vvEPA
United States
Environmental Protection
Agency
Office of Research and
Development
Washington, D.C. 20460.
EPA/600/R-98/084
October 1998
Technology Evaluation
Report
Electroanalytical Measurement
Techniques for Metals-
Contaminated Soil Characterization
Battelle Pacific Northwest Laboratory,
New Mexico State University, and
Environmental Technologies Group,
Inc.
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EPA/600/R-98/084
October 1998
Technology Evaluation
Report
Electroanalytical Measurement
Techniques for Metals-Contaminated Soil
Characterization
Battelle Pacific Northwest Laboratory, New
Mexico State University, and Environmental
Technologies Group, Inc.
by
Wayne Einfeld
Gary Brown
(s, Environmental characterization and Monitoring Department
N Sandia National Laboratories
^ Albuquerque, New Mexico 87185-01-0
L->
IAGDW89936700-01-0
Project Officers
Eric Koglin
Stephen Billets
Environmental Sciences Division
National Exposure Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Las Vegas, Nevada 891 93-3478
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Notice
The information in this document has been funded by the U.S. Environmental Protection Agency (EPA) under an
Interagency Agreement (No. DW89936700-01-0) with the U.S. Department of Energy's Sandia National
Laboratories. This technology evaluation was supported by the Consortium for Site Characterization
Technology, a pilot program operating under the EPA Environmental Technology Verification (ETV) Program.
This report has been subjected to Agency peer and administrative review, and it has been approved for
publication as an EPA document. Mention of corporate names, trade names, or commercial products does not
constitute endorsement or recommendation for use of specific products.
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Executive Summary
Consortium for Site Characterization Technology
The U.S. Environmental Protection Agency (EPA), through the Environmental Technology Verification
Program, is working to accelerate the acceptance and use of innovative technologies that improve the way the
nation manages its environmental problems. As part of this program, the Consortium for Site Characterization
Technology was established as a pilot program to test and verify field monitoring and site characterization
technologies. The Consortium is a partnership involving the U.S. Environmental Protection Agency, the
Department of Defense, and the Department of Energy.
This report describes the results of a field demonstration conducted at contaminated sites near Butte, Montana, in
which developers of soil characterization technologies were invited to participate. The report presents soil
sample analysis results from anodic stripping voltammetry systems operated by Battelle Pacific Northwest
National Laboratory. This electroanalytical technique was one of four technologies that were used to analyze
soil samples for target elements. Other technologies that were tested include a mobile atomic absorption
spectrometer operated by Pace Environmental Laboratories, Inc., and two laser-induced breakdown
spectrometers from MelAok Instruments, Inc., and Los Alamos National Laboratory. The results from these
technology demonstrations are published as separate reports.
Technology Classification
The Consortium classifies each candidate technology into one of three development levels on the basis of the
maturity of the technology and its expected time to commercialization. Level 1 designates the least developed
and Level 3 the most developed technologies. The electrode stripping analysis technologies operated by Battelle
Pacific Northwest National Laboratory were classified as Level 1. Although many of the system components
used to make the field measurements are commercially available, this test was the first full-scale field trial of
these technologies for the analysis of metals-contaminated soil.
The Consortium has further determined that an exhaustive verification of the relatively new and developing
Level 1 technologies could not be performed. The field demonstration data sets from the stripping analysis
technologies are compiled, organized, and presented in this report along with a validated data set from analytical
laboratories using conventional analytical methods. The degree of comparative analysis of the data is purposely
limited. The results are intended for distribution to the technology developers in order to assist them in further
instrument development and refinement.
in
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Demonstration Design
A demonstration of selected Department of Energy-funded technologies was being planned by MSE-HKM, Inc.,
under contract to the Department of Energy. The Consortium chose to augment the planned demonstration by
bringing in additional technologies and enhancing the laboratory analysis component of the project. Two sites
contaminated with heavy metals were identified in the Butte, Montana, area for the demonstration. The first site,
Butte/Silver Bow Creek, was contaminated by heavy metals deposited as mill tailings. The second site,
Anaconda Smelter/Mill Creek, was contaminated by dry aerosol deposition of smelter stack emissions. The
surface soils at both sites contained varying concentrations of heavy metals. Soil conditions at each site were
judged to be representative of typical field conditions under which the technology would be expected to operate.
Sixty samples were collected and processed using a preestablished sampling protocol. The soil samples were
dried, homogenized, and split ten ways for distribution and analysis by three analytical laboratories and four
technologies.
The demonstration plan incorporated the use of reference laboratories to analyze metals in the soil samples using
standard EPA laboratory protocols. Laboratory data produced by inductively coupled plasma atomic emission
spectroscopy and direct-aspiration, flame atomic absorption spectroscopy (AAS) methods were validated to
produce a reference set of target metal concentrations in the field soil samples. The reference data set was used
for comparison with analytical results from the demonstration technologies. Quality control samples were also
incorporated into the sample analysis plan to obtain additional performance measures for the laboratory and field
tests.
Demonstration Results
Anodic stripping voltammetry and potentiometric stripping analysis are related electroanalytical techniques that
are used to measure metals in solution. The target metal is first preconcentrated onto a working electrode by
placing a voltage potential on the electrode so that a portion of the metal in solution migrates to and is deposited
on the electrode surface. In anodic stripping voltammetry, the accumulated metal species is released from the
electrode by applying an increasing voltage to the working electrode. During the stripping phase of the analysis,
the release of the target metal is measured as peak current and is proportional to the concentration of the metal in
the test solution. Potentiometric stripping analysis employs a variation of anodic stripping voltammetry in the
stripping stage. In this procedure, either a chemical oxidant is added to the test solution or a constant current is
used to strip the target elements from the electrode. The elements are sequentially stripped in order of their
oxidation potential. The length of time required to strip the element at a particular electrode potential is used as a
measure of the concentration of the element in solution.
The electrochemical stripping analysis techniques were demonstrated alongside three other participating
technologies in this study. All participants set up and operated their instruments during a 1-week period in the
Butte, Montana, area in September 1995. The incorporation of conventional laboratory analysis into the
demonstration provided a validated data set that could be used by developers to evaluate the performance of the
technology.
IV
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A comparison of the field soil sample results from the reference laboratories showed very close agreement. This
observation suggests that the soil samples distributed to the demonstration participants were homogeneous in
terms of their chemical composition. A high degree of homogeneity facilitates comparison of the soil analysis
results from the demonstrated technologies with those from the laboratories. Data from the reference laboratory
and from Battelle Pacific Northwest National Laboratory, New Mexico State University, and Environmental
Technologies Group, Inc., are presented in a variety of formats to assist in comparing the data sets produced
during the demonstration.
The performance of the stripping analysis methods was examined in three ways: by evaluation of quality control
sample analysis results, by evaluation of duplicate sample analysis results, and by comparison of stripping
analysis results from field soil sample analysis with conventional laboratory results. The time required to
complete stripping analysis limited the analysis to four of the nine target analytes: cadmium, chromium, copper,
and lead.
These stripping analysis techniques fall into Level 1 in terms of technology maturity. Consequently, a formal
assessment of the systems' performance was not within the scope of this report.
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Contents
Notice ii
Executive Summary iii
Figures ix
Tables x
Acronyms and Abbreviations xi
Acknowledgments xii
Chapter 1 Introduction 1
Site Characterization Technology Challenge 1
Technology Demonstration Process 1
Technology Identification and Selection 2
Demonstration Planning and Implementation 2
Performance Assessment, Evaluation, and Verification 2
Information Distribution 3
The Soil-Metals Characterization Demonstration 3
Chapter 2 Technology Description 5
General Description 5
Technology Advantages 6
Technology Limitations 6
Physical Characteristics 6
Schematic Diagram 7
Operational Features 7
Sample Preparation 7
Sample Analysis 8
Calibration 8
Technology Maturity 9
VI
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Technology Performance Indicators 9
Chapter 3 Demonstration Design and Description 10
Technology Demonstration Objectives 10
Site Selection and Description 10
Site 1 Butte/Silver Bow Creek 11
Site 2 Anaconda Smelter/Mill Creek 14
Sample Collection, Handling, and Distribution 16
Laboratory Selection and Analysis Methodology 17
Columbia Analytical Services 17
MSE Laboratory 18
SNL Environmental Restoration Program Laboratory 18
Demonstration Narrative 18
Deviations from the Demonstration Plan 19
Chapter 4 Laboratory Data Results and Evaluation 20
Laboratory Data Validation Methodology 20
Qualitative Factors 20
Quantitative Factors 20
Laboratory-to-Laboratory Data Comparison 21
Columbia Analytical Services Data 23
General Indicators of CAS Data Quality 23
Quantitative Indicators of CAS Data Quality 23
CAS Performance 27
MSE-HKMData 27
General Indicators of MSE Data Quality 27
Quantitative Indicators of MSE Data Quality 27
MSE Performance 31
Sandia National Laboratories Environmental Restoration Program Laboratory Data 31
General Indicators of SNL Laboratory Data Quality 31
Quantitative Indicators of SNL Laboratory Data Quality 32
vn
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SNL Laboratory Performance 32
Laboratory-to-Laboratory Data Comparison 34
Mean Percent Difference 34
Scatter Plots 34
Statistical Bias Testing 38
Intra- and Interlaboratory Variability 39
Reference Laboratory Data Set 40
Chapters Demonstration Results 42
Technology-Laboratory Data Comparison Methods 42
Field Observations 42
General Description of Electrochemical Analysis Results 42
Quality Control Sample Results 43
Blank Soil Sample Analysis 43
Control Soil Sample Analysis 43
Duplicate Sample Analysis 43
Recovery Analysis 45
Field Soil Sample Analysis Results 45
Comparison of Stripping Analysis Results with Reference Laboratory Data 45
Mean Percent Difference 45
Linear Regression Coefficients 49
Statistical Bias Testing 49
Conclusions 50
Chapter 6 Developer's Comments 51
References 52
Appendix A: Tabular Data for PNNL/NMSU/ETG Stripping Analysis and Reference Laboratory Field Soil
Samples A-l
Vlll
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Figures
2-1. Schematic diagram of atypical ASV analysis cell 7
3-1. Montana regional map showing the Silver Bow and Mill Creek (Anaconda) sampling sites 11
3-2. Local map of the Silver Bow sampling site 12
3-3. Local map of the Mill Creek sampling site 14
4-1. Control soil sample analysis results from CAS 25
4-2. Duplicate soil sample analysis results from CAS 25
4-3. Continuing calibration verification results from CAS 26
4-4. Spiked soil sample recovery results from CAS 26
4-5. Control soil sample results from MSB 29
4-6. Duplicate soil sample results from MSB 29
4-7. Continuing calibration verification results from MSB 30
4-8. Spiked soil sample recovery results from MSB 30
4-9. Control soil sample results from SNL 33
4-10. Continuing calibration verification results from SNL 33
4-11. CAS AAS vs. CAS ICP silver measurements on field replicate soil samples 35
4-12. CAS AAS vs. CAS ICP chromium measurements on field replicate soil samples 35
4-13. CAS AAS vs. CAS ICP iron measurements on field replicate soil samples 36
4-14. MSB ICP vs. CAS ICP silver measurements on field replicate soil samples 36
4-15. MSB ICP vs. CAS ICP chromium measurements on field replicate soil samples 37
4-16. MSB ICP vs. CAS ICP iron measurements on field replicate soil samples 37
5-1. Control soil sample analysis results from the PNNL/NMSU ASV and PSA systems 44
5-2. Duplicate sample analysis results for the EG&G ASV (Cr) and the TraceLab PSA (Cd, Cu, Pb)
systems 44
5-3. EG&G ASV vs. reference laboratory chromium measurements 46
5-4. TraceLab PSA vs. reference laboratory cadmium measurements 46
5-5. TraceLab PSA vs. reference laboratory copper measurements 47
5-6. TraceLab PSA vs. reference laboratory lead measurements 47
5-7. Metalyzer PSA vs. reference laboratory copper measurements 48
5-8. Metalyzer PSA vs. reference laboratory lead measurements 48
IX
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Tables
2-1. Physical Characteristics and Electrical Requirements Associated with the ASV and PSA Systems 6
2-2. Detection Level and Accuracy Estimates for the ASV and PSA Systems as Reported by PNNL,
NMSU, and ETG 9
3-1. Demonstration Participants 10
3-2. Typical Heavy Metal Soil Contamination at the Butte/Silver Bow Creek Site 13
3-3. Typical Heavy Metal Soil Contamination at the Anaconda Smelter/Mill Creek Site 15
4-1. Reference Laboratory Blank Soil Sample Results 24
4-2. Serial Dilution Results from MSE 31
4-3. Mean Percent Differences from MSE ICP and CAS AAS Data 34
4-4. Reference Laboratory Linear Regression Results 38
4-5. Wilcoxon Matched Pair Statistical Test Results 39
4-6. Estimates of Intra- and Interlaboratory Sample Variation 40
5-1. Blank Soil Analysis Results for PNNL/NMSU ASV and PSA, MSE Laboratory and Accompanying
Certified Levels 43
5-2. Mean Percent Difference for PNNL/NMSU ASV and PSA Analyses Relative to Reference
Laboratory Data 49
5-3. Comparison of Linear Regression Coefficients for the ASV and PSA Systems and Reference
Laboratory Data Set 49
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Acronyms and Abbreviations
AAS
AdSV
ASV
CAS
CCV
CLP
cm
°C
DoD
DOE
EPA
ETG
g
ICP
ICP-AES
kg
LANL
LCL
LIBS
MCHD
MCLD
MCMD
MPD
NERL
NIST
NMSU
PAR
PE
PNNL
PSA
RPD
SBHD
SBLD
SBMD
SNL
UCL
atomic absorption spectroscopy
adsorptive stripping voltammetry
anodic stripping voltammetry
Columbia Analytical Services
continuing calibration verification
Contract Laboratory Program
centimeter
degrees centigrade
Department of Defense
Department of Energy
Environmental Protection Agency
Environmental Technologies Group, Inc.
gram
inductively coupled plasma
inductively coupled plasma atomic emission spectroscopy
kilogram
Los Alamos National Laboratory
Lower 95 percent confidence limit
Laser-induced breakdown spectrometer
Mill Creek-high demonstration
Mill Creek-low demonstration
Mill Creek-medium demonstration
mean percent difference
National Exposure Research Laboratory
National Institute of Standards and Technology
New Mexico State University
Princeton Applied Research
performance evaluation
Pacific Northwest National Laboratory
potentiometric stripping analysis
relative percent difference
Silver Bow-high demonstration
Silver Bow-low demonstration
Silver Bow-medium demonstration
Sandia National Laboratories
upper 95 percent confidence limit
XI
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Acknowledgments
The demonstration of contaminated soils measurement technology benefited from the contributions of numerous
personnel from the U.S. Environmental Protection Agency, the Department of Energy, and the Department of
Defense and their contract organizations.
Participants in the demonstration planning, execution, and analysis were:
EPA National Exposure Research Laboratory, Environmental Science Division
Stephen Billets, Eric Koglin, Gary Robertson
EPA Office of Solid Waste and Emergency Response
Oliver Fordham, Jr.; Howard Fribush
Sandia National Laboratories
Gary Brown, Wayne Einfeld, Michael Hightower, Art Verardo, Susan Bender, Robert Helgesen
MSE-HKM, Inc.
Jay McCloskey, Frank Cook
Columbia Analytical Services
Linda Huckestein
Ames Laboratory
Glenn Bastiaans, Marv Anderson
Naval Research Laboratory
John Moon
Los Alamos National Laboratory
David Cremers
Pace Environmental Laboratories, Inc.
Jim Archer
Battelle Pacific North west National Laboratory
Khris Olsen
MelAok Instruments, Inc.
Hayward Melville
XII
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Chapter 1
Introduction
Site Characterization Technology Challenge
Rapid, reliable, and cost-effective field analysis and screening technologies are needed to assist in the complex
task of characterizing and monitoring hazardous and chemical waste sites. Environmental regulators and site
managers often are reluctant to use new technologies that have not been validated in an objective U.S.
Environmental Protection Agency (EPA)-sanctioned testing program or through a similar process that facilitates
acceptance. Until the performance of field characterization technologies can be verified through objective
evaluations, users will remain skeptical of innovative technologies, despite the promise of better, less expensive,
and faster environmental analyses.
The Consortium for Site Characterization Technology was established as a pilot program under the
Environmental Technology Innovation, Commercialization and Enhancement Program, as outlined in 1993 by
President Clinton's Environmental Technology Initiative, to specifically address many of these concerns. The
Consortium is a partnership among the EPA, the Department of Energy (DOE), and the Department of Defense
(DoD). The mission of the Consortium is to identify, demonstrate, and assess innovative field instruments. It
also disseminates information about technology performance to developers, environmental remediation site
managers, consulting engineers, and regulators. As a partnership, the Consortium offers valuable expertise to
support the demonstration of new and emerging technologies. Through its organizational structure, it provides a
formal mechanism for independent assessment, evaluation, and verification of emerging field analytical site
characterization technologies.
Technology Demonstration Process
The Consortium provides technology developers a clearly defined performance assessment, evaluation, and
verification pathway for EPA acceptance. The pathway is outlined in the four components of the Consortium's
evaluation and verification process:
Technology identification and selection
Demonstration planning and implementation
Performance assessment, evaluation, and verification
Information distribution
Each component is discussed in detail in the following paragraphs.
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Technology Identification and Selection
The first step of the process is a determination of technology needs. Because a wide range of field
characterization and monitoring needs exists, the Consortium must prioritize a technology's suitability for
demonstration. Priority is based on the environmental and fiscal impact of the technology and on the likelihood
that its acceptance and use will provide cost-effective and efficient environmental solutions. Surveys of EPA,
DOE, DoD, state, local, and tribal agencies and industry are carried out to identify candidate technologies that
could meet the needs of the environmental characterization community.
Beyond the initial identification, a critical aspect of technology selection is an assessment of the technology's
field deployment readiness. Commercialized instruments, or those ready for production, that have a history of
successful laboratory or field operation are prime candidates for the demonstration process. Early evolving
technology's prototypes, or laboratory instruments requiring extensive testing and modification prior to field
deployment are less desirable as demonstration candidates. The candidate technology must meet criteria for one
of three levels of maturing:
Level 1 Demonstrated in a laboratory environment and ready for initial field trials
Level 2 - Demonstrated in a laboratory environment and in limited field trials
Level 3 - Demonstrated extensively in the laboratory and in field trials and commercially available
Assessment of the readiness of candidate technologies for field demonstration is based on the following criteria:
Field portability or transportability
Applicability to numerous environmentallyaffected sites
Potential for solving problems inherent is current analytical methods
Per sample cost factors
Potential improvements in data quality, sample preparation, or analysis time
Ease of use
Demonstration Planning and Implementation
A technology demonstration plan is prepared according to guidelines provided by the Consortium. This plan
includes a technology description, an experimental design, a sampling and analysis plan, a quality assurance
project plan, and a health and safety plan. These plans are designed to enable an objective test of technology
performance. The demonstration plan also calls for the generation of a validated reference laboratory data set
with which the field technology can be compared. Following approval by the EPA and acceptance by the
technology developers, the demonstration plan is implemented at appropriate field locations. The Consortium
provides technical support to the technology developer during plan preparation and execution and also audits the
data collection process.
Performance Assessment, Evaluation, and Verification
In this component of the demonstration process, the technology analytical results are compared with a reference
laboratory data set. The principal product of this phase of the project is a technology report, prepared by an
independent party known as the verification organization. The report documents demonstration results and
provides an assessment of the technology's performance. The degree of data analysis in the report is determined
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by the level of maturity of the technology under evaluation; the more mature technologies receive more detailed
analysis.
Level 1 demonstrations are intended to provide the technology developer with access to a controlled field
demonstration in which the system can be tested. A detailed evaluation of system performance is left to the
developer using the validated reference data set obtained during the demonstration. Level 2 technology
performance is evaluated by the Consortium on a limited basis. The most extensive evaluation is done for
Level 3 technologies. In this case, the capabilities of the technology are evaluated by the Consortium, and a
formal verification statement documenting the technology's performance is issued by the EPA.
Information Distribution
Innovative technology evaluation reports from these demonstrations are peer reviewed and approved for
distribution by the EPA. The Consortium has developed an information distribution strategy to ensure that these
documents are readily available to interested parties. This strategy includes access to information via the World
Wide Web through a program supported by the Superfund Technology Innovation Office.
The Soil-Metals Characterization Demonstration
The objectives of the metals-contaminated soil characterization technology demonstration were twofold:
1. provide an opportunity for technology developers to analyze soil samples under a documented and
scientifically sound experimental plan and
2. provide a validated soil analysis data set from conventional analytical laboratories using prescribed EPA
laboratory analysis methods with which technology developers could compare their results
The process used for technology selection involved the publication of a notice of intent to conduct a technology
demonstration, which was accompanied by solicitation of applications from interested parties. Usually, the
Consortium selects applicants based on the readiness of the technology for field demonstration and on its
applicability at environmentally affected sites as determined by the level of regional and national interest in the
specific technology.
For this demonstration, the Consortium joined a project funded by the Department of Energy in which several
technologies had already been selected for demonstration. The Consortium formalized the demonstration plan
development, brought additional technologies to the demonstration, and enhanced the analytical laboratory
component of the project.
Contractual arrangements were established with several chemistry laboratories to conduct soil analyses by
conventional methodologies. Included in these arrangements was a plan to carry out a preliminary site
assessment that involved limited sampling and analysis of soils from the area selected for the demonstrations.
These preliminary data were used to further develop the site sampling and analysis plan, prior to the actual
demonstration.
The following chapters of this report present the details of the demonstration project. Chapter 2 describes the
stripping technologies demonstrated by Battelle Pacific Northwest National Laboratory (PNNL). Chapter 3
describes the site selection, soil sampling, laboratory selection, and analysis methodology. The technical
approach taken in evaluation and validation of laboratory data is also outlined in Chapter 3. Chapter 4 gives a
detailed analysis of the laboratory data validation process and describes how a reference laboratory data set was
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determined. Chapter 5 gives results and an analysis of the performance of the PNNL technologies. Chapter 6
contains developer's comments regarding the demonstration.
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Chapter 2
Technology Description
General Description
Anodic stripping voltammetry (ASV)1 and potentiometric stripping analysis (PSA) are related electroanalytical
techniques that are used to measure metals in solution. The target metal is first preconcentrated onto a working
electrode by placing a voltage potential on the electrode so that a portion of the metal in solution migrates to and
is deposited on the electrode. In ASV, the accumulated metal species is then stripped from the electrode by
applying an increasing voltage to the working electrode. The accumulated metal is released from the electrode
when the voltage potential on the electrode is equivalent to the oxidation potential of the target metal. During the
stripping phase, electrode current is measured as a function of electrode potential and produces a voltammogram.
The release of the target metal from the electrode is measured as peak current and is proportional to the
concentration of the metal in the test solution. Potentiometric stripping analysis employs a variation from the
ASV method in the stripping stage. Following the metal accumulation stage, the addition of a chemical oxidant
or a constant current is used to strip the target elements from the electrode. The elements are sequentially
stripped from the electrode in order of their oxidation potential. The length of time required to strip the element
at a particular electrode potential is used as a measure of the concentration of the element in solution. Further
descriptions of ASV and PSA technologies can be found in the literature (Jagner et al., 1982; Olsen et al., 1994;
Wang; 1982, 1985).
Three electrochemical systems were deployed in this demonstration. The ASV system, operated by individuals
from Pacific Northwest National Laboratory and New Mexico State University (NMSU), consisted of an
EG&G/Princeton Applied Research (PAR) Model 264A voltammetric analyzer, a PAR Model 303A static
mercury drop electrode, and a PAR Model 0073 X-Y recorder. A PSA system was also operated by
PNNL/NMSU personnel. The system was a TraceLab Trace Element Laboratory, consisting of a PSU 20
potentiometric stripping unit (Radiometer A/S, Copenhagen, Denmark). A SAM 20-sample station accessory
was used that included a glassy carbon disk as the working electrode in the system. System operation and control
were via a personal computer with appropriate software. The third demonstration unit was the Metalyzer 3000,
another PSA system from Environmental Technologies Group, Inc. (ETG) of Baltimore, Maryland. The
Metalyzer is a hand-held, battery-operated system with disposable electrodes. The instrument is commercially
available and is typically used for water analysis. Technology developers from ETG were interested in assessing
their system's performance in the measurement of metals from soil and from residue extracts.
' Anodic stripping voltammetry is also referred to as adsorptive stripping voltammetry (AdSV), and the two terms are used
interchangeably in this report.
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Technology Advantages
According to the technology developers, the ASV and PSA techniques offer several features consistent with, and
in some cases, better than, conventional atomic emission or absorption spectroscopic methods. The most
important features of these electroanalytical techniques include the following:
High sensitivity
High precision
Ability to speciate metals
Portab le, com pact apparatus
Low power consumption
Low acquisition cost
Technology Limitations
The developers indicate several features of the systems that may be viewed as system limitations.
Like conventional laboratory techniques, the metal to be analyzed must be in solution achieved through
acid digestion preliminary step.
Some wet chemistry is required in processingthe samples.
Not all elements can be analyzed by electrochemicaltechniques.
The presence of some metal pairs in solution can result in the formation of intermetallic compounds,
requiring additional chemical additives in the analysis.
Metals present in solution that have similar oxidation potentials can result in peak overlap,
difficulty in quantitative analysis.
an
, causing
Physical Characteristics
Physical attributes and electrical requirements of the two instruments as provided by the developers are given in
Table 2-1.
Table 2-1. Physical Characteristics and Electrical Requirements Associated
with the ASV and PSA Systems
Instrument Parameter
Weight, pounds
Electrical requirements
Volume (cubic feet)
ASV
EG&G
25
115V/3A
6
PSA
TraceLab
50
115V/5A
9
PSA
Metalyzer
3
Battery powered
1
Ancillary equipment for all systems includes a microwave digestion unit, a top-load balance, laboratory
glassware and hardware, and a personal computer and printer. Sample preparation and instrument operation are
relatively simple; however, samples must be digested in order to get the elements of interest into solution. One
person with technical skills and training is capable of operating the instrument under normal conditions.
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Schematic Diagram
A simple schematic diagram of a typical ASV analysis cell is shown in Figure 2-1. The cell consists of three
electrodes: a working electrode (single-drop mercury electrode or glassy carbon disk), a reference electrode, and
an auxiliary electrode. The cell also has a nitrogen gas inlet that is used to purge oxygen from the system. The
configuration of a PSA system is fundamentally the same with minor variations. The system component that
varies most between ASV and PSA systems is the configuration of the working electrode.
Working
electrode
Reference
electrode
, Auxiliary
/ electrode
N, inlet
I
Figure 2-1. Schematic diagram of a typical ASV
analysis cell.
Operational Features
Sample preparation, sample analysis, and calibration features, as summarized by the instrument developers, are
given below.
Sample Preparation
The ASV and PSA systems both require that the target elements be in solution. Consequently, acid leaching
and/or digestion of the sample was carried out in a preanalysis sample preparation step. A microwave digestion
method similar to those prescribed by the EPA in Method SW-846 (EPA, 1996) was used in this demonstration
prior to electrode analysis. Hydrochloric acid was used in place of nitric acid, which is specified in SW-846.
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The change was made to ensure compatibility with the electrode analysis systems. The 100-g soil samples were
placed in 100-ml beakers and dried in a microwave oven. A 1-g aliquot of the dried soil sample was used in
follow-on microwave-assisted acid digestion.
Sample Analysis
EG&G AdSV analysis procedures for chromium were as follows:
1. The 9.9 ml of supporting electrolyte solution was pipetted into the sample cell and purged with nitrogen for
4 minutes.
2. An accumulation potential of-0.8 V was applied to a fresh mercury drop electrode as the solution was
stirred for 10 to 30 seconds.
3. Stirring was stopped and a voltammogram was recorded by applying a negative-going differential pulse
potential scan terminating at 1.65 V.
4. A known volume of soil leachate and 10 u.1 of 0.1 M KMnO4 were added and steps 2 and 3 were repeated
for the analysis of Cr.
5. Quantification of the Cr in solution was achieved by the method of additions using National Institute of
Standards and Technology (NIST)-traceableCr standards.
TraceLab PSA analysis procedures were as follows:
1. The soil leachate was diluted tenfold in a nonaerated HC1 solution.
2. An accumulation potential of-1.1 V was applied to a preplate mercury film electrode as the solution was
stirred for 2 minutes.
3. The metals were then chemically stripped from the electrode in a quiescent (nonmixed) solution.
4. Quantification was achieved through the method of additions using Cd, Cu, and Pb standard solutions.
ETG Metalyzer 3000 analysis procedures for copper, cadmium, and lead were as follows:
1. The disposable analysis cell was uncapped and filled with extract solution to the indicated level on the cell.
2. The cell cap was closed with the twist cap, forcing the sample into the electrode chamber.
3. The sensor was flexed at the center, breaking a glass ampoule containing chemical reagents which then
mixed with the sample.
4. The disposable cell was inserted into the meter, automatically starting the approximate 3-minute analysis
cycle.
5. The metal concentrations were read from the digital display.
Calibration
Calibration of the ASV and TraceLab PSA instruments was carried out using the method of standard additions.
Analysis of an unspiked test solution was followed by spiking known amounts of target metals into the solution
and repeating the analysis. Alternatively, calibration curves can be prepared and used to determine metal content
in the test solutions. The Metalyzer was equipped with a plug-in electronic chip that contained calibration
information for the particular lot of disposable analysis cells used in this demonstration.
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Technology Maturity
The ASV and PSA systems operated by PNNL/NMSU personnel have undergone considerable methods
development in a laboratory setting. The electrochemical techniques have been well established for the analysis
of water samples for trace metal content. Use of these systems for metals-contaminated soil or residue analysis
is a relatively new application. The Metalyzer 3000 has also been marketed for routine water testing
applications, but has not been previously tested for analyzing soil residue.
Technology Performance Indicators
The analytical capabilities of the three systems, as reported by the developers are presented in Table 2-2.
Instrument detection limits and accuracy and precision data are given in the table for four of the nine target
elements. As a result of analysis time constraints, only four elements were selected for analysis. These
performance data are included for informational purposes only and are not further evaluated or verified as a part
of this demonstration.
Table 2-2. Detection Level and Accuracy Estimates for the ASV and PSA Systems as
Reported by PNNL, NMSU, and ETG
Element
Chromium (Cr)
Cadmium (Cd)
Copper (Cu)
Lead (Pb)
ASV (EG&G)
Detection
Level
(mg/kg)
5
NR
NR
NR
Accuracy/
Precision
(%)
±33 / ±40
NR
NR
NR
PSA (TraceLab)
Detection
Level
(mg/kg)
NR
1
5
5
Accuracy/P
recision
(%)
NR
±20 / ±40
±20 / ±40
±20 / ±40
PSA (Metalyzer)
Detection
Level
(mg/kg)
NR
1
5
5
Accuracy/
Precision
(%)
±20 / ±40
±20 / ±40
±20 / ±40
Notes: Accuracy levels are given relative to conventional laboratory analysis using EPA standard methods.
NR = Not reported.
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Chapter 3
Demonstration Design and Description
Technology Demonstration Objectives
The primary objective of this demonstration was to prepare and execute a scientifically sound test protocol for
the collection and analysis of data from metals-contaminated soil samples as determined by candidate
technologies. To assist the technology developers in evaluating the data collected from their instruments, the
Consortium conducted a parallel analysis of replicate soil samples by conventional laboratory methods.
Table 3-1 lists the demonstration participants and their accompanying technologies.
Table 3-1. Demonstration Participants
Participant
Los Alamos National Laboratory
MelAok Instruments, Inc.
Pace Environmental Laboratories, Inc.3
Battelle Pacific Northwest National Laboratory
MSE-HKM, Inc.
Sandia National Laboratories Environmental
Restoration Program Laboratory
Columbia Analytical Services, Inc.
Technology/ReferenceLaboratory
Laser-induced breakdown spectrometer(LIBS) (technology)
Laser-induced breakdown spectrometer (technology)
Flame atomic absorption spectroscopy (technology)
Anodic stripping voltammetry (technology)
Inductively coupled plasma atomic emission spectroscopy
(reference laboratory)
Inductively coupled plasma atomic emission spectroscopy
(reference laboratory)
Inductively coupled plasma emission spectroscopy and
flame atomic absorption spectroscopy (reference laboratory)
"Point of contact: Khris Olsen (509) 376-4114.
The technologies demonstrated, with one exception, were at the low end of the maturity curve. Consequently, a
rigorous technology assessment was not performed on these systems. The soil analysis data from the analytical
laboratories were validated and provided to the developers along with their own data for use in further
development and refinement of their instruments.
Site Selection and Description
To properly assess a field screening technology, a suitable site with soil contaminated by metals was required.
Early in the project, a demonstration plan was developed that presented the following criteria to assist in site
selection.
The site soils must contain a wide concentration range of the heavy metals arsenic, cadmium, chromium,
copper, iron, manganese, lead, silver, and zinc.
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The site must have at least two sample col lection areas with significantly different soil types.
The heavy metal concentration levels in the soil must be reasonably well characterized and documented.
The site must be readily accessible for conducting technology demonstrations.
The DOE Characterization Monitoring and Sensor Technology Cross-Cut Program had funded a demonstration
project through the Western Environmental Technology Office in Butte, Montana, at a metals-contaminated soil
site. The project had been awarded to MSE-HKM, Inc., an on-site contractor (hereafter referred to as MSE).
Consortium members, including the EPA Environmental Sciences Division of the National Exposure Research
Laboratory (NERL) and Sandia National Laboratories (SNL), chose to augment this demonstration by soliciting
additional technologies for demonstration and by providing additional laboratory analysis of the soil samples
used in the demonstration. During the preparation of the demonstration plan, two sites, Butte/Silver Bow Creek
and Anaconda Smelter/Mill Creek, were selected for the study. Figure 3-1 shows the general location of the sites.
Site 1 Butte/Silver Bow Creek
Location
The Butte/Silver Bow Creek site extends from the west side of Butte, Montana, along Silver Bow Creek to the
confluence of Sand Creek and Silver Bow Creek. The site is contaminated by heavy metals from historic and
modern mining and mill tailings deposits. Figure 3-2 shows the Butte/Silver Bow Creek collection site.
Upper Clark Fork
Superfund Sites
Silver Bow Creek/
Butte Area Site
Figure 3-1. Montana regional map showing the Silver Bow and Mill
Creek (Anaconda) sampling sites.
11
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SBH - High metali concentration
SBM - Medium matal* concentration
SBL - Low metals concentration
Figure 3-2. Local map of the Silver Bow sampling site.
History
Mining activities in the Butte area started with a group of small gold, silver, and copper mining operations. Butt
became an important mining district in the late 1800s as the size and number of mines grew. With the growth of
ore extraction activities came the need for easy access to ore processing facilities. Consequently, many mills an;
smelters were constructed in the region to concentrate and purify ores from the underground mines. Waste
materials from the mineral extraction process, known as tailings, were impounded in ponds and were eventually
discharged into Silver Bow Creek.
Approximately 230 km of stream and riparian habitat have been affected by these local operations. The region tf
contamination begins in Butte and extends westward along Silver Bow Creek to the Milltown Reservoir.
Significant mill tailings deposits are found along the creek as well as dispersed over the Silver Bow Creek flood
plain, resulting in a large area of contaminated soil.
During the 1960s and 1970s, mining activities gradually shifted from underground to open-pit mining. In 1982,
the Anaconda Minerals Company discontinued underground mining in Butte. In the same year, the EPA started
site contamination investigations in the area. By the early 1990s, mining operations had ceased and remediation
efforts were implemented.
Characteristics
The Butte/Silver Bow Creek sample area encompasses approximately 5.5 km of Silver Bow Creek. The
principal groundwater-bearing structure is a shallow alluvial aquifer composed of coarse-grained fan and
floodplain deposits. Bedrock formations are found at approximately 1 to 10 m below the surface. The deposits
are moderately permeable and are hydraulically connected to the perennial Silver Bow Creek surface stream.
Because the Silver Bow Creek is an eroding bedrock valley, the erosion slopes are narrow and near the stream.
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A relatively high surface stream gradient of 3.2 mm/m produces a high-energy stream characterized by a straight
stream channel and narrow floodplain.
Mill tailings deposits at the Butte/Silver Bow Creek site have produced widespread soil contamination. The
contaminated areas are continuous and confined to the narrow floodplain surrounding Silver Bow Creek.
Preliminary characterization efforts, conducted during the site selection process, revealed that heavy metals
deposits are most concentrated in the top 15 to 50 cm of the soil to a maximum depth of 1.2 m (MSB, 1996). A
soil analysis to assess the degree of mill tailings contamination of the local soils was carried out by MSB.
Surface soil analysis results for three sampling locations showing the range of contaminant metal concentrations
are summarized in Table 3-2.
Table 3-2. Typical Heavy Metal Soil Contamination at the Butte/Silver Bow
Creek Site
Metal
Aluminum (Al)
Arsenic (As)
Cadmium (Cd)
Chromium (Cr)
Copper (Cu)
Iron (Fe)
Lead (Pb)
Manganese (Mn)
Silver (Ag)
Zinc (Zn)
Soil Concentration (mg/kg)
Sample 1
6,780
1,200
41.1
7.23
2,150
31,800
2,110
2,490
90.4
12,300
Sample 2
2,990
297
11
6.25
1,350
16,500
681
1,160
15.9
2,710
Samples
9,480
174
0.46
13.5
315
12,200
182
2,170
231
321
Note: Data from a preliminary soil assessment by MSE-HKM, Inc. See MSE, 1996.
Sampling Location Details
The first of three sample areas was selected at a location approximately 45 m north of the Silver Bow Creek bed
in the creek floodplain. The predemonstration samples from this area generally showed the highest
concentrations of contaminant metals of all predemonstration samples. Consequently, this site was designated
"SBHD" (Silver Bow-high demonstration).1 A 27-m, northwest-to-southeast transect of the SBHD sample area
was divided into ten 400-cm2 sample plots equally spaced at 3-m intervals along the transect. Each plot was
designated with the SBHD identifier followed by a plot number ranging from 1 to 10, with the number increasing
from northwest to southeast.
A second sample area was located stream-side, within the Silver Bow Creek bed, and was designated area
"SBMD" (Silver Bow-medium demonstration). A 27-m, northwest-to-southeast transect running along the
streamside of the SBMD sample area was divided into ten 400-cm2 sample plots, equally spaced at 3-m
intervals. Each plot was designated with the SBMD identifier followed by a plot number ranging from 1 to 10,
with the number increasing from northwest to southeast.
A third sample area was located on a hilltop overlooking the SBHD and SBMD sites approximately 120 m from
the stream side and was designated area "SBLD" (Silver Bow-low demonstration). A 27-m, northwest-to-
1 The naming convention uses high, mid, and low as a matter of convenience. These designations do not always correspond
to the metal concentrations encountered in the samples.
13
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southeast transect running along the hill top of the SBLD sample area was divided into ten 400-cm2 sample plots,
equally spaced at 3-m intervals. Each plot was designated with the SBLD identifier followed by a plot number
ranging from 1 to 10, with the plot number increasing from northwest to southeast.
Site 2 Anaconda Smelter/Mill Creek
Location
The Anaconda Smelter/Mill Creek sample area, as shown in Figure 3-3, covers approximately 16 km2 between
Anaconda and Opportunity, Montana. The site is located approximately 40 km west of Butte and near the
Anaconda smelter. It is bounded by state highway 1 to the north and state highway 241 to the west. Flue dust
produced by 100 years of smelter operation has contaminated the site with heavy metals by the process of aerosol
deposition.
30m«t«r»
MCH - High metele concentration
MCM - Medium meule concentration
MCL - Low metili concentration
Figure 3-3. Local map of the Mill Creek sampling site.
History
The first copper smelting facilities to process ore from Butte area mining operations were in the Anaconda
Smelter/Mill Creek area. The site consists of two facilities, the Upper Works, started in 1884, and the Lower
Works, started in 1888. A silver ore refinery was also located between the copper smelting complexes. Smelter
flue dust containing high levels of metals such as copper, arsenic, cadmium, and lead was produced as a by-
product of the Anaconda smelting activities. Until 1976, flue dust generated by reverberatory furnaces was
reprocessed for arsenic recovery. After 1976, the reverberatory furnaces were replaced by an electric furnace,
and flue dust was collected by a pollution control system.
From 1976 through 1992, nine dust piles with a total volume of approximately 350,000 m3 were deposited on the
hills around the smelter. From 1985 through 1992, wind scouring of the dust piles was controlled by surfactant
14
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application. Since 1992, however, considerable amounts of the flue dust have been resuspended and deposited
downwind from the smelter stack and dust piles.
Characteristics
The Anaconda Smelter/Mill Creek sample area is immediately adjacent to the Anaconda Smelter site. The area
consists of a thick layer of moderately permeable, coarse-grained, floodplain deposits over bedrock. Mill Creek
and the sample collection area lie in a structurally broad valley with an accompanying wide floodplain. Mill
Creek is also a tributary of Silver Bow Creek.
Deposition of smelter flue dust at the Anaconda Smelter/Mill Creek site has produced widespread soil
contamination with metals across the entire floodplain. Arsenic, cadmium, and lead are most concentrated in the
top 15 cm of the soil. Cadmium and lead concentrations decrease more rapidly with depth than does arsenic
concentration. Typical analysis results from three surface soil samples taken in the Mill Creek area are presented
in Table 3-3, as measured during the predemonstration site assessment carried out by MSB.
Table 3-3. Typical Heavy Metal Soil Contamination at the
Anaconda Smelter/Mill Creek Site
Element
Al
As
Cd
Cr
Cu
Fe
Pb
Mn
Ag
Zn
Concentration (mg/kg)
Sample 1
5,150
1,170
7.9
10.3
1,320
17,400
515
305
10.3
689
Sample 2
3,450
887
4.66
6.71
573
13,800
400
146
5.03
577
Samples
3,640
617
2.92
6.52
506
16,300
277
106
4.63
414
Note: Data from a preliminary soil assessment by MSE Inc.. See MSE, 1996.
Sampling Location Details
The first Mill Creek sampling location was approximately 115m southwest of the highway 1 and highway 241
intersection, and was designated area "MCHD" (Mill Creek-high demonstration).2 A 27-m, southwest-to-
northeast transect of the MCHD sample area was divided into ten 400-cm2 sample plots, equally spaced at 3-m
intervals along the transect. Each plot was designated with the MCHD identifier followed by a plot number
ranging from 1 to 10, with the plot number increasing from southwest to northeast.
A second sample area was located approximately 180 m southwest of the intersection of highway 1 and highway
241, and was designated area "MCMD" (Mill Creek-medium demonstration). A 27-m, west-to-east transect of
the MCMD sample area was divided into ten 400-cm2 sample plots, equally spaced at 3-m intervals. Each plot
was designated using the MCMD identifier followed by a plot number ranging from 1 to 10, with the plot
number increasing from west to east.
2 The naming convention uses high, mid, and low as a matter of convenience. These designations do not always correspond
to the metal concentrations encountered in the samples.
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The third Mill Creek sample area was located approximately 115m south of the intersection of highway 1 and
highway 241 and was designated area "MCLD" (Mill Creek-low demonstration). A 27-m, west-to-east transect
of the MCLD sample area was divided into ten 400-cm2 sample plots equally spaced at 3-m intervals. Each plot
was designated using the MCLD identifier followed by a plot number ranging from 1 to 10, with the number
increasing from west to east.
Sample Collection, Handling, and Distribution
Sampling Methods
Ten samples were taken from each of three locations at two sites for a total sample size of 60. The soil in each
400-cm2 sample plot was removed with a clean stainless steel hand trowel to a depth of 2.5 cm, passed through a
No. 10 mesh sieve, homogenized by five passes through a 14-channel riffle splitter, and placed in 1,000-cm3
labeled glass containers. Each 1,000-cm3 sample contained approximately 2.5 kg of soil. Sample collection
proceeded from levels of low metals concentration to high concentration. All sampling equipment was
decontaminated by a detergent wash and double rinse with deionized water between use at each sampling
location.
Sample Handling
All soil samples were taken to MSE, Inc., where they were dried for 12 hours at 105 °C in an oven. After drying,
each soil sample was split ten ways. Each split contained an estimated 150 g of soil and was placed in a labeled
container. Splits were distributed to analytical laboratories, various technology demonstrators, and archives.
Soil sample collection, homogenization, drying, and splitting were carried out during the week of September 18,
1995, by SNL and MSE laboratory personnel prior to the technology demonstration. Samples were stored in
locked coolers at room temperature until distribution.
Sample Distribution
The distribution of the ten sample splits is shown in Table 3-4. The sample numbering convention was in the
format: AABB-NN-nnn, where
AA = Site (SB or MC)
BB = Transect (HD,MD or LD)
NN = PlotNo. (01-10)
nnn = Split No. (001-010)
With the exception of Columbia Analytical Services (CAS) and Los Alamos National Laboratory (LANL), each
analytical laboratory and technology demonstrator received a total of 64 samples (60 field soil samples plus 2
blank and 2 control samples). LANL received two sets of splits for a total of 124 samples and CAS received a
total of 32 samples (the 30 field samples plus 1 blank and 1 control sample), because only half of the field soil
samples were selected for analysis at this laboratory.
In addition to soil from the site, each laboratory and technology demonstrator received several quality control
samples. Included in this set were two blank soil samples and two control soil samples prepared and analyzed by
Environmental Resource Associates, Arvada, Colorado, a soils analysis quality control laboratory. These blank
and control samples consisted of topsoil that was dried, ground, sieved, and spiked with various metals (in the
case of the control sample). The soil was then thoroughly homogenized and split into samples that were
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Table 3-4. Distribution of Field Soil Sample Splits
Soil Sample
Split No.
01
02
03
04
05
06
07
08
09
10
Recipient Technology/ReferenceLaboratory
Los Alamos National Laboratory LIBS (technology)
Los Alamos National Laboratory LIBS (technology)3
MelAok Instruments, Inc. LIBS (technology)
Battelle Pacific Northwest National Laboratory-anodicstripping voltammetry (technology)
Pace Environmental Laboratories, Inc.-flame atomic absorption spectroscopy (technology)
MSE-HKM, Inc. (reference laboratory)
Sandia National Laboratories (reference laboratory)
Columbia Analytical Services, Inc. (reference laboratory)
Sandia National Laboratories- archive
Sandia National Laboratories- archive
Originally, two similar laser-induced breakdown spectroscopy systems were to be fielded by Los Alamos researchers, with each requiring a
sample split. As a result of logistical difficulties, only one system was actually brought to the site and used in the demonstration.
subjected to a round-robin analysis at qualified laboratories. The results from 20 or more analyses of the soil
batch were used to define a mean value for each element along with a 95 percent confidence interval (mean value
± 2 x standard deviation).
Each laboratory and developer of a demonstration technology was also instructed to produce matrix duplicates of
at least two of the field soil samples so that a measure of analytical precision could be obtained. In the interest of
having a diverse but manageable list of target elements, nine metals were selected for analysis by all participants:
arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), lead (Pb), manganese (Mn), silver (Ag), and
zinc (Zn).
Laboratory Selection and Analysis Methodology
Columbia Analytical Services
Analysis of soil samples was carried out at Columbia Analytical Services, Inc., in Kelso, Washington, along with
analysis of several quality control samples. Analysis was carried out at this EPA Contract Laboratory Program
(CLP) laboratory to provide a soil analysis data set that could be used as a cross check with the more
comprehensive soil sample analysis carried out at the MSB laboratory. As a result of program cost constraints,
analysis at the CAS laboratory was limited to half (30) of the 60 field soil samples collected during the
demonstration.
Soil samples were digested using EPA SW-846 Method 3050A: Acid Digestion of Sediments, Sludges, and Soils.
Columbia Analytical Services analyzed all 32 control and field soil samples by inductively coupled plasma
atomic emission spectroscopy using the EPA SW-846 Method 6010A.
The laboratory also generated its own duplicates of the 32 soil, control, and blank soil sample digestates and
conducted a second analysis by atomic absorption spectroscopy (AAS) using EPA SW-846 Method 7000A. The
specific methods employed in the analysis included flame aspiration and graphite furnace. They are listed below
for each of the target elements.
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Ag (silver) Method 7760A: silver (atomic absorption, direct aspiration)
As (arsenic) Method 7060A: arsenic (atomic absorption, furnace technique)
Cd (cadmium) Method 7131 A: cadmium (atomic absorption, furnace technique)
Cr (chromium) Method 7190: chromium (atomic absorption, direct aspiration)
Cu (copper) Method 7210: copper (atomic absorption, direct aspiration)
Fe(iron) Method 7380: iron (atomic absorption, direct aspiration)
Mn (manganese) Method 7460: manganese (atomic absorption, direct aspiration)
Pb (lead) Method 7420: lead (atomic absorption, direct aspiration)
Zn (zinc) Method 7950: zinc (atomic absorption, direct aspiration)
A matrix duplicate sample was also made of original sample number MCLD-1-008. This duplicate was digested
and analyzed by ICP and AAS methods to give a measure of overall laboratory analytical precision on matrix
samples,
MSE Laboratory
The MSE laboratory, located near the sampling site in Butte, Montana, did the preassessment soil sampling and
analysis. It also performed, in collaboration with SNL, the actual demonstration soil sampling, processing, and
distribution. The MSE laboratory carried out a complete analysis of all demonstration soil and quality control
samples. Although MSE is not a CLP laboratory, it used standard EPA SW-846 methodology in its analyses.
The laboratory adheres to quality control procedures specified in the standard EPA analysis protocols used for
soils analysis and operates under a written quality assurance plan.
Sixty soil samples plus 2 control soil samples and 2 blank soil samples were digested using EPA SW-846
Method 3050A: Acid Digestion of Sediments, Sludges, and Soils. All 64 samples were analyzed by ICP using
EPA protocol SW-846 Method 6010A. Matrix duplicates were also made of 4 samples. These underwent
digestion and analysis by ICP so that a measure of method precision could be obtained for this particular soil
matrix.
SNL Environmental Restoration Program Laboratory
The SNL Environmental Restoration Laboratory was selected as an additional reference laboratory. This
laboratory primarily provides rapid screening data which are used in conjunction with conventional CLP-type
analysis for the Sandia internal environmental restoration program. A laboratory quality assurance/control plan
was under development during this study. Data from this laboratory were obtained with a mobile inductively
coupled atomic emission spectroscopy system. The unit is a conventional benchtop ICP system that has been
adapted for field use. The instrument exhibits higher detection limits and more calibration drift than benchtop
units normally used in the laboratory.
Soil samples were digested at the SNL laboratory in a slightly different manner than that used at the other two
laboratories. This laboratory used a microwave-assisted acid digestion method formally designated SW-846
Method 3051: Microwave Assisted Acid Digestion of Sediment, Sludges, Soils, and Oils. The SNL laboratory
analyzed all 64 soil and quality control samples by ICP using EPA protocol SW-846 Method 6010A.
Demonstration Narrative
Predemonstration soil samples were collected during the week of August 21, 1995. These samples were used by
the participants in instrument setup and calibration. The actual demonstration soil samples were collected
18
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September 18-22, about 1 week prior to the technology demonstration. Sample processing and packaging was
completed on September 24. Participants in the demonstration were on the site during the week of September
24-29. A complete set of 60 soil samples plus quality control samples were given to each of the participants at
the beginning of the week.
Because access to the actual soil sampling sites was limited and the local media were invited to observe activities
on selected days during the demonstration, the demonstration area was set up on an easily accessible, paved
parking lot about one-half mile from the Silver Bow sampling site. Several vans, tents and generators were
installed at the site to support the various systems. Temperatures ranged from freezing in the morning to the
mid-sixties during the day. Space heaters were used in some of the tents and vehicles during the cold morning
hours. The actual demonstration lasted 6 days; about 2 days were used for instrument setup, checkout, and
disassembly and 4 days for soil analysis. Participants worked at their own pace. A typical day during the
demonstration period began at 9 a.m. and ended at 7 p.m.
Deviations from the Demonstration Plan
A comparison of the demonstration plan prepared prior to the study and the actual conduct of the study as
recorded in the various field and data logbooks reveals a number of discrepancies, which are discussed below.
The initial soil sampling effort at Silver Bow Creek had to be repeated because a temperature control circuit
failed during sample drying. Soil temperatures were determined to be well in excess of the 105 °C specified
in the demonstration plan. The samples were discarded and additional samples were collected and
processed.
All soil samples were dried at an oven temperature of 175 °C instead of the 105 °C specified in the
demonstration plan. As noted in the previous paragraph, the primary oven failed and a backup oven had a
minimum temperature control level of 175 °C. In the interest of maintaining the project schedule, the
175 °C drying temperature was used.
Some of the soil sampling was carried out during inclement, rainy weather. Problems were encountered
when sieving moist soil with a No. 10 screen. Larger (No. 6 and No. 8) sieve sizes were used to facilitate
soil processing of the SBLD samples in the field. These and all other samples were homogenized following
sieving so demonstrators and laboratories received comparable samples. Intercomparison of SBLD,
SBMD, and SBHD samples was not done in this study, so sieve size differences among sample sets does
not appear to be significant.
The certificates of analysis that accompanied the soil control samples were distributed to participants after
all analytical results were submitted to SNL. Access to control soil sample results during the demonstration
was not specified in the demonstration plan, however. This procedure did not compromise the
demonstration design since final analytical data were submitted prior to access to control sample results.
Analysis of the data from the CAS laboratory revealed beyond a reasonable doubt that two blocks of five
samples were mislabeled. The specific blocks in question were from the Mill Creek sampling site, series
MCHD and MCMD. The switch could have occurred either as a result of mislabeling of sample containers
in the field or during receipt and logging of the samples at the CAS laboratory. An investigation to
determine the source of the error was carried out; however, the source could not be determined from the
available chain-of-custody documentation. Despite the fact that a clear incidence of mislabeling could not
be determined, the data were corrected since the switch was unmistakable in the data analysis phase of the
project.
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Chapter 4
Laboratory Data Results and Evaluation
Laboratory Data Validation Methodology
One of the objectives of this study was to provide the technology developers with a validated set of soil analysis
results from reference laboratory methods for comparison with field results. Both qualitative and quantitative
laboratory data quality indicators were used in the data validation process for all participating laboratories.
These are described more fully in the following sections.
Qualitative Factors
Qualitative factors included degree of experience of the laboratory staff, experience in soils analysis, level of
certification, if any, and past performance on laboratory audits. These factors were used along with additional
quantitative factors in assessing laboratory data quality.
Quantitative Factors
Five specific quantitative factors were also evaluated in the soil analysis data set provided by each laboratory to
assist in the data validation process. These factors were blank sample analysis, control sample analysis,
analytical precision, instrument stability, and spike recovery. Each factor is described more fully in the
following paragraphs.
Soil Blank Analysis
The results from the blind blank soil analyses were directly compared with the information given on the
certificate of analysis accompanying the samples, which were provided by Environmental Resource Associates.
These analysis data were used as a semiquantitative check on the methods used by the laboratories to detect
contaminant levels, because the soil contained either low or nondetectable levels of many of the target elements.
Control Soil Sample Analysis
The results from the blind control soil sample analysis from each reference laboratory were directly compared
with the certified heavy metal concentrations in the soil, as determined by interlaboratory analyses of the same
lot of soil. Environmental Resource Associates prepared the soil and coordinated the interlaboratory study. An
analysis certificate shipped with the control sample included a certified value and a "performance acceptance
limit"1 for each element in the sample. The results from the control samples from each of the laboratories were
The certificate from Environmental Resource Associates indicates that the performance acceptance limits for each element
"closely approximate the 95% confidence interval about the certified value."
20
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an important indicator of laboratory performance levels. Analysis results that fell within the 95 percent
confidence interval were judged to indicate an acceptable level of performance.
Duplicate Analysis Precision
Laboratory analytical precision was estimated by calculating the relative percent difference (RPD) between two
analyses of predigestion duplicate soil samples prepared by each laboratory. The following equation was used.
where
RPD = relative percent difference
Ya = sample result
Yb = duplicate sample result
Relative differences in excess of 20 percent, as specified in EPA Methods 6010A (ICP) and 7000A (AAS), are
taken to indicate questionable laboratory analytical process control.
Instrument Stability
The analytical laboratories also carried out continuing calibration procedures during their sample analyses. In
this procedure, a calibration solution for each of the target elements was analyzed at the onset of the analysis.
The same solutions were periodically analyzed throughout the course of the analysis, typically after every tenth
sample analysis. The results of each check were reported as a percent recovery of the starting calibration value.
The data give an indication of calibration drift encountered over the course of an extended analysis interval. The
control limits, prescribed in EPA Methods 6010A and 7000A, are ± 10 percent of the initial calibration value.
Calibration checks falling outside these limits indicate inadequate analytical process control.
Matrix Spike Recoveries
Some of the laboratories also conducted spiked sample recovery measurements on one or more soil samples. In
this procedure, a measured quantity of each of the target elements was added to a laboratory replicate of a soil
sample. Digestion and analysis of unspiked and spiked samples were carried out. The difference between the
spiked and unspiked sample was compared with the known spiked amount and expressed as a percent sample
recovery. Sample recoveries falling outside the range of 75 to 125 percent, as prescribed in EPA Methods 6010A
and 7000A, are indicative of questionable analytical process control.
Laboratory-to-Laboratory Data Comparison
Summary statistical parameters and data presentation formats were used to provide a quantitative measure of the
degree of comparability among the data sets from the participating laboratories. These are more fully described
below.
21
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Method Difference
The method difference or bias is a summary statistic of the difference observed for a particular method relative to
a reference method. The mean percent difference (MPD) of one data set versus another reference data set was
calculated using the following equation:
(100)
where,
MPD = mean percent difference
n = number of measurement values
x, = designated reference value
y, = paired value from other method
Scatter Plots
Scatter plots and associated statistical parameters were also used to compare data from one laboratory with that
from another. These plots enable a quick visual comparison. Related statistics include a least-squares method
linear regression giving the best straight line through the data. The regression line has the following equation:
Y=AX+B
where A is the slope of the line and B is the ^-intercept value.
The Pearson product-moment correlation coefficient (r) was also computed. This is a measure of the degree of
linearity between the two data sets (Havlicek and Grain, 1988). A correlation coefficient of 1 suggests perfect
correlation while a correlation of 0 indicates no correlation between two data sets.
Statistical Tests
The statistical equivalence of the analytical laboratory data sets was further evaluated with the Wilcoxon
matched pair test. In essence, this nonparametric statistical test allows assessment of whether a statistically
significant bias exists between two methods on a set of paired samples. The test produces a test statistic through
an arithmetic scheme that ranks the differences encountered in sample pair results. The test statistic is essentially
a measure of the ratio of observed differences in the two data sets to expected random differences in the same
two data sets. Knowledge of the test statistic and the sample size allows one to determine whether the
differences encountered in the paired data values can be attributed to the random variation that would be
expected to occur between equivalent methods, or to bias in the methods or data sets. The quantitative aspect of
the test is related to the p-value, which is associated with the test statistic and the number of paired samples used
in the test. By convention, a p-value of 0.05 is often used as the decision point as to whether a statistically
significant bias exists. For example, the determination of a test statistic with an associated p-value of 0.05
indicates that the observed differences between two methods carry a 5 percent chance of being attributable to
random variation alone. Additional information on the use of this nonparametric test for paired-sample analysis
can be found in Conover (1980).
The statistical test results are used in conjunction with linear regression parameters such as slope and intercept to
further compare the two data sets. The statistical test provides an indication as to whether one method is
22
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consistently biased relative to another. A second determination is made regarding the extent of that bias, if it
exists. For example, consider the case where the statistical test indicates a significant bias between two sets of
laboratory data. Examination of the linear regression data may reveal that the methods differ by only 5 percent.
In consideration of the overall uncertainties encountered in the sampling and analytical processes, a 5 percent
method bias is tolerable and is not a reason for rejecting one data set over another. This two-phase evaluation of
the data is discussed further in the section dealing with laboratory-to-laboratory data comparison.
Columbia Analytical Services Data
Half of the total number of soil samples generated in this demonstration project were analyzed by CAS. A more
detailed qualitative and quantitative assessment of the laboratory's performance follows.
General Indicators of CAS Data Quality
As noted earlier, CAS is a CLP laboratory and follows standard EPA analysis protocols and procedures in its soil
analysis work. Since it is a part of the CLP program, the laboratory also undergoes periodic system audits and
analytical process audits through the use of blind control sample analyses. The laboratory provided a quality
assurance document along with the analysis results for the sample set submitted. Laboratory performance
indicators, such as matrix spike recovery data, duplicate sample summary data, laboratory internal control
sample analysis, and periodic instrument blank and calibration data collected throughout the analysis interval
were included in the report. CAS also provided copies of sample chain-of-custody forms and all raw data
generated in the analysis. No warning flags or out-of-limits quality control indicators were noted in the cover
letter provided with the quality control data package. Personnel from MSE audited the CAS laboratory. The
audit confirmed that CAS operations were in accordance with the standard procedures used in these analyses.
Quantitative Indicators of CAS Data Quality
The analytical results and an accompanying quality control data package were sent by CAS to the Sandia project
leader. The data package contained concentration levels or nondetects reported for all nine target elements in all
32 samples. Specific quantitative data quality factors are discussed in the following paragraphs.
Blank Soil Sample Results
Analytical results from the soil blank analysis are given for CAS ICP and AAS methods as well as for other
participating laboratories in Table 4-1. The "true" metal levels in the soil, as determined by round-robin analysis
of the blank soil lot number at qualified laboratories, are given in the final column of the table.
The CAS analysis results on the blank soil sample track the certified levels reasonably well. Detection levels for
the CAS ICP are slightly higher for As and Pb than for the other target elements. Iron, manganese, chromium,
and zinc are all reported at levels very close to the certified levels. During the course of the analysis, a blank
solution was periodically analyzed with the ICP instrument to check for contamination or excessive calibration
drift. The results from these periodic checks showed consistent instrument detection levels in the expected
concentration range for all target elements.
Control Soil Sample Results
The analytical results for the control soil samples are shown in Figure 4-1 as a percent difference from the
certified value for each element. The analysis certificate supplied with the control soil sample also gives a 95
23
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Table 4-1. Reference Laboratory Blank Soil Sample Results
Element
As
Cd
Cr
Cu
Fe
Pb
Mn
Ag
Zn
Metal Concentration Level (mg/kg)
CAS ICP
<40
<1
5
8
6,760
<20
159
<2
27
CAS AAS
1
<0.5
<10
6
7,210
<10
167
<2
28
MSE ICP
2.1
0.4
6.7
5.6
7,740
9.3
172
0.4
24.4
SNLICP
<98
<8
<19
<76
6,350
<13
<38
<6
76
Certified Level
<2
<1
7
<5
8,180
9
159
<2
24
Notes: A "less than" (<) symbol indicates not detected. The number following the symbol gives the detection limit. MSE and
SNL data shown are the average of two analyses.
percent confidence interval about the average value as determined by a round-robin study of the soil batch by a
number of qualified analytical laboratories. The upper 95 percent confidence limit (UCL) and lower 95 percent
confidence limit (LCL) are also plotted in Figure 4-1. The CAS results show that the results for all of the target
elements fall within these limits. Most fall within ±10 percent of the certified value for both ICP and AAS
analysis. These data indicate acceptable laboratory performance.
Duplicate Sample Analysis Results
Duplicate results from two soil samples analyzed by both ICP and AAS are given in Figure 4-2. The relative
percent difference between duplicate samples, as described earlier in this section, is plotted for each of the runs.
Plotted RPD values of unity indicate a value of less than or equal to 1. With two exceptions, all RPDs fall within
20 percent. The two exceptions are Cr by AAS and Cd by ICP. No explanation is given as to why these
duplicates showed poor agreement. In general, however, the data reveal acceptable analytical process control.
No precision data are shown for Cr analysis by AAS on sample SBLD-1-008 since a no-detect was reported for
at least one of the determinations.
Instrument Stability
An indication of instrument stability throughout the course of the analysis is given by continuing calibration
verification (CCV) analysis. A known standard is repeatedly run, typically following every 10 analyses on the
ICP or AAS instrument, in order to check instrument calibration drift. The time interval between successive
calibration checks is on the order of 1 hour. Typical CCV results for CAS ICP analysis of four elements are
given in Figure 4-3. The results are plotted in a control chart format with percent recovery relative to the starting
value of the calibration solution on the^-axis and the calibration number on the *-axis. All CCV data for all
target elements from both ICP and AAS analysis indicated recoveries between 90 and 110 percent, which is
within the quality control criteria specified in the method.
Spike Recoveries
Spike recovery data from the CAS analyses are shown in Figure 4-4. Here the deviations from 100 percent
recovery are shown for four spiked soil samples, two of which were analyzed by ICP and two by AAS methods.
In accordance with the standard method, the laboratory did not report recoveries for spiked elements when the
24
-------
o
60
40
20
0 _
§
g -20
-40 -
-60
-80
QCAS-AAJT
CAS-ICP
. LCL
Ag As
Cd
Cr Cu Fe
Element
>UCL
Pb Mn Zn
Figure 4-1. Control soil sample analysis results from CAS. The upper and
lower 95 percent confidence limits with respect to the certified values are also
shown.
As
Ag
Zn
]SBLD-1-008 (ICP) HMCLD-1-008 (ICP) aSBLD-1-008 (AAS) gMCLD-1-008 (AAS)
Figure 4-2. Duplicate soil sample analysis results from CAS.
25
-------
234
Calibration No.
As + Cr -*"Pb
Zn
Figure 4-3. Continuing calibration verification results from CAS.
50
40
30
20
10
0
-10
-20
-30
-40
-50
I
5?
o
o
c
o
o>
Q
As Cd Cr Cu Fe Pb
Element
Mn
Zn
|BSBLD-1-008(ICP) [||MCLD-1-008 (ICP) >SBLD-1-008 (Flame) >MCLD-1-008 (Flame)
Figure 4-4. Spiked soil sample recovery results from CAS. See text for explanation of missing
data.
26
-------
spike amount added was less than 25 percent of the unspiked metal content of the sample. Hence, no data are
seen for iron, which was present at high concentration levels in the unspiked soil samples. Spike levels were too
low for As, Cu, Mn, and Zn in selected samples as well, as reflected by no data entries in the accompanying
graph. Standard ICP Method 6010A specifies lower and upper recovery limits at 75 and 125 percent,
respectively (corresponding to ±25 percent difference as plotted in Figure 4-4). The data show that with the
exception of Cr, none of the valid spike recovery levels fall outside this range.
CAS Performance
The foregoing quantitative and qualitative indicators reveal that overall performance of the CAS laboratory was
acceptable. In particular, analysis of blank soil and control soil samples by ICP and AAS reveals acceptable
performance. Spiked sample analysis using the soil matrix generated in the study also gave acceptable recoveries
in all cases, except Cr, in which an adequate spike of each target element was introduced into the original soil
sample. Instrument stability, as evidenced by periodic calibration checks, was also within control limit
guidelines. Together, the quality control parameters suggest a high level of confidence in the accompanying
field soil sample data.
MSE-HKM Data
This DOE contract laboratory has not been part of the EPA CLP program; however, in practice, the laboratory
follows CLP guidelines and standard EPA analysis protocols. A more detailed qualitative and quantitative
assessment of the laboratory's performance follows.
General Indicators ofMSE Data Quality
MSE has a complete quality assurance/control plan, which was sent to the SNL project leader as a part of the
analysis results package. A member of the SNL project team also conducted an audit of the MSE laboratory
prior to the demonstration to determine compliance with standard EPA methods used in this analysis. The audit
report indicated acceptable laboratory procedures and conformance with standard methods used in these
analyses.
MSE included quality control sample documentation in its package. Laboratory performance indicators such as
matrix spike recovery data, duplicate sample summary data, results from an in-house control sample analysis,
periodic instrument calibration data throughout the analysis interval, and periodic blank analysis data throughout
the analysis interval were included. Several out-of-limits conditions were noted in the cover letter associated
with the data package. These anomalies are discussed in detail in later sections of the data presentation.
Quantitative Indicators of MSE Data Quality
Blank Soil Sample Results
Data from the quality control blank soil sample are given in Table 4-1, along with similar data from other
participating laboratories. Detectable amounts of all target elements were reported by MSE, and the agreement
between MSE values and the certified blank soil levels was the best of all three laboratories. The MSE
laboratory detection levels for most of the target elements were the lowest reported of all the participating
laboratories. During the course of the analysis, a blank solution was periodically analyzed with the ICP instrument
to check for contamination or excessive calibration drift. Results from these periodic checks showed consistent
instrument detection levels in the expected concentration range for all target elements.
27
-------
Control Soil Sample Results
The analytical results for control soil samples are shown in Figure 4-5 as a percent difference from the certified
value for each element. The analysis certificate supplied with the control soil sample also gives a 95 percent
confidence interval about the average value as determined by a round-robin study of the soil batch by qualified
analytical laboratories. The upper 95 percent confidence limit and lower 95 percent confidence limit are also
plotted in Figure 4-5. The MSB results, like those from CAS, fall within ±10 percent of the certified value for
nearly all of the target elements. Larger differences on the order of-30 percent are noted for Ag; however, the
reported results still fall within the 95 percent confidence interval about the mean certified level. These data
indicate acceptable laboratory performance.
Duplicate Analysis Results
The relative percent differences are plotted in Figure 4-6 for each laboratory analyses of the duplicate field soil
sample. All RPDs, with two exceptions, fall within the 20 percent criteria. The exceptions are an Mn
measurement with an RPD slightly in excess of 35 percent and a Cd measurement with an RPD of about 28
percent. Three other Mn and Cd precision determinations were within the 20 percent criteria specified in
standard Method 6010A. The laboratory uses an RPD limit of 20 percent as the acceptable range of variability in
duplicate analysis. Consequently, these results reveal an acceptable degree of analytical process control.
Instrument Stability
A plot of continuing calibration verification data for MSE analysis runs is given in a control chart format in
Figure 4-7. The results for only four elements are given for one of the four batch analyses conducted by the
laboratory. All CCV data for all analyses showed acceptable (± 10 percent of original value) recoveries,
indicating acceptable instrument stability over the course of the analyses.
Spike Recoveries
Spike recovery data from the MSE analyses are shown in Figure 4-8. Element recovery values are shown for
samples that were spiked prior to digestion and analysis of the sample on the ICP instrument. The laboratory
reported recoveries for spiked elements even when the spike amount was less than 25 percent of the unspiked
metal content of the sample. For comparability of the MSE data with CAS data, however, the same spike
validation criteria specified in EPA Method 6010A were applied to the MSE data as well. If the spiked amount
was less than 25 percent of the total elemental content of the sample before the spike, the spike was judged
invalid and no data were reported. Consequently, no data are shown for Fe, Cu, and other elements in selected
instances. The valid set of spike recovery data revealed that only Pb fell outside laboratory acceptance limits of
75 to 125 percent in one of the four batch analyses.
Additional Quantitative Laboratory Data Quality Measures
The MSE quality control data package also revealed several out-of-limits conditions for a serial dilution test that
was carried out on selected field samples. In this test, the concentrations of target elements were measured by
ICP in a dilution of the sample digestate. A fivefold or greater serial dilution was then made of this original
sample and also analyzed by ICP. The measured amount in the diluted sample, taking dilution factors into
account, is expected to agree to within ±10 percent of the original sample amount. Large deviations suggest
sample matrix effects, which may affect quantitative results. The sample matrix may introduce either positive or
negative interferents for a particular element when the sample is analyzed in a relatively concentrated form. The
data from these serial dilution tests are given in Table 4-2. The data show that the ± 10 percent limit of these
28
-------
60
40
0
£ -20
-40
-80 i_
_n
Ag
As
Cd
Cr Cu
Element
Fe
BMSE-ICP2
, LCL
Pb Mn
Zn
. 40
35
.2 25
£
H)
20
15
10
5
0
Figure 4-5. Control soil sample results from MSE. The upper and lower 95
percent confidence limits with respect to the certified values are also shown in
the graph.
As
gSBLD-1-006 (ICP) BSBMD-7-006 (ICP) ^MCLD-1-006 (ICP) gMCMD-7-006 (ICP)
Zn
Figure 4-6. Duplicate soil sample results from MSE.
29
-------
CO
1
.41
OT
14
o
s
o
o
to
CC
105'
104-
103-
102-
101-
100
99
98
97
96
95
^ j-i ^ y
"i'iia^i'*"'* "»«-,: >"/
-?.?:», *T3( /.»
* *"/
2 3 4 5 6.7 89 10
Calibration Check No.
As
Cr
Figure 4-7. Continuing calibration verification results from MSE.
60 - -
As
Zn
|$SBLD-1-008 (ICP) HSBMD-7-008 (ICP) QMCLD-1-008 (ICP) >MCMD-7-008 (ICP)
Figure 4-8. Spiked soil sample recovery results from MSE. See text for explanation of
missing data.
30
-------
Table 4-2. Serial Dilution Results from WISE
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
Percent difference between measurements at two dilution levels
Sample No.
SBLD-1
62
24
48
17
2.7
1.9
1.7
1.4
0.2
Sample No.
SBMD-7
2.7
0.9
8.3
71
2.6
0.1
1.4
3.6
0.2
Sample No.
MCLD-1
4.2
4.1
64
7.0
2.6
1.7
0.1
4.7
0.2
Sample No.
MCMD-7
100
6.8
39
11
5.7
5.8
4.7
13
4.8
Note: Those values in excess of 10 percent are shown in bold type.
measurements was exceeded for Ag, As, Cd, Cr, and Pb in selected dilution tests. Although these results are not
cause for exclusion of the data, they do reveal that, for at least some of the samples, sample matrix effects
contribute to overall uncertainty in the analytical results.
MSE Performance
The MSE laboratory analysis results on blank and control soil samples, instrument precision and stability, and
spike recovery, in general, reveal acceptable laboratory process control. Several out-of-limits warnings were
encountered in the quality control reports; however, their presence does not warrant rejection of the data set.
Serial dilution recoveries outside the ±10 percent range indicate that sample matrix effects were influential in the
overall quantitative recovery of the field soil samples.
Sandia National Laboratories Environmental Restoration Program Laboratory Data
The SNL Environmental Restoration Laboratory was selected as an additional laboratory. This laboratory
primarily serves to provide rapid screening data which are used in conjunction with CLP-type analyses for
Sandia's internal environmental restoration program.
A quality assurance/control plan was under development during this study. In this analysis the SNL laboratory
followed formal laboratory procedures for soil analyses. Data from this laboratory were obtained with a mobile
laboratory ICP-AES system (shortened to ICP in this report). The unit is a conventional benchtop unit that has
been adapted for field use. Consequently, it exhibits higher detection limits and more calibration drift than the
ICP systems commonly used in the laboratory. A more detailed qualitative and quantitative assessment of the
laboratory's performance follows.
General Indicators of SNL Laboratory Data Quality
The SNL laboratory followed the SW-846 analysis protocols in the soil analysis. The demonstration project
leader did not receive a copy of the laboratory quality assurance plan because the plan was under development at
the time of the demonstration. The SNL laboratory did provide some quality control data such as CCV and
method blank results.
31
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Quantitative Indicators ofSNL Laboratory Data Quality
Blank Soil Sample Results
Blank soil data for SNL are presented in Table 4-1, along with similar data from the other participating
laboratories. Nondetectable amounts of all except two target elements were reported by SNL. Detection limits,
in general, were higher for SNL than for the other laboratories owing to the characteristics of the mobile ICP
instrument used in this analysis. Some of the elements, such as Cr and Pb, that were known to exist in the blank
were not detected in the SNL blank analysis as a result of these high detection levels.
Control Soil Sample Results
The analytical results for control soil samples are plotted in Figure 4-9 as percent difference from certified
values. The results show that, with the exception of Ag, all of the target element results fall within the lower and
upper bounds of the 95 percent confidence interval established by the quality control laboratory that developed
and tested the control sample. In general, the results for the target elements fall within ±30 percent of the
certified value. Silver results fall outside the lower confidence limit by a margin of nearly 20 percent.
Discussions with laboratory personnel indicated that these results were most likely a result of the poor solubility
of silver in the microwave digestion technique used in this analysis. The microwave method relies solely on
nitric acid rather than on a mixture of nitric and hydrochloric acids used in the conventional digestion technique.
With the exception of the silver analysis, the results reveal acceptable laboratory performance.
Duplicate Analysis Results
No duplicate sample analyses were conducted by the SNL Environmental Restoration Program laboratory.
Instrument Stability
A plot of CCV data for four elements in the SNL runs is given in control chart format in Figure 4-10. Calibration
recoveries fell outside the ±10 percent limits for the following elements: Cd, Cr, Cu, Pb, and Zn. Recovery data
outside the normal control limits revealed stability problems attributable to the mobile ICP system.
Spike Recoveries
No spike recovery analysis was done by the SNL Environmental Restoration Program Laboratory.
SNL Laboratory Performance
Laboratory results for the control soil samples fell within the 95 percent confidence interval of the certified soil
concentration value of the standard for all elements except Ag. The CCV data were outside the normal tolerance
limits of ±10 percent by as much as a factor of two for some of the target elements. Duplicate analyses were not
run on any of the field samples. Consequently, no measure of instrument precision on the actual field soil sample
matrix was available. Matrix spike recovery analysis also was not carried out. In light of the limited extent of
laboratory quality control data, and the fact that a less stable mobile ICP system was used, the judgment was
made to regard these data as informational and not include them in the validated data set from the other reference
laboratories.
32
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125
120
115
0)
| 110
J5 105
o 100 -
1 95
I 90
* 85
80
75
80
60
> 20 .
"S
1 0
Difference from Ci
j». ro
0 0
3*
-60 -
-80 _
-100
-
A
g
In rm
Fl J 1
til ^ n . 1
_
As Cd Cr Cu Fe Pb
Element
Fl
IlLl n_Tl
QSNMai
QSNLIbi
OSNL2a!
SNL2b
» LCL ; ;
»UCL ! |
1
Mn Zn
Figure 4-9. Control soil sample results from SNL. The upper and lower 95 percent
confidence limits with respect to the certified values are also shown in the graph.
3 4
Calibration No.
.As . -t,. Cr »- Pb _»_Zn
Figure 4-10. Continuing calibration verification results from SNL.
33
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Laboratory-to-Laboratory Data Comparison
The results of several quantitative comparisons of MSE and CAS laboratory data are given in the following
paragraphs. Included are the results and discussion of mean percent difference computations, scatter diagrams,
statistical test results, and a semiquantitative analysis of overall sample variability.
Mean Percent Difference
An estimate of MPD for the soil samples collected at the two sites is given for each target element in Table 4-3.
In this computation, CAS ICP is the designated reference data set on the basis of the laboratory's experience and
acceptable performance on the quality control samples. Thirty sample pairs from each laboratory were used for
comparison because CAS analyzed only half of the total number of soil samples collected. These percent
difference estimates provide a measure of the overall comparability of the three data sets from the two
laboratories. Low difference values reveal agreement between the analyses. The standard deviation is also given
in the table and is a measure of the degree of variability encountered in the computed MPD for each element.
With only a few exceptions, mean differences for nearly all elements are less than ±10 percent in the
comparisons of the CAS ICP reference data set with the CAS AAS and MSE ICP data sets. The comparison of
Ag and Cd between CAS ICP and CAS AAS data sets showed differences on the order of 15 percent. Chromium
by CAS AAS does not compare well at all; however, the comparison with MSE ICP Cr data is quite good. The
poor figures for the CAS AAS Cr data may be attributable to the fact that most of the soil samples had Cr levels
near the lower limit of detection of the AAS method.
Table 4-3. Mean Percent Differences from MSE ICP and CAS AAS Data
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
Mean Percent Difference (ref: CAS ICP Data Set)
MSE Laboratory (ICP)
1.3±12.8
0.6 + 21.3
10.8 ±25.9
7.1 ±31.4
0.2 ±13.6
6.1+20.4
0.1 ±19.7
-2.1 ± 15.3
-4.7 ±14.4
CAS Laboratory (AAS)
15.7+13.6
-10.9 ±7.8
-16.6 ±22.9
105.1 ±109.6
4.0 ±3.6
10.5 ±3.2
4.3 ±5.2
5.4 ±1.9
4.2 ± 22.4
Notes: The mean value is followed by the standard deviation. The CAS laboratory ICP AES data set was
used as the reference in this analysis.
Scatter Plots
Scatter plots showing intercomparisons of the CAS AAS and MSE ICP field soil sample data with the
corresponding CAS ICP analysis data are presented in Figures 4-11 through 4-16 for selected elements to
illustrate the various degrees of comparability encountered in the data. The CAS ICP data are plotted on the x-
axis with either the CAS AAS or the MSE ICP data plotted on the^-axis. The comparison of the CAS AAS data
with the CAS ICP data was very good with the exception of Cr data, shown in Figure 4-12, corroborating the
high mean percent difference value noted for Cr in the previous section.
The MSE data show as good or better correlation with the CAS ICP data. This very close agreement is observed
despite the fact that the CAS ICP and CAS AAS samples were laboratory duplicates from the same field soil
34
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100
90
80
70
O)
JC
O)
60
1
55 5°
40
30
20 .
10
0 ._"
0 10 20 30 40 50 60 70 80 90 100
CAS-ICP Silver, mg/kg
Figure 4-11. CAS AAS vs. CAS ICP silver measurements on field replicate soil
samples.
35
30 -
25 -
I 20,
S«-
° 10,
0 5 10 15 20 25 30 35
CAS-ICP Chromium, mg/kg
Figure 4-12. CAS AAS vs. CAS ICP chromium measurements on field replicate soil
samples. Nondetectable results are not shown in the plot.
35
-------
50,000
45,000
40,000
5* 35,000
"5>
c
J 30,000
CO
<
< 25,000
o
20,000 _
15,000
10,000
10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000
CAS-ICP Iron, mg/kg
Figure 4-13. CAS AAS vs. CAS ICP iron measurements on field replicate soil
samples.
70 -
I"
,_- 50
o>
_>
55
m
(/>
=
30-
20 -
10 -
0 10 20 30 40 50 60 70 80 90
CAS-ICP Silver, mg/kg
Figure 4-14. MSE ICP vs. CAS ICP silver measurements on field replicate soil
samples.
36
-------
30
25
Ol
E
,3
| 15
£
o
Q.
O
111
-------
sample digestate whereas the MSE samples were from a different field sample split. A good comparison
between MSE ICP and CAS ICP data reveals that soil sample splits were chemically similar and that soil
processing and mixing produced relatively homogeneous samples.
The slope and intercept of the best straight line through the data and the correlation coefficient, r, which is a
quantitative measure of the degree of linearity in the data pairs, is given in Table 4-4 for CAS AAS and MSE ICP
data set comparisons with the CAS ICP data set. Coefficients greater than about 0.8 indicate a reasonably strong
linear relationship between the two data sets. Correlation coefficients less than 0.8 are encountered for Cr in
both data sets. The CAS AAS Cr data were plotted against the MSE ICP Cr data and a scatter plot much like that
shown in Figure 4-12 was obtained. This result further suggests that the CAS AAS Cr data may be suspect. The
MSE ICP Cr data show slightly better correlation when plotted against the CAS ICP data, as shown in
Figure 4-15. The slope parameters shown in Table 4-4 are a measure of the bias of one method with respect to
another. With a few exceptions the regression line slopes are in the range of 0.9 to 1.10, which corresponds to a
bias in the range of ±10 percent. Exceptions are encountered for Cd and Cr in the CAS AAS data set as well as
for Cr and Fe in the MSE data set.
Table 4-4. Reference Laboratory Linear Regression Results
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
CAS AAS Data Set
Corr. Coeff.
1.00
0.99
0.85
-0.13
1.00
0.99
1.00
1.00
1.00
Slope
1.10
0.96
0.49
0.34
1.07
1.04
1.08
1.06
1.09
Intercept
0.26
-29
2.2
23
-16
1,350
-10
-3.8
-28
MSE ICP Data Set
Corr. Coeff.
1.00
0.99
0.98
0.66
0.99
0.86
0.95
0.92
0.99
Slope
1.02
1.04
0.90
0.83
0.99
1.16
0.93
0.95
0.91
Intercept
-0.1
-16
1.1
2.2
13
-1,980
36
3.1
72
Notes: The CAS ICP data set was used as the reference data set (x variable) in these regression analyses. The y variable was either the CAS
AAS or MSE ICP data set. The slope and intercept values correspond to the values A and B in the linear equation y = Ax + B.
Statistical Bias Testing
The Wilcoxon matched pair test was used to compare the CAS AAS and MSE ICP data sets with the CAS ICP
data set. The SNL laboratory data were not included in this test because they did not meet the data validation
criteria. The Wilcoxon test is a nonparametric test which enables a decision to be made as to whether a
statistically significant bias exists between two methods. The term "nonparametric" refers to the fact that the
observations (in this case the reported metal concentrations in the soil samples) need not conform to a particular
statistical distribution. The Wilcoxson test provides a quantitative measure of the likelihood or probability that
observed differences between two methods are attributable to random variation only. Application of the test
produces a test statistic and an accompanying p-value. The p-value represents the probability of observing a test
statistic value greater than or equal to that obtained in the test from the null or "no difference" distributionthe
distribution of test statistic values that would be encountered if in fact no bias is present between the two
methods in question.
A p-value of 0.05 is often chosen as the boundary point in deciding whether two methods are statistically
different. A test statistic with an accompanying p-value of 0.05 or less indicates that the two methods being
38
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compared are statistically different and that the decision to call them different carries a 95 percent chance of
being correct. Alternatively, it can be stated that the decision to call the methods different has a 5 percent chance
of being incorrect.
The results of the statistical test as applied to the CAS AAS and MSB ICP laboratory data sets are summarized in
Table 4-5. The test results between CAS ICP and CAS AAS data sets indicate that significant differences were
observed between the two methods for all elements. The p-values associated with the test statistics for all
elements are less than 0.01, indicating that a clearly distinguishable bias exists between the ICP and AAS
analysis. This observation is corroborated by the scatter plots shown in Figures 4-11 through 4-13. Nearly all
the plotted points fall above a diagonal line extending from the lower left to the upper right corner of the figures.
This line is the zero bias line. Points falling above the diagonal line reveal a positive bias of the AAS method
relative to the ICP method and those falling below the line reveal a negative bias.
Table 4-5. Wilcoxon Matched Pair Statistical Test Results
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
Statistically Significant Bias Between Two Methods?
CAS (AAS) vs. CAS (ICP)
Yes(<0.01)
Yes(<0.01)
Yes(<0.01)
Yes(<0.01)
Yes(<0.01)
Yes(<0.01)
Yes(<0.01)
Yes(<0.01)
Yes(<0.01)
MSB (ICP) vs. CAS (ICP)
No (0.67)
No (0.91)
No (0.39)
No (0.94)
No (0.68)
No (0.31)
No (0.99)
No (0.98)
No (0.68)
Note: The p-value associated with the test statistic is given in parentheses.
A statistical comparison of the MSE ICP data with the CAS ICP data reveals that the two data sets are
statistically equivalent; thus no statistically significant method bias exists in one data set with respect to the
other. In this case all p-values associated with the computed test statistic are significantly greater than 0.05. For
example, the p-value associated with the test statistic for Cu was 0.68. This indicates that the observed
differences between the MSE ICP data and the CAS ICP data carry a 68 percent likelihood of being attributable
to random variation between two equivalent methods. These results are corroborated by the scatter plots shown
in Figures 4-14 through 4-16. The plotted points fall above and below the diagonal "zero bias" line with
approximately equal frequency, indicating no consistent bias in the results.
Intra- and Interlaboratory Variability
Each laboratory conducted a duplicate analysis of a digestate from a soil sample split made from a homogenized
bulk field soil sample. The intralaboratory ICP instrument variability was estimated by computing the RPD for
each target element from the duplicate analysis results of sample number MCLD-1 from the CAS and MSE
laboratories. The average of these RPD values is shown in column 2 of Table 4-6 for each target element. The
interlaboratory variability was estimated by computing four RPD values between the four measurement results
from both laboratories and averaging the results. These data are shown in column 3 of Table 4-6. A comparison
of the two columns of data (intra- and interlaboratory RPDs) suggests that in most cases instrument variability is
39
-------
Table 4-6. Estimates of Intra- and Intel-laboratory Sample Variation
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
Average Intralab RPD
5.1
1.5
14.3
15.6
3.9
1.9
2.1
3.9
2.2
Average Interlab RPD
5.1
8.1
14.3
9.8
7.4
1.7
2.9
4.6
4.7
of the same order of magnitude as the variability arising from heterogeneity in the sample splits going to the
different laboratories and technologies.
Reference Laboratory Data Set
Based on the foregoing analyses, a reference data set was compiled by averaging the MSB TCP, CAS ICP, and
CAS AAS data sets. This reference data set was then further used for comparison with the soil analysis data sets
provided for the various demonstration technologies. A summary of the reasons for including or excluding the
laboratory data sets in the reference data set is given below.
The CAS ICP data are judged to be valid, based on the laboratory's acceptable performance on the various
control, duplicate, and soil recovery analyses. The 30-sample CAS ICP data set is used as one component
in the reference data set.
The 30-sample CAS AAS data set is also included in the reference data set despite the fact that the data set
was shown to be biased with respect to the CAS ICP data set. The decision to include these data in the
reference set was founded upon the linear regression results. Linear regression and correlation analysis
show a high degree of correlation and small bias between the CAS ICP and CAS AAS data. The CAS AAS
biases relative to the CAS ICP method are typically less than 10 percent for most target elements. A bias of
± 10 percent is relatively small and acceptable in light of the ±20 percent tolerance in laboratory precision
that was deemed acceptable in the laboratory data validation process. The AAS Cr data, although not well
correlated with the ICP data, were also included in the reference data set. No substantive reasons to exclude
one set of measurements over another were apparent in this particular case. Consequently, both were
included.
The MSE data are similarly accepted as valid in light of their very good correlation with the CAS ICP data
for all elements and their demonstrated statistical equivalence with the CAS ICP data set.
The SNL laboratory data are not used in the reference data set. The data package could not be validated
because some key quality control parameters were not provided in the analysis results package.
Furthermore, a less sensitive, lower precision, mobile ICP instrument was used, which contributed to
greater uncertainty in this data set.
In summary, the reference data set is made up of an average of the MSE ICP, CAS ICP, and CAS AAS data sets
for the 30 field soil samples that were analyzed by all three methods. Single values from the MSE ICP data set
are used for the other 30 field samples not analyzed by CAS.
40
-------
The Intel-laboratory comparisons revealed that all validated data had either a tolerable bias or were statistically
equivalent. Consequently, no elements were excluded in compilation of the reference data set. Although all of
the target elements were included in this set, it should be noted that interlaboratory comparisons revealed that the
results from some elements should be regarded with a lower level of confidence than others. In particular, Cr
results were variable among all three methods and should be treated with appropriate caution when they are used
for comparison with field technology results.
41
-------
Chapter 5
Demonstration Results
Technology-Laboratory Data Comparison Methods
For Level 1 technologies such as the stripping analysis techniques, a formal comparison of field technology and
laboratory results is left to the instrument developer. To assist the developer in the interpretation of the data,
several data formats and simple comparative analyses are included with the raw data. The stripping analysis
results from the quality control samples (blank soil, control soil, and duplicates) are presented in the same
manner as described earlier for the laboratory data, but with little interpretation or assessment. In addition, the
field soil sample analysis data are presented in tabular format in Appendix A. The validated results from each
laboratory are shown alongside the stripping analysis results for each target element. This chapter contains
scatter plots in which the stripping analysis data are plotted against the reference laboratory data set. To further
assist the technology developer in understanding the data, possible analytical approaches are suggested for
comparing the technology data and reference laboratory data.
Field Observations
Periodically during the demonstration, an observer checked in with the electrochemical analysis teams to monitor
progress. No instrument breakdowns were noted and, in general, the soil analysis went smoothly. Personnel
from PNNL, NMSU, and ETG began their soil analysis on Monday, September 25, and completed their work on
Thursday, September 28, averaging about 15 soil samples per 10-hour work day. Field observers noted that the
electrochemical analyses appeared to be quite labor intensive, involving considerable wet chemistry in the
sample workup. Although the weather during the demonstration was occasionally rainy, windy, and cold, it did
not appear to adversely affect the performance of the electrochemical systems.
General Description of Electrochemical Analysis Results
A total of 60 field soil samples plus 2 control and 2 blank soil samples were submitted for various
electrochemical analyses using anodic stripping voltammetry and potentiometric stripping analysis. The EG&G
ASV system was used only for Cr analysis. The two PSA systems (TraceLab and Metalyzer) were used for
analysis of Cd, Cu, and Pb. As a result of time constraints, analysis was not carried out for the other 5 target
elements. For the elements analyzed (Cd, Cr, Cu, and Pb), a nearly complete analysis report was submitted. For
several samples, neither a detected amount nor an indication of no detect was given. No details or explanations
were given in the analysis report for these few cases of no reported data. Soil performance evaluation and soil
blank samples were analyzed by the PNNL/NMSU ASV and PSA systems only. Duplicate analyses were carried
out on three field soil samples as well. No performance evaluation (PE), blank, or duplicate sample analyses
were done with the Metalyzer PSA system.
42
-------
Quality Control Sample Results
Results from a stripping analysis of quality control samples are presented in the following sections. The field
technology results are presented in a format that facilitates comparison of the technologies and laboratory data.
In light of the relatively new application of these electroanalytical techniques to soil residue analysis, only a
limited discussion of the results is presented. Further evaluation of the data and an overall assessment of the
systems' performance are left to the technology developer.
Blank Soil Sample Analysis
Blank soil sample analysis results from the PNNL/NMSU ASV and PSA systems are given in Table 5-1, along
with certified sample contamination levels. The MSE laboratory results are also shown because these results
tracked the certified values most closely among the participating laboratories. The ASV system was used for Cr
analysis; the PSA system was used for Cd, Cu, and Pb analysis. No blank sample analysis data were available
from the ETG Metalyzer system.
Table 5-1. Blank Soil Analysis Results for PNNL/NMSU ASV and
PSA, MSE Laboratory and Accompanying Certified Levels
Element
Ag
As
Cd
Cr
Cu
Fe
Pb
Mn
Zn
Metal Concentration Level (mg/kg)
ASV/PSA
NA
NA
<1(PSA)
21 (ASV)
0.7 (PSA)
NA
9 (PSA)
NA
NA
MSE by ICP
0.4
2.1
0.4
6.7
5.6
7,740
9.3
172
24.4
Certified Level
<2
<2
<1
7
<5
8,180
9
159
24
Notes: NA = no analysis. A "less than" (<) symbol indicates not detected. The number following is
the reported instrument detection level.
Control Soil Sample Analysis
Control soil samples, with well-characterized target element concentrations, were analyzed with the
PNNL/NMSU ASV and PSA stripping analysis systems. The ETG personnel did not analyze PE samples during
the demonstration. The results for each control sample analysis from the PNNL/NMSU ASV and PSA systems
for Cd, Cr, Cu, and Pb are shown in Figure 5-1. The results are expressed in terms of a percentage deviation
from a certified concentration level of each element in this particular soil lot determined through a
multilaboratory, round-robin study as described in Chapter 4. The plotted data reveal that ASV/PSA analysis
results were within the 95 percent upper and lower confidence limits about the mean certified value for Cr, Cd,
and Pb. Copper results fall below the lower 95 percent confidence interval of the PE sample.
Duplicate Sample Analysis
Duplicate sample analysis results are shown as RPD values in Figure 5-2. Relative percent deviations were
computed for 4 duplicate sample analyses for the PNNL/NMSU ASV and PSA systems. (No duplicate samples
43
-------
J 40
5
o
I 0... _
o
I
£ -20 .
-60 .
-80
:!1PNL-ASVPE1 j
;OPNL-ASVPE2]
jLCL !
«UCL I
Cr Cu
Element
Fe
Pb
Mn
Zn
Figure 5-1. Control soil sample analysis results from the PNNL/NMSU ASV and
PSA systems. The upper and lower confidence limits with respect to the certified
level are also shown on the graph. The ASV system was used for Cr and the PSA
system for Cd, Cu and Pb.
Cd
Cr Cu
Element
gigg SBHDM-1 -004 B SBMD-4-004 f^j MLD-2-004 | | PE 1 &2
Figure 5-2. Duplicate sample analysis results for the EG&G ASV (Cr) and the
TraceLab PSA (Cd, Cu, Pb) systems.
44
-------
were run with the ETG Metalyzer.) One set of duplicate performance evaluation samples and three sets of field
soil samples were included in this data set. Ten of the fifteen RPD determinations were less than 20 percent.
Twelve of the 15 RPD determinations were less than or equal to 30 percent.
Recovery Analysis
None of the soil and control samples analyzed with the various electrochemical analysis systems were spiked
prior to analysis. Consequently, there are no recovery data to present.
Field Soil Sample Analysis Results
Analysis results were returned for 53 of 60 field soil samples from the Metalyzer (Cd, Cr, and Pb) analysis, 60 of
60 for the EG&G ASV (Cr) analysis, and 59 of 60 for the TraceLab PSA (Cd, Cu, and Pb) analysis. The results
tally reported indications of no detect. The field sample analysis data are presented in graphical and tabular
formats to assist the developers in comparing their data against the reference data set from the analytical
laboratories. A series of seven scatter plots (Figures 5-3 through 5-9) are presented on the following pages where
the data from the three stripping analysis systems are plotted with respect to reference laboratory data. As a part
of the laboratory data validation process, laboratory data from the CAS ICP, CAS AAS, and MSE ICP laboratory
results were averaged together to yield a reference laboratory value. (See Chapter 4 of this report for a
discussion of the makeup of the reference laboratory data set.) All reported data in excess of the instrument
detection limit are plotted; however, in many cases, the points on the scatter plots are overlaid and are
indistinguishable from each other. The zero bias line extends from the lower left to the upper right of each plot.
Points falling on or close to this line are indicative of good comparability of the stripping analysis data with
reference laboratory data.
The various electrochemical analysis data are also presented in tabular form in Appendix A to facilitate their
comparison with individual reference laboratory results. Tables are presented in which analysis results for each
of the 60 soil samples are given for CAS ICP, CAS AAS, MSE ICP, reference laboratory, and each of the three
electrochemical analysis systems for the four target elements selected for analysis by the participants.
Comparison of Stripping Analysis Results with Reference Laboratory Data
The following analytical approaches are offered as illustrations of how an evaluation of instrument performance
relative to a laboratory data set might be carried out.
Mean Percent Difference
The MPD, as defined in Chapter 4, for the data from the stripping analyses relative to the reference laboratory
data set are given in Table 5-2. A low MPD and an accompanying low standard deviation can be taken as an
indicator of good comparability between methods. The best MPD is noted for Pb analysis by the TraceLab PSA
system. The worst is for Cr by the EG&G ASV technique.
45
-------
180
160
140
E"
.2 100
o
.c
"so "
w
< J
i 60 "
u Bf
40
20
0 20 40 60 80 100 120 140 160 180
Lab Reference Chromium, mg/kg
Figure 5-3. EG&G ASV vs. reference laboratory chromium measurements.
50 __ _ .. _.
I
45 i
40 !
O) '
r
13° -
i
O 25 -
(/)
I"
n 15
H
10 m m
" "
5 . I.
0 5 10 15 20 25 30 35 40 45 50
Lab Reference Cadmium, mg/kg
Figure 5-4. TraceLab PSA vs. reference laboratory cadmium measurements.
46
-------
3,500
3.000
D> 2'50°
I
S
Q. 2,000
a
o
O
w
°- 1.500
J3
3
a>
o
E
H- 1.000
500
0
0 500 1,000 1,500 2,000 2,500 3,000 3,500
Lab Reference Copper, mg/kg
Figure 5-5. TraceLab PSA vs. reference laboratory copper measurements.
2,500
2,000 -
E. 1,500 -
35
0.
3
1.000 -
500 _
0
0 500 1,000 1,500 2,000 2,500
Lab Reference Lead, mg/kg
Figure 5-6. TraceLab PSA vs. reference laboratory lead measurements.
47
-------
3.500
3.000
JC
E
g. 2,000
CL
O
o
35
°- 1,500
8
5s
3
o
S 1,000
500
0 500 1.000 1.500 2.000 2,500 3,000 3,500
Lab Reference Copper, mg/kg
Figure 5-7. Metalyzer PSA vs. reference laboratory copper measurements.
2,500 _...... . -
2,000
^ 1,500
o
<
Q.
»
1,000
500
0
0 500 1,000 1,500 2,000 2,500
Lab Reference Lead, mg/kg
Figure 5-8. Metalyzer PSA vs. reference laboratory lead measurements.
48
-------
Table 5-2. Mean Percent Difference for PNNL/NMSU ASV and PSA Analyses
Relative to Reference Laboratory Data
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
ASV (EG&G)
Mean Percent
Difference
NA
NA
NA
322 ± 203
NA
NA
NA
NA
NA
PSA (TraceLab)
Mean Percent
Difference
NA
NA
-22 ± 28
NA
-4 ±16
NA
NA
-4 ±16
NA
PSA (Metalyzer)
Mean Percent
Difference
NA
NA
NA
NA
^8 ±28
NA
NA
-37 ± 25
NA
Note: NA = no analysis. Only selected target elements were analyzed in this technology demonstration.
Linear Regression Coefficients
The linear regression slope, _y-intercept, and correlation coefficient for the stripping analysis and reference
laboratory data are given in Table 5-3. The slope yields a measure of the linear association between the two data
sets. A slope of 2 indicates that a technology reports a value two times that of the reference laboratory, whereas
a slope of 0.5 indicates the technology reports a value half the reference laboratory value. A regression analysis
will always yield a slope value, even when the data are poorly correlated. The correlation coefficient is an
indication of the strength of linear association between two variables. Values near unity suggest good correlation
between the data sets. Values near zero suggest no correlation of the data. The correlation coefficients shown in
Table 5-3 are best for the TraceLab instrument and poorest for the EG&G ASV instrument. Correlation results
for the Metalyzer fall in between.
Table 5-3. Comparison of Linear Regression Coefficients for the ASV and PSA
Systems and Reference Laboratory Data Set
Element
Cr (ASV)
Cd (TraceLab)
Cu (TraceLab)
Pb (TraceLab)
Cd (Metalyzer)
Cu (Metalyzer)
Pb (Metalyzer)
Slope
3.75
1.02
0.81
1.08
NA
0.47
0.27
Intercept (mg/kg)
3
-2
-210
-54
NA
-18
146
Correlation Coefficient
0.50
0.90
0.98
0.98
NA
0.72
0.71
Notes: NA = no analysis. Nearly all reported results for Cd analysis with the Metalyzer were no detects. Consequently, a
regression analysis was not carried out for this element.
Statistical Bias Testing
A statistical test such as the Wilcoxon matched pair test can be used to investigate whether a statistically
significant bias exists between the stripping analysis and the reference laboratory data set. The results from such
a test should be used in conjunction with linear regression data, such as the data presented in Table 5-3.
Although the statistical test may indicate that a significant bias exists between the two methods, the magnitude of
49
-------
that bias must also be considered in the overall assessment of method comparability. Because the stripping
analysis technologies are designated Level 1, formal statistical testing is left to the discretion of the technology
developer.
Conclusions
Since the stripping analysis technologies are developing technologies that have not undergone extensive field
testing, a comprehensive assessment of their performance was not undertaken in this demonstration.
Conclusions as to the systems' overall performance are left to the technology developer.
50
-------
Chapter 6
Developer's Comments
A review draft version of this report was sent to Dr. Khris Olsen of PNNL. Following his review, suggested
changes and corrections were submitted in writing to SNL. All of the suggested changes were made. No further
developer comments were received from PNNL for inclusion in this section.
51
-------
References
Conover, W. J., 1980. Practical Nonparametric Statistics, 2nd ed, Wiley, New York.
EPA, 1996. "Test Methods for Evaluating Solid Waste: Physical/Chemical Methods," Final Update III, Report
No. EPA SW-846.3-3, Government Printing Office Order No. 955-001-00000-1, Office of Solid Waste and
Emergency Response, Washington, DC.
Havlicek, L., and R. D. Grain, 1988. Practical Statistics for the Physical Sciences, American Chemical Society,
Washington DC, pp. 84-93.
Jagner, D., K. Josefson, and S. Westerlund, 1982. "Determination of zinc, cadmium, lead and copper in sea
water by means of computerized potentiometric stripping analysis," Analytica ChimicaActa, 129: 153-161.
MSE, 1996. "Final Report for RCRA and Other Heavy Metals in Soils Demonstration," MSB Technology
Applications, Inc., Butte, Montana.
Olsen, K., J. Wang, R. Setladji, and J. Lu, 1994. "Field screening of chromium, cadmium, zinc, copper and lead
in sediments by stripping analysis," Environ. Sci. Technoi, 28:2074-2079.
Wang, J, 1982. "Anodic stripping voltammetry as an analytical tool," Environ. Sci. Technoi, 16:104A-109A.
Wang, J., 1985. Stripping Analysis: Principles, Instrumentation and Applications, VCH Publishers, Deerfield
Beach, FL.
52
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Appendix A
Tabular Data
for
PNNL/NMSU/ETG Stripping Analysis
and
Reference Laboratory
Field Soil Samples
A-l
-------
Table Description
The results are organized by element with two tables for each element. The first table gives results from the
Silver Bow site and the second gives results from the Mill Creek site. The data are further described as follows:
Column 1 Sample Number
Column 2 MSB Laboratory ICP AES Results
Column 3 CAS Laboratory ICP AES Results
Column 4 CAS Laboratory Flame AAS Results
Column 5 Reference Laboratory Data Set (Average of Columns 2-4)
Column 6 Field Technology Results
Note that stripping analysis results are reported for only four (Cd, Cr, Cu and Pb) of the nine target elements.
A-2
-------
Table A-1. Cadmium Analysis Results for TraceLab PSA and Reference Laboratories (Part 1,
Silver Bow Site)
Sample No.
SBHD1
SBHD2
SBHD3
SBHD4
SBHD5
SBHD6
SBHD7
SBHD8
SBHD9
SBHD10
SBMD1
SBMD2
SBMD3
SBMD4
SBMD5
SBMD6
SBMD7
SBMD8
SBMD9
SBMD10
SBLD1
SBLD2
SBLD3
SBLD4
SBLD5
SBLD6
SBLD7
SBLD8
SBLD9
SBLD10
MSE_Cd
(mg/kg)
22.6
12.5
21.6
9.9
48.5
18.3
19.0
18.0
15.5
24.3
5.8
11.8
7.8
16.5
14.6
7.8
9.8
4.6
6.6
5.7
4.9
3.5
3.8
2.7
3.1
4.9
7.3
3.1
2.4
3.7
C_IC_Cd
(mg/kg)
27
22
54
18
14
6
15
11
7
6
5
3
3
8
4
C_AA_Cd
(mg/kg)
23.7
14.9
20.1
15.7
11.5
2.7
3.4
7.1
9.7
5
3.7
2.8
2.7
6.6
2.6
Ref_Cd
(mg/kg)
24.4
12.5
19.5
9.9
40.9
18.3
17.6
18.0
13.7
24.3
4.8
11.8
8.7
16.5
10.9
7.8
8.8
4.6
5.9
5.7
4.5
3.5
3.2
2.7
2.9
4.9
7.3
3.1
3.0
3.7
Tracel_ab_Cd
(mg/kg)
17.7
10.2
7.6
7.4
48.8
10.4
21.8
33.4
15.1
19.4
3.8
<1
<1
9.8
4.8
3.9
<1
<1
5.2
3.0
2.0
2.0
2.4
2.2
3.3
7.8
3.1
1.8
2.6
A-3
-------
Table A-2. Cadmium Analysis Results for TraceLab PSA and Reference Laboratories (Part 2,
Mill Creek Site)
Sample No.
MCHD1
MCHD2
MCHD3
MCHD4
MCHD5
MCHD6
MCHD7
MCHD8
MCHD9
MCHD10
MCMD1
MCMD2
MCMD3
MCMD4
MCMD5
MCMD6
MCMD7
MCMD8
MCMD9
MCMD10
MCLD1
MCLD2
MCLD3
MCLD4
MCLD5
MCLD6
MCLD7
MCLD8
MCLD9
MCLD10
MSE_Cd
(mg/kg)
4
4
3
4
5
3
4
6
27
4
3
4
4
4
6
5
7
7
8
6
2
4
4
4
4
4
5
4
5
7
C_IC_Cd
(mg/kg)
3
3
4
3
25
4
3
5
5
7
2
3
4
4
3
C_AA_Cd
(mg/kg)
3
2
3
2
22
3
3
5
5
6
2
3
3
4
3
Ref_Cd
(mg/kg)
3
4
3
4
4
3
3
6
25
4
4
4
3
4
5
5
5
7
7
6
2
4
3
4
4
4
4
4
4
7
Tracel_ab_Cd
(mg/kg)
<1
<1
<1
<1
<1
<1
<1
<1
17.5
<1
<1
<1
<1
<1
<1
<1
<1
5.3
5.2
<1
1.4
1.5
2.2
2.5
<1
<1
3.6
<1
<1
6.9
A-4
-------
Table A-3. Cadmium Analysis Results for Metalyzer PSA and Reference Laboratories (Part 1,
Silver Bow Site)
Sample No.
SBHD1
SBHD2
SBHD3
SBHD4
SBHD5
SBHD6
SBHD7
SBHD8
SBHD9
SBHD10
SBMD1
SBMD2
SBMD3
SBMD4
SBMD5
SBMD6
SBMD7
SBMD8
SBMD9
SBMD10
SBLD1
SBLD2
SBLD3
SBLD4
SBLD5
SBLD6
SBLD7
SBLD8
SBLD9
SBLD10
MSE_Cd
(mg/kg)
22.6
12.5
21.6
9.9
48.5
18.3
19.0
18.0
15.5
24.3
5.8
11.8
7.8
16.5
14.6
7.8
9.8
4.6
6.6
5.7
4.9
3.5
3.8
2.7
3.1
4.9
7.3
3.1
2.4
3.7
C_IC_Cd
(mg/kg)
27
22
54
18
14
6
15
11
7
6
5
3
3
8
4
C_AA_Cd
(mg/kg)
23.7
14.9
20.1
15.7
11.5
2.7
3.4
7.1
9.7
5
3.7
2.8
2.7
6.6
2.6
Ref_Cd
(mg/kg)
24.4
12.5
19.5
9.9
40.9
18.3
17.6
18.0
13.7
24.3
4.8
11.8
8.7
16.5
10.9
7.8
8.8
4.6
5.9
5.7
4.5
3.5
3.2
2.7
2.9
4.9
7.3
3.1
3.0
3.7
Metalyzer
PSA_Cd
(mg/kg)
18
<10
<10
<10
26.2
<10
<10
<10
21.6
<10
<10
<10
<10
<10
<10
<10
<10
<10
<10
<5
<5
<5
<5
<5
<10
<5
<5
<10
A-5
-------
Table A-4. Cadmium Analysis Results for Metalyzer PSA and Reference Laboratories (Part 2,
Mill Creek Site)
Sample No.
MCHD1
MCHD2
MCHD3
MCHD4
MCHD5
MCHD6
MCHD7
MCHD8
MCHD9
MCHD10
MCMD1
MCMD2
MCMD3
MCMD4
MCMD5
MCMD6
MCMD7
MCMD8
MCMD9
MCMD10
MCLD1
MCLD2
MCLD3
MCLD4
MCLD5
MCLD6
MCLD7
MCLD8
MCLD9
MCLD10
MSE_Cd
(mg/kg)
4
4
3
4
5
3
4
6
27
4
3
4
4
4
6
5
7
7
8
6
2
4
4
4
4
4
5
4
5
7
C_IC_Cd
(mg/kg)
3
3
4
3
25
4
3
5
5
7
2
3
4
4
3
C_AA_Cd
(mg/kg)
3
2
3
2
22
3
3
5
5
6
2
3
3
4
3
Ref_Cd
(mg/kg)
3
4
3
4
4
3
3
6
25
4
4
4
3
4
5
5
5
7
7
6
2
4
3
4
4
4
4
4
4
7
Metalyzer
PSA_Cd
(mg/kg)
<10
<10
<10
<10
<10
<10
<10
<10
<10
<10
<10
<10
<10
<10
<10
<7.2
<10
<8.8
<8.8
<10
<10
<10
<10
<10
<10
A-6
-------
Table A-5. Chromium Analysis Results for EG&G ASV and Reference Laboratories (Part 1,
Silver Bow Site)
Sample No.
SBHD1
SBHD2
SBHD3
SBHD4
SBHD5
SBHD6
SBHD7
SBHD8
SBHD9
SBHD10
SBMD1
SBMD2
SBMD3
SBMD4
SBMD5
SBMD6
SBMD7
SBMD8
SBMD9
SBMD10
SBLD1
SBLD2
SBLD3
SBLD4
SBLD5
SBLD6
SBLD7
SBLD8
SBLD9
SBLD10
MSE_Cr
(mg/kg)
6
4
5
6
7
7
7
6
7
9
13
20
27
21
25
14
14
14
10
8
15
14
13
13
12
14
13
13
12
14
C_IC_Cr
(mg/kg)
8
5
8
5
6
17
12
16
10
9
15
14
14
17
16
C_AA_Cr
(mg/kg)
<10
<10
23
<10
<10
<10
15
11
<10
<10
<10
11
<10
<10
<10
Ref_Cr
(mg/kg)
6.8
4.4
5.0
5.7
12.7
6.8
6.2
5.7
6.6
9.2
15.0
20.0
18.1
21.2
17.3
13.7
12.0
13.8
9.4
7.8
15.2
14.0
12.5
12.7
12.8
13.5
14.9
12.6
13.9
13.5
EG&G
ASV_Cr
(mg/kg)
32.3
29.4
32.0
26.2
34.0
37.2
38.4
33.4
39.8
36.3
70.2
76.6
145.6
165.0
154.0
83.6
88.5
55.8
52.3
29.4
36.0
46.5
55.6
76.9
51.0
45.2
68.8
52.8
44.9
67.9
A-7
-------
Table A-6. Chromium Analysis Results for EG&G ASV and Reference Laboratories (Part 2, Mill
Creek Site)
Sample No.
MCHD1
MCHD2
MCHD3
MCHD4
MCHD5
MCHD6
MCHD7
MCHD8
MCHD9
MCHD10
MCMD1
MCMD2
MCMD3
MCMD4
MCMD5
MCMD6
MCMD7
MCMD8
MCMD9
MCMD10
MCLD1
MCLD2
MCLD3
MCLD4
MCLD5
MCLD6
MCLD7
MCLD8
MCLD9
MCLD10
MSE_Cr
(mg/kg)
8
10
4
6
11
10
7
10
10
13
11
10
11
13
13
10
13
12
12
13
7
8
9
12
8
11
10
7
9
11
C_IC_Cr
(mg/kg)
7
3
10
6
9
10
14
14
12
14
8
7
12
10
8
C_AA_Cr
(mg/kg)
10
11
28
12
21
30
17
21
27
33
19
21
32
15
Ref_Cr
(mg/kg)
8
10
4
6
11
10
14
10
10
13
14
10
18
13
15
10
15
12
18
13
16
8
12
12
14
11
17
7
11
11
EG&G
ASV_Cr
(mg/kg)
41.2
43.0
39.2
44.7
64.6
30.4
21.4
33.6
36.7
35.4
54.6
26.2
35.5
32.8
29.1
23.1
23.6
35.2
39.4
42.0
9.1
27.8
33.7
47.4
34.0
34.2
36.4
24.1
30.0
23.9
A-8
-------
Table A-7. Copper Analysis Results for TraceLab PSA and Reference Laboratories (Part 1
Silver Bow Site)
Sample No.
SBHD1
SBHD2
SBHD3
SBHD4
SBHD5
SBHD6
SBHD7
SBHD8
SBHD9
SBHD10
SBMD1
SBMD2
SBMD3
SBMD4
SBMD5
SBMD6
SBMD7
SBMD8
SBMD9
SBMD10
SBLD1
SBLD2
SBLD3
SBLD4
SBLD5
SBLD6
SBLD7
SBLD8
SBLD9
SBLD10
MSE_Cu
(mg/kg)
1,570
1,330
2,460
991
2,620
1,680
1,010
1,030
1,620
1,970
281
864
788
2,180
1,090
780
1,270
449
608
710
394
351
339
414
347
404
566
414
305
363
C_IC_Cu
(mg/kg)
1,670
2,510
2,410
1,010
1,400
385
512
1,240
1,290
644
374
357
332
647
376
C_AA_Cu
(mg/kg)
1,790
2,700
2,620
1,060
1,500
371
522
1,270
1,280
635
376
359
338
648
370
Ref_Cu
(mg/kg)
1,677
1,330
2,557
991
2,550
1,680
1,027
1,030
1,507
1,970
346
864
607
2,180
1,200
780
1,280
449
629
710
381
351
352
414
339
404
620
414
350
363
TraceLab
PSA_Cu
(mg/kg)
1,164
670
2,006
708
2,020
994
520
660
869
1,539
124
566
264
1,328
862
408
745
208
233
513
271
223
273
284
183
308
251
160
156
112
A-9
-------
Table A-8. Copper Analysis Results for TraceLab PSA and Reference Laboratories (Part 2, Mill
Creek Site)
Sample No.
MCHD1
MCHD2
MCHD3
MCHD4
MCHD5
MCHD6
MCHD7
MCHD8
MCHD9
MCHD10
MCMD1
MCMD2
MCMD3
MCMD4
MCMD5
MCMD6
MCMD7
MCMD8
MCMD9
MCMD10
MCLD1
MCLD2
MCLD3
MCLD4
MCLD5
MCLD6
MCLD7
MCLD8
MCLD9
MCLD10
MSE_Cu
(mg/kg)
682
792
419
687
956
533
589
859
3,340
889
631
532
585
632
825
893
890
871
1,020
784
476
477
595
554
721
971
853
784
624
1,090
C_IC_Cu
(mg/kg)
663
400
828
626
3,490
631
621
795
821
1,010
513
598
775
878
598
C_AA_Cu
(mg/kg)
701
420
880
668
3,640
657
651
845
885
1,130
535
610
837
916
622
Ref_Cu
(mg/kg)
682
792
413
687
888
533
628
859
3,490
889
640
532
619
632
822
893
865
871
1,053
784
508
477
601
554
778
971
882
784
615
1,090
TraceLab
PSA_Cu
(mg/kg)
245
413
194
296
372
202
228
400
2,797
486
224
232
230
292
333
441
432
427
530
270
191
167
274
260
406
392
488
381
280
669
A-10
-------
Table A-9. Copper Analysis Results for Metalyzer PSA and Reference Laboratories (Part 1
Silver Bow Site)
Sample No.
SBHD1
SBHD2
SBHD3
SBHD4
SBHD5
SBHD6
SBHD7
SBHD8
SBHD9
SBHD10
SBMD1
SBMD2
SBMD3
SBMD4
SBMD5
SBMD6
SBMD7
SBMD8
SBMD9
SBMD10
SBLD1
SBLD2
SBLD3
SBLD4
SBLD5
SBLD6
SBLD7
SBLD8
SBLD9
SBLD10
MSE_Cu
(mg/kg)
1,570
1,330
2,460
991
2,620
1,680
1,010
1,030
1,620
1,970
281
864
788
2,180
1,090
780
1,270
449
608
710
394
351
339
414
347
404
566
414
305
363
C_IC_Cu
(mg/kg)
1,670
2,510
2,410
1,010
1,400
385
512
1,240
1,290
644
374
357
332
647
376
C_AA_Cu
(mg/kg)
1,790
2,700
2,620
1,060
1,500
371
522
1,270
1,280
635
376
359
338
648
370
Ref_Cu
(mg/kg)
1,677
1,330
2,557
991
2,550
1,680
1,027
1,030
1,507
1,970
346
864
607
2,180
1,200
780
1,280
449
629
710
381
351
352
414
339
404
620
414
350
363
Metalyzer
PSA_Cu
(mg/kg)
180
1,814
758
1,820
403
278
<132
587
341
158
<192
906
492
446
832
370
349
706
248
240
373
309
337
237
278
163
215
A-ll
-------
Table A-10. Copper Analysis Results for Metalyzer PSA and Reference Laboratories (Part 2,
Mill Creek Site)
Sample No.
MCHD1
MCHD2
MCHD3
MCHD4
MCHD5
MCHD6
MCHD7
MCHD8
MCHD9
MCHD10
MCMD1
MCMD2
MCMD3
MCMD4
MCMD5
MCMD6
MCMD7
MCMD8
MCMD9
MCMD10
MCLD1
MCLD2
MCLD3
MCLD4
MCLD5
MCLD6
MCLD7
MCLD8
MCLD9
MCLD10
MSE_Cu
(mg/kg)
682
792
419
687
956
533
589
859
3,340
889
631
532
585
632
825
893
890
871
1,020
784
476
477
595
554
721
971
853
784
624
1,090
C_IC_Cu
(mg/kg)
663
400
828
626
3,490
631
621
795
821
1,010
513
598
775
878
598
C_AA_Cu
(mg/kg)
701
420
880
668
3,640
657
651
845
885
1,130
535
610
837
916
622
Ref_Cu
(mg/kg)
682
792
413
687
888
533
628
859
3,490
889
640
532
619
632
822
893
865
871
1,053
784
508
477
601
554
778
971
882
784
615
1,090
Metalyzer
PSA_Cu
(mg/kg)
360
<135
292
378
150
226
298
<140
325
338
<143
259
566
146
157
<100
203
424
328
392
472
338
312
143
265
A-12
-------
Table A-11. Lead Analysis Results for TraceLab PSA and Reference Laboratories (Part 1 Silver
Bow Site)
Sample No.
SBHD1
SBHD2
SBHD3
SBHD4
SBHD5
SBHD6
SBHD7
SBHD8
SBHD9
SBHD10
SBMD1
SBMD2
SBMD3
SBMD4
SBMD5
SBMD6
SBMD7
SBMD8
SBMD9
SBMD10
SBLD1
SBLD2
SBLD3
SBLD4
SBLD5
SBLD6
SBLD7
SBLD8
SBLD9
SBLD10
MSE_Pb
(mg/kg)
1,170
1,010
946
936
2,080
1,310
1,030
1,770
1,500
1,140
410
631
456
779
677
836
696
466
537
342
200
166
139
245
173
217
324
193
264
294
C_IC_Pb
(mg/kg)
1,220
902
1,850
992
1,310
1,260
513
823
798
471
166
147
161
374
302
C_AA_Pb
(mg/kg)
1,290
955
2,000
1,060
1,370
1,290
539
883
840
494
171
154
165
393
315
Ref_Pb
(mg/kg)
1,227
1,010
934
[ 936
1,977
1,310
1,027
1,770
1,393
1,140
987
631
503
779
794
836
778
466
501
342
179
166
147
245
166
217
364
193
294
294
TraceLab
PSA_Pb
(mg/kg)
1,402
1,114
990
888
2,280
1,258
1,018
1,895
1,416
1,184
638
296
877
517
842
732
482
336
456
165
148
135
241
144
255
310
198
236
287
A-13
-------
Table A-12. Lead Analysis Results for TraceLab PSA and Reference Laboratories (Part 2, Mill
Creek Site)
Sample No.
MCHD1
MCHD2
MCHD3
MCHD4
MCHD5
MCHD6
MCHD7
MCHD8
MCHD9
MCHD10
MCMD1
MCMD2
MCMD3
MCMD4
MCMD5
MCMD6
MCMD7
MCMD8
MCMD9
MCMD10
MCLD1
MCLD2
MCLD3
MCLD4
MCLD5
MCLD6
MCLD7
MCLD8
MCLD9
MCLD10
MSE_Pb
(mg/kg)
391
582
384
312
520
484
355
376
388
332
229
350
267
256
442
265
362
349
484
413
298
316
291
331
264
342
350
432
540
499
C_IC_Pb
(mg/kg)
391
415
521
361
396
235
283
424
336
495
306
279
275
330
497
C_AA_Pb
(mg/kg)
417
452
556
388
423
240
294
441
362
529
319
288
297
340
530
Ref_Pb
(mg/kg)
400
582
417
312
532
484
368
376
402
332
235
350
281
256
436
265
353
349
503
413
308
316
286
331
279
342
340
432
522
499
TraceLab
PSA_Pb
(mg/kg)
343
692
610
322
474
414
372
372
351
394
220
390
253
256
400
288
274
312
494
302
266
241
248
282
234
284
298
431
488
500
A-14
-------
Table A-13. Lead Analysis Results for Metalyzer PSA and Reference Laboratories (Part 1,
Silver Bow Site)
Sample No.
SBHD1
SBHD2
SBHD3
SBHD4
SBHD5
SBHD6
SBHD7
SBHD8
SBHD9
SBHD10
SBMD1
SBMD2
SBMD3
SBMD4
SBMD5
SBMD6
SBMD7
SBMD8
SBMD9
SBMD10
SBLD1
SBLD2
SBLD3
SBLD4
SBLD5
SBLD6
SBLD7
SBLD8
SBLD9
SBLD10
MSE_Pb
(mg/kg)
1,170
1,010
946
936
2,080
1,310
1,030
1,770
1,500
1,140
410
631
456
779
677
836
696
466
537
342
200
166
139
245
173
217
324
193
264
294
C_IC_Pb
(mg/kg)
1,220
902
1,850
992
1,310
1,260
513
823
798
471
166
147
161
374
302
C_AA_Pb
(mg/kg)
1,290
955
2,000
1,060
1,370
1,290
539
883
840
494
171
154
165
393
315
Ref_Pb
(mg/kg)
1,227
1,010
934
936
1,977
1,310 '
1,027
1,770
1,393
1,140
987
631
503
779
794
836
778
466
501
342
179
166
147
245
166
217
364
193
294
294
Metalyzer
PSA_Pb
(mg/kg)
608
456
370
460
921
534
472
77.4
690
229
392
203
412
250
442
432
400
240
287
116
120
155
108
190
343
136
175
386
A-15
-------
Table A-14. Lead Analysis Results for Metalyzer PSA and Reference Laboratories (Part 2, Mill
Creek Site)
Sample No.
MCHD1
MCHD2
MCHD3
MCHD4
MCHD5
MCHD6
MCHD7
MCHD8
MCHD9
MCHD10
MCMD1
MCMD2
MCMD3
MCMD4
MCMD5
MCMD6
MCMD7
MCMD8
MCMD9
MCMD10
MCLD1
MCLD2
MCLD3
MCLD4
MCLD5
MCLD6
MCLD7
MCLD8
MCLD9
MCLD10
MSE_Pb
(mg/kg)
391
582
384
312
520
484
355
376
388
332
229
350
267
256
442
265
362
349
484
413
298
316
291
331
264
342
350
432
540
499
C_IC_Pb
(mg/kg)
391
415
521
361
396
235
283
424
336
495
306
279
275
330
497
C_AA_Pb
(mg/kg)
417
452
556
388
423
240
294
441
362
529
319
288
297
340
530
Ref_Pb
(mg/kg)
400
582
417
312
532
484
368
376
402
332
235
350
281
256
436
265
353
349
503
413
308
316
286
331
279
342
340
432
522
499
Metalyzer
PSA_Pb
(mg/kg)
330
350
353
224
280
244
226
220
189
224
278
148
252
200
334
107
252
205
203
190
228
208
296
294
257
A-16
------- |