - L0 7 7 ¦ - FmCT0': ¦ ! '• '
t. 1" • :!' >7 l
• i-i I Lot "\ct~"j
-------
a 10 FuR 17. = 0 TO o: READ LLibU i \¦ i hl.-. i j. ..
c FOR 17.= 1 TO S4
C \ \12
is-rO CLIGU(I7.) = CLIGUT NEXT I*.
REM *¦** Use mitchell Ca data and divide bv .37 tor ash weiaht
L v DATA 30.40,45.50.55.60.65.75.80.85.92.100
210 DATA 105,105,110.115.120.122,125,130.135,137,140,145
DATA 150.151,155.157.160.162.165,167.170,173.175,130
. DATA ISO.182,185,185,188,190,190,192,195,196,198.200'
340 DATA 200,203.205.206.20".210.210.213.214.215.217.220
DATA 220.221.223,225.226,230,230,231,232,235,236,240
DATA 241,243.245.247,250,251.254.255.257.260.262.265: REM Added line
o.O FOR IV.- 1 TO 84
READ UJTBO (I7.)
WTBO (IV.) = WTBO (17.)/. 37
NE>T IV.
~ 10 REM *•+*¦«¦ **•¦*¦**» ¦**¦)»¦¦*¦»¦**¦*¦-**~¦********************************** *******
• PRINT LFJ"; "Beqin calculations -for each cohort within census tracts:"
j OF EN FILE* FOR INPUT AS #1
FOP CTRACT = 1 TO 9999
CT = CTRmCT
IF EOF(1> THEN GOTO 1140
"v FOR AG = o TO 0 STEP -1
INPUT #1. BLANt:-^: REM Blank line precedes aae arouo data.
FOR f = AG TO 0 STEP —1
INPUT #1. TF ACT, CGROUP(AG). CROP (AG), CYEAR
TRACTS = STR*(TRACT): PRINT LFf; LFS
:: FOR L= 1 TO 5: IF LEN (TRACT J) -.7 THEN TRACT $ = TRACT a +" " : NE/.T L
PRINT LFf: TRACT X: CGFOUP(rtG): CROP'AG): C'i EAR :
. . t-0 "OF: PIG = I TD 12
IiiFUT ttl. UPTAKE . V . MC' >
FRINT UPTAKE'.Y, MO) ;
. ." : me\t
: r.i£..'T
¦ FIN' LFi": i.Ff: : bU'SUB ll'-'1.1: F'EM Ccr.ort ciilc. i or ioe oroue .-i'j
.. :ie-: ag
l ' FRINT LFi : LF-T
I1. Gu5US 1-00: FErl - ** Outout Tabli -for 1 can sue: tract
- .. J lie..-, ; CTRACT
I 1-i-''- CCSUB 2590: REM r + -r Outout tables reauir^d i0/li/£5. ---n
50 I.CUi" ¦= TI '.-IE-- j LPRINT CHRa'dl); LF-T; uFi-. TOD.->.i: '' ' : I'XuU
i J END
~0 PEh .......«- »•->••.-.• ¦» *-;•-.»»-* .
F"1
1 I REM t v 1 -iit: 5] values tor esch cohcri;:
''"hl - 2-. 0: D.-1-OiJE = .
- 7'. 71. I'.T.F- =
-------
12P0 CBLKI = LOG<2)/(30*T): CKIBL = LOG(2)/(10*T>
i: j WBL = 5200: WBO = 5000: WLI = 1700: WK'I = 300
1 rem
1310 REM *** Calculations -for each month o-f li-fe ***
r :• AG'/. = AG
i: . D ENDMO = YR'/. = < I7.-1 ) \12: MO*/. = 17. - YR7.*12
i: It PRINT "TRACT="; TRACTS; " AGE GRF-";AG; " VR=";YR7.; " M0=";M07.;
1370 INJECT = UPTAKE (YRJi,MO'/.)
1~~0 PRINT " INJECT="; INJECT: " BLOOD=";
i: :i FOR J7.= 1 TO 30
I4v0 REM *** blood **•*
1410 DBLOOD = INJECT + (LOG (2) /CLIGU (17.) ) *TLIVER*GI (IV.)
1- D DBLOOD = DBLOOD - CBLBO ( 17.) *TBLOOD - CBLLI*TBLOOD - CBLKI*TBLOOD
1 . .D DBLOOD = DBLOOD + CBOBL (17.) *TBONE + CLIBL+TLIVER + CKIBL+TKIDNEY
1440 DBLOOD = DBLOOD - CBLUR (17.) *TBLOOD
1 :» TBLOOD = TBLOOD + DBLOOD
1 0 REM *** liver ***
1470 DLIVER = CBLLI*TBLOOD - CLIBL*TLIVER - 1 /CLIGU (17.) *LOG (2) *TLI VER
1- TLIVER = TLI VER + DLIVER
1 0 REM **¦* kidnev ***
1300 DKIDNEY = CBLKI*TBLOOD - CKIBL*TKIDNEY
lriO TKIDNEY = TKIDNEY + DKIDNEY
1 o FiEM bone *+#
lo-O DBONE = CBLBO ( 17.) *TBLOOD - CBOBL (I'/.) *TBONE
1540 TBONE = TBONE + DBONE
1 0 NEXT J7.
!__0 TB (AG7. ,17.)= (TBLOOD/ WTB(I7.)) * 100: REM Convert ua/'ml to uq/dl
l5~0 PRINT USING "###.##": TB THEN GOTO 1700
•I- := OF W T = CROP • AG > ~LOG i TB (AGV., 17.) )
5Ui iMu ¦. f R\ . MQ7.= 5UMM0 i YR7., rIO",:) POF'UjT
-~0 IF a/. = 3o.' THEN SUMM36 = SUMM36 + POF'WT
IF -.TB I AG',. IV.) • HI GHo (CT . YP'l) ) THEN HIGH6 CT . R/.) = TB'. AS'/l. I \ ;
SL.Ilin ' VF,\; = 5UM12M YR7.) + TB (AG"/.. I /.)
-¦ : .E T r.
* , TFAVGQit-tG) = TRSUMQ,¦ 12: TRSUMQ - 0: F'EM reset tor ne:: t census trict
. PRINT AG: " TRAVGC ¦ AG) =" : TRAVGC (AG >
-~30 FZi"! »-¦* Geom. means tor 7- 'eer cohorts (AG^o-1
-'j ii'- ' i-iG .'r .¦ THEN GOTO lES'j
: FCR '.'2=u T"G a
¦ SUi'lH I i Y2) = 3Ui"i!-l I i'2) + CF'OP '. AG) *LDG (hi GHo CT , Y2 ! >
EARA'.'G = SUM12M •' Y2) / 12: SUM i 2M (Y2 !¦ = 0: PE:! F:s = et
1 . i UM\ F, , j; = 5Ui*1'i R 2) + CF'OF (AG) *LGb 'i'Emi- n v'b
i. TF-AVGo ; 2) = 'EAF'AVG
1 _ . NEXT V2
- .0 JZTJs ~ TOTo 1- CF'OF' ' AG)
i 10 £U/! = 0
1 130 FOR 2=0 TO 3: SLrl = SUM + HiGhc '.CT. i 2) : NEXT 't 2
1 n-'. w'Ui'lrl.-. - '-FGP '.AG ¦ *• lGu '. SUM 14) " i*EM JUiTi 4 - -a .¦ z
I ".' E'JI- ~
i'-c.' FOR 'i ,L Til 6: CJi'i = 3U."1 + HI u.Hc 1 CT. i2) : l-iE.:-7 r2
1 • 'J " i,:Ji :_F'C'P ¦. .-iG 1 "LUG '.'_<¦_>!' r r-.LM Si.'.rfi/ . ~ j
-------
i I 1 I LC4 — 3r\Lr«* "*• " ^ ' • » —-
"^"0 TL7. = 35 - LEN (TITLE#) / 2
0 FDR B7. = 1 TD TL7.: TITLE# = " " + TITLE#: NEXT B7.
i,60 LPRINT CHR#(12); LF#; LF#; TITLE#
1570 LPRINT TAB(13) BD#; " BOUND ESTIMATES OF END-OF—MONTH BLOOD LEAD "
0 LPRINT TAB(13) "CONCENTRATIONS FOR COHORTS IN CENSUS TRACT"; TRACT#
.0 LPRINT LF#: "==============================================================
0 LPRINT " Aae End-o-f-Month Blood Lead Concentration (ua/dl
2010 LPRINT YEAR: " Pod Year 123456789 10 11 1
0 LPRINT"
-¦-•-¦0 FOR AG = 6 TO 0 STEP -1
0 LPRINT LF#;: LPRINT USING"### #####"; CGROUF'(AG), CPOP(AG);
_.jO FOR Y = 0 TO AG
20e0 YY = YEAR -AG + Y: LPRINT TAB(13) YY; " ";
0 FOR MO = 1 TO 12
JO I = V * 12 + MO
209O LPRINT USING "### ": TB(AG.I);
" 0 IF YY < YEAR THEN GOTO 2120
0 IF TB(AG,I) ' HIGHPB(CT,AG) THEN HIGHPB(CT;AG) = TB(AG,I)
_i20 NEXT MO
'-¦"-.0 NEXT Y
•O NEXT AG
_Jd0 LPRINT LF#; "============================================»=================
¦ 0 TRPOP = 0
..'0 FOR AG = 0 TO 6: TRPOP = TRPOP + CPOP(AG): NEXT AG
2150 REM Donna Sledae option:
'0 IF (GMQ#="N" OR GMQ#="n") THEN GOTO 2280
TRPOPQ = TRPOP - CPOP(O): REM aae 0 not born in ne:: t-to-1 ast vear.
~_21v FDR AG = 1 TD 6
LOGAVG = LOG(TRAVGO(AG))
:0 WTSUMQ = WTSUMQ + CPOP(AG) * lOGAVG
— ME 1 T mG
SEDMD = EXP (WTSUMQ/TRPOPQ) : WTSUMQ = 0: REM Reset -for ne:.t census tract
:0 L.FRINT "PoduI at i on-Wei ahted Geometric Mean Cone, durinc"; CrEAP-i;: " = "
_ LF F I NT USING "###.#"; GEOMQ;: LPRINT " uo/al."
2280 REM «¦*¦* Jet+ Cohen footnote:
¦. 7F.SUM3o=l.>: TRF0F'3&=O
. FDR i-.G = 2 TO s
.3: TRP0F3O = TRF0P3a CPOP(AG)
~ 7RSUM3o = TRSUM36 + CROP(AG) * i_OG (TRL'vL36 (AG)
•" I ii, ' T t-iG
. . -i1 • To = t. ,* F" ¦ T.-,SUM3o / TROr 3o;
H. J i-iT " Pcdu 1 at l on-Wei anted ijeometric Me-?n Cone, in "•Jt!" .tio.= ':
L-'F INT USING "-.'tUtt. «¦" : TRGI136:
. " L"F INT " ua, ol . "
z'. Di'i
" F"DF. ^"2=0 Tj ":j TPDUMA = 7RSJMA LOG TF'A'.-'Go (72) > : hl/T r2
TRC-.-iA = E~F ¦ TP3UMA/4) : TR3UMA = 0: REM reset -for ne\t census trj.c"
"1-11 "I- LFRINT "G='.-:ii = f:ric Mean ot Annual Ava. Cones, tor the 54-month iJor.or
" :: LFRINT " Durina tear 3": < . E<-.F:-6 'VEfirt-3): " = ";
LFPiiJT USING "##*!¦.£"; TRGilA: : LPRINT " uc/tfl"
_ 'if'.1 r-uP f'2 —4 1G o: — TRSL'MB + LOG(TRA.'Go( 1 : rJfr a T r'j
3"F.2:iB = E..:" TPSUMG, 3 • : T'"'S! i.'liB - 0: T>Eri i-p;et -tor- no..!; cor. s ir tr'CT.
•v. L. F1"-: [. '' ".'.rinrn t sar=": '-EAR-2): C1E1-.R;: " = :
U3:uG "II-tnt.it"; T.~Gi*!r.; ; LFF [l»T " uq.'ul."
'"-i'r--". ¦= . : TZLs\i< - •'<: FIT;-!: F.'sir-t -.:c:- r.e.. ::-ri = ..;= trcict
LFFIilT ii a~ie=:t end-ct-morth blood lead ocournna 1 r, E--F : " b • j i - -
-------
2540 IF (G=2) THEN LFRINT Lr"4-j
Z^' :> NEXT G
:> F'G = F'G+1: lF'RINT LF#;LFi: LFRINT TAB (32) "Facie"; PG
2b70 RETURN
25":) REM
I' REM **+¦***•*•* Output Tables -for All 84-Month Cohorts in Studv Area ***•~**+
2^00 REM
2610 LFRINT CHR*(12); LF$;LFf
2. 5 LFRINT TAB (17) "SUMMARY DATA FOR 84-MONTH COHORTS "
2. ..0 LFRINT TITLE*; LF$; LF.J; LF-f; LF$; TAB (33): "Table 1."
2640 LFRINT TAB(13) "GEOMETRIC MEANS OF " BOUND ESTIMATES OF END-GF-MONTH
i|
2 _j LFRINT TAB(16) "BLOOD LEAD CONCENTRATIONS FOR ALL 84-MONTH COHORTS "
2660 LFRINT LF$; " ===================================================
2 J LFRINT " Mean Blood Lead Concentration (ua/dl)"
2=30 LFRINT " Year 1 2 3 4 5 6 7 8 9 10 11
2 j LFRINT "
- ¦: LF*:
2700 FOR Y = 0 TO 6
2 j YY = YEAR - 6 + Y: LFRINT TAB(13) YY; "
2- _j FOR MO = 1 TO 12
2730 GEOMMO = EXF(SUMMO(Y,MO)/TOTo)
2~" 3 LFRINT USING "### GEOMMO:
I 2 NEXT MO
2760 NEXT Y
2"0 LFRINT LFf; " ====================
2 >50 LFRINT LF'f: LF-1"; LF*; LF*: LFRINT TAB (33) "Table 2."
27'0 LP": INT TAB ( 12) "GEOMETRIC MEANS OF " ; BDf; " BOUND ESTIMATES OF ANNUAL AVERAGE
Z_.'0 LFRINT TAB (15) "BLOOD LEAD CONCENTRATIONS FOR ALL 84-MONTH COHORTS "
21 iO LFRINT TAB(20) "=================================="
1 0 LFFINT TAB (20,' " Mean Blood Lead "
2 0 LF'RINT TAB(20) " rear Concentration (ua/dl)"
254 '> LTPINT TAB',20) " LFS-
2~~0 F3P Y = 0 TO 6
; 't — t-'E.-iF: — o + Y: LF'RINT TAB '.20) i'Y; "
2c"." G2'0M\R = EXF'<.SUMYR (Y)/T076) : LFRINT USING "###.#": GEO IT: ft
1~-=j IF Y = 3 THEN SUM1 = SUM1 + GEGMYR
7. 0 17 r : THEN' SUM2 = SUM2 + GEOMyP
~ NEXT' ,
~ l — bUiii 4: liEAN2 = SUM2 / 3
2 . LPFiMT >_FS: LFJ"; TAB (20); (YY-6; iYY-3): 7A£-(33):: LFFII'JV USING
MEAN 1
\ ~ 3 L~ > I ijT LFi: TAP<2\"; 'Y,-2: N Y) : TAB • 73 '• ; : L'PlMT
:'1E,-.:12
2 " 50 LPRI NT CHPi" : 2 j ; LF i:; LFC
lr 0 LF'RINT TAB '• i 7' 'SUMMARY DATA FOR 54-ttGNTH COHCF.-S"
: LPRINT TITLE*: LFi:LPf
FG? -j2-=0 TO 6: GEQrl i'i2j = EXP i SUMHI (Y2) . TOT.-. > ; NEXT \2
2~~v LFF.IN7 TAB l_ ( i1 1 -•— — — ______ —+ "
~"'_0 LFFIimT "i", . l ¦:' > Co.iort ! Calencar ! Blood Lejd
3 .. l'FiIi.T T;AI? 10 ¦ "1 Ac ='i e;-r 3) Year I Concentration ' ua ' o 1 1 !"
3 " LFRINT TAil. ¦ i'- ,• " +•
3.-50 FZ7' .'2 = 0 TO J
:¦ "• i_." ~ 11 I" ; i-i L' 1' ; 1 ; " ; , 2: " : :
3--. iO L_:~ r . • r U5.UG "-,11^ . 1: 2-201-1-.Y 2.' : ¦; L-FTIliT " I"
-------
U20
" l .0
¦0
• A 50
1 -.0
(I)
.. 30
• 1^0
III)
¦220
:0
•0
-50
""" > 0
'0
—30
->Oij
)0
10
32 0
"0
r0
• _ 7 0
""iO
>0
T .'.'0
5E0i"1A ;
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LFRINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
GE0M36
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
LF'RINT
•
LFFINT
LF'F INT
LPF.ZNT
LFRINT
LPPINT
RETURN
Gc.Uf"li? — t a(-'v csUi'n'it?/ i 1J i o
4. Studv Area Means (b) o-f Blood
Indicators(c) by Cohort Aae
! Cohort
Calendar
1 Blood Lead Indicator
I il
i
! Aae(Years)
Years
! Concentration (ua/dl)
l ll
l
i ll
0-3
(YEAR-6);
(YEAR-3); "!
i
" •
4
: tXr'k sUilT'lA/ f'Ufoj :
TAB(10) " Table
TAB(10) "
TAB(10) "+
TAB(10)
TAB(10)
TAB(10)
TAB(10)
USING "###
TAB(10) "!
USING "###.#";
TAB(10) " +
LF-T;LF.f
= EXP(5UMM36/T0T6)
TAB(10) "F'oduI at l on-wei ahted Geometric
TAB(IO) "in 36th month o-f life =":
USING "###.#": GEQM36: : LF'RINT " uq/dl
LF-S; LF-f; LF*; " FOOTNOTES:
(a)
Lead
GEOMA;
4-6
GEOMB;
LF'RINT "
1; (VEAR-2)
LF'RINT "
YEAR;
Mean Concentration
the
(b)
Seven vear (84-month) cohorts are born January 1 o-f
-first vear and experience 7 -full years (34 months)"
o-f exposure prior to their 7th birthday."
Table 1-4 means are populatlon-weiahted aeometric means "
o-f a blood lead indicator -for the seven-year cohort in each
census tract."
lc) Table 4 blood lead indicator -for the seven-vear cohort in
one census tract is the arithmetic mean of hiahest end-o-f-
month blood concentration durina each year in a series o-f
years."
-------
0 UL f 1
i .a? 1 ,B / u
AGE
-f^f—v :a*
ir LC0 D
pr
—3~
cor;c
-
-4-?-
6 cK. 1*74 51 41 35 21 2* 27 2£ 24 24 23 23 22
-e m *¦« *-» *-= ^ s-5 H H V? a—
t 6 ° . 1*76 2 o 2 c 2 6 26 2 5 25 25 25 23 24 24 2 4
t r—:— «—rz—rt—"—?3—??—r:—n—2~i—~—K—
t oc . "-Hi 21 21 21 21 21 22 2 1 2 1 2 2 21 22 ?:•
rtn t-t-^ *r* Vt H= *-9 2— Yj \-t rt T9
- c'-r. 1 7 i : 14 1 «, 14 1L ".i, 15 H 1s u 14 1j 17
;
—rr
75
•
•
1 r 7 d
111 j
1 7
!» .
1 7
1 7
.1
13
—rz—
17
1 7
_ y
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