&EPA
United States
Environmental Protection
Agency
Office of Research and
Development
Washington, D.C. 20460
EPA/600/R-98/081
October 1998
Technology Evaluation
Report
Laser-Induced Breakdown
Spectrometer for Metals-
Contaminated Soil Characterization
MelAok Instruments, Inc.
-------
EPA/600/R-98/081
October 1998
Technology Evaluation
Report
Laser-Induced Breakdown Spectrometer
for Metals-Contaminated Soil
Characterization
MelAok Instruments, Inc.
by
Wayne Einfeld
Gary Brown
Environmental characterization and Monitoring Department
Sandia National Laboratories
Albuquerque, New Mexico 87185-01-0
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 89193-3478
-------
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.
-------
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
United States 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 soil sites near Butte,
Montana, in which developers of soil characterization technologies were invited to participate. The report
presents soil sample analysis results from a laser-induced breakdown spectrometer (LIBS) operated by MelAok
Instruments, Inc. This laser-assisted spectroscopic technique was one of four technologies that were used to
analyze soil samples for a number of target elements. Other technologies that were tested include a mobile
atomic absorption spectrometer operated by Pace Environmental Laboratories, Inc.; a second laser-induced
breakdown spectrometer from Los Alamos National Laboratory; and anodic stripping voltammetry systems
fielded by Battelle Pacific Northwest National Laboratory. The results from these three 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
maturity of the technology and its expected time to commercialization. Level 1 designates the least developed
and Level 3 the most developed technologies. The MelAok laser-induced breakdown spectroscopy system falls
in the Level 1 category since the system is under development. The Consortium has determined that an exhaustive
verification of the relatively new and developing Level 1 technologies should not be performed. The field
demonstration data sets from the MelAok technology are compiled, organized, and presented in this report along
with a validated data set from 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 to
assist them in further development and refinementof their instruments.
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,
111
-------
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 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
Laser-induced breakdown spectroscopy is a form of atomic emission spectroscopy that uses a high-powered laser
to vaporize a soil sample, causing excitation of the metal atoms in the sample. As the atoms decay back to
ground state, they emit photons at specific wavelengths for each element. With appropriate calibration of photon
detectors, quantitative analysis of the metal content in soil and other media is possible. The MelAok laser-
induced breakdown spectroscopy system is a relatively new technology that has successfully completed
laboratory testing and is ready for initial field evaluation. This system was demonstrated alongside three other
participating technologies in this study. All participants set up and operated their instruments over a 1-week
period in the Butte, Montana, area in September 1995. The incorporation of conventional laboratory analysis
into the demonstration plan provided a validated data set that could be used by developers to evaluate the
performance of the technology.
A comparison of the field soil sample data sets 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 reference laboratories. Data from the reference
laboratory and MelAok LIBS technology data are presented in a variety of formats to assist in comparing the data
sets produced during the demonstration.
The MelAok laser-induced breakdown spectrometer system falls into a Level 1 category. Consequently, a formal
assessment of the system's performance is not within the scope of this report.
IV
-------
Contents
Notice ii
Executive Summary iii
Figures viii
Tables ix
Acronyms and Abbreviations x
Acknowledgments xi
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 5
Technology Limitations 6
Physical Characteristics 6
Schematic Diagram 6
Operational Features 6
Calibration 6
Sample Preparation 6
Sample Analysis 7
Technology Maturity 7
Technology Performance Indicators 8
-------
Chapter3 Demonstration Design and Description 9
Technology Demonstration Objectives 9
Site Selection and Description 9
Site 1 Butte/Silver Bow Creek 10
Site 2 Anaconda Smelter/Mill Creek 13
Sample Collection, Handling, and Distribution 15
Laboratory Selection and Analysis Methodology 16
Columbia Analytical Services 16
MSB Laboratory 17
SNL Environmental Restoration Program Laboratory 17
Demonstration Narrative 18
Deviations from the Demonstration Plan 18
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-HKM Data 27
General Indicators of MSE Data Quality 28
Quantitative Indicators of MSE Data Quality 28
MSE Performance 32
Sandia National Laboratories Environmental Restoration Program Laboratory Data 32
General Indicators of SNL Laboratory Data Quality 33
Quantitative Indicators of SNL Laboratory Data Quality 33
SNL Laboratory Performance 33
VI
-------
Laboratory-to-Laboratory Data Comparison 33
Mean Percent Difference 33
Scatter Plots 33
Statistical Bias Testing 37
Intra- and Interlaboratory Variability 38
Reference Laboratory Data Set 39
Chapters Demonstration Results 41
Technology-Laboratory Data Comparison Methods 41
Field Observations 41
General Description of MelAok LIBS Results 41
Quality Control Sample Results 41
Blank Soil Sample Analysis 42
Control Soil Sample Analysis 42
Duplicate Sample Analysis 42
Recovery Analysis 42
Field Soil Sample Analysis Results 43
Comparison of LIBS Results with Reference Laboratory Data 48
Mean Percent Difference 48
Correlation Coefficients 48
Statistical Bias Testing 49
Conclusions 50
Chapter 6 Developer's Comments 51
References 52
Appendix A: Tabular Data for MelAok LIBS and Reference Laboratory Field Soil Samples A-l
vn
-------
Figures
2.1 Schematic diagram of the MelAok LIBS system 7
3-1. Montana regional map showing the Silver Bow and Mill Creek (Anaconda) sampling sites 10
3-2. Local map of the Silver Bow sampling site 11
3-3. Local map of the Mill Creek sampling site 13
4-1. Control soil sample analysis results from CAS 24
4-2. Duplicate soil sample analysis results from CAS 24
4-3. Continuing calibration verification results from CAS 25
4-4. Spiked soil sample recovery results from CAS 25
4-5. Control soil sample results from MSB 28
4-6. Duplicate soil sample results from MSE 28
4-7. Continuing calibration verification results from MSE 29
4-8. Spiked soil sample recovery results from MSE 29
4-9. Control soil sample results from SNL 32
4-10. Continuing calibration verification results from SNL 32
4-11. CAS AAS vs. CAS ICP silver measurements on field replicate soil samples 34
4-12. CAS AAS vs. CAS ICP chromium measurements on field replicate soil samples 34
4-13. CAS AAS vs. CAS ICP iron measurements on field replicate soil samples 35
4-14. MSE ICP vs. CAS ICP silver measurements on field replicate soil samples 35
4-15. MSE ICP vs. CAS ICP chromium measurements on field replicate soil samples 36
4-16. MSE ICP vs. CAS ICP iron measurements on field replicate soil samples 36
5-1. Control soil sample analysis results from the MelAok LIBS system 43
5-2. MelAok LIBS vs. reference laboratory silver 44
5-3. MelAok LIBS vs. reference laboratory arsenic 44
5-4. MelAok LIBS vs. reference laboratory cadmium 45
5-5. MelAok LIBS vs. reference laboratory chromium 45
5-6. MelAok LIBS vs. reference laboratory copper 46
5-7. MelAok LIBS vs. reference laboratory iron 46
5-8. MelAok LIBS vs. reference laboratory manganese 47
5-9. MelAok LIBS vs. reference laboratory lead 47
5-10. MelAok LIBS vs. reference laboratory zinc 48
vui
-------
Tables
2-1. LIBS Analytical Capabilities as Reported by MelAok, Inc 8
3-1. Demonstration Participants 9
3-2. Typical Heavy Metal Soil Contamination at the Butte/Silver Bow Creek Site 12
3-3. Typical Heavy Metal Soil Contamination at the Anaconda Smelter/Mill Creek Site 14
4-1. Reference Laboratory Blank Soil Sample Results 23
4-2. Serial Dilution Results from MSE 30
4-3. Mean Percent Differences from MSE ICP and CAS AAS Data 33
4-4. Reference Laboratory Linear Regression Results 37
4-5. Wilcoxon Matched Pair Statistical Test Results 38
4-6. Estimates of Intra- and Interlaboratory Sample Variation 39
5-1. MelAok LIBS Blank Soil Sample Results 42
5-2. Mean Percent Differences for MelAok LIBS and Reference Laboratory Data 49
5-3. Linear Regression Parameters for MelAok LIBS and Reference Laboratory Data 49
IX
-------
Acronyms and Abbreviations
AAS
ac
CAS
CCV
CLP
DoD
DOE
EPA
ICP
ICP-AES
K
kg
kW
LANL
LCL
LIBS
MCHD
MCLD
MCMD
MPD
RPD
SBHD
SBLD
SBMD
SNL
UCL
jam
V
W
atomic absorption spectroscopy
alternating current
Columbia Analytical Services
continuing calibration verification
Contract Laboratory Program
Department of Defense
Department of Energy
Environmental Protection Agency
inductively coupled plasma
inductively coupled plasma atomic emission spectroscopy
Kelvin
kilogram
kilowatt
Los Alamos National Laboratory
lower 95 percent confidence limit
laser-induced breakdown spectroscopy
Mill Creek-high demonstration
Mill Creek-low demonstration
Mill Creek-medium demonstration
mean percent difference
relative percent difference
Silver Bow-high demonstration
Silver Bow-low demonstration
Silver Bow-medium demonstration
Sandia National Laboratories
upper 95 percent confidence limit
micrometer
volt
watt
-------
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 Northwest National Laboratory
Khris Olsen
MelAok Instruments, Inc.
Hayward Melville
XI
-------
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.
-------
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 prototypes,
evolving technologies, 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 maturity:
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 in 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
-------
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 briefly describes
the MelAok laser-induced breakdown spectroscopy system (LIBS). Chapter 3 gives a description of 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 determined.
-------
Chapter 5 gives results and a brief analysis of the MelAok LIBS system performance. Chapter 6 contains
developer's comments regarding the demonstration.
-------
Chapter 2
Technology Description
General Description
Laser-induced breakdown spectroscopy is a form of atomic emission spectroscopy that utilizes a pulsed laser to
vaporize the sample matrix. In the LIBS system, a high-powered, pulsed laser beam is focused on a soil sample.
The interaction of the laser beam with the sample matrix results in the formation of a very hot (8,000 to 10,000
K) plasma in which all sample components are converted to atomic species. In this high-energy plasma, atomic
species are elevated to various energy states above the ground state. As they decay back to the ground state, the
atoms emit photons at discrete wavelengths for each element. A detection system counts the photons in selected
spectral regions associated with each element, yielding a quantitative measure of the number of atoms of a
particular element in the plasma. With appropriate calibration of the system using elemental standards, the
photon count data can be directly related to mass concentration of the elements in the plasma and
correspondingly, in the soil sample under analysis.
The LIBS system yields a total measure of element in the sample matrix since the entire sample volume is
converted to the atomic state in the plasma. Conventional inductively coupled plasma (ICP) and atomic
absorption spectroscopy (AAS) laboratory methods, on the other hand, give only a measure of acid-extractable
elements in a sample. Acid-extractable content may or may not be the same as total content for a particular
element. For example, if a particular element is strongly bound to an acid-insoluble component of the soil
matrix, conventional laboratory methods would not detect this species. The LIBS system, on the other hand,
reduces all species to their atomic state in the very high temperature plasma region it produces. Consequently,
the system would detect such acid-insoluble species as well.
Technology Advantages
According to the technology developers, the LIBS analytical technique offers several advantages over
conventional atomic emission or absorption spectroscopic methods. The most important advantages include the
following:
Solid, liquid, or gaseous materials may be analyzed.
Electrically conducting and nonconducting samples may be analyzed.
A relatively small (submicrogram) sample mass is required, making the method essentially nondestructive.
No wet chemistry sample preparation is required.
Sample vaporization and atomic excitation is possible in one step.
Quasi real-time analysis may be performed.
-------
In situ analysis can be performed at a distance in hostile environments with the use of fiberoptic links
between the laser and the detector.
Technology Limitations
The developers indicate several limitations of the system, compared with conventional laboratory methodologies.
They include the following:
Minimum detection levels for most elements are an order of magnitude higher than laboratory methods.
Accuracy figures are ±20% compared with ± 0% for conventional laboratory methods.
Physical Characteristics
The MelAok, Inc. (El Paso, Texas), Model MD5095 laser analyzer system has dimensions of 0.4 m (high) x
0.22 m (wide) x 0.48 m (deep) and weighs about 30 kg. The system draws about 60 W of 110-120 V ac power
and is categorized as a field-transportable instrument. Ancillary equipment includes a computer and monitor, a
laser printer, a sample pellet press (approximately 18 kg), a coffee mill/grinder, a microwave oven, and a large
cylinder of laboratory-grade argon gas. Instrument setup is rapid, requiring about 5 minutes. At remote field
locations, the time requirements are longer because a portable 5-kW generator has to be set up. Sample
preparation and instrument operation are relatively simple. One person with technical skills and training can
operate the instrument under normal conditions. Automated data processing capabilities are included in the form
of proprietary spectrum analysis software.
Schematic Diagram
A schematic diagram of the MelAok LIBS system is shown in Figure 2-1. Major components of the system
include a laser, a motor-driven sample stage, collection optics, spectrograph, detector, and computer.
Operational Features
A number of operational features of the instrument as summarized by the developer are given below.
Calibration
Warm-up and calibration of the instrument takes about 15 minutes. Calibration is normally performed once per
day. Two types of calibration are required, namely, laser power output calibration and spectrometer calibration.
A reference thermistor is used to calibrate laser output power; the thermistor in turn requires its own independent
annual calibration. A National Institutes of Standards and Technology lead metal Standard Reference Material is
used for spectrometer calibration. The system software compares the spectral output from the lead metal
standard with its internal spectral reference library and automatically adjusts for variations in spectral line
location. Spectral line intensity, which is controlled by instrument gain settings, is also automatically adjusted
using the signal output from the lead metal standard.
Sample Preparation
The accuracy and precision of the instrument depend, to a large extent, on the physical characteristics of the
sample. The best results are obtained when the sample has the following characteristics:
-------
Microscope
I ' tasa 1
1 - Attenuator
2 - Detector
3 - Power Supply
4 - Diffraction Grating
5-CCD
6 - Interrupting Device
7 - Measuring Device
8 - Power Stabilization
Device
9 - Controller CCD
10 -Step motors
11 - Step Motors Controller
12-Interface
13-IBM 486
14 - Protection Glass
IS-Sample
16 -Motor "X"
17 -Motor "Z"
18 - Protection Filters
i 80-150V
~ 50-SOHz
Figure 2-1. Schematic diagram of the MelAok LIBS system. (Courtesy of MelAok, Inc.)
Particle diameter less than 100 p.m
Relatively dry, with a moisture content less than 10 percent
Firmly compressed analysis pellet with a flat surface and a minimum of irregularities and voids
Chemically homogeneous
Sample Analysis
The recommended sample analysis method with the MelAok LIBS system is termed surface mapping by the
developers. This technique consists of firing the laser at ten different locations on the sample pellet using ten
laser firings for each location. The measurement produces an average reading from these different locations on
the sample pellet and helps to minimize the variable results that can result from inhomogeneous samples. The
analysis time for this approach is on the order of 5 minutes per sample.
Technology Maturity
The MelAok LIBS system has undergone considerable design, development, and testing in a laboratory setting.
Extensive field testing has not been done, however, and this particular demonstration was one of the first
opportunities for testing in a field environment.
-------
Technology Performance Indicators
The analytical capabilities of the MelAok LIBS system, as reported by MelAok, Inc., are presented in Table 2-
Minimum detection levels and accuracy and precision data are given in the table for a number of elements.
These are included for informational purposes only and were not further evaluated or verified as a part of the
demonstration.
Table 2-1. LIBS Analytical Capabilities as Reported by MelAok, Inc.
Element
Silver (Ag)
Arsenic (As)
Barium (Ba)
Cadmium (Cd)
Chromium (Cr)
Copper (Cu)
Iron (Fe)
Manganese (Mn)
Lead (Pb)
Strontium (Sr)
Zinc (Zn)
Analytical Parameter
Minimum
Detection Level8
(mg/kg)
10
10
10
10
10
10
10
10
10
10
10
Typical
Detection Level"
(mg/kg)
100-150
100-150
100-150
100-150
100-150
100-150
. 100-150
100-150
100-150
100-150
100-150
Accuracy
(%)
±5
±5
±5
±5
±5
±5
±5
±5
±5
±5
±5
Precision
(%)
<1
<1
<1
<1
<1
<1
<1
<1
<1
<1
<1
Estimate based on analysis of pure material, no matrix effects.
Estimate based on analysis of material in a sample matrix.
-------
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: Hayward Melville (915) 858-7055.
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.
-------
The site must have at least two sample collection 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 MSB).
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
@ Montana Slat* L
- ....-IB.-^r.vl..^
d»p *93irco56p
Figure 3-1. Montana regional map showing the Silver Bow and Mill
Creek (Anaconda) sampling sites.
10
-------
SBH - High metal* concentration
SBM - Medium metals 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. Butte
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 and
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 of
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.
11
-------
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 (MSE, 1996). A
soil analysis to assess the degree of mill tailings contamination of the local soils was carried out by MSE.
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
Sample 3
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-
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.
12
-------
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.
30 m«tir
MCH - High mitili comantntion
MCM - Madlum nwuto conctntntion
MCL - Low rrwtili concwnntfon
-I
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
13
-------
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
Sample 3
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.
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.
14
-------
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 MSB, 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 MSB 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
15
-------
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-anodic stripping 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
a 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 MSE 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.
16
-------
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
17
-------
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-custodydocumentation. 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.
18
-------
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
1 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."
19
-------
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.
RPD =
where
RPD = relative percent difference
Ya = sample result
Y/, = 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.
20
-------
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)
"~LV * )
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 y-intercept value.
The Pearson product-moment correlation coefficient (/) 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 zero 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
21
-------
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
22
-------
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
SNL ICP
<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 they-axis and the calibration number on the x-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
23
-------
60
a
_3
5
5 20
£
S..EL
n~
Eh.
CL
g -20
40
-60
-80
As
Cd
Cr
Cu
Element
Fe
Pb
nCAS-AAS
CAS-ICP
LCL
*UCL
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.
EjSBLD-1-008 (ICP) aMCLD-1-008 (ICP) aSBLD-1-008 (AAS) gMCLD-1-008 (AAS)
Figure 4-2. Duplicate soil sample analysis results from CAS.
Zn
24
-------
_
03
o
o
o>
tr
1ft
105
104-
103-
102-
101-
100-
99-
98--
97-
96-
95
3 4
Calibration No.
50
40
30
20
10
0
-10
-20
-30
-40
-50
'As
Cr
Zn
Figure 4-3. Continuing calibration verification results from CAS.
£
0)
c
o
ra
I
As Cd Cr Cu Fe Pb
Element
Mn
Zn
|SBLD-1-008(ICP) |]MCLD-1-008(ICP) ^SBLD-1-008 (Flame) aMCLD-1-008 (Flame)
Figure 4-4. Spiked soil sample recovery results from CAS. See text for
explanation of missing data.
25
-------
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.
26
-------
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 MSE 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
27
-------
80
40
20 .
s
E o
2
o
-20 1
I
5
-40 -
-80 .
Ag
As
Cd Cr Cu Fe
Element
pMSE-ICP 1 j
MSE-ICP2 i
LCL i
»UCL !
Pb
Mn
Zn
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.
-------
CD
lo
(0
4'
CO
"o
(D
o
o
CO
or
105
104-
103-
102-
101-
100-
99-
98-
97
96
95
"' '*
4567
Calibration Check No.
10
As * Cr
-o-Zri
Figure 4-7. Continuing calibration verification results from MSE.
60
-60
As
SSBLD-1-008 (ICP) aSBMD-7-008 (ICP) gMCLD-1-008 (ICP) gMCMD-7-008 (ICP)
Figure 4-8. Spiked soil sample recovery results from MSE. See text for explanation of
missing data.
29
-------
Table 4-2. Serial Dilution Results from MSE
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.
30
-------
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.
31
-------
125
120
115
110
105
100
95
90
85
80
75
80
60
40 .
% Difference from Certified V
o ao at A ro K,
o o o o o o c
-: - - -' f-- - + ' !
-
i
I n J -in
tm 1 hH EI j. . n _ . ' 1 liL-I nJl
L_r~^ uJ !
LT
» :HSNL1ai
IgSNLIbi
" !oSNL2a|
|SNL2b|
i LCL !
;»ucf |
Ag As Cd Cr Cu Fe Pb Mn Zn
Element
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.
0)
J3
OJ
c
S
in
I
8
CD
IT
3 , 4
Calibration No.
As - -4 - Cr
Pb __Zn
Figure 4-10. Continuing calibration verification results from SNL.
32
-------
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 pr-
axis with either the CAS AAS or the MSE ICP data plotted on thej-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
33
-------
100
90
70
O)
55 50^
T1 40
CO
30 -
20
10 -
o
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
3
a,
20
3 '
3 i
° 10 i
5 I
0
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.
34
-------
50.000
45,000
40,000
£ 35,000
C
2 30,000 -
in
25,000
20.000
15,000
10,000 , , , I
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 -
60
S
I
s 5°
55
& <°
30.
20 i
10 ;
0 T_
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.
35
-------
30
25
0)
I 15
O
Q.
o
111
m 10
5 10 15 20 25 30
CAS-ICP Chromium, mg/kg
Figure 4-15. MSE ICP vs. CAS ICP chromium measurements on field replicate soil
samples.
60,000
55,000
50,000
45,000 1
O>
75, 40,000 :
£
£ 35,000 -!-
n.
Ill 30,000 -
i
25,000 -
20,000 1
15,000 t % ^
10,000 J *J i
10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000 55,000 60,000
CAS-ICP Iron, mg/kg
Figure 4-16. MSE ICP vs. CAS ICP iron measurements on field replicate soil
samples.
36
-------
sample digestate whereas the MSB samples were from a different field sample split. A good comparison
between MSB 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
1JJO
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
37
-------
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 MSE 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)
MSE (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
38
-------
Table 4-6. Estimates of Intra- and Interlaboratory 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 ICP, 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 MSB 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 MSB 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 MSB ICP data set
are used for the other 30 field samples not analyzed by CAS.
39
-------
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.
40
-------
Chapter 5
Demonstration Results
Technology-Laboratory Data Comparison Methods
For Level 1 technologies such as the MelAok LIBS system, 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, data
formats and simple comparative analyses are included with the raw data. The MelAok LIBS 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 with the validated results from each laboratory
shown alongside the MelAok LIBS results for each target element. Scatter plots are included in this chapter in
which the MelAok LIBS data are plotted against the laboratory reference data set. To further assist the
technology developer in understanding the data, possible analytical approaches are suggested that might be taken
in comparing the technology data with reference laboratory data.
Field Observations
Periodically during the demonstration, an observer checked in with the MelAok LIBS demonstration team to
monitor progress. No instrument breakdowns were noted, and the soil analyses proceeded smoothly. Two
MelAok personnel were at the site and operated the instrument. The MelAok LIBS team began soil analysis on
Monday, September 25, and completed their work on Thursday, September 28, averaging about 15 soil samples
per 10-hour work day. Although the weather during the demonstration interval was occasionally rainy, windy,
and cold, it did not appear to adversely affect the performance of the MelAok LIBS instrument.
General Description of MelAok LIBS Results
A total of 60 field soil samples plus 2 control soil samples and 2 blank soil samples were analyzed with the
MelAok LIBS system for 9 target elements. The MelAok LIBS analysts produced a complete report in which an
analytical result (either a reported level or an indication of nondetectable) was included for each sample that was
submitted to them. Although duplicate analyses of several field soil samples were requested, no duplicate
analyses were reported.
Quality Control Sample Results
The results of various MelAok LIBS analyses of quality control samples are presented in the following sections.
The results are presented in a format that facilitates comparison of LIBS and laboratory data. Since the MelAok
LIBS technology is Level 1, a limited analysis of the data is presented.
41
-------
Blank Soil Sample Analysis
Table 5-1 shows a comparison of the MelAok LIBS and certified levels for blank soil samples. The MSB
laboratory results are also shown since their results tracked the certified values most closely of all the
participating laboratories. Three of the nine target elementsFe, Pb, and Crwere detected by the MelAok
LIBS system in the blank samples. No detection limits were given by the MelAok team for the other six
elements for which a "no detect" was reported; however, a generic detection limit of 100-150 rng/kg has been
reported by the developers for all elements.
Table 5-1. MelAok LIBS Blank Soil Sample Results
Element
Ag
As
Cd
Cr
Cu
Fe
Pb
Mn
Zn
Metal Concentration Level (mg/kg)
MelAok LIBS
-------
500
400
300
200
« 100 .
U
I o
-100 .
200 +
-300 -
-500
[QMLDKPE1!
iE]MLDKPE2|
j.LCL j
I * UCL |
Ag
As
Cd
Cr
Cu
Element
Fe
Pb
Zn
Figure 5-1. Control soil sample analysis results from the MelAok LIBS system.
The upper and lower confidence intervals about the certified level are also shown
on the graph. The percent difference of the lead determination was > 1,000 percent
and is off the graph scale.
Field Soil Sample Analysis Results
Analysis results were returned for all 60 field soil samples submitted to the MelAok analysis team during the
demonstration. In nearly all cases, measured values above instrument detection limits were reported. The field
sample analysis data are presented in both graphical and tabular formats to assist the developers in comparing
their data against the reference data set from the analytical laboratories. A series of nine scatter plots (Figures
5-2 through 5-10) are presented in which the MelAok LIBS data are plotted against the reference laboratory data.
As a part of the laboratory data validation process, laboratory data from the CAS ICP, CAS AAS, and MSB ICP
analyses were averaged together to yield a reference laboratory value. (See Chapter 4 for a discussion of the
makeup of the reference laboratory data set.) Normally, 60 data points are plotted in the scatter plots; however,
in many cases the points on the scatter plots are overlaid and are thus indistinguishable from each other. The
zero bias line extends from the lower left to the upper right of each plot. Plotted points falling on or close to this
line reveal close agreement between MelAok LIBS and reference laboratory data.
The MelAok LIBS data are also presented in tabular form in Appendix A to facilitate their comparison with
individual reference laboratory results. In the appendix, a series of tables are given in which the 60 sample
analysis results are given for CAS ICP, CAS AAS, MSB ICP, reference laboratory, and MelAok LIBS analysis
for the nine target elements.
Care must be taken in comparing the MelAok LIBS and laboratory results since differences in measurement
technique are likely to influence the results. For example, it was noted in Chapter 2 that the LIBS method gives a
measure of total elemental content in a sample whereas the conventional laboratory method yields a measure of
43
-------
90
80
70
O) 60
hT
O
> 50
55
in
m
j 40
o
3 30,
111
20 -
0
0 10 20 30 40 50 60 70 80 90
Lab Reference Silver, mg/kg
Figure 5-2. MelAok LIBS vs. reference laboratory silver.
1.800 ,
1,600
1,400 -
O)
H 1.200 _
E
I '.
» 1,000 , _ _ I
S3 soo :
o
3 600
UJ
400 -
200 _
200 400 600 800 1,000 1,200 1,400 1,600 1,800
Lab Reference Arsenic, mg/kg
Figure 5-3. MelAok LIBS vs. reference laboratory arsenic.
44
-------
45
40
35
O)
Jf
~a> 30
|
25 _
n
O
20,
.
3 15-
10 _
5 _
o , -T ^ , , , ,
0 5 10 15 20 25 30 35 40 45
Lab Reference Cadmium, mg/kg
Figure 5-4. MelAok LIBS vs. reference laboratory cadmium.
40
35 :
30
S
D>
I"25
C. 20
O
in
m
_i
± 15
O
S"
d>
10 .
5 1
10 15 20 25 30 35 40
Lab Reference Chromium, mg/kg
Figure 5-5. MelAok LIBS vs. reference laboratory chromium.
45
-------
4.500
4.000
3.500
"3) 3,000
E
2.500
O
in
2,000
O
a
-I 1.500
UJ
1,000
500
0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500
Lab Reference Copper, mg/kg
Figure 5-6. MelAok LIBS vs. reference laboratory copper.
50,000 - _. ... .._ _ _ ... .
45,000
40,000
O)
&
I 35,000
o '
«g 30.000
-?
o ' "
Q 25.000 - *
01 _
20,000
15,000
10,000
10.000 15,000 20,000 25,000 30.000 35,000 40,000 45,000 50,000
Lab Reference Iron, mg/kg
Figure 5-7. MelAok LIBS vs. reference laboratory iron.
46
-------
12,000
10,000 .
D)
I,
E 8,000
6.000
i
§
UJ
4,000 ._
2,000 J.
2.000
4,000 6.000 8,000
Lab Reference Manganese, mg/kg
Figure 5-8. MelAok LIBS vs. reference laboratory manganese.
10,000
12,000
3.000
2,500 .
2.000
V) 1,500 .
00
o
Q
UJ 1,000
E
500 J.
500
1,000 1,500 2,000
Lab Reference Lead, mg/kg
Figure 5-9. MelAok LIBS vs. reference laboratory lead.
2,500
3,000
47
-------
25.000
20.000
. 15.000 -
O
c
N
3 . .
^
si
O 10.000
LU
5,000 ^
0 5,000 10,000 15,000 20,000 25,000
Lab Reference Zinc, mg/kg
Figure 5-10. MelAok LIBS vs. reference laboratory zinc.
acid-extractable elemental content. The LIBS technique, as noted in the MelAok informational literature, works
best for finely ground, well-mixed soil samples. Large heterogeneous soil particles can skew the analysis results
since the laser spot diameter is on the order of 50 |im and may be influenced by single large particles of metal-
contaminated soil.
Comparison of LIBS Results with Reference Laboratory Data
The following analytical approaches are offered as illustrations of how an evaluation of LIBS performance
relative to a laboratory data set might be carried out.
Mean Percent Difference
The mean percent differences, as defined in Chapter 4, for the MelAok LIBS data set relative to the reference
laboratory data set are given in Table 5-2. A small number for mean percent difference and for the
accompanying standard deviation is an indicator of good comparability between methods. Mean percent
differences between MelAok and reference laboratory data range from a low of 20 percent for zinc to a high of
143 percent for Cd. In all cases the mean percent differences are greater than zero. The accompanying standard
deviations are generally greater than the mean percent difference values shown.
Correlation Coefficients
The slope, ^-intercept, and correlation coefficient from linear regression analysis between the MelAok and
reference laboratory data are given in Table 5-3. The slope yields a measure of the linear association of two data
48
-------
Table 5-2. Mean Percent Differences for MelAok LIBS and
Reference Laboratory Data
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
Mean Percent Difference
Reference Laboratory Data Set
74 ±72
139 ±227
143 ±179
107 + 124
81 ±69
33 ±23
57 ±98
91 ±73
20 ±49
Note: The mean value is followed by the standard deviation.
Table 5-3. Linear Regression Parameters for MelAok LIBS and Reference
Laboratory Data
Element
Ag
As
Cd
Cr
Cu
Fe
Mn
Pb
Zn
Slope
0.90
0.13
0.44
-0.04
1.15
0.72
2.43
1.31
1.51
Intercept (mg/kg)
7
850
10
20
480
13,000
-270
220
-280
Correlation Coefficient
0.89
0.20
0.40
-0.02
0.83
0.81
0.80
0.84
0.94
sets. A slope of 2 indicates that MelAok reports a value two times that of the reference laboratory, whereas a
slope of 0.5 indicates a MelAok value half of the laboratory value. The slope should always be examined
alongside the correlation coefficient. 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. With three exceptions, the correlation coefficients shown in Table 5-3 are greater than
0.8, indicating relatively good correlation of the MelAok LIBS data with the reference laboratory data.
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 MelAok LIBS data set and the reference laboratory data set. The results from
such a test should be used in conjunction with the linear regression data such as that presented in Table 5-3.
Although the statistical test may indicate that a significant bias exists between the two methods, the magnitude of
that bias must also be taken into account in the overall assessment of method comparability. In light of the fact
49
-------
that the MelAok LIBS is designated a Level 1 technology, statistical testing is left to the discretion of the
technology developer.
Conclusions
Since the MelAok LIBS system is a developing technology that has not undergone extensive field testing, a
comprehensive assessment of its performance was not undertaken in this demonstration. Conclusions as to the
system's overall performance are left to the technology developer. Comments from the developers concerning
their own performance assessment, if any, may be found in Chapter 6.
50
-------
Chapter 6
Developer's Comments
A copy of this report in draft form was sent to MelAok, Inc. for review and comment. Despite repeated attempts
to contact personnel at MelAok to obtain review comments, no response was obtained.
51
-------
References
Conover, W. J., 1980. Practical Nonparametric Statistics, 2nd ed, Wiley, New York.
Havlicek, L., and R. D. Grain, 1988. Practical Statistics for the Physical Sciences, American Chemical Society,
Washington DC, pp. 84-93.
MSB, 1996. "Final Report for RCRA and Other Heavy Metals in Soils Demonstration," MSB Technology
Applications, Inc., Butte, Montana.
52
-------
Appendix A
Tabular Data
for
MelAok LIBS
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
A-2
-------
Table A-1. Silver Analysis Results for MelAok LIBS 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_Ag
(mg/kg)
38
53
36
34
88
58
48
73
54
35
10
22
11
76
18
28
18
18
20
10
2
2
2
3
2
3
4
3
4
5
CJC_Ag
(mg/kg)
41
35
86
48
49
10
17
18
17
16
2
2
2
5
5
C_AA_Ag
(mg/kg)
46
39
95
53
54
11
19
20
19
18
2
3
3
6
6
Ref_Ag
(mg/kg)
42
53
37
34
90
58
50
73
52
35
10
22
16
76
19
28
18
18
18
10
2
2
2
3
3
3
5
3
5
5
MDK_Ag
(mg/kg)
60
70
60
50
80
60
60
70
48
66
27
28
20
36
31
32
35
16
27
23
4
5
3
5
4
7
5
5
7
9
A-3
-------
Table A-2. Silver Analysis Results for MelAok LIBS 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_Ag
(mg/kg)
3
5
4
4
6
6
5
5
8
5
4
4
4
4
4
5
5
5
6
7
4
4
4
4
4
5
5
5
6
7
C_IC_Ag
(mg/kg)
3
4
5
4
9
4
4
4
5
5
4
4
4
5
5
C_AA_Ag
(mg/kg)
3
4
7
5
10
5
4
4
5
7
5
4
4
5
7
Ref_Ag
(mg/kg)
3
5
4
4
6
6
5
5
9
5
4
4
4
4
4
5
5
5
6
7
4
4
4
4
4
5
5
5
6
7
MDK_Ag
(mg/kg)
11
12
13
12
11
11
11
13
38
15
7
8
5
5
10
13
11
12
14
12
8
10
12
10
3
11
12
6
10
16
A-4
-------
Table A-3. Arsenic Analysis Results for MelAok LIBS 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_As
(mg/kg)
1060
1660
874
764
947
1670
1510
1610
1680
111
145
254
315
549
290
357
414
399
423
260
136
152
130
165
165
132
113
128
101
88
C_IC_As
(mg/kg)
1110
866
866
1470
1490
162
155
316
408
405
144
156
181
148
137
C_AA_As
(mg/kg)
1010
765
766
1570
1530
137
132
291
380
342
120
129
157
106
102
Ref_As
(mg/kg)
1060
1660
835
764
860
1670
1517
1610
1567
111
148
254
201
549
299
357
401
399
390
260
133
152
138
165
168
132
122
128
113
88
MDK_As
(mg/kg)
470
460
570
585
410
700
740
650
680
541
710
560
320
870
720
860
990
660
760
500
900
870
960
970
980
890
1000
930
890
870
A-5
-------
Table A-4. Arsenic Analysis Results for MelAok LIBS 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_As
(mg/kg)
637
1,570
326
583
1,260
813
466
812
697
882
586
860
717
689
1,240
940
907
1,090
1,650
1,080
640
647
576
757
619
726
814
722
877
1190
C_IC_As
(mg/kg)
629
347
1,240
461
716
604
757
1,190
828
1,680
704
580
668
811
837
C_AA_As
(mg/kg)
565
275
1,130
366
663
587
708
1,030
789
1,440
604
581
612
753
808
Ref_As
(mg/kg)
610
1,570
316
583
1,210
813
431
812
692
882
592
860
727
689
1,153
940
841
1,090
1,590
1,080
649
647
579
757
633
726
793
722
841
1,190
MDK_As
(mg/kg)
1050
1550
760
1100
1080
1040
870
1320
1300
1340
1155
1230
1160
1090
1370
1520
1270
1400
1260
1460
1040
1010
1070
890
750
830
1000
1115
1120
1500
A-6
-------
Table A-5. Cadmium Analysis Results for MelAok LIBS 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
MDK_Cd
(mg/kg)
24
15
16
30
18
20
17
21
21
0
0
0
0
0
4
3
2
1
5
13
4
11
8
2
14
11
12
16
14
A-7
-------
Table A-6. Cadmium Analysis Results for MelAok LIBS 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
MDK_Cd
(mg/kg)
15
15
5
9
8
5
7
6
35
24
20
13
16
16
20
17
8
17
25
23
17
13
15
9
18
15
15
22
18
20
A-8
-------
Table A-7. Chromium Analysis Results for MelAok LIBS 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
MDK_Cr
(mg/kg)
29
29
19
25
22
26
25
20
19
20
23
22
22
21
20
L 19
18
16
22
24
32
34
32
32
36
31
26
30
29
30
A-9
-------
Table A-8. Chromium Analysis Results for MelAok LIBS 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
MDK_Cr
(mg/kg)
14
9
22
13
12
11
14
17
28
16
15
12
13
13
9
21
18
15
16
15
24
16
19
13
24
18
18
33
7
19
A-10
-------
Table A-9. Copper Analysis Results for MelAok LIBS 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
MDK_Cu
(mg/kg)
2920
3400
4080
2160
4440
2290
2230
2150
2050
2575
1250
1960
1250
2900
2280
1620
2050
960
1326
1350
540
610
580
600
440
750
780
650
640
800
A-ll
-------
Table A-10. Copper Analysis Results for MelAok LIBS 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
MDK_Cu
(mg/kg)
1390
1140
2470
1210
1530
1240
1160
1280
2770
1600
1300
980
1040
1030
1150
1470
1360
1350
1450
1300
950
1000
1310
880
880
1060
1170
1000
970
1540
A-12
-------
Table A-11. Iron Analysis Results for MelAok LIBS 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_FE
(mg/kg)
28,700
19,200
21,900
26,300
30,100
26,500
20,700
22,900
29,800
23,700
27,800
43,000
55,200
46,700
49,000
31,300
34,100
33,100
26,300
23,200
15,500
13,900
13,300
13,900
13,500
12,700
11,100
12,000
10,700
11,400
C_IC_FE
(mg/kg)
30,800
21,700
28,100
19,400
25,400
34,000
29,200
33,100
28,000
25,400
13,000
12,300
13,400
12,400
13,300
C_AA_FE
(mg/kg)
35,100
24,400
31,600
22,000
28,400
36,900
32,600
37,600
31,200
28,200
14,200
13,500
14,900
13,700
14,400
Ref_Fe
(mg/kg)
31,533
19,200
22,667
26,300
29,933
26,500
20,700
22,900
27,867
23,700
32,900
43,000
39,000
46,700
39,900
31,300
31,100
33,100
26,633
23,200
14,233
13,900
13,033
13,900
13,933
12,700
12,400
12,000
12,800
11,400
MDK_Fe
(mg/kg)
45510
40290
36760
38440
43980
39230
33310
33970
33910
36948
33880
37930
38250
39280
38560
34810
35500
39050
33570
31950
16910
18760
18270
18230
17380
19670
18890
18440
19890
20800
A-13
-------
Table A-12. Iron Analysis Results for MelAok LIBS 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_Fe
(mg/kg)
24,100
21,400
23,900
25,900
24,700
23,800
23,000
22,800
49,800
15,400
14,800
16,700
15,600
16,200
17,700
15,700
18,200
16,300
16,200
16,300
18,600
20,100
20,600
21,700
18,400
20,600
20,200
18,400
22,700
18,200
C_IC_Fe
(mg/kg)
23,100
26,300
24,400
24,100
49,200
13,500
17,200
17,500
16,500
16,800
19,200
18,500
20,400
18,900
20,600
C_AA_Fe
(mg/kg)
25,100
27,300
26,800
26,600
49,500
14,800
18,900
19,200
19,800
18,900
21,000
20,000
22,900
20,800
22,800
Ref_Fe
(mg/kg)
24,100
21,400
25,833
25,900
25,300
23,800
24,567
22,800
49,500
15,400
14,367
16,700
17,233
16,200
18,133
15,700
18,167
16,300
17,300
16,300
19,600
20,100
19,700
21,700
20,567
20,600
19,967
18,400
22,033
18,200
MDK_Fe
(mg/kg)
30,890
27,070
31,030
30,550
27,620
28,440
31,340
30,130
39,630
22,840
22,870
23,540
21,440
19,900
21,170
20,490
22,890
22,390
22,320
24,510
28,490
30,350
30,470
25,210
23,490
25,380
26,790
30,460
28,440
25,790
A-14
-------
Table A-13. Manganese Analysis Results for MelAok LIBS 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_MN
(mg/kg)
2,460
2,940
2,100
1,380
2,000
2,700
1,920
2,930
1,800
1,960
935
2,500
1,150
3,320
2,560
2,090
1,070
549
1,080
850
708
478
409
379
563
556
391
505
434
513
C_IC_MN
(mg/kg)
2,520
2,130
L 1,900
1,870
1,780
794
2,270
2,130
1,530
608
730
458
532
448
540
C_AA_MN
(mg/kg)
2,720
2,320
2,070
2,040
1,970
847
2,320
2,380
1,680
652
794
456
564
456
593
Ref_Mn
(mg/kg)
2,567
2,940
2,183
1,380
1,990
2,700
1,943
2,930
1,850
1,960
859
2,500
1,913
3,320
2,357
2,090
1,427
549
780
850
744
478
441
379
553
556
432
505
522
513
MDK_Mn
(mg/kg)
8300
11890
7800
3160
8200
9210
7930
7920
3850
7093
1660
1730
840
2060
1120
2070
1550
160
996
960
1120
600
860
500
770
1160
960
1200
1150
1120
A-15
-------
Table A-14. Manganese Analysis Results for MelAok LIBS 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_Mn
(mg/kg)
113
122
71
94
121
75
88
161
2,180
222
284
202
263
210
222
170
288
235
219
188
119
102
120
139
132
146
163
139
115
357
C_IC_Mn
(mg/kg)
115
78
124
96
2,230
267
266
206
270
225
124
113
138
155
108
C_AA_Mn
(mg/kg)
115
82
105
98
2,350
280
271
210
277
236
125
113
143
158
108
Ref_Mn
(mg/kg)
114
122
77
94
117
75
94
161
2,253
222
277
202
267
210
213
170
278
235
227
188
123
102
115
139
138
146
159
139
110
357
MDK_Mn
(mg/kg)
90
90
37
70
37
0
70
120
5360
350
340
220
300
250
190
240
270
250
240
210
150
110
220
160
270
250
240
220
130
320
A-16
-------
Table A-15. Lead Analysis Results for MelAok LIBS 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
MDK_Pb
(mg/kg)
2220
2170
2500
1650
1700
2340
2520
2670
1930
1797
1020
1180
770
1280
1120
1260
1160
690
923
870
600
530
560
630
570
670
680
650
670
650
A-17
-------
Table A-16. Lead Analysis Results for MelAok LIBS 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
MDK_Pb
(mg/kg)
340
660
370
380
470
330
400
440
1560
730
620
530
550
550
690
650
590
680
860
670
430
500
460
520
610
740
780
760
720
820
A-18
-------
Table A-17. Zinc Analysis Results for MelAok LIBS 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_ZN
(mg/kg)
7,410
3,830
6,750
3,620
14,800
5,530
5,440
5,870
4,710
7,160
1,270
3,440
1,410
3,760
4,080
2,550
2,810
1,300
2,020
1,660
426
327
310
404
343
413
543
363
325
420
C_IC_ZN
(mg/kg)
8,590
6,540
16,600
5,240
4,510
2,040
2,810
3,390
2,640
2,040
396
343
341
700
429
C_AA_ZN
(mg/kg)
9,340
7,130
18,000
5,810
5,000
2,190
3,040
3,860
2,950
2,230
442
381
375
773
473
Ref_Zn
(mg/kg)
8,447
3,830
6,807
3,620
16,467
5,530
5,497
5,870
4,740
7,160
1,833
3,440
2,420
3,760
3,777
2,550
2,800
1,300
2,097
1,660
421
327
345
404
353
413
672
363
409
420
MDK_Zn
(mg/kg)
11710
12640
11150
6880
22600
10970
10610
12170
5300
12230
1420
1580
1190
1980
1730
2480
2440
930
1175
2440
400
290
390
260
180
560
540
490
550
630
A-19
-------
Table A-18. Zinc Analysis Results for MelAok LIBS 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_Zn
(mg/kg)
609
525
577
662
640
474
538
669
4,080
430
388
447
406
387
722
596
746
657
858
698
437
543
587
529
591
687
755
642
654
994
C_IC_Zn
(mg/kg)
640
623
611
588
4,130
417
441
686
671
887
468
541
651
751
610
C_AA_Zn
(mg/kg)
141
137
673
657
4,600
462
483
739
741
1,000
517
586
727
805
668
Ref_Zn
(mg/kg)
463
525
446
662
641
474
594
669
4,270
430
422
447
443
387
716
596
719
657
915
698
474
543
571
529
656
687
770
642
644
994
MDK_Zn
(mg/kg)
940
730
800
970
800
770
890
930
5570
650
540
550
460
380
520
520
580
550
680
670
670
740
660
540
660
710
700
850
740
830
A-20
------- |