United States Office of Research and EPA/600/R-02/060
Environmental Protection Development September 2002
Agency Washington, D.C. 20460
4>EPA Environmental Technology
Verification Report
Lead in Dust Wipe Measurement
Technology
Monitoring Technologies International
PDV 5000 Trace Element Analyzer
on\l
Oak Ridge National Laboratory
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THE ENVIRONMENTAL TECHNOLOGY VERIFICATION
PROGRAM
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Oak Ridge National Laboratory
Verification Statement
TECHNOLOGY TYPE:
APPLICATION:
TECHNOLOGY NAME:
COMPANY:
ADDRESS:
WEB SITE:
E-MAIL:
ANODIC STRIPPING VOLTAMMETRY
MEASUREMENT OF LEAD IN DUST WIPES
PDV 5000 Trace Element Analyzer
Monitoring Technologies International
78 Collingwood Street
Osborne Park 6017
Perth, Western Australia
www.mti.com.au
cgreen@colingreen.idps.co.uk
PHONE: +61 8 9204 3600
FAX: +61 8 9204 2602
The U.S. Environmental Protection Agency (EPA) has created the Environmental Technology
Verification Program (ETV) to facilitate the deployment of innovative or improved environmental
technologies through performance verification and dissemination of information. The goal of the ETV
Program is to further environmental protection by substantially accelerating the acceptance and use of
improved and cost-effective technologies. ETV seeks to achieve this goal by providing high-quality,
peer-reviewed data on technology performance to those involved in the design, distribution, financing,
permitting, purchase, and use of environmental technologies.
ETV works in partnership with recognized standards and testing organizations and stakeholder groups
consisting of regulators, buyers, and vendor organizations, with the full participation of individual
technology developers. The program evaluates the performance of innovative technologies by developing
test plans that are responsive to the needs of stakeholders, conducting field or laboratory tests (as
appropriate), collecting and analyzing data, and preparing peer-reviewed reports. All evaluations are
conducted in accordance with rigorous quality assurance protocols to ensure that data of known and
adequate quality are generated and that the results are defensible.
Oak Ridge National Laboratory (ORNL) is one of the verification organizations operating under the
Advanced Monitoring Systems (AMS) Center. AMS, which is administered by EPA's National Exposure
Research Laboratory (NERL), is one of six technology areas under ETV. In this verification test, ORNL
evaluated the performance of lead in dust wipe measurement technologies. This verification statement
provides a summary of the test results for Monitoring Technologies International's (MTI) PDV 5000
Trace Metal Analyzer.
EPA-VS-SCM-53
The accompanying notice is an integral part of this verification statement.
September 2002
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VERIFICATION TEST DESCRIPTION
This verification test was designed to evaluate technologies that detect and measure lead in dust wipes.
The test was conducted at the Capitol Community Technical College in Hartford, CT, from November 5
through November 9, 2001. The vendors of commercially-available, field portable technologies blindly
analyzed 160 dust wipe samples containing known amounts of lead, ranging in concentration from <2 to
1,500 |J,g/wipe. The experimental design was particularly focused on important clearance standards,
such as those identified in 40 CFR Part 745.227(e)(8)(viii) of 40 |_lg/ft2 for floors, 250 |_lg/ft2 for window
sills, and 400 |-lg/ft2 for window troughs. The samples included wipes newly-prepared and archived from
the Environmental Lead Proficiency Analytical Testing Program (ELPAT). These samples were prepared
from dust collected in households in North Carolina and Wisconsin. Also, newly-prepared samples were
acquired from the University of Cincinnati (UC). The UC dust wipe samples were prepared from
National Institute of Standards and Technology (NIST) Standard Reference Materials (SRMs). The
results of the lead analyses generated by the technology were compared with results from analyses of
similar samples by conventional laboratory methodology in a laboratory that was recognized as
proficient by the National Lead Laboratory Accreditation Program (NLLAP) for dust testing. Details of
the test, including a data summary and discussion of results, may be found in the report entitled
Environmental Technology Verification Report: Lead in Dust Wipe Detection Technology—Monitoring
Technologies International, PDV 5000 Trace Metal Analyzer, EPA/600/R-02/060.
TECHNOLOGY DESCRIPTION
MTFs PDV 5000, a field portable instrument, is a self-contained anodic stripping analyzer. Anodic
Stripping Voltammetry (ASV) works by electroplating metals in solution onto an electrode. This
concentrates the metal. The metals on the electrode are then sequentially stripped off, which generates a
current that can be measured. The current (milliamps) is proportional to the amount of metal being stripped
off. The potential (voltage in millivolts) at which the metal is stripped off is characteristic for each metal.
This means the metal can be identified as well as quantified. The PDV 5000's reporting limits during this
verification test was < 20 |_lg/wipe.
VERIFICATION OF PERFORMANCE
The following performance characteristics of the PDV 5000 were observed:
Precision: Precision, based on the average percent relative standard deviation (RSD), 22% for the
ELPAT samples and 21% for the UC samples, excluding two outlier values. Both values are above the
level of acceptable precision (< 20% average relative standard deviation).
Accuracy: Accuracy was assessed using the estimated concentrations of the UC and ELPAT samples.
The average percent recovery value for all samples reported above 30 |_lg/wipe was 87% for the UC
samples and 93% for the ELPAT samples. The range of percent recoveries values was from 35% to
137%. This negative bias is statistically significant, but the average value is within the acceptable bias
range of 100% ± 25%. For the NLLAP laboratory results, the average percent recovery values were 91%
and 98%, respectively, for the UC and ELPAT samples. The negative bias for both the UC and ELPAT
samples was statistically significant.
Comparability: A comparison of the PDV 5000 results and the NLLAP-recognized laboratory results
was performed for all samples (UC and ELPAT) that were reported above 30 |_lg/wipe. The correlation
coefficient (r) for the comparison to NLLAP lab results for the UC samples was 0.999 [slope (m) = 1.074,
intercept = -14.345], and for the ELPAT samples was 0.988 [m = 0.885, intercept = 15.633]. While the
slopes for both the UC and ELPAT samples were statistically different than 1.00, correlation coefficients
greater than 0.990 indicate a strong linear agreement with the NLLAP laboratory data.
EPA-VS-SCM-53 The accompanying notice is an integral part of this verification statement. September 2002
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Detectable blanks: All twenty samples, prepared at concentrations < 2 |_lg/wipe, were reported
correctly as < 20 |-lg/wipe by the PDV 5000. Performance was also assessed at levels near the reporting
limits of 20 |-lg/wipe. The instrument reported the eight samples near 17 |_lg/wipe as < 20 |_lg/wipe, but the
four samples around 30 |-lg/wipe were reported as < 20, < 20, 24, and 25.
False positive results: A false positive (fp) result is one in which the technology reports a result that is
above the clearance level when the true (or estimated) concentration is actually below. For the UC
samples, the PDV 5000 reported four of a possible 29 results as false positives, while the NLLAP
laboratory did not report any false positives. For the ELPAT samples, the PDV 5000 reported three of a
possible 12 fp results and the NLLAP laboratory reported two of 12.
False negative results: A false negative (fn)result is one in which the technology reports a result that is
below the clearance level when the true (or estimated) concentration is actually above. For the UC samples,
the PDV 5000 reported 17 of 29 possible fii results, while the NLLAP laboratory reported 23 of 30 fii
results. For the ELPAT samples, the PDV 5000 reported 12 of a possible 28 fn results, while the NLLAP
laboratory reported 7 of 12.
Completeness: Completeness is defined as the percentage of measurements that are judged to be usable
i.e., the result is not rejected). An acceptable completeness rate is 95% or greater. The PDV 5000
generated results for all 160 dust wipe samples. However, two results for UC samples were reported as
non-detects for sample concentrations of 40 and 250 |_lg/wipe. These were considered outliers and excluded
from the data analysis. Therefore, completeness was 99%.
Sample Throughput: Two analysts (one expert and one novice analyst) each operated their own
instrument, with the expert running odd-numbered samples and the novice analyzing the even-numbered
samples. The analysts completed the analysis of 160 samples over the course of three days. The first day
was spent setting up, training the novice, and running approximately 32 samples. On the second day (a 14-
hour day), 130 samples were analyzed. The data was checked and transposed onto the results sheets on the
third day. The MTI team spent a total of about 18 hours analyzing the samples.
EPA-VS-SCM-53 The accompanying notice is an integral part of this verification statement. September 2002
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Overall Evaluation: The overall performance was characterized as having an acceptable amount of
negative bias, larger than acceptable precision, but in good linear agreement with an NLLAP-recognized
laboratory's data. The verification team found that the PDV 5000 was relatively simple for the trained
analyst to operate in the field, requiring less than an hour for initial setup. As with any technology
selection, the user must determine if this technology is appropriate for the application and the project
data quality objectives. Additionally, ORNL and ETV remind the reader that, while the ETV test
provides valuable information in the form of a snapshot of performance, state, tribal, or federal
requirements regarding the use of the technologies (such as NLLAP recognition where required) need to
be followed. For more information on this and other verified technologies, visit the ETV web site at
http: //www. epa. gov/etv.
Gary J. Foley, Ph.D.
Director
National Exposure Research Laboratory
Office of Research and Development
W. Franklin Harris, Ph.D.
Associate Laboratory Director
Biological and Environmental Sciences
Oak Ridge National Laboratory
NOTICE: EPA verifications are based on evaluations of technology performance under specific, predetermined
criteria and appropriate quality assurance procedures. EPA and ORNL make no expressed or implied warranties as
to the performance of the technology and do not certify that a technology will always operate as verified. The end
user is solely responsible for complying with any and all applicable federal, state, and local requirements. Mention
of commercial product names does not imply endorsement or recommendation.
EPA-VS-SCM-53
The accompanying notice is an integral part of this verification statement.
September 2002
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EPA/600/R-02/060
September 2002
Environmental Technology
Verification Report
Lead in Dust Wipe Measurement
Technology
Monitoring Technologies International
PDV 5000 Trace Metal Analyzer
By
Amy B. Dindal
Charles K. Bayne, Ph.D.
Roger A. Jenkins, Ph.D.
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831-6120
Eric N. Koglin
U.S. Environmental Protection Agency
Environmental Sciences Division
National Exposure Research Laboratory
Las Vegas, Nevada 89193-3478
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Notice
The U.S. Environmental Protection Agency (EPA), through its Office of Research and Development (ORD),
funded and managed, through Interagency Agreement No. DW89937854 with Oak Ridge National
Laboratory, the verification effort described herein. This report has been peer and administratively reviewed
and has been approved for publication as an EPA document. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use of a specific product.
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Table of Contents
Notice ii
List of Figures v
List of Tables vi
Acknowledgments vii
Abbreviations and Acronyms viii
Section 1 — Introduction 1
Section 2 — Technology Description 2
General Technology Description 2
Sample Preparation and Analysis 2
Theory of Operation 2
Section 3 — Verification Test Design 4
Objective 4
Testing Location and Conditions 4
Drivers and Objectives for the Test 4
Summary of the Experimental Design 4
ELPAT and Blank Sample Description 4
University of Cincinnati Sample Description 5
Distribution and Number of Samples 6
Sample Randomization 6
Description of Performance Factors 6
Precision 7
Accuracy 7
Comparability 8
Detectable Blanks 8
False Positive/Negative Results 8
Completeness 9
Sample Throughput 9
Ease of Use 9
Cost 9
Miscellaneous Factors 9
Section 4 — Laboratory Analyses 10
Background 10
NLLAP Laboratory Selection 10
Laboratory Method 10
Section 5 — Technology Evaluation 17
Objective and Approach 17
Precision 17
Accuracy 17
Comparability 18
Detectable Blanks 18
iii
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False Positive/False Negative Results 19
Completeness 22
Sample Throughput 22
Ease of Use 22
Cost Assessment 22
PDV 5000 Costs 23
Labor 23
Laboratory Costs 23
Sample Shipment 23
Labor, Equipment, and Waste Disposal 24
Cost Assessment Summary 24
Miscellaneous Factors 24
Summary of Performance 24
Section 6 — References 26
Appendix 27
IV
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List of Figures
1. Mil's PDV 5000 system 2
2. Distribution of both UC and ELPAT sample concentrations. Four samples were analyzed at each
concentration level 7
3. Plot of DataChem reported values versus estimated values, shown for concentrations less than 500
|-lg/wipe 12
4. False negative probabilities for DataChem average concentrations at a target concentration level of 40
|-lg/wipe 14
5. False negative probabilities for DataChem average concentrations at a target concentration level of
250 |_lg/wipe 15
6. False negative probabilities for DataChem average concentrations at a target concentration level of
400 |_lg/wipe 15
7. Plot of the PDV 5000 average concentrations versus DataChem's average concentrations, for both UC
and ELPAT samples (n=20), shown for concentrations less than 500 |_lg/wipe 19
8. Comparison of the false negative probabilities for MTI PDV 5000 and DataChem at a target
concentration level of 40 |_lg/wipe 20
9. Comparison of the false negative probabilities for MTI PDV 5000 and DataChem at a target
concentration level of 250 |_lg/wipe 21
10. Comparison of the false negative probabilities for MTI PDV 5000 and DataChem at a target
concentration level of 400 |_lg/wipe 21
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List of Tables
1. Summary of DataChem Pre-Test Results 11
2. Summary of DataChem Percent Recovery Values by Sample Source 12
3. Summary of DataChem Precision Estimates by Sample Source 12
4. False Positive/False Negative Results for DataChem Measurements of UC Samples 14
5. Summary of the Linear Regression Constants and Recovery Data for DataChem's Measurements
Versus the Estimated Concentrations at the Clearance Levels 16
6. Precision of the PDV 5000 Analyzer 17
7. Accuracy of PDV 5000 Analyzer 17
8. Linear regression constants for the plots of the PDV 5000 versus the estimated values and versus the
DataChem average measurements 18
9. False Positive/False Negative Results for PDV 5000 Measurements of UC Samples 20
10. Summary of the Linear Regression and Recovery Data for the PDV 5000 Response versus the
Estimated Concentrations 22
11. Estimated analytical costs for lead dust wipe samples 23
12. Performance Summary for the PDV 5000 System 25
VI
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Acknowledgments
The authors wish to acknowledge the support of all those who helped plan and conduct the verification test,
analyze the data, and prepare this report. In particular, we recognize: Patricia Lindsey, Capitol Community
Technical College, for providing a site for the verification test; Sandy Roda (University of Cincinnati) and
Laura Hodson (Research Triangle Institute) for coordination of sample preparation; the inorganic analytical
laboratory in EPA/Region 1 (North Chelmsford, MA) for the analysis of quality control samples; and the
expertise of the technical advisory panel, including Kenn White (American Industrial Hygiene Association),
John Schwemberger, Dan Reinhart, Oksana Pozda, and Darlene Watford (EPA/Office of Pollution
Prevention and Toxics), Paul Carroll (EPA/Region 1), Sharon Harper (EPA/Research Triangle Park), Peter
Ashley, Warren Friedman, Gene Pinzer, and Emily Williams (U.S. Department of Housing and Urban
Development); Paul Halfmann and Sharon Cameron (Massachusetts Childhood Lead Poisoning Prevention
Program), Kevin Ashley (National Institute for Occupational Safety and Health); Walt Rossiter and Mary
McKnight (National Institute of Standards & Technology); Bill Gutknecht (Research Triangle Institute), and
Bruce Buxton (Battelle Memorial Institute). The authors would specifically like to thank Kevin Ashley and
John Schwemberger for serving as peer reviewers of this report. The authors also acknowledge the
participation of Monitoring Technologies International (Colin Green) and Owen Scientific (Felecia Owen).
For more information on the Lead in Dust Wipe Measurement Technology Verification contact:
Eric N. Koglin
Project Technical Leader
Environmental Protection Agency
Environmental Sciences Division
National Exposure Research Laboratory
P.O. Box 93478
Las Vegas, Nevada 89193-3478
(702) 798-2332
koglin.eric@epa.gov
For more information on MTFs PDV 5000, contact:
Colin Green
Monitoring Technologies International
29 Chinthurst Park
Shalford Surrey
GU48JH United Kingdom
phone: 441-483-564183
cgreen@colingreen.idps.co.uk
Roger A. Jenkins
Program Manager
Oak Ridge National Laboratory
Chemical Sciences Division
P.O. Box 2008
Oak Ridge, TN 37831-6120
(865) 574-4871
i enkinsra@ornl. gov
Felecia Owen
Owen Scientific
1609 Ebb Drive
Wilmington, NC 28409
phone: 910-391-5714
foweni@,owenscientific.com
vn
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Abbreviations and Acronyms
AIHA American Industrial Hygiene Association
AMS Advanced Monitoring Systems Center, ETV
ASTM American Society for Testing and Materials
ASV Anodic Stripping Voltammetry
CDC Centers for Disease Control and Prevention
CFR Code of Federal Regulations
CL clearance level of 40, 250, or 400 |_lg/wipe
ELPAT Environmental Lead Proficiency Analytical Testing program
EPA U. S. Environmental Protection Agency
ETV Environmental Technology Verification Program
ETVR Environmental Technology Verification Report
fn false negative result
fp false positive result
ICP-AES Inductively coupled plasma-atomic emission spectrometry
MTI Monitoring Technologies International
NERL National Exposure Research Laboratory, U.S. EPA
NIST National Institute of Standards & Technology
NLLAP National Lead Laboratory Accreditation Program, U.S. EPA
OPPT Office of Pollution Prevention and Toxics, U.S. EPA
ORNL Oak Ridge National Laboratory
QA quality assurance
QC quality control
RSD relative standard deviation
RTI Research Triangle Institute
SD standard deviation
SRM Standard Reference Material
UC University of Cincinnati
Vlll
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Section 1 — Introduction
The U.S. Environmental Protection Agency (EPA)
created the Environmental Technology Verification
Program (ETV) to facilitate the deployment of
innovative or improved environmental technologies
through performance verification and dissemination
of information. The goal of the ETV Program is to
further environmental protection by substantially
accelerating the acceptance and use of improved and
cost-effective technologies. ETV seeks to achieve
this goal by providing high-quality, peer-reviewed
data on technology performance to those involved in
the design, distribution, financing, permitting,
purchase, and use of environmental technologies.
ETV works in partnership with recognized standards
and testing organizations and stakeholder groups
consisting of regulators, buyers, and vendor
organizations, with the full participation of
individual technology developers. The program
evaluates the performance of innovative
technologies by developing verification test plans
that are responsive to the needs of stakeholders,
conducting field or laboratory tests (as appropriate),
collecting and analyzing data, and preparing peer-
reviewed reports. All evaluations are conducted in
accordance with rigorous quality assurance (QA)
protocols to ensure that data of known and adequate
quality are generated and that the results are
defensible.
ETV is a voluntary program that seeks to provide
objective performance information to all of the
participants in the environmental marketplace and to
assist them in making informed technology
decisions. ETV does not rank technologies or
compare their performance, label or list technologies
as acceptable or unacceptable, seek to determine
"best available technology," or approve or
disapprove technologies. The program does not
evaluate technologies at the bench or pilot scale and
does not conduct or support research. Rather, it
conducts and reports on testing designed to describe
the performance of technologies under a range of
environmental conditions and matrices.
The program now operates six centers covering a
broad range of environmental areas. ETV began
with a 5-year pilot phase (1995-2000) to test a wide
range of partner and procedural alternatives in
various technology areas, as well as the true market
demand for and response to such a program. In these
centers, EPA utilizes the expertise of partner
"verification organizations" to design efficient
processes for conducting performance tests of
innovative technologies. These expert partners are
both public and private organizations, including
federal laboratories, states, industry consortia, and
private sector entities. Verification organizations
oversee and report verification activities based on
testing and QA protocols developed with input from
all major stakeholder/customer groups associated
with the technology area. The verification described
in this report was administered by the Advanced
Monitoring Technology (AMT) Center, with Oak
Ridge National Laboratory (ORNL) serving as the
verification organization. (To learn more about
ETV, visit ETV's Web site at
http://www.epa.gov/etv.) The AMT Center is
administered by EPA's National Exposure Research
Laboratory (NERL), Environmental Sciences
Division, in Las Vegas, Nevada.
The verification of a field analytical technology for
measurement of lead in dust wipe samples is
described in this report. The verification test was
conducted in Hartford, Connecticut, from November
5 through November 9, 2001. The performance of
the Monitoring Technologies International (MTI)'s
PDV 5000 trace metal analyzer, an anodic stripping
voltammetry system, was determined under field
conditions. The technology was evaluated by
comparing its results to estimated concentration
values and with results obtained on similar samples
using a recognized laboratory analytical method. For
background information, additional information on
anodic stripping voltammetry for dust wipe analysis
can be found in other published reports (Ashley et
al., 2001).
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Section 2 — Technology Description
In this section, the vendor (with minimal editorial changes by ORNL) provides a description of the
technology and the analytical procedure used during the verification testing activities.
General Technology Description
MTFs PDV5000 is a self-contained anodic
stripping analyzer. Anodic stripping voltammetry
(ASV) works by electroplating metals in solution
onto an electrode. This concentrates the metal.
The metals on the electrode are then sequentially
stripped off, which generates a current that can be
measured. The current (milliamps) is proportional
to the amount of metal being stripped off. The
potential (voltage in millivolts) at which the metal
is stripped off is characteristic for each metal.
This means the metal can be identified as well as
quantified.
The PDV 5000 system is a new type of three-
electrode device. Instead of liquid mercury as the
electrode, this device uses a glassy carbon
electrode that is plated with a very thin film of
mercury (mercury thin film electrode, MTFE).
This is carried out at the beginning of an
analytical run and lasts for between 10 and 30
subsequent analyses. The mercury is contained as
a salt in the supporting buffer used. This means
only a very small amount of mercury is used and
ensures the operator never comes into contact with
liquid mercury. The amount of mercury used per
analysis is measured in parts per billion. If
however the analysis is for arsenic, selenium or
mercury, the glassy carbon electrode is given a
gold film. Ease of use has been the primary
objective in the design. A simple, menu driven
software allows the user to select the metal and
concentration range of interest. Analysis time is
dependent on the metal concentration, but ranges
from a few minutes to 20 minutes for an ultra low
concentration. The initial calibration can be used
for many subsequent "unknown" analyses without
the need for recalibration.
Sample Preparation and Analysis
During the verification test, MTI performed the
following procedure. Fifteen mL of 2M
hydrochloric acid was added to each 20-mL
scintillation vial which contained a dust wipe
sample. The vials were sonicated in a water bath
Figure 1. MTI's PDV 5000 system.
for 20 min. After sonication, 400 |_lL of sample
was added to 20 mL of electrolyte solution, which
was an aqueous solution of sodium chloride,
sodium acetate, and acetic acid. The electrode
was placed in the same, the "run" button was
pushed, and the result was produced in 120 s.
Every fifth analysis was a calibration check. If the
calibration check standard was more than 50%
different than the expected value, the calibration
was re-done and the last sample run before the
calibration check was reanalyzed.
Theory of Operation
The liquid sample is added to the supporting
electrolyte (buffer) to ensure the oxidation states
of the metal ions are optimized for
electrochemistry. This also dilutes the sample,
which removes many of the potentially interfering
compounds. Another component of the buffer
removes any dissolved oxygen in the sample that
would interfere with the analysis.
The analysis proceeds by initially plating the
working electrode with mercury or gold. Several
quick runs with a standard are performed to
stabilize the mercury or gold film and to confirm
the analyzer is working correctly. Each film lasts
between 10 and 30 subsequent analyses. The
diluted sample is then added to the cell and the
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working electrode is given a negative potential
relative to the reference electrode. The value can
be varied depending on which metals are to be
analyzed. The negative potential attracts the
positive metal ions to it, where electrons combine
with the metal ions to produce the metal. The use
of the mercury film enhances the process as when
the metal ion is reduced to the metallic state, it
forms an amalgam with the mercury, which
stabilizes it during the stripping phase. Mercury
on glassy carbon also has a high over potential
relative to hydrogen. This means the potential can
be set that allows metals such as zinc to be plated
onto the electrode, without producing hydrogen
gas. Hydrogen is very reducing and will interfere
with the subsequent stripping. The potential is
then held for around 60 seconds (up to 300 in
some applications) while the metal ions
accumulate on the electrode, effectively
concentrating the sample.
During the plating process, the sample is mixed at
high speed. This ensures that the metal ion
concentration at the electrode/sample interface is
the same as the concentration in the bulk sample.
This also helps prevent a capacitive buildup on the
electrode where a layer of positive ions shield the
negative electrode from other ions in the sample.
By ensuring the negative potential is the dominant
factor during the analysis, the reproducibility of
the analysis is dramatically improved. An added
bonus is the complex mathematical formula used
to calculate the amount of metal deposited for a
given time at a given potential is simplified.
The potential is then allowed to become less
negative and the metals re-oxidize (or are stripped
from the electrode), which generates electrons.
Each metal will strip from the electrode at a
specific potential, which allows for identification
of a metal. The rate at which the potential is
changed is called the sweep rate and is another
variable that can be altered to optimize an
analysis. The faster the sweep rate (mV/sec), the
better the resolution. However, sensitivity is
lowered because, at high sweep rates, the metals
on the electrode have a much shorter time to strip
off, giving less chance for the peaks to overlap. A
slow sweep rate allows more metal to strip off,
giving a larger signal, but conversely increases the
noise on the baseline, potentially masking the
metal of interest. By applying different waveforms
to the sweep, stripping potentials can be shifted,
which is useful when 2 metals of interest strip at a
similar potential.
The generation of electrons is measured by the
counter electrode as a current produced in the cell.
The current in micro- or nano-amps is
proportional to the metal concentration on the
electrode. As each metal strips from the electrode,
a graph is produced showing a series of peaks
corresponding to current (metal concentration) at
specific potentials. By selecting a potential
"window" where a specific metal is expected to
appear, ASV can be used to identify and quantify
the metal concentration in the sample.
The instrument can be used to detect and quantify
other metals (As, Cd, Cr, Cu, Au, Fe Mn, Hg Ni,
Ag, Sn , Zn, Co), but the performance of the
instrument was only verified for lead in this test.
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Section 3 — Verification Test Design
Objective
The purpose of this section is to describe the
verification test design. It is a summary of the test
plan (ORNL, 2001).
Testing Location and Conditions
The verification of field analytical technologies for
lead in dust wipes was conducted at the Capitol
Community Technical College in Hartford,
Connecticut. The test was conducted in the
basement of a classroom building. The temperature
and relative humidity were monitored during field
testing, but remained fairly constant. The average
temperature and relative humidity over the four days
of testing were 68 °F and 32%, respectively.
Drivers and Objectives for the Test
The purpose of this test was to evaluate the
performance of field analytical technologies that are
capable of analyzing dust wipe samples for lead
contamination. This test provides information on the
potential applicability of field technologies to EPA
standards for dust clearance testing. The
experimental design was designed around the three
clearance standards of 40 |-lg/ft2 for floors, 250
|~lg/ft2 for window sills, and 400 |-lg/ft2 for window
troughs that are outlined in 40 CFR Part
745.227(e)(8)(viii) (CFR, 2001).
The primary objectives of this verification were to
evaluate the field analytical technologies in the
following areas: (1) how well each performs relative
to a conventional, fixed-site analytical method for
the analysis of dust wipe samples for lead; (2) how
well each performs relative to results generated in
previously rounds of ELPAT testing (described in
the next section), and (3) the logistical and
economic resources necessary to operate the
technology. Secondary objectives for this
verification were to evaluate the field analytical
technology in terms of its reliability, ruggedness,
cost, range of usefulness, sample throughput, data
quality, and ease of use. Note that this verification
test does not provide an assessment of the selection
of locations for dust samples in a facility or an
assessment of the way that dust samples are
collected. The planning for this verification test
follows the guidelines established in the data quality
objectives process.
Summary of the Experimental
Design
All of the samples analyzed in this verification test
were prepared gravimetrically. At the time of the
test, both of the wipes utilized in the test
(PaceWipe™ and Aramsco LeadWipe™) were on
the list of wipes recommended for lead testing by
the American Society for Testing and Materials
(ASTM, 1996). Initial consideration was given to
conducting the test in a real-world situation, where
the technologies would have been deployed in a
housing unit that had been evacuated due to high
levels of lead contamination. In addition to the
safety concern of subjecting participants to lead
exposure, the spatial variability of adjacent samples
would have been so great that it would be much
larger than the expected variability of these types of
technologies, thereby making it difficult to separate
instrument/method variability and sampling
variability. The availability of well-characterized
samples derived from "real-world" situations made
the use of proficiency testing samples (so-called
"ELPAT" samples) and other prepared samples an
attractive alternative.
ELPAT and Blank Sample
Description
In 1992, the American Industrial Hygiene
Association (AIHA) established the Environmental
Lead Proficiency Analytical Testing (ELPAT)
program. The ELPAT Program is a cooperative
effort of the American Industrial Hygiene
Association (AIHA), and researchers at the Centers
for Disease Control and Prevention (CDC), National
Institute for Occupational Safety and Health
(NIOSH), and the EPA Office of Pollution
Prevention and Toxics (OPPT). The ELPAT
program is designed to assist laboratories in
improving their analytical performance, and
therefore, does not specify use of a particular
analytical method. Participating laboratories are
sent samples to analyze on a quarterly basis. The
reported values must fall within a range of
acceptable values in order for the laboratory to be
deemed proficient for that quarter.
Research Triangle Institute (RTI) in Research
Triangle Park, NC, is contracted to prepare and
distribute the lead-containing paint, soil, and dust
wipe ELPAT samples. For the rounds of testing
-------
which have occurred since 1992, archived samples
are available for purchase. Some of these samples
were used in this verification test. Because the
samples have already been tested by over one-
hundred laboratories, a certified concentration value
is supplied with the sample. This certified value
represents a pooled measurement of all of the results
submitted, with outliers excluded from the
calculation.
The following description, taken from an internal
RTI report, briefly outlines how the samples were
prepared. RTI developed a repository of real-world
housedust, collected from multiple homes in the
Raleigh/Durham/Chapel Hill area, as well as from
an intervention project in Wisconsin. After
collection, the dust was sterilized by gamma
irradiation, and sieved to 150 |_lm. A PaceWipe™
was prepared for receiving the dust by opening the
foil pouch, removing the wet folded wipe and
squeezing the excess moisture out by hand over a
trash can. The wipe was then unfolded and briefly
set on a Kimwipe™ to soak up excess moisture.
The PaceWipe was then transferred to a flat plastic
board to await the dust. After weighing a 0.1000 ±
0.0005 g portion of dust on weighing paper, the pre-
weighed dust was gently tapped out onto the
PaceWipe. The wipe was then folded and placed in
a plastic vial, which was then capped. All vials
containing the spiked wipes were stored in a cold
room as a secondary means of retarding mold
growth until shipment.
Before use in the ELPAT program, RTI performed a
series of analyses to confirm that the samples were
prepared within the quality guidelines established
for the program. The data quality requirements for
the ELPAT samples were: 1) the relative standard
deviation of the samples analyzed by RTI must be
10% or less; 2) the measured concentrations must be
within 20% of the target value that RTI was
intending to prepare; and 3) analysis by an
accredited laboratory must yield results within ±
20% of the RTI result. Ten samples were analyzed
by RTI and nine samples were sent to the Wisconsin
Occupational Health Laboratory for independent,
confirmatory analysis. All ELPAT samples used in
this test met the data quality requirements described
above. The estimated concentration for an ELPAT
sample used in this evaluation was the certified
("consensus") value (i.e., an analytically derived
result).
RTI prepared the blank samples using the same
preparation method as the ELPAT samples, but the
concentration of lead was approximately < 2
|J,g/wipe, well below the expected reporting limits of
the participant technologies.
University of Cincinnati Sample
Description
The ELPAT samples consisted of dust mounded in
the center of a PaceWipe. The University of
Cincinnati (UC) prepared "field QC samples" where
the dust was sprinkled over the wipe, more similar
to how a wipe would look when a dust wipe sample
is collected in the field. In a typical scenario, UC
sends these control samples to a laboratory along
with actual field-collected samples as a quality
check of the laboratory operations. Because the
samples are visually indistinguishable from an
actual field sample, are prepared on the same wipe,
and are shipped in the same packaging, the
laboratory blindly analyzes the control samples.
This provides the user with an independent
assessment of the quality of the laboratory's data.
A cluster of twenty UC samples prepared at the key
clearance levels were added to the experimental
design, primarily so that an abundance of data
would exist near the clearance levels, in order to
assess false positive and false negative error rates.
For MTI, the UC samples were prepared on
Aramsco LeadWipes™. The UC wipe samples
were prepared using National Institute of Standards
& Technology (NIST) Standard Reference Materials
(SRMs). NIST SRM 2711 was used to prepare the
40 |_lg/wipe samples, and NIST SRM 2710 was used
to prepare the 250 and 400 |_lg/wipe samples. Both
SRM 2711 and SRM 2710 are Montana Soil
containing trace concentrations of multiple
elements, including lead. Some NIST SRM
materials that are spiked on dust wipes are known to
have low extraction recoveries when prepared by
standard analytical methods (e.g., lead silicates
cannot be extracted unless hydrofluoric acid is used)
(Ashley et al., 1998). These particular SRMs are not
known to contain lead silicates or to give lower lead
recoveries. However, it is important to note the
possibility of such when using NIST SRMs for lead
dust wipe analysis, since similar SRMs (e.g.,
Buffalo river sediment from Wyoming) do show
recoveries in the low 90% range (Ashley et al.,
1998).
-------
Because accurate and precise estimated
concentrations for the UC samples were imperative,
ORNL imposed the following data quality
requirements for the UC-prepared wipe samples: 1)
each estimated concentration had to be within a ±
10% interval of the target clearance level; 2)
additional quality control (QC) samples (at least 5%
of the total samples ordered) were to be prepared
and analyzed by UC as a quality check prior to
shipment of the samples; and 3) the relative standard
deviation of the QC samples had to be < 10%. It is
important to note here the reason why the data
quality requirements between the UC and ELPAT
samples were different. The data quality
requirements for the ELPAT samples (i.e., ± 20% of
the target value) were established by the ELPAT
program. Since archived samples were being used,
those data quality requirements could not be
changed.
As a quality check of the sample preparation
process, UC prepared an additional 24 samples (5%
of the total number ordered). UC extracted and
analyzed the samples following internal procedures
(nitric/hydrochloric acid extraction, followed by
atomic absorption spectrometry - see EPA, 1996 for
Method 3 05 OB and Method 601 OB) and provided
those results to ORNL. For the 24 samples (eight at
each of the three clearance levels), the average
percent recovery (i.e., UC measured
concentration/UC estimated concentration x 100%)
was 97% (median value = 96%, standard deviation =
3%, range = 93% to 102%). (102%), but both values
within the data quality r Additionally, 42 randomly-
selected samples (14 at each of the three clearance
levels) were analyzed by the EPA Region 1
laboratory in North Chelmsford, MA, as an
independent quality control check of the accuracy
and precision of UC's sample preparation procedure
(nitric acid digestion followed by ICP/AES analysis
- see EPA, 1996). The average percent recovery
(EPA Region 1 reported concentration/UC estimated
concentration x 100%) was 90% (median 89%,
standard deviation = 2%), with a range of values
from 86% to 93%. The average recovery determined
from the EPA Region 1 analyses (90%) was lower
than that which was determined by UC (102%), but
both values met the data quality requirement of 100
± 10%. Based on these data, ORNL determined that
the UC sample preparation process met the
established data quality criteria and was deemed
acceptable for use in the determination of false
positive/false negative error rates.
Distribution and Number of Samples
A total of 160 samples were analyzed in the
verification test. Figure 2 is a plot containing the
distribution of the sample concentrations that were
analyzed in this study. Twenty samples were
prepared by the University of Cincinnati at +/- 10%
of each of the three clearance levels (3 test levels x
20 samples = 60 samples total). Research Triangle
Institute prepared 20 "blanks" at lead concentrations
< 2 |J,g/wipe. These samples are noted as such in
Figure 2. The remaining samples in Figure 2 are
ELPAT samples. For most of the ELPAT samples,
four samples were analyzed at each concentration
level (16 test levels x 4 samples each = 64 samples
total). There were two concentration levels (at 49
and 565 |-lg/wipe) where eight samples were
analyzed. While the set of samples at each
concentration level were prepared using
homogeneous source materials and an identical
preparation procedure, ELPAT samples cannot be
considered true "replicates" because each sample
was prepared individually. However, these samples
represent four samples prepared similarly at a
specified target concentration, with an estimated
value calculated from more than 100 analyses of
similarly prepared samples.
Sample Randomization
The samples were packaged in 20-mL plastic
scintillation vials and labeled with a sample
identifier. Each participant received the same suite
of samples, but in a randomized order. The samples
were distributed in batches of 16. Completion of
chain-of-custody forms documented sample transfer.
Description of Performance Factors
In Section 5, technology performance is described in
terms of precision, accuracy, completeness, and
comparability, which are indicators of data quality
(EPA, 1996). False positive and negative results,
sample throughput, and ease of use are also
described. Each of these performance characteristics
is defined in this section.
-------
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Estimated Concentrations of Test Samples (ug/wipe)
Figure 2. Distribution of concentration levels.
Precision
Precision is the reproducibility of measurements
under a given set of conditions. Standard deviations
estimated at each concentration level can be used to
establish the relationship between the uncertainty
and the average lead concentration. Standard
deviation (SD) and relative standard deviation
(RSD) for replicate results are used to assess
precision, using the following equation:
RSD = (SD/average concentration) x 100% .
(Eq. 1)
The overall RSD is characterized by two summary
values:
• mean — i.e., average;
• range — i.e., the highest and lowest RSD values
that were reported.
The average RSD may not be the best representation
of precision, but it is reported for convenient
reference. An average RSD value less than 10%
indicates very precise measurements. RSDs greater
than 20% should be viewed as indicators of larger
variability and possibly non-normal distributions.
Accuracy
Accuracy is a measure of how close the measured
lead concentrations are to estimated values of the
true concentration. The estimated values for the
ELPAT samples are the certificate values that are
reported on the certificate of analysis sheet provided
with the samples. The ELPAT certified values
represent an average concentration determined by
more than 100 accredited laboratories that
participated in previous rounds of ELPAT testing.
The UC estimated value is the concentration
reported by UC for individual samples, calculated
by the amount of NIST-traceable material loaded on
the dust wipes. The accuracy and precision of the
UC value was assessed by an independent
laboratory analyzing randomly selected QC samples.
An EPA laboratory in Region 1 analyzed 10% of the
total number of samples prepared by UC at each of
the three concentration levels and confirmed that the
process used to prepare the samples met the pre-
determined data quality objective of accuracy within
a ± 10% interval of the estimated value.
Accuracy of the field technology measurements was
statistically tested using t-tests or non-parametric
tests at the 5% significance level. These statistical
tests compared the average results with the overall
estimated values using the precision of the sample
-------
measurements. Bias was quantified by computing
the percent recovery for four similar samples or a
single sample using the equation:
percent recovery = [measured amount(s)/estimated
value] x 100% (Eq. 2)
Accuracy was assessed using both the ELPAT and
UC estimated concentrations. The comparison to the
ELPAT value represents how close the technology
reported results to the consensus value, which
represents the amount of "recoverable" lead in the
sample. Because the UC samples were prepared
gravimetrically from samples of known lead content,
the comparison to the UC samples represents how
close the technology reported results to an absolute
lead value. Comparison to the gravimetric values
reveals any bias imposed by the tested sampling and
analytical method.
The optimum percent recovery value is 100%.
Percent recovery values greater than 125% indicate
results that are biased high, and values less than
75% indicate results that are biased low. A small but
statistically significant bias may be detectable for a
field technology if precision is high (i.e., low
standard deviation). The field technology can still
have acceptable bias with an average percent
recovery in the interval of 75% to 125%. Bias
within the acceptable range can usually be corrected
to 100% by modification of calibration methods.
Comparability
Comparability refers to how well the field tech-
nology and the NLLAP-recognized laboratory data
agree. The difference between accuracy and
comparability is that accuracy is judged relative to a
known value, comparability is judged relative to the
results of a laboratory procedure, which may or may
not report the results accurately. Because true
"replicates" were not available for use in this study,
the averages from similar samples measured by the
technology was compared with corresponding
averages measured by the laboratory for all target
concentration levels.
A correlation coefficient quantifies the linear
relationship between two measurements (Draper and
Smith, 1981). The correlation coefficient is denoted
by the letter r; its value ranges from -1 to +1, where
0 indicates the absence of any linear relationship.
The value r = -1 indicates a perfect negative linear
relation (one measurement decreases as the second
measurement increases); the value r = +1 indicates a
perfect positive linear relation (one measurement
increases as the second measurement increases).
Acceptable r values are 0.990 or greater. The slope
of the linear regression line, denoted by the letter m,
is related to r. Whereas r represents the linear
association between the vendor and laboratory
concentrations, m quantifies the amount of change
in the vendor's measurements relative to the
laboratory's measurements. A value of+1 for the
slope indicates perfect agreement. Values greater
than 1 indicate that the vendor results are generally
higher than the laboratory, while values less than 1
indicate that the vendor results are usually lower
than the laboratory.
Detectable Blanks
Twenty samples in the test were prepared at <2
|J,g/wipe, below the anticipated reporting limits of
both the field technologies and the laboratory. Any
reported lead for these samples is considered a
"detectable blank". Performance was also assessed
at concentrations near the reporting limits of the
technology.
False Positive/Negative Results
A false positive (fp) result is one in which the
technology detects lead in the sample above a
clearance level when the sample actually contains
lead below the clearance level (Keith et al., 1996). A
false negative (fn) result is one in which the
technology indicates that lead concentrations are
less than the clearance level when the sample
actually contains lead above the clearance level. For
example, if the technology reports the sample
concentration to be 35 |-lg/wipe, and the true
concentration of the sample is 45 |-lg/wipe, the
technology's result would be considered a fn at the
40 |-lg/wipe clearance level. Accordingly, if the
technology reports the result as 45 |-lg/wipe and the
true concentration is 35 |-lg/wipe, the technology's
result would be a fp at the 40 |-lg/wipe clearance
level.
A primary objective for this verification test was to
assess the performance of the technology at each of
the three clearance levels of 40, 250, and 400
|J,g/wipe, and estimate the probability of the field
technology reporting a fp or fn result. For each
clearance level, the probabilities of fn were
estimated as curves that depend on a range of
-------
concentrations reported about the clearance level.
These error probability curves were calculated from
the results on the 60 UC samples at concentrations ±
10% of each clearance level. In order to generate
probability curves to model the likelihood of false
negative results, it was assumed that the estimated
concentration provided by UC was the true
concentration. However, this evaluation did not
include the gravimetric preparation uncertainty in
the UC estimated concentration. This error is likely
to be much smaller than other sources of
measurement error (e.g., extraction efficiency and
analytical).
The fp/fn evaluation also included a comparison to
the ELPAT sample results. The "estimated" value
for the UC and ELPAT samples are defined
differently. The UC value is based on weight of the
NIST-traceable material, while the ELPAT
estimated value is the average analytical reported
value from more than 100 accredited laboratories.
The UC sample estimated lead content is determined
gravimetrically, which should be closer to the "true"
concentration than an analytical measurement that
includes preparation and instrumental errors. In
contrast, determining the technology's fp/fn error
rates relative to the ELPAT estimated
concentrations represents a comparison to typical
laboratory values. One limitation of using the
ELPAT sample is that concentrations covered a
wider overall distribution of lead levels. Thus, the
availability of sample concentrations that were
tightly (i.e., +/- 10%) clustered about the clearance
levels was limited. In order to perform a broader
fp/fn analysis, the range of lead levels in the ELPAT
samples that bracketed the pertinent clearance levels
was extended to ± 25% of the target concentration.
Completeness
Completeness is defined as the percentage of
measurements that are judged to be usable (i.e., the
result is not rejected). An acceptable completeness
is 95% or greater.
Sample Throughput
Sample throughput is a measure of the number of
samples that can be processed and reported by a
technology in a given period of time. Sample
throughput is reported in Section 5 as number of
samples per day per number of analysts.
Ease of Use
A significant decision factor in purchasing an
instrument or a test kit is how easy the technology is
to use. Several factors are evaluated and reported on
in Section 5:
• What is the required operator skill level (e.g.,
technician or advanced degree)?
• How many operators were used during the test?
• Could the technology be run by a single person?
• How much training would be required in order
to run this technology?
• How much subjective decision-making is
required?
Cost
An important factor in the consideration of whether
to purchase a technology is cost. Costs involved
with operating the technology and a typical
laboratory analyses are estimated in Section 5. To
account for the variability in cost data and
assumptions, the economic analysis is presented as a
list of cost elements and a range of costs for sample
analysis. Several factors affect the cost of analysis.
Where possible, these factors are addressed so that
decision makers can independently complete a site-
specific economic analysis to suit their needs.
Miscellaneous Factors
Any other information that might be useful to a
person who is considering purchasing the
technology is documented in Section 5 under
"Observations". Examples of information that might
be useful to a prospective purchaser are the amount
of hazardous waste generated during the analyses,
the ruggedness of the technology, the amount of
electrical or battery power necessary to operate the
technology, and aspects of the technology or method
that make it user-friendly or user-unfriendly.
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Section 4 — Laboratory Analyses
Background
EPA regulations (40 CFRPart 745.227(e)(8)(vii))
specify that residences and child occupied facilities
built before 1978 that have undergone an abatement
must pass clearance testing (CFR 2001). These EPA
regulations also state in 40 CFR Part 745.227(f)(2)
that dust samples for clearance must be analyzed by
a laboratory recognized by EPA (CFR 2001). Many
EPA-authorized state and tribal lead programs have
the same or similar requirements. EPA's vehicle for
recognizing laboratory proficiency is the National
Lead Laboratory Accreditation Program (NLLAP).
Although the NLLAP was initially designed to
accredit fixed site laboratories, in August 1996 the
NLLAP was modified so that mobile laboratory
facilities and testing firms operating portable testing
technologies could also apply for accreditation.
Despite this modification, the NLLAP list of
accredited laboratories has almost exclusively
consisted of fixed site laboratories. One possible
outcome of this ETV test is that more mobile
laboratory facilities and testing firms operating
portable testing technologies will apply for NLLAP
accreditation. In order to assess whether the field
portable technologies participating in this
verification test produce results that are comparable
to NLLAP-recognized data, an NLLAP-recognized
laboratory was selected to analyze samples
concurrently with the field testing.
NLLAP Laboratory Selection
NLLAP was established by the EPA Office of
Pollution Prevention and Toxics under the
legislative directive of Title X, the Lead-Based Paint
Hazard Reduction Act of 1992. In order for
laboratories to be recognized under the NLLAP,
they must successfully participate in the ELPAT
Program and undergo a systems audit. The
acceptable range for the ELPAT test samples is
based upon the reported values from participating
laboratories. Acceptable results are within three
standard deviations from the consensus value. A
laboratory's performance is rated as proficient if
either of the following criteria are met: (1) in the last
two rounds, all samples are analyzed and the results
are 100% acceptable; or (2) three-fourths (75%) or
more of the accumulated results over four rounds are
acceptable.
The NLLAP required systems audit must include an
on-site evaluation by a private or public laboratory
accreditation organization recognized by NLLAP.
Some of the areas evaluated in the systems audit
include laboratory personnel qualifications and
training, analytical instrumentation, analytical
methods, quality assurance procedures, and record
keeping procedures.
The list of recognized laboratories is updated
monthly. ORNL obtained the list of accredited
laboratories in July 2001. The list consisted of
approximately 130 laboratories. Those laboratories
which did not accept commercial samples and those
located on the U.S. west coast were automatically
eliminated as potential candidates. ORNL
interviewed at random approximately ten
laboratories and solicited information regarding
cost, typical turnaround time, and data packaging.
Based on these interviews and discussions with
technical panel members who had personal
experience with the potential laboratories, ORNL
selected DataChem (Cincinnati, OH) as the fixed-
site laboratory. As a final qualifying step, DataChem
blindly analyzed 16 samples (8 ELPAT and 8
prepared by UC) in a pre-test study. As shown in
Table 1 below, DataChem passed the pre-test by
reporting concentrations that were within 25% of
the estimated concentration for samples above the
reporting limit.
Laboratory Method
The laboratory method used by DataChem was hot
plate/nitric acid digestion, followed by inductively
coupled plasma-atomic emission spectrometry (ICP-
AES) analysis. The preparation and analytical
procedures, as supplied by DataChem, can be found
in the test plan (ORNL, 2001). To summarize the
procedure, the wipe was digested in 2 mL of nitric
acid, heated in a hotblock for 1 hour at 95 °C,
diluted to 20 mL with distilled water, and analyzed
by ICP-AES. DataChem's procedures are
modifications of Methods 3 05 OB and 601 OB of EPA
SW-846 Method Compendium for the preparation
and analysis of metals in environmental matrices
(EPA, 1996). Other specific references for the
preparation and analysis of dust wipes are available
from the American Society for Testing and
Materials (ASTM, 1998).
10
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Table 1. Summary of DataChem Pre-Test Results
Sample
Type
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
UC
UC
UC
UC
UC
UC
UC
UC
DataChem
Reported Cone
(|J,2/wipe)
<20
<20
41
44
190
210
440
450
<20
<20
25
38
150
200
250
310
Estimated
Cone
(|J,2/wipe)
2.12
2.12
41.3
41.3
201.6
201.6
408.7
408.7
10.3
5.9
29.9
44
172.4
237.5
327.3
379
Percent
Recovery
n/a
n/a
99%
107%
94%
104%
108%
110%
n/a
n/a
84%
86%
87%
84%
76%
82%
Analysis
Order
16
12
6
3
15
9
2
13
4
1
14
10
11
7
5
8
Laboratory Performance
ORNL validated all of the laboratory data according
to the procedure described in the verification test
plan (ORNL, 2001). During the validation, the
following aspects of the data were reviewed:
completeness of the data package, correctness of the
data, correlation between "replicate" sample results,
and evaluation of QC sample results. Each of these
categories is described in detail in the verification
test plan. An evaluation of the performance of the
laboratory results through statistical analysis of the
data was performed and is summarized below. (See
Section 3 for a detailed description of how the
performance factors are defined and the calculations
that are involved.)
In Table 2, DataChem's reported values are
compared to the estimated values to determine
percent recovery (i.e., accuracy of the DataChem
results) for both the ELPAT and the UC samples.
The results are also shown graphically in Figure 3.
The average percent recovery for the ELPAT
samples was 98%, while the average for the UC
samples was 91%. Both Table 2 and Figure 3
indicate that the analytical results from the
University of Cincinnati wipe samples were
generally reported lower than the estimated value,
while the results for the ELPAT samples were closer
to the estimated value. The better agreement with
the ELPAT samples is not unexpected, given that
the ELPAT estimated concentrations represent
analytical consensus values that include typical
extraction inefficiencies and instrumental error.
The negative bias observed with the UC and the
ELPAT samples was statistically significant. The
cause of the negative bias for the UC samples could
be related to: 1) extraction inefficiencies (due to the
use of NIST SRMs that contain lead that is
unrecoverable with the extraction procedure which
was used) and/or, 2) typical analytical variation due
to preparation and measurement errors. Another
indication of accuracy is the number of individual
ELPAT results which were reported within the
acceptance ranges that have been established for
those samples. For the 72 ELPAT samples (> 20
|-lg/wipe), DataChem reported 71 (99%) within the
acceptable ranges of values.
The precision assessment presented in Table 3
indicates that the analyses were very precise. The
average RSD for the ELPAT samples was 7%, while
the average RSD for the UC samples was 8%. The
variability of the UC sample preparation process,
provided for reference of the minimal achievable
RSD for the UC samples, was 6%. A single
estimate of the ELPAT variability was not
determined, since the ELPAT samples were
comprised of 20 different batches of samples.
DataChem reported all 20 detectable blank samples
correctly as < 20 |_lg/wipe. In addition, DataChem
reported seven of the eight samples with estimated
concentrations of either 16.9 |_lg/wipe or 17.6
|-lg/wipe as less than their reporting limit of 20
|-lg/wipe and only one was incorrectly reported as 30
|-lg/wipe.
11
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Table 2. Summary of DataChem Percent Recovery Values by Sample Source
Statistic
n a
average % recovery
standard deviation
minimum % recovery
maximum % recovery
ELPAT
72
98
9
81
143
uc
60
91
o
J
86
102
1 excludes estimated values <20 jig/wipe (n=28)
~£i
^s,
_s
>•
S
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An important evaluation parameter for the analysis
of dust wipe samples is how the method performs at
the clearance levels and the method's likelihood of
reporting false positive (fp) and false negative (fn)
results. Recall from the experimental design that 20
UC samples were prepared at ± 10% of each
clearance level of 40, 250, and 400 |-lg/wipe, for a
total of 60 UC samples. The ELPAT samples
covered a wider range of concentrations. There was
a total of 40 ELPAT samples that fell within a ±25%
interval of the target values that could be used for the
fp/fn assessment. The number of false negative and
false positive results reported by DataChem relative
to the UC and ELPAT estimated concentrations is
summarized in Table 4. There are a specific number
of possible fp and fn results. For example, if the
estimated lead level on the wipe is less than the
clearance level (CL), then it is not possible to
produce a false negative result; only a false positive
(i.e., > 40) result is possible. For the UC samples, in
every case where the estimated concentration was
less than the CL, DataChem reported a result for that
was also less than the CL, indicating no fp results at
any of the three CL. DataChem reported two fp
results for the ELPAT samples out of a possible 12.
When the estimated concentration was above the
clearance level, however, DataChem sometimes
reported results as less than the clearance level.
DataChem reported a higher rate of fn results for the
UC samples than the ELPAT samples (23 of 30 vs 7
of 28 possible fn results, respectively). This finding
is not surprising, since the results reported above
indicated that DataChem's results were negatively
biased, or reported lower than the estimated values
for the UC samples. As stated in Section 3, it is
important to note that in this evaluation, the
estimated concentration of the UC samples is
assumed to be the "true"concentration, and the
uncertainty in gravimetric preparation for the UC
estimated concentration is not considered in the
evaluation.
Figures 4, 5, and 6 show models of the likelihood of
DataChem reporting a false negative result at each of
the clearance levels versus the true concentrations of
the UC samples. (Note that only the UC samples
must be used in generation of probability curves
because these estimated values are a closer
representation of the true lead concentration than the
ELPAT estimated concentration. See Song et al.,
2001.) These figures indicate that the likelihood of
DataChem reporting false negative results for the UC
samples at the exact clearance level is high, near
100% in all three cases. This means, for example,
that if DataChem reported a value as exactly 250
|-lg/wipe, the probability that the true concentration
is >250 is essentially 100%. Again, this is due to the
negative bias that was observed in the measurement
of the UC samples. The plots also demonstrate that,
due to the relatively high level of precision of results
reported by DataChem, the performance is very
minimally impacted by performing replicate
analyses, as the distribution of false negative
probabilities is very similar whether 1 or 5
measurements (in Figures 4, 5, and 6, delineated as
N = 1, N = 2, etc.) are performed. The interpretation
of these curves for use in a "real-world" situation
can be demonstrated by the following example.
Suppose that a user decides that an acceptable level
of risk for having false negative results is 5%. Using
Figure 4, 5% FN probability (y = 0.05) corresponds
to a "true" lead concentration of 46 |-lg/wipe
(meaning if the true concentration of the sample is
46 |-lg/wipe, there is only a 5% chance/risk that
DataChem will report the value as < 40 |-lg/wipe.)
By plotting DataChem's measured values versus the
estimated concentrations, the equations of the linear
regression lines can be calculated for each of the
three CL. The slope, intercept, and correlation
coefficient for the ELPAT and UC samples are
presented in Table 5. The user might like to know at
what reported value (and at what associated
probability) will DataChem be likely to report a
"clean" sample (i.e., there is a high probability that
the true concentration is < CL). For example, for the
UC samples, we know that a value reported by
DataChem as 39 |-lg/wipe is biased low and will have
a true concentration of > 40 (41.8 |-lg/wipe, using the
linear regression equation in Table 5). A true
concentration of 40 |-lg/wipe for a UC sample would
correspond to a reported value rounded to the nearest
whole number of 37 |-lg/wipe (see Table 5). For an
ELPAT sample, a true concentration of 40 |-lg/wipe
corresponds to a DataChem reported value of 40
|J,g/wipe, because the negative bias was not as large
for the ELPAT samples. Estimates of the reported
concentration at the 250 and 400 |-lg/wipe levels are
reported in Table 5. In both cases, the reported
concentrations for the ELPAT samples are higher
(i.e., closer to the clearance level) than those of the
UC samples.
The user is reminded that the data obtained during
this verification test represent performance at one
13
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point in time. The data produced by DataChem at
some other time after the writing of this report may
or may not be similar to what has been produced
here. To understand a method's performance at
critical clearance levels, it is recommended that the
user perform their own assessment of the method's
performance by including samples of known
concentration (at or near the clearance levels) along
with the analysis of "real-world" samples.
Table 4. False Positive/False Negative Results for DataChem Measurements of UC Samples
Evaluation Parameter
fp: # samples where
DataChem reported the result
as > CL a of the # samples
where the estimated
concentration was < CL
fn: # samples where
DataChem reported the result
as < CL of the # samples
where the estimated
concentration was > CL
Sample
Source
UC
ELPAT
UC
ELPAT
Number of Samples
40 |_lg/wipe
Oof 9
Oof 4
5 of 11
lof 12
250 |J,g/wipe
Oof 11
2 of 8
9 of 9
5 of 8
400 |J,g/wipe
Oof 10
OofOb
9 of 10
lof 8
Total
Oof 30
2 of 12
23 of 30
7 of 28
a CL = clearance level
b Because all eight ELPAT values were above 400 |_ig/wipe,
no samples were available to assess fp results at this level.
True Pb Concentration (ug/wipe)
Figure 4. False negative probabilities for DataChem average concentrations at a target
concentration level of 40 |ig/wipe.
14
-------
250
260
270
280
290
300
310
320
True Pb Concentration (ug/wipe)
Figure 5. False negative probabilities for DataChem average concentrations at a target
concentration level of 250 |_ig/wipe.
0.0 -I
400
410 420 430 440 450 460 470 480 490 500
True Pb Concentration (ug/wipe)
Figure 6. False negative probabilities for DataChem average concentrations at a
target concentration level of 400 |ig/wipe.
15
-------
Table 5. Summary of the Linear Regression Constants and Recovery Data for DataChem's
Measurements Versus the Estimated Concentrations at the Clearance Levels
Evaluation Parameter
n
slope
intercept
correlation coefficient
average % recovery
SD of % recovery
Reported concentration at
theCL
40 |_lg/wipe
UC
20
1.021
-3.673
0.884
93%
4%
37
l-ig/wipe
ELPAT
16
1.612
-6.182
0.840
101%
13%
40
l-ig/wipe
250 |J,g/wipe
UC
20
0.829
18.557
0.879
90%
3%
226
l-ig/wipe
ELPAT
16
0.578
90.826
0.549
96%
9%
234
l-ig/wipe
400 |J,g/wipe
UC
20
0.736
67.649
0.861
91%
3%
362
l-ig/wipe
ELPAT
8
2.394
-575.771
0.492
100%
5%
382
l-ig/wipe
16
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Section 5 — Technology Evaluation
Objective and Approach
The purpose of this section is to present a statistical
evaluation of the PDV 5000 data and determine the
technology's ability to measure lead in dust wipe
samples. This section includes an evaluation of
comparability through a one-to-one comparison with
NLLAP-recognized laboratory data. Other aspects of
the technology (such as accuracy, precision, cost,
sample throughput, hazardous waste generation, and
logistical operation) are also evaluated in this section.
The Appendix contains the raw data provided by the
vendor during the verification test that were used to
assess the performance of the PDV5000.
Precision
Precision is the reproducibility of measurements
under a given set of conditions. Precision was
determined by examining the results of blind analyses
for replicate samples with estimated concentrations
greater than 30 |_lg/wipe (see "Detectable Blanks"
section below for explanation of why sample
concentrations below 30 |_lg/wipe were not included).
For the ELPAT samples, precision was measured on
each set of four samples from a particular round of
archived samples. For the 17 sets of samples, the
PDV 5000's average RSD value was 22%, with a
range from 6 to 44%, indicating that the PDV 5000's
precision was higher than acceptable levels of
variability of < 20% stated in Section 3. For the UC
samples, 20 samples were analyzed at each of three
target concentration levels of 40, 250, and 400
|J,g/wipe. The average precision of the UC sample
measurements by the PDV 5000 was 21% RSD
(excluding two outliers where MTI reported a 40 and
250 |_lg/wipe samples as non-detects). With the
expectation that UC was to prepare the samples as
close to the target concentrations as possible, the
allowable variability was 10% RSD. As presented in
Table 6, the actual variability of the UC preparation
process was an average of 6% RSD.
Accuracy
Accuracy represents the closeness of the PDV 5000's
measured concentrations to the estimated content of
spiked samples. One measure of accuracy is the
number of ELPAT results which were reported
within the acceptance ranges that have been
established for those samples. For the 68 ELPAT
samples above 30 |_lg/wipe, the PDV 5000 reported
Table 6. Precision of the PDV 5000 Analyzer
Source
ELPAT
UC
UC prep c
No. of
sample
sets
17a
3b
o
6
% RSD
average
22
21
6
min
6
19
6
max
44
24
6
" 4 replicates in each sample set
619 or 20 replicates in each sample set
c precision of UC sample preparation process
54 results (79%) within the acceptance ranges
(Table 7). The results reported by the PDV 5000
can also be compared to the ELPAT certificate
value, i.e., the average concentration reported by
100+ laboratories who participated in previous
rounds of ELPAT testing. The average percent
recovery for the 68 ELPAT samples reported by the
PDV 5000 was 93%, although the range of values
was quite large, from 39 to 134%. The UC sample
results were lower, with an average percent recovery
of 87%. The possible explanations for this
difference in performance include: 1) that ELPAT
"estimated" values are, in fact, consensus values
from a large number of laboratories that may be
similar in performance to DataChem and to the PDV
5000, and 2) the reference material used to prepare
the UC samples may be more challenging than the
ELPAT reference material.
Table 7. Accuracy of PDV 5000 Analyzer
Statistic
na
average
standard
deviation
minimum
maximum
% recovery
ELPAT
68
93
22
39
134
UC
58
87
20
35
137
1 Excludes estimated values < 30 |_ig/wipe and two erroneous
MTI non-detect values for the UC samples.
17
-------
Another way to assess accuracy is to plot the PDV
5000 results versus the estimated values that are > 30
|-lg/wipe. The linear regression constants for the plot
of the ELPAT and UC data are listed in Table 8. As
expected, the conclusions gained from this
assessment are similar to the above conclusions
regarding the percent recovery calculations. The
samples were generally biased low, as evidenced by
the slope values < 1.0 (0.964 for the UC samples and
0.875 for the ELPAT samples.). The rvalues (0.936
and 0.951 for the UC and ELPAT samples,
respectively) indicate that the PDV 5000 results were
in fair agreement with the estimated values.
Comparability
Comparability refers to how well the PDV 5000 and
the NLLAP-recognized laboratory data agreed. In
this evaluation, the laboratory results are not
presumed to be the "correct" answers. Rather, these
results represent what a typical fixed laboratory
would report for these types of samples. A direct
comparison of the PDV 5000 results and the
laboratory results was performed for all ELPAT (>
30 |_lg/wipe) and UC samples. Because each wipe
was prepared individually, a true one-to-one
matching of PDV 5000 and laboratory results could
not be performed. However, the average
concentrations of the samples prepared at specific
levels was compared for the PDV 5000 and
laboratory results. In Table 8, the regression
constants for the average PDV 5000 results versus
the average DataChem results for both the ELPAT
and UC values are presented. The difference
between the regression slopes (m = 0.885 for
ELPAT and m = 1.074 for UC) and a slope with a
perfect agreement line (m = 1.000) is statistically
significant, but the correlation coefficients (r =
0.988 for ELPAT and r = 0.999 for UC) show a
strong linear relationship between DataChem and
PDV 5000 average results. To illustrate the strong
linear agreement between the PDV 5000 and
NLLAP laboratory results, Figure 7 is a plot of the
average PDV 5000 results versus the average
DataChem results for both ELPAT and UC data. For
clarity, only those values < 500 |_lg/wipe are shown.
Detectable Blanks
Of the samples that were prepared at < 2 |_lg/wipe,
the PDV 5000 correctly reported all 20 as < 20
|J,g/wipe, so no detectable blanks were reported.
Two UC samples at 40 and 250 |_lg/wipe were also
reported as < 20 |_lg/wipe. These were presumed to
be sample preparation errors and excluded from the
analysis as outliers. The instrument reported the
eight samples near 17 |_lg/wipe as < 20 |_lg/wipe, but
the four samples around 30 |_lg/wipe were reported
as < 20, < 20, 24, and 25, indicating the reporting
limits might have been closer to 30 |_lg/wipe. For
this reason, much of the data analysis in this section
considers only the data that is greater than 30
|-lg/wipe rather than 20 |_lg/wipe.
Table 8. Linear regression constants for the plots of the PDV 5000 versus the estimated values and
versus the DataChem average measurements
Statistic
n
slope
(standard error)
intercept
(standard error)
r
versus estimated values
UC
58
0.964
(0.048)
-7.371
(13.331)
0.936
ELPAT
68
0.875
(0.035)
12.790
(17.132)
0.951
versus DataChem average concentrations
UC
3
1.074
(0.008)
-14.354
(2.068)
0.999
ELPAT
17
0.885
(0.036)
15.633
(17.242)
0.988
18
-------
ID
2
01
>
8
o
Q
O.
500.0 -,
450.0 -
400.0 -
350.0 -
300.0 -
250.0 -
200.0 -
150.0 -
100.0 -
50.0 -
0.0 -
100.0 200.0 300.0 400.0
DataChem average concentration (ug/wipe)
500.0
Figure 7. Plot of the PDV 5000 average concentrations versus DataChem's average concentrations,
for both UC and ELPAT samples (n=20), shown for concentrations less than 500 |ig/wipe.
False Positive/False Negative Results
Similar to the evaluation described and presented in
Section 4 for DataChem, the number of false
negative and false positive results reported by the
PDV 5000 relative to the estimated concentrations of
both UC and ELPAT samples are summarized in
Table 9. For the cases where the estimated
concentration was less than the clearance level (CL),
the PDV 5000 reported a result that was more than
the CL in four of 29 UC samples and three of 12
ELPAT samples. When the estimated concentration
was equal to or above the clearance level, the PDV
5000 reported many of the results as less than the
clearance level (17 of 29 possible fn results for UC
samples and 12 of 28 possible fn results for ELPAT
samples). This finding is not surprising, since the
accuracy results reported above indicated that the
PDV 5000 results were negatively biased, or
reported lower than the estimated values.
The distribution of the PDV 5000's fn results, and
the comparison to DataChem's fn performance, can
be examined more closely using Figures 8, 9, andlO.
In these figures, the two-sided 90% confidence
intervals (not shown for clarity) are used to
express uncertainty on the false negative curves.
In Figure 8, the likelihood of false negative results
for the PDV 5000 and DataChem are comparable,
because both curves have probability values near 1.0
at 40 |_lg/wipe. In Figure 9, it is shown that, at
exactly 250 |_lg/wipe, the PDV 5000 has a much
lower probability of reporting a fn result (0.5 or 50%
probability) than DataChem (1.0 or nearly 100%).
However, the likelihood of fn results over a wide
range of concentrations is much greater for the PDV
5000 than for DataChem, due to the higher
variability observed in the PDV 5000 measurements.
At the 400 |_lg/wipe clearance level, a trend similar
to the 250 |_lg/wipe level is observed (Figure 10).
These conclusions are further substantiated in Table
10 which contains the linear regression constants for
the PDV 5000 measured concentration versus
estimated concentration for the three CLs, average
percent recovery values, standard deviations, and
estimates of the reported PDV 5000 concentrations
at the clearance levels. The PDV 5000 reported
concentrations at the clearance levels using the linear
regression constants are 29, 240, and 375 |_lg/wipe
for the UC samples. For example, this would
indicate that if the PDV 5000 reported a value for a
UC sample at 29 |_lg/wipe, the true concentration is
probably near 40 |_lg/wipe. As shown in Table 5,
DataChem results for the UC samples of 37, 226,
and 362 |_lg/wipe would correspond to true values at
the CLs. These data concur with the conclusions
above for the UC samples, where at a true
concentration exactly at the 40 |_lg/wipe CL, the
PDV 5000 is more likely to produce fn results than
19
-------
the NLLAP laboratory, but is less likely to do so at
the upper two clearance levels. The PDV 5000
ELPAT sample results less negatively biased at the
40 |_lg/wipe CL, but more negatively biased at the
upper two CLs.
Regardless of analytical technique, there is some
uncertainty in assessing false positive and false
negative error rates around critical action levels due
to "normal" levels of variability (see Song et al,
2001). Analytical values falling near the level of
interest should be interpreted with care for both
fixed-laboratory and field-based analytical methods.
Table 9. False Positive/False Negative Results for PDV 5000 Measurements of UC Samples
Evaluation Parameter
fp: # samples where PDV 5000
reported the result as > CLa of
the # samples where the
estimated concentration was <
CL
fn: # samples where PDV 5000
reported the result as < CL of
the # samples where the
estimated concentration was >
CL
Sample
Source
UC
ELPAT
UC
ELPAT
Number of Samples
40 |ig/wipe
Oof 10
Oof 4
8 of 9
2 of 12
250 |ig/wipe
2 of 9
3 of 8
5 of 10
5 of 8
400 |ig/wipe
2 of 10
OofOb
4 of 10
5 of 8
Total
4 of 29
3 of 12
17 of 29
12 of 28
' CL = clearance level
3 Because all eight ELPAT values were above 400 jig/wipe, no samples were available to assess fp results at this level.
Tiue Pb Concentration (ugA/vipe)
Figure 8. Comparison of the false negative probabilities for
MTI PDV 5000 and DataChem at a target concentration
level of 40 |ig/wipe.
20
-------
MT1 PDV 5000
DataChem
100 125 150 175 2X) 225 250 275 300 325 350 375 400 425 450
True Pb Concentration (ug/wipe)
Figure 9. Comparison of the false negative probabilities for
MTIPDV 5000 and DataChem at a target concentration level
of 250 |ig/wipe.
0.0-
300350400450500550600650 700
True Pb Concentration (ug/wipe)
Figure 10. Comparison of the false negative probabilities for
MTI PDV 5000 and DataChem at a target concentration level of
400 |ig/wipe.
21
-------
Table 10. Summary of the Linear Regression and Recovery Data for the PDV 5000 Response versus
the Estimated Concentrations
Evaluation Parameter
slope
intercept
correlation coefficient
average % recovery
SD of % recovery
Reported concentration
atCL
40 |_lg/wipe
UC
0.997
-10.700
0.388
73%
14%
29
l-ig/wipe
ELPAT a
0.626
18.655
0.0317
103%
17%
44
l-ig/wipe
250 |J,g/wipe
UC
1.3583
-99.780
0.431
96%
16%
240
l-ig/wipe
ELPAT
0.356
123.757
0.130
88%
29%
213
l-ig/wipe
400 |J,g/wipe
UC
1.047
-43.847
0.267
94%
21%
375
l-ig/wipe
ELPAT
6.356
-2284.1
0.372
83%
21%
258
l-ig/wipe
' Excludes four ELPAT samples at 29.8 jig/wipe because MTI report two of the four samples at non-detects.
Completeness
Completeness is defined as the percentage of
measurements that are judged to be usable (i.e., the
result was not rejected). Results were reported by the
technology for all 160 dust wipe samples. However,
two results for UC samples were reported as non-
detects for sample concentrations of 40 and 250
|J,g/wipe and were excluded from the data analysis.
Therefore, completeness was 99% and within the
acceptable completeness rate of 95% or greater.
Sample Throughput
Sample throughput is representative of the estimated
amount of time required to prepare and analyze the
sample and perform the data analysis. Two analysts
(one expert and one novice analyst) each operated
their own instrument, with the expert running odd-
numbered samples and the novice analyzing the
even-numbered samples. The analysts completed the
analysis of 160 samples over the course of three
days. The first day was spent setting up, training the
novice, and running approximately 32 samples. On
the second day (a 14-hour day), 130 samples were
analyzed. The data was checked and transposed onto
the results sheets on the third day. The MTI team
spent a total of about 18 hours analyzing the
samples.
Ease of Use
Two operators were used for the test because of the
number of samples and the working conditions, but
the technology can be operated by a single person.
Users unfamiliar with the technology may need
approximately one-half day of additional training to
operate the instrument. No particular level of
educational training is required for the operator.
During the test, one analyst that operated the PDV
5000 was an expert and the other was a novice.
Cost Assessment
The purpose of this economic analysis is to estimate
the range of costs for analysis of lead in dust wipe
samples using the PDV 5000 and a conventional
analytical laboratory method. The analysis was based
on the results and experience gained from this
verification test, costs provided by MTI, and
representative costs provided by the laboratory to
analyze the samples. To account for the variability in
cost data and assumptions, the economic analysis is
presented as a list of cost elements and a range of
costs for sample analysis by the PDV 5000
instrument and by the laboratory.
Several factors affected the cost of analysis. Where
possible, these factors were addressed so that
decision makers can complete a site-specific
economic analysis to suit their needs. The following
categories are considered in the estimate:
• sample shipment costs,
• labor costs, and
• equipment costs.
Each of these cost factors is defined and discussed
and serves as the basis for the estimated cost ranges
presented in Table 11. This analysis assumed that the
individuals performing the analyses were fully
22
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Table 11. Estimated analytical costs for lead dust wipe samples
Analysis method:
Analyst/manufacturer:
Sample throughput:
Cost category
Sample shipment
Labor
Rate
PDV 5000
MTI
80 samples/day
Cost ($)
0
50-100/h per analyst
Equipment
Mobilization/demobilization 0-150
Instalment purchase price
Reagents/supplies
Waste Disposal
$7,500
$99 per 10 samples
250
Analysis method:
NLLAP Laboratory:
Actual turnaround:
Cost category
Sample shipment
Labor
Overnight shipping
Labor
Rate
Equipment
Waste Disposal
EPASW8466010b
DataChem
18 working days
Cost ($)
100-200
50-150
30 per sample
Included a
Included
""Included" indicates that the cost is included in the labor rate.
trained to operate the technology. Costs for sample
acquisition and pre-analytical sample preparation,
tasks common to both methods, were not included in
this assessment.
PDV 5000 Costs
The costs associated with using the instrument
included labor and equipment costs. No sample
shipment charges were associated with the cost of
operating the instrument because the samples were
analyzed on site.
Labor
Labor costs included on-site labor to perform the
analyses. The cost of the on-site labor was estimated
at a rate of $50-100/h, depending on the required
expertise level of the analyst. This cost element
included the labor involved during the entire
analytical process, comprising sample preparation,
sample management, analysis, and reporting. If the
user would have to travel to the site, the cost of
mobilization and demobilization, travel, and per
diem expenses should also be considered. However,
in a typical application where the PDV 5000 might
be used, the analysis would usually be carried out by
a person located on site.
Equipment
Equipment costs included purchase of equipment,
and the reagents and other consumable supplies
necessary to complete the analysis.
• Instrument purchase. The instrument can be
purchased for $7,500. This price includes the
handheld analyzer with Voltscan software,
patented three- electrode device, battery and
charger, AC adapter, and carrying case. Leasing
of the instrument is available; terms are
dependent on the intended application for use.
Training is provided upon instrument purchase
for a nominal fee. The fee varies based on the
number of trainees and the scope of the
application.
• Reagents and supplies. The dust sample
preparation kit can be purchased for $99 for 10
tests.
Laboratory Costs
Sample Shipment
The costs of shipping samples to the laboratory
included overnight shipping charges as well as labor
charges associated with the various organizations
involved in the shipping process.
• Labor. This cost element included all of the
tasks associated with shipping the samples to the
reference laboratory. Tasks included packing the
shipping coolers, completing the chain-of-
custody documentation, and completing the
shipping forms. The estimate to complete this
task ranged from 2 to 4 h, at $50 per hour.
23
-------
• Overnight shipping. The overnight express
shipping service cost was estimated to be $50 -
100 for two boxes of samples.
Labor, Equipment, and Waste Disposal
The labor quotes from commercial analytical
laboratories that offered to perform the analysis for
this verification test ranged from $20 to $30 per
sample with turnaround time estimates ranging from
7 to 14 days. Some laboratories can provide a 1-2
day turnaround, but the quick turnaround was not
necessary for this test. The quotes were dependent
on many factors, including the perceived difficulty
of the sample matrix, the current workload of the
laboratory, data packaging, and the competitiveness
of the market. This rate was a fully loaded analytical
cost that included equipment, labor, waste disposal,
and report preparation. The cost for DataChem to
analyze samples for this verification test was $30 per
sample, with a turnaround time of 18 working days.
Cost Assessment Summary
An overall cost estimate for use of the PDV 5000
instrument versus use of the NLLAP- laboratory was
not made because of the extent of variation in the
different cost factors, as outlined in Table 11. The
overall costs for the application of any technology
would be based on the number of samples requiring
analysis, the sample type, and the site location and
characteristics. Decision-making factors, such as
turnaround time for results, must also be weighed
against the cost estimate to determine the value of
the field technology's providing immediate answers
versus the laboratory's provision of reporting data
within 18 days of receipt of samples.
Miscellaneous Factors
The following are general observations regarding the
field operation and performance of the PDV 5000
instrument:
• During the test, the PDV 5000 was run using
electrical power, but it does come with a
rechargeable nickel metal hydride battery.
The MTI analysts were ready for the first set of
samples within 1 h of arriving on site.
• Tests with the PDV 5000 generated a 5-gal
bucket full of vials containing 2M hydrochloric
acid waste, which cost approximately $250 to
dispose by a commercial vendor. The waste
contained a small amount of mercury (parts per
billion level) from the electrode.
Two analysts analyzed the samples using two
instruments. One analyst was an expert (the
developer of the technology) and analyzed the
odd-numbered samples. The other analyst, a
novice who was operating the instrument for the
first time, analyzed the even-numbered samples.
It is possible that the experience level of the
novice versus the expert operator impacted the
consistency of the data. (Of the 14 ELPAT
sample results that were outside of the
acceptable range, 10 of these were even-
numbered samples that were presumably
analyzed by the novice.) This trend was not
further investigated, as the vendor was informed
prior to the test that ORNL would make no
distinction between operators and/or instruments
in the performance of the PDV 5000.
• The PDV 5000's reporting limit was 20 |_lg/wipe
One set of samples around 30 |_lg/wipe indicated
that the PDV 5000 had difficulty consistently
detecting lead at this concentration level. For the
four samples prepared at 29.8 |_lg/wipe, MTI
reported 24, 25, <20, and < 20 |_lg/wipe,
indicating that these samples were near the
reporting limits of the instrument. More data
would need to be generated at this concentration
to substantiate this conclusion.
Summary of Performance
A summary of performance is presented in Table 12.
Note that performance is based on the specific
protocols employed for this verification test. If
different testing protocols are used, different
performance results may be obtained. The
verification test found that the PDV 5000 instrument
was relatively simple for a trained analyst to operate
in the field, requiring less than an hour for initial
setup. The sample throughput of the PDV 5000 was
eighty samples per day with two analysts each
operating their own instrument.
The overall performance of the PDV 5000 for the
analysis of lead in dust wipe samples was
characterized as biased low, but within acceptable
levels of bias, having greater than acceptable levels
of variability, and in good linear agreement with the
average results reported by the NLLAP laboratory.
ORNL and ETV remind the reader that, while the
ETV test provides valuable information in the form
of a snapshot of performance, state, tribal, or federal
requirements regarding the use of the technologies
(such as NLLAP recognition where required) need to
be followed.
24
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Table 12. Performance Summary for the PDV 5000 System
Feature/parameter
Precision : average RSD
Accuracy: average % recovery
Positive results on "detectable
blank" samples (< 2 jag/wipe)
False positive results
False negative results
Comparison with slope
laboratory results intercept
l-ig/wipe samples) correlation
coefficient
Overall evaluation
Completeness
Size and Weight
Sample throughput (2 analysts)
Power requirements
Training requirements
Cost
Waste generated
Performance summary
UC Samples
21%
87%
n/a
DataChem PDV 5000
Oof 30 4 of 29
DataChem PDV 5000
23 of 30 17 of 29
1.074
-14.345
0.999
- Statistically significant negative
bias but within the acceptable bias
range
- Less precise than acceptable levels
- Strong linear relationship to the
NLLAP lab results
- Few fp results
- Higher number of fn results
ELPAT Samples
22%
93%
0 of 20 samples
DataChem PDV 5000
2 of 12 3 of 12
DataChem PDV 5000
7 of 28 12 of 28
0.885
15.633
0.988
- Statistically significant negative
bias but within the acceptable bias
range
- Less precise than acceptable levels
- Strong linear relationship to the
NLLAP lab results
- Few fp results
- Higher number of fn results
99% of 160 dust wipe samples
10 cm x 18 cm x 4 cm; 0.7 kg
Average 80 samples/day
32 samples/7 hr-day (day#l); 128 samples/ 11-hr day (day #2); data analysis
(day#3)
battery operated (nickel metal hydride) or AC power
One-half day instrument-specific training
Purchase: $7,500
Reagents/Supplies: $99 for 10 tests
5 -gal bucket of vials of 2M hydrochloric acid/extracted dust wipes
(Total number of samples analyzed: 160)
25
-------
Section 6 — References
American Society for Testing and Materials. 1996. "Specification E1792-96a: Standard Specification for Wipe Sampling
Materials for Lead in Surface Dust" mASTM Standards on Lead Hazards Associated with Buildings. West
Conshohocken, PA.
American Society for Testing and Materials. 1998. "Practice E1644: Standard Practice for Hot Plate Digestion of Dust
Wipe Samples for the Determination of Lead" in ASTM Standards on Lead Hazards Associated with Buildings. West
Conshohocken, PA.
Ashley, Kevin, Korrie Mapp, and Mark Millson. 1998. "Ultrasonic Extraction and Field-Portable Anodic Stripping
Voltammetry for the Determination of Lead in Workplace Air Samples." AIHA Journal. 59(10), 671-679.
Ashley, K., TJ. Wise, W. Mercado, and D.B. Parry. 2001. "Ultrasonic Extraction and Field-Portable Anodic Stripping
Voltammetric Measurement of Lead in Dust Wipe Samples." Journal of Hazardous Materials. 83, p 41-50.
Code of Federal Regulations. 2001. "Identification of Dangerous Levels of Lead", Final Rule, 40 CFR Part 745, January.
Draper, N. R., and H. Smith. 1981. Applied Regression Analysis. 2nd ed. John Wiley & Sons, New York.
EPA (U.S. Environmental Protection Agency). 1996. "Method 3050B-1: Acid Digestion of Sediment, Sludge, and Soils."
In Test Methods for Evaluating Solid Waste: Physical/ Chemical Methods, Update II. SW-846. U.S. Environmental
Protection Agency, Washington, D.C., December.
EPA (U.S. Environmental Protection Agency). 1996. "Method 6010B-1: Inductively Coupled Plasma-Atomic Emission
Spectrometry." In Test Methods for Evaluating Solid Waste: Physical/ Chemical Methods, Update II. SW-846. U.S.
Environmental Protection Agency, Washington, D.C., December.
Keith, L.H., G. L. Patton, D.L. Lewis and P.O. Edwards. 1996. Chapter 1: Determining What Kinds of Samples and How
Many Samples to Analyze, pp. 19. In Principles of Environmental Sampling. Second Edition. Edited by L. H. Keith, ACS
Professional Reference Book, American Chemical Society, Washington, DC.
ORNL (Oak Ridge National Laboratory). 1998. Quality Management Plan for the Environmental Technology
Verification Program's Site Characterization and Monitoring Technologies Pilot. QMP-X-98-CASD-001, Rev. 0. Oak
Ridge National Laboratory, Oak Ridge, Term., November.
ORNL (Oak Ridge National Laboratory). 2001. Technology Verification Test Plan: Evaluation of Field Portable
Measurement Technologies for Lead in Dust Wipes. Chemical Sciences Division, Oak Ridge National Laboratory, Oak
Ridge, Term., November.
Song, Ruiguang, Paul C. Schlecht, and Kevin Ashley. 2001. "Field Screening Test Methods: performance criteria and
performance characteristics." Journal of Hazardous Materials. 83, 29-39.
26
-------
Appendix
MTFs PDV 5000 Results Compared with Laboratory Results
Sample
Analysis
Order
87
111
115
123
145
5
42
78
136
150
15
22
109
151
155
28
32
49
60
131
70
116
67
81
33
9
68
69
101
34
6
24
Source
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
Rep
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
MTI PDV 5000
Result
|ig/wipe
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
24
25
<20
<20
Estimated
|ig/wipe
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
16.9
16.9
16.9
16.9
17.6
17.6
17.6
17.6
29.8
29.8
29.8
29.8
DataChem
Result
|ig/wipe
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
<20
30
<20
<20
<20
33
26
28
28
Estimated
|ig/wipe
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
16.9
16.9
16.9
16.9
17.6
17.6
17.6
17.6
29.8
29.8
29.8
29.8
27
-------
Sample
Analysis
Order
104
117
133
37
47
138
76
106
50
103
26
30
112
129
134
144
110
99
90
147
94
43
53
149
119
65
154
105
137
55
18
124
121
95
132
122
Source
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
Rep
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
MTI PDV 5000
Result
|ig/wipe
27
32
34
27
36
23
31
32
35
20
33
27
<20
40
20
22
28
24
39
27
30
51
52
45
55
48
49
50
45
57
38
53
54
61
57
51
Estimated
|ig/wipe
38.6
38.9
43.2
39.5
44.2
35.9
39.6
41.8
37.0
39.3
43.7
38.5
40.6
41.3
40.2
42.5
38.9
40.8
42.1
37.0
41.3
41.3
41.3
41.3
49.0
49.0
49.0
49.0
49.1
49.1
49.1
49.1
58.6
58.6
58.6
58.6
DataChem
Result
|ig/wipe
33
32
31
29
32
38
37
36
37
37
33
41
32
38
30
35
36
31
34
34
37
42
44
41
43
52
49
48
70
54
48
44
64
55
56
52
Estimated
|ig/wipe
35.4
35.7
38.5
36.4
35.1
40.7
39.4
41.0
41.0
38.8
39.3
44.7
36.0
44.7
39.9
37.5
37.4
36.7
35.8
39.7
41.3
41.3
41.3
41.3
49.0
49.0
49.0
49.0
49.1
49.1
49.1
49.1
58.6
58.6
58.6
58.6
28
-------
Sample
Analysis
Order
12
54
39
10
36
89
74
114
79
85
128
7
98
44
3
141
152
107
62
108
102
25
64
16
143
84
148
130
125
139
127
31
17
91
27
66
160
126
38
4
Source
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
Rep
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
MTI PDV 5000
Result
|ig/wipe
48
63
89
59
112
77
133
130
130
163
185
147
78
270
255
188
278
219
199
115
273
224
308
212
179
151
222
219
240
306
183
306
219
242
231
258
253
205
<20
282
Estimated
|ig/wipe
88.0
88.0
88.0
88.0
117.0
117.0
117.0
117.0
162.3
162.3
162.3
162.3
201.6
201.6
201.6
201.6
239.0
239.0
239.0
239.0
263.3
244.5
250.0
240.6
252.3
226.3
253.4
225.7
273.8
263.3
233.5
246.7
226.8
241.2
268.9
245.1
250.0
258.9
261.1
253.9
DataChem
Result
|ig/wipe
82
83
79
100
120
120
120
110
150
160
150
160
200
190
200
220
230
250
250
230
210
250
230
230
200
240
210
210
220
220
230
170
190
210
210
250
220
210
210
220
Estimated
|ig/wipe
88.0
88.0
88.0
88.0
117.0
117.0
117.0
117.0
162.3
162.3
162.3
162.3
201.6
201.6
201.6
201.6
239.0
239.0
239.0
239.0
244.0
274.4
252.8
258.9
241.7
274.9
244.5
236.2
244.0
242.3
260.0
228.5
242.3
267.2
236.2
275.5
262.2
226.3
227.4
243.4
29
-------
Sample
Analysis
Order
51
75
88
13
23
52
72
41
45
40
1
80
146
153
8
120
48
46
100
57
73
21
58
29
63
2
113
61
59
140
92
96
11
93
77
83
Source
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
UCLAB
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
Rep
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
MTI PDV 5000
Result
|ig/wipe
215
276
106
258
182
169
244
291
474
436
351
145
508
258
340
311
382
448
329
438
261
444
363
476
418
330
379
378
406
405
170
274
327
382
427
358
Estimated
|ig/wipe
256.7
256.7
256.7
256.7
260.8
260.8
260.8
260.8
436.5
390.0
383.4
416.6
370.1
390.0
363.5
410.5
391.7
407.7
370.6
417.7
369.0
408.8
395.0
437.6
407.7
372.9
418.8
414.9
408.7
408.7
408.7
408.7
418.1
418.1
418.1
418.1
DataChem
Result
|ig/wipe
290
240
230
250
220
250
210
210
320
360
350
340
350
340
370
340
370
340
370
390
330
320
330
360
340
360
390
330
360
430
410
410
440
410
430
420
Estimated
|ig/wipe
256.7
256.7
256.7
256.7
260.8
260.8
260.8
260.8
377.8
395.0
399.4
385.0
395.5
382.8
413.8
374.0
426.5
378.9
401.1
423.2
372.9
362.9
384.5
411.0
397.2
393.3
437.6
375.1
408.7
408.7
408.7
408.7
418.1
418.1
418.1
418.1
30
-------
Sample
Analysis
Order
158
20
82
159
156
142
56
71
86
118
135
19
35
97
157
14
Source
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
ELPAT
Rep
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
MTI PDV 5000
Result
|ig/wipe
651
596
403
580
689
598
620
613
704
898
719
804
1069
885
1716
1281
Estimated
|ig/wipe
561.9
561.9
561.9
561.9
564.7
564.7
564.7
564.7
805.1
805.1
805.1
805.1
1482.6
1482.6
1482.6
1482.6
DataChem
Result
|ig/wipe
580
540
560
540
560
560
570
530
760
770
760
740
1500
1500
1500
1400
Estimated
|ig/wipe
561.9
561.9
561.9
561.9
564.7
564.7
564.7
564.7
805.1
805.1
805.1
805.1
1482.6
1482.6
1482.6
1482.6
31
------- |