305268 ADMINISTRATIV E RECOR D

BASELINE HUMAN HEALTH RISK ASSESSMENT F OR THE CALIFORNIA GULCH SUPERFUND SITE

PART C

EVALUATION OF WORKER SCENARIO

APRIL 1995

Prepared for:

U.S. Environmental Protection Agency Region Vff l One Denver Place

999 18th Street, Suite 500 Denver, Colorado 80202-2405

E PA Work Assignment No. Document Control No. 4800-32-0090

Prepared by:

R OY F. WESTON, INC.

215 Union Boulevard, Suite 550 Lakewood, Colorado 80228-1622
Foreword

This document is a portion of one of three parts of the baseline human health risk assessment

at the California Gulch Superfund Site. Although this part (Part C) was prepared first (prior to

the completion of Parts A and B), the text makes reference to the planned contents of Parts A

and B so that Part C may be combined with these sections without further editing after they are

completed.

This assessment has been performed following extensive consultation with EPA Headquarters

offices , regional offices , and the Agency's Technical Review Workgroup for Lead. This

assessment represents Region VIIFs best estimate of risk based on exposure parameters specific

to the California Gulch site. Use of these parameters at other sites without careful consideration

of site-specific information is discouraged.

Baseline Human Health Risk Assessment for the April 1995

California Gulch Superfund Site — Part C - Worker Page - ii THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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TABLE OF CONTENTS

Section Title

Forward ............................................. ii

1.0 Introduction ........................................... 1

1.1 Site Description and History ............................. 1

1.2 Final Human Health Risk Assessment ....................... 1

1.3 Approach to Part C of the Risk Assessment .................... 2

2.0 Lead Evaluation ......................................... 3

2.1 Overview ........................................ 3

2.2 Population of Principle Concern ........................... 4

2.3 Target Blood Lead Levels in Pregnant Women .................. 5

2.4 Measured Blood Lead Values in Women hi Leadville .............. 5

2.5 Predicted Blood Lead Levels in Pregnant Women ................ 6

2.5.1 Basic Equation ................................. 7

2.5.2 Input Parameters ................................ 7

2.5.3 Results .................................... 13

2.6 Calculation of Workplace Soil Action Levels for Lead ............ 13

2.6.1 Overview ................................... 13

2.6.2 Basic Equation ................................ 15

2.6.3 Uncertainty PDFs .............................. 16

2.6.4 Results .................................... 20

2.6.5 Comparison of Action Levels with Measured Concentrations .... 20

2.6.6 Sensitivity Analysis ............................. 20

2.7 Weight-Of-Evidence Evaluation .......................... 20

3.0 Arsenic Evaluation ...................................... 24

3.1 Predicted Arsenic Risks hi Leadville Workers ................. 24

3.1.1 Basic Equations ............................... 24

3.1.2 Input Parameters ............................... 24

3.1.3 Results .................................... 27

3.2 Calculation of Workplace Soil Action Level for Arsenic ........... 29

3.2.1 Basic Equation ................................ 29

3.2.2 Uncertainty PDFs .............................. 30

3.2.3 Results .................................... 31

3.2.4 Comparison with Site Concentrations .................. 34

4.0 Discussion and Conclusions ................................. 36

5.0 References ........................................... 37

Baseline Human Health Risk Assessment for the April 1995

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LIST OF TABLES

Table Title

1 Summary of Variability Distribution Functions For Estimation of Lead Exposure

in Workers

2 Summary of Uncertainty Distribution Functions For Estimation of Lead Soil Action Level

3 Summary of Variability Distribution Functions For Estimation of Arsenic

Exposure in Workers

4 Summary of Uncertainty Distribution Functions For Estimation of Arsenic Soil Action Level

LIST OF FIGURES

Figure Title

1 Uncertainty in Soil Action Level for Lead

2 Lead Isoconcentration Map

3 Uncertainty in Soil Action Level for Arsenic

4 Arsenic Isoconcentration Map

APPENDIX A — ESTIMATION OF LEAD BKSF

APPENDIX B — SENSITIVITY ANALYSIS OF BOWERS MODEL

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EVALUATION OF WORKER SCENARIO

1.0 INTRODUCTION

1 .1 SITE DESCRIPTION AND HISTORY

The California Gulch Superfund Site is located in and around the community of Leadville, Colorado, about 100 miles southwest of Denver. Leadville was the site of extensive mining, milling and smelting operations beginning about 1860. Most of the operations had ceased by

about 1900, although several facilities continued operations into the 1920s (Western Zinc) and

the 1960s (AV Smelter) (Walsh 1993). Nearly all of the mines within the site boundaries are

presently inactive and all of the mills and smelters have been demolished. Part A of this report

presents a more detailed history of the mining and refining operations hi Leadville, along with

detailed site maps.

The site was placed on the National Priorities List (NPL) in 1983 mainly because of concern

over the impact of mine drainage on surface waters hi the California Gulch and the Arkansas River. Subsequent site investigations revealed the presence of a number of heavy metals in soils

in and around the current residential and commercial areas of Leadville, and a preliminary risk

assessment (WESTON 1991) indicated that contaminant levels were high enough to be of

potential human health concern. Lead and arsenic were identified as being the primary

chemicals of potential human health concern.

1 .2 FINAL HUMAN HEALTH RISK ASSESSMENT

Since the tune the site was placed on the NPL, the U.S. Environmental Protection Agency

(EPA) and a number of Potentially Responsible Parties (PRPs) have performed a variety of

studies to define the nature and extent of contamination at the site and to help evaluate the level

of risk which site contaminants pose to humans. Based on these data, the EPA is preparing a Final Baseline Human Health Risk Assessment for the site. This comprehensive risk assessment

will consist of three main parts, as follows:

• Part A is to evaluate the risks which lead hi the environment poses to current and

future residents of the community

• Part B is to evaluate the risks which metals other than lead pose to current and

future residents of the community

• Part C is to evaluate the risks which environmental contamination poses to current

or future workers hi the commercial and business district of the community, and

to people who engage hi recreational activities (hunting, hiking, bike riding,

picnicking, etc.) hi areas hi and around the community.

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superfund Site — Part C - Worker Page -1 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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This document is one portion of Part C of the risk assessment, covering populations exposed to

environmental contaminants in the workplace.

1.3 APPROACH TO PART C OF THE RISK ASSESSMENT

In response to concerns raised by Leadville officials and business leaders over potential liabilities

associated with development of businesses within the Superfund site, EPA committed to

performing an "expedited" risk evaluation to determine, as quickly as possible, if environmental

contamination was of concern at any locations presently zoned for commercial and industrial

purposes, and if so, to define where remedial actions were and were not needed. Similarly, in

order to address potential concerns regarding the development of a proposed bike path around

the community, EPA committed to performing an expedited evaluation of potential risks

associated with recreational land use.

In order to perform these risk assessments on an accelerated schedule, EPA incorporated the

followin g assumptions and approaches into the standard risk assessment procedures:

1. The assessments focus only on lead and arsenic. Even though other metals occur

at elevated concentrations hi the environment around Leadville (e.g., see WESTON 1991), experience at other sites, as well as the results of preliminary

calculations at this site, indicate that lead and arsenic are the "risk drivers". Thus, focusing on these two chemicals is not likely to underestimate risk.

2. The assessments focus only on exposure to soil and dust, and only by the

ingestion pathway. Exposure to other media (e.g., waste piles, sediments,

surface water, etc.) and exposure to soil/dust via other pathways (e.g., dermal,

inhalation of particulates) are considered to be of minor concern for workers.

3. Rather than calculating risk at all specific properties and locations where

commercial land use is possible, calculations were performed for both lead and

arsenic to identify concentrations ("action levels") in soil which were of potential

concern, and these concentrations were compared to findings of remedial

investigations of soil concentration values in order to identify locations where

these values might be exceeded.

The specific methods used for calculating action levels for lead and arsenic hi soil are detailed

below, along with the results of the evaluations for commercial land use scenarios.

Baseline Human Health Risk Assessment for the April 1995

California Gulch Superfund Site — Part C - Worker Page - 2 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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2.0 LEAD EVALUATION

2.1 OVERVIEW

The health risks which lead poses to a specified population can often be investigated in two

different ways:

• Direct measurement of blood lead values hi members of the population of concern

• Measurement of lead hi environmental media, and calculation of the range of

risks those levels of lead could pose to individuals or populations

As discussed below, each of these approaches has some advantages and some limitations, and

the best assessment of lead risks incorporates the results of both types of approaches.

Blood Lead Monitoring

One way to investigate the human health risks from lead in the environment is to measure the

concentration of lead in the blood (PbB) hi randomly-selected members of the population of

concern. The health risks associated with these measured PbB values can be evaluated by

comparison te current guidelines for acceptable values. Blood lead studies that also include

reliable environmental and demographics data can provide valuable insights into the media and

exposure pathways that are the primary sources of concern hi a population.

However, there are some limitations to the use of blood lead measurements as the only index

of lead risk. First , care must be taken to ensure that a sufficient number of people are studied,

and that these people are a representative sub-set of the population of concern. Second, blood

lead values hi an individual may vary as a function of tune, so a single measurement may not

be representative of the long-term average value hi that individual. Third, it is expected that

blood lead values will differ between individuals, even when they are exposed under the same

environmental conditions. Thus, an acceptable blood level measured in one individual (e.g., a

worker at a commercial establishment) does not necessarily mean that some other individual

(e.g., some other worker who might be exposed at the same location hi the future) might not

have a higher (and possibly unacceptable) blood lead level. Fourth, population-based studies are

not well-suited to detecting the occurrence of occasional sub-locations where risk is elevated,

even if average risks are acceptable. Finally , blood lead measurements reflect exposures and

risks under current site conditions, which may not always be representative of past or future site

conditions. For these reasons, results from blood lead studies may not provide a complete

description of the range of risks which might exist hi a population.

Predictive Approach

Because of the limitations hi the direct measurement approach, it is valuable to employ a

predictive as well as an empirical method for evaluation of lead risk. These models can then

be used to assess the risks from lead under conditions which cannot be measured (e.g., risks to

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superfund Site — Part C - Worker Page - 3 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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hypothetical future people in an area where there are no current exposures), to identify which

exposure pathways are likely to be contributing the largest risk to a population, and to evaluate

the likely efficacy of various remedial alternatives.

A number of predictive lead exposure models exist. For example, the EPA has developed an

integrated exposure, uptake and biokinetic (IEUBK) model to assess the risks of environmental

exposure hi residential children. In addition, models have also been developed by Bowers et.al

(1994), O'Flaherty (1993), Legget (1993) and the State of California (CEPA 1992) to assess the

effect s of lead exposure hi older children and adults. In general, these models require (as sitespecific input) information on the levels of lead hi various environmental media, and on the

amount of these media contacted by the population of concern. From this input, the models

calculate the expected levels of blood lead hi the exposed population.

However, all predictive models are subject to a number of limitations. First, there is inherent

difficulty hi providing the model with reliable estimates of human exposure to lead-contaminated

media. For example, exposure to soil and dust is difficul t to quantify because since human

intake of these media are likely to be highly variable, and it is very difficul t to derive accurate

measurements of actual intake rates. Second, it is often difficul t to obtain reliable estimates of

key pharmacokinetic parameters hi humans (e.g., absorption fraction, distribution and clearance

rates), since direct experiments in humans is not acceptable. Finally , the absorption, distribution

and clearance of lead hi the human body is an extremely complicated process, and any mathematical model intended to simulate the actual processes is likely to be an oversimplification. Thus, model calculations and predictions are usually rather uncertain.

Weight-of-Evidence Evaluation

As the discussions above make clear, there are advantages and limitations to both the direct

blood measurement approach and the UBK modeling approach. Therefore, the most appropriate

means for evaluating risks from lead is to consider the results of both analyses, taking into

account the uncertainties and limitations of each. Final conclusions regarding current and future

risk should thus be based on a balanced assessment of information from all sources.

2.2 POPULATION OF PRINCIPLE CONCERN

Usually, lead risk assessments focus on young children, since young children tend to have higher

lead exposures than older children or adults, because young children tend to absorb more lead

than do adults, and because young children are more susceptible to the adverse effect s of lead

on the nervous system. Part A of this risk assessment provides a more thorough description of

the adverse effect s of lead hi children, and presents an evaluation of the risks which lead may

pose to children who live hi Leadville.

This part of the risk assessment focuses on lead risks to workers (assumed to be adults). Within

this population, the subpopulation most likely to be of concern are pregnant women. This is

because pregnant women may tend to absorb more lead than non-pregnant women or men, and

because the fetus of the pregnant women is likely to be especially susceptible to the adverse

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superfund Site — Part C - Worker Page - 4 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR ffl PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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effect s of lead. Therefore, pregnant women and women of child-bearing age are selected as the

sub-population of principle concern.

2.3 TARGET BLOOD LEAD LEVELS IN PREGNANT WOMEN

The EPA has not yet issued formal guidance on the blood lead level that is considered

appropriate for protecting the health of pregnant women or other adults. However, EPA

recommends that there should be no more than a 5% likelihood that a young child should have

a PbB value greater than 10 ug/dL (EPA 1991b). Since the exposed worker and recreational

populations at this site are assumed to include pregnant women, and because the fetus is exposed

to lead levels nearly equal to those of the mother, the health criterion selected for use in this

evaluation is that there should be no more than a 5% chance that the fetus of a pregnant woman

would have a PbB above 10 ug/dL. This health goal is equivalent to specifying that the 95th

percentile of the PbB distribution hi fetuses does not exceed 10 ug/dL:

PbB^fetal < 10 ug/dL

The relationship between fetal and maternal blood lead concentration has been investigated hi

a number of studies. Goyer (1990) reviewed a number of these studies, and concluded that there

was no significant placental/fetal barrier for lead, with fetal blood lead values being equal to or

just slightly less than maternal blood lead values. The mean ratio of fetal PbB to maternal PbB

in three recent studies cited by Goyer was 0.90. Based on this, the 95th percentile PbB hi the

mother is then:

PbB^maternal = 10/0.90 = 11.1 ug/dL.

That is, there should be no more than a 5% chance that a pregnant women will have a blood

lead value above 11.1 ug/dL.

It is important to note that the choice of 10 ug/dL as the upper 95th percentile limit for the fetus

does not imply that exposures above this definitely cause unacceptable health effect s and that

levels below mis are definitely without risk. Rather, there is a graded increase in the severity

of adverse effect s as blood lead levels increase. Typically , frank clinical effect s are not

observed in children at blood lead levels less than 60-80 ug/dL, and effect s that occur at blood

levels of about 10 ug/dL are subtle and are generally observable only hi well-designed population

studies. Therefore, there are differences hi opinion between health professionals as to what

blood lead level should be treated as the acceptable limit. The choice of a health limit of 10

ug/dL by EPA is based on a consensus among agency scientists that effect s which begin to

appear at this exposure level are sufficiently undesirable to warrant avoidance (EPA 1991b).

2.4 MEASURED BLOOD LEAD VALUES IN WOMEN IN LEADVILLE

Data on blood lead levels in 173 adults hi Leadville were collected hi 1991 by Dr. Robert Bornschein of the University of Cincinnati. Within this group were 127 women of child-bearing

age (assumed to be age 16 to 45 years), 29 of whom were pregnant and 23 of whom were

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nursing at the time of the survey. A summary of the blood lead values observed in these women

is presented below.

Parameter

Number of people

Measured PbB Values Mean Standard deviation Geometric mean (GM) Geom. Std.Dev. (GSD) Maximum

Calculated 95th Percentile PbB

A ll Women Age 16-45

127

2.7 ug/dL

1.3 ug/dL

2.4 ug/dL

1.8

7.1 ug/dL

6.3 ug/dL

N ot pregnant

or nursing

75

2.8 ug/dL

1.3 ug/dL

2.5 ug/dL

1.7

6.8 ug/dL

6.1 ug/dL

Pregnant Women

29

2.3 ug/dL

1.3 ug/dL

1.9 ug/dL

2.1

7.1 ug/dL

6.4 ug/dL

Nursing Women

23

3.1 ug/dL

1.0 ug/dL

2.9 ug/dL

1.5

5.3 ug/dL

5.4 ug/dL

Comparison of these data with the health goal described above in Section 2.3 (95th percentile PbB = 11 ug/dL) indicate that, at the population level, current women residents of Leadville,

including pregnant and nursing women, are unlikely to be exposed to sufficient levels of lead

to be of concern.

Despite the indication that current exposures are below a level of concern, there are limitations

to these data and the results should be interpreted with some caution. First , there were a

relatively small number of women surveyed, so confidence in the population statistics (GM, GSD , 95th percentile) is only moderate. For example, the 95 % confidence interval for the mean

blood lead in pregnant women is approximately 1.5 to 3.3 ug/dL. Second, information is not

available on which (if any) of these women were exposed in the workplace, so it is difficul t to

utilize these observations to draw direct conclusions regarding the acceptability of exposures in

the workplace. Third, as noted above (see Section 2.1), blood lead data of this sort only

indicate exposures under current conditions, and may not reveal risks which could arise in the

future.

2.5 PREDICTED BLOOD LEAD LEVELS IN PREGNANT WOMEN

There are several mathematical models which have been proposed for evaluating lead exposure

in adults, including those developed by Bowers et al. (1994), O'Flaherty (1993), Legget (1993),

and the State of California (CEPA 1992). Of these, the model of Bowers et al. is most nearly

consistent with the approach employed by the EPA in the IEUBK model for children, and is also

very simple to apply. For these reasons, this method was used (with some modifications) for

calculating the concentration of lead in soil which would be of potential concern to adults

engaged in recreational activities at this site.

Baseline Human Health Risk Assessment for the April 1995

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2.5.1 Basic Equation

The Bowers model predicts the blood lead level hi an adult exposed to lead hi a specified

occupational setting by summing the "baseline" blood lead level (PbB0) (that which would occur

hi the absence of any occupational exposures) with the increment hi blood lead that is expected

as a result of occupational exposure to soil or dust. The latter is estimated by multiplying the

absorbed dose of lead from occupational soil/dust exposures by a "biokinetic slope factor"

(BKSF). Thus, the basic equation is:

PbB = PbB

0

 + BKSF*[CS*IRS*EFS*AFS + Cd*IRd*EFd*AFJ (

where:

PbB = Blood lead level (ug/dL) in a population of adults exposed to leadcontaminated soil or dust via occupational activities

PbB

0

 = "Baseline" blood lead level hi adults not exposed to lead-contaminated soil

via occupational activities, but including other background exposures,

including residential exposure

BKSF = Biokinetic slope factor (ug/dL increase in blood lead per ug/day lead

absorbed)

C = Arithmetic mean concentration (ug/g) of lead in soil (Cs) or dust (Cd),

averaged over the workplace location where exposure occurs

IR = Mean daily intake rate of soil (IRj) or dust (IRj) during occupational

activities hi areas of contamination (g/day)

EF = Exposure frequency (days/yr) to soil (EFS) or dust (EFd) during

occupational hi areas of contamination

AF = Absolute absorption fraction (bioavailability) of lead hi soil (AFS) or dust

2.5.2 Input Parameters

Most of the parameters hi this model are not constants, but vary from person to person or from

place to place. Thus, to use this model to predict the distribution of blood lead values that

would be observed hi a population of women hi the workplace, it is necessary to describe the

range and relative likelihood of values for each parameter. This is done hi the form of Probability Distribution Functions (PDFs). Once PDFs are defined for each parameter,

commercially available software systems can be used to combine the inputs and predict the

distribution of likely blood lead values hi women workers. The text below discusses what is

known about each parameter, and the PDF selected to represent each.

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Background Blood Lead Level (PbB9)

As discussed above, it is assumed the subpopulation of workers of greatest potential concern for

risks from lead are women of child-bearing age. Two sources of data are available that could

be useful in characterizing PbB

0

 for this subpopulation. First are the site-specific data collected

during the study performed hi Leadville by the University of Cincinnati in 1991 (Bornschein

1994). As noted above, this study collected data from 126 women between the ages of 16 and

45, including a sub-set of 29 pregnant women. The GM values for these two groups were 2.4

ug/dL and 1.9 ug/dL, respectively, with GSD values of 1.8 and 2.1, respectively.

A second source of information on baseline blood lead levels is available from the NHANES III

study (Brody et al. 1994). The geometric mean PbB values (ug/dL) reported for women aged

20-49 was 1.7 for whites, 2.0 for Hispanics, and 2.2 for blacks, each with GSD values close

to 2.0. Because Leadville is primarily a mixture of whites and Hispanics, these data suggest that

a GM value of about 1.9 might be expected for women in Leadville. Comparison of this value

with those from the Bornschein study suggests that women in Leadville have blood lead values

that are similar to national averages, although the value of 2.4 ug/dL for women age 16-45 is

consistent with the view that levels in Leadville women might be about 0.4-0.6 ug/dL higher

than the national average. (If so, this difference is not large enough to be of toxicological

significance in the average case).

Based on the combined site-specific data on blood lead distributions hi pregnant women and

women age 16-45, and supported by the data from the national survey, the PDF selected to

model the value of PbB

0

 is as follows:

PbB

0

 = LOGNORMAL(1.8,2.0)

BKSF

The biokinetic slope factor proposed by Bowers et al. is 0.375 ug/dL per ug/day absorbed. This

value is estimated from an observed slope of 0.06 ug/dL increase hi blood lead of adult men per

ug/L of lead in first draw water. Calculation of the BKSF from the Pocock data requires a

number of assumptions regarding how much total water was Digested, how much of this was first

draw and how much was drawn after the pipes were flushed, the decrease in lead concentration

when the pipes were flushed, and the amount of lead absorbed from the ingested water. Appendix A presents an analysis of the range of possible BKSF values which might be derived

from the Pocock study, depending on the input assumptions. Based on this analysis, EPA

believes the Pocock study data are consistent with a BKSF of about 0.4 ug/dL per ug/day

absorbed. A similar value of 0.444 can be derived from the data of Rabinowitz et al. (1974),

although this study is based on only two male individuals, so the resulting value may not be

highly representative. Calculations performed using the pharmacokinetic model developed by O'Flaherty (1993) show that BKSF is not a constant, but depends on age, sex, and lead body

burden. Estimated values range from 0.25 to 0.53 for a 25 to 35 year-old woman, assuming an

absorption fraction of 0.08 (Gradient 1995). Based on this information, the PDF selected to

model the value of BKSF is as follows:

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BKSF = UNIFORM(0.25,0.50)

It should be noted that this range of BKSF values is still based mainly on data from adult males. However, data from the NHANES in survey reveal that the blood level of men tends to be

higher than for women (Brody et al. 1994). This suggests that either men tend to have higher

exposures to lead, or that the BKSF for women is lower than for men. It is not known which

of these is true, but if the exposures are thought to be similar, then use of a BKSF based on

adult males may tend to be conservative when applied to women.

C. and C.

Data are available from a number of studies on the distribution of lead values hi soils in the

community of Leadville. These data reveal that average lead concentrations vary as a function

of location within the community, tending to be highest hi the eastern sections of town where

most of the historic mining-related activities occurred. However, for the purposes of simulating

the expected distribution of blood lead values hi current women residents, the most appropriate

data are for the community as a whole. Statistics available from several major studies are

summarized below.

Study

Walsh 1988

WESTON 1991

Bornschein 1994

COM 1994

Sample Type

Depth = 0-6"

Depth = 0-6"

Perimeter Bare Area

Depth = 0-6"

N

354

3489

202

174

2762

Mean

1890

2320

1520

1510

1900

S T D

3220

2260

2450

2290

3200

In all of these studies, the data are observed to be left-skewed in an approximately lognormal

distribution. Based on these studies, the variability hi Cs was estimated with the followin g PDF:

Cs = LOGNORMAL(2000,2500)

Only one study (Bornschein 1994) has investigated the distribution of lead levels hi 243 interior

dust samples in Leadville. These data were collected in private residences, but it seems

reasonable to assume that levels hi commercial establishments are likely to be similar. The

observed mean and standard deviation of the dust values were 850 ppm and 700 ppm,

respectively. As was the case for soils, the data are observed to be left-skewed in an

approximately lognormal distribution. Based on this, the value of Cd was modeled as:

Cd = LOGNORMAL(850,700)

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J Rs_andJRd

The parameters IRj and IRj are the average daily intake of soil and dust during occupational

exposures. Such intake is believed to occur mainly as a result of soil or dust adherence to the

hands, followed by hand-to-mouth contact. It is expected that the amount of soil and dust

ingested by workers is highly variable, depending on parameters such as:

• The type of business, and whether or not workers at the business frequently

come into direct contact with soil. EPA refers to such businesses as "contactintensive", while occupations such as office worker, teacher, storekeeper, etc.,

are considered "non-contact intensive".

• The amount of soil or dust available for adherence to the hand. For indoor

exposures, this is probably related to the dust "loading" on surfaces which

come into contact with the hands. For outdoor exposure, it is probably related

to the amount of soil that is available for direct contact (i.e., not covered with

pavement or vegetation).

• The tendency of soil or dust to adhere to the hand. This , in turn, probably

depends on the particle size and moisture content of the soil or dust, and

possibly the amount of moisture on the hand as well

• The frequency of hand-to mouth contact by workers followin g contact with

contaminated dust or soil

Based on information provided by the Leadville Chamber of Commerce, most businesses in Leadville fall into the "non-contact intensive" category. This includes 65 retail stores, 21 offic e

buildings, 22 restaurants, 13 motels/hotels, and 46 service-type businesses. Of the relatively few

"outdoor businesses" (lumberyard, gas stations, yard maintenance service, etc), many have

paved parking or working areas, and are not likely to involve extensive and repeated contact

with soil.

There are relatively few studies on the amount of soil and dust ingestion by adults, and there are

no direct measurements of soil/dust ingestion during non-contact intensive occupational activities. Thus, there is very high uncertainty associated with selection of these parameters. To address

this uncertainty, the EPA (1993) has issued draft guidance on recommended defaul t soil and dust

intake by non-contact intensive workers, as follows:

Central tendency = 50 mg/day Reasonable maximum = 100 mg/day

These recommendations are adopted for use in this assessment, and are expressed as a PDF as

follows:

= TRIANGULAR(10,30,120)

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This PDF has a mean of approximately 50 mg/day and a 95th percentile of approximately 100 mg/day , consistent with EPA recommendations.

E F, and EFd

There are no site-specific data on the number of days each year a worker is at work, but draft EPA guidance (EPA 1993) recommends an assumed central tendency exposure frequency at the

workplace of 219 days per year and an RME value of 250 days per year. Assuming a lower

bound of 200 days/yr, the total number of days at work is modeled as:

EFfctf = TRIANGULAR(200,219,250)

As noted above, most businesses in Leadville are not soil-contact intensive, so most exposure

is expected to be associated with dust ingestion while indoors at the workplace. However, some

workers may spend some days, or parts of some days outside. There are no data on the amount

of time spent outdoors by workers in Leadville, but because there are over 150 days/year when

the ground is either frozen or snow-covered, it is expected that the maximum number of work

days when soil exposure could occur is probably not higher than 100 days/yr, with an average

value of approximately 10 days/yr. Based on these concepts, the indoor (dust) and outdoor (soil)

exposure frequencies for workers are modeled with the followin g PDFs:

E FS = TRIANGULAR(0,10,100) E Fd

 = EFtotai - EFS

A FT and

"Baseline" Absorption Fraction. A number of studies have been published on the absorption

of lead by adults. In a study with 5 adult male volunteers, Rabinowitz et al. (1980) found that

the absorption fraction depended on whether the lead was ingested along with food or was

ingested 9 hours after the last meal. For lead ingested along with food (or for lead ingested in

the diet), the absorption fraction was 8-10%. For lead ingested by 9-hr fasted subjects, the

absorption fraction was 30-37%. (No food was ingested by these subjects until hour 16). O'Flaherty (1993) reviewed several reports (including Rabinowitz et al. 1980) and concluded

that gastrointestinal absorption of lead in adults ingesting mixed diets is 4-11%, with a mean

probably about 8-9%.

Clearly the choice of the most appropriate absorption fraction depends on what is assumed

regarding the time of lead ingestion in relation to the tune of last eating. For workers, it seems

reasonable to assume that most will arrive at work shortly after having breakfast, and will also

ingest food at lunch time. Likewise, it seems reasonable to expect that most recreational visitors

will have eaten within several hours of visiting the site. Thus, EPA considers a value of 10%

likely to be representative the absorption fraction in most people, but individuals who do not eat

breakfast or lunch, or who otherwise are exposed a number of hours after the last meal, might

have an absorption fraction as high as 30%. Based on this, the PDF selected to model the

baseline absorption fraction (AF0) in workers is as follows:

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A F

0

 = TRIANGULAR(0.04,0.10,0.30)

Effect of Pregnancy. Several studies have established that calcium absorption increases about

two-fold in women during pregnancy (e.g., Heaney and Skillman 1971). Because at least some

lead absorption from the gastrointestinal tract probably occurs via calcium transport systems, it

is quite plausible that during pregnancy the absorption of lead also increases, and there are

scattered observations from recent studies which provide partial support for this conclusion

(Rothenberg et al. 1994, Manton and Angle 1995, Franklin et al. 1995). However, both the

site-specific data and data from other studies (e.g., Alexander and Delves, 1981) show that blood

lead values do not increase two-fold during pregnancy, and may even decrease. This supports

the view that the absorption fraction for lead does not increase (at least not as much as for

calcium), or that other changes in distribution and clearance kinetics occur. Based on this

information, it is assumed that the absorption fraction during pregnancy is about 1.5-times that

in non-pregnant women:

A F

0(pregnancy) = 1.5*AF0

As noted above, because observed blood lead values do not usually increase by this large a factor during pregnancy, inclusion of this adjustment without a compensatory adjustment in the BKSF term is more likely to overestimate than underestimate blood lead values during

pregnancy.

Adjustment for Unavailability in Mine Wastes. There are several studies which provide

evidence that lead in soil and mine wastes may be absorbed less-extensively than lead in food

or water. This includes a study performed by the EPA in which absorption of lead from a

composite soil sample from Leadville was measured in immature swine. Based on preliminary

analyses of the data from this study (EPA 1995), it appears that lead in the Leadville soil was

absorbed about 60-80% as much as was a known soluble form of lead (lead acetate). Thus, it

is reasonable to expect that the amount of lead absorbed from ingested soil would be about 60-

80% of the "default" value for lead absorption by pregnant women. In order to be consistent

with the current assumption regarding absorption of lead from soil that is used in the IEUBK

model (EPA 1994a), a relative bioavailability of 60% was assumed for these calculations. Data

are not available on how RBA might vary from location to location across the site, but speciation

studies indicate that there are differences in the relative abundance of differen t forms of lead in

differen t locations. In the absence of data, it is assumed that RBA could vary from about 30%

to 80%, and is modeled as follows:

RBA = TRIANGULAR(0.3,0.6,0.8)

The net absorption fraction for lead hi soil or dust is given by:

A FS d(pregnancy) = AF

0(pregnancy)*RBA

Baseline Human Health Risk Assessment for the April 1995

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Summary of Inputs

Table 1 lists the PDFs selected to model the variability in each of the inputs needed to estimate

blood lead levels in the population of pregnant women who work in Leadville.

2.5.3 Results

Monte Carlo simulations were performed (5000 iterations per simulation) using the PDFs above

to describe the variability in blood lead values predicted in women hi Leadville as a result of

workplace exposure to environmental lead. The results are summarized below.

Parameter

Geometric Mean

Average

95th Percentile

G SD

Calculated Values for Pregnant Workers

3.3

3.9

8.7

1.8

Measured Values

Women

(16-45)

2.4

2.9

6.3

1.8

Pregnant Women

1.9

2.3

6.4

2.1

As shown, the predicted population-based blood lead distribution for pregnant workers in Leadville is within the health-based goal described hi Section 2.1 (95th percentile < 11 ug/dL) ,

supporting the conclusion that current environmental exposure levels in Leadville are not likely

to be of concern to pregnant women.

Comparison of the calculated values with the values reported by Bornschein reveal that the

calculated values are higher than the measured values. This observation is consistent with two

interpretations (which are not mutually exclusive):

• The women who participated in the study were not exposed in the workplace

• One or more of the PDFs selected for use in the simulations tend to

overestimate current exposure levels in the workplace

2 .6 CALCULATION OF WORKPLACE SOIL ACTION LEVELS FOR LEAD

2.6.1 Overview

Even though both the measured and the predicted blood lead distributions in the population of

women in Leadville indicate that the risks of unacceptable exposure to lead are low, it is still

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TABLE 1. SUMMARY OF VARIABILITY DISTRIBUTION FUNCTIONS F OR ESTIMATION OF LEAD EXPOSURE IN WORKERS

Model Input

Baseline blood lead

Biokinetic slope

factor

Concentration in soil

Concentration in dust

Ingestion rate of

soil and dust at

workplace

Exposure frequency

at work

Exposure frequency

outdoors

Exposure frequency

indoors

Absorption fraction

from food and water

during pregnancy

Relative

bioavailability of

lead in soil

Abbr.

PbB

0

BKSF

c

s

c

d

iRsd

EFr

 tota F l

E FS

E Fd

A F

preg

RBA

Units

ug/dL

ug/dL per

ug/d

mg/kg

mg/kg

mg/day

days/yr

days/yr

days/yr

—

~"~

Distribution Shape

Lognormal

Uniform

Lognormal

Lognormal

Triangular

Triangular

Triangular

Calculated as

EF^ - EFS

Triangular

Triangular

Parameters of Distribution

GM = 1.8 GSD = 2.0

Min = 0.25 Max = 0.50

Mean = 2000 S TD = 2500

Mean = 850

STD = 700

Min = 10 Mode = 30 Max = 120

Min = 200 Mode = 219 Max = 250

Min = 0 Mode = 10 Max = 100

—

Min = 0.06 Mode = 0.15 Max = 0.45

Min = 0.3 Mode = 0.6 Max = 0.8

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possible that there are sub-locations within the community where the concentrations of lead are

sufficiently high to pose a risk to individuals exposed at those locations, now or in the future. If such locations exist, they might not have been detected by either the measurement of blood

lead or the calculation of predicted values if a) no women are currently exposed at those areas,

b) women are exposed, but the areas are relatively small compared to community as a whole,

or c) if, by chance, no women with higher than average intakes of soil or dust were exposed hi

these areas.

One way to estimate the maximum soil concentration at some specified workplace or recreational

area that is not of concern to pregnant workers or recreational visitors is to find the soil

concentration that gives a 95th percentile PbB value of 1 1 ug/dL. The steps needed to achieve

this solution are discussed below.

2.6.2 Basic Equation

Recall that the basic equation used to predict blood lead in an exposed individual is:

P bB = PbB

0

 + BKSF*[CS*IRS*EFS*AFS + C/IR/EF/AF J 

Because this equation contains terms for both soil and dust exposure, it cannot be solved for the

soil term (Cs) unless the dust term (C<,) is defined as a dependent variable whose value can be

predicted from the value of soil. Assuming that soil comprises some (but not all) of the mass

of indoor dust, the concentration of lead hi dust can be described using an equation of the

followin g form:

Cd = D

0

 + Ksd*Cs

where:

D

0

 = Concentration of lead in dust that is not due to contamination from soil at the

workplace

Ksd = Mass fraction of dust that comes from outdoor soil at the workplace

Substituting this expression into the basic equation above and solving for the value of Cs which

corresponds to some specified target blood lead value yields:

Cs = (a - c*D

0)/(b + c*Ksd)

where:

a = (PbB^et - PbB

0)/BKSF

b = IRS*EFS*AFS

c = IRd*EFd*AFd

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2.6.3 Uncertainty PDFs

The desired value for each of the input parameters above is the true mean. If these true means

were known, then the equation would yield a single numeric value (the action level) that is equal

to the soil lead concentration corresponding to a 5% chance that any woman exposed at that

workplace would have a blood lead value above 11 ug/dL. However, there is substantial

uncertainty in the true mean for most of these variables. Therefore, each input parameter was

described by a PDF which describes uncertainty about the true mean, and these PDFs were used

in a Monte Carlo simulation to estimate the plausible range of the true action level. It is

important to distinguish this analysis of uncertainty around the true action level from the

analysis of variability in community blood lead levels presented above in Section 2.5.

Target Blood Lead Level

As discussed earlier, EPA has chosen 11.1 ug/dL as the upper 95th percentile of the acceptable

blood lead distribution in exposed women. This value can be used to estimate the geometric

mean of the blood lead distribution if the GSD is known, using the followin g equation::

PbBG Mtarget = 11.1/GSD; 164 5 (3)

The GSD, in this equation is intended to describe the individual variability between differen t

people in the amount of environmental media which they ingest, in the fraction of the lead which

they absorb from those media, and in the increment which that absorbed lead causes on their

average PbB value. Normally, values of GSD; are estimated from observed distributions of PbB

values in a population. The observed GSD from the population is referred to as GSDP. At this

site, the measured GSDp value hi women age 18-40 was 1.7 (N = 66), and in pregnant women

was 2.1 (N = 29).

T he relationship between GSD p and GSD( is usually difficul t to resolve. Conceptually, a GSDp value reflects variability of two main types: 1) variability hi individual activity patterns and

toxicokinetic factors, and 2) variability hi the concentrations of lead in environmental media. The first component is equal to GSDj. Thus, empirical GSDp

s represent an upper bound on the

value of GSDt.

EPA has described a general method for estimating GSDS from a data set by stratifying the

population into groups with similar environmental exposure levels (EPA 1994a). This

stratification tends to reduce the contribution due to environmental variation, and the value of GSD p

 will tend to approach GSDi . The results of this approach using the site-specific data for

women of child-bearing age at this site yields the followin g results:

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Area

A

B

C

D

E

F

G

H

N

8

7

21

12

3

2

4

2

G SD

2.0

1.5

1.8

1.5

1.5

1.4

1.4

1.2

Interpreting these sub-population GSDp values as GSD; values is complicated because exposures

in sub-areas may not really be uniform (this is of special likelihood in Leadville), and because

the value tends to become statistically unstable as the number of people in the subpopulation

becomes small. Nevertheless, the analysis by subareas generally supports the conclusion that

the GSDt is probably lower than the population-based value of 1.7. Based on these

considerations, the PDF selected to describe the range of possible true mean values for GSDS is:

GSD; = TRIANGULAR(1.4,1.6,1.8 )

Baseline Blood Lead (PbBn)

As discussed above, site specific data identify a geometric blood lead value of 2.5 for women

of child-bearing age and 1.8 for pregnant women in Leadville (Bornschein 1994). Comparison

of these values with the national mean of about 2.0 for women age 20-40 suggests that women

hi Leadville may have blood lead values that are perhaps about 0.5-0.6 ug/dL higher than the

national average. If so, this is most likely due to the higher-than-average exposure to lead hi

the home or hi the general community. To the extent that the measured GM blood lead value

does include contributions from the environment that will be addressed as part of the residential

risk assessment, it is not appropriate to include this contribution hi the derivation of the PRG

for recreational areas. In essence, this would require these areas to meet a more stringent goal

to account for the exposures occurring hi other areas. Based on these considerations, the PDF

selected to describe the range of plausible values for the true GM PbB

0

 is:

PbB

0

 = TRIANGULAR(1.7,2.0,2.5)

Soil/Dus t Relationship (Dn and Ksd)

The normal EPA default assumption is that the concentration of contaminants in indoor dust are

equal to those hi outdoor soil (EPA 1989, 1994a). However, this assumption has proved to be

overly conservative at most mining sites. At Leadville, the University of Cincinnati obtained

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paired measurements of lead concentrations in soil and dust at about 200 locations (Bornschein

1994). Based on simple mass-fraction considerations, the contribution of soil to dust can be

described by an equation of the form:

Cd = D

0

 + K^C,

where:

D

0

 = Concentration of lead in dust due to sources other than yard soil

= Mass fraction of yard soil in indoor dust

Finding the best-fit values for these two parameters (D0, K^ is complicated by the effect of

measurement error, which tends to obscure any relationships which do exist. As discussed in Part A of this risk assessment, one approach that is fairly insensitive to the effect s of

measurement error is to estimate D

0

 as the mean dust concentration in locations where the

concentration hi outdoor soil is low (e.g., less than 300 ppm), and to estimate K^ as:

.IP-".

where:

D = Average concentration of lead in dust S = Average concentration of lead in soil

Based on this analysis, the estimated values are:

DO = 500 ppm

= 0.26

Because D

0

 reflects the contribution of sources outside the boundaries of a property to

contamination of dust at that property, EPA does not consider it appropriate to include this term

when calculating an action level. In essence, this would penalize a property and require a more

stringent clean-up than if adjacent areas were not contaminated. Therefore, for the purposes of

this calculation, D

0

 is set to zero. Because of the relatively high uncertainty in the calculated

value for K^, this parameter was described with the followin g PDF:

= TRIANGULAR(0.2,0.25,0.6)

Other Parameters

All of the other parameters needed to calculate the nominal action level for lead in workplace

soil are the true means from the variability distributions discussed in Section 2.5 above. Professional judgement was used to select PDFs that describe the range of plausible values for

the trues means, as summarized hi Table 2.

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TABLE 2. SUMMARY OF UNCERTAINTY DISTRIBUTION FUNCTIONS F OR ESTIMATION OF LEAD SOIL ACTION LEVEL

Model Input

Individual geometric

standard deviation

Baseline blood lead

Biokinetic slope factor

Ingestion rate of

soil and dust

Exposure frequency at

work

Exposure frequency

outdoors

Exposure frequency

indoors

Absorption fraction

from food and water

during pregnancy

Relative bioavailability

of lead in soil

Mass fraction of yard

soil in dust

Abbr.

GSD;

PbB

0

BKSF

IRsd

EF^

E FS

E Fd

A F

preg

RBA

K sd

Units

—

ug/dL

ug/dL per

ug/d

mg/day

days/yr

days/yr

days/yr

—

—

—

Distribution Shape

Triangular

Triangular

Uniform

Uniform

Uniform

Triangular

Calculated as

EFtotai " EFS Triangular

Uniform

Triangular

Parameters of Distribution

Min = 1.4 Mode = 1.6 Max = 1.8

Min = 1.7 Mode = 2.0 Max = 2.5

Min = 0.3 Max = 0.5

Min = 10 Max = 90

Min = 210 Max = 230

Min = 5 Mode = 10 Max = 20

—

Min = 0.1 Mode = 0.15 Max = 0.4

Min = 0.4 Max = 0.8

Min = 0.2 Mode = 0.25 Max = 0.6

Baseline Human Health Risk Assessment for the April 1995

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epa\48_32_90
2.6.4 Results

The results of a Monte Carlo simulation of the uncertainty around the action level are shown in Figure 1. As seen, the plausible range of action levels could conceivably range from as low as

2,200 ppm (the 5th percentile) to as high as 19,100 ppm (the 95th percentile). Central tendency

values include 6,100 ppm (the geometric mean) and 7,700 ppm (the arithmetic mean).

2.6.5 Comparison of Action Levels with Measured Concentrations

Numerous studies have been performed to collect data on lead levels hi soil in and around Leadville. Figure 2 is a map taken from CDM (1994), which shows lead levels in surficial soils

(0-1 inch) hi and around Leadville. These results are similar to those described in WESTON (1994) (e.g., see Figure 5-4 hi that report), which shows lead levels hi the 0-6 inch layer of soil

hi and around Leadville. Inspection of these maps reveals that average lead levels are mostly

below the central-tendency range of plausible action levels (6100-7700 ppm) for most areas

zoned for commercial land use, except possibly for some areas located hi the historic mining

area east of town and hi the vicinity of the former AV Smelter located southwest of town.

Note that it is average lead levels over an area which should be compared to the soil action

level. That is, occasional measurements or small "hot-spots" of concentrations above the action

level do not necessarily constitute evidence that an area is unsafe.

2.6.6 Sensitivity Analysis

Appendix B presents a sensitivity analysis of the Bowers model as it is used to calculate an

action level for lead. In brief, the most important parameters, judged hi terms of how much the

calculated value may vary as a function of the range of plausible input values, are the target

blood lead level, the soil/dust ingestion rate, the absorption fraction from food and water, and

the mass fraction of soil hi indoor dust. The sensitivity to these parameters is due mainly to the

large uncertainty (credible range) around these parameters.

2 .7 WEIGHT-OF-EVEDENCE EVALUATION

Three types of information are available to evaluate the risks to women of exposure to

environmental lead contamination hi the workplace.

1) Direct Blood Lead Measurements hi Women

Direct blood lead measurements of women hi Leadville indicate that, under current conditions,

there is a low probability that of a woman will have a blood lead level higher than the goal set

by EPA. Based on the expectation that a number of these women do work, this observation

supports the view that current workplace exposures to lead are not of concern. However, direct

measurement techniques might not detect the occurrence of a few specific locations where risks

are high, and these data may not reflect risks which could occur in the future.

Baseline Human Health Risk Assessment for the April 1995

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epa\48_32_90
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Baseline Human Health Risk Assessment for the California Gulch Superfund Site — Part C - Worker THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

epa\48_32_90

April 1995 Page-22

IT SHALL NOT BE RELEASED OR DISCLOSED IN
2) Predicted Blood Lead Distribution in Working Women

Use of a mathematical model to predict the range of blood lead values that could occur in

working women, now or in the future, also supports the view that there is a low probability that,

at the population level, women would be exposed to sufficient environmental lead hi the

workplace to exceed EPA's health-based goal. However, the predictions of this model are

considered to be uncertain, both because the basic model may be an oversimplification of lead

exposure and pharmacokinetics hi pregnant women, and because of substantial uncertainty in

many of the input parameters. In addition, this population-based approach does not identify the

range of risks which might occur at specific workplaces.

3) Calculated Action Levels

Even if there is low risk at the population level, it may still be possible for locations to exist

where risks to individuals at those locations could be of concern. Calculations of the

concentration of lead hi soil that is likely to ensure EPA's blood lead goal is not exceeded

indicates that concentrations hi the range of 6100 to 7700 ppm are likely to be protective with

a reasonable degree of confidence. Review of available data on lead concentrations hi soil

suggest that there are few current workplaces where the mean concentrations are likely to exceed

this range of action levels, although there are some locations zoned for possible future

commercial development where this range of action levels might be exceeded. As noted above,

there is substantial uncertainty in the use of a mathematical model to calculate action levels.

Weight-of Evidence Evaluation

Although all three of these lines of analysis have significant limitations and uncertainties, all

three yield generally consistent results, and all support the conclusion that current workplace

exposures to environmental lead are unlikely to be of significant concern to working women. Future workplace exposures might be of concern hi areas where soil concentrations substantially

exceed the range of plausible action levels for lead.

Baseline Human Health Risk Assessment for the April 1995

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3 .0 ARSENIC EVALUATION

No site-specific data are available on the level of arsenic exposure for citizens of Leadville. In

the absence of reliable biomarkers of exposure, the level of exposure and risk to workers must

be predicted from measured levels of arsenic in the environment. The followin g sections

describe the estimated range of risks from arsenic which might occur in workers, and the range

of soil concentrations that are plausible action levels for individual workplaces.

3 .1 PREDICTED ARSENIC RISKS IN LEADVILLE WORKERS

3.1.1 Basic Equations

The basic equations recommended by EPA (1989) to predict the risk from arsenic in soil and

dust are as follows:

Noncancer Risk

HI = (C^cHIF^RBA, + C^cHIF/RBA^/oRfD (4)

Cancer Risk

Risk = (C^lffiF^RBA, + C/lHIFd*RBAd)*oSF (5)

where:

cHIF = chronic human intake factor for soil or dust

= (IR/BW)*(EF/365)

1HIF = lifetime average human intake factor for soil or dust

= (IR/BW)*(EF/365)*(ED/AT)

oRfD = Oral reference dose for arsenic

oSF = Oral slope factor for arsenic

3.1.2 Input Parameters

As was discussed previously, exposure parameters vary widely from person to person and from

place to place, so it is expected that there is a wide range of doses and risks that could occur

in the population of workers in Leadville. Therefore, a Monte Carlo simulation of variability,

similar to that described in Section 2.5 above, was used to estimate this range of risks. The PDFs chosen to represent the variability hi each input parameter are described below.

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superfun d Site — Part C - Worker Page - 24 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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C, and Q

Data are available from a number of studies on the distribution of arsenic values in soils in the

community of Leadville. These data reveal that average arsenic concentrations vary as a function of location within the community, tending to be highest in the eastern sections of town

where most of the historic mining-related activities occurred, and southwest of town near the

location of the AV smelter. However, for the purposes of simulating the expected distribution

of exposures in workers (now or in the future), the most appropriate data are for the community

as a whole. Statistics available from several major studies are summarized below.

Study

Walsh 1988

WESTON 1991

Bornschein 1994

COM 1994

Sample Type

Depth = 0-6"

Depth = 0-6"

Perimeter Bare Area

Depth = 0-6"

N

599

121

14

28

3826

Mean

51

140

61

68

83

S T D

81

181

153

53

191

In all of these studies, the data are observed to be left-skewed in an approximately lognormal

distribution. Based on these studies, a representative value for the mean is judged to be about

70 ppm and a representative value for the standard deviation is judged to be about 150 ppm. Thus , variability in Cs

 was estimated with the followin g PDF:

Cs = LOGNORMAL(70,150)

Only one study (Bornschein 1994) has investigated the distribution of arsenic levels in interior

dust samples in Leadville. These data were collected in 241 private residences, but it seems

reasonable to assume that levels in commercial establishments are likely to be similar. The

observed mean and standard deviation of the dust values were 32 ppm and 23 ppm, respectively. As was the case for soils, the data are observed to be left-skewed in an approximately lognormal

distribution. Based on this, the value of Cd was modeled as:

Cd = LOGNORMAL(32,23)

The PDFs selected for evaluating soil and dust intake hi the workplace are the same as used in Section 2.5 for lead.

EF. ED. and AT

The PDFs selected to model variability in exposure frequency to soil and dust hi the workplace

are the same as described in Section 2.5 for lead.

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superfund Site — Part C - Worker Page - 25 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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Standard guidance (EPA 1991a) indicates that the RME exposure duration for workers is 25

years. Draft guidance (EPA 1993) suggests that the default for central tendency exposure

duration is 5 years, although no supporting rational for this value is provided. Assuming that

the minimum duration of workplace exposure to environmental arsenic that is of potential

toxicological concern is two years, variability in exposure duration was modeled as:

ED = TRIANGULAR(2,5,25)

Averaging time for cancer risks was 70 years (treated as a constant), and averaging tune for

noncancer was equal to the exposure duration (EPA 199la).

Body Weight (BW)

Data on the distribution of body weights in males and females has been summarized and

analyzed by Brainard and Burmaster (1992). The data are well fit by lognormal distributions,

with the following parameters:

Population

Males

Females

Mean of

ln(BW) (Ibs)

5.14

4.95

STDo f m(BW) (Ibs)

0.17

0.21

These PDFs were converted to units of kg (1 Ib = 0.454 kg), and the two separate PDFs were

combined into one by sampling from each with a relative frequency of 0.5, and fittin g the

resulting data to a lognormal distribution. The resulting PDF has a GM of 70 kg and a GSD

of 1.24. Based on this, the PDF for BW is as follows:

BW = LOGNORMAL2(70,1.24)

EBA,

EPA Region VIII guidance recommends a default relative bioavailability factor for arsenic in soil

of 0.8 (EPA 1993).

There have not yet been any studies of arsenic absorption from soils from the California Gulch

site, but there have been two studies of arsenic absorption from soils collected in Anaconda, Montana (Johnson et al. 1991, Freeman et al. 1994). These studies are subject to some

limitations and uncertainties, but the data suggest that in animals (rabbits and monkeys), arsenic

absorption from the soil used hi these studies is about 20% of that for soluble sodium arsenate.

EPA does not feel it is appropriate to extrapolate data from site to site and from sample to

sample without careful assessment of the similarity (or lack thereof) in geochemical

characteristics of the soils, but these data do suggest that bioavailability of arsenic may vary

Baseline Human Health Risk Assessment for the April 1995

California Gulch Superfund Site — Part C - Worker Page - 26 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

epa\48_32_90
from location to location. In the absence of any site-specific data, the possible range of arsenic

bioavailability in soils at the California Gulch site were modeled as follows:

RBA = UNIFORM(0.2,0.8)

It should be emphasized that this PDF is based on professional judgement only, and might lead

to either an overestimate or an underestimate of the true range of RBA for arsenic in site soils.

oRfD and oSF

The oral reference dose and oral cancer slope factors used are those recommended by the EPA (IRIS 1994):

oRfD = 3E-04 mg/kg-d

o SF = 1.75E+00 (mg/kg-d)'1

Although it is likely that there is variability in the susceptibility to arsenic between individuals,

these terms were modeled as constants. Uncertainties and controversies regarding these toxicity

values are discussed in Part B of this risk assessment.

Summary of Variability PDFs

Table 3 lists the PDFs selected to evaluate the range of arsenic risks that could be experienced

by workers in Leadville.

3.1.3 Results

Monte Carlo simulations were performed (5000 iterations per simulation) using the PDFs above

to describe the variability in noncancer and cancer risk levels in workers associated with

exposure to arsenic in soil or dust at the workplace. The results are summarized below.

Variability Parameter

Median

Mean

95th Percentile

Risk Estimate

Hazard Index

2E-02

3E-02

8E-02

Cancer Risk

IE-06

2E-06

7E-06

As shown, the predicted population-based distribution of risks from arsenic is below the normal

health-based criterion both for noncancer and cancer effects . However, this does not necessarily

prove that there are no specific sublocations within the site where arsenic concentrations in soil

and dust might be high enough to be of potential concern to workers at those sublocations. The

following section evaluates the range of arsenic concentrations which might be of concern to

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superfun d Site — Part C - Worker Page - 27 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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TABLE 3. SUMMARY OF VARIABILITY DISTRIBUTION FUNCTIONS F OR ESTIMATION OF ARSENIC EXPOSURE IN WORKERS

Model Input

Concentration in soil

Concentration in dust

Ingestion rate of

soil/dust at

workplace

Exposure frequency

at work

Exposure frequency

to soil outdoors

Exposure frequency

to dust indoors

Exposure duration at

workplace

Body weight

Averaging time

Arsenic relative

bioavailability

Abbr.

c

s

c

d

iRsd

E F,

E FS

E Fd

ED

BW

AT

RBA

Units

mg/kg

mg/kg

mg/day

days/yr

days/yr

days/yr

years

kg

years

—

Distribution Shape

Lognormal

Lognormal

Triangular

Triangular

Triangular

Calculated as

EF^ - EFS

Triangular

Lognormal

Noncancer: AT = ED Cancer: AT = 70

Uniform

Parameters of Distribution

Mean = 70 STD = 150

Mean = 32 S TD = 23

Min = 10 Mode = 30 Max = 120

Min = 200 Mode = 219 Max = 250

Min = 0 Mode = 10 Max = 100

—

Min = 2 Mode = 5 Max = 25

GM = 70 GSD = 1.24

--

Min = 0.2 Max = 0.8

Baseline Human Health Risk Assessment for the April 1995

California Gulch Superfund Site — Pan C - Worker Page - 28 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. FT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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individuals at a workplace.

3 .2 CALCULATION OF WORKPLACE SOIL ACTION LEVEL FOR ARSENIC

3.2.1 Basic Equation

Recall that the basic equations used to predict noncancer and cancer risks hi an individual

exposed to arsenic in soil and dust are:

Noncancer Risk

HI = (Cs*cHIFs*RBAs + C/cfflF^RBA^/oRfD (4)

Cancer Risk

Risk = (CS*1HIFS*RBAS + Cd*lHIFd*RBAd)*oSF (5)

Because these equations contain terms for both soil and dust exposure, they cannot be solved for

the soil term (Cs) unless the dust term (C^) is defined as a dependent variable whose value can

be predicted from the value of soil. Assuming that soil comprises some (but not all) of the mass

of indoor dust, the concentration of lead hi dust can be described using an equation of the

following form:

Cd = D

0

 + Ksd*Cs

Setting the value of D

0

 to zero (for the reasons discussed previously), and substituting this

expression into the basic equations above, the equations for calculating the noncancer and cancer

action levels for arsenic are as follows:

A Ln c = m^*oRffl/(cfflF.*RBA1 + Ks d*cHIFd) (6)

A LC = Risk

iarget/((lHIFs*RBAs

 + Ks d*lfflFd)*oSF) (6)

The overall action level for soil is then the more stringent (lower) of these two values:

Typically , the health-based goals for these calculations are that a person at the upper portion of

the dose distribution (i.e., the RME individual) should have a Hazard Index which does not

exceed 1E+00 and an excess cancer risk which does not exceed IE-04. Screening level

calculations show that for arsenic, based on these health goals, it is cancer risk which yields the

more stringent action level. Therefore, only the equation for the cancer-based action level is

evaluated below.

Baseline Human Health Risk Assessment for the April 1995

California Gulch Superfund Site — Pan C - Worker Page - 29 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

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3.2.2 Uncertainty PDFs

The object of the action level calculation is to estimate a concentration that will be protective

even for a person at the upper end of the exposure distribution. Therefore, several of the inputs

into the equation above are intended to be values appropriate for the RME individual. If the true

values of these RME parameters were known, then the equation would yield a single numeric

value (the action level) that is equal to the soil arsenic concentration that ensures the heath-based

goals are met for RME individuals. However, there is substantial uncertainty hi the true value

for most of these variables. Therefore, each input parameter was described by a PDF which

describes uncertainty about the intended value, and these PDFs were used hi a Monte Carlo

simulation to estimate the plausible range of the action level.

RME IR. and IR,

Draft EPA guidance specifies that the RME soil and dust intake by workers should be 100 mg/day. Because this estimate is based on relatively little data, it is considered to be highly

uncertain. Based on professional judgement, uncertainty about this parameter was modeled as:

RME IR,,, = UNIFORM(50,200)

Exposure Frequency

The same uncertainty PDFs for workplace exposure frequency to soil and dust that were used

to evaluate the action level for lead were also used to evaluate uncertainty hi the action level for

arsenic.

RME Exposure Duration

EPA guidance specifies that the RME exposure duration for workers should be 25 years, but

does not provide any information on the confidence hi that value. Based on professional

judgement, uncertainty about this parameter was modeled as follows:

RME ED = UNIFORM(20,30)

Averaging Tune

Averaging time was assumed to be 70 years, and this was treated as a constant rather than an

uncertain variable. This is because application of the cancer slope factor for arsenic is based

on the assumption of a 70-year lifetime. Mean Body Weight

Data on adult body weights are derived from measurements hi a very large number of people,

so there is very little uncertainty hi the true mean value. Because of this, the value for body

weight was simply treated as a constant (70 kg).

Baseline Human Health Risk Assessment for the April 1995

California Gulch Superfund Site — Part C - Worker Page - 30 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

epaW8_32_90
RME Relative Bioavailabilitv

There are presently no measurements of arsenic relative bioavailability hi site-specific soils or

dusts, so it is difficul t to evaluate the uncertainty around the default RME value of 0.8. Based

on professional judgement, the following PDF was used:

RME RBA = UNIFORM(0.7,0.9)

Soil/Dus t Relationshi

Data on the relationship between arsenic concentration levels hi dust and soil (Cs, Cd) are

available from the environmental data set collected by the University of Cincinnati in 1991.

Employ ing the same analysis approach as described hi Part B and hi Section 2.6.3 (above), the

values estimated for D

0

 and K.d are as follows:

Parameter

Number of paired samples

Mean of dust (D)

Mean of soil (S)

Estimated D

0

a

Calculated Kj*

Soil Type

Perimeter

14

51

61

29

0.36

Bare Area

28

33

68

18

0.22 a

b Mean of dust samples where soil arsenic is low (< 10 ppm)

 Calculated as (D - D

0)/(S)

Because these calculations are based on a rather small data set, the results are considered to be

rather uncertain. Therefore, the uncertainty around the mean value of Ksd was modeled as:

K,,, = UNIFORM(0.2,0.6)

As noted above, the value of D

0

 is set at zero for the purposes of estimating an action level.

Summary of Uncertainty PDFs

Table 4 summarizes the PDFs selected to describe the uncertainty around the inputs needed to

calculate an action level for workers exposed to arsenic hi soil and dust.

3.2.3 Results

The results of a Monte Carlo simulation of the uncertainty around the action level are shown in Figure 3, As seen, the plausible range of action levels could conceivably range from as low as

Baseline Human Health Risk Assessment for the April 1995

California Gulch Superfund Site - Part C - Worker Page - 31 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

epa\48_32 90
TABLE 4. SUMMARY OF UNCERTAINTY DISTRIBUTION FUNCTIONS F OR ESTIMATION OF ARSENIC SOIL ACTION LEVEL

Model Input

RME ingestion rate

of soil/dust

RME exposure

frequency at work

Exposure frequency

to soil outdoors

Exposure frequency

to dust indoors

RME exposure

duration at

workplace

Body weight

Averaging time

Mass fraction of soil

in dust

RME relative

bioavailability

Abbr.

IRsa

E Ft

E FS

E Fd

ED

BW

AT

K sd

RBA

Units

mg/day

days/yr

days/yr

days/yr

years

kg

years

—

—

Distribution Shape

Uniform

Uniform

Triangular

Calculated as: F•

c/Fr

 tota - l

 J F-'- Fr

s

Uniform

Constant

Constant

Uniform

Uniform

Parameters of Distribution

Min = 50 Max = 150

Min = 240 Max = 260

Min = 5 Mode = 10 Max = 20

--

Min = 20 Max = 30

70

70

Min = 0.2 Max = 0.6

Min = 0.7 Max = 0.9

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superfund Site — Part C - Worker Page - 32 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR IN PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

epa\48_32_90
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330 ppm (the 5th percentile) to as high as 1300 ppm (the 95th percentile). Central tendency

values include 610 ppm (the geometric mean) and 690 ppm (the arithmetic mean).

3.2.4 Comparison with Site Concentrations

Data on arsenic levels measured in surficial soil (0-1 inch) in and around Leadville are shown

hi Figure 4 (CDM 1994). Inspection of this map reveals that average arsenic levels are not

expected to exceed about 50 ppm hi the main business section of Leadville, and that expected

mean levels do not appear to exceed the soil action level for workers anywhere at the site except

possibly for the area near the former AV Smelter located southwest of town.

As before, it is important to understand that it is average arsenic level over an area which

should be compared to the soil action level. That is, occasional measurements or small "hotspots" of concentrations above the action level do not necessarily constitute evidence that an area

is unsafe.

Baseline Human Health Risk Assessment for the April 1995 California Gulch Superrund Site — Part C - Worker Page - 34 THIS DOCUMENT WAS PREPARED BY ROY F. WESTON, INC. EXPRESSLY FOR EPA. IT SHALL NOT BE RELEASED OR DISCLOSED IN WHOLE OR m PART WITHOUT THE EXPRESS WRITTEN PERMISSION OF EPA.

epa\48 32_90
nO 8 I * S e

a I S

-fci g

ta •<

§

COtn

8

s ?

1760000,

520000

1790000,

520000

LEGEN D

Sampl e Locatio n

Isoconcentratio n Lin e

CAMP DRESSER & McKEE , INC . COM

CALIFORNI A GULC H SOIL S INVESTIGATIO N

ARSENI C ISOCONCENTRATIO N MA P

A L L SOILS , 0--1" DEPTH

APPf'NIU

Figure 4: Arsenic Isoconcentration Map