January 14, 1977
Quarterly Progress Report No. 1
September 28 - December 31, 1976
EPIDEMIOLOGIC STUDY CONDUCTED IN POPULATIONS LIVING AROUND
NONFERROUS SMELTERS TO DETERMINE BODY TISSUE BURDENS OF
SELECTED NONFERROUS METALS
EPA Contract No. 68-02-2442
RTI Project No. 31U-1372
Robert W. Handy
Benjamin S. H. Harris, III
Tyler D. Hartwell
Steven Williams
Chemistry and Life Sciences Division
and
Statistical Sciences Group
Research Triangle Institute
Post Office Box 12194
Research Triangle Park, N.C. 27709
Prepared for
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27709
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Table of Contents
I. INTRODUCTION ...................... 1
II. DESCRIPTION OF OVERALL PROGRESS ............. 2
A. Field Operations ................. 2
1. Development of the Detailed Work Plan and
Data Collection Instruments .......... 2
2. Pretest Site ................. 4
a. Attitude of the Smelter ......... 4
b. Attitude of Federal, State, and Local
Agencies ................ 5
c. Availability of Independent Subcontrac-
tors .................. 5
d. Nature of the Site ............ 5
e. Cost ...... . ............ 6
3. Public Relations ............... 6
4. Paint and Dietary Lead ............ 8
a. Paint Lead " ............... 8
b. Dietary Lead .............. 11
REFERENCES ....................... 16
B. Sampling Methodology ............... 17
1. Overview ................... 17
2. Work Plan Summary ........... ... 17
3. Pretest .................... 18
4. Target Population .............. 20
5. The Sampling Frame .............. 24
6. Sample Selection ............... 25
ii
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Table of Contents (continued)
Page
7. Sample Size and Quality Control 28
8. Coordination of Related Studies 30
C. Chemical Analysis 33
1. Water 33
2. Urine 33
3. Hair 33
4. Creatinine in Urine 37
5. Curve Fitting of Calibration Data 38
6. Analytical Data Sheets 48
D. Quality Control 48
1. Calibration of Hi-Volume Samplers 48
2. Precision Measurements - Urine and Hair ... 48
3. Working Reference Materials-Air Particulates. 48
4. Working Reference Materials-Tap Water .... 49
E. Sample Packaging and Shipment 49
F. Statistical Methods of Analysis 58
1. Confidentiality of Data Files 58
2. Data Analysis 59
a. Analysis of Environmental Levels .... 59
b. Analysis of Tissue Levels 60
REFERENCES 63
III. POTENTIAL PROBLEM AREAS 64
A. Field Operations 64
1. Anaconda 64
2. Project Schedule 54
iii
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Table of Contents (continued)
Page
B. Chemical Analysis 65
1. FEP Analysis 65
2. Blood Clotting 65
3. Conversion of Organometallics Into an
Assayable Form 65
4. Air Particulate Collection - Power Drops . . 66
C. Statistical Methods of Analysis 67
1. Missing Observation 67
IV. DESCRIPTION OF FUTURE WORK 71
A. Field Operations 71
B. Chemical Analysis 72
C. Quality Control 72
APPENDIX A - Instructions for Feces Collection
APPENDIX B - Study Questionnaire
APPENDIX C - Analytical Data Sheets
IV
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List of Figures (continued)
No. Page
D-l Calibration of Sierra Instrument Orifice, Model 330 51
D-2 HI-VOL Calibration 52
vi
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I. INTRODUCTION
The major effort during the quarter covering September 28 -
December 31, 1976 was directed toward development of the Detailed Work
Plan. This report includes a summary of some aspects of the Work Plan
and in addition, the following major work areas:
a) Proposed plans for the Corpus Christi pretest;
b) Discussion of alternative dietary lead procedures;
c) Description of paint lead methodology;
d) Nonlinear curve fit to calibration data.
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II. DESCRIPTION OF OVERALL PROGRESS
A. Field Operations
During the first quarter of the technical performance period on this research
effort, field operations activities have focused on the following areas:
1. Development of the detailed Work Plan and data collection instruments,
2. Selection of the Pretest site,
3. Public relations related to two of the performance sites, and
4. Considerations regarding the collection of data on paint and dietary
lead.
These aspects of field operations are discussed in subsequent sections.
1. Development of the Detailed Work Plan and Data Collection Instruments
During October, work began on the detailed Work Plan and the data collection
instruments. The Survey Director performed a limited literature review and •
obtained various materials from and through the Environmental Protection Agency
(EPA) relative to various methods of collecting the necessary environmental and
biological samples. RTI learned the six performance sites for this research
effort, which are as follow:
a. Anaconda, Montana,
b. Palmerton, Pennsylvania,
c. Herculaneum, Missouri,
d. Bartlesville, Oklahoma,
e. Bixby, Missouri, and
f. Ajo, Arizona,
probably in that order.
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During November, work continued on the detailed Work Plan and data collec-
tion instruments. A draft of the text of the Work Plan was delivered to the
EPA Project Officer on November 18.
For this study, RTI envisions five data collection instruments: a House-
hold Screening Log (HSL) to maintain a record of households/residence units
screened/contacted; a Household Screening Questionnaire (HSQ) to determine
eligible and cooperative households and participants; a Participant Consent
Form (PCF) to describe the study and the participant's role and obtain the par-
ticipant's informed consent; a Study Questionnaire (SQ) to obtain household
and individual information on demographic variables, residence histories, and
potential special exposure situations; and a Chemical Analysis Report Form
(CARF) for recording and reporting results of chemical analyses. Drafts of the
HSL, HSQ and PCF were delivered to the EPA Project Officer on December 2, and a
•
draft of the SQ was delivered to the EPA Project Officer on December 20; the
CARF is still in various stages of development. On December 10, the RTI Survey
Director met with Dr. Stephen H. Gehlbach of Duke University and the University
of North Carolina (UNC) to discuss the field operations section of the Work
Plan and the SQ. Among Dr. Gehlbach1s comments were that venipuncture should
be used as much as possible for the collection of the blood sample, and that,
at least for lead, the small amount and questionable value of data collected
via feces (see below) and urine do not justify the collection problems and
participant (and interviewer) burden; however, if urine is to be collected,
the RTI procedure for collection and analysis is acceptable. On December 23,
40 copies of the detailed Work Plan were delivered to the RTI Project Officer,
five in loose-leaf form and 35 spiral bound; an informational copy was also
provided to the EPA Contracting Officer.
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2. Pretest Site
As the result of a meeting at EPA, Research Triangle Park (RTP), on
October 28, 1976, involving EPA Project Officer Dr. Warren Galke, Dr. Carl Hayes
of EPA, and RTI Survey Director Benjamin Harris, RTI considered two possible
sites for the Pretest effort—Hayden, Arizona, and Corpus Christi, Texas.
Over the period November 21-25 the Survey Director was in the Phoenix,
Arizona, area to visit prospective and potential performance sites and attend
a meeting of interested and/or involved agencies. On November 22, the Survey
Director visited prospective performance site Ajo, Arizona, and on November 24
he visited potential Pretest site Hayden, Arizona. The purpose of these visits
was to investigate the logistics and staff burden associated with study activities
at these sites, particularly Hayden, such as the availability and problems
associated with transportation, accomodations, and various ancillary and support
•
services. Not withstanding the support expressed by the Arizona Department of Health
Services (ADHS) and the University of Arizona College of Medicine at a meeting
on November 23 (see below), RTI has decided in favor of Corpus Christi, Texas,
as the Pretest site for this study. This decision has been based on a number
of considerations related to the logistics of executing the study protocol at
a site for the first time, in particular the availability and costs of, and
problems and staff burden associated with, various ancillary and support services
.including:
a. Attitude of the Smelter; Both of the smelter firms with
operations at Hayden are involved in various litigations, although only the
Asarco plant at Hayden is specifically involved in such litigation. In addition,
there is information that the smelter industry may undertake an epidemiological
study at Hayden.
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b. Attitude of federal, State, and local agencies; RTI would
prefer a Pretest site where the appropriate federal, State and local agencies
would be interested, perhaps experienced, and hopefully could be actively
involved, in such a study. At the aforementioned meeting at Phoenix, Arizona,
on November 23, 1976, RTI was encouraged by support expressed by ADHS and the
University of Arizona College of Medicine; however, the primary focus of that
meeting was Ajo (see below).
c. Availability of independent subcontractors; The Pretest
will attempt to simulate the main study as closely as possible, except on a
smaller scale, and will therefore follow the Work Plan as closely as possible,
including involvement of independent subcontractors. There are a number of
interviewers from the current RTI listings living in counties within a reasonable
distance of the sites in Texas and Arizona which were under consideration for
the Pretest. That is not to say, however, that all of those individuals would
be available or suitable for this research effort. For example, RTI has two
other major survey research efforts planned for the Phoenix area in early 1977
which would deplete the number of available interviewers in Maricopa county
during that time. Mdre important, however, is the distance which the inter-
viewers must travel to reach the site and the cost and burden associated with
that travel.
d. Nature of the Site; RTI would prefer a community large enough
to permit some flexibility in the event of a large number of nonparticipants, and
so that the logistics of implementing the field operations for the first time
would not be too involved. Both of the Pretest sites under consideration would
present a bilingual population. However, Hayden and Winkelman, Arizona, which
together make up the Hayden smelter community, have a combined population of
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less than 2,000, have extremely limited transportation and medical facilities,
and are approximately two hours driving one way from the nearest transportation
facilities and sources of supplies and support services.
e. Cost; Since the performance sites for the main study were
not known when the proposal was written, one of the smelter communities in the
St. Louis area was considered as a Pretest site for the purpose of estimating
Pretest cost. Several of the considerations cited in preceding paragraphs will
have some impact on cost, particularly the availability of independent sub-
contractors within a reasonable distance of the site, the magnitude of the Pre-
test, and the site itself. For example, round trip tourist air fare Raleigh to
Corpus Christi is $230, and Raleigh to Tucson is $308 (plus ground transportation
to Hayden).
Some of these same considerations entered into the choice of the three
performance sites where elderly persons will be studied (Herculaneum, Bartlesville,
and Ajo), in that RTI will need a larger population base and additional indepen-
•
dent subcontractors. The outcome of the Pretest may have some impact on RTI's '
time and cost projections.
3. Public Relations
On November 23, a meeting at ADHS in Phoenix was attended by the RTI Survey
Director and representatives of EPA/RTP; various offices within ADHS; the Univer-
sity of Arizona College of Medicine, Tucson; EPA Region IX, San Francisco; EPA
Region VIII, Denver; and the Phoenix Laboratory Division of the Center for
Disease Control (CDC). After a general presentation of each agency's interest
in Arizona copper smelters, the group divided into two subgroups, one interested
in emissions control standards and regulations, and one interested in health
effects and primarily Ajo. This latter group consisted of the RTI Survey
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Director and representatives of EPA/RTP; EPA Regions VIII and IX; ADHS; CDC;
and the University of Arizona College of Medicine. The primary concern was the
coordination of activities in Ajo and, to a lesser extent, Anaconda, Montana.
The tentative decisions reached were that CDC will study a group of children
ages 6 to 18 in Ajo in early 1977 using data collection techniques and procedures
compatible with those planned by RTI with support and assistance from EPA, ADHS
and the University of Arizona; RTI will conduct its study in Ajo in late 1977
with support and assistance from EPA, CDC, ADHS and the University of Arizona;
and RTI and CDC will work toward a concurrent effort at Anaconda in the late
spring of 1977 with support and assistance from EPA—that is, Anaconda would
be RTl's first performance site and Ajo the last.
On December 2, 1976, a meeting at EPA/RTP was attended by EPA Project
Officer Galke and Dr. Hayes of EPA/RTP; Dr. Malcolm Harrington of CDC, Atlanta;
and RTI study principals Dr. Robert W. Handy, Survey Director Harris, and Steve
Williams. Again, the primary focus of the meeting was the coordination of
*
activities in Ajo and Anaconda. With regard to Ajo, it was decided that CDC
would proceed with their study of 6-18 year olds in early 1977, but that par-
ticipants will be informed that the CDC activity is the first of a two-part
effort, the second part to be completed by RTI later in 1977. RTI will provide
CDC with a copy of the SQ so that any questions which CDC asks seeking similar
information can be worded the same way, thereby making the data more comparable;
similarly, RTI will provide CDC with details of its sampling plan for Ajo, so
that the population can be selected in the same manner. With respect to Anaconda,
it was decided that RTI and CDC would work toward a coordinated simultaneous
effort with the State of Montana, represented by Harry Hull, with work to be
completed before the end of June 1977- In order to assure quality control of
chemical analysis, CDC is considering contracting their chemical analysis to RTI.
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On December 20, 1976, RTI Survey Director Harris met at EPA/RTP with EPA
Project Officer Galke and Dr. Hayes. At that time, there was some discussion of
initiating public relations activities with representatives of the smelter
industry—American Mining Congress, Washington, D. C.; International Lead Zinc
Research Organization, New York; and the Smelter Environmental Research Association,
represented by Ralph Smith, University of Michigan, Ann Arbor—and Mildred Smith,
EPA, Dallas and Ken Nelson of Asarco regarding the Corpus Christi Pretest site.
There may be some problems with the RTI/CDC joint effort in Anaconda (see
Problems section).
4. Paint and Dietary Lead
In addition to the environmental and biological samples specified in Exhibit
A: Scope of Work for this contract, the Project Officer has asked RTI to con-
sider two additional measurements, paint and dietary lead, which might increase
the significance of data collected in this research effort. Since these measure-
ments are not part of the Scope of Work, procedural and cost considerations are
*
discussed in this report.
a. Paint Lead; Paint lead would be determined by the field
interviewer (FI) at the time of household data collection using a portable
lead detector. Since the EPA Project Officer has indicated that EPA would
purchase the lead detectors, the primary impact on the study as described in
the detailed Work Plan would be the time and cost for the FI to make the
determination(s) and record them on a supplement to the SQ. If one assumes
that 30 households will be investigated for every 40 participants, and that the
paint lead determination will require 30 minutes per household, then the paint
lead determination would require 678 hours of FI t'ime for 1,356 households
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containing 1808 Pretest and study participants; at an FI rate of $3.50
per hour for this study, costs for the paint lead determination would
oome to $2373 plus appropriate overhead and fee rates.
According to EPA and manufacturers, the portable lead detectors can
be operated by non-scientists and the readings recorded for interpre-
tation by a more qualified person at a later point in time. There are
other methods that can be used for the detection of lead paint in houses,
such as chemical spot tests and sophisticated laboratory analysis;
however, these alternatives to the use of portable lead detectors are
more time consuming, expensive and likely to be unacceptable to dwelling
occupants than the portable lead detectors [1].
Mr. John Rhodes, Columbia Scientific Industries (CSI), Austin,
Texas, was contacted for information on portable XRF analyzers. CSI has
developed new procedures and technology for the detection and measure-
ment of lead in paint under contract to HUD. CSI supplies a Model 700
unit.which has the capability of scanning surfaces in situ for lead
levels. Since the device is not a high resolution instrument, scattering
from the wall material interferes with the direct determination of lead.
These interferences must be measured and appropriate corrections made.
CSI has devised a method for overcoming much of this difficulty. An
initial reading is made with no filter (lead plus background) followed
by a second reading with a tungsten filter (background only). Both
readings may be referred to a graph to give a lead concentration value
2
(mg/cm ) - if the nature of the backing material is known. However, CSI
has prepared a nomograph which allows one to read the corrected Pb
•
content without prior knowledge of the backing. The nomograph procedure
is clearly the measurement method of choice. The cost of the Model 700
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is $4,750. Mr. Rhodes made the comment that the unit should be operated
by a trained individual. On the other hand, he claimed that the improved,
direct-reading Model 750 (see below) is easily operated by semiskilled
personnel (i.e., field interviewers).
A new Model 750 portable lead in paint film analyzer has been
developed by Columbia Scientific Industries, under contract with the
HUD. This portable device is capable of rapid, in situ measurement of
lead content in a variety of painted surfaces, irrespective of the
substrate or wall material. The unit provides a direct readout of lead
2
content with a detection limit of 0.1-0.3 mg/cm . This instrument is
claimed to be the only one with adequate sensitivity, accuracy and
applicability to meet the needs of HUD and other lead control programs.
Mr. Rhodes stated that the Model 750 will not be commercially
available for 5-6 months; only 4 experimental units exist at this time.
The cost of the Model 750 Analyzer will be in the $5,000-$10,000.
Bill Hall and Phil Cramp were contacted at NBS concerning available
XRF lead analyzers. They indicated that in addition to Columbia Scientific,
Princeton Gamma Tech, Rocky Hill, New Jersey also offers an analyzer
designed to determine lead content in wall paint.
The latest Princeton Gamma Tech Instrument, Model XK-3, appears to
have some advantages over the Columbia Scientific device. It is lighter
in weight (5.5 Ibs.) and does not require calibration as often. The
Model XK-3 is direct reading and will provide accuracy at the +0.3
2 2
mg/cm level. Sensitivity is claimed at 0.5 mg/cm . The cost is approxi-
mately $4,500 less expensive than CSI's Model 750. Although NBS is
still in the process of evaluating this instrument, Princeton Gamma Tech
is already offering them for sale.
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On the basis of its preliminary evaluation, NBS ranks the Princeton
Gamma Tech instrument ahead of the Columbia Scientific analyzer. This
fact coupled with the lower price directs us to recommend the Princeton
Gamma Tech Model XK-3 for use in the upcoming study.
b. Dietary Lead; Diet is an important contributor of
trace metal to an individual. EPA personnel have indicated that the
proportion due to diet of the total lead absorbed by individuals may be
as high as .66. In addition, the 'amount of lead in various diets may
vary by several orders of magnitude. Accordingly, it may be quite
important to the success of the present study to obtain some measure of
the amount of trace metals in the diets of the sample individuals.
Procedures which have been suggested for obtaining diet trace metal
levels include:
(i) Feces samples,
(ii) Analyzing duplicate diets or meals from sample individuals,
(iii) Adding questions about diet to the Study Questionnaire,
and
(iv) Analyzing area grocery store food samples (Market Basket
procedure).
It may be appropriate to field test these procedures to determine
their accuracy and feasibility; however, RTI would like to offer the
following comments regarding these procedures:
i. Feces
At the time of household data collection, the FI would explain to
each participant the procedures for collecting the feces sample and
provide the necessary apparatus. RTI anticipates that the procedure and
apparatus employed would be similar to that utilized by Southwest Research
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Institute and described in a letter to EPA Project Officer Galke and
reproduced as Appendix A. Feces samples would not be collected from
pre-school age participants since the participant must be toilet-trained
and able to understand and adhere to the collection procedure.
RTI is concerned about the rationale, procedure, interviewer and
participant burden, and expense of collecting feces samples from smelter
community subjects in this study. At a meeting on December 10 with the
RTI Survey Director, RTI consultant Dr. Stephen Gehlbach was of the
opinion that the limited amount and questionable value of data regarding
dietary lead from such a feces sample would not justify the collection
problems and interviewer and participant burden; his opinion is based
partly upon the rapid turnover of feces lead with respect to the objectives
of the study and other study measurements. The oost for the sample
Qolleotion alone could be as mueh or move than $14,934, plus appropriate
overhead and fee, based upon the following assumptions:
1. A feces sample is required from each non-pre-school
subject in the Pretest and study populations (1,296
persons)-
2. A feces sample is collected from each of those 1,296
persons.
3. It is not necessary to go beyond 1,296 persons.
4. Fifteen (15) minutes of interviewer time are required per
subject to explain the procedure for collecting the feces
sample (at $3.50/hour).
5. A ten dollar ($10.00) incentive per subject for the feces
sample will be sufficient.
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6. One hundred (100) of the portable seats will be sufficient
at an estimated retail unit cost of $5.97 not including
the collection bags, at an additional estimated retail
price of 5 bags for $.94.
The analysis will be carried out on a Perkin-Elmer Model 403 atomic
absorption spectrophotometer with a HGA-200 Graphite Furnace and deuterium
background.
The total feces collection will be lyophilized overnight, ground
with a mortar and pestle and well mixed. A total weight will be obtained
and an aliquot (approx. 500 mg) weighed and placed in an Erlenmeyer
flask to which 5-20 ml of cone. HNO_ is added. A Vigreaux column will
be placed on each flask to prevent loss due to foaming and the total
heated for 1 hour. After cooling, the columns will be rinsed with de-
ionized water, the digests transferred to a volumetric flask and the
final solution analyzed directly for lead.
A control feces sample will be collected and analyzed for lead by
the method of standard additions. The lyophilized control material will
be stored frozen and used to prepare calibration solutions.
Suggested graphite furnace conditions [2]:
Time T, °C
Dry 20 sec 150
Char 20 sec 550
Atomize 15 sec 2200
The cost (exclusive of fee) of packaging, shipping and analyzing
feces samples from all pretest and study participants is approximately
$32,000. This amount is in addition to the sample collection cost cited
above.
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ii. Duplicate Diets
In this procedure, a duplicate of everything ingested by a participant
over a certain time period would be collected in a plastic bag and
provided RTI for analysis for dietary lead intake. Apparently, various
experts differ regarding the amount and time over which this duplicate
intake should be collected, ranging from one meal to nine meals over a
one month period.
Mr. Wayne Watson was contacted at Environmental Science Associates.
They have developed a technique for estimating dietary lead intake they
refer to it as the "fifth meal concept." For each family being evaluated
a fifth or extra place is set at the table. The food prepared for that
meal is portioned out and finally placed in a plastic bag. The meal(s)
is ground in a Teflon blender and analyzed by anodic stripping voltametry.
Eight or nine meals (including breakfast, lunch and dinner) are collected
from each family over one month. This approach is claimed to be superior
to the market basket technique developed by FDA since it takes into
account the preparation of the food (i.e., cooking utensils, tableware,
etc.) .
RTI feels that the participant burden would be unjustified, even in
the light of an incentive and reimbursement for food; the collection
problems could be enormous; and participants might change their eating
habits to simplify the collection process, thereby reducing the value of
the procedure.
iii. Dietary History
RTI has included several questions regarding eating habits and diet
in the SQ which will be completed for every participant by the FI during
household data collection, including the frequency with which the partici-
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pant eats certain foodstuffs known to be high or low in various heavy
metal content [3]. RTI has planned that these questions would be part
of the data collection process from the beginning; therefore, this
method of collecting information on dietary lead results in no additional
cost. A copy of the draft questionnaire is presented as Appendix B.
iv. Market Basket
In this approach, which is relatively inexpensive, the RTI Site
Administrator would purchase exemplary market baskets of food from
grocery stores at the smelter sites. The food would then be returned to
RTI for analysis for lead content.
Based upon the preceding paragraphs, RTI would recommend that an
estimation of dietary lead be based upon a combination of limited dietary
history and market basket approaches3 and that the collection of feces
samples and duplicate diets not be considered further for this research
effort.
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REFERENCES
1. Hall', W. G., and L. T. Slovic, U. S. Department of Commerce, National
Bureau of Standards. Survey Manual for Estimating the Incidence of
Lead Paint in Housing (NBS Technical Note 921). Washington, D. C.:
U. S. Government Printing Office, 1976.
2. Riner, J. C., F. C. Wright and C. A. McBeth, Atomic Absorption
Newsletter, 13_, 129 (1974).
3. Bureau of Foods, Compliance Program Evaluation, FY 1974 Heavy Metals
in Foods Survey (7320.130, Chemical Contaminants Project), June 19,
1975.
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B. Sampling Methodology
1. Overview
During the quarter ending December 31, 1976, RTI staff met on
several occasions with the project officer, project consultants, and RTI
staff to outline the initial planning for the study. Additionally,
joint RTI-EPA meetings were held with a representative of the Center for
Disease Control (CDC) to coordinate related studies being conducted by
RTI and CDC at common sites, specifically, Ajo, Arizona and Anaconda,
Montana. The sampling implications of these meetings are either reflected
or summarized in this section. Also, preparatory sampling work completed
to date are summarized. This work consisted largely of specifying the
sampling tasks for the work plan and obtaining detailed mapping and
climatic information on Corpus Christi, Texas (the pre-test site).
Also, availability of such materials was investigated, and a preliminary
profile was developed for all study sites.
2. Work Plan Summary
The sampling methodology described in the work plan is basically
the same as that alluded to in the RTI proposal, that is, the plan
involves a stratified area sample in which a sequential sample of persons
is to be selected for participation in the study survey. Also, a probability
sample of sites and days is to be selected for the purpose of obtaining
high-volume air samples. Selective sampling is to be used to collect
samples of tap water, house dust, and soil because random sampling for
these data was deemed impractical. Additionally, the work plan listed
the key persons in the sampling center that will be working on this
study and their responsibilities as they relate to this project. The
work plan outlines survey methodology that will result in the selection
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of a stratified probability sample of individuals that reside downwind
of selected nonferrous smelters. Approximately 240 persons, aged 35 and
under, will be selected at varying distances from the emission source in
each of six smelter communities (a selective sample of study sites was
identified by the Project Officer on the basis of prior investigation).
Additionally, 80 residents aged 60 and older will be selected in each of
three of these communities. Blood, urine, and scalp-hair samples will
be obtained and analyzed for these persons and will comprise the basis
for estimating community uptake coefficients of lead, zinc, arsenic,
copper, manganese, and cadmium. To estimate the exposure levels of the
downwind residents to these six elements, individual and residence data
and samples of soil, household dust, and tap water will be obtained at
each of the six communities selected for study. To estimate levels of
atmospheric exposure, high-volume air samples will be obtained at random
locations throughout the target area and at random points in time. The
number of dust and tap water samples will be equivalent to the number of
households that have individuals in the sample; that is, less than or
equal to 1,680, the total number of individuals to be selected. It has
been assumed for planning purposes that sample households will contain
an average of approximately 1.3 sample individuals. Additionally, we
anticipate that a minimum of 90 high-volume air samples will be taken at
each smelter site, a total of approximately 540 (90 x 6) air samples for
the study. One soil sample will be collected at each pre-schooler play
area, school playground, and 20-30 air sampling sites.
3. Pre-test
Prior to the studies in the six sample communities, a pretest,
or pilot survey, will be conducted at Corpus Christi, Texas. The methodology
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will be identical to that planned for the survey sites except that a
smaller sample of persons will be selected to participate. Approximately
two persons per age/sex cohort will be selected from each geographic
stratum resulting in a total of approximately 128 (2x8x8) individuals.
The survey design for air sampling will also be equivalent to that
planned for the main study sites except the period of time that is
"sampled will be reduced from 20 to 10 days—that is, approximately 45
high-volume air samples will be collected during the pretest.
Each study site (community) will be visited prior to the survey in
order to ascertain the appropriate delineation of target (high-risk)
population and to develop sampling materials. The actual sampling plan
will be developed individually to suit the particular circumstances of
the community, such as, availability of mapping materials, prevailing
atmospheric patterns, geographic topography, type and location of the
smelter and other major emission sources, and population densities.
Tentatively, we expect to obtain a balanced sample of five individuals
in each cohort from each cohort from each of approximately eight distance
strata (40 persons in each age/sex cohort being studied). These strata
will generally increase in size (land area) as the distance from the
stack emission increases, in order to optimize the sample design according
to the usual pattern of particulate fallout.
Although the actual number of high-volume air samples will ultimately
depend upon the site circumstances, the number of air samples per stratum
will range from approximately, 2 obtained on each of 3 days to 3 obtained
on each of 7 days; the number of observations will incease as the distance
from the stack increases. The number of electric hookups needed to
accommodate the air samplers at each of the study sites is expected to
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range from 8 to 18 depending upon the number of strata used for sampling
at the particular site.
4. Target Population
The target population consists of the relatively high-risk
human population that resides "downwind" of lead, zinc, and copper
smelters in selected U.S. smelter communities. Specifically, American
Smelting and Refining Company (zinc), Corpus Christi, Texas, will be
used as a pilot test and the six study smelters consist of :
(1) St. John Mineral Corporation (lead), Herculaneum, Missouri;
(2) Missouri Lead Operating Company, Bixby, Missouri;
(3) Anaconda Company (copper), Anaconda, Montana;
(4) Phelps Dodge Corporation (copper), Ajo, Arizona;
(5) National Zinc Company, Bartlesville, Oklahoma; and
(6) New Jersey Zinc Company, Palmerton, Pennsylvania.
The sites are characterized in table 1 according to population,
migration, and age characteristics. Other neighboring communities, some
of which are listed in this table, may also be included in the target
populations.
Delineation of the target population will be based largely on
prevailing wind patterns. Wind roses have been developed and are presented
in the work plan for all study sites. Also, wind data for the pretest
site were obtained from the National Climatic Center of the U.S. Department
of Commerce and the resulting wind rose is depicted in figure 1. These
diagrams depict the relative frequency of wind by velocity and direction.
At Corpus Christi, for example, winds from the south-east, south, and
east prevail 63 percent of the' time—largely at 7 to 16 miles per hour.
The target population for Corpus Christi, therefore, would ideally
-------
Table B-l Selected population characteristics of survey sites.*
_ Smelter
State
town
Arizona . Ajo
Missouri Bixby
Herculaneum
Montana Anaconda
Oklahoma Bartlesville
Pennsylvania Palmerton
Texas Corpus Christi
(pretest site)
Neighboring
towns
Rowood
Bass
Buick
Viburnum
Fes t us
Crystal City
Horine
Povely
Gregson
Warmsprings
Dewey
Tuxedo Park
„ ., . Net migration
Population i , iqrn '
. since ±yt>u,
number , c
percent 1-5
5,881 -16.6 12
-
<1,000
-
—
520
1,885
7,530
3,898
-
517
9,771 -18.9 10
-
—
29,683 6.4 10
3,958
*
5,620 -5.4 9
204,525 22.0 11
^ge groups, percent
6-17 20-35 60+
25 19 14
22 18 19
20 20 17
17 20 22
26 19 12
*Based on the 1970 Census of Population.
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:Figure B-l
22
CORPUS CHRISTI, TEXAS
0.00
10.8
17.8
0.05 0.10 j 0.15 :- < 0.20
Per-cent Occurence i i ' .
17.0
1-3 4-6 7-10 L
11-16 17-21 Over 21
Based on data obtained from National Climatic Center, U.S. Department
of Commerce. "
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23
comprise all persons (with exceptions noted below) residing in a fan-
shaped area to the northwest af the smelter.
The population in these communities is additionally restricted to
the relatively young (preschool, school age, and age 20 to 35), and to
the relatively old (age 60 and older) that have not had occupational
exposure at the community smelter. The exact delineation of this population
will differ by site depending on local circumstances such as those
alluded to in the previous section. Presurvey site visits are being
anticipated for the purpose of gaining the pertinent local information
needed to construct a sample frame.
Several aspects of the study present somewhat unique sampling
problems. For example, most smelter communities are relatively small
(population 1,000 to 5,000) and show net outmigration during the past
decade. In this stereotype community, relatively few of the older male
residents will not have had occupational exposure, and relatively few of
the 20 to 35 age group will remain in the community. The minimum size
for each stratum will be imposed by the expected number in the population
of the most scarce cohort, usually the preschool group. Again, the
stratification will differ by site. We anticipate, depending on the
community, that virtually all of the families residing near the stack
will need to be screened in order to obtain adequate information about
uptake of some of the cohort groups in that area. Residential exposure
of the population near the smelter stack is highly variable and, hence,
a larger sampling rate there than in more distant neighborhoods, the
efficiency of the sample and, additionally, will yield approximately
equal precision for each stratum estimate.
It is noteworthy that from 5 to 8 kilometers downwind of the smelter
is generally considered to be beyond the range of atmospheric transport
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24
and, therefore, will serve to some extent as a control group with minimal
exposure; More accurately, however, the mobility of individuals in the
area can be expected to result in some exposure for most individuals
living in the community, thus precluding selection of a true control
group from a smelter community.
5. The Sampling Frame
For the planned survey, one must assume that a complete list
of the target population at each study site will not be available and
will be costly to develop. Therefore, an area sampling frame will be
developed. Such a frame will result in a probability sample; that is,
all persons in a yet unspecified target population will have a known,
nonzero probability of being selected for the study. The method and
materials used to obtain a stratified area sample will vary by site. As
shown in table 1, the sites to be studies are generally characterized by
such small populations that Census of Population data are not sufficiently
detailed to use as a sampling frame. Corpus Christi, the one exception
to this characterization, is a tracted area for which the Census material
constitutes a suitable base for constructing an area frame. The following
tasks, completed and planned, are needed to construct a sampling frame
for Corpus Christi:
(1) The -pertinent Census materials have been obtained by RTI and
include 16 sheets of enumeration district/block maps and block
statistics (on magnetic tape);
(2) County highway maps showing roads and other boundaries useful
for constructing area segments outside the urban area and also
showing locations of dwelling units outside the urban area have
been ordered from the state highway department for Pima
county which contains all the area within approximately 25
kilometers of Corpus Christi;
(3) Pertinent stratification information from local sources, such
as, health departments and weather services will be sought at the
site;
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25
(4) Target area and strata boundaries will then be delineated;
(5) For each stratum, enumeration districts (EDs) will be selected
with probability proportional to their 1970 population, and a
sufficient number of sample segments (a sample segment will com-
prise a cluster of from 6 to 14 households).
The process of developing the sampling frame for less populated
areas encompasses the same tasks except that aerial photography and
street maps will be used to delineate the primary sampling units (PSUs).
To facilitate the selection of sample segments, the sample PSUs will be
cruised and subsegmented and households will be listed according to
methodology developed at RTI. The date and scale of available aerial
photography for all study sites was obtained from the National Cartographic
Information Center. For Ajo and Rowood, Arizona, for example, 1961
photography at 1:23,000 scale is available. Prints with a scale of
approximately 1:7,670 were ordered for the Ajo area. The culture at
this scale should be sufficiently detailed for constructing a sampling
frame of dwellings.
6. Sample Selection
Recall that the downwind population in each "distance stratum"
will be partitioned into small segments such as city blocks. To obtain
randomized samples from an adequate representation over a wide range of
distances from smelters for 6 to 8 cohort groups, instructions to data
collection field staff will necessarily contain the following informaton:
A list of segments to be surveyed and the order of visiting
these segments;
- Maps showing segment locations and specific boundaries;
- A form on which a tally will be maintained for each cohort
group for each stratum;
A form for recording a count of all eligible persons in those
segments visited, which of them were asked to participate, and
which did participate.
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26
The field enumerator will continue to visit segments and households
in the predesigned order in each stratum until either the cohort samples
(5 in each cohort group) are filled or until all households in the
stratum have been either contacted or verified as not containing any of
the eligible individuals still needed. Except for eligible individuals
that do not cooperate, this technique will result in a probability
sample of the target populations that will facilitate valid inferences
and analyses of the data. The use of cash incentives is expected to
hold the nonresponse and hence the departure from a probability sample
to a minimum level.
The placement of the air-sample locations will coincide with the
first segments selected in each stratum for the sample of individuals.
Also, for each air-sample location, a list of days during which the 24-
hour samples are to be obtained will be provided to the field enumerators.
This list of days comprises a probability sample of time periods throughout
the survey period. From 4 to 6 air-samplers will be operating virtually
throughout the survey period, and the requisite number of electric hook-
ups is expected to range from 8 to 18 for each smelter site depending on
the number of strata. Constraints on the allocation require that no
more than 2 strata are designated for monitoring on a particular day,
and that no stratum will be assigned more than 3 monitors on any single
day. The procedure is as follows:
(1) Randomly select 3 days from the first 19 days of the survey
period without replacement and assign these to stratum 1—two
locations proximate to the first two segments (household
sampling units) will be monitored on each of these 3 days;
(2) Repeat the procedure for the remaining strata except that
days already assigned twice are ineligible, and the number of
days to be assigned to each stratum increases for strata that
are more distant from the smelter.
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27
Composite samples of surface soil are to be collected in play areas
of all study children. Approximately 80 (or less to the extent that
some families may have more than one child in the study) of these soil
samples will be obtained from residential play areas for each smelter
site, and one composite sample will be taken from each school yard where
study children attend.
Variation in the soil content of study elements throughout the play
areas, both for different locations and timesj is expected to be small
relative to variation in the air samples. For this reason, and because
random sampling appears impractical, a selective composite sample will
be relied upon to measure element exposure from soil in the play area.
The enumerators will first establish the boundaries of the most commonly
used play area and will then select from 3 to 5 surface soil samples
from scattered points in the play area. These samples, which will be
obtained concurrently with the interview, will comprise the composite
sample for that play area.
A sample of tap water will be obtained during the interview at the
residence of each study participant. The tap water sample will be
obtained from the kitchen tap or other source commonly used for drinking
and cooking (a single pass after the water has been allowed to run for a
few seconds). Random sampling at different locations and times was not
proposed for this measure of exposure, because it should be relatively
homogeneous within a household, and because what little improvement in
data that might result from a suitable randomization of this measure
does not appear to justify the accompanying increase in respondent and
interviewer burden.
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28
7- Sample Size and Quality Control
To the extent possible, the sample data will be stored in the
lab and analyzed in random groups rather than in batch groups as they
are sent in from the field in order that analysis error can be identified
as error rather than as factor effect. Also, the forms used for tallying
eligibles in the sample segments will identify 10 percent of the eligibles
as quality-control individuals. Two samples of blood and hair will be
obtained for each of these individuals and two samples of tap water and
dust will be taken at their dwelling. Also, two soil samples will be
taken for 10 percent of the sample preschool children that are designated
for quality control. The purpose of these quality control observations
is to measure the possible influence of sample acquisition, packaging,
shipping, and lab analysis. Additionally, 10 percent of the sample
individuals will be reinterviewed at a later date to verify the information
obtained on the survey questionnaire; the identity of these persons will
be unknown to the initial interviewer.
The desired sample allocation of the 1,680 sample persons is described
in table 2, although, as noted earlier, the actual stratum sizes may
differ among smelter sites. Based on what prior studies have shown,
this sample size should result in a reasonable capability (Type I and
Type II error both at 0.05) for detecting a lead difference, for example,
of 5yg/100 ml blood; 40 is generally accepted to constitute the point
above which health problems are likely to result).
The high-volume air samples are needed to estimate exposure levels
at varying distances from the emission source, at varying distances from
the transit line of the downwind pattern (corresponds to primary wind
direction), and at varying wind velocity and direction. Several 24-hour
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29
'Table B-2 -Tentative sample allocation for individuals*
at the study sites .
Number of
Geographic
Site
Lead (1)
Lead (2)
Zinc (1)
Zinc (2)
Copper (1)
Copper (2)
Preschool
Male Female
5
5
5
5
5
5
5
5
5
5
5
5
Individuals by Cohort Group in Each Stratum
School Age
Male Female
5
5
5
5
5
5
5
5
5
5
5
5
20-35 Years
Male Female
5
5
5
5
5
5
5
5
5
• 5
5
5
60 Yrs
Male
5
0
5
0
5
0
& Older
Female
5
0
5
0
5
0
*Assuming, tentatively, eight strata as depicted in figure 1.1: 0.0 - 0.29 km,
0.3 - 0.69 km, 0.7 - 1.09 km, 1.1 - 1.59 km, 1.6 - 2.19 km, 2.2 - 2.99 km,
3.0 - 4.99 km, and 5.0 - 7.99 km.
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30
readings are needed in each stratum in order to measure the variation
over time as well as the need to measure the influence on exposure of
different wind velocities and directions. The approximate sample size
and allocation, which is presented in table 3, will be adapted to suit
the individual site circumstances. The per-site sample size totals 87
location-days. This size sample is expected to produce a coefficient
variation for element content of atmosphere of 0.20 or less at the
stratum level.
8. Coordination of Related Studies
Recall that meetings were held with CDC to investigate the
feasibility of coordinating CDC and RTI efforts in Ajo, Arizona and
Anaconda, Montana. It was concluded at these meetings that many of the
same families would be contacted for both studies and that many of the
same children would be asked to participate in both studies. Also, the
participant information requested and even selected types of biological
samples will be common to both studies. It was concluded, therefore,
that the purpose and scope of each study must be carefully explained"to
all individuals that might be participants in both studies. It was also
agreed that the sample selection and data collection would be coordinated
to reduce the combined cost of conducting the surveys and to facilitate
combined analyses of data from the two studies. It is noteworthy that
some information and tests will still be duplicated but that such duplication
can be useful as a quality check of data collection and analysis. The
protocol for this coordination effort is presently being developed. The
CDC survey in Ajo is expected to be conducted first, using questionnaires
and methodology that will be compatible to the RTI survey. In Anaconda,
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31
Table B-3 -Tentative sample allocation for air samples*.
Type of Observation
Locations (A)
Days (B)
24-hour samples (A x B)
Ratio, days/locations
Sl
2
3
6
1.5
Number
S2
2
3
6
1.5
of Observations,
S3
2
4
8
2.0
S4
2
4
8
2.0
S5
2
5
10
2.5
S . , in Each
S6
2
5
10
2.5
S7
3
6
18
2.0
Stratum
S8
3
7
21
2.3
Total
18
-
87
-
*Based on data presented in appendix 1.2 of.the work plan.
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32
it is expected that the CDC and RTI studies will be based on a single,
dual-purpose survey, which will obtain the information and samples
requisite to both studies.
-------
33
C. Chemical Analysis
1. Water
The drinking water and lab tap water at Dreyfus Labs., RTI, was
analyzed for the metals of interest, except arsenic. Samples were spiked
with cone. HNCL to give a final acid content of 0.5% in the sample. In
every case, the quality of the tap water in the laboratory was better
than that from a refrigerated water fountain. The analytical results
are shown in Table C-l.
2. Urine
A urine sample was analyzed for the metals of interest, except
arsenic. Samples were diluted 1:1 with dilute HNO, (except for Zn in
which case a 50:1 dilution was necessary) and analyzed directly. Con-
centration values were obtained by the method of standard additions
(except for Cd). These data are included in Tables C-2.
3. Hair
Sample preparation and analytical conditions have been established
for the analysis of all'the elements of interest, except arsenic.
Development of these procedures were carried out on male and female
hair samples collected at a local barbershop and beauty salon. A summary
of these hair washing and metal analysis results is given in Table C-3.
The optimum washing, digestion and instrumental conditions are detailed
below.
Wash Procedure
Hair samples should be cut into 3-5 mm lengths by use of a paper
cutter or stainless steel scissors. The hair is then rinsed in 1:1
ether/methanol solution, using about 25 ml solution for a 500 mg hair
sample. The organic solvents are then drawn off through a Buchner funnel.
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34
Table C-l
Analysis of a Lab Tap Water and a Drinking Water Sample
Concentration
Element Tap water Drinking water
Cd ND .92 yg/1
Cu ND 203 yg/1
Mn 3.44 yg/1 5.2-yg/1
Pb ND 1.6 yg/1
Zn 626 yg/1 1.4 mg/1
ND - Not detected
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35
~,
Table C-2
Analysis of a Urine Sample
= 2087 ml (from creatinine analysis)
Est. weight
excreted over
Element Dilution Concentration 24 hrs
Zn
Pb
Mn
Cu
Cd
1:50
1:1
1:1
1:1
1:1
4.3 yg/ml
24.0 ng/ml
40.8 ng/ml
21.6 ng/ml
4.6 ng/ml
9.0 mg
50.0 yg
85.1 yg
45.1 yg
9.6 yg
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36
Table C-3
Effect of Washing Procedure on Metal Content of Hair
Sample
female
female
female
male
male
male
Wash Wash
Soln. No.
deionized
water 1
2
3
10% Snoop
1
2
3
10% Prell
1
2
3
deionized -
water 1
2
3
10% Snoop
1
2
3
10% Prell
1
2
3
ppm Zri
167
164
164
157
167
159
163
160
167
150
132
128
151
148
137
132
151
140
141
142
151
138
141
138
ppm Cu
32.5
26.4
26.7
29.6
32.5
29.0
26.2
28.1
32.5
24.9
23.4
27.5
26.0
28.1
29.5
28.1
26.0
28.9
28.1
31.5
26.0
28.0
24.5
29.3
ppm Cd
12.1
1.25
1.13
1.08
12.1
1.85
1.49
0.98
12.1
1.27
2.08
1.92
1.83
1.57
1.34
1.08
1.83
1.81
1.51
1.60
1.83
1.44
1.29
1.37
ppm Pb
12.9
10.6
11.3
11.2
12.9
10.9
10.2
10.8
12.9
8.9
8.5
8.9
148*
134*
125*
124*
148*
125*
75*
117*
148*
114*
84*
113*
ppm Mn
1.38
1.36
1.02
1.17
1.38
1.65
1.07
1.09
1.38
0.96
0.57
0.43
1.49
1.02
0.99
1.10
1.49
1.28
1.08
1.08
1.49
0.88
0.67
1.30
Pb values are about 10X the normal range of Pb in hair, which is 5-25 ppm.
-------
37
The sample is washed by sonicating 30 min in 10% Prell solution. After
washing, the sample is rinsed six times in about 100 ml deionized water,
followed by about 25 ml acetone. The wash procedure is performed a
total of 2x. The sample is then dried for 1 hr at 110°C.
Digestion Procedure
All glassware used for digesting and diluting samples should be
cleaned by standing overnight in 1.0% HNO, followed by rinsing with
deionized water.
Approximately 250 mg washed hair are accurately weighed into 50 ml
beakers. The sample is then heated at 103°-104°C for 3 hrs in 10 ml
50% HNO-. At the end of the heating period, the volume is reduced to
0.5 ml by gently boiling off excess solvent. The residue is transferred
to a 5 ml volumetric flask and diluted to the mark with deionized water.
The Zn analysis can then be performed at this concentration if the less
sensitive Zn wavelength is used. The Cu, Cd, Mn and Pb analyses are
performed by diluting 1 ml of the 5 ml sample to 10 ml with 0.5% HNO~.
4. Creatinine in Urine
A standard creatinine curve was generated using the 490 nm absorption
maximum of the Jaffe Reagent complex. Linearity was noted for creatinine
concentrations from 0 to 2.5 mg % (see Figure C-l). Although literature
accounts of the analysis stress the necessity of carrying out the analysis
15-20 mins after the addition of the Reagent, we found no change in the
absorption characteristics of the analytical solution two hours later.
A urine sample (diluted 100 fold) was analyzed and showed a creatinine
content of 80 mg % or 0.8 mg/ml.
Calculation of estimated 24 hr urinary output (V0/ ):
-------
38
WC
v _ c
V24e ~ C
u
W = 72.6 kg (weight of individual)
C = 23 mg/kg (creatinine coeff. for male)
C =0.8 mg/ml (creatinine cone.)
V07 - 2087 ml
24e
This creatinine value has been used to estimate weight of metals
excreted over 24 hrs (see Table C-2).
5. Curve Fitting of Calibration Data
Although it is conventional to describe calibration data in linear
terms and to limit the analytically usable range within these bounds,
there appears to be no theoretical basis for this restriction. A study
was initiated to test the premise that typical calibration data might be
better fit by either an exponential (y = a exp (bx) - k) or a^ quadratic
2
expression (y = ax + bx + c).
In Figs. C-2 to 7 are shown plots of the least squares nonlinear
regression curves generated by a small computer plotting program. Note
that recorder response (in millivolts) is given on the x-axis and y is
equated to weight of metal (in nanograms). Examples of all six elements
are shown on these graphs. In Fig. C-2, the clearly nonlinear Cd data
points are fitted equally well by the exponential and quadratic curves.
Copper calibration data (Fig. C-3) are nearly linear and are adequately
represented by both nonlinear equations. Figure C-4 shows a set of poor
Pb data obtained with an unstable EDL light source; both expressions
yield similar curves. Zn calibration data tends to be nonlinear. This
phenomenon is shown in Figs. C-5 and 6. A basic difference between the
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39
two treatments is shown dramatically in Fig. C-5. The parabola described
by the quadratic expression possesses a negative minima and a blank
signal twice that of the experimental value. On the other hand, the
exponential treatment yielded an equation which was much more successful
in accommodating all of the calibration data - particularly near the
blank value. Another Zn plot is shown in Fig. C-6. These data are
handled equally well by both treatments. The As (Fig. C-7) and the Mn
(Fig. C-8) plots show essentially linear characteristics and super-
imposable fits by both expressions.
2
Closeness of Fit, r
y = a+bx (linear)
.983
.994 '
.920
Fig.
C-l
C-3
C-4
C-5
C-6
C-7
C-8
Element
Cd
Cu
Pb
Zn
Zn
As
Mn
y = a exp (bx)-k
.999
.995
.915
.990
.974
.998
.999
.996
.994
The following conclusions can be drawn from this study:
a) In no case was the linear regression line superior to either
nonlinear curve.
b) One advantage of the nonlinear approach is their ability to
fit calibration data near the blank. In the case of Zn, the exponential
equation is clearly superior to the quadratic expression.
c) There is an obvious advantage to using nonlinear expressions
for data outside the "linear range." An upper weight limit appropriate
for each metal is being investigated.
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40
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48
6. Analytical Data Sheets
A data sheet format has been developed for use in this project.
These forms will be filled out by the chemical analyst and will include
information ranging from sample code number and peak height to the final
result. These forms and the instructions for their use is included in
Appendix C.
D. Quality Control
1. Calibration of Hi-Volume Samplers
The quality assurance group at EPA, RTF, has calibrated our top
loading orifice calibrator, Sierra Instruments, against a standard
(RWOTS) Meter (positive displacement meter) (see Fig. D-l). A Hi-Vol
sampler has been calibrated using one, two and three filters to simulate
resistance to air flow. The results of this trial are shiwn in Figure
•
D-2.
2. Precision Measurements - Urine and Hair
As part of the development of the urine and hair procedures, standard
deviation and % RSD (i.e., coefficient of variation) values were calculated
for these matrices spiked with known amounts of the metals of interest.
These data are shown in Tables D-l to D-5.
3. Working Reference Materials-Air Particulates
The quality assurance group at EPA, RTF has available glass fiber
filter strips (3/4" wide) containing known amounts of arsenic and lead.
These reference materials are available in 9 different concentration
levels. They are submitted and analyzed blind. Results are then for-
warded to EPA. On request, similar materials will be made available for
the four other metals. The preparation of these "standards" is being
considered by EPA.
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49
We have requested the presently available arsenic and lead standards
to validate our analytical methodology. The evaluation will be done
directly with the Project Officer. These materials will also form the
basis of our air particulate QC program.
4. Working Reference Materials-Tap Water
The quality assurance branch of EPA, Cincinnati has quality control
water samples available to laboratories involved in monitoring water
quality. Samples "certified" for trace metal content are available free
of charge. They are prepared as concentrates and are supplied in three
different concentration ranges. Wehave received a set of these QC
samples for method validation purposes. These materials will become a
part of our routine QC program.
E. Sample Packaging and Shipment
The following summary describes our proposed packaging and shipping
protocol.
All samples will be chilled to 0°-5° (not frozen) after collection
and will be shipped in this condition via Federal Express. It is also
proposed that samples on arrival at RTI be stored under refrigeration.
High density polyethylene containers (120 ml) will be used for tap
water, urine and soil samples. Polyseal caps will be used to provide
a leak-proof seal. Shipment by Federal Express eliminates the possi-
bility of sample contamination and leakage due to pressure gradients in
transit.
Ziploc plastic containers will be used for air and hair samples.
Dust samples will be enclosed in glassene envelopes. Provisions will
be made to insure a tight seal to prevent sample loss and contamination.
The plastic bags will be shipped in a styrofoam-lined box.
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50
Plastic containers will be shipped in styrofoam blocks in which
depressions are cut to exactly hold each container. Our experience with
such shippers has resulted in no container damage and a minimum of sample
temperature change during transit.
Blood samples will be shipped to RTI in specially designed 8-tube
vacutainer shippers. Blood samples will be chilled (not frozen).
-------
»= O. 00 AH
13=0.77^
0.0HJIB0
Figure D-l Calibration of Sierra Instrument Orifice, Model
330
-------
HT-VdL. C
52
.__£.
iiidiir,
j- ;
/.68
EEE=.
o
I-t
m
E«
£=
u£
2S
•h^1
S
uj£
X ui
H|2
^
OU
x|
ii
^
Pie
=4rz
H
^^H
T^>T/9A7^.7Zr'/<
3/ f
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-------
53
Element
— EDL (8.4)/D
5mV 218 nm
Gas Int. Auto
Slit 4
— HC(8mA)/D
2mV 229 nm
Gas Int. Man.
lOmV
HC/D,
lOmV
Gas Int. Man.
— HC(8mA)/D2
2mV 326 nm
Gas Int. Auto
5mV
Table
Urine Spiked
Blank
0.5 ng/25yl
1.0
2.5
Blank
0.1
0.2
0.5
Blank
0.1
0.2
0.5
1.0
2.0
3.0
Blank
1.0
2.0
3.0
5.0-
7.5
Blank
0.5
1.0
Blank
0.5
1.0
2.5
5.0
D-l
Standards
Mean
(mV)
0.39
0.773
1.335
3.115
0.438
0.036
0.518
1.323
0.38
0.075
0.425
1.130
3.23
5.667
5.943
0.41
0.715
1.630
2.54
3.56
4.59
0.24
0.185
0.912
0.28
0.265
0.813
2.127
4.197
Std. Dev.
0.040
0.032
0.068
0.173
0.045
0.018
0.014
0.027
0.007
0.007
0.014
0.094
0.188
0.147
0.014
0.126
0.085
0.071
0.191
0.605
0.058
0.014
0.044
0.035
0.035
0.031
0.045
0.371
R.S.D.
10.26
4.15
5.06
5.55
10.36
48.8
2.66
2.02
9.33
1,
1,
2,
3,
65
24
91
32
2.47
3.44
17.62
5,
2.
5.
21
80
37
13.20
24.16
7.57
4.85
12.36
13.21
3.81
2.12
8.86
-------
54
Table D-2
Hair Samples Spiked With Copper
Sample No
female 4
female 8
Cone, of
aqueous std.
(ng/25 ul)
blank (0.5% HN03>
2
4
6
8
blank (0.5% HN03)
2
4
6
8
SD
0.0057
0.0424
0.0282
0.0424
0.0353
0.0212
0.0353
0.0707
0.0212
0.0707
X
2.60
3.37
4.02
4.75
5.43
2.59
3.40
4.05
4.59
5.25
% RSD
0.22
1.3
0.70
0.89
0.65
0.82
1.0
1.7
0.46
1.3
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55
Table D-3
Hair Samples Spiked With Manganese
Sample No.
female 2
(no corrector)
female 2
(corrector)
Cone, of
aqueous std.
(ng/25 nl)
blank (0.5% HN03)
0.1
0.2
0.3
0.4
0.5
blank (0.5% HN03)
O.l"
0.2
0.3
0.4
SD
0.0100
0.0208
0.0305
0.0288
0.0665
0.0057
0.0115
0.0458
0.0503
0.0200
0.0472
X
0.45
1.36
0.97
1.14
1.41
1.56
0.56
0.86
1.18
1.27
1.66
% RSD
2.2
1.5
3.1
2.5
4.7
0.37
2.1
5.3
4.3
1.6
2.8
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56
Table D-4
Hair Samples Spiked With Lead
Sample No.
female 4
female 8
male 2
Cone, of
aqueous std.
(ng/125 pi)
blank (0.5% HN03)
2
4
6
8
10
blank (0.5% HNO.)
2
4
6
8
10
blank (0.5% HN03)
2
6
8
10
SD
0.0
0.0424
0.0282
0.0
0.0707
0.0212
0.0288
0.0707
0.0565
0.0
0.0212
0.0070
0.0353
0.0
0.0353
0.1414
0.0
X
1.65
2.45
3.19
3.80
4.35
4.70
1.57
2.36
3.02
3.70
4.20.
4.77
1.38
2.20
3.54
4.20
4.55
% RSD
-
1.7
0.88
-
1.6
0.45
1.8
3.0
1.9
-
0.50
0.15
2.6
-
1.0
3.4
_
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57
Table D-5
Hair Samples Spiked With Zinc
Sample
No.
7
12
Cone, of
aqueous std.
(ng/25 yl)
blank (0.5% HN03)
50
100
150
250
blank (0.5% HNO,)
50
100
150
200
250
SD
0.0389
0.0035
0.0450
0.0353
0.353
0.0202
0.0141
0.0106
0.0141
0.0212
0.0212
X
0 . 706
0.923
1.043
1.225
1.500
0.828
1.045
1.173
i:330
1.465
1.735
%
RSD
5.5
0.4
4.3
2.9
23.5
2.4
1.3
0.9
1.1
1.4
1.2
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58
F. Statistical Methods of Analysis
1. Confidentiality of Data Files
In carrying out its statistical analyses, RTI will utilize machine-
readable data files maintained at the Triangle Universities Computation
Center (TUCC) located in the Research Triangle Park. To maintain the
confidentiality of these data files, RTI will use an encrypting of data
procedure.
The encrypting procedure involves the use of a routine which scrambles
data passed to the routine so that they are meaningless to anyone unless
they are decrypted. The routine draws random numbers and adds a different
number to each character of the data. The starter for the random number
generator, referred to as the key, is passed to the routine in the
calling sequence. Thus with the same starter to the -random number
•
generator, the data can be decrypted when required for processing. An
encrypting procedure has the advantage of not splitting the primary data
base and not having to depend on computer center personnel (non^RTI
personnel) to maintain the confidentiality of a link file.
In addition to the encrypting procedure, TUCC has developed an
extensive security system which RTI programmers use to protect computer
account codes and data from other users. This is accomplished through a
password protection system for account codes, data sets, and data storage
volumes. These facilities are different from and replace the similar
features provided by IBM. This system is described in TUCC publication
GI-066-0, TUCC Security Features [Ref. 4.1]. Copies of this publication
are available on request.
-------
59
2. Data Analysis
RTI will use the TUCC IBM 370/165 computer facility for its data
analysis. The data will be stored on 9-track tapes written at 1000 bpi
with an OS standard label.
In its analysis, RTI will examine the following relationships:
(a) the relationship between environmental levels of the trace
metals of interest (i.e., levels of metals in air, water, soil
and dust samples), the distance from the smelter, wind speed,
and wind direction; and
(b) the relationship between tissue levels of the trace metals
(i.e., levels in hair, blood and urine), environmental levels,
and sociodemographic variables (e.g., age, sex).
As is now envisioned, the principal statistical techniques that will
be used to examine these relationships are the analysis of variance,
multiple regression and stepwise regression. In addition, it may also
be worthwhile to examine some multivariate techniques (i.e., techniques
which consider the above relationships for more than one trace metal at
a time).
a) Analysis of Environmental Levels
In particular, for the relationships in (a) above, the following type of
model will be analyzed for each trace metal being studied:
Y.jk(M) = u + D. + S. + Wk + e..k (1)
where
Y.-t(M) = concentration of metal M in either air, water, soil, or dust
samples for the i distance, j wind speed,
J.-T
and k wind direction,
u = mean metal M level,
-------
60
D. = i distance effect
i
S. = j wind speed effect,
W, = k wind direction effect, and
e. ., = random error.
1JK
In the above model, the independent variables (distance from smelter,
wind speed, wind direction) have been categorized and indexed by i, j,
and k, respectively. This'allows for a general type of relationship
between the levels of the metals and the independent variables rather
than imposing a functional relationship as does regression. With this
model, one may use the technique of analysis of variance to test for the
effects of different distances from the smelter, differences in wind
speed, and also differences in wind direction. These correspond to
tests of equality of the D., the S., and the W, , respectively.
1 J *
As required by the subject Request for Proposal (RFP), the analyses of
the environmental levels, whether they be air, water, dust, or soil,
will be done separately for each site. If differences between sites ase
also of interest, this may be investigated by including a site variable,
L, , in model (1) to produce
Yhijk(M) ' U + Lh + Di + Sj + Wk + ehijk . (2)
Site differences may then be tested by testing the equality of the L,
and the differences may be exhibited by displaying the adjusted site
means from model (2).
b) Analysis of Tissue Levels
For the relationships in (b) above, the analysis will again be done by
site and in this case will also be done by broad age categories, since
soil samples are taken only for school and preschool children. In
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61
particular, the following type of model will be analyzed for each trace
metal:
Y (M) - u + A + S + B X + B X
-LJK 1 J J. J.K £ £K
where
Y.-k(M) = concentration of metal M in either blood, hair or
urine samples for the k individual in the i age
, .th
group and 3 sex group;
A
u = mean metal M level;
.. = age effect for the i age group;
S. = sex effect for the j sex group;
B,,...,B_ = regression coefficients to be estimated;
X,,,...,X_, = corresponding concentration of metal M in the air,
water, soil, and dust samples, respectively,
for the k individual; and
e. ., = random error.
ijk
The above model will permit the examination of the effect of age and sex
as well as environmental levels on metal M tissue levels. A similar
model may also be used to examine the effects of distance and wind
direction on metal M tissue levels. In model (3), testing for age and
sex effects corresponds to testing the equality of the A. and S. while
testing for the relationship between tissue levels and environmental
levels corresponds to testing the nullness of B-.,...,B,.. When the
parameters in model (3) have been estimated, the resulting fitted equation
may serve as a predictive model for the reference population.
In order to help determine the form of model (3) for the various*
metals, it may be worthwhile to employ the technique of stepwise regression.
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62
This technique can be used to give insight into the relative strengths
of the various demographic, environmental and meteorological variables
in predicting tissue levels in humans. In essence, this technique selects
those variables (in a stepwise manner) which best predict the dependent
variable of interest (i.e., tissue levels).
In addition to using the various statistical models given above,
other techniques which will be employed to examine the relationships of
interest include: computing correlations between pairs of variables;
examining scatter plots of tissue levels versus the demographic, environ-
mental, and meteorological variables; and computing means of the demo-
graphic, environmental, and meteorological variables for various cate-
gories of tissue levels and then plotting these means.
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63
REFERENCES
4.1. Triangle Universities Computation Center (TUCC), Memorandum:
TUCC Security Features (General Information Series Document
No. GI-066-1). Research Triangle Park, North Carolina: TUCC,
February 1976.
4.2. Sarhan and Greenberg, Contributions to Order Statistics. New
York: John Wiley & Sons, Inc., 1962.
4.3. Cochran, W. G. and G. M. Cox, Experimental Designs. New York:
John Wiley & Sons, Inc., 1962.
4.4. Service, J., A User's Guide to the Statistical Analysis System
(SAS). Raleigh: North Carolina State University, 1972.
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64
III. POTENTIAL PROBLEM AREAS
A. Field Operations
1. Anaconda
In the course of various conversations with EPA Project Officer Galke and
Dr. Carl Hayes of EPA, and at the aforementioned meeting at EPA on December 20,
RTI learned that there may be some problems with the RTI/CDC joint effort at
Anaconda in that the State of Montana may proceed with their study very early
in 1977, in which case RTI may have some involvement with public relations
at the site, similar to that in Ajo. EPA is investigating the possibility
of delaying the State study to coincide with an RTI/CDC effort. There is a
possibility of a meeting in early January to discuss this matter involving
representatives of EPA/RTP, RTI, CDC, and the State of Montana.
2. Project Schedule
The RTI field operations schedule as presented in the detailed Work Plan
calls for RTI to develop the training manual during February; conduct a
training session for central project staff at RTI the first week of February;
conduct a training session at the Pretest site March 5-6; and begin data
collection at the Pretest site on March 7. This schedule assumes appropriate
approvals of the protocol and data collection instruments by EPA and the
Office of Management and Budget (OMB) in time to implement this schedule. At
the meeting at EPA on December 20, EPA Project Officer Galke and Dr. Hayes of
EPA indicated that the detailed Work Plan would be distributed for review
shortly after it was delivered; that they hope to have comments back from
appropriate persons by the end of January; that the EPA review committee would
meet at the end of February; and that in the meantime it was hoped that pre-
liminary Pretest approval could be obtained from OMB.
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65
B. Chemical Analysis
1. FEP Analysis
Our development work on the FEP assay has not produced a satisfactory
analytical method. Both the Granick-Sassa and the Piomelli procedures
have given unsatisfactory FEP response. This problem was discussed with
Mr. Tom Porro, Analytical Applications Department at Perkin-Elmer
Corp., Norwalk, Conn. He strongly emphasized the necessity of using a
red sensitive photomultiplier tube. Work done to date has been carried
out with a standard R-106 tube. On Mr. Porro's recommendation the re-
cently developed R-777 photomultiplier tube has been ordered and will
replace the currently used PMT.
In view of this difficulty, the December CDC quality control samples
for blood protoporphyrin were not analyzed.
2. Blood Clotting
This phenomenon will not only make FEP analysis impossible but will
require the use of more time consuming trace metal workup conditions.
Clotting is clearly undesirable and must be prevented. Implementation
of adequate anticoagulant treatment is absolutely essential.
3. Conversion of Organometallics Into An Assayable Form
Certain organometallics may escape detection by AA analysis. This
potential analytical problem is of particular concern with arsenic. A
thorough recovery study of organo-arsenites (arsenates) will be conducted
and if required, appropriate sample preparation methods developed for
total metal assay.
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66
It is also possible that other forms of the metals of interest will
resist degradation to assayable forms. More severe workup conditions
will be investigated on real samples to determine the magnitude of this
phenomenon.
4. Air Particulate Collection - Power Drops
An unknown factor in the placement of power drops for the Hi-vol
air samplers is the time lag between the request for such drops and
their installation. Undue delay will result in air sampling operations
continuing after all other smelter site activities are concluded. To
avoid this potential difficulty, air sampling strata will be identified
and requests for drops will be made at the earliest possible time.
-------
67
C. Statistical Methods of Analysis
1. Missing Observations
Because of the nature of the data being collected for the present
study, there undoubtedly will be a large number of missing observations.
These missing observations may consist of all or only selected observations
from a sample individual (e.g., the individual refuses to give any data
at all or he gives all the data desired except a urine sample). In
order to carry out the analyses described in section 4.2, it will be
necessary to determine how these missing observations are to be handled,
keeping in mind that the easiest solution of only analyzing individuals
with complete observations is probably unsatisfactory because too many
individuals with partial observations would have to be discarded.
The specific techniques to be used for handling missing observations
will be determined during the analysis, and will depend upon several
considerations. Some of the pertinent considerations include the
following:
The reason for the missing observation,
The type of measurement (e.g., tissue level) for which the
observation is missing,
The type of analysis or estimate for which the missing obser-
vation is needed,
The number of missing observations for that measurement,
The minimum measurable level if the observation is missing
because it is less than that level, and
The information available from that and other individuals that
may facilitate the estimation of the missing observation.
-------
68
The methodology decided upon will be made available for Project Officer
review and will be fully documented in the final report. The following
methodologies will be among those considered.
If relatively few observations are approximately "randomly" missing
for a particular measurement, cohort means will probably be substituted
for the value and the degrees of freedom will be appropriately modified.
If relatively few observations are missing because they are below a
Xi
measurable minimum, the range midpoint of this observation, —=-, may be
substituted for the missing value, particularly if the range is small
(i.e., if [0,x!] is small where x! is the smallest measurable value for
X.)- However, if the number or range of unmeasurable observations is
large, a more refined technique may be used. Under this condition,
methodology for the estimation of distributional location and scale
parameters under the situation of singly censored samples, would be
appropriate for the initial analysis. In Sarhan and Greenberg [Ref. 4.2],
order statistics are used to obtain unbiased best linear estimates of
location and scale parameters from samples of size 20 or smaller and
unbiased "nearly best" linear estimates from larger samples in which
single censoring occurs. Once the distributional parameters are estimated,
it will then be possible to substitute values for the unmeasurable
observations based upon the estimated distribution.
In running the regression analyses described in section 4.2, one
may encounter either missing dependent (Y) or missing independent (X)
variables. To handle this problem, one might use a model in which an
indicator variable reflects the missing independent variables and "two-
stage" estimation models [Ref. 4.3] are used to predict missing dependent
variables. The two-stage method is used in SAS [Ref. 4.4], one of the
-------
69
software systems utilized by RTI. The method uses a least squares
solution to obtain parameter estimates from the available observations,
and then uses estimates of missing values from this preliminary model in
place of the missing values—the analysis can then be conducted as if
the data were complete except for changes in degrees of freedom. However,
if information is known about the range of the dependent variable, i.e.,
that 0 <_ y. . <_ y! where y! is the minimum detectable level for Y., then
the two-stage estimation alone would ignore this useful bit of informa-
tion. Therefore, the two-stage estimation (estimating missing data on
the basis of complete observation vectors) would be used to set values
when they fall below the minimum measurable level, but only if these
estimated values were within the known range [0,y!]. Thus, the following
inputed value would be used for a missing y^.:
r. ., if 0 2 y < v1
1J i j i
7* =
0, if y± < 0
y! otherwise
where
y*. is the imputed value for the missing y. . value,
s\
y^ is the first-stage estimate of the missing y.., and
y! is the minimum detectable level of Y..
The indicator variable model suggested above for accommodating
missing X variables in regression analysis might be of the following
type :
where
-------
70
y. is an observed dependent variable for individual j,
I. is an indicator variable (0,1) according to whether the X obser-
vation is present or missing because it is below measurability,
g, are parameters to be estimated, and
e. is a stochastic error term.
-------
71
IV. DESCRIPTION OF FUTURE WORK
A. Field Operations
During January, RTI hopes to accomplish the following tasks:
1. Finalize the Chemical Analysis Report Form;
2. Initiate public relations with the smelter industry;
3. Initiate public relations with regard to the Pretest site,
including a possible visit to Texas;
4. Investigate the availability of interviewers in the Corpus
Christi area; and
5. Continue communications with CDC regarding Ajo and Anaconda,
including possible trips to Atlanta and Anaconda.
-------
72
B. Chemical Analysis
1. A series of experiments will be performed to determine the
extent of metal losses during digestion of hair samples.
2. A series of experiments will be carried out to determine
the stability (retention of titer) of dilute aqueous standards, hair di-
gests and diluted urine samples on storage at room temperature and in
the refrigerator.
3. Establish instrumental conditions for blood analysis.
4. Establish workup and instrumental conditions for dust
samples.
5. A series of experiments will be performed to determine
the extent of metal losses during soil, dust, and air particulate diges't
conditions.
6. Spike glass fiber filter strips with known amounts of
metals of interest and determine workup recoveries.
7. Determine atomic absorption response to solutions of
cacodylic acid (dimethylarsinic acid) and establish the means for its
optimization.
C. Quality Control
The following external quality control samples will be analyzed:
a) Water samples for all six elements - EPA/Cincinnati,
b) Blood samples for Pb - CDC/Atlanta,
c) Glass fiber filter samples for Pb and As - EPA/RTP.
-------
APPENDIX A
Southwest Research Institute
Instructions for Feces Collection
-------
SOUTHWEST RESEARCH INSTITUTE
8500 CULEBRA ROAD • POST OFFICE DRAWER 28510 • SAN ANTONIO. TEXAS 78284
Division of Chemistry and
Chemical Engineering
October 29, 1976
Dr. Warren Galke
Mail Drop 54
Population Studies Center
NERC, EPA
Research Triangle Park, N.C. Z7711
Dear Dr. Galke
Enclosed please find a drawing of the portable toilet seats that
have been used on projects requiring a feces collection. These seats
were used by the participants of the study concerning John E. Egan
Wastewater Plant in Schaumburg, Illinois.
An instruction sheet for the proper collection of the feces sample
was given to each participant. A copy of these instructions is attached.
The bags provided were attached to the seat and the sample was
collected. All excess air was squeezed from the bag and sealed with a
twist-tie. The participants were cautioned against contaminating the
outside of the collection with feces.
The use of the toilet is fairly straightforward and the only
assembly required is the attachment of the seat to the folding legs.
Quick connect plastic catches are provided for this purpose on the
bottom on this seat.
Two precautions were pointed out to the users of the toilets.
Even though the legs had rubber feet, it was suggested that carpeted
floor would prevent the assembled toilet from sliding. Secondly,
although the seat can support up to 200 Ibs., anyone of lesser weight
could break the plastic catches holding the legs if the person sat down
heavily upon the seat. It was suggested that the participant carefully
sit down on the seat.
SAN ANTONIO. HOUSTON. CORPUS CHRISTI. BLOOMFIELD. AND WASHINGTON.
D.C
-------
Dr. Warren Galke : October 29, 1976
NERC, EPA Page 2
Research Triangle Park, N.C.
These portable camping seats can be purchased at a number of
sporting good stores or department stores with camping or sporting
good departments.
If this letter does not meet your requirements, or if you have
further questions, please don't hesitate to call.
Very truly yours,
V-
John M. Hosenfeld
Research Chemist
Department of Environmental Sciences
JMH:pb
Encl.
-------
^'^^^
-------
SOUTHWEST RESEARCH INSTITUTE
8500 CULE8RA ROAD " • POST OFFICE DRAWER 28510 • SAN ANTONIO, TEXAS 78281
INSTRUCTION SHEET
The success of this research project depends on your complete
cooperation. Only through the assistance of volunteers, such as you, can
we obtain information on environmental pollutants. Your samples will
also provide a free check on your current health status. Incomplete
sampling of feces and sputum will produce incomplete information, so
please follow these instructions.
Feces Collection
1. You will be given a collection container for feces that has
been cleaned in a special manner. Your feces will be the only contents
placed in this container.
2. The portable toilet bag assembly has been provided for your
convenience in feces collection. Open the sample bag and place it on the
portable seat as shown in the instructions included with the kit. Beginning
in the evening (approximately 5 PM) you will begin collecting all of your
feces in the container provided. Please collect all of your feces until
approximately 8 AM the next morning, the day of your blood test. If
possible, continue to collect your feces until your appointment time. We
realize that this may not be possible due to you being away from home, etc.,
but at the minimum collect all your feces between 5PM and 8. AM the next
day.. If your appointment for the blood test is on Friday, begin feces
collection on Thursday .evening. If your appointment is for Saturday, begin
collecting on Friday evening.
" 3. When collecting your specimen, be sure not to mix any urine or
toilet paper with the feces. Analysis cannot be done on a sample that has
•been mixed with urine or paper. Also, take great care not to contaminate
the outside of the collection vessel with feces. The specimen bag is to be
sealed with the twist ties and then placed in the polyethylene container
designated for feces.
4. There is no restriction on your diet. You can eat or drink
anything you wish.
over, please . . . .
SAN ANTONIO. H O'U STON. CORPUS CHRIST
ItXAS. AND WASHINGTON. D.C
-------
Sputum Collection
1. You will be given a collection container that has been cleaned
in a special manner for your sputum. Remove the lid from this container
only when collecting your sputum and then immediately replace the lid.
2. Upon arising in the morning, cough deeply at least several
times. The material collected on the back of the tongue or in the mouth is
to be placed in the container provided. Remember we are interested in
collecting the material coughed up from the throat, not saliva which
normally collects in your mouth.
3. If you are unsuccessful in producing a specimen after coughing
deeply, lie across a bed with your head and chest slanting downward
toward the floor for 10 or 15 minutes. Coughing after this procedure will
very likely result in producing an acceptable specimen for collection.
Current Health Status Questionnaire
Please bring with you to the collection centef; the questionnaire
that we mailed to you in March. If you have misplaced it, another form is
included with this instruction sheet. Please fill out this questionnaire at
home. This will save time at the collection center.
Please report to the collection center at the time designated for
blood and throat swab collections. Please bring your feces and sputum
specimens and the completed current Health Status Questionnaire with you.
Thank you very much-for your help.
-------
APPENDIX B
Study Questionnaire
(Draft 12-17-76)
-------
OMB No.
Approval Expires
STUDY OF HUMAN TISSUE HEAVY METAL BURDEN IN
NON-FERROUS SMELTER COMMUNITIES
Sponsored by:
Health Effects Research Laboratory
Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Conducted by:
Research Triangle Institute
P.O. Box 12194
Research Triangle Park, North Carolina 27709
QUESTIONNAIRE
THE RESEARCH TRIANGLE INSTITUTE OF RESEARCH TRIANGLE PARK, NORTH CAROLINA
IS UNDERTAKING A RESEARCH STUDY FOR THE U.S. ENVIRONMENTAL PROTECTION
AGENCY OF THE HEALTH EFFECTS, IF ANY, OF HEAVY METAL ABSORPTION BY PERSONS
LIVING IN COMMUNITIES NEAR NON-FERROUS SMELTERS. WE WILL BE ASKING SEVERAL
QUESTIONS ABOUT YOU AND YOUR FAMILY. YOUR COOPERATION, ALTHOUGH ENTIRELY
VOLUNTARY, IS ESSENTIAL TO ASSURE THE SUCCESS OF THIS STUDY.
IMPORTANT
ALL INFORMATION RECORDED ON THIS DOCUMENT WHICH WOULD PERMIT
IDENTIFICATION OF AN INDIVIDUAL WILL BE HELD STRICTLY CONFIDENTIAL, WILL BE
USED ONLY BY PERSONS ENGAGED IN OR FOR THE PURPOSES OF THIS RESEARCH STUDY,
AND WILL NOT BE DISCLOSED OR RELEASED TO OTHER PERSONS OR BE USED FOR ANY
OTHER PURPOSE.
Study Number
Site Number
Segment Number
Household Number
Participant Number
-------
A. HOUSEHOLD INFORMATION
1. For each person in your household, including yourself, please indicate age and educational level, beginning with the oldest and
proceeding to the youngest (enter responses in matrix below):
Household
Member
Number
01
02
03
04
05
06
07
08
09
10
Age
(years)
Educa-
tional
Level
(Years)
•
Currently
Employed at
Smelter
1 = Yes 2 = No
Normally
Spend Day
at Home
1 = Yes 2 = No
-
Excess Metal Absorption
Screened
Diagnosed
Partici-
pant
Number
2. Does anyone in your household currently work at the smelter? (Enter responses in matrix above.)
3. Which members of your household normally spend their day at home? (Enter responses in matrix above.)
4. Has anyone in your household ever been screened for excess heavy metal absorption?
Yes
No
3 Do not know
(Enter response in matrix above.)
5. Has any member of your household ever been diagnosed as having excess heavy metal absorption?
Do not know (Enter response in matrix above.)
No
6. Male head of household:
a. Household member number:
b. Occupation
c. Highest educational level completed:
8th grade or less
College - incomplete
2 High school - incomplete 5 College graduate
Technical school beyond high school
8 Do not know
| 3 I High school graduate
7. Female head of household:
a. Household member number:
6 Graduate school
9 Other (Specify)
b. Occupation
c. Highest educational level completed:
0
8th grade or less
2 High school - incomplete
3 I High school graduate
College - incomplete [ 7 | Technical school beyond high school
College graduate
6 ] Graduate school
-2-
8 Do not know
9 Other (Specify)
-------
8. What is the approximate age of your house?
Years
Do not know
9. What type of structure is your house? (51 percent or more of exterior surface.)
Solid brick, concrete, or rock
Brick or rock veneer
Stucco
4l Asbestos
5 Aluminum siding
6 Composition siding
7 Wood frame
Do not know
j_9j Other (Specify)
10. Is there evidence of flaking paint present in the home? Ill Yes | 2 J No
11. Are paint chips present in the soil surrounding the home?
Yes
No
3 Do not know
12. Do you cool your home with any of the following appliances? (Check all that apply.)
Central air conditioning
Window fan(s)
2 Window air conditioner(s) 5 Ceiling exhaust fan(s)
None of these
Do not know
Evaporative cooler! s) | 6| Circulating fan(s) [ 9 | Other (Specify)
13. Are any of the following articles used in storing, preparing, and/or serving food in your household? (Check all that apply.)
I 1 | Unglazed pottery (home-made or craft) | 4| None of these
| 21 Glazed pottery (home-made or craft) | 5 [ Do not know
I 3J Hand-painted flatware
14. Does your household grow any of its own food in a home garden? , | 1 | Yes [ 2 | No | 3 | Do not know
15. Where does your household obtain fresh fruit and/or vegetables? (Specify) .
16. What is the primary source of your water for drinking?
| i I Bottled water | 3 [ Tap - community well 5 Tap - cisterrt
Tap - municipal supply [ 4 | Tap - private well | 6 | Do not know
Other (Specify)
17. What is the primary source of your water for cooking?
I 1 I Bottled water | 3 | Tap - community well
2 Tap - municipal supply 4 Tap - private well
5 Tap • cistern
Do not know
7'
Other (Specify)
18. Has anyone in your family ever been treated for:
No Yea Relationship to respondent and/or household member number:
a. Seizures?
b. Hyperactivity?
c. Mental retardation?
LiJ
1
1
2
2
2
(Specify)
(Specify)
(Specify)
-3-
-------
B. PARTICIPANT INFORMATION
IF THE PARTICIPANT IS UNDER 18 YEARS OF AGE. THIS SECTION OF THE QUESTIONNAIRE MA Y HA VE
TO BE ADMINISTERED IN WHOLE OR IN PART TO THE PARENT OR GUARDIAN, AND MUST BE
ADMINISTERED IN THAT PERSON'S PRESENCE. IF THE PARTICIPANT SUFFERS FROM A SPEECH OR
HEARING DEFICIT. THIS SECTION OF THE QUESTIONNAIRE MAY HAVE TO BE ADMINISTERED TO THE
SPOUSE OR ANOTHER SPOKESMAN-SEE SECTION C.
First, I would like to ask some general questions about you/the participant.
1. Sex (by observation): \ 1 | Male [ 2 [ Female
I 1 I 1
2. Race (by observation):
1 White 2 Black
3 American Indian 4 Asiatic 5 surname
I Other
7 | (Specify).
6 Unknown
3. What was your/the participant's age in years at last birthday?
Years
4. What is your/the participant's birth date?
(Month) (Day) (Year)
5. What is your/the participant's approximate weight in
pounds?
6. What is your/the participant's marital status?
I 1 I Married [ 2 [ Never married [ 3 | Widowed
til
Divorced
Separated
6 Other (Specify).
Next, I would like to ask some questions about your/the participant's education.
7. Are you/is the participant in school now? | 1 [ Yes (Go to question 8) \ 2 | No (Go to question 11)
8. What type of school do you/does the [ 1 [ Nursery school or kindergarten (Go to question 10)
participant attend? ___ , 1
2 Elementary school I 5 | Junior college
3 Junior high school
Senior high school
(Go to question 9) \ 6 | College
9. What grade are you/is the participant in?
10. What is the address of the school?
(Continue)
(Street)
11. Highest educational level completed:
| 1 I None I 4 [ High school graduate
I _2J 8th grade or less | 5 [ College - incomplete
3 I High school - incomplete 6 College graduate
Graduate school
8 I Technical school
Other
(Specify)
(Go to question 12)
(City)
(Go to question 12)
I 7 [ Graduate school
I 8 I Technical school beyond high school
I 9 | Other (Specify)
-------
Next, I would like to ask some questions about your/the participant's occupation and residence.
Yes (Go to question 14)
12. Are you/is the participant presently employed in any capacity?
No (Go to question 13)
13. If not presently employed, which of the following best describes your/the participant's status?
I 4 | Unemployed
(Go to question 15)
(Go to question 20)
I 1 I Housewife
2 I Student | J3j Retired
| 3 | Child (Go to question 23) \ 6 [ Disabled
14. If presently employed,, which of the following best describes your/the participant's status?
3 I Employed part-time
1
Self-employed
Employed full-time
15. What is/was your/the participant's usual occupation? (Specify)
16. Are you/is the participant presently employed in this occupation?
Yes 2 No
17. If yes to above question, how many years have you/has the participant been employed in that occupation?
If no to above question, how many years were you/was the participant employed in that occupation?
18. If you are/the participant is presently employed, what is the nature of the company for which you/the participant worlds)?
(Specify) ,
19. How long have you/has the participant been employed by your/the participant's present employer?
Units
Months
Years
20. How many times have you/has the participant changed occupations during the past 5 years?
21. Does your/the participant's occupation usually take you/the participant away from home? | 1 |
22. Have you/has the participant worked at a smelter at any time during the past 12 months?
Yes I 2 | No
Yes (STOP!) 2 I No (Continue)
23. Have you/has the participant ever worked at or lived within 2 miles of:
Worked at
Ye» No
0 a 0
a. Paper/wood industry
b. Smelting industries
c. Glass manufacturing plant
d. Pesticide manufacturing plant | 1 |
e. Mining area | i [
Lived near
Yes No
2
0
24. How many hours of the day, on the average, do you/does the participant normally spend away from home? Hours
25. How many hours of the day, on the average, do you/does the participant normally spend more than 2 miles from home?
Years (If less than 1 year, STOP!
26. How many years have you/has the participant lived in this city or town?
27. How long have you/has the participant lived at this address?
Units
Days
Months 3 Years
28. How many times have you/has the participant changed living quarters during the last 5 years?
-5-
-------
Next, I would like to ask some questions regarding your/the participant's personal habits.
29. What is the natural color of your/the participant's scalp hair?
0
Brown 2 Black 31 Red
Blonde 5 Gray
6
Bald
0
Other (Specify)
30. How many times per week, on the average, do you/does the participant shampoo your /the participant's hair?
31. Which of the following hair care products do you/does the participant use? (Check all that apply and specify the most frequently
used brand.) „. , Brantj
Brand
1 Washing (Shampoo or soap)
Setting lotion
3 Hair spray
Artificial coloring
5 Permanent
Last application date (Month) (Day)
(Year)
32. Do you/does the participant use any foot powder or toenail polishes? [ 1 |
If yes, specify brand) s)
Yes
No
33. Oo you/does the participant drink? (Check all that apply and indicate amount.)
How much/week?
m
Beer
2 Wine
Liquor
None of these
0
| 5 I Other alcoholic beverage (Specify)
34. Have you/has the participant ever smoked as many as 5 packs of cigarettes—that is, as many as 100 cigarettes during your/the
participant's entire life?
I i I Yes (Go to question 35) \ 2 | No (Go to question 39)
35. Do you/does the participant now smoke cigarettes? | 1 | Yes [ 2 | No
36. How old were you/was the participant when you/the participant first started smoking?
Years
37. If you/the participant no longer smoke(s), how old were you /was the participant when you/the participant last gave up smoking?
Years
38. On the average, how many cigarettes do (did) you/does (did) the participant smoke per day?
I 1 [ Less than % pack (1-5 cigarettes) | 4] About 11/i packs (26-34 cigarettes)
| 2[ About 1/2 pack (6-14cigarettes)
3 About 1 pack (15-25 cigarettes)
5 | About 2 packs (35 or more cigarettes)
39. What is the average number of hours that you/the participant spend(s) out of doors each day?
40. Do you/does the participant ever eat non-food substances such as paint, clay, dirt, or plaster?
Hours
Yes
No
-------
41. (For children participants only) Where does the participant play most frequently? (Check one.}
At home indoors
3 On the same block indoors
On a different block indoors
2 At home outdoors
On the same block outdoors 6 On a different block outdoors
Other (Specify!
Next, I would like to ask some questions regarding your/the participant's health.
42. What do you consider the current status of your/the participant's health?
1 Excellent
43. Are you/is the particip
I 0 I None
| 1 | Tranquiiizer
2 Sedative
I 2 I Good I 3 | Fair
4 Poor
ant currently taking any prescription medication(s) on a regular daily basis?
• I 3 | Analgesic I
I 4 I Hormone
| 5 | Oral contraceptive
44. Do you/does the participant suffer from any of the folio
If yes, specify
Yes No how long
a. Loss of appetite | 1 | | 2 |
b. Weight loss
c. Fatigue
d. Nausea and/or
vomiting
e. Diarrhea
f. Abdominal -pain
g. Sore throat
mm
mm
mm
mm
mm
m m
wing symptoms?
h. Cough
i. Changes in skin pigmentation
j. White lines across fingernails
k. Pins and needles, numbness or
pain of the limbs
I. Weakness or wasting of the
muscles of the limbs .
m. Pain or soreness of the
mouth, nose, or eyes
(Check all that apply.)
Z LJU 1 "1 1 "1
sQQQ
M =
If yes, specify
o how long
1
1
1
HFI
mm
Next, I would like to ask some questions regarding your/the participant's diet.
45. Which meal(s) do you/does the participant usually eat at home? (Check all that apply.)
[ 1 [ Breakfast [ 2 [ Lunch | 3 [ Dinner
46. When you do not/the participant does not eat at home, where do you/does the participant eat? (Check all that apply.)
I 1 I Meal prepared at home but eaten elsewhere [ 2 | School , | 3 [ Work
Restaurant
5 Other (Specify)
47. Are you/is the participant presently following any of the following dietary regimens? (Check all that apply.)
1
Formula/prepared baby foods
Bland food ulcer diet
3 Diabetic diet
[ 4 [ Reducing diet
| 5 I Organic foods
6 Vegetarian
I 7 I None of these
8 Other (Specify)
-------
48. On the average, how often do you/does the participant eat the following foods? (Check the appropriate box.)
Foodstuff
a. Shellfish
b. Fish
c. Liver
d. Kidney
e. Hamburger
f. Eggs
g. Milk
Canned Foods:
n. Tomatoes
i. Beans
j. Peas
k. Peaches
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Foodstuff
Baby Foods:
1. Oranqe iuice
m. Apple juice
n. Applesauce
o. Peaches
p. Spinach
q. Mixed vegetables
r. Beef
8
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Comments!.
C. RESPONDENT/INTERVIEWER INFORMATION
1. Site number
5. Interviewer number
2. Segment number
3. Household number
*
(Month) (Day)
6. Date of interview
4. Participant number
(Year)
7. Part A Respondent (Check all that apply.) Household member number
Participant 2 Parent or guardian of participant [ 3| Head of household
Other household member
8. Part B Respondent (Check one.) Household member number
1J Participant j 2J Parent or guardian of participant
9. Does participant have transportation to central data collection facility? | 1 [ Yes | 2 |
(Month) (Day) (Year)
Appointment date
And time
Comments:
No
-------
COMMENTS
-9-
-------
D. SAMPLE INFORMATION
For each sample collected for a given household or
individual, attach the appropriate label to the appropriate
container before collecting the sample. Complete section D
below when appropriate.
Study Number
1. Site Number
2. Segment Number
3. Household Number
4. Participant Number
5
6
7.
8.
9.
i
10.
Type of
Sample
Soil
Tap Water
Source:
House Oust
Scalp Hair
Blood
Urine
Original Sample
Collected
Yes
1
1
1
1
1
1
No
2
2
2
2
2
2
If Collected, Date
Month
Day
Year
If Not Collected,
Reason
Interviewer
Number
Duplicate Sample
Selected
Yes
1
1
1
1
1
AA
XX
No
2
2
2
2
2
A<^
vv
AA
Collected
Yes
1
1
1
1
1
1
No
2
2
2
2
2
2
If Collected, Date
Month
Day
Year
If Not Collected,
Reason
11. Hurnatocrit
{Month} (Day} (Year)
% Date
COMMENTS:
12. Urine Protein
Interviewer Number
-10-
-------
APPENDIX C
Analytical Data Sheets
-------
ANALYTICAL DATA SHEETS - AA ANALYSIS
INSTRUCTIONS
There is a separate form for reporting the analytical results of
each matrix. The individual forms have several features in common and
some which are unique for the matrix material being analyzed. The
following information will be supplied in the appropriate space:
a) The chemical symbol of the element being analyzed,
b) A bound notebook reference will be cited for each analytical
run. This notebook will be used to record all operating con-
ditions and any observations or remarks concerning the analysis.
The notebook reference will also be noted on the strip chart
recording.
c) The date and the operator(s) initials will be shown.
d) All calibration standards will be injected in duplicate and the
corresponding peak height recorded.
e) A least squares regression analysis will be carried out on four
standard solutions run in duplicate and the equation representing
the best fit will be noted.
y = weight of metal injected
x = peak height
All samples analyzed during a run will be injected in duplicate. The
following data will be recorded for each matrix type:
a) Column 1.
Each sample will be identified by the same code numbers used to
label the sample container at the smelter site.
-------
b) Column 2.
Instrument response during atomization is. measured as peak height,
expressed in units of millivolts (mv).
c) Column 3.
The weight of metal injected is calculated from calibration equation.
y = weight of metal injected
x = peak height
d) Column 4.
F is a function of the volume of analytical solution injected into
the graphite furnace.
Volume injected I?
10 yl 100
25 pi 40
50 ul 20
e) Column 5.
The weight of metal contained in each ml of the solution injected into
the furnace is calculated by multiplying the number in Column 3 by F.
The remaining columns on the Data Sheet are treated differently for
each matrix.
a) Drinking Water -
To convert weight of metal/ml water to weight of metal/liter water
simply change the units of weight as follows:
Units wt/ml Equiv. units wt/1
Pg ng (ppt)
ng yg (ppb)
Ug mg (ppm)
-------
b) Urine -
The constant D (Column 6) is defined as the volume (ml) to which one
ml of urine sample is diluted prior to injection in the graphite furnace.
For example, if a 1:1 dilution is performed, D = 2; if a 1:49 dilution
is necessary, D = 50.
The weight of metal/ml urine (Column 7) is determined by multiplying
the value in Column 5 by D.
c) Blood -
As with urine, the constant D (Column 6) is defined as the volume (ml)
to which one ml of urine sample is diluted prior to injection in the graphite
furnace. For example, if a 1:9 dilution is carried out, D = 10.
The weight of metal/100 ml blood (Column 7) is determined by multiplying
the value in Column 5 by 100D.
d) Hair -
D (Column 6) = V. (-r^) .
1 *l
where, V. = volume (ml to which sample digest is diluted.
Vf = final volume (ml) of diluted aliquot.
A = volume (ml) of aliquot withdrawn from initial sample
volume (V.) for further dilution to V,.
NOTE - If no aliquoting of V. is performed, the term V-/A = 1.
D = V.
i
The weight of metal/gm hair (Volumn 8) is found by multiplying Column 5
by D and dividing this product by the sample weight, W (gm)(Column 7).
Wt. metal/gm hair = Column 5 (—)
Example; A 250 mg hair sample was digested and diluted to 5 ml. Two
ml of this solution was diluted to 10 ml prior to furnace injection.
-------
V. = 5; Vf = 10; A = 2; W = .25
D - 5 <") - 25; | - 100
Wt. metal/gm hair = Column 5 (100).
e) Air Particulates
In the case of air particulate analysis, D is defined as follows:
V F
D (Column 6) = V±(^) ^.
a
where, V. = volume (ml) to which the extract of the entire filter
strip is diluted.
V - final volume (ml) of diluted aliquot.
A = volume (ml) of aliquot withdrawn from initial sample
volume (V.) for further dilution to V_.
F = total filter area
F = area of filter used in analysis
NOTE
- If no aliquoting of V. is performed, the term Vf/A = 1.
a
The weight of metal on the entire filter (Column 7) is determined
3
by multiplying Column 5 by D. Column 7 is divided by air volume (m )
3
(Column 8) to give weight of metal/m air (Column 9) . The calculation
of air volume is shown on the air collection log sheet.
3
Wt. metal/m air = Column 5 (D/air volume)
2
Example : A 40.6 cm section of a 20.3 x 25.4 cm filter was treated
with acid and diluted to 100 ml. Two ml of this solution was diluted
3
to 5 ml prior to furnace injection. Air volume = 2500 m .
= 100; V = 5; A = 2; F = 515.6; F = 40.6
I t Si
V.
D = 100(4) TTTZ " 25° <12-7) • 3175
-------
Wt metal/m3 air = Column 5 (3175)/2500
= Column 5 (1.27)
f) Housedust
Vf
D (Column 6) = VjL(^i-).
where, V. = volume (ml) to which sample digest is diluted.
V = final volume (ml) of diluted aliquot.
A = volume (ml) of aliquot withdrawn from initial sample
volume (V.) for further dilution to Vf.
NOTE - If no aliquoting of V. is performed, the term Vf/A = 1.
D = V.
i
The weight of metal/gm dust (Column 8) is found by multiplying
Column 5 by D and dividing this product by the sample weight, W(gm)
(Column 7).
Wt. metal/gm dust = Column 5 (—) .
Example; A 250 mg dust sample was digested and diluted to 25 ml.
Two mis of this solution was diluted to 25 ml prior to furnace injection.
V± = 25; Vf = 25; A = 2; W = .25
D = 25 (jp) = 312.5; |= 1250
Wt. metal/gm dust = Column 5 (1250).
2
The total weight of metal in a .25 cm collection is found by either
multiplying Column 8 by the weight of sample collected over this area or
multiplying Column 5 by D.
g) Soil
Vf
D (Column 6) = V.C-r^).
X A
-------
where, V. = volume (ml) to which sample digest is diluted.
V = final volume (ml) of digested aliquot.
A = volume (ml) of aliquot withdrawn from initial sample
volume (V.) for further dilution to V-.
NOTE - If no aliquoting of V. is performed, the term Vf/A = 1.
D = V.
The weight of metal/gm soil (Column 8) is founding by multiplying
Column 5 by D and dividing this product by the sample weight, W(gm)
(Column 7) .
Wt. metal/gm soil = Column 5 (— ) .
Example ; A 1.0 gm soil sample was digested and diluted to 250 ml.
One ml of this solution was diluted to 100 ml prior to furnace injection.
V± = 250; Vf = 100; A = 1; W = 1
D = 250 (p-) = 25,000; = 25,000
Wt. metal/gm soil = Column 5 (25,000).
-------
Matrix
- Housedust
Standard (wt/vol . )
1.
Sample
code
2.
Peak
height
(mv)
3.
Wt.
metal
injected
ANALYTICAL DATA SHEET
Peak Height (mv)
>
>
9
5
4. 5.
Wt. metal/
ml anal.
F soln .
- AA ANALYSIS
Element -
Notebook No.
Date
Operator (s)
Calibration Equ.
6. 7.. 8. 9. 10.
Wt . metal .
Sample Wt. metal/ .25 cm2
D weight gm dust area Comment
-------
ANALYTICAL DATA SHEET
Matrix
- Air Participates
Standard (wt/vol
1.
Sample
code
2.
Peak
height
(mv)
3.
Wt.
metal *
injected
.) Peak
4.
F
Height (mv)
.5.
Wt. metal/
ml anal.
soln.
- AA ANALYSIS
Element -
Notebook No.
Date
Operator (s)
Calibration Equ.
6. 7. 8. 9. 10.
Air Wt.
Wt. metal volume metal/
D on 'filter (m^) m^ Comment
-------
ANALYTICAL DATA SHEET - AA ANALYSIS
1.
Sample
code
Matrix -
Standard
2.
Peak
height
(mv)
Blood
(wt/vol.) Peak Height
3. 4.
Wt.
metal
injected F
Element -
(mv) Notebook No.
Date
Operator (s)
Calibration Equ.
5. 6. 7. 8.
Wt. metal/ Wt. metal/
ml anal. 100 ml
soln. D blood Comment
-------
ANALYTICAL DATA SHEET - AA ANALYSIS
1.
Sample
code
Matrix -
Standard
2.
Peak
height
(mv)
Urine
(wt/vol.) Peak Height
»
j
»
»
3. 4.
Wt.
metal
injected F
Element -
(mv) Notebook No.
Date
Operator (s)
Calibration Equ.
5. 6. 7. 8.
Wt. metal/ Wt. metal/
ml anal. ml
soln. D urine Comment
-------
ANALYTICAL DATA SHEET - AA ANALYSIS
1.
Sample
code
Matrix - Drinking Water
Standard (wt/vol.) Peak Height (mv)
»
»
>
»
2. 3. 4.
Peak Wt .
height metal
(mv) injected F
Element -
Notebook No.
Date
Op era tor (s)
Calibration Equ.
5. 6. 7.
Wt. metal/
ml anal. Wt. metal/
soln. 1. water Comment
-------
1.
Sample
code
Matrix -
Standard
2.
Peak
height
(mv)
Soil
(wt/vol.)
3.
Wt.
metal
injected
ANALYTICAL DATA SHEET -
Peak Height (mv)
>
»
»
9
4. 5.
Wt. metal/
ml anal.
F soln
AA ANALYSIS
Element -
Notebook No.
Date
Operator (s)
Calibration Equ.
6. 7. 8. 9.
Sample Wt. metal/
D weight gm soil Comment
-------
ANALYTICAL DATA SHEET - AA
1.
Sample
code
Matrix -
Standard
2.
Peak
height
(mv)
Hair
(wt/vol.)
3.
Wt.
metal
injected
Peak Height (mv)
»
5
»
»
4. 5.
Wt. metal/
ml anal.
F soln.
ANALYSIS
Element -
Notebook No.
Date
Operator (s)
Calibration Equ.
6. 7. 8.. 9.
Sample Wt. metal/
D weight gm hair Comment
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ANALYTICAL DATA SHEET - CREATININE IN URINE
1.
Sample
code
ESTIMATION
Standard Soln. OD at 490 nm
.01 mg/ml
C (Creatinine coeff.) =
V2, (Estimated
2. 3.
Diluted
urine
OD at Cu, creatinine
490 nm cone (mg/ml)
OF 24 HOUR URINE VOLUME
23 mg/kg (males) ;
24 hr urine vol.)
4. 5.
W, subject
F/M. weight (kg)
Notebook No.
Date
Operator (s)
18 mg/kg (females)
we
u
6. 7. 8.
Wt. metal/
C V0, ml urine
9.
Est. wt.
metal
excreted
in 24 hr
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