United Statas cran r TM
Environmental Protection . t |j i f, ¦ CLmJ-tiH-
Ag«ncy ~ January, 1991
EPA Research and
Development
USERS GUIDE FOR LEAD:
aVc software application of the uptake/biokinetic model
VERSION 0.50
Prepared for
OFFICE OF
Prepared by
Environmental Criteria and Assessment Office
Office of Health and Environmental Assessment
U.S. Environmental Protection Agency
Cincinnati, OH 45268
DRAFT: 00 NOT CITE OR QUOTE
NOTICE
This document Is a preliminary draft. It has not been formally released
by the U.S. Environmental Protection Agency and should not at this stage be
construed to represent Agency policy. It 1s being circulated for comments
on Its technical accuracy and policy Implications.
-------
DISCLAIMER
This report Is an external draft for review purposes only and does not
constitute Agency policy. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
11
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PREFACE
The U.S. EPA 1s developing health-related guidance for lead that can be
applied to a wide range of different media (soil/dust, air, diet). As part
of this effort an Uptake/B1ok1net1c Model for lead was developed that
provides a method to predict blood lead levels In populations exposed to
lead In air, diet, drinking water, Indoor dust, soil and paint; thus making
1t possible to evaluate the effects of regulatory decisions concerning each
medium on blood lead levels and potential health effects. The lead program
Is designed to accept user Input of variables pertaining to s1te-spec1f1c
exposure to lead through air, diet, water, soil, dust and paint. The user
can select either a linear or nonlinear "active-passive" absorption mode'i to
calculate uptake from diet, soil, water or paint. It 1s recommended that
the user select a nonlinear model when either Intake to 61 tract exceeds 100
yg/day or when soil lead levels exceed 1000 ppm. A preliminary version of
"Fetal Model" has been Incorporated into this program to estimate blood lead
levels 1n newborns based on maternal uptake and b1ok1net1cs. It 1s advised
that the model be used only 1f maternal exposure data are available. The
fetal model will be refined based on outcome o.f further review.
Ill
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TABLE OF CONTENTS
Page
1. INTRODUCTION 1
2. COMPUTER-SOFTWARE REQUIREMENTS 2
2.1. POSSIBLE SOFTWARE CONFLICTS 2
3. STARTING THE LEAD PROGRAM 4
4. GENERAL INFORMATION 3
4.1. OVERVIEW 8
4.2. CHOICE OF ABSORPTION METHOO 19
4.3. CHOICE OF MATERNAL CONTRIBUTION METHOO 20
4.4. FILE VIEWER-PRINTER 20
5. ENTERING DATA 22
5.1. USE OF VARIOUS KEYS 22
5.2. THE HELP WINOOW 23
5.3. YES/NO ANSWER FIELOS 23
5.4. SUBLEVEL DATA 23
5.5. Entering Data Ranges 25
5.5.1. Range Selection Menu 25
5.5.2. Blood Pb vs. Media Cone Menu . 27
6. GRAPHING 29
6.1. GRAPHIC HARDWARE REQUIREMENTS 29
6.2. GRAPH SELECTION MENU ^9
6.2.1. Graph of Media Cone vs. Blood Level 29
6.2.2. Graph of Distribution Probability Percent .... 32
6.2.3. Graph of Bell-Shaped Distribution 35
6.2.4. Change the GSD and/or Cutoff 37
6.2.5. Set the X-AxIs Scaling on Probability Graphs. . . 37
6.2.6. Plotting Overlay Files 38
6.3. EXITING A GRAPH 39
6.4. PRINTING A GRAPH 39
7. SAVING PROGRAM PARAMETERS ANO RESULTS 44
7.1. RESULTS OF A MODEL RUN 44
7.2. SAVING PROGRAM PARAMETERS 45
8. LOADING PROGRAM PARAMETERS 48
9. VALUES OF DEFAULT PARAMETERS 49
1 v
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TABLE OF CONTENTS (cont.)
Page
10. HOW THE UPTAKE/BIOKINETIC MOOEL ESTIMATES 8L000 LEAD LEVELS . . 51
10.1. UPTAKE SECTION OF THE MOOEL 51
10.1.1. Air Intake 52
10.1.2. Water Intake 52
10.1.3. Soil and Oust Intake 52
10.2. BIOKINETIC SECTION OF THE MOOEL 53
11. REFERENCES 55
APPENDIX A: CALCULATION OF ABSORPTION FACTORS FOR THE UPTAKE MOOEL . . 65
APPENDIX B: CALCULATION OF TRANSITION TIMES IN THE 8I0KINETIC MOOEL. . 67
APPENOIX C: SELECTION OF DEFAULT VALUES OF MOOEL PARAMETERS 68
APPENOIX 0: GENERAL SCHEMATIC OF THE HEAT PROGRAM 97
v
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No
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
13
19
20
21
LIST OF FIGURES
Title Page
Initialization Screen 5
Introduction Screen 7
Main Menu 9
Data Entry Screen for Air 11
Data Entry Screen for Diet 12
Data Entry Screen for Drinking Water 13
Data Entry Screen for Soil/Dust 14
Data Entry Screen for Paint 15
Data Entry Screen for Maternal Data 16
Run Menu (used to start the Model) 17
Example Summary Output Screen 18
Range Selection Menu 26
Graph Selection Menu 30
Age Range Selection Menu for Graphs 31
Example Graph of Soil Lead Concentration vs. Blood Lead
Level 33
Example Graph of Blood Lead Concentration vs. Probability
Percent 34
Example Graph of Blood Lead Concentration vs. Probability
Density 36
Example Overlay Graph - Probability Percent 40
Example Overlay Graph - Probability Density 41
Printer Selection Menu 42
Save Screen for Program Parameters 46
v1
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LIST OF FIGURES (cont.)
No. Title Page
C-l Total Lead Uptake In 2- to 3-Year-01d Children Exposed to
Various Levels of Soil Lead as Predicted by the Lead Uptake
Model 92
C-2 Effect of Varying the Absorption Coefficients for Lead
In Diet and Water (Aq w) on Total Lead Uptake 1n
2- to 3-Year-Old Children as Predicted by the Lead Uptake
Model 93
C-3 Effect of Varying the Concentration of Lead In Drinking
Water on Total Lead Uptake In 2- to 3-Year-Old Children as
Predicted by the Lead Uptake Model 94
D-l General Schematic of Lead 0.50 (December-Version) 98
*
v 11
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1. INTRODUCTION
The LEAD program Is a personal computer Implementation of the Uptake/
B1ok1net1c Model for lead. The purpose of the Uptake/B1ok1net1c Model 1s to
estimate the total lead uptake (yg Pb/day) 1n humans that results from
diet. Inhalation and Ingestion of soil, dust and paint, and to predict a
blood lead level (yg Pb/di) based upon the total lead uptake. The
current LEAO program estimates lead uptake and blood lead levels In children
of ages 0-6 years old. Graphical results of the program can be used to
predict the percentage of children of a specific age range that may be
expected to have blood lead levels above and below a specified concentra-
tion. The program can also estimate the relationship 1n blood lead levels
with variable lead concentrations In a selected media (soil, dust, water,
air or diet).
The LEAO program 1s designed to accept user Input of variables pertain-
ing to s1te-spec1f1c exposure to lead through air, diet, water, soil, dust
and paint. It Is also designed to be as user-friendly as possible with most
program movement controlled by menus and assisted by help messages. This
user's guide describes the application of the various features of the LEAD
program and briefly describes the Uptake/B1ok1net1c Model upon which the
LEAD program 1s based.
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2. COMPUTER-SOFTWARE REQUIREMENTS
The LEAD program Is designed to run on IBM and IBM-compatible PCs
(personal computers) that use the MS-DOS or PC-DOS operating system. The
program may not function properly when used on an MS-DOS computer that Is
not IBM-compatible.
The LEAD program requires -390K of free memory In order to run. Since
most MS-DOS computers contain 512-640K of memory, this memory requirement Is
not likely to be Important. Additional' memory 1s required when the text
file viewer Is used.
It Is recommended that a math co-processor be Installed In computers
running the LEAD program. A math co-processor will Increase the computa-
tional speed of the LEAD program by as much as 10-20 times. Although a math
co-processor will greatly accelerate the model Iterations, It Is not
required.
2.1. POSSIBLE SOFTWARE CONFLICTS
Various computer users utilize programs that are known as TSRs (Termi-
nate and Stay Resident). TSRs remain loaded In the computer's memory while
other programs are being executed and may be activated by pressing desig-
nated key sequences. Examples of TSRs Include the programs known commer-
cially as "Metro," "Sldekey," "Prokey," "Ooskey" and "PC Tools Shell." A
TSR and the designated main program can conflict with each other, although
this happens Infrequently. This conflict usually occurs when both programs
want to use the same memory at the same time. Conflicts are more likely to
occur when nearly all of a computer's memory Is required to run both -
programs simultaneously.
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A conflict between a main program and a TSR can cause a computer to
•lock-up" and require a "re-boot." Portions of the main program could also
act In an abhorrent manner. If execution of the LEAD program causes a
computer to "lock-up" or act strangely (incorrect operation), unload any TSR
program and re-execute LEAD to see If the TSR was causing the problem. If
the autoexec.bat file loads the TSR Into memory during boot-up, boot the
computer with the original MS-OOS disk.
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3. STARTING THE LEAD PROGRAM
The LEAD program Is supplied on a floppy disk containing the following
file: LEAD5.EXE
The LEAD program can be run from a floppy disk drive; however, 1t Is
suggested that frequent users copy the files to a separate subdirectory on a
hard disk (If available) and run the program from the hard disk. An example
of creating a separate subdirectory and copying the files from the floppy
disk to the hard disk 1s shown below. The example assumes that the hard
disk 1s designated as the "c:' drive. F.lrst, make sure the "c:" drive Is
the current drive by typing c: at the DOS system prompt and pressing return.
Put the floppy disk 1n the "a:" drive. Remember to press the ENTER key
after each line entry:
The program Is started by typing LEAOS at the system prompt of the
subdirectory containing LEAD5.EXE and pressing the ENTER key. If the
message "bad command or file name" appears, it means that LEAD5.EXE 1s not
1n the current subdirectory.
LEAD begins with an Initialization screen, which 1s shown 1n Figure 1.
The length of time the Initialization screen remains visible depends upon
the speed of the computer and the presence or absence of a math co-processor. .
At the Initialization point, the program determines the available computer
hardware for correct video display and calculates a large variety of
c:>cd lead
c:>cd:
c:>md lead
c:>copy a:*.*
(go.to the root directory of c:)
(create LEAD subdirectory) •
(change to the LEAD subdirectory)
(copy all files from a: drive)
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Laid Program: Baca 0.S0
Computing ayacam initialixationa....
Thi» initialisation can raq-uira up to 60 aaconda on aa.XT aachina
which DOCS NOT hava a math co-procaaaorlI
Mach Co-Procaaaor Chacks IS DETECTED in thia maehina.
NOTE: a mach co-procaaaor will incruaaa modal computation apaad
by 10 co 20 timaa I I 11
FIGURE 1
Initialization Screen
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parameters for later use by the Uptake/81ok1net1c Model. On a 286/AT or
386/AT class PC with a math co-processor, the Initialization screen remains
visible for only one second or less before automatically displaying the
Introduction Screen, which 1s shown 1n Figure 2.
If a math co-processor Is not, present, the Initialization takes much
longer. The Initialization screen displays a message that shows whether or
not a math co-processor has been detected by the LEAO program. The follow-
ing 4s an example of the time difference between the absence and presence of
a math co-processor on a Zenith XT class-PC. Without a math co-processor,
the Initialization requires 35 seconds at 8 MgHz and 56 seconds at 4.77
MgHz. With a math co-processor, the Initialization takes <2.5 seconds.
Note that a single Uptake/81ok1net1c run during the LEAD program takes *60%
as long as the Initialization. A math co-processor Is much faster at
computing decimal point numbers than the regular CPU (central processing
unit) because 1t can directly process logarithms, exponentials and frac-
tional powers. The Uptake/81ok1net1c Model makes significant, repetitive
use of logarithms, exponentials, fractional powers and high precision
decimal point numbers.
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UPTAKt/BIOJCINXTIC MODEL for LZAO
Version 0.50 (D«c«ab«r 1590)
^Program Davalopaant by
U.S. ENVIRONMENTAL PROTECTION AGZHCY
BBIBU
Tha purpoaa of thla progru la Co dataraina Total Laad Uptaka (ug/day) la
ehildran 0 to I yaara old which raaulta from Inhalation. dlat, ud aoil/duac
ingaation ud to pradiet a Blood Laval (ug/dL) baaad upon Total Laad Uptake.
BIS
Praaa any kay to eontinua...
FIGURE 2
Introduction Screen
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4. btNERAl INFORMATION
4.1. OVERVIEW
After the program has been Initialized, the Introduction Screen (see
Figure 2) appears, followed by the software Disclaimer Screen and an
Information screen. User execution of the Uptake/B1ok1net1c Model begins at
the MAIN Menu. The MAIN Menu 1s Illustrated 1n Figure 3 and Is the central
control point of the LEAO program. It 1s used to access the primary data
entry screens, run the model, load and save program parameters, display
various help screens, access the graph and range selection menus and exit
the program. As with all menus used 1n the LEAD program, selection from the
main menu 1s made 1n either of two ways. One method 1s to press any of the
keys that correspond to the first number or letter In each row. The other
method 1s to use the up or down arrow keys to move the highlight bar to the
selection and then press the ENTER key. Any menu In the LEAO program can be
exited without making a selection by simply pressing the ESC key.
A general schematic diagram of the LEA05.EXE program 1s Illustrated 1n
Appendix D, Figure 0-1. It outlines the basic flow of the program and
demonstrates how the MAIN Menu 1s used to access various features In the
program. Although the LEAD program may seem complicated to new users, 1t Is
simple In concept. Data are entered for Pb exposure In the various environ-
mental media. The model Is then run for that data set and the results of
the model run are then saved and/or graphed. The current version of the
LEAD program has the ability to graph the results of 7 different model runs
on the same probability graph. Two of the selections from the MAIN Menu
(•M-MULTIPLE Runs " and "B-8L000 Pb ") are useful for making
consecutive model runs 1n which the only data entry parameter that changes
1s one of the media concentrations.
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UptaJca/BioJciaatie Modal
HAM KZMUi
I 1 - Ent»r Pic* tog AIR.|
2 - Kntec Ddti tair OLKT.
3 - Enter- Data, far OR INK INC WATER-V .
4.— Enterr DatJL, far- SOIL/HCIST"-*.",,.-—' i . ( • _ .
Si'— Enter: Daf~.r tor: *
SI — Enter: MATERNAEi Oat -
R\ — RUTJy the- Mode 13 (us incp current! value
' ST— SAVEI ProrjxJEC! Parameters* tori F i I
IL.'— LOAIT.Proqrjul Pdranutcra fronrrai File-t^/^f^i'
G" — General. InfciniiatiaTr.abau.tz.thiG-prarjraiir—'i!.*'.
r — INFORMATION" about, variaui menu i-eluctionsj
F - PLOT Exietincj Graph Fiilecr (CRAPir Menu).- '
M - MULTIPLE. Rune.. — RANGE Menu. (Overlay tiles) -
V - VIEW / PRINT a. Data (TXTJ File.
B — BLOOD Pb v& Media Cane: HodcL Huns & Find.
Q - QUIT (EXIT to 0O5)_ 5
To aalaet, praaa auabar (or Lattar) of aalactioa OK uaa
arrow kaya to highlight aalactlon and praaa ratum.
FIGURE 3
MAIN Menu
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The LEAD program contains the following six primary data entry screens
Illustrated 1n Figures 4-9: (1) Air, (2) Diet, (3) Drinking Water,
(4) Soil/Oust, (5) Paint and (6) Maternal. Each of the primary data entry
screens allows the user to enter/edit data and/or change various default
data already built Into the model. Any of the six primary data entry
screens can be accessed directly from the MAIN Menu. From any of the
primary data entry screens, the PgUp or PgDn keys can be used to switch from
the current primary data entry screen to the next or previous primary data
entry screen. To return to the MAIN Menu from any primary data entry
screen, simply press the ESC key. An Information bar at the bottom of each
primary data entry screen displays the various keys that can cause program
movement. Press the FT key to display a General Help Screen at the primary
data entry screens. The ESC key can be used at any time In the program to
return to a previous screen.
After the appropriate lead Intake and parameter data have been entered
by the user, the Uptake/B1ok1net1c Model can be started using one of the
following two methods: (1) select "RUN the Model (using current values)"
from the MAIN Menu or (2) press the F5 key at any primary data entry screen.
Either method displays the Run Menu Illustrated In Figure 10. Iteration of
the Uptake/B1ok1net1c Model 1s started from the Run Menu. The Run Menu also
allows access to various default parameters In the B1ok1netlc portion of the
Model.
After the model has been run, the screen displays a summary output of
the blood lead levels and various lead uptakes for each yearly period for
the current data set. An example summary output screen (using all default -
data) Is shown In Figure 11. A selection menu appears at the bottom the
screen. The "HELP" choice from the menu describes the "GRAPH Results" and
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Uatick. hntrv tor- AJ.R
Vary Air Coae. by Itu 117 «
Outdoor Air La ad Concentration (ug/aJ) i
Indoor Mr Pto Cone. (Parcantaga of Ouedoor) i
Viaw/Changa Tlaa Spant Outdoor! i
Viaw/Cbanga Vantilation Rataa i
Viaw/Changa Lung Abaorpeion X i
•' * ; e iv u rrn^Mir^rnistii!
SiSSIiiSS!
0.200
Dafault
Prpcc. oithrrr^
M for NO
f tor YEa.
-mkKt-iuit i %
I yt*
l-iSijSi., % t\
HXLP WINDOW
If you want to vary air eoneaneraeion for aach yaar or riaw currant
varlabia data » Praaa T for II8.
NO ia diaplayad in thia fiald if all yaarly concantratiana ara aqual.
YES ia diaplayad in thia fiald if all yaarly concaneraeiona ara NOT aqual.
NO MOST ba aalactad to anear a aingla cone, for Ouedoor Air Laad Cone.
Esc: MAIM Menu Fl: General HKLP
EE
: HUN Model
faUp/fgUn; MeciiA Switch
FIGURE 4
Data Entry Screen for A1r
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Data. Entry tar" DIKT
5| rt-H n " "-H
intake ft?
Values TTT
Method/BioAvailability??
nTmsrrrjjpfyi
s % « £ « K s ** l& ^
<*o/Tes>
»
i
NO
Hon-Line
iiiiwiviiioiiiiiiiviii
hzlp window
Exposure to lead la food is based oa eh* typical American diet and
quarterly surveys of Pb concentrations la this diee. It you want to
change or view the current dietary Intake levels of lead for each yearly
period (based upon these surveys)! Press » Y for TZS.
The program default values (in ug Pb/day) are 5.II, 5.92, 4.79, S.ST,
S.3(,t.75, 7.48 for the respective yearly periods.
Esc: MAIN Menu
bob
; RUN Hadel
PgUp/PgDn: Media. Switcti
FIGURE 5
Data Entry Screen for Diet
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Data, iizitry tar LIHINKINC; WATKR
mv.
[Stfjiij-iii
Mictivl
Esear Laad Cobo la Drinking Macar (ug/L)i
jlihfi aw /cbanga Drinking Watar Xntaka? i
Default
Mo
Hon-Linaar
| > J h * * £
liipiilli!
*lvsi -I
®" * # > I >
iJ'SKt i% t | > r«
*1.
HS1P WXNDOW
tntar tha concentration of laad in eha drinking waear (ug Pb/L).
This concentration ia hold eouttnt over the entire savea year period.
The prograa default 'concentration is > 4.00 ug Pb/L
Drinking waear is defined mo the tap waear consumed in a glass or froa a
drinking fountain. Tap waear uaad for nixing beverage* or coolcing ia pare
of ebe dietary exposure and changes bars ara reflected in Cap waear uaad
for cooking and mixing. THIS rXZLS HOT ACCZSSZBLI IF ALTZXXATZ NATZR ZS TZSI
Kcc: MAIN Menu
: RUN Model
PaUp/PaQn: Media. Switcti
FIGURE 6
Oata Entry Screen for Or Inking Water
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Lkicjt EnctTf tor ;ian,/DUi
< «jL aH-S
Sell Pa Laxala (ug/3) i BKBHHiHil
1 Xadoor Duat fb Lavala (ug/8)» 200,0
c itJxerr: * * *
T - Eater a. conttant. vjlue.
2.— ;'.::tiT variable
:;:y+'it$¥:>rWJ
jiilsjBiiiiiSiiWSSaiSB.
ISoil/Buat Zas««tsies Weight
t * fc«t |i b traaala# tha ¦alaeeion aumbar 2m tha nanu abova,
Tha 'coaaeaae valua* aalaetloa allowa a aiagla eoae Co ba aatarad, which ia
thaa uaad for all agaa. Tha 'varlabla valua' aalactioa allows a diffarani
aoil eoae to ba aacarad Cor aach aga.
Tha prosraai dafault eoaataat ceac la > 300 uff fb/g aoil. .
Kec: MAIN Mfnil f
Fb; HUN Model
fqjUp/l'cjUn; Mcdld Switch
FIGURE 7
Data Entry Screen for Soil/Oust
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Uata. Entry tor PAXNT
Ylaw/Chaas* Paint La ad lataJca 777 i
Chaaga 01 Kaehod/lloAvallatollley?? t
-> 3«fc
' " •**
S i > V (It*
:gj tfP§jijj;:il|!i&:Si
itttt
I T tor YIS.
Tba program dafault valua la
0.0 ug Pb/day for all aga*.
Kbc: MAIN Menu. Fli General BtXP
OB
: HUN Model
PaUp/l'uUn; Media. Switcti
FIGURE 8
Oata Entry Screen for Taint
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HK.P WIHTX3W
Salact aithar eh* Infant Medal or tha Fatal Modal for tha Mothar'a
Pb contribution to tha child. Tha only data aaadad to usa tha Infant Modal
is tha Mothar's Blood Pb laval at birth. Tha Fatal Modal currantly in this
program la a alapllflad varsion of tha Matareal-Fatal Modal. Tba Fatal Modal
uaas Pb input for aatamal air, dlat, watar aad dust to dataraina Pb 1 aval a
in tha fatua during aaeh ao&th of fatal davalopaant. It raqulraa tha antry
of various data and/or tha usa of various dafault data.
£bc: MAIN Menu.
; General. HELP Fb: HUN Model
tJaUp/lJaOn; Media- o'witcii
FIGURE 9
Data Entry Screen for Maternal Oata
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WW tha MODEL baa b*«a Choaaa
lalact fro» aaaut
|1 - ROM tha Modal wlch curr«at pumctri. |
C- — t'h.inqt-; aiolcxiieti.c, detault^ parjmeters^^y
— CcncraEt Inf anoatiam j_bcrut3. thoi Mode^
RS — HETUHJC tee. h.i j it- Monui arz Data; Entry* ecrpi'ir-^
— To aalact, praaa numbar (or Lattar) of aalactioa OR uaa
arrow kays Co hlghliffhe aalaceioa and praaa raeurn.
FIGURE 10
Run Menu (Used to Start the Model)
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Blood Laval
Toeal Uptaka
Soil+Duac tTptaka
TZAR
(ug/dL)
(ug/day)
(ug/day)
0.5-11
3.30
9.38
6.00
3.01
10.03
6.00
3-3 t
2.98
10.5C
C.OO
3-4 i
3.04
10.48
C.OC
4 - 5 t
3.13
10.41
C.OO
5-6 t
3.15
10.73
6.00
6-7 t
3.18
11.11
C.OO
Dlat Uptaka
Wata* Uptaka
Paiac Uptaka
Air Uptak#
TIM
(ug/day)
(ug/day)
(ug/day)
(ug/day)
O.S-li
3.94
0.40
0.00
0.04
1-2 i
3.95
1.00
0.00
0.07
2-3 i
3.40
1.04
0.00
0.12
3-4 i
3.39
1.0«
0.00
0.13
3.18
1.10
0.00
0.13
S-6 t
3.38.
l.lf
0.00
0.19
3.74
1.18
0.00
0.19
Salact from Maui
I
FIGURE 11
Example Summary Output Screen
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"SAVE Results" selections. The "SAVE Results" selection allows the summary
output (and the values used to calculate 1t) to be saved to either a printer
or a text file. The "GRAPH Results" selection allows the user to choose
various ways to graph the current data set.
The LEAD program Is currently set up to allow the Model to run wlthout
the user having to enter any data. This can be accomplished by selecting
"RUN the Model (using current values)" as soon as the Main Menu appears when
the LEAD program is started. Of course, these results are simply the output
of using the complete set of default data.
4.2. CHOICE OF ABSORPTION METHOO
Version 0.5 of the LEAO program allows the user to select either a
Linear Absorption Method or a Nonlinear Active-Passive Absorption Method for
the Uptake portion of the Model. The Nonlinear Method Is the program
default. The method currently selected Is displayed In a data entry field
on each of the 01et, Water, Soil/Oust and Paint primary screens. When the
data entry field Is accessed, the user answers a question to access
the Absorption Method selection menu and to change the default absorption
values.
The TSO contains a discussion of the Linear and Nonlinear Methods.
Briefly, the Linear Method simply uses a constant absorption percentage (for
each age and exposure route) that 1s multiplied by the lead Intakes to
calculate the lead Uptakes. In the Nonlinear Method, the absorption
percentage varies with the lead concentration, volume of the gut, and other
factors.
The equations used by the Nonlinear Active-Passive Method are listed 1n -
Appendix A. The default values for both methods are also listed In Appendix
A. After choosing the absorption method from the selection menu, the user
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can change the default values. The default values should not be changed
unless the selected method 1s clearly understood.
4.3. CHOICE OF MATERNAL CONTRIBUTION METHOD
The concentrations of lead occurring 1n a baby at the time of birth help
to determine the lead levels 1n Us body for several years after birth. The
Importance decreases as the child gets older. Version 0.5 of the LEAO pro-
gram allows the user to select either the Infant Method or the Fetal Method
for determining the Mother's contribution to the newborn's lead levels.
The only data required to use the Infant Method Is the Mother's lead
blood level at birth. This lead level Is then used to estimate the lead
levels In the baby's blood and organs at birth. The default value for the
Mother's blood 1s 7.50 yg Pb/di.
The Fetal Method 1s a simplified version of the Maternal-Fetal Model.
It 1s actually a separate uptake/bloklnetlc model within the LEAO Uptake/
81ok1net1c Model. The user 1s asked to provide lead exposures values for
the Mother Instead of the child. The program provides default values. The
lead levels In the fetus are then determined by an Iterative method
throughout pregnancy.
4.4. FILE VIEWER-PRINTER
The LEAO program contains a text file viewer that can be used to browse
any of the text summary files generated by the program. These files have
the file extension ".TXT". The File Viewer Is accessed from either the MAIN
Menu or the Graph Selection Menu. When the File Viewer 1s selected, a list
of the available TXT files 1s displayed on a menu.
The File Viewer screen contains an Information line at the bottom of the
screen that lists the available action keys. The top of the screen lists
the file name and the line number In the file that appears at the top of the
viewing window. The entire file can be printed by pressing the F7 key.
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The File Viewer Is limited to 3000 lines In a single file. For example,
1f a file contains 4000 lines of text, only the first 3000 can be viewed.
In addition, the File Viewer requires as much free computer memory as the
size of the file since the entire file Is loaded Into memory.
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5. ENTERING DATA
5.1. USE OF VARIOUS KEYS
In order to enter data pertaining to air, diet, drinking water, soil/
dust or paint concentrations of lead exposure, 1t Is necessary to first
access the appropriate primary data entry screen. As Illustrated In Figures
4-9, each of the primary data entry screens contains an upper portion where
the user can enter data, and a lower portion, which contains a "Help
Window." The current field for data entry 1s highlighted 1n reverse video
(white background with black letters) and contains the flashing cursor. The
following list of keys can be used during data entry to perform the
Indicated function:
Tab:
Up Arrow:
Oown Arrow:
Left Arrow:
Right Arrow:
change fields.
go to the previous field.
go to the next field.
move cursor to the left within a data field. If
at the beginning of a data field, move to previous
data field.
move cursor to the right within a data field. If
at the end of a data field, move to the next data
field.
Home: send the cursor to the beginning of the current
field.
End: send the cursor to the end of the data 1n the
current field.
PgUp & PgDn: go to the previous or next primary data entry
screen, (must be at the primary data entry level)
ESC: go to the Main Menu (IP at the primary data entry
level) or go to the primary data entry level (If
at a sublevel).
F1: display General Help.
F5i: go to the Run Menu (1P at a primary data entry
level).
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The Backspace and Oelete keys operate the same as In most word processors.
Data entry occurs 1n "typeover" mode since all data entry 1s numeric.
5.2. THE HELP WINDOW
The "Help Window" displays Information and Instructions pertaining to
the highlighted data field. Various default values are also listed In the
"Help Window."
5.3. YES/NO ANSWER FIELDS
All of the primary data entry screens contain fields In which the user
can enter data with either a YES or NO selection. NO selections generally
Indicate use of program default data. When NO is selected, the cursor and
hlghllqht move to the next field. When YES 1s selected (with the exception
of the GI tract absorption fields), a sublevel of the primary data entry
screen appears on the upper portion of the screen. The "Help Window"
continues to display relevant Information. The user enters much of the
s1te-spec1f1c data that needs to be entered at the various sublevel screens.
With the exception of the GI tract absorption fields, most of the YES/NO
answer fields display either "Default" or "Changed." When "Default" Is
displayed. It means that the data accessed from the field contain the
program default data. When "Changed" Is displayed, 1t means that the
program default data (one or more values) have been changed.
It 1s not necessary to answer a YES or NO selection field with a YES or
NO to change fields. Use the Tab key or Up and Down arrow keys to change
fields.
5.4. SUBLEVEk OATA
A sublevel of a primary data entry screen is another data entry screen .
related to the primary screen. Most of the sublevel screens are accessed by
answering YES to a YES/NO field. Sublevels for Soil/Oust and Maternal are
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also accessed by selected answers from a menu r Id. The lowing Is a
list of the data that Is entered at the various sublevels of the primary
data entry screens:
mIR: (1} variation of air conc. by year.
(2) time spent outdoors.
(3) dally ventilation rates by year.
(4) percent lung absorption.
DIET: (1) dally consumption (yg Pb/day) by year.
(2) alternative diet variables.
(a) home-grown fruit conc and percent.
(b) home-grown vegetable conc and percent.
(c) recreational f1sh conc and percent.
(d) wild game conc and percent.
(to be added at a later date:)
(e) regional preferences.
(f) ethnic preferences.
DRINKING HATER:
(1) amount of water consumed dally by year.
(2) alternative drinking water sources.
(a) first-draw conc and percent.
(bj fountain conc and percent.
SOIL AND DUST:
(1) user specified variable soil and dust levels by year.
(2) amount of soil and dust Ingested dally by year.
(3) Multiple Source Analysis:
(a) soil contribution conversion factor for house dust.
(b) air contribution conversion factor for house dust.
(c) alternative sources of dust exposure.
(1) second occupation conc and percent.
(2) school conc and percent.
(3) daycare conc and percent.
(4) second home conc and percent.
(5) paint dust conc and percent.
PAINT: (1) dally paint Ingestion by year.
MATERNAL:
(1) Fetal Model:
(a) Mother's age.
(b) air conc. Indoors, outdoors, and work.
{c) vent, rate (raVhour) indoors, outdoors, work, sleeping.
(d) hour/day Indoors, outdoors. work.
(e) water conc. at home and work.
(f) water consumption at *otm and work.
(g) diet consumption and conc
(h) dust consumption conc.
(1) absorption air, water, diet. dust.
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5.5. ENTERING DATA RANGES
5.5.1. Range Selection Menu. l_EAD5.EXE contains a new "Range" feature
that was not available In previous versions of the LEAO program. This new
feature Is accessed by selecting "M - MULTIPLE Runs - RANGE Menu (Overlay
files.)" from the MAIN Menu. The Range Selection Menu Is Illustrated In
Figure 12. The Range Selection Menu 1s Intended to simplify consecutive
model runs In which the only parameter that changes from run-to-run Is one
of the constant media concentrations. For example, a user may want to
determine blood Pb levels at constant soil concentrations of 100, 200, 300,
400 and 500 yg/g. Without using the Range Menu, the user could enter a
constant soil concentration of 100 at tfre Data Entry Screen for Soil/Oust,
run the model manually, save the results manually and then repeat these
steps for the other concentrations. The Range Menu automates this process.
The Range Menu 1s used to select the media, the starting and ending
concentrations, and several output choices. The bottom half of the Range
Menu screen displays the values currently selected for each of these
selections. The media choices Include soil, dust, water, air and diet. For
model runs made from the Range Selection Menu, the program automatically
sets the selected media (with the exception of diet) to use a constant
concentration for all age groups. If diet Is selected, the program propor-
tionally scales each concentration for each age group relative to the 6- to
7-year-old group. The selected range values pertain specifically to' the 6-
to 7-year-old group. The diet concentrations for the other age groups are
then calculated as the diet Intake fraction of the 6- to 7-year-old concen-
tration. The fractions are determined from ne current diet Intake values .
entered at the Data Entry Screen for Diet For example. If the current diet
Intake for a 6- to 7-year-old Is 20 Mg/day and the current diet Intake for
a 2- to 3-year-old Is 10 ug/day, then the fraction used Is 0.50.
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HATJGK ELECTION MOJU
II - Salact MZOIA for Raaga Valuaa.
Z - tluter HJtVNLihl uAi.iiK-; tor Selected Mtida.a._
1 - RUN McxleL- Car ^i^lccted HediA fc- VaLueSw *
4-.: — Chair rje-_ OUTPUT: CHQICEH* Lor; the- Models Run.
m — HELP"- Iaformxitiarr-^Wv£^'^4.V^
Hi- RETUHTt;
Currant Salactad Madias Soil
Currant lUnga Valuta
for Salactad Madiai
Start Valuai
Cad Valua i
0.000
1000.000
Modal Run Output Choieaat
Saad To Ovarlay Fila t i HO
Dlaplay Simsnary OutputaTi TKS
Busbar of Jtuna for taagai 7
FIGURE 12
Range Selection Menu
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The Output Choices Include (1) "Send to Overlay File?', (2) "Display
Summary Results" and (3) "Number of Runs for Range". The first two choices
are answered Yes or No. The third choice 1s the number of times to run the
Uptake/Bloklnetlc Model for the range between the starting and ending con-
centrations. The minimum and maximum number of runs are 2 and 7, respec-
tively. The range 1s divided Into evenly spaced Increments determined by
the number of model runs. For example, 1f the range 1s 100-500 and the
number of runs 1s 5, the model runs at concentrations of 100. 200, 300, 400
and finally 500.
The model runs are started by selecting "3 -RUN Model for Selected Media
and Values" from the Range Menu. If the user wants to obtain summary
results and/or save them to a file. Output Choice (1) "Send to Overlay File"
must be set to "YES". When "YES" is selected, two overlay files are created
for the entire range. The files are assigned the names "RANGE#.LAY" and
"RANGE#.TXT" where the "#" symbol 1s replaced by a number. The "LAY" file
contains data to plot the results of each model run for the whole range on
the same graph. The "TXT" file contains a corresponding text summary of
each model run. The first Range run creates the files RANGE1.LAY and
RANGE 1.TXT; the next Range run creates RANGE2.LAY and RANGE2.TXT. The
program checks the current directory/subdirectory for the existence of
RANGE# files and does not overwrite existing files. A limit of 40 RANGE#
files 1s allowed 1n the current directory. The overlay "LAY" files are
graphed by retrieval from the Graph Selection Menu, which can be accessed
from the Main Menu.
5.5.2. Blood Pb vs. Media Cone Menu. This feature, which 1s also new to .
the LEAD program, 1s accessed by selecting "B - BLOOD Pb vs. Media Cone:
Model Runs & Find" from the MAIN Menu. It 1s similar to the Range Selection
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Menu described above. It Is Intended to simply output consecutive mode)
runs for determining the relationship between the media Pb concentration and
the blood Pb concentration. Output from a series of model runs Is used to
graph blood Pb concentration versus media Pb concentration. Each model run
series can be graphed without saving 1t to files. However, graphing at a
later time or graphing more than one series on the same graph requlres
saving to files.
Files created at this menu are assigned file names of "MEOBLD#.PBM" and
"ME0BL0#.TXT" where the symbol 1s replaced by a number. The "PBM" file
1s used to graph the relationship for one series of model runs. Graphing
more than one PBM file on the same graph can only be accomplished at the
Graph Selection Menu, which Is accessed from the MAIN Menu.
Menu selection "F - FIND Media CONC Associated with a Blood Pb" Is used
to find a specific media concentration that corresponds with a known blood
Pb concentration. It assumes that the only variable Pb Intake-parameter Is
the selected media concentration. The program determines the specific media
concentration by Iterating the model up to 25 runs (less than 10 runs are
usually required). The Iteration 1s completed when estimates from two model
runs are within 10 percent of the known blood level. The two estimates and
the desired media concentration are assumed to have a linear relationship
that determines the media concentration. This specific media concentration
could also be determined graphically from the graphs generated at this menu.
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6. GRAPHING
The graphing features of the LEAD program are controlled by the Graph
Selection Menu which 1s shown 1n Figure 13. The general schematic diagram
of the LEAD program (Appendix D) Illustrates the location and access of the
Graph Selection Menu. This menu can be accessed directly from the MAIN Menu
or by selecting "2-GRAPH Results" from the menu that appears at the bottom
of the summary output screen after a single model run.
6.1. GRAPHIC HARDWARE REQUIREMENTS
The LEAD program automatically detects the type of graphics card present
1n the computer. The types of graphics cards that can be identified are
Hercules, CGA, EGA, VGA and MCGA. The program has been tested on Hercules
and Hercules-compatible monochrome cards, CGA, EGA and VGA. In CGA mode,
the graph appears in light-blue with a black background with a resolution of
640x200 pixels. In EGA and VGA color modes, the graph appears In white
letters with a blue background. EGA resolution Is 640x350 pixels while VGA
resolution 1s 640x480 pixels. Resolution of MCGA Is 640x480 pixels with
monochrome coloring.
6.2. GRAPH SELECTION MENU
Various selections from the Graph Selection Menu are discussed below.
When most of the "GRAPH" or "PLOT" selections are chosen from the Graph
Menu, the Range Menu (shown In Figure 14) 1s displayed. The Range Menu
allows selection of the age range to graph.
6.2.1. Grap& of Media Cone vs. Blood Level. This selection requires a
P8M file of data points. P8M files are generated by the MAIN Menu selection -
"B - BL000 Pb vs. Media Cone". They show the relationship between media Pb
concentration and blood Pb concentration. Each PBM file plots one curve of
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GRAPH Madia Pb Concantracion wrwi Blood Pb Coac
Crapluci. ieitction
Hnr.U:
2. — GHAI'fL Di^itjrit!utj.ari» Probability t'ercunD -^- PLOT? OVEHLAYT File- aC Multiple MadeET Humr-iJ (Be-IX iJhapccili'S^i'
ft — HELL1 ^InfansatiorL. about: then threes. GHAPIE'aeL«.-ctioiui_'vr,i.' r>'~
K- — Infornution; jhout OVEHLAT Plat? Files-_r )->•». -• '
cr — CHANGE:, thi-CCD ,ir.d/or CraptCuta££— i,: ' *•• '
L : Intarmtiaa about CGO and. Graph C?at.ot t ,
IT - Ut't X-AXirr SCALING (Auta/Canntant J • uri Probability Craphs_
V - VIEW / I'HIHT a Data (TXT) Kile-
Ft - HETURN (Exit this. Ei'nu, Return to Main. Menu/Data Entry)-
Currant GSDi 1.42
Currant Cutoff« 10.00 ug Pb/dL blood
Currant X-«xlai Automatic Sealing
FIGURE 13
Graph Selection Menu
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Blood la*d distributioa eaus b« srr*pfc«d
for * ~*ri«cy of mgm raaa«s. X&ka your
••Iscslsa from eh* aaau, Th« oaomerie
sui&a eaac. wromad which six* di»tribueioa
i« gx*ph«d is eta,* av«r*ga
-------
up to 15 data points. Each consecutive data point Is connected by a
straight line. The graph 1s designed to allow a maximum of 5 PBM files to
be plotted on the same graph. Files to be plotted are selected Individually
by the user. Consecutive selection adds a new file to the existing graph.
Identical media are required for plotting more than one file on the same
graph; however, different age ranges are allowed. The contents of each
selected PBM file are shown before plotting to allow user screening.
A sample graph 1s shown In Figure 15. The top line In Figure 15 (marked
by triangle data points) uses the default set of program parameters and
varies the soil concentration from 0 to 2000 »g/g. The bottom line, which
contains an observable curve, uses the same data set but modifies the
non-linear absorption half-saturation concentration from the default of
100,000 ug/g to 100 yg/g.
6.2.2. Graph Distribution Probability Percent. This selection uses the
current data set to plot the S-shaped, cumulative probability percent
curve. The geometric mean blood lead level for the selected age range 1s
plotted at 50%. At 50%, there Is a 50% chance of being above the geometric
mean value and a 50% chance of being below the geometric mean value. In
addition to 50%, points on the graph may be plotted at the percents which
correspond to 0.25, 0.5, 1, 1.5, 2, 2.5, 3. 3.5, 4, 5, 6, 8, 10, 12, 14, 16,
18, 20, 24, 28, 32, 36, 40, 45, 50, 60, 75, 100, 150, and 200 wg Pb/l.
A sample graph Is shown In Figure 16, which was generated from the default
set of parameters and a water concentration of 40 ug/l-
The geometric mean (Geo Mean), the cutoff concentration and Intersect
percent are displayed near the upper right corner of the graph. The -
geometric mean pertains to the geometric mean blood concentration for the
selected age range. The cutoff concentration (Section 6.2.4.) Is a user-
selectable value used to separate the percentages of children predicted to
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11.8
ta.a -
9.0
8.0
7.0 -
6.0 -
5.8 -
4.0
3.0
2.0
1.0-
J I——J L.
600 800 1800 1280 1400 1600 1800 2880 2288
Soil Pb COMCXMTJWTION (ug/9)
FIGURE 15
Example Graph of Soil Lead Concentration vs. Blood Lead Level
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tee
H
z
u
u
s
w
k
a
e
a
o
s
a.
Cuto^r: to.ee usscix.
Cm H»an - S.54
Int»r*«et: 4.57 »
A 6 8 18 12
BLOOD UERD COHCENT1WTION ( ue'dL )
24 to 38 Wont**
FIGURE 16
Example Graph of Blood Lead Concentration vs. Probability Percent
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have blood lead levels above and below the selected concentration. It
appears on the graph as a vertical, dashed line. The Intersect percent 1s
the percent value where the dashed cutoff line Intersects the S-shaped
curve. On the sample graph (see Figure 16), the Intersect Is 4.57%. This
Indicates that 4.57% of the children In the age range have blood lead lavels
above the cutoff concentration (10 yg/dl).
The Intersect percent directly corresponds to the "Above X," which
appears on Figure 17 (Bell-Shaped Distribution Graph). Figures 16 and 17
were plotted from the exact same data set to demonstrate the relationship
between the two graphs. In theory, the "Intersect %" from Figure 16 and the
"Above %" from Figure 17 should be Identical for the same model run. The
values are close (4.57% vs. 4.15%) but are not Identical. The variance
occurs because the S-shaped graph Is plotted from a polynomial approximation
derived from the algorithm used to plot the bell-shaped graph. For the
current algorithms, the variance Is usually <2%, which should be suffi-
ciently accurate.
The algorithm used to plot the S-shaped curve was taken from a previous
Uptake/B1ok1net1c Model and may need to be updated In the future.
6.2.3. Graph of Bell-Shaped Distribution. This selection uses the
current data set to plot a Gauss-like distribution curve that displays the
probability density corresponding to the geometric concentration and
geometric standard deviation. The vertical dashed line appearing on the
graph Is the cutoff concentration. The default cutoff concentration 1s 10
ug Pb/di. The percentage of children (of the selected age range)
expected to have blood levels above and oeiow tne cutoff are calculated and -
shown In the upper right-hand corner of tne graph. The percentages are
calculated by determining the area under each portion of the curve.
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cutorr
at flbou
JH BoIom
U. H«an
ie.8
4. IS
95.85
5.54
4 6 8 10 12 14
BLOOD LERD CONCENTBRTION < u«/dL)
24 to 36 Horittis
20
FIGURE 17
Example Graph of Blood Lead Concentration vs. Probability Density
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The geometric mean (G. Mean) blood level {vg/dl) 1s also displayed. A
sample graph 1s shown In Figure 17.
6.2.4. Change the GSO and/or Cutoff. GSO Is the geometric standard
deviation. It 1s used In the equations that draw the bell-shaped distribu-
tion curve and the S-shaped distribution curve. A GSO range of 1.30-1.52 1s
considered reasonable for children living near a point source. The program
default for GSO 1s 1.42. The selection from the Graph Menu allows the user
to change the GSO and cutoff.
The cutoff value applies to both of the probability graphs. It Is drawn
as a vertical dashed line at the default or user-selected value. The
default' value Is 10 ug Pb/di blood. On the bell-shaped graph, the
cutoff value Is the separation point used to calculate the percentage of
children with blood levels above and below the cutoff value. On the
S-shaped graph, the Intersection of the cutoff and the curve corresponds to
the "Above X" on the bell-shaped graph. Because the S-shaped curve 1s a
polynomial approximation of the bell curve, the corresponding values may
differ by several percent.
6.2.5. Set the X-Ax1s Scaling on the Probability Graphs. This option on
the Graph Selection Menu applies to both of the probability graphs and to
the Overlay Plots. It Is used to select the method that determines the
highest numerical value plotted on the x-ax1s of the graph (which corre-
sponds to Blood Lead Concentration). The program default 1s "Automatic
Scaling." With "Automatic Scaling," the program determines the width of the
curve that will be plotted from the current data set and automatically sets
the x-ax1s range for optimal display, with "Constant Scaling," the range .
and upper limit of the x-ax1s are held constant at an upper limit value
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determined by the user. The "Constant Scaling" option 1s helpful for
comparing differences between different data sets and model runs.
PLEASE NOTE: When "Constant Scaling" Is selected end the constant
value differs significantly from the value used by "Automatic
Scaling," the shape of graph may change considerably.
*
6.2.6. Plotting Overlay Files. Overlay Plot Files are used to graph the
results of up to 7 separate model runs on the same graph. They are created
at two different locations In the LEAD program (refer to Figure 0-1 In
Appendix 0). The first location Is vTa the SAVE Menu and the second
location Is via the RANGE Menu. When results are sent to overlay files at
either location, the model run results are placed 1n two separate, but
corresponding files. The files have the same file name but different file
extensions. The file with extension "LAY" contains numeric values of the
geometric mean Pb levels for the seven age groups (e.g., 1-2, 2-3, etc.} and
all 85 monthly Iteration periods for each model run that Is added to the
file. This data Is used to plot the overlay graphs. The file with
extension "TXT" contains the corresponding text summary output for each
model run.
Although an Overlay Plot File can contain results for more than 7 model
runs, only the first 7 model runs 1n an Overlay Plot File are graphed. When
the RANGE Menu 1s used to create Overlay files, the resulting RANGE# files
do not contain more than 7 model runs. However, 1t 1s possible to exceed 7
model runs In Overlay files accessed via the SAVE Menu, where overlay data
are appended one model run at a time. The program shows a warning message
If the 7 run limit has been already been reached. Please note that 1t 1s -
not possible to edit (e.g. delete Individual model runs) Overlay files from
within the LEAD program.
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When one of the two "PLOT" options 1s chosen from the Graph Selection
Menu, a 11st of the available Overlay Plot Files In the current directory/
sub-directory Is displayed. A file Is selected from this list by "high-
lighting" the file name and pressing the Enter key. A maximum of 72 files
1s selectable via this 11st.
Graphs of Overlay Plot Files always use the "Constant" selection for
X-AxIs Scaling. Graphs can be compressed or expanded by changing the X-Ax1s
Limit.
Example Overlay graphs are shown In Figures 18 and 19. The percent data
shown In the upper" right corner of a bell-shaped Overlay graph are the "X
Above" (percent above the cutoff) for each consecutive model run In the
file. For the S-shaped Overlay graphs, the percent data are the cutoff
Intersect values for each consecutive model run. Figures 18 and 19 were
generated from the same Overlay file, which used a soil concentration range
of 0 to 2000 vg/g.
6.3. EXITING A GRAPH
Any of the graphs can be exited by pressing the ESC key, Enter key or
Space bar. A reminder that the ESC key can be used 1s displayed at the
bottom right-hand corner of each graph.
6.4. PRINTING A GRAPH
Any of the graphs may be printed by pressing the F10 key when the graph
1s displayed (a reminder Is displayed at the bottom right-hand corner of
each graph). After the F10 key 1s pressed, the Printer Selection Menu Is
displayed, whlclfc lists the various printers currently supported by the LEAO
program. The Printer Selection Menu Is shown In Figure 20. As needed, new
printer drivers can be added to the program provided that sufficient Infor-
mation on the escape codes recognized by the new printer can be obtained.
2178A
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4
'i
u
a.
>
N
¦
s
¦
o
K
a.
180
90
80
70
'60
50
¦m
30
20
10
t " r
Cutoff: 10.00 us^dL
Run 1:¦ 0.00k
Run 2:* 0.1691
Hurt 3:4 1.7991
Run *:~ 7.86X
Run 5:0 19.38*
Run 6:V 34.33*
Run 7:A 49.78*
HHMtJtii! - LHV
6 S 10 12 14
BLOOD UDW CONCEMTBHT ION
24 to 36 Months
FIGURE 18
Example Overlay Graph - Probability Percent
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cutorr:
t0
.8 usydl.
Run
t:
8.8891
Run
2:
8.1291
Run
3:
i .8391
Run
4:
7.3191
Run
5:
17.84*
Run
8:
32.8891
Hun
7:
47.7491
HHNIiKU - LHV
4 6 8 18 12 1-4
BLOOD LI710 CONCENIDH7ION
24' ta 3S «or»th*
' FIGURE 19
Example Overlay Graph - Probability Density
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8SLZCT PUMTSfti
11 - IBM Oraphlca, Proprlntar; Ipaon LX, MX.. FX (ao—H
2^ — Ukidata^ liut matr l if (tiQ'L. lilM. campdCible
3Jf— ijiiL-rJcti; ot?rxi-^t CITJi (portraitornado JS
M" r . . r.,i—^ T~ T~ ~ ' T" T. I T . „. J . ... 3..'
' ta.scrilt'tr^i Series* ImT(land
5»j— Epsarrt LQ^t EXi (i.cmuit-^4 JXT Scries
Epson: LQX ( portraits node ESflfiS**'*#
T! — Epaarr: canip '- ^ * ' - *-•'
9 —Texas Inst runcrits:-
Aj — ABORT Print" L- ¦ . '-.V
i«i pes model
HOTZi For J-Pin Dot Matrix Prlntarai try #1
For Xpaon Oct Matrix Printerai if il
de«a nee work proparly, try # 5 and
rie« v«ru.
FIGURE 20
Printer Selection Menu
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On computer systems containing a color graphics adaptor card connected to a
monochrome monitor, the graphics screen printing may not work properly. All
printing of graphs within the LEAD program operate by "dumping" the video
screen.
If the LEAD program cannot adequately support your printer, there are
several good commercial software packages that may be used to obtain a
printed copy of the graph. These packages are memory-resident programs that
can be used to dump a graphics screen to a printer during any program. One
reasonably Inexpensive (142) and useful package Is "Raindrop," which Is sold
by Rainbow Technologies, 8106 St. Oavld Ct., Springfield, VA 2?1 53 (713/440-
0064). Another software package that Is easier to use (but slightly more
expensive) 1s "Pizazz Plus," which Is sold by Application Techniques, Inc.,
10 Lomar Park Drive, Pepperell, HA 01463. A very good shareware product
(J10-J20) known as "FASTDUMP" Is available from Systems Technology, Inc.,
13766, So. Hawthorne Blvd., Hawthorne, CA 90250.
PLEASE NOTE: If the wrong printer has been selected and printing
has started, press the ESC key. It may take several seconds for
printing to terminate. If It doesn't, turn off the printer.
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7. SAVING PROGRAM PARAMETERS AND RESULTS
The LEAD Program performs two different types of "save" functions. The
first function- saves the results of a model run to output files or to a
printer. The second function saves data Input values (program parameters)
to a file that can be reloaded for later use. These functions are described
below.
7.1. RESULTS OF A MODEL RUN
The text results of a model run can be saved by selecting "SAVE Results"
from the horizontal menu that appears at the bottom of the summary output
screen. An example summary output screen Is shown In Figure 11. After
selecting "SAVE Results", the SAVE Menu appears and contains the following
options: (1) Send Current Result to Printer, (2) Send Current Results to
Text File (RESULTS.TXT), and (3) Send Current Results to Overlay Plot File.
Option 2 sends the text summary of the model run to a file named
RESULTS.TXT; this file cannot be renamed from within the LEAO program.
Option 1 sends the exact same text summary to a printer. If the file
RESULTS.TXT does not already exist. It Is created. Every time that results
are sent to RESULTS.TXT, the results are appended to the end of the current
contents of the file. If you wish to rename the file after sending a
specific series of results to It, you must exit the LEAO program. The text
summary Includes the output as shown on tne summary output screen and most
of the data parameters used to compute tne summary results. The text
summary files (RESULTS.TXT and the TXT Overlay Mies) are written In common
ASCII (text) format that can be loaded into *ost word processing programs .
such as Word Perfect, Microsoft Word, and WordStar.
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Option 3 of the SAVE Menu sends the results of the model to two
separate, but corresponding Overlay files. The text summary Is sent to a
file with' a file extension of ".TXT". The data necessary to plot the
results on a graph are sent to a file with a file extension of ".LAY".
Before the results are sent to either Overlay file, the user must select the
file name. If the file name selected already exists, the appropriate
results are appended to both Overlay files. The Overlay Plot Files that are
created can be retrieved by the Graph Selection Menu for graphing the
results of the first 7 model runs 1n the .file on the same graph.
The same types of Overlay files can be created by using the RANGE Menu
(see Section 5.5.). However, the file names are automatically assigned when
the RANGE Menu Is used to create Overlay files.
7.2. SAVING PROGRAM PARAMETERS
Program parameters can be saved to a file by selecting "SAVE Program
Parameters" from the Main Menu. Program parameters are ajj. of the variables
that the user 1s allowed to enter, access and change. After "SAVE Program
Parameters" has been selected from the Main Menu, a Save Screen appears,
which Is Illustrated In Figure 21. This screen allows the user to enter the
name of the file to which the parameters will be saved. The user cannot,
however, designate the file extension; it Is always ".SV3." If the user
simply presses the Enter key at a blank line, the parameters are saved to
BACKUP.SV3.
Any file with the *.SV3" extension can be loaded Into the LEAD program
at any time by selecting "LOAD Program Parameters* from the Main Menu.
Saving program parameters can be a tin*-taking feature for complex data
sets. The user does not have to remember each parameter and then go to the
trouble of entering 1t.
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DATA SAVB-
Prograa piruieiri will b« aavod to * usar opacified file.
Unlaaa rttiMd. eh« data will b« aavad Co £11* > BACKUP.SV3
Hnter Name: ot Pile- WITHOUT" extension:
l^.i|:.^.i^t:f^.:;:.ytin44irt:|,,4ii4.RT.I'|[.!:. ¦ -¦
NOTSi (1) An axtanaioa of ".SV3" la appaodad to th« £11* qui.
(2) Bnterin? a blank 11a* eauiai the default file oaa* Co be uaed.
(3) Praia BSC Co BZZT Save with NO saving Co a file II
FIGURE 21
Save Screen for Program Parameters
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Versions 0.1 and 0.2 of the LEAO program used the file extension *.SAV
for saving the program parameters. This has* been changed to ".SV3" In
subsequent versions since many more parameters are being saved 1n these
versions. It makes sure that a "*.SAV" file cannot be loaded Into the
current LEAO program.
PLEASE NOTE: The bloklnetlc residence times and allometrlc scaling factors
are not saved.
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8. LOADING PROGRAM PARAMETERS
Program parameters that have been saved to a file using the SAVE
selection from the Main Menu can be loaded Into the LEAD program using the
LOAD selection from the Main Menu. When LOAD 1s selected, a 11st of files
In the current subdirectory with the ".SV3" file extension 1s displayed.
Each file Is numbered consecutively by alphabet. To load a file, simply
enter the number of the file as 1t 1s displayed 1n t.he list and press the
Enter key.
As soon as the file Is loaded, the values of all parameters In the file
take effect. If a saved file has become garbled or truncated for some
reason, the LEAD program usually detects the error and Informs the user. If
a warning message appears, 1t 1s unsafe to use the current set of param-
eters. Either exit the program and re-start or load the DEFAULT.SV3 file.
A saved file must exist 1n the current subdirectory (the subdirectory
from which LEAD5 was started) to be listed by the LOAD function.
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9. VALUES of DEFAULT PARAMETERS-
The values of various default parameters that can be changed by the user
are listed below. Oefault values for 61 tract absorption and bloklnetlc
residence times are listed 1n Appendix A and Appendix B.
A1r Data: Air Concentration: 0.20 ug Pb/ro"
Lung Absorption: 32.OX
Vary Air Cone by Year: NO
Ventilation Rate
Age 0-1: 2.0 ni'/day
1-2: 3.0 MVday
2-3: 5.0 mVday
3-4: 5.0 mVday
4-5: 5.0 mVday
5-6: 7.0 mVday
6-7: 7.0 mVday
Water Data: Water Concentration: 4.00 »g/i
Use Alternate Values: NO
Water Consumption
Age 0-1:
0.20 t/day
1-2:
0.50 l/day
2-3:
0.52 l/day
3-4:
0.53 l/day
4-5:
0.55 l/day
5-6:
0.58 l/day
6-7:
0.59 l/day
Use Alternate
Values: NO
Diet Intake
Age 0-1:
5.88 ug Pb/day
1-2:
5.92 ug Pb/day
2-3:
6.79 Pb/day
3-4:
6.57 u
-------
Multiple Source Analysis:
Son Contribution to House
Lead Oust (conversion factor); 0.28
Air Contribution to House
Lead Dust (conversion factor): TOO
Use Alternate Dust Sources: NO
Paint Data: Amount Ingested Dally: 0.0 »g Pb/day (all ages)
Maternal Data: Infant Model:
Mother's Hood lead Cone at 81rth: 7.50 »g Pb/l
Fetal Model:
Air:
Cone Outdoors:
Cone Indoors:
Cone at Work:
Vent Rate Outdoors:
Vent Rate Indoors:
Vent Rate at Work:
Vent Rate Sleeping:
0.200 jif Pb/iB"
0.060 jig Pb/m3
0.060 »g Pb/m®
1.0 mVhour
1.0 m'/hour
1.0 mVhour
1.0 mVhour
Water:
Cone at Home:
Cone at Work:
Consumption at Home:
Consumption at Work:
9.00 yg Pb/t
9.00 Mg Pb/l
2.0 i/day
2.0 i/day
Diet:
Consumption:
Cone:
1000.0 g food/day
0.10 wg Pb/g food
Dust;
House Consumption:
House Cone:
2nd Occupation Exposure:
Other Dust Intake:
0.020 g dust/day
200.0 wg Pb/g dust
0.00 jig Pb/day
0.00 yg Pb/day
Absorption:
Air:
Diet:
Water:
Dust:
Sraph Values;
GSD:
Cutoff:
1.42
10 jig Pb/dl
SO.OX (In lungs)
10.0% {1n GI tract)
10.0% (In GI tract)
10.0% (in GI tract)
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10. HOU THE UPTAKE/BIOKINETIC MODEL ESTIMATES BLOOD LEAD LEVELS
This section Is a brief technical description of the method used by the
!Jptake/81ok1net1c Model to estimate blood lead levels. The Model contains
two separate sections: (1) the Uptake section estimates the monthly uptake
of lead from diet, air, soil/dust, water and paint, and (2) the 81ok1net1£
section uses the monthly lead uptake to estimate the blood lead levels on a
monthly basis. Final results are reported on a yearly basis.
10.1. UPTAKE SECTION OF THE MODEL
The Uptake section of the Model uses the user-entered values or default
values to estimate a dally Intake of lead from air, diet, water, soil/dust,
and paint. It Is Important to understand that "Intake" of lead Is different
from "uptake" of lead. Intake of lead 1s the amount of lead brought Into
the body by the various exposure routes. Uptake of lead 1s the amount of
lead absorbed Into the body's blood-plasma system. Uptake Is calculated
from the Intake by the following general formula:
UPTAKE - INTAKE x ABSORPTION factor
For each of the exposure routes, the following formulas are used:
UPAIR » INAIR x ABSAIR
UPDIET » INDIET x ABSDIET
UPDUST . INOUST x ABSDUST
UPSOIL . INSOIL x ABSSOIL
UPWATER . INWATER x ABSWATER
UPPAINT . INPAINT x A8SPAINT
The absorption factors are determined by either the Linear Absorption
Method or the Nonlinear Active-Passive Method (see Section 4.2.). The
formulas and defaults used to estimate the absorption factors for both
methods are listed In Appendix A. The Intakes entered by the user are on a
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dally basis. Multiplying the dally Intakes by 30 yields* the estimated
monthly intake#*.- The total monthly uptake Is therefore:
UPTAKE » UPAIR > UPDIET ~ UPDUST ~ UPSOIL ~ UPWATER ~ UPPAINT
The monthly uptakes are then passed to the Bloklnetlc section of the
Model for estimation of blood lead levels.
Information pertaining to the Intake values for various exposure routes
are discussed below.
10.1.1. A1r Intake. The dally Intake of lead resulting from air exposure
1s calculated using a time-weighted average (TWA) method as follows (the
asterisk symbolizes multiplication):
Intake (yg Pb/day) - ((T0*C0 ~ TI*CI) / 24) * Vent Rate (mJ air/day)
where TO and TI are the time outdoors and Indoors (hour) and CO and CI are
the concentrations outdoors and indoors (wg Pb/m3).
10.1.2. Water Intake. The dally drinking water Intake of lead 1s
calculated by multiplying the water concentration (wg Pb/i) by the dally
consumption rate (t/day). Alternate factors (which Include 'first-draw'
and 'fountain' water) are Included In the formula 1f the user specifies
their use. If specified, the formula for drinking water Intake becomes:
INWATER * water consumption x ((flushed concxflushed fraction) *
(first draw concxflrst draw fraction) +
(fountain concxfountaln fraction))
10.1.3. Soil and Oust Intake. The lead concentrations of soil are
directly entered by the user. No formulas or equations are used by LEAOS to
calculate a default soil concentration. This differs from previous versions
of the LEAO program where soil and dust concentrations were calculated from
the air concentrations using regression equations. These regression
equations are no longer used.
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For each age group, the soil Intake Is calculated by multiplying the
soil concentration by the amount of solHdust Ingested. This value 1s then
multiplied by the fraction of the solHdust amount that Is son. The
program uses defaults of 4554 soil to 55% dust.
If the user selects a constant dust concentration or variable dust
concentrations, the dust Intake Is calculated exactly the same as for soil.
Oust differs from soil 1n that 1t has the added option of using Multiple
Source Analysis to determine dust Intake. Multiple Source Analysis sums the
dust Intake from three primary sources: (1) contribution to house dust from
soil dust, (2) contribution to house dust from airborne fallout, and
(3) contribution from alternate dust sources. The alternate dust sources
Include lead 1n house dust from paint sources and lead exposures at occupa-
tional settings, second homes, daycare and schools. If the user does not
use alternate dust sources, the dust Intake Is calculated only from contri-
butions (1) and (2) above.
10.2. BIOKINETIC SECTION OF THE MODEL
The B1ok1net1c section of the Model uses the total lead uptake for each
month to calculate the amount of lead that occurs In a number of body
compartments for each month. The body compartments Include the plasma & ECF
(extra cellular fluid) pool, the RBC (red blood cell) pool, the kidney, the
liver, trabecular bone, cortical bone, and other soft tissue pools.
The first consideration Is the amount of lead occurring 1n these
compartments at time zero (birth). This 1s determined by the Maternal
contribution. In this version of the LEAO program, the user 1s able to
select either the Infant Method or the Fetal Method to estimate the Maternal
contribution (see Section 4.3.). Currently, the Infant Method uses default
values to determine the compartment lead levels for a newborn. For example.
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the blood lead level of a newborn 1s estimated to be 85% of the Maternal
blood level (current default for Maternal level 1s 7.50 yg Pb/di). The
newborn organ lead levels are then estimated from the blood lead level. The
Fetal Method 1s a self-contained model that Iteratlvely determines lead
levels 1n a fetus during pregnancy.
Although complicated mathematically, the B1ok1net1c Model 1s relatively
simple 1n concept. In general, lead enters the body through Uptake, lead
leaves the body through urine and feces* and lead Is exchanged among body
compartments. The Uptake section of the Model has already been discussed.
The Important factor of the B oklnetlc Model 1s the transition of lead among
body compartments (which Incluaes Us removal by urine and feces via transi-
tion to kidney and liver). The transition times (residence times) are the
rate determining factors that determine the rate at which lead enters,
leaves, and remains 1n each compartment during each monthly Iteration. The
formulas used to estimate the transition times are listed In Appendix B.
The transition times are calculated on a monthly basis and depend upon the
body weight and the weight of the organs at that monthly age.
Blood lead levels Increase with Increases of lead uptake. If the lead
uptake Is Increased to excessively high levels (several hundred yg Pb/day
or more), the lead concentration 1n the red blood cells begin to equal or
exceed the saturation concentration of the red blood cells. When the LEAD
program recognizes this condition, the Bloklnetlc Model Iterations are
terminated arnica warning Is displayed. It Is still possible, however, to
get very close to the saturation concentration without a warning being
Issued. In some of these situations, unreallstlcally high blood levels are
be generated.
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11. REFERENCES
Azar, A., R.D« Snee and K. Hablbl. 1975. An epidemiologic approach to
community air lead exposure using personal air samplers. In: Lead.
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Baker, E.L., Jr., C.G. Hayes, P.J. landrlgan et al. 1977. A nationwide
survey of heavy metal absorption In children living near primary copper,
lead and zinc smelters. Am. J. Epidemiol. 106: 261-273.
Barltrop, D. 1966. The prevalence of pica. Am. J. DIs. Child. 112:
116-123.
Barltrop, 0. 1972. Children and environmental lead. In.: Conf. Proc.: Lead
In the Environment. Institute of Petroleum* London, United Kingdom,
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Barltrop, D. and F. Meek. 1979. Effects of particle size and lead absorp-
tion from gut. Arch. Environ. Health. 34: 280-285.
Barry, P.S.I. 1975. A comparison of concentrations of lead 1n human
tissues. Br. J. Ind. Med. 32: 119-139.
Beck, 8.0. and H.J. Steele. 1990. Evaluation of soil Ingestion in
/
children. Unpublished report.
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Bllllck. I.H., A.S. Curran and D.R. Shier. 1979. Analysis of pediatric
blood lead lev«U In Mew York City for 1970-1976. Environ. Health Perspect.
31: 183-190. '
Binder, S., 0. Sokal and 0. Maugham. 1986. Estimating soil Ingestion: The
use of tracer elements In estimating the amount of soil Ingestion by young
children. Arch. Environ. Health. 41: 341-345.
Calabrese, E.J., H. Pastldes, R. Barnes et al. 1989. How much soil do
young children Ingest: An epidemiological study. Reg. Toxicol. Pharmacol.
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CDC (Centers for Disease Control). 1983. East Helena, Montana Child Lead
Study, Sumner, 1983. Lewis and Clark Health Department, Montana Department
of Health and Environmental Science, U.S. Department of Health and Human
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Chamberlain, A.C. and M.J. Heard. 1981. Lead tracers and lead balances.
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Chamberlain, A.C., M.J. Heard, P. Little, 0. Newton, A.-C. Wells and R.D.
Wlffen. 1978. Investigations Into lead from motor vehicles. United
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Chan, T.l. and M. Uppmann. 1980. Experimental measurements and empirical
modeling of the regional deposition of Inhaled particles In humans. Am.
Ind. Hyg. Assoc. J. 47: 399-408.
Chaney, R.L., H.W. Hlelke and S.8. Sterrett. 1988. Spec1at1on, mobility
and bioavailability of soil lead. Environ. Geochem. Health. (In press)
Chaney R.L.. H.W. Mlelke and S.B. Sterrett. 1989. Spec1at1on, mobility
and bioavailability of lead 1n soil. Environ. Goechem. Health. 11: 105-129.
Clausing, P., 8. Brunekreef and J.H. van W1Jen. 1987. A method for
estimating soil Ingestion by children. Int. Arch. Occup. Environ. Health.
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Cohen, J. 1987. Respiratory deposition and absorption of lead particles.
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U.S. EPA, Office of A1r Quality Planning and Standards, Ambient Standards
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Cohen, J. 1988a. Oletary lead estimates for case study exposure analyses.
Memorandum to Files, U.S. EPA, Office of Air Quality Planning and Standards,
Ambient Standards Branch, Research Triangle Park, NC. May 16, 1988.
Cohen, J. 1988b. Revisions to dietary lead estimates for case-study
exposure analyses. Memorandum to Files, U.S. EPA, Office of Air Quality
Planning and Standards, Ambient Standards 8ranch, Research Triangle Park,
NC. September 9, 1988.
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Cohen, A.F. and 8.1. Cohen. 1980. Protection from being Indoors against
Inhalation of suspended particulate matter of outdoor origin. Atmos.
Environ. 14: 184-184.
Dacre, 3.C. and G.L. TerHaar. 1977. Lead levels 1n tissues from rats fed
soil containing lead. Arch. Environ. Contam. Toxicol. 6: 111-119.
Davidson, C.I. and J.F. Osborn. 1984. The sizes of airborne trace metal-
containing particles. In: Toxic Metals In the A1r, J.U. Nrlagu and C.I.
Davidson, Ed. John Wiley and Sons, Inc., New York, NY.
Davles, 8.E., P.C. Elwood, J. Gallacher and R.C. Glnnever. 1985. The
relationships between heavy metals 1n garden soils and house dusts 1n an old
lead mining area of North Wales, Great Britain. Environ. Pollut. (Series
B). 9: 255-266.
Davis, S., P. Waller, R. Buschbom. J. Ballou and P. White. 1990. Quantita-
tive estimates of soil Ingestion In normal children between the ages of 2
and 7 years: Population-based estimates using aluminum, silicon, and
titanium as soil tracer elements. Arch. Environ. Health. (In press)
Day, J.P., J.E. Fergusson and T.M. Chee. 1979. Solubility and potential
toxicity of lead urban street dust. Bull. Environ. Contam. Toxicol. 23:
497-502.
Duggan, N.J. and S. Williams. 1977. Lead-1n-dust In city streets. Scl.
Total Environ. 7: 91-97.
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Gross, S.B., E.A. Sltzer, D.W. Yeager and R.A. Kehoe. 1975. lead- In human
tissue. Toxicol. Appl. Pharmacol. 32: 638-651.
Hardy, H.L., R.I. Chamberlain, C.C. Maloof, G.W. Boylen, Jr. and M.C.
Howell. 1971. Lead as an environmental poison. Clin. Pharmacol. Ther.
12: 982-1002.
Harrison, R.M. 1979. Toxic metals In street and household dusts. Scl.
Total Environ. 11: 89-97.
Hartwell, T.D., R.W. Handy, B.S. Harris, S.R. Williams and S.H. Gehlbach.
1983. Heavy metal exposure In populations living around zinc and copper
smelters. Arch. Environ. Health. 38: 284-295.
Hawley, J.K. 1985. Assessment of health risk from exposure to contaminated
soil. Risk Anal. 5: 289-302.
Healy, M., P. Morrison, M. Aslam, S. Davis and C. Wilson. 1982. Lead
sulfide and traditional preparation: Routes for ingestion and solubility and
reactions 1n gastric fluid. J. Clin. Hosp. Pharmacol. 7: 169-173.
Hoffman, W.F., G. Stelnhauser and E. Pohl. 1979 Dose calculations for the
respiratory tract fronr Inhaled natural rad1oact'*e tucleldes as a function
of age. I. Compartmental deposition, retention, jno reciting dose. Health
Physics. 37: 517-532.
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Hunt2lcker, J.J., S.K. Frledlander and C.I. Oavldson. 1975. Material
balance for automobile-emitted exhaust lead In Los Angeles basin. Environ.
%t*i. . V. VA-W.
James, A.C. 1978. Lung deposition of sub-micron aerosols calculated as a
function of age and breathing rate. In: National Radiological Protection
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tion Board, Harwell, United Kingdom, p. 71-75.
Kehoe, R.A. 1961a. The metabolism of lead In man 1n health and disease;
The normal metabolism of lead. (The Harben Lectures, 1960). J.R. Inst.
Public Hyg. 24: 81-97.
Kehoe, R.A. 1961b. The metabolism of lead In man 1n health and disease;
The normal metabolism of lead. (The Harben Lectures, 1960). J.R. Inst.
Public Hyg. 24: 129-143.
Kehoe, R.A. 1961c. The metabolism of lead In man 1n health and disease;
the normal metabolism of lead. (The Harben Lectures, 1960). J.R. Inst.
Public Hyg. 24: 177-203.
Koontz, M.D. and J.P. Robinson. 1982. Population activity patterns - St.
Louis study. Environ. Monlt. Assess. ?: 197-?l?.
LePow, M.L., L. Bruckman, H. Gillette, S "jrkowltz, R. Rob 1 no and J.
Kaplsh. 1975. Investigations Into sources of lead In the environment of
urban children. Environ. Res. 10: 415-426
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«
Marcus. A.H. 1990. Biological basis for the uptake/b1ok1net1c model.
Unpublished report.
Millar, F.J., T.8. Martonen, M.G. Menache, D.M. Spektor and M. llppmann.
1986. Influence of breathing mode and activity level on the regional
deposition of Inhaled particles and Implications for regulatory standards.
Cambridge, United Kingdom: Inhaled Particle IV.
MllUcan, F.K., E.M. Layman, R.S. Lourle, L.Y. Takahashi and C.C. Dublin.
1962. The prevalence of Ingestion and mouthing of nonedlble substances by
children. Clin. Proc. Child. Hosp. 18: 207-214.
Morrow, P.E., H. Belter, F. Amato and F.R. G1bb. 1980. Pulmonary retention
of lead; An experimental study 1n man. Environ. Res. 21: 373-384.
Pennington, J.A.T. 1983. Revision of the total diet study food 11st and
diets. J. Am. Diet. Assoc. 82: 166-173.
Phalen, R.F., N.J. Oldham, C.8. Beaucage, T.T. Crocker and J.D. Mortensen.
1985. Postnatal enlargement of human tracheobronchial airways and Implica-
tions for particle deposition. Anat. Rec. 212: 368-380.
Pope, A. 1985. Development of activity patterns for population exposure to
ozone. Prepared by PEI Associates, Inc., Durham, NC, for Office of Air
Quality Planning and Standards, August 23, 1985.
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RablnowHz, H.B., G.U. Wether 111 and J.D. Kopple. 1977. Magnitude of lead
Intake from respiration by normal man. J. Lab. Clin. Med. 90: 238-248.
Roels, H.A., J-P. Buchet, R. Lauwerys et al. 1980. Exposure to lead by the
oral and pulmonary routes of children living In the vicinity of a primary
lead smelter. Environ. Res. 22: 81-94.
Rubinstein, E.A., G.A. Comstock and J.P. Murray. 1972. Television and
Social Behavior, Volume ,IV. National Institute of Mental Health, U.S.
Department of Health, Education and Welfare, Rockvllle, MD.
Schwartz, 3. 1985. Modeling the blood lead distribution In children.
Office of Policy Analysis, U.S. EPA, Washington, DC. Memorandum to J.
Cohen, Office of Air Quality Planning and Standards, U.S. EPA, Research
Triangle Park, NC.
Schwartz, 3., C. Angle and J. Pitcher. 1986. Relationship between child-
hood blood lead levels and stature. Pediatrics. 77: 281-288.
Sedman, R.M. 1989. The development of applied action levels for soil
contact: A scenario for the exposure of humans to soil 1n a residential
setting. Environ. Health Perspect. 79: 291-331.
Sledge, D.J. 1987. Size distributions of lead particles at major lead
stationary sources: Source sampling and ambient air monitoring. Memorandum
to John Haines, Chief, ASS, Section B, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC,
September 23, 1987.
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Steele, H.J., 8.0. Beck, B.l. Murphy and H.S. Strauss. 1989. Assessing the
contribution for lead In mining wastes to blood lead. Reg. Toxicol.
Pharmacol. (In press)
Suter, L.E. 1979. Travel to school. U.S. Bureau of Census, Series P-20,
No. 392.
Tepper, L.8. and L.S. Levin. 1975. A survey of air and population lead
levels 1n selected American communities. In: Lead, T.B. Griffin and J.H.
Knelson, Ed. Academic Press, New York, NY. p. 152-195. (Environmental
Quality and Safety: Suppl. v. 2, F. Coulston and F. Korte, Ed.)
Ter Haar, G. and R. Aronow. 1974. New Information on lead In dirt and dust
as related to the childhood lead problem. Environ. Health Perspect. 7:
83-89.
U.S. EPA. 1986. A1r Quality Criteria for Lead. June, 1986 and Addendum,
September, 1986. Office of Research and Development, Office of Health and
Environmental Assessment, Environmental Criteria and Assessment Office,
Research Triangle Park, NC. EPA 600/8-83-028AF, BF, CF, OF. EPA/602/8-
83/028A.
U.S. EPA. 198®. Reference Dose (RfO): Description and Use In Health Risk
Assessments. Online. Appendix A: Integrated Risk Information System
Supportive Documentation. Office of Health and Environmental Assessment,
Environmental Criteria and Assessment Office, Cincinnati, OH.
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U.S. EPA. 1989a. Review of the National Ambient A1r Quality Standards for
Lead: Exposure Analysis Methodology and Validation. Final Draft. Office of
Air Quality ,J»T4nn1ng and Standards, Air Quality Management Division,
Research Triangle Park, NC.
U.S. EPA. 1989b. Exposure Factors Handbook. Office of Health and Environ-
mental Assessment, Washington, DC. EPA/600/8-89/043.
Xu, G.B. and C.P. Yu. 1986. Effects of age on deposition of Inhaled
aerosols 1n the human lung. Aerosol. Sc1. Technol. 5: 349-357.
Yankel, A.J., I.H. Van Llndern and D.S. Walter. 1977. The Silver Valley
lead study: The relationship of childhood lead poisoning and environmental
exposure. J. A1r Pollut. Control Assoc. 27: 763-767.
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APPENDIX A „
CALCULATION OF ABSORPTION FACTORS FOR THE UPTAKE MOOEL
Nonlinear Active-Passive Absorption Method:
Definitions of the variable names used by the Nonlinear Active-Passive
Absorption Method are listed below. Program default values are given for
the variables that have default values.
A8S0IET Total absorption coefficient for diet
ABSVIATER Total absorption coefficient for water
ABSSOIL Total absorption coefficient for soil
ABSDUST Total absorption coefficient for dust
ABSPAINT Total absorption coefficient for paint
ABDIETP « 0.15 Passive absorption coefficient for diet
A8WATERP * 0.15 Passive absorption coefficient for water
ABSOILP » 0.15 Passive absorption coefficient for soil
ABOUSTP » 0.15 Passive absorption coefficient for dust
ABPAINTP * 0.15 Passive absorption coefficient for paint
A80IETA * 0.35 Active absorption coefficient for diet
ABWATERA » 0.35 Active absorption coefficient for water
ABS0ILA ¦ 0.15 Active absorption coefficient for soil
ABDUSTA - 0.15 Active absorption coefficient for dust
ABPAINTA » 0.15 Active absorption coefficient for paint
ABC0IET - 100,000 Half-saturation conc. for active absorption diet Ug/i)
ABCWATER » 100,000 Half-saturation conc. for active absorption water (vg/t)
ABCS0IL « 100,000 Half-saturation conc. for active absorption soil Ug/i)
ABCOUST « 100,000 Half-saturation conc. for active absorption dust (»g/i)
ABCPAINT » 100,000 Half-saturation conc. for active absorption paint (yg/l)
PB6DIET Average conc. of Pb 1n gut from diet
PBGWATER Average conc. of Pb 1n gut from water
PBGSOIL Average conc. of Pb In gut from soil
PBGDUST Average conc. of Pb In gut from dust
P8GPAINT Average conc. of Pb In gut from paint
VOLGUT Volume of the gut
TGOIET - 1.00 Residence time In gut of dietary lead (days)
TGWATER » 1.00 Residence time 1n gut of water lead (days)
TGSOIL ¦ 1.00 Residence time In gut of soil lead (days)
TGDUST » 1.00 Residence time 1n gut of dust lead (days)
TGPAINT * 1.00 Residence time In gut of paint lead (days)
The total absorption factors, which are multiplied by the INTAKES from
the various exposure routes, are calculated by the following equations:
ABSOIET . ABDIETP ~ (AB0IETA/(1~{PBGDIET/ABCOIET)*))
ABSHATER « A8WATERP * (ABUATERA/(1~(PBGWATER/ABCWATER)'))
ABSSOIL - ABSOILP * (ABSOILA/(1>(PBGSOIL/ABCSOIL)»))
ABSOUST « ABOUSTP ~ {AB0USTA/(1MPBG0UST/A3C0UST)»))
ABSPAINT < ABPAINTP > (AflPAINTA/(1~(PBGPAINT/ABCPAINT)'))
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The PBG variables used above are calculated by the following equations:
PBGDIET » INDIET x T6DIET / VOLGUT
PBGWATER « INMATER x TGWATER / VOLGUT
PBGSOIL ¦ INSOIL x TGSOIL / VOLGUT
PBGDUST ¦ INDUST x TGDUST / VOLGUT
PBGPAINT • INPAINT x TGPAINT / VOLGUT
It should be remembered that each of the equations listed above 1s calcu-
lated on a monthly basis starting at time zero (birth) and continuing until
age 7. The default values can be accessed from the Diet, Water, Soil/Oust
and Paint Data Entry Screens by selecting YES at the GI tract absorption
field. DO NOT change any of the default values unless you completely
understand their meaning! Their access has been Included for expert users
only.
Linear Absorption Method:
The default values for the Linear Absorption Method are as follows:
DIET: 50% for all ages.
WATER: 50% for all ages.
SOIL: 30% for all ages.
DUST: 30% for all ages.
PAINT: 30% for all ages.
These defaults should be changed only by knowledgeable users.
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APPENOIX B
CALCULATION OF TRANSITION TIMES IN THE BIOKINETIC MODEL
(Residence Time Equations)
TPLRBC Average transition
TRBCPL Average transition
TPLLIV Average transition
TLIVPL Average transition
TPLKI0 Average transition
TKIDPL Average transition
TPLOTH Average transition
TOTHPL Average transition
TPLTRAB Average transition
TTRABPL Average transition
TPLCORT Average transition
TCORTPL Average transition
TPLUR Average transition
TLIVFEC Average transition
TOTHQUT Average transition
WTBOOY 8ody weight
WTIIVER Height of the liver
WTKIONEY Height of the kidney
HTOTHER Height of the other soft tissue
HTTRAB Height of the trabecular bone
WTCORT Height of the cortical bone
ALSCAL-0.33 Allometrlc scaling exponent
The equations for each transition time (residence time) are calculated
on a monthly basis and are listed below (the asterisk Indicates multiplica-
tion). The first number 1n each equation 1s the residence time coefficient
that can be accessed and changed during the LEAD program. The allometrlc
scaling exponent can also be accessed and changed. These values are
accessed from the "RUN Menu* by selecting "C - Change B1 ok 1 net 1c default
parameters." The residence time values are similar In concept to half-life
values. DO NOT change any of the coefficients or exponents unless you
completely understand their use and effect on the Model. Their access has
been Included for expert users, only.
TPLRBC . 0.172 / 30
TRBCPL -2.16/30
TPLLIV - (1.20 * (HTBOOY/3.7)ALSCAL* / 30
TLIVPL - (120 * (WTLIVER/0.171ALSCAC) / 30
TPLKID - (13.6 * (HTB00Y/3.7)ALSCALi / 3Q
TKIDPL - (60 *
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APPENOIX C
SELECTION OF DEFAULT VALUES OF MODEL PARAMETERS
This section of the Users Guide provides details on the rationale for
the selection of default values used 1n the Lead Uptake/81ok1net1c Model and
guidance for the selection of Input values for the primary data screens used
In the Uptake/B1ok1net1c Model software. A more comprehensive discussion of
these subjects 1s presented In the Technical Support Document on Lead.
Oefault values for all parameters (numbering several hundred) In the
Uptake/B1ok1net1c Model have been Incorporated Into the software package to
enable the user to run the model In the absence of site-specific data. To
the extent possible, these default values reflect the current scientific
consensus of the central tendency for the value of each parameter 1n the
U.S. population and are not meant to be applicable to* all exposure
scenarios. The default values for the various parameters are to be used 1n
the absence of empirical or theoretical support for other values that are
more applicable to a given site or exposure scenario (hence the designation
"default"). The Uptake/81ok1net1c Model software has been designed to allow
the user to modify values of primary parameters (those not derived from
other parameters) as required to accommodate new or site-specif 1c quantita-
tive Information regarding each parameters.
C.l. LEAD UPTAKE FROM INHALED LEAD
Lead uptake, from Inhalation of airborne lead (U^f wg/day) 1s calcu-
lated as follows:
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where IA Is the Intake of airborne lead by the respiratory tract
(yg/day) and OA Is the product of the respiratory deposition and absorp-
tion fractions. The primary data entry screen allows the user to Input data
on outdoor and Indoor air lead levels and values for time spent outdoors,
ventilation rates and absorption parameters as described below.
C.1.1. Outdoor A1r Lead. The user can accept the default value of 0.20
yg/m> or Input values. Sources of data on which to derive Input values
can Include site monitoring or predictions based on air dispersion models
(U.S. EPA, 1986).
Levels of lead In air will vary depending on the source and distance
from the source. Whereas, at one time, automobile exhaust accounted for
-90% of all air emissions 1n the United States, the recent phase-down of
lead content of gasoline and reductions 1n usage of leaded gasoline have and
will continue to substantially decrease the contribution of automobile
exhaust to air lead (U.S. EPA, 1986). Lead 1n automobile exhaust originates
from the combustion of gasoline containing organic lead additives, primarily
tetraethyl and tetramethyl lead. Lead 1s emitted from vehicles primarily as
particles of Inorganic lead, with a small percentage as volatile lead
alkyls. Of the automotive lead emissions deposited, >50% 1s within less
than a few kilometers of roadways, whereas smaller particles can travel for
thousands of kilometers (Huntzlcker et ai . 1975; U.S. EPA, 1986).
Sources of Industrial emissions include fugitive emissions from lead
mining, primary and secondary lead smelting, battery plants and combustion
of oil, coal and municipal waste (U.S. 1986). Dispersal of particles
released from such processes depends on rwteoroioglcal variables. Including
wind speed and direction and precipitation. The most abundant deposition
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generally occurs within 10 km around emission sources, which can result 1n
high local concentrations of lead In dust, soil and ambient water (Yanks! et
al., 1977).
C.1.2. Indoor Air Lead. The user Is given the option of either entering
a value for Indoor air lead or estimating Indoor air lead from outdoor air
lead. When the second option 1s selected. Indoor air lead 1s calculated as
follows:
[PbJA1 - 0.30 ; [Pb]Ao
where [Pb3^^ and fPb3^o are the concentrations of lead 1n Indoor and
outdoor air, respectively, and 0.30 Is an empirically derived conversion
factor.
Transport of lead from outdoors to Indoors accounts for virtually all
Indoor air lead Inmost modern buildings. Outdoor air lead enters buildings
through windows, doors, walls and air vents. Because the transport
processes are complex, relationships between outdoor and Indoor air lead
concentrations can be expected to vary from site to site. Factors that can
be expected to affect Indoor/outdoor ratios at a given site Include the
proximity to emission sources, which determines the size of outdoor air lead
partl.cles, the permeability of entrance pathways (e.g., windows, doors,
walls) to lead, airflow patterns 1n and out of the building and meteorolog-
ical conditions.
U.S. EPA (1986) summarized data on '-moor and outdoor air lead levels
and concluded that, at most sites, outdoor concentrations exceeded Indoor
concentrations. Indoor/outdoor concentration ratios ranged from 0.3-0.8,
with values 1n the lower end of the range near point sources, where lead
particles are larger (Cohen and Cohen, 1980)
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C.I.3. Time Spent Outdoors. An estimate of dally exposure to lead must
be a time-weighted average of exposure to outdoor and Indoor lead; there-
fore, Information on the relative amount of time spent 1n each environment
1s required to estimate average exposure levels. Time spent outdoors varies
extensively with age, season, geographical location and a variety of
cultural and behavioral Influences. The following ige-speclflc estimated
ranges for hours spent outdoors were derived frora a literature review (U.S.
EPA, 1989a) summarized 1n Pope (1985) and reflect data reported 1n various
studies (Hoffman et al.t 1979; Rubinstein et al., 1972; Suter, 1979; Koontz
and Robinson, 1982):
Age (years): 0-1 1-2 2-3 3-7
Time Outdoors (hours/day): 1-2 1-3 2-4 2-5
Based on Information on Indoor and outdoor air lead concentrations and the
average time spent outdoors and Indoors, an estimate of the time-weighted
average exposure concentration (fbly^) can be calculated as follows:
[Pb]TWA » {([Pb]A
-------
C.I.5. Respiratory Deposition and Absorption of Inhaled Lead. The entry
of Inhaled lead Into the systemic circulation Involves the processes of
deposition and absorption. Amounts and patterns of deposition of particu-
late aerosols* tn the respiratory tract are affected by the size of the
Inhaled particles, age-related factors that determine breathing patterns
(e.g., nose breathing vs. mouth breathing), airway geometry and alrstream
velocity within the respiratory tract. In general, large particles (>2.5
vm) deposit' 1n the nasopharyngeal regions of the human respiratory tract
where high alrstream velocities and airway geometry facilitate Inertlal
Impaction (Chamberlain et al., 1978; Chan and Llppmann, 1980). In the
tracheobronchial and alveolar regions, where alrstream velocities are lower,
processes such as sedimentation and Interception become Important for.
deposition of smaller particles (<2.5 ym). Diffusion and electrostatic
precipitation become Important for submlcron particles reaching the alveolar
region. Mouth breathing can be expected to Increase aerosol deposition In
the tracheobronchial and alveolar regions because air Inhaled through the
mouth bypasses the nasal region where Inertlal Impaction and mucociliary
Interception occur (Mller et al., 1986).
Absorption of lead from the respiratory tract Is Influenced by particle
size and solubility as well as the pattern of regional deposition.
Particles >2.5 ym 1n size that are deposited primarily In the ciliated
airways of the nasopharyngeal and tracheobronchial regions of the respira-
tory tract can be transferred by mucociliary transport Into the esophagus
and swallowed; only a fraction of what Is swallowed Is absorbed In the
gastrointestinal tract. Sneezing and coughing will clear a fraction of this
lead from the nasopharyngeal region. Therefore, absorption of lead
Initially deposited In the upper respiratory tract will not be complete.
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Estimates for fractional absorption of large particles (>2.5 ym) deposited
In the upper respiratory tract range from 40-50% (Kehoe, 1961a,b,c;
Chamberlain and Heard, 1981).
Particles deposited 1n the alveolar region can enter the systemic
circulation after dissolution 1n the respiratory tract or after Ingestion by
phagocytic cells (e.g., macrophages). Available evidence Indicates that
lead particles deposited in the alveolar region of the respiratory tract are
absorbed completely. Human autopsy results have shown that lead does not
accumulate in the lung after repeated Inhalation. This suggests absorption
from the alveolar region 1s complete (Barry, 1975: Gross et al., 1975).
Chamberlain et al. (1978) exposed adult human subjects to aojPb In engine
exhaust, lead oxide or lead nitrate (<1 wm particle size) and observed
that 90% of the deposited lead was cleared from the lung within 14 days.
Morrow et al. (1980) reported 50% absorption of deposited lead Inhaled as
lead chloride or lead hydroxide (0.25+0.01 yg MMAD) within 14 hours. An
analysis of the radioisotope dilution studies of Rab1now1tz et al. (1977) 1n
which adult human subjects were exposed dally to ambient air lead Indicated
that -90% of the deposited lead was absorbed dally (U.S. EPA, 1986).
The default value of 32% was derived from a quantitative analysis of the
relationship between aerosol particle size and deposition In the human
respiratory tract combined with Information on size distributions of ambient
air lead aerosols (U.S EPA, 1986; Cohen, 1987). Inorganic lead 1n ambient
air consists primarily of particulate aerosols, having a size distribution
that Is related to the characteristics of and proximity to emission
sources. Lead particles 1n most urban and rural air are 1n the submlcron
range. Particle sizes 1n the vicinity of point sources can vary consider-
ably with distance from the source and meteorological patterns (Davidson and
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Osborne, 1984; Sledge, 1987). Particles >10 win make up a substantial
proportion of the air lead near point sources. The number of Inhaled lead
particles of a» gtven size range will vary with ambient air concentration and
breathing rates, which vary with age and physical activity.
The default value applies to children exposed to general atmospheres In
which submlcron particles dominate the airborne lead mass. For atmospheres
near point sources, where larger particle sizes may be found, higher values
for respiratory deposlt1on/absorpt1on may be more appropriate. Breathing
patterns, airflow velocity and airway geometry change with age, giving rise
to age-related differences 1n particle deposition (Barltrop, 1972; James,
1978; Phalen et al., 1985). Depositions 1n various regions of the respira-
tory tract In children may be higher or lower than 1n adults, depending on
particle size (Xu. and Yu, 1986). For submlcron particles, fractional
deposition 1n 2-year-old children has been estimated as -1.5 times higher
than that 1n adults (Xu and Yu, 1986).
C.2. DIETARY UPTAKE OF LEAD
Dietary uptake (U^) Is calculated as follows:
UD * *0 " *0
where Ig (ug Pb/day) Is the Intake from dietary sources and Is the
fractional gastrointestinal absorption of dietary lead. The primary data
entry screen allows the user to Input data on dietary Intake and values for
gastrointestinal absorption parameters as described below.
C.2.1. Dietary Lead Intake. Typical dietary lead Intakes for each age
group are defined from the results of FDA Market Basket Surveys and analyses
of food lead content. The default values are based on data from dietary
surveys completed In 1988. However, current and future dietary levels may
be lower because of decreases of lead 1n canned food (Cohen, 1988a,b).
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The default values for dietary lead Intake used In the model do not
change with Increasing air, soil or water lead. The basis for this assump-
tion Is that the typical U.S. diet consists of foods harvested and processed
In diverse geographical locations. Thus, environmental contributions are
not likely to be related to local environmental lead levels. Exceptions to
this can be anticipated. For example, In rural areas where consumption of
home-grown vegetables 1s common, local air or soil lead levels may be an
Important determinant of dietary Intake. In this case, site-specific
estimates of dietary intake or adjustments to the atmospheric source
category could be used In the model In place of default values. In the
sublevel of primary diet data entry screen, "Use Alternate Diet Values," the
model accepts data on the concentrations of lead In home-grown fruits and
vegetables, locally harvested fish and game animals, and data on the esti-
mated portion of the diet derived from each food category. This Information
1s Incorporated Into the calculations of dietary and total lead uptakes.
C.2.2. Gastrointestinal Absorption of Dietary Lead. Empirical observa-
tions suggest that gastrointestinal absorption of dietary lead decreases
from a range of 40-50% In Infants to 7-15% 1n adults. Since there Is
evidence to suggest that saturable (passive) and nonsaturable (active)
mechanisms contribute to the gastrointestinal absorption of lead, a compre-
hensive model of absorption should Include quantitative expressions for both
passive and active mechanisms. Both "linear" and "nonlinear active-passive"
models of gastrointestinal absorption have been Incorporated Into the Lead
Uptake/B1ok1net1e Model. The user Is given a choice as to which model Is to
be used to estimate lead uptake. The linear model assumes a constant
absorption coefficient for dietary lead of 0.50, representing the high end
of the range of empirical observations In Infants. The following relatively
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simple active-passive model has been Incorporated Into the Uptake/Blok1net1c
Model (Marcus, 1990). The model assumes a "Michael 1s-Menten type" of
saturable functtorr for the active component of lead absorption. The absorp-
tion coefficient {) at any given dietary Intake 1s expressed as the sum
of the passive absorption coefficient (Agp) and the active absorption
coefficient (A^), factored by the concentration for lead In the gastro-
intestinal tract and the apparent Km for active absorption, as follows:
AD " ADP + 100 mg/l
The relatively high value for Km of 100 mg/l was selected to force the
model to be linear over anticipated dietary Intakes In children (I.e.,
constant saturable absorption coefficient). Thus, the values for saturable
and nonsaturable absorption coefficients sum to yield an absorption coeffi-
cient of 0.50, which Is Identical to the default value used In the linear
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model. However, the default outputs of the linear and active-passive models
diverge significantly If total value for the km Is decreased. Although the
act1ve-passtve model Is theoretically sound and Is a more accurate represen-
tation of gastrointestinal absorption than one In which the lead absorption
coefficient depends on Intake, strong empirical support for values for each
parameter In the model Is lacking. Default values used 1n the Uptake/Blo-
klnetlc Model were selected as reasonable estimates for these values and
will be revised as new Information becomes available.
C.3. UPTAKE OF ORINKING WATER LEAD
Lead uptake from drinking water 1s calculated as follows:
UW 3 !W * AW
where 1^ (vg/day) Is the Intake from drinking water and A^ 1s the
fractional absorption of Ingested lead. Lead Intake from drinking water Is
Is as follows:
lU ' ^W * WING
where [Pb]y (vg/l) Is the average dally concentration of lead 1n
drinking water and WjNg 1s the average amount of drinking water Ingested.
The primary data entry screen allows the user to Input data on levels of
lead In drinking water and values for drinking water Intake and gastro-
intestinal abosrptlon parameters as described below.
C.3.1. 0r1nk1ng Water Lead Level. The default value of 4 yg/l for
the level of lead In drinking water assumes a mix of water sources Including
first draw and flushed from household plumbing, and water from drinking
fountains.. The default values for the relative amounts of each water source
consumed and the concentrations of lead in each water source are presented
In the OMnktng Water Lead secondary data entry screen, "Use Alternate
Drinking Water Values." The user can change each of these default values by
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accessing the secondary data entry screen. In some areas of the country,
substantial Increases 1n lead exposure may occur 1f drinking.water stands 1n
the pipe for several hours. This Is especially Important for houses with
lead pipe or newly soldered copper pipes (when the solder contains lead) and
when the water 1s corrosive. First Draw 1s this standing water. Flushed
water occurs after the standing water 1s removed.
C.3.2. Drinking Water Intake. The default value for dally water Intake
1n 2- to 3-year-old children 1s 0.5 l/day. This Includes tap water
consumed as water; tap water used to prepare food and beverages 1s
considered tn the dietary section of the model.
C.3.3. % Gastrointestinal Absorption of Drinking Water Lead. The
approach taken for calculating gastrointestinal absorption of drinking water
lead 1s Identical to that described previously for dietary lead. The user
1s given the choice between a linear model or a nonlinear active-passive
model. The default value for the absorption coefficient 1n-the linear model
1s 0.50. The Km for active absorption 1s set to yield a sum of 0.50 for the
active and passive absorption components.
C.4. LEAD UPTAKE FROM DUST AND SOIL
Lead uptake from Ingested dirt calculated as follows:
U0S * !0S * A0S
where Iis the Intake from dust and soil (yg/day) and Is the
fractional absorption. The primary data entry screen allows the user to
Input data on levels of lead 1n soil and indoor dust, and values for soil
and dust weighting factors, amounts of soil and dust Ingested and gastro-
intestinal absorption parameters as described below.
C.4.1. Levels of Lead 1n Soil and Indoor Oust. The Lead Uptake Model
allows the user to select from three options: 1) accept a default value of
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200 yg/g; 2) Input values in place of the default value, or 3) accept a
multiple source model that partitions Indoor dust lead' Into several
contributing sources. The multiple source model sums the contributions of
external environmental sources (1-e., air and soil) and "all other" sources
to arrive at total Indoor air lead.
Levels of lead 1n dust and soil are determined by a variety of factors
related to the exposure source, meteorological conditions, transport of dust
'mYo Yrre 'front*
-------
and dust are 1n dynamic equilibrium. The derivation of the linear relation-
ships does not consider many complex variables that can affect alr/soll
relationship for lead, such as chemical and physical properties of the lead
particles and soil, topographic and meteorological conditions, and the
frequency of precipitation and washing of streets and Interior surfaces.
The coefficients of the linear equations used to estimate soil/dust lead
from air lead were determined from monitoring data collected at sites where
both air lead levels and dust and surface soil concentrations were measured
and averaged over varying periods of time. The data used to determine the
coefficients were collected near lead point sources where emissions were
comparable with current lead exposure situations and lead contributed by new
houses and factories. The raw data were log transformed to yield geometric
mean concentrations and the following linear equations (U.S. EPA, 1989a):
[Pb]SOIL - ^ b • (PblAo
[PbIDUST " c * d * tPb)Ao
where [Pb^son an(* tp^Ao are the concentrations of lead 1n
dust (jig/g), soil Ug/g) and outdoor air (ug/ma), respectively and
the coefficients a, b, c and d are 50.1, 579.0, 57.6 and 972.0, respectively.
The above equations are based on monitoring data for point source sites
such as smelters. The use of the linear equations to estimate soil and dust
lead levels near primary and secondary lead smelters may underestimate
current exposure because of historical iccmnjiations of relatively large
particles at these sites, regardless of current emissions controls (U.S.
EPA, 1989a). These sites will probably require separate estimates for
current soil and dust levels.
The relationship between air lead and soil and indoor dust lead may
vary, depending on the lead emission source. For example, mining sites with
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no history of smelter activity represent a situation In which the above
equations relating soil and dust lead with air lead may not apply. Review
of actual measurements of soil and house dust lead reported at mining sites
Indicated that, when soil lead was <500 ppm, house dust lead concentration!
were usually greater than soil lead. Indicating the greater contribution of
Indoor sources of lead. However, when soil lead was >1000 .ppm, house dust
lead concentrations ranged from 18-48/4 of soil lead concentrations (Steele
et al., 1989). Thus, the air and soil lead levels at mining sites are not
likely to be related, and the relationship between soil lead and Indoor dust
lead levels may be nonlinear (Steele et al., 1989). Davles et al. (1985)
reported the following quantitative expression relating vegetable garden
soil lead and Indoor dust lead 1n a mining area:
[Pb]DUST - (0.3) . (log [Pb]S(JIL) ~ 1.65
The data on the time scales for soil and dust lead changes do not lead
to definite conclusions (U.S. EPA, 1989a). The current opinion 1s that lead
In undisturbed soil matrix persists for an extremely long time; however,
soil lead concentrations 1n disturbed (especially urban) environments will
change, on average, over periods of a few years to reflect changes In
surface deposition (U.S. EPA, 1989a). Although lead does deposit on the
surface of soils, significant lead concentrations have been found down to 12
Inches below the surface. This Indicates that human activities such as
gardening and new building construction can result In significant concentra-
tions of atmospherically deposited lead 1n deeper soils. Interior dust lead
concentrations will likely change over periods of weeks to months 1n
response to air lead changes, depending on Inter1or-exterior access and
Interior recirculation or removal of dust as well as the primary sources of
dust and soil lead. Sources such as lead paint dust, mine-tailing and
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smelters that have ceased to operate may continue to contribute lead to soil
and dust regardless of changes In air lead.
The linear ami nonlinear equations yield approximations based upon the
best available monitoring data and interpretations, but do not consider
various complex variables that may significantly affect soil and dust con-
centrations. One approach to a more comprehensive model of Indoor dust lead
levels 1s to partition Indoor dust Into various source categories Including
air, soil, Indoor paint dusts, secondary occupational * dusts and hobbles
(e.g., soldering). This approach has been Incorporated Into the Uptake/B1o-
klnetlc Model as a user option (So11/Dust Lead secondary data entry screen,
"Multiple Source Analysis"). The multiple source model sums the contribu-
tions of external environmental sources (I.e., air and soil) and ."all other"
sources to arrive at total Indoor dust lead. The contributions of soil and
air are calculated as follows:
[Pb3DUST * s * [Pb]S0IL
tPblDUST s a * CPb]Ao
where C^ouST* ^Pb^S0IL and ^Pb^Ao rePresent ^ea(l 1n dust
soil Ug/g) and outside air (yg/m»), respectively, and "s" (yg Pb/g
soil per wg Pb/g dust) and "a" (jig Pb/m3 air per wg Pb/g dust) are
conversion factors for soil and air. Other sources of Indoor dust lead are
added to the external environmental contribution to yield an estimate of
total Indoor dust lead. Including occupatlonally-derlved dusts brought Into
the home, Indoor dusts encountered outside the primary home (e.g., school,
day care and second home), and dusts from lead-based paint In the home.
Although a multiple-source model Is theoretically sound, much more
research 1s needed to develop empirical support for predictive quantitative
expressions of the relative contribution of each source to the levels of
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lead In Indoor dust. Measurements of tracer elements In soil and Indoor
dusts provide data from which to derive an estimate for the soil-dust con-
version factor. Davis et al. (1990) measured the concentration of aluminum
and silicon In soil and Indoor dust and found the dust/soil ratios for both
metals to be -0.28. Assuming that Indoor aluminum and silicon are derived
entirely from transport of soil Into the house, these data support a conver-
sion factor of 0.28 (I.e., s » 0.28). As noted above, the 0.28 conversion
factor will not be appropriate for all exposure sources. Monitoring data
from mine sites suggest that the relationship between soil lead and Indoor
dust may be nonlinear.
Empirical support for the a1r-dust conversion factor 1s difficult to
obtain because unique airborne dust tracers have not been Identified. An
a1r-dust conversion factor of 100 (I.e., 1 yg Pb/g dust for each 100 pg
Pb/ma air) was selected as an Interim default value for the multiple
source model until better data are available. It cannot be over emphasized,
however, that the use of adequately measured soil and dust concentrations 1s
preferable to use of models or empirically derived equations.
C.4.2. Soil/Oust Ingestion Weighting Factors. The relative amounts of
soil and Indoor dust lead that are Ingested depend on the time spent Indoors
and outdoors and activity patterns In each environment. These will vary
with geographical location, climate and cultural and socioeconomic factors
that affect behavior patterns. An empirical basis for a weighting factor
does not currently exist; however, for young children who spend most of the
awake time Indoors, Ingestion of Indoor dust will most likely exceed Inges-
tion of soil. The default value of 45 for soil reflects this view (I.e.,
45% of lead Intake from soil and dust 1s derived from Ingestion of soil, 55%
from Ingestion of Indoor dust). The user can change the weighting factor to
accommodate activity patterns specific to a given exposure scenario.
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C.4.3. Amount of So11/Dust Ingested Dally. Infants and children Ingest
soil and dust as a result of hand-to-mouth activity, consumption of food
Hems that h&v«- been In contact with dust and soil, and soil pica.
Considerable age-related and Individual variation can be expected 1n these
activities. Hand-to-mouth activity reportedly occurs 1n -80% of children
1-2 years old, and declines In years 3-6 (Mllllcan et al., 1962; Barltrop,
1966).
Average soil Ingestion rates 1n young children have been estimated by
measuring the amount of soil or soil components on children's hands and from
assumptions regarding hand to mouth activity (LePow et al., 1975; Duggan and
Williams, 1977; Roels et al., 1980). Hawley (1985) summarized these data
and estimated that average soil Ingestion rates for 2- to 3-year-old
children range from 50-250 mg/day.
A more recent advance 1n this area has been the application of mass
balance studies. In which estimates of soil and dust Intake 1n children are
derived from measurements of the fecal excretion of poorly absorbed soil
minerals (e.g., aluminum, silicon and titanium) (81nder et al., 1986;
Clausing et al., 1987; Calabrese et al., 1989; Davis et al., 1990). A mass
balance equation used to calculate soil Ingestion (1^) 1s as follows:
Is - ((([1]F • F)/EF) - I)/[M]S
where [M]p 1s the concentration of the mineral In feces (mg/g feces); F Is
the amount of feces excreted each day (g/day); EF Is the fraction of
Ingested mineral that Is excreted 1n the feces; I 1s the gastrointestinal
Intake of th* mineral from all sources other than soil Ingestion; and [M]^
1s the concentration of mineral 1n soil (mg/g). Sources of nonsoll gastro-
intestinal Intake of tracer minerals (I) can Include diet, medication,
toothpaste and Inhaled airborne minerals. The above estimates can be
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generalized to dust and soil (I.e., dirt), assuming that concentrations 1n
dust are similar to concentrations in soil. Estimates derived from the mass
balance approach are subject to errors associated with estimates of gastro-
intestinal absorption and nonsoll Intake of the mineral.
Sedman (1989) analyzed data on fecal mineral excretion (Binder et al.,
1986), on mineral content of the diet and on food consumption 1n Infants and
young children (Pennington, 1983) to estimate soil Ingestion for 1- to
3-year-old children. Estimates were 40., 70 and 640 mg soil/day based on
mass balances for aluminum, silicon and titanium, respectively. Clausing et
al. (1987) examined aluminum, silicon and titanium excretion In 18 nursery-
school children and 6 hospitalized children, ages 2-4 years. Estimates of
dietary Intake of each mineral were based on measurements of fecal excretion
of each mineral 1n the hospitalized children. The average estimated soil
Ingestion 1n the nursery school children for all three tracers was 56 mg
soil/day. If the values for dietary Intake from Clausing et al. (1987) are
applied to the Binder et al. (1986) data on fecal excretion, estimates of
soil Ingestion range from 80-135 mg soil/day for 1- to 3-year-old children
(U.S. EPA, 1989a).
The most comprehensive mass balance studies are those of Calabrese et
al. (1989) and Davis et al. (1990), In which concurrent nonsoll Intakes of
the tracer elements were estimated for each subject In the study and
measurements of soil and house dust were used to estimate rates of Ingestion
of combined soil and house dust. The Calabrese et al. (1989) study.
Included 64 children ranging 1n age from 1-4 years. The Davis et al. (1990)
study examined 101 children ranging In age from 2-7 years. The results
reported for two tracer elements (aluminum and silicon) are considered to be
the most reliable (Beck and Steele, 1990). Estimated mean combined soil-
dust Ingestion rates for the two studies were 64 and 160 mg/day (Davis et
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al., 1990) and 154-483 mg/day (Calabrese et al., 1989). In the Calabrese et
al. (1989) study, one child out of 64 was Identified as having an extremely
high so11-dustr Ingestion (5-8 g/day). When the data were reanalyzed exclud-
ing this subject, the estimated mean soil Ingestion rate for the group was
95 mg/day for aluminum and 78 mg/day for silicon (Beck and Steele, 1990).
The results of the Calabrese et al. (1989) and Davis et al. (1990)
studies are In reasonable agreement with earlier mass-balance studies
(Binder et al.. 1986; Clausing et al., 1987) and estimates obtained from
measurements of soil and soil components on the hands of children (Hawley,
1985). Thus, the current weight of empirical evidence supports a value of
-100 as an average soil-dust Ingestion rate in young children (ages 1-7
years). The results of the mass balance studies also suggest that the
distribution of soil Ingestion rates 1n the population may be highly skewed,
with a small percentage of Individuals exhibiting very high rates of
Ingestion (I.e., pica for soil). This is evident from differences between
the mean and median values for soil Ingestion reported In the Calabrese et
al. (1989) and Davis et al. (1990) studies.
Given the skewed distribution of soil-dust Ingestion rates, selecting
the most appropriate measure of central tendency, from which reference
values for so11-dust Ingestion can be established, 1s crucial. Basing the
reference values on the median so11-dust Ingestion rate rather than on the
arithmetic mean results 1n lower predicted soil lead exposures (and there-
fore lower predicted blood lead levels) because the median attaches no
weight to the level of exposure received by Individuals at the high end of
the so11-dust Ingestion distribution. Such an approach Is consistent with
current U.S. EPA risk assessment strategies for numerous other chemicals,
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which are focused on the "general population" rather than on Individuals
expressing abnormal conditions or behavior that would promote exposure to a
toxic agent; *
The Issue 1s complicated by the fact that there 1s no clear consensus
regarding a quantitative definition of soil pica or the Incidence of
"abnormal" soil Ingestion behavior 1n children (U.S. EPA, 1989b). The
Incidence of abnormal soil Ingestion behavior 1s estimated to range from
2-50% (U.S. EPA, 1989b). The wide range Is attributable to several factors,
Including the lack of a consensus among Investigators on a definition of
"abnormal" Ingestion behavior, as well as age, cultural, socioeconomic, and
disease related factors that may Influence Ingestion behavior In the various
populations of children. The only studies likely to provide definitive
Information on the distribution of soil Ingestion rates 1n the U.S. popula-
tion and thus useful for risk assessment are the mass-balance studies, 1f
applied to a sufficiently large sample. Studies that provide reliable
estimates of soil Ingestion (Calabrese et al., 1989; Davis et al., 1990)
have been limited to relatively small sample sizes.
Until reliable estimates of the frequency distribution of soil Ingestion
rates for the U.S. population are developed, the reference value for soil
Ingestion 1n young children should be based on empirically derived arith-
metic means from the Calabrese et al. (1989) and Davis et al. (1990) studies
(-100 mg/day); however, extraordinarily high Ingestion rates reported by
Calabrese et al. (1989) (I.e., one child exceeding S g so11/day) should be
excluded. The reference value should be regarded as a default estimate to
be used 1n the absence of more specific data on soil Ingestion behavior In
the population being assessed. As such. It Is likely to overestimate
average soil Ingestion among some populations and underestimate soil
Ingestion In other study populations.
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C.4.4. Gastrointestinal Absorption of Dust and Soil Lead. The greatest
source of uncertainty In the prediction of lead uptake from dust and soil 1s
the estimate of~ gastrointestinal absorption of lead. In vitro studies have
shown that the lead tn dust and soil 1s solublllzed 1n acidic solutions
similar to that found 1n the stomach; however, In alkaline solutions similar
to Intestinal fluids, lead can remain bound to soil (Oay et al., 1979;
Harrison, 1979; Ouggan and Williams, 1977). Dietary balance studies have
yielded estimates of 42-53% for gastrointestinal absorption of dietary lead
In Infants and children; however, absorption efficiency may differ for lead
In dust and soil. Two studies 1n rats have demonstrated that the bioavail-
ability of soil lead Is less than that of lead added to basal diets as lead
acetate (Dacre and TarHaar, 1977; Chaney et al., 1989). Diets supplemented
with lead acetate are not entirely analogous to diets 1n which environmental
lead has been Incorporated Into the dietary components; nevertheless, these
results suggest that the absorption coefficient for soil may be lower than
that for dietary lead. This may not apply to all lead species and particle
sizes and all soil types.
Absorption of lead for dust and soil Is Influenced by three Important
factors: chemical species, particle size and concentration In soil. Chaney
et al. (1988) demonstrated that absorption of lead from soil varies with
lead concentration In soil.
Particle size also determines the degree to which lead Is absorbed Into
the body; the larger the particle size, the less the absorption (Barltrop
and Meek, 1979). For example, lead sulfide on larger particles eventually
dissolves 1n gastric fluid to the same concentration as lead sulfide on
smaller particles, but the process takes longer (100 vs. 200 minutes) (Healy
et al., 1982). Thus, absorption may be less 1n the stomach for the larger
particles because the particles do not remain In the stomach long enough to
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become completely solub1T1zed. Therefore, H Is very Important when review-
ing site-specific data to determine the prevalent particle size on which the
lead 1s located. In some locations where lead contamination In soil 1s
high, such as mining areas, the particle sizes are much larger than In other
locations, such as smelter towns, possibly resulting 1n decreased bioavail-
ability. Lead species 1s another critical factor In determining bioavail-
ability. Barltrop and Meek (1979) reported that lead sulfide Is signifi-
cantly less absorbed than lead acetate and lead oxides.
The Issue of bioavailability of lead for soil 1s a malor source of
uncertainty 1n the Uptake/Bloklnetlc Model and merits further Investigation.
Applying Information on particle size, lead species and soil characteristics
1n bioavailability estimates would prove very useful 1n further calibration
of the model.
Both linear and nonlinear active-passive models of gastrointestinal
absorption of lead from Ingested water have been Incorporated Into the Lead
Uptake/B1ok1net1c Model (see discussion of gastrointestinal absorption of
dietary lead 1n this section for a description of the nonlinear active-
passive model). The user Is given a choice about which model to use to
estimate lead uptake. The linear model assumes a constant absorption
coefficient of 0.30 for soil-dust lead, whicn Is lower than value of 0.50
assigned to dietary lead, reflecting trie empirical evidence for lower
absorption from soil. The active-passive *>dei 1s as follows:
A0S ¦ ADSP * ^SA/{U{^WXm)a))
where:
Aqs ¦ absorption coefficient for dust-toil lead
Aqsp * coefficient for nonsaturable (passive) absorption
Aqsa ¦ coefficient for saturable (active) aosorptlon
[PblGI ¦ concentration of dust-soil lead m the gastrointestinal tract
(vg/l)
Km * apparent Km for saturable absorption (ug/l)
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The default values for i~ 10 j-year-oid cni iaren wnu ¦„. « usea ...<« muuei
are as follows:
Aq3 - 0.3 for the default dust-soil lead Intake of 20 yg/day
Aqsp » 0.15
ADSA * O'lS for the dust-soil lead Intake of 20 yg/day
[Pb]Qi » 107 yg/a. for the default dust-soil lead Intake of 20 yg/day
Km a 100 mg/i
The default value for the Km for active absorption has been set at 100
mg/t to force the model to linearity. Thus, the active and passive
absorption components sum to 0.30, which is Identical to the default value
for the linear model. However, the default outputs of the linear and
active-passive models diverge significantly 1f the total value for the km Is
decreased. This occurs when soil lead levels exceed 1000 ppm.
C.5. LEAD UPTAKE FROM INGESTED PAINT
Ingestion of lead-based paint chips can be a quantitatively Important
source for lead uptake 1n children living or playing 1n areas 1n which
decaying paint surfaces exist. Lead levels 1n the Indoor dust of homes with
lead paint can be 2000 yg/g (Hardy et al., 1971; Ter Haar and Aronow,
1974). A child who Ingests 0.1 g of Indoor dust each day would have a paint
lead Intake of 200 yg/day. Although not illustrated 1n the example, the
model accepts Input of age specific estimates of intake from lead paint and
Incorporates these values In the calculation of total lead uptake. The
computation strategy 1s similar to that used for calculating uptake from
Ingestion of soil and Indoor dust lead. Nonsaturable and saturable absorp-
tion mechanisms are assumed to contribute to trie uptake of lead solublllzed
from paint 1n the gastrointestinal tract.
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C.6. TOTAL LEAO UPTAKE
Total lead uptake {U^.) Is the sura of uptakes from breathing lead In
air, diet, drinking water and dust/soil Ingestion:
UT " UA * UD * UDS * UW
The calculation of media-specific uptakes shows that the largest contri-
bution to total uptake fn 2- to 3-year-old children Is from dust, soil and
diet. The contribution of Inhaled airborne lead 1s relatively minor.
Because of the relatively large contribution of dust and soil and diet lead
to total uptake, predictions of total up'take will be highly sensitive to
changes In the values of Input parameters related to these exposure media.
Several examples are Illustrated 1n Figures C-l through C-3.
Figure C-l shows the change 1n predicted total lead uptake In 2- to
3-year-old children as soil and dust lead Increases from 100-1200 >ig/g.
Three different values for the gastrointestinal absorption coefficient for
dust and soil were assumed In each plot (I.e., ApS * 10, 30 or 50% linear
absorption model). Values for all other parameters remained constant. The
figure Illustrates the sensitivity of the model to changes 1n the valu* of
the dust and soil absorption coefficients over a range that Is easily
accommodated by the currently available empirical data on gastrointestinal
absorption of lead.
The model Is also highly sensitive to the values used for gastrointes-
tinal absorption of dietary lead. The model defaults to gastrointestinal
absorption coefficients of 50% for both diet and drinking water; however, a
value of 30% would not be entirely Inconsistent with currently available
empirical data. The effect modifying the absorption coefficients for diet
and drinking water from 50 to 30% 1n 2- to 3-year-old children Is Illus-
trated 1n Figure C-2. The result Is a downward parallel shift 1n the
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60
50
A(DS) - 30S
20
A(0S) - 10
i
i
0.1 0.3 0.5 0.7 0.9 1.1
Soil and Oust Lnd (rrq/q)
FIGURE C-l
Total Lead Uptake 1n 2- to 3-Year-01d Children Exposed to Various Levels
of Soil Lead as Predicted by the Lead Uptake Model. Each line represents
the predicted lead uptake assuming different values for the gastrointestinal
absorption coefficients (Aqj) for dust and soil (10, 30 or 50%).
Source: U.S. EPA, 1989a
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4«
*0
33
30
23
20
13
10
3
0.3
0.9
0.1
0.7
1.1
Soil and Oust L*od (mg/q)
FIGURE C-2
Effect of Varying the Absorption Coefficients for Lead 1n 01et and Water .
(Aq y) on Total Lead Uptake In 2- to 3-Year-01d Children as Predicted by -
the'Lead Uptake Model
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X
0
\
9
3
1
A
o
a
"9
O
o
©
0.3 0.7
Soil and Oust L#ad (mg/g)
FIGURE C-3
Effect of Varying the Concentration of Lead 1n Drinking Water on Total
Lead Uptake 1n 2- to 3-Year-Old Children as Predicted by the Lead Uptake
Model
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uptake-soil lead relationship. Thus, the model predicts that at a soil lead
of 200 yg/g, decreasing the gastrointestinal absorption coefficients for
diet and drlnklnf water from SO to 30%, will decrease total lead uptake by
30%.
The model predicts that uptake from drinking water will have the next
greatest Impact on total lead uptake, after dust-soil and dietary lead
uptakes are considered. However, the contribution of drinking water lead 1s
relatively small, compared with the contribution of dust-soil and diet.
Hence, decreasing the concentration of lead 1n drinking water from 4 to 0
yg/i will have a relatively small effect on total lead uptake 1n 2- to
3-year-old children (see Figure C-3).
C.7. CALCULATIONS OF PROJECTED MEAN BL000 LEAD DISTRIBUTIONS: LEAD UPTAKE
LEVELS
The Uptake/81ok1net1c Model predicts mean blood lead levels associated
with defined multimedia exposure levels. However, to assess the risks
associated with such exposures In a given population and evaluate potential
effects of regulatory or abatement decisions, the frequency distribution for
the population blood lead levels Is a more useful parameter than population
means. The fraction of the population with the highest blood lead levels
will be the focus of regulatory and abatement decisions.
The distribution of blood lead levels Is approximately log normal (U.S.
EPA, 1986) and, thus. Is defined by Its geometric mean and GSD. It Is,
therefore, possible to calculate the frequency distribution for blood lead
levels, given a mean blood lead level and estimated GSQ. for the population.
Estimated GSDs for bipod lead levels In humans range from 1.3-1.4 (Tepper
and Levin, 1975; Azar et al., 1975; B1ll1ck et al., 1979). Schwartz (1985)
estimated a GSO of 1.428 for young children after removing the variance In
blood lead levels attributable to air lead exposure.
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The OAQPS analyzed the NHANES II data on blood lead levels 1n adults;
estimated GSOs are 1.34-1.39 for adult women and 1.37-1.40 for adult men
(U.S. EPA, 1986}* The OAQPS (U.S. EPA, 1989a) also analyzed data from
various studies of blood lead levels 1n children living near lead point
sources (e.g., smoke stacks, smelters) (Baker et al., 1977; Yankel et al.,
1977; Roels et al., 1980; CDC, 1983; Hartwell et al., 1983; Schwartz et al.,
1986). The OAQPS concluded that
"Until additional data are available, a range of 1.30-1.53 will
therefore be assumed for children 11-vlng near point sources as a
reasonable range of GSO values (Roels et al., 1980; CDC, 1983), and
the midpoint of 1.42 will be assumed as a reasonable best estimate."
The Uptake/B1ok1net1c Model assumes a GSD of 1.42 as a default value.
It should be noted, however, that this value pertains to fairly homogeneous
populations (with respect to behavioral and pharmacokinetic factors) exposed
to similar mean levels of lead from the same sources. Other distributions
and levels of variability may be encountered In populations having subgroups
exposed to very different soil or air lead concentrations.
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APPENDIX D
GENERAL SCHEMATIC 0F THE LEAD PROGRAM
Figure 0-1 Is a schematic diagram of the LEADS Program. The dotted
lines on the diagram Indicate the paths available for retrieval of files
created by the program. For example, the Overlay Plot files created at the
Range Menu and SAVE Menu are simultaneously retrievable via the GRAPH
Selection Menu. The data entry section of the diagram lists several
keystrokes (F5, PgUp, PgDn, ESC) that are used to direct program flow.
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'kittlia Parameter y<
Filt ••SVJ- J
[ TXT File Viewer
RANGE MENU
(ffcn tx UodaQ
(Sand to Owl* Mat
/(iVhRlAY Texl
\KANCt:» ITT
/OVhHJAY n*
\KAN(it:» I AY
LI
MAIN MENU
1 EmmOmIuMA
2 ( nlef fku I04 Dtt'f
J tnUi Datakx DHNKING WAICH
* Inta< Dm Um SCHAXti I
S t iUm Oil loi PAINI
a E«tai MA (EmALOw*
R Hun *m Uodal |yiM| wml wliml
S SAVEPnyMPiMMlmlttFh
L IOAO PiogiMi PwumIm In* ¦ ftm
Q fiwul Miwimi akoul Mm p*oyi
I - MmmIwi about wm »wi Mtetlmi
P PlOl EutkngOopfc Fife* (OBAPH Item.)
U UU IIKE AiM lUNGf Mm p»xUy fin
V VlCW/PHNls Data (1*1) F*
B BIOOOPl>»M«itwCm>
) GliAPlI Ball Skipa^ Pfo(>»bMy DinMy ftNichON
4 f\Ot OVCfCAf Fit* at Molli Run* (OiMifeulKM)
ft R OI 0/Et*AV fte ol UulH Run* (B«l Sfc«p«d)
fGRAPH ^
l^Dltpliy^l
I .
(fWMlAY let! l-'ikr ••.TXT) }
(oVhHIAY t'Ul hk *•JAY:
Summafy Output
1 GRAPH HauiUs
2 ¦ SAVE Results
SAVE MENU
Pg UpJPgOn
F5
F5
F5
DIET DATA
| PgUp/PgDn
WATER DATA
^ Palip/PgDn
f SOIL-OUST DATA
~r
PgUp/PgDn
4 I PAINT DATA
1
p0t4VP«Ofi
F5
MATERNAL DATA
p
-------
DISCLAIMER
This report 1s an Internal draft for review purposes only and does not
constitute Agency policy. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
11
-------
EXECUTIVE SUMMARY
#
This technical support document presents the rationale for an uptake/
b1ok1net1c modeling approach to developing health criteria for lead.
Because of the lack of empirical evidence for a threshold for many of the
noncancer effects of lead In Infants and young children, coupled with multi-
media exposure scenarios, meaningful oral and Inhalation reference doses
cannot be developed for lead. Blood lead levels, however, provide an
Important and useful Index of risk because most toxicity endpolnts asso-
ciated with exposure to lead can be correlated with blood lead levels. The
Uptake/B1ok1net1c Model described 1n this document, and described In greater
detail In U.S. EPA (1989a), provides a method for predicting blood lead
levels 1n populations exposed to lead 1n the air, diet, drinking water.
Indoor dust, soil and paint, thus making 1t possible to evaluate the effects
of regulatory decisions concerning each medium on blood lead levels and
potential health effects. This model was developed by the Office of Air
Quality Planning and Standards (OAQPS). The model Integrated with the
Industrial Source Complex Dispersion Model (U.S. EPA, 1986c) has been used
to predict s1te-spec1f1c distributions of blood lead levels 1n populations
In the vicinity of lead point sources.
Infants and young children are the most vulnerable populations exposed
to lead and are the focus of the U.S. EPA's risk assessment efforts. The
relatively high vulnerability of Infants and children results from a combi-
nation of several factors: 1) an apparent Intrinsic sensitivity of develop-
ing organ systems to lead; 2) behavioral characteristics that Increase -
contact with lead from dust and soil (e.g., mouthing behavior and pica);
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3) various physiologic factors resulting 1n greater ^deposition of airborne
lead in the respiratory tract and greater absorption efficiency from the
gastrointestinal tract 1n children than 1n adults; and 4) transplacental
transfer of lead that establishes a lead burden 1n the fetus, thus
Increasing the risk associated with additional exposure during Infancy and
childhood.
A diverse set of undesirable effects has been correlated with blood lead
levels In Infants and children. Impaired or delayed mental and physical
development. Impaired heme biosynthesis and decreased serum vitamin 0 levels
are correlated with blood lead levels across a range extending below 10
yg/dl. Although considerable controversy remains regarding the bio-
logical significance of some of the effects attributed to low lead exposure
(e.g., blood lead levels below 10 yg/dl), the weight of evidence 1s
convincing that 1n Infants and children, exposure-effect relationships
extend to blood lead levels of 10-15 yg/dl and possibly lower.
The Uptake/B1ok1net1c Model provides a means for evaluating the relative
contribution of various media to establishing blood lead levels (U.S. EPA,
1989a). The Uptake/81ok1net1c Model provides a useful and versatile method
for exploring the potential Impact of future regulatory decisions regarding
lead levels 1n air, diet and soil.
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/
TABLE OF CONTENTS
Page
1. INTRODUCTION. 1-1
1.1. Rfft METHODOLOGY ANO RATIONALE FOR RfO DEPARTURE 1-1
1.1.1. Absence of a Discernible Threshold for Health
Effects of Lead 1-2
1.1.2. Multimedia Exposure Scenarios 1-3
1.1.3. Blood Lead as the Primary Index of Exposure ... 1-4
1.1.4. Predictive B1ok1net1c Models for Lead 1-5
1.1.5. Multimedia Exposure Analysis 1-5
2. HEALTH EFFECTS SUMMARY 2-1
2.1. OVERVIEW 2-1
2.2. TOXICOKINETICS: ABSORPTION, DISTRI8UTI0N/B00Y BURDEN.
METABOLISM AND EXCRETION 2-3
2.2.1. Absorption 2-3
2.2.2. Tissue Distribution of Lead 2-11
2.3. SYSTEMIC AND TARGET ORGAN TOXICITY 2-18
2.3.1. Neurobehavloral Toxicity 2-18
2.3.2. Effects of Lead on Heme Biosynthesis and
Erythropo1es1s 2-21
2.3.3. Effects of Lead on the Kidney 2-29
2.3.4. Effects of Lead on Blood Pressure 2-29
2.3.5. Effects of Lead on Serum Vitamin D Levels .... 2-34
2.4. DEVELOPMENTAL/REPRODUCTIVE TOXICITY AND GENOTOXICITY . . . 2-36
2.4.1. Mental Development In Infants and Children. . . . 2-36
2.4.2. Growth Deficits 2-45
2.4.3. Effects on Fertility and Pregnancy Outcome. . . . 2-46
2.4.4. Genotox1c1ty 2-46
2.5. SUMMARY 2-47
3. EXPOSURE ASSESSMENT 3-1
3.1. BIOLOGICAL EFFECTS: ENVIRONMENTAL EXPOSURE 3-1
3.2. MULTIMEDIA LEAO EXPOSURES: AIR. SOIL. DUST. WATER.
PAINT 3-3
3.2.1. Lead 1n Air 3-5
3.2.2. Lead 1n Soil 3-7
3.2.3. Lead In Dust 3-8
3.2.4. Lead 1n Diet 3-9
3.2.5. Lead 1n Water 3-9
3.2.6. Lead 1n Paint 3-10
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TABLE OF CONTENTS (cont.)
Page
3.3. MEDIA-SPECIFIC ESTIMATES FOR DIFFERENT LEVELS OF LEAD
UPTAKE . 3-11
3.3.1. Uptake from Ambient A1r 3-11
3.3.2. Uptake from the Diet 3-14
3.3.3. Uptake from Dust and Soil 3-16
3.3.4. Uptake of Lead from Drinking Water 3-29
3.4. ENVIRONMENTAL EXPOSURE LEVELS ASSOCIATED WITH BLOOD
LEAD LEVELS 3-30
3.4.1. Blood Lead/A1r Lead Relationships 3-30
3.4.2. Blood Lead/Dust and Soil Lead Relationships . . . 3-31
3.4.3. Blood Lead/Diet and Drinking Water Lead
Relationships 3-32
3.5. SUMMARY 3-33
4. RISK CHARACTERIZATION 4-1
4.1. INTEGRATED LEAO UPTAKE/BIOKINETIC EXPOSURE MODEL 4-1
4.1.1. Estimates of Lead Uptake 4-2
4.1.2. Uptake of Lead from Ingested Paint 4-17
4.1.3. Uptake and Blood Lead Concentrations 4-18
4.2. CALCULATIONS OF PROJECTED MEAN 8L000 LEAD DISTRIBUTIONS:
LEAD UPTAKE LEVELS 4-23
4.3. SUMMARY 4-29
5. REFERENCES 5-1
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LIST OF TABLES
• •
No. Title Paq>
2-1 Estimates of Regional Deposition and Absorption of
AmMtfit A1r Lead Particles 1n the Adult Respiratory Tract
(Found Near Point Sources) 2-7
2-2 Age Factor Adjustments for Calculating Deposition and
Absorption of Ambient Air Lead Particles (Found Near Point
Sources) 1n the Respiratory Tract of 2-Year-Old Children. . . 2-8
3-1 Typical Lead Concentrations In Various Exposure Media .... 3-6
3-2 Age-Spec1f1c Estimates of Total Dietary Lead Intake
for 1990-1996 (jig/day) 3-15
3-3 Dally Soil Ingestion (mg/day) Based on Aluminum, Silicon,
Titanium and YHtrlum Mass Balance . 3-25
4-1 Lead Intake and Uptake 1n 2- to 3-Year-01d Children Exposed
to Lead In Air, Diet, Dust, Soil and Orlnklng Water 4-3
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LIST OF FIGURES
Wo. Title Page
2-1 Schematic Model of Lead Metabolism 1n 2-Year-01d Children,
with Compa^tmental Transfer Rate Constants . . . 2-17
2-2 Child IQ as a Function of Blood Lead Level In Children
3-7 Years Old 2-20
2-3 British Ability Scales Combined Score (BASC, Means and
95% Confidence Intervals) as a Function of Blood Lead
Levels 1n Children 6-9 Years Old 2-22
2-4 Maximal Nerve Conduction Time as a Function of Blood Lead
Level In Children 5-9 Years Old 2-23
2-5 Effects of Lead on Heme Biosynthesis 2-24
2-6 Blood ALA-D Activity as a Function of Blood Lead Level
1n 158 Adults 2-26
2-7 Problt Dose-Response Functions for Elevated Erythrocyte-
Protoporphyrin as Function of Blood Lead Level In Children. . 2-27
2-8 Erythrocyte Pyr1m1d1ne 5'-Nucleotidase Activity (P5N Units)
as a Function of Blood Lead Level In 25 Children, ,1-5 Years
Old.. 2-30
2-9 Comparison of Study Results from Four Larger-Scale
Epidemiology Studies of Lead-Blood Pressure Relationships
In Adult Men . . . 2-32
2-10 Serum 1,25-01hydroxycholecalc1ferol (1,25-CC) Levels as a
Function of Blood Lead Levels In 50 Children, 2-3 Years Old . 2-35
2-11 Mental Development Index Score (Covarlate Adjusted, Mean
and SO) as a Function of Age for Children Grouped Into Three
Ranges of Cord Blood Lead Level; Low, <3 yg/dl; Medium,
6-7 yg/dl; High, 10-25 Mg/dl 2-38
2-12 Comparison of Results from Prospective and Cross-Sectional
Studies of Mental Development 2-44
2-13 Suimiry of Studies Relating Blood Lead Levels and Effects
on Various Toxicity Endpolnts In Infants and Children .... 2-49
3-1 Pathways of Lead from the Environment to Humans 3-4
3-2 Plot of Soil Lead Concentration vs. A1r Lead Concentration
Monitored In Various Locations 3-19
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LIST OF FIGURES (cont.)
Wo. Title Page
4-1 Total Lead Uptake In 2- to 3-Year-01d Children Exposed
to Various Levels of Soil Lead as Predicted by the Lead
Uptake Model 4-14
4-2 Effect of Varying the Absorption Coefficients for Lead
1n Diet and Water (Aq h) on Total Lead Uptake 1n 2- to
3-Year-01d Children as Predicted by the Lead Uptake Model . . 4-15
4-3 Effect of Varying the Concentration of Lead 1n Drinking
Water on Total Lead Uptake 1n 2- to 3-Year-01d Children
as Predicted by the Lead Uptake Model 4-16
4-4 Summary of Relationships Between Dally Lead Uptake and
Blood Lead for Infants, Adults and 2- to 3-Year-01d
Children, Derived from the Hawley and Knelp (1985)
B1ok1net1c Model 4-20
4-5 Probability Distribution of Blood Lead Levels 1n 2- to
3-Year-Old Children Exposed as Predicted by the Lead
Uptake/B1ok1net1c Model 4-25
4-6 Mean Blood Lead Levels 1n 2- to 3-Year-Old Children vs.
Total Lead Uptake as Predicted by the Lead B1ok1net1c
Model 4-26
4-7 Comparison of Distribution of Measured Blood Levels 1n
Children 1-5 Years of Age, Living within 2.25 Miles of a
Lead Smelter with Levels Predicted from the Uptake/
B1ok1net1c Model 4-27
4-8 Comparison of Distribution of Measured Blood Lead Levels
In Children, 1-5 Years of Age, Living within 2.25 Miles of
a Lead Smelter with Levels Predicted from the Uptake/
B1ok1net1c Model 4-28
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LIST OF ABBREVIATIONS
ALA-D {-aminolevulinic acid dehydratase
ALA-S a-am1nolevul1n1c acid synthetase
bw body weight
DNA Deoxyribonucleic add
EP Erythroblast protoporphyrin
GCI General Cognitive Index
G-R Grahara-Rosenbleth Behavioral Examinations for Newborns
GSD Geometric standard deviation
KID Kent Infant development scale
LOAEL Lowest-observed-adverse-effect level
HOI Mental development Index
MMAD Mass median aerodynamic diameter
NBAS Neonatal behavioral assessment scale
NOAEL No-observed-adverse-effect level
OAQPS Office of Air Quality Planning and Standards
POI Psychomotor development Index
P5N Pyr1m1d1ne-5'-nucleotidase
RfO Reference dose
S.E. Standard error
WPPSI Wechsler preschool and primary scale of Intelligence
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1. INTRODUCTION
»
1.1. RfD METHODOLOGY AND RATIONALE FOR RfD DEPARTURE
The Ageneyr has established the RfO for the purpose of quantitative risk
assessment of noncarclnogenlc chemicals. The RfO 1s an estimate (with
uncertainty spanning perhaps an order of magnitude) of the dally exposure to
the human population (Including sensitive subgroups) that 1s likely to be
without appreciable risk of deleterious effects during a lifetime (U.S. EPA,
1987, 1988a). In developing an RfO for a specific chemical, the best avail-
able scientific data on the health effects of the chemical are reviewed to
Identify the highest levels of exposure that are clearly not associated with
adverse health effects 1n humans. Typically, the highest NOAEL Is adjusted
by an uncertainty factor to derive the RfO. The uncertainty factor reflects
the degree of uncertainty associated with extrapolating the NOAEL Identified
from analysis of relevant human toxlcologlcal studies to the most sensitive
fraction of the "healthy" human population.
When human toxlcologlcal data are inadequate to base conclusions regard-
ing human NOAELs, NOAELs or LOAELs for the most sensitive animal species, as
defined by well-designed animal studies, are used to derive the RfO. Ooses
or exposure levels are adjusted by conversion factors to account for allo-
metrlc (e.g., body weight) and physiologic (e.g., breathing rates) differ-
ences between animals and humans. The adjusted NOAELs or LOAELs are then
adjusted by an uncertainty factor to derive the RfO. Uncertainty factors
for NOAELs derived from animal studies are larger than that for human
NOAELs, reflecting the greater uncertainty associated with extrapolating
dose-effect relationships from animals to humans. Consideration Is given to
uncertainties associated with extrapolations made from 1ess-than-l1fet1me
exposures to lifetime exposures, from LOAELs to NOAELs and for differences
1n sensitivity between animals and humans.
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The RfO ?pproach has yielded useful quantitative estimates of toxic
threshold for many chemicals, and thus, has been used as a "benchmark" on
which to consider regulatory decisions 1n relation to potential Impacts on
human health; however, for reasons that are enumerated below 1t Is Inappro-
priate to derive an RfD for risk assessments related to environmental lead.
1.1.1. Absence of a Discernible Threshold for Health Effects of Lead. A
critical assumption Implicit to the RfD 1s the concept of threshold (I.e., a
dose level exists below which adverse health effects will not occur). This
assumption precludes developing RfDs based on effects for which thresholds
have not been established from experimental or epidemiological data or for
chemicals for which theoretical considerations suggest the absence of a
threshold. Carcinogens fall Into the latter category; for example, theoret-
ical considerations suggest a finite probability that cancer could arise
from the Interactions of a single molecule of a mutagen with DNA (U.S. EPA*
1986a).
Unlike the case for carcinogens, there 1s no widely accepted theoretical
basis for the absence of a threshold for many of the health effects asso-
ciated with lead exposure. However, analyses of correlations between blood
lead levels and ALA-D activity, vitamin D and pyr1m1d1ne metabolism, neuro-
behavloral Indices, growth and blood pressure Indicate that associations may
persist through the lowest blood lead levels In the populations tested
(<10-15 xg/di). Thus, it 1s possible that If a threshold for the toxic
effects of leadexists, 1t may He within a range of blood lead levels
<10-15 yg/dl; however, the data currently available are not sufficient
to adequately define the dose-response relationship for many of the toxic ~
effects of lead 1n populations having blood lead levels <10 wg/di.
Hence, 1t Is not possible to confidently Identify a blood lead level below
which no undesirable health effects would occur.
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PREFACE
The U.S. EPA Is developing health-related guidance for lead that can be
applied to uldt range of different media (soil/dust, air, diet). This
report sumttmtzes relevant Information on health effects of lead and on lead
exposure and presents a description of a proposed modeling approach for
deriving media-specific criteria that can be tailored to specific exposure
scenarios or cases. The rationale for using a modeling approach in place of
more traditional risk assessment strategies such as Reference Dose 1s
discussed. Much of the Information presented In this report Is taken from
recent and more comprehensive Agency reviews, Including the Air Quality
Criteria Document (U.S. EPA, 1986a) and Review of the National Ambient A1r
Quality Standards for Lead (U.S. EPA, 1989a). The first draft of this
report was prepared by Syracuse Research Corporation under Contract No.
68-C8-0004. The literature search Is current as of March, 1990. This
Technical Support Document (TSD) describes an Uptake/B1ok1net1c model of
lead that provides a method to predict blood lead levels In populations
exposed to lead In a-1r, diet, drinking water, Indoor dust, soil and paint,
thus making It possible to evaluate the effects of regulatory decisions
concerning each medium on blood lead levels and potential health effects.
This model represents generalization of a model developed by OAQPS
(Integration of Harley and Knelp's Bloklnetlc model with OAQPS uptake model)
that has been used to predict site-specific distribution of blood lead
levels In populations In the vicinity of lead point sources.
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