3. QUICK REFERENCE FOR THE 

EXPERIENCED USER 

3.1 FINDING YOUR WAY THROUGH THE MENUS 

The Lead Model is a menu driven program. There is no need to remember special 

commands, just a cursory understanding of the menu structure. Often you can find what you 

want just by exploring the various menu options, and familiarity with the model is the best 

way to shorten this journey. For your reference, a complete menu tree is given in 

Figure 3-1. Use caution with unfamiliar menu options. Detailed explanations are given in 

Chapter 2, and more complete documentation may be found in Chapter 4 for most menu 

options. These should be reviewed before final decisions are made on critical model runs. 

3.2 PARAMETER LIST WITH DEFAULT VALUES 

The values in Table 3-1 have been assumed for the parameters of the model. These are 

our best estimates for urban residents with no unusual lead exposures. The estimated blood 

lead levels with the default parameters represent our best estimate of the blood lead 

"background" levels that cannot be avoided. The adjustable parameters are listed by screen 

in the order in which they appear in the model. 

Default values are provided for the convenience of the user, but these values may not be 

appropriate for specific applications. The user has the ultimate responsibility for justification 

of values used in the applications of the model. We recommend that the user review each of 

the parameter values in Table 3-1. Most of the parameters will not need to be modified, but 

the user should be aware of them. Sensitivity analyses on parameters will be useful in 

documenting results. Many default parameters in the model have only a minor effect on the 

results (i.e., a 10% change in the air lead concentration parameter will change blood lead 

levels by less than 1%), but some parameters may be more influential. 

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Figure 3-1. Lead model menu tree.

3.3 BATCH MODE INPUT FORMAT

You may find a number of circumstances in which it is convenient to enter input data

for many similar exposure scenarios in a single run of the model. 

Computation Menu allows you to use a different age or a different value of the lead

concentrations in soil, dust, water, air, and alternate lead intake sources for each exposure

scenario. 

scenario in the run and must be specified before using this option, unless default values are

used. 

Option 4 of the

The media intake and absorption parameters are the same for every exposure

These situations may include, but are not limited to:
TABLE 3-1. DEFAULT VALUES FOR MODEL PARAMETERS

PARAMETER DEFAULT VALUE UNITS

AIR (constant) 

Outdoor air lead concentration 0.10 Fg/m3 

Ratio of indoor to outdoor air lead concentration 30 % 

AIR (by year) 

Air concentration 

Age = 0-1 year (0-11 mo), .10 Fg/m3

1-2 years (12-23 mo) .10 

2-3 years (24-35 mo) .10 

3-4 years (36-47 mo) .10 

4-5 years (48-59 mo) .10 

5-6 years (60-71 mo) .10 

6-7 years (72-84 mo) .10 

Time outdoors 

Age = 0-1 year (0-11 mo), 1 h/day

1-2 years (12-23 mo) 2

2-3 years (24-35 mo) 3

3-7 years (36-83 mo) 4

Ventilation rate 

Age = 0-1 year (0-11 mo), 2 m

3

/day

1-2 years (12-23 mo) 3

2-3 years (24-35 mo) 5

3-4 years (36-47 mo) 5

4-5 years (48-59 mo) 5

5-6 years (60-71 mo) 7

6-7 years (72-84 mo) 7

Lung absorption 32 % 

DATA ENTRY FOR DIET (by year) 

Dietary lead intake 

Age = 0-1 year (0-11 mo), 5.53 Fg Pb /day 

1-2 years (12-23 mo) 5.78 

2-3 years (24-35 mo) 6.49 

3-4 years (36-47 mo) 6.24 

5-6 years (48-59 mo) 6.01 

5-6 years (60-71 mo) 6.34 

6-7 years (72-84 mo) 7.00 

DATA ENTRY FOR ALTERNATE DIET SOURCES (by food class) 

Concentration: 

home-grown fruits 0 Fg Pb/g 

home-grown vegetables 0 

fish from fishing 0 

game animals from hunting 0 

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TABLE 3-1 (cont'd). DEFAULT VALUES FOR MODEL PARAMETERS 

PARAMETER DEFAULT VALUE UNITS 

Percent of food class: 

home-grown fruits 0 % 

home-grown vegetables 0 

fish from fishing 0 

game animals from hunting 0 

DATA ENTRY FOR DRINKING WATER

Lead concentration in drinking water 4 Fg/L 

Ingestion rate 

Age = 0-1 year (0-11 mo), 0.20 liters/day 

1-2 years (12-23 mo) 0.50 

2-3 years (24-35 mo) 0.52 

3-4 years (36-47 mo) 0.53 

4-5 years (48-59 mo) 0.55 

5-6 years (60-71 mo) 0.58 

6-7 years (72-84 mo) 0.59 

DATA ENTRY FOR ALTERNATE DRINKING WATER SOURCES

Concentration Fg/L 

first-draw water 4 

flushed water 1 

fountain water 10 

Percentage of total intake 

first-draw water 50 % 

flushed water 100 minus first draw 

and fountain 

fountain water 15 

DATA ENTRY FOR SOIL/DUST (constant) 

Concentration 

soil 200 Fg/g 

dust 200 

Soil ingestion as percent of total soil and dust ingestion 45 % 

DATA ENTRY FOR SOIL/DUST INGESTION (by year) 

Soil/dust ingestion 

Age = 0-1 year (0-11 mo), 0.085 g/day 

1-2 years (12-23 mo) 0.135 

2-3 years (24-35 mo) 0.135 

3-4 years (36-47 mo) 0.135 

4-5 years (48-59 mo) 0.100 

5-6 years (60-71 mo) 0.090 

6-7 years (72-84 mo) 0.085 

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TABLE 3-1 (cont'd). DEFAULT VALUES FOR MODEL PARAMETERS 

PARAMETER DEFAULT VALUE UNITS

DATA ENTRY FOR DUST (by year) 

Dust lead concentration 

1-2 years (12-23 mo) 0 Fg/g 

2-3 years (24-35 mo) 0 

3-4 years (36-47 mo) 0 

4-5 years (48-59 mo) 0 

5-6 years (60-71 mo) 0 

6-7 years (72-84 mo) 0 

DATA ENTRY FOR SOIL/DUST MULTIPLE SOURCE ANALYSIS (constant) 

Ratio of dust lead concentration to soil lead concentration 0.70 unitless 

Ratio of dust lead concentration to outdoor air lead concentration 100 Fg Pb/g dust per 

Fg Pb/m3

 air 

DATA ENTRY FOR SOIL/DUST MULTIPLE SOURCE ANALYSIS WITH ALTERNATIVE 

HOUSEHOLD DUST LEAD SOURCES (constant) 

Concentration 

household dust 150 Fg/g 

secondary occupational dust 1,200 

school dust 200 

daycare center dust 200 

second home 200 

interior lead-based paint 1,200 

Percentage 

household dust 100 minus all other % 

secondary occupational dust 0 

school dust 0 

daycare center dust 0 

second home 0 

interior lead-based paint 0 

BIOAVAILABILITY DATA ENTRY FOR ALL GUT ABSORPTION PATHWAYS

Total lead absorption (at low intake) 

diet 50 % 

drinking water 50 

soil 30 

dust 30 

alternate source 0 

Fraction of lead absorbed passively at high intake 

diet 0.2 unitless 

drinking Water 0.2 

soil 0.2 

dust 0.2 

alternate source 0.2 

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TABLE 3-1 (cont'd). DEFAULT VALUES FOR MODEL PARAMETERS 

PARAMETER DEFAULT VALUE UNITS

DATA ENTRY FOR ALTERNATE SOURCES (by year) 

Total lead intake 

Age = 0-1 year (0-11 mo), 0 Fg/day 

1-2 years (12-23 mo) 0 

2-3 years (24-35 mo) 0 

3-4 years (36-47 mo) 0 

4-5 years (48-59 mo) 0 

5-6 years (60-71 mo) 0 

6-7 years (72-84 mo) 0 

DATA ENTRY MENU FOR MATERNAL-TO-NEWBORN LEAD EXPOSURE

Mother's blood lead level at time of birth 2.5 Fg/dL 

DATA ENTRY MENU FOR PLOTTING AND RISK ESTIMATION

Geometric standard deviation for blood lead, GSD 1.6 unitless 

Blood lead level of concern, or cutoff 10 Fg/dL 

COMPUTATION OPTIONS

Iteration time step for numerical integration 4 h 

(1) comparison of predicted values from the Integrated Exposure/Uptake 

Biokinetic (IEUBK) model with actual blood lead levels observed in a 

blood lead and environmental lead field study such as illustrated in Table 

3-2.; 

(2) risk estimation using predicted values from the IEUBK model with actual 

environmental lead levels observed in an environmental lead field study; 

(3) estimation of the effect of variability in environmental lead levels on the 

distribution of blood lead levels in the population; 

(4) sensitivity analyses on the impact of environmental lead exposure. 

The input data file for a batch run must be created outside the IEUBK model using whatever 

text editor the user prefers. The following conventions MUST be observed in creating the 

batch file: 

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1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

TABLE 3-2. FORMAT FOR BATCH MODE INPUT DATA FILE

(SIMULATED DATA)

Header line 1> INPUT DATA FILE FOR A MONTE CARLO SIMULATION 

Header line 2> FIRST THREE COLUMNS RANDOM NOS. FOR SOIL, DUST, BLOOD 

Header line 3> ID FAM NBHD AGE PBS PBD PBW PBA ALT PBB 

FP-1 PIONEER_HILL 18 510.0 457.8 4.0 0.1 0.0 2.6 

FP-2 PIONEER_HILL 18 200.0 159.8 4.0 0.1 0.0 2.3 

FP-3 PIONEER_HILL 18 373.1 475.3 4.0 0.1 0.0 3.4 

FP-4 PIONEER_HILL 18 1042.5 1361.6 4.0 0.1 0.0 8.7 

FP-5 PIONEER_HILL 18 519.2 332.7 4.0 0.1 0.0 2.9 

FP-6 PIONEER_HILL 18 3123.6 1117.6 4.0 0.1 0.0 6.3 

FP-7 PIONEER_HILL 18 1938.2 1295.8 4.0 0.1 0.0 4.9 

FP-8 PIONEER_HILL 18 287.5 649.9 4.0 0.1 0.0 11.8 

FP-9 PIONEER_HILL 18 1227.0 1997.5 4.0 0.1 0.0 23.3 

FP-10 PIONEER_HILL 18 321.7 405.5 4.0 0.1 0.0 4.4 

FR-1 RIVERSIDE 18 631.9 58.4 4.0 0.1 0.0 5.6 

FR-2 RIVERSIDE 18 55.7 23.9 4.0 0.1 0.0 2.0 

FR-3 RIVERSIDE 18 336.3 658.6 4.0 0.1 0.0 4.1 

FR-4 RIVERSIDE 18 666.9 221.5 4.0 0.1 0.0 3.2 

FR-5 RIVERSIDE 18 2005.6 1532.1 4.0 0.1 0.0 26.2 

FR-6 RIVERSIDE 18 394.8 92.7 4.0 0.1 0.0 2.3 

FR-7 RIVERSIDE 18 1183.3 692.8 4.0 0.1 0.0 2.7 

FR-8 RIVERSIDE 18 450.8 83.6 4.0 0.1 0.0 2.4 

FR-9 RIVERSIDE 18 210.2 94.7 4.0 0.1 0.0 1.5 

FR-10 RIVERSIDE 18 650.6 682.0 4.0 0.1 0.0 4.5 

FR-11 RIVERSIDE 18 238.4 314.2 4.0 0.1 0.0 2.0 

FR-12 RIVERSIDE 18 256.6 48.0 4.0 0.1 0.0 2.0 

FR-13 RIVERSIDE 18 636.2 219.6 4.0 0.1 0.0 4.4 

FR-14 RIVERSIDE 18 100.3 31.5 4.0 0.1 0.0 3.2 

FB-1 BRIDGE_ST 18 678.6 605.4 4.0 0.1 0.0 10.0 

FB-2 BRIDGE_ST 18 249.5 136.3 4.0 0.1 0.0 2.0 

FB-3 BRIDGE_ST 18 291.5 127.8 4.0 0.1 0.0 4.1 

FB-4 BRIDGE_ST 18 750.9 2514.8 4.0 0.1 0.0 4.5 

FB-5 BRIDGE_ST 18 89.3 135.4 4.0 0.1 0.0 3.3 

FB-6 BRIDGE_ST 18 943.2 282.4 4.0 0.1 0.0 6.7 

FB-7 BRIDGE_ST 18 1668.6 369.2 4.0 0.1 0.0 11.9 

FB-8 BRIDGE_ST 18 1399.1 503.0 4.0 0.1 0.0 6.0 

FB-9 BRIDGE_ST 18 1226.8 503.0 4.0 0.1 0.0 5.9 

FB-10 BRIDGE_ST 18 1905.1 978.3 4.0 0.1 0.0 4.6 

FB-11 BRIDGE_ST 18 366.3 2727.8 4.0 0.1 0.0 13.4 

FB-12 BRIDGE_ST 18 62.5 464.7 4.0 0.1 0.0 3.9 

FB-13 BRIDGE_ST 18 75.8 49.3 4.0 0.1 0.0 5.4 

FB-14 BRIDGE_ST 18 393.5 88.6 4.0 0.1 0.0 1.2 

FB-15 BRIDGE_ST 18 461.6 883.7 4.0 0.1 0.0 1.7 

FB-15 BRIDGE_ST 18 461.6 883.7 4.0 0.1 0.0 1.9 

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• The input data file must be an ASCII file with no special characters. 

• The data set must have a DAT extension (i.e., [name].DAT). 

• The first three lines of the input data file can be any identifiers that the user 

requires; we usually use the first line for the run name, the second line for 

modelling options used in the run, and the third line as headers for variables 

in the data set; 

• The data fields are entered format-free, although the use of regular spacings 

and alignment of decimal points are recommended to improve readability; 

• Maximum width 80 columns; 

• Variable values should be separated by spaces; 

• Missing values must be shown by an isolated decimal point as in some 

examples in Chapter 5; 

• Each line in the input data file must contain the following 10 variables: 

1. Child identifier or code 

2. Family or residence unit identifier or code 

3. Area or neighborhood identifier code 

4. Child's age in months 

5. Soil lead concentration in Fg Pb/g 

6. Dust lead concentration in Fg/g 

7. Drinking water lead concentration in Fg/L 

8. Air lead concentration in Fg/m3 

9. Daily intake of lead from other sources, Fg Pb/day 

10. Observed child blood lead level. 

In Chapter 5 we will demonstrate an approach to using the IEUBK model in the batch 

mode option. Soil, dust, and blood lead "data" were simulated using realistic parameters for 

sites with active air lead point sources. The attached Table 3-2 shows a batch mode input 

data file for 40 children. All were assumed to be 18 months old and had default air, water, 

and alternate source lead values. The first three columns in Table 3-2 are the child identifier, 

the family identifier (note simulated twins as ID 39 and 40), and the "neighborhood". These 

fields could be any alpha-numeric identifiers defined by the user. 

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3.4 OUTPUTS FOR DOCUMENTATION, BRIEFING, AND 

PRESENTATION 

3.4.1 Overview of Output Options 

The IEUBK model includes some output options that facilitate presentation of the results 

and testing of the results for parameter sensitivity. These options may be a useful part of the 

documentation for decisions in which the IEUBK model plays a role. We will first describe 

the output options, and then show some of their applications. Some sensitivity analyses can 

be facilitated by the use of these options. 

3.4.1.1 Plotting (Option 2) 

Single-Plot Options (Selections 2 and 3) 

Some plot options can be used with single runs of the IEUBK model, and others require 

multiple runs. Single-run options include: 

• Plotting the log-normal probability density function of blood lead levels for 

a single exposure scenario predicting geometric mean blood lead (Selection 

3); 

• Plotting the cumulative probability distribution for exceeding any user 

specified blood lead level of concern for a single exposure scenario 

(Selection 2). This is sometimes called the exceedance probability 

distribution. 

The probability density function gives most users a better idea of the spread of blood 

lead levels for children exposed to a single set of environmental lead concentrations. The 

exceedance probability distribution may be used to visually estimate the fraction of children 

above a blood lead level of concern for the single-exposure case (e.g., what fraction of 

children are above 10 Fg/dL), or to visually estimate the blood lead level corresponding to a 

specified fraction of children (e.g., what blood lead concentration encompasses 95% of the 

children). The user may route the probability plots to a printer after viewing the display. 

Multiple-Plot Options (Selections 1, 4, and 5) 

There are additional features that allow the user to combine output from several runs 

onto single plots. These multiple-run options include: 

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• Overlaid plots of the log-normal probability density functions of blood lead 

levels for multiple exposure scenarios, where each run increases the lead 

concentration in a specified medium by a user-defined amount (Selection 5); 

• Overlaid plots of the cumulative exceedance probability distributions of 

blood lead levels for multiple exposure scenarios, where each run increases 

the lead concentration in a specified medium by a user-defined amount 

(Selection 4); 

• Plots of geometric mean blood lead levels versus environmental lead levels 

for the medium whose values are varied (Selection 1). 

Selection 1 cannot be used unless the user has previously created an output file from the 

Computation Menu, designated *.PBM. Selections 4 or 5 cannot be used unless the user has 

previously created an output file from the Computation Menu, designated *.LAY. 

The overlaid probability density functions give most users a better idea of how the 

probability of exceeding a blood lead level of concern increases with each increment in 

environmental lead. The exceedance probability distributions may be used to estimate the 

increases in the fraction of elevated blood lead levels or to visually estimate the 

environmental lead levels corresponding to a specified fraction of non-protected children 

above the level of concern. 

3.4.1.2 Uses of Batch Mode Analysis (Option 4) 

Results from multiple exposure scenarios can be accumulated using the batch mode 

options. For sensitivity analyses involving constant concentrations in air, water, dust, soil, 

or an alternate medium whose intake is constant, it is possible to create a batch mode input 

file in which each line represents a different case for the analysis. However, with Option 4 it 

is only possible to carry out sensitivity analyses in which the cases differ on the basis of 

concentration. Other types of sensitivity analyses require the accumulation of single runs in 

an overlay file. 

Another application in which batch mode methods are useful is a Monte Carlo analysis 

in which all the modelled variability is assigned to differences in the environmental 

concentrations. The results can be stored in a batch mode output file which may then be used 

for statistical analyses. 

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3.4.2 Detailed Instructions on Output Options 

3.4.2.1 Save Output from a Single Run 

1. Develop an exposure scenario. 

2. Run the model (Selection 2 on Computation Menu, or F5 from any Data 

Entry Menu). 

3. Save results (Selection 2 after running the model). Results may be 

appended to the file RESULTS.TXT, or added to an overlay plot file 

defined by the user with name [name].LAY. 

4. Results may be sent to a printer. 

3.4.2.2 Save Output from Multiple Runs for Probability Plots (Option 3 on Range 

Selection Menu) 

1. Develop an exposure scenario 

2. Use the Multiple Runs option (Option 2) on the Computation Menu. 

1- Select the medium (Soil, Dust, Air, Water, Diet) 

2- Select the lower and upper values for the medium 

4- OUTPUT CHOICES 

- Select number of steps from small to large 

- Send results to overlay file RANGE(#+1).LAY, where the output 

file is automatically named by increasing the index of the largest 

numbered (#) current RANGE#.LAY file. 

3. Results may be sent to a printer. 

3.4.2.3 Save Output from Multiple Runs for Media-Level Plots (Option 3 on the 

Computation Menu) 

1. Develop an exposure scenario 

2. Use the Media Run option (Option 3) on the Computation Menu. 

1- Select the medium (Soil, Dust, Air, Water, Diet) 

2- Select the lower and upper values for the medium 

4- OUTPUT CHOICES 

- Select number of steps from small to large

- Change the age range for calculating mean blood lead.

- Send results to overlay file MEDBLD(#+1).PBM, where the output file is

automatically named by increasing the index of the largest current 

MEDBLD#.PBM file. 

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3. Results may be sent to a printer. 

3.4.2.4 Save Output from a Batch Mode Run (Option 4 on the Computation Menu) 

1. Create a batch mode input data file, [name].DAT. 

2. Use the Batch Mode Run option (Option 4) on the Computation Menu. 

3. Load the [name].DAT file you have created. 

4. Rename the output data file [newname].* if required in the Run step. 

5. Run the model. 

The output data sets are named [newname].ASC and [newname].TXT, or 

[name].ASC and [name].TXT if not renamed. 

3.4.2.5 Probability Plots for Single Runs 

For Current Runs Using Option 2 on Output Menu: 

1. Run the model with user-defined exposure scenario in Option 2 on Output Menu. 

2. Then choose Selection 2 or 3 in the Graphics Selection Menu. 

3. Choose the Age Range. 

4. Print graph, without exiting, by using the F10 key, then selecting printer type. 

If the user has exited from the current Run, but has not done any further runs, then 

Steps 3 through 5 can be executed by returning to the Graphics Menu and executing 

Option 2 or 3. 

For Current Runs Using Option 2 on Output Menu: 

1. Run the model with user-defined exposure scenario in Option 2. If the user has 

aborted the runs in Option 2, but has not done any runs since, then the last 

complete run may be plotted as above. The procedure is: 

2. Select Option 3 in the Main Menu, then option 2 on the Output Menu. 

3. Then choose Selection 2 or 3 in the Graphics Selection Menu. 

4. Choose the Age Range. 

5. Print graph, without exiting, by using the F10 key, then selecting printer type. 

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3.4.2.6 Probability Plots for Multiple Runs 

1. Run the model with user-defined exposure scenario in Option 2 on the 

Computation Menu. Do not abort the runs in Option 2. 

2. Select Option 3 in the Main Menu, then Option 2 on the Output Menu. 

3. Then choose Selection 4 or 5 in the Graphics Selection Menu. 

4. Identify the *.LAY data set to plot. 

5. Choose the Age Range. 

6. Print graph, without exiting, by using the F10 key, then selecting printer type. 

3.4.2.7 Multi-Level Plots for Blood Lead Versus Media Lead 

1. Run the model with user-defined exposure scenario in Option 2 on the 

Computation Menu. 

2. Select Option 3 in the Main Menu, then Option 2 on the Output Menu. 

3. Then choose Selection 1 in the Graphics Selection Menu. 

4. Identify the MEDBLD#.PBM data set to plot. 

5. Print graph, without exiting, by using the F10 key, then selecting printer type. 

Batch mode files can be used for display or documentation through the statistics 

module on the Batch Mode Menu, Option 4. 

3.4.3 Recommendations on Multi-Level Soil Lead Exposure Scenarios 

The IEUBK model carries out multi-level analyses by increasing the concentration of 

the user-specified medium by equal steps at each run, and holding everything else constant. 

When evaluating different soil lead exposure scenarios, it may be preferable to keep a 

constant soil-to-dust coefficient so that dust lead exposure increases with increasing soil lead 

exposure. This can be done by first invoking the Multiple Source Analysis for dust and 

defining the dust lead to soil lead coefficient. This is particularly important if some 

component of the soil lead abatement is expected to permanently alter the soil to dust 

pathway. 

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