MWTP-284
FINAL REPORT— DOMESTIC PETS AS BIOSAMPLERS OF MINING-RELATED
CONTAMINANTS
MINE WASTE TECHNOLOGY PROGRAM
ACTIVITY IV, PROJECT 37
Prepared by:
Montana Tech of The University of Montana
1300 W. Park Street
Butte, Montana 59701
and
MSE Technology Applications, Inc.
P.O. Box 4078
Butte, Montana 59702
IAG ID. No. DW89939550-01-0
Prepared for:
U.S. Environmental Protection Agency
National Risk Management Research Laboratory
Cincinnati, Ohio 45268
IAG No. DW899398987-01-0
and
U.S. Department of Energy
Environmental Management Consolidated Business Center
Cincinnati, Ohio 45202
Contract No. DE-AC09-96EW96405
October 2006
REVIEWS AND APPROVALS (MWTP-258):
Prepared by:
Project Engineer
Reviewed by:
Chief Scientist
Approved by:
Program Manager
October 2006
MINE WASTE TECHNOLOGY PROGRAM
FINAL REPORT
DOMESTIC PETS AS BIOSAMPLERS
OF MINING-RELATED CONTAMINANTS
By:
Holly G. Peterson, Ph.D. and Stacie Barry, M.S.
Department of Environmental Engineering
Montana Tech of The University of Montana
Butte, Montana 59701
and
MSE Technology Applications, Inc.
Mike Mansfield Advanced Technology Center
Butte, Montana 59702
Under Contract No. DE-ACC09-96EW96405
Through EPA IAG NO: DW8993987-01-0
George Huffman
Sustainable Technology Division
National Risk Management Research Laboratory
Cincinnati, Ohio 45268
This study was conducted in cooperation with
U.S. Department of Energy
Environmental Management Consolidated Business Center
Cincinnati, Ohio 45202
National Risk Management Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
Notice
The U.S. Environmental Protection Agency through its Office of Research and Development funded the
research described here under IAG DW899395500-01-0 through the U.S. Department of Energy (DOE)
Contract DE-AC09-96EW96405. It has been subjected to the Agency’s peer and administrative review
and has been cleared for publication as an EPA document. Reference herein to any specific commercial
product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily
constitute or imply its endorsement or recommendation. The views and opinions of authors expressed
herein do not necessarily state or reflect those of the EPA or DOE, or any agency thereof.
ii
Foreword
The U.S. Environmental Protection Agency is charged by Congress with protecting the Nation’s land, air,
and water resources. Under a mandate of national environmental laws, the Agency strives to formulate
and implement actions leading to a compatible balance between human activities and the ability of natural
systems to support and nurture life. To meet this mandate, EPA’s research program is providing data and
technical support for solving environmental problems today and building a science knowledge base
necessary to manage our ecological resources wisely, understand how pollutants affect our health, and
prevent or reduce environmental risks in the future.
The National Risk Management Research Laboratory is the Agency’s center for investigation of
technological and management approaches for preventing and reducing risks from pollution that threatens
human health and the environment. The focus of the Laboratory’s research program is on methods and
their cost effectiveness for prevention and control of pollution to air, land, water, and subsurface
resources; protection of water quality in public water systems; remediation of contaminated sites,
sediments, and ground water; prevention and control of indoor air pollution; and restoration of
ecosystems. The NRMRL collaborates with both public and private-sector partners to foster technologies
that reduce the cost of compliance and to anticipate emerging problems. NRMRL’s research provides
solutions to environmental problems by developing and promoting technologies that protect and improve
the environment; advancing scientific and engineering information to support regulatory and policy
decisions; and providing the technical support and information transfer to ensure implementation of
environmental regulations and strategies at the national, state, and community levels.
This publication has been produced as part of the Laboratory’s strategic long-term research plan. It is
published and made available by EPA’s Office of Research and Development to assist the user
community and to link researchers with their clients.
Sally Gutierrez, Director
National Risk Management Research Laboratory
iii
Abstract
This document summarizes a research project designed to develop a new way of investigating residential
exposure to environmental contaminants. Specific objectives were as follows: 1) to develop and test a
simple, inexpensive, biomonitoring system to characterize existing chronic exposure to mining-related
contaminants in the Butte area; and 2) to use the biomonitoring method to try to document efficacy of
localized remediation efforts. Domestic pets were chosen as the sentinel species, and the protocol
involved collection of hair samples with subsequent analysis using inductively coupled plasma – mass
spectrometry (ICP-MS). The method was tested during the summer of 2005 in a field campaign
involving more than 200 dogs, and concentration data in hair specimens were examined for 32 elements,
including mining-related elements such as arsenic and lead.
In this investigation, 72.6 percent of the samples contained arsenic concentrations greater than a reference
value of 0.02 mg %, and 41.6 percent of the lead concentrations were higher than 0.2 mg %. Thirty dogs
were identified as pets of concern (POCs) based on pet hazard indices greater than or equal to 1.0, and 26
of the POCs resided inside the Butte Priority Soils Operable Unit (BPSOU), a boundary established by
the Environmental Protection Agency to represent the bulk of the residential contamination in Butte.
The following eight elements were defined as elements of concern (EOCs) for the campaign based on
element hazard indices greater than or equal to 1.0: aluminum, arsenic, boron, lead, lithium, manganese,
molybdenum, and selenium. In addition, of the eight elements of concern, the nonparametric
Kolmogorov-Smirnov test showed that pets residing inside the BPSOU exhibited significantly higher
levels of aluminum, arsenic, lead, lithium, and manganese than Butte pets living outside the BPSOU.
Effectiveness of yard or attic remediation was evaluated by repeat sampling of four dogs over a period of
five months at houses undergoing remediation. Manganese and arsenic concentrations in the hair of one
dog, for example, decreased 95 and 71 percent, respectively, during a three-month period following
cleanup of contaminated dust in the dog’s home.
While results of the research project were site-specific, the approach developed for this site may be of
interest and directly transferable to other facilities across the United States. In particular, our method may
become a simple, screening-level tool for studying residential exposure to environmental contaminants
and for documenting effectiveness and sustainability of cleanup actions.
iv
Table of Contents
Notice ......................................................................................................................................................... ii
Foreword.....................................................................................................................................................iii
Abstract....................................................................................................................................................... iv
Table of Contents ........................................................................................................................................ v
List of Tables .............................................................................................................................................. vi
List of Figures............................................................................................................................................. vi
Acronyms and Abbreviations .................................................................................................................viii
Units ........................................................................................................................................................ ix
Acknowledgments ....................................................................................................................................... x
Executive Summary ................................................................................................................................... xi
1.
INTRODUCTION ......................................................................................................................... 2
2.
OBJECTIVES ................................................................................................................................ 3
3.
METHODS ..................................................................................................................................... 5
4.
RESULTS ....................................................................................................................................... 9
4.1 Mining History of Butte and Anaconda .............................................................................. 9
4.2 Environmental Impact........................................................................................................ 10
4.3 Cancer Statistics for Silver Bow County........................................................................... 10
4.4 Sentinel Species for Studying Exposure ............................................................................ 11
4.5 Hair Analysis for Studying Chronic Exposure................................................................. 12
4.6 General Information about the Field Campaign.............................................................. 12
4.7 General Statistics of the Dataset ........................................................................................ 12
4.8 Risk Analysis........................................................................................................................ 13
4.9 Identification of Pets of Concern ....................................................................................... 14
4.10 Identification of Elements of Concern............................................................................... 14
4.11 Probability Distribution Analysis ...................................................................................... 14
4.12 Spatial Distribution Analysis.............................................................................................. 15
4.13 Remediation Investigation.................................................................................................. 15
5.
DISCUSSION ............................................................................................................................... 53
6.
SUMMARY AND RECOMMENDATIONS............................................................................. 54
7.
QUALITY ASSURANCE/QUALITY CONTROL (QA/QC).................................................. 57
7.1 Deviations from the Quality Assurance Project Plan ...................................................... 57
7.2 Laboratory and Field QA ................................................................................................... 57
7.3 General Recordkeeping and Reporting............................................................................. 58
8.
REFERENCES............................................................................................................................. 63
APPENDIX A ............................................................................................................................................ 66
v
List of Tables
Table 2- 1. Project Schedule and Milestones. .............................................................................................. 4
Table 3- 1. Questionnaire Used in the 2005 Campaign ............................................................................... 7
Table 3- 2. Example Laboratory Report from Trace Elements, Inc............................................................. 8
Table 4- 1. Cancer Rates from National Cancer Institute for 1997-2001 .................................................. 17
Table 4- 2. Summary of Information for Pets in the 2005 Hair Sampling Campaign ............................... 18
Table 4- 3. Concentration Statistics of Elements in the 2005 Hair Samples ............................................. 19
Table 4- 4. Arsenic Concentration Statistics for Groups ........................................................................... 20
Table 4- 5. Pet Hazard Index (HIj) Data for Pets 1-100.............................................................................. 21
Table 4- 6. Pet Hazard Index (HIj) Data for Pets 101-200.......................................................................... 22
Table 4- 7. Element Hazard Index (HIi) Data for the 2005 Campaign ....................................................... 23
Table 4- 8. Results from the Remediation Campaign ................................................................................ 24
Table 7- 1. Quality Analysis Checklist from Laboratory Summary Reports............................................. 59
Table 7- 2. Quality Control Checklist for Replicate and Split Samples .................................................... 60
Table A- 1. Summary of Laboratory QA/QC Checks for Critical Measurements of Metals in Hair ........ 71
List of Figures
Figure 4- 1. Historical mining activity in the Butte area (including the boundary of the Butte Priority Soils
Operable Unit). ................................................................................................................................... 25
Figure 4- 2. Map of arsenic concentrations in the soil from the BPSOU database.................................... 26
Figure 4- 3. Map of cadmium concentrations in the soil from the BPSOU database. ............................... 27
Figure 4- 4. Map of copper concentrations in the soil from the BPSOU database. ................................... 28
Figure 4- 5. Map of lead concentrations in the soil from the BPSOU database. ....................................... 29
Figure 4- 6. Map of zinc concentrations in the soil from the BPSOU database ........................................ 30
Figure 4- 7. Residence locations of Butte pets sampled during the 2005 Campaign.................................. 31
Figure 4- 8. Residence locations of Anaconda pets sampled during the 2005 Campaign, in addition to
pets living in Opportunity, Sheep Gulch, and Warm Springs............................................................. 32
Figure 4- 9. Percent of samples in the 2005 campaign where the concentration exceeded the reference
level for each element. ........................................................................................................................ 33
Figure 4- 10. Ratio of the maximum concentration in the 2005 campaign to the reference concentration
for each element.................................................................................................................................. 34
Figure 4- 11. Hazard quotient (HQ) graph for Dog 184. Green shading indicates a HQ value less than
1.0, and red shading corresponds to a HQ value of 1.0 or above........................................................ 35
Figure 4- 12. Hazard quotient (HQ) graph for Dog 195. Green shading indicates a HQ value less than
1.0, and red shading corresponds to a HQ value of 1.0 or above........................................................ 36
Figure 4- 13. Hazard index (HIj) graph for Pets 1-100. While green shading indicates a HIj value less
than 1.0, red shading corresponds to a HI value of 1.0 or above. Pets with a HIj value greater than or
equal to 1.0 are defined as pets of concern (POCs). ........................................................................... 37
Figure 4- 14. Hazard index (HIj) graph for Pets 101-200. While green shading indicates a HIj value less
than 1.0, red shading corresponds to a HI value of 1.0 or above. Pets with a HIj value greater than or
vi
equal to 1.0 are defined as pets of concern (POCs). .......................................................................... 38
Figure 4- 15. Hazard index (HIi) graph for all elements in the 2005 campaign. While green shading
indicates a HIi value less than 1.0, red shading corresponds to a HIi value of 1.0 or above. Elements
with HIi values greater than or equal to 1.0 are defined as elements of concern (EOCs). .................. 39
Figure 4- 16. Cumulative fraction plot for KS Test 7: phosphorous HQs in Butte dogs residing inside the
BPSOU (N = 94) and phosphorous HQs in Butte dogs residing outside the BPSOU (N= 84). The
solid line represents the dogs residing inside the BPSOU and the dashed line represents the dogs
outside the BPSOU. ............................................................................................................................ 40
Figure 4- 17. Cumulative fraction plot for KS Test 9: manganese HQs in Butte dogs residing inside the
BPSOU (N = 94) and manganese HQs in Butte dogs residing outside the BPSOU (N= 84). The solid
line represents the dogs inside the BPSOU and the dashed line represents the dogs outside the
BPSOU................................................................................................................................................ 41
Figure 4- 18. The Kolmogorov-Smirnov statistic D for the comparison of cumulative distributions inside
versus outside the BPSOU. The statistic D represents the maximum (vertical) distance between the
distributions......................................................................................................................................... 42
Figure 4- 19. The Kolmogorov-Smirnov p-value for the comparison of cumulative distributions inside
versus outside the BPSOU. If the p-value is small (approaching 0.000), the null hypothesis may be
rejected; if the p-value is large (approaching 1.000), there is likely no difference between the
distributions......................................................................................................................................... 43
Figure 4- 20. Residence locations of pets sampled in the vicinity of Butte with color-coding to indicate
hazard quotients in the hair samples above and below 1.0. ................................................................ 44
Figure 4- 21. Residence locations of pets sampled in the vicinity of Anaconda with color-coding to
indicate hazard quotients in the hair samples above and below 1.0.................................................... 45
Figure 4- 22. Residence locations of the pets of concern (POCs) in the Butte area. A POC was defined as
a pet with a hazard index of 1.0 or higher when all elements were considered. ................................. 46
Figure 4- 23. Hazard index values of the pets of concern (POCs) and associated hotspots in the Butte
area...................................................................................................................................................... 47
Figure 4- 24. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium for the
remediation control dog, Luna. ........................................................................................................... 48
Figure 4- 25. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium for the
remediation dog, Trip.......................................................................................................................... 49
Figure 4- 26. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium for the
remediation dog, Sweetie.................................................................................................................... 50
Figure 4- 27. Time series of concentrations of aluminum, arsenic, lead, manganese, and lithium for the
remediation dog, Max. ........................................................................................................................ 51
Figure 4- 28. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium for the
remediation dog, Teddy. ..................................................................................................................... 52
Figure 7- 1. Concentration comparison of replicate samples..................................................................... 61
Figure 7- 2. Concentration comparison of inter-laboratory split samples.................................................. 62
vii
Acronyms and Abbreviations
BPSOU
C
DOE
EOC
EPA
GPS
GIS
H0
H1
HIi
HIj
HQ
HQij
IAG
ICP-MS
IDL
IRIS
ISO
MSE
MWTP
NIST
NPL
OU
POC
QA
QC
QAPP
RfC
RPD
RI
Sc
SDI
SHS
SSL
TEI
USEPA
Butte Priority Soils Operable Unit
Average Concentration
U.S. Department of Energy
Element of Concern
Environmental Protection Agency
Global Positioning System
Geographic Information System
Null Hypothesis
Alternative Hypothesis
Pet Hazard Index
Element Hazard Index
Hazard Quotient
Hazard Quotient of Element i for Pet j
Interagency Agreement
Inductively Coupled Plasma-Mass Spectrometry
Instrument Detection Limit
Integrated Risk Information System
International Organization for Standardization
MSE Technology Applications
Mine Waste Technology Program
National Institute of Standards and Technology
National Priorities List
Operable Unit
Pet of Concern
Quality Assurance
Quality Control
Quality Assurance Project Plan
Reference Concentration
Relative Percent Difference
Remedial Investigation
Standard Deviation of Concentration
Standard Deviation Index
Split Hair Specimen
Soil Screening Level
Trace Elements, Incorporated
U.S. Environmental Protection Agency
viii
Units
lb
mg
mg/kg
mg %
ppm
hr
%
yr
Pound
Milligram
Milligram/Kilogram
Milligram Percent
Parts per Million
Hour
Percent
Year
ix
Acknowledgments
This document was prepared by MSE Technology Applications, Inc. (MSE) for the U.S. Environmental
Protection Agency’s (EPA) Mine Waste Technology Program (MWTP) and the U.S. Department of
Energy’s (DOE) Cincinnati Operations Office. Ms. Diana Bless is EPA’s MWTP Program Manager,
while Mr. Gene Ashby is DOE’s Technical Program Officer. Ms. Helen Joyce is MSE’s MWTP Program
Manager. Mr. Mark Peterson is Montana Tech’s MWTP Program Director, and Tina Donovan is
Montana Tech’s MWTP Quality Assurance Officer.
x
Executive Summary
Nearly a century of mining and smelting activities in the Butte/Anaconda area of Montana resulted in
widespread contamination throughout southwest Montana. Some of the contamination has been
investigated and remediated as a direct result of the National Priorities List (NPL) designations of sites in
the area. Little is known, however, about the long-term health impact for residential populations exposed
on a daily basis to residual contaminants in the local soil, air, and water. The purpose of this research was
to develop a new way of investigating residential exposure to environmental pollutants, and the following
two objectives were identified for this project: 1) to develop and test a simple, inexpensive, biomonitoring
system to characterize existing chronic exposure to mining-related contaminants in the Butte area; and 2)
to use the biomonitoring method to try to document efficacy of localized remediation efforts.
Domestic dogs were chosen as sentinel species, and the protocol involved collection of hair samples with
subsequent analysis using inductively-coupled plasma/mass spectrometry (ICP-MS) to assess chronic
exposure of environmental contaminants. The innovative approach developed for this site may be useful
as a powerful screening tool for identifying contaminants in any residential environment that may require
investigation and/or remediation.
During the course of a field campaign in summer of 2005, hair samples were collected from more than
200 dogs and analyzed for 32 elements with inductively coupled plasma – mass spectrometry (ICP-MS).
Arsenic concentrations in the samples ranged from 0.006 to 0.272 milligrams percent (mg %) with 72.6
percent of the samples exhibiting arsenic concentrations higher than a reference concentration of 0.02 mg
%. In addition, 36 dogs were identified as pets of concern (POCs) based on pet hazard indices greater
than or equal to 1.0, and 26 of the 36 POCs resided inside the envelope of the Butte Priority Soils
Operable Unit (BPSOU). Two locations, the 500 block of Mercury Street and the 100 block of East Daly,
were considered the hotspots of the dataset (i.e., residential neighborhoods with the highest exposures).
The following elements were defined as elements of concern (EOCs) for the campaign based on element
hazard indices of 1.0 or greater: aluminum, arsenic, boron, lead, lithium, manganese, molybdenum, and
selenium. Of the eight elements of concern, the Kolmogorov-Smirnov test showed that pets residing
within the BPSOU exhibited significantly higher levels of aluminum, arsenic, lead, lithium, and
manganese than Butte pets living outside of the BPSOU.
In addition, effectiveness of remediation was evaluated via sampling four dogs over the course of several
months at houses undergoing remediation of yards and house dust. Manganese and arsenic
concentrations in the hair of one dog, for example, were shown to decrease 95 and 71 percent,
respectively, during a three-month period following cleanup of contaminated dust inside the dog’s home.
The new biomonitoring technique was designed as a screening-level tool for studying incidental exposure
to environmental contaminants. Pets are companion animals, however, and results may have implications
for human health risk assessment.
xi
1. INTRODUCTION
Nearly a century of mining and smelting activities in the Butte/Anaconda area of Montana resulted in
widespread contamination throughout southwest Montana. Specific pollutants of concern include arsenic,
cadmium, copper, lead, and zinc. Some of the contamination has been investigated and remediated as a
direct result of the National Priorities List (NPL) designations of sites in the area. Little is known,
however, about the long-term health impact for residential populations exposed on a daily basis to
residual contaminants in the local soil, air, house dust, and water.
Human health risk assessments are routinely conducted on or near Superfund sites to estimate potential
risks to exposed (and potentially-exposed) human populations, and ecological risk assessments are
conducted to estimate environmental impacts to wildlife, vegetation, fish, and ecosystems. Both types of
risk assessments utilize on-site measurements of contaminants in the soil, sediments, water, and air, while
applying conservative assumptions about intake rates and resulting effects. Few data, however, are
currently available for characterizing “actual” exposures and for documenting efficacy of remediation.
This project proposed to develop and test a novel type of environmental health research to improve our
understanding of actual, long-term exposure to widespread contamination in residential areas. The
biomonitoring system utilized domestic dogs as sentinel species with hair sampling and subsequent
analysis using inductively-coupled plasma/mass spectrometry (ICP-MS). Elements in a hair sample
reflect chronic exposure periods of 1-10 months and longer. While the levels of contact with
contaminated soil and water are probably much higher for pets than for humans, domestic dogs
represented exciting opportunities for conservatively assessing chronic health risks.
Detailed results of our study are site-specific. The innovative approach, however, developed for this site
may be directly transferable to every rural or urban area in the United States, and elsewhere, that is
affected by widespread contamination problems. While the field campaign described here was the first of
its kind, the project is cultivating into a new research program at Montana Tech focused on understanding
dose-response mechanisms related to animal and human exposure.
The remainder of this document consists of additional information about the research project. Section 2
describes project objectives. Experimental and analysis methods are explained in Section 3, while
Section 4 contains a summary of results. Section 5 is a discussion, and Section 6 includes a summary and
recommendations. Quality assurance/quality control (QA/QC) is addressed in Section 7, and Section 8
concludes with a list of references. Appendix A contains a detailed description of the QA/QC policy for
the laboratory used in sample analysis.
2
2. OBJECTIVES
The overall goal of our research was to improve our understanding of chronic exposure to contaminants in
the environment, and the following two objectives were identified for this project:
Objective 1. To develop and test a simple, inexpensive, biomonitoring system to characterize
existing chronic exposure to mining-related contaminants for dogs residing in Butte, Montana;
and
Objective 2. To use the biomonitoring method to try to document efficacy of localized
remediation efforts.
Regarding Objective 1, our novel protocol involved collection of hair samples with subsequent analysis
using ICP-MS as an easy, non-invasive way to obtain biological data regarding toxin/contaminant
environmental exposure. The method was tested in the summer of 2005 by sampling more than 200 pets,
including a variety of breeds, ages, and residence locations. For Objective 2, hair samples were collected
over the course of several months from dogs living at houses with attics or yards undergoing remediation.
In addition to the two objectives, the following four questions were posed prior to the research campaign:
1. Are levels of toxic elements in Butte dogs higher than reference levels?
2. Are the levels of toxic elements for dogs living inside the envelope of the Butte Priority Soils
Operable Unit (BPSOU) higher than elsewhere in the community?
3. Are there “hotspots”, or neighborhoods in Butte where domestic dog exposures are highest?
4. If yards or homes are remediated, how long will it take to reduce the body burden of
contaminants in the biosamplers?
Table 2-1 identifies 10 specific tasks that were identified in the Quality Assurance Project Plan (QAPP)
and that were performed throughout the project to meet our objectives and to answer the four questions.
The dog sampling efforts were divided into two phases: 1) a “hotspots” campaign where dogs were
sampled throughout the community to identify neighborhoods with highest exposure data; and 2) a
“remediation” campaign where hair samples from dogs were collected over time to observe exposure
effects before and after remediation of yards and house dust. The remediation campaign took longer than
anticipated because of coordinating remediation activities with sampling schedules, but the rest of the
tasks were completed on time throughout a one-year period. In addition, detailed results from the project
were analyzed and summarized in a Master of Science thesis by Stacie Barry (Barry 2006) during the
spring of 2006.
3
Task
Table 2- 1. Project Schedule and Milestones.
Month
1 2 3 4 5 6 7
1. Developing the QAPP.
2. Researching literature regarding health effects
(in humans and animals) of arsenic and other
mine-waste-related contaminants.
3. Researching the literature regarding other
studies using hair samples for biosampling
purposes.
4. Identifying a group of animals to be sampled
for the “hotspots” campaign, and for the
“remediation” campaign.
5. Collecting and analyzing hair samples for the
“hotspots” campaign.
6. Collecting and analyzing hair samples for the
“remediation” campaign.
7. Mapping and interpreting biosampling data for
arsenic.
8. Mapping and interpreting biosampling data for
other mining-related contaminants.
9. Preparing Interim Reports
10. Preparing Final Report
Red shading = proposed schedule
Red and white shading = actual schedule
4
8
9
10
11
12
3. METHODS
The primary sampling campaign for this project occurred during June through September of 2005. Over
the course of four months, more than 200 hair specimens were collected. These samples represented a
variety of dog ages, breeds, and socio-economic areas.
At the time of sampling, dog owners were asked a series of standard questions. The questionnaire is
shown in Table 3-1. The survey elicited basic information, such as pet breed, sex, age, and weight, as
well as specific information regarding the health of the pet and persons residing with the pet. Pet owners
were also asked if pets were given water from the residential water supply, what type of food the pets
were fed, and if the homes had recently been remediated as a part of Superfund cleanup. In addition,
location coordinates of the residence were measured using a Global Positioning System (GPS), and
sample locations were then mapped with the Geographic Information System (GIS).
Specimens were collected from the dogs by cutting approximately 150 mg of hair between the shoulder
and neck. To avoid cross contamination of samples, the stainless steel scissors were wiped between
samples. Immediately following collection, each hair sample was cataloged and placed in an envelope
specifically provided by the testing laboratory, Trace Elements, Incorporated (4501 Sunbelt Drive,
Addison, TX 75001). Specimens were sent to Trace Elements within a few days of collection.
Trace Elements, Incorporated (TEI) is a licensed and certified clinical laboratory. They specialize in hair
analysis and are regularly inspected by the Clinical Laboratory Division of the U.S. Department of Health
and Human Services. For our samples, laboratory personnel used a state-of-the-art Sciex Elan 6100 for
the inductively coupled plasma-mass spectrometry measurements. Extensive quality assurance and
quality control checks were factored into all analytical procedures, and replicate samples were submitted
with each batch of specimens as an external check. In addition, four samples were sent to an independent
laboratory, Doctor’s Data, Incorporated (3755 Illinois Avenue, St. Charles, IL 60174).
Table 3-2 is an example laboratory report from Trace Elements. The reports included concentrations for
32 elements, broken into sub-groupings of toxic, nutritional, and supplemental elements. Element
concentrations were reported in units of milligram percent (milligrams of the element per 100 grams of
hair), with one milligram percent (mg %) being equal to ten parts per million (ppm).
The report also included a reference concentration (RfC) or reference range for each element. Reference
concentrations and ranges represent levels of the element seen in healthy dogs, based on a major study of
all common breeds (TEI 2005). Toxic elements, such as arsenic, are examined with respect to a specific
reference concentration, while nutritional elements, such as calcium, are compared to reference ranges.
This range, comprised of a lower reference limit and an upper reference limit, represents the zone of
element concentrations seen in a healthy dog. The RfC for arsenic, for example, is 0.02 mg %, but the
acceptable RfC range for calcium is 41-129 mg %. Concentrations above these RfCs are not necessarily
toxic, but the values can be considered “guidelines for comparison with reported test values” (TEI 2005).
Because no established protocol was available for performing a risk assessment on results from hair
sample analyses, we developed a simple method in a companion project (Madden 2006, Peterson and
Madden 2006) employing hazard quotients and hazard indices similar to those commonly used in the field
of risk analysis (USEPA 2004, USEPA 1989). In particular, relative risk was defined via the following
term:
5
HQij =
C ij
RfC i
where HQij was the hazard quotient of element i for pet j; Cij was the concentration of element i in the hair
sample of pet j; and RfCi was the reference concentration for element i. The RfC for each element was
the healthy reference level from research regarding healthy populations of dogs (TEI 2000).
In addition, a pet hazard index (HIj’) was calculated for each pet by summing the hazard quotients across
the elements:
i= N
HI j = ∑ HQij
'
i =1
where N is the number of elements. Likewise, an element hazard index (HIi’) was calculated for each
element by summing the hazard quotients across the pets:
'
HI i =
j =M
∑ HQ
ij
j =1
where M was the total number of pets.
To arrive at indices that were not dependent on the number of elements in the lab reports, nor dependent
on the number of pets in the study, we normalized hazard values by the number of elements and pets as
follows:
i=N
HI j =
∑ HQ
ij
i =1
N
and
j =M
HI i =
∑ HQ
ij
j =1
M
where the target value was 1.0 for both HIj and HIi. Pets with HIj values greater than or equal to 1.0 were
defined as pets of concern (POCs), and elements with HIi values greater than or equal to 1.0 were defined
as elements of concern (EOCs).
6
Table 3- 1. Questionnaire Used in the 2005 Campaign
Domestic Pets as Environmental Biosamplers
MWTP Campaign
Summer 2005
Field Data
Pet/Sample Number: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Pet species: Dog Cat Other:____________
Pet gender: Male Female
Pet’s name: ______________________
Pet’s breed: _____________________
Pet’s age: __________
Length of time the pet lived at his/her home: ____________
Pet’s approximate weight: ___________
Pet’s owner: ______________________
Pet’s home address: ______________________
Pet’s phone number: ______________ or e-mail address: __________________
Brief description of pet’s yard (approximate size, fenced, grass-covered, exposed soil, etc.):
Approximate time per day the pet spends indoors? ____ hours
Approximate time per day the pet spends in the yard? ____ hours
Approximate time per day the pet spends outside the yard? ____ hours
Regarding #15, where does the pet normally go?
What brand of pet food is the pet normally fed? ________________
Is the pet food canned or dry? Canned Dry
Does the pet drink water from the residential water supply? Yes No
Does (or did) the pet have health problems? Yes No If yes, what and when?
Does (or did) anyone in your family have health problems? Yes No If yes, what and when?
Has your home or yard been recently remodeled or remediated as part of the Superfund cleanup?
Yes No If yes, which and when?
Do you want us to keep any of the data regarding your pet “confidential” for any reason?
Yes No
24. Anything else?
Field investigator(s): ________________________________________________________________
Signature of investigator taking notes: ________________________
Date and time of sample collection: ___________________
Make and model number of GPS unit: _____________________________________
GPS location of dog’s residence: _________________________________________
Make and model number of digital camera:_______________________________________
Photo number(s) of sampled dog in camera’s memory:________________________
Laboratory for Analysis: Trace Elements, Inc.; 4501 Sunbelt Drive; Addison, TX 75001
Date Sample Was Mailed to Laboratory for Analysis: ______________
7
If so, what?
Table 3- 2. Example Laboratory Report from Trace Elements, Inc.
8
4. RESULTS
4.1 Mining History of Butte and Anaconda
Butte mining activity began in the 1870s, with the discovery of gold, silver, and copper deposits. By
1890, copper production approached 113 million concentrated pounds per year, and Butte soon became
the largest North American copper producer (MacMillian 2000). Many mining enterprises employed a
process known as heap roasting in the initial stages of smelting. In this process, sulfide ores were slowly
burned for two to three weeks in large, layered woodpiles, often as large as a city block, to remove the
sulfur from the ore. The smoke released from this process inundated the Butte area with metal-bearing
smoke, which was often thick enough to immerse the town in darkness (MacMillian 2000). In addition to
the deposition of metals from smoke, the mines, mills, smelters, and concentrators created metal-bearing
tailings and waste piles that were discharged to Silver Bow Creek or left in mine yards and residential
areas (USEPA 2005).
At the turn of the century, the Amalgamated Copper Company built the Washoe Smelter near Anaconda
to process Butte’s ores. Smoke from the smelter blanketed the Deer Lodge Valley and Butte area. Within
one year of smelter start-up, several hundred horses and cows in the Deer Lodge Valley died. A postmortem examination of one horse showed arsenic levels of 13 ppm. Hay used to feed the horse was also
tested and determined to contain 13 ppm arsenic (MacMillan 2000).
During the century of large-scale mining operations, approximately 500 underground mines operated on
the Butte hill, also know as Uptown Butte and Walkerville (USEPA 2005). These mines, along with
several mills, smelters, and concentrators, created millions of cubic yards of mine waste, which was left in
the area. This waste includes mill tailings, slag, waste rock, and dust from aerial deposition. This waste
is often in residential areas and is mobilized during storm events (USEPA 2005).
The largest physical reminder of the scale of Butte mining activities is the Berkeley Pit. This is the site of
a former open-pit copper mine that operated from 1955 to 1982. The 675-acre, 1.2x1010 cubic-foot pit
was dewatered during mining operations but, after mine closure, the dewatering operations ceased and
groundwater connected to underground mine workings flooded the pit (USEPA 2005). This groundwater
is connected to bedrock and alluvial aquifers and is known to affect the groundwater flow within the
alluvial aquifer (USEPA 2005).
Portions of Silver Bow Creek are now referred to as the Metro Storm Drain. This drain is a man-made
water conveyance used to transport storm water, mine water, and sewage. Historically, the drain was
used by the Anaconda Company to convey wastewater from the Berkeley Pit. Silver Bow Creek
currently begins at the confluence of the Metro Storm Drain and Blacktail Creek and becomes the
headwaters of the Clark Fork River (USEPA 2005).
Mining activity continued in the Butte and Anaconda area throughout the 20th century, particularly
during World War II, but curtailed at the close of the 20th century, following the Washoe Smelter closure
in 1980 and the end of Anaconda Copper Mining Company operations in 1982 (USEPA 2005).
Currently, Montana Resources Incorporated runs a large-scale operation adjacent to the old Anaconda
workings. Figure 4-1 details historic and current mining activity in the Butte area and includes the outline
of the Butte Priority Soils Operable Unit (BPSOU).
9
The EPA designated the Silver Bow Creek area as a Superfund site in September of 1983. The
significance of the Butte area as a continued source of contamination to the creek caused the EPA to
enlarge the site in 1987, when it became the Silver Bow Creek/Butte Area NPL site (USEPA 2005). This
site consists of several operable units, including: Butte Priority Soils, West Side Soils, Active Mining
Area, Streamside Tailings, Rocker Timber Framing and Treating Plant, and Warm Springs Ponds
(USEPA 2005). Contaminants of concern at the site include: arsenic, cadmium, copper, iron, lead,
manganese, mercury, sulfate, zinc, and others (USEPA 2005).
4.2 Environmental Impact
As part of the Superfund activities in the region, many soil, sediment, and water samples have been
collected in the Butte and Anaconda area during the past two decades. In particular, the database
submitted as part of the remedial investigation (RI) report for the BPSOU contained concentrations of
arsenic, cadmium, copper, lead, and zinc measured in approximately 2,700 soil samples collected in the
Butte area. In Figures 4-2 through 4-6, we mapped spatial distributions of arsenic, cadmium, copper,
lead, and zinc concentrations, respectively. Concentrations as high as 11,900 ppm arsenic; 56,100 ppm
cadmium; 1,380,000 ppm copper; 67,100 lead; and 3,150,000 zinc were observed. Overall, areas of
maximum environmental impact coincide with the historical mining, milling, and smelting activities
(Figure 4-1), but some of the samples collected outside of the BPSOU also had elevated levels of arsenic,
copper, lead, and zinc.
Concentrations observed in the Butte Priority Soils database indicated obvious impacts of mining and
smelting activities. For example, the average and maximum arsenic concentrations from 2,739 soil
samples were 214 ppm and 11,900 ppm, respectively. Reference or background concentrations of arsenic
can be highly variable, but a reasonable value in soil is 7 ppm (WA 1994). According to the EPA’s
Integrated Risk Information System (IRIS), arsenic is believed to cause noncancer effects such as
hyperpigmentation, keratosis, and possible vascular complications from oral exposures. It is also believed
to cause skin cancer from oral exposures and lung cancer from inhalation exposures (USEPA 2006a).
Using EPA’s Soil Screening Guidance (USEPA 2006b), the risk-based soil screening levels (SSLs) for
arsenic are: 1) 23.5 ppm to protect against noncarcinogenic health effects, 2) 3.82 ppm to protect against
cancer effects, and 3) 0.426 ppm to protect against cancer effects when adjusted for age to account for
increased exposure as a child. Based on this, the average soil sample for arsenic in the Butte database
was 9 times higher than the SSL for noncancer effects and 500 times higher than the SSL for age-adjusted
cancer effects. The maximum arsenic concentration was 500 times higher than the SSL for noncancer
effects and 27,900 times higher than the SSL for age-adjusted cancer effects.
4.3 Cancer Statistics for Silver Bow County
Butte is located in Silver Bow County, the only county in Montana that was assigned a “priority 1” index
by the National Cancer Institute in 2004 (U.S. National Cancer Institutes of Health 2004). Priority 1
indicates an area where the annual death rate from cancer is above the U.S. rate, and an area that also
exhibits a rising trend of deaths from cancer (Table 4-1). The annual death rate from cancer for Silver
Bow County between the years of 1997 and 2001 was 238.6/100,000 people compared to rates for
Montana and the U.S. of 195.0/ and 199.8/100,000 people, respectively. In addition, trends showed that
10
the annual rate of cancer death was rising in Silver Bow County but declining in the rest of Montana and
the rest of the nation.
In addition to data from the National Cancer Institute, a request from the Montana Department of Public
Health and Human Services (MDPHHS) in 2001 prompted the Agency of Toxic Substances and Disease
Registry (ATSDR) to conduct a health consultation, and the report was released in December of 2003
(Dearwent and Gonzalez 2002). Cancer incidences in Silver Bow County for the years 1979 to 1999 were
compared to data from the entire state of Montana, and to the United States as a whole. Six types of
cancer (urinary bladder, kidney, liver, lung, prostate, and skin) were chosen as those most often linked to
arsenic exposure. Based on the average standardized incidence ratios (SIRs), Silver Bow County had
higher cancer rates than the rest of Montana, and higher rates than the rest of the U.S., in at least one age
group for nearly all six types of cancer. The only exception was for prostate cancer, where Silver Bow
County had less than the national rate, but even in that case, the incidence of prostate cancer for Silver
Bow County was dramatically higher than the rest of Montana.
Cancer data described above were averaged over the whole county. A variety of mining and smelting
operations over the years, however, resulted in levels of soil contamination with extreme spatial variations
throughout the area. Spatial variations in residential exposure and health effects throughout Silver Bow
County are likely. To date, however, incidence of cancer, or incidence of other health problems, has not
been investigated on neighborhood scales with the purpose of relating environmental exposure to health
effects.
4.4 Sentinel Species for Studying Exposure
According to O’Brien et al. (1993), “Sentinels are organisms in which changes in known characteristics
can be measured to assess the extent of environmental contamination and its implications for human
health and to provide early warning of those implications.” Over the years, many animals have been used
as sentinel species to advance the field of toxicology (O’Brien et al. 1993). Heyder and Takenaka (1996)
noted that small mammals have been used as primary sentinel species in most laboratory studies, but they
also concluded that dogs (Canis familiaris) were preferred for evaluating pulmonary responses to air
pollutants in controlled laboratory settings. Calderon-Garciduenas et al. (2001a, 2001b) expanded on this
idea and examined dogs residing in Mexico to study effects of air pollution on respiratory, cardiac, and
brain pathology. Thomas et al. (1976) and Berny et al. (1995) found correlations between blood lead
levels in dogs and children residing in the same households, and Hayes et al. (1981) related incidence of
bladder cancer in dogs to bladder cancer in humans. House cats (Felis domesicus) were also found to
exhibit similar responses as humans to methyl mercury poisoning (O’Brien et al. 1993), and the study of
Berny et al. (1995) resulted in no significant difference in blood lead levels between house cats and
humans.
Compared to other species, dogs and cats live parallel to humans and are exposed to the same toxins in
soils, water, and house dust in a residential setting. In addition, dogs and cats are known to develop
clinical signs more rapidly than humans after exposure, thus providing an “early warning” of threat to
human health for reasons such as shorter life spans and decreased latency (O’Brien et al. 1993). Prior to
our work, however, no one addressed exposures to mining-related contaminants or incidence of disease
among domestic pets living in the Butte area.
11
4.5 Hair Analysis for Studying Chronic Exposure
The body has physiological mechanisms that remove contaminants after exposure such as excretion
through the hair, which immobilizes the toxin in the keratin. Hair analysis, according to Lauwerys and
Hoet (2001), is a good indicator of long-term absorption of inorganic arsenic, and concentrations in the
hair shaft represents exposure periods of 1-10 months and longer (United States Department of Public
Health and Human Services 2000). Controversial views exist about how much of the hair analysis might
be contamination externally adsorbed to the hair shaft (Siedel et al. 2001), but the method is considered a
good “screening” level indicator of chronic exposure to environmental toxicants (Hinwood et al. 2003),
and the Agency for Toxic Substances and Disease Registry (ATSDR) has used the method with human
subjects in recent health consultations elsewhere (Orloff and Mistry 2001). We found no data in the
literature, however, for levels of contaminants in hair samples from human or pet populations living on
Superfund sites.
In summary, many residents of Butte live inside a contaminated zone known as the Butte Priority Soils
Operable Unit. Although cancer statistics for Silver Bow County are elevated when compared to rest of
Montana and the rest of the U.S., residential exposure and health problems have not been investigated on
neighborhood scales. Our research introduced a new type of screening tool using domestic pets as
sentinel species with hair sampling and analysis to study incidental, chronic contact with contaminants in
the environment.
4.6 General Information about the Field Campaign
The primary campaign for this project consisted of the sampling of approximately 200 dogs during
summer of 2005. Background data from the questionnaires were included in the Master of Science thesis
(Barry 2006), but general information is summarized in Table 4-2. In particular, 180 of the sampled pets
were dogs residing in the vicinity of Butte, 15 were dogs from Anaconda and Opportunity, and two lived
in Deer Lodge and Whitehall. Of the dogs residing in Butte, 94 lived within the envelope of the BPSOU,
and 84 lived outside the BPSOU. Average age and weight of the pet were 5.3 years and 45.6 lbs,
respectively. In addition, five dogs were sampled repeatedly over time for the remediation campaign.
Figures 4-7 and 4-8 are maps showing residence locations for the pets living in the Butte and Anaconda
areas.
4.7 General Statistics of the Dataset
The Master of Science thesis (Barry 2006) contains the complete dataset from the laboratory reports, but
Table 4-3 summarizes concentration statistics for each element, including the reference concentration
(RfC), range of concentrations observed, average, median, standard deviation, and percent of observations
that exceeded the RfC. Arsenic and lead concentrations, for example, were above the RfCs in 72.6 and
41.6 percent of the samples, respectively. Levels of boron, selenium, manganese, and molybdenum were
above reference in 43.1-79.7 percent of the specimens. At the other end of the spectrum, levels of
mercury, tungsten, and platinum never exceeded the reference concentrations.
Figures 4-9 and 4-10 provide graphic representations of the percent of samples with concentrations above
the RfCs and the ratio of the maximum concentration to the RfC for each element. Elements with the
highest percentages were manganese, selenium, boron, molybdenum, arsenic, lead, and aluminum (Figure
12
4-9). Also, zinc, manganese, arsenic, lithium, lead, cadmium, and tin had the highest maximum
concentration-to-RfC ratios (Figure 4-10).
Because arsenic is a known human carcinogen, concentration statistics for arsenic were developed for
subgroups of the sample population. These subgroups included pets residing in Butte, pets residing in
Anaconda and Opportunity, pets residing in Deer Lodge or Whitehall, male pets, female pets, pets
residing within the BPSOU, and pets residing outside of the BPSOU. Both Butte and Anaconda showed a
high percentage of samples with arsenic concentrations above the reference concentration, at 71.7 percent
and 93.3 percent, respectively (Table 4-4). Of the 94 specimens collected within the BPSOU, 78.5
percent of the samples contained arsenic levels above the RfC. Of the 84 Butte samples collected outside
the BPSOU, 64.3 percent were above the arsenic reference concentration. Average and median
concentrations were the lowest for the Deer Lodge and Whitehall dogs, and highest for the Anaconda and
Opportunity pets. Sex of the pet did not appear to affect results.
4.8 Risk Analysis
As described previously, Madden (2006) developed a simple method of risk analysis for biosampling data
by employing the concepts of hazard quotients and hazard indices (Peterson and Madden 2006). This
method of analyzing risk was applied to the data from the 2005 campaign. Hazard quotient charts for all
197 hair samples are located in the Master of Science thesis (Barry 2006), but Figures 4-11 and 4-12
contain the charts for Dogs 184 and 195.
Dog 184 (Mandy) was a 13 year-old pomeranian who resided in the downtown area of Butte, outside the
BPSOU. Mandy’s hazard index was 0.36, the smallest hazard index of the 2005 campaign. As shown in
Figure 4-11, the hazard quotients were less than 1.0 for all of the 32 elements. In addition, three other
dogs (Dogs 183, 185, and 186) were tested at the same house, and they also had low hazard indices (0.49,
0.38, and 0.8, respectively).
Dog 195 (Crockett) exhibited the largest hazard index of the campaign, a value of 3.57. Crocket was a 16
year-old husky who resided on Mercury Street in Butte, inside the BPSOU, near the site of the former
Stephens Mine (Sanborn Map Company 1894). As shown in Figure 4-12, the hazard quotients for
Crockett were greater than or equal to 1.0 for 69 percent of the elements, and the highest HQ is a value of
26.9 for manganese. The three additional dogs (Dogs 192, 193, and 194) living at this house also
revealed elevated hazard indices (1.87, 1.12, and 1.91, respectively).
Tables 4-5 and 4-6 summarize the pet hazard index data for all 197 dogs. Hazard indices were not
calculated for Dogs 127, 134, and 150. Dogs 127 and 134 were pets with very short hair, and the
samples were too small for the laboratory to analyze, and the number 150 was inadvertently omitted from
the campaign. In addition, Dog 126 exhibited a large concentration of lithium (12.778 mg %), which
equated to an HQ value of 1600, so the hazard index listed in the table for Dog 126 does not include
lithium.
13
4.9 Identification of Pets of Concern
While Dogs 184 and 195 represent the two extremes, Figures 4-13 and 4-14 illustrate the HIj data for all
pets sampled in the 2005 campaign. Thirty-six pets were identified as pets of concern based on pet
hazard indices of 1.0 or greater. Of the 30 POCs in Butte, 26 resided inside the BPSOU and four of the
Butte pets resided outside the BPSOU boundary. While there were no pets of concern in the Anaconda
samples, there were two in Sheep Gulch, two near the Butte reservoir, one in Rocker, and one in
Opportunity.
4.10
Identification of Elements of Concern
Table 4-7 contains the element hazard index data for the 2005 campaign. As shown in Figure 4-15, the
following eight elements were identified as elements of concern, based on element hazard indices of 1.0
or greater: aluminum, arsenic, boron, lead, lithium, manganese, molybdenum, and selenium. Of these
elements, arsenic and manganese had the largest hazard indices with values of 2.24.
4.11
Probability Distribution Analysis
Because our data distributions were not Gaussian, the commonly-used Student’s t-test was not
appropriate for analyzing our results; therefore, the Kolmogorov-Smirnov (KS) test was used to examine
whether levels of toxic elements of dogs residing inside the envelope of the Butte Priority Soils Operable
Unit were different from pets living elsewhere in the community. The KS test is a “goodness of fit” test
designed to determine if two datasets belong to the same population. The KS test is non-parametric and
does not assume a specific distribution of data, and the null hypothesis is that there is “no difference”
between the probability distributions of the datasets. Two statistics are considered: 1) a D-value,
representing the maximum difference between the cumulative distributions; and 2) a p-value, used to
reject or accept the null hypothesis. In particular, the null hypothesis is rejected if the p-value is small,
approaching 0.000, and accepted if the p-value is large, approaching 1.000 (Kirkman 2006).
Figures 4-16 and 4-17 show cumulative fraction plots for phosphorous and manganese, respectively. In
Figure 4-16, distributions of phosphorous HQs were nearly identical for pets residing inside and outside
of the BPSOU, and the D and p-values for this test were 0.046 and 1.000, respectively. In Figure 4-17,
however, the distribution for manganese was distinctly higher for pets residing inside the BPSOU
compared to those living outside the BPSOU, and the D and p-values were 0.314 and 0.000, respectively.
Therefore, KS tests for these two elements indicate that there was no significant difference in
phosphorous levels for pets residing inside and outside of the BPSOU, but the levels of manganese were
significantly higher in pets residing inside the BPSOU.
The Master of Science thesis contains the cumulative fraction plots for all 32 elements in addition to the
tabulated statistics from the KS testing (Barry 2006). Four elements (beryllium, mercury, platinum, and
tungsten) exhibited discrete rather than continuous distributions and were omitted from the KS analysis,
but Figures 4-18 and 4-19 depict the D and p-values for the remaining 29 elements. The highest D
statistics (approximately 0.3) and the lowest p-values (0.000) corresponded to manganese and lead, and in
both cases, concentration distributions for pets living inside the BPSOU were significantly higher than for
pets living outside the BPSOU. At the other extreme, copper, zinc, phosphorous, and strontium had the
14
lowest D statistics (approximately 0.05) and highest p-values (0.998-1.000), suggesting no difference
inside and outside the BPSOU.
Of the eight elements defined as elements of concern, the KS statistics showed that manganese and lead
exhibit the most dramatic difference between inside and outside the BPSOU, while selenium and
molybdenum showed the least difference. Overall, aluminum, arsenic, lead, lithium, and manganese
levels tended to be more elevated in pets living inside the BPSOU, especially at the higher concentrations.
On the other hand, differences in boron, molybdenum, and selenium distributions were less evident.
4.12
Spatial Distribution Analysis
While the KS method was useful in statistically analyzing probability distributions of the hazard quotient
data, maps were developed to investigate spatial distributions. The Master of Science thesis contains the
maps of residence locations for pets with HQ values greater than 1.0 for the eight EOCs (Barry 2006), and
Figures 4-20 and 4-21 depict results for the arsenic data in the Butte and Anaconda areas, respectively.
As reported, 78.5 percent of the pets residing within the BPSOU exhibited concentrations above the RfC
for arsenic and 64.3 percent of Butte pets living outside of the BPSOU exceeded the reference, as did 93.3
percent of the pets in Anaconda and Opportunity. In Figure 4-20, the existence of some pets residing
within the BPSOU with low arsenic levels may reflect a positive outcome of remediation that has taken
place throughout the past two decades. On the other hand, elevated arsenic concentrations in the hair of
pets living both inside and outside of the BPSOU boundary may suggest the need for ongoing
investigation and/or remedial actions.
Similar results were seen for the pets of concern. According to this study, there was a 27.7 percent
probability that the pet HIj exceeded 1.0 for pets living within the BPSOU, compared to a 4.8 percent
chance for Butte pets residing outside the BPSOU. Figure 4-22 shows that most of the POCs were
located within the central portion of the BPSOU.
To identify “hotspots,” or neighborhoods with highest exposure rates, the hazard index for each POC was
mapped. Based on the 2005 data, two locations (the 500 block of Mercury and the 100 block of East
Daly) were shown to have higher hazard indices than other areas in Butte. The hazard index values and
locations of these hotspots are shown in Figure 4-23. Those two neighborhoods should be investigated to:
1) determine the source(s) of the pets’ exposures, and 2) remediate. Although exposure to environmental
contaminants should be more extreme for pets than for humans, human residents at those locations may
also be at risk.
4.13
Remediation Investigation
To investigate the efficacy of remediation, hair samples from five dogs were collected over time. Luna,
the control dog, resided at a home where no remediation occurred. Trip lived at a house where the attic
dust was removed as part of the local Superfund activities. Sweetie, Max, and Teddy lived at residences
undergoing cleanup of contamination in the yard soil. Because remediation of the houses occurred at
different times, the campaign was conducted over the course of eight months, from June of 2005 through
February of 2006. The Master of Science thesis contains detailed results from the remediation study for
all five dogs (Barry 2006).
15
After employing the K-S test, five elements were determined to have significant differences for pets
residing inside and outside of the BPSOU (aluminum, arsenic, lead, lithium, and manganese). Table 4-8
summarizes the hazard quotients of these elements for each sampling round. Figures 4-24 through 4-28
depict the time series of hazard quotient data for these elements over the course of the remediation
campaign.
As shown in Figure 4-24, hazard quotients for all five elements were less than 1.0 for the control dog,
Luna. Lead and lithium did not vary at all throughout the eight-month period, while the hazard quotients
for aluminum, arsenic, and manganese varied slightly, possibly attributed to changes in outdoor/indoor
activities during winter months.
Data for Trip exhibited dramatic decreases in hazard quotients of the five elements during the four-month
period following the remediation of the house dust, and a leveling off to HQ values less than 1.0 during
the last three months (Figure 4-25). Manganese and arsenic exhibited the largest decreases at 95 percent
and 71 percent, respectively, compared to the initial concentrations measured before the remediation.
Similar results were seen for Sweetie in Figure 4-26. Hazard quotients for aluminum, arsenic, and lithium
decreased as much as 96 percent during the first three months after yard remediation. Lead and
manganese did not show any trends, and the hazard quotients increased in two of the samples. While the
increases in lead concentration resulted in hazard quotients less than or equal to 1.0, the HQ values for
manganese were greater than 1.0 in all but two of the samples.
Trends in the data for Max were less remarkable because his exposures were minimal prior to the
remediation of his yard. Hazard quotients for all five elements were less than 1.0 in the first four samples
and a HQ value greater than 1.0 in the last sample (Figure 4-27). The arsenic level in the last sample
represented an increase compared to the first round of sampling, which caused the HQ to elevate above
1.0.
Finally, in Figure 4-28, most of the hazard quotients for Teddy were less than 1.0 for all of the elements
except arsenic. In this case, arsenic levels actually increased over the sampling period, and the last
sample represented a 100 percent increase in arsenic compared to the initial sample. These results
indicated the likelihood that Teddy’s primary exposure to arsenic was a source other than the yard. In
addition, Teddy was the only remediation dog residing in a house with exposure to cigarette smoke.
Overall, results from the remediation campaign suggest that our biomonitoring method is capable of
documenting efficacy of cleanup actions. In particular, removal of contaminated house dust resulted in
measurable decreases of elements in the hair over a three-month period. Remediation of yards also
resulted in lower contaminant levels in the hair samples, but improvement was less evident when the preremediation concentration levels were not elevated and when other sources may have impacted exposure
(i.e., smoking).
16
Table 4- 1. Cancer Rates from National Cancer Institute for 1997-2001
RISING
ANNUAL
HIGHER
AREA
ANNUAL DEATH
OR
PERCENT
OR
RATE FROM
FALLING
CHANGE IN
LOWER
CANCER PER
TREND
DEATH RATE
THAN
100,000 PEOPLE
NATIONAL FROM CANCER
(95 % CI)
(95 % CI)
RATE
Silver Bow County
238.6 (218.3, 260.6)
Higher
+3.2 (0.4, 6.1)
Rising
Montana
195.0 (191.0, 199.0)
Lower
-0.6 (-1.0,-0.2)
Declining
United States
199.8 (199.6, 200.0)
-
-1.1 (-1.2, -1.0)
Declining
Reference: U.S. National Cancer Institutes of Health 2004
17
Table 4- 2. Summary of Information for Pets in the 2005 Hair Sampling Campaign
DESCRIPTION
NUMBER
Total number of samples in the primary campaign
200
Total pets with complete lab reports
197
Pets sampled that resided in or around Butte
180
Pets sampled that resided in Anaconda or Opportunity
15
Pets sampled that resided in Deer Lodge or Whitehall
2
Range of ages of pets (years)
0.25-17
Average age of pets (years)
5.3
Range of weight of pets (lbs)
3.5-160
Average weight of pets (lbs)
45.6
Number of male pets
116
Number of female pets
81
Butte pets residing within the BPSOU
94
Butte pets residing outside of the BPSOU
84
Total samples for the remediation investigation
24
Total sample splits (replicates) for Quality Control (QC)
9
Total laboratory splits for Quality Control (QC)
4
18
Table 4- 3. Concentration Statistics of Elements in the 2005 Hair Samples
AVERAGE &
MEDIAN
(MG %)
Calcium (Ca)
129
22-386
107 & 78
Magnesium (Mg)
27
1.4-57.4
16.9 & 12.1
Sodium (Na)
205
4-461
96 & 77
Potassium (K)
62
1-165
22 & 14
Copper (Cu)
1.7
0.8-4.7
1.5 & 1.4
Zinc (Zn)
20
11-312
19.5 & 18
Phosphorus (P)
35
5-62
25 & 25
Iron (Fe)
9.9
0.9-40.9
5.3 & 3.6
Manganese (Mn)
0.33
0.031-8.892
0.740 & 0.325
Chromium (Cr)
0.12
0.009-0.24
0.074 & 0.07
Selenium (Se)
0.16
0.05-1.53
0.21 & 0.20
Boron (B)
0.59
0.09-6.83
1.27 & 1.15
Cobalt (Co)
0.026
0.001-0.047
0.005 & 0.003
Molybdenum (Mo)
0.022
0.003-0.152
0.023 & 0.020
Sulfur (S)
4885
2859-5107
4030 & 4065
Uranium (U)
0.02
0.0005-0.0244
0.002 & 0.001
Arsenic (As)
0.02
0.006-0.272
0.045 & 0.032
Beryllium (Be)
0.002
0.0001-0.002
0.001 & 0.001
Mercury (Hg)
0.04
0.01-0.03
0.01 & 0.01
Cadmium (Cd)
0.02
0.001-0.25
0.016 & 0.007
Lead (Pb)
0.2
0.02-3.6
0.28 & 0.10
Aluminum (Al)
3.2
0.3-32
3.7 & 2.3
Germanium (Ge)
0.04
0.003-0.07
0.007 & 0.007
Barium (Ba)
0.4
0.02-1.81
0.27 & 0.16
Lithium (Li)
0.008
0.001-12.778
0.008 & 0.005
0.001-0.215*
0.073 & 0.005*
Nickel (Ni)
0.25
0.01-2.27
0.09 & 0.05
Platinum (Pt)
0.02
0.001-0.001
0.001 & 0.001
Vanadium (V)
0.06
0.002-0.111
0.019 & 0.015
Strontium (Sr)
0.54
0.001-1.37
0.23 & 0.16
Tin (Sn)
0.04
0.01-0.54
0.02 & 0.01
Tungsten (W)
0.04
0.001-0.023
0.002 & 0.001
Zirconium (Zr)
0.06
0.01-0.41
0.05 & 0.03
*
Statistics without the lithium concentration for Dog #126
ELEMENT
RFC
(MG %)
RANGE
(MG %)
19
STANDARD
DEVIATION
(MG %)
72
12.2
80
22
0.6
21.1
7
5.8
1.249
0.028
0.12
0.88
0.006
0.018
384
0.003
0.045
0.000
0.003
0.030
0.42
4.9
0.005
0.31
0.910
0.008*
0.18
0.000
0.015
0.24
0.05
0.002
0.05
≥ RFC
(%)
32.0
22.8
8.1
5.1
25.9
21.3
8.1
10.7
48.7
7.1
69.0
79.7
2.5
43.1
1.0
1.5
72.6
2.0
0.0
21.8
41.6
34.0
0.5
16.8
28.9
4.6
0.0
2.5
16.2
8.1
0.0
28.4
Table 4- 4. Arsenic Concentration Statistics for Groups
STANDARD
DEVIATION
(MG %)
0.042
0.062
≥
RFC
(%)
0.006-0.272
0.017-0.217
AVERAGE &
MEDIAN
(MG %)
0.043 & 0.030
0.077 & 0.048
2
0.012-0.015
0.0135 & 0.0135
0.002
0.0
116
81
94
0.006-0.272
0.007-0.270
0.006 – 0.272
0.044 & 0.032
0.046 & 0.034
0.049 & 0.032
0.045
0.044
0.051
72.1
72.8
78.7
84
0.008 – 0.210
0.038 & 0.030
0.035
64.3
GROUP
N
RANGE
(MG %)
Pets residing in Butte
Pets residing in Anaconda
and Opportunity
Pets residing in Deer
Lodge and Whitehall
Male pets
Female pets
Pets residing within the
BPSOU
Pets residing outside of the
BPSOU
180
15
20
71.7
93.3
Table 4- 5. Pet Hazard Index (HIj) Data for Pets 1-100
PET
NUMBER
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
41
42
43
44
45
46
47
48
49
50
PET NAME
HIj
PET
NUMBER
Maxine
Kaliah
Sinkers
Mirage
Blue Berry
Cookie
Maddy
Thelma
Rosco
Bones
Cody
Rudy
Willie
Thumper
Hombre
Poco
Ruger
Luna
Dorito
Noah
Yogi
Misty
Fritz
Hershey
Chocko
Kyo
Casey
Dino
Baby
Alena
Duffy
Kasey
Blackie
Tobie
Justice
Bailey
Nellie
Sophia
Abby
Aussie
Benson
Sanuf
Trip
Patches
Tucker
Max
Beaut
Poco
Lucy
Butch
0.77
0.74
0.57
0.64
0.66
0.49
0.93
0.50
0.40
0.37
0.63
0.40
0.77
1.69
0.61
0.61
0.76
0.52
0.64
0.61
0.51
0.40
0.78
0.46
0.43
0.69
0.70
0.74
0.48
1.61
0.38
0.53
1.38
0.92
0.44
0.36
0.55
0.75
0.63
0.91
0.56
0.42
1.03
0.83
0.97
1.01
1.01
1.23
0.78
0.49
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
21
PET NAME
HIj
Murphy
Kissy
Kerby
Bear
Lady
Timber
Angus
Zoe
Kosmos
Niko
York
Sammie
Bosley
Maisy Mae
Ole
Tsara
Penny
Koots
Moe
Ari
Dewey
Bart
Boomer
Griz
Angus
Rowe
Tucker
Tanner
Magnum
Miss Piggy
Bear
Buddy
Penny
Griz
Panda
Allie
Ali
Shasta
Sadie
Rosco
Clover
Arrow
Jinxy
Curious
KOA
Resee
Cobuk
Emilio
Yukon
Naiki
0.93
0.54
0.84
0.80
0.42
1.13
1.02
0.70
0.53
0.62
0.49
0.53
0.48
0.72
0.53
0.60
0.84
0.59
0.73
0.53
0.51
0.40
0.44
1.23
0.53
0.85
0.40
0.53
0.67
0.70
0.51
0.69
0.56
0.76
0.69
0.59
0.48
0.60
0.55
0.67
0.56
0.54
1.27
0.57
1.26
0.44
1.63
0.54
1.35
1.83
Table 4- 6. Pet Hazard Index (HIj) Data for Pets 101-200
PET NUMBER
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
PET NAME
Rick
Billie
Tosh
Collette
Nellie
Duke
Pepper
Bud
Hunter
Akita
Chance
Shelby
Gracie
Bozo
Boo
Tawney
Pork Chop
Boone
Gus
Andy
Bebe
Rosco
Hosser
Jackson
Bear
Einstein
Suzie
Nikita
Max
Shaq
Shilo
Catie
Breezy
Angel
Pebbles
Missy
Shasta
Shylo
Tessa
Brandi
Bear
Shylo
Sidney
Mop Head
Duke
Momma Dog
Little Girl
HIj
0.93
0.57
0.70
0.62
0.67
1.01
0.58
0.59
0.97
0.82
0.56
0.91
1.17
1.33
2.56
0.53
0.61
0.43
0.52
0.54
1.16
0.99
0.60
0.59
0.47
1.42*
NA
0.60
0.90
0.39
0.63
0.70
0.62
NA
0.37
0.59
0.68
0.61
0.58
0.84
0.76
0.70
0.61
0.65
0.59
0.67
0.70
2.31
2.76
NA
PET NUMBER
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
* = Hazard Index without Lithium
22
PET NAME
Tiger
Bear
Kyra
Max
Dodger
Casey
Curley
Harley
Kelsey
Griz
Deeka
Benson
Katy
Max
Maggie
Whyley
Bear
Harley II
Pete
Sweetie
Mana
Angus
Morgan
Oscar
Ike
Lily
Shelton
Chewie
Little Boy
Jenna
Maggie
Onyx
Camy
Mandy
Dante
Toby Joe
Annie
Bob
Ireland
Norman
Buddy
Cody
Flint
Striper
Crockett
Rudy
Ramone
Mattie
Phil
Teddy
HIj
0.99
1.81
1.02
0.40
1.60
0.57
1.35
0.69
0.51
0.71
0.65
0.41
1.36
0.44
0.66
0.77
0.62
1.10
0.87
0.93
0.71
1.28
0.40
0.53
0.52
0.41
2.11
0.48
0.49
0.49
0.50
0.53
0.49
0.36
0.38
0.80
1.36
0.75
0.61
0.52
0.68
1.87
1.12
1.91
3.57
0.45
0.46
0.66
0.42
0.37
Table 4- 7. Element Hazard Index (HIi) Data for the 2005 Campaign
ELEMENT
HIi
ELEMENT
HIi
ELEMENT
ELEMENT
HIi
Calcium
0.83 Manganese
2.24 Arsenic
2.24 Lithium*
Magnesium
0.62 Chromium
0.61 Beryllium
0.51 Nickel
Sodium
0.47 Selenium
1.29 Mercury
0.27 Platinum
Potassium
0.36 Boron
2.16 Cadmium
0.80 Vanadium
Copper
0.89 Cobalt
0.19 Lead
1.38 Strontium
Zinc
0.98 Molybdenum
1.03 Aluminum
1.15 Tin
Phosphorus
0.72 Sulfur
0.83 Germanium
0.18 Tungsten
Iron
0.54 Uranium
0.19 Barium
0.67 Zirconium
* not including lithium concentration from Dog 126.
23
HIi
1.04
0.34
0.05
0.32
0.64
0.51
0.04
0.76
DOG
Luna
(control)
Trip
Sweetie
Max
Teddy
Table 4- 8. Results from the Remediation Campaign
DATES OF
HAZARD QUOTIENT FROM THE HAIR SAMPLES
SAMPLING ALUMINUM ARSENIC LEAD MANGANESE LITHIUM
6-16-2005
0.25
0.75
0.50
0.30
0.13
10-15-2005
0.22
0.65
0.50
0.35
0.13
12-12-2005
0.22
0.65
0.50
0.35
0.13
1-15-2006
0.16
0.55
0.50
0.20
0.13
2-15-2006
0.25
0.70
0.50
0.22
0.13
6-22-2005
0.72
2.90
2.00
5.06
0.75
9-28-2005
0.75
1.80
0.50
0.81
0.50
12-12-2005
0.19
0.95
0.50
0.29
0.50
1-15-2006
0.19
0.85
0.50
0.29
0.38
2-15-2006
0.22
0.90
0.50
0.25
0.13
9-14-2005
4.91
6.65
0.50
1.27
3.25
10-15-2005
0.91
2.55
1.00
0.71
0.50
12-12-2005
0.44
1.55
0.50
2.36
0.25
1-15-2006
0.31
0.90
0.50
0.89
0.13
2-15-2006
0.50
1.85
0.50
1.46
0.25
8-10-2005
0.19
0.45
0.50
0.27
0.25
10-15-2005
0.13
0.50
0.50
0.15
0.25
12-12-2005
0.16
0.60
0.50
0.18
0.13
1-15-2006
0.09
0.30
0.50
0.12
0.13
2-15-2006
0.16
1.50
0.50
0.16
0.13
9-14-2005
0.31
1.70
0.50
0.24
0.25
10-15-2005
0.19
1.75
0.50
0.35
0.25
12-12-2005
0.34
2.35
0.50
0.35
0.13
1-15-2006
0.13
1.05
0.50
0.20
0.13
2-15-2006
0.56
3.40
1.50
0.55
0.25
24
Figure 4- 1. Historical mining activity in the Butte area (including the boundary of the Butte
Priority Soils Operable Unit).
25
Figure 4- 2. Map of arsenic concentrations in the soil from the BPSOU database.
26
Figure 4- 3. Map of cadmium concentrations in the soil from the BPSOU database.
27
Figure 4- 4. Map of copper concentrations in the soil from the BPSOU database.
28
Figure 4- 5. Map of lead concentrations in the soil from the BPSOU database.
29
Figure 4- 6. Map of zinc concentrations in the soil from the BPSOU database
30
Figure 4- 7. Residence locations of Butte pets sampled during the 2005 Campaign.
31
Figure 4- 8. Residence locations of Anaconda pets sampled during the 2005 Campaign, in addition
to pets living in Opportunity, Sheep Gulch, and Warm Springs.
32
100
GREATER THAN RfC (%)
80
60
40
20
Ca
Mg
Na
K
Cu
Zn
P
Fe
Mn
Cr
Se
B
Co
Mo
S
U
As
Be
Hg
Cd
Pb
Al
Ge
Ba
Li
Ni
Pt
V
Sr
Sn
W
Zr
0
ELEMENT
Figure 4- 9. Percent of samples in the 2005 campaign where the concentration exceeded the
reference level for each element.
33
MAXIMUM CONCENTRATION-TO- RFC RATIO
50
40
30
20
10
Ca
Mg
Na
K
Cu
Zn
P
Fe
Mn
Cr
Se
B
Co
Mo
S
U
As
Be
Hg
Cd
Pb
Al
Ge
Ba
Li
Ni
Pt
V
Sr
Sn
W
Zr
0
ELEMENT
Figure 4- 10. Ratio of the maximum concentration in the 2005 campaign to the reference
concentration for each element.
34
DOG 184 - MANDY
6
HAZARD QUOTIENT
5
4
3
2
1
Ca
Mg
Na
K
Cu
Zn
P
Fe
Mn
Cr
Se
B
Co
Mo
S
U
As
Be
Hg
Cd
Pb
Al
Ge
Ba
Li
Ni
Pt
V
Sr
Sn
W
Zr
0
ELEMENT
Figure 4- 11. Hazard quotient (HQ) graph for Dog 184. Green shading indicates a HQ value less
than 1.0, and red shading corresponds to a HQ value of 1.0 or above.
35
DOG 195 - CROCKETT
36
HAZARD QUOTIENT
30
24
18
12
6
Ca
Mg
Na
K
Cu
Zn
P
Fe
Mn
Cr
Se
B
Co
Mo
S
U
As
Be
Hg
Cd
Pb
Al
Ge
Ba
Li
Ni
Pt
V
Sr
Sn
W
Zr
0
ELEMENT
Figure 4- 12. Hazard quotient (HQ) graph for Dog 195. Green shading indicates a HQ value less
than 1.0, and red shading corresponds to a HQ value of 1.0 or above.
36
PETS OF CONCERN (POC) - 2005 CAMPAIGN
5
4
3.5
3
1
Pet 93
Pet 95
Pet 97
Pet 99
Pet 100
Pet 74
Pet 56
Pet 57
48
Pet 43
1.5
Pet 46
Pet 47
Pet
Pet 30
2
Pet 33
2.5
Pet 14
NORMALIZED HAZARD INDEX
4.5
0.5
97
93
89
85
81
77
73
69
65
61
57
53
49
45
41
37
33
29
25
21
17
9
13
5
1
0
Pet Number
Figure 4- 13. Hazard index (HIj) graph for Pets 1-100. While green shading indicates a HIj value
less than 1.0, red shading corresponds to a HI value of 1.0 or above. Pets with a HIj value greater
than or equal to 1.0 are defined as pets of concern (POCs).
37
PETS OF CONCERN (POC) - 2005 CAMPAIGN
5
Pet 195
4
Pet 193
Pet 187
Pet 192
Pet 194
Pet 177
Pet 172
Pet 168
Pet 163
Pet 153
1
Pet 121
1.5
Pet 113
Pet 114
2
Pet 126
2.5
Pet 152
3
Pet 155
Pet 157
Pet 115
Pet 148
Pet 149
3.5
Pet 106
NORMALIZED HAZARD INDEX
4.5
0.5
197
193
189
185
181
177
173
169
165
161
157
153
149
145
141
137
133
129
125
121
117
113
109
105
101
0
Pet Number
Figure 4- 14. Hazard index (HIj) graph for Pets 101-200. While green shading indicates a HIj value
less than 1.0, red shading corresponds to a HI value of 1.0 or above. Pets with a HIj value greater
than or equal to 1.0 are defined as pets of concern (POCs).
38
ELEMENTS OF CONCERN (EOC) - 2005 CAMPAIGN
As
B
Al
Li
Mo
1.5
Pb
2
Se
NORMALIZED HAZARD INDEX
2.5
Mn
3
1
0.5
Ca
Mg
Na
K
Cu
Zn
P
Fe
Mn
Cr
Se
B
Co
Mo
S
U
As
Be
Hg
Cd
Pb
Al
Ge
Ba
Li
Ni
Pt
V
Sr
Sn
W
Zr
0
ELEMENT
Figure 4- 15. Hazard index (HIi) graph for all elements in the 2005 campaign. While green shading
indicates a HIi value less than 1.0, red shading corresponds to a HIi value of 1.0 or above. Elements
with HIi values greater than or equal to 1.0 are defined as elements of concern (EOCs).
39
Figure 4- 16. Cumulative fraction plot for KS Test 7: phosphorous HQs in Butte dogs residing
inside the BPSOU (N = 94) and phosphorous HQs in Butte dogs residing outside the BPSOU (N=
84). The solid line represents the dogs residing inside the BPSOU and the dashed line represents
the dogs outside the BPSOU.
40
Figure 4- 17. Cumulative fraction plot for KS Test 9: manganese HQs in Butte dogs residing inside
the BPSOU (N = 94) and manganese HQs in Butte dogs residing outside the BPSOU (N= 84). The
solid line represents the dogs inside the BPSOU and the dashed line represents the dogs outside the
BPSOU.
41
1
KS STATISTIC D
0.8
0.6
0.4
0.2
V
Sr
Sn
W
Zr
Cd
Pb
Al
Ge
Ba
Li
Ni
Ca
Mg
Na
K
Cu
Zn
P
Fe
Mn
Cr
Se
B
Co
Mo
S
U
As
0
ELEMENT
Figure 4- 18. The Kolmogorov-Smirnov statistic D for the comparison of cumulative distributions
inside versus outside the BPSOU. The statistic D represents the maximum (vertical) distance
between the distributions.
42
1
KS P-VALUE
0.8
0.6
0.4
0.2
V
Sr
Sn
W
Zr
Cd
Pb
Al
Ge
Ba
Li
Ni
Ca
Mg
Na
K
Cu
Zn
P
Fe
Mn
Cr
Se
B
Co
Mo
S
U
As
0
ELEMENT
Figure 4- 19. The Kolmogorov-Smirnov p-value for the comparison of cumulative distributions
inside versus outside the BPSOU. If the p-value is small (approaching 0.000), the null hypothesis
may be rejected; if the p-value is large (approaching 1.000), there is likely no difference between the
distributions.
43
Figure 4- 20. Residence locations of pets sampled in the vicinity of Butte with color-coding to
indicate hazard quotients in the hair samples above and below 1.0.
44
Figure 4- 21. Residence locations of pets sampled in the vicinity of Anaconda with color-coding to
indicate hazard quotients in the hair samples above and below 1.0.
45
Figure 4- 22. Residence locations of the pets of concern (POCs) in the Butte area. A POC was
defined as a pet with a hazard index of 1.0 or higher when all elements were considered.
46
Figure 4- 23. Hazard index values of the pets of concern (POCs) and associated hotspots in the
Butte area.
47
REMEDIATION CONTROL DOG: LUNA
8
HAZARD QUOTIENT
7
6
5
4
3
2
1
0
5/3/2005
6/17/2005
8/1/2005
9/15/2005
10/30/2005 12/14/2005
1/28/2006
3/14/2006
SAMPLING DATE
Al
As
Pb
Mn
Li
Figure 4- 24. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium
for the remediation control dog, Luna.
48
REMEDIATION DOG: TRIP
8
HAZARD QUOTIENT
7
6
5
4
3
2
1
0
5/3/2005
6/17/2005
8/1/2005
9/15/2005
10/30/2005
12/14/2005
1/28/2006
SAMPLING DATE
Al
As
Pb
Mn
Li
Figure 4- 25. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium
for the remediation dog, Trip.
49
REMEDIATION DOG: SWEETIE
8
HAZARD QUOTIENT
7
6
5
4
3
2
1
0
5/3/2005
6/17/2005
8/1/2005
9/15/2005
10/30/2005 12/14/2005
1/28/2006
3/14/2006
SAMPLING DATE
Al
As
Pb
Mn
Li
Figure 4- 26. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium
for the remediation dog, Sweetie.
50
REMEDIATION DOG: MAX
8
HAZARD QUOTIENT
7
6
5
4
3
2
1
0
5/3/2005
6/17/2005
8/1/2005
9/15/2005
10/30/2005 12/14/2005
1/28/2006
3/14/2006
SAMPLING DATE
Al
As
Pb
Mn
Li
Figure 4- 27. Time series of concentrations of aluminum, arsenic, lead, manganese, and lithium for
the remediation dog, Max.
51
REMEDIATION DOG: TEDDY
8
HAZARD QUOTIENT
7
6
5
4
3
2
1
0
5/3/2005
6/17/2005
8/1/2005
9/15/2005
10/30/2005 12/14/2005
1/28/2006
3/14/2006
SAMPLING DATE
Al
As
Pb
Mn
Li
Figure 4- 28. Time series of hazard quotients of aluminum, arsenic, lead, manganese, and lithium
for the remediation dog, Teddy.
52
5.
DISCUSSION
As with all biological or ecological indices, our data contained variability in accumulation of the elements
of concern. In this report, we focused on introducing the method, presenting results from our field
campaign, and devising a way to examine the data. Sources of variability (such as breed type, sex, age of
the pet, etc.) were not discussed here, but will be addressed in a future publication regarding a larger
dataset.
In terms of limitations, exposure to environmental toxins is likely extreme for pets, compared to exposure
for humans, because of self-grooming habits and because pets have more direct contact with soil, house
dust, and mud puddles; thus, we should not assume that the method can be directly extrapolated to
humans. Furthermore, our method of assigning hazard quotients and hazard indices is based on
concentrations relative to reference concentrations. This is a simple, initial step toward evaluating
incidental exposure to environmental contaminants, but relative toxicity of individual elements is not
incorporated. Refinement of the method could include relative toxicity factors derived from data
employed in the field of human health risk assessment.
Overall, our new biomonitoring technique was designed as a screening-level tool to identify contaminants
that may be of concern in a community. For a residential area like Butte, the method may be useful for
discovering homes or neighborhoods that may be in need of further investigation and/or remediation.
Justification of the project involved the use of dogs and cats as sentinels to protect the health of adults and
children residing in a contaminated area, but protection of health and well-being of the local pets is also
important.
53
6.
SUMMARY AND RECOMMENDATIONS
As a review, the overall goal of our research was to improve our understanding of chronic exposure to
contaminants in the environment. The following two objectives were identified for this project:
Objective 1. To develop and test a simple, inexpensive, biomonitoring system to characterize
existing chronic exposure to mining-related contaminants for dogs residing in Butte, Montana;
and
Objective 2. To use the biomonitoring method to try to document efficacy of localized
remediation efforts.
Regarding Objective 1, our new protocol involved collection of hair samples with subsequent analysis
using inductively coupled plasma – mass spectrometry (ICP-MS) as an easy, non-invasive way to obtain
biological data regarding toxin/contaminant environmental exposure. The method was tested in the
summer of 2005 by sampling more than 200 pets, including a variety of breeds, ages, and residence
locations. For Objective 2, hair samples were collected over the course of several months from dogs
living at houses with attics or yards undergoing remediation.
In addition to the two objectives, the following four questions were posed prior to the research campaign:
1) Are levels of toxic elements in Butte dogs higher than reference levels?
2) Are the levels of toxic elements for dogs living inside the envelope of the Butte Priority Soils
Operable Unit (BPSOU) higher than elsewhere in the community?
3) Are there “hotspots”, or neighborhoods in Butte where domestic dog exposures are highest?
4) If yards or homes are remediated, how long will it take to reduce the body burden of
contaminants in the biosamplers?
Concentrations from the hair samples were compared with reference levels, and concentration statistics
were developed for each of 32 elements. Concentrations of arsenic, for example, were above the
reference concentration of 0.02 mg % in 72.6 percent of the samples, while boron, lead, manganese,
molybdenum, and selenium were above reference concentration in 41.6-79.7 percent of the samples,
respectively. Based on a method of risk analysis using hazard quotients and hazard indices, 36 of 200
pets were identified as pets of concern, and the following eight elements were identified as elements of
concern: aluminum, arsenic, boron, lead, lithium, manganese, molybdenum, and selenium.
To determine if the levels of toxic elements in dogs living inside the envelope of the BPSOU were higher
than elsewhere in the community, concentration data were examined from 178 dogs with roughly half of
the dogs residing inside the BPSOU and half outside. Probability distributions of these two data sets were
compared using the non-parametric Kolmogorov-Smirnov test. Among the eight elements defined as
elements of concern, pets residing within the BPSOU exhibited significantly higher levels of aluminum,
54
arsenic, lead, lithium, and manganese than Butte pets living outside of the BPSOU. Differences in boron,
molybdenum, and selenium were less dramatic.
Regarding neighborhoods or areas in Butte with highest exposures, a series of maps were developed
showing residence location of pets with hazard quotients and hazard indices greater than 1.0. Of the 36
pets of concern, 30 resided in Butte with 26 living inside the BPSOU boundary and four living outside the
BPSOU. Most of the pets of concern were located within the central portion of the BPSOU, and two
locations, the 500 block of Mercury and the 100 block of East Daly, were considered hotspots.
Finally, to assess the efficacy of remediation, hair samples were collected over the course of several
months from dogs living at houses with attics or yards undergoing remediation. Luna, the control dog,
exhibited low variability in hazard quotients. Of the remediation dogs, Trip exhibited the largest
reduction in hazard quotients. Trip resided at a house where attic dust was removed, and he experienced a
reduction of 95 percent manganese and 71 percent arsenic during the course of the study. Of the other
remediation dogs, all of whom resided at a house with a remediated yard, Sweetie had the largest decrease
in aluminum, arsenic, and lithium concentrations. Max experienced reductions aluminum, lead, lithium,
and manganese, but had a spike in arsenic in the final sample. Teddy’s results revealed an increase in
arsenic over the course of the study, but Teddy was the only remediation dog residing in a house with
exposure to cigarette smoke.
This project was the first step in developing the new biomonitoring technique into a screening-level tool
for studying incidental exposure to environmental contaminants. Although the use of animals as sentinel
species is not a new idea, this project is the first of its kind to draw on domestic pets as biosamplers with
subsequent hair sampling and analysis to study chronic exposure of environmental contaminants in a
residential Superfund area. Although results from our campaign were site specific, the method developed
and tested here has potential for applications elsewhere. Pets are companion animals and results from
our research may have implications for human health risk assessment.
Regarding follow-up projects, there are several studies that could aid in a better understanding of the
long-term health impacts associated with living within the Butte/Anaconda Superfund area. An
expansion of the biosampling project to gain a broader sample size and coverage would further identify
areas with elevated exposure rates. It would also enable researchers to determine change in community
exposure rates over time. These data could be compared with metals-related disease rates (in pets and in
humans) to determine the impact of the exposure. Hair sampling of human residents of the Superfund
area would also prove invaluable in a public health assessment and could aid in the understanding of other
metals-contaminated Superfund sites.
Based on this investigation, it would be worthwhile to perform environmental sampling of the ground,
water, and air at residences, particularly at houses corresponding to the pets identified as pets of concern.
To further investigate these houses, hair, blood, and urine samples of human residents would help
document chronic and acute exposure to environmental contamination. In addition to an investigation of
the houses with pets of concern, an investigation of houses with pets exhibiting arsenic levels higher than
the reference concentration of 0.02 mg % would be beneficial. A detailed study of cancer rates in these
houses would also help characterize the carcinogenicity of the arsenic in the Butte and Anaconda areas.
Finally, a large-scale epidemiological study is also necessary to understand long-term health impacts of
residents of Butte and Anaconda. In this study, an investigation of cancer, neurological, respiratory,
cardiovascular, and developmental diseases should be performed. If death certificates are used, care
55
should be taken to search for cancer as a secondary cause of death. Early death certificates should also be
checked for diseases, such as tuberculosis, which may also be the result of exposure to metalscontaminated dust. This epidemiological study should be correlated with environmental samples, past
mining activity, and current hazardous waste sites within the Superfund area. The Butte and Anaconda
areas are important because people reside within the Superfund boundaries, and this should be seen as an
excellent opportunity for the scientific community to better understand health impacts of contamination at
Superfund sites.
56
7.
7.1
QUALITY ASSURANCE/QUALITY CONTROL (QA/QC)
Deviations from the Quality Assurance Project Plan
The QAPP was followed closely throughout the project. The following three deviations, however, were
necessary:
1. The QAPP indicated that we would utilize t-tests for examining differences between population
means. Concentration distributions within our dataset were not Gaussian, so the t-test was not an
appropriate method of hypothesis testing. Instead, the Kolmogorov-Smirnov (KS) test was used.
This test is a “goodness of fit” test designed to determine if two datasets belong to the same
population. The KS test is non-parametric and does not assume a specific distribution of data,
and the null hypothesis is that there is “no difference” between the probability distributions of the
datasets.
2. The QAPP specified that we would use AutoCAD or Surfer programs to map the biosampling
results. The GIS program was used in place of the AutoCad or Surfor programs because this
program had the capability of integrating environmental data from the Butte Superfund Site.
While the GPS locations were taken, as specified in the QAPP, the sampling addresses were
instead mapped with the GIS.
3. The QAPP proposed a five-month period for conducting the remediation campaign with analysis
using time series graphs, mean concentrations, and standard deviations. While the campaign
schedule was followed as closely as possible, coordinating with remediation activities and pet
owners caused some of the sampling periods to last longer than 5-months. In addition, time series
graphs were used to illustrate the results, but percent change was used in place of mean and
standard deviation statistics. With only five data points collected over time, average and standard
deviation statistics were not appropriate measures of efficacy of remediation.
Overall project outcome was not compromised by any of these deviations. In fact, in all cases, project
quality was improved as a result of these minor changes.
7.2
Laboratory and Field QA
Appendix A contains a description of QA/QC policy and procedure for Trace Elements, Incorporated. In
addition, we requested quality analysis summary reports corresponding to each batch of samples analyzed
for our project. Table 7-1 is a checklist of the information provided in those reports.
As proposed in the QAPP, replicate samples were submitted to Trace Elements, Incorporated with every
batch of samples, and four split samples were sent to an independent laboratory (Doctor’s Data
Incorporated, DDI). Figures 7-1 and 7-2 show the comparison of concentrations of the 32 elements from
the replicate and split samples, respectively.
As itemized in Table 7-2, average relative percent difference (RPD) for the replicate samples ranged from
-24.2 % (for Dog 100) to 15.2 % (for Dog 160). All replicates met the criteria of RPD ≤ 20 %, except for
Dog 100. The original hair sample from Dog 100 was much larger than the rest, so it is possible that the
replicate and split samples were not identical. Likewise, average RPD for inter-laboratory splits ranged
57
from -21.6 % (Dog 40) to 21.1 % (Dog 100), and all four samples met the criteria of RPD ≤ 35 %. Unlike
a water sample, for example, hair samples are not perfectly homogeneous, so some variation in
concentration for replicates and splits is expected. To reduce this uncertainty in future campaigns, we
will mix the hair more thoroughly before dividing into replicate and split samples.
7.3
General Recordkeeping and Reporting
As set forth in the QAPP, all sampling and analysis activities were documented in a logbook maintained
by Stacie Barry. The logbook was bound, and pages were numbered. Each page with an entry was
initialed and dated by Stacie and by Dr. Holly Peterson. All corrections in the logbook consisted of a
single line out deletion followed by the author’s initials and date. Unused portions of a page were lined
out. The logbook included a written record of all appropriate data and observations. The QAPP was
followed throughout the project, so no major deviations from the initial plan were noted.
In addition to the logbook, a questionnaire for each pet was completed during sampling. The
questionnaires were photocopied and bound in 3-ring notebooks. The notebook with the originals was
stored in Dr. Peterson’s office, and Stacie Barry maintained one complete copy. A third copy was given
to the Montana Tech MWTP office.
Regarding laboratory reports from Trace Elements, the originals were photocopied upon receipt and
stored in a 3-ring binder in Dr. Peterson’s office. Stacie maintained a copy and the Montana Tech MWTP
office received a third copy of the binder. In addition, all data from the lab reports were entered into a
spreadsheet and checked by at least one other person. The spreadsheet file was copied to more than one
computer and submitted on CD with the final report.
Monthly reports were submitted to document progress, and meetings were held with the Montana Tech
QA Manager on a regular basis. At the conclusion of the project, this final report was prepared by the
graduate student and the principal investigator. The final report included a summary of the original
project objectives, and these objectives were met.
Project details and results of this work were summarized by Stacie Barry in a Master of Science thesis
during the spring of 2006 and presented in an oral defense at Montana Tech on June 27, 2006. After the
final report is accepted, the information will be condensed and submitted for publication in the
Intermountain Journal of Sciences. A copy of the manuscript will be submitted for review and approval
by the MWTP Program prior to the time of submission to the journal, and reprints will be provided
following publication.
58
Table 7- 1. Quality Analysis Checklist from Laboratory Summary Reports
DATE OF QUALITY ANALYSIS
LABORATORY SUMMARY REPORT
07/19/2005
08/23/2005
11/07/2005
1/05/2006
03/03/2006
Standard 1 Concentrations Concentrations Concentrations Concentrations Concentrations
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD
Standard 2 Concentrations Concentrations Concentrations Concentrations Concentrations
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD
Standard 3 Concentrations Concentrations Concentrations Concentrations Concentrations
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD
Low
Concentrations Concentrations Concentrations Concentrations Concentrations
Check
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD
High
Concentrations Concentrations Concentrations Concentrations Concentrations
Check
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD
China Hair Concentrations Concentrations Concentrations Concentrations Concentrations
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD
Hair Pool Concentrations Concentrations Concentrations Concentrations Concentrations
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD
± 2 SD: Quality control limits of ± 2 standard deviations
59
Table 7- 2. Quality Control Checklist for Replicate and Split Samples
SAMPLE
TEI
DOES REPLICATE RPD
TEI/DDI
DOES SPLIT RPD
REPLICATE
MEET CRITERIA OF
SPLIT
MEET CRITERIA OF
RPD (%)
≤ 20% ?
RPD (%)
≤ 35% ?
Dog 20
-10.3
Yes
Dog 40
2.0
Yes
-21.6
Yes
Dog 60
1.4
Yes
Dog 80
-6.5
Yes
Dog 100
-24.2
No
21.1
Yes
Dog 120
1.4
Yes
Dog 140
13.8
Yes
-14.5
Yes
Dog 160
15.2
Yes
-12.4
Yes
Dog 180
-5.8
Yes
60
10000
TRACE ELEMENTS SPLIT SAMPLE 2 (mg %)
1:1
1000
100
DOG 20 - NOAH
DOG 40 - AUSSIE
DOG 60 - NIKO
DOG 80 - MISS PIGGY
DOG 100 - NAIKI
DOG 120 - ANDY
DOG 140 - SHYLO
DOG 160 - GRIZ
DOG 180 - JENNA
10
1
0.1
0.01
0.001
0.0001
0.0001 0.001
0.01
0.1
1
10
100
1000
TRACE ELEMENTS SPLIT SAMPLE 1 (mg %)
Figure 7- 1. Concentration comparison of replicate samples.
61
10000
10000
DOCTOR'S DATA SPLIT SAMPLE (mg %)
1:1
1000
100
10
DOG 40 - AUSSIE
DOG 100 - NAIKI
DOG 140 - SHYLO
DOG 160 - GRIZ
1
0.1
0.01
0.001
0.0001
0.0001 0.001
0.01
0.1
1
10
100
1000
10000
TRACE ELEMENTS SPLIT SAMPLE (mg %)
Figure 7- 2. Concentration comparison of inter-laboratory split samples.
62
8. REFERENCES
Barry, S. 2006. Domestic Pets as Biosamplers of Mining-Related Contaminants. M.S. Thesis. Montana
Tech, Butte, MT. 279 pp.
Berny, P.J., L.M. Cote, and W.B. Buck. 1995. Can household pets be used as reliable monitors of lead
exposure to humans? The Science of the Total Environment. 172:163-73.
Calderon-Garciduenas, L., T.M. Gambing, H. Acuna, R. Garcia, N. Osnaya, S. Monroy, A. VillarrealCalderon, J. Carson, H.S. Koren, and R.B. Devlin. 2001a. Canines and sentinel species for
assessing chronic exposures to air pollutants: Part 1. Cardiac Pathology. Toxicological Sciences.
61:356-367.
Calderon-Garciduenas, L., A. Mora-Tiscarena, L.A. Fordham, C.J. Chung, R. Garcia, J. Hernandez, H.
Acuna, T.M. Gambing, A. Villarreal-Calderon, J. Carson, H.S. Koren, and R.B. Devlin. 2001b.
Canines and sentinel species for assessing chronic exposures to air pollutants: Part 1. Respiratory
Pathology. Toxicological Sciences. 61:342-355.
Dearwent, S. and A. Gonzalez. 2002. Health consultation: Silver Bow Creek/Butte Area, Butte Silver
Bow and Deer Lodge counties, Montana. Agency of Toxic Substances and Disease Registry.
Atlanta, GA.
Hayes, H.M., Hoover, R., and R.E. Tarone. 1981. Bladder cancer in pet dogs: a sentinel for
environmental cancer? American Journal of Epidemiology. 144(2): 229-233.
Heyder, J. and S. Takenaka. 1996. Long-term canine exposure studies with ambient air pollutants.
European Respiratory Journal. 9: 571-584.
Hinwood, A.L., Sim, M.R., Jolley, D., de Klerk, N., Bastone, E. B., Gerostamoulos, J., and O.H.
Drummer. 2003. Hair and toenail arsenic concentrations of residents living in areas with high
environmental arsenic concentrations. Environmental Health Perspectives. 111: 187-194.
Integrated Risk Information System (IRIS). 2005. Arsenic, inorganic (CASRN 7440-38-2). U.S.
Environmental Protection Agency. Office of Research and Development. National Center for
Environmental Assessment. Washington, D.C. (www.epa.gov/iris/index.html)
Kirkman, T. 2006. Kolmogorov-Smirnov Test. (http://www.physics.csbsju.edu/stats/KS-test.html).
Lauwerys, R. and P. Hoet. 2001. Industrial chemical exposure: guidelines for biological monitoring.
CRC Press, Boca Raton, FL.
Madden, M. 2006. Development of a biomonitoring technique using domestic pets as sentinel species in
a mining-impacted community. M.S. Thesis. Montana Tech, Butte, MT. 141 pp.
Macmillan, D. 2000. Smoke wars: anaconda copper, Montana air pollution, and the courts, 1890-1924.
Montana Historical Society Press, Helena, MT.
63
O’Brien, D.J., Kaneene, J.B., and R.H. Poppengda. 1993. The use of mammals as sentinal species for
human exposure to toxic contaminant in the environment. Environmental Health Perspectives.
99, 351-368.
Orloff, K.G. and K. Mistry. 2001. Health consultation: exposure investigation – Spring Valley chemical
munitions, Washington, DC. Agency of Toxic Substances and Disease Registry. Atlanta, GA.
Peterson, H.G. and M.A. Madden. 2006. Development of a new biomonitoring technique using domestic
pets as sentinel species. Intermountain Journal of Sciences. In press.
Sanborn Map Company. 1894. Butte city 1894. Sanborn Map and Publishing Company, New York,
NY, 1894.
Siedel, S., Kreutzer R., Smith D., McNeel S., and D. Gliss. 2001. Assessment of commercial
laboratories performing hair mineral analysis. Journal of the American Medical Association.
253: 67-72.
Thomas, C.W., Rising, J.L., and J.K. Moore. 1976. Blood lead concentrations of children and dogs from
83 Illinois families. Journal of the American Veterinary Medical Association 169(11), 12371240.
Trace Element Incorporated (TEI) 2000. Tissue mineral analysis manual and references, balancing body
chemistry. Trace Elements, Inc. Box 514, Addison, Texas 75001.
Trace Element Incorporated (TEI) 2005. Reference ranges and HTMA materials and methods. Trace
Elements, Inc. Box 514, Addison, Texas 75001.
U.S. Department of Public Health and Human Services. 2000. Toxicological profile for arsenic. Agency
for Toxic Substances and Disease Registry. Atlanta, GA.
U. S. Environmental Protection Agency (USEPA). 1989. Risk assessment guidance for superfund:
volume I. Human health evaluation manual (Part A). EPA/540/1-89/002. Office of Emergency
and Remedial Response. Washington, DC.
U. S. Environmental Protection Agency (USEPA). 2004. Air toxics risk assessment reference library:
volume 2. Facility-specific assessment. EPA-453-K-04-001B. Office of Air Quality Planning
and Standards. Research Triangle Park, NC.
U. S. Environmental Protection Agency (USEPA). 2005. Superfund program cleanup proposal, Butte
priority soils operable unit of the Silver Bow Creek/ Butte Area Superfund Site. 56 pp.
U. S. Environmental Protection Agency (USEPA). 2006a. Integrated Risk Information System (IRIS):
arsenic, inorganic (CASRN 7440-38-2). U.S. Environmental Protection Agency. Office of
Research and Development. National Center for Environmental Assessment. Washington, D.C.
(www.epa.gov/iris/index.html)
64
U. S. Environmental Protection Agency (USEPA). 2006b. Soil screening guidance calculator. EPA
Office of Superfund and Oak Ridge National Laboratory. Oak Ridge, TN.
(http://risk.lsd.ornl.gov/calc_start.shtml)
U.S. National Cancer Institutes of Health. 2004. State cancer profiles. Bethesda, MD.
(http://statecancerprofiles.cancer.gov)
Washington State (WA). 1994. Natural background soil metals concentrations in Washington state.
Publication #94-115. Toxics Cleanup Bureau. Seattle, WA.
65
APPENDIX A
66
The following detailed description of QA/QC was extracted, with written consent from Trace Elements
Incorporated, at the laboratory’s web site: www.traceelements.com.
Trace Elements uses state-of-the-art ICP-Mass Spectrometry (Sciex Elan 6100 and 9000)
methodology for all trace element determinations. These systems are capable of easily handling a
high volume of specimens in applications such as HTMA where limits of detection requirements
are in the part-per-million (ppm) and low part-per-billion (ppb) range. TEI uses the most
advanced high-volume and uniform temperature-controlled microwave digestion (CEM Mars 5
Plus) technique. Microwave digestion is the method of choice for speed, reduced contamination,
complete digestions, and retention of analytes to insure precise results.
Trace Elements laboratory is equipped with a trace element class clean room utilizing HEPA
filtration systems. The clean room ensures that air quality and temperatures are isolated in order
to protect equipment and processed specimens from potential contamination. High sensitivity
balances used by the laboratory for calibration/QC check standards and specimen weighing are
calibrated with weight sets traceable to NIST.
All stock standards used for daily calibration and Quality Control are prepared by a leading ISO
9001 certified laboratory. In addition, all standard material is sourced from NIST standard
reference material. Further, the laboratory uses 16 megohm double-deionized water and acidleached, triple-rinsed glassware and plasticware. All glassware when used is Class A.
Trace Elements conducts daily, weekly and monthly QA/QC studies to confirm and validate all
aspects of test methodology, including precision, accuracy and verifiable detection limits.
Further, the laboratory is continuously evaluating the different aspects of daily laboratory
performance, such as: reagents, QC reference materials, split specimen analysis, spiked samples,
calibration-verification studies and routine daily monitoring of patient data trends, before, during
and after each daily analytical run. Additional audits involve personnel training, laboratory
reporting, safety issues, customer service, etc.
Laboratory management has also recently developed an extremely comprehensive and thorough
state-of-the art automated quality control (AQC) software to assist the chief technologist and
laboratory director in validating all QC test results and individual specimen test results prior to
release for eventual report processing. Trace Elements successfully participates in an on-going
proficiency testing program with Le Centre de Toxicologie du Quebec, which offers urine, blood
and hair tissue elemental testing involving clinical laboratories that utilize high resolution
instrumentation in North America and Europe. Also participating in various other interlaboratory
test comparison studies, Trace Elements is committed to providing the clinician with timely,
precise and reliable test data.
Quality Control
Following is a brief description of the quality control materials and solutions that Trace Elements
utilizes in each daily analytical run. This sequential format does not represent other daily and
routine QC procedures that are performed by technologists in the laboratory prior to each
analysis.
Calibration Blank
Calibration Standard 1
67
Calibration Standard 2
Calibration Standard 3
Initial Calibration Check Standard--Low Level (ICCS)
Initial Calibration Check Standard--High Level (ICCS)
Laboratory Reagent Blank (LRB)
Pooled Hair Check Solution (PHCS)
Split Hair Specimen (SHS)
Pooled Hair Check Material (PHCM)
Certified Reference Material--Hair (CRM-H)
Patient Specimen 1
Patient Specimen 2
Patient Specimen 3
Patient Specimen 4
Patient Specimen 5
Patient Specimen 6
Patient Specimen 7
Patient Specimen 8
Patient Specimen 9
Patient Specimen 10
Patient Specimen 11
Patient Specimen 12
Continuing Calibration Check Standard (CCCS)
Continuing Calibration Blank (CCB)
Patient Specimen 13
Patient Specimen 14
Patient Specimen 15
Patient Specimen 16
Patient Specimen 17
Patient Specimen 18
Patient Specimen 19
Patient Specimen 20
Patient Specimen 21
Patient Specimen 22
Patient Specimen 23
Patient Specimen 24
End Calibration Check Standard--Low Level (ECCS)
End Calibration Check Standard--High Level (ECCS)
Initial Calibration Check Standard -- Low Level (ICCS)
Initial Calibration Check Standard -- High Level (ICCS)
Solutions (two levels) prepared in the same manner as the calibration standards and used to verify
the calibration curve before analysis of patient specimens and QC samples begin.
Laboratory Reagent Blank (LRB)
Used to evaluate all potential contaminants/interferences in the reagents, laboratory environment
and apparatus within the test method.
68
Pooled Hair Check Solution (PHCS)
Homogenous solution of pooled hair that has been pre-digested using standard method digestion.
Used to indicate day-to-day and within-run precision associated with instrument calibration.
Split Hair Specimen (SHS)
Second analysis of a random patient specimen taken from the previous day's run. Using a
submitted patient sample to indicate day-to-day laboratory precision associated with the entire
test method; sample preparation, digestion and instrument analysis.
Pooled Hair Check Material (PHCM)
Homogenous pooled hair that is exposed to the same laboratory environment, reagents and
apparatus as the patient specimens throughout the entire test method. Used to indicate day-to-day
laboratory precision associated with sample preparation, digestion and calibration.
Certified Reference Material --Hair (CRM-H)
Certified Hair Reference Material, obtained from National Institute for Environmental Studies,
Japan. Used to indicate day-to-day accuracy and precision of the test method; including reagents,
sample prep, digestion and analysis.
Continuing Calibration Check Standard (CCCS)
Solution prepared in the same manner as the calibration standards and analyzed in the middle of
each subset of patient specimens. Used to verify the previously established calibration curve and
confirms the accurate analyte quantitation for all patient specimens occurring after the initial
calibration check standards.
Continuing Calibration Blank (CCB)
A solution prepared in the same manner as the calibration blank then analyzed after the CCCS to
show any contamination or carryover.
End Calibration Check Standard -- Low Level (ICCS)
End Calibration Check Standard -- High Level (ECCS)
Solutions (two levels) prepared in the same manner as the calibration standards and analyzed at
the end of each subset of patient specimens. Used to verify the previously established calibration
curve and confirms the accurate analyte quantitation for all patient specimens occurring after the
continuing calibration check standards (CCCS).
Test results for all of the above Quality Control materials/solutions and patient specimens are
analyzed in detail by the AQC lab software and then reviewed by the Chief Chemist and
Laboratory Director for compliance to strict quality control limits. Failure to meet the QC criteria
requires that the analysis is repeated until all QC data is within acceptable limits. No data is
released from the laboratory until such time.”
In compliance with CLIA ’88 federal regulations, the SHS analysis is a primary tool to assess and assure
accuracy and precision of the lab’s methods and instrumentation. After calibrations are performed, and
before any patient specimens are analyzed, a sample is randomly chosen out of the most recently analyzed
set of samples, reanalyzed, and a Standard Deviation Index (SDI) score is calculated. The SDI score is:
69
SDI = Repeat Analysis Result – Original Analysis Result
Standard Deviation of Element’s Normal or 2SD Range
An “acceptable” SDI score is ± 3.0, so when any SDI score is out of the acceptable range, the Clinical
Lab Supervisor reviews all pre-analytical, analytical, and post analytical data, and corrective actions are
taken. The calibration series and SHS are then repeated, and no patient specimens are analyzed until an
acceptable SDI score is achieved.
Table A-1 provides a summary of the laboratory QA/QC checks for critical measurements.
70
Table A- 1. Summary of Laboratory QA/QC Checks for Critical Measurements of Metals in Hair
QA/QC Check
Calibration
Blank
Calibration
Standard 1
Calibration
Standard 2
Calibration
Standard 3
Initial
Calibration
Check-Low
Level (ICCS)
Initial
Calibration
Check-High
Level (ICCS)
Laboratory
Reagent Blank
(LRB)
Poole Hair
Check Solution
(PHCS)
Split Hair
Specimen
(SHS)
Pooled Hair
Check Material
(PHCM)
Reference
Material (CRMH)
Continuing
Calibration
Verification
(CCV)
Continuing
Calibration
Blank (CCB)
End Calibration
Check – Low
Level (ECCS)
End Calibration
Check – High
Level (ECCS)
Frequency
At beginning of run
At beginning of run
Criteria
≤ 2 times the
IDL
NA
Action
Clean apparatus, check reagents for contamination
NA
At beginning of run
NA
NA
At beginning of run
NA
NA
Following initial
standardization
± 15%
Terminate analysis, correct problem, recalibrate
Following initial
standardization
± 15%
Terminate analysis, correct problem, recalibrate
Following second
ICCS
≤ 2 times the
IDL
Clean apparatus, check reagents for contamination,
restandarize
Following LRB
≤ 20% RPD
Terminate analysis, correct problem, recalibrate
Following PHCS
≤ 20% RPD
Terminate analysis, correct problem, recalibrate
Following SHS
≤ 20% RPD
Terminate analysis, correct problem, recalibrate
Following PHCM
75% to 125%
recovery
Terminate analysis, correct problem, recalibrate
Every 12 samples
± 15%
Terminate analysis, correct problem, recalibrate and
rerun affected batch
Every 12 samples
≤ 2 times the
IDL
Clean apparatus, check reagents for contamination,
restandarize and rerun affected batch
At end of batch
± 15%
Terminate analysis, correct problem, recalibrate and
rerun affected batch
At end of batch
± 15%
Terminate analysis, correct problem, recalibrate and
rerun affected batch
71