United States
Environmental Protection
Agency
Office of Toxic Substances
Office of Solid Waste
Office of Office of
Toxic Substances Solid Waste
Washington, D.C. 20460 Washington, D.C. 20460
EPA 560/5-90-008B
April 1991
PCB, LEAD, AND CADMIUM
LEVELS IN SHREDDER WASTE
MATERIALS: A PILOT STUDY
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U.S. ENVIRONMENTAL PROTECTION AGENCY
PCB, LEAD, AND CADMIUM LEVELS IN SHREDDER WASTE MATERIALS:
A PILOT STUDY
FINAL REPORT
Contract No. 68-02-4293 (Westat)
Contract No. 68-02-4252 (MRI)
Contract No. 68-02-4294 (BCL)
April 1991
Prepared by:
Westat, Inc.
1650 Research Boulevard
Rockville, MD 20850
Midwest Research Institute
425 Volker Boulevard
Kansas City, MO 64110
Battelle Columbus Division
505 King Avenue
Columbus, OH 43201
For the:
Exposure Evaluation Division
Office of Toxic Substances
and
Characterization and Assessment Division
Office of Solid Waste
U.S. Environmental Protection Agency
Washington, DC 20460
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DISCLAIMER
This document has been reviewed and approved for publication by the Office of Toxic
Substances, Office of Pesticides and Toxic Substances, and the Office of Solid Waste, Office of
Solid Waste and Emergency Response, U.S. Environmental Protection Agency. The use of trade
names or commercial products does not constitute Agency endorsement or recommendation for
use.
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AUTHORS AND CONTRIBUTORS
The initial project planning, field sampling, chemical analysis, and statistical analysis
contained in this report represent the joint efforts of several organizations and many individuals.
The field sampling team participated jointly in a training workshop just prior to taking the field.
The names of the principal authors and the contributions of the various organizations are
summarized below.
Westat. Inc. - Organized and conducted the training workshop; contacted shredder
operators and scheduled the visits; provided two team leaders; and wrote portions
of the Quality Assurance Project Plan. Upon completion of the Chemical Analysis
Phase, Westat performed the statistical analysis and wrote portions of the final
report.
John Rogers John Michael
Stephen K. Dietz William Devlin
Midwest Research Institute (MRI) - Participated in the training workshop;
procured and prepared the required field sampling materials; conducted the field
sampling portion of the study in cooperation with the team leaders; performed
chemical analyses for PCBs, lead, and cadmium; wrote portions of the Quality
Assurance Project Plan and the final report.
Paul Constant Chuck Vaught
Rob Scuderi Jelena Vukov
Randy Nelson Dan March
Battelle Columbus Lahoratpp'qt (BCL) — Participated in the training workshop and
provided a team leader for several of the field visits.
Bruce Buxton
EPA. OTS. Exposure Evaluation Division - EPA Staff had overall responsibility
for this project and played an active role in guiding this pilot study, from the
conceptual design through the sampling and analysis period and data reduction,
analysis, and interpretation. Principal EPA contributors included:
EPA/EED
Cindy Stroup, DDE Branch Chief
Joseph J. Breen, FSB Branch Chief/MRI Contract Project Officer
Mary Frankenberry, Westat/BCL Contract Project Officer
Edith B. Sterrett, Westat/BCL Contract Project Officer
Dan Reinhart, Westat/BCL Work Assignment Manager /Statistician
Khoan Dinh, Senior Statistician
John Scalera, MRI Work Assignment Manager/Chemist
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EPA. OSW. Characterization and Assessment Division
Co-sponsors of design, sampling, and analysis consultation for lead and
cadmium portion of the pilot study, Principal contributor: Alexander
McBride.
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ACKNOWLEDGMENTS
The study sponsors, EPA's Offices of Toxic Substances and Solid Waste, wish to
thank everyone involved for working together in a highly cooperative manner. The pilot study, in
particular, the planning and field portions, were conducted under extremely strict time constraints
Special recognition is due to Paul Constant, of Midwest Research Institute, for his management
support in forming and equipping well-qualified field teams on very short notice, and Bill Devlin,
of westat, for his almost heroic efforts in scheduling the site visits in an extremely short time-
frame.
We greatly appreciate the efforts of the Institute of Scrap Recycling Industrie's, Inc.
(ISRI), in particular to ensure the cooperation of their member facilities. Herschel Cutler, ISRI's
Executive Director, and his staff members: Duane Siler and David Wassum, all participated in
planning meetings and in the training of the EPA field crews. They were actively involved in
crafting the specific language of the Individual agreements between EPA and the participating
shredder facilities. Ben Baker, an ISRI member and shredder operator, provided invaluable
information as part of the training session for the field crews.
We also wish to thank Dean S. Hill and Arturo Palomares of the EPA's National
Enforcement Investigation Center for their chemical analysis support which was conducted under
severe time restrictions. We are also grateful tor the external laboratory quality assurance support
provided by Llewellyn Williams ana Wayne Sovocol of the EPA Environmental Monitoring
Systems Laboratory in Las Vegas, Nevada.
Many other individuals contributed their time and effort to this challenging project.
Especially helpful in providing overall technical direction during the planning stages of the pilot
was Martin P. Helper, then Director of the Exposure Evaluation Division in EPA's Office of Toxic-
Substances. Contributors to the Quality Assurance Project Plans included Jay Glatz of EPA, Jack
Baisinger of MRI, and David Morganstein of Westat. Preparation of the training manual was
assisted by Leslie Athey, Dani Bassett, Charlotte Lass, and Victoria Albright of Westat. Doug
Duncan of Westat conducted systems analysis and data processing. Technical editing was provided
by the Westat Editorial Support Group,
lii
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IV
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TABLE OF CONTENTS
Chapter Page
EXECUTIVE SUMMARY xv
1 INTRODUCTION 1-1
1.1 Background 1-1
1.2 Scrap Recycling Industry 1-1
1.3 Environmental Concerns 1-2
1.4 Perspectives on PCBs 1-3
1.5 Pilot Study Objectives 1-4
1.6 Roadmap to Report 1-5
2 RESULTS AND CONCLUSIONS 2-1
3 STUDY DESIGN 3-1
3.1 Pilot Program Design Objectives 3-1
3.2 Site Selection 3-1
33 Composition of Input Streams by Category 3-2
3.4 Sampling Design Procedures 3-2
33 Chemical Analysis Design 3-3
3.6 Statistical Analysis Design 3-4
3.7 Data Coding, Processing, and Storage 3-4
3.8 Design Definitions 3-5
3.9 Final Analysis Design 3-5
4 FIELD METHODS 4-1
4.1 Planning and Preparations 4-1
4.1.1 Training 4-1
4.12 Preparation of Sampling Equipment 4-1
4.2 Sampling 4-2
42.1 Documentation, Transportation, and Storage 4-2
4.3 Site Selection 4-2
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TABLE OF CONTENTS (Continued)
Chapter Page
4.4 Shredder Equipment and Operations at Various Sites 4-3
4.4.1 Sampling Task 4-3
4.42 Auto Fluff 4-6
4.4.3 White Goods 4-7
4.4.4 Mixed Goods 4-8
4.4.5 Spillover Sampling 4-8
4.4.6 Ferrous Metals Sampling 4-9
4.4.7 Nonferrous Metals Sampling 4-9
4.4.8 Stored Fluff (Materials Stored Over 8 Hours) 4-9
4.4.9 Soil 4-9
4.5 Questionnaire 4-9
5 SUMMARY OF THE DATA - STATISTICAL ANALYSIS 5-1
5.1 Introduction 5-1
5.1.1 Aggregating Nested Components and
Components of Variance 5-7
52 Polychlorinated Biphenyls 5-10
52.1 Total PCBs 5-10
5.22 PCB Aroclors 5-21
523 Hot and Room Temperature Water
Extraction of PCB 5-24
52.4 Components Analysis 5-31
53 Total Lead and Cadmium 5-38
53.1 Total Lead 5-40
532 Total Cadmium 5-44
5.4 EPTOX Lead and Cadmium 5-48
5.4.1 EPTOX Lead 5-48
5.42 EPTOX Cadmium 5-52
5.5 Relationship Between Lead and Cadmium Total
and EPTOX Measurements 5-54
5.6 Summary of Results for Lead and Cadmium 5-60
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TABLE OF CONTENTS (Continued)
Chapter Page
6 SAMPLE ANALYSIS 6-1
6.1 Background 6-1
6.2 Sample Preparation 6-5
6.2.1 Sample Homogenization and Subsampling 6-5
6.22 Comparison of PCB Extraction Techniques
Using Organic Solvents 6-5
6.23 Sample Extractions with Water to Examine
PCB Leachability 6-11
6.2.4 Components Analysis 6-11
6.3 Chemical Analysis 6-12
63.1 Apparatus and Materials 6-12
632 Reagents 6-18
633 Contamination Avoidance 6-21
63.4 Instrumental Analysis 6-21
7 QUALITY ASSURANCE 7-1
7.1 Quality Assurance Project Plan Development 7-1
72 Field Sampling Activities 7-2
7.2.1 Data Quality Objectives (DQOs) 7-2
722 Standard Operating Procedures (SOPs) 7-2
723 Presampling 7-2
72.4 Sampling and Tracking 7-4
73 Laboratory Activities - Chemical Analysis Phase 7-4
73.1 Sample Handling 7-4
732 Sample Preparation 7-4
7.4 Field Sampling Quantitative Results 7-6
7.5 Sample Analyses 7-6
7.6 Quality Control Samples/Chemical Analysis
Results and Comparison 7-8
7.6.1 Data Quality Objectives 7-9
7.6.2 Accuracy and Precision Results 7-9
7.63 Inter-Lab Comparison 7-9
7.7 Auditing Activities 7-19
7.7.1 Internal Audit (MRI) 7-19
7.7.2 External Audits 7-20
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TABLE OF CONTENTS (Continued)
Chapter page
GLOSSARY GL-1
List of Appendices
Appendix
4-A FLUFF PILOT PROGRAM TRAINING MANUAL 4-A-l
4-B CONFTDENTIALrrY PLAN 4-B-l
4-C LETTERS 4-C-l
4-D QUESTIONNAIRE RESULTS FROM WORKSHEET 9 4-D-l
5-A TOTAL CONCENTRATION OF PCBs IN PPM BY
SITE, SAMPLE TYPE, TOTAL CONCENTRATION
OF LEAD (EFTOX LEAD) IN PPM BY SITE, SAMPLE
TYPE, AND TOTAL CONCENTRATION OF CADMIUM
(EPTOX CADMIUM) IN PPM BY SITE, SAMPLE TYPE 5-A-l
5-B STATISTICAL ANALYSIS TECHNICAL APPENDIX 5-B-l
6-A TEST PATTERN FOR LABORATORY ANALYSES 6-A-l
6-B SOXHLET/TUMBLER DESIGN COMPARISON 6-B-l
6-C AROCLORS LOT NUMBERS 6-C-l
6-D CERTIFICATES OF ANALYSIS 6-D-l
6-E PCB AROCLORS 6-E-l
6-F METHOD 8080, ORGANOCHLORINE PESTICIDES
AND PCBs 6-F-l
7-A STANDARD OPERATING PROCEDURE -
PROCEDURE FOR DRAWING A REPRESENTATIVE
SUBSAMPLE 7-A-l
7-B STANDARD OPERATING PROCEDURE -
INTRODUCTION TO FLUFF AND SAFETY 7-B-l
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TABLE OF CONTENTS (Continued)
List of Appendices (Continued)
Appendix Page
7-C STANDARD OPERATING PROCEDURE -
WILEY MILL OPERATION 7-C-l
7-D STANDARD OPERATING PROCEDURE -
WILEY MILL CLEANING 7-D-l
7-E MODIFIED METHOD 8080 7-E-l
7-F SEPARATORY FUNNEL LIQUID-LIQUID
EXTRACTION AND CLEANUP 7-F-l
7-G SOXHLET EXTRACTION AND CLEANUP 7-G-l
7-H TUMBLER EXTRACTION 7-H-l
7-1 THE DETERMINATION OF POLYCHLORINATED
BIPHENYLS IN TRANSFORMER FLUID AND
WASTE OILS 7-1-1
7-J METHOD 680: DETERMINATION OF PESTICIDES
AND PCBs IN WATER AND SOIL/SEDIMENT BY
GAS CHROMATOGRAPHY/MASS SPECTROMETRY 7-J-l
List of Tables
Table
2-1 Mean concentrations of total lead and cadmium in fluff 2-3
2-2 Mean concentrations of EPTOX lead and cadmium in
leachate from fluff 2-3
3-1 Number of samples analyzed for PCBs, by site and
sample type 3-6
5-1 Number of samples analyzed for PCBs by site and
sample type 5-10
5-2 Summary of PCB concentrations by type of sample (ppm) 5-12
*
5-3 Mean PCB concentrations, with approximate 95% confidence
intervals, in fluff and soil, by type of sample material
(confidence intervals obtained by bootstrap method) 5-15
IX
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TABLE OF CONTENTS (Continued)
List of Tables (Continued)
Tables Page
5-4 Relative PCB concentrations in ferrous and nonferrous
stream compared with fresh fluff from the same run 5-17
5-5 Aroclor 1242 as a percent of total PCB concentration by
sample type, with approximate 95% confidence intervals 5-24
5-6 Extractability of PCBs from fluff using hot and room
temperature water (approximate 95% confidence intervals
shown in parentheses) 5-27
5-7 Component data documentation 5-33
5-8 Precision of the measurements of PCBs in component
samples, expressed as the coefficient of variation of the
concentrations in replicate subsamples 5-35
5-9 Total PCB concentration in five components from four
composite fluff samples 5-37
5-10 Ratio of the PCB concentrations in each component to the
concentration in fine material, dirt, and dust in the same
composite sample, with approximate 95% confidence intervals 5-38
5-11 Number of samples analyzed for total lead and cadmium by
site and sample type 5-40
5-12 Summary of total lead concentrations by type of sample (ppm) 5-42
5-13 Mean with approximate 95% confidence intervals for total
lead concentrations (ppm) in fluff and soil by type of sample 5-44
5-14 Summary of total cadmium concentrations by type of
sample (ppm) 5-46
5-15 Mean with approximate 95% confidence intervals for
total cadmium concentrations (ppm) in soil and fluff
by type of sample 5-46
5-16 Number of samples analyzed for EPTOX lead and
cadmium by site and sample type 5-48
5-17 Summary of EPTOX lead concentrations by type of
sample (ppm) 5-50
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fables
TABLE OF CONTENTS (Continued)
List of Tables (Continued)
5-18 Mean with approximate 95% confidence intervals for
EPTOX lead concentrations (ppm) in fluff by type
of sample 5-50
5-19 Summary of EPTOX cadmium concentrations by type
of sample (ppm) 5-52
5-20 Mean with approximate 95% confidence intervals for
EPTOX cadmium concentrations (ppm) in fluff and soil
by type of sample 5-54
5-21 Concentration ratio (EPTOX/Total) for lead and cadmium 5-56
6-1 Gas chromatographic conditions for HRGC/ECD
analysis (HP5890) 6-15
6-2 Gas chromatographic conditions for HRGC/EDC
analysis (Varian 3500) 6-15
6-3 Gas chromatographic conditions for GC/ECD analysis
of Aroclor combinations to be quantitated by
the Webb-McCall method 6-16
6-4 HRGC/HRMS operating conditions for PCB analysis 6-17
6-5 Individual PCB isomer mix calibration standards 6-20
6-6 PCB quantitation ions and ion abundance ratios 6-24
7-1 Field sampling equipment 7-3
7-2 Analytical limits of detection (LOD) and limits of quantification
(LOQ) 7-5
7-3 Ratio of concentrations measured by MRI to those measured by
EMSL on the sample, with approximate 95% confidence
intervals 7-17
7-4 Performance audit sample (PAS) results 7-20
XI
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TABLE OF CONTENTS (Continued)
List of Figures
Figure Page
4-1 Illustrated Shredder System 4-4
4-2 Schematic illustration of the shredding process 4-5
5-1 Boxplot example 5-2
5-2 Confidence interval example 5-3
5-3 Histogram of PCB concentration in fresh fluff using no
transformation 5-4
5-4 Histogram of PCB concentration in fresh fluff using log
transformation 5-5
5-5 Distribution of PCB concentrations in fluff samples by
type of material 5-11
5-6 Mean with approximate 95% confidence interval for PCB
concentration in fluff and soil by output stream 5-14
5-7 Comparison of output streams from the same run: PCB
concentrations in ferrous and nonferrous versus fluff 5-16
5-8 Comparison of PCBs in fluff and ferrous output streams
from the same run 5-18
5-9 Comparison of PCBs in fluff and nonferrous output
streams from the same run 5-19
5-10 Distribution of PCBs among output streams 5-20
5-11 Aroclor 1242 as a percent of total PCBs in all fresh
fluff runs, by dominant non-1242 Aroclor 5-22
5-12 PCB Aroclor 1242 as a percent of the total PCB
concentration, by sample type and input material type 5-23
5-13 Aroclor 1242 as a percent of total PCB concentration by
sample type, with appropriate 95% confidence intervals 5-25
5-14 Extraction of PCBs from fluff using hot and room
temperature water versus using hexane/acetone 5-28
5-15 Percentage of PCBs extracted from fluff using hot
and room temperature water 5-29
xu
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Figure
TABLE OF CONTENTS (Continued)
List of Figures (Continued)
5-16 PCB concentration in the water extract after hot and
room temperature extraction 5-30
5-17 Weight of five components in four composite fluff samples
as a percent of the total weight of the composite sample 5-34
5-18 PCB concentrations in five components of four composite
fluff samples 5-36
5-19 Amount of PCBs in five components of four composite
fluff samples as a percent of the total PCBs measured 5-39
5-20 Total lead concentration in fluff and soil samples
by type of material 5-41
5-21 Total lead concentration with 95% bootstrap
confidence interval by sample type 5-43
5-22 Total cadmium concentrations in fluff and soil samples
by type of material 5-45
5-23 Total cadmium concentration with 95% bootstrap
confidence interval by sample type 5-47
5-24 EPTOX lead concentrations in fluff samples
by type of material 5-49
5-25 Mean with approximate 95% confidence intervals for
EPTOX lead concentration in fluff by output stream 5-51
5-26 EPTOX cadmium concentrations in fluff samples by
type of material 5-53
5-27 EPTOX cadmium concentration with approximate 95%
confidence interval by sample type 5-55
5-28 EPTOX lead versus total lead concentrations
at seven shredder sites by sample type 5-57
5-29 EPTOX cadmium versus total cadmium concentrations
at seven shredder sites by sample type 5-58
5-30 Concentration ratio (extract/total) for lead and
cadmium using the EPTOX extraction process 5-59
Xlll
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TABLE OF CONTENTS (Continued)
List of Figures (Continued)
Figure Page
6-1 PCB analysis steps using Soxhlet and tumbler extraction 6-2
6-2 Total lead and cadmium analysis steps 6-3
6-3 EPTOX lead and cadmium analysis steps 6-4
6-4 PCB measurements using Soxhlet versus tumbler extraction 6-7
6-5 Comparison of analytical methods: Soxhlet versus tumbler,
tumbler with one versus three rinses 6-8
6-6 PCB measurements using one rinse versus three rinses
during tumbler extraction 6-10
6-7 Agitation apparatus for tumbler extraction 6-14
7-1 Inter-laboratory comparison of sample measurements of PCB 7-11
7-2 Inter-laboratory comparison of sample measurements
of total lead 7-12
7-3 Inter-laboratory comparison of sample measurements
of total cadmium 7-14
7-4 Inter-laboratory comparison of sample measurements
of EPTOX lead 7-15
7-5 Inter-laboratory comparison of sample measurements
of EPTOX cadmium 7-16
7-6 Inter-laboratory comparison of sample concentrations 7-18
List of Exhibits
Exhibit
1-1 Perspectives on the PCB Problem 1-4
xiv
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EXECUTIVE SUMMARY
The U.S. Environmental Protection Agency (EPA) is investigating the presence of
polychlorinated biphenyls (PCBs) and other hazardous substances in waste products produced at
metal salvage and recycling facilities. Under both the Toxic Substances Control Act (TSCA) and
the Resource Conservation and Recovery Act (RCRA), EPA has the responsibility to control the
disposal of toxic materials. This report describes the results and methods of a study conducted in
1989-90 which was co-sponsored by EPA's Offices of Toxic Substances and Solid Waste.
Information received by EPA prior to this study indicated that PCBs, lead, and
cadmium are released during the shredding of automobiles and consumer products, resulting in
the contamination of shredder waste materials. Some scrap metal recyclers felt that capacitors in
consumer appliances (called "white goods") might be the source of PCB contamination and, in
reaction to the growing awareness of waste contamination, stopped accepting them for shredding.
That decision created a solid waste disposal dilemma in several states because of the accumulation
of refrigerators, stoves, and washing machines.
The EPA continued to receive reports of contaminated shredder waste that
indicated a possible need for regulatory action. However, the information was insufficient to
determine the source of the contamination or what regulatory action, if any, would be appropriate.
Further, EPA needed information on the teachability of PCBs from shredder waste materials.
In light of the growing solid waste disposal dilemma and the lack of conclusive
information on contaminant sources, the EPA's Offices of Toxic Substances and Solid Waste
undertook this pilot study to learn more about shredder operations. The results of the pilot study
will be used to determine whether rulemaking activity is needed and to design future studies, if
necessary. EPA recognizes the valuable contribution of the recycling industry and wants to keep
the facilities operating in the most environmentally safe and economically practical manner
possible.
Pilot Study Design and Operations
Shredder faculties typically have three separate output streams: recyclable ferrous
metal, recyclable nonferrous metal, and waste materials which are commonly called "fluff." The
overall objectives of the pilot study were to improve our knowledge of shredding operations; to
develop sampling and analysis methods for shredder sites; to determine ranges of PCB, lead, and
cadmium levels in the fluff; to determine PCB levels in ferrous, and nonferrous metallic output
streams; to collect information on the leachability of PCBs from fluff, to measure lead and
cadmium levels in leachate from fluff; and to gain insight on the sources of contaminants in fluff.
It is important to keep in mind that this was a pilot study and the results are not
necessarily representative of the whole recycling industry. The sample selection process began
with a selection of seven geographic clusters of shredder facilities spread across the United States.
Within each geographic cluster, one shredder facility was randomly selected. Although this
selection process was not completely random, EPA has no indication that any substantial bias was
introduced by the sampling plan.
xv
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Operators do not normally separate their materials as they put them into the
shredder, but for the purpose of the pilot study, they segregated their input materials by type in
order to allow separate shredding of three distinct material categories: automobiles only, white
goods only, and mixed-input. The mixed-input materials included construction materials,
demolition waste, and at some sites, appliances and/or automobiles. This segregation of input
materials allowed EPA to separately sample fluff produced from each input category.
EPA developed field sampling methods in order to collect representative samples
of all output materials at each site. Any fluff that had previously been shredded and was piled up
or stored at the study sites was also sampled and analyzed for comparison to newly produced or
"fresh" fluff. Soil samples were collected, as well
The great heterogeneity of the collected output materials required the development
of innovative methods for their handling and preparation in the laboratory. An existing extraction
method was adapted for PCB analysis to allow a much larger amount of material to be analyzed
and thus reduce measurement variability. Standard chemical analysis detection methods were
then used to determine PCB, lead, and cadmium concentrations.
A special study was conducted to obtain information concerning the water
teachability of PCBs from fluff. The standard Extraction Procedures Toxicity Test (EPTOX)
specified by RCRA was applied to the fluff samples for lead and cadmium analysis.
A subset of samples was divided into its primary physical components (e.g., glass,
rubber, metal) and each component analyzed separately. This separate analysis was done in order
to understand the potential sources of PCB contamination in fluff.
A rigorous quality assurance program was implemented at every step of the study,
from design through sample collection; chemical analysis; and data reduction, analysis, and
interpretation.
Pilot Study Results and Conclusions
The results and conclusions of this pilot study must be appropriately interpreted.
The pilot study results do not necessarily represent the shredding industry as a whole. In addition,
certain estimates are based on a very limited number of samples. Details of these estimates can be
found in Chapter 5. The EPA cautions readers against overgeneralizing from these data.
The primary objectives and conclusions of the pilot study are as follows:
Objective 1. To develop field sampling, sample preparation, and laboratory
analysis methods for shredder output materials.
A variety of specific methods were developed for sampling the three shredder
output streams: fluff, ferrous metal, and nonferrous metal.
xvi
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Objective 2. To determine ranges of PCB levels in fluff.
PCBs were found in all sampled material at all pilot study sites. Fluff from the
shredding of automobiles had levels in the same general range as fluff from the
shredding of white goods. Fluff from mixed-input materials had significantly higher
average levels than the other types of fluff. The average PCB concentration across
sites for all fresh fluff is 43 ppm (approximate 95% confidence interval from 22 to
120 ppm).
Objective 3. To determine the ranges of PCB levels in the ferrous and nonferrous
metallic output streams.
PCBs were found in both ferrous and nonferrous metallic output streams in much
lower levels than in the fluff. The average PCB level across all sites for the ferrous
metallic output stream was 0.20 ppm (approximate 95% confidence interval from
0.14 to 030 ppm), and for the nonferrous metallic output stream it was 1.0 ppm
(approximate 95% confidence interval from 0.47 to 6.8 ppm). On the average, the
PCB concentrations in fresh fluff are roughly 200 times that in the ferrous material
and 50 times that in nonferrous material. When the relative weights and PCB
levels of the output streams are considered together, 98% of the PCBs are found to
be associated with the fluff.
Objective 4. To determine the teachability of PCBs from fluff.
A Soxhlet extraction using hot water as the solvent was run on selected fluff
material that had been found to have high PCB concentrations. This was
considered to be a reasonable "worst case" scenario of leachability. After eight days
of hot water extraction, the amount of PCBs extracted corresponds to 0.0073% of
the PCBs present (approximate 95% confidence interval from 0.0019% to 0.028%).
The PCB concentration in the extract water was 0.0018 ppm. An 8-day room-
temperature extraction was conducted on portions of the same fluff samples using a
slurry extraction apparatus and, as might be expected, the percentage of PCBs
extracted was lower (0.0050%) than with hot water. From these analyses, it
appears that leachability of PCBs from fluff is lower than that found in most soil
matrices.
Objectives. To examine the major physical components of fluff in order to
discover possible sources of PCBs in fluff.
To determine possible sources of PCBs in fluff, the fluff was separated into major
physical components which were individually analyzed for PCBs. About half the
mass of the material in fluff consists of dirt, dust, and other fine material too small
for precise classification; this comprised one category. Other components included
metal and wire fragments, soft and hard plastic and rubber, glass, fabric, paper, and
wood. This analysis did not yield dear conclusions relating sources of PCBs in fluff
to particular categories of physical components. There were no statistically
significant differences in measured PCB levels between the categories of physical
components.
xvu
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Objective 6. To determine ranges of total lead and cadmium levels in fluff.
Total lead concentrations in most samples were within the range of 1,000 to 10,000
ppm. Total cadmium concentrations in most samples were lower, within the range
of 10 to 100 ppm. Soil samples had the lowest and most variable total lead (10 to
10,000 ppm) and total cadmium (0.10 to 100 ppm) concentrations.
Objective 7. To measure the lead and cadmium levels in leachate from fluff.
The results of the Extraction Procedures Toxicity test showed values ranging from
0.8 ppm to 220 ppm for lead, and 0.2 ppm to 4.0 ppm for cadmium.
Objective 8. To relate input materials to contaminants in fluff.
The pilot study data do not clearly point to any particular input material type as the
source of PCBs, lead, or cadmium. These contaminants were found in all sampled
materials at all sites. The highest PCB levels were found in fluff produced by
shredding mixed-input materials, which at some sites included automobiles and
white goods. White goods fluff and automobile fluff had similar levels of PCB.
Objective 9. To collect information to help design future studies.
The pilot study yielded a substantial amount of information that is being utilized by
the EPA in its regulatory and technical support activities. If further studies are
needed, this information will be used to plan them.
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1. INTRODUCTION
1.1 Background
The U.S. Environmental Protection Agency is investigating the presence of
polychlorinated biphenyls and other hazardous substances in waste products, commonly called
"fluff," produced at metal shredding and recycling facilities. Under both the Toxic Substances
Control Act and the Resource Conservation and Recovery Act, EPA is responsible for controlling
the disposal of toxic materials. This effort was co-sponsored by EPA's Office of Toxic Substances
and Office of Solid Waste.
Preliminary information received by EPA indicated that PCBs, lead, and cadmium are
released during the shredding of automobiles and consumer products, resulting in the
contamination of fluff. Some scrap metal recyclers felt that capacitors in consumer appliances
(called "white goods") might be the source of PCB contamination and, in reaction to the growing
awareness of fluff contamination, stopped accepting appliances for shredding. That decision
precipitated a solid waste disposal crisis in several states because recycling of refrigerators, stoves,
and washing machines was backlogged.
The EPA continued to receive reports of contaminated shredder waste that indicated
a possible need for regulatory action. However, the information was insufficient to determine the
source of the contamination or what regulatory action, if any, would be appropriate. In light of the
growing solid waste disposal crisis and the lack of conclusive information on contaminant sources,
the EPA's Offices of Toxic Substances and Solid Waste undertook a pilot study to learn more
about shredder operations and fluff.
1.2 Scrap Recycling Industry
The United States scrap recycling industry is an important component of this
country's environmental management program. It is a young industry; most of the existing
shredding equipment was installed during the past 15 to 20 years. The industry's physical facilities
are located nationwide, with a concentration in heavy industrial areas, and include about 2001
shredders, 1,200* balers, and 1,000* shearers.
The Federal, state and local governments value highly the industry's recycling
activities and its effects in helping to extend precious solid waste landfill capacity. Reports that
shredding activities and wastes may be regulated under TSCA, or that fluff may be a hazardous
waste under RCRA Subtitle C, have concerned all parties, government and industry alike.
*Melallk Scrap - The Manufactured Resource, Institute of Scrap Iron and Steel, Inc., 1984.
1-1
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Approximately 12 to 14 million tons of steel scrap2 are generated for recycling each
year from shredders being fed by:
• Approximately 8-10 million cars, trucks, and vans;2
• Several million appliances; and
• A wide variety of industrial and household scrap.
The commercial value of the recycled materials is over $1.5 billion per year.3
A major environmental benefit of shredding automobiles and appliances is that the
volume of waste to be deposited in landfills is reduced by two-thirds to three-quarters. There are
reductions in energy requirements of recycled scrap metals over metals produced from raw ores
and a reduction in air pollutants. These benefits include:
For steel:
• A reduction of 94% in participates;4
• A reduction of 74% in energy;4
• Major reduction in benzene by-product from coke, which is not needed for the
electric furnaces which process mostly scrap steel.
For aluminum:
• A reduction of 76% in particulates 4
13 Environmental Concerns
Shredding operations produce over 3 million tons of fluff per year, which has typically
been disposed of in nonhazardous or municipal landfills. However, reports of PCB contamination
have prompted EPA to investigate the need to control the disposal of fluff.
2 Robert J. Schmitt, Automobile Shredder Residue - The Problem and Potential Solutions, (Center for Materials Production, CMP
Report No. 90-1, January 1990).
^American Metal Market, March S, 1990. Shredded Scrap Price Composite graph shows an average price over the past 26 months as S126
per ton. Applied to approximately 12 million tons of steel scrap, this equates to $1.512 billion for the steel scrap alone.
4Assessment of the Impact of Resource Recovery on the Environment, EPA-600/8-79-011, August 1979, MITRE Corp/MERL/ORD/
EPA, Cincinnati, Ohio.
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1.4 Perspectives on PCBs
Polychlorinated biphenyls are produced either intentionally or inadvertently.
Inadvertent generation of PCBs occurs in the manufacture of soaps and skin lotions, paper,
colored inks, poiyvinyl chloride plastics, and poiyurethanes. Intentional production for commercial
purposes began with PCBs' introduction into commerce in 1929. Before concerns were raised
about PCBs' toxicity and persistence in the early 1970's, various U.S. industries used some 1.25
billion pounds5 because of their chemical and thermal stability and their nonflammability.
Of the intentionally produced PCBs, approximately 965 million of the 1.25 billion
pounds (77%) used in the United States were installed in the dielectric fluids of transformers and
capacitors. Another 100 million pounds (8%) of PCBs were placed in the fluids of hydraulic and
heat transfer equipment, while 45 million pounds (3.6%) were used as plasticizers in carbonless
copy paper. In addition, 155 million pounds (9.2%) of PCBs were used in dispersive applications
such as plasticizers in synthetic resins and rubbers, epoxy paints, and protective coatings. PCBs
have also been used in machine-tool cutting oils, in high-vacuum oils, mining machinery oils, and
the oils used in the compressors of natural gas pipelines; in specialized lubricants and gasket
sealers; in printing inks, textile dyes, and synthetic adhesives; in sealers for waterproofing
compounds and putty; and as extenders in investment casting waxes and pesticides. Most of the
latter applications dispersed PCBs to the environment years ago, and are no longer controllable by
regulation. The "closed" uses such as electrical fluids and coolants are responsible for the greatest
volumes of PCB wastes that are subject to the TSCA disposal regulations.6
Over 388 million pounds7 of PCB-contaminated material are estimated to be in
landfills presently, placed in landfills and dumps prior to the enactment of the regulations
controlling PCB disposal. Each 10-year additional deposit of fluff would add only 0.9% to the
present amount. Exhibit 1-1 presents perspectives on PCBs.
5Donakl McKay, Comments and Studies on the Use of PotycUorinaied Biphenyls in Response to an Order of the United States Court of
Appeals for the District of Columbia Circuit (Washington, DO The Utility Solid Waste Activities Group, The Edison Electric
Institute; and the National Rural Electric Cooperative Association, 1982).
6Federat Register, (September 26,1988), VoL S3, No. 186: 37438.
7Donald McKay, Comments and Studies.
1-3
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Exhibit 1-1. Perspectives on the PCB Problem
There are currently estimated to be 1.73,0007 tons of PCBs in landfills from
all sources.
Annually, 3 million tons of fluff are sent to landfills.
Assuming PCB concentrations in fluff of 50 ppm, 150 tons of PCBs
associated with fluff are disposed of annually.
The PCBs from fluff contribute to an annual increase in PCBs in landfills of
0.09%, or a 0.9% increase over a decade.
L5 Pilot Study Objectives
EPA's overall objectives in conducting the pilot study were to investigate reports of
contamination in fluff and determine sources, to the extent possible. The Agency wants to keep
the industry recycling materials in the most environmentally safe and economically practical
manner and in compliance with Federal laws.
The specific objectives of the pilot study were:
1. To develop field sampling, sample preparation, and laboratory analysis methods
for shredder output materials;
2. To determine ranges of PCB levels in fluff;
3. To determine the range of PCB levels in the ferrous and nonferrous metallic
output streams;
4. To determine the teachability of PCBs from fluff;
5. To examine the major physical components of fluff in order to discover possible
sources of PCBs in fluff;
6. To determine ranges of total lead and cadmium levels in fluff;
7. To measure the lead and cadmium levels in leachate from fluff;
8. To relate input materials to contaminants in fluff; and
9. To collect information to help design future studies.
7Donald McKay, Comments and Studies.
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1.6 Roadmap to Report
The rest of this report is devoted to presentation of the technical aspects of the pilot
study. Chapter 2 presents the major conclusions. Chapter 3 describes the study design. Chapter 4
discusses the field methods. Chapter 5 presents the statistical results and analysis. Chemical
analysis is presented in Chapter 6; the Quality Assurance Program and results are described in
Chapter 7. To provide cross-references for the reader, the appendices and exhibits are keyed to
the specific chapter to which they directly relate; for example, Appendices 4-A through 4-D include
material relevant to Chapter 4, Field Methods. A glossary that defines many of the technical
terms used in this report may be found at the end of this report, immediately before the
appendices.
1-5
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2. RESULTS AND CONCLUSIONS
The EPA's overall objectives in conducting the pilot study were to investigate
reports of contamination in shredder fluff and to determine, where possible, the potential sources
of contamination. Additional information was collected on the leachability of PCBs from fluff.
The Agency recognizes the valuable contribution of the recycling industry and wants to keep scrap
shredders operating in the most environmentally safe and economically practical manner possible.
Information gained through the pilot study will be used to determine the need for rulemaking
activity and to help design future studies, if they are deemed necessary.
There are limitations pertaining to the conclusions which may be drawn from the
pilot study data. One limitation concerns the restriction that was placed on the selection of
shredder sites. Practical considerations required that not all shredder sites in the United States be
considered for inclusion in the study. For the purpose of having substitute sites readily available, it
was necessary that each site included in the Pilot Program be selected from one of seven clusters
which were chosen, based on practical considerations. No more than one site per EPA region was
selected. Another limitation pertains to the sparsity of data. Some estimates are based on a very
small number of samples (details are included in Chapter 5). The EPA cautions the reader against
overgeneralizing from these data.
The results and conclusions of the pilot study are presented below for each of nine
specific objectives. All PCB measurements were calculated on a dry weight basis which is standard
EPA practice. The EPTOX and total lead and cadmium results are calculated on the sample
material as it was received. No steps were taken to bake the sample material to dry weight in
order to be consistent with the EPTOX protocols. Approximate 95% confidence intervals for
population means are presented in parentheses for each contaminant level reported.
Objective 1. To develop field sampling, sample preparation, and laboratory
analysis methods for shredder output materials.
A variety of specific methods were successfully developed for field sampling,
sample preparation and lab analysis of the three shredder output streams: fluff,
ferrous metal, and nonferrous metals. These methods are documented in the Study
Design (Chapter 3), Field Methods (Chapter 4), and Chemical Analysis (Chapter
6).
Objective 2. To determine ranges of PCBs levels in fluff.
PCBs were found in all sampled material at all pilot study sites. The average PCB
concentration across sites for all fresh fluff is 43 ppm (approximate 95% confidence
interval from 22 to 120 ppm). Fluff from the shredding of automobile had levels in
the same general range as fluff from the shredding of white goods. Fluff from
mixed-input materials had a significantly higher average PCB level (180 ppm) than
other types of fluff.
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Objective 3. To determine the range of PCBs levels in the ferrous and nonferrous
metallic output streams.
PCBs were found in both ferrous and nonferrous metallic output streams, but at
much lower levels than in the fluff. The average PCB level across all sites for the
ferrous metallic output stream was 0.20 ppm (approximate 95% confidence interval
from 0.14 to 0.30 ppm) and for the nonferrous metallic output stream was 1.0 ppm
(approximate 95% confidence interval from 0.47 to 6.8 ppm). On the average, PCB
concentrations in fresh fluff are roughly 200 times in the ferrous material and 50
times of the nonferrous material When the those relative weights and PCB levels
of the output those streams are considered together, 98% of the PCBs in the total
shredder output are associated with the fluff.
Objective 4. To determine the leachability of PCBs from fluff.
A Soxhlet extraction using hot water as the solvent was run on selected fluff
material that had been found to have high PCB concentrations. This was
considered to be a reasonable "worst case" scenario of leachability. After eight days
of hot water extraction, the amount of PCBs extracted corresponds to 0.0073% of
the PCBs present (approximate 95% confidence interval from 0.0019% to 0.028%).
The PCB concentration in the extract water was 0.0018 ppm. An 8-day room-
temperature extraction was conducted on portions of the same fluff samples using a
slurry extraction apparatus and, as might be expected, the percentage of PCBs
extracted was lower (0.0050%) than with hot water. From these analyses, it
appears that leachability of PCBs from fluff is lower than that found in most soil
matrices.
Objectives. To examine the major physical components of fluff in order to
discover possible sources of PCBs in fluff.
To determine possible sources of PCBs in fluff, the fluff was separated into major
physical components which were individually analyzed for PCBs. About half the
mass of the material in fluff consists of dirt, dust, and other fine material too small
for precise classification; this comprised one category. Other components included
metal and wire fragments, soft and hard plastic and rubber, glass, fabric, paper, and
wood. This analysis did not yield clear conclusions relating sources of PCBs in fluff
to particular categories of physical components. There were no statistically
significant differences in measured PCB levels between the categories of physical
components.
Objective 6. To determine ranges of total lead and cadmium levels in fluff.
For the majority of samples, across all types of material, total lead concentrations
fell within the range of 1,000 to 10,000 ppm, and total cadmium concentrations fell
within the range of 10 to 100 ppm. Samples of soil (collected from beneath fluff
piles) had the lowest and most variable total lead (10 to 10,000 ppm) and total
cadmium (0.10 to 100 ppm) concentrations. Mean concentrations of total lead and
cadmium in fluff are shown in the following Table 2-1. Total lead concentrations
2-2
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differ significantly among types of fluff, with fluff material that fell off the conveyor
belts (spillover) having the highest, and freshly produced fluff (auto, white goods,
mixed input) the lowest total lead concentrations.
Table 2-1. Mean concentrations of total lead and cadmium in fluff.
Analytes
Total lead
Total cadmium
Mean Concentration (ppm)
(Approximate 95%
Confidence Interval)
2800
(1800 to 4100)
47
(31 to 65)
Objective 7. To measure the lead and cadmium levels in leachate from fluff.
The results of the Extraction Procedures Toxicity test showed values ranging from
0.8 ppm to 220 ppm for lead, and 0.2 ppm to 4.0 ppm for cadmium.
Table 2-2. Mean concentrations of EPTOX lead and cadmium in leachate from fluff.
Mean Concentration (ppm)
Analytes (Approximate 95%
Confidence Interval)
EPTOX lead
EPTOX cadmium
12
(4.8 to 13)
0.84
(0.53 to 12)
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Objective 8. To relate input materials to contaminants in fluff.
The pilot study data do not clearly point to any particular input material type as the
source of PCBs, lead, or cadmium. These contaminants were found in aU sampled
materials at all sites. The highest PCB levels were found in fluff produced by
shredding mixed-input materials, which at some sites included automobiles and
appliances in addition to demolition waste and other assorted scrap.
Objective 9. To collect information to help design future studies.
The pilot study yielded a substantial amount of valuable information that is being
utilized by the EPA in its regulatory and technical support activities. If further
studies are needed, this information will be used to plan them.
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3. STUDY DESIGN
3.1 Pilot Program Design Objectives
The primary objectives of this pilot effort were:
1. To develop field sampling, sample preparation, and laboratory analysis methods
for shredder output materials;
2. To determine ranges of PCB levels in fluff;
3. To determine the range of PCB levels in the ferrous and nonferrous metallic
output streams;
4. To determine the leachability of PCBs from fluff;
5. To examine the major physical components of fluff in order to discover possible
sources of PCBs in fluff;
6. To determine ranges of total lead and cadmium levels in fluff;
7. To measure the lead and cadmium levels in leachate from fluff;
8. To relate input materials to contaminants in fluff; and
9. To collect information to help design future studies.
3.2 Site Selection
It was decided that seven shredder sites would be included in the Fluff Pilot Program
and that the sites should come from geographically diverse regions of the country. Because it
would be costly and time-consuming to relocate a sampling crew in the event that a shredder either
broke down or the operator decided not to participate in the program, it was critical that
predetermined alternate sites be conveniently located. This requirement imposed a restriction on
the selection of sites. For the purpose of having substitute sites readily available, it was necessary
that each site included in the Pilot Program be selected from one of seven geographical clusters or
groups of sites (three or more sites per group), located in separate EPA regions. From each
geographic cluster, a site was randomly selected. Four of the seven original selection sites were
visited. Three alternate sites were also visited.
3-1
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33 Composition of Input Streams by Category
• Automobile Input includes:
- Passenger cars
- Light trucks
-Vans
- Small school buses
• White Goods Input includes:1
- Refrigerators
- Washers
- Dryers
- Dishwashers
- Freezers
- Ranges
- Air conditioners
- Microwave ovens
- Hot water heaters
• Mixed Input includes a variety of scrap materials which are not predominantly
white goods or autos, but may contain components of automobile or white
goods input along with other metallic scrap such as demolition waste.
3.4 Sampling Design Procedures
Since the relationship between input material and collected fluff samples could be
positively determined only when the sampling crew was present, the sampling design gave priority
to "fresh" fluff. Depending on which categories of input material were being shredded, up to 12
samples of "fresh" fluff were collected from each site. If only autos were shredded, the study
design called for eight runs of two autos each (with one sample collected from each run) with the
shredder to be cleared between runs. If autos and one other category of input material were
processed, five runs (with one sample per run) from each of the two input types were included for
that site (10 runs with one sample each). If all three categories of input materials were processed
at a site, then 4 runs of each input type were required, resulting in a total of 12 samples. Three
options for obtaining the samples were outlined in the Project Training Manual (Appendix 4-A).
There was an awareness of the possibility of cross-contamination of input materials.
While efforts were made to ensure that all the processed input materials from one run did not
affect subsequent runs, no efforts were made to clean the shredder apparatus itself between runs.
Field teams waited for all materials from the run to exit the apparatus before sampling
commenced on the next run. While there is no specific basis for believing that some materials may
have been retained by the shredder apparatus, it must be acknowledged that retention of such
*As the result of the heightened environmental concerns and the *White Goods scare,* most shredders had posted notices that prohibited
appliances with motors attached, as well as mufflers, air bags, compressed gases, etc The white goods shredded during the pilot
generally reflected the efforts to remove the motors and capacitatois, and are in all probability not representative of the white goods
processed 5 years ago.
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materials may occur. The level of precaution taken was considered appropriate in the context of a
pilot study, and it was felt that it was more reflective of real world operations.
If stored fluff (fluff produced prior to the arrival of the sampling crew) was available,
four samples were to be obtained using the protocol in the Training Manual
Based on previous observations by EPA personnel in site familiarization visits,
provision was made for two discretionary "spillover" samples per site. These samples included fluff
materials which spilled over from the conveyor belt or other machinery and were observed to
accumulate at various points around the shredder apparatus.
Two samples of ferrous metal were to be obtained per site, as well as two samples of
nonferrous metals.
Soil grab samples were to be obtained, four per site, in accordance with the
instructions in the training manual, Le., the soil samples were taken from the areas where fluff
would accumulate.
The sample goals, as applied under field conditions were met 100% for auto fluff (36
samples obtained); 100% for stored fluff (20 of 20 possible samples obtained); 100% for mixed
input materials (12 of 12); 95% for white goods fluff (19 of 20 targeted samples, one lost due to
time constraints); 64% for spillover (9 of 14 targeted samples, the remainder lost due to time
constraints); 100% for both ferrous and nonferrous metals (14 of 14 possible samples obtained),
with 3 extra ferrous samples obtained at one site; and 100% of possible soil samples (24 of 24
possible samples obtained), with 1 extra soil sample obtained at one site.
3.5 Chemical Analysis Design
The design of the chemical analysis portion of the pilot program was intended to
expand the limited information concerning concentrations and potential sources of chemical
contaminants in fluff, soil, and other shredder output.
Laboratory procedures existing before this study for the preparation and chemical
analysis of sampled materials were judged to be deficient. For example, with PCBs, too small a
quantity of material was subjected to the analytical procedure. This resulted in a high level of
variability occurring in PCB concentrations between split samples, as reported by several state and
independent laboratories. Two procedures were used in the pilot program to reduce the variability
of the results: the size of the sample analyzed was increased, and the techniques for drawing
subsamples from the initial large sample were improved. (This produced more representative
subsamples. The technique is described in Appendix 7-A.)
To address the above concerns, new methods and procedures were developed. Two
extraction techniques, a tumbler extraction using a TCLP agitation apparatus, and a Soxhlet
extraction using large-volume (500 cc) extractors were designed. Results are discussed in Section
6.2, Chemical Analysis. Methods and Deviations are discussed in Section 7.5.1. Standard
Operating Procedures (SOP's) were developed to ensure that the same procedures were followed
throughout the study and are listed in Sections 63 and 15.
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3.6 Statistical Analysis Design
When designing a study such as the Fluff Pilot Program, the number of samples
selected and the number of sites visited are generally determined by two factors: (1) the level of
precision required for resulting estimates and (2) knowledge about the general variability in
contaminant levels between samples within sites and between sites. (There are clearly other
sources of variability that are expected to be important, but these are fundamental) For the
present study, the coefficient of variation is an appropriate way to represent the variability for both
the average PCB concentration at a site and across sites, and is used to delineate the relationship
between level of precision and sample size requirements.
The derivation of the appropriate number of sites requires knowledge of the
coefficient of variation for the average PCB concentration at a site. Likewise, the derivation of the
appropriate number of samples per site requires knowledge of the coefficient of variation (cv) for
measurements taken at a given site. Information available from previous studies is sparse:
however, it does provides some limited insight into the distribution of PCB concentrations in fluff.
Based on these limited data, Westat made the following preliminary estimates of the components
of variance: cv = 0.9 for sites and 0.8 for samples taken at the same site. Based on these estimates,
Westat determined that four samples collected at each of seven sites would result in a coefficient
of variation for the average across sites of less than 0.5 (i.e., less than 50%).
A minimum of 11 samples of fluff were collected from each of 7 sites. These samples
included at least four fluff samples from shredding autos and four from white goods and mixed
input materials where available. These sample sizes meet the minimum sizes derived above which
are based on reasonable precision requirements.
While more data will typically lead to more precise estimates, budgetary
considerations restricted the number of sites that could be visited and the number of samples that
could be collected from each site. The incremental cost of visiting a site, before collecting a single
sample, is substantial For each site, all samples were collected in a single (long) day. The
addition of many more samples per site would have pushed the data collection effort into a second
day, resulting in additional costs and more disruption to the facility.
The number of samples collected for metals and soil was small because of the
relatively lower priority assigned to the analyses of these materials.
3.7 Data Coding, Processing, and Storage
The data collected in the field were recorded on worksheets (shown in the Training
Manual) that were mailed to Westat. The laboratory results were recorded in hard-copy form at
MRI and mailed to Westat. All data transcription, keying, and verification were done at Westat.
Hardcopy data were transcribed into data entry forms and 100% sight-verified.
The sample buckets delivered to MRI, and the worksheets completed in the field,
were linked through a barcode label affixed to both items in the field. A unique site and sample
number can be associated with each barcode. To maintain confidentiality, new numbers were
assigned to the data.
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3.8 Design Definitions
The definitions of the following terms as used in the Fluff Pilot Program, are as
follows:
Site - a shredder facility.
Sample - a bucket (or jar in the case of soil) of material collected. From 22 to
27 samples were collected from each site.
Subsample - material randomly selected from a sample. Each sample bucket
should yield about 8-10 subsamples of 450-500 grams each. Multiple
subsamples were analyzed in the laboratory for most samples.
Split - material randomly selected from a subsample that has been sized, or
pulverized, and thoroughly mixed. Due to the relatively uniform consistency of
sized material, we expect little variation from split to split. The term "split" is
thus appropriate in that it suggests a precise copy. The true variability from
split to split will be assessed in this study.
Injection - a small amount of liquid that is analyzed. Typically an injection is
selected from a larger quantity of liquid extract that results from liquid
extraction, acid digestion, etc. Since a liquid can be mixed to a relatively
uniform consistency, we expect little variation from injection to injection.
Analyte - the substance being analyzed for, e.g., PCB Arodor 1242, lead, and so
forth.
Duplicate is a measurement term, and refers to an additional measurement
from the same homogeneous base. In this context, it is applied only to multiple
chemical analysis measurements from the homogeneous extract, ie., duplicate
measurements of the same extract.
Replicate refers to different physical subsamples, taken from the same sample,
or splits further down the hierarchy of physical separation, i.e., replicate splits
from a subsample.
There can be multiple injections per split, multiple splits per subsample, etc. In
statistical terms, injections are "nested" within splits which are "nested" within subsamples, and so
on.
3.9 Final Analysis Design
The final analysis design was developed immediately after the sample collection
phase, and was based on review of the samples obtained and program priority funding constraints.
Table 3-1 presents the number of samples analyzed for PCBs, by site and sample type. Not all of
the collected samples were analyzed.
3-5
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Table .VI. Number of samples analyzed for PCBs, by site and sample type
Material
Input
Site: 1234567 Total
f?r«»ah CM i iff Anfn
rresn nun /\uio
Fresh Fluff Mixed Input
Fresh Fluff White
Stored Fluff
Spillover
Ferrous
Nonferrous
Soil
Total
0
3
2
0
1
0
2
12
3
3
2
1
2
2
2
19
3
3
0
1
0
0
0
11
0
0
2
1
1
1
2
11
0
3
2
1
1
0
0
11
3
3
0
0
2
2
0
14
0
0
2
1
1
0
2
10
oft
4O
9
15
10
5
8
5
8
88
More samples were collected than we expected to analyze. Collecting the extra
samples added little to the total cost of sampling and provided material which could be used for
additional analyses and studies, if EPA deemed them necessary. Some of this sample material is
presently being used for additional analysis. In addition to the above samples, 3 samples of rubber
were collected The rubber samples are not addressed further in this report. A total of 168
containers of materials was collected, including blanks.
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4. FIELD METHODS
4.1 Planning and Preparations
Preparations for the field activities began in November, 1988 with logistics planning
and development of a training manual for the training workshop. Battelle Columbus Laboratories,
Midwest Research Institute (MRI), and Westat provided staff for the workshop and field activities
MRI provided and prepared the materials for collecting and transporting the samples to the lab for
chemical analysis.
4.1.1 Training
Training sessions were held at Westat in RocicvUle, Maryland, on December 1 and 2,
1988. These sessions provided guidance to the personnel who conducted the site visits, gathered
information about shredder operation from the operating personnel, completed the worksheets,
and collected the samples of fluff, metal, and soil. Training emphasized the importance of a high
degree of consistency and standardization in sampling activities. Westat developed a training
manual with assistance from EPA and MRI. A copy is included as Appendix 4-A.
The training sessions were attended by the three team leaders (two from Westat and
one from Battelle), and four of the five team members from MRI. The industry association, the
Institute for Scrap Recycling Industries (ISRI), which cooperated in the preparation for the pilot
study, sent two observers and one shredder operator. The site operator made a presentation on
shredder operations and the need for safety precautions.
The Quality Assurance Project Plan was developed in parallel with the workshop and
was completed on December 7,1988.
4.12 Preparation of Sampling Equipment
MRI purchased sufficient quantities of sampling equipment for sample collection and
transportation at seven sites. The types and quantities of materials and equipment required for
each site are listed in Table 7-2.
MRI cleaned all surfaces of the sampling equipment and sample containers that could
come in contact with sampled materials. The cleaning procedure consisted of soaking equipment
in dilute (20%) nitric acid and rinsing with deionized water, followed by separate acetone and
hexane rinses. After the last hexane rinse evaporated, the sampling containers were sealed with
lids and placed inside plastic bags. The same procedure was generally followed for the sampling
tools.
Several containers and tools were randomly selected and screened for PCBs, lead, and
cadmium to verify that laboratory contamination had not occurred during cleaning. One set of
containers and tools was rinsed with hexane, and another set with Milli-Q water. The analysis
results of water and hexane rinses were below the LOQ for each analytc (see Table 7-3).
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4.2 Sampling
The MRI staff assigned to the sampling activities worked under the guidance of a
Westat or Battelle team leader. The staff responsibilities arid activities were to:
• Arrange the transport of sampling equipment and containers to the site.
• Collect samples at times and locations designated by the team leader, and label
and document collection of each sample. (Sampling procedures are found in
Appendix 7-A.)
• Arrange for and ship samples.
42.1 Documentation, Transportation, and Storage
The collection activities performed were documented in field notebooks. Each
notebook contained inventory logs for the recording of sample identification and all other required
information.
The material collected was shipped by a carrier providing traceable service from the
shipping point to the final destination.
Samples were stored at MRI at room temperature in the original sampling containers.
43 Site Selection
For the first step of site selection, seven groups or geographical clusters of shredders
were chosen from the membership list furnished by ISRI. These seven clusters of sites were
selected to provide a broad geographical representation of shredders from the entire continental
United States. Each geographical group was composed of three or more shredder operations.
From each group, a primary site and two alternate sites were randomly chosen. This procedure
resulted in the selection of seven primary sites, one site from each of seven geographic regions of
the country.
Immediately following the training sessions, scheduling of site visits by the three
teams was arranged. In addition to scheduling dates, the arrangements for the site visits included
confidentiality and Lability agreements. (See Appendix 4-B.) Scheduling was somewhat time-
consuming because of the need to coordinate information among the sites, the contractors, and
EPA.
Two sites declined to participate in the program; one site was unable to participate.
In each of these three cases, an alternate site replaced the primary selection. The cooperation
from sites was undoubtedly enhanced by two letters on confidentiality, one from Martin P. Halper
of EPA, November 30, 1988 and the other from Herschel Cutler, Executive Director of ISRI,
December 6, 1988. (See Appendix 4-C.)
Site visits were conducted between December 9 and December 20, 1988. In
accordance with the confidentiality pledges and written agreements, site locations and results are
being treated with anonymity. Visiting teams consisted of a team leader from Westat or Battelle
4-2
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and two members from MRI. In all cases, the team was accompanied by an observer from
VERSAR, Inc., under contract to ISRI.
4.4 Shredder Equipment and Operations at Various Sites
Some components of the shredder apparatus are common to every operation, while
other components vary from site to site. Virtually every shredder includes a hammermill which
tears/pulverizes/shreds the scrap input into fist-size pieces of material This piece of equipment is
approximately 80 to 100 inches wide, 10 to 15 feet high, and 20 feet long. All shredders use
magnetic separators to remove the ferrous metallic output from the remainder of the output.
These separators usually consist of top and bottom conveyor belts with a magnetized end pulley for
the top belt. The magnetized pulley lifts the ferrous materials away from the remaining
nonmagnetic material which is conveyed to the next separation stage.
Greater variation in shredder design is associated with separation of the nonferrous
metallic products from the fluff. One or more cyclone air separators are frequently used to
segregate the lighter fluff from the denser nonferrous (and nonmagnetic) residue. At other
shredder operations, water separation devices and/or shaker machines are used to separate the
nonferrous metals from the fluff. The industry pattern seems to be to produce standard shredder
components and then construct an apparatus to suit local conditions and requirements.
Regardless of their exact configuration, almost all shredders produce three end products: ferrous
metal, nonferrous metal, and fluff. Market factors and fluff disposal options often dictate local
requirements.
Variations in shredder operations include:
• Some shredders manually separate aluminum from the fluff/nonferrous stream,
with other nonferrous scrap materials ignored and discarded with the fluff. At
other sites, the aluminum, copper, and any other heavy materials form a
combined product from the cyclone, with no manual intervention.
• Some shredders differentiate the nonferrous stream into small (1/2") pieces
and larger pieces, with separate product marketing for each. At some sites,
there is one combined stream containing all sizes.
• The fluff may be segregated by size, with one disposal path for the smaller size
and another disposal path for the larger fluff. At other sites, only one fluff
stream exists.
Generally, on-site storage of fluff is not practiced to any large degree. Rather, the
pattern is to get rid of the material as quickly as possible. Figure 4-1 illustrates a shredder system,
and Figure 4-2 is a schematic illustration of the shredding process.
4.4.1 Sampling Task
The sampling task was to obtain fluff samples from three categories of input materials
processed in shredders: auto, white goods, and "mixed input." "Mixed input," which was initially
called "other," was an exclusionary category - it included any materials that are not autos and not
4-3
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ferrous conveyor
ferrous metal
magnetic separation system air ?yo1ont
scrubber
air cyclone 2
waste stockpile conveyor
closed loop air system
non-ferrous metal
fluff
infeed conveyor
Figure 4-1. Illustrated shredder system
-------
air cyclone
input:
metal scrap
shredded material
Figure 4-2. Schematic illustration of the shredding process
4-5
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white goods, which are fed into a shredder. Later in the project, it became evident that "mixed"
was a more appropriate term than "other" because auto and appliance components were included
in the materials. White goods can also be subdivided to motorized or nonmotorized appliances.
Motorized appliances are believed to be a possible source of PCBs in fluff.
Teams were also to obtain samples of existing or stored fluff, ferrous and nonferrous
metals, and "spillover". Spillover was a fine material observed to accumulate under the various
conveyors. Soil sample collection was also part of the sampling task.
Initially, three options for sampling fresh fluff were prescribed in Chapter 7 of the
Fluff Pilot Program Training Manual. The options were:
1. Collect fluff directly off a conveyor belt, out of an air cyclone, or from some
other piece of apparatus.
2. Collect fluff after it piles up.
3. Use a front end loader to collect all fluff from a single run.
Option 1 was not utilized, primarily due to safety concerns expressed by the site
operators at the initial site visit orientation meetings. Option 2 was used at three sites. At one
site, four sample buckets of auto fluff were collected from one run of seven automobiles. The
protocol required a minimum of two autos; seven were shredded. At another Option 2 site, which
was experiencing equipment breakdowns, two long runs (over 30 minutes of auto shredding) were
sampled. Eight buckets of fresh auto fluff were obtained, with four sample buckets collected in
each run. At a third Option 2 site, nine autos were shredded and four sample buckets of auto fluff
were collected.
After gaining some experience on site, discussions were held among the team leaders
and EPA/OTS personnel These discussions resulted in the decision to standardize on Option 3,
using methods described next, assuming that a bucket loader would be available. Fortunately, all
remaining sites had operational bucket loaders, and Option 3 was used at the remaining four sites.
4.4.2 Auto Fluff
As the teams gained experience, they learned that one safe, quick, and satisfactory
method of collecting fluff materials was to perform the following protocol at each shredder:
1. Interrupt the feedstock stream until the shredder cleared itself.
2. Have the site operator run two autos through the shredder. Generally, a senior
facility person who was made available to the teams communicated with the
shredder operator in the shredder tower by using a two-way radio.
3. Catch all the fluff from the two autos in a front-end loader bucket. Usually, the
loader cab was equipped with a steel roof to protect the operator; the presence
of others near the shredder was not required. This protocol was safer than
requiring persons to be at the end of the conveyor operation to catch the fluff
product. Pieces of shredded material were sometimes propelled from the
shredder and escaped the various flaps or guards, thus creating a potential
4-6
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hazard to the fluff collector. One site built large screens to protect persons
working near the "line of fire" of the shredder hammermilL
4. If there was an area or a roadway that could be made temporarily available to
the survey team, the materials were deposited there.
5. The deposit was leveled by dragging the loader over it, with the bucket
positioned a few inches above the ground.
6. The shredded product of two autos was spread to produce a rectangular pile
with rounded corners which, if it were perfectly square, would have been about
9' x 9' x 1', 81 cubic feet, or 3 cubic yards. Four pieces of string were laid across
the large pile, two pairs of two each, and adjusted until the pile was divided into
nine approximately equal sectors. The 5-gallon sampling bucket was then filled
with successive portions from the centers of the nine sectors by team members
wearing gloves and using a small plastic pail.
7. As soon as the pile was leveled, the loader was returned to the fluff conveyor,
the next two autos were fed into the mouth of the shredder, and the process
repeated.
8. The overlap of steps 2 through 7 allowed the operation to proceed at a brisk,
businesslike, but still safe fashion.
One site was unique in that a mechanical shaker separated the fluff stream into two
streams of different-sized materials. The larger pieces were predominantly greater than 1 inch in
diameter, and smaller pieces were mostly less than 1 inch in diameter. The larger pieces were
transported by conveyor belt and dumped on the ground in the conventional manner, forming a
cone. The cone-shaped pile sampling protocol was followed for this material. The smaller-size
pieces were transported by an open auger into a bin for chemical treatment. (An auger is a large
rotating screw partially enclosed, used for transporting loose granular materials such as grain, coal,
etc., or feeding the cutting blade of a meat grinder.) Due to the serious safety concerns associated
with attempting to extract materials from an open auger while it was running, smaller-sized
materials which had fallen to the ground were sampled. This material was demonstrated to be
comparable by the site engineer, who stopped the shredder briefly and obtained a small
comparison sample from inside the auger.
4.43 White Goods
The protocol for sampling "white goods" was as follows:
1. Preferably when the shredder was not operating, the teams examined the
materials waiting to be processed to find an identifiable group of goods. The
team leader asked the shredder operator, through the senior person assigned as
the team's liaison, to run these selected goods through the shredder as a set.
2. The shredder was run until it was cleared of materials, and the order given by
radio to process the selected materials.
4-7
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3. A "spread-in-place" approach (spreading tarps out on a small area near the
conveyor) was used because of the small amount of fluff material produced by
this type and quantity of goods (five hot water heaters, five ranges, etc.). The
light nature of the goods also lessened the danger of large flying objects. When
the material from the run was dumped, it was quartered, and samples were
taken from the four sectors.
4. The markedly different nature of the various processed materials (size, gauge,
or thickness) and their composition required an adjustment in the air flow to
the cyclones since, otherwise, the nonferrous materials would have too much
fluff or vice versa.
5. The parallel operations of shredding and sampling that were possible with
automobiles were not possible with "the spread in place" approach, but the time
saved in not having to transport the material from the conveyor to a distant
area partially compensated for this. The effort of dumping the fluff and
repositioning the tarps required two people.
4.4.4 Mixed Goods
All seven sites offered the opportunity to collect auto fluff, and most had white goods
set aside. However, the opportunities to sample "mixed" materials were more limited. At some
sites, only autos and trucks are run.
Because "mixed" stocks were more difficult to divide into predetermined discrete units
than were autos (two autos = one run) or appliances (five appliances = one run), it was far more
difficult to positively identify specific materials that were processed. Precise identification of
processed materials was a low priority of the program. It would have been especially time-
consuming and difficult to identify the components of "mixed" stock. For these reasons, the actual
constituents comprising this input category were not recorded. In most cases, the shredded output
from "mixed" stock was relatively light, reflecting the construction of the items in this category.
4.4.5 Spillover Sampling
Earlier visits by EPA personnel to other shredder sites found cone-shaped materials
accumulating in the vicinity of the conveyor belts. These materials were named "spillover."
Spillover typically accumulates underneath the section of the belt that vibrates the most. Spillover
sampling used the method of sampling a pile of shredded material, as defined in the training
manual, Option 2. Where there were similar, unmodified shredder plants with similar long
conveyors, the spillover appeared to be consistent in size, volume, and relative locations. Because
of this consistency, at one site the team cleared a contiguous group of piles, started fresh with two
tarps, and obtained a sample that was related by weight and volume to a quantity of processed
material and the total shredded product.
4-8
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4.4.6 Ferrous Metals Sampling
For safety reasons, ferrous sampling was accomplished when the shredder was either
not running at all or when there was a clear break between runs. Chunks of ferrous metal were
selected from the pile of iron and steel product in accordance with the protocol. In a number of
instances, it was possible to collect ferrous product, nonferrous product, and fluff from the same
specific input material. When this was accomplished, direct comparison of contaminant levels in
the three types of output by processing run was possible.
4.4.7 Nonferrous Metals Sampling
Nonferrous metals sampling was readily accomplished in accordance with the
protocol The nonferrous conveyors were usually located away from the path of hazardous
materials ejected from the hammermill. Occasionally, nonferrous metals are separated into large
and small components.
4.4.8 Stored Fluff (Materials Stored Over 8 Hours)
Stored fluff was obtained at five sites. Shredder sites are often very crowded. For
example, at one site the stored fluff pile was surrounded on three sides by piles of scrap material,
so one cut, rather than the preferred five cuts specified by the protocol, was made with the front-
end loader. In most cases, the team could differentiate materials on the bottom of the pile from
those on the top.
4.4.9 Soil
"Soil" samples of the underlying material were obtained from shredder facilities at
most site locations. Ordinary soil (such as sandy loam) was not found because most of these sites
were located on fill The teams were able to differentiate between the fluff layer and the
underlying materials, which ranged from 100% clay, to 50-50 sand and pebbles, to thumb-sized
rock. The teams established the line of sampling from the fluff pile center outward without major
difficulty, thus strictly following the sampling protocol.
Questionnaire
Questionnaires were administered and used as background information only.
4-9
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5. SUMMARY OF THE DATA-STATISTICAL ANALYSIS
5.1 Introduction
Overview of Chapter 5
Chapter 5 provides the results of the statistical analysis of the contaminants found in
the sampled materials. The analyses are presented separately for PCBs, lead, and cadmium, and
by the various sample types: autos, ferrous, soil, and so on. Appendix 5-A lists total
concentrations per sample of PCBs, lead, and cadmium by site and sample type. The chapter
provides two types of summary for each data subset:
• A description of the concentration measurements in the sample buckets
collected in the field, presented in tables and boxplots
• Conclusions which can be drawn from the data, usually presented as confidence
intervals.
Figure 5-1 illustrates the use of boxplots. For each subset of data, the boxplot uses the
central box to show the range of the central 50% of the measurements. The "whiskers" on each
end of the box extend to the maximum and minimum measurement.
Figure 5-2 illustrates the display of 95% confidence intervals for the mean. The
confidence interval is shown as a vertical line with a bar at both ends. The line covers the range of
concentrations within which the mean concentration is likely to lie. The 95% confidence interval
will include the true mean in roughly 95% of all cases. In tables and text, confidence intervals are
shown in parentheses.
Hypothesis tests are used to compare different categories of responses. Differences
which are significant at the 5% level are called "statistically significant." In many cases, the exact
probability level is provided in parentheses. For example, (p=.03) means that the differences are
significant at the 3% level
Data were reported by the laboratories in several units of measure. All of these
measures were converted to parts per million for the analysis and presentation of results.
Concentrations in water solutions, such as the EPTOX extract, are reported as milligrams per liter,
which is essentially identical to parts per million.
The data values are often positively skewed, Le., there are many low concentration
measurements and a few very high concentrations. This is illustrated in Figure 5-3 using PCB
concentrations. Because many statistical procedures are based on the assumption that the data
have a normal distribution, the natural logarithm is often used to transform the data for analysis.
The results of this transformation for the PCB measurements are shown in Figure 5-4.
Many of the plots used to present the data and the results use a log scale, compressing
the larger concentrations in order to get all the data on the plots in a way which allows easy
comparison of low and high concentrations. When the analysis is based on log-transformed data,
the results are presented in the original untransformed units, but often with a log scale. Thus the
scales for all data plots are labeled in the original untransformed concentration units.
5-1
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V
Measurement
and units
(ppm)
(May use log
or original
scale)
100.00 ^
.. Maximum data value
10.00 ..
1.00 ..
0.10
The box covers the
center 50% of the
data.
T
Minimum data value
First Second Third Symmetric Skewed
Category Category Category Data Data
(n=28) (n=12) (n=15) Relative to the vertical axis
Number of samples on which
the boxplot is based
Median
mean —Boxplot
Figure 5-1. Boxplot example
-------
1 -^
0.1 -.
Description of
plotted values
0.01 -.
0.001 -.
0.0001
Either the original or log scale may be used.
The data will often be outside the
limits of the confidence interval.
The confidence interval will cover
the "true" mean 95% of the time.
Data and
Confidence
Interval
Confidence
Interval
Without Data
A Data
A Mean of Data — 95% confidence
interval
Figure 5-2. Confidence interval example
5-3
-------
35
30 -
25 -
Number of Fluff 20
samples with
concentrations
within the
indicated ranges 15
10 -
5 -
0
1 I ' I
0 100 200 300 400 500 6(K) 700 800 900 1000
PCB Concentration (ppm)
Figure 5-3. Histogram of PCB concentration in fresh fluff using no transformation
-------
12 n
10 1
8 -1
Number of Fluff
samples with
concentrations 6
within the
indicated ranges
4 -|
2 A
0
O.I
10
PCB Concentration (ppm)
100
10(K)
Figure 5-4. Histogram of PCB concentration in fresh fluff using log transformation
-------
Limitations of Data
The data collected in the Fluff Pilot Program possess some important limitations.
• The shredder sites which were chosen to participate in the study were not a
random sample of the entire population of shredder operations (about 200
sites). The reason for this was that the sample was selected for pilot study
purposes and several other considerations, Le., desire for geographic diversity,
crew time and cost, unknown extent of cooperation expected, etc, were of
greater importance in the pilot. A map was drawn with shredder locations
plotted and seven clusters of shredder facilities, in separate geographic regions
and separate EPA regions, were identified. Two EPA regions did not have high
density clusters, and two EPA regions were combined into one large cluster.
Within each of the seven chosen clusters, a random selection of shredder
facilities was made. The requirement to form clusters was based on the fact
that it would be costly and time-consuming to relocate a sampling crew in the
event that a shredder either broke down or the operator decided not to
participate in the program. It was critical that alternate sites be conveniently
located. Site replacement was necessary for three sites. This sampling design
ensured that the seven study sites possesses geographic diversity, but clearly led
to the exclusion of more isolated or rurally located shredder operations.
Whether or not such exclusions may have biased the results is unknown.
• Field sampling protocols had to be developed by EPA and its contractors on
fairly short notice after limited exposure to shredder operations. Many
decisions concerning how and when to sample were necessarily made on a "best
engineering judgment" basis. Methods for the capture of sample materials were
"logically" designed to yield unbiased samples, but systematic comparison of
alternative sampling methodologies was too impractical to conduct. In
addition, because of unexpected differences in the manner in which shredder
operations were administered, it sometimes was necessary to vary the
prearranged sampling protocol. For example, the protocol called for each "run"
of shredder material to produce one sample of fluff. At two sites, it was
necessary, due to time constraints, to collect four samples of fluff from a single
run. At another site, four samples were collected from each of two runs.
• The potential for cross-contamination between samples at each shredder site
created another problem. The sampling protocols specified that the feed of
material to the shredder apparatus be stopped and all shredded material
emptied from the apparatus before sample collection commenced. This
interruption was required both for reasons of safety and to minimize cross-
contamination. Even taking this precaution, however, some shredded material
or components of that material may have been retained by the apparatus.
It would probably have been preferable to allow a much longer period of time
(with the shredder operating) between sample collections. If one sample were
collected per day, the potential for cross-contamination between samples would
have been, in all probability, substantially reduced, but sampling of one site
would have taken weeks instead of 1 day. Budget limitations precluded this
approach.
5-6
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• The relatively low number of measurements in the fluff data set is a major
limitation, especially in relation to attempts to draw specific conclusions about
contaminant levels in various categories of output material. Up to 12 samples
of fresh fluff, 4 samples of stored fluff, 2 of spillover, 2 of metallic output, and 4
soil samples were collected, if available, at each site. At only one site were all
categories of sample material obtainable, so the total number of samples
collected was much lower than the total theoretical number. Budgetary
restrictions limited the number of samples which were chemically analyzed.
Critical decisions about the number of samples to analyze from each category
were based on several factors, including existing information about shredder
operation, in general, and specific questions about the shredder industry which
EPA wanted to answer. It should be noted that, for some categories of
material, very few measurements were generated. For example, one category
of fresh fluff, "mixed input", was produced at only three of the seven sites. Since
three of the four samples collected for this category were analyzed, only nine
measurements presently represent this important category. There were 15 PCB
measurements for "white goods" fluff, and 28 for auto fluff (possibly the most
important category). Only five samples of nine collected (one from each site
where available), representing spillover fluff, were analyzed. With eight
categories of material from seven shredder sites, and three types of
contaminant evaluated with two types of extraction procedure, cost limitations
restricted the quantity of data collected.
• Finally, means and confidence intervals for those means were calculated for
most of the contaminant levels in the various categories of material The
calculation of confidence intervals, especially for small sample sizes, requires
that some theoretical assumptions be made about the underlying distribution of
the measurements. For example, the confidence interval for the mean probably
will be very different if a lognormal distribution is assumed versus, say, a
normal distribution, given the same set of measurements. Since it is very
difficult to evaluate what distribution best fits the data when so few
measurements are available, it was decided that "bootstrap" confidence
intervals (for the mean) would be used. This approach, however, may
underestimate the true confidence interval when the sample is very small, which
frequently happened in this study. Cases where "bootstrap" confidence intervals
were calculated using very small samples are noted throughout the results
section of the report. These cases are especially vulnerable to underestimation
of the actual confidence intervals.
5.1.1 Aggregating Nested Components and Components of Variance
For the first three sites visited, one or two runs of similar materials, either white
goods, autos, or mixed input, were shredded. Later, as discussed in Section 4.4.1, multiple runs of
5-7
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similar material were shredded. From the fluff produced by a run, one or more sample buckets
were obtained. The contents of each sample bucket were divided into several subsamples, and
possibly further subdivided into splits depending on which chemical analyses were to be conducted
on the material The sites, runs, samples, subsamples, splits, and subsplits are called nested.
components in the sample design. It is recognized that the differences in sampling runs at the
initial stage of the pilot and the final stage means that there is varying precision for the site level
average. After careful evaluation, it was decided that producing the most reliable sample
measurements, on a sample by sample basis, was preferable to disregarding some relevant
information in order to render aU sample measurements of equivalent precision.
When multiple measurements are taken within a run, sample bucket, and so forth, a
procedure must be selected to combine or aggregate the multiple measurements into one
measurement for that run or sample, that is used for analyzing and reporting the results. The
procedure selected is as follows:
1. Average all measurements within a split to determine the concentration in that
split;
2. Average the concentrations in all splits within a subsample to determine the
concentration in that subsample. If splits are not used, average all
measurements within a subsample to determine the concentration in that
subsample;
3. Average the concentrations in all subsamples within a sample to determine the
concentration in that sample;
4. For fresh fluff:
Average the concentrations in all samples within a run (front end loader
bucket) to determine the concentration in that run;
Average the concentrations in all runs with the same input type (autos,
white goods, or mixed input) to determine the concentration for that
input type at that site;
Use a weighted average across input types within a site to determine the
concentration for fresh fluff at that site. The weights reflect the relative
proportion of each input type at the site as recorded during the site visit;
(the weights are in Appendix 5-A) and
5. For stored and spillover fluff and soil, average the concentrations in all samples
within a site to determine the concentration in these sample types at the site.
For example, consider the problem of measuring the PCB concentration in a 5-gallon
bucket of fluff. Because it is impractical to measure the PCB concentration in the entire bucket,
each 5-gallon sample bucket was divided into approximately 10 subsamples weighing 500 grams
each. PCBs are clearly not uniformly distributed throughout fluff so that PCB concentrations vary
from subsample to subsample. The discrepancy between the actual PCB concentration in the
entire 5-gallon bucket and that in the specific 500 gram subsample selected for laboratory
extraction is called sampling error.
5-8
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Sampling error is associated with each of the following sampling steps: selecting the
sites to be visited from the list of all shredder sites, selecting the material to be run through the
shredder, selecting the sample bucket of fluff from the fluff pile, selecting the subsample from the
sample bucket, selecting a split from the subsample, and measuring the contaminant level in the
split or subsample. A components of variance analysis estimates the magnitude of the errors
contributed in each of these sampling steps. The results of the components of variance analysis
are presented in Appendix 5-B.
Based on components of variance analysis, the following general statements can be
made:
• For 95% of the samples, the measured EPTOX cadmium, total lead, and total
cadmium concentration in one sample of fluff will be within a factor of 2 of the
true concentration in the fluff run from which the sample was obtained;
• For 95% of the samples, the measured EPTOX lead concentration in one
sample of fluff will be within a factor of 3 of the true concentration in the fluff
run from which the sample was obtained; and
• For 95% of the samples, the measured PCS concentration in one sample of
fluff will be within a factor of 8 of the true concentration in the fluff run from
which the sample was obtained.
Corrections for Recovery
In order to measure the PCB concentration in a fluff or soil sample, the PCBs must
first be extracted from the fluff or soil sample using a solvent. After extraction is completed, the
quantity of PCBs in the solvent PCB mixture is determined. Unfortunately, neither the PCB
extraction nor the measurement of the PCB concentration is achieved without error. In the
extraction step, some of the PCBs may not transfer to the solvent. Recovery is defined as the
percentage of the PCBs in the original sample which are transferred to the solvent.
The concentrations can be reported as measured or corrected for recovery.
Measurements corrected for recovery estimate the concentration in the original sample. However,
these can be adversely affected by poor estimates of recovery. Uncorrected concentrations
estimate the concentration in the solvent extract and will, on the average, be lower than the true
concentration in the sample by an amount corresponding to the recovery.
The uncorrected concentrations were used in this report because:
• The confidence intervals for the recovery all include 100%, and thus, there is no
compelling statistical support for using a recovery correction;
• The estimated recoveries are close to 100%, and thus, the corrected and
uncorrected concentrations will be similar. Therefore, the conclusions are not
expected to differ; and
• Given agreement on the recovery correction to use, corrections for recovery
can be made either before or after the analysis is complete by dividing aU
concentration values by the appropriate recovery estimates.
5-9
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5.2 Polychlorinated Biphenyls
5.2.1 Total PCBs
The number of samples analyzed for PCBs by site and sample type is shown in Table
5-1. Because of cost considerations, not all of the samples collected were analyzed for PCBs.
Table 5-1. Number of samples analyzed for PCBs by site and sample type
Material
PVaeVi fluff
rresn nun
Fresh fluff
Fresh fluff
Stored fluff
Spillover
Ferrous
Nonferrous
Soil
Total
Input Site: 1
Auto 4
Mixed Input 0
White Goods 3
2
0
1
0
2
12
2
3
3
2
1
2
2
2
19
3
3
3
0
1
0
0
0
11
4
0
0
2
1
1
1
2
11
5
0
3
2
1
1
0
0
11
6
3
3
0
0
2
2
0
14
7
0
0
2
1
1
0
2
10
Total
<5Q
Zo
9
15
10
5
8
5
8
88
More samples were collected than we expected to analyze. Collecting the extra
samples added little to the total cost of sampling and provided material which could be used for
additional analyses and studies, if EPA deemed them necessary. In addition to the above samples,
13 blanks and 3 samples of rubber were collected. The blanks and rubber samples are not
addressed further in this report. A total of 168 containers of materials was collected, including
blanks.
The PCB concentrations in the sample buckets, in parts per million, are shown in
Figure 5-5 and summarized by type of sample in Table 5-2.
5-10
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1000 T
100 -.?
PCB
Cone. 10
(ppm)
1 -.:
0.1
JL
"O
D
T
D
D
T
D
D Median
* mean
— Boxplot
Auto
Fluff
(n=28)
Mixed
Input
Fluff
(n=9)
White
Goods
Fluff
(n=15)
Stored Fluff Ferrous Non- Soil
Fluff Spillover (n=8) ferrous (n=8)
(n=10) (n=5) (n=5)
Figure 5-5. Distribution of PCB concentrations in fluff samples by type of material
-------
Table 5-2. Summary of PCB concentrations by type of sample (ppm)
Output Input Number of
Stream type samples
Fresh fluff Auto
Fresh fluff Mixed input
Fresh fluff White
Stored fluff
Spillover
Ferrous
Nonfeirous
Soil
28
9
15
10
5
8
5
8
Number
of sites
7
3
5
5
5
6
3
4
Mean*
32
180
80
68
28
0.20
1.0
44
Standard
deviation
43
170
190
43
25
0.11
1.1
38
Median
13
88
21
52
28
021
0.90
32
Minimum
1.7
12
0.67
16
4.0
0.10
0.13
0.13
Maximum
210
500
760
150
65
0.42
2.6
100
The average of the sample bucket measurements and the mean concentration aggregated across all nested components are different only
for ferrous and nonfenous material. The mean aggregated across nested components is reported. All other statistics are based on the
sample measurements.
Figure 5-5 graphically displays the important distributional characteristics of the data
by type of material Some of these aspects are the skewness of the concentrations, which is
accounted for by utilizing a logarithmic scale on the concentration (vertical) axis; the similarity of
the PCB concentrations in the auto and limited white goods samples; and an apparent difference
between the PCB concentrations in auto fluff and fluff from mixed input materials. Note that
mixed input includes a variety of scrap materials which are not predominantly white goods or
autos, or are of unknown type. The figure also shows very low concentrations in the ferrous and
nonferrous product streams, and similar PCB concentrations in stored fluff, spillover, and soils
under or near fluff piles.
Note that, because (a) different numbers of samples of each type were collected at
each site and (b) the boxplots do not change with sample size, a statistical comparison of PCB
concentrations among different types of fluff cannot be made, based on the boxplots. These
comparisons are provided by confidence intervals and hypothesis tests.
Confidence intervals for the mean concentrations across all sites are sensitive to the
calculation assumptions used. Alternate sets of assumptions can result in very different 95%
confidence intervals. The data do not provide enough information to determine which
assumptions are most reasonable. Several methods of calculating the confidence intervals and
their associated assumptions have been considered and are discussed in detail in Appendix 5-A.
5-12
-------
All procedures must assume that the sites represent a random sample of all shredder
sites. Since this assumption is not strictly true, the confidence intervals should be considered
approximate. The bootstrap procedure was selected for calculation of the confidence intervals. In
general, the bootstrap confidence intervals are too narrow, ie., the correct confidence interval will
be somewhat wider than that calculated using the bootstrap procedures. Therefore, the intervals
calculated using the bootstrap procedure are labeled "approximate 95% confidence intervals." The
bootstrap intervals tend to become shorter as the sample size decreases. In the tables presenting
the bootstrap confidence intervals, intervals that are most likely to be too narrow due to small
sample sizes are flagged with footnotes.
Figure 5-6 and Table 5-3 show approximate 95% confidence intervals for the average
PCB concentrations by type of material1 The average PCB concentration is calculated using a
weighted average of the concentrations in fluff from white goods, auto, and mixed input material at
each site. The weights are based on the reported quantity of each material shredded at the site.
A split plot analysis of variance was used to assess differences in PCB concentrations
(a) among fresh fluff from different input materials (white goods, autos, and mixed-input
material); (b) among types of fluff (fresh, spillover, and stored fluff); and (c) between fluff and soil
samples. The tests were based on the site average of the log transformed concentrations.
Differences in PCB concentrations among input materials were statistically significant
(p=.01). Other differences tested were not significant. A further analysis of the data indicated
that the differences among types of material were associated primarily with the difference between
mixed-input material and the auto and white goods. The PCB concentrations in the mixed-input
material are greater than those in white goods and autos. Unfortunately, a review of the field
records provides no useful clues as to why the difference exists.
The difference between PCB concentrations in fluff from autos and white goods was not
statistically significant, even though white goods fluff has a mean PCB concentration 2.5 times that
of auto fluff. It is not too difficult to understand how this apparently large difference fails to
achieve statistical significance if one compares the mean PCB levels from the two categories of
fluff after dropping one high measurement from the white goods category. When the highest
measurement is dropped, the mean PCB concentration for white goods (31.1 ppm) is slightly lower
than that found in autos (31.8 ppm). Note also that the fluff samples with both the highest and
lowest PCB concentrations are from white goods. Except for these two extreme samples, the PCB
measurements for auto fluff and white goods fluff are in the same general range.
As the result of the heightened environmental concerns, most shredders had
implemented policies and posted notices that prohibited appliances with motors attached, as well
as mufflers, air bags, compressed gas containers, etc. The white goods shredded during the pilot
may have reflected the efforts to remove the motors and capacitators, and may not be
representative of the white goods processed 5 years ago. This is a possible explanation of the lack
of a statistically significant difference in the PCB levels found in auto fluff and white goods fluff.
1Sce Appendix S-A for details on how the confidence intervals were calculated.
5-13
-------
1000 T-
100 --
Concentration
(ppm)
10 :-
0.1
o
Fresh Fluff Stored* Spillover* Ferrous Non-
ferrous*
Soil*
Output Stream
The confidence interval is approximate due to small numbers of samples.
The true interval is wider than shown.
Q Mean
- 95% C. I.
Figure 5-6. Mean with approximate 95% confidence interval for PCB concentration in fluff and soil by output stream
-------
Table 5-3. Mean PCB concentrations, with approximate 95% confidence intervals, in fluff and
soil, by type of sample material (confidence intervals obtained by bootstrap method)
Type of sample
material
Fresh fluff
Stored fluff
Spillover
Ferrous
Nonferrous
SoU
Mean PCB
concentration
(ppm)
43
68
28
0.20
1.0
44
Approx. 95%
confidence
interval
22 to 120
44 to 120
16 to 86 *
0.14 to 030
0.47 to 6.8 *
24 to 160 *
Number of
sites
7
5
5
6
3
4
The confidence interval is approximate, due to the small number of samples. The true 95% confidence interval is wider than shown.
Any site-to-site variation in fluff PCB concentrations may be due to consistent
concentration differences among fluff from separate sites, or to differences among the
concentrations in samples collected on separate visits at the same site, or both. Consistent
differences among sites might be associated with differences in the types of material shredded or
differences in the handling of PCB-contaminated material in the shredding process. Differences
among samples collected on separate visits might be associated with changes in procedures at the
site or changes in the sources of input material Because each site was visited only once during the
survey, changes in concentration over time cannot be assessed using the survey data. As a result,
differences over time are confounded with inter-site differences. The concentrations found in this
pilot study may not be representative of typical operations at each site. For this reason, no test of
differences among sites was performed.
For each run of input material, fresh fluff, ferrous, and nonferrous material are
produced. The relative proportion of PCBs in each output stream is assessed by comparing the
PCB concentrations in ferrous, nonferrous, and fluff samples from the same run. Paired fluff and
ferrous samples were collected from eight runs (four with auto runs, four with white goods) at five
sites. Paired fluff and nonferrous samples were collected from five runs (three with auto runs, two
with white goods) at three sites.
Figure 5-7 and Table 5-4 show the geometric mean of the ratio of PCB concentrations
in either ferrous or nonferrous material to that in fluff material from the same run, along with 95%
confidence intervals. No significant differences in the ratio were found between auto and white
goods runs.
5-15
-------
I -r
V
•—»
Os
Ratio of
PCB Concentrations
in Ferrous and
Non-ferrous Streams
lo Concentrations
in Fluff
0.1 --
0.01 --
0.(KM)I
Ferrous Non-ferrous
Outpul Stream
A Ferrous
A Ferrous geometric mean
* Non-ferrous
o Non-ferrous geometric menu
— 95% confidence interval
• - No Difference
Figure 5-7. Comparison of output streams from the same run: PCB concentrations in ferrous and nonferrous versus fluff
-------
Table 5-4. Relative PCB concentrations in ferrous and nonferrous metals streams compared with
fresh fluff from the same run
Output
stream
Ferrous metals
Nonferrous metals
Geometric mean ratio of
PCB concentrations to
those in the fluff stream
0.0048
0.019
95% confidence
interval
0.0014 to 0.017
0.0023 to 0.16
Number of
runs
8
5
The concentrations in both ferrous and nonferrous metal material are significantly
and substantially below those in fresh fluff. As a rule of thumb, the PCB concentrations in fresh
fluff are roughly 200 times those in the ferrous material and 50 times those in nonferrous material.
Assuming the materials destined for each output stream are well-mixed prior to
separation, one might expect higher concentrations in fluff to be associated with higher
concentrations in the ferrous and nonferrous output streams. Figures 5-8 and 5-9 plot the PCB
concentrations in ferrous and nonferrous material versus that in fluff from the same run. The data
show no significant relationship between PCB concentrations in different output streams for the
same run. This may be due to the very low PCB levels and low variability in PCB levels found with
all metallic samples.
Based on estimates of the relative weight of material in each output stream and the
PCB concentrations in the output materials, the proportions of total PCBs in each output stream
have been calculated and are displayed in Figure 5-10. A majority of the weight (78%) of the
output material is in the ferrous stream. However, the PCB concentrations in the ferrous and
nonferrous streams are so low that the vast majority (98%) of the PCBs are associated with the
fluff stream.
In summary, the PCB analyses indicate that:
• PCBs were found in measurable quantities in sampled material at all pilot study
sites;
• The mean PCB concentration in fresh fluff averaged across all sites is 43 ppm
(with an approximate 95% confidence interval of 22 to 120 ppm);
• Concentrations in fluff samples from mixed input material have PCB levels that
are statistically significantly higher than fluff from autos and white goods; and
• Ferrous and nonferrous materials have significantly lower concentrations of
PCBs than fluff. In addition, the vast majority of the PCBs are associated with
the fluff;
• The data are not sufficient to make conclusions about the relationship between
the items shredded and the output PCB concentrations.
5-17
-------
1 -r-
V
i—*
oo
PCB
Concentration
in Ferrous 0.1
Material
(ppin)
0.01
H 1 1 I i I I I
H 1 1 I I I I I |
10 100
PCB concentration in Fluff (ppm)
H 1 1 I I I I I |
1000
Figure 5-8. Comparison of PCBs in fluff and ferrous output streams from the same run
-------
I/I
10 -r
PCB
Concentrarion
in Non-Ferrous
Material
(ppm)
I --
O.I
H 1—I I I I I |
-\ 1—I Mill
H 1 1 I I I I I |
10 100
PCB concentration in Fluff (ppm)
1000
Figure 5-9. Comparison of PCBs in fluff and nonferrous output streams from the same run
-------
Although most of the weight of an auio is associated with the ferrous portion, the concentration of
PCBs in the non-fluff streams is so low that most of the PCBs are found in the fluff output stream.
Disposition among output
streams of shredded
automobiles by weight:
Distribution among output
streams of PCB s from
automobiles, by weight:
Ui
tb
O
Ferrous
(78%)
Non-ferrous
(4%)
Fluff
(18%)
Fluff
(98%)
Ferrous (2%)
^^Non-ferrous
(.04%)
Figure 5-10. Distribution of PCBs among output streams
-------
522 PCB Aroclors
Aroclors were commercially produced complex mixtures of PCBs, composed of a
variety of homologs and isomers. Each Aroclor has somewhat different chemical and lexicological
properties and different applications. An analysis of the specific Aroclors in fluff samples was
conducted to see if it might provide some insight into the sources of PCBs, the necessity of
regulating fluff material, and/or the regulatory options. For most samples, the PCB analysis
included an identification of three PCB Aroclors; 1242, 1254, and 1260. For this program, these
three Aroclors are assumed to be the only ones present. This section summarizes the analysis of
the PCB concentrations by Aroclor.
Due to the similarity in the laboratory instrument response for Aroclors 1254 and
1260, the individual Aroclors are very difficult to distinguish. Therefore, the sum of the
concentrations of Aroclors 1254 and 1260 (referred to here as 1254/1260) was reported along with
the identification of the dominant Aroclor.
The PCB data analyzed in this part of the study consist of three measures:
1. The total PCB concentration determined by adding the concentrations for 1242
and 1254/1260;
2. The percentage of the total PCBs associated with Aroclor 1242 (the rest is
assumed to be a mixture of 1254 and 1260); and
3. An indicator for the dominant Aroclor in the non-1242 portion, either 1254 or
1260. (For samples in which only 1242 was detected, there is no information on
the relative importance of Aroclor 1254 or 1260).
Because of the necessity to calculate the percent of Aroclor 1242 in the total, all
calculations for the Aroclor analysis were based on the original untransformed concentrations,
aggregated over nested components.
The data were looked at in many different ways; no apparent or significant differences
in the distinction between Aroclors 1254 and 1260 were found to be related to sample type, input
material, or concentration. As an example, Figure 5-11 shows the percent of Aroclor 1242 versus
total PCB concentration for all fresh fluff runs, broken down by the dominant non-1242 Aroclor.
As can be seen from the plot, the distribution of the data for Aroclor 1254 is very similar to that
for Aroclor 1260. In the subsequent analyses, the distinction between Aroclor 1254 and 1260 is
assumed to be insignificant and is ignored.
Figure 5-12 shows the percentage of the PCBs in Aroclor 1242 versus total PCB
concentration by sample type and type of input material. These data are based on the average
concentrations for each site. As can be seen in Figure 5-12 (using the solid plotting symbols), there
is an apparent increase in the percentage of Aroclor 1242 (and a corresponding decrease in
Aroclor 1254/1260) with increasing total PCB concentration in fluff material. One data point for
fresh fluff from mixed-input material is noticeably different from this apparent trend. Based on
analysis
5-21
-------
V
100% -r
90% 4-
80% 4-
70% 4-
60% 4-
Percent
of Aroclor 50%
1242
40% -f
30%
20%
10%
0%
0.1
x xx
D
D
D
D
D DCP
DD
D
a
U I i I I I I l I I
i iiiii
1 10 100
Total PCB concentration (ppm)
D
D
• 1260 More Abundant
O 1254 More Abundant
X All 1242
1000
Figure 5-11. Aroclor 1242 as a percent of total PCBs in all fresh fluff runs, by dominant non-1242 Aroclor
-------
Percent
if Aroclo
1242
111170 -
90% -
80% -
70%
60% -
50% -
40% -
30% -
•inoj.
f\riO -
10%
t\f/L
\}/o -
0
0
o
11 * H
u
O
*
(1 "* A
• 0 •
•« **
A^ m
A *
B PI
111
A •
1
-
I 1 10 100 HUM)
... ., ....
• Auto
Q Other
• While Goods
• Stored
A Spillover
A Ferrous
LI Non-ferrous
o Soil
Total PCB Concentration (ppiu)
Figure 5-12. PCB Aroclor 1242 as a percent of the total PCB concentration, by sample type and input material type
-------
of covariance, the trend is not significant (p=.08).2 When the one discrepant point is removed, the
slope is significantly different from zero (p = .0047). This result suggests that sources of Aroclor
1242 are primarily responsible for high PCB concentration; however, there can be notable
exceptions. The fact that Aroclor 1242 is usually the dominant Aroclor provides little specific
information about the source(s) of the PCBs.
The average percentages of Aroclor 1242 by material type are shown in Figure 5-13
and Table 5-5, with approximate 95% confidence intervals. The confidence intervals assume that
the sites have been randomly selected and that the arcsine-square-root transformed percentages
have an approximate normal distribution. Although this transformation is strictly appropriate only
for binomial percentages, simulations suggest that the distribution of the transformed data is closer
to normal and the variance is closer to constant than for the untransformed data.3
Table 5-5. Aroclor 1242 as a percent of total PCB concentration by sample type, with
approximate 95% confidence intervals
Sample type
Fresh fluff
Stored fluff
Spillover
Ferrous material
Nonferrous material
SoU
Number of
sites
7
5
4
3
3
4
Percent of total
PCBs represented
by Aroclor 1242
58
71
64
57
85
83
95% confidence
interval
(percentage)
36 to 80
58 to 83
36 to 88
51 to 64
27 to 100
60 to 99
523 Hot and Room Temperature Water Extraction of PCB
Objectives
One of the principal objectives of the pilot study was to determine the extractability of
PCBs from fluff.
2Thc model assumed a common slope and different intercepts for each category of sample and input material type. The ANCOVA
results should be considered approximate because the percentage of Axodor 1242 does not have a normal distribution; however, the
distribution is roughly symmetric
3For the nonfenous data, the upper end of the confidence interval was truncated at 100%.
5-24
-------
Ul
100%
90%
80%
70%
60% 4-
Pcrcent
ofAroclor 50%
1242
40% 4-
30%
20%
10%
0%
V
T 1
• Mean
o Data
— 95% C.I.
Fresh Fluff Stored Fluff Ferrous
(n=7) Fluff (n=5) Spillover (n=3)
(n=4)
Non- Soil (n=4)
ferrous
(n=3)
Figure 5-13. Aroclor 1242 as a percentage of total PCB concentration by sample type, with appropriate 95% confidence intervals
-------
Approach
Subsamples from seven samples with known (previously measured) PCB
concentrations were selected to determine the extractability of the PCBs using hot and room
temperature water. The subsamples subject to the hot water extraction were Soxhlet-extracted for
8 days using water at 65 degrees centigrade. The subsamples subject to room temperature
extraction were tumbled in a water solution at room temperature for 8 days, after which the water
was separated and filtered. The filtered extract was analyzed for PCBs.
The results of the extraction experiments can be summarized using either:
• The PCB concentration in the extract water;
• The ratio of the PCB concentration in the water extract to the PCB
concentration in the fluff, (called the extract-fluff concentration ratio in this
section); or
• The percentage of the PCBs in the fluff which were extracted in the water.
All three of these summary measures are presented below. Note that if the PCB
concentration in the extract is in equilibrium with the PCBs in the fluff, the PCB concentration in
the extract and the extract-fluff concentration ratio will be roughly constant independent of the
quantity of water used in the extraction procedure. However, the percentage of PCBs extracted
will depend on the quantity of water used. On the other hand, if the quantity of leachable PCBs is
fixed and small enough that the extract water solution is not saturated, the percentage of PCBs
extracted will remain roughly constant while the PCB concentration in the extract and the extract-
fluff concentration ratio will depend on the volume of extraction water used. Note also that the
quantity of PCBs extracted using the tumbler (room temperature water) extraction is limited by
the solubility of PCBs in water, however this limitation does not apply to the soxhlet (hot water)
extraction.
The samples chosen for analysis included three samples with fluff from autos, three
with fluff from white goods, and one sample with fluff from mixed input material The average
concentration of PCBs in these samples was greater than for typical samples collected in the pilot
study. Because the samples were not randomly selected and because values based on the limit of
detection were used in the calculations, the confidence intervals are at best approximate. These
confidence intervals indicate the precision with which the parameter can be estimated from the
data if the parameter is assumed to be constant across all samples, which in turn depend on the
factors which are believed to affect the extraction process.
Hot Water Extraction Results
PCB measurements in four samples were below the detection limit, providing only
three reliable measurements for calculating the PCB extractability. Following the general analysis
procedures discussed with EPA, the concentration in the extracts were assumed to be equal to the
detection limit when the measured response was below the detection limit. An examination of the
data suggested that using the detection limit in these cases is not inconsistent with the other
measurements. If any error is introduced by this procedures, it will be to overestimate the quantity
of PCB extracted and perhaps underestimate the variability.
5-26
-------
Figure 5-14 shows a plot of the PCB concentration in the hot water extract versus the
native concentration. Also shown in this figure is the solubility of PCB Aroclors 1242 (found in
two samples) and 1254 (found in one sample). In the water extract with the highest PCB
concentration, only Aroclor 1242 was identified, and then at levels below the solubility of Aroclor
1242. Concentrations in all other water extracts were also below the solubility level
On the assumption that the percentage of PCBs extracted is constant, the geometric
mean percentage of PCBs extracted using hot water is shown in Figure 5-15 with an approximate
95% confidence interval. The extract PCB concentrations are plotted in Figure 5-16, with
approximate 95% confidence intervals based on the assumption that the extract concentrations are
constant.
Table 5-6 summarizes the PCB concentration in the water extract, the extract-fluff
concentration ratio, and the percentage of the PCBs extracted for both the hot water and room
temperature water extractions.
Table 5-6. Extractability of PCBs from fluff using hot and room temperature water
(approximate 95% confidence intervals shown in parentheses)
Extraction using
Hexane/Acetone
(Tumbler
extraction)
Hot Water
(65°, Soxhlet,
8 days)
Room Temperature
(Tumbler, 8 days,
filtered)
Number of Samples
(4 results based on
the detection limit)
(1 result based on
the detection limit)
Geometric mean PCB
concentration (ppm)
Geometric mean extract-
fluff concentration ratio
210
(85 to 520)
.0018
(0.00057 to 0.0058)
0.0000087
(.0000030 to .000025)
0.00045
(0.00010 to 0.0020)
0.0000021
(.00000050 to .0000092)
Geometric mean
Percent PCB Extracted
0.0073
(.0019 to .028)
0.0050
(.0012 to .022)
The approximate 95% confidence intervals in parentheses apply only if the parameter being
estimated can be assumed to be constant across samples.
5-27
-------
1000 z
100
10
1 ir
PCB
Concentration 0.1
(ppm)
0.01
0.001
0.0001
0.00001
H 1—I I I I I I |
H 1 1 I I I I I |
10 100 1000
Total PCB Concentration Using Hexane Extraction (ppm)
A Hot Water
A Hot Water (LOD)
* Room Temperature Water
o Room Temperature Water (LOD)
— Hexane/ Acetone
- - Solubility of Aroclor 1242
Solubility of Aroclor 1254
- - Adsorption Coef. = 120,000
— Adsorption Coef. = 460,000
Figure 5-14. Extraction of PCBs from Huff using hot and room temperature water versus using hexane/acetone
-------
0.1 T
0.01 ::
Percentage
ofPCBs
Extracted
0.001 --
0.0001
t
A
A
A Percentage based on measurements
A Percentage based on detection limit
Approximate 95% confidence interval
A
A
Hot Water Room Temperature Water
Extraction Method
Figure 5-15. Percentage of PCBs extracted from fluff using hot and room temperature water
-------
0.1 T
0.01 -
PCB
Concentration 0.001
(ppm)
0.0001 ::
0.00001
A
A
4
i
....
Hot Water Room Temperature
Water
Extraction Method
A Measurements
A Detection limit
Approximate 95% confidence interval
Figure 5-16. PCB concentration in the water extract after hot and room temperature extraction
-------
In another study4 comparing the water extraction of PCBs from soil materials which
used similar but not identical methods, the extract-fluff concentration ratio varied from roughly
0.0005 to 0.05. The ratio varied by type of soil material, however was relatively constant over the
range of concentrations tested (less than 0.5 ppm). Assuming that these results are comparable to
the present study, the teachability of PCBs from fluff is lower than for soil.
Room Temperature Water Extraction Results
The PCB measurement in one sample was below the detection limit, leaving six
reliable measurements for calculating the PCB extractability. The concentrations in the extracts
were assumed to be equal to the detection limit when the measured response was below the
detection limit. An examination of the data suggested that using the detection limit in this one case
is not inconsistent with the other measurements. If any error is introduced by this procedures, it
will be to overestimate the quantity of PCB extracted and perhaps underestimate the variability.
Figure 5-14 shows a plot of the PCB concentration in the room temperature extract
water versus the native concentration. This figure also shows the solubility of PCB Aroclors 1242
(found in six samples) and 1254 (found in one sample). On the assumption that the percentage of
PCBs extracted is constant, the geometric mean extraction percentage using hot water is shown in
Figure 5-15 with an approximate 95% confidence interval. The extract PCB concentrations are
plotted in Figure 5-16, with approximate 95% confidence intervals based on the assumption that
the extract concentrations are constant.
Table 5-6 summarizes the PCB concentration in the water extract, the extract-fluff
concentration ratio, and the percentage of the PCBs extracted for both the hot water and room
temperature water extractions. On the average, the PCB concentrations in the hot water extract
are slightly higher than in the room temperature extract.
52.4 Components Analysis
Objectives
The objective of component analysis was to link PCB levels to specific components to
the fluff. The first step was to identify the major physical components of fluff; then calculate
proportions (by weight and volume) for each component; and, finally, determine the PCB
concentration in each component.
^Attenuation of Water-Soluble Polychlorinated Biphenyts by Eanh Material' by R_ A. Griffin (Univeisity of Illinois) and E S. K. Chian
(Georgia Institute of Technology) Grant No. R-804683-01, Municipal Environmental Research Laboratory, Office of Research and
Development, US. Environmental Protection Agency, Cincinnati, Ohio 45268, May 1980 (EPA-600/2-80-027)
5-31
-------
Implementation
Selected samples of fluff were composited and divided into the following five
component categories:
1. Metals, wire, and glass;
2. Soft plastics, foams, soft rubber, vinyls;
3. Fabrics, paper, and wood;
4. Hard materials, hard plastics, hard rubber;
5. Fines too small to classify, dirt, dust; and
A small quantity of material that did not fit any of the above categories was not
analyzed.
The components of each composite sample were divided into two subsamples which
were sent to NEIC for analysis. After mixing the subsample well at NEIC, a 10-gram split was
removed from each subsample for chemical analysis.
The weights of the original samples, composite samples, and component samples are
documented in Table 5-7. Figure 5-17 shows graphically the weight of each component in each
composite sample as a percent of the total weight of the composite.
As can be seen from Table 5-7 and Figure 5-17, about half of the fluff is fine material
too small to classify, such as dirt and dust About half of the material is divided among the other
five categories.
Results
The data received from NEIC included the sample identifiers,5 the measured PCB
concentration (ppm) and the Aroclors identified (either 1242 or 1254/1260). Quantities for
individual Aroclors were not determined. For one sample (metals, wire, and glass from
other/mixed input material), the measurements in the two subsamples differed substantially. As a
result, a second 10-gram split from each subsample was analyzed. The two splits in one subsample
showed no substantial disagreement, and the average concentration in the two splits was reported
by NEIC. The two splits in the second subsample showed substantial disagreement (1400 and 24
ppm) and both values were reported by NEIC. The small quantities of material (10 grams) used
for the analysis and the possibility of localized concentrations of PCBs may have contributed to the
differences between spUts. For the statistical analysis, the average concentration from the two
splits (712 ppm) is used Unless noted the statistical results do not substantially change if the
concentration in either split is used in place of the average.
5The sample identifiers are the component number (1-5), composite sample letter (A-D), and the subsample letter (a or b).
5-32
-------
Table 5-7. Component data documentation
OJ
Site Sample8
Other
2/10
6/10
6/12
Auto
6/2
6/3
6/4
Auto
4/6
5/3
5/1
White Good
5/6
6/5
Composite1*
No.
A
A
A
B
B
B
C
C
C
D
D
Weight of
Fluff per
Composite
(Grams)
362
360
360
Total 1080
364
364
364
Total 1090
413
417
428
Total 1260
428
431
Total 859
Categories of Materials
Weight in Grams/Composite Sum of Parts0
12345 (Grams)
23.7 189 282 51.9 481 1030
123 179 188 98.7 440 1030
21.0 174 358 26.8 484 1060
29.0 65.6 74.3 89.0 554 812
aFrom Mr. Reinhart's plan of June 13,1989.
bMRI identification code.
CAII above weights are on a wet weight basis. The difference in weight between the sum of the individual bucket aliquots and sum of the categories is
attributed to the unclassified components making up category 6.
Categories, Single Analyst's Interpretation
1 = Metals, wires, glass.
2 = Soft plastics, foams, soft rubber, vinyls.
3 = Fabrics, paper, wood.
4 = Hard materials, hard plastics, hard rubber.
5 = Fines loo small to classify, din, dust.
-------
100% -r
60%
Percent of
Constituent 50%
by Weight
40%
Metal
Glass
Soft
Plastic
Fabric
Paper
Wood
Hard Fine
Plastic Material
O
Unclassified
•o Olher
• Autol
•* Auto2
o White
Figure 5-17. Weight of five components in four composite fluff samples as a percent of the total weight of the composite sample
-------
The differences between subsamples from the same component sample were used to
estimate the precision of the PCB measurements within the sample. The sample concentration
(the average of the two subsample measurements) was used in the statistical analysis. The
measurement error increases with the concentration, and the log transformed sample
concentrations are used in the statistical analysis.
The measurement error differed by type of component. Low variability was found
among concentrations in replicate subsamples of fine material, dirt, and dust. This might be
expected because the fine material can be easily mixed and subdivided. The concentrations in
subsamples of hard plastic and metal and glass have the largest variability, potentially reflecting
localized concentrations of PCBs and problems in dividing the material into similar subsamples
and splits due to its heterogeneity. The large difference between splits within one subsample of
metal, wire, and glass material (noted above) is consistent with the large differences between
subsamples for all metal, wire, and glass samples.
The variability of the total PCB measurements within samples, expressed as the
coefficient of variation of the measurements, is shown in Table 5-8.
Table 5-8. Precision of the measurements of PCBs in component samples, expressed as the
coefficient of variation of the concentrations in replicate subsamples
Coefficient of variation between
PCB measurements on subsamples
from the same sample
Component (95% confidence intervals)
Metals, wire, and glass 3.2 (> 1.2)3
Soft plastics, foams, soft rubber, vinyls 0.42 (025 to 1.7)
Fabrics, paper, and wood 0.37 (0.22 to 1.4)
Hard materials, hard plastics, hard rubber 13 (> 0.66)a
Fines too small to classify, dirt, dust 0.12 (0.073 to 0.36)
aThe confidence intervals are calculated assuming that the measurements have a lognonnal distribution over the entire range of the
interval. Because this assumption is unlikely to be reasonable at the very high concentrations corresponding to the upper end of the
confidence interval, no upper confidence interval is calculated.
The average concentration for each component in each composite sample is shown in
Table 5-9 and Figure 5-18. The concentrations for components in the same sample are connected
by a line in Figure 5-18 to indicate that they are all related. A 95% confidence interval for the
geometric mean measurement within one sample (calculated from two or more subsamples) is
shown for comparison. Using the confidence intervals as a guide to interpretation, the
concentration differences between samples of hard plastic and rubber can be attributed to
measurement errors. However, for fines, dirt, and dust and soft plastic, foam, and rubber, the
concentration differences among samples are too large to be attributed only to measurement
errors.
5-35
-------
1000 -r
£
100 -
PCB
Concentration 10
(ppm)
0.1
o-..
Metal
Glass
Soft Fabric Hard Fine
Plastic Paper Plastic Material
Wood
•O Other
» Autol
•A- Aulo2
« While
Meas Error
Figure 5-18. PCB concentrations in five components of four composite fluff samples
-------
Table 5-9. Total PCB concentration in five components from four composite fluff samples
PCB concentration (ppm) (average of 2 subsamples)
Component Other Autol Auto2 White Goods
Metals, wire, and glass 390 13 9.9 0.60
Soft plastics, foams, soft
rubber, vinyls 260 66 7.0 35
Fabrics, paper, and wood 63 37 12 24
Hard materials, hard plastics,
hard rubber 46 11 24 5.5
Fines too small to classify,
dirt, dust 140 43 29 62
Although the PCB concentrations in metal, wire, and glass from other/mixed input
material are significantly greater than that from white goods input material in the composite
samples analyzed, it is incorrect to conclude that this relationship holds in general for other similar
samples. Without more composite samples from each type of input material, significant
differences among input types cannot be identified from the data.
A statistical comparison of the PCBs in a selected component can be accomplished
using analysis of variance, with the component as a fixed factor and the sample as a random factor.
Because the variability is not the same in all component groups, a weighted analysis of variance is
used1. The choice of weights makes very little difference to the results. Based on the analysis of
variance, the differences in PCB concentrations among components are marginally significant, at
the 5% level.2
The differences between components can be shown by comparing the PCB
concentration in each component with the corresponding concentration in fine material, dirt, and
dust. The ratio of the PCB concentration in each component to the concentration in fine material
is shown in Table 5-10, with the associated 95% confidence interval for the ratio. Although all
components have a lower average PCB concentration than the fine material, only fabrics, paper,
wood and hard materials, hard plastics, and hard rubber have significantly lower concentrations
than in the fine material.
^e weights used are l/(var(meas)+C) where vai(meas) is the measurement error calculated from the replicates subsamples using log
transformed data. C is a constant reflecting the variance contributed by differences between samples. Values of C between .OS and 5
were used.
Probability values for the hypothesis test were between 0.05 and 0.06 (depending on the weights used).
5-37
-------
Table 5-10. Ratio of the PCS concentrations in each component to the concentration in fine
material, dirt, and dust in the same composite sample, with approximate 95%
confidence intervals
Ratio of PCB concentrations
Component (Approximate 95% confidence interval)
Metals, wire, and glass 0.14 (0.0047 to 4.5)*
Soft plastics, foams, soft rubber, vinyls 0.76 (0.16 to 35)
Fabrics, paper, and wood 0.48 (0.27 to 0.85)
Hard materials, hard plastics, hard rubber 0.22 (0.059 to 0.84)
Fines too small to classify, dirt, dust 1.0
The mean and confidence interval are sensitive to how the different concentrations in two splits are combined.
The measurements on different components within a sample will be correlated to the
extent that the same source of PCB contributes to the PCBs in different component samples. In
particular, the fine material, which makes up a large portion of the fluff and has a relatively high
PCB concentration, may distribute PCBs among all components as the input material is shredded
and mixed. As a result, the variability of PCBs among components in the unshredded items may
be greater than indicated by these data.
An analysis of the Arodors identified showed no statistically significant patterns.
The quantity of PCB associated with each fluff component can be determined by
combining the data on the concentration of PCBs and the weight of each component in the
composite samples. Figure 5-19 shows the amount of PCBs in each component in each composite
sample, expressed as a percentage of all PCBs in the five components analyzed. The majority of
the PCBs are associated with the fine material, dirt, and dust.
53 Total Lead and Cadmium
The number of samples analyzed for total lead and cadmium by site and sample type
is shown in Table 5-11. As discussed earlier, when more samples were collected than were
analyzed, the samples to be analyzed were randomly selected.
5-38
-------
100% -r
90% --
80% --
70% --
60% --
V
u>
Percent of
ofPCBsby 50%
Weight
40%
•o Other
-» Autol
Auto2
) While
Metal
Glass
Soft
Plastic
Fabric
Paper
Wood
Hard
Plastic
Fine
Material
Figure 5-19. Amount of PCBs in five components of four composite fluff samples as a percent of the total PCBs measured
-------
Table 5-11. Number of samples analyzed for total lead and cadmium by site and sample type
Output
stream
ProcK fluff
rresn iiun
Fresh fluff
Fresh fluff
Stored fluff
Spillover
Soil
Total
Input
type Site:
Auto
Mixed input
White
1
0
3
4
0
4
15
2
4
3
4
1
4
20
3
4
3
0
2
0
13
4
0
0
4
2
4
14
5
0
3
4
2
0
13
6
4
3
0
0
0
11
7
0
0
4
2
4
14
Total
Ofi
2X>
12
15
20
9
16
100
Most of the analyses conducted on the sampled materials were relatively costly.
Budget restrictions precluded the analysis of all samples, therefore a specified number of samples
were randomly selected from the various categories of samples which were collected. More
samples were collected than we expected to analyze. Collecting the extra samples added little to
the total cost of sampling, and provided material which could be used for additional analyses and
studies, should EPA decide to do so. Some of this sample material is presently being used for
additional analysis.
53.1 Total Lead
The total lead concentrations in the sample buckets, in parts per million, are shown in
Figure 5-20 and summarized by type of sample in Table 5-12.
5-40
-------
Oi
100000 T
10000 T:
1000 :r
Lead
Cone.
(ppm)
100 -r
10 -.:
1
Auto Fluff Mixed Input White Stored Fluff Fluff Soil(n=16)
(n=28) Fluff (n=12) Goods Fluff (n=20) Spillover
(n=15) (n=9)
o mean
• Median
— Boxplot
Figure 5-20. Total lead concentration in fluff and soil samples by type of material
-------
Table 5-12. Summary of total lead concentrations by type of sample (ppm)
Output Input Number of
stream type samples
Fresh fluff Auto
Fresh fluff Mixed input
Fresh fluff White
Stored fluff
Spillover
Soil
28
12
15
20
9
16
Number
of sites
7
3
5
4
5
5
Mean*
2700
4600
3100
3900
6100
2200
Standard
deviation
2200
3500
3200
3500
5600
3900
Median
2400
3600
1800
2600
4300
1100
Minimum
570
1100
1300
1300
2800
8.1
Maximum
12000
12000
14000
13000
21000
16000
The average of the sample bucket measurements and the mean concentration aggregated across all nested components are different only
for spillover. The mean aggregated across nested components is reported. All other statistics are based on the sample measurements.
As can be seen from Figure 5-20, the total lead concentrations in most samples are
within the range of 1000 to 10,000 ppm. The measurements are highly skewed; however, the use of
the log scale makes the boxplots appear roughly symmetric around the medians. Soil samples have
the lowest total lead concentrations and the most variability, ranging from 8.1 to 16,000 ppm.
A careful comparison of the lead and PCB data will indicate that the PCB
measurements are more highly skewed than the lead data. Many factors contribute to the
skewness of the data. Differences between sites may contribute to the skewness if typical
concentrations at one site are significantly higher than at the other sites. Similarly, differences
between runs of material at the same site may contribute to the skewness. For instance, the
skewness of the PCB measurements will be greater than the lead measurements if the lead
concentrations are similar in all autos but the PCB concentrations are relatively variable, with a
few autos having contaminated components. The process of selecting a fluff sample and
subsample will also affect the skewness of the data. Other factors being equal, the data are likely
to be less skewed when the contaminant is more evenly distributed throughout the fluff. The
results of the components of variance analysis (Appendix 5-A) suggest that the PCB measurements
are more highly skewed than the lead measurements because there are greater differences
between runs in PCB concentrations than in lead concentrations.
A statistical comparison of total lead concentrations among different types of fluff
cannot be made based on the boxplots. These comparisons are provided by confidence intervals
and hypothesis tests.
Figure 5-21 and Table 5-13 show approximate 95% confidence intervals for the
average total lead concentrations by type of material.3 The average total lead concentration is
calculated using a weighted average of the concentrations in fluff from white goods, auto, and
mixed-input material at each site.
^See Appendix 5-A for details on how the confidence intervals were calculated.
5-42
-------
100000 -r
10000 --
Concentration
(ppm)
1000 --
100
+
+
+
Fresh Fluff Stored Spillover41 Soil
Output Stream
* The confidence interval is approximate due to small numbers of samples.
The true interval is wider than shown.
D Mean
— 95% C. I.
Figure 5-21. Total lead concentration with 95% bootstrap confidence interval by sample type
-------
Table 5-13. Mean with approximate 95% confidence intervals for total lead concentrations
(ppm) in fluff and soil by type of sample
Type of sample
material
Fresh fluff
Stored fluff
Spillover
Soil
Mean total lead
concentration
(ppm)
2800
3900
6100
2200
Approximate 95%
confidence
interval
1800 to 4100
2200 to 7000
3200 to 11000*
870 to 9400
Number of
sites
7
5
5
4
The confidence interval is approximate, due to the small number of samples. The true 95% confidence interval is wider than shown.
A split plot analysis of variance was used to assess differences in total lead
concentrations (a) among fresh fluff from different input materials (white goods, autos, and mixed
input material); (b) among types of fluff (fresh, spillover and stored fluff); and (c) between fluff
and soil samples. The tests were based on the site average of the log transformed concentrations.
Differences between types of fluff were statistically significant (p = .03), with fresh fluff having the
lowest, and spillover having the highest total lead concentrations. In addition, soil concentrations
of total lead are significantly lower than for fluff (p = .03).
Because the differences in total lead concentrations among site visits can be attributed
either to differences among sites or to differences over time at the same site, it would be a mistake
to conclude automatically that the concentrations found in this pilot survey are representative of
typical operations at each site. For this reason, no test of differences among sites was performed.
53.2 Total Cadmium
The total cadmium concentrations in the sample buckets, in parts per million, are
shown in Figure 5-22 and summarized by type of sample in Table 5-14.
As can be seen from Figure 5-22, the total cadmium concentrations in most samples
are within the range of 10 to 100 ppm. The measurements are highly skewed. However, the use of
the log scale makes the boxplots roughly symmetric. Soil samples have the lowest total cadmium
concentrations and the most variability, ranging from 0.1 to 100 ppm. In the summary and analysis
of the data, the detection limit, 0.1, is used.
5-44
-------
fe
1000.00 or
100.00 : r
Cadmium
Cone. 10.00
(ppm)
1.00 :r
0.10
Auto Fluff Mixed White Stored
(n=28) Input Fluff Goods Fluff
(n=12) Fluff (n=20)
(n=15)
Fluff Soil (n=16)
Spillover
(n=9)
o mean
• Median
— Boxplot
Figure 5-22. Total cadmium concentrations in fluff and soil samples by type of material
-------
Table 5-14. Summary of total cadmium concentrations by type of sample (ppm)
Output Input Number of
stream type samples
Fresh fluff Auto
Fresh fluff Mixed input
Fresh fluff White
Stored fluff
Spillover
Soil
28
12
15
20
9
16
Number
of sites
7
3
5
5
5
4
Mean*
47
46
48
35
32
22
Standard
deviation
36
14
19
13
11
24
Median
40
46
47
35
33
18
Minimum
14
29
23
16
18
0.10
Maximum
200
70
87
59
59
100
The average of the sample bucket measurements and the mean concentration aggregated across all nested components are different only
for spillover. The mean aggregated across nested components is reported. All other statistics are based on the sample measurements.
A statistical comparison of total cadmium concentrations among different types of
fluff cannot be made based on the boxplots. These comparisons are provided by confidence
intervals and hypothesis tests.
Figure 5-23 and Table 5-15 show approximate 95% confidence intervals for the
average total cadmium concentrations by type of material4 The average total cadmium
concentration is calculated using a weighted average of the concentrations in fluff from white
goods, auto, and mixed input material at each site.
Table 5-15. Mean with approximate 95% confidence intervals for total cadmium concentrations
(ppm) in soil and fluff by type of sample
Mean total cadmium Approximate 95%
Type of sample concentration confidence
material (PFm) interval
Fresh fluff
Stored fluff
Spillover
Soil
The confidence
47
35
32
22
interval is approximate due to the small number of samples.
31 to 65
27 to 46
24 to 43*
11 to 67
Number of
sites
7
5
5
4
4See Appendix 5-A for details on how the confidence intervals were calculated.
5-46
-------
Ut
100 -r
Concentration
(ppm)
10
Fresh Fluff Stored Spillover* Soil
Output Stream
* The confidence interval is approximate due to small numbers of samples.
The true interval is wider than shown.
0 Mean
— 95% C. I.
Figure 5-23. Total cadmium concentration with 95% bootstrap confidence interval by sample type
-------
A split plot analysis of variance was used to assess differences in total cadmium
concentrations (a) among fresh fluff from different input materials (white goods, autos, and mixed-
input material); (b) among types of fluff (fresh, spillover, and stored fluff); and (c) between fluff
and soil samples. The tests were based on the site average of the log transformed concentrations.
Soil concentrations of total cadmium are significantly lower than for fluff (p = .001).
Because the differences in total cadmium concentrations among site visits can be
attributed to either differences among sites or differences over time at the same site, the
concentrations found in this pilot survey may not be representative of typical operations at each
site. For this reason, no test of differences among sites was performed.
5.4 EPTOX Lead and Cadmium
The number of samples analyzed for EPTOX lead and cadmium by site and sample
type is shown in Table 5-16. As discussed earlier, when more samples were collected than were
analyzed, the samples to be analyzed were randomly selected.
Table 5-16. Number of samples analyzed for EPTOX lead and cadmium by site and sample type
Material
ProcVi
rresn
Fresh
Fresh
•Huff
nun
fluff
fluff
Stored fluff
Spillover
Total
Input Site: 1
Auto 4
Mixed input 0
White 3
4
0
11
2
4
3
4
1
16
3
4
3
0
2
13
4
0
0
4
2
10
5
0
3
4
2
13
6
4
3
0
0
11
7
0
0
4
2
10
Total
->0
Zo
12
15
20
9
84
5.4.1 EPTOX Lead
The EPTOX lead concentrations in the sample buckets, in parts per million, are
shown in Figure 5-24 and summarized by type of sample in Table 5-17.
As can be seen from Figure 5-24, the EPTOX lead concentrations in most samples are
within the range of 0.1 to 10 ppm. The measurements are highly skewed. However, the use of the
log scale makes the boxplots roughly symmetric.
5-48
-------
1000 or
Lead
£ Cone.
vo (ppm)
100 •::
10 : r
1
D
I
•
D
•Q
•
n
n Median
* mean
— Boxplot
0.1
Auto Fluff Mixed Input White Goods Stored Fluff
(n=28) Fluff (n=12) Fluff (n=15) (n=20)
Fluff
Spillover
(n=9)
Figure 5-24. EPTOX lead concentrations in fluff samples by type of material
-------
Table 5-17. Summary of EPTOX lead concentrations by type of sample (ppm)
Output Input Number of
stream type samples
Fresh fluff Auto
Fresh fluff Mixed input
Fresh fluff White
Stored fluff
Spillover
28
12
15
20
9
Number
of sites
7
3
5
5
5
Mean*
6.9
23
6.1
22
18
Standard
deviation
5.5
24
5.0
47
12
Median
5.0
13
32
9.5
20
Minimum
0.8
W
1.6
1.6
1.7
Maximum
21
78
14
220
36
The average of the sample bucket measurements and the mean concentration aggregated across all nested components are different only
for spillover. The mean aggregated across nested components is reported. All other statistics are based on the sample measurements.
A statistical comparison of EPTOX lead concentrations among different types of fluff
cannot be made based on the boxplots. These comparisons are provided by confidence intervals
and hypothesis tests.
Figure 5-25 and Table 5-18 show approximate 95% confidence intervals for the
average EPTOX lead concentrations by type of material5 The average EPTOX lead
concentration is calculated using a weighted average of the concentrations in fluff from white
goods, auto, and mixed-input material at each site.
Table 5-18. Mean with approximate 95% confidence intervals for EPTOX lead concentrations
(ppm) in fluff by type of sample
Type of sample
material
Fresh fluff
Stored fluff
Spillover
Mean EPTOX lead
concentration
(ppm)
7.2
22
18
Approximate 95%
confidence
interval
4.8 to 13
6.6 to 69
11 to 43*
Number of
sites
7
5
5
The confidence interval is approximate due to the small number of samples.
5See Appendix 5-A for details on how the confidence intervals were calculated.
5-50
-------
100 T-
Concentration in •
£ (ppm) 10 +"
t)
Q Mean
— 95% C. I.
1
Fresh Ruff
Stored
Spillover*
Output Stream
* The confidence interval is approximate due to small numbers of samples.
The true interval is wider than shown.
Figure 5-25. Mean with approximate 95% confidence intervals for EPTOX lead concentration in fluff by output stream
-------
A split plot analysis of variance was used to assess differences in EPTOX lead
concentrations (a) among fresh fluff from different input materials (white goods, autos, and mixed
input material); (b) among types of fluff (fresh, spillover, and stored fluff); and (c) between fluff
and soil samples. The tests were based on the site average of the log transformed concentrations.
None of these test showed significant differences.
Because the differences between site visits can be attributed to either differences
among sites or differences over time at the same site, the concentrations found in this pilot survey
may not be representative of typical operations at each site. For this reason, no test of differences
among sites was performed.
5.4.2
EPTOX Cadmium
The EPTOX cadmium concentrations in the sample buckets, in parts per million, are
shown in Figure 5-26 and summarized by type of sample in Table 5-19.
As can be seen from Figure 5-26, the EPTOX cadmium concentrations in most
samples are within the range of 0.4 to 2.0 ppm. The measurements are highly skewed. However,
the use of the log scale makes the boxplots roughly symmetric.
Table 5-19. Summary of EPTOX cadmium concentrations by type of sample (ppm)
Output
stream
Fresh fluff
Fresh fluff
Fresh fluff
Stored fluff
Spillover
Input
type
Auto
Mixed
input
White
Number of
samples
28
12
15
20
9
Number
of sites
7
3
5
5
5
Mean*
0.81
1.0
13
0.73
0.45
Standard
deviation
0.67
027
0.77
0.41
026
Median
0.70
1.0
13
0.61
03
Minimum
035
0.48
0.45
02
0.18
Maximum
4.0
1.4
13
2.0
0.81
The average of the sample bucket measurements and the mean concentration aggregated across all nested components are different only
for spillover. The mean aggregated across nested components is reported. All other statistics are based on the sample measurements.
A statistical comparison of EPTOX cadmium concentrations among different types of
fluff cannot be made based on the boxplots. These comparisons are provided by confidence
intervals and hypothesis tests.
5-52
-------
10 -r
in
£3
Cadmium
Cone. 1
(ppm)
0.1
X
a
i
D
T
Auto Fluff Mixed Input White Goods Stored Fluff
(n=28) Fluff (n=12) Fluff (n=15) (n=20)
Fluff
Spillover
(n=9)
D Median
* mean
— Boxplot
Figure 5-26. EPTOX cadmium concentrations in fluff samples by type of material
-------
Figure 5-27 and Table 5-20 show approximate 95% confidence intervals for the
average EPTOX cadmium concentrations by type of material.6 The average EPTOX cadmium
concentration is calculated using a weighted average of the concentrations in fluff from white
goods, auto, and mixed input material at each site.
Table 5-20. Mean with approximate 95% confidence intervals for EPTOX cadmium
concentrations (ppm) in fluff by type of sample
Mean EPTOX cadmium Approximate 95%
Type of sample concentration confidence Number of
material (ppm) interval sites
Fresh fluff 0.84 0.53 to 1.2 7
Stored fluff 0.73 0 JO to 1.1 5
Spillover 0.45 030 to 0.79 5
A split plot analysis of variance was used to assess differences in EPTOX cadmium
concentrations (a) among fresh fluff from different input materials (white goods, autos, and mixed
input material); (b) among types of fluff (fresh, spillover, and stored fluff); and (c) between fluff
and soil samples. The tests were based on the site average of the log transformed concentrations.
None of these test showed significant differences.
Because the differences among site visits can be attributed to either differences
among sites or differences over time at the same site, the concentrations found in this pilot survey
may not be representative of typical operations at each site. For this reason, no test of differences
among sites was performed.
5.5 Relationship Between Lead and Cadmium Total and EPTOX Measurements
As a general rule, the EPTOX lead and cadmium measurements increase as the total
lead and cadmium measurements increase. An analysis was performed to determine the
relationship between these measurements and to estimate the proportion of the lead and cadmium
which are removed using the EPTOX procedure. The analysis assumes that the proportion of the
lead and cadmium that is extracted depends on the type of material shredded and the effect of the
shredding process on the input material Since these factors can vary from site to site, the average
site concentrations are used in the analysis.
6See Appendix 5-A for details on how the confidence intervals were calculated.
5-54
-------
10 -r
Concentration
(ppm)
1 --
0.1
n
Q Mean
-95%C.I.
Fresh Fluff
Stored
Output Stream
Spillover
Figure 5-27. EPTOX cadmium concentration with approximate 95% confidence interval by sample type
-------
Figure 5-28 shows the EPTOX and total lead concentrations by type of material at the
seven shredder sites in the survey. Figure 5-29 shows the EPTOX and total cadmium
concentrations by material type for each site. Although the EPTOX lead and cadmium
concentrations show an increase with total lead and cadmium concentrations, neither the slope nor
differences between input types is statistically significant.
The extractability can be summarized by the "concentration ratio", i.e. the ratio of the
lead (or cadmium) concentrations in the EPTOX leachate to those in the fluff. For calculating the
average concentration ratio across all sites, the values for each material type are averaged within
at each site and then averaged across all sites. The log transformed concentrations are used in the
calculations, and the concentration ratio is summarized using the geometric mean of the ratio of
EPTOX to total lead and cadmium concentrations. The concentration ratio is summarized in
Table 5-21 and Figure 5-30 for both lead and cadmium.
Table 5-21. Concentration ratio (EPTOX/Total) for lead and cadmium
Analyte
Geometric mean ratio of EPTOX to
total concentration
(95% confidence interval)
Lead
Cadmium
0.0026 (0.0017 to 0.0040)
0.019 (0.014 to 0.026)
Assuming that the proportion of lead and cadmium removed by the EPTOX
procedure is constant, the proportion removed can be approximated by the ratio of the EPTOX to
total measurements multiplied by 20.7 The calculations are based on the log transformed site
averages and are summarized using the geometric mean proportion. Based on these calculations,
roughly 5 percent of the lead and 38 percent of the cadmium are removed using the EPTOX
extraction procedures.
7The weight of water added to the sample in the EPTOX extraction is equal to 20 times the weight of the sample. This value of 20, which
is used in the calculations, may result in an overestimate of the proportion of lead or cadmium removed because, at the end of the test,
not all of the water added to the sample can be removed from the test material for analysis.
5-56
-------
V
100 T
EPTOX
Lead 10 +
(ppm)
1000
O D
Total Lead Concentration (ppm)
• FFAuto
D FFOther
* FFWhite
o Spillover
A Stored
10000
Figure 5-28. EPTOX lead versus total lead concentrations at seven shredder sites by sample type
-------
oo
10 T
EPTOX
Cadmium 1 4-
(ppm)
0.1
10
D
• A
A
O
Total Cadmium Concentration (ppm)
• FFAuto
n FFOther
• FFWhite
o Spillover
* Stored
H
100
Figure 5-29. EPTOX cadmium versus total cadmium concentrations at seven shredder sites by sample type
-------
0.1 T
RatioofEPTOX
to Total Analyte 0.01
Concentration
0.001
I
o Geometric Mean
— 95% C.I.
-H 1
Lead Cadmium
Analyte
Figure 5-30. Concentration ratio (extract/total) for lead and cadmium using the EPTOX extraction process
-------
5.6
Sammary of Result* for Lead and Cadmium
In summary, the lead and cadmium analyses indicate that:
• Mean concentrations in fresh fluff are:
Anah/tes
Mean concentration (ppm)
(approximate 95%
confidence interval)
Total lead
Total cadmium
EPTOXlead
EPTOX cadmium
2800
(1800 to 4100)
47
(31 to 65)
(4.8 to 13)
0.84
(0.53 to 1.2)
Fluff samples have higher levels of total lead and cadmium than do soil
samples.
Total lead concentrations differ significantly among types of fluff, with spillover
having the highest, and fresh fluff having the lowest total lead concentrations.
5-60
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6. SAMPLE ANALYSIS
This chapter documents chemical analysis activities, with emphasis on support of
portions of Objective 1, namely the development of sample preparation and laboratory analysis
methods for shredder output materials. Two comparative methods of PCB extraction, the Soxhlet
and tumbler methods, were evaluated. The tumbler method was selected for the bulk of the work,
PCB instrumental analysis was done by Gas Chromatography/Electron Capture Detection,
although one sample was analyzed by Gas Chromatography/Mass Spectrometry.
6.1 Background
Chemical analyses were conducted to determine the concentrations of PCBs and total
and leachable lead and cadmium in selected fluff, soil, and metal samples. The buckets of sample
collected during the pilot study were designated for analysis according to a sample selection plan
"test pattern" (see Appendix 6-A). This selection plan groups subsamples drawn from the buckets
into batches that were designated for a specific chemical analysis. The purpose of the test pattern
was to develop data that could be used to compare types of extraction methods, Le,, tumbler vs.
Soxhlet, compare analytical results from different laboratories, and compare splits from the same
subsample, Leachabiu'ty comparisons of hot water versus room temperature water were made.
The chemical analyses required for the subsamples, or splits of subsamples within batches, are as
follows:
Batch Analysis Laboratory
Ml PCBs MRI
12-18 Leachable lead and cadmium ENSECO
19 Total lead and cadmium ENSECO
20 PCBs EMSL
21 Leachable lead and cadmium EMSL
22 Total lead and cadmium EMSL
All subsamples were drawn from the field samples at MRI. The chemical analyses of
subsamples and splits in batches 1 through 19 were performed by MRI and ENSECO, a
subcontractor to MRL Batches 20 through 22 were analyzed by the Environmental Monitoring
Systems Lab (EMSL), Las Vegas. Figures 6-1 through 6*3 show an overview of the chemical
analysis process.
Test samples were prepared and chemical analysis performed according to standard
or modified standard procedures except in the case of the extraction of fluff for PCB
determinations. For this, a new extraction approach (tumbler extraction) was used to minimize
the variability of PCB concentrations between subsamples drawn from the same original sample.
Samples in batches 1 through 4 were used to compare the Soxhlet extraction results to the tumbler
results and to compare using one versus three rinses in the tumbler extraction. All PCB values
repotted are based on dry weight. Dry weight correction factors were obtained by taking split
samples from the fluff samples undergoing extraction and analysis and conducting a dry weight
analysis, baking the split out at 105* C for 12 hours. The actual samples used for PCB
determinations were not baked out All values reported for total and EPTOX Lead and Cadmium
were reported on an as received sample basis. The EPTOX procedure states that solid samples
are not to be dried out before undergoing analysis. In order to relate the leachable amount of lead
6-1
-------
Sample for analysis
Select Subsample From Sample
by Quartering
Subsamples, 400-500 grains
Prepare the Sample for Soxhlet:
Sieve the Subsample
Mill the Large Pieces
Include a Portion of the
Non-millable material
Send Fluff to the Designated
Lab, if Required
Select Split From
the Subsample if Required
Splits for EPTOX
Extraction
Spike if Required for
Recovery Analysis
Extract PCB's Using
Tumbler or Soxhlet Method
1
r
Tumbler
grams UOO/grarns
Analyze and Calculate
Concentrations
Figure 6-1. PCB analysis steps using Soxhlet and tumbler extraction
6-2
-------
Sample for analysis
Select Subsample From Sample
Subsamples, 400-500 grains
Select Split From
the Subsample
Splits for EPTOX
Extraction
Prepare the Fluff Split
Sieve the Split (9.5 mm),
Mill the Large Pieces,
Discarded Non-millable
Portions
Send Fluff to the Designated
Lab, if Required
Divide Split into Subsplits
for Spiking, if Required
Subsplits (2 grams)
Spike if Required for
Recovery Analysis
Acid Digest Lead and
Cadmium Sample
Using EPA Method 3050
Atomic Absorption
Analysis to
Determine Lead and
Cadmium Concentrations
I1™ GJ
pNSECO
\
r
3050
Figure 6-2. Total lead and cadmium analysis steps
6-3
-------
EPTOX Lead and Cadmium Analysis Steps
Sample for analysis
Select Subsample From Sample
by Quartering (Sample pieces > 4"
in diameter were cut and
redistributed before quartering)
Subsamples, 400-500 grams
Prepare the Subsample:
Sieve (9.5 mm) the Subsample. Non-sieved
Material was Size Reduced by Tin Snips and
Hacksaws. Sieved Material Plus Non-sieved
Material with Surface Area to Weight Ratio
of > 3.1 sq.cmVg Were Combined to Make
lOOg Sample.
Select Split From
the Subsample
Splits for EPTOX
Extraction
EPTOX Extraction
Procedure
Send Extract to the Designated
Lab, if Required
Divide Effluent form EPTOX
Extraction into Subsplits
Spike if Required for
Recovery Analysis
Atomic Absorption
Analysis to
Determine Lead or
Cadmium Concentrations
ttOOJgrams nOOfgrams UOO/grams
Figure 6-3. EPTOX lead and cadmium analysis steps
6-4
-------
and cadmium present to the total lead and cadmium present, the total lead and cadmium analyses
were also conducted on samples on an as received basis.
Three additional sets of chemical analyses were performed for PCBs on the fluff
sample. The first was a physical components analysis and the latter two were hot and room
temperature water extraction (leachate) studies. The physical components of fluff were analyzed
to identify and determine quantities of Aroclors. It was hoped that the qualitative and quantitative
information obtained from these analyses might indicate possible sources of PCB contamination
because industrial uses of various Aroclors are known. The composite preparation plan is
contained in Appendix 7-A. The analysis of these materials was performed by the National
Enforcement Investigations Center in Denver, Colorado. The second and third sets of chemical
analysis are a series of PCB extractions using water (hot and room temperature) performed at
MRI.
62 Sample Preparation
62.1 Sample Homogenization and Subsampling
The representative subsampling procedure used for the initial comparison study of
Soxhlet and tumbler extractions (batches 1 through 4) was used for all remaining sample batches.
This method is described in Appendices 7-G and 7-H.
EPTOX Splits
Fluff subsamples designated for total and leachable lead and cadmium were split by
the subsampling method described in Appendix 7-A. Splits designated for EPA Method 1310
(EPTOX) extractions were processed according to the particle size and surface area criteria
described in the method. Splits were prepared by sieving a subsample through a 9.5 mm sieve.
Material which did not pass through the sieve was manually cut and reduced in size if necessary in
order to achieve a surface area to weight ratio of > 3.1 cm2/g and then recombined with the sieved
fraction to form a 100 gram split sample.
Total Lead and Cadmium Splits
Splits of fluff subsamples designated for total lead and cadmium determination were
placed in a 93-mm sieve. Material which did not pass through the sieve was segregated into
millable and nonmillable portions. The millable portion was then reduced in a Thomas-Wiley mill
to particle size to < 9.5 mm. Portions which passed through the sieve and the mill were combined
and mixed before shipment to ENSECO for analysis. The nonmillable portions were discarded.
622 Comparison of PCB Extraction Techniques Using Organic Solvents
Before the chemical analysis phase of the project began, EPA expressed concern over
the high level of variability occurring in measured PCB concentrations between split samples, as
reported by several state and independent laboratories. These laboratories were performing the
extractions with standard techniques such as Soxhlet and sonication extraction. The samples
weighed generally less than 20 grams (g) although, in some cases, they weighed up to 50 g. The
6-5
-------
major source of PCB concentration variability was believed to be associated with the
heterogeneous nature of fluff. A fluff sample can consist of chunks of rubber-like materials,
fabrics, hard and soft plastics, small metallic and nonmetallic parts, and fine particles of hard
materials such as road dirt. Also, the components of fluff have a wide range of surface areas and
oil-absorbing properties. These properties become important when a mass of material is selected
for extractions if, for example, small oil-filled capacitors and plastics are major sources of PCBs.
An attempt was made to alleviate some of the potential problems with sample
extractions. For example, larger subsample weights were selected for extraction. Using a larger
sample mass should allow the sample components between subsamples to be distributed more
evenly, increasing the chances of the sample components being represented in proportions better
approximating the initial sample. Efforts to lessen sample variability also included using a
different technique of drawing subsamples from the initial large sample. This procedure produces
a stratified random subsample with large weights (from 400 to 500 g).
Two extraction techniques were selected that could accommodate samples larger than
the 20 gram samples generally used previously in routine Soxhlet extraction procedures. A
tumbler extraction using a TCLP agitation apparatus (Slurry Extraction Procedure) could handle
500 grams of materials. Soxhlet extraction using large-volume (500 cc) extractors could handle 100
grams of milled materials. Before deciding which extraction approach to use for the pilot project,
the two techniques were compared. The Soxhlet and tumbler extraction approaches were applied
separately to eight paired samples (five with fluff from autos, three with fluff from white goods).
Both extraction methods employed the same initial subsampling technique, the same solvent
mixture, and final instrumental analysis methods. The Soxhlet extraction method, however, had an
additional preparation step to reduce particle size by milling. The experimental design for the
comparative study can be found in Appendix 6-B.
The Soxhlet and tumbler extraction methods provided similar measurements for
PCBs over a wide range of concentrations. The measurements are illustrated in Figures 6-4 and 6-
5. A linear regression analysis on the log transformed data shows no significant differences
between the two sets of measurements.1 Based on the geometric mean of the ratio of the Soxhlet
to the tumbler measurements from the same sample, the Soxhlet data were, on the average, 114%
(95% confidence interval of 85% to 151%) of the comparable tumbler data.
The result of this comparison was the adoption of the tumbler method for the pilot
project, since it allowed for larger samples of the materials and did not require the milling process
to perform the extraction procedures. The PCB concentrations obtained from the samples in this
comparison study comprise batches 1 through 4.
622.1 Sample Extraction with Organic Solvents
Subsamples or splits of subsamples were extracted in batches as designated in the test
pattern.
*The regression method used assumed that measurement errors for the Soxhlet and tumbler samples were identical
6-6
-------
1000 -r
100 ::
PCB
Concentration
Soxhlet
Method
(ppm)
10 --
a
a
i i M nil
D -'
.d
.d
- - Equality
D Measurement Data
1 — i i i i mi - 1 — t i M nil
1 10 100
PCB Concentration Tumbler Method (3 Rinses) (ppm)
1000
Figure 6-4. PCB measurements using Soxhlet versus tumbler extraction
-------
(5o
200% -r
180% - -
160% --
140% - -
120% - -
Ratio of
Measured
PCB'sto
Corresponding 100%
Tumbler
Concentration onfa
Using 3 Rinses 80%
60% --
40%
20%
0%
Tumbler with
"""3" rinses
Soxhlet Tumbler with 1 Rinse
Measurement Method
A Soxhlet
A Soxhlet geometric mean
* Tumbleifl]
o Tumbeif 1] geometric mean
— 95% confidence interval
- - Perfect agreement
Figure 6-5. Comparison of analytical methods: Soxhlet versus tumbler, tumbler with one versus three rinses
-------
Tumbler
The tumbler extraction approach for the comparison study (batches 1 through 4) was used to
prepare the fluff samples in batches 5 through 10 for total PCBs present. Whole subsamples
weighing approximately 400 to 500 g were extracted three times with 2 L of hexane/acetone (1:1,
v/v). Samples were tumbled at approximately 33 rpm for 1 hour during each sequential extraction.
The recovered solvent from each extraction was measured, and a composite was made from
proportional aliquots of the individual extracts. The method is presented in Appendix 7-H. The
composite extract was analyzed for PCBs.
During the comparison study, the first individual extract from seven samples and all
three extracts from one sample were analyzed for PCBs. Also, the maximum amount of
recoverable solvent from all three sequential extractions was determined for 10 samples. This was
accomplished by pressing as much solvent as possible out of the fluff after each of the three
extractions.
The tumbler extraction with one rinse and three rinses provided similar
measurements over a wide range of concentrations. A linear regression analysis on the log
transformed data shows no significant differences between the two sets of measurements.2 Based
on the geometric mean of the ratio of the tumbler measurements with one rinse to the
corresponding measurements with three rinses, the one-rinse data were, on the average, 88%
(69% to 111%) of the comparable measurements using three rinses.3 The measurements are
illustrated in Figures 6-5 and 6-6.
The tumbler method with three rinses was used for the extraction of PCBs in batches
5 through 11.
Soxhlet
Fluff. The fluff subsamples designated for Soxhlet extraction were first sieved. Fluff
which did not pass through the 9.5-mm sieve was separated into millable and nonmillable portions.
The particle size of the millable portion was reduced with a Thomas-Wiley mill to < 9.5 mm. The
sieved and the milled portions (particle size <, 9.5 mm) were combined. This material was then
homogenized, and 80-g aliquots were placed in Soxhlet extractors. A portion of the nonmillable
material was added to the top of the extractors at a weight percent equivalent to the original
sample (approximately 1 to 30%). The fluff material was extracted with 600 mL of 1:1 (v/v)
hexane/acetone. The extractions were contained for 18 hours at a Soxhlet syphon rate of
3 cycles/hour.
SoiL Batch 11 soil samples, each sample weighing approximately 20 g, were extracted
for a minimum of 16 hours in Soxhlet glassware using hexane/acetone (1:1, v/v).
2The regression method used assumed that measurement errors for the Soxhlet and tumbler samples were identical.
3Note that the concentration based on three rinses can be tower than that based on one rinse due to measurement errors. The
concentrations for three rinses are based on a composite extract sample, not on the sum of the measured concentrations in each extract.
6-9
-------
1000 T
100 ::
PCB
Concentration
with
1 Rinse
(ppm)
10 ::
D
*D
D
H 1 I I I MM
D
,'D
- Equality
Measurement Data
H 1 I I I lll| 1 1 I I I I M|
10 100
PCB Concentration with 3 Rinses (ppm)
1000
Figure 6-6. PCB measurements using one rinse versus three rinses during tumbler extraction
-------
623 Sample Extractions with Water to Examine PCB reachability
The objective of conducting the extraction studies was to determine the amounts of
PCBs leached from fluff after Soxhlet extractions and tumbler extractions using water as the
solvent. EPA designed the Soxhlet and tumbler extraction studies to be performed sequentially.
The Soxhlet extractions using hot water were first performed as a worst-case test of teachability.
Seven samples with known PCB concentrations from the work performed in batches 1
through 10 were selected for this test. Each sample was prepared for extraction by the same
particle size reduction method that was used for the Soxhlet extraction in the comparison study of
Soxhlet and tumbler extractions. The samples consisted of milled material and a percentage of
nonmillable material that approximated the composition of the original sample. The weight of
each sample was approximately 80 g. The samples were Soxhlet-extracted with Milli-Q water for
8 days at approximately 65°C. At the end of this period, the water was placed into a separately
funnel or continuous liquid-liquid extractor. The continuous liquid-liquid extractor procedures
were performed on the first three sample extracts for approximately 16 hours with methylene
chloride. The water from the last four extracts was placed in the separatory funnels and extracted
three times with methylene chloride. The methylene chloride extracts were concentrated and
exchanged to isooctane. The final volume was adjusted to 2 mL. Prior to GC/ECD analysis, the
diluted extracts were subjected to cleanup with concentrated sulfuric acid.
A room temperature water leachability test for PCBs was conducted on fluff from the
same set of seven samples used for the hot water leachability test. For the room temperature test,
80 grams of fluff milled to <, 9.5 mm were placed in a tumbler with 2 liters of Milli-Q water. The
samples were tumbled at 33 rpm for 8 continuous 24-hour days at a temperature of approximately
22°C. After 8 days of tumbling, samples were filtered through a 0.45 /on filter before undergoing a
separatory funnel solvent exchange using methylene chloride. As in the hot water leachability test,
the concentration of PCBs extracted was found to be over an order of magnitude lower than the
solubility limit of PCBs in water.
62.4 Components Analysis
The objectives for component analysis were to identify the major physical components
of fluff material; calculate proportions (by weight and volume) of the various components; and
determine the PCB concentrations in each component.
Selected samples of fluff were composited and divided into the following five
component categories:
1. Metals, wire, and glass;
2. Soft plastics, foams, soft rubber, vinyls;
3. Fabrics, paper, and wood;
4. Hard materials, hard plastics, hard rubber; and
6-11
-------
5. Fines too small to classify, dirt, dust.
A small quantity of material that did not fit any of the above categories was not analyzed. It is
accounted for in Figure 5-17 under "unclassified".
The components of each composite sample were divided into two subsamples which
were sent to NEIC for analysis.
The procedure followed at NEIC involved the following:
(a) Each sample was well mixed;
(b) A 10 gram split was obtained from the subsample; and
(c) Chemical analysis was performed by Soxhlet extraction and GC/ECD packed
column method.
63 Chemical Analysis
6 J.I Apparatus and Materials
• Glassware and Bottles
Glass jars (1 gal) with approximately 4-in diameter openings were used for the
storage of subsamples and extractions.
Soxhlet extractors (50 cc) were used for soil sample extractions. For fluff
sample extractions, Soxhlet extractors (500 cc) were used.
Kuderna-Danish evaporative concentrators were used to exchange solvents.
Miscellaneous glassware was used as appropriate, including volumetric flasks,
pipets, gastight syringes, graduated cylinders, beakers, jars, and vials.
Polyethylene bottles (4oz) were used for the soil, solid fluff, and EPTOX
leachate designated for lead and cadmium determinations.
• Milling Apparatus
A Model 4 Thomas-Wiley laboratory mill with a 9.5-mm grate fabricated by
MRI from stainless steel was used to reduce the particle size of fluff.
6-12
-------
Agitation Apparatus (Tumbler)
Four boxes were constructed by MRI for tumbler extractions. Each box could
hold eight 1-gal jars in separated compartments and was mechanically rotated
by an electric motor at approximately 33 rpm (see Figure 6-7).
Fiberglass Trays
Fiberglass trays (4 ft x 2 ft) were purchased from Consolidated Plastics
Company and used for preparation of subsamples and splits.
Sieves
Polyethylene sieves fabricated at MRI were used to size the fluff analyzed for
lead and cadmium.
A 3/8-in (9-5-mrn opening) standard sieve purchased from Dual Manufacturing
was used in the comparison of extraction approaches for preparation of
samples.
Analytical Balance
A Mettler PC 4400 and an Ohaus triple-beam analytical balance were used in
the preparation of samples. The balance was checked for accuracy using
weights supplied by the MRI Quality Assurance Unit. Calibration was checked
at the beginning and end of each day that samples were weighed. The
calibration check ranged above and below the sample weights. The weights
used for the calibration check were evaluated against National Institute of
Standards and Technologies (formerly the National Bureau of Standards)
traceable weights, which resulted in a 0.05% difference.
Gas Chromatographs
Hewlett-Packard Model 5890
Varian Model 3500
Varian Model 3700
All gas chromatographs were equipped with electron capture detectors and
automatic samplers. The GC conditions and columns are presented in Tables
6-1,6-2, and 6-3.
Gas Chromatograph/Mass Spectrometer
A high-resolution VG 7-250 S GC/MS system was used for PCB
determinations. The GC/MS conditions and column description are presented
in Table 6-4.
Atomic Absorption Spectrophotometers (ENSECO)
A Perkin-Elmer Model 5000 A with deuterium background correction was used
for flame atomic absorption analysis.
6-13
-------
Figure 6-7. Agitation apparatus for tumbler extraction
-------
Table 6-1. Gas chromatographic conditions for HRGC/ECD analysis (HP5890)
Gas chromatograph: Hewlett-Packard 5890
Detector: ^Ni electron capture detector
Column: 30 m x 0.32 mm fused silica, DB-5 at 1.0 /im
Column temperature: 90°C/1 min -»• 210°C/8 min at 25°C/min;
- 280°C/22 min at 20°C/min
Injector temperature: 270°C
Detector temperature: 320°C
Carrier gas: 2 mL/min helium
Carrier makeup gas: 30 mL/min P-5
Injection volume: 2jiL
Data System: Nelson Analytical Model 4400 Chromatography Data System
Table 6-2. Gas chromatographic conditions for HRGC/ECD analysis (Varian 3500)
Gas chromatograph: Varian 3500
Detector: ^Ni electron capture detector
Column: 30 m x 0.32 mm fused silica, DB-5 at 1.0 ^m
Column temperature: 90°C/1 min -»210°C/8 min at 25°C/min;
-» 280°C/22 min at 20°C/min
Injector temperature: 270°C
Detector temperature: 320°C
Carrier gas: 2 mL/min helium
Carrier makeup gas: 30 mL/min N2
Injection volume: 2/iL
Data System: Nelson Analytical Model 4400 Chromatography Data System
6-15
-------
Table 6-3. Gas Chromatographic conditions for GC/ECD analysis of Aroclor combinations to be
quantitated by the Webb-McCall method
Gas chromatograph: Varian3700
Detector: ^Ni electron capture detector
Column: 280 cm x 0.2 cm glass, 3% OV-1 on 100/120 mesh Supelcoport
Injector temperature: Isothermal, 170°C
Detector temperature: 320°C
Nitrogen flow: 50 mL/min
Injection volume: 3.0
Data system:
1. Nelson Analytical Model 4400 Chromatography Data System
2. Heath Model SR-240 analog strip-chart recorder
Autosampler: Varian Series No. 8000
-------
Table 6-4. HRGC/HRMS operating conditions for PCB analysis
Mass spectrometer
Accelerating voltage:
Trap current:
Electron energy:
Photomultiplier voltage:
Source temperature:
Resolution:
Overall SIM cycle time:
Gas chromatograph
Column coating:
Film thickness:
Column dimensions:
He linear velocity:
He head pressure:
Injection type:
Split flow:
Purge flow:
Injector temperature:
Interface temperature:
Injection size:
Initial temperature:
Initial time:
Temperature program:
Final hold time:
8,000 V
500/iA
35 eV
320V
280°C
> 10,000 (10% valley definition)
Is
DBS
0.25
60 m x 0.25 mm ID
~25cm/s
25psi
Splitless, 45 s
30mL/min
3mL/min
290°C
290°C
90°C
2min
90° to 300°C at 8°C/min
lOmin
6-17
-------
A Perkin-Elmer Model 5100 Z with Zeeman background correction was used
for graphite furnace atomic absorption analysis.
A Perkin-Elmer Model 2380 H with deuterium background correction was used
for graphite furnace atomic absorption analysis.
63.2 Reagents
• Solvents
Isooctane, hexane, and acetone, purchased from Burdick & Jackson, were all
pesticide-grade distilled in glass.
Acids
Concentrated nitric acid purchased from Fisher Scientific, ACS reagent grade,
diluted with Milli-Q water, was used for container cleaning.
Concentrated sulfuric acid purchased from Taychemco, ACS reagent grade, was
used for sample cleanup.
Standards and Internal Quality Control Samples
PCB Standards: For GC/ECD analysis, the PCB standards used for
quantitation included Aroclors 1242, 1254, and 1260. For GC/MS analysis, an
individual PCB isomer mix was used as a standard. As an internal standard, a
solution of carbon-13 labeled PCBs, including ^Q-mono-PCB, ^C^-tetra-
PCB, and ^C^-octa-PCB, was used.
In contrast to Method 680 which uses chrysene-dl2 and phenanthrene-dlO as
internal standards, MRI uses 13C-PCBs in an effort to use internal standards
which are more specific to the chemical nature of the PCB analytes being tested
and having both elution and mass/ion ratios in the range of the PCB analytes of
concern. The use of nonochlorobiphenyl was included in the calibration
standard mixture in order to show the analytical response for the array of PCB
homologs associated with the Aroclors of interest.
The Aroclor working standards were prepared from concentrated stock
solutions by serial dilutions in isooctane. The Aroclor 1242, 1254, and 1260
stock standard solutions were prepared at MRI by direct weight measurement
of the neat Aroclor followed by dilution in toluene. The neat Aroclors were
obtained from EPA as 100% technical grade; lot numbers are listed in
Appendix 6-C.
The Aroclor working solution standards were validated during previous
activities for Work Assignment 8862-30 under EPA Contract No. 68-02-4252.
The concentrations of the working calibration solutions were validated by
GC/ECD analysis versus internal quality control solutions. The internal quality
control solutions were prepared from EPA solutions 10402, 10502, and 10902
6-18
-------
for Aroclors 1242, 1254, and 1260, respectively. Vials containing identical stock
Aroclor standards were provided to each laboratory perforxning PCB analyses.
The individual PCB isomer mixture was prepared from concentrated stock
solutions. Concentrated solutions of each isomer were prepared by direct
weight measurement of the neat isomer followed by dilution in hexane. A
mixture of the individual isomer standards was then prepared by dilution in
hexane.
The carbon-13 internal standard mixture was prepared from concentrated stock
solutions of the individual carbon-13 compounds. The stock solutions (MRI
No. 819:4) were prepared by direct weight measurement of the neat compounds
followed by dilution in toluene. The neat materials (99% purity) were made at
MRI by the Isotope Synthesis Group. The reference lot numbers are as
follows: ^Cfi-mono, lot 82-139-21; ^C^-tetra, lot 82-124-18; and ^C^-octa,
lot 82-120-44-24.
The GC/MS instrument calibration standards were prepared by combining
appropriate aliquots of the individual isomer mixture standard with an aliquot
of the carbon-13 internal standard mixture and diluting in isooctane. The
concentrations of the instrument calibration standards are presented in
Table 6-5.
An appropriate aliquot of the carbon-13 internal standard mixture was added to
the sample extracts to yield concentrations equivalent to the internal standards
in the calibration standards.
Spikes and Blanks, Batches 5 through 11: Method spikes were prepared using
Aroclors 1242,1254, or 1260 to evaluate recoveries. The designated subsample
was spiked with the predominant Aroclor observed in subsamples from the
same bucket analyzed previously. Sources and lot numbers of Aroclors are
listed in Appendix 6-C.
In addition to internal quality control measures for evaluating method
recoveries, a method blank was prepared and analyzed with each batch to
determine whether laboratory contamination had occurred during preparation
activities. Method blanks consisted of sea sand (Fisher, lot 862179A).
Lead and Cadmium Standards: Certified standard solutions of lead and
cadmium were purchased from SPEX Industries, Inc. Unopened bottles of
these standards were distributed by MRI to each laboratory performing lead
and cadmium analyses. A copy of the certificates of analysis is presented in
Appendix 6-D.
Spikes and Blanks, Batches 12 through 19: Each laboratory performing lead
and cadmium analyses prepared and analyzed method spikes and blanks at the
frequency intervals specified in the test pattern (Appendix 6-A).
6-19
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Table 6-5. Individual PCB isomer mix calibration standards
Low std.
Final cone.
Compound (ng/mL)
2-Chlorobiphenyl
2,3-Dichlorobiphenyl
2,4,5-Trichlorobiphenyl
2,2 ' ,4,6-Tetrachlorobiphenyl
2,2 ' 3,4,5 ' -Pentachlorobiphenyl
2,2 ' ,4,4 ' ,5,6 ' -Hexachlorobiphenyl
2,2 ' 3,4 ' ,5,6,6 ' -Heptachlorobiphenyl
2,2 ' ,33 ' ,4,5,6,6 ' -Octachlorobiphenyl
2,2 ' ,3,3 ' ,4,5,5 ' ,6,6 ' -Nonachlorobiphenyl
Decachlorobiphenyl
^Cg-Monochlorobiphenyl
13C12-Tetrachlorobiphenyl
13C12-Octachlorobiphenyl
24
25
34
25
51
53
55
53
54
68
49
92
146
Med. std.
Final cone.
(ng/mL)
98
99
135
96
206
213
219
214
214
272
49
92
146
High std.
Final cone.
(ng/mL)
244
248
337
240
515
533
548
535
536
680
49
92
146
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633 Contamination Avoidance
All glassware was cleaned according to the intended use:
PCBs-acetone and hexane rinses;
Lead and cadmium-nitric acid followed by Milli-Q water; and
Archiving-nitric acid, Milli-Q water, acetone, and hexane.
Polyethylene bottles used for soil, fluff, and leachate for the lead and cadmium
determinations were rinsed with nitric acid and Milli-Q water. Fiberglass trays and sieves were
cleaned between samples by removing visible particles, followed by multiple hexane and acetone
rinses.
The standard operating procedures for operating and cleaning the Thomas-Wiley mill
are described in Appendices 7-C and 7-D.
63.4 Instrumental Analysis
63.4.1 Gas Chromatography/EIectron Capture Detection
Samples designated for PCB determinations were analyzed for Aroclor content by a
modified EPA Method 8080, a gas chromatography/electron capture detection method. See
Appendices 6-F and 7-E for details. This section describes the calibration, data reduction, and
quantification procedures used during the analysis of samples in batches 1 through 11 by
GC/ECD.
Calibration
The instrument was calibrated with Aroclor 1242, 1254, and 1260 standards. The
calibration standards were prepared and verified under Work Assignment 30 of EPA Contract
No. 68-02-4252. During the analysis, samples were bracketed by the standards used to construct
the three-point calibration curves with respect to both concentration and analysis order. Standards
were analyzed that gave instrument responses above and below the responses found for the
samples. After the initial calibration curve was developed, standards were analyzed daily.
Additionally, standards were analyzed at the end of a series of sample analyses.
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Data Reduction-Identification of PCBs in Samples
Sample extracts were screened for Aroclor pattern recognition by capillary GC/ECD.
A series of individual Aroclor standards (1016, 1221, 1232, 1242, 1248, 1254, and 1260) were
analyzed under the same analytical conditions as the sample extracts.4 Identification of Aroclors in
the sample extracts was performed by comparison of the HRGC/ECD sample chromatogram to
the standards. Identification of an Aroclor was performed by comparing the sample
chromatogram to the standards retention time window and peak intensity ratios. Both the sample
and standard retention time windows were narrowed when suspect Aroclor patterns in the samples
were partially interfered with by large peaks that did not match a standard chromatogram.
Quantification
The concentration of Aroclors in samples was determined from the sum of the peak
areas in retention time windows using the response factor of appropriate Aroclor calibration
curves. Where a single Aroclor was present in the sample chromatogram, the maximum number of
available Aroclor peaks was used to produce summed areas for quantification.
During the analysis of batches 1 through 4, samples containing complex mixes' of
Aroclors were quantified by the method of Webb and McCalL Although this method produced
total PCB results, it produced no data for individual Aroclors. This unfortunately eliminated the
possibility of using Aroclor type as an indication of PCB source. For the majority of samples, the
problem of quantifying individual Aroclors in Aroclor mixes was overcome by using the capillary
column.
The quantification of combined Aroclors 1242 and 1260 or Aroclors 1242 and 1254
required the reduction in the quantification window of each chromatographic pattern. The
reduction in the Aroclor windows was performed for both the samples and standards. Due to the
separation afforded by the capillary column, this procedure resulted in maintaining approximately
80% of the original Aroclor 1242 and 1260 responses. When the combination of Aroclor 1242 and
1254 was encountered, approximately 45% and 30% of the Aroclor 1242 and 1254 responses,
respectively, were maintained.
The reduced quantitation window procedure for the overlap cases of Aroclors 1242
and 1254 was evaluated after completion of batch 4 samples. The results of this method were
compared to the results obtained by the Webb and McCall method. This evaluation was initiated
by a request from EPA to continue the use of capillary columns through the remainder of the
project. The evaluation included four samples from the pilot project which were analyzed and
quantified by both techniques. The results indicate that the total Aroclor results differed by no
more than 7%. The evaluation resulted in the extended use of capillary columns and the
elimination of the packed column with isothermal GC oven conditions required by Webb and
McCalL
4See Appendix 6-E for additional discussion of Aroclor 1016 vs 1242 and Aroclor 1254 vs 1260.
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63.4.2 Gas Chromatography/Mass Spectrometry
During the course of the project, one sample was analyzed by GC/MS. In general,
EPA method 680: Determination of Pesticides and PCBs in water and soil/sediment by Gas
Chromotography/Mass Spectrometry was used (See Appendix 7-J).
Calibration
Mass calibration of the mass spectrometer was conducted according to the
manufacturer's specifications with a calibration gas, perfluorokerosene (PFK), to ensure proper
mass identification.
Before analysis of the sample, calibration curves for mono through deca individual
PCB isomers were established over three concentration levels. These standards gave instrument
responses above and below the responses found for the sample. Following the analysis of the
sample, the mid-level calibration standard was analyzed to ensure stable instrument performance.
The sample was bracketed by the standards used to construct the calibration curves with respect to
concentration and analysis order.
Data Reduction
The data were reduced using a high-speed computer program. The program filters
noise and calculates the sum of all responses in the appropriate mass window with ion abundance
ratios at ±20% of the theoretical ratio. The same program was used to calculate the curve relative
response factors (RRFs), daily standard RRF relative percent differences (RPDs), and sample
concentrations.
The samples and standards were spiked with equal concentrations of uC-labeled PCB
standards. For standardization, RRFs were calculated versus the labeled internal standard.
Response identifications for each congener group were made based on ion abundance ratios being
within 20% of the theoretical value and greater than 3X background noise. The PCB quantitation
ions and theoretical ion abundance ratios are presented in Table 6-6.
Quantification
The responses from the sample were compared to a standard curve made with known
concentrations of individual PCB isomers. For the specific isomer mix, the ^Cg-mono-PCB was
used to quantitate the mono- through tri-PCB responses, the ^C^-tetra-PCB was used to
quantitate the tetra- through hepta-PCB responses, and the ^C^-octo-PCB was used for octa-
through deca-PCB responses. Each homolog was quantitated using the representative ion pair
shown in Table 6-6.
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Table 6-6. PCB quantitation ions and ion abundance ratios
Analyte
"C-Mono-PCB
^-Tetra-PCB
^-Octa-PCB
Mono-PCB
Di-PCB
Tri-PCB
Tetra-PCB
Penta-PCB
Hexa-PCB
Hepta-PCB
Octa-PCB
Nona-PCB
Deca-PCB
Mass 1
amu
196.0561
303.9602
441.8014
190.0363
223.9974
257.9584
291.9194
325.8804
361.8385
395.7995
429.7606
465.7186
499.6797
Mass 2
amu
194.0591
301.9632
439.8043
188.0393
222.0003
255.9613
289.9224
323.8834
359.8415
393.8025
427.7635
463.7216
497.6826
Ion abundance
ratio 2/1
2.99
0.76
0.87
2.99
1.52
1.01
0.76
0.61
1.22
1.02
0.87
131
1.15
Ratio
tolerance
(%)
50
50
50
20
20
20
20
20
20
20
20
20
20
63.43
Atomic Absorption Spectroscopy
The majority of the samples were analyzed by Flame AA using EPA Methods 213.1
and 239.1 for lead and cadmium. In samples where the cadmium or lead concentrations were
below the limits of quantification of the FLAA, the GFAA Methods 7131 and 7431 for lead and
cadmium were used.
The instrument calibrations were established using three-point calibration curves for
both lead and cadmium. Sample responses were maintained within the calibration range of the
instruments by dilution. The midpoint calibration standard was analyzed with each batch of
samples to check for instrument stability.
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7. QUALITY ASSURANCE
Quality assurance (QA) procedures were applied to all phases of the Fluff Pilot
Project to ensure that the data are of known quality. These procedures are detailed in the three-
phase Quality Assurance Project Plan (QAPjP)1, which covers Field Sampling, Chemical Analysis,
and Statistical Data Processing and Analysis. Phase I, Field Sampling, was completed on
December 7, 1988. Phase n, Chemical Analysis, was completed on December 16, 1988. Phase HI,
Statistical Data Processing and Analysis, was completed on April 12,1989.
Quality Assurance
In addition to the procedures outlined here and detailed in the QAPjP, the pilot
project was audited by EPA QA personnel This audit involved a site visit, data review, and
parallel analysis of portions of the data.
This chapter presents:
• Development of the Quality Assurance Project Plan;
• Field sampling, pre-sampling, and tracking activities;
• Laboratory activities;
• The results of the field sampling;
• Chemical analysis results and comparison;
• Auditing Activities.
7.1 Quality Assurance Project Plan Development
The quality assurance activities for the Fluff Pilot Program began with the
development by Westat and MRI of the QAPjP, in November 1988. As the pilot program evolve,
it became apparent that a phased approach would be required, and the decision was made to
develop the QAPjP in three parts. Phase I, Field Sampling, was completed on December 7, 1988.
Phase n, Chemical Analysis, was completed on December 16, 1988. Phase m, Statistical Data
Processing and Analysis, was completed on April 12,1989.
1 Pilot Program for Fluff Sampling and Analysis, Phase 1, II, and m, dated December 7, 1988, March 3, 1989, and April 12, 1989,
respectively.
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72 Field Sampling Activities
72.1 Data Quality Objectives (DQOs)
The DQOs for Field Sampling were:
• Collection of representative samples by volume of fluff, ferrous metals, and
nonferrous metals.
• Collection of samples representative of surface soil where fluff has resided.
• Avoidance of contamination from field sampling and sample handing.
• Traceability of the collected samples from time of collection to arrival at the
MRI.
These objectives were met but the quantities that were collected varied slightly from the targets.
122 Standard Operating Procedures (SOPs)
The standard operating procedures (SOPs) listed below were developed to ensure
that the same procedures were followed throughout the study. Copies of the complete SOPs may
be found in Appendices 7-A through 7-D of this report.
Standard Operating Procedures:
• Drawing a Representative Subsample;
• Introduction to Fluff and Safety;
• Wiley Mill Operation; and
• Wiley Mill Cleaning.
123 Presampling
The presampling activities consisted of preparing the sampling equipment and
containers (see Table 7-1). MRI cleaned the sample containers and equipment prior to their
shipment to the field. The cleaning procedure consisted of soaking in dilute (20%) nitric acid,
rinsing with deionized water, followed by separate acetone and hexane rinses. The quality control
procedure for the cleaning activity consisted of randomly selecting several containers which were
then rinsed with deionized water. An aliquot of the rinse water was then evaluated for cadmium
and lead content. Containers were also evaluated for PCBs as Aroclors. The evaluation for PCBs
consisted of a hexane rinse of several containers and analysis of the rinse by gas
chromatography/electron capture detector (GC/ECD). The sampling equipment was checked by
similar procedures.
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Table 7-1. Field sampling equipment
1. Sample Container
Matrix
Fluff (New and Old)
Metals (Fe and NonFe)
Soil
Other
Number
8
4
5
2
Container
5-gal pail
5-gal pail
32-oz jar (wide mouth)
5-gal pail
Sampling Tools
4 trowels
4 disposable 10 x 10-cm templates
Safety Equipment
1 box Latex gloves
4 pair cotton gloves
2 safety eyeglasses
4. Labels
25 barcode sample label pairs
25 information labels
4 shipping boxes
4 return Federal Express shipping labels
Packing Supplies
2 rolls duct tape
2 rolls strapping tape
1 razor blade box knife
1 pair scissors
1 roll cellophane tape and dispenser
6. Support Materials
1 lab notebook containing sample inventory sheets
3 black ink pens
3 glass-marking pens
2 large trash bags
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The analyses for the water rinse gave results below the LOQ for cadmium and lead
(see Table 7-2). The results of the hexane rinse analysis were below the LOQ for the Aroclors.
7.2.4 Sampling and Tracking
Sampling activities were conducted by the methods described in Section 7 of
Appendix 4-A, Fluff Pilot Program Training Manual The samples were collected as described in
the SOP, and deviations from the SOP were documented in the field notebooks. The sampling
activities are further discussed in Chapter 3 of this report. The collected samples were maintained
under a sample traceability procedure. A barcode label was assigned to each sample and
documented on the traceabiliry forms in the back of the field notebooks. Traceability was checked
during the systems and data audits. The actual tracking of samples started with the data report
and followed the samples back to the collection notebook by means of an assigned barcode
number. The use of the sets of barcode labels and logging the time of sample collection on the
worksheets proved invaluable.
The samples were shipped at ambient temperature to MRI by common carrier.
Quality assurance systems audits included review of the field sampling notebooks and
worksheets.
73 Laboratory Activities - Chemical Analysis Phase
The quality assurance activities that pertain to the chemical analyses are presented in
this section. These activities cover methodology, sample handling, sample preparation, and sample
analysis.
73.1 Sample Handling
At MRI, project personnel received the samples and checked each sample barcode
against the corresponding barcode on the traceability form. The sample containers were then
visually checked for damage and stored in a room at ambient temperature.
73.2 Sample Preparation
The samples were prepared for subsampling using the design supplied by the Office of
Toxic Substances (see Drawing a Representative Subsample SOP in Appendix 7-A).
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Table 7-2. Analytical limits of detection (LOD) and limits of quantification (LOQ)
Analytical
type
Flame AA
GFAA
GC/ECD
Method
no.
213.1
239.1
7131
7421
8080
LOD
Analyte
Cadmium
Lead
Cadmium
Lead
Aroclor
Fluff
0.5 Mg/g
0.01 mg/g
0.05 /ig/g
0.1 Mg/g
a
Leachate
5.0 Mg/L
0.1 mg/L
0.5 Mg/L
1.0 Mg/L
a
LOO
Fluff
5.0 Mg/g
0.1 mg/g
0.5 Mg/g
1.0 Mg/g
0.1 Mg/g
Leachate
50 Mg/L
1.0 mg/L
5.0 Mg/L
10 Mg/L
1.0 Mg/L
•The LOD was not determined for the Aroclor analyses. The samples were reported either as positive quantification or as no value if the value
was less than the lowest standard.
-------
7.4 Field Sampling Quantitative Results
The number of samples, that is, buckets of metal or fluff, or bottles of soil collected,
are as follows. Number of samples in parentheses represent numbers collected from individual
sites.
Auto fluff - 36 samples from 7 sites (8,8,4,4,4,4,4)
White goods fluff - 19 samples from 5 sites (4,4,4,4,3)
Other fluff- 12 samples from 3 sites (4,4,4)
Spillover - 9 samples from 5 sites (2,2,2,2,1)
Old fluff - 20 samples from 5 sites (4,4,4,4,4)
Ferrous metals - 17 samples from 7 sites (4,3,2,2,2,2,2)
Nonferrous metals ~ 14 samples from 7 sites (2,2,2,2,2,2,2)
Soil - 25 samples from 6 sites (5,4,4,4,4,4)
7.5 Sample Analyses
The sample analyses were conducted as described in the Phase 2 QAPjP with only
those deviations listed herein.
Polychlorinated Biphenyls
The PCB analyses were conducted using the GC/ECD analytical system for all but
one sample. This sample was analyzed using a GC/MS analytical system. The quantification
procedures used to determine the types and concentration of PCBs in the fluff samples were for a
specific Aroclor or Aroclor combination.
Lead and Cadmium Analyses
The analyses for cadmium and lead were conducted as described in the Phase 2
QAPjP. The approved deviation from the QAPjP for the cadmium and lead analyses is presented
in Section 7.3.1.
The EPTOX extraction of the leachable cadmium and lead was performed at MRI.
The Method 3050 digestion of fluff for total cadmium and lead was performed by Rocky Mountain
Analytical Laboratory (RMAL), a division of ENSECO. The quantification of the EPTOX
extracts and the total cadmium and lead digestions was performed by flame AA and GFAA at
ENSECO-RMAL.
During the cadmium and lead sample preparation and analyses, there were two other
deviations in addition to the substitution of the flame AA for the GFAA, discussed in Section
7.3.1. The first deviation was caused by the loss of all subsamples in a batch during sample
extraction. Consequently, other subsamples were substituted. The second deviation was caused by
the change of quantification procedures from GFAA to flame AA. The matrix spiked samples
were remade at a higher concentration for flame AA determination.
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Data Measurement Objectives (DMO)
The instrument performance was checked daily for each analytical method. The
instrument performances for the GC/ECD, GC/MS, flame AA, and GFAA were checked using
calibration check standards, method blank samples, method spiked samples, internal QC samples,
and performance audit samples (PASs).
The GC/ECD calibration performance was established using a three-point calibration
curve for each Aroclor. Thereafter, the calibration curve was checked daily with the midpoint
calibration standards. When the RF of the daily calibration check failed the acceptance criterion
of + or - 20%, standards for a new three-point standard calibration curve were analyzed.
The flame AA calibration performance was established using a three-point calibration
curve for each analyte (cadmium and lead). The midpoint calibration standard was analyzed with
each batch of samples to check for instrumental drift. The standard analytical protocol for the
Quality Control samples was performed as recommended in the QAPjP and OSW 7000 series for
the four methods (see third deviation). The four methods used were 7131 and 213.1 for cadmium
and 7421 and 239.1 for lead. These samples were within the established acceptance + or - 3
standard deviation units, which was based on the average, historical data.
The limits of detection and limits of quantification for each method are presented in
Table 7-2.
Internal Quality Control Samples
The internal quality control samples for the GC/ECD analyses for PCBs consisted of
method blanks, replicate samples, matrix spike samples, and performance audit samples.
The cadmium and lead analyses consisted of method blanks, replicate samples, matrix
spike samples, and a standard addition spike.
A further quality control was duplicate analyses for PCBs, cadmium, and lead from
selected samples.
Deviations
During the analytical phase of the work there were three deviations from the
approved methodology as given in the Phase 2 QAPjP. Each deviation was reviewed and
evaluated to determine how it would affect the data. The deviation and associated comparison
data, or a discussion of the effect on the data, were then submitted to the EPA for approval
The first approved deviation allowed the Webb and McCall calculation procedure for
total PCBs to be replaced with a "Least Overlap" procedure (see Section 53 of Modified Method
8080, Appendix 7-E) for calculating the concentration of samples containing PCBs as Aroclor 1242
and 1254. Since a large portion of the samples contained Aroclor 1242 and 1254, the Webb and
McCall calculations would have required more time than was available, and the results would only
give a total PCB concentration. With the Least Overlap procedure, the individual Aroclor 1242
and 1254 results could be calculated. The comparative data submitted to EPA showed that the
7-7
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total PCB concentration calculated by this procedure for a sample containing Aroclor 1242 and
1254 was similar to the results obtained using the Webb and McCall procedure.
The second approved deviation allowed the use of a response factor (RF) for each
Aroclor calculated rather than a curve derived from the linear regression. Another part of this
deviation was the use of a three-point rather than a five-point calibration curve. The use of
response factors made MRI's approach more comparable to EMSL-LV, the external QA
laboratory. Where overlapping Aroclor patterns were observed, both EMSL-LV and MRI based
the calibration response factors on Aroclor peaks that were outside the regions of most overlap.
During the cadmium and lead analyses by GFAA, high levels of both analytes were
found in several samples. This made it necessary either to change the method or to make several
serial dilutions to bring the samples into the range of the GAFF analytical methods. Thus, the
third deviation was the selection of the flame AA for the high level samples because of the
potential significant errors associated with serial dilutions. However, all samples below the limit of
quantification for the flame AA were analyzed by the GFAA method.
7.6 . Quality Control Samples/Chemical Analysis Results and Comparison
The following conclusions were drawn from the inter-lab comparison:
• For most data, the measurements indicate good agreement between the two
labs;
• For a few samples (8% in these data) the labs showed significant disagreement
due, possibly, to chunks of contaminated material that are not distributed in the
subsample;
• The measurements from one lab may be higher or lower on the average than
for the other, although significant differences were noted only for the EPTOX
measurements where the MRI values are higher than the EMSL values by an
average of 39%; and
• The data suggest that the measurements from EMSL may be more variable
than those from MRI or that the steps involved in using another lab may add
variability to the measurements.
The results of the samples and matrix spiked samples were used to assess the accuracy
and precision of the analytical results. The comparison of the accuracy and precision to the data
quality objectives has shown the data to be of the quality required by the Phase 2 QAPjP. The
comparison of the data generated by MRI with the data generated by the external quality
assurance laboratory gives an additional degree of confidence to the data.
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7.6.1 Data Quality Objectives
The DQOs for chemical analysis are given in Phase 2 of the QAPjP. In general, the
DQO's for MRI and the external quality assurance laboratory are as follows:
• Accuracy: an accuracy of greater than or equal to 60% recovery for spiked
samples will be achieved;
• Precision: analytical precision of + or - 50% will be required for all replicate
subsamples with values greater than the Limit of Quantification (LOQ);
• Completeness: completeness of the data will be greater than or equal to 90%;
and
• Comparability: the comparability of inter-laboratory data will be 100%.
All analytical methods used by MRI and the external quality assurance laboratory are subject to
these DQOs.
1.62 Accuracy and Precision Results
The accuracy of the analytical methods was determined from the matrix spiked
samples. In this study, the matrix had a greater effect on the accuracy data than did the actual
analytical system. It is improbable that the sample matrix causes a significant positive bias in the
measurement of recovery (accuracy). It is far more likely that the sample matrix contributes to
large variability (error) in the estimation of both the native and spiked, and native concentrations,
which may result in very high (or low) recovery measurements. (See Appendix 5-A for additional
discussion). The nonhomogeneity of the samples gave a larger range of recoveries than would be
expected with the analytical methods: 55% to 280% for PCBs, 60% to 320% for total cadmium,
and 60% to 230% for total lead. The exception to this was the EPTOX method, where the
replicate accuracies were 81% to 104% for cadmium and 93% to 120% for lead. With the
exception of two PCB recoveries (55% and 58%), the DQO for accuracy of greater than or equal
to 60% for spiked samples was achieved.
The analytical precision of + or - 50% required for the replicate subsamples which
have values greater than the LOQ was achieved for all but one of the replicates. The cadmium
analysis for this replicate exceeded the DQO with a precision of 63%. The precision ranged from
4% to 44% for the PCB analyses; from 0% to 25% for cadmium and 2% to 32% for lead in the
EPTOX analyses; and from 0% to 63% for cadmium and 0% to 19% for lead in the total cadmium
and lead analyses.
7.63 Inter-lab Comparison
For the inter-lab comparison of PCBs conducted by MRI and the EPA Environmental
Monitoring Systems Laboratory in Las Vegas (EMSL-LV), replicate subsamples (subsamples
within the same sample) were used in a matched pair design. One member of each pair of
replicate subsamples was analyzed by MRI and the other by EMSL. The laboratory procedures at
MRI and EMSL differed in that MRI analyzed the entire subsample
7-9
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(about 500 grams) while EMSL analyzed a split (about 100 grams) from the subsample. Using 10
pairs of subsamples from 9 samples, PCBs were extracted using the tumbler (slurry) extraction
method. Measurements in the subsamples were used to estimate the PCB concentration in the
samples from which they were derived. The statistical analysis used the concentrations in the
samples. The results for two subsamples from the same sample were averaged to obtain the
concentration in that sample. Because only one sample analyzed by EMSL had multiple
subsamples, there are not enough data to reliably estimate the within-lab contribution to
measurement error at EMSL, or to compare the within-lab measurement error at EMSL to that at
MRI.
The PCB results from the two labs for the nine samples are shown in Figure 7-1 using
a log scale graph. Two dashed lines show the range within which 95 percent of measurements are
expected to lie. On the average, 1 in 20 observations will fall outside the expected range due to
chance alone. The expected range of the data is based on the estimated variance components (see
Appendix 5-A) and the assumptions that 1) the log transformed data have a normal distribution, 2)
the within-lab variability is the same for both labs, and 3) the steps involved in using another lab
and the process of selecting a split from the subsample used by EMSL contribute no significant
additional variability to the measurements. Due to small sample sizes and the related uncertainty
in the estimated components of variance, the expected range for the data should be considered to
be approximate.
As Figure 7-1 clearly shows, there is substantial discrepancy between the labs on two
of the nine sample measurements of PCB. Measurements for another sample are just outside the
expected range, indicating possible disagreement. For one sample, the MRI measurement
(19 ppm) is substantially less than the EMSL measurement (582 ppm). For the second sample, the
MRI measurement is 6.6 ppm; however, PCBs were not detected by EMSL above the limit of
detection (LOD). For this measurement, the nominal LOD of 0.1 ppm is used for the plot and the
calculations. It must be noted that the distribution of PCBs (and lead and cadmium) within fluff
can be very heterogeneous, with small concentrated regions. This heterogeneity contributes to the
relatively poor precision with which the variance components are estimated. From this
perspective, it may not be unusual to encounter discrepancies such as those reported above.
For the inter-lab comparison of total lead and cadmium, replicates splits (splits from
the same sample and subsample) were used in a matched pair design, with 14 pairs of splits from
13 samples. One member of each pair of replicate splits was analyzed by MRI and the other by
EMSL. The results for two splits from the same sample were averaged to obtain the concentration
in that sample. Because EMSL analyzed multiple splits in only one sample, there are not enough
data to compare the within-lab variability between the two Jabs. The total lead and cadmium
results from the two labs for the 13 samples are shown in Figures 7-2 and 7-3 using log scale
graphs. The two dashed lines in each figure show the range within which 95 percent of
measurements are expected to lie.
As can be seen in Figure 7-2, the majority of the total lead measurements from the
two labs are in good agreement (within the expected range). For two samples, however, the MRI
measurement is substantially greater than the EMSL measurement. For one sample, the EMSL
measurement is 23 ppm and the MRI measurement is 990 ppm, the average of measurements on
three splits (860, 1300 and 800 ppm). For the other sample, the EMSL measurement is 910 ppm
and the MRI measurement is 16,000, the average of three splits (1,400, 2,300 and 43,000 ppm).
For this sample, the large discrepancy is due primarily to one split with a very high concentration,
with 4% of the fluff being lead. With the high split removed from the calculations, the two labs are
in reasonable agreement for this sample.
7-10
-------
10000 T
Sample
Concentration
Measured by
MRI (ppm)
1000 I-
100 •:-
10 -.-
1 -.-
0.1
0.01
D
• Data
- - Expected range
n Not detected by EMSL
0.1 1 10 100 1000
Sample concentration measured by EMSL-LV (ppm)
10000
Figure 7-1. Inter-laboratory comparison of sample measurements of PCB
-------
•vl
*^
K>
100000 -r
10000 :-
Sample
\~oncentnuion
Measured by
MRI(ppm)
1000 - •
100 --
10
10
rf
100 1000 10000
Sample cumcmution mumncd by EMSL-LV (ppm)
• Data
-- Expected range
100000
Figiure 7-2. Inter-laboratory comparison of sample measurements of total lead
-------
Factors which contribute to the high variability between total lead measurements on
splits from the same lubsample are 1) the small amount of fluff used in the test (2 grams) and 2)
the form in which lead is found in the fluff. Due to the small amount of fluff analyzed, the
inclusion or exclusion of small amounts of lead can make a relatively large change in the measured
concentration. Because pieces of lead may be present in the fluff, large differences in
concentrations between splits may be due to the occurrence of a few lead pieces in one split which
are not present in another.
The total cadmium measurements are shown in Figure 7-3. As can be seen from the
figure, all but one measurement is within the expected range. That one measurement is close to
the expected range, indicating generally good agreement between the labs.
The EPTOX lead and EPTOX cadmium measurements are shown in Figures 7-4 and
7-5. These measurements were made on 11 paired splits within 10 samples. For the EPTOX lead
measurements (see Figure 7-4), half of the paired samples have concentrations within the expected
range and half are outside the expected range. Measurements from neither lab are consistently
higher than the other lab. For the EPTOX cadmium measurements (see Figure 7-5), half of the
paired samples have concentrations within the expected range and half are outside the expected
range. However, the measurements from MRI are generally similar to, or greater than, those from
EMSL.
For both EPTOX lead and cadmium, half of the data lie outside the expected range.
This suggests that either the variance estimates on which the expected range was based
underestimated the true measurement variance for EPTOX lead, or that other sources of error
(within-lab measurement errors at EMSL and additional variation associated with using a second
lab) contribute to the measurement error.
With the exception of the four extremes in the PCB and total lead plots that show
particularly poor agreement, the measurements from two labs are consistent with a proportional
relationship, Therefore, the data are summarized in Table 7-3 and Figure 7-6 by calculating the
confidence interval on the geometric mean ratio of the MRI measurement to the EMSL-LV
measurement. The confidence intervals are calculated assuming the data have a lognormal
distribution.2 For calculating the confidence intervals, the four points noted above are considered
outliers and are not included. These intervals are approximate since the samples were not
randomly selected, and outliers have been excluded. They serve primarily to indicate the level of
precision with which the geometric mean concentration ratios can be estimated from the data.
JAi dlicuued In Appendix 3-A, the lognomul distribution providM • good deecrlpilon of the data. Therefore, the dUlribullon of the log
iraniformed concentration ratio will be • normal. The confidence Interval! an baaed on a t-statlitlc for the mean log ratio, transformed
back to the original unlta.
7-13
-------
1000 -r
Sample
Concentration
Measured by
MRI (ppm)
100 --
10 •-
• Data
- Expected range
1 10 100
Sample concentration measured by EMSL-LV (ppm)
1000
Figure 7-3. Inter-laboratory comparison of sample measurements of total cadmium
-------
100 -T-
10 --
Sample
Concentration
Measured by
MRI (ppm)
1 --
0.1
0.1
• Data
- - Expected range
i • I r
1 10
Sample concentration measured by EMSL-LV (ppm)
II I I I F if
100
Figure 7-4. Inter-laboratory comparison of sample measurements of EPTOX lead
-------
10 -r
Sample
Concentration
Measured by
MR1 (ppm)
o\
1 --
0.1
0.1
Data
Expected range
1
Sample concentration measured by EMSL-LV (ppm)
10
Figure 1-5. Inter-laboratory comparison of sample measurements of EPTOX cadmium
-------
Table 7-3. Ratio of concentrations measured by MRI to those measured by EMSL on the same
sample, with approximate 95% confidence intervals
Analyte
PCBs
Total lead
Total cadmium
EPTOXlead
EPTOX cadmium
Geometric mean ratio
MRI/EMSL
(Approx. 95% Conf. Int.) i
i Comments
1.09 8 With outliers included,
(.61 to 1.98) .77 (30 to 2.02)
.95 11 With outliers included,
(.79 to 1.14) 1.59 (.72 to 3.5)
1.02 13
(.71 to 1.45)
125 10
(.69 to 230)
139 10
(1.03 to 1.88)
The confidence intervals indicate generally good agreement between the labs, given
the variability in the measurements. All confidence intervals include 1.0 (perfect agreement)
except for EPTOX cadmium, for which the MRI measurements are statistically significantly
greater than the EMSL measurements at the 5% level. On the average, the MRI EPTOX
cadmium measurements are 39% higher than the EMSL measurements.
Assuming that the components of variance are the same for both labs, the variability
in the concentration ratios is generally greater than is to be expected. Although there are not
enough data from EMSL to estimate variance components for that lab, and conclusions about the
sources of variability are difficult to make due to the small sample sizes, the data suggest that the
measurements from EMSL are more variable than from MRI, or that the steps involved in using
another lab add significant variability to the data. Because EMSL analyzed a smaller quantity of
fluff than did MRI (100 grams versus 500 grams), the variability contributed by the process of
selecting a split for analysis is likely to have been greater at EMSL than at MRI, possibly
contributing to greater overall variance in the measurements from EMSL.
7-17
-------
oo
100 -r
10 --
Concentration
Ratio: 1
MRI/EMSL
0.1 :-
0.01
O
O
B Tf-
T «
• - ® • >
-f -j
PCB Total Total EPTOX EPTOX
Lead Cadmium Lead Cadmium
-- Interlab Agreement
— 95% Conf. Int.
D Geometric Mean
* Data for C.I.
o Outliers
A Based on approximate LOD, Not
detected by EMSL
Figure 7-6. Inter-laboratory comparison of sample concentrations
-------
Overall, the following conclusions can be drawn from the inter-lab comparison:
• For most data, the measurements indicate good agreement between the two
labs;
• For a few samples (8% in these data) the labs showed significant disagreement
due, possibly, to chunks of contaminated material that are not distributed in the
subsample;
• The measurements from one lab may be higher or lower on the average than
for the other, although significant differences were noted only for the EPTOX
measurements where the MRI data are greater than the EMSL data by an
average of 39%; and
• The data suggest that the measurements from EMSL may be more variable
than those from MRI or that the steps involved in using another lab may add
variability to the measurements.
7.7 Auditing Activities
The audit activities during this study consisted of three system audits, three sets of
performance audit samples, three data audits, and assistance in the preparation of a tracking
report.
7.7.1 Internal Audits (MRI)
The system audits were an integral part of the total activity for this study. Three
system audits were performed by the MRI Quality Assurance Coordinator (QAC). The first
system audit was conducted during the preparation and PCB analyses of samples in the first two
batches. Each critical phase of the procedure was audited starting with the subsample, proceeding
through the milling procedure, and ending with the two types of sample extraction, slurry and
Soxhlet. The second audit was performed during the EPTOX extractions of fluff material for
cadmium and lead. The primary phases audited were the pH adjustments, the agitation, and the
filtration of the fluff along with the necessary volume adjustments required in the EPTOX
procedure. The third audit was performed at ENSECO-RMAL, the laboratory selected to
perform the Method 3050 digestion for cadmium and lead and the cadmium and lead analyses
from both the leachable extract and the total digestion procedures.
Three performance audits were conducted during the PCB analytical phase. The
performance audit samples sets were used to evaluate the data generated during the analytical
activities for PCBs and determine the accuracy of the total analytical system. The PAS's sets were
prepared using a polyurethane foam and sea sand mixture for the synthetic fluff matrix and sea
sand for the soil matrix. A synthetic matrix blank PAS and a synthetic matrix spike PAS were
prepared by the QAC from an independent Aroclor stock. The PAS's sets were placed into the
analytical system as blind samples. One set was prepared for the tumbling procedure, a second set
for the Soxhlet extraction procedure for fluff, and the third set for the soil extraction procedure.
The results, presented in Table 7-4, are within the criteria established by the Phase 2 QAPjP.
7-19
-------
Table 7-4. Performance audit sample (PAS) results
PAS no.
06065
06066
06068
06069
06071
06072
Sample
type
Synthetic Fluff*
Synthetic Fluff
Synthetic Fluff*
Synthetic Fluff
soil
soil
Extraction
method
Soxhlet
Soxhlet
tumble
tumble
Soxhlet
Soxhlet
Aroclor
none
1260
none
1260
1260
none
Found
concen-
tration
G*g/g)
<0.1
42.1
<0.1
27.5
5.4
<0.1
Actual
concen-
tration
(Mg/g)
< 0.1
51.0
<0.1
303
8.0
<0.1
Percent
accuracy
blank
82.5
blank
91.1
67.5
blank
PAS nos. 06065, 06066, 06068, and 06069 were synthetic fluff composed of polyurethane and sand.
Three data audits evaluated the data measurements, data operations, and analytical
process to ensure that no systematic errors were introduced. The audited data were randomly
selected and tracked through the data-generating system. The purpose of the initial data audit was
to ensure that calculations were properly performed, that the calculation system was in place, and
that data were properly checked and reviewed. The first audit was performed on the data from the
first two PCB sample batches. The second was conducted on the data generated from the
cadmium and lead analyses. The third audit was conducted on the PCB data.
7.7.2
External Audits
Sampling Audit
An external sampling audit of one site's sampling effort was conducted by EPA
OTS personnel, accompanied by ISRI representatives.*
Analysis Audit
The external analysis audit consists of a comparison analysis of approximately
10% of replicates by the EPA Environmental Monitoring Systems Laboratory-
Las Vegas. For the total lead and cadmium analyses, acid digestion Method
3050 was used. For the leachable lead and cadmium analyses, the fluff samples
were extracted using the EPTOX procedure (Method 1310); the extracts were
acid digested for graphite furnace atomic absorption spectroscopy (GFAA),
Method 3020. All the fluff sample digests were screened by GFAA and found
to contain lead levels far higher than anatyzable by GFAA. The samples were
then analyzed by inductively coupled plasma-atomic emission spectroscopy
(ICP-AES) for lead and cadmium. No deviations were made from the
*As mentioned in Section 43, in all cases, the team was accompanied by an observer from VERSAR, INC, under contract to ISRI.
7-20
-------
extraction and sample methods specified in the QAPjP. The results of the
external analysis audit are presented in Section 123 of this chapter.
The fluff samples used for PCB analysis were extracted using the tumbler
extraction procedure developed by MRI (see Appendix 7-H).
Several deviations from the PCB analysis protocol described in Appendix D of
the QAPjP-Phase 2 were made by EMSL-LV in order to reduce the analysis
time and to facilitate the accurate quantitation of the samples. These
deviations were made after consultation with MRI and are described as follows:
MRI provided calibration standards for only three Aroclors (1242, 1254, 1260).
One-point calibration was utilized for Aroclors 1016, 1221, 1232, and 1248.
Three-point calibration of 1242,1254, and 1260 was performed using a point-to-
point (K) curve rather than an average response factor. The fluff extracts were
analyzed for PCBs using a DB-5 gas chromatography column. All of these
changes were made in order to be consistent with the analysis procedures of
MRI.
c. External System Audit
The majority of the external systems audit consisted of the external review and
approval process of the Quality Assurance Project Plan submitted. The QAPjP
consisted of three documents: Phase I—Field Sampling, Phase n—Chemical
Analysis, and Phase in-Statistical Data Processing and Analysis. The first two
documents were drafted by MRI and the third by Westat. Each document
provides a detailed protocol covering the various phases of the project including
field sampling procedures, the methods of chemical analyses and the statistical
analyses to be used.
The EPA officials who reviewed and approved the final QAPjP included the
Project Officers, OTS QA Officer, OSWER Project Manager, and the EMSL-
LV QA Officer. Any modifications or amendments to the approved QAPjP
were submitted in writing to the EPA Project Officers for approval.
Other activities included in the external systems audit included an on-site audit
of the MRI and National Enforcement Investigation Center (NEIC)
laboratories as well as several meetings between Westat and EPA personnel to
review the statistical analyses being done on incoming data.
7-21
-------
GLOSSARY OF TECHNICAL TERMS
Accuracy - Degree of conformity of a measure to a standard or "true" value. Pertaining to
chemical analysis, the closeness of the analytical result to the "true" value. Accuracy of
chemical analysis is usually evaluated using spiked samples.
Aliquot - A fractional part or portion of a sample or solution.
Aroclor - Tradename (Monsanto) for a series of commercial PCB mixtures marketed in the
United States. Typically used with a number such as "1242". The first two digits, "12", stand
for a chlorinated biphenyl. The latter two digits represent the percentage of chlorine.
Auto fluff - The waste product from shredding automobiles, light trucks, vans, small buses, etc.
Capacitor - An electric circuit element capable of temporarily storing an electric charge which,
when released, provides the surge of electric current necessary to start motors; sometimes
contains PCBs.
Components Analysis - In this study, component analysis refers to the separation of fluff into
similar types of physical materials, e.g., metals, wire, and glass, soft plastics, foams, soft
rubber, and vinyls for weighing and chemical analysis.
Duplicate - A measurement term which refers to an additional measurement made on the same
sample or extract for quality assurance purposes.
EMSL - The EPA Environmental Monitoring Systems Laboratory in Las Vegas, Nevada. In this
study, EMSL was designated as the external quality assurance laboratory.
Extraction Procedure Toxicity Test (EPTOX) - An EPA standard operating procedure used to
extract leachable analytes from various waste products using pH adjusted water. This test
was used until September 1990 to classify hazardous waste under RCRA.
Ferrous metal - A metal containing iron, a magnetic metal.
Fluff The waste product of shredders, so named because of its light weight and fibrous, fluffy
appearance.
Fresh fluff - As defined for this study, fresh fluff is shredder waste product material less than 8
hours old. Fresh fluff is distinguished from stored fluff.
Gas chromatography/electron capture detector (GC/ECD) - A chemical analysis method which
can be used for organochlorine pesticides and PCBs.
Hazardous waste - A regulatory term describing a waste as defined in 40 CFR 261.3.
Heterogeneous • Consisting of dissimilar elements.
Leachability - The characteristic of being extractable from a matrix by a solvent, e.g., water or
hexane.
GL-1
-------
Leachate - The solvent and contaminant extracted from a matrix.
Limit of Detection (LOD) - Lowest concentration at which an analyte can be identified as present
in the sample at a stated statistical confidence level, using a specific analytical technique.
Limit of Quantification (LOQ) - The lowest quantity of an analyte that can be measured by a
specific analytical technique.
Matrix Spiked Sample - A sample of the matrix, to which a known quantity of the target analyte
has been added or "spiked."
Mixed goods fluff - The waste product from shredding a miscellaneous mixture of items which
generally includes light grade miscellaneous construction materials and may contain
automobiles and white goods.
Municipal landfill - A sanitary landfill operated by a municipality, that primarily receives
residential, commercial, and institutional solid waste.
NEIC - The EPA National Enforcement Investigation Center, Denver, Colorado. In this study
NEIC conducted the physical component analyses of the fluff.
Nonferrous metal - Metals that do not contain enough iron to be magnetic.
Plasticizer - A substance added to plastics or other materials to keep them soft or pliable.
Precision - A measure of the reproducibility of analyses under a given set of conditions.
Quality Assurance Project Plan (QAPjP) - A formal document describing the detailed quality
control procedures by which the data quality requirements/objectives in a specific project
are to be achieved.
Resource Conservation and Recovery Act (RCRA) - The primary legislation controlling hazardous
waste management by EPA.
Replicate - A measurement term which refers to different physical subsamples taken from the
same sample, for quality assurance purposes.
Representative subsample - A term used in this study to describe a subsample of fluff which was
selected to nominally contain the various components of constituents of fluff in
approximately the proportions in which they occur in the original sample.
Runs - In this study, a set of operating intervals established to obtain distinct samples of input
materials. The shredder was operated for a specific period of time (a run), and then cleared
before the next run was started and samples collected.
Sample - A portion of material collected for chemical analysis in this study; i.e., fluff, ferrous
metal, soil
GL-2
-------
Shredder - A very large machine consisting of a hammermill, feed mechanism, conveyors,
magnetic separators, and cyclonic or water separators. Shredders are used in the recycling
industry to shred automobiles, appliances, construction materials, etc. and separate output
products for recycling and disposal.
Site - For this study, a site was a facility which contains an operating shredder.
Slurry extraction procedure - Chemical extraction procedure described in Chapter 6.
Soxhlet - A special glass device used in the chemical extraction process.
Spillover Fluff - For this study, fine material which fell off the conveyer belt during the shredder
separation process.
Split - A split is a subdivision of a subsample.
Subsample - A subdivision of a sample.
Subsplits - A subdivision of a split.
Symmetric data - Data which are balanced or symmetric about the mean.
Toxic Substances Control Act (TSCA) - An Act of Congress enacted in 1976, which became
effective on January 1, 1977. TSCA directs the Environmental Protection Agency (EPA) to
evaluate and, if necessary, regulate the effects of chemical substances and mixtures on
human health and the environment.
Toxicity Characteristic Leaching Procedure (TCLP) - A chemical analysis procedure presently
required by EPA under RCRA to analyze wastes for the presence of hazardous materials.
Traceability - The ability to track when and where a sample has been since its collection.
TSCA-permitted hazardous waste landfill - A landfill permitted to accept PCB waste in
concentrations between 50 and 500 ppm. Such a landfill has met special technical
requirements concerning location relative to the historical high groundwater table, linings,
monitoring wells and leachate-collection system, operating and record-keeping, etc.
Tumbler extraction - In this study, a process utilizing a tumbler and one gallon jar for the slurry
extraction phase of a chemical analysis.
White goods - Consumer appliances including refrigerators, washers, dryers, dishwashers, freezers,
ranges, air conditioners, microwave ovens, and hot water heaters, etc.
White goods fluff - The waste product from shredding white goods.
GL-3
-------
Appendix 4-A
Fluff Pilot Program
Training Manual
4-A-l
-------
U.S. ENVIRONMENTAL PROTECTION AGENCY
Fluff Pilot Program
Training Manual
Sample Collection Phase
Contract No. 68-02-4293
December 9,1988
William M Devlin
Westat
Project Director
Paul Constant
Midwest Research Institute
Project Director
Westat, Inc. Midwest Research Institute
1650 Research Boulevard 425 Volker Boulevard
Rockvffle, MD 20850 Kansas City, MO 64110
(301) 251-1500 (816) 753-7600
Dan Reinhart, Task Manager
Mary Frankenberry, Project Officer
Design and Development Branch
Exposure Evaluation Division
Office of Toxic Substances
U.S. Environmental Protection Agency
Washington, DC 20462
-------
TABLE OF CONTENTS
Page
INTRODUCTION 1-1
1.1 Purpose of the Training Manual 1-1
12 Contents of the Training Manual 1-1
13 Overview of the Fluff Pilot Program 1-2
13.1 Pilot Program Objectives 1-2
13.2 Fluff Definitions by Input Stream- 1-3
133 Pilot Program Implementation: Sampling Phase 1-3
1.4 The Role of the States 1-3
1.5 The Role of the Institute of Scrap Recycling
Industries 1-3
1.6 Outline of Site Visit 1-4
1.7 Target Sampling Table „ 1-5
FIELD TEAM ORGANIZATION 2-1
2.1 Introduction 2-1
22 Assignment of Field Duties 2-1
22.1 Field Team Leader 2-1
2.22 Sampler 2-2
223 State Coordinator 2-3
23 Training 2-3
2.4 Points of Contact 2-3
2J Summary 2-3
SHREDDER FACILITY DATA COLLECTION MATERIALS 3-1
3.1 Introduction ................................................ 3-1
32 Team Leader Introduction Form 3-1
33 Contact Form ...... ...... ... ................... 3-2
3.4 Shredder Facility Worksheets 3-2
3.4.1 Worksheet 1. Shredder Facility Description 3-2
3.42 Worksheet 2. Shredder Description and Diagram ... 3-2
3.43 Worksheets. Sketch of Area 3-3
3.4.4 Worksheet 4. Product Stream Description 3-3
3.4 J Worksheet 5. Sample Options 3-3
3.4.6 Worksheet 6. Sample Description, Non-Soil 3-3
3.4.7 Worksheet?. Soil Sample Description 3-3
3.4.8 Worksheet 8. General Observations 3-3
3.4.9 Worksheet 9. Recognizance 3-4
3.4.10 Worksheet 10. Shredder Sampling Suggestions 3-4
3.4.11 Worksheet 11. Team Closure 3-4
3.5 Equipment Supply Kit Checklist 3-4
3.6 Final Site Checklist 3-4
3.7 Shipping Confirmation Sheet 3-4
ui
-------
TABLE OF CONTENTS (continued)
Page
3.8 Transmittal Sheet 3-4
3.9 Summary 3-5
GENERAL INSTRUCTIONS FOR THE SITE VISIT 4-1
4.1 Introduction 4-1
42 Health and Safety 4-1
43 Quality Assurance and Quality Control (QA/QC) 4-1
4.4 Communications 4-2
4.4.1 Initial Contacts with Shredder Facilities 4-2
4.42 Scheduling Interview and Sample Collection Date 4-2
4.43 Communications During Field Sampling 4-3
4.4.4 Commonly Asked Questions 4-3
4.5 Summary 4-5
WORKSHEETS 1-9 AND QUESTION BY QUESTION
INSTRUCTIONS 5-1
Worksheet 1. Shredder Facility Description
Worksheet 2. Shredder Description and Diagram
Worksheet 3. Sketch of Area
Worksheet 4. Product Stream Description
Worksheet 5. Sample Options
Worksheet 6. Sample Description, Non-Soil
Worksheet 7. Soil Sample Description
Worksheet 8. General Observations
Worksheet 9. Recognizance
Worksheet 10. Shredder Sampling Suggestions
Worksheet 11. Team Closure
FIELD SAMPLING 6-1
6.1 Introduction 6-1
6.2 Safety 6-1
63 Sampling Equipment 6-1
6.4 Sample Collection and Handling 6-3
6.4.1 Collection Procedures 6-3
6.42 Documentation— 6-4
6.43 Prevention of Contamination 6-4
6.4.4 On-Site Material Storage 6-5
6.5 Sample Shipping — 6-5
IV
-------
TABLE OF CONTENTS (continued)
Page
7 IN-FIELD SAMPLING PROCEDURES 7-1
7.1 Introduction 7-1
12 Sampling Procedures 7-1
72.1 Fresh Fluff 7-1
122 Stored Fluff 7-4
123 Metal Samples 7-4
12A Discretionary Fluff 7-6
12JS Soil Grab Samples 7-6
72.6 Special Circumstances 7-8
73 Sample Labeling 7-8
73.1 Objectives of Sample Labeling 7-8
132 Sample Labeling Procedures 7-9
List of Tables
1-1 Table of sampling parameters vs. measurement parameters 1-6
6-1 Field sampling equipment 6-2
-------
1. INTRODUCTION
1.1 Purpose of the Training Manual
The purpose of this manual is to provide guidance to personnel who will be
conducting site visits to complete the Worksheets and collect samples of fluff product streams for
the U.S. Environmental Protection Agency's (EPA) Fluff Pilot Program. The information and
procedures outlined in this manual are intended to provide the level of knowledge necessary to
ensure a high degree of consistency and standardization in sampling activities.
12 Contents of the Training Manual
This manual contains seven chapters, each dealing with specific aspects of the design
and conduct of the Fluff Pilot Program (FPP). This chapter provides an overview of the study and
its objectives, discusses the site selection process, describes the communication roles, and outlines
the activities that the sampling team will perform.
Chapter 2 discusses the field team organization. It includes the assignment of field
duties, training, and practice of field procedures.
Chapter 3 discusses the use of data collection forms that have been developed for the
Fluff Pilot Program. These forms include: the FPP Shredder Facility Worksheets and various
observation records that comprise the Field Logbook.
Chapter 4 contains the general instructions for sampling fluff, soil, ferrous and non-
ferrous metals, including health and safety aspects, quality assurance and quality control, and
scheduling and communications procedures.
Chapter 5 includes the FPP Worksheets and specific instructions for completing them.
Chapter 6 contains instructions for taking samples of fluff product streams.
Chapter 7 contains the detailed in-field-sampling procedures.
1-1
-------
13 Overview of the Fluff Pilot Program
The 1984 Amendments to the Resource Conservation and Recovery Act authorize
EPA to monitor the disposition of toxic materials. The Agency's efforts to obtain information on
the components of fluff product streams, as generated by shredder faculties in the scrap recycling
industry, indicate that fluff is a highly heterogeneous material that may contain PCB's, lead,
cadmium and other toxic materials. Unfortunately, previous efforts to obtain information on the
components of fluff have provided only limited data. In order to learn more about fluff product
streams, EPA has designed a Fluff Pilot Program in four parts. These are sample collection,
measurement, analysis, and evaluation. This manual addresses the first part of the program:
Sample Collection.
Pilot Program Objectives
The objectives of the program, on a pilot basis, include gathering samples from which
the following case can be determined:
1. Determine the average total PCB levels in fluff materials;
2. Determine lead and cadmium levels in fluff material and determine teachability
using both standard EP tox and TCLP analyses;
3. Determine the extractability of PCBs from fluff for use in OTS' risk assessment
(to replace soil-based parameters used in current risk assessment models);
4. Identify the major physical components of fluff material; calculate proportions
(by weight and volume) of the various components; and determine the PCB
concentrations in each component;
5. Determine the average PCB levels in ferrous and nonferrous metallic shredder
output;
6. Examine the relationships between categories of shredder input materials and
any contamination concentrations in resulting output material in order to
determine, to the extent possible, which input materials may be the sources of
chemical contaminants in fluff (PCBs, lead, cadmium); and
7. Determine PCB levels in upper soil layer.
1-2
-------
132 Fluff Definitions by Input Stream
(A) White Goods Fluff is the residual of the following:
Regrigerators
Washers
Dryers
Dishwashers
Freezers
Ranges
Air conditioners
Microwaves
Hot water heaters
(B) Automobile Fluff is the residual of the following:
• Passenger cars
• Light trucks
• Vans
• Small school buses
(C) "Other" Fluff is the residual of anything typically shredded that is not "White
Goods" and not "Autos."
133 Pilot Program Implementation: Sampling Phase
The Environmental Protection Agency randomly selected seven shredder sites. Each
of these sites will be visited between December 5 and December 21, 1988, by field teams who will
complete Worksheets to obtain sufficient information to characterize site operations. They will
also obtain samples of fluff product streams.
The field teams will be composed of a team leader from Westat or Battelle, a sampler
from the Midwest Research Institute (MRI) and one representative from the State RCRA office.
Data and samples collected through site visits will be confidential so that they cannot
be linked to the site from which they were taken. Interview data will be tabulated and analyzed by
Westat Fluff samples will be analyzed in MRI laboratories.
1-3
-------
1.4 The Role of the States
This section addresses the role of State personnel in communication efforts that occur
prior to site visits and the collection of fluff samples. Communication efforts rely on the active
involvement of several State government agencies. Specifically, States will contact site owners and
provide information about the FTP.
1.5 The Role of the Institute of Scrap Recycling Industries
The Institute of Scrap Recycling Industries (ISRI) has assisted EPA by providing a
current list of its membership from which study sites were selected. ISRI wfll also send a letter or
place telephone calls urging sites to cooperate in the pilot program.
1.6 Outline of Site Visit
At least a week prior to the visit, the site owner or operator will be called to
determine that the site will be operating during the day of the field visit If the site will be
operating, an appointment with a responsible individual who is knowledgeable about site
operations, and will assist in identifying fluff material for sampling, will be scheduled. At the time
of the call, permission to sample fluff at the site will be obtained.
Upon arrival at the site, the field team will be introduced and the fluff piles to be
sampled will be selected The team wfll then collect the fluff samples and complete the
Worksheets. If possible, samples wfll be collected from fresh fluff (ideally shredded in front of the
field team). In addition, some stored fluff and metallic (ferrous and non-ferrous) shredder output
will be collected. Soil samples wfll also be collected, if possible. All Worksheets will be reviewed
and edited to be sure that the information collected is complete and legible before leaving the site.
The remainder of this manual covers detailed descriptions of field team activities,
survey procedures and materials needed for the site visits.
1-4
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1.7 Target Sampling Table
The sampling targets are still evolving as additional data become available. Table 1-1
shows the targets based on information available November 29,1988.
1-5
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Table 1-1. Sampling parameters vs. measurement parameters
Table of Sampling Parameters vs Measurement Parameters
Sample
Material
Fresh Fluff
*Auto
* White
* Other
Sub-total
Stored fluff
Discretionary
Ferrous Metal
Non-Fe Metal
Soil
Total /Site
Total /All
* These are case
PCBs
4 ; 5/0; 8/0 Note 1
4 ; 5/0; 8/0 Note 1
4 ; 5/0; 8/0 Note 1
12-0
4
2
2
2
4
26; 24; 22
154-182
Per Site Measurements
Lead Cadmium
same sai
same sai
same sai
12-0 12
Composite Measurements
Lechate Constituent
Analysis
Tie 4/0 1/0
me 4/0 1/0
me 4/0 1/0
-0 12-0 3-0
4 420
2 200
? 700
7 700
4 400
18-26 18
•26 14 3
126-182 126-182 86 21
s where input stream is known
(Maximum)
Total
Buckets
Note 2
Note 2
Note 2
12
4
2
2
2
(Bottles)
22 |
154 |
Note 1 If all 3 types are available, take 12 samples, 4 each,
If 2 types are available, take 10 samples, 5 each
If only 1 type available, take 8 samples of it.
Note 2 If first case above, 12 buckets will be needed.
If second case above, 10 buckets will be needed.
If last case above, 8 buckets will be needed.
Fluffpl2.xls
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2. FIELD TEAM ORGANIZATION
2.1 Introduction
This chapter discusses field team organization and responsibilities including the
assignment of field duties, logistical arrangements, and practicing field procedures. Field team
organization and coordination will assist in ensuring the smooth implementation of field sampling
and interviewing activities. Field team organization is an important factor in how the study is
perceived by site owners and operators. Proper implementation improves cooperation of site
owners and operators.
2.2 Assignment of Field Duties
Sampling and data collection activities for the FPP will require the assembly of field
sampling teams consisting of three individuals. A team involves individuals who have the
qualifications to perform in specific roles and who will be available within the time frame for the
study. To accomplish the collection of fluff samples in an efficient and timely manner, individual
positions or roles in the team will be assigned. These assignments include a Field Team Leader,
two Samplers and a State Coordinator.
22.1 Field Team Leader
The Westat representative is designated as the Field Team Leader and is responsible
for overall coordination of sampling and data collection activities. This role includes preparation,
mobilization, sampling, completing Worksheets, supervising the shipment of samples to the
laboratories, and return of field equipment and completed forms and Worksheets after all the site
assignments have been completed. The Field Team Leader will also be responsible for monitoring
all activities affecting the quality of information generated by the sampling efforts. Additional
2-1
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activities, designed to ensure a good team relationship and maximum cooperation of site
personnel, and assigned to the Field Team Leader are:
• Introduction of field team personnel to site owners and operators;
• Explanation of sampling activities to site personnel including reviewing the
study's purpose and explaining sampling procedures; and
• Supervision of completion of Worksheets by the field team.
The Field Team Leader will also be responsible for several activities related to data
collection including:
• Review and preparation of Worksheets used for interviewing prior to the visit;
• Review and edit of all completed Worksheets; and,
• Returning all completed Worksheets and other interviewing materials to
Westat
2.2.2 Samplers
The MRI representatives will be designated as the Samplers. The Samplers are
responsible for collecting samples, taking field measurements, shipment of samples to the
laboratories and documenting sampling activities. Activities assigned to the Samplers are:
• Coordinating the sampling effort with the shredder facility owner. This
coordination includes obtaining concurrence on the safety and logistical details
of all sampling at the site.
• Arranging the transport of sampling materials and team personnel to the site.
• Arranging and shipping survey samples. This responsibility includes locating
the shipping office nearest to the site, determining the latest time that samples
can be dropped off for overnight delivery, and ensuring that Sample Tracking
Forms have been completed, that samples have been properly packaged, and
that appropriate shipping papers have been completed for each package of
samples shipped from the site to the designated laboratory.
2-2
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2.23 State Coordinator
The State officials represent the recycling interests of State government. As such,
they potentially enjoy a rapport with shredder operators, and may be useful in gaining the
cooperation of the shredder operators. They have no specifically assigned tasks, other than
facilitation.
23 Training
Prior to implementation of fluff sampling activities, the field team must be trained in
survey sampling and data collection procedures. This manual is the basis of survey sampling
training. Prior to sampling, the field team should review and practice the procedures presented in
this manual
2.4 Points of Contact
Westat has established a toll-free telephone hotline that field personnel should use if
any problems or questions arise. This hotline will be staffed with operators Monday through
Friday during business hours (8:30 to 5:30 EST). The toll-free hotline telephone number is 1-800-
937-8288/"l-800-WESTAT8". Outside of business hours, callers wfll be directed to an electronic
message system.
Summary
This chapter has presented an introduction to field team responsibilities and
organization including the assignment of field duties, logistical arrangements, and procedures.
2-3
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3. SHREDDER FACILITY DATA COLLECTION MATERIALS
3.1 Introduction
This chapter describes the data collection materials that have been developed for the
Fluff Pilot Program. Prior to leaving for site visits, the Team Leader will receive a Field Logbook
and a packet of materials to be completed for each site. The Field Logbook is the primary
reference document for all data collection, recording and sampling for the site visit. It contains
examples of documents and forms needed for sampling and interviewing including the following
documents:
• Team Leader Introduction Form;
• Contact Form;
• Shredder Facility Worksheets;
• Equipment Supply Kit Checklist;
• Final Site Checklist;
• Shipping Confirmation Sheet; and
• Transmittal Sheet.
32 Team Leader Introduction Form
The Team Leader Introduction Form contains a script to be used to confirm or
reschedule the appointment with the shredder site, verify the eligibility of the shredder, and obtain
the respondent's cooperation for the sampling. It also has space to record directions to the
shredder facility site.
3 J Contact Form
The Contact Form is used to document all in-person or telephone contacts with the
representatives of the shredder facility after the initial contact call At the top of the Contact
Form is a Respondent Information Label containing the name(s), address and telephone number
3-1
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of the presumed respondent. The label also contains the shredder facility Identification Number
assigned for this study.
3.4 Shredder Facility Worksheets
The Shredder Facility Worksheets are to be completed for each site by the Team
Leader in consultation with the Sampler. The Worksheets are used to record information
regarding the shredder facility area, its topography, features, equipment and any additional
comments noted by the team that may enhance interpretation of the samples. Space is provided
for the addition of site specific notes and sketches of the site.
3.4.1 Worksheet 1. Shredder Facility Description
Worksheet 1 is used to identify the name and location of the site. One copy of
Worksheet 1 must be completed for each site.
3.42 Worksheet 2. Shredder Description and Diagram
Worksheet 2 is used to document the number of shredders at the site, the number of
operating shredders, as well as the number and types of waste streams leaving the shredder(s). It
also provides for manufacturer's data and a diagram. One copy (2 sheets) of Worksheet 2 must be
completed for each site.
3.4 J Worksheet 3. Sketch of Area
Worksheet 3 is self explanatory. One copy of Worksheet 3 must be completed for
each site.
3-2
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3.4.4 Worksheet 4. Product Stream Description
-Worksheet 4 is used to document the characteristics of each product stream from a
single shredder from which samples are to be taken. One copy of Worksheet 4 must be completed
for each product stream sampled at the site.
3.4.5 Worksheet 5. Sample Options
Worksheet 5 describes the options established for sampling.
3.4.6 Worksheet 6. Sample Description, Non-Soil
Worksheet 6 is used to describe the shredder, transect, product stream, procedure,
and input of the fluff that was sampled. One copy of Worksheet 6 must be completed for each
sample taken at the site.
3.4.7 Worksheet?. Soil Sample Description
Worksheet 7 is used to describe the soil sample and its location. One copy of
Worksheet 7 must be completed for each sample taken at the site.
3.4.8 Worksheet 8. Shredder Sampling Suggestions
Worksheet 8 is self explanatory. One copy of Worksheet 8 must be completed for
each site.
3.4.9 Worksheet 9. Recognizance
Worksheet 9 records owner/operator's comments on operations and trends.
3-3
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3.4.10 Worksheet 10. Shredder Sampling Suggestions
Worksheet 10 asks for recommendations and suggestions on the sampling procedures.
3.4.11 Worksheet 11. Team Closure
Worksheet 11 is used to identify the name of the contact person, and the names of the
team members. It is also used to record the date and time of the visit One copy of Worksheet 11
must be completed for each site.
3.5 Equipment Supply Kit Checklist
The Equipment Supply Kit Checklist is a form used to ensure that the field team has
all the equipment and materials needed to sample.
3.6 Final Site Checklist
The Final Site Checklist is a form used to ensure that all sampling tasks have been
completed before leaving the shredder facility site and that all shipping tasks have been completed
before leaving the shipping office.
3.7 Shipping Confirmation Sheet
The Shipping Confirmation Sheet is a reference guide to use when making the
verification phone call to the Fluff Pilot Program tracking system after completion of sampling
activities.
3-4
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3.8 Transmittal Sheet
The Transmittal Sheet is a form used as a packing slip for the return of completed
questionnaires and forms.
3.9 Summary
This chapter has presented basic information about the data collection and sampling
materials assembled in the Field Logbook. The next chapter discusses general instructions for the
site visit
3-5
-------
4. GENERAL INSTRUCTIONS FOR THE SITE VISIT
4.1 Introduction
This chapter contains general instructions for collecting fluff product stream samples.
It includes a discussion of health and safety, quality control in the field, and responses to
commonly asked questions.
4.2 Health and Safety
Field teams should be aware of potential hazards at shredder facility sites. These
include moving trucks, trains, fork-lifts, conveyer belts, and cranes as well as dust, debris and
chemicals in the fluff itself. You should ask the owner or operator to point out areas where it
would be too dangerous for you to visit. Hard hats, gloves and face masks should be worn at all
times while you are working in operational areas.
Should an accident occur, immediately contact emergency rescue units in the area so
that the victim can receive medical attention. After the victim has received medical attention, and
has been treated, contact the Westat coordinator to report the accident.
43 Quality Assurance and Quality Control (QA/QC)
Since one of the objectives of this part of the pilot is to test field sampling procedures,
it is important that the procedures be followed. It is also important that field teams refer any
suggestions about modifications to the procedures to the Project Director before implementing
them. Any breakdown in the strict adherence to the procedures described in this manual could
undermine the conclusions of the pilot program.
The field team will be responsible for ensuring that the field sampling collection
procedures are being properly conducted by performing their own QA/QC review. To implement
this requirement, each team member should check the other's work before leaving the site. Check
4-1
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the data collection forms to see that they have been completely filled out, and make sure that the
information on the labels corresponds to the information on the Worksheet.
4.4 Communications
4.4.1 Initial Contacts with Shredder Facilities
Initial contact with shredder facilities will be made by telephone and/or introductory
letter by Westat The shredder facility will also receive a letter explaining the program from the
ISRI and from EPA. You will have copies of the introductory letters in your Field Logbook.
State RCRA offices will have been informed through the EPA Regional Offices of the
purpose and timing of the Fluff Pilot Program site visits. State personnel will be involved in
planning and conducting preliminary communications activities with the shredder facility sites
selected for the pilot program. In addition, a State coordinator may accompany you on the site
visit. You will have the names and telephone numbers of both State and Regional officials in your
Field Logbook should you need their assistance.
Questions from third parties should be referred to EPA Headquarters. The contact
there is Cindy Stroup at (202) 382-3886.
4.4.2 Scheduling Interview and Sample Collection Date
The sampling schedule has been developed by EPA and has been shared with the
States. Each shredder facility has agreed to an appointment and a back-up appointment. Both
appointments have been scheduled for days on which the machinery wfll be operating.
Each facility has also defined arrangements if either party needs to reschedule or
cancel the appointment. Should the site need to cancel or reschedule, the shredder operator will
telephone the Westat coordinator. Should severe weather occur, you must confirm that the facility
will be operating before you set out for the site. You must relay any schedule changes through the
Westat coordinator. -
4-2
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4.43 Communications During Field Sampling
Before you go into the field, you should be prepared to respond to questions about
the study. In most cases the questions will be straightforward and relate to the technical purposes
of the sampling. You should answer these questions dearly and briefly, using non-technical terms.
Although in most cases the introduction is all you will need to gain the respondent's
cooperation, there will be times when you will have to answer questions before you begin. Keep
this in mind: questions mean that the respondent is interested and concerned. You need to be
prepared to answer in ways that respond to that interest and concern.
Listen to the respondent's questions, and answer by providing only the information
needed to handle the specific question posed. Make your answers brief and to the point. Do not
volunteer extra information or unnecessarily lengthy explanations because the unasked
information may be misunderstood and confusing to the respondent.
4.4.4 Commonly Asked Questions
The following is a list of commonly asked questions and appropriate responses. Use
the supplemental text in parentheses only if the respondent is not satisfied.
1. Who is sponsoring this study?
The United States Environmental Protection Agency.
(Specifically the Office of Toxic Substances and the Office of Solid Waste and
Emergency Response)
2. Why is EPA conducting this study?
The purpose of the study is to learn more about fluff product streams generated
by shredder facilities.
4-3
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3. Why did you select this facility?
This site was randomly selected as part of a sample of all shredder facilities in
the United States.
(The selection of this site does not mean the EPA knows or suspects that the
site has toxic or hazardous chemicals.)
4. How did you get this company's name and address?
Your name and address were given to EPA by ISRI which is supporting the
study.
5. Am I required to participate (answer your questions)?
No, your participation is strictly voluntary. However, your participation is very
important This site represents other shredders throughout the United States,
and the answers you supply are very important to the success of this research.
How long will this interview (sampling) take?
The interview will take about 30 minutes; the sampling will take about two to
four hours. However, after you have given us information on how the shredder
operates, you may choose to accompany us or not, as you prefer, for the
sampling.
7. What will you do with the information?
The information will be used for an analysis of the levels and sources of
chemical contaminants in fluff material
8. Are you going to send me the results?
If you (the owner of this facility) would like a copy of the results, you/your
owner can sign and have notarized this request form and we will mail the results
in four to six weeks.
9. What if you do find pollutants in my fluff?
The measurements will become part of the analysis of the magnitude of the
problem, nationwide.
4-4
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10. Who can I call to verify that you are a legitimate representative of EPA?
You may call Cindy Stroup at (202) 382-3886 or Dan Reinhart at
(202) 382-3585, in the Headquarters of the Environmental Protection Agency,
Washington, DC.
4.5 Summary
Chapter 4 has provided general instructions for the site visit. Chapter 5 provides
specific instructions for completing the Worksheets and Chapter 6 contains instructions for taking
samples of fluff and other shredder materials.
4-5
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FLUFF PILOT PROGRAM
Team Leader Introduction Form
Good Morning, I'm of
We are working under contract with the Environmental Protection Agency. Our project is
collecting materials samples from shredders for analysis of toxic materials. May I speak to the
manager?
Their Response
Our Response: I wish to confirm/reschedule our appointment with your facility. I also wish to
confirm that you are still operating.
Their Response
Our Response: We would also like directions to your facility from our hotel at
Their Response: Directions are
-------
FLUFF PILOT PROGRAM
Contact Form
Contact #1
Name
They/we initiated contact
Contact #2
Name
They/we initiated contact
Contact #3
Name
They/we initiated contact
-------
Sheet of
Date
FLUFF PILOT PROGRAM
Shipping Confirmation Sheet
Site Number
Sample Identification Shipping Document Numbers
-------
FLUFF PILOT PROGRAM
Equipment Supply Kit Check List
1.
Sample Container
Matrix
Fluff (New and Old)
Metals (Fe and NonFe)
Soil
Other
Number
18
4
5
2
Container
5-gal pail
5-gal pail
32-oz jar (wide mouth)
5-gal pail
2.
3.
Sampling Tools
• 4 trowels
• 4 disposable 10 x 10-cm templates
Safety Equipment .
• 1 box latex gloves
• 4 pairs cotton gloves
• 2 pairs safety eye glasses
4.
Labels
30 barcode sample label pairs
30 information labels
4 shipping boxes
4 return Federal Express shipping labels
5.
Packing Supplies
2 rolls duct tape
2 rolls strapping tape
1 razor blade box knife
1 pair scissors
1 roll cellophane tape and dispenser
6.
Support Materials
• 1 lab notebook that contains sample inventory sheets
• 3 black ink pens
• 3 glass marking pens
• 2 large trash bags
-------
1. Worksheet 1
2. Worksheet 2
3. Worksheet 3
4. Worksheet 4
5. Worksheet 5
6. Worksheet 6
7. Worksheet 7
8. Worksheet 8
9. Worksheet 9
10. Worksheet 10
11. Worksheet 11
FLUFF PILOT PROGRAM
Final Site Checklist
Part I Shredder Site
Target = 1
Target = 1
Target = 1
Target = Several
Target = Several
Target = Many
Target = 4
Target = 1
Target = 1
Target = 1
Target = 1
TOTAL
copy
copy
copy
copies
copies
copies
copies
copy
copy
copy
copy
Part H Shipping Site
1.
2.
Ship Samples, number equals sum (6) and (7) combined.
List Facility Number, Transect Number, Sample Number for non-soil Samples. List
Facility Number and Sample Number for soil samples.
-------
FLUFF PILOT PROGRAM
Transmitted Sheet
1. Worksheet 1 Target = 1 copy
2. Worksheet 2 Target = 1 copy
3. Worksheet 3 Target = 1 copy
4. Worksheet 4 Target = Several copies
5. Worksheet 5 Target = Several copies
6. Worksheet 6 Target = Many copies
7. Worksheet 7 Target = 4 copies
8. Worksheet 8 Target = 1 copy
9. Worksheet 9 Target = 1 copy
10. Worksheet 10 Target = 1 copy
11. Worksheet 11 Target = 1 copy
TOTAL
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Questions for Shredder Facility Operator
Check List
This check list identifies Worksheet questions that involve information you may need to obtain from the
facility operator or information that may require the collaboration of the operator. Before leaving the
site, compare the check list and your Worksheets to ensure that you have asked the operator all the
questions that require his/her knowledge of the facility. N/A means that there are no operator
questions on the Worksheet.
Worksheet 1. Shredder Facility Description
1.1
12
1.3
1.4
Worksheet 2. Shredder Description
2J
2.4
2.5
2.6
2.7
Worksheets. Sketch of Area
Worksheet 4. Product Stream Description
4.1
43
4.4
45
4.6
Worksheet 5. Sample Options
5.1
52
Worksheet 6. Sample Description: Non-soil
6.1
63
6.4
6.5
6.7
Worksheet 7. Soil Sample Description
N/A
Worksheet 8. General Observations
N/A
-------
Worksheet 9. Recognizance
9.1
92
93
9.4
9.5
Worksheet 10. Shredder Sampling Suggestions
10.1
Worksheet 11. Team Closure
11.1
112
113
11.4
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Chapter 5.
Fluff Pilot Program
Worksheets 1-9
and
Question by Question Instructions
5-1
-------
Worksheet 1. Shredder Facility Description
1.1 Location of Shredder Facility
Shredder Facility Name:
Address:
P.O. Box:
City: State: ZIP Code:
1.2 Shredder Facility Contact
Name(s):
Trtie(s):
Phone number (
1.3 Does the operator have a sheet(s) that describes accepted or forbidden materials?
Yes ED Go to 1.4
No End
1.4 Describe sheets and attach copies.
Complete a copy of Worksheet 1 for each site.
-------
Question by Question Instructions
Worksheet 1.
1.1 Enter the location of the Shredder Facility. Record mailing address, and also
common name address if applicable, ie., "Corner Route 40 and State Line Road"
1.2 Enter the name of the Shredder Facility Contact. Names of principal contacts.
1J Look for and inquire as to the availability of such materials.
1.4 Attach handwritten or xerox copies of the materials.
-------
Worksheet 2. Shredder Description
Shredder Facility Number:
2.1 Number of Shredders at the site:
DD
2.2 Number of Operating Shredders at the site:
U
Answer the questions below to describe the operation of one shredder at the site. Choose the shredder
to be described by the following rules: if there are multiple shredders, randomly choose one from which a
fluff sample can be taken; if no fresh fluff samples can be taken, randomly choose an operating shredder;
if there are no operating shredders, randomly choose any shredder present
2.3
2.4
There will probably be several distinct product streams leaving the shredder machine and
associated equipment, for example, ferrous metal, non-ferrous metal, fluff, waste water, or other
product streams.
Enter the total number of product streams leaving the shredder
In the list below, describe each product stream in a way which uniquely identifies it Use one line
per product stream. The letter at the left of each line will be used to identify the product stream on
other worksheets.
Product
Stream
Letter
Product Stream Description and Location
FSH1
FSH2
FM
NF
01
02
(Fresh Fluff-1)
(Fresh Fluff-2)
(Ferrous Metal)
(Non-Ferrous Metal)
(Other-1)
(Other-2)
Complete a copy of Worksheet 4 for each fluff and metal product stream.
-------
Question by Question Instructions
Worksheet 2.
Shredder Facility Number. This number will be assigned by MRI, prior to the site
visit and will be used throughout a particular site visit. It will be receded later by MRI
to preserve confidentiality for the survey.
2.1 Number of Shredders at the site: Enter total number of shredders, regardless of
status.
22 Number of Operating Shredders at the site: The number that are in fact processing
goods at the time of the visit.
23 Number of product streams leaving the shredder. This is the number of separate
streams of a product, including waste water if applicable, that are leaving the
shredder. This pilot project has no provision for collection of waste water.
2.4 Product Stream Description and Location. Describe the various product streams in
terms of ferrous metals, non-ferrous metals, fluff, waste water, and any other. If
several streams of one type, but slightly different characteristics exist, indicate this, for
example, large ferrous and small ferrous. Define "large" or "small" in inches. There
may be more than one fresh fluff stream.
-------
Worksheet 2. Shredder Description (continued)
Diagram
Diagram the Shredder, using terminology from the enclosed sketch.
2.5 What is the Manufacturer's Name: | | Don't Know
2.6 What is the Manufacturer's Model Designation: | | Don't Know
2.7 Diagram of Shredder
-------
Question by Question Instructions
Worksheet 2. (continued)
2.5 Manufacturer's Name: If the manufacturer's name is visible in a safely obtainable
location record it, otherwise, inquire of the facility personnel
2.6 Enter Manufacturer's Model Designation in the space provided: Attempt to obtain
this data from the manager, if it is not readily visible on the machinery name plate.
2.7 Sketch. Indicate the input stream, or streams, and each output stream. Show
elevation of key points, i.e., input hopper is 18' from ground, etc. Please be as
complete as time allows.
-------
Worksheet 3. Sketch of Area
Shredder Facility Number
Sketch the area that surrounds the shredder. Indicate access, slope direction, if any, and significant
features. Property boundaries should touch two sides, and fill most of tf?e allotted space. Indicate an
approximate scale.
-------
Question by Question Instructions
Worksheet 3.
Sketch the area.
Shredder should be about 10% of the area, for scaling purposes.
Show vehicle entry, exits, railroads, if any, major storage areas, major buildings, etc.
Also show creeks and bodies of water.
-------
Worksheet 4. Product Stream Description
Complete one copy of Worksheet 4 for each product stream.
Shredder Facility Number: | | [
Product Stream Letter (from Worksheet 2): | j
All questions below about the product stream refer to the shredder described in Worksheet 2 and the
product stream designated above. Use additional copies of Worksheet 4 for questions about other
product streams from this shredder.
4.1 Was the shredder producing material from the product stream during the visit? (Check one box)
Yes | | Go to Q 4.2
No [""] Go to Q 4.3
4.2 During operation of the shredder, the product material may be deposited on the product pile at a
constant rate or a variable rate. Check the one box that best describes the rate at which the
material arrives at the product pile.
(a) Material is deposited at a constant rate | |
(b) Material is continuously deposited but at a variable rate | __J
(c) Intermittent rate, there are alternating periods of no deposit and significant deposit [ ]
4.3 Do specific constituents of the product stream fall off the conveyor belts (spfllover)?
Yes | | Go to Q 4.4
No I I Go to Q 4.5
Not Applicable | | Go to Q 4.5
4.4 If yes, describe how this occurs, i.e., does it occur selectively according to size of the particles or some
other way?
4.5 Do the large and small items behave differently on the product pile, for instance, do the large pieces
roll to the bottom of the pile and the small pieces stay on the top?
Yes
No
Not Applicable
4.6 Describe how the large and small fluff particles behave differently at the fluff pile:
Go to Q 4.6
End
End
-------
Question by Question Instructions
Worksheet 4.
Shredder Facility Number: Enter the shredder facility number.
Enter the Product Stream Letter (from Worksheet 2): Carefully match the Product
Stream Description sheets with the Product Stream letters from Worksheet 2.
4J. Was the shredder producing material? Check "Yes" if the shredder was producing
material during your visit Otherwise, check "No."
Constant Rate: Material was coming out without more than 3 seconds elapsing with
no product exiting.
4.2.2 Variable Rate: Material was coming out more or less continuously, but with intervals
of more than 3 seconds with no product exiting.
423 Intermittent Rate: Periods of no deposit exceed 30 seconds.
43 Is there "spillover"? Where in the processing?
4.4 Description of the spillover process. Free form description of the spillover process.
4.5 Differences in large item and small item behavior? Base this on actual observations
of movement.
4.6 Description of the differences, product piles: Enter a free form description of the
differences.
-------
Worksheet 5. Sample Options
Shredder Facility Number:
5.1
Describe the option established for sampling. Use the option identification on Worksheet 6.
Options available:
Sample Option
FP1.FF2.FF3
OF1.OF2
ME
S01.S02
Title
Fresh Ruff 1,2, or 3
Old Ruff 1 or2
Metals
Soils 1 or 2
Sample Option
Title
TOTAL
Number of Samples
-------
Question by Question Instructions
Worksheet 5.
5.1 Describe the Sample Options. Total number of samples should balance for entire site.
-------
Worksheet 5. Sample Options (continued)
5.2 If you used a Sample Option ending with a 2 or 3, briefly explain why:
Sample Option
Explanation
-------
Question by Question Instructions
Worksheet 5.
S3. Explain factors in Sample Options. Insight into why that particular decision was made
will be very useful in the design of potential follow-on efforts.
-------
Affix, barcode
here
Worksheet 6. Sample Description, Non-soil
Shredder Facility Number: | |
Sample Option: | | |
Sample Number: |
6.1 Please describe the material sampled (check one box).
Fresh fluff (Ruff shredded in the last 8 hours) (1)
Stored fluff (2) F""1
Ferrous metals (3) | |
Non-Ferrous metal (4) [ |
Spillover (5)
6.2 Sample Option title
6.3 How did you estimate the input mix? (Check one box)
Observation of items entering shredder (1) | | Go to 6.4
Reports from operators of the shredder facility (2) | | Go to 6.4
No information available (3) | | Go to 6.5
Complete one copy of Worksheet 6 for each bucket collected.
-------
Question by Question Instructions
Worksheet 6.
Enter the Shredder Facility Number, Sample Option, and Sample Number.
Coordinate these numbers with MRI person.
If processing White Goods, our first priority is getting separate runs first with
capacitors removed and second with capacitors not removed. Clearly label.
6.1 Method of determining the input mix. Enter method used, if applicable. Check (1)
only if shredder is actually in operation.
62 Describe the Sample Option title to match Sample Option code.
63 How you estimated the input mix.
-------
Worksheet 6. Sample Description, Non-soil (continued)
6.4 List exactly what went into the shredder that resulted in the fluff materials that you collected, if
possible.*
Shradd* input urns
Whte goods
Nan*
Tramd?
How?
Wl?
Oiyn
Rang«
HatwMsr
Other.
AuuxnooMs
Nam
PanaflQaT CV3
UgrttnicJa
Vans
Siral aetaal bus
Otfisr.9safy
folium
TreaM?
Ho«^?
wt?
%wt?
OttMr
H*m»
COIMUUClkJII RISttttlMlS
Fumnn
OO*r.soK*f
fat torn
Jnuetf?
Ho*fi
Wl?
%Wl?
Complete all information In this table if it is available (Le., the weights may not always be attainable, the
percentage can be computed after the fact). Fresh fluff samples will be typically of only one type of
input materials, so only one table will be filled out Always record the total number of items and the
weight when it is known. For "stored" fluff, record information to the best of your ability, probably
relying on facility operator for source information.
-------
Question by Question Instructions
Worksheet 6. (continued)
6.4 Review each of the three tables: white goods, automobiles and other. List exactly
what went into the shredder and fill in the information across the row. Ask the facility
operator what went into the shredder if the fluff has been "stored." You may use all
three tables or only one. Percentage can only be calculated after totals are known.
-------
Worksheet 6. Sample Description, Non-soil (continued)
6.5 Age of the materials. Enter the time since the sample material was shredded.
minutes j | | hours | | | days
months
Don't Know
6.6 Collection Time. Time from when the sampling staff entered the shredder site until when the sample
was collected (expressed as Hrs:Min).
Hrs.
•
~Min7
6.7 Expand on treatment of goods, if additional comments are deemed appropriate.
-------
Question by Question Instructions
Worksheet 6. (continued)
Age of the material Enter the single smallest unit
6.6 Time from entering site until collection: (Hours:Minutes)
Enter the approximate time that has elapsed from site entry to collection of this
sample.
6.7 If space does not allow adequate explanation of the treatment, expand on that here.
-------
Worksheet 7. Soil Sample Description
Affix barcode
here
Shredder Facility Number I T
Sample Option: I T
Sample Number
7.1 Was the sample taken at the product stream or away from it? (1) Q At the product
stream
•—- Go to 7.4
(2) | I Away from it
7.2 If away, how far? feet
7.3 If away, in what direction? N NE E SE S SW W NW
7.4 How deep did you go to hit 50% soil?
7.5 Was the sample taken up slope, down slope, or level relative to the fluff pile?
(1) Up slope
(2) | I Down slope
(3) Level
7.6 Mark sketch in Worksheet 2 with barcode number.
7.7 How was it taken?
Heavy equipment assistance [[[ (1 ) J I
-------
Question by Question Instructions
Worksheet 7.
Enter the Shredder Facility Number, Sample Option, and Sample Number;
coordinate with MRI person.
7.1 Enter the requested data.
72 If away, how far? Measure from edge of fluff pile.
73 If away, in what direction? Indicate direction by octants (North, Northeast, East, etc).
If it's a cloudy day, ask for assistance.
7.4 How deep? This may be the most judgmental issue the sample team will face.
Preliminary reports indicate a layer of decayed fluff may exist. The intent is to locate
the interface where a 50-50 mix of fluff and soil exists, within the limitations of hand
tools. Do not attempt to go more than 2 spade depths with the hand tools.
7.5 Was it up slope, down slope, or level relative to the fluff pile? Self explanatory.
7.6 Put a reference to the barcode number of the soil sample on sketch 2.
7.7 Enter the method used to obtain the soil sample.
-------
Worksheet 8. General Observations
Shredder Facility Number
Sample Number
8.1 Please record any general observations that would assist in the interpretation of the results.
-------
Question by Question Instructions
Worksheet 8.
8.1 Your thoughts on general matters will assist future survey design.
-------
Worksheet 9. Recognizance
Shredder Facility Number
9.1 Owner/operator characterization of types of materials processed over past year, 5 years, 10 years.
Any changes as result of "White Goods Scare?'
9.1.1 Year!
9.1.2 5 Years
9.1.3 10 Years
9.2 How have operations changed over past year?
9.3 Precipitation. Describe:
9.3.1 Past 24 hours,
9.3.2 Past 48 hours.
9.3.3 Past 30 days_
9.4 Ruff storage.
9.4.1 Have you stored fluff on the ground over the past 1 -5 years?
Yes
No
9.4.2 How often is it removed, on average?
D
9.4.3 Where do you dispose of fluff?
Municipal Landfill?
Hazardous Landfill?
Scrap Dealer?
Other?
-------
Question by Question Instructions
Worksheet 9.
Enter Shredder Facility Number.
9.1 Enter owner's comments on operations and trends. Emphasis on response to "White
Goods Scare."
92 Note any recent trends.
93 Ascertain precipitation from newspapers, other media or weather bureau inquiry.
9.4 Goal is determining an average storage time, and also requests specific data.
-------
Worksheet 9. Recognizance (continued)
9.5 Processing volumes.
9.5.1 Volumes processed
Material
Ferrous
Non-Ferrous
Ruff
Weekly
Monthly
Annual
-------
Question by Question Instructions
Worksheet 9. (continued)
9.5 Obtain a measure of volume processed Weekly, monthly, annual measures are to be
level peaks that might stand out in someone's memory.
-------
Worksheet 10. Shredder Sampling Suggestions
Shredder Facility Number I I
10.1 Based on your experience in collecting this sample and your knowledge of the operation at
shredder facilities, please make suggestions and recommendations for a written procedure for
sampling fluff as it leaves the shredder and associated equipment. Any suggestions are welcome,
including: gaining access to the site and shredder area, necessary equipment for sampling the fluff
product stream, procedures for collecting samples of different sizes, handling and packaging of the
samples for shipment to a lab.
-------
Question by Question Instructions
Worksheet 10
Enter Shredder Facility Number. See Worksheet 2.
10.1 Suggestions. Please comment on the sampling procedures. This is your opportunity
to make constructive criticisms, suggestions and recommendations. •
-------
Worksheet 11. Team Closure
11.1 Sample collected by:
Name:
Title:
Address:
City:
State:
ZIP Code:
Phone number ( )
11.2 Date of the site visit:
Mo Day Yr
11.3 Time of the site visit: From
AM
PM
AM
PM
to
11.4 Contact record
Date completed
Completed by
-------
Question by Question Instructions
Worksheet 11.
Enter Shredder Facility Number.
11.1 Sample collected by: Enter the name of the Midwest Research Institute person(s)
and their local address.
Enter the date of the initial site visit
113 Time of site visit: use local time, start with arrival time.
11.4 Record any significant comments relating to the discussions which were held with the
manager(s) of the shredder site.
Enter the date Worksheet completed. Should be same as date of site visit.
Enter the Westat or Battelle Team Leader's name who completed the Worksheets.
-------
6. FIELD SAMPLING
6.1 Introduction
This chapter, provided by Midwest Research Institute (MRI), provides guidance to
personnel responsible for on-site collection on fluff, ferrous and nonferrous metals, and soil at
shredder plants.
In addition, these recommendations list the safety and collection equipment needed,
the collection procedures, on-site material storage procedures, and shipping procedures. Details
of material collection locations will be provided in the sampling design.
63 Safety
Each Sampler must arrive at the site with the following safety equipment: steel-toed
shoes, hard hat, hearing protection, safety glasses and gloves. The sampling kit will contain
additional gloves and goggles. This safety equipment must be worn while on the site.
Samplers must obey ail company safety regulations.
63 Sampling Equipment
Sampling kits will be provided for each site. The Sampler is responsible for picking up
these kits from the designated carrier office. Equipment included in the sampling kit is presented
in Table 6-1.
6-1
-------
Table 6-1. Field Sampling Equipment
Sample Container
Fluff (New and Old)
Metals (Fe and NonFe)
Soil
Other
Number Container
18 5-gal pafl
4 5-gal pafl
5 32-oz jar (wide mouth)
2 5-gal pafl
Sampling Tools
4 trowels
4 disposable 10 x 10-cm templates
2tarps
Safety Equipment
• 1 box latex gloves
• 4 pairs cotton gloves
• 2 pairs safety eye glasses
Labels
25 barcode sample label pairs
25 information labels
4 shipping boxes
4 return Federal Express shipping labels
Packing Supplies
2 rolls duct tape
2 rolls strapping tape
1 razor blade box knife
1 pair scissors
1 roll cellophane tape and dispenser
6. Support Materials
1 lab notebook that contains sample inventory sheets
3 black ink pens
3 glass marking pens
2 large trash bags
6-2
-------
6.4 Sample Collection and Handling
6.4.1 Collection Procedures
Collection Procedures for Fluff and Metals
(1) Locate the designated sampling location.
(2) Fill the 5-gallon pafl with fluff or metal scrap.
(3) Replace the lid to the 5-gallon pail Secure the lid with the hammer provided in
the kit
(4) Affix a barcode label securely to the pafl. Also, place the information label on
the pail with the required information.
(5) Affix the mate of the barcode label number used in Step 4 to the Sample
Inventory Log and complete with the information requested. Use the notebook
to briefly describe the sample and location.
Collection Procedures for Soil
(1) Locate the designated collection location.
(2) Place the template over the collection area.
(3) Using a spade, locate the soil/old fluff interface. Stop if not found at 2 spade
depths.
(4) Using a trowel, dig out the sample to an approximate 10-cm depth.
(5) Remove the lid of the 32-ounce jar and place on a plastic sheet.
(6) Transfer the soil to the jar and replace the lid of the jar.
(7) Close the jar securely. Affix tape to the lid and the jar to prevent the lid from
unscrewing during shipment. Encase the jar in bubble wrap for shipping.
(8) Affix a barcode label securely to the container. Also, place the information
label on the jar with all the required information.
(9) Place the jars in the same 5-gallon pafl in which they were received.
(10) Affix the mate of the barcode label number used in Step 7 to the Sample
Inventory Log and complete the information requested. Store the 5-gallon
container of jars in the shipping box.
6-3
-------
6.4.2
Documentation
Each sampling kit is provided with a notebook and sample inventory logs. Two type
of labels will be provided for sample identification, pairs of barcode labels, and information labels.
Information Labels
Site
ate
Time
Location
Sample No.
•f Collector initials label
Samplers wifl affix both types of labels to each pafl or jar containing a sample. The
sample number on the information label will be the same as the barcode.
6A3
Prevention of Contamination
Because of the importance of the sample analysis results to the project, great care
must be exercised in the collection of valid samples. The Sampler must take precautions against
contamination of the samples. For example, all sample collection vessels are cleaned before being
shipped to the field, but they should be visually inspected for any obvious contamination before
taking the sample. The pafl or jar should not be opened until immediately before the material is
taken. Templates are disposal, and trowels are used once and then placed into a plastic bag for
return to MRI with the collected materials.
6-4
-------
6A4 On-Site Material Storage
Collected material should be packaged in the sample boxes or crates in which they
were received. All materials must be maintained in a locked van at all times. Under no
circumstances are the samples to remain on-site overnight or when the Sample are not present.
Normally, the collected material can be stored at ambient temperatures unless otherwise specified.
6J Sample Shipping
After the completion of sampling, the samples should be shipped by UPS or Federal
Express to MRI using the pretyped shipping Labels included in the sampling kit Return any
unused barcode sample labels.
6-5
-------
7. IN-FIELD SAMPLING PROCEDURES
7.1 Introduction
The field sampling procedures described below are intended to produce roughly
representative samples (by volume) of (1) fluff; (2) ferrous metals, and (3) non-ferrous metals. In
addition, (4) grab samples of soil will be obtained. The fluff samples will be obtained both for (a)
fresh fluff, (b) stored fluff, and (c) discretionary fluff (e.gn fluff that spills off a conveyor belt). The
procedures to be used are described below for each sample drawn and for each category of
materials. Special circumstances may require variations from these procedures (see Section 7.2.5).
12 Sampling Procedures
72.1 Fresh Fluff
Three options are given below for sampling fresh fluff. They are listed in order of
preference. For any one type of input product (e.g., cars), use one of the following options and
repeat it as required. (See Table 1-1 for sample sizes.)
Option 1: Get It As It Flows
Obtain site manager agreement to make a continuous run of the desired category of
material (e.g., cars) lasting at least five minutes. As the cyclone (or conveyor) is running, position
a container below the mouth of the cyclone (or conveyor) and collect approximately one gallon of
fluff as it falls. Repeat this procedure five times at equal time intervals. Composite the samples in
a five-gallon bucket
If there are two cyclones (or conveyors) side by side, collect five half-gallon samples
from each in alternating fashion. This is more work and may require a longer run.
The objective is to get a representative sample of fluff by volume. So be careful that
the timing of samples is not in sync with the input of materials. For example, if cars are shredded
7-1
-------
at one-minute intervals, pick a different interval, say every minute and one-half, for sampling. If
the flow of fluff is sporadic and it is difficult to obtain representative samples, use Option 2 below.
CAUTION: Safety is paramount. If you have any doubt about the safety of sampling
fluff as it flows, sample it after it piles up, as described next in Option 2.
Option 2: Get it After it Piles Up
Try to arrange for the operator to shut down the line after shredding at least two cars,
five appliances, or three minutes of other material Take five, one-gallon samples, randomly from
the pile(s) by systematically sampling around the safely accessible parameter of the pile. Take
four, one-gallon samples, one foot off the ground and one, one-gallon sample, mid-way up the pile.
Dig into the pile in order to sample layers of fluff deposited at different times.
If the pile of fresh fluff is not easily and safely accessible, use Option 3.
Option 3: Front End Loader Assisted
Arrange for a front end loader to spread on the ground the output from the shredding
of at least two cars, five appliances, or three minutes of other material. In order to do this, the
front end loader can either (1) position its bucket under the mouth of the cyclone (or conveyor)
during shredding and then spread the fluff on the ground, (2) scoop up the pile of fresh fluff and
then spread it in another location, or (3) spread out the pile of fresh fluff underneath the cyclone
(or conveyor) and then remove it after each sample. A tarp will be used for this purpose and
shaken between samples to remove all observable evidence of fluff.
Have the front-end loader spread out the fluff on the ground to an even depth.
Divide sample into nine roughly equal subsections. Select one-half gallon from the center of each
segment using a shovel and composite the samples in the five-gallon bucket. Figure 7-1 shows
where to take samples under this option.
7-2
-------
Figure 7-1. Top view of grid for sampling fresh fluff under Option 3
7-3
-------
122 Stored Fluff
The goal is to obtain, in order of priority, one composite sample of (a) the oldest fluff,
(b) the deepest fluff, and two composite samples of (c) surface fluff. (If (a) » (b), replace (b) by a
sample halfway between the deepest and the surface.)
A total of four, five-gallon composite samples, are to be taken. To prevent cross-
contamination between five-gallon samples, collect one, five-gallon bucket at a time, before moving
on to the next sample. The following steps are keyed to Figure 7-2.
1. Take five, one-gallon samples, of surface fluff from the edge of pile, one foot off
the ground. Dig straight into the surface but include the actual surface material
in the sample. Composite these five samples in one five-gallon bucket.
2. Use heavy moving equipment to cut five notches in pile for the other samples.
(See diagram.) These notches should be located equidistant along the
perimeter of the pile, if possible. From each notch, take a one-gallon sample
from the deepest fluff in the pile. Composite these five samples in one five-
gallon bucket.
3. Collect five, one-gallon samples, of the oldest fluff and composite them in a
five-gallon bucket. If the deepest fluff is also the oldest fluff, then from each
notch take a one-gallon sample from a point mid-way from the bottom of the
pile and the surface. Composite these five samples in one five-gallon bucket.
4. Collect five, one-gallon samples, of fluff from the surface of the pile at points
near the center of the pile. The notches may provide easy access to points near
the center of the pile. Composite these five samples in one five-gallon bucket.
CAUTION: Safety is paramount. Do not cut notches deeper than five feet. Proceed
with caution at all times.
Metal Samples
Sample as in Section 2.1, Option 2. The procedure is the same for ferrous and non-
ferrous metals. Collect two, five-gallon composite samples, each for ferrous and non-ferrous
metals.
7-4
-------
Figure 7-2. Where to sample stored fluff
7-5
-------
12A Discretionary Fluff
Field teams should inspect the area along the conveyor belt to see if any spillover
materials exist, and to identify their locations. Take five 1-gallon sub samples of the spillover
material along the conveyor belt at approximately equal distances.
These five 1-gallon samples will be composited into one 5-gallon bucket. Repeat one
time to provide enough for a second bucket If it is apparent that the procedure will not work due
to the pattern of spillover deposition, then the team leader will develop an appropriate sampling
method to achieve two 5-gallon samples that are representative of the spillover material.
12JS Soil Grab Samples
Option 1: Soil Near Fluff Can Be Identified
Collect a total of four samples of soil near the pile(s) of stored fluff or where fluff is
typically stored even if on a temporary basis. Collect each sample with a trowel and deposit it in a
quart container. Take samples from material that appear to be at least 50 percent soil
If practical, collect one sample from near the center of the oldest fluff pile. If a notch
has been cut for purposes of sampling stored fluff, this may afford access to the soil underneath the
pile. If the ground underneath the center of the pile is not easily accessible, select a point where a
modest amount of digging will expose the soft. Take the remaining samples at approximately equal
intervals in the downgradient (i.e., downhill) direction. The last sample should be taken near the
edge of the pile. If there is no apparent gradient, sample in a different direction and at varying
distances from the center of the pile with each sample.
Figure 7-3 shows where to take the samples if a notch allows access into the pile.
Option 2: Soil Near Fluff Cannot Be Identified
If it is not possible to determine depths where the material is at least 50 percent soil,
take core samples instead of sampling with the trowel Collect four core samples at points
described in Option 1. Each core should be two to three feet deep, if possible.
7-6
-------
Figure 7-3. Where to sample soU
7-7
-------
Option 3: No Stored Fluff
If there is no stored fluff, then sample soil under hoppers/fresh pile. If concrete pad,
then sample soil at perimeter of pad, at down slope point
12.6 Special Circumstances
It is anticipated that situations encountered at individual sites may vary substantially
(e.g., mix of input products, willingness of site manager to interrupt process, accessibility of piles,
amount of working space available, wet versus dry fluff, etc.). For this reason, the team leader will
customize/adjust the sampling procedure as necessary in order to obtain samples that are as close
to "representative" as possible. Any adjustments to sampling procedures will be carefully
documented.
7 J Sample Labeling
73.1 Objectives of Sample Labeling:
Following the proper procedures in labeling are important to:
a. Provide certainty of identification;
b. Provide for confidentiality through recoding of site and barcode numbers
following receipt of the materials at MRI; and
c. Provide compatibility with standard MRI procedures to the extent practical,
consistent with (a) and (b) above.
7-8
-------
73 J Sample Labeling Procedures
a. One of the set of four barcodes will be placed on each of the following:
(1) Sample container, either bucket or bottle (Side Not Top);
(2) MRI Sample Inventory Sheets;
(3) Westat Worksheets #6 and #7; and
(4) Westat Shipping Confirmation Sheet.
b. Information labels will also be affixed to each sample.
7-9
-------
Appendix 4-B
Confidentiality Plan
4-B-l
-------
August 28. 1989
Confidentiality Plan for Fluff Pilot Program
EPA Contract Number 68-02-4293
Work Assignment Task Number 2-5
Introduction:
In order to obtain the active cooperation of the site owners and managers of
scrap recycling and shredder facilities, these facilities required pledges of confidentiality.
Following Joint EPA-contractor consultations, these pledges were made by:
a. The Environmental Protection Agency, through the November 30. 1988
open letter from Martin P. Halper. Director. Exposure Evaluation
Division. (Enclosure 1).
b. Westat, Inc.. through contracts with the various site owners. (Enclosure
2).
c. Battelle Memorial Institute. Columbus Division, through contracts with
the various site owners. (Enclosure 3).
d. Midwest Research Institute, through contracts with the various site
owners. (Enclosure 4).
The thrust of these pledges was to prevent the chemical analytical results from
being identified with any specific study facility.
-------
Confidentiality Plan:
Steps to date -
The data collection forms were designed with confidentiality in mind. The site
identifier codes which appear on all worksheets were assigned by MRI in a random manner.
The only worksheet that has the facility name is Worksheet 1 which will be separated from the
other worksheets.
Report of site conditions -
A narrative report will be written describing the generation, segregation, and
storage of the shredder materials at the sites visited.. The report will be aggregated and
anonymous in its nature, Le.. "2 sites had concrete throughout, or were built on fill of
unknown origin thus no meaningful soil samples could be obtained". The purpose of this
report will be to add to the agency's knowledge base on fluff characteristics, production
streams and industry practice. This report will be written prior to the generation of any
analytic data, and could be useful in directing the analytical analysis effort's direction, while
maintaining confidentiality.
Laboratory Analytical Results -
When the results of the laboratory analysis are made available to Westat. Inc..
an analysis will be made that covers each of the 7 objectives listed in the Pilot Program
Objectives, (enclosure 5 ). and a micro-data file will be furnished to EPA. This file's site
identifiers would be randomly assigned codes, e.g. site #1, site #2, etc. (see format, enclosure
6).
-------
Further protection of Site Confidentiality:
In addition to removing site Identifiers (Name. Address. Phone Numbers). Westat
has met with the EPA/OTS staff Involved in the Fluff Pilot Program to discuss methods for
preventing Inadvertent identification by other means. In this meeting EPA confirmed that no
additional information from the proposed survey data base (see preliminary draft in enclosure
6) contains information which will enable the identification of a specific site.
List of enclosures:
Enclosure 1:
Enclosure 2:
Enclosure 3:
EPA Letter of November 30. 1988
Confidentiality Agreement. Westat, Inc.and Shredder.
Confidentiality Agreement. Battelle Memorial Institute and
Shredder.
Enclosure 4:
Confidentiality Agreement Midwest Research Institute
and Shredder.
Enclosure 5:
Pilot Program Objectives, extract from FPP Training
Manual.
Enclosure 6:
Fluff File Layout
-------
Enclosure 1
* -*— i UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
V <$ WASHINGTON. DC 20460
^«tf -^
OFFICE OF
fW 30 !~SO
*"^ W
T03QC SUBSTANCES
OPEN T.k"l"pHft TO OWNERS AND MANAGERS OF
SCRAP RECYCIiING AND SHREDDING FACIUTTES
The Environmental Protection Agency (EPA) is conducting a
pilot data collection activity to learn more about the industry
operations, input materials, and output product streams in order
to determine the need for a more comprehensive industry study.
This information is needed to develop any necessary regulations,
designed to allow the continuing of shredding in the most
environmentally sound and cost effective manner. EPA has
received largely anecdotal information indicating that there can
be PCB's and other compounds in the.waste materials, or fluff.
However, very little information is currently available about the
possible sources of these compounds.
We have selected facilities across the country to provide
geographic spread and variety in the materials being studied.
The facilities were selected essentially at random from seven
geographic clusters of shredders. The field teams are comprised
of technical field personnel under contract to the EPA's Office
of Toxic Substances. The members of the teams work for one of
the following contractors: Midwest Research Institute in Kansas
City, Missouri; Westat, Inc. in Rockville, Maryland; or Battelle
Columbus Laboratories in Columbus, Ohio.
The field teams will collect samples of fluff, ferrous
output, non-ferrous output, and soil, as well as other incidental
samples. The samples will be analyzed for PCBs, lead, and
cadmium content. All results will be reported upon request to
the facility owner. The field teams will provide a form for use
in requesting that information.
This effort is being conducted by the Office of Toxic
Substances in collaboration with the Office of Solid Waste and
Emergency Response. It is an information collection activity
(i.e., regulation development and not an enforcement action). We
-------
Enclosure 1 (continued)
will protect the identification of the study participants. The
Agency will not receive, from its contractors, any data
connecting the chemical analytical -results to any specific study
facility.
We appreciate your cooperation very much. If you wish to
speak to someone at EPA about the study, please call Cindy stroup
on 202-382-3886 or Dan Reinhart on 202-382-3585. ThanJc you.
Sincere,
Martin P. Haifcel:, Director
Exposure Evaluation Division
(TS-798)
-------
WE3TAT
Emotovee-Ownea Researcn Carooracion
=9OF)««*«rcneiva • AocKvmv.MO 2OB5C 3123*301 251-1SOO
1. Westat. Inc. (Westat) needs to go on the premises of
. to collect shredder residue samples in order to fulfill its contract with the U.S.
Environmental Protection Agency.
2. Westat hereby agrees that in exchange for permission to allow Mr.
to go on; premises to collect such data, Westat and its employees will not
fjtyfogg to any party outside the >««« c^ndwtfffg the study (Westat, MRL and Battelle) any
information that will enable the identification of samples collected (or any test results or any other
information gleaned from such samples) with facility or
locale where the data and material are collected, except as required by law.
3. In exchange for the agreement by Westat set forth in Paragraph No. 2,
hereby agrees to allow Mr.. to enter upon
and collect shredder residue *amp>«»«
4. This agreement pertains only to the visit scheduled for
WESTAT. INC.
BY: >dfa^^yj- BY:
TTTLE: Vice President * TITLE:
DATE: December 20. 1988 DATE:
-------
Enclosure 3
CONFIDENTIALITY AGREEMENT
1. Battelle Memorial Institute, Columbus Division (Battelle) needs to go on
the premises of
to collect shredder residue samples in order to fulfill its contract
with the U.S. Environmental Protection Agency.
2. Battelle hereby agrees that in exchange for permission to allow
~ to go on premises to collect such data, Battelle
and its employees will not disclose to any party outside the team
conducting the study (HESTAT, MRI, and Battelle) any information that
will enable the identification of the samples collected at (or any
test results or any other information gleaned from such samples) with
facility or locale where the data and material are
collected, except as required by law.
3. In exchange for the agreement by Battelle set forth in Paragraph No. 2,
hereby agrees to allow Or. to enter upon
premises in I and collect shredder residue samples.
4. This agreement pertains only to samples collected on
BATTELLE MEMORIAL INSTITUTE
COLUMBUS DIVISION
BY; /fi ^f S*rt*^+>+~-~- BY:
TITLE/
General Counsel TITLE:
HATE: December 13. 1988 DATE:_
-------
Enclosure 4
CONFIDENTIALITY AGREEMENT
1. Midwest Research Institute (MRI) needs to go on the premises of
, to
collect shredder residue samples in order to fulfill its contract
with the U.S. Environmental Protection Agency.
•
2. MRI hereby agrees that in exchange for T permission to
allow MRI employees to go on premises to collect such
data, MRI and its employees will not disclose to any party
outside the team conducting the study (WESTAT, MRI, and
Battelle) any information that will enable the identification of the
samples collected at (or any test results or any other
information gleaned from such samples) with or the
fadHty or locale where the data and material are
collected, except as required by law.
3. In exchange for the agreement by MRI set forth in Paragraph
No. 2, hereby agrees to allow MRI employees to enter
upon and collect
shredder residue samples.
4. This agreement pertains only to samples collected on
MIDWEST RESEARCH INSTITUTE
By: vA>i«*-W" - By:
Title: Manager. Procurement t Title:
General Services
••^^•^•^•••••^••^^•^^MMIMH^^M^^MI^MBBBH^W ^••^•^^M
Date: December 13. 1988 Date:
-------
Enclosure 5
1J Overview of the Fluff Pilot Program
The 1984 Amendments to the Resource Conservation and Recovery Act authorize
EPA to monitor the disposition of toxic materials. The Agency's efforts to obtain information on
the components of fluff product streams, as generated by shredder facilities in the scrap recycling
industry, indicate that fluff is a highly heterogeneous material that may contain PCB's, lead,
cadmium and other toxic materials. Unfortunately, previous efforts to obtain information on the
components of fluff have provided only limited data. In order to learn more about fluff product
streams, EPA has designed a Fluff Pilot Program in four parts. These are sample collection,
measurement, analysis, and evaluation. This manual addresses the first part of the program:
Sample Collection.
L3J. Pilot Program Objectives
The objectives of the program, on a pilot basis, include gathering samples from which
the following case can be determined:
1. Determine the average total PCB levels in fluff materials;
2. Determine lead and eadmhitn levels in fluff material and determine ieachabiliry
using both standard EP tox and
3. Determine the extractability of PCBs from fM? for use in OTS* risk assessment
(to replace soil-based parameters used in current risk assessment models);
4. Identify the major physical components of fluff material; calculate proportions
(by weight and volume) of the various components; and determine the PCB
concern trstions m
5. Determine the average PCB levels in ferrous and nonferrous metallic shredder
output;
6. Examine the relationships between categories of shredder input materials and
any contamination concentrations in resulting output material in order to
determine, to the extent possible, which input materials may be the sources of
chemical contaminants in fluff (PCBs, lead, cadmium); and
7. Determine PCB levels in upper soil layer.
1-2
-------
Enclosure 6
FILE LAYOUT: FLUFF SAMPLE FILE
8/21/89
Field Name
Site
Sample
SubAvail
Stream
Type
N
N
N
A
Definiti
InType
N
Run
Option
Age
Unit
N
N
A
Time
InSrc
InMix
N
N
Site Number (1-7)
Sample Number (1-27) assigned to each bucket/jar
Number of Subsampies Available
Output Stream:
Bb=blank bucket
Bj=blankjar
re^rcrrous
FF=fresh fluff
Nf=non-fenous
Ru=rubber
So=soil
Spsspillover
S restored
Input Type:
A=autos
B=autos and white goods only
Oother
W=white goods
Code assigned by Westat whose only purpose is to link different
samples collected from the
-------
Appendix 4-C
Letters
4-C-l
-------
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, DC 20460
MOV 3 0 -"3«o
^ U ,v,y^,
TOMC SUBSTANCES
OPEN T.KTTFTj TO OWNERS AND MANAGERS OF
SCRAP RECYCLING AND SHREDDING FACILITIES
The Environmental Protection Agency (EPA) is conducting a
pilot data collection activity to learn more about the industry
operations, input materials, and output product streams in order
to determine the need for a more comprehensive industry study.
This information is needed to develop any necessary regulations,
designed to allow the continuing of shredding in the most
environmentally sound and cost effective manner. EPA has
received largely anecdotal information indicating that there can
be PCB's and other compounds in the.waste materials, or fluff.
However, very little information is currently available about the
possible sources of these compounds.
We have selected facilities across the country to provide
geographic spread and variety in the materials being studied.
The facilities were selected essentially at random from seven
geographic clusters of shredders. The field teams are comprised
of technical field personnel under contract to the EPA's Office
of Toxic Substances. The members of the teams work for one of
the following contractors: Midwest Research Institute in Kansas
City, Missouri; Westat, Inc. in Rockville, Maryland; or Battelle
Columbus Laboratories in Columbus, Ohio.
The field teams will collect samples of fluff, ferrous
output, non-ferrous output, and soil, as well as other incidental
samples. The samples will be analyzed for PCBs, lead, and
cadmium content. All results will be reported upon request to
the facility owner. The field teams will provide a form for use
in requesting that information.
This effort is being conducted by the Office of Toxic
Substances in collaboration with the Office of Solid Waste and
Emergency Response. It is an information collection activity
(i.e., regulation development and not an enforcement action). We
-------
will protect the identification of the study participants. The
Agency will not receive, from its contractors, any data
connecting the chemical analytical results to any specific study
facility.
We appreciate your cooperation very much. If you wish to
speak to someone at EPA about the study, please call Cindy Stroup
on 202-382-3886 or Dan Reinhart on 202-382-3585. Thank you.
Sincere
lurs,
Martin P. Hai^elr, Director
Exposure Evaluation Division
(TS-798)
-------
Institute of Scrap
Recycling
Industries, Inc.
December 6, 1088
OPEN LBTTEH TO I SHI MEMBERS WHO ABB SUBJECTS OF EPA PILOT SHREDDER STUDY
Tilt United States Environmental Protection Agency has advised ISRI of
EPA'i intent to conduct 4 pilot data collection activity at seven shredder
facilities around the country. The ecope and purpose of the study is
described in detail in a letter from EPA's Martin P. Halper to owners and
manager* of shredder facilities dated November 30, 1988. At EPA's
request, ISHI has prepared this letter, which we understand will be
proTided with the EPA November 30 letter to the site operator at the time
EPA's contraotors Tisit the study facility.
ISHI believes that there is potential benefit for the industry In the
conduct of a properly designed study of shredder residue from various
Inputs. We share EPA's stated goal of developing data that will allow the
continuation of shredding in "the most environmentally sound and cost
effective manner."
Ve note that, as a result of concerns presented by ISHI, EPA's open letter
provides written confirmation that the etudy is "an information collection
activity (i.e., regulation development and not an enforcement action)."
EPA represents that all on-slte sampling and subsequent analysis will be
done by employees of three contractors. The open letter says the
contractors will not give EPA any data connecting specific test results to
a given facility.
EPA official! have advised ISHI that the assurances set forth In the open
letter refleot the conourrence of responsible program and enforcement
personnel at EPA headquarters and in the EPA regional offices with
jurisdiction over the study facilities.
In recent discussions with ISHI staff, EPA and its.contractors have
described in more detail the Internal procedures to be used to maintain
anonymity of test results. They have confirmed that no data which could
be used to link speolfio findings to specific facilities will be presented
to EPA and that the contractors will destroy such data as soon as the
anonymous results are reported to EPA.
-------
Page a
In addition, we understand that the contraotore arc prepared to prorlda to
the ilt« owner/operator at the time of the visit a signed confidentiality
agreement ( which I8BZ has not reviewed), binding the contractors not to
dlvulg* to EPA (or, to the maximum lawful extent, to an? third party) data
which would enable EPA or a third party to attribute specific test result*
to a particular facility.
Baatd on th«a« r«pr«i*ntatlon«, I8BI b«ll«T«« that EPA haa taken
rtasonabl* prtoaution* to oak* «ur« that «tudy results do not impact
adrenely on any participating facility.
ISHI did not participate in the deiign of the itudy. Therefore, the
association cannot take a postlon as to ths validity of ths study design
or whether it will ultimately result in information useful to EPA and the
industry. However, in the Interest of continued cooperation between the
Industry and the Agenoy, and in light of BPA's efforts to structure the
study so as to preserve confidentiality of the results, members are
encouraged to assist, to the extent feasible and practicable, BPA's
oontraotors in expedltlously and efficiently oonduoting the planned
sampling activities.
ainoerely,
Bersohel Cutler
Executive Director
-------
Appendix 4-D
Questionnaire Results
from Worksheet 9
4-D-l
-------
Worksheet 9, Recognizance
9.1 Owner / operator characterization of types of materials processed over past year,
five years, ten years. Any Changes as result of "White Goods Scare?"
9.1.1 Yean
Site One No change 75% cars 25% other goods
Site Two Increasing trend to more plastics in automobiles
Site Three Dropped White Goods in May or June
Site Four Few White Goods
Site Five 50% crushed autos, 41% uncrushed autos,
9% loose metals
Site Six No capacitors. Gradually more copper. Same W.G. mix
Site Seven Stopped White Goods absolutely
9.1.2 5 Years
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
No change
Increasing trend to more plastics in automobiles
None
Used to run 50-50 Auto / White Goods,
gone to treatment of fluff fines
86% uncrushed autos, 5% crushed autos. 9% loose metals
No changes
Level
9.1.3 10 Years
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
Missing
Missing
None
Missing
63% uncrushed autos, 27% crushed autos,
9% loose metals / white goods
No changes
Level
-------
9.2 How have operations changed over past year?
Site One Missing
Site Two Upgraded air cleaning system, added wet air scrubber
Site Three Dropped heavy metals to protect shredder
Site Four Strict controls over chemically treated fine fluff, sampled
and tested daily prior to trans-shipment
Site Five New shredder, heavier, mid-September. Results in tripled
volume, more flat cars (from longer distance). Find more
iron mixed in construction material, suppliers not recycling.
Site Six Only goods without capacitors are now accepted.
Site Seven No White Goods, no drums with hazardous labels.
-------
9.3 Precipitation. Describe:
9.3.1 Past 24 hours
9.3.2
9.3.3
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
Past 48 hours
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
Past 30 days
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
less than 0.1" during samp
.3"
none
none
Missing
none
none
Missing
none
none
none
Missing
none
none
Missing
mostly dry
light rain
none, very dry, high winds
Missing
<1/2'
2" two weeks ago, still star
-------
9.4 Fluff Storage.
9.4.1 Have you stored fluff on the ground over the past 1-5 years?
Site One Yes
Site Two Yes
Site Three Yes Short periods, 1-2 months
Site Four Yes
Site Five Yes Fire in 1987
Site Six No. Concrete for several years.
Site Seven Yes
9.4.2 How often is it removed, on average?
Site One Not kept more than 2-3 days
Site Two Not kept more than 2-3 days
Site Three Daily
Site Four Daily
Site Five Daily
Site Six missing
Site Seven One week to one month
9.4.3 Where do you dispose of fluff?
Site One Municipal Landfill
Site Two Municipal Landfill
Site Three Municipal Landfill
Site Four Municipal Landfill
Site Five Missing
Site Six Missing
Site Seven Municipal Landfill
-------
9.5 Processing volumes.
9.5.1 Volumes Processed
Ferrous
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
. Long Tons
Weekly
4800
1800
Monthly
Annual
50,000
70.000
240,000
156,000
90,000
140,000
34.000
%
annual
78%
77%
78%
78%
72%
77%
76%
Non-Ferrous
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
Long Tons
Weekly
246
50
Monthly
Annual
2,200
2.700
12,300
8,000
2.500
2,200
1.600
%
annual
3%
3%
4%
4%
2%
1%
4%
Fluff
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
Long Tons
Weekly
1108
650
Monthly Annual
12,000
18.000
55,400
36,000
32.500
40,000
8,900
%
annual
19%
20%
18%
18%
26%
22%
20%
Totals
Site One
Site Two
Site Three
Site Four
Site Five
Site Six
Site Seven
Long Tons
Weekly
6,154
2,500
Monthly
Annual
64,200
90,700
307,700
200,000
125,000
182.200
44.500
-------
Questionnaire results for Worksheet 9 are summarized here as follows:
Question 9.1 - Owner/operator characterization of types of materials processed over
the past year, five years, ten years. Any changes as result of "White Goods Scare?"
In the 1 year context, five sites reported changes, three had stopped or reduced white
goods, one reported an increasing trend to more plastics in automobiles.
In the 5 year context, four sites reported no changes from 5 years ago to 1 year ago,
one noted the increasing plastics trend, and one had gone to treatment of fluff fines.
In the 10 year ago to 5 year ago context, 3 were missing, and 4 reported no changes.
Question 9.2 - How have operations changed over the past year?
All but one reported some changes, 3 reported changes related to the "White Goods
Scare", 3 reported changes relating to production or maintenance efficiencies.
Question 93 - Precipitation. Describe:
Question 93.1 - Past 24 Hours:
Two sites reported small amounts of participation, .1 and .3 inches.
Question 9.3.2 - Past 48 hours:
All reported none or missing.
-------
Question 9.3.3 - Past 30 days:
One reported 2 inches, two weeks previously, one reported
-------
Appendix 5-A
Total Concentration of PCBs
in ppm by Site, Sample Type
Total Concentration of Lead
(EPTOX Lead) in ppm
by Site, Sample Type
Total Concentration of Cadmium
(EPTOX Cadmium) in ppm
by Site, Sample Type
5-A-l
-------
Total Concentration of PCB s in ppm by Site, Sample Type
Site
Number
1
2
3
4
5
6
7
count
average
stdev
Fresh Ruff
Auto
4.7
62
8
12.05
6.7
72
10
18
1.65
2.8
4.4
34
6.575
32
38
67
14
42
50.5
88
45
64
76.5
210
8.1
8.5
11
13
28
31.78
42.80
White
0.67
12
755
19
21
40
7
82
2725
14
15
86
60
58
67
15
7924
188.66
Mixed
12
80
88
14
65
360
170
300
500
9
176.56
172.00
Spillover
Ruff
4.8
4
28
38
65
5
27.96
25.41
Stored
Ruff
90
36
42
73
16
50
53
150
43
130
10
6820
43.02
Soil
100
86
36
76
14
28
0.13
13
8
44.14
37.85
Ferrous
Metal
0.12
0.18
0.1
027
024
0.42
026
0.11
8
021
0.11
Non-ferrous
Metal
0.9
2.1
0.2
2.6
0.13
5
1.19
1.12
-------
Total Concentration of Lead (EPTOX Lead) in ppm by Site, Sample Type
Site
Numbe
1
2
3
4
5
6
7
count
average
stdev
Fresh Fluff
Auto
570 (4.1)
1000 (5)
1100 (6.3)
2400 (6.5)
1000 (1.2)
1900 (1.5)
2800 (1)
2700 (1.8)
1600 (0.8)
987 (0.833)
1100 (9.1)
2600 (5)
6200 (14)
2367 (20.5)
1100 (14)
2700 (9)
5100 (13)
1700 (3.6)
2200 (3.1)
12000 (15)
2900 (15)
3500 (11)
2800 (12)
2300 (4.3)
2200 (5)
4566 (5.7)
2900 (2.1)
1200 (1.1)
White
1300 (1.9)
1733 (4.0167)
1600 (7.5)
14000 (12)
3200 (14)
2900 (13)
1800 (1.8)
1400 (2.4)
1600 (1.6)
5300 (3.2)
2800 (10)
3433 (13.67)
1900 (2.4)
1800 (1.9)
1800 (2.2)
Mixed
2300 (10.5167)
4500 (43)
3200 (10)
12000 (78)
1100 (1)
1800 (2.2)
1700 (8.6)
1500 (2.4)
9500 (50)
5200 (31.833)
8000 (26)
3900 (14)
Spillover
Fluff
2800 (1.7)
6900 (19)
4233 (11.833)
6800 (33)
4300 (36)
21000 (22)
3800 (3.4)
2900 (30)
5600 (20)
Stored
Ruff
2500 (13)
2200 (15)
2100 (6.2)
2300 (24.67)
2500 (9)
2400 (1.6)
2800 (4.4)
2700 (3.7)
1400 (11)
9700 (16)
1300 (6.8)
2533 (8.5833)
2700 (10)
4500 (1.9)
2600 (7.9)
2400 (21)
13000 (220)
2700 (5.8)
3500 (27)
13000 (20)
Soil
286
1900
3600
4700
15567
2200
1200
530
840
1400
1600
620
8.1
11
1000
27
Note: Decimal values ending in 33 or 67 represent rounding of 3.33+ and 6.66+, respectively
28
2696 (6.84)
2241 (5.48)
15
3104 (6.11)
3195 (4.99)
12
4558 (23.13)
3523 (23.73)
9
6481 (19.66)
5648 (12.28)
20
3942 (21.68)
3546 (47.25)
16
2218
3790
-------
Total Concentration of Cadmium (EPTOX Cadmium) in ppm by Site, Sample Type
Site
Number
1
2
3
4
5
6
7
count
average
stdev
Fresh Fluff
Auto
19 (1.1)
50 (1)
29 (4)
110 (1.4)
45 (0.49)
58 (0.8)
39 (0.4)
35 (0.5)
31 (0.38)
31 (0.7933)
26 (0.52)
41 (0.7)
20 (0.7)
52.67 (0.5467)
14 (0.51)
45 (0.86)
35 (0.58)
41 (1)
83 (0.74)
68 (0.37)
31 (1)
32 (0.77)
48 (0.81)
200 (0.7)
19 (0.63)
43.33 (0.6167)
28 (0.44)
46 (0.35)
White
47 (1.3)
34.33 (1.0267)
35 (3.3)
23 (0.56)
53 (1.8)
39 (1.4)
58 (0.45)
32 (0.69)
42 (0.7)
82 (1.4)
87 (2.4)
23.33 (0.567)
49 (1.3)
55 (1.5)
58 (0.94)
Mixed
43.67 (1.4167)
31 (1.2)
48 (0.48)
29 (0.99)
32 (1.2)
34 (0.7)
50 (1.4)
36 (1)
58 (0.98)
70 (1.0767)
60 (0.9)
58 (0.84)
Spillover
Ruff
18 (0.26)
25 (0.28)
33.33 (0.26833)
34 (0.77)
26 (0.63)
32 (0.18)
37 (0.3)
59 (0.81)
36 (0.71)
Stored
Ruff
35 (1.1)
44 (0.82)
46 (0.9)
34.67 (1.26833)
40 (0.57)
25 (0.33)
59 (0.53)
28 (0.57)
52 (0.6)
52 (1.1)
17 (0.69)
56 (0.84)
25 (0.23)
37 (0.48)
36 (0.49)
19 (0.2)
29 (2)
21 (0.67)
16 (0.61)
24 (0.54)
Soil
3.17
37
40
28
102
26
16
21
14
20
24
8
0.1
0.13
9
2
Note: Values ending in .33, .67 or .17 represent rounding of .33+, .66+ and .16+, respectively,
28
47.14 (0.811)
36.12 (0.673)
15
47.84 (1.289)
18.74 (0.768)
12
45.81 (1.015)
13.61 (0.272)
9
33.37 (0.468)
11.4 (0.256)
20
34.78 (0.727)
13.32 (0.41)
16
21.9
24.75
-------
Appendix 5-B
Statistical Analysis
Technical Appendix
5-B-l
-------
STATISTICAL ANALYSIS TECHNICAL APPENDIX
5.1 Summary of the Procedures Used to Analyze and Present the Data
Concentration Units
Data were reported by the laboratories in several units of measure. All of these
measures were converted to parts per million for the analysis and presentation of results.
Concentration units reported as parts per million (ppm), micrograms per gram (pg/g), and
milligrams per kilogram (mg/kg) are equivalent. Concentrations in water solutions, such as the
EPTOX extract, are reported as milligrams per liter, which is essentially identical to parts per
million. Some low concentrations were reported as micrograms per liter (/ig/L). These values
were converted into parts per million.
Use of the Log Scale for Data Plots
The data values are often positively skewed, i.e., there are many low concentration
measurements and a few very high concentrations. Many of the plots used to present the data and
the results use a log scale, compressing the larger concentrations in order to get all the data on the
plots in a way which allows easy comparison of low and high concentrations.
Many of the statistical results are based on the analysis of the natural logarithm (log)
of the original concentration measurements. When the analysis is based on these log-transformed
data, the results are presented in the original untransformed units, but often with a log scale. Thus
the scales for all data plots are labeled in the original untransformed concentration units.
Use of the Coefficient of Variation
When describing the variability of the measurements, two types of measures are
used: the standard deviation and the coefficient of variation. The coefficient of variation (cv) is
the ratio of the standard deviation of the measurements to the mean:
Coefficient of variation = standard deviation
mean
The coefficient of variation is particularly useful for describing data in which the
standard deviation increases with increasing concentration, as with much of the fluff data. The
coefficient of variation can be expressed as a fraction or as a percent. In this report the cv is
always expressed as a fraction.
Aggregating Nested Components
When multiple measurements are taken within a run, sample bucket, etc., a procedure
must be selected to combine or aggregate the multiple measurements into one concentration for
-------
the run, sample, etc. that is used for analysis and reporting the results. The procedure selected in
consultation with EPA is as follows:
1. Average all measurements within a split to determine the concentration in that
split;
2. Average the concentrations in all splits within a subsample to determine the
concentration in that subsample. If splits are not used, average all
measurements within a subsample to determine the concentration in that
subsample;
3. Average the concentrations in all subsamples within a sample to determine the
concentration in that sample; and
4. For fresh fluff:
Average the concentrations in all samples within a run (front end loader
bucket) to determine the concentration in that run;
Average the concentrations in all runs with the same input type (autos,
white goods, or other) to determine the concentration for that input type
at that site;
Use a weighted average across input types within a site to determine the
concentration for fresh fluff at that site. The weights reflect the relative
proportion of each input type at the site as recorded during the site visit;
and
5. For stored and spillover fluff and soil, average the concentrations in all samples
within a site to determine the concentration in these sample types at the site.
These steps to aggregate nested components can be applied to either the untransformed
measurements or the log-transformed data.
A weighted average of the concentrations in fresh fluff from autos, white goods, and
mixed input material is used to calculate the within site average concentrations for fresh fluff. The
weights used are based on information obtained at the site visit on the relative proportion of each
type of material typically shredded at a site.
The weights, wsj, for each site (s = 1 to 7), and each input type (i = 1 to 3) are
contained in Table 5-1. The average concentration across sites is calculated as:
3
*«, — f~t f—t **•
s s=i i=:
5c = 2 2 xsi "si
where x$- is the average concentration for all runs with input type i at site s.
-------
Table 5-1. Weights used to calculate site average concentrations in fresh fluff
Site(s)
1
2
3
4
5
6
7
Weights by type of fluff (wsi)
Auto
(i=l)
.75
.90
.90
1.0
.90
.90
1.00
White goods
(i=2)
.25
.05
.05
0
.10
.05
0
Mixed Input
(i=3)
0
.05
.05
0
0
.05
0
5.2
Components of Variance
Components of variance refers to any variability in the results contributed by sample
selection and processing steps. Perhaps the most effective way to describe components of variance
is through example. Consider the problem of calculating the PCB concentration for a 5-gallon
sample bucket of fluff. Because it is impractical to measure the PCB concentration for an entire 5-
gallon bucket (and because other chemical analyses must be conduced using fluff from each
bucket), each 5-gallon bucket was divided into approximately 10 subsamples weighing 500 grams
each. PCBs are clearly not uniformly distributed throughout fluff so that PCB concentrations vary
from subsample to subsample. The discrepancy between the actual (but unknown) PCB
concentration for the entire 5-gallon sample and that in the 500-gram subsample selected for
laboratory extraction and analysis is called sampling error. While the PCB concentration for the
entire bucket of fluff may be 40 ppm, the concentration for the subsample chosen for analysis may
be 46 ppm. In this example the sampling error is 6 ppm.
The laboratory analysis procedures for measuring the PCBs in the subsample involves
several steps, including (a) extracting the PCBs from the fluff using a solvent; (b) measuring the
volume of the solvent mixture; and (c) measuring the quantity of PCB in the mixture. Any
variability associated with the extraction and measurement steps will affect the final estimate
(measurement) of the PCB concentration and must be evaluated.
Since with actual field samples the true PCB concentrations are never known,
measurement variability or error can never be determined with certainty. One way of estimating
the variability associated with each component of the sample preparation and measurement
process is to collect multiple measurements at each level of analysis. That is by comparing
concentrations in multiple subsamples from the same sample bucket, and more than one
measurement from the same extracted solution, etc., the magnitude of the measurement error or
variability associated with each component of the analysis process can be estimated.
These components are nested. Subsamples are said to be nested within samples (5-
gallon buckets) because only subsample measurements from the same sample are relevant to
-------
calculating the PCB concentration in that sample. Similarly, analytical measurements are nested
within subsamples. The measurement error for the concentration in a sample bucket is the
cumulative error or variability resulting from all nested components (sampling and analytical
variability).
The components of variance analysis describes the sources of variability in the
measurement process and the magnitude of the error contributed in each processing step. The
results of this components of variance analysis can be used (a) to select appropriate statistical
analysis procedures, (b) to determine the sample size required for a specified measurement
precision, (c) to estimate the precision of the measurements, and (d) to select cost-effective
sampling strategies.
Table 5-2 lists the variance components analyzed in the analysis of the fluff data.
Identification of these components is based on the sample selection and processing steps.
Table 5-2. Variance components in the analysis of fluff data1
Component
Sources of variation in the PCB,
lead, and cadmium concentrations
Nested
within:
Site and time
Run (Including
Input Materials)
Sample
Subsample
Spltf
Duplicate
Systematic differences between sites and
differences between sampling dates2
Differences between runs due to differences Site
in the input material and any contamination
within the shredder
Differences between sample buckets associated Run
with selecting the sample material from the
fluff output
Differences between subsamples associated Sample
with selecting the subsample material from
the sample bucket
Differences between splits associated with Subsample
both selecting the split material from the
subsample and extraction of the analyte
from the split material
Differences between measurements on Split
different aliquots of extract due to variation
in the measurement process
1Due to the sampling design, some components cannot be estimated for some analytes.
^Because samples were collected at one time at each site, differences over time cannot be determined from the data.
3For PCB measurements using the tumbler extraction, splits were not used and the subsample component includes variation
during extraction.
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52.1 Distribution of the Variance Components and Calculation Procedures
The magnitude and distribution of the errors contributed by each processing step will
vary. Two models, or explanations, for the distribution of the errors are introduced below, a
normal model with additive errors and a lognormal model with multiplicative errors. Specification
of the model determines how to best summarize and analyze the data. These two models are
considered because (a) both models can be supported based on theoretical mechanisms that could
create the error; (b) both models can be easily handled using statistical techniques; and (c) the two
models span the range of characteristics likely to be found in the fluff data. These two models
represent the points along a continuum which defines the transformation which most reasonably
normalizes the data and stabilizes the variance. Along this continuum are many transformations,
including no transformation, square root, cube root, log transformation, and inverse
transformation, in that order. Moving along the continuum from no transformation to the inverse
transformation, the effect of the transformation becomes stronger in the sense that the change in
the shape of the distribution due to the transformation increases. Although mixed distribution
models are not explicitly considered due to their complexity, the data analysis and theoretical
discussions address other transformations along the continuum.
The first model assumes the measurement errors have a normal distribution, that the
magnitude of the measurement errors is constant and independent of concentration, and that the
errors associated with different components are additive. Because concentration measurements
cannot be negative, this model does not provide a good description of data that have a large
coefficient of variation1, however this model may provide a reasonable description of some of the
components of variance.
The second model assumes that measurement errors have a lognormal distribution,
i.e., that the errors in the log-transformed data have a normal distribution. Data following this
model will have the following characteristics:
• The data will never be negative;
• The data will have a positively skewed distribution (however, the skewed nature
of the data may not be apparent if the coefficient of variation is small); and
• The magnitude of the measurement error will be proportional to the
concentration (Le, the errors are proportional or multiplicative).
These two models span the range of characteristics likely to be found in fluff data, and
are only two of many possible models. Some components may have different distributions than
others. Some processes which create the error may result in additive errors while others result in
multiplicative error. If the lognormal model describes all variance components, the log
transformed data will have variance components with constant variance and a normal distribution,
required by most statistical procedures. If some components have a normal distribution with
additive effects, another transformation, such as the square root or cube root might provide data
with a better approximation to a normal distribution with constant variance. If the normal model
fits the data, then no transformation is required in the statistical analysis.
*Data with a normal distribution and a coefficient of variation of .61 will have 5% of the data values below zero. With a coefficient of
variation of 1.19,20% of the data would be below zero.
-------
The normal and lognormal model have different implications for the characteristics of
the data. These factors are compared in Table 5-3.
Table 5-3. Comparison of data characteristics for the normal and lognormal model
Factor being compared: Normal Lognormal model
Distribution of the Normal Lognormal
measurement errors (symmetric and bell shaped) (skewed to the right)
Standard deviation of constant, independent standard deviation
the measurement errors of concentration is proportional to
concentration
Coefficient of variation Small, perhaps less than 0.5 Any value
of the concentration
measurements
Effect of sources of error Variation results in additive Variation results in
errors multiplicative errors
The following sections discuss the theoretical and analytical considerations to
determine which model best fits the data: the normal model, lognormal model, or some other
unspecified model, and presents evidence that the lognormal model provides a reasonable
description of the contaminant measurements in fluff.
In the following discussion, note that the term variance component refers to the
variance contributed at only one stage in the processing. Thus, the variance component associated
with selecting a sample bucket is the variance among the true concentrations in replicate sample
buckets from the same run. The term measurement refers to the measured concentrations
obtained by aggregating the concentrations across nested components. Thus, the variance of the
sample measurement includes the variance contributed by subsampling and measurement. If all
variance components have a normal distribution, so will all measurements. Similarly, if all
variance components have a lognormal distribution, so will all measurements.
The model provides a framework within which the data can be parsimoniously
described. Because the model used to describe the data cannot be known with certainty, the model
selection process answers the question: Which model provides the best description of the data?
To select an appropriate model for the data, the following items are considered:
• Theoretical considerations that might support each model;
• The coefficient of variation of the measurements;
• The relationship between the magnitude of the measurement error (standard
deviation) and the concentration; and
• The distribution of the data as suggested by a histogram of the data.
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Theoretical Considerations Determining the Distribution of the Data
Theoretical considerations that provide some insight into the likely distribution of the
data and the effect of sources of error on the measurements for each variance component are
discussed below.
Sites - The systematic differences between concentrations at different sites may be
due to many factors, possibly including:
• Differences in the input material received by the sites, which may be a function
of the region of the country where the shredder facility is located, or of the
operating policies of the shredder;
• Differences in the treatment used at the shredder sites to remove contaminated
portions of the shredder input material; or
• Differences in the shredding equipment, resulting in different fates for the
contaminated material as it goes through the shredder.
Because similar shredder input items can be found in all parts of the country,
systematic differences between sites might be relatively small Differences in the sites' policies on
what material is accepted or how items are treated will increase differences between sites.
Without more information, it is difficult to make conclusions about this variance component.
To the extent that the systematic differences between sites are relatively small:
• Either the normal or the lognormal model would provide a reasonable
description of the site component of variation; and
• The distribution of the site concentration measurements will be largely
determined by the variation between runs within the site.
Runs - Differences between runs within a site will depend on the characteristics of the
input material to the shredder. The sampling design considered automobiles, white goods, and
mixed input material separately. Thus, the differences between runs of autos and white goods are
due to design and not due to chance. Therefore, these differences are not considered as part of
this component of variance. Calculation of the variance between runs of the same input material
assume that the items selected for each run are randomly selected from all such available items.
The distribution of the contaminant concentrations across runs of the same type of
material is difficult to specify. However, to the extent that most of the contamination is associated
with a few items, the distribution can be expected to be skewed to the right, and the variability
between runs would likely increase as the contaminant level increased. The suspicion that most of
the contamination is associated with a few items gains some support from the following
observations from the pilot study:
• There may be significant variation between runs (based on the Type I
estimation procedure but not the maximum likelihood procedure) and
-------
• There are significantly higher PCB concentrations in mixed input material than
in auto and white goods (see Chapter 5, Section 5.2).
The arguments above suggest that the lognormal model may describe the component
of variance between runs better than the normal model.
Sample, Subsample, Split - The process of constructing (a) a sample bucket of
material from a fluff pile from a run of input material, (b) a subsample from a sample bucket of
fluff, (c) or a split from a subsample all require a similar process of selecting a random subset of
fluff from a larger set of fluff material
The components of variance associated with samples, subsamples, and splits measure
the extent to which the contaminants are evenly distributed throughout the fluff. If the
contaminant in the larger set is evenly distributed, there will be very little difference between
subsets. On the other hand, if there are regions of higher and lower concentrations in the larger
set, concentrations within a subset will depend on which regions in the larger set were selected for
the subset.
Consider the following model for selecting a subset of fluff from a larger set of fluff:
Assume the PCBs in the larger set are in n nuggets of fixed size. Using an
appropriate unit of concentration, the concentration in the subset is equal to the
number of nuggets in the subset. Assuming the nuggets are randomly mixed, the
number of nuggets in the subset will have a binomial distribution. If the subset
volume is 10% of the volume of the larger set, the probability of selecting a nugget is p
= .10. The distribution of the true concentration in the subset has an expected value
to np, a variance np(l-p), and a coefficient of variation of ^/ (1-p)
v ~np~'
The distribution of the true concentration wfll be positively skewed if p is less than JO.
In most situations the proportion, p, of the fluff which is actually analyzed at the lab is quite small.
Therefore, the distribution of the true concentration in the subsets is expected to be positively
skewed. When analyzing many samples, the data transformation which equalizes variance depends
on the relationship between the standard deviation of concentrations in subsets from the same set
of fluff and the mean concentration in the set of fluff. If one set has twice the concentration of
another because it has twice as many nuggets, then the variance among subsets will increase with
concentration; however, the coefficient of variation will decrease. If the components have this
characteristic, the square root transformation is likely to stabilize the variance. If the increase in
concentration is due to an increase in the amount of PCBs in each nugget, then the standard
deviation will increase linearly with the concentration, the coefficient of variation will remain fixed,
and the log transformation is appropriate.
Although this model can be made more realistic by assuming there are several sizes of
nuggets or that there is a continuous but variable concentration, the conclusions should remain the
same:
The distribution of measurement errors contributed by subsetting the fluff is
probably skewed; and
8
-------
• The standard deviation of the variance components associated with selecting a
sample, subsample, or split increases with the concentration (although perhaps
not as fast as might be predicted by the lognonnal model).
These arguments suggest that the distribution of the variance components associated
with selecting a sample, subsample, or split of material will be better described by the lognormal
model than the normal model, and that the best transformation will be in the range from a square
root to a log transformation.
Extraction and sample preparation • The errors contributed by the sample
preparation and extraction process cannot be estimated separately from the final subsample or
split selection process. However, the processes resulting in the errors are different and therefore
are discussed separately.
Sample preparation involves many steps such as dissolving the PCBs into a solvent,
and adjusting a sample to a measured volume. Procedural errors in these steps are likely to result
in proportional errors in the concentration (for instance, an error in adjusting to a measured
volume by 1% will result in an error of .01 ppm for a concentration of 1 ppm but an error of 10
ppm in a concentration of 1,000 ppm). The cumulative effect of many proportional errors will
result in data with a lognormal distribution.
The characteristic of the lognormal model that the measurement error will be
proportional to the concentration is supported in practice by MRI's procedure of reporting all
concentrations to two significant figures.
The arguments above would suggest that the lognormal model will provide a good
description of the component of variance associated with sample preparation and extraction.
Quantifying the concentrations - Associated with all measurements is the error in the
final measurement step. This error may be due to fluctuations in the internal operation of the
equipment, the handling or the equipment, or any calculations required to determine the
concentrations. For measuring PCBs, this error is the error associated with injections into the gas
chromatograph.
This component of error is likely to be small; thus, either the normal or lognormal
distribution might be used. However, because quantitation of a compound often involves
calculating a ratio, proportional errors can often be expected, suggesting that the lognonnal
distribution may describe this variance component better than a normal distribution.
Overall, there is more support for using the lognonnal model for the most nested
variance components, Le., measurement and extraction components, then for the least nested
components between sites and runs. To the extent that most of the variation between runs is
contributed by the components which have a significantly skewed or lognormal distribution, the
lognormal model may provide a reasonable description of all measurements.
Using the Coefficient of Variation to Suggest a Reasonable Model
Since all reported concentrations are greater than or equal to zero, concentration data
with high coefficients of variation must also be associated with a skewed distribution rather than
-------
the symmetric normal distribution. Analysis of the coefficient of variation can provide some
information on which model can best describe the fluff data.
Table 5-4 shows the coefficient of variation of the measurements for replicate runs,
samples, subsamples or splits, and measurements for lead, cadmium, and PCB measurements. The
coefficients of variation were calculated by determining the variance of replicate measurements
using the log transformed data and then converting these variances in the coefficients of variation
for the untransformed measurements. Due to the small number of runs with other/mixed and
white good input material, separate values for each input type were not calculated.
Table 5-4. Coefficient of variation of fluff measurements by level of aggregation and analyte.
Parameter
PCB
EPTOX
Lead
EPTOX
Cadmium
Total Lead
Total
Cadmium
Level of
Aggregation
Run
Sample
Subsample
Measurement
Run
Sample
Split
Measurement
Run
Sample
Split
Measurement
Run
Sample
Split
Run
Sample
Split
Df
21
16
11
8
22
18
7
14
22
18
7
14
22
18
13
22
18
14
CV with 95% CI (assumes
lognormal distribution)
2.5 (1.4 to 6.8)
0.76 (0.52 to 13)
033 (0.22 to 0.55)
0.15 (0.093 to 0.27)
0.92 (0.64 to 1.5)
0.59 (0.42 to 0.92)
026 (0.16to0.52)
0.057 (0.04 to 0.086)
0.48 (035 to 0.69)
035 (0.25 to 0.52)
0.13 (0.079 to 0.25)
0.044 (0.031 to 0.067)
0.47 (035 to 0.68)
0.47 (033 to 0.71)
0.26 (0.18 to 0.41)
0.47 (035 to 0.68)
0.5 (036 to 0.76)
0.33 (0.23 to 0.52)
10
-------
The coefficients of variation for samples and measurements nested within samples are
generally less than 0.50, except for PCB sample measurements with a coefficient of variation of
0.76. Coefficients of variation for measurements in runs are greater than or equal to 0.47.
The coefficients of variation indicate that the PCB measurements are more highly
skewed than the lead and cadmium measurements and that measurements for runs and sometimes
samples can be highly skewed. The large coefficients of variation would suggest that a
transformation having a significant effect on the distribution is required to normalize the
measurement error. Although the exact transformation cannot be determined from this analysis,
the desired transformation should be much closer to a log transformation to no transformation.
Standard Deviation Versus the Mean for Replicated Measurements
Replicated measurements can be used to compare the standard deviation of replicate
measurements to the concentration level to determine if the normal or lognormal model best fits
the measurement data. Use of the lognormal model is supported if the standard deviation
increases linearly with the concentration. The normal model is supported if the standard deviation
is constant, independent of the mean.
The following model can be used to test if the measurement error (STD), estimated
by the standard deviation among replicate measurements, increases with the concentration,
estimated by the mean (MEAN) of the replicate measurements. Because the variability in the
standard deviation estimate increases linearly with the estimate, the following model with the log
transformed statistics is used:
In(STD) = intercept + slope * In(MEAN) (equation 1).
If the data is consistent with the lognormal model, the confidence interval for the
slope includes 1.0. The data are consistent with the normal model if the confidence interval for the
slope includes 0.0. Slopes between 0.0 and 1.0 would indicate that transformations between no
transformation and the log transformation are required to stabilize the variance. Slope greater
than 1.0 indicate that transformations stronger than the log transformation are required. Cases in
which the calculated standard deviation (STD) is zero (due to rounding) have been eliminated
from the analysis. Elimination of these cases will tend to reduce the estimated slope, thus biasing
the conclusions to slightly favoring a normal distribution.
Because simple linear regression assumes no error in the independent variable, a
modified estimation procedure is used which adjusts for errors in the dependent and independent
variables2. This method requires specification of the ratio of the measurement errors in the
dependent and independent variables. On the assumption that the data have a lognormal
distribution, the ratio of the error in In(STD) to the error in In(MEAN) is approximately
This value was used in the analysis.
In some cases the number of samples on which the mean and standard deviation are
based differs. Although a weighted analysis is possible, combining the weights with the adjustment
for error in the independent variable is difficult Therefore, the weighted analysis was not
performed. This simplification should have little effect on the results.
2Fuller, Wayne A., "Measurement Error Models.', (1987): John Wiley & Sons, Inc.
11
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The slope from equation 1 is shown in Table 5-5 for different levels of aggregation
and different analytes.
Table 5-5. Relationship between the standard deviation and mean of replicate measurements
and implications for variance component models.
Parameter
PCB
EPTOX
Lead
EPTOX
Cadmium
Total lead
Total
Cadmium
Level of Slope: log standard deviation
aggregation versus log mean, with 95% CI n
Runa
Sample
subsample
or split
measurement0
Runa
Sample
Subsample
Measurement
Runa
Sample
Subsample
Measurement
Runa
Sample
Split
Runa
Sample
Split
129 (0.85 to 1.71)
0.92 (039 to 1.26)
1.07 (0.63 to 1.51)
0.97 (.54 to 1.40)
12 (-1.9 to 43)
1.50 (0.94 to 2.06)
0.81 (-0.10 to 1.71)
1.16 (0.72 to 1.61)
1.99 (1.11 to 2.87)
2.28 (0.73 to 3.82)
1.67 (-0.12 to 3.87)
0.44 (-0.06 to 0.94)
1.29 (0.85 to 1.71)
2.63 (033 to 4.94)
127 (0.64 to 1.89)
32 (-3.6 to 10)
14.6 (-130 to 160)
131 (0.63 to 1.98)
6
15
8
15
6
8
10
10
6
8
10
10
6
9
13
6
8
13
Consistent with
which model
Lognormal
Lognormal
Lognormal
Lognormal
Lognormal and
Normal
Lognormal
Lognormal and
Normal
Lognormal
LognormaF
Lognormal
Lognormal and
Normal
Normal
Lognormal
Lognormal
Lognormal
Lognormal and
Normal
Lognormal and
Normal
Lognormal
aBased on auto runs only.
^Confidence interval is approximate, not all points are independent.
°The confidence interval is most consistent with the lognormal assumption, and inconsistent with the normal assumption.
12
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The slopes relating the standard deviation to the mean, for different aggregation
levels for the same analyte will be related. For example, if the measurement error in subsamples
increases linearly with concentration, measurement error in samples will tend to increase with
concentration because part of the measurement error in a sample is due to the error in the
subsample measurement. Thus the results in Table 5-5 can provide general support for using
either the normal or lognormal model; however, it cannot be used to select a model for individual
components.
As can be seen from Table 5-5, the relationship between the mean and standard
deviation of the data provides strong support for using a lognormal model for the fluff data. Only
one regression (for replicate measurements of EPTOX cadmium) favored the normal model more
than the lognormal. That many of the estimated slopes were greater than 1.0 suggests that a
stronger transformation than the log transformation may be required to stabilize the variance for
most components.
Using the Distribution of the Data to Select a Model
In general, a larger sample size is required to test the distribution of the data than is
available in the fluff dataset. On the assumption that systematic differences between sites and runs
are small compared to differences between sample measurements, the distribution of the samples
measurements can be assessed by looking at all samples. Figures 5-3 and 5-4 (in Chapter 5) show
histograms of the untransformed and log transformed concentrations from fresh fluff samples. As
can be seen from these plots, the sample measurements are highly skewed and the log transformed
measurements have a roughly symmetric or normal distribution. This result is consistent with
using the lognormal model, rather than the normal model, to describe the variance components.
Selecting a Model of the Data
Although the discussion has focused on a comparison of the normal and lognormal
models, these models represent the extremes along a continuum which defines the transformation
which most reasonably normalizes the data and stabilizes the variance. As a result of the previous
analysis, the log transformed data is used for all calculating confidence intervals and hypothesis
tests for all but the confidence intervals on averages across sites. As is discussed in Section 5.5,
due to the sensitivity of the confidence intervals for means across sites to the lognormal
assumption, a bootstrap procedure is used to calculate these intervals.
Calculating Mean Concentrations and Aggregating Nested Components
On the assumption that the lognormal model describes the data, the preferred
procedure for calculating confidence intervals for the geometric mean and comparing groups of
data using hypothesis tests is to aggregating the log-transformed measurements over the
appropriate nested components.
For calculating the arithmetic mean concentrations for splits, subsamples, samples,
etc., the following two calculation procedures will give similar results, neither of which is clearly
preferred:
1. Aggregate the nested components using the untransformed measurements; and
13
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2. Aggregate the nested components using log-transformed data and then convert
back to the untransformed concentration.
The agreement between the two aggregated estimates decreases as the skewness of
the data increases. Aggregating using the untransformed measurements (1. above) has the
advantage that the arithmetic mean is a statistically unbiased estimate of the true mean, no matter
what the underlying distribution. Approach 2. above will have lower error if the data has a
lognormal distribution, however if this assumption is not correct, the estimate may be biased. The
second method is also more difficult to implement and understand.
For the data analysis, the following procedures were selected in discussion with EPA:
(1) the untransformed averages will be used to calculate the arithmetic average concentrations
across sites, and (2) the untransformed concentrations will be aggregated up to the sample level for
analyses based on sample measurements (above the sample level, the log-transformed sample
averages are aggregated for tests using the geometric mean). Any differences in the statistical
tests between this procedure and that using the log-transformed values exclusively are expected to
be small
Thus, the calculation procedures for the fluff data analysis are:
• Use the log-transformed concentrations for calculating components of variance;
• Aggregate using the log-transformed concentrations for statistical tests and
confidence intervals for measurements within samples, such as comparison of
the tumbler results after one or three rinses.
• Aggregate using the untransformed concentrations up to the sample level, take
the log of this sample average and continue to aggregate using the logs for
statistical tests and confidence intervals for comparing types of input material
• Aggregate using only the untransformed concentrations for calculating
arithmetic averages across sites.
53 Magnitude of the Variance Components
The magnitude of the variance components are estimated from the duplicate
measurements on the same extract, sample, etc. The variance estimates obtained from the
statistical analysis depend on the following factors:
1. The subset of the data that is used for the estimates (e.g. variance components
estimated for white goods may be different than for autos);
2. The assumed model for the components, including which components are
assumed to be random and which fixed; and
3. The statistical estimation procedure.
These three aspects are discussed below.
14
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Once a sample of fluff is collected, the variability contributed by the subsequent
processing steps is assumed to be independent of the source of the fluff material. Thus, the
magnitude of the variability contributed in the subsampling step is assumed to be the same for fluff
from autos and white goods.
For PCBs, variance components are based on fresh fluff samples in which the PCBs
were extracted using the tumbler method (no duplicate measurements were made on stored or
spillover fluff, as specified in the QAPjP). The variance components for the PCBs were based on
the total PCB concentration. In many cases, the duplicate measurements were provided for only
one Aroclor and no total PCB concentration was reported. For these measurements, the total
PCB concentration was constructed by assuming the unreported Aroclors have the same
concentration as reported in the duplicate injection. Therefore, the variance between
measurements for the PCBs represents a combination of the variance between total PCB
determinations and the variance between determinations for individual Aroclors.
For lead and cadmium, variance components for samples and runs are based on fresh
fluff samples. Variance components for splits and measurements were based on all fluff samples.
The statistical model assumed that the measurement errors for the measurements
within splits, splits within subsamples, subsamples within samples, samples within runs, and runs
with the same type of input material within a site have a normal distribution with a constant
variance for each component. The distribution of the concentrations in different input types and
sites was assumed to be non-random or fixed because there may be systematic non-random
differences between input types and the site selection was not entirely random. To satisfy the
assumption of constant variance, the log-transformed measurements were analyzed.
The variance components were estimated using the SAS procedure VARCOMP. This
procedure provides several mathematical methods for estimating the magnitude of the variance
components. In general, the estimates for each method are the same in large balanced (equal
number of replicates within each sample, subsample, etc.) datasets. The fluff data are neither
balanced nor large. With an unbalanced dataset, the estimates depend on the mathematical
criteria that are to be optimized.
Two estimation methods were used: Type I and maximum likelihood. The Type I
procedure provides unbiased estimates of variance. However, the estimates may be negative even
though the variances being estimated must be positive. Confidence intervals for the measurement
component can be calculated based on the chi-squared distribution. The maximum likelihood
procedure provides variance estimates that are always greater than or equal to zero, along with
information for calculating confidence intervals. The confidence intervals have several drawbacks:
they are only approximate, particularly in small datasets such as the fluff data; and they are not
available when the estimated variance is zero or when only one component has a non-zero
variance.
15
-------
Tables 5-6 through 5-8 present the variance component estimates for PCBs, total lead
and cadmium, and EPTOX lead and cadmium. The tables include:
• The coefficient of variation for each variance component based on both the
Type I and maximum likelihood estimation methods, with 95% confidence
intervals if available;
• The average of the coefficient of variation for the Type I and maximum
likelihood estimation methods; and
• The coefficient of variation for the cumulative effects of all variance
components within runs.
The output from PROC VARCOMP provides variance estimates for the log-
transformed data. These variance estimates and the associated confidence intervals are presented
as the coefficient of variation of the variance components in Tables 5-6 through 5-8. For a random
variable with a lognormal distribution, the transformation from the variance (r^) to the coefficient
of variation (cv) is:
cv = Vexp(r2)-l
The coefficients of variation in Tables 5-6 through 5-8 are plotted in Figures 5-1
through 5-5. In each case, the maximum likelihood estimate of the variance component for runs
within input type is zero. The reason for this value being zero is unknown. However, it is probably
an artifact of the particular algorithm and the very limited data set. The discrepancy between the
estimates produced by the two methods indicates that caution must be employed when using these
results.
Table 5-6. Coefficient of variation of the variance components for PCB measurements based
on SAS PROC VARCOMP using two estimation methods
Coefficient of
variation
Parameter Component (Method = Type I)
PCB Measurement within
subsample
Subsample within
sample
Sample within run
Run within input type
0.15
(0.099 to 029)
030
0.64
2.3
Coefficient of
variation
(Method = Maximum
Likelihood)
0.15
(0.029 to 021)
0.29
(0.030 to 0.42)
1.2
(0.81 to 1.6)
0
Average of
the Type I
and ML
Cv
.15
.30
.92
1.15
Combined effects 1.51
within run
16
-------
Table 5-7. Coefficient of variation of the variance components for total lead and cadmium
measurements based on SAS PROC VARCOMP using two estimation methods
Parameter
Total lead
Total
cadmium
n* 69
Coefficient of
variation
Component (Method = Type I)
Measurement within
sample
Sample within run
Run within input type
Combined effects
within run
Measurement within
sample
Sample within run
Run within input type
0.24
(0.18 to 0.37)
038
0.10
0.29
(0.22 to 0.45)
035
0.094
Coefficient of
variation
(Method = Maximum
Likelihood)
0.24
(0.14 to 0.32)
0.29
(0.085 to 0.41)
0
031
(0.17 to 0.40)
0.26
(0 to 039)
0
Average of
the Type I
and ML
Cv
.24
34
.05
.42
30
31
.047
Combined effects .44
within run
17
-------
Table 5-8. Coefficient of variation of the variance components for EPTOX lead and cadmium
measurements based on SAS PROC VARCOMP using two estimation methods
Parameter
EPTOX
lead
n = 76
EPTOX
cadmium
n = 76
Component
Measurement within
split
Split within sample
Sample within run
Run within input
type
Combined effects
within run
Measurement within
split
Split within sample
Sample within run
Run within input
type
Coefficient of
variation
(Method = Type I)
0.053
(0.040 to 0.079)
0.27
0.52
0.57
0.060
(0.045 to 0.089)
0.11
032
033
Coefficient of
variation
(Method = Maximum
Likelihood)
0.048
(0.032 to 0.059)
0.088
(0.069 to 0.10)
0.60
(0.44 to 0.73)
0
0.046
(0.036 to 0.055)
0.023
(0 to 0.035)
0.33
(0.27 to 039)
0
Average of
the Type I
and ML
Cv
.05
.18
.56
.29
.66
.05
.07
33
.17
Combined effects
within run
38
18
-------
2.5 -r
2 --
1.5 --
Coefficient of variation
1 --
0.5 --
0
DTypel
H Max Likelihood
— 95% Conf. Int.
Measurement Subsample Sample
Variance component
Run
Figure 5-1. Coefficient of variation for individual variance components when measuring PCB concentrations, using two
estimation methods
-------
0.45 -r
0.4 --
0.35 --
0.3 --
0.25 - -
Coefficient of variation
Measurement + split Sample
Variance component
D Type 1
EH Max Likelihood
— 95% Conf. Interval
Run
Figure 5-2. Coefficient of variation for individual variance components when measuring total lead concentrations, using two
estimation methods
-------
Coefficient of variation
0.45 -r
0.4 --
0.35 --
0.3 --
0.25 --
0.2 --
0.15 --
0.1 --
0.05 --
0
Measurement + split Sample
Variance component
Run
D Type 1
H Max Likelihood
— 95% Conf. Interval
Figure 5-3. Coefficient of variation for individual variance components when measuring total cadmium concentrations, using two
estimation methods
-------
0.8 -T-
0.7
0.6
0.5 --
Coefficient of variation 0.4 --
0.3
0.2
Measurement
Split Sample
Variance component
Run
DTypel
H Max Likelihood
— 95% Conf. Int.
Figure 5-4. Coefficient of variation for individual variance components when measuring EPTOX lead concentrations, using two
estimation methods
-------
0.4 T-
0.35 --
0.3 --
0.25 --
Coefficient of variation 0.2 - -
Measurement
Split Sample
Variance component
Run
DTypel
H Max Likelihood
— 95% Conf. Int.
Figure 5-5. Coefficient of variation for individual variance components when measuring EPTOX cadmium concentrations, using
two estimation methods
-------
Comparison of the cv's from the two estimation procedures and their confidence
intervals provides an indication of the precision with which the cv's can be estimated and the
sensitivity to the calculation method. The confidence intervals are often as large as ±50% of the
estimate. In addition, the difference between methods is often as great as 50% of the estimate.
The two estimation methods have better agreement for the components nested within samples for
which there are more data. For the between run component the two estimation procedures
provided very different results, the maximum likelihood procedures always estimated a zero cv (no
difference), whereas the Type I procedure often estimated a cv as large or larger than other
components.
The Type I and maximum likelihood cv estimates have been averaged to provide one
value for discussion. These values may be used in later analyses. Based on these values, the cv
representing the combined effect of all measurement errors within a run has been calculated and
appears in Tables 5-6 through 5-8.
Consider the problem of measuring the concentration in a run or front-end loader
bucket of fluff. If the concentration is based on one measurement in one sample bucket of fluff,
the expected magnitude of the measurement error can be approximated from the combined cv for
all components nested within runs. Thus, the coefficient of variation for a PCB measurement is
about 1.51, while for lead and cadmium (total or EPTOX) measurements, the cv is between .38
and .66. Therefore, the PCB measurements are less precise (have more measurement error) than
the lead and cadmium measurements.
For measurements with a lognormal distribution and a known cv, the confidence
interval can be expressed as a factor of the measured concentration. Thus, measurements with a
cv of 1.0 will be within a factor of 5 of the true concentration 95% of the time, i.e., the true
concentration will be within one-fifth and five times the measured concentration 95% of the time.
The factors for converting the cv to the 95% confidence interval are shown in the Table 5-9. These
factors should be considered approximate because the variance is never known precisely and the
distribution may not be lognormal.
24
-------
Table 5-9.
Factors for determining a 95% confidence interval for one observation from a
lognormal distribution
Coefficient of
variation
.1
2
3
.4
5
.6
.7
.8
.9
1.0
1.1
1.2
1.3
1.4
1.5
Factor for
determining a 95%
confidence interval
1.2
1.5
1.8
2.1
2.5
3.0
3.4
4.0
4.5
5.1
5.7
6.4
7.0
7.7
8.4
Based on components of variance analysis and the table above, the following general
statements can be made:
• For approximately 95% of the samples, the measured EPTOX cadmium, total
lead, and total cadmium concentration in one sample of fluff will be within a
factor of 2 of the true concentration in the fluff run from which the sample was
obtained;
• For approximately 95% of the samples, the measured EPTOX lead
concentration in one sample of fluff will be within a factor of 3 of the true
concentration in the fluff run from which the sample was obtained; and
• For approximately 95% of the samples, the measured PCB concentration in
one sample of fluff will be within a factor of 8 of the true concentration in the
fluff run from which the sample was obtained.
More precision than indicated above can be obtained by collecting multiple samples
within the run.
25
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5.4 Recovery
In order to measure the PCB concentration in a fluff or soil sample, the PCBs must
first be extracted from the fluff or soil matrix. This extraction step conventionally involved the use
of a soxhlet apparatus, but was accomplished in the Fluff Pilot Program with the use of a tumbler
(slurry extraction procedure). After the extraction step is completed, the quantity of PCBs in the
solvent PCB mixture is determined. Unfortunately, neither the PCB extraction nor the
measurement of the PCB concentration is achieved without error.
In the extraction step, not all of the PCBs in the original portion of fluff or soil get
transferred to the solvent mixture. The actual percentage of PCBs residing in the sample which
are extracted will depend, among other factors, on the nature of the sample matrix and the
adsorption of the PCBs to the material. Recovery is defined as the percentage of the PCBs in the
original sample which are transferred to the solvent. Recovery for all compounds theoretically
varies between 0% and 100%.
It is critical that recovery (extraction efficiency) be carefully evaluated. Recovery is
estimated in the lab by splitting a sample into two theoretically equivalent portions, one of which is
spiked (or injected) with a known amount of PCB before extraction and analysis of both
subsamples. By comparing PCB concentrations in the spiked and unspiked portions, the fraction
of the spiked material that was extracted and transferred to the final solvent can be estimated.
The procedures for determining recovery for lead and cadmium analyses are similar
to those for PCBs. Note that replicate subsamples are used to estimate PCB recoveries using
tumbler extraction and replicate splits are used for estimating recovery for PCBs using the soxhlet
extraction. Both total and EPTOX lead and cadmium recoveries are based on subsplits of splits.
The recovery is calculated as:
R = 100(Cspiiced-Cunspiked) (eq 1)
where:
R = percent recovery;
measured concentration in the spiked portion (native concentration);
measured concentration in the unspiked portion; and
S = the amount of material spiked into the sample, expressed as a
concentration.
Although the true recovery must always be between 0% and 100%, the estimated
recovery using equation 1 may be less than 0% or greater than 100%. The precision with which
the recovery can be estimated depends on the number of recovery determinations (analyses of
replicate spiked and unspiked portions) and the error present in various stages of the
measurement process. Errors in the estimation of both the unspiked and spiked concentrations
contribute to errors in determining recovery and the possibility that the estimated recovery is less
than 0% or greater than 100%.
26
-------
Using PCBs as an example, if the PCBs are to be injected into subsample A, PCB
recovery is the difference in the true concentration of PCBs in the extract from subsample A after
spiking and the true concentration of PCBs in the extract from subsample A that would be
obtained without spiking divided by the concentration of the PCBs injected into the sample.
Recovery
' T(A)unspflced
where:
Variable
T(A) -ke
T(A)un«)jked
Definition
True unknown concentration in
the extract from subsample A
after spiking
True unknown concentration in
the extract from subsample A
which would have been
obtained if the unspiked
sampled were processed
Increase in the PCB
concentration in the sample
due to spiking
Estimated by:
Measured concentration in
the extract from spiked
subsample A (C(A)spiked)
Measured concentration in
the extract from unspiked
subsample B (C(A)unspiked)
Known to adequate precision
The estimated recovery will not equal the true recovery due to errors in the
measurement process for both the spiked and unspiked subsamples and due to differences in the
true PCB concentrations between the subsamples A and B. As a result of these errors, the
calculated recovery can be outside the range of 0% to 100%. If the spike concentration is small
relative to the native concentrations, TCA)^^ and T(A)unq,iked will be almost identical. In this
case any error in estimating these concentrations will have a large effect on the estimated recovery.
The error in determining the recovery is not the same for all samples. Samples in
which the spike amount is greater than the native quantity in the sample will have more precise
recovery estimates than those samples in which the spike amount is much smaller than the native
amount. Because the recovery precision varies greatly between samples, a weighted analysis is
used to calculate the average and the confidence intervals. Determination of the weights is
discussed in the following section.
Although the concentration measurements have a skewed, roughly log-normal
distribution, simulations suggest that confidence intervals calculated on the assumption that the
recovery data have a normal distribution perform well. Therefore the recovery data are assumed
to have a normal distribution and confidence intervals are calculated using a t-statistic.
5.4.1
Weights for Calculating Recovery Estimates
Because the recovery precision varies (sometimes greatly) between samples, a
weighted analysis is used to calculate the average recovery and its confidence interval. The weights
27
-------
will be proportional to the inverse of the variance of the recovery estimates. The variance of the
recovery estimates can be written as:
100 \2
r~ I iVarfC -, ,.\ + Var (C ., ^
y j ^ V<"^v-spiked^ ^ Vdx ^Minspiked/ /
Using the coefficient of variation to estimate the variance of the measured
concentrations and noting that the measurement error for the unspiked concentration is due to
both measurement error and differences between portions of material, the following relationship
holds approximately;
where:
^meas = coefficient of variation for measurements the fluff portions used for
recovery estimation;
cv2epiicare = coefficient of variation for differences between fluff portions used for
recovery estimation.
These coefficients of variation can be estimated from the components of variance
analysis. However, because (1) the precision of the variance components is often poor, (2) cv2meas
is roughly equal to cv^^^g for all analytes, (3) most of the differences in the weights are due to
the relative size of the spike concentration to the native concentration, and (4) because the weights
need only be proportional to the inverse of the variance, the following weights are used:
Weight(R) = "
cadmium.
^inspiked
The following sections summarize the recovery results for PCBs and lead and
5.4.2 Recovery for PCBs using the Tumbler and Soxhlet Extraction Methods
In order to estimate PCB recovery, one sample of fluff or soil in each of eleven
batches was spiked with measured quantities of a PCB Aroclor. The selected samples included at
least one sample from six of the seven sites. Of the 11 samples, there were 10 fluff samples and 1
soil sample. All samples were analyzed using the 8080 method. The Soxhlet extraction method
was used for three samples and the tumbler extraction method was used for eight samples. Each
sample was spiked with only one PCB Aroclor; four samples were spiked with Aroclor 1242, four
samples were spiked with Aroclor 1254, and three samples were spiked with Aroclor 1260.
The recovery estimates vary from 60% and to 284%. The distribution of the
measurements is positively skewed. Nine of the eleven values range from 60% to 100% with two
higher values of 171% and 284%. Both high values are in samples in which the spiked amount was
much smaller than the native quantity, and thus these recovery values may have considerable
28
-------
measurement error. The variability of the recoveries is consistent with the results from the
analysis of variance components.
The recovery in the one soil sample is not unusual when compared to the recovery in
the fluff samples. Therefore, for summarizing the recovery values, the recoveries in soil and fluff
samples are assumed to be the same and the data are combined.
On the assumption that the recovery for the Soxhlet and tumbler methods may be
different, the data for these two methods are summarized separately.
Figure 5-6 shows a plot of the PCB recovery versus the spike amount. Because there
is no significant linear relationship between the spike amount and the recovery for the tumbler
measurements, the data are summarized using the average recovery. For the Soxhlet
measurements, the apparent linear relationship between the logarithm of the spike amount and
the recovery is not significant, based on a weighted analysis. Therefore, the Soxhlet recovery data
are also summarized below, using the average recovery.
Table 5-10 summarizes the recovery measurements for the Soxhlet and tumbler
extraction methods. The 95% confidence intervals are calculated using a weighted analysis and a t-
statistic which assumes that data have a normal distribution. Note that both confidence intervals
include 100%.
Table 5-10. PCB recovery for the Soxhlet and tumbler extraction methods
Extraction Method
Sample
Size
Percent
Recovery
(95% C.I.)
Comments
Soxhlet 3 78%a Highest measurement
is 280%
Tumbler 8 78%
aThe sample size for the Soxhlet recovery measurements is too small to reliably determine the 95% confidence interval.
Figure 5-7 shows the PCB recoveries data for the Soxhlet and tumbler extraction
methods with confidence intervals.
5.43 Recovery for Total and Leachable Lead and Cadmium
In order to estimate total lead and cadmium recovery, three soil samples and ten fluff
samples were spiked with a mixture of lead and cadmium. The selected samples included at least
one sample from each site. Due to missing values in the dataset, there are only 11 determinations
for total lead. Only the 10 fluff samples were spiked for estimating recovery of leachable lead and
cadmium using the EPTOX procedure.
29
-------
Percent
Recovery
300% -r
250% --
200% --
150% --
100% --
50% --
A Tumbler Recovery
o Soxhlet Recovery
0%
1 I I I I III 1 1—I I I I III 1 1—I I I I M|
10 100
Spike Amount (ppm)
1000
Figure 5-6. PCB Recovery versus Spike Amount
-------
300% -r
250% --
200% - -
Percent
Recovery
100% --
50% --
0%
Tumbler
Method
(n=8)
Soxhlet
Method
(n=3)
A Tumbler Recovery
A Mean Tumbler Recovery
* Soxhlet Recovery
o Mean Soxhlet Recovery
— 95% confidence interval
- - Perfect Recovery
Figure 5-7. PCB recovery for the tumbler and Soxhlet methods
-------
The recovery estimates for total lead vary from 60% to 230%. The recovery estimates
for total cadmium vary from 60% to 320%. The distribution of the measurements is positively
skewed. The high recovery values are associated with samples in which the native amount is large
relative to the spike amount, and thus these values may have considerable measurement error.
The variability of the recoveries is consistent with the results from the analysis of variance
components.
The recovery estimates for EPTOX lead vary from 93% to 109%. The recovery
estimates for total cadmium vary from 77% to 104%. The variability of the recoveries is consistent
with the results from the analysis of variance components.
No statistically significant differences by site, fluff input type (auto, white goods, or
mixed) or sample type (fluff versus soil) were found. For summarizing the recovery
measurements, it is assumed that these factors do not affect recovery. Therefore, all
measurements for each analyte are summarized together.
Figure 5-8 shows a plot of the estimated total lead and cadmium recovery versus the
spike amount (the spike amount was set to be similar to the native amount in the sample). Figure
5-9 shows a plot of the estimated EPTOX lead and cadmium recovery versus the spike amount.
Because there is no significant linear relationship between the spike amount and the recovery, the
data are summarized using the average recovery.
Table 5-11 summarizes the recovery measurements for lead and cadmium. The 95%
confidence intervals are calculated using a weighted analysis and a t-statistic which assumes that
data have a normal distribution. Note that all confidence intervals include 100%.
Figure 5-10 shows the total and leachable (EPTOX) lead and cadmium recovery data
and confidence intervals for the mean recovery.
32
-------
350% T-
300% --
250% --
Percent
Recovery
150% --
100% --
50% --
X
x
X
X Total Lead
A Total Cadmium
X
X
H—1 I I Mill 1—I I I I Mil 1—I M I Mil 1—I I I I lll|
10
100
Spike Amount (ppm)
1000
10000
Figure 5-8. Total lead and cadmium recovery versus Spike Amount
-------
120% -,
115% -
110% -
105% -
100% -
Percent
Recovery
95% -
90% -
85% -
80% -
TiCtL J
O
0 o
O
" "• °
• • o
•
0
o
o
• B
•
••
1 1 1 — 1 1 1 1 1 1 1 1 1 1 I 1 14 1 1 1 1 — 1 1 1 1 1 1
0.1
1 10
Spike Amount (ppm)
O EPTOX Lead
• EPTOX Cadmium
100
Figure 5-9. EPTOX lead and cadmium recovery versus Spike Amount
-------
350% -r
300% --
250% --
200% --
Percent
Recovery
150% --
100% ---
50% --
0%
Total Lead Total Cadmium
(n=13)
Leachable
Lead
(n=10)
Leachable
Cadmium
(n=10)
• Total Lead
* Total Cadmium
A Leachable Lead
X Leachable Cadmium
a Mean Total Pb = 102%
o Mean Total Cd = 109%
A Mean EPTOX Pb = 102%
* Mean EPTOX Cd = 97%
— 95% Confid. Interval
• - Perfect Recovery
Figure 5-10. Total and EPTOX lead and cadmium recovery
-------
Table 5-11. Total and leachable (EPTOX) lead and cadmium recovery
Analyte Measured
Total Lead
Total Cadmium
EPTOX Lead
EPTOX Cadmium
Sample
Size
11
13
10
10
Percent
Recovery
102%
(73%- 131%)
109%
(85%- 133%)
102%
(96%- 108%)
97%
(92%-103%)
Comments
One very high value of
320% in a soil sample
Extractability of the spiked
lead is much greater
than for the native lead
Extractability of the spiked
cadmium is much greater
than for the native cadmium
5.5 Calculation of Confidence Intervals for Mean Concentrations Across Sites
The procedures for calculating the confidence intervals for the average concentrations
across sites are sensitive to the assumptions used because the confidence intervals must be based
on relatively few samples with highly variable and skewed measurements. Alternate sets of
assumptions can result in very different confidence intervals, each with nominal coverage
probabilities of 95%. Several methods of calculating the confidence intervals and their associated
assumptions are considered and discussed below.
All procedures for calculating confidence intervals assume that the selected sites
represent a random sample of all shredder sites. This assumption is important to the
interpretation of the confidence intervals, however it cannot be tested using the data. Although
the procedure for selecting sites to be visited had some random components, the selection was not
entirely random. As a result, the confidence intervals must be interpreted as those which would be
determined if the sampled values had been obtained using a random sample.
All procedures for calculating confidence intervals also assume that the there is one
transformation which equalizes variance for all possible mean values. It is possible that the
variance increases linearly with the mean for small concentrations (consistent with a lognormal
distribution) and more slowly for high concentrations. This situation cannot be handled easily. All
of the procedures for calculating confidence intervals which were considered assume that the same
transformation equalizes variance over the range of the interval.
The two procedures considered for calculating confidence intervals are (1) a method
proposed by Land3 for calculating confidence intervals for averages from a log normal distribution
(analogous to using a t-statistic with a sample from a normal distribution), and (2) the methods
, C, E., Tables of Confidence Limits for Linear Functions of the Normal Mean and Variance.', Selected Tables in Mathematical
Statistics, Volume III (1975): 385-419, American Mathematical Society, Providence R.I.
36
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based on the bootstrap procedure. Criteria for selecting the procedure for calculating confidence
intervals include: (1) the applicability of the assumptions behind each procedures; and (2) the
performance of the method on data such as that obtained from the shredder sites. When
discussing alternate calculation methods the confidence intervals for the average PCB
concentration in fresh fluff is presented for the purposes of illustration.
The procedures adopted for performing hypothesis tests, calculating confidence
intervals for values other than site means, and calculating variance components assume that the log
transformed data have a normal distribution with constant variance. If these assumptions can be
extended to include differences between sites, an appropriate procedure for calculating confidence
intervals for means across sites is:
1. Calculate the average concentration at each site; and
2. Calculate the confidence interval for the mean using an appropriate procedure
for data with a lognormal distribution, as in Land.
These intervals can have very large upper limits when the estimated standard
deviation of the measurements is large or the sample sizes are small. For example, the upper limit
for the concentration of PCBs in soil is 10 billion ppm based on the Land procedure. This value is
clearly ridiculous. Although the assumption that the data have a lognormal distribution may
reasonably describe measurements at low concentrations, it cannot describe measurements in
samples with a high proportion of PCB.
The confidence interval using the Land procedure for the PCB concentration in fresh
fluff is 24 to 250 ppm. Although the assumption that the data have a lognormal distribution may
provide a reasonable description of the data for most purposes, the magnitude of the upper end of
the confidence interval is sensitive to the lognormal assumption. Due to averaging across nested
components and the likely affects of the sampling and subsampling procedures, the true
distribution of the site averages may be less skewed than that of the lognormal distribution, and
thus the Land procedure is likely to over-estimate the upper limit of the confidence intervals.
Another transformation, such as the square root, cube root, etc., might be more
appropriate than the log transformation for normalizing the data. Land provides a procedure for
calculating approximate confidence intervals for these transformations. The 95% confidence
intervals for PCB concentrations in fresh fluff, assuming the square root of the site concentrations
has a normal distribution, is 21 to 100 ppm. The upper end of this interval is substantially below
that based on the lognormal assumption.
Assuming that no transformation is required to normalize the data, a t-statistic can be
used to calculate the confidence interval. Due to the central limit theorem, this approach works
well in large samples, regardless of the distribution of the underlying data. In small samples of
data from a skewed distribution such as the fluff data, nominal 95% confidence intervals based on
a t-statistic may have an actual coverage probability as low as 80%4. When the intervals do not
cover the true concentration, they are almost always too low. i.e. the upper end of the interval is
below the true mean. With highly variable data, the lower end of this confidence interval may be
4Bascd on 1000 simulations, 7 sites, site concentrations have lognoimal distribution with cv= 15, the 'normal' confidence interval was too
high 2% of the time and too low 18.9% of the time (nominal values are 15% for both) for a total error rate of 19%.
37
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less than zero, an unreasonable value for concentration measurements. Using this normal
assumption, the 95% confidence interval for PCBs in fresh fluff is 7.8 to 79 ppm.
To the extent that unreasonably high upper confidence limits from the Land
procedure are due to variance estimates based on few degrees of freedom, some stability can be
gained from using a pooled variance. Pooling the variance across categories of measurements
requires being able to identify categories in which the variance can be expected to be the same.
This approach will reduce the size of confidence intervals in categories with few measurements or
higher variance and increase the length of the intervals for categories with low variance and many
measurements. Assuming the data have a lognormal distribution and that fresh fluff, stored fluff,
spillover, ferrous, nonferrous, and soil all have the same variance between site measurements, the
confidence interval for fresh fluff using a pooled variance (see Land 1975) is 13 to 290. This is
larger than without pooling because the fresh fluff data have lower variance that most other
categories of data.
Another procedure for calculating the confidence interval is to assume that the
differences between sites can be ignored and, therefore, that the measurements among runs are
independent. Confidence intervals based on runs will usually be smaller than those based on sites
because there will be more degrees of freedom (and thus more precision) for the variance
estimates. Using the Land procedure with PCB measurements in all fresh fluff runs, the 95%
confidence interval is 32 to 140 ppm. Because the majority of fluff comes from autos, the
confidence interval for auto runs might be used to make conclusions about all fresh fluff, provided
the user believes that contributions from other types of fluff can be ignored. Using PCB
measurements in auto runs, the 95% confidence interval is 14 to 58 ppm. If there are no
differences between sites and if the concentrations in runs have a lognormal distribution, the true
95% confidence interval will be between these two. To the extent that this interval ignores
systematic differences between sites, this nominal 95% interval will have a lower coverage
probability, perhaps as low as 80%5.
Because the procedures considered so far require assumptions (such as the
assumption that the data have a lognormal distribution) which are difficult to support or reject
based on the data, bootstrap procedures which require less specific assumptions were considered.
The bootstrap method assumes that the unknown distribution of the data is exactly equal to the
observed distribution. Simulations are then used to determine the distribution of the parameter of
interest, in this case the average concentrations aggregated over nested components. This
distribution is called the bootstrap distribution. Confidence intervals are then determined from
the bootstrap distribution.
The following steps were used to calculate the bootstrap distribution for PCBs in fresh
fluff:
(1) For each site, divide the sample measurements into the three types of input
material, auto, white goods, and mixed input. Determine the number of
observations, ns-, for each site, s = 1 to 7, and input type, i = 1 to 3.
^Simulations assuming a normal distribution, four sites, three runs per site, and equal components of variance for between runs and
between sites bad 83% coverage based on 1000 simulations.
38
-------
(2) For each bootstrap sample k, k = 1 to 10,000, repeat the following steps:
(2.1) From the sample measurements for each type of input material within
each site, select a random sample with replacement, x^x • k» J ' = * to "si-
Calculate the input type average from the random sample within each
ste as:
nsi
"
s
(2.2) Calculate a weighted average of the auto, white good and other input
type averages within each site to determine the site average
concentration (weights are shown in Table 5-1):
(23) Select with replacement a random sample of size seven from the seven
site averages. The average of these seven randomly selected site
concentrations is the overall average:
(2.4) Steps (2.1), (2.2, and (23) are repeated 10,000 times to obtain 10,000
bootstrap estimates of the overall average.
(4) Order the 10,000 bootstrap estimates from smallest to largest. This ordered list
defines the bootstrap distribution of the average PCB concentration.
A similar procedure is used for lead and cadmium in fresh fluff. For measurements in
stored fluff, spillover, and soil, the same procedure is used with the exceptions that the weighted
average in step (2.2) does not need to be calculated and the average in step (2.3) is over sites with
measurements.
Three methods of determining the confidence intervals from the bootstrap
distribution were considered and are listed below along with a brief description of their
characteristics.
(1) Percentile method The percentile method produces good confidence intervals if
there is a monotonic transformation which both makes the
distribution symmetric and stabilizes the variance for all
possible parameter values, and if the parameter estimated is
the median of the sampling distribution.
(2) Bias Corrected (BC) The bias corrected method assumes that there is a monotonic
normalizing and variance stabilizing transformation, however
39
-------
the requirement that the parameter of interest be the median
of the sampling distribution is dropped.
(3) Pivotal Quantity Method If there exists a known monotonic transformation such that the
transformed bootstrap distribution has the same distribution
(except for location) for all parameter values, then the
confidence interval for the parameter can be obtained from the
bootstrap distribution using the known transformation.6
The percentile and bias-corrected intervals require that the same distribution stabilize
the variance and normalize or symmetrize the data. If the data have a lognormal distribution, such
that the log transformed data have constant variance, the log transformation will stabilize the
variance, however the distribution of the mean will not be normal or symmetrical. Thus the same
transformation will not both normalize the distribution and stabilize the variance. If the
distribution of the data is skewed but not lognormal, it is also likely to be true that different
transformations are required to normalize the distribution and to stabilize the variance.
Therefore, the assumptions behind the percentile and BC methods do not strictly to apply to the
fluff data.
The pivotal quantity method can be used if the transformation which stabilizes the
variance is specified. A likely candidate is the log transformation. This choice is consistent with
the data analysis and is easy to implement. To the extent that the log transformation is close to the
correct (but unknown) transformation, the confidence intervals may perform well.
All of the procedures described above assume that the true variance of the data is the
same as the observed variance of the data, and thus that the variance is known. If the data is
known to be normally distributed, this is equivalent to using a z-statistic instead of a t-statistic for
calculating confidence intervals. Because the variance of the data is not actually known, all of the
bootstrap procedures considered will tend to underestimate the length of the confidence intervals.
The formulas for calculating the confidence intervals using the percentile, bias-
corrected, and pivotal quantity methods are presented in Table 5-12,
iis is a simplified version of the pivotal quantity method as presented in Introduction to the Theory of Statistics by Mood, Graybill,
and Boes, McGraw-Hill, Inc. 3rd Ed!, 1974, pp. 379-380.
40
-------
Table 5-12. Formulas for calculating bootstrap confidence intervals
Method
Bootstrap CI method
Percentile
to
Bias Corrected
to
Pivotal Quantity Method
Pivotal Quantity Method Log
transformation stabilizes variance.
to
to
Where 0 is the parameter estimate from the original sample,
$ is the cumulative normal distribution function,
G is the cumulative bootstrap distribution, and
H is a known transformation which standardizes the bootstrap distribution.
Monte Carlo simulations were used to evaluate the performance of the selected
bootstrap confidence interval calculation procedures. Each simulation involved 1000 simulations,
each with 1000 bootstrap samples. The data were assumed to have a normal distribution with
constant variance (mean= 1, sigma = .25) or a lognormal distribution with constant coefficient of
variation (mean=l, cv=l). Sample sizes of 7 and 20 were used, approximating either 7 sites
dominated by between site differences or 20 samples where between site differences are small.
The parameter to be estimated is the average. Table 5-13 provides coverage probabilities overall,
and the probability that the interval is either too low (the upper limit is less than the true mean) or
too high (the lower limit is greater than the true mean). All confidence intervals were nominal
95% intervals, so the desired percentages are 5% for overall lack of coverage, 2.5% for being too
high or too low.
41
-------
Table 5-13. Coverage probability of bootstrap confidence intervals based on simulations
Distribution and
sample size
Normal (cv=.25)
n=7
Normal (cv= 25)
n=20
Lognormal (cv= 1)
n = 7
Lognormal (cv= 1)
n=20
Equation
Percentile
BC
Pivotal
Percentile
BC
Pivotal
Percentile
BC
Pivotal
Percentile
BC
Pivotal
Interval too low
(Nominal = .025)
.059
.062
.033
.031
.034
.024
.186
.177
.125
.099
.095
.071
Probability
Interval too high
(Nominal = .025)
.067
.059
.092
.027
.026
.034
.014
.015
.056
.017
.018
.034
Non-coverage
(Nominal = .050)
.126
.121
.125
.058
.060
.058
.200
.192
.181
.116
.113
.105
Within the bootstrap simulation error, the overall coverage probability does not
depend on the equation used. Bootstrap confidence intervals perform better on normal than
skewed lognormal data. Bootstrap intervals perform better on larger sample sizes. The nominal
95% confidence intervals are 88% confidence intervals for 7 normal data, 81% intervals for 7
lognormal data, 94% intervals for 20 normal data, and 89% intervals for 20 lognormal data.
For data from a lognormal distribution, the pivotal quantity method provides the best
central 95% confidence intervals.
For normal data, the percentile and bias-corrected intervals perform best, however
the upper limit of the confidence interval based on the pivotal quantity is closer to the nominal
value of 0.025 for the simulation with a coefficient of variation of 0.25.
The pivotal quantity method with a log transformation was chosen for calculating the
confidence intervals. Of the three bootstrap procedures, this method appears to perform best for
highly skewed data. Compared to the parametric procedures, explicit assumptions about the
distribution of the data are not necessary. In addition, the bootstrap sampling may reflect the
components of variance better than the parametric methods based on the site average
42
-------
concentrations. Note however that the bootstrap intervals have a true coverage of less then the
nominal 95%.
The confidence intervals for PCBs in fresh fluff based on different assumptions are
presented in Table 5-14 and shown in Figure 5-11. These different confidence intervals are
presented to provide some information on the sensitivity of the intervals to the calculation
assumptions.
Table 5-14. Confidence intervals for mean PCB concentrations in fresh fluff calculated under
several assumptions
Calculation
assumptions
Nominal 95%
confidence interval
(ppm)
Comments
Log transformed site 24 to 250
concentrations have a normal
distribution
Square root of site 21 to 100
concentrations have a normal
distribution
Untransformed site 7.8 to 79
concentrations have a normal
distribution
Log of the site concentrations, 13 to 290
have a normal distribution
(pooled variance)
Log of run concentrations 32 to 140
have a normal distribution
(all input types)
Log of run concentrations 14 to 58
have a normal distribution
for auto runs
Percentile method with the 16 to 84
bootstrap
Bias Corrected method 17 to 86
with the bootstrap
Pivotal quantity method, 22 to 120
assuming the log transformation
stabilizes variance
If data is not as skewed as
lognormal, CI may be too high.
Choice of square root
transformation is arbitrary.
Because the data is skewed, this
CI will be too low, coverage
probability will be below 95%.
Depends on identification of
categories assumed to have
similar variance
Proportion or runs by input type
difficult to represent, CI coverage
probability may be below 95%.
Represents auto runs only, CI
coverage probability may be
below 95%.
Assumptions are only approximately
met, coverage will be less than 95%
Assumptions are only approximately
met, coverage will be less than 95%
Assumptions are consistent with the
data, coverage will be less than 95%
43
-------
1000 T
100 —
PCB
Cone.
(ppm)
10 - -
Log (site) Sqrt (site) Site Log (site), Log (all Log (auto
pooled
variance
runs) runs)
Percen - Bias
Pivotal
Values assumed to have a normal distribution using Land
die Corrected Quantity
(log)
Bootstrap method
Figure 5-11. Nominal 95% confidence intervals for the average PCB concentration in fresh fluff under varying assumptions
-------
Appendix 6-A
Test Pattern for Laboratory Analyses
6-A-l
-------
Test Pattern for Laboratory Analyses
The tables in this appendix contain the assignment of laboratory tests and batch
numbers to subsamples and splits of material. There is one line for each discrete sample of
primary material (e.g fluff or soil) that is to be analyzed. Two Listings are given: one sorted
by Site-Sample-Subsample-Split and the other sorted by Batch-Site-Sample-Subsample-
SpliL
The codes used for ExtrMeth are "Tum"=Tumbler, "Tuml"=Tumbler for which the
first rinse is analyzed, and "Sox"=SoxhleL
The field Analvte indicates which subsamples are to be archived, and which
samples are "Unused."
The codes for the field Comment are "Rep"=Replicate, "Spike"=Spike, and
(Dup)=Duplicate to indicate the analysis of a duplicate injection. For one subsampie the
"Jar Broke" during the tumbler extraction. Site "A" in Batch 10 is a "Composite" of all 7
Field Blank buckets. Site "B" in Batch 11 is a "Composite" of all 6 Field Blank jars. For
ExtrMeth=EPTOX, the terms "Repl" and"Rep2" specify replicates which themselves will
be replicated and spiked. With "Repl", both a Replicate and a Spike will be generated at
the digestion stage, for a total of three extracts. In addition, there will be a Duplicate
measurement for the primary extract. "Rep2" is the same as "Repl" except that there will
also be a Duplicate measurement for the Spike.
-------
Test Pattern - Site Sort
4/1 1/89
I Site I
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Sample I
1
1
1
1
1
2
2
2
2
2
3
3
3
3
3
4
4
4
4
4
5
5
5
5
5
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
7
8
8
8
8
8
9
9
9
9
9
10
1 0
10
Subsamp
1
2
2
3
4
1
1
2
3
4
1
2
2
3
4
1
2
3
3
4
1
2
3
4
4
1
1
2
2
3
4
5
6
6
6
6
6
6
6
7
1
1
2
3
4
1
2
3
4
4
1
2
3
(Split
1
2
1
2
1
2
1
2
1
2
1
2
1
2
3
4
5
6
7
1
2
1
2
1
| Analyte 1
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
Pb/Cd
Pb/Cd
Archive4
Archived
PCB
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
PCB
PCB
Pb/Cd
Pb/Cd
PCB
Archive4
Archived
PCB
Pb/Cd
Pb/Cd
PCB
PCB
PCB
PCB
PCB
PCB
PCB
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
PCB
Unused
Pb/Cd
Pb/Cd
Archived
PCB
Archive4
Archive4
PCB
Archived
Pb/Cd
Pb/Cd
Archive4
PCB
Pb/Cd
Stream
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
St
St
llnTypel
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
ExtrMeth
EFTOX
3050
Turn
EFTOX
3050
Turn
EPTOX
3050
Turn
Turn
Turn
EPTOX
3050
Turn
Turn
EFTOX
3050
Turn
Tumi
Sox
Sox
Turn
Turn
Turn
EPTOX
EPTOX
3050
3050
3050
3050
EPTOX
Turn
EPTOX
3050
Turn
Turn
EPTOX
3050
Turn
EFTOX
I Comment I Batch I
12
1 9
5
13
19
6
14
1 9
7
8
Rep(Dup) 8
15
1 9
20
10
16
1 9
1
1
2
Rep 2
Jar Broke 3
Rep(Dup) 3
Spike 6
15
Rep1 1 5
19
Rep(Dup) 1 9
Spike(Dup) 1 9
22
21
20
17
19
5
7
18
19
8
12
-------
Test Pattern - Site Sort
4/1 1/89
I Site I Sample I Subsamp | Split | Analyte | Stream MnType I ExtrMeth |
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1 0
1 0
1 1
1 1
1 1
1 1
1 1
12
12
12
12
12
12
12
12
12
12
13
14
14
14
14
15
1 6
17
1 7
1 7
17
17
17
17
18
18
18
18
19
19
19
19
20
20
20
20
21
3
4
1
2
3
4
4
1
2
2
2
2
2
2
2
3
4
1
2
3
4
1
2
3
4
4
4
4
1
2
3
4
1
2
3
4
1
2
3
4
2
1
2
1
2
3
4
5
6
7
1
1
2
3
4
1
1
1
1
Pb/Cd
Archives
Archived
Archive2
Archive4
Pb/Cd
Pb/Cd
Archived
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archive2
Archive4
Unused
PCS
Archive4
Archives
Archive2
Unused
Unused
PCB
Archive4
Archives
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archive2
Archived
Archive4
Pb/Cd
Archives
Archive4
PCB
Archives
Archive2
Pb/Cd
Archive4
Unused
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
Fe A
Fe W
Fe W
Fe W
Fe W
Nf A
Nf W
So
SO
So
So
SO
So
So
So
So
So
So
So
So
So
SO
So
So
So
So
Bb
3050
EPTOX
3050
EPTOX
EPTOX
3050
3050
3050
EPTOX
3050
Turn
Sox
3050
3050
3050
3050
3050
3050
Sox
3050
1 9
13
19
12
Rep1 1 2
19
Rep(Oup) 1 9
Spike 1 9
21
22
10
1 1
19
Rep(Oup) 1 9
Spike(Oup) 1 9
22
19
19
1 1
19
22
Unused
Bi
2
2
2
2
2
2
2
2
2
1
1
1
1
1
2
2
2
2
1
2
3
3
4
1
2
2
3
1
2
1
Archive4
Archived
Pb/Cd
Pb/Cd
PCB
Archive4
PCB
PCB
Pb/Cd
FF
FF
FF
FF
FF
FF
FF
FF
FF
A
A
A
A
A
A
A
A
A
EPTOX
3050
Turn
Turn
Tumi
EPTOX
16
19
9
1
1
17
-------
Test Pattern - Site Sort
4/1 1/89
Site
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Sample |
2
2
3
3
3
3
3
4
4
4
4
4
5
5
5
5
5
6
7
7
7
7
7
7
7
7
7
8
8
8
8
8
9
9
9
9
9
9
9
9
9
9
10
10
1 0
10
1 0
1 1
1 1
1 1
1 1
1 1
12
12
Subsamp
3
4
1
1
2
3
4
1
2
3
4
4
1
1
2
3
4
1
2
2
3
4
5
6
7
8
1
2
3
4
4
1
2
2
2
2
2
2
2
3
4
1
1
2
3
4
1
2
3
3
4
1
1
Split
2
1
1
2
1
2
1
2
1
2
1
2
1
2
3
4
5
6
7
1
2
1
2
1
2
I Analyte
Pb/Cd
PCB
Pb/Cd
Pb/Cd
Archived
PCB
Archive4
Archive4
Archives
PCB
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archived
PCB
Archive4
Unused
PCB
Pb/Cd
Pb/Cd
PCB
PCB
PCB
Archives
Archive7
Archives
PCB
Archive4
Archived
Pb/Cd
Pb/Cd
PCB
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archived
Archive4
Pb/Cd
Pb/Cd
PCB
Archived
Archive4
Archived
Archive4
Pb/Cd
Pb/Cd
PCB
Pb/Cd
Pb/Cd
Stream
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
I InTypel
A
A
A
A
A
A
A
A
A
A
A
A
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
O
O
0
O
O
O
O
O
O
O
0
0
O
0
O
0
O
O
O
O
O
O
ExtrMeth I Comment
dOSO
Sox (Dup)
STOX
3050
Turn
Turn
STOX
3050
B=TOX
3050
Turn
Turn Rep(Oup)
BTOX
3050
Turn Spike
Turn
Turn
Turn
BTOX
3050
Turn
ETOX
STOX Rep1
3050
3050 Rep(Dup)
3050 Spike
BTOX
3050
BTOX
3050
Turn
BTOX
3050
Turn
STOX
3050
I Batch I
1 9
2
18
1 9
10
5
12
1 9
18
19
6
7
12
1 9
1 0
7
20
8
id
19
10
17
17
19
19
19
21
22
15
19
5
16
19
6
17
19
-------
Test Pattern - Site Sort
4/1 1/89
Site |
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Sample
12
12
12
13
13
13
13
13
14
14
14
14
14
15
1 5
15
1 5
15
16
16
16
1 6
16
17
17
1 7
17
17
18
18
18
18
19
19
19
19
20
20
20
20
21
21
21
21
22
22
22
22
22
22
22
23
23
23
Subsamp
2
3
4
1
2
2
3
4
1
2
3
3
4
1
2
2
3
4
1
2
3
3
4
1
2
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
2
2
2
3
4
1
2
3
(Split
1
2
1
2
1
2
1
2
1
2
1
2
3
5
1
1
I Analyte J
Archive2
Archived
Archive4
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
Archived
Archive4
Pb/Cd
Pb/Cd
PCB
Archive4
Pb/Cd
Pb/Cd
Archive2
Archives
Archive2
Archive4
Pb/Cd
Pb/Cd
Archived
Archived
Pb/Cd
Pb/Cd
Archive4
PCB
Archives
PCB
Archive4
Archive2
Archived
Archive4
PCB
Archive2
PCB
Archive2
Archived
Archive4
Archive4
PCB
Archived
Archive2
Archived
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archive4
PCB
Pb/Cd
Archived
Archive4
Stream
FF
FF
FF
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
SP
SP
SP
Sp
Sp
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Nf
Nf
Nf
Nf
Nf
Nf
Nf
Nf
So
So
So
So
So
So
So
So
So
So
I InTypel
0
O
o
A
A
A
A
W
W
W
W
A
A
A
A
W
W
W
W
ExtrMeth
STOX
3050
Turn
STOX
3050
Turn
BTOX
3050
EPTOX
3050
EPTQX
3050
Turn
Turn
Turn
Turn
Turn
3050
3050
3050
3050
Sox
3050
I Comment I Batch I
14
19
9
15
19
1 0
16
19
17
19
15
19
5
5
6
6
7
19
Rep(Dup) 1 9
Spike(Dup) 1 9
22
11
19
-------
Test Pattern - Site Sort
4/1 1/89
I Site I
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
Sample I
23
24
24
24
24
25
25
25
25
26
27
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
4
4
4
4
4
5
6
6
6
6
6
7
7
7
7
7
Subsamp
4
1
2
3
4
1
2
3
4
1
2
3
4
4
1
2
3
3
4
4
4
5
6
6
6
6
6
6
6
7
8
1
2
3
3
4
1
1
2
3
4
1
2
3
4
4
1
2
3
4
4
Split
1
1
1
1
2
1
2
3
1
2
3
4
5
6
7
1
2
1
2
1
2
1
2
I Analyte
PCB
Archived
Archive4
Archive2
Pb/Cd
Archive2
Archive4
Pb/Cd
Archives
Unused
Unused
Archive4
PCB
Archived
Pb/Cd
Pb/Cd
PCB
PCB
PCB
PCB
PCB
PCB
PCB
Archive7
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archives
PCB
Archive4
Archived
Pb/Cd
Pb/Cd
PCB
Pb/Cd
Pb/Cd
Archives
PCB
Archive4
Unused
PCB
Archives
Archive4
Pb/Cd
Pb/Cd
Archived
Archive4
PCB
Pb/Cd
Pb/Cd
Stream
So
So
So
So
So
So
so
So
So
Bb
Bj
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
UnTypel
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
W
W
W
W
W
W
W
W
W
W
W
ExtrMeth I Comment
Sox
3050
3050
Turn
BTOX
3050
Turn
Turn Spike
Turn Rep
Tumi
Sox
Sox Rep
Sox Spike
BTOX
EPTOX Rep1
3050
3050 Rep(Dup)
3050 Spike
BTOX
3050
Turn
BTOX
3050
Turn
BTOX
3050
Turn
Turn
BTOX
3050
Turn
BTOX
3050
I Batch I
1 1
19
19
6
13
1 9
1
3
3
1
2
4
4
12
12
1 9
19
19
21
22
20
14
19
7
15
19
8
9
14
19
10
15
19
-------
Test Pattern - Site Sort
4/1 1/89
Site I
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
Sample I
8
8
8
8
8
8
8
8
8
9
9
9
9
9
1 0
1 0
1 0
1 0
1 0
1 1
1 1
1 1
1 1
1 1
12
12
12
12
12
13
13
13
13
13
14
14
14
14
14
14
14
14
14
14
15
16
17
18
19
20
21
22
23
24
Subsamp
1
2
3
3
4
5
6
7
8
1
1
2
3
4
1
2
2
3
4
1
2
3
3
4
1
2
3
4
4
1
2
3
4
4
1
2
2
2
2
2
2
2
3
4
I Split
1
2
1
2
1
2
1
2
1
2
1
2
1
2
3
4
5
6
7
I Analvte I
PCB
PCS
Pb/Cd
Pb/Cd
PCB
Archived
PCB
PCB
PCB
Pb/Cd
Pb/Cd
Archive4
Archive2
Archives
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
PCB
Archived
Pb/Cd
Pb/Cd
Archive4
PCB
Archive4
Archived
Pb/Cd
Pb/Cd
Archive2
Archived
Archive4
Pb/Cd
Pb/Cd
Archive4
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archived
PCB
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Stream
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
Sp
SP
Sp
Sp
Sp
Sp
SP
SP
SP
SP
SP
Sp
SP
SP
Sp
Fe
Fe
Nf
Nf
So
So
So
So
So
Bb
llnTypel
W
W
W
W
'W
W
W
W
W
O
O
O
0
O
O
O
0
O
O
O
0
0
O
O
0
O
O
O
O
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
W
A
A
ExtrMeth | Comment
Turn Rep(Dup)
Turn
EPTQX
3050
Turn Spike
Turn Spike
Turn
Turn Rep(Dup)
B=TDX
3050
BFTOX
3050
Turn
Turn
STOX
3050
Turn
BTOX
3050
BTOX
3050
BTOX
STOX Rep1
3050
3050 Rep(Dup)
3050 Spike
EPTOK
3050
Turn
I Batch I
5
5
16
19
8
20
20
20
18
19
12
19
7
8
13
19
9
14
19
16
19
14
14
19
19
19
21
22
6
-------
Test Pattern - Site Sort
4/1 1/89
|Site| Sample I Subsamp | Split | Analyte [Stream [inTypej ExtrMeth | Comment [Batch]
25
Unused
Bi
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
1
1
1
1
1
2
3
4
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
7
7
7
7
7
7
8
9
9
9
9
9
10
10
10
10
10
11
1 1
11
1 1
11
12
12
12
12
12
12
12
12
1
2
3
4
4
1
2
2
2
2
2
2
2
3
4
1
2
3
3
4
1
1
2
3
4
4
1
2
3
3
4
1
1
2
3
4
1
2
3
4
4
1
2
2
2
2
2
2
2
1
2
1
2
3
4
5
6
7
1
2
1
2
1
1
2
1
2
1
2
1
2
3
4
5
6
7
PCB
Archive4
Archived
Pb/Cd
Pb/Cd
Unused
Unused
Unused
PCB
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
PCB
PCB
Archive4
PCB
Pb/Cd
Pb/Cd
Archives
Pb/Cd
Pb/Cd
PCB
Archive4
PCB
PCB
Unused
Archived
PCB
Pb/Cd
Pb/Cd
Archive4
Pb/Cd
Pb/Cd
PCB
Archived
Archive4
Archive2
Archive4
Archived
Pb/Cd
Pb/Cd
Archived
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
Turn
EPTQX
3050
Turn
BPTOX
BPTOX
3050
3050
3050
STOX
3050
Turn
Turn
Turn
S=TOX
3050
EPTQX
3050
Sox
Turn
Tumi
Turn
EPTOX
3050
B=TOX
3050
Turn
B=TOX
3050
BPTOX
BPTOX
3050
3050
3050
EPTOX
3050
9
16
19
20
13
Rep1 1 3
1 9
Rep(Dup) 1 9
Spike 1 9
21
22
10
Rep(Dup) 1 0
5
17
19
18
19
2
1
1
5
18
19
12
19
6
13
19
13
Rep2 13
19
Rep(Dup) 1 9
Spike 1 9
21
22
-------
Test Pattern - Site Sort
4/1 1/89
(Site
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
I Sample I
12
12
13
13
13
13
13
14
14
14
14
14
15
16
16
16
16
1 7
18
18
18
18
19
19
19
19
20
20
20
20
21
21
21
21
22
22
22
22
23
24
1
1
1
1
1
1
1
2
2
2
2
2
3
3
Subsamp ]
3
4
1
2
3
3
4
1
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
2
3
4
5
6
1
2
3
4
4
1
2
1
2
1
2
1
1
1
1
1
1
1
2
1
2
1
t| Analvte I
Archive4
Archive2
PCB
Archived
Pb/Cd
Pb/Cd
Archive4
Pb/Cd
Pb/Cd
Archived
Archive2
Archive4
Unused
Archived
Archive4
Archive2
PCB
Unused
Archive2
Archive4
Archived
PCB
PCB
Pb/Cd
Archived
Archive4
Archived
Pb/Cd
Archive4
Archive2
PCB
Pb/Cd
Archive4
Archived
Archived
Archive2
Archive4
Pb/Cd
Unused
Unused
PCB
Pb/Cd
Pb/Cd
PCB
PCB
Archive 6
PCB
Archive4
Archived
PCB
Pb/Cd
Pb/Cd
Archive4
Pb/Cd
Stream
St
St
Sp
SP
SP
Sp
Sp
SP
SP
SP
Sp
Sp
Fe
Fa
Fe
Fe
Fe
Nf
Nf
Nf
Nf
Nf
So
So
So
So
So
So
So
So
So
So
So
So
So
So
So
So
Bb
Bi
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
UnTvoel
B
B
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
ExtrMeth | Comment
Turn
EPTOX
3050
EFTOX
3050
Turn
Turn
Sox
3050
3050
Sox
3050
3050
Turn Spike
EPTOX
3050
Turn
Turn Rep(Dup)
Turn
Turn
BPTOX
3050
EPTOX
I Batch I
7
17
19
18
19
7
8
1 1
19
19
1 1
19
19
9
12
19
6
6
20
7
13
19
14
8
-------
Test Pattern - Site Sort
4/1 1/89
| Site |
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
Sample |
3
3
3
4
4
4
4
4
5
5
5
5
5
6
6
6
6
6
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
8
8
8
8
8
9
9
9
9
9
10
10
10
10
10
1 1
11
1 1
1 1
Subsamp
2
3
4
1
2
2
3
4
1
1
2
3
4
1
2
2
3
4
1
2
3
3
4
4
5
6
7
8
8
8
8
8
8
8
8
1
2
3
4
4
1
2
2
3
4
1
2
2
3
4
1
2
2
3
Split
2
1
2
1
2
1
2
1
2
1
2
3
4
5
6
7
8
1
2
1
2
1
2
1
2
Analyte
Pb/Cd
Archived
PCB
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
Pb/Cd
Pb/Cd
Archive4
PCB
Archived
Archive4
Pb/Cd
Pb/Cd
Archives
PCB
PCB
PCB
PCB
PCB
PCB
PCB
Archives
PCB
Archive7
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archived
Archive4
Archive2
Pb/Cd
Pb/Cd
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
Archives
Pb/Cd
Pb/Cd
Archive2
Stream
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
St
llnTypel
A
A
A
A
A
A
A
A
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
ExtrMeth
3050
Turn
BTOX
3050
Turn
EPTOX
3050
Turn
BTOX
3050
Turn
Turn
Turn
Sox
Sox
Turn
Tumi
Turn
BTOX
BTOX
3050
3050
3050
BTOX
EPTOX
3050
BTOX
3050
BTOX
3050
Turn
BTOX
3050
Turn
BTOX
3050
I Comment I Batch I
19
8
15
19
9
17
19
6
18
1 9
7
Spike(Dup) 7
1
2
Rep 2
Rep 1
1
20
16
Rep1 1 6
19
Rep(Oup) 1 9
Spike 1 9
21
Rep1 2 1
22
14
19
15
19
7
16
19
8
17
19
-------
Test Pattern • Site Sort
4/1 1/89
I Site I
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
Sample I
1 1
12
12
12
12
12
13
13
•13
13
13
14
15
15
15
1 5
16
17
18
1 9
20
21
22
23
1
1
1
1
1
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
5
5
5
5
Subsamp
4
1
2
3
4
4
1
2
3
4
4
1
2
3
4
1
2
2
3
4
1
2
3
4
4
1
2
2
3
3
4
5
6
7
8
8
1
1
2
3
4
1
2
2
3
(Split
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
I Analyte I
Archive4
Archive4
Archived
PCS
Pb/Cd
Pb/Cd
Archive2
Archive4
Archived
Pb/Cd
Pb/Cd
Unused
PCB
Archive2
Archived
Archive4
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Archive4
Pb/Cd
Pb/Cd
Archived
PCB
PCB
Archived
Archive4
Pb/Cd
Pb/Cd
PCB
PCB
PCB
PCB
PCB
PCB
Archive7
Archives
PCB
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archive4
Archived
PCB
Archive4
Pb/Cd
Pb/Cd
PCB
Stream
St
Sp
SP
Sp
Sp
Sp
SP
SP
SP
SP
Sp
Fe
Fe
Fe
Fe
Fe
Nf
Nf
So
So
So
So
Bb
Bj
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
UnTypel
A
W
W
W
W
A
W
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
W
W
W
W
ExtrMeth I Comment
Turn
EPTOX
3050
BTOX
3050
Turn
BTOX
3050
Turn
Turn
EPTOX
3050
Turn
Turn Rep
Tumi
Sox
Sox Rep(Dup)
Turn Spike
Turn
STOX
3050
EPTOX
3050
Turn
EPTOX
3050
Turn (Dup)
I Batch I
8
12
19
13
19
8
16
19
10
5
17
19
1
3
3
2
4
5
20
18
19
12
19
6
12
19
1
1 0
-------
Test Pattern • Site Sort
4/1 1/89
I Site I
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
'6
6
6
6
6
6
Sample I
5
5
6
6
6
6
6
7
7
7
7
7
8
9
9
9
9
9
10
10
10
10
10
10
10
10
10
10
1 1
1 1
1 1
1 1
1 1
12
12
12
12
12
13
13
13
13
14
15
15
15
15
16
17
18
18
18
18
19
Subsamp
3
4
1
1
2
3
4
1
1
2
3
4
1
2
2
3
4
1
2
3
3
3
3
3
3
3
4
1
2
3
3
4
1
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
I Split
1
1
2
1
2
1
2
1
2
3
4
5
6
7
1
2
1
2
I Analyte I
PCB
PCB
Pb/Cd
Pb/Cd
PCB
Archives
Archive4
Pb/Cd
Pb/Cd
PCB
PCB
PCB
Unused
Archive2
Pb/Cd
Pb/Cd
Archives
Archive4
Archived
Archive4
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
PCB
PCB
Archive4
Pb/Cd
Pb/Cd
Archived
Pb/Cd
Pb/Cd
PCB
Archive4
Archives
Archive2
Archive4
Archived
PCB
Unused
Archive2
PCB
Archived
Archive4
Unused
Unused
Archived
PCB
Archive2
Archive4
Archive4
Stream
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Nf
Nf
Nf
Nf
Nf
HnTypel
W
W
W
W
W
W
W
W
W
W
W
W
W
O
0
0
O
O
O
O
O
O
O
0
O
0
O
O
O
O
O
O
O
0
O
O
0
O
A
A
A
A
A
W
W
W
W
O
O
A
A
A
A
W
ExtrMeth I
Tumi
Sox
EFTOX
3050
Turn
EFTOX
3050
Turn
Turn
Turn
EPTDX
3050
EFTOX
EFTOX
3050
3050
3050
EFTOX
3050
Turn
Turn
EFTOX
3050
EFTOX
3050
Turn
Turn
Turn
Turn
I Comment | Batch |
1
2
13
19
8
14
19
Rep(Dup) 9
20
9
15
19
18
Rep1 1 8
19
Rep(Dup) 1 9
Spike 1 9
21
22
10
5
16
19
17
19
6
9
10
9
11
-------
Test Pattern - Site Sort
4/1 1/89
Site |
6
6
6
6
6
6
6
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
Sample
19
19
1 9
20
21
22
23
1
1
1
1
1
2
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
6
6
6
6
6
7
7
7
7
7
8
9
9
9
9
9
10
10
10
10
Subsamp
2
3
4
1
1
2
3
4
1
1
2
2
2
3
4
5
6
6
6
6
6
6
6
6
6
7
8
1
2
3
4
4
1
2
2
3
4
1
1
2
3
4
1
2
3
3
(Split
1
2
1
2
3
1
2
3
4
5
6
7
8
9
1
2
1
2
1
2
1
2
I Analyte I
PCS
Archive2
Archived
Unused
Unused
Unused
Unused
Pb/Cd
Pb/Cd
Archive4
PCB
Archives
Unused
Unused
PCB
PCB
PCB
PCB
PCB
PCB
PCB
Archive?
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archived
PCB
Unused
PCB
Archives
Archive4
Pb/Cd
Pb/Cd
Archive4
Pb/Cd
Pb/Cd
PCB
Archives
Unused
Pb/Cd
Pb/Cd
Archive4
PCB
Archives
PCB
Archived
Pb/Cd
Pb/Cd
Stream
Nf
Nf
Nf
Ru
Ru
Ru
Bb
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
St
St
St
UnTypel
W
W
W
A
A
W
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
ExtrMeth
Turn
BPTOX
3050
Turn
Turn
Tumi
Sox
Sox
Sox
Turn
Turn
E=TOX
BTOX
3050
3050
3050
E=TOX
3050
3050
3050
Turn
Turn
BPTOX
3050
BTOX
3050
Turn
BTUX
3050
Turn
Turn
BFTOX
3050
{ Comment
Rep
Rep(Dup)
Spike(Dup)
Spike(Dup)
Rep2
Rep(Dup)
Spike
Rep(bup)
Spike
I Batch I
10
13
19
7
1
1
2
2
2
1
1
14
14
19
19
19
21
22
22
22
20
8
14
19
15
19
9
18
19
9
10
12
19
12
-------
Test Pattern - Site Sort
4/1 1/89
| Site |
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
A
B
Sample I
10
1 1
1 1
1 1
1 1
1 1
12
12
12
12
12
13
13
13
13
13
14
14
14
14
14
15
15
15
15
16
17
18
19
19
19
19
20
20
20
20
21
21
21
21
21
21
21
21
21
22
22
22
22
23
24
Subsamp
4
1
2
3
3
4
1
2
3
3
4
1
2
3
4
4
1
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
1
1
1
2
2
2
3
4
1
2
3
4
[Split
1
2
1
2
1
2
1
2
1
1
1
1
2
3
4
1
2
3
1
I Analyte I
Archive4
Archives
Archive2
Pb/Cd
Pb/Cd
Archive4
Archive4
Archived
Pb/Cd
Pb/Cd
Archive2
Archived
PCB
Archive4
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archive4
Archive2
Archived
Archive4
PCB
Archive2
Archived
Unused
Unused
Unused
Archive4
Archives
Pb/Cd
PCB
Archive4
Archives
Pb/Cd
Archive2
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
PCB
PCB
PCB
Archive4
Archives
Archives
Archive4
Archive2
Pb/Cd
Unused
Unused
PCB
PCB
Stream
St
St
St
St
St
St
St
St
St
St
St
SP
SP
SP
Sp
Sp
SP
Sp
Sp
SP
Sp
Fe
Fe
Fe
Fe
Fe
Nf
Nf
So
So
So
S3
So
So
So
So
So
So
So
So
So
So
So
So
So
So
So
So
So
Bb
Bi
Bb
Bi
HnTypel
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
ExtrMeth
BTOX
3050
EPTOX
3050
Turn
BTOX
3050
BTOX
3050
Turn
3050
Sox
3050
3050
3050
3050
3050
Sox
Sox
Sox
3050
Turn
Sox
I Comment I Batch I
13
19
14
19
9
1 4
19
15
19
5
19
1 1
19
19
Rep(Dup) 1 9
Spike 1 9
22
1 1
Rep(Dup) 1 1
Spike 1 1
19
Composite 1 0
Composite 1 1
13
-------
Test Pattern - Batch Sort 4/11/89
| Site |
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
Sample I
10
10
11
11
11
12
12
13
13
13
14
15
15
15
16
17
18
19
20
21
22
23
1
1
2
2
3
3
4
4
5
6
6
8
9
9
9
10
10
1 1
11
12
12
13
13
13
14
15
15
15
16
17
18
18
Subsamp
1
3
1
3
4
1
2
1
2
3
2
3
4
1
3
2
3
5
6
2
3
1
3
4
1
3
4
1
2
2
4
3
' 4
1
2
3
1
3
4
1
3
I Split I Analyte |
Archive4
Archived
Archived
Archive2
Archive4
Archive4
Archived
Archive2
Archive4
Archived
Unused
Archive2
Archives
Archive4
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Archive4
Archives
Archived
Archive4
Archive7
Archives
Archive4
Archived
Archive4
Archived
Archive4
Unused
Archive2
Archived
Archive4
Archived
Archive4
Archive4
Archived
Archive4
Archived
Archive2
Archive4
Archived
Unused
Archive2
Archived
Archive4
Unused
Unused
Archived
Arcnive2
Stream
St
St
St
St
St
so
SP
Sp
SP
Sp
Fe
Fe
Fe
Fe
Nf
Nf
So
So
So
So
Bb
Bj
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Fe
Nf
Nf
llnTypel ExtrMeth I Comment I Batch I
A
W
W
W
A
W
A
A
A
A
A
A
A
A
W
W
W
W
0
0
O
O
O
0
O
O
O
A
A
A
A
W
W
W
0
O
A
A
12
-------
Test Pattern - Batch Sort 4/11/89
| Site |
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
Sample |
8
9
9
10
10
11
1 1
1 1
12
12
12
13
13
14
14
14
15
16
16
16
17
18
18
18
19
19
20
20
20
21
21
22
22
22
23
24
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
8
9
9
Subsamp
1
4
3
4
1
2
3
1
3
4
2
4
2
3
4
1
2
3
1
2
3
3
4
1
3
4
3
4
1
2
3
5
1
2
1
3
1
3
2
4
1
3
5
7
1
2
3
1
3
I Split I Analvte I
Unused
Archived
Archive4
Archived
Archive4
Archive2
Archive4
Archived
Archived
Archive4
Archive2
Archives
Archive4
Archived
Archive2
Archive4
Unused
Archived
Archive4
Archive2
Unused
Archive2
Archive4
Archived
Archived
Archive4
Archived
Archive4
Archive2
Archive4
Archived
Archived
Archive2
Archive4
Unused
Unused
Archive 6
Archive4
Archived
Archive4
Archived
Archive4
Archived
Archive4
Archives
Archive4
Archived
Archived
Archive7
Archived
Archive4
Archive2
Archive4
Archived
Stream
FF
St
St
St
St
St
St
St
St
St
St
Sp
SP
SP
SP
Sp
Fe
Fe
Fe
Fe
Nf
Nf
Nf
Nf
So
So
So
So
So
Sb
So
So
So
So
Bb
Bj
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
MnTypel ExtrMeth I Comment I Batch!
A
B
B
B
B
B
B
B
B
B
B
A
A
A
A
A
A
A
A
A
A
A
A
A
*
A
A
A
A
A
A
A
W
W
W
W
W
W
11
-------
Test Pattern - Batch Sort 4/11/89
| Site |
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
-4
Sample I
24
24
25
25
25
26
27
1
1
2
2
3
3
4
4
5
6
6
7
7
8
9
9
9
10
10
1 1
1 1
12
12
13
13
13
14
14
15
16
17
18
19
20
21
22
23
24
25
1
1
2
3
4
6
6
7
Subsamp
2
3
1
2
4
1
3
5
7
1
2
2
4
2
3
1
2
5
2
3
4
1
3
2
4
2
3
1
2
3
1
3
2
3
1
4
3
I Split I Analvte I
Archive4
Archive2
Archive2
Archive4
Archived
Unused
Unused
Archive4
Archived
Archive7
Archives
Archive4
Archived
Archived
Archive4
Unused
Archives
Archive4
Archived
Archive4
Archives
Archive4
Archive2
Archived
Archive4
Archived
Archived
Archive4
Archive4
Archived
Archive2
Archived
Archive4
Archive4
Archived
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Unused
Archive4
Archived
Unused
Unused
Unused
Archive4
Archived
Archive4
Stream
So
So
So
S3
So
Bb
Bj
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
SP
SP
SP
Sp
Sp
Fe
Fe
Nf
Nf
S3
S3
S3
So
So
Bb
Bj
FF
FF
FF
FF
FF
FF
FF
FF
UnTypel ExtrMeth | Comment I Batch |
A
A
A
A
A
A
A
A
W
W
W
W
W
W
O
O
O
O
O
O
0
O
O
A
A
A
A
A
A
W
A
A
A
A
A
A
A
A
A
A
10
-------
Test Pattern - Batch Sort
4/11/89
| Site |
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Sample I
22
1
1
2
3
3
4
4
5
5
6
7
7
7
8
8
9
9
10
10
1 1
1 1
12
12
12
13
13
14
14
15
15
15
16
16
16
17
17
18
18
18
19
19
19
20
20
20
21
21
21
22
22
23
23
24
Subsamp
1
2
1
2
4
1
2
2
4
6
7
8
2
3
3
4
3
4
1
2
2
3
4
1
3
1
2
1
3
4
1
2
4
1
3
1
3
4
1
2
' 4
2
3
4
1
3
4
1
3
2
3
1
1 Split 1 Analvte 1
Unused
Archive4
Archived
Arcrtive4
Archived
Archive4
Archive4
Archived
Archived
Archive4
Unused
Archived
Archive?
Archived
Archive4
Archives
Archived
Archive4
Archived
Archive4
Archived
Archive4
Archive2
Archived
Archive4
Archive4
Archived
Archived
Archive4
Archive4
Archive2
Archived
Archive2
Archive4
Archived
Archived
Archive4
Archived
Archive4
Archive2
Archived
Archive4
Archive2
Archive2
Archived
Archive4
Archive4
Archived
Archive2
Archived
Archive4
Archived
Archive4
Archived
Stream
Bj
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
St
St
St
St
SP
SP
Fe
Fe
Fe
Fe
Fe
Fe
Nf
Nf
Nf
Nf
Nf
Nf
S3
So
So
So
So
llnTypel ExtrMeth | Comment I Batch I
A
A
A
A
A
A
A
W
W
W
W
W
W
W
W
O
O
O
O
0
O
0
O
O
*
A
A
A
W
W
W
A
A
A
W
W
W
-------
Test Pattern • Batch Sort
4/11/89
| Site |
7
1
1
1
2
2
3
3
4
4
5
6
7
7
7
7
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Sample I
4
6
12
17
9
22
2
14
5
12
7
10
4
4
4
21
1
1
2
2
3
3
5
5
7
8
8
9
9
10
10
1 1
11
1 1
12
12
12
13
14
14
14
15
16
17
17
18
18
18
19
19
20
20
20
21
Subsamp
6
6
2
4
2
2
6
2
2
2
8
3
6
6
6
1
1
3
2
3
1
3
1
2
2
4
1
3
1
4
1
2
3
1
3
4
2
3
4
2
3
2
3
4
2
3
1
2
4
I Split
6
6
7
4
7
5
7
7
7
7
8
7
7
8
9
4
I Analyte I
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Archive4
Archived
Archive4
Archived
Archive4
Archived
Archive4
Archived
Unused
Archived
Archive4
Archive4
Archived
Archive4
Archived
Archived
Archive2
Archive4
Archived
Archive2
Archive4
Unused
Archive4
Archived
Archive2
Unused
Unused
Archive4
Archived
Archive2
Archived
Archive4
Archived
Archive4
Archived
Archive2
Archive4
Unused
Stream
FF
FF
St
So
FF
S3
FF
Sp
FF
St
FF
FF
FF
FF
FF
So
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
St
St
St
St
Fe
Fe
Fe
Fe
Nf
Nf
So
So
So
So
So
So
So
So
So
So
Bb
llnTypel
A
W
O
A
A
A
B
W
O
A
A
A
A
A
A
A
A
A
W
W
W
W
W
A
W
W
W
A
W
ExtrMeth I Comment
EPTOX
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050 Rep(Dup)
3050 Spike
3050
I Batch I
21
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
8
-------
Test Pattern - Batch Sort
4/1 1/89
| Site |
6
6
6
6
6
6
6
6
6
6
6
6
6
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
1
1
2
3
3
3
3
4
5
5
6
6
7
1
1
2
3
3
4
4
5
5
6
Sample I
1
2
3
4
5
6
7
9
10
10
1 0
1 1
12
1
4
4
4
6
7
9
10
1 1
12
13
14
19
20
21
21
21
22
4
6
7
2
8
8
8
5
1
7
3
7
4
6
12
9
2
14
5
12
7
7
10
Subsamp
2
4
8
1
2
1
1
2
3
3
3
3
1
1
6
6
6
4
2
1
3
3 -
3
4
1
3
3
1
1
1
4
4
7
5
8
6
7
8
1
6
6
7
3
8
6
2
2
6
2
2
2
8
8
3
I Split I
2
2
2
2
2
2
2
2
3
4
5
2
2
2
3
4
5
2
2
2
2
2
2
2
2
1
1
1
2
3
1
i
7
6
6
6
6
6
6
6
7
6
Analyte
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
PCB
PCS
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
I Stream
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
SP
SP
So
So
So
SO
So
So
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
FF
FF
SP
FF
St
FF
FF
FF
MnTypel
A
A
A
A
W
W
W
O
O
O
0
O
0
A
A
A
A
A
A
A •
A
A
W
W
A
W
W
W
A
A
W
A
W
A
W
O
A
A
A
B
W
W
O
ExtrMeth |
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
EPTOX
EPTQX
BFTOX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
I Comment I Batch I
19
19
19
19
19
19
19
19
19
Rep(Oup) 1 9
Spike 1 9
19
19
19
19
Rep(Dup) 1 9
Spike 1 9
19
19
19
19
19
19
19
19
19
19
19
Rep(Dup) 1 9
Spike- 19
19
20
20
20
20
Spike 2 0
20
Rep(Dup) 20
20
20
20
20
20
20
21
21
21
21
21
21
21
21
Rep1 21
21
-------
Test Pattern - Batch Sort
4/1 1/89
| Site |
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
Sample I
22
23
24
25
1
2
2
2
3
4
6
7
8
9
10
1 1
12
13
14
14
14
1
5
5
5
6
7
9
10
1 1
12
12
12
13
14
19
20
21
22
1
2
3
4
5
6
7
7
7
8
9
10
11
12
13
Subsamp
2
1
4
3
4
6
6
6
3
1
4
4
3
1
2
3
4
4
2
2
2
4
2
2
2
3
1
3
1
4
2
2
2
3
1
2
2
2
4
2
4
2
2
1
2
8
8
8
4
2
2
2
4
4
I Split I
3
1
1
1
2
3
4
5
2
2
2
2
2
2
2
2
2
2
3
4
5 '
2
3
4
5
2
2
2
2
2
3
4
5
2
2
1
1
1
1
2
2
2
2
2
2
3
4
5
2
2
2
2
2
2
Analyte
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
I Stream
So
So
So
So
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
SP
SP
SP
Sp
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
SP
SP
So
So
So
So
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
Sp
Sp
llnTypel
A
A
A
A
A
A
W
W
W
O
O
0
O
A
A
A
A
A
A
A
A
A
A
B
B
B
B
B
B
A
A
A
A
A
A
W
W
W
W
W
ExtrMeth
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
I Comment
Spike(Dup)
Rep(Dup)
Spike
Rep(Dup)
Spike
Rep(Dup)
Spike
Rep(Dup)
Spike
Rep(Dup)
Spike
I Batch I
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
1 9
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
-------
Test Pattern - Batch Sort
4/11/89
|Site|
6
1
2
2
3
4
4
4
5
6
6
6
7
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Sample (
12
9
3
5
9
7
9
14
6
3
10
10
9
1
2
3
4
5
6
6
6
8
9
10
1 1
12
12
12
17
17
17
18
19
20
1
2
3
4
5
7
8
9
9
9
10
1 1
12
13
14
15
16
17
22
22
Subsamp
1
4
1
1
1
1
3
1
2
8
3
3
1
2
1
2
3
4
6
6
6
1
4
3
4
2
2
2
4
4
4
1
1
3
3
3
1
4
1
2
4
2
2
2
1
3
1
2
3
2
3
2
2
2
I Split I
1
1
1
1
1
1
1
1
1
1
1
2
1
2
2
2
2
2
3
4
5
2
2
2
2
3
4
5
1
2
3
1
1
1
2
2
1 2
2
1 2
2
2
3
4
5
2
2
2
2
2
2
2
2
1
2
Analyte
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
LStream
FF
St
FF
FF
FF
FF
St
Sp
FF
FF
FF
FF
St
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
S3
So
So
So
So
So
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
SP
So
So
UnTvpel
O
A
W
O
A
B
A
W
A
0
O
A
A
A
A
W
W
W
W
W
A
A
A
A
W
W
W
O
O
0
O
O
0
ExtrMeth
EPTOX
EPTOX
EFTOX
EPTDX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
EPTOX
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
3050
I Comment
Rep1
Rep(Dup)
Spike(Dup)
Rep(Dup)
Spike
Rep(DiSp)
Spike(Dup)
Rep(Oup)
Spike
Rep(Dup)
I Batch I
17
18
18
18
18
18
18
18
18
18
18
18
18
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
-------
Test Pattern - Batch Sort
4/1 1/89
Site |
6
7
7
1
2
3
3
3
3
3
5
5
6
7
7
7
7
7
1
1
1
2
2
2
3
3
5
5
6
7
7
1
2
2
2
3
3
4
5
5
5
6
6
1
2
2
2
2
2
4
4
5
5
6
Sample I
6
1
1 1
3
13
3
6
12
14
14
3
8
7
4
4
6
12
13
4
6
6
10
14
17
4
7
4
9
9
7
14
5
1
11
15
8
13
1
7
7
10
1
11
8
2
9
9
12
16
6
13
5
11
2
Subsamp
1
1
3
2
2
3
4
4
2
2
2
4
1
6
6
4
3
4
3
6
6
1
3
2
1
4
2
2
2
2
1
4
3
3
2
3
4
4
8
8
2
2
3
1
3
2
2
1
3
3
3
1
2
4
Split I
1
1
1
1
1
1
1
1
1
2
1
1
1
1
2
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
l"
1
1
1
1
1
2
1
1
1
1
1
1
2
1
1
1
1
1
1
1
Analyte
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
I Stream
FF
FF
St
FF
St
FF
FF
FF
Sp
Sp
FF
St
FF
FF
FF
FF
St
Sp
FF
FF
FF
FF
St
Sp
FF
FF
FF
St
FF
FF
SP
FF
FF
FF
St
FF
Sp
FF
FF
FF
St
FF
FF
FF
FF
FF
FF
FF
St
FF
SP
FF
St
FF
UnTypel
W
A
A
A
W
O
A
A
A
W
A
A
A
A
A
W
W
0
A
W
A
O
A
A
W
A
O
W
A
A
W
W
A
O
W
A
0
O
O
A
A
W
A
ExtrMeth | Comment
EPTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BFTOX
BTOX Rep1
BTOX
EPTOX
BTOX
BTOX
BTOX Rep2
BTOX
STOX
BTOX
BTOX
BTOX
BTOX Rep1
BTOX
BTOX
STOX
STOX
STOX
BTOX
STOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
STOX Rep1
BTOX
BTOX
BTOX
BTOX
BTOX
STOX
BTOX Rep1
BTOX
BTOX
BTOX
BTOX
BTOX
STOX
BTOX
I Batch I
13
13
13
14
4
4
4
4
4
14
14
14
14
14
14
14
14
14
15
15
15
15
15
15
15
15
15
15
15
15
15
16
16
16
16
16
16
16
16
16
16
16
16
17
17
17
17
17
17
17
17
17
17
17
-------
Test Pattern - Batch Sort
4/11/89
| Site |
7
1
1
2
2
2
2
3
4
4
6
6
6
6
7
A
1
1
2
2
4
4
7
7
7
7
B
1
1
1
1
2
2
3
3
3
4
5
5
6
6
7
1
1
2
3
3
4
4
4
4
4
5
5
Sample |
13
5
14
3
7
9
14
7
5
5
1
1 0
1 5
19
10
17
19
22
23
19
21
19
21
21
21
1
1 0
12
12
4
7
2
2
10
10
1
12
4
5
10
2
1 1
8
1
11
5
5
1 1
12
12
2
13
Subsamp
2
3
1
3
3
1
4
3
3
4
4
4
2
2
1
1
4
4
4
1
1
4
2
2
2
2
3
2
2
4
2
6
6
2
1
2
4
1
2
3
1
4
4
4
3
2
2
4
2
2
4
4
I Split I
1
1
1
1
1
1
1
1
2
3
1
1
1
2
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
2
1
1
Analyte
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Pb/Cd
Stream
Sp
FF
Fe
FF
FF
FF
St
FF
FF
FF
FF
FF
Fe
Nf
St
Bb
So
So
So
So
So
SO
So
So
So
So
Bj
FF
St
St
St
FF
FF
FF
FF
FF
St
FF
Sp
FF
FF
St
FF
St
FF
FF
FF
FF
FF
St
St
St
FF
Sp
MnTvoel
A
W
W
A
W
O
W
A
A
A
O
W
W
A
A
W
A
A
O
B
A
A
W
A
W
A
O
A
A
B
B
B
A
ExtrMeth
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
BTOX
1 Comment 1 Batch I
9
10
10
10
Spike 1 0
10
10
10
10
Rep(Dup) 1 0
10
10
10
10
10
Composite 1 0
1 1
1 1
1 1
11
1 1
1 1
1 1
1 1
Rep(Dup) 1 1
Spike 1 1
Composite 1 1
12
12
12
Rep1 1 2
12
12
12
Rep1 1 2
12
12
12
12
12
12
12
13
13
13
13
13
13
Rep1 1 3
13
13
Rep2 13
13
13
-------
Test Pattern - Batch Sort
4/1 1/89-
I Site I
1
2
2
2
2
3
3
4
5
5
5
6
6
1
1
2
2
2
3
3
4
4
5
5
5
5
7
1
1
1
2
3
3
3
4
5
5
5
5
6
7
2
2
3
3
4
5
5
6
6
6
6
7
7
Sample I
6
5
1 1
19
20
1
14
10
1
1
5
4
12
3
9
7
7
21
3
10
13
16
2
6
7
9
1
4
4
10
8
4
8
1 1
18
3
10
12
15
6
6
1
13
6
12
1
1
4
7
7
13
18
7
9
Subsamp
5
3
4
3
1
2
4
2
3
4
3
4
2
4
2
1
4
2
4
4
1
4
3
4
1
4
3
1
2
2
1
3
4
1
4
4
4
3
1
2
1
4
4
1
1
1
1
4
2
4
4
2
3
3
Split | Analvte
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
Stream
FF
FF
FF
Fe
Nf
FF
Sp
St
FF
FF
FF
FF
FF
FF
St
FF
FF
Nf
FF
FF
Sp
Fe
FF
FF
FF
St
FF
FF
FF
St
FF
FF
FF
FF
Nf
FF
St
SP
Fe
FF
FF
FF
St
FF
FF
FF
FF
FF
FF
FF
Fe
Nf
FF
St
UnTvpel
W
W
O
W
A
A
A
B
A
A
W
A
O
A
W
W
W
A
0
A
A
A
W
W
A
A
A
W
A
W
O
A
A
W
W
A
A
W
O
A
A
A
W
W
A
A
A
ExtrMeth
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
I Comment I Batch I
Spike 6
6
6
6
6
6
6
6
6
Rep(Oup) 6
6
6
6
7
7
Rep(Oup) 7
7
7
7
7
7
7
7
7
Spike(Dup) 7
7
7
8
Rep(Dup) 8
8
8
8
Spike 8
8
8
8
8
8
8
8
8
9
9
9
9
9
Spike 9
9
Rep(Dup) 9
9
9
9
9
9
-------
Test Pattern • Batch Sort
4/11/89
| Site |
1
1
2
2
3
3
4
4
5
5
5
6
6
6
7
7
7
7
1
1
2
3
4
5
5
6
6
7
7
7
1
1
3
3
6
6
3
3
6
1
1
2
2
2
2
3
3
4
4
6
6
6
7
1
Sample)
6
6
2
2
2
2
7
7
7
7
7
3
5
5
4
4
4
4
6
6
2
2
7
7
7
3
5
4
4
4
6
6
2
2
3
3
2
2
3
1
8
4
10
17
18
8
8
6
9
2
3
1 1
15
2
Subsamp i
1
1
2
2
1
3
4
4
2
4
4
1
3
3
1
1
3
4
2
2
4
4
2
3
3
3
4
2
2
2
3
4
2
3
2
2
4
4
3
4
3
3
2
4
2
1
2
2
2
1
4
1
2
4
I Split |
1
2
1
1
1
1
2
1
1
1
2
3
2
3
2
Analyte
PCB
PCS
PCS
PCS
PCB
PCS
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
PCB
I Stream
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
SP
Fe
FF
FF
FF
St
FF
FF
FF
Fe
FF
I In Type |
W
W
A
A
A
A
A
A
W
W
W
A
W
W
A
A
A
A
W
W
A
A
A
W
W
A
W
A
A
A
W
W
A
A
A
A
A
A
A
A
W
A
O
A
W
W
A
B
A
A
O
A
A
ExtrMeth
Turn
Tumi
Turn
Tumi
Turn
Tumi
Turn
Tumi
Turn
Turn
Tumi
Turn
Turn
Tumi
Turn
Tumi
Turn
Turn
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Sox
Turn
Turn
Turn
Turn
Turn
Tumi
Sox
Sox
Sox
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
Turn
I Comment
Rep
(Dup)
Rep
Spike(Dup)
Rep
(Dup)
Rep
Rep(Dup)
Spike(Oup)
Jar Broke
Rep(Dup)
Spike
Rep
Rep
Rep
Spike
Rep(Dup)
Rep(Dup)
Spike
I Batch I
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
6
-------
Test Pattern - Batch Sort 4/11/89
| Site |
6
6
6
6
6
6
6
6
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
Sample!
18
19
19
19
20
21
22
23
1
1
2
3
4
4
5
6
6
7
7
8
9
9
10
10
11
1 1
11
12
12
12
13
13
14
14
14
15
15
15
16
17
18
19
19
20
20
20
21
21
22
22
22
23
24
Subsamp | Split
4
1
3
4
2
4
5
7
2
3
1
4
2
4
2
4
1
2
4
1
2
4
1
3
2
3
4
1
3
4
1
2
1
2
4
3
4
1
2
3
I Analyte |
Archive4
Archive4
Archive2
Archived
Unused
Unused
Unused
Unused
Archive4
Archived
Unused
Unused
Archive7
Archived
Unused
Archived
Archive4
Archive4
Archived
Unused
Archive4
Archived
Archived
Archive4
Archived
Archive2
Archive4
Archive4
Archived
Archive2
Archived
Archive4
Archive4
Archive2
Archived
Archive4
Archive2
Archived
Unused
Unused
Unused
Archive4
Archived
Archive4
Archived
Archive2
Archive4
Archived
Archived
Archive4
Archive2
Unused
Unused
Stream
Nf
Nf
Nf
Nf
Ru
Ru
Ru
Bb
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
FF
St
St
St
St
St
St
St
St
St
St
SP
SP
SP
Sp
Sp
Fe
Fe
Fe
Fe
Nf
Nf
So
So
So
So
So
So
Sb
So
So
So
Bb
Bj
llnTypel ExtrMeth I Comment I Batch |
A
W
W
W
A
A
W
A
A
A
A
A
A
A
A
A
A
A
A
•
A
A
A
A
A
A
A
A
A
A
A
13
-------
Appendix 6-B
Soxhlet/Tumbler Design
Comparison
6-B-l
-------
METHOD COMPARISON OF SOXHLET AND TUMBLER EXTRACTION TECHNIQUES
USING PAIRED METHODS
The purpose of this experiment is to compare extraction efficiencies of the Tumbler
and Soxhlet extraction methods. The Soxhlet procedure is the conventional method. The Tumbler
protocol is an attempt to improve precision and reduce cost without seriously compromising
extraction efficiency (accuracy). To determine if the Tumbler extraction procedure will be
appropriate for the remainder of the pilot study PCB analyses, eight buckets of fluff will be
analyzed using paired subsample comparisons.
For the Soxhlet extraction method, the subsample will be pulverized (to 9mm) and
mixed to provide as homogeneous a mixture as is practically possible (other analyses may be run
on this material in the future). One split of approximately 80 grams of this material will be
randomly selected for each Soxhlet extraction.
In addition to the estimate of the difference in extraction efficiency between the two
methods, this study will provide an estimate of variability between subsamples from each bucket
(using the Tumbler extraction method) and variability between splits within pulverized subsamples
(using the Soxhlet extraction Method).
Number of Samples:
From each of five buckets, two subsamples will be analyzed for PCB concentration
using the Tumbler method and two splits from the same pulverized subsample will be analyzed
using the Soxhlet extraction method. In addition, for each of three buckets of fluff, one subsample
will be analyzed by the Tumbler method and one split will be analyzed by the Soxhlet method. In
all, there will be 13 Soxhlet analyses and 13 Tumbler analyses performed on eight buckets of fluff.
The five Replicates will provide an estimate of the variability associated with each method.
Results:
The results of this method comparison was the adoption of the tumbler method for
the Fluff Pilot Program.
-------
Appendix 6-C
Aroclors Lot Numbers
6-C-l
-------
Analytical Reference Materials
The type, source, lot numbert and purity of the analytical reference
Materials are as follows:
lype Source Lot no. Purity
Aroclor 1016
Aroclor 1221
Aroclor 1232
Aroclor 1242
Aroclor 1242
Aroclor 1248
Aroclor 1254
Aroclor 1260
Aroclor 1262
U.S. EPA
U.S. EPA
Supelce
U.S. EPA
Monsanto Electric Grade
U.S. EPA
U.S. EPA
U.S. EPA
U.S. EPA
K032
5701
LA07745
L04C
KA4015
L01D
L03E
L02F
L046G
100S technical
IOCS technical
100% technical
10W technical
98*
10W technical
100* technical
100« technical
100$ technical
C-2
-------
Appendix 6-D
Certificates of Analysis
6-D-l
-------
Catalog Number:
Cement and Matrix:
Starting Material:
Starting Material Lot Number:
PLPB2 Lot No. K-2
Pb/KNO,. Pb/Wultia
lead nitrate Pb(N03}2
103418
CC ARC: Trace MetaiBc Impurities in starting material via DC ARC [4C elements checked: only
values detected are Sated].
Element PPM
Kg
Si
10-20
.5-2
Traceafciiity Documentation For Solution Standard:
1. Classical Wet Assay:
Titrimetry: KOTA titration using Xylenol Orange indicator. EDTA
standardized assist, Fb(K03)2 NBS S8« 9928.
S. Instrumentation Analysis Ey !nductve;y Coupled Piaema Spectrometer [ICP]:
Via NSS SF« U2121-2.
S.Saiances srs ctfibratad with NSS weight sets NIJ. #78552, f75543, #82355, according :c
NBS circuiar 547 3.4.3.
Spax plasma sobdo^ sundards BI-Q guaranteed stabfe and acorsca to ± 0.5% of iaoeiM cencart-acicr for sre year
dat« «f purcAasa. This vama is tfw «« af arnyidsv* errons aassdatcd with enaJytiesl datemviatcns. pipetcng and e
ea faw voiurne. For chese scktitt^ w« «sa rt^ ptrty acids. 18 megofcm double dacwod wawr and t-rpw iviaae uottfes. Ail
used is dess A.
Signed by:
>/. v
Chea.Prod.Manager 27MAR89
Titie: ^_________ Da:e:
-------
Catalog Number:
Eemant and Matrix:
Starting Material:
Starting Materiel Lot Number:
PLCD2 (BB-2)
Cd/HN03, Cd/Wultie
CadmiuB Cd
07381R
DC ARC: Trees MatfiiBc Im^rifcas in starting material via OC APC [40 elements checked; oniy
values detected sre feted].
Sament PPM
NO METALLIC IMPURITIES DSTSCTED
Trsceability Documentation For Solution Standard;
1 Classics! ^VB* Assav
' Tltria«try: EDTA titretloti uelng Xyi*Bol Orange as Indicator.
standardized against ?bC?03}2 MSS SfiM
SB!
S. InscruTieneacion AriaJvs/s Sy 'nciucsivsly Coupled Plasma Spectrometer [J
Via NBS SR« 2121-1.
3.Be!ances are calibrated with NBS
NSS circular 547 3.4.3.
-^C sets N.J. #78552. #7S543, ^62395, according :c
«e*xl£ffl8 gr« g-^er^ceed swtfe artd 8ccure:e w ± 0.5% af labeled sdrcanvstan fee ou year ?
cf porcnasa. TT-ia veius «efte «u« o( cunxi«e
-------
Appendix 6-E
PCB Aroclors
6-E-l
-------
AROCLORS
PCBArodors
Arodors were commercially produced complex mixtures of PCB's, composed of a
variety of homologs and isomers. Each Arodor has somewhat different chemical and lexicological
properties and different applications. An analysis of the specific Arodors in fluff samples was
conducted to obtain some insight into the sources of PCB's, the necessity of regulating fluff
material, and/or the regulatory options. For most samples, the PCB analysis included an
identification of three PCB Arodors: 1242,1254, and 1260. For this program, these three Arodors
are assumed to be the only ones present. This section summarizes the analysis of the PCB
concentrations by Arodor.
Due to the similarity in the response for Arodors 1254 and 1260, the individual
Arodors are very difficult to dfomgniyh Therefore, the sum of the concentrations of Arodors
1254 and 1260 (referred to here as 1254/1260) was reported along with the identification of the
dominant Arodor. A similar but more pronounced situation exists with Arodors 1016 and 1242,
the dominant PCB's used in capacitors. Arodor 1016 (41% Chlorine) is a successor product to
Arodor 1242 (42% Chlorine). Figures 6-E-l and 6-E-2 illustrate the gas chromatographic
separation of Arodors 1254 and 1260, and Arodors 1016 and 1242, respectively Tables 6-E-l and
6-E-2 describe the molecular composition of some Arodors induding 1016,1242, 1254, and 1260.:
Table 6-E-L Molecular composition of Arodors 1242,1248,1254,1260
Presence (%) in Arodor
Chlorobiphenvl
composition 1242 1248 1254 1260
c12H9a
C^Hgdj
C12H703
c12H6a4
Cj2 ^dj
C^ HA CL
3
13
28
30
22
4
2
18
40
36
4
11
49
34
12
38
41
8
1
tOnuuscrr of PCB's, Hatzmger. Safe, aad Zipx Krieprr. Mabbu. Plooda. 1981
6-E-3
-------
Table 6-E-2. Molecular composition of Aroclors 1221,1016, 1242,1254
Presence (%) in Aroclor*
Chlorobiphenyl
composition
C12 H10
12 :)
a IT t-*\
12 8 2
C112 H7 C13
C12 H6 C14
C12 H5 C15
C12 H4 C16
C12 H3 C17
C12 H2 C18
1221
11
51
32
4
2
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AROCLOR 1254
AROCLOR 1260
Aidrifi
Figure 6-E-l. Gas chromatographic separation of Aroclors 1254 and 1260
6-E-5
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AROCLOR
AROCLOR 1242
Time (mm)
Figure 6-E-2. Gas chromatographic separation of Aroclor 1016 and Aroclor 1242
6-E-6
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Appendix 6-F
Method 8080, Organochlorine
Pesticides and PCBs
6-F-l
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METHOD 8080
ORGANOCHLORINE PESTICIDES AND PCBs
/
1.0 SCOPE AND APPLICATION
1.1 Method 8080 Is used to determine the concentration of various
organochlorlne pesticides and polychlorlnated blphenyls (PCBs). Table 1
Indicates compounds that may be determined by this method and lists the method
detection Hm1t for each compound In reagent water. Table 2 lists the
practical quantltatlon limit (PQL) for other matrices.
2.0 SUMMARY OF METHOD
2.1 Method 8080 provides gas chromatographlc conditions for the
detection of ppb levels of certain organochlorlne pesticides and PCBs. Prior
to the use of this method, appropriate sample extraction techniques must be
used. Both neat and diluted organic liquids (Method 3580, Waste Dilution) may
be analyzed by direct Injection. A 2- to 5-uL sample 1s Injected Into a gas
chromatograph (GC) using the solvent flush technique, and compounds 1n the GC
effluent are detected by an electron capture detector (ECD) or a halogen-
specific detector (HSD).
2.2 The sensitivity of Method 8080 usually depends on the level of
Interferences rather than on Instrumental limitations. If Interferences
prevent detection of the analytes, Method 8080 may also be performed on
samples that have undergone cleanup. Method 3620, Flor1s1l Column Cleanup, by
Itself or followed by Method 3660, Sulfur Cleanup, may be used to eliminate
Interferences In the analysis.
3.0 INTERFERENCES
3.1 Refer to Methods 3500 (Section 3.5, In particular), 3600, and 8000.
3.2 Interferences by phthai ate esters can pose a major problem 1n
pesticide determinations when using the electron capture detector. These
compounds generally appear In the chromatogram as large 1 ate-eluting peaks,
especially In the 15X and SOX fractions from the Florlsll cleanup. Common
flexible plastics contain varying amounts of phthalates. These phthalates are
easily extracted or leached from such materials during laboratory operations.
Cross contamination of clean glassware routinely occurs when plastics are
handled during extraction steps, especially when solvent-wetted surfaces are
handled. Interferences fron phthalates can best be minimized by avoiding
contact with any plastic materials. Exhaustive cleanup of reagents and
glassware may be required to eliminate background phthalate contamination.
The contamination from phthalate esters can be completely eliminated with a
m1crocoulometr1c or electrolytic conductivity detector.
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TABLE 1. GAS CHROMATOGRAPHY OF PESTICIDES AND PCBs*
Compound
Aldrln
a-BHC
tf-BHC
0-BHC
7-BHC (Llndane)
Chlordane (technical)
4, 4 '-ODD
4, 4 '-DDE
4, 4 '-DDT
Dleldrln
Endosulfan I
Endosulfan II
Endosulfan sulfate
Endrl n
Endrfn aldehyde
Heptachlor
Heptachlor epoxlde
Methoxychlor
Toxaphene
PCB-1016
PCB-1221
PCB-1232
PCB-1242
PCB-1248
PCB-1254
PCB-1260
Retention
Col. 1
2.40
1.35
1.90
2.15
1.70
e
7.83
5.13
9.40
5.45
4.50
8.00
14.22
6.55
11.82
2.00
3.50
18.20
e
e
e
e
e
e
e
e
time (m1n)
Col. 2
4.10
1.82
1.97
2.20
2.13
e
9.08
7.15
11.75
7.23
6.20
8.28
10.70
8.10
9.30
3.35
5.00
26.60
e
e
e
e
e
e
e
e
Method
Detection
limit (ug/L)
0.004
0.003
0.006
0.009
0.004
0.014
0.011
0.004
0.012
0.002
0.014
0.004
0.066
0.006
0.023
0.003
0.083
0.176
0.24
nd
nd
nd
0.065
nd
nd
nd
aU.S. EPA. Method 617. OrganocnloHde Pesticides and PCBs,
Environmental Monitoring and Support Laboratory, Cincinnati, Ohio 45268.
e * Multiple peak response.
nd * not determined.
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TABLE 2. DETERMINATION OF PRACTICAL QUANTITATION LIMITS (PQL) FOR VARIOUS
MATRICES4
Matrix Factor1*
Ground water " 10
Low-level soil by sonlcatlon with GPC cleanup 670
High-level soil and sludges by sonlcatlon 10,000
Non-water mlsdble waste 100,000
aSample PQLs are highly matrix-dependent. The PQLs listed herein are
provided for guidance and may not always be achievable.
bPQL » [Method detection limit (Table 1)] X [Factor (Table 2)]. For non-
aqueous samples, the factor 1s on a wet-weight basis.
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4.0 APPARATUS AND MATERIALS
4.1 Gas chromatograph;
4.1.1 Gas Chroaatograph: Analytical system complete with gas
chromatograph suitable for on-column Injections and all required
accessories* Including detectors, column supplies, recorder, gases, and
syringes. A data system for measuring peak heights and/or peak areas 1s
recommended.
4.1.2 Columns:
4.1.2.1 Column 1: Supelcoport (100/120 mesh) coated with 1.5%
SP-2250/1.95X SP-2401 packed 1n a 1.8-m x 4-mm I.D. glass column or
equivalent.
4.1.2.2 Column 2: Supelcoport (100/120 mesh) coated with 3%
OV-1 1n a 1.8-m x 4-mm 1.0. glass column or equivalent.
4.1.3 Detectors: Electron capture (ECD) or halogen specific (HSD)
(I.e., electrolytic conductivity detector).
4.2 Kuderna-Danlsh (K-D) apparatus:
4.2.1 Concentrator tube: 10-mL, graduated (Kontes K-570050-1025 or
equivalent). Ground-glass stopper Is used to prevent evaporation of
extracts
4.2.2 Evaporation flask: 500-mL (Kontes K-570001-500 or
equivalent). Attach to concentrator tube with springs.
4.2.3 Snyder coluan: Three-ball macro (Kontes K-503000-0121 or
equivalent).
4.2.4 Snyder col ton: Two-ball micro (Kontes K-569001-0219 or
equivalent).
4.3 Boiling chips; Solvent extracted, approximately 10/40 mesh (silicon
carbide or equivalent).
4.4 Water bath; Heated, with concentric ring cover, capable of
temperature control (±5*C). The bath should be used In a hood.
4.5 Volumetric flasks; 10-, 50-, and 100-raL, ground-glass stopper.
4.6 Mlcrosyrlnqe; 10-uL.
4.7 Syringe; 5-nL.
4.8 Vials: Glass, 2-, 10-, and 20-mL capacity with Teflon-Hned screw
cap.
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5.0 REAGENTS
5.1 Solvents: Hexane, acetone, toluene, Isooctane (2,2,4-trlmethyl-
pentane) (pesticide quality or equivalent).
5.2 Stock standard solutions;
5.2.1 Prepare stock standard solutions at a concentration of
1.00 ug/uL by dissolving 0.0100 g of assayed reference material 1n
Isooctane and diluting to volume 1n a 10-mL volumetric flask. A small
volume of toluene may be necessary to put some pesticides 1n solution.
Larger volumes can be used at the convenience of the analyst. When
compound purity 1s assayed to be 96X or greater, the weight can be used
without correction to calculate the concentration of the stock standard.
Commercially prepared stock standards can be used at any concentration 1f
they are certified by the manufacturer or by an Independent source.
5.2.2 Transfer the stock standard solutions Into Teflon-sealed
screw-cap bottles. Store at 4*C and protect from light. Stock standards
should be checked frequently for signs of degradation or evaporation,
especially just prior to preparing calibration standards from them.
5.2.3 Stock standard solutions must be replaced after one year, or
sooner 1f comparison with check standards Indicates a problem.
5.3 Calibration standards; Calibration standards at a minimum of five
concentration levelsforeach parameter of Interest are prepared through
dilution of the stock standards with Isooctane. One of the concentration
levels should be at a concentration near, but above, the method detection
limit. The remaining concentration levels should correspond to the expected
range of concentrations found 1n real samples or should define the working
range of the GC. Calibration solutions must be replaced after six months, or
sooner, If comparison with check standards Indicates a problem.
5.4 Internal standards (1f Internal standard calibration 1s used); To
use this approach, the analyst must select one or more Internal standards that
are similar 1n analytical behavior to the compounds of Interest. The analyst
must further demonstrate that the measurement of the Internal standard 1s not
affected by method or matrix Interferences. Because of these limitations, no
Internal standard can be suggested that Is applicable to all samples.
5.4.1 Prepare calibration standards at a minimum of five
concentration levels for each analyte of Interest as described in
Paragraph 5.3.
5.4.2 To each calibration standard, add a known constant amount of
one or more Internal standards, and dilute to volume with Isooctane.
5.4.3 Analyze each calibration standard according to Section 7.0.
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5.5 Surrogate standards; The analyst should monitor the performance of
the extraction, cleanup(when used), and analytical system and the effec-
tiveness of the method 1n dealing with each sample matrix by spiking each
sample, standard, and reagent water blank with pesticide surrogates. Because
GC/ECD data are much more subject to Interference than GC/MS, a secondary
surrogate 1s to be used when sample Interference 1s apparent. D1butyl-
chlorendate (DBCX Is also subject to acid and base degradation. Therefore,
two surrogate standards are added to each sample; however, only one need be
calculated for recovery. OBC 1s the primary surrogate and should be used
whenever possible. However, 1f DBC recovery 1s low or compounds Interfere
with DBC, then the 2,4,5,6-tetrachloro-meta-xylene should be evaluated for
acceptance. Proceed with corrective action when both surrogates are out of
limits for a sample (Section 8.3). Method 3500, Section 5.3.2, Indicates the
proper procedure for preparing these surrogates.
6.0 SAMPLE COLLECTION, PRESERVATION, AND HANDLING
6.1 See the Introductory material to this chapter, Organic Analytes,
Section 4.1. Extracts must be stored under refrigeration and analyzed within
40 days of extraction.
7.0 PROCEDURE
7.1 Extraction:
7.1.1 Refer to Chapter Two for guidance on choosing the appropriate
extraction procedure. In general, water samples are extracted at a
neutral, or as 1sr pH with methylene chloride, using either Method 3510
or 3520. Solid samples are extracted using either Method 3540 or 3550.
7.1.2 Prior to gas chroroatographlc analysis, the extraction solvent
must be exchanged to hexane. The exchange 1s performed during the K-D
procedures listed 1n all of the extraction methods. The exchange 1s
performed as follows.
7.1.2.1 Following K-D of the methylene chloride extract to
1 mL using the macro-Snyder column, allow the apparatus to cool and
drain for at least 10 mln.
7.1.2.2 Increase the temperature of the hot water bath to
about 90*C. Momentarily remove the Snyder column, add 50 mL of
hexane, a new boiling chip, and reattach the macro-Snyder column.
Concentrate the extract using 1 ml of hexane to prewet the Snyder
col mm. Place the K-D apparatus on the water bath so that the
concentrator tube Is partially Immersed In the hot water. Adjust
the vertical position of the apparatus and the water temperature, as
required, to complete concentration 1n 5-10 m1n. At the proper rate
of distillation the balls of the column will actively chatter, but
the chambers will not flood. When the apparent volume of liquid
reaches 1 mL, remove the K-D apparatus and allow It to drain and
cool for at least 10 m1n.
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7.1.2.3 Remove the Snyder column and rinse the flask and its
lower joint Into the concentrator tube with 1-2 ml of hexane. A
5-mL syringe 1s recommended for this operation. Adjust the extract
volume to 10.0 ml. Stopper the concentrator tube and store
refrigerated at 4*C, 1f further processing will not be performed
Immediately. If the extract will be stored longer than two days, It
should be> transferred to a Teflon-sealed screw-cap vial. Proceed
with gas chromatographlc analysis 1f further cleanup 1s not
required.
7.2 Gas chromatoqraphy conditions (Recommended);
7.2.1 Column 1: Set SI methane/95% argon carrier gas flow at
60 mL/m1n flow rate. Column temperature 1s set at 200*C Isothermal.
When analyzing for the low molecular weight PCBs (PCB 1221-PCB 1248), it
1s advisable to set the oven temperature to 160*C.
7.2.2 Col inn 2: Set 55 methane/95% argon carrier gas flow at
60 ml/m1n flow rate. Column temperature held Isothermal at 200*C. When
analyzing for the low molecular weight PCBs (PCB 1221-PCB 1248), 1t 1s
advisable to set the oven temperature to 140*C.
7.2.3 When analyzing for most or all of the analytes 1n this
method, adjust the oven temperature and column gas flow so that 4,4'-DDT
has a retention time of approximately 12 m1n.
7.3 Calibration; Refer to Method 8000 for proper calibration
techniques'! Use Table 1 and especially Table 2 for guidance on selecting the
lowest point on the calibration curve.
7.3.1 The procedure for Internal or external calibration may be
used. Refer to Method 8000 for a description of each of these
procedures.
7.3.2 Because of the low concentration of pesticide standards
Injected on a GC/ECD, column adsorption may be a problem when the GC has
not been used for a day. Therefore, the GC column should be primed or
deactivated by Injecting a PCB or pesticide standard mixture
approximately 20 times more concentrated than the mid-level standard.
Inject this prior to beginning Initial or dally calibration.
7.4 Gas chromatoqraphlc analysis;
7.4.1 Refer to Method 8000. If the Internal standard calibration
technique 1s used, add 10 uL of Internal standard to the sample prior to
Injection.
7.4.2 Follow Section 7.6 1n Method 8000 for Instructions on the
analysis sequence, appropriate dilutions, establishing dally retention
time windows, and Identification criteria. Include a mid-level standard
after each group of 10 samples 1n the analysis sequence.
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7.4.3 Examples of GC/ECO chromatograms for various pesticides and
PCBs are shown 1n Figures 1 through 5.
7.4.4 Prime the column as per Paragraph 7.3.2.
7.4.5 DDT and endrln are easily degraded In the Injection port If
the Injection port or front of the column 1s dirty. This 1s the result
of buildup of high boiling residue from sample Injection. Check for
degradation problems by Injecting a mid-level standard containing only
4,4'-DDT and endrln. Look for the degradation products of 4,4'-DDT
(4,4'-ODE and 4,4'-ODD) and endrln (endrln ketone and endrln aldehyde).
If degradation of either DDT or endrln exceeds 20X, take corrective
action before proceeding with calibration, by following the GC system
maintenance outlined in Section 7.7 of Method 8000. Calculate percent
breakdown as follows:
x 100
% breakdown Total DDT degradation peak area (DDE + ODD)
for 4,4'-DDT " Total DOT peak area (DDT + DDE + ODD)
X breakdown
for Endrln
Total endrln degradation peak area (endrln aldehyde + endrln ketone) 1QQ
Total endrln peak area (endrln + endrln aldehyde + endrln ketone)
7.4.6 Record the sample volume Injected and the resulting peak
sizes (1n area units or peak heights).
7.4.7 Using either the Internal or external calibration procedure
(Method 8000), determine the Identity and quantity of each component peak
1n the sample chromatogram which corresponds to the compounds used for
calibration purposes.
7.4.8 If peak detection and Identification are prevented due to
Interferences, the hexane extract may need to undergo cleanup using
Method 3620. The resultant extract(s) may be analyzed by GC directly or
may undergo further cleanup to remove Sulfur using Method 3660.
7.5 Cleanup;
7.5.1 Proceed with Method 3620, followed by, If necessary, Method
3660, using the 10-mL hexane extracts obtained from Paragraph 7.1.2.3.
7.5.2 Following cleanup, the extracts should be analyzed by GC, as
described 1n the previous paragraphs and 1n Method 8000.
7.6 Calculations (exerpted from U.S. FDA, PAM):
7.6.1 Calculation of Certain Residues: Residues which are mixtures
of two or more components present problems 1n measurement. When they are
found together, e.g., toxaphene and DDT, the problem of quantltation
becomes even more difficult. In the following sections suggestions are
offered for handling toxaphene, chlordane, PCB, DDT, and BHC. A column
10X DC-200 stationary phase was used to obtain the chromatograms in
Figures 6-9.
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Column: 1.5% SP-22SO*
1J9% SP-2401 on SuotieopofT
Timptfituft: 200°C
Ottoctor: Cioetron Cttturt
t t • > • • t • •
4 • 12 II
RCTfNTlON TIME (MINUTC5)
Figurt 1. Gas chromatogrim of ptftieidts.
8080 - 9
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Column: 1.5%S?-22SO»
1.M* Sf 2401 en Swpticopon
Temperiturt 70C°C
Octtcier: Electron
_i • i l ; • • i
I 12
TIME (MINUTES)
16
Figure 2. GM ehromategram of ehlordant.
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Column: 1 J% 9-2250*
US* SP-2401 on Suoticooen
Ttmptrnurt. 200°C
Dtltctor: Electron Cioturt
10 t4 ia
DETENTION TIME (MINUTES)
22
26
. Gas chromatogram of toxaphtnt.
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Column: 1.5% 5*2250-
US% SP 2401 on Soo«icoocn
Ttmotraturt: 200°C
Otwctor: Electron Caoturt
• 10 U
MCTENrriON TIME (MINUTES)
IS
22
Pigurt 4. Gas cfcremttogrim of
8080 > 12
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Column: 1.5*92250*
1JS% P-2401 en Suoticeoon
Ttmniuuft; 200°C
Oftactor Eifctren Caoturt
t ttt »
10 14 It
MCTINTION TIME (MINUTES)
Figure S. 6«s chrematognm of PCS-1260.
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J..L
fit, 0—Baaollae construction for some typical fas chromatofcraphic peaks.
a, symmetrical separated flat baseline; b and c, overlapping flat baseline;
d, «aparatad (pen do*a not raturn to baadim batwooa poaks); •. aaparatad
slopiat PM«UM: f. toparatad (pan fOM balow basalina bacwaaa peaks):
b «- andT-BHC sloping baMlio*; h,«^ /f-, and V-BHC sleptng baMltiw;
1. chlortana flat bateiine; J, bapcaebior and btptaehlor apoxido super-
tmpoaed OB eblerdano; k, efaair-ahapad poaka, unaynunetrlca] peak; 1,
p,p'-OOT aupertmpotad on toxapbene.
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Fig.7i—•Baseline construction for multiple residues with standard
toxapnene.
coMtructioa for multiple residues with t
DOE tad O.PX tad p*'-DOT.
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i ftr mulilpli ft•MtMii nit Iran wlili IHC*
OUT, Mrf mffeuyiMw-
8010 - 16
Rtvtifon
Oati
-------
Pt|itiM|*MiiM ftnitrwilon ftr muinpU rtillkMii HM4irtf
Iff mlttpto
MM Inn wtrt
iM DOT,
•010 • 17
Riv1i1on
Diti
-------
7.6.2 Toxaphene: Quantitative calculation of toxaphene or Strobane
is difficult, but reasonable accuracy can be obtained. To calculate
toxaphene on GC/ECD: (a) adjust sample size so that toxaphene major
peaks are 10-30% full-scale deflection (FSD); (b) Inject a toxaphene
standard that is estimated to be within +10 ng of the sample; (c)
construct the baseline of standard toxaphene~between 1t extremities; and
(d) construct the baseline under the sample, using the distances of the
peak troughs to baseline on the standard as a guide (Figures 7, 8, and
9). This procedure 1s made difficult by the fact that the relative
heights and widths of the peaks in the sample will probably not be
identical to the standard. A toxaphene standard that has been passed
through a Florisil column will show a shorter retention time for peak X
and an enlargement of peak Y.
7.6.3 Toxaphene and DDT: If DDT 1s present, 1t will superimpose
itself on toxaphene peak V. To determine the approximate baseline of the
DDT, draw a line connecting the trough of peaks U and V with the trough
of peaks W and X and construct another line parallel to this line which
will just cut the top of peak W (Figure 61). This procedure was tested
with ratios of standard toxaphene-DDT mixtures from 1:10 to 2:1 and the
results of added and calculated DDT and toxaphene by the "parallel lines"
method of baseline construction were within 10X of the actual values 1n
all cases.
7.6.3.1 A series of toxaphene residues have been calculated
using total peak area for comparison to the standard and also using
area of the last four peaks only 1n both sample and standard. The
agreement between the results obtained by the two methods Justifies
the use of the latter method for calculating toxaphene in a sample
where the early elutlng portion of the toxaphene chromatogram is
interfered with by other substances.
7.6.3.2 The baseline for methoxychlor superimposed on
toxaphene (Figure 8b) was constructed by overlaying the samples on a
toxaphene standard of approximately the same concentration (Figure
8a) and viewing the charts against a lighted background.
7.6.4 Chlordane 1s a technical mixture of at least 11 major
components and 30 or more minor ones. Gas chromatography-mass
spectrometry and nuclear magnetic resonance analytical techniques have
been applied to the elucidation of the chemical structures of the many
chlordane constituents. Figure 9a 1s a chromatogram of standard chlor-
dane. Peaks E and F are responses to trans- and cis-chlordane, respec-
tively. These are the two major components of technical chlordane, but
the exact percentage of each in the technical material Is not completely
defined and 1s not consistent from batch to batch. Other labelled peaks
in Figure 9a are thought to represent: A, monochlorinated adduct of
pentachlorocyclopentadiene with cyclopentadiene; B, coelution of
heptachlor and a-chlordene; C, coelution of 0-chlordene and 7-chlordene;
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D, a chlordane analog; G, coelutlon of c1s-nonachlor and "Compound K," a
chlordane Isomer. The right "shoulder" of peak F 1s caused by trans-
nonachlor.
7.6.4.1 The GC pattern of a chlordane residue may differ
considerably from that of the technical standard. Depending on the
sample substrate and Its history, residues of chlordane can consist
of almost any combination of: constituents from the technical
chlordane; plant and/or animal metabol1t1es; and products of
degradation caused by exposure to environmental factors such as
water and sunlight. Only limited Information 1s available on which
residue GC patterns are likely to occur 1n which samples types, and
even this Information may not be applicable to a situation where the
route of exposure Is unusual. For example, fish exposed to a recent
spill of technical chlordane will contain a residue drastically
different from a fish whose chlordane residue was accumulated by
IngestIon of smaller fish or of vegetation, which 1n turn had
accumulated residues because chlordane was 1n the water from
agricultural runoff.
7.6.4.2 Because of this Inability to predict a chlordane
residue GC pattern, 1t 1s not possible to prescribe a single method
for the quantltatlon of chlordane residues. The analyst must Judge
whether or not the residue's GC pattern 1s sufficiently similar to
that of a technical chlordane reference material to use the latter
as a reference standard for quantltatlon.
7.6.4.3 When the chlordane residue does not resemble technical
chlordane, but Instead consists prlmarTTy of Individual,
Identifiable peaks, quant1tate each peak separately against the
appropriate reference materials and report the Individual residues.
(Reference materials are available for at least 11 chlordane
constituents, metabolites or degradation products which may occur 1n
the residue.)
7.6.4.4 When the GC pattern of the residue resembles that of
technical chlordane, quantItate chlordane residues by comparing the
total area of the chlordane chromatogran from peaks A through F
(Figure 9a) 1n the sample versus the same part of the standard
chromatogram. Peak G may be obscured 1n a sample by the presence of
other pesticides. If G Is not obscured, Include It 1n the
measurement for both standard and sample. If the heptachlor epoxlde
peak 1s relatively small, Include 1t as part of the total chlordane
area fo* calculation of the residue. If heptachlor and/or
heptachTor epoxlde are much out of proportion as 1n Figure 6j,
calculate these separately and subtract their areas from total area
to give a corrected chlordane area. (Note that octachlor epoxlde,
metabolite of chlordane, can easily be mistaken for heptachlor
epoxlde on a nonpolar GC column.)
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7.6.4.5 To measure the total area of the chlordane
chromatogram, proceed as 1n Section 7.6.2 on toxaphene. Inject an
amount of technical chlordane standard which will produce a
chromatogram In which peaks E and F are approximately the same size
as those In the sample chromatograms. Construct the baseline
beneath the standard from the beginning of peak A to the end of peak
F as shpwn 1n Figure 9a. Use the distance from the trough between
peaks E and F to the baseline 1n the chromatogram of the standard to
construct the baseline 1n the chromatogram of the sample. Figure 9b
shows how the presence of toxaphene causes the baseline under
chlordane to take an upward angle. When the size of peaks E and F
In standard and sample chromatograms are the same, the distance from
the trough of the peaks to the baselines should be the same.
Measurement of chlordane area should be done by total peak area 1f
possible.
NOTE: A comparison has been made of the total peak area
Integration method and the addition of peak heights method for
several samples containing chlordane. The peak heights A, B,
C, D, E, and F were measured 1n millimeters from peak maximum
of each to the baseline constructed under the total chlordane
area and were then added together. These results obtained by
the two techniques are too close to Ignore this method of "peak
height addition" as a means of calculating chlordane. The
technique has Inherent difficulties because not all the peaks
are symmetrical and not all are present 1n the same ratio 1n
standard and In sample. This method does offer a means of
calculating results 1f no means of measuring total area Is
practical.
7.6.5 Polychlorlnated blphenyls (PCBs): Quant1tat1on of residues
of PCB Involves problems similar to those encountered 1n the quant1 tat1 on
of toxaphene, Strobane, and chlordane: In each case, the chemical 1s
made up of numerous compounds and so the chromatograms are multi-peak;
also In each case the chromatogram of the residue may not match that of
the standard.
7.6.5.1 Mixtures of PCB of various chlorine contents were sold
for many years 1n the U.S. by the Monsanto Co. under the tradename
Aroclor (1200 series and 1016). Though these Aroclors are no longer
marketed, the PCBs remain In the environment and are sometime found
as residues In foods, especially fish.
7.6.5.2 PCB residues are quantItated by comparison to one or
more of the Aroclor materials, depending on the chromatographlc
pattern of the residue. A choice must be made as to which Aroclor
or mixture of Aroclors will produce a chromatogram most similar to
that of the residue. This may also Involve a Judgment about what
proportion of the different Aroclors to combine to produce the
appropriate reference material.
8080 - 20
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Date September 1986
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7.6.5.3 Quant 1tate PCS residues by comparing total area or
height of residue peaks to total area of height of peaks from
appropriate Aroclor(s) reference materials. Measure total area or
height response from common baseline under all peaks. Use only
those peaks from sample that can be attributed to chloroblphenyls.
These peaks must also be present In chromatogram of reference
materials. Mixture of Aroclors may be required to provide best
match of GC patterns of sample and reference.
7.6.6 DOT: DDT found 1n samples often consists of both o,p'- and
p,p'-DDT. Residues of DDE and TDE are also frequently present. Each
Isomer of DDT and Its metabolites should be quant Itated using the pure
standard of that compound and reported as such.
7.6.7 Hexachlorocyclohexane (BHC, fro* the former naae, benzene
hexachlorlde) : Technical grade BHC Is a cream-colored amorphous solid
with a very characteristic musty odor; 1t consists of a mixture of six
chemically distinct Isomers and one or more heptachloro-cyclohexanes and
octachl oro-cycl ohexanes .
7.6.7.1 Commercial BHC preparations may show a wide variance
1n the percentage of Individual Isomers present. The elimination
rate of the Isomers fed to rats was 3 weeks for the a-, 7-, and 6-
Isomers and 14 weeks for the /Msomer. Thus It may be possible to
have any combination of the various Isoners 1n different food
commodities. BHC found 1n dairy products usually has a large
percentage of £- Isomer.
7.6.7.2 Individual Isomers (a, ft, 7, and 6) were Injected Into
gas chroma tographs equipped with flame 1on1zat1on, mlcrocoulometrlc,
and electron capture detectors. Response for the four Isomers 1s
very nearly the same whether flame 1on1zat1on or mlcrocoulometrlc
GLC 1s used. The a-, 7-, and 5- Isomers show equal electron
affinity. £-BHC shows a much weaker electron affinity compared to
the others Isomers.
7.6.7.3 Quant 1tate each Isomer (a, p, 7, and 6) separately
against a standard of the respective pure Isomer ( using a GC column
which separates all the Isomers from one another.
8.0 QUALITY CONTROL
8.1 Refer to Chapter One for specific quality control procedures.
Quality control to validate sample extraction Is covered In Method 3500 and 1n
the extraction method utilized. If extract cleanup was performed, follow the
QC 1n Method 3600 and 1n the specific cleanup method.
8.2 Mandatory quality control to evaluate the GC system operation 1s
found In Method 8000, Section 8.6.
8080 - 21
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Date September 1986
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8.2.1 The quality control check sample concentrate (Method 8000,
Section 8.6) should contain each single-component parameter of Interest
at the following concentrations In acetone: 4,4'-ODD, 10 ug/mL; 4,4'-
OOT, 10 ug/nL; endosulfan II, 10 ug/ml; endosulfan sulfate, 10 ug/mL;
endrln, lOug/nL; and any other single-component pesticide, 2 ug/mL. If
this method 1s only to be used to analyze for PCBs, chlordane, or
toxaphene, the QC check sample concentrate should contain the most
representative muIt1-component parameter at a concentration of 50 ug/mL
1n acetone.
8.2.2 Table 3 Indicates the calibration and QC acceptance criteria
for this method. Table 4 gives method accuracy and precision as
functions of concentration for the analytes of Interest. The contents of
both Tables should be used to evaluate a laboratory's ability to perform
and generate acceptable data by this method.
8.3 Calculate surrogate standard recovery on all samples, blanks, and
spikes. Determine If the recovery Is within limits (limits established by
performing QC procedures outlined 1n Method 8000, Section 8.10).
8.3.1 If recovery Is not within limits, the following Is required.
• Check to be sure there are no errors In calculations,
surrogate solutions and Internal standards. Also, check
Instrument performance.
• Recalculate the data and/or reanalyze the extract If any of
the above checks reveal a problem.
• Reextract and reanalyze the sample If none of the above are
a problem or flag the data as "estimated concentration."
8.4 GC/MS confirmation: Any compounds confirmed by two columns may also
be confirmed by GC/MSIf th« concentration Is sufficient for detection by
GC/MS as determined by the laboratory generated detection limits.
8.4.1 The GC/MS would normally require a minimum concentration of
10 ng/uL In the final extract, for each single-component compound.
8.4.2 The pesticide extract and associated blank should be analyzed
by GC/MS as per Section 7.0 of Method 8270.
8.4.3 The confirmation may bt from the GC/MS analysis of the
base/neutral-acid extractables extracts (sample and blank). However, 1f
the compounds are not detected In the base/neutral-acid extract even
though the concentration 1s high enough, a GC/MS analysis of the
pesticide extract should be performed.
8.4.4 A reference standard of the compound must also be analyzed by
GC/MS. The concentration of the reference standard must be at a level
that would demonstrate the ability to confirm the pest1c1des/PCBs
Identified by GC/ECD.
8080 - 22
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Date September 1986
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9.0 METHOD PERFORMANCE
9.1 The method was tested by 20 laboratories using reagent water,
drinking water, surface water, and three Industrial wastewaters spiked at six
concentrations. Concentrations used In the study ranged from 0.5 to 30 ug/L
for single-component pesticides and fro* 8.5 to 400 ug/L for mu1t1 -component
parameters. Single operator precision, overall precision, and method accuracy
were found to be directly related to the concentration of the parameter and
essentially Independent of the sample matrix. Linear equations to describe
these relationships for a flame 1on1zat1on detector are presented In Table 4.
9.2 The accuracy and precision obtained will be determined by the sample
matrix, sample-preparation technique, optional cleanup techniques, and
calibration procedures used.
10.0 REFERENCES
1. U.S. EPA, "Development and Application of Test Procedures for Specific
Organic Toxic Substances 1n Wastewaters, Category 10: Pesticides and PCBs,"
Report for EPA Contract 68-03-2605.
2. U.S. EPA, "Interim Methods for the Sampling and Analysis of Priority
Pollutants In Sediments and F1sh Tissue," Environmental Monitoring and Support
Laboratory, Cincinnati, OH 45268, October 1980.
3. Press ley, T.A., and J.E. Longbottom, "The Determination of Organohallde
Pesticides and PCBs 1n Industrial and Municipal Wastewater: Method 617," U.S.
EPA/EMSL, Cincinnati, OH, EPA-600/4-84-006, 1982.
4. "Determination of Pesticides and PCB's In Industrial and Municipal
Wastewaters, U.S. Environmental Protection Agency," Environmental Monitoring
and Support Laboratory, Cincinnati, OH 45268, EPA-600/4-82-023, June 1982.
5. Goerlltz, D.F. and L.M. Law, Bulletin for Environmental Contamination and
Toxicology, 6, 9, 1971.
6. Burke, J.A., "Gas Chromatography for Pesticide Residue Analysis; Some
Practical Aspects," Journal of the Association of Official Analytical
Chemists, 48, 1037, 1965.
7. Webb, R.G. and A.C. McCall, 'Quantitative PCB Standards for Electron
Capturt Gas Chromatography," Journal of Chroma tog raphlc Science, 11, 366,
1973.
8. Millar, J.B., R.E. Thomas and H.J. Schattenberg, "EPA Method Study 18,
Method 608: Organochlorlne Pesticides and PCBs," U.S. EPA/EMSL, Research
Triangle Park, NC, EPA-600/4-84-061, 1984.
9. U.S. EPA 40 CFR Part 136, "Guidelines Establishing Test Procedures for the
Analysis of Pollutants Under the Clean Water Act; Final Rule and Interim Final
Rule and Proposed Rule," October 26, 1984.
8080 - 23
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Date September T956
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10. Provost, L.P. and R.S. Elder, "Interpretation of Percent Recovery Data,"
American Laboratory, 15, pp. 58-63, 1983.
11. U.S. Food and Drug Administration, Pesticide Analytical Manual, Vol. 1,
June 1979.
12. Sawyer, L.Dr, JAOAC, 56, 1015-1023 (1973), 61 272-281 (1978), 61 282-291
(1978).
13. Official Methods of Analysis of the Association of Official Analytical
Chemists, 12th Edition; Changes In Methods, JAOAC 61, 465-466 (1978), Sec.
29.018.
8080 - 24
Revision
Date September 1986
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TABLE 3. QC ACCEPTANCE CRITERIA4
Parameter
AldHn
a-BHC
/J-BHC
0-BHC
7-BHC
Chlordane
4,4'-DDD
4,4'-DDE
4,4'-OOT
D1eldr1n
Endosulfan I
Endosulfan II
Endosulfan Sulfate
Endrln
Heptachlor
Heptachlor epoxlde
Toxaphene
PCB-1016
PCB-1221
PCB-1232
PCB-1242
PCB-1248
PCB-1254
PCB-1260
Test
cone.
(ug/L)
2.0
2.0
2.0
2.0
2.0
50
10
2.0
10
2.0
2.0
10
10
10
2.0
2.0
50
50
50
50
50
50
50
50
Limit
for s
(ug/L)
0.42
0.48
0.64
0.72
0.46
10.0
2.8
0.55
3.6
0.76
0.49
6.1
2.7
3.7
0.40
0.41
12.7
10.0
24.4
17.9
12.2
15.9
13.8
10.4
Range
for 7
(ug/L)
1.08-2.24
.98-2.44
0.78-2.60
1.01-2.37
0.86-2.32
27.6-54.3
4.8-12.6
1.08-2.60
4.6-13.7
1.15-2.49
1.14-2.82
2.2-17.1
3.8-13.2
5.1-12.6
0.86-2.00
1.13-2.63
27.8-55.6
30.5-51.5
22.1-75.2
14.0-98.5
24.8-69.6
29.0-70.2
22.2-57.9
18.7-54.9
Range
P. PS
w
42-122
37-134
17-147
19-140
32-127
45-119
31-141
30-145
25-160
36-146
45-153
D-202
26-144
30-147
34-111
37-142
41-126
50-114
15-178
10-215
39-150
38-158
29-131
8-127
s * Standard deviation of four recovery measurements, In ug/L.
7 » Average recovery for four recovery measurements. In ug/L.
P, Ps « Percent recovery measured.
0 • Detected; result must be greater than zero.
aCr1ter1a from 40 CFR Part 136 for Method 608. These criteria are based
directly upo* the method performance data 1n Table 4. Where necessary, the
limits for rtcovtry have been broadened to assure applicability of the limits
to concentrations below those used to develop Table 4.
8080 - 25
Revision 0
Date September 1986
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TABLE 4. METHOD ACCURACY AND PRECISION AS FUNCTIONS OF CONCENTRATION*
Paramtttr
Accuracy, as Slnglt analyst Overall
recovery, x' precision. ir' precision.
(ug/L) (ug/L) S' (ug/L)
Aldrln
a-BHC
;-BHC
5-BHC
7-BHC
Chlordane
4,4'-DDO
4,4'-DDE
4,4'-DDT
D1t1dr1n
Endosulfan I
Endosulfan II
Endosulfan Sulfatt
Endrln
Htptachlor
Htptachlor tpoxldt
Toxaphtnt
PCB-1016
PCB-1221
PCB-1232
PCB-1242
PCB-1248
PCB-1254
PCB-1260
0.81C*0.04
0.84C*0.03
0.81C*0.07
0.81C*0.07
0.82C-0.05
0.82C-0.04
0.84C*0.30
0,8500.14
0.93C-0.13
0.90C+0.02
0.97C+0.04
0.93C+0.34
0.89C-0.37
0.89C-0.04
0.69C+0.04
0.89C+0.10
0.80C+1.74
0.81C+0.50
0.96C+0.65
0.91C+10.79
0.93C+0.70
0.97C+1.06
0.76C+2.07
0.66C^3.76
0.167-0.04
0.13T*0.04
0.22T*0.02
0.18X+0.09
0.12X+0.06
0.13T+0.13
0.20T-0.18
0.131*0.06
0.17T+0.39
0.12T*0.19
0.107*0.07
0.41T-0.65
0.131*0.33
0.20T*0.25
0.067*0.13
0.18T-0.11
0.09T*3.20
0.131*0.15
0.29T-0.76
0.211-1.93
0.11X*1.40
0.171*0.41
0.151*1.66
0.22T-2.37
0.20T-0.01
0.237-0.00
0.33T-0.95
0.257*0.03
0.2ZX*0.04
0.187*0.18
0.277-0.14
0.287-0.09
0.317-0.21
0.167*0.16
0.187*0.08
0.477-0.20
0.247*0.35
0.247*0.25
0.167*0.08
0.257-0.08
0.207*0.22
0.157*0.45
0.357-0.62
0.317*3.50
0.217*1.52
0.257-0.37
0.177*3.62
0.397-4.86
x* • Expected rtcovtry for ont or more measurements of a sample
containing a concentration of C, In ug/L.
sr' • Exptcttd slnglt analyst standard deviation of measurements at an
avtragt concentration of 7, 1n ug/L.
S1 • Exptcttd Interlaboratory standard deviation of measurements at an
avtragt concentration found of 7, 1n ug/L.
C • True valut for tht concentration, In ug/L.
7 • Avtragt rtcovtry found for measurements of samples containing a
concentration of C, In ug/L.
8080 - 26
Revision 0
Date September 1986
-------
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8080 - 27
Rtvlilon _ 0
Dtt«
-------
Appendix 7-A
Standard Operating Procedure -
Procedure for Drawing a Representative Subsample
7-A-l
-------
PROJECT STANDARD OPERATING PROCEDURE
PROCEDURE FOR DRAWING A REPRESENTATIVE SUBSAMPLE FROM A BUCKET
The goal is to create a stratified random subsample of fluff which
will be called a "representative subsample.11 Each "representative subsample"
will nominally contain the various components of constituents of fluff in
approximately the proportions in which they occur in the original sample
(bucket). Since this approach is designed to produce subsamples which are
similar in composition to the original sample, the PCB (also lead and cadmium)
level measured in each subsample should be a more precise estimate of the PCB
level of the entire bucket.
1. Determine the weight of the entire fluff sample (fluff in
bucket). Since 400 to 500 g of fluff are required for each
subsample, weighing will indicate what fraction of each bucket
of material will comprise a subsample. (Preliminary estimates
suggest that approximately 1/8 of a bucket will yield the
desired amount of fluff for each subsample.)
2. Pour the contents of the bucket onto the tray/table. Pieces of
material as large as 4 in2 on the largest surface are cut to no
larger than 4 in* and mixed back into the sample. Larger
pieces of material (metal, atypical wire, hard plastics) which
cannot be cut with shears will be segregated. Determine and
record the weight of the segregated material. Pieces of wire
distributed uniformly throughout the sample will remain with
the sample.
3. Uniformly distribute the fluff which remains in the tray. This
material will vary in composition. Dense granular materials
(dirt, pulverized metal, plastics, glass, ceramics, etc.) will
tend to settle below lighter, shredded fabric and foam rubber
materials. Care must be taken to ensure that these components
of the fluff are uniformly distributed throughout the
tray/table.
4. Using the information on the total weight of each sample (fluff
in bucket), plan the specific sample partitioning strategy
needed to produce the 400- to 500-g subsamples. For the
majority of samples, the first step is to divide all the fluff
on the table into two "equal" parts, and randomly select one of
the parts. The selected part will then be divided into four
equal portions, which will result in the four subsamples. When
more than four subsamples are required, an additional four
subsamples (or less if there is not enough material) will be
drawn using the same procedures. Determine and record the
weight of each subsample. Place each subsample in a clean
1-gal jar according to analyte type as indicated on the Bucket
Sort List. Subsamples designated for Pb/Cd are placed in an
acid-washed jar. Subsamples designated for PCBs are placed in
-------
a solvent-rinsed jar. Samples designated for archive are
placed in an acid- and solvent-rinsed jar. If subsamples weigh
over 500 g or under 400 g, repeat step 4.
5. The larger constituents which have already been separated from
the tabled material (see step 2 above) will be reduced in size
to the above criteria by cutting with either tin snips or a
hack saw. If either of these cutting methods fails, the
material will remain segregated from the sample. If size
reduction can be performed, then a random portion of cut
material proportional (by weight) to the subsamples will be
amended back into each subsample. Record the weight of the cut
material amended back into each subsample.
6. Each "representative subsample" shall be placed in a container,
sealed, then labeled and numbered so that both the subsample
number and original bucket number are included (e.g., subsample
No. 2 of four from bucket No. 12).
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Appendix 7-B
Standard Operating Procedure -
Introduction to Fluff and Safety
7-B-l
-------
WA 8862-32-01
P-SOP No. 32-2
Revision No.: 0
Date: 3/13/89
Project-Standard Operating Procedure
Introduction and Safety
INTRODUCTION
The Environmental Protection Agency's (EPA) Office of Toxic Substances (OTS) and
Office of Solid Waste and Emergency Response (OSWER) are undertaking a pilot program
in order to learn about fluff waste streams as generated by shredder facilities in the
scrap recycling industries. Previous Agency efforts to obtain information on the
components of fluff or the levels and sources of chemical contaminants in fluff material
have provided only limited data. The large quantities of nonmetallic waste from the
shredding of automobiles and large consumer appliances have been reported by several
states to contain polychlorinated biphenyls (PCBs). The shredder waste or fluff consists
of small chunks of foam-like material of fine, hard and soft plastics, small metallic
and nonmetallic parts. The sources of PCB contamination of fluff are unknown.
However, the most probable source of PCBs in the shredder waste is from the processing
of equipment containing small oil-filled capacitors. The information EPA has received
to date indicates fluff is a very heterogeneous material. Further, there appears to
be a high level of variability in the PCB levels. The data indicate a range of PCB
levels in fluff from nondetectable levels to 1,242 parts per million (ppm).
Safety precautions for working with fluff should be the same as those followed when
working with any solid such as soil.
* Activities which may generate dust must be performed in a hood. These
activities include milling and subsampling.
* A lab coat, latex gloves and safety glasses must be worn at all times when
manipulating fluff. These personal safety requirements will be folllowed
during all work with samples and solvents.
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Appendix 7-C
Standard Operating Procedure
Wiley Mill Operation
7-C-l
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WA8862-32-01
P-SOP No. 32-1
Revision No.: 0
Date: 2/21/89
Project- Standard Operating Procedure
Wiley Mill Operation
The following procedure applies to a mill which has been cleaned
after use.
1. Inspect the clearance between the stationary blades and rotor
blades. First turn off the mill and allow time for the blades to
stop turning. Check the edges of each blade for wear. Report to
the supervisor anything which is unsafe about the operation or
damaging to the mill.
2. Make certain that all parts are properly assembled per the
manufacturer's instructions. A copy of the manufacturer's
instructions can be found in rooms 302 West and 300 West.
3. Close and latch the grinding chamber door. When the chamber
door is latched a click sound should come from the micro switch.
Inspect the chamber door safety switch, it should complete the
electrical circuit to the motor only when the chamber door is
closed and latched and should open this circuit immediately as
soon as the door is opened.
4 . Place a clean stainless steel beaker in the delivery chute.
5. Feed samples into the hopper slowly so that the mill does not
slow down or become jammed. Report to the supervisor any
problems with mill operation.
6. Remove milled sample. Clean mill between samples.
7. Complete the use log each day.
Saftey Note: Never look, place hands or probe into the feed
hopper when the mill is operating. A sliding shutter at the
bottom of the hopper controls the rate of feed. If the mill jams,
turn the mill off immediately. Open the grinding chamber and
inspect.
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Appendix 7-D
Standard Operating Procedure
Wiley Mill Cleaning
7-D-l
-------
WA8862-32-01
P-SOP No. 32-2
Revision No.: 0
Date: 2/21/89
Project-Standard Operating Procedure
Wiley Mill Cleaning
1. Turn off the mill and allow time for the blades to stop
turning. After the sample container has been removed from the
delivery chute disassemble the following parts:
feed hopper
sliding shutter
delivery chute
screen base and screen
stainless steel beaker
Clean all of these parts in the.fume hood by first brushing and
picking away all visible particles of fluff. Use a stiff bottle
brush and small spatula for cleaning. Then rinse each part with a
solution of hexane/acetone using a squirt bottle. Allow rinsed
parts to air dry on clean lab bench paper inside the hood.
2. Clean the grinding chamber/ knife blades, rotor and inside of
the door with brushes to remove fluff. The backsides of rotor
blades and the space between the stationary blades and chamber
wall should receive special attention when removing particles of
fluff. Wipe surfaces with a kimwipe to remove large oil spots or
streaks.
Place a pan beneath the grinding chamber to catch solvent.
Squirt a solution of hexane/acetone on all surfaces inside the
grinding chamber and grinding chamber door. Let all surfaces air
dry.
3. After all surfaces of the mill which have contact with samples
are cleaned/ inspect all parts for cleanlyness and wear before
reassembly.
4. If the surfaces of the mill appear to have particles of Fluff
or oil repeat steps 1 through 3.
5. Reassemble the mill.
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Appendix 7-E
Modified Method 8080
7-E-l
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MODIFIED METHOD 8080
INSTRUMENTAL ANALYSIS
1.0 Scope and Application
This Instrumental method is used for the determination of poly-
chlorinated biphenyls (PCBs) in "fluff." The reported detection limit
for total PCBs in the sample is 0.1 ppm.
2.0 Summary of Method
This 1s a gas chromatographic (GC) method employing either an electron
capture detector (ECD) or a Hall electrolytic conductivity detector
(HECD). Both packed column and capillary columns may be used. The
analyst is responsible for choosing appropriate analytical conditions
for quant1tation of standards and samples.
3.0 Apparatus and Materials
3.1 Gas Chromatoqraph
3.1.1 Gas Chromatoqraph; Analytical system complete with gas
chromatograph suitable for use with capillary and packed
columns and all required accessories, including
detectors, column supplies, recorder, gases, and
syringes. A data system for measuring peak heights
and/or peak areas is recommended.
3.1.2 Columns
3.1.2.1 Column 1: J & U DB-5 fused silica 30 m x
0.32 mm 1.0. capillary column.
3.1.2.2 Column 2: Supelcoport (100/120 mesh) coated
with 1.535 SP-2250/1.95X SP-2401 packed in a
1.8-ra x 4-mm I.D. glass column or equivalent.
3.1.2.3 Column 3: Supelcoport (100/120 mesh) coated
with 3* OV-I in a 1.8-m x 4-mm I.D. glass
column or equivalent.
3.1.3 Detectors: Electron capture (ECD) or electrolytic
conductivity detector (HECD).
-------
4.0 Reagents
4>1 Solvents; Isooctane (pesticide quality or equivalent).
4.2 Stock Standard Solutions: Stock standard solutions art prtpertd
by dissolving a known weight of neat reference material PCBt to a
known volume solvent.
4.3
Calibration Standards: Calibration standards at a minimum of
thrtt concentrations levels art prtpartd by dilution of tht stock
standards with Isooctant.
5.0 Procedurt for Instrumental Analysis
5.1 Gas chromatography conditions art stt by tht analyst for tht
packtd column or capillary column analysis, Either ECD or HECO
dtttctors may bt ustd. Tht analyst 1s rtsponslblt for optimi-
zation of tht analytical systtm for quantltatlon of tht samplt
rtlatlvt to appropriate standards.
5.2 Calibration
5.2.1 Tht proctdurt of txttrnal calibration will bt ustd with a
minimum thrtt-ltvtl Initial calibration curve for
HRGC/ECO analyses.
5.2.2 A standard will be Injtcttd bttwttn tvtry flvt sampIts to
tnsurt Instrument stability.
5.3 Quantltatlon: PCBs 1n tht samplt art quantltated by comparison
to one or more of tht Aroclor standards, depending on tht chro-
matographlc patttrn of tht samplt. A choice must bt made as to
which Aroclor or mixture of Aroclors will product a chromatogram
most similar to that of tht samplt.
5.3.1 Aroclor Quantltatlon (total areasThe total area
quantltatlon is ustd for samples with a single unmodified
Aroclor pattern or where the Aroclor patterns do not
significantly ovtrlap (t.g., 1242 and 1260). If mort
than ont Aroclor 1s obstrvtd 1n tht samplt and tht
patterns ovtrlap < SOX, thtn tht quantltatlon windows can
be rtductd to eliminate the overlapping regions. The
window reduction method may also bt ustd to exclude a
non-Aroclor peak from quantltatlon. If two or more
Aroclor patterns overlap > SOX. thtn tht analyst will
analyze tht major Aroclor 1f 1t 1s tstlmattd to bt t 90X
of tht total mixed Aroclor reiponst. Quantltatlon 1s
bastd on tht major Aroclor with Interferences eliminated.
-------
If a mlxturt of Aroclors 1s estimated to contain a major
Aroclor < 90X of tht total mlxtd Aroclor rtsponse, si1 act
ai many 1dtnt1f1ablt PCB ptaks as possible 1n tht regions
of tht least ovtrlap to quantify Individual Aroclors. In
tht judgmtnt of tht analyst, tht mtthod of Wtbb and
McCall may bt stltcttd for multlplt ovtrlapplng Aroclor
patterns.
5.3.2 Wtbb-McCall Quantisation; Whtn samplt chromatograms show
a combination of Aroclor patttrns whtrt tht ovtrlapping
artas txcttd 50* of tht total PCB arta, tht quantltatlon
routlnt followtd 1s tht EPA Ttst Mtthod 600/4.81-045
(Stpttmbtr 1982). Aroclor standards which rtprtstnt the
Aroclor typts found 1n tht samplts art analyztd with tht
samplts by tht GC/ECD conditions llsttd 1n tht mtthod.
NOTE THAT A DIFFERENT GC COLUMN IS USED FOR THE WEBB-
MCCALL ANALYSIS THAN THE ROUTINE ANALYSES. Tht standard
chromatograms art txamlntd and tach ptak 1dtnt1f1td by
rtttntlon tlmt. Tht standard chromatograms art thtn
compartd to tht Aroclor chromatograms 1n tht EPA ttst
mtthod or to a library of Aroclor chromatograms. Each
ptak 1n tht standards 1s thtn asslgntd a Wtbb-McCall
numbtr and alvtn tht wtlght ptrctnt for that numbtr.
Rtiponst factors art calculated for tach ptak 1n tach
Aroclor standard typt:
Ptak arta „ Wtlght ptrctnt
RF . Puk arta Wtlghtp
Standard conctntration 100
whtrt standard conctntration 1s 1n mlcrograms ptr
mllUlUtr and tht 1njtct1on volumt for standards and
samplts 1s tht samt.
Thtn by using tht division flowchart, samplt ptaks art
quantUattd vtrsus tht more strongly weighted Aroclor
ptak. Tht conctntration of all ptaks 1s summed, and tht
total PCB conttnt rtporttd with an approximation of
Aroclors (wt:wt) glvtn.
5.3.3 Visually Insptct tht samplt chromatograms and determine
tht proptr Aroclor to ust for quantltatlon. If that
Aroclor was not run with this samplt stt, rerun samples
with appropriate standards.
5.3.4 Determine tht rtttntlon windows. This 1s tht time rangt
over which tht Aroclor standard tlutts.
5.3.5 QuantUatt PCBs 1n samplt by comparing total arta or
htlght of ptaks to total arta of height of ptaks from
appropriate Aroclor(s) rtftrtnct materials. Measure
total arta or htlght response from common baseline under
-------
all peaks. Use only those peaks from sample that can be
attributed to chlorobiphenyls. These peaks must also be
present in chromatogram of reference materials. Mixtures
of Aroclors may be required to provide best match of GC
patterns of sample and reference.
5.3.6 Those samples for which recognizable Aroclor patterns are
present will be quantitated using the mean response
factors established during instrument calibration.
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Appendix 7-F
Separately Funnel Liquid-Liquid
Extraction and Cleanup
7-F-l
-------
SEPARATORY FUNNEL LIQUID-LIQUID EXTRACTION AND CLEANUP
1.0 Scope and Application
1.1 This method describes a procedure for isolating organic compounds
from aqueous samples. The method also describes concentration
techniques suitable for preparing the extract for GC/ECD,
GC/HECD, or GC/MS determinative methods.
1.2 This method is applicable to the isolation and concentration of
water-insoluble and slightly water-soluble organics in prepara-
tion for a variety of chromatographic procedures.
2.0 Summary of Method
2.1 A measured volume of sample, usually 1 L, is serially extracted
with methylene chloride using a separatory funnel. The extract
is concentrated and, as necessary, exchanged into a solvent
compatible with the cleanup or determinative step to be used.
3.0 Interferences
3.1 Any halogenated organic compounds that coelute from the analy-
tical chromatographic columns with the analytes can interfere
with the GC/ECD or GC/HECD determinative methods. Refer to the
appropriate cleanup methods.
4.0 Apparatus and Materials
4.1 Separatory Funnel: 2 L or 1 L, with Teflon stopcock.
4.2 Drying Column: 20-mm I.D. Pyrex chromatographic column with
Pyrex glass wool at bottom and a Teflon stopcock.
Note: Fritted glass discs are difficult to decontaminate after
highly contaminated extracts have been passed through. Columns
without frits may be purchased. Use a small pad of Pyrex glass
wool to retain the adsorbent. Prewash the glass wool pad with
50 ml of acetone followed by 50 ml of elution solvent prior to
packing the column with adsorbent.
-------
TABLE 1. EXTRACTION CONDITIONS
Determinative
method
Initial
extraction
PH
Secondary
extraction
PH
Exchange
solvent
required for
analysis
Exchange
solvent
required for
cleanup
Volume
of extract
required for
cleanup (ml)
Final extract
volume for*
analysis (ml)
8080
5-9
None
Isooctane
Isooctane
10.0
10.0
aThe final volume move require further reduction or dilution depending on the Initial weight of sample
extracted of the level of analytes persented In the sample.
rsi
-------
4.3 Kuderna-Danish (K-D) Apparatus
4.3.1 Concentrator tube: 10-mL, graduated (Kontes K-570050-
1025 or equivalent). Ground-glass stopper is used to
prevent evaporation of extracts.
4.3.2 Evaporation flask: 500-mL (Kontes K-570001-500 or
equivalent). Attach to concentrator tube with springs.
4.3.3 Snyder column: Three-ball macro (Kontes K-503000-0121 or
equivalent).
4.4.4 Snyder column: Two-ball micro (Kontes K-569001-0219 or
equivalent).
4.4 Boiling Chips: Solvent extracted, approximately 10/40 mesh
(silicon carbide or equivalent).
4.5 Mater Bath; Heated, with concentric ring cover, capable of tem-
perature control (±5°C). The bath should be used in a hood.
4.6 Vials: Glass, 2-mL capacity with Teflon-lined screw cap.
4.7 pH Indicator Paper; pH range including the desired extraction
pH.
4.8 Erlenmeyer Flask; 250-mL.
4.9 Syringe: 5-mL.
4.10 Graduated Cylinder; 1-L.
5.0 Reagents
5.1 Reagent Water; Reagent water is defined as water in which an
interferent is not observed at the method detection limit of the
compounds of interest.
5.2 Sodium Hydroxide Solution 10 N; (ACS) Dissolve 40 g NaOH in
reagent water and dilute to 100 mL.
5.3 Sodium Sulfate: (ACS) Granular, anhydrous (purified by heating
at 400°C for 4 h in a shallow tray).
5.4 Sulfuric Acid Solution (1:1); Slowly add 50 ml of H2SOH (sp. gr.
1.84) to 50 mL of reagent water.
-------
5.5 Extraction/Exchange Solvent: Methylene chloride and isooctane.
6.0 Procedure
6.1 Using a 1-L graduated cylinder, measure 0.5 to 1-L of sample and
transfer it to the separatory funnel. For the sample in each
analytical batch selected for spiking, add the matrix spiking
standard.
6.2 Check the pH of the sample with wide-range pH paper and, if
necessary, adjust the pH to that indicated in Table 1 for the
determinative method used to analyze the extract.
6.3 Add 60 mL of methylene chloride to the separatory funnel.
6.4 Seal and shake the separatory funnel vigorously for 1 to 2 min
with periodic venting to release excess pressure.
Note: Methylene chloride creates excessive pressure very
rapidly; therefore, initial venting should be done immediately
after the separatory funnel has been sealed and shaken once.
6.5 Allow the organic layer to separate from the water phase for a
minimum of 10 min. If the emulsion interface between layers is
more than one-third the size of the solvent layer, the analyst
must employ mechanical techniques to complete the phase sepa-
ration. The optimum technique depends upon the sample and may
include stirring, filtration of the emulsion through glass wool,
centrifugation, or other physical methods. Collect the solvent
extract in an Erlenmeyer flask. If the emulsion cannot be broken
(recovery of < 80% of the methylene chloride, corrected for the
water solubility of methylene chloride), transfer the sample,
solvent, and emulsion into the extraction chamber of a continuous
extractor and proceed with EPA Method 3520.
6.6 Repeat the extraction two more times using fresh portions of
solvent (steps 7.3 through 7.5). Combine the three solvent
extracts.
6.7 If further pH adjustment and extraction is required, adjust the
pH of the aqueous phase to the desired pH indicated in Table 1.
Serially extract three times with 60 ml of methylene chloride, as
outlined in paragraphs 6.3 through 6.5. Collect and combine the
extracts and label the combined extract appropriately.
6.8 If performing GC/MS analysis (Method 680), surrogate recovery
compounds may be added to the sample before separatory funnel
extraction.
-------
6.9 Assemble a Kuderna-Oanish (K-D) concentrator by attaching a 10-mL
concentrator tube to a 500-mL evaporation flask.
6.10 Dry the extract by passing it through a drying column containing
about 10 on of anhydrous sodium sulfate. Collect the dried
extract in a K-D concentrator. Rinse the Erlenmeyer flask, which
contained the solvent extract, with 20 to 30 ml of methylene
chloride and add it to the column to complete the quantitative
transfer.
6.11 Add one to two clean boiling chips to the flask and attach a
three-ball Snyder column. Prewet the Synder column by adding
about 1 ml of methylene chloride to the top of the column. Place
the K-D apparatus on a hot water bath (80 to 90°C) so that the
concentrator tube is partially immersed in the hot water and the
entire lower rounded surface of the flask is bathed with hot
vapor. Adjust the vertical position of the apparatus and the
water temperature as required to complete the concentration in 10
to 20 min. At the proper rate of distillation, the balls of the
column will actively chatter, but the chambers will not flood.
When the apparent volume of liquid reaches 1 ml, remove the K-D
apparatus from the water bath and allow it to drain and cool for
at least 10 min.
6.12 If a solvent exchange is required (as indicated in Table 1),
momentarily remove the Snyder column, add 50 ml of the exchange
solvent, a new boiling chip, and reattach the Snyder column.
Concentrate the extract, as described in paragraph 6.11, raising
the temperature of the water bath, if necessary, to maintain
proper distillation.
6.13 Remove the Snyder column and rinse the flask and its lower joints
into the concentrator tube with 1 to 2 mL of methylene chloride
or exchange solvent. If sulfur crystals are a problem, use
mercury for cleanup. The extract may be further concentrated by
using the technique outlined in paragraph 6.14 or adjusted to
10.0 ml with the solvent last used.
6.14 If further concentration is indicated use a stream of nitrogen to
blowdown the sample volume and adjust the final volume to the
desired level.
7.0 SuIfuric Acid Cleanup of Concentrated Extract
7.1 Add about 1 mL of concentrated sulfuric acid to the 10.0 mL
extract in the culture tube, and agitate for 1 min. (It is
advisable to limit the acid digestion to 1.0 min to prevent poor
recoveries.) If adequate separation of the solvent and acid is
not achieved, it may be necessary to centrifuge the mixture.
7.2 Remove organic layer to clean culture tube; discard acid layer.
-------
7.3 If acid layer is colored, repeat steps 6.1 and 6.2 up to a total
of five times. Adhere to the 1.0-min time allotted for each acid
digestion iteration.
7.4 Withdraw aliquots for subsequent dilutions or autosampler vials
as needed.
8.0 Florisil Chromatography Cleanup (only as necessary)
Perform this cleanup only 1f the sulfuric acid cleanup does not remove
major interferences.
8.1 Take a known volume of extract from 6.4 and concentrate to 2.0 ml
hexane (the exact aliquot of extract must be known for later
dilution factor calculations).
8.2 Remove the prepackaged miniature Florisil column from its package
and preelute with 20 ml of hexane.
8.3 Apply the extract from 7.1 to the column and elute with the
following sequence of solvents:
8.3.1 2 ml of 6% diethyl ether/hexane (v/v).
8.3.2 2 ml of 15% diethyl ether/hexane (v/v).
8.4 Dilute the extract from 7.3.1 as necessary and withdraw aliquots
for autosampler vials as necessary. Archive the fraction from
8.3.2 for future reference.
9.0 Quality Control
9.1 Internal Quality Control
9.1.1 Procedural blanks will be analyzed with each batch of
samples. A reagent blank will consist of all reagents
used in the procedure. A method blank of "clean" foam
may be used as a similar matrix to the fluff.
9.1.2 Method spikes will be used to determine accuracy of the
analytical procedure. This will include spiking a sample
of fluff with a known concentration of PCBs.
9.1.3 Duplicate analysis of samples will be included with each
set of samples to determine the precision of the analyt-
ical procedure.
-------
Appendix 7-G
Soxhlet Extraction Cleanup
7-G-l
-------
SOXHLET EXTRACTION AND CLEANUP
1.0 Scope and Application
This is a procedure for extracting polychlorinated biphenyls (PCBs) from
"fluff" and soil. The Soxhlet extraction process ensures intimate
contact of the sample matrix with the extraction solvent. The cleanup
with sulfuric acid 1s a widely accepted method for removal of interfer-
ences from the PCBs. Additional cleanup with a florisil column may also
be necessary. The instrumental analysis with GC/ECD or GC/HECD relies
on pattern recognition and retention time markers for quantitation of
PCBs as Aroclors. Detection limits of 0.1 ppm may be obtained by this
method.
2.0 Summary of Method
The "fluff" sample is first reduced in particle size. The sample is
compressed into a Soxhlet extractor and a layer of sea sand is placed on
top of the "fluff." For extremely wet samples, a Dean-Stark may be used
in series with the Soxhlet extractor. The extraction is continued for
16 h with an appropriate solvent. The extract is concentrated and
exchanged to isooctane. The extract is then subjected to an acid
cleanup and florisil column chromatography, if necessary. The extract
is analyzed by GC/ECD or GC/HECD. Quantitation of detected peaks is
then performed relative to appropriate standards.
3.0 Interferences
3.1 Any halogenated organic compounds that coelute from the analyt-
ical chromatographic columns with the analytes can interfere with
the GC/ECD or GC/HECD determinative methods. Refer to the
appropriate cleanup methods.
4.0 Apparatus and Materials
4.1 Soxhlet Extractor; Complete with condenser, boiling flask, and
optional Dean-Stark.
4.2 Kuderna-Danish (K-D) Apparatus
4.2.1 Concentrator tube: 10 ml.
4.2.2 Evaporator flask: 500 ml; attach to concentrator tube
with springs.
4.2.3 Snyder column: Three ball macro.
-------
4.3 Boiling Chips: Teflon, solvent extracted.
4.4 Water Bath: Heated, with concentric ring cover (steam bath
temperature).
4.5 Culture Tubes: Calibrated to a known volume (10 ml).
4.6 Glass Wool: Pyrex, preextracted with solvent.
4.7 Heating Mantle; Rheostat controlled.
4.8 Syringes: Gastight, Hamilton Teflon-tipped.
5.0 Reagents
5.1 Sea Sand: Fisher S-25 precleaned with solvent (CAS 14808-60-7).
5.2 Sodium Sulfate; (ACS) Granular anhydrous (preextracted with
methylene chloride followed by heating at 400°C for at least
4 h).
5.3 Extraction Solvents; Optional solvent systems (pesticide
guality).
5.3.1 Toluene/methane!: 10:1 (v/v).
5.3.2 Hexane/acetone: 1:1 (v/v).
5.3.3 Methylene chloride.
5.3.4 Hexane.
5.3.5 Reagent water: Milli-Q purification system or
equivalent.
5.4 Solvent Exchange Solvent; Isooctane, pesticide quality.
5.5 Sulfuric Acid (ACS): Concentrated for extract cleanup.
5.6 Florisil Miniature Columns: J. T. Baker®, Baker®-10 SPE
disposable Florisil columns, 1 g.
5.7 Elution Solvents
5.7.1 Hexane: Pesticide quality.
5.7.2 Diethyl ether: Pesticide quality, peroxide-free.
-------
6.0 Procedure for Extraction
6.1 Sample handling (assume particle -ize reduction has been
completed). For soil samples, remove rocks, sticks, and leaves
by sieving.
6.2 Extraction of Sample: Weigh 20 to 80 g of material into a tared
container and transfer to a Soxhlet extractor capable of holding
a volume of 500 ml in the body of the extractor. Place a plug of
precleaned glass wool in the bottom of the extractor and place a
layer of sea sand on top of the sample to hold the sample in the
extractor.
Place 600 mL of the extraction solvent (Section 4.3) into a
1000-mL round bottom flask containing one or two clean boiling
chips. Attach the flask to the extractor and extract the sample
for 16 to 24 h.
6.3 For samples that contain more than 10% moisture, the water con-
tent may decrease the efficiency of the Soxhlet extractor. For
these samples, removal of the water during the Soxhlet extraction
with a Dean-Stark apparatus could greatly increase the extraction
efficiency. This modified Soxhlet extraction follows:
6.3.1 Attach the Dean-Stark glassware to the top of the Soxhlet
and then attach the condenser to the top of the Dean-
Stark. Water from the sample will collect in the Dean-
Stark during the Soxhlet extraction. The solvent will
condense into the extraction apparatus and the PCBs will
be concentrated in the round bottom extraction flask.
(This procedure is currently being used for extraction of
wet samples for PCDD/PCDF analysis.)
6.4 Allow the extract to cool after extraction is complete.
6.5 Assemble a Kuderna-Danish (K-D) concentrator by attaching a 10-mL
concentrator tube to a 500-mL evaporation flask.
-------
6.6 Dry the extract by passing it through a drying funnel containing
about 20 g of anhydrous sodium sulfate. Collect the dried
extract in a K-D concentrator. Wash the extractor flask and
sodium sulfate column with 100 to -125 mL of extraction solvent to
complete the quantitative transfer.
6.7 Add one or two clean boiling chips to the flask and attach a
three-ball Snyder column. Prewet the Snyder column by adding
1 ml of solvent to the top of the column. Place the K-D
apparatus on a hot water bath (15 to 20°C above the boiling point
of the solvent) so that the concentrator tube is partially
immersed in the hot water and the entire lower rounded surface of
the flask is bathed with hot vapor. Adjust the vertical position
of the apparatus and the water temperature, as required, to com-
plete the concentration in 10 to 20 rain. At the proper rate of
distillation, the balls of the column will actively chatter, but
the chambers will not flood. When the apparent volume of liquid
reaches 1 mL, remove the K-D apparatus from the water bath and
allow it to drain and cool for at least 10 min.
6.8 For the solvent exchange, momentarily remove the Snyder column,
add 50 mL of the exchange solvent and a new boiling chip, and
reattach the Snyder column. Concentrate the extract as described
in paragraph 5.6,. raising the temperature of the water bath, if
necessary, to maintain proper distillation.
6.9 Remove the Snyder column and rinse the flask and its lower joints
into the concentrator tube with 1 to 2 mL of exchange solvent.
6.10 Transfer the concentrated extract to a calibrated culture tube
(10.0 mL) and dilute to the calibration mark.
7.0 SuIfuric Acid Cleanup of Concentrated Extract
7.1 Add about 1 mL of concentrated su If uric acid to the 10.0 mL
extract in the culture tube, and agitate for 1 min. (It is
advisable to limit the acid digestion to 1.0 min to prevent poor
recoveries.) If adequate separation of the solvent and acid is
not achieved it may be necessary to centrifuge the mixture.
7.2 Remove organic layer to clean culture tube; discard acid layer.
7.3 If acid layer is colored, repeat steps 6.1 and 6.2 up to a total
of five times. Adhere to the 1.0-min time allotted for each acid
digestion iteration.
7.4 Withdraw aliquots for subsequent dilutions or autosampler vials
as needed.
-------
8.0 Florisll Chromatography Cleanup (only as necessary)
Perform this cleanup only if the sulfuric acid cleanup does not remove
major interferences.
8.1 Take a known volume of extract from 6.4 and concentrate to 2.0 ml
hexane (the exact aliquot of extract must be known for later
dilution factor calculations).
8.2 Remove the prepackaged miniature Florisil column from its package
and preelute with 20 ml hexane.
8.3 Apply the extract from 7.1 to the column and elute with the
following sequence of solvents:
8.3.1 2 ml of 6% diethyl ether/hexane (v/v).
8.3.2 2 ml of 15% diethyl ether/hexane (v/v).
8.4 Dilute the extract from 7.3.1 as necessary and withdraw aliquots
for autosampler vials as necessary. Archive the fraction from
7.3.2 for future reference.
9.0 Quality Control
9.1 Internal Quality Control
9.1.1 Procedural blanks will be analyzed with each batch of
samples. A reagent blank will consist of all reagents
used in the procedure. A method blank of "clean" foam
may be used as a similar matrix to the "fluff."
9.1.2 Method spikes will be used to determine accuracy of the
analytical procedure. This will include spiking a sample
of "fluff" with a known concentration of PCBs.
9.1.3 Duplicate analysis of samples will be included with each
set of samples to determine the precision of the analy-
tical procedure.
-------
Appendix 7-H
Tumbler Extraction
7-H-l
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WA8862-32-01
P-SOP No. 32-2
Revision No.: 0
Date: 3/27/89
PROJECT-STANDARD OPERATING PROCEDURE
TUMBLER EXTRACTION
1.0 Scope and Application
This is a procedure for extracting polychlorinated biphenyls (PCBs) from
"fluff." The cleanup with sulfuric acid is a widely accepted method for
removal of interferences from the PCBs. Additional cleanup with a
florisil column may also be necessary. The instrumental analysis with
6C/ECD or GC/HECD relies on pattern recognition and retention times for
quantitation of PCBs as Aroclors. Detection limits of 0.1 ppm may be
obtained by this method.
2.0 Summary of Method
An entire subsample ranging from 400 to 500 g is extracted with 2 L of
hexane:acetone (1:1) in an agitation apparatus used for the TCLP extrac-
tion. The slurry extraction is carried out in three sequential 1-h
extractions. After the end of each 1-h extraction the solvent is
decanted into another jar. The recovered solvent from each extraction
is measured, and a composite is made from proportional aliquots of the
individual extracts. An aliquot of the composited extracts is exchanged
to isooctane. Concentrated sulfuric acid washings are used to clean up
the subsample extract before GC analysis.
3.0 Interferences
3.1 Any halogenated organic compound that coelutes from the analyt-
ical chromatographic columns with the analytes can interfere with
the GC/ECD or GC/HECD determinative methods. Refer to the appro-
priate cleanup methods.
4.0 Apparatus and Materials
4.1 Agitation Apparatus: Enclosed box which holds 1-gal wide-mouth
jars and rotates end over end at approximately 33 rpm.
4.2 Extraction Bottles: 1-gal glass bottle with 4-in opening and
screw cap which is lined with Teflon.
4.3 Graduated Cylinder; 2,000 ml.
4.4 Water Bath: Heated, with concentric ring cover (steam bath
temperature).
4.5 Culture Tubes: Calibrated to a known volume (10 ml).
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WA8862-32-01
P-SOP No. 32-2
Revision No.: 0
Date: 3/27/89
4.6 Glass Wool: Pyrex, preextracted with solvent.
4.7 Syringes: Gastight, Hamilton Teflon-tipped.
5.0 Reagents
5.1 Sea Sand; Fisher S-25 precleaned with solvent (CAS 14808-60-7).
5.2 Extraction Solvents: Pesticide quality.
5.2.1 Hexane/acetone: 1:1 (v/v).
5.3 Solvent Exchange Solvent: Isooctane, pesticide quality.
5.4 Sulfuric Acid (ACS): Concentrated for extract cleanup.
5.5 Florisil Miniature Columns: J. T. Baker*, Baker*-10 SPE dis-
posable Florisil columns, 1 g.
5.6 Elution Solvents
5.6.1 Hexane: Pesticide quality.
5.6.2 Diethyl ether: Pesticide quality, peroxide-free.
6.0 Procedure for Extraction
6.1 Extraction of Subsample
6.1.1 The entire subsample is extracted in the same 1-gal jar
as received from the subsampling team.
6.1.2 Place 2,000 mL of hexane/acetone into the sample jar and
tightly screw on the Teflon-lined lid.
6.1.3 The jar containing the solvent and "fluff" must be vented
several times before extraction. Shake the jar end over
end three times. Vent the jar after shaking in a fume
hood by unscrewing the lid. Before replacing the lid on
the jar wipe off any fine particles from the jar lip and
inside of the lid threads. Repeat the venting process
for a total of three times.
6.1.4 Place the jar containing the subsample and solvent into
the agitation apparatus. Lock the I1d of the agitation
apparatus. Start the apparatus and continue to tumble
for 1 h.
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WA8862-32-01
P-SOP No. 32-2
Revision No.: 0
Date: 3/27/89
6.1.5 Remove the jar at the end of 1 h to a fume hood. Unscrew
the lid and hold the lid over the jar top but allowing
approximately 1/2-in gap between lid and jar- Decant the
solvent into a precleaned 1-gal jar.
6.1.6 Label the jar with the bar code number, subsample number
and rinse number, date, and initial the label.
6.1.7 Repeat the extraction process with the addition of new
solvent. Perform the extraction process for a total of
three times. Keep the recovered solvent from each rinse
cycle separate.
6.2 Determine the Volume of Solvent Recovered: Take an unused 1-gal
jar and place it next to the jar containing the recovered sol-
vent. Add water to the empty jar up to the level found in the
jar containing the.solvent. Pour the water into a 2-L graduated
cylinder. Record the volume on the label and in the laboratory
sample preparation record.
6.3 Composite Aliquots From Each Rinse: Transfer proportional
volumes of recovered solvent form each rinse to a 50-mL culture
tube. Archive a fraction of the composited extract for future
reference.
6.4 Solvent Exchange; Transfer 10 mL of the combined extract to a
calibrated culture tube (10 ml). Add 1 ml of isooctane as a
keeper solvent. Concentrate the volume of extract to approxi-
mately 1 ml under a stream of N2. Bring the volume of the
extract back to 10 mL with isooctane.
7.0 SuIfuric Acid Cleanup of Concentrated Extract
7.1 Add about 1 mL of concentrated su If uric acid to the 10.0 mL
extract in the culture tube, and agitate for 1 min. (It is
advisable to limit the acid digestion to 1.0 min to prevent poor
recoveries.) If adequate separation of the solvent and acid is
not achieved it may be necessary to centrifuge the mixture.
7.2 Remove organic layer to clean culture tube; discard acid layer.
7.3 If acid layer is colored, repeat steps 7.1 and 7.2 up to a total
of five times. Adhere to the 1.0-min time allotted for each acid
digestion iteration.
7.4 Withdraw aliquots for subsequent dilutions or autosampler vials
as needed.
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WA8862-32-01
P-SOP No. 32-2
Revision No.: 0
Date: 3/27/89
8.0 Florisil Chromatoqraphy Cleanup (only as necessary)
Perform this cleanup only If the sulfurlc acid cleanup does not remove
major interferences.
8.1 Take a known volume of extract from 6.3 and concentrate to 2.0 ml
hexane (the exact aliquot of extract must be known for later
dilution factor calculations).
8.2 Remove the prepackaged miniature Florisil column from its package
and preelute with 20 ml hexane.
8.3 Apply the extract from 8.1 to the column and elute with the
following sequence of solvents:
8.3.1 2 ml of 656 diethyl ether/hexane (v/v).
8.3.2 2 mL of 15% diethyl ether/hexane (v/v).
8.4 Dilute the extract as necessary and proceed to step 6.4.
9.0 Sample Concentration
Composited subsample extracts will be concentrated after the first GC
analysis indicates that the quant i tat ion level of 0.1 yg/g has not been
obtained. An aliquot of the composited subsample will be concentrated
using a stream of N2 the appropriate volume as determined by the chemist
responsible for GC analyses.
10.0 Quality Control
10.1 Internal Quality Control
10.1.1 A method blank of sea sand will be used as a similar
matrix to the "fluff."
10.1.2 Method spikes will be used to determine accuracy of the
analytical procedure. This will include spiking a sample
of "fluff" with a known concentration of PCBs.
10.1.3 Replicate subsamples will be extracted at an interval
designated in the experimental design.
-------
Table 1. Solvent Recovered from Tumble extractions
SUe/sample/subsafflple
7/4/1
7/4/3
7/4/4
6/5/3
5/7/2
5/7/4
2/2/2
3/2/1
4/7/4
6/3/1
Percent
Extraction I
82
78
78
76
76
66
51
70
76
82
recovery of solvent*
Extraction Z
97
96
100
92
96
99
96
93
102
98
Extraction 3
ICO
98
93
84
94
92
92
86
98
96
Total
recovery
93
91
90
84
89
86
80
83
92
92
Percent recovery • (volume of solvent recovered/volume of solvent added) x
, where the balance of solvent added * 2000 ml.
-------
Appendix 7-1
The Determination of Polychlorinated
Biphenyls in Transformer Fluid
and Waste Oils
7-1-1
-------
United States
Environmental Protection
Agency
Environmental Monitoring 1 Sussorr
Laacratory
Cincsnnati CH 4S2S3
Researcn and Develooment
EPA-600/4-3 1-3*5 Sest.:S32
Test Method
The Determination of
Polychlorinated Biphenyls in
Transformer Fluid and
Waste Oils
Thomas A. Sellar and James J. Licf.tenberg
1. Scope
1.1 This is the e?A preferred method
for the determination of polychlonnated
biphenyls (PCSs) in w*st«.oils according
to PCS regulations.' This gas
chrematograohie (GO procedure is
applicable to tne determination of
commercial mixtures of PCSs in
transformer fluids and certain otner
hydroearaen-oased waste oils. The
metnod can 6e used to analyze waste oils
for individual PCS isomers or camolex
mixtures of cnlorinated bionenyis from
monoehiorooipnenyl tnrougn
decacnlorooiohenyl only if :ne isomers
have been previously identified by otner
methods' or by knowledge of tne samole
history.
1.2 The detection limits are dependent
ueon the complexity of the samole matrix
and the aeiliry of the analyst to property
maintain tn« analytical system. Using a
carefully optimized instrument. :nts
metnod has seen mown to ae useful for
tne determination of commercial PCS
mixtures spiked into transformer fluid
over a range of S.O to 500 mg/kg. Eased
uoon a statistical calculation at 5 mg/kg
for a simple oil matrix, tne metnod
detection limit for Arodors 1221. 1242.
1254. and 1260 is 1 mg/kg. The method
detection limn (MOD is defined as tne
minimum concentration of a substance
that can be measured and reported witn
99% confidence tnat tne value is aoove
zero.
1 .3 This metnod is restricted :o use sy
or under tne supervision of analysts
experienced in tne use of gas
cnromatograony and in :.ie interpretation
of ;as chromatograms. Prior :a samole
analysis. :acn analyst must demonstrate
tne ability to generate accestaoie results
witn tnis metnod Sv following tne proce-
dures descssaed in Secaen 10.Z.
2. Summary
2.1 The sample is diluted on a weight/
volume basis so tnat trie csncentration of
eacn PCS isomer is withm caoaoility of
the GC system (0.01 to 1 0
2.2 The diluted samole is men injected
into a gas cnromatograpn (or seaaration
of tne PCS isomers. Measurement is '
accomoiisned witn a nalogen-soeofic
detector wmcn maximizes aaseiine
staoilitv ana minimizes interferences
normally encountered witn otner
detectors. The electron capture detector
(ECO) can normally se suestitvited for -.ne
nalogen-«oecrfic detvctor wnen samples
contain dicMoro througn
decachlorobiphenyl isomers (Arociors
1016. 1232. 1242. 1248. 1254. 126O.
-------
1 252 and 126S) or wnen me sample
mains does not interfere witn me PCSs.
Several cleanuo techniques are provided
for sample* containing interferences. A
mass spectrometer ooerattng m trie
selected ion monitoring mooa of data
acquisition may aiso oe used as me GC
detector wn«n PCS levels are sufficiently
high and tn« PCS m/z ranges are free
from interference, interferences mav
occur in some waste oil samples even
arter exhaustive cleanup.
2.3 The concentration of tn« PCSs are
calculated on a .tig/kg basis, using
commercial mixtures of PCSs as
standards. The analysis time, not
Inducing cata reduction, is approximately
35 mm/ sample.
3. Interferences
3.1 Qualitative misidentificattons are
always a potential problem in GC
analysis. The use of a halogen-specific
detector and the analyst's skill in
recognizing cnromatograonic patterns of
csrnmerciai PCS mixtures minimizes tnis
possibility.
3.2 Whenever analyzed samples do not
provide cnromatograonic patterns nearly
identical to me standards prepared
from commencal PCSs. Lie
analyst must confirm the presence of
rC3s ay one of tnree ways; py analysis
after column cleanup; fey analysis on
dissimilar GC columns: or. by gas
chromatograony/mass soectrometry
(GC/MSl.
3.3 3urmg the deveioome.it and testing
of this metnod. certain analytical
parameters and ecuioment designs were
'ound to affect :ne validity of tne
analytical results. Proper use of :ne
metnod reouires mat suc.1 parameters or
sesigns are to se used as saeefied. These
items are identified m tne text ay tne
wora "must." Anvone wisning to deviate
from tne metnod in areas so identified
must demonstrate tnat the deviation does
not affec: ;ne validity of tne data and
alternative test procedure aooroval must
be ootamed tnrough tne UScPA.
s.ivtronmental Monitoring and Suooort
laboratory, equivalency Program. 25 W.
St. Cair Street. Cincinnati. Ohio 45263.'
An exoerienced analyst may make
modifications to parameters or ecuioment
centified 3v tne term "recommenced."
sac.i time sucn modifications are made to
me metnod. me analyst must reoeat :ne
procedure m Section 10.2. In tnts case.
formal aoorovai is not required, but tne
documented data from Section 10.2 must
be on file as part of :n« overall cuaiity
assurance program.
3.4 Samoies wnicn are diluted at a ratio
of 100:1 and are analyzed by electron
capture GC. consistently produce results
tnat are 10 to 20% lower tnan tne true
value (Se« Section 121. This is due to
quenching of tne detector resoonse by
nigh boiling hydrocarbons coeiuting witn
the PCSs. The degree of error is matrix
deoendent and is not predictable for
samples of unknown origin. As tne PCS
concentration approaches 20% of a
control level, for example. 50 mg/kg. tne
analyst must routinely reanalyze a
duplicate spiked sample to determine me
actual recovery. The duplicate or diluted
sample is spiked at two times the electron
capture observed value and reanalyzed
according to Section 10.2. The results are
corrected accordingly.
4. Apparatus
4.1 Gas C.Voma/ograpn—The gas
c-iromatograpn should be equipped witn
on-column '/4-inch injectors. The oven
must be large enough to accept a v&~ 00
2-meter coiled glass column, if halogen-
specific Selectors are used, then the
column oven snould have programming
capabilities.
4.2 Gas Chromatognphic Detector
4.2.1 A halogen-specific detector is
used to eliminate interferences causing
misidentificanons or false-positive values
due to non-organonalides wnicn
commonly coeiute witn tne PCSs.
4.2.1.7 Electrolytic conductivity detector
— the Hail electrolytic csnductrvity
detector. Model 700-AIHSD). availaale
from Tracar. Inc.. has been found :o
provide tne sensitivity and staotlity
needed 'or the current PCS Regulations.1
4 2.1.2 Other halogen-specific
detectors, including older model
electrolytic conductivity detectors and
microcoulometnc titration. may be used.
However, tne stability, sensitivity, and
response time of tnese detectors may
raise tne MOL and adversely affect peak
resolution. Eacn system must be snown
to be operating witnm recuirements of
me PCS regulations oy collecting single
laboratory accuracy and precision cata
and MOL on simple spiked samples, as
described in Section 10.2.
4.2.2 Semi-soecrfic selectors, sucn is
=C3. may be suostttuted wnen samcie
cnromatograonic patterns closely ma.rrn
those of the stancares. Aed eeanuo (See
Section 8.1) or rtorisil slurry ciaanuo (See
Section 8.7) snouid be incorporated
routinely when tne SCO is used. See
Section 3.4 for additional quality control
procedures for 5CO.
4.2.3 Quantitative GC/V.S tecnmcues
can be used. The recommended ascrsacn
is selected ion monitoring, lut me
GC/MS data system must have a
program that supports this method of
cata acquisition. The program must be
capaole of monitoring a minimum of eignt
ions, and it is cesirabie for tne system to
have the ability to cnange tne ions
monitored as a function of time, ror PCS
measurements, several sets of ions may
be used, depending gn the objectives o'
the study and me cata system
capabilities. The alternatives are as
follows:
4.2.3.1 Single ions 'or hign sensitivitv:
154. 1S8. 222. 255. 2S2: 32S. 360. 33*.
4.2.3.2 Short mass ranges wnicn mav
give enhanced sensitivity, oesencing on
tne data system capacities: 154-; 55.
188-192, 222-228. 255-150. 2SO-2S5.
322-32B. 355-364. 330-398.
4.2.3-3 Single ions giving eecreased
sensitivity but are selective for levels of
chlorination:1 190. 224. 250. 294. 330.
362. 334.
4.2.3.4 The data svstem must nave tne
caoaoiliry of integrating an aouneance of
tne selected ions between specified limits
and relating integrated aouncances tp c=n-
cemrations. using me calibration
procedures described in this metnod.
4.3 Gas Cnramatograomc Columns
4.3.1 The GC columns and conditions
listed below are recommenced for tne
analysis of PCS mixtures in oil. If tnese
columns and conditions are not adequate.
me analyst may vary tne column
parameters to improve separations. The
columns and conditions selected must Se
capaole of adequately rssolvmg me PCSs
in tne various Arocor mixtures so tnat
eacn Arocior
-------
in Section 4.2:2. Capillary
columns and their assseated saecialized
inj«oon tecnnicues are acsestaole
alternatives: however. Sue to proolems
associated witn tne use of capillary
columns tne analyst must demonstrate
mat tne entire SYS!""* «"" produce
acseotaoie rtsulu by performing :ne
operations described in Section 10.2.
Vj.7 Recommended primary analytical"
column: Glass, %-incn 0.0. (2-mm I.O.I.
5-ft. (180 cm) long, packed witn Gas-
CVom Q 100/120 mesn coated witn 3%
i.OV-1. ^
CI/T/W gas: 40 to 60 mL/min (helium.
nitrogen or mixtures o1 methane in argon,
as recommenced by the manufacturer of
We detector).
Temeeraiure Program: 120°C isothermal
for 2 minutes, 6°/min to 220°C and hoid
until all compounds elute. Figure 7 shows
a cnromatogram of the PCS locator
mixture (See Section 5.3) analyzed under
tnese conditions. sacn PCS geak has
been identified by assigning :ne same
relative retention times determined in me
isotnermal runs (Figures 1 tnrougn 6).
Isothermal Operation: Aroclor 1221.
1232. sr CI. through C!« isomers —
recommended range 140 :o 1 50°C ._
rirodor 1016. 12*2. 12*8. 125*. 1260. \
I 1252. 1263. or C13 tnrougn Clio isomers \
| — recommended range 170 to 200*C \
4.3.3 Recommended confirmatory
column: Glass tuomg. Vi-incn 0.0. (2-mm
I.D.). 5-ft (130 enl long, sacked witn
Gas-Chrom Q 100/120 mesn coated witn
1.5% OV-17 - 1.35% CV-210.
Carrier gax «0 :o 60 mL/ min (helium.
nitrogen or mixtures of metnane in argon.
as recommended by the manufacturer of
:ne detector).
Column ttmeeratures: Arocior. 1221.
1232. or Cl, tnrougn CU isomers
recommended range — 170 to 180°C
Aroclor 1016. 1242. 1248. 1254. 1260.
1263. or CIj tnrougn C.g isomers 2CO°C
4.4 Volumetric flasks — 10. 100. 200.
and 250- mt_
4.5 Pipets — 0.10. 1.0. and 5.0 ml.
Monr delivery (for viscous oils cut off tin
of pioen.
4.6 Micro svnnges — 1 Q.QuL
4.7 Samoie containers — 20 mL or
larger screw-cap bottles witn Teflon-
faced cao liners. (Aluminum foil cao
liners can oe used for non-corrosive
samples.)
4.3 Chromatograonic column —
Chromaflex. *00-mm long x 19-mm 1.3.
(Kontes <-t2054Q-90' Tor equivalent).
4.3 ^el Permeation Chromatograoh —
GPC Autooreo 1002 or eduivaient.
avaiiaoie from Analytical 3io Chemistry
Laooratones. Inc
4.10 Salanca — Analvneal. eaoaale of
weighing 99 g witn a sensitivity of ^
0.0001 5.
4.11 Kuderna-Oanisn (K-S] Svaoorative
Concentrator Aooaratus
4.J1.1 Concentrator nioe — 10 mL.
graduated (Kontes <• 570050-1025 or
equivalent). Calibration must be cnecxed.
Ground glass stoaoer (size 19/22 joint) is
used to prevent evaooration of solvent.
A.11.2 evaporative flask — 500 mU
(Kontes K-57001-0500 or equivalent).
Attach to concentrator tube with ssrings
(Kontes K-S62750-0012 or equivalent).
A. 11.3 Snyder column — Three-ball
macro (Kontes K503000-C121 or
equivalent).
5. Reagents and Materials
5.1 Reagent safety precautions
S.1.1 The toxicty or earcinogenicitv of
each reagent used in tnis metnod has not
been precisely defined: however, eacfl
cfiemical comoound snould be treated as
a potential health hazard. From this
viewpoint, exposure to tnese cnemicais
must ae reduced to the lowest possible
level by whatever means avaiiaoie. The
laooratory is responsible for maintaining
a current awareness file of Occuoational
Safety and Health Administration
regulations regarding trie safe handling of
the cnemical specified in tnis metnod. A
reference file of material cata-nancling
sheets snouid also be made avaiiaoie to
all oersonnel involved in me cnemical
analysis.
5.1.2 ?C3s have been tentatively
ctasstfied as known or suspected, ^uman
or mammalian carcinogens. Primary
standards of these toxic compounds
should be prepared in a hood.
5.7.3 Oietnyl etner snould be monitored
regularly to determine the peroxide
content. Under no circumstances snould
dietnyt etner be used «"tn a aerexice
content m excess of SO cam as an
explosion could result. Peroxide test
strips manufactured by =M Laooratones
(avaiiaoie from Scientific Products Co..
Cat. No. P112S-3 and other suppliers) are
recommended for :r»s test. Pro
for removal of persxices from dietnyl
etner are included in tne instructions
supplied with tne oercxice test kit.
5.2 Hexane (mixed hexanes). isooctane.
acetonitrile. metnyiene cnionce.
cydonexane. and dietnyl einer of
pesticide grade.
5.3 Recommended Column Packings
3. 3. 1 Gas Chrom Q 1 0C/ 1 20 mesn
coated witn 3% OV-i.
5. 3.2 Gas Chrom Q 1 00/1 20 mesn
coated with 1.5% OV-17 - 1.95%
OV-210.
5.4 Standards
5.4.7 Arodors 1015. 1221. 1232.
12*2. 1248. 1254. 12SO. 1252. 1253.
Primary dilutions of various Aroclors are
available from USePA. environmental
Monitoring and Suaoon Laboratory.
Quality Assurance Ersncr. 25 W. St.
Cair Street. Cincinnati. Ohio £5253.
S.4.2 2-Chlorcbior.enyl. 3-
cnlorobiphenyi. and eecacniorooicnenyi.
5.4.3 Pure, individual PCSs. as
identified in the samcia by mass
ssectrometry or mocated by rsiention
data.
5.4.4 Alumina (Ftsner AS^O or
equivalent).
5.4.5 Silica gel (Oavison Grade 950 cr
equivalent).
5.4.6" Florisil (PR grade or equivalent).
5.4.7 Sulfunc acid A.C.S.
5.4.3 Quality Control Check Sample —
Certified Samples of PC3s m oil matrices
are available from UScrA. invirenmental
Monitoring and Supaon Laooratory.
Quality Assurance Srancn. 25 W. St.
Clair Street. Cncr.nari. Ohio >S2S3.
5.5 Standard Stoat Solutions
primary dilutions of eacn of tne Arociors
or individual PC3s by weigning
approximately 0.01 5 of material witnm
sO.0001 g. Dissolve and dilute to 10.0 mL
with isooctane or nexane. Calculate tne
concentration in tn}/ia_ Store tne primary
dilutions at 4°C in 1 0- to 1 5-mL narrow-
mouth, screw-cao aonies witn Teflon caa
liners. Primary dilutions are staple
indefinitely if me seats are maintained.
The validity of mnouse-generated or
stored primary and seconoary dilutions
must 9e verified on a auarerty oasis ay
analyzing Environmental Mcnuormg ana
Support Laboratory-Cinonnati-Ouality
-------
Camrji Check Samples or certified PCS
standarcs.
5.8 Wonting Standards — Prepare
wonting standarcs simitar in PCS
composition and concentration to tne
samples ay mixing and diluting the
individual standard stock solutions. Dilute
tne mixture to volume witn pesticide
quality hexane. Calculate the
concentration in ng/ji. as tne ir.dividusi
Arociors I Section 11.4) or as :.ia
individual PCSs (Section 11.51 Store
dilutions at 4«C in 10- to 15-mL narrow-
mourn, screw-cap bottles witn Teflon cao
liners. If tne seals are maintained, tr.ese
secondary dilutions can be stored
indefinitely. (See Section 5.5.)
5.7 Laboratory control standard (LCS) —
Preoare a LCS ay soiking a PCS-free oil
typical of tne matrix normally analyzed.
suc.n as a transformer oil. at 50.0 mg/kg
witn a PCS mixture typical of :."iose
normally found in tne samples, sucn as
Aroclor 1250 at 50.0 mg/kg.
5.8 PCS Locator Mixture — Pregara a
PCS locator mixture containing 0.1 ng/ii.
of 2-c.ilorooipnenyl. 0.1 ng/;/L3-
chlorocipnenyl. 0.5 ng/^L Arodor 1242.
0.5 ng/^L Arodor 12SO. and 0.2 nq/n\.
ArocSor 12S8 in nexane (0.1 ng/vL of
decacniorobionenyl can be substituted for
Aroelor 1268). Use tne cnromatogram
generated by tne PCS locator mixture to
helo identify tne retention times of tne
various PCS isomers commonly found in
commercial PCS mixtures.
6. Sample Collection and
Handling
6.1 Samole containers snould nave a
voiume of 20 ml. or more and nave Teflon
or foil-Kned screw caos.
6.2 Sampl* Sortie Preoaration
6.2.1 Wasn all samole borfles and seals
in detergent solution. .Rinse first witn tao
water and tnen witn distilled water. Allow
:rte sorties and seals to dram dry m a
contaminant-free area. Then rinse seals
witn pesticide-grade hexane and allow to
air dry.
6.2.2 Heat samole denies to AOC°C for
15 to 20 minutes or rinse witn pesticide-
craae acetone or nexane and allow to air
dry.
6.2.3 Store the ciean 3en:es inverted or
seated until use.
6.2.* Samole sorties can :e reused.
Prior to reuse, rinse ine settles ar.d seals
tnree times witn hexane. allow TO air cry.
and then proceed to Section 6.2.1.
8.3 Samole Preservation — The
samples snould be stored in a cool. dry.
dark area until analysis. Storage times in
excess of four weeks are not
recommended for unknown or undefined
samole matrices.
8.4, Sample Collection
6.4. i rill a large container, sue.*) as a
500-mL beaker, from a representative
area of tne sample source. If practical.
mix the sample source prior to sampling.
6.4.2 rill a minimum of two 20-mL
sample booles (Field Sample 1 (FS1) and
rield Samole 2 (FS2)} approximately 80%
full from tne sampling container.
6.4.3 Repeat Sections 6.4.1 and 6.4.2 if
mere is a need to monitor sampling
precision, as described in Section 10.S.
7. Procedure
7.1 The approximate PCS concentration
of tne sample may be determined by X-
ray fluorescence (total halogen
measurement), microcoulometry (total
halogen measurement), density
measurements, or fry analyzing a very
dilute mixture of tne sample (10.000:1)
according to Section 7.4.
7.2 ror samples in tne 0- to I0p-mg/kg
.range, dilute at tne rate of 100:1 in
Ihexane.
7.2.1 Pioet 1.0 mi. of sample into a
JOO-mL volumetric flask, using a 1.0-mL
Mohr pipet. ror viscous samples, cut tne
-caoillary no off tne otoet. Dilute to volume
witn hexane. Stoooer and mix.
7.2.2 Using tne same pipet as in
Section 7.2.1. deliver 1.0 mL of sample
into a tared 10-mL aeaker weigned to
=.001-g. Reweign tne oeake'r to •£. .001 9
to determine tne weight of sample used
in 7.2.1.
7.2.3 As an alternative to Sections
7.2.1 and 7.2.2. weign aoproximately 1 g
to s .001 g of samole in a 100-mC
volumetric flask and dilute to volume witn
nexane.
7.2.4 Analyze tne diluted sample
according to Section 7.4 or store tne
diluted samole m a narrow-moutn bottle
witn a Teflon-lined screw cao.
7.3 ror samples aeove 100 mg/kg in
concentration, dilute at a rate of 1000:1
in nexane.
7.3.1 Pioet 0.10 mL of samole into a
100-mC volumetric flask, using a 0.10
mL-Monr pipet. Dilute to volume witn
nexane. stopper and mix.
7.3.2 Using the same pioet zs m
Seeion 7.3.1. deliver 0.10 ml. of samole
into a tared 10-mL beaker to = .0001 g.
Seweign tne beaker :a determine tne
weignt of sample used in Secnon 7.3.1.
7.3.3 As an alternative to Secnons
7.3.1 and 7.3.2, weign aooroximately 0.1
g to ± .0001 g of samole and in a 100 mL
volumetric flasx. Dilute to volume witn
hexane.
7.3.4 Analyze the diluted samole
according to Section 7.4 or store in a
narrow-mouth bottle witn a Teflon-lined
screw cao.
7.3.5 If The concentration of PCSs is
still too hign for the chromatograoriic
system, preoara secondary dilutions from
Sections 7.3.1 or 7.3.3 until acceptable
levels are obtained.
7.4 Analyze the sample by injecting the
hexane mixture into the gas
chromatograph. using auto injectors or
tne solvent flush technique.*
7.4.1 Recommended injecaon volumes:
Halogen-soeefic detector — 4 to StiL.
EC3 2 :o 3 «l_ Smaller volumes may be
injected wnen auto injectors are used if
tne resulting MOL are acceptable.
/Voter When semi-specific detectors are
used, cleanup techniques (See Section
4.2~2) snould be routinely incorporated
into tne analysis scneme prior to
injection.
7.5 if the resulting cnromatogram
snows evidence of column flooding or
nonlinear detector responses, further
dilute tne sample according to Section
7.3.5.
7.8 Determine wnether or not PCSs are
present m the samole by csmoarmg tne
sample cnromatogram to tnat of tne PCS
locator mixture. Section 5.3.
7.6.1 If a senes of peaks in tne samole
match some of tne retention times of
PCSs in tne PCS locator mixture, artemot
to identify tne source by comparing
cnromatograms of «acn standard
prepared from commerce! mixtures of.
PCSs (See Section 5.61. Proceed to
Section 11.4 if the source of PCSs is
identified.
7.S.2 If tne samole contains a csmoiex
mixture of PCSs. proceed to Section 11.5.
7.6.3 if a dilution ratio of 1000:1
(Section 7 3) or iigner was anaiv:ed and
no measuraole PCS aeaks were ceiectte.
analyze an aliquot of sample diluted to
10O-.1.
-------
7.S.* If several ?C3 interference
prooiems are encountered or rf ?C3 ratios
oo not match stanaares. proceed :a
Section 3. Us* alternate columns or use
GC/MS: to verify wnetner or not tne
nonreeresentative patterns are Cue to
PCS*.
8. Cleanup
Several tested cleanup techniques are
describee. Oeoenoing upon tne
complexity of tne samole. one or all of trie
techniques may Be required ;o resolve tne
PCSs from interferences.
8.1 Aad Cleanup
8.1.1 Place 5.0 mL of concentrated
sulfuric aod into a 4O-mL narrow-mouth
screw-cap Sonle. Add 10.0 mL of tne
diluted sample. Seat tne bottle with a
Teflon-lined screw-cap and snake for one
minute.
8.1.2 Allow the pnases TO separate.
transfer tne sample (upper shasel to a
clean narrow-mouth scr*w-cao bottle.
Seal witn a Teflon-lined cap.
8.1.3 Analyse according to Section 7.4.
3.1.4 If tne samole is highly
contaminated, a second or tnird acid
cleanup may be employed.
NotK This cleanup technique was tested
over a 6-montn period, using botn
electron capture and electrolytic
conductivity detectors. Care was taken to
exclude any samples tnat formed an
emulsion witn tne aod. The sample was
withdrawn well aoove me sample-acid
interface. Under these conditions, no
aoverse effects associated witn column
performance and detector sensitivity to
PCSs were noted. This cleanup technique
could adversely affect Tne
chromatograpnic column performance for
samples containing analyses otner than
PCSs.
8.2 Florisil Column Cleanup
8.2.1 Variances between batches of
flonsil may affect :ne elution volume of
tne various PCSs. for :nis reason. :he
volume of solvent required to completely
elute ail of tne PC3s must Se verified by
:n« analyst. The weigm of Flonsil can
cnen be adjusted accordingly.
3.2.2 Place a 20.0-9 charge of FJonsil.
activated at 130°C. into a Chromaflex
column. Seme tne rlorisil by tapping tne
column. Acd aoout 1 cm of annvcrous
sodium suifate to tne top of tne rlonsil.
Pre-etute tne column witn 70 to 30 mL of
hexane. Just before tne exposure of tne
sodium suifate layer to air. stop tne flow.
Discard the eluate.
8.2,3 Add 2.0 mL of tne undiluted
sample to tne column witn a 2-mL. Mohr
pipet. For viscous samples, cut tne
capillary Tip off tne pipet. Add 225 mL of
hexane to tne column. Carefully wash
down tne inner wall of tne column witn a
small amount of tne hexane prior to
adding tne total volume. Collect and
discard tne first 2S.O ml.
3.2.4 Collect exactly 200 mL of hexane
eluate in a 200-mL volumetric flask. All
the PCSs must be in this fraction.
8.2.5 Using tne same pipet as in
Section 8.2.2. deliver 2.0 mL of sample
into a tared 10-mL beaker weighed to
± 0.001 g. Reweign tne beaker to
determine the weight of the sample
diluted to 200 mL.
8.2.6 Analyze the sample according to
Section 7.4.
8.3 Alumina Column Cleanup
8.3.1 Adjust the activity of the alumina
by heating to 200°C for 2 to 4 hours.
When cool, add 3% water (weigntrweight)
and mix until uniform. Store m a tigntty
sealed bottle. Allow the alumina to
equilibrate at least 30 minutes before
use. Adjust acsvrty weekly.
8.3.2 Variances between bat cries of
alumina may affect the elution volume of
the various PCSs. ror this reason, the
volume of solvent required to completely
elute all of tne PCSs must be verified by
the analyst. The weignt of alumina can
then be adjusted accordingly.
8.3.3 Place a 50.0-g charge of alumina
into a Ciromaflex column. Sent* the
alumina by tapping. Add about 1 crn of
annydrous sodium suifate to the too of
tne alumina. Pro-«iute the column witn
70 to 80 mL of hexane Just Before
exposing tne sodium suifate layer to air.
stoo tne flow. Discard tne eluate.
3.3.* Add 2.5 mL of tne undiluted
samole to tne column witn a S-«nL Monr
piper. For viscous samples, cut tne
capillary end off tne oipet Add 3OO mL of
hexane to tne column. Carefully wasn
down me inner walls of the column witn
a small volume of hexane prior to adding
:n« total volume. Collect and discard tne
0- to SO-flM. fraction.
8.3.S Collect exactly 2SO mL of the
hexane in a 250-mL volumetric Uasx. All
tne PCSs must be in this fraction.
8.2.6 Using tne same sicet as n rveior.exana
(volume:volumei as the mooile ;.".ase.
3.5.2 Place 1 .0 mL of samoie into a
100-mL volumetnc flask, ^sing a ' -mL
Monr pioet. rcr viscous samsies. €••: tr.e
capillary tip orf the oipet.
-------
8.S.3 3ilu:« me sample to volume.
using 1 S% rnet.Tvleri* cnionde in
cycionexane (voiumervoiumei.
6.5.4 Unrig me same aicet as in
Section 8-5.2, sefiver 1 .0 me of samoi*
into a tared 1 0-me beaker ir 0.001 3>-
fleweign me aeacer (= 0.001 9) to
d*t*rmin* me wetgnt of samole used in
Section 8.5.2.
4.5.5 A* an alternative to Sections
8.5.2 ane 3.5.2. weign aoaroximateiv 1 g
(= 0.001 gj of sample ana dilute to 1 00.0
mt in 1 5* metnylene cnloride in
cyetonexane (voiumervoiumei.
4.5.5 inject 5.0 me of me diluted
samel* into cne instrument. Collect me
fraction eamzming me C1, mreugn Ct«
PCSs (see instruction manual. Section
3.5.1) m a KO f!ask esuieped wrm a 10-
mL ampul.
4.5.7 Concentrate tne Section 8.5.4
fraction Sown :o less man 5 m(_ using <•
C evaporative concentration teennicues.
3.5.3 0>lu:e to 5.0 mL wrm -exane.
men anaivze according :o Section 7.4. 3e
sure to us* 1 00 ml. as tne diluccn
volume for me final calculation.
8.8 Acatonrtrile Partition
3. S. 1 'face • 0.0 mL of We areviously
cUuted samsie into a 1 25-mL separator?
funnel Add 3.0 me of hezane. Extract me
sample four times by making vigorously
for one minute wnn 3C-me portions of
neaune-saturated acetannnle.
8.6.2 Transfer and csmsme me
acetormnle snases to a 1 -i. sesararorv
funnel and aed 550 me af eistiiled water
and AQ mL of saturated sodium c-iionce
soiucon. Mis tnorouenly for 20 to 25
leesnds. Extract witn two 10O-me
portions of .lexane by vigorousfy snaking
aoout 1 5
8.6.3 Csmome we nezane extracts m a
M. sesaraterv runnel and wesn witn TWO
1 00-mc aertions of eisalied water.
Discard t.ie water (aver and sour tne
lexane layer :nrouon a column (Section
48) sacked witn 3 to 4 mcnes of
annverous sodium suifate. Oram tne
column into a 500-n Section 10.2.
10.1.3 The laboratory must seike and
analyze a minimum of iO% of all samples
to manner continuing laboratory
performance. This arocadure is described
in Section 10.4.
10.2 To estabiis.i m* aoiliry to generate
acceptable accuracy and sreesien m me
use ef mis metnod. :ne analyst nust
perform me following operations.
10.2.1 For eacn ssmnercai PCS
mixture or individual PCS .somer
normally measured, prepare a PCS
spiking concentrate, in iseoetane wnnin
m* rang* of 40 to 60 mg/me.
10.2.2 Using a microsyringe. add 100
0L of m* PCS cancantrat* to «acn of a
minimum of four 100 g aiiduots ef PC3-
fre* oil. A representative waste oil may
be used in place of me dean oil. but one
or more additional aliquot* must be
analyzed to determine tne PCS
background level, and me seike level
/nust exceed twice tne background level
for me test to be valid. Anarvze tne
aiiduots according to tne metnod
beginning in Section 7.
1O.2.3 Calculate tne average percent
recovery, (fll. ano tn* relative standard
deviation (si ef me concentration found.
Waste oil background corrections must ae
made 9*for* a calculations are
aerformec.
1Q.2.* Using tne aaereanate data from
Taoies 1. 2. and 2. setermme m*
recovery and smgie ooerater srectsicn
exoected 'or me metrod ano csmoare
:nes* results to tre values calculated in
Section 10.2.2. if me cata are net
camearaole. me analyst must review and
'•medv potential arsoiem areas and
repeat tne test.
-------
1 0.2.5 After January 1 . 1 383. me
values for A and s must meet memod
performance criteria provided 5v me
USE? A. Environmental Monitoring and
Support Labortory. Cincinnati Ohio
AS2S3. aefore any samoles may ae
analyzed.
1 0.3 The analyst must calculate
metnoo performance of tne laboratory for
eacn soi«e concentration and parameter
aetng measured.
JO.3.1 Calculate uooer and lower
control limits for metnod performance!
Upper Control Limit (UCU » S - 3 s
Lower Control Limit (LCU * 3 - 3 s
and s art calculated as in
Secaon 10-2.3. The Ud. and Ld. can 5e
used to construct control enara' tftat are
useful in observing trends in
performance. After January 1. 1983. :ne
control limits above must Se replaced by
r^etnod performance criteria gravities' ay
me USE? A.
TO. 3. 2 The laooratory must ievetoa and
maintain separate accuracy statements of
laboratory performance for waste od
samples. An accuracy statement for tne
metnod is defined as 3 s $. The accuracy
statement snou^d ae develooed ay we
analysis of A aiicuots of waste orf. is
described in Section • 0.2-2. foilcwed 9y
me calculation of R and s. Alternately, me
analyst may use four waste oil cats
points satnered mrougn tne reduirement
for continuing Quality control in Section
1 O.A. The accuracy statements mould Se
vacated regularly.
1 0.* The laboratory >s reouired :o
coilec: a portion of tnetr samoies in
cuoticata to monitor saika recoveries. The
Tecuency of soikea sanoie analysis must
5e at least 1 0% of ail samoies or cne
samoie ser montn. wnicnever ts creater.
One aiicuot of rte samoie must ae soiced
and analyzed, as described in Secnon
10.2.2. at two times :ne oackcround level.
if tne recovery for a aarticular sarameter
aoes not fail wnnin tne control limns 'or
Tietnod aerformance. a»e results reaoned
.'or :r« sarameter m all samoies
aroeessed as oart of we same MI must
ae Qualified, as described in Secaon 11. 3.
The laeoratory snouid monitor »e
freouencv of cata so ouaiifieo :a ensure
:.-.at it remains at or 5e«ow 5%.
1 0.5 3e/ore srocessmq any samoies.
tne anarvst snouid eemonstrate ir.rougn
:.-.e analysts of a ?C3-'c*e cil samci*. :.-.at
ail glassware and reagents are free of
interferences. Eaen ame a set of sa males
is analysed or Triere is a crtange m
reagents, a laboratory reagent aiann
snouid be grecessed as a safeguard
agamsi eontammation.
10.6 If is recommended tftat tne
laboratory adoot additional quality
assurance oraoccs for use witn ous
metnod. The most producuve. specific
araences deoend uoon tne needs of tne
laboratory and me .nature of tne samoies.
rieid duplicates may se analyzed to
monitor me areesjon of tne samoling
tecnnicue. When doubt etists regarding
me idemrfieatJon of a peak on tne
crtrematocram. confirmatory techniques
juen as 6C witn a dissimilar column.
saecific element detector, or MS must ae
used. Whenever aossiote. me laboratory
should perform analysis of standard
reference materials and sanieoate m
relevant performance evaluation studies.
10.7 Analyze tne LCS. Secaon 5.7.
daily before any samples are analyzed.
Instrument status checks, calibration
curve validation and loVtg-eerm greesion
are obtained from these data. In addition.
resaonse fata obtained from me LCS can
ae used to estimate me concentration of
me unknowns, rrom mis information, me
aeprooriate standard dilutions can ae
determined for single-point calibrations.
10.8 Analyze on a cuarterty basis a
Quality Control Samoie (Secson 5.4.S.) of
PC3s m oil or wnenever new standard
eilutjons are oreoared.
JO.A. 1 The results cf me Quality
Control Sample sneuld agree wnnm 15%
of me true value. If tnev co nee me
analyst must eneek eacn steo m me
standard preparation procedure to resolve
me grootem.
11. Calculations
11.1 Locate eaen PC3 in me samoie
cnromatogram by comparing tne
retention time of me sussed peak to me
retention data garnered from analyzing
standards and interference-free Quality
Control Samples. The w>etn of me
retention ame window used to make
identifications snouid ae eased uoon
measurement of acruai retention ame
variations of Jtancarcs over tne course of
a cay. Three times me standard deviation
of a retention time for «acn i*C3 can ae
used co calculate a suggested window
VZK nowever. tne experience of tne
analyst snouid wetgn neavtiy m tne
interpretation of cnromatograms.
1 1 .2 '•( me resocnse for any ?C3 pea«
«xc*eC3 me wonting range of tr.e svstem.
Silute acssrding to Sedan 7 2.5.
11-3 If ac^irate measurement of me
seeks in me ?C3 eluoon area of tne
cnromatogram is arevemed ay me
presence of interferences, furtner
cieanua is reouired.
11.4 If me parent Aroders or PC3s are
identified :n me samoie. calibrate
according to Secaon 3. The concentration
at tne PC3s m me samoie is calculated 3y
comoaring me sum of me responses for
each PCS in me standard to me sum of
all of tne ?C3s in tne samoie. This is
particularly important as samp>a
concentrations aooroacn wrtnm 20% of
50 mo/kg or any otner EpAwesuiated
concentration. If calculations are based
uoon a single ?C3 peak or -joon a small
percentage of tne total ?C2 aeaks.
senous errors .nay result. Peaks
comprising less than 50% of me total can
ae disregarded only if ( ' 1 interference
problems persist after deanuo. (21 me
source of PC3s >s obvious, or (31 tne
concentration of PC3s is not within =10%
of an £?A-controtled value sucn as 50
rag/kg.
JJ.4.J Measure me aea< .«.eignt or
peak area of eacn peak identified as a
PC3 (Section 1 t.t) in aotn me sample
and me standard,
7 1.4.2 Use me following formula to
calculate me concentration of PCSs m me
sample:
3 * V
Concentration
wnere:
Sum of standard
Peak He>gnts lareasi
ng of standard mjeeed
Sum of sample.
Peak Heicnts (areas)
w
a mm/rt=
Vt * dilution volume of samoie >n mt.
W 3 wetgnt of me samoie m grams
', 11 .S if me parent Arocers or source of
\ PCSs is not apparent, calculate tne
: concentration according to me arocedure
of Weao ano MeCail.* The concentration
' af tne PC3S m eacn acak >s cetermmed
:mdnoouan tne
-------
samole must ae induced in tnese
calculations.
7 7.5.7 Small venations between
Arocler batcnes make it necessary to
obtain standards preoared from a soecrfic
source of Arociors. Primary dilutions of
these reference Arociors will be available
in 1981 from tne USE?A. Environmental
Monitoring and Suooon Laboratory.
Quality Assurance Sranc.1. Cincinnati.
Ohio 4S2S3.
7 7.5.2 Analyze a standard mixture of
Arocicrs 1242. 1254. and 12SO under the
conditions shown in Figures 3. 5. and 6.
"Analyze the sample under the same
conditions. Compare the resulting
standard chromatograms to those shown
in Figures 3. 5. and 6. Each PCS peak
must be resolved as well or better than
those shown in the figures. Determine
the relative retention time (RRT) of each
peak in the standards with rsspect to
p.p'-OOE or assign the HRT shown in the
figures to the corresponding peak >n the
standard. Identify the RRT of eacn PCS in
the sample ay comparing tne sample
chromatogram to me standard
criromatograms.
7 7.5. J identify tr.e most likely Arociors
present in the sample, using the
Identification riow Chart. Figure 3.
7 7.5.4 Analyze standards according to
Section 9. using the appropriate Arodors.
7 7.5.5 Determine the instrument
resoonse factor (A) for each individual
PC3. using the following formula:
Peak Heignt (area)
Ngi x mean weignt %
Too
wnere:
Ngj 3 Ng of Arodor standard injected
(mean weight percent is obtained
from Tables 4 through 91.
7 7.5.5 Calculate the concentration of
•acn PCS in tne sample, using tne
following formula:
Concentration mg/kg ».*..!
A = Resoonse lacor from 11.5.5
3 =
Peak Heignt (areas) of samole mm/id.
t£, injected
V, a dilution volume of samole in mi.
W a w«ignt of samole in grams
The concentration of each PCS must be
calculated and added togetner to obtain
tne total amount of PCSs present.
11.6 Report all data in mg/kg.
11.7 Round off all data to two
significant figures.
11.8 Add all Arociors and report what
was used as the standard. For example.
57 mg/kg measured as Arocior 1 260 or
57 mg/kg measured as Arociors 12*2
and 1 260.
11.9 Data for the affected parameters
of samples processed as part of a set
where the laboratory spiked sample
recovery falls outside tne control limits in
Section 1 0.4 must be labeled as suspect.
11.10 Determine- tne actual recovery
for eleeTon capture analyses of each
sample in the uneorrected 40* to 50-
mg/kg concentration range (See Section
3.4). Report tne corrected value and :ne
recovery.
12. Precision and Accuracy
12.1 The data shown in Tables 1
through 3 were generated using the
recommended procedures described in
this method to analyze both spiked and
nonsoiked oil samples of varying degrees
of complexity. Data for both the HED and
SCO were generated ay the USePA,
Environmental Monitoring and Support
Laooratorv. Physical and Chemical
Metnpes Sranch. Gnennati. Ohio 452S3.
References
1. rederal Register. 4Q CF3. Part 761.
Jury M981.
2. sicnelberger. J. W.. L £. Hams, and
W. 1_ Sudde. AnaL Chem.. 4£. 227
(197*).
3. rederal Register. 40 CrR. Sections
136.4 and 136.5. July 1. 1981.
4. White. L 0.. et ai..~'HA Journal. 31.
22S.H 970).
5. Handbook of Analytical Quality
Control m Water and Wastewater
Laboratories. e?A-6OO/4-7S-01 9.
USc?A. Environmental Monitoring
and Suooon Laboratory. Cincinnati.
Ohio 45268. Marcn 1979.
Webb. R. G. and A. C McCall. J.
Chrom. Sci« 11. 366 (1973).
a
-------
Table 1. AcKiract and areasian using sai*ed motor o/f
iPracisianl
Dilution
100:1
100:1
100.1
100:1
100:1
-
-
~
-
••
-
»
-
~
~
~
"
~
~
~
*
*
"
*
"
~
MED
SCO
MED
SCO
SCO
H£O
SCO
M£0
SCO
H£0
SCO
HSO
SCO
HSD
SCO
HSO
SCO
HSO
SCO
HSD
SCO
HSD
SCO
HSD
SCO
HSD
SCO
Metnod
Cleanup
None
None
Nona
None
3.1
3.1
3.1
3.1
3.2
8.2
8.2
8.2
3.3
8.3
8.3
8.3
8.4
3.4
3.4
8.4
3.5
3.5
8.5
3.5
8.6
8.6
8.6
8.5
Soike
mg/kg
30.3
30.3
31.1
31.1
30.3
30.3
31. 1
31.1
30.3
30.3
31. 1
31.1
30.3
30.3
31.1
31.1
30.3
30.3
31.1
31.1
30.3
30.3
31.1
31.1
30.3
31.1
30.3
31.1
Aroclor
Spiked
1242
1242
1260
1260
1242
1242
1250
1260
1242
1242
1260
1260
1242
1242
1260
1260
1242
1242
1260
1260
1242
1242
1250
1260
1242
1242
1250
1250
Cane.
found
mg/kg
28.2
2S.T
27.2
23.9
23.4
25.-*'
28.1
24.3
30.7
27.3'
3O.9
31.0
30.3
29.5'
23.3
30.3
29.4
25.4*
29.4
23. 5
31.9
23.4'
33.5
3O.9
3-4.4
23.41
29.1
27.0
Xel. Std.
Deviation
4.2
5.7
2.0
23
11.5
5.1
3.0
7.3
2.4
10.2
3.6
3.6
8.5
5.0
4.7
6.5
5.3
5.3
5.2
4.5
3.5
3.0
9.2
5.5
3.3
4.4
4.2
4.5
Percent
Recovered
33.1
88.1
37.3
7S.3
93.7
33.3
30.3
78.1
101.
30.1
99.4
39.7
100.
35.4
35.3
39.0
370
27.}
S4.5
JOS.
75.3
77.2
108.
59.4
707.
77.2
36.7
86.7
Numter
of
Oilutions
5
3
5
J
3
3
3
3
4
4
4
A
3
3
3
3
3
3
3
3
3
2
3
3
4
4
4
4
1 ' Severe interference orooJems in e/uo'on tret of 1242. Measurement ossed upon ost/y 3 of trie 10 norma/fy resolved me/or seats.
deanuo tecrinigue. Sections 8.1. 3.2. 3.3. 3.4. 8.5. and 8.6 did not improve tne ova/fry of tn« 1242 chromatogram. If this were an
•jnknovtn sample, it would be impossible to auatitatrve/y identify ifie aresencs of Arocior 1242 using SCO. The HSD provided an
interference-free ctwomatogram.
-------
T*64e 2. Aesuraer »nd precision using vesse transformer fluids
Samale <
>4
<4
A
A
A
A
A
A
A
A
A
A
A
A
a
3
3
a
Dilution
Ratio
rOQ:J
~
-
<•
~
t»
"
•
«#
*
•
"
~
**
10OO:1
-
~
"
Oetatzor
SCO
HEO
SCO
HEO
SCO
HEO
SCO
HEO
SCO
HEO
SCO
HSO
SCO
HEO
SCO
HEO
SCO
HEO
Method
Cleanuo
None
None-
8.1
8.T
&2
8~2
8.3
8.3
8.4
8.4
8.5
8.5
None
None
None
m
t9
~
1260
Spike
mg/leg
_ m
M
_
..
.«
_
—
—
_
_
«.
_
27.0
27.0
-—
mm
453
4SS
A*g.(Ql
Cane.
found
22.8
27.0
22.8
29.7
22,4
23.2
22.7
27.8
20.9
30.2
23.8
28.6
45.0
55.2
452
471
875
916
(Precisian)
*eL Std.
Oevietion
. %
3.5
1.7
2.5
1.4
1.0
2.2
1.3
2.3
_
_
0.3
4.1
3.3
1.5
0.8
1.2
0.5
2,0
(AesuracYl
Pereant
Aecyvered'
^
_
„
—
—
• «
~
—
..
_
..
..
91
102
— —
«•
S5
99
Numaaf
at
Dilutions
7*
7»
7*
7
3*
3*
31
3»
;
;
7*
7»
7
71
7*
7
71
7»
c
c
c
c
;ooo.-r
»
-
SCO
HEO
SCO
- HEO
None
*
-
m
_
..
300
300
284
300
507
636
1.2
1.4
3.6
3.9
..
..
704
114
7
7
7*
7
susatnded solids
1 A • dark waste oil
3 • olacic vaste
C ' dear westa ail
3 - til samoles contained Arodor 1260
2 Quslicato analyses made tt eaen dilution
JO
-------
Tmbie 3. Accuracy and'precision tnd limit of detection data results a/ analyses of
Shell transformer fluid spiked with PC3s it 5.0 and 27 mg/kg
electron datura Detector
[JOQ:I dilution!
Arocior
1221
1242
1254
12SO
Soike
(mg/kg)
5.0
5.0
5.0
£0
Number of
Analyses
7
14
7
14
Avg.
(mo/kg)
7.5
3.8
4.1
4.7
Standard
Deviation
0.43
0.18
0.08
0.18
Percent
Recovery
ISO
76
32
9*
MDL*
Img/kg)
1.4
0.5
0.2
0.5
A r odor
SCO
HSO
Electrolytic Conductivity Detector
(100:1 dilution)
Soike Number of Avg. Standard Per cant
(mg/kgi Analyses (mg/kg) Deviation Recovery
(mg/kgj
1221
1242
1254
1250
5.0
5.0
5.0
5.0
5
7
e
7
7.5
5.9
5.8
5.4
0.23
0.17
0.1 S
0.10
ISO
118
IIS
108
0.7
0.5
0.5
0.3
Shell Transformer OH •~ 27 sent Arocior 1250
(100:1 dilution)
•
Soi*e Number of Avg. XeL StA Percent
Detector fmg/kgf Analyses fmg/kg) Deviation. % Recovery
27
27
14
7
24.0
283
.70
2.1
39
705
MCL = Metnod Oetecdon Limit at 39% confidence tnat the value is not zero.
Nora: At these values,it would be impossible to identify ArocJor patterns with
any degree of confidence. 1 mg/kg appears to be a reasonable MOL
where:
' the method detection limit
' the students' t value appropriate for a 35%
confidence level and a standard deviation
estimate with n-1 degrees of freedom.
• standard deviation of the rep/icata analyses
T*b4e 4. Composition at Arocior 1231'
Meen
Weight Relative Number of
RRT"* Percent StdL Dev. J Chlorines«
11
14
IS
13
21
28
32
r-37
Uo
Total
31.8
13.3
1O.1
2,3
20.3
5.4
1.4
1.7
93.3
15.3
3.1
3.7
9.7
9.3
13.9
30.1
48.3
1
1
2
2
2
3J rs%
2T/C%
3
3
' Data obtained from Weab and McCail.'
1 Retention time relative ta f.s'-OO£—10O.
Measured from first aopearanca
of solvent. Overlapping peaks tnat are
quantitated as one peak are bracketed.
3 Relative standard deviation of 17 analyses
(as percentages of the /nean of if.e resultsl
* From GC/MS data. Peaks containing
mixtures of isomers of different cnlorine
numbers are oraciseted.
-------
Table S.
•tffT-
11
1&
IS
[20
28
22
37
40
&7
S4
53
70
73
Total
Composition of Aroclar 1232 '
Mean
Weignt
Percent
1S.2
9.9
7.1
17.3
9.5
3.9
6.3
0.4
4.2
3.4
2.6
4.5
1.7
942
Relative
Std. Oev. »
3.4,
2.5
6.3
2.4
3.4
4.7
2.5
2.7
4.1
3.4
3.7
3.1
7.5
Number of
Chlorines*
1
1
2
2
2
2'\4O%
5-1 50%
3
3
3
4
3-133%
4167%
4
4-i 90%
5-1 10%
4
i Oata obtained from Weao and McCall.'
: Detention time relative :o p.p'-OOE—lOO. Measured from first aopearanca
sf solvent. Overlapping peaks tftat are quantnated as one peak are aracieesad.
3 Relative standard deviation of four analyses fas percentages of tfte mean of tne resuttsi
t from GC/MS data. Peaks containing matures of isomers of afferent chlorine numeers
are iraeketed.
Table S. Composition of Aroelor 1242'
Mr*
it
IS
21
23
32
37
4Q
47
54
53
70
78
34
33
'04
125
:4S
Mean
Weight
Percent
1.1
2.9
11.3
11.0
0.1
11.5
11.1
a. a
S.3
5.5
10.3
3.3
2.7
1.5
2.3
1.6
1.0
Relative
Std. Oav.3
3S.7
4.2
3.0
5.0
4.7
5.7
6.2
4.3
2.9 ~
3.3
2.3
4.2
9.7
9.4
16.4
20.4
19.9
Number of
Chlorines*
1
2
2
2-1.25%
3
3
3
4,
J-i 33%
4
4-i 90%
5J 10%
4
5
5
5
5-1 35%
oJ'5%
5"T 75%
5-1 25%
Total 58.5
' 2ata ootamed from Weoo »ntf McCail. •
: Detention time reietrve :o 3.3 -3CE = »00. Measured from first appearance of solvent.
'• Relative stancard ceviaoon of zx tnatvses fas percentages of the mean of the resunsi
• ?rom GC/MS :ata. Peats containing mixtures of isomers of different chlorine
are bracketed.
12
-------
ft*. 7.
21
23
32
47.
40
47
54
S3
70
75
34
38
104
112
125
146
Total
Composition of Arocior 1248*
Mean
Weignt
Percent
1.2
5.2
3.2
3.3
8.3
1S.S
9.7
9.3
19.0
6.6
4.9
3.2
3.3
1.2
2.8
1.5
103.1
Relative
Sid. Oev.*
23.9
3.3
3.8
3.6
33
1.1
6.0
5.3
1.4
2.7.
2.5
3.2
3.6
6.5
5.9
10.0
Number of
CMorines*
2
3
3
3
f]*fy
4
3j/0%
4
4-j ao%
4
S
5
4-t1O%
5-1 S0%
5
5-j50%
. 5-1 70%
5n£5%
5-175%
1 0*ts obtained from Weto anti McCalL*
• Detention time relative to p.s'-OO£»>00. Measured from first tooearance ofsolvent.
1 Xetoma saneani deviation of sot analyses fas percentages of the mean of tf>e rasuttsi.
• ?rom GC/MS data. Peats containing mixtures of isomers of different numbers
are oracxeteH
TaeJe 8. Composition of ^roe/or 1254*
Mean
/W7*
47
54
S3
70
34
53
104
125
14$
ISO
174
ISO
174
203
232
Total
Weignt
Percent
6.2
2.9
1.4
13.2
17.3
7.5
13.6
15.0
10.4
1.3
8.4
1.3
8.4
1.8
1.0
100.0
Relative
SttL Oev.*
3.7
ZS
2.3
2.7
;_a.
S.3
3.8
2.4
2.7
8.4
5.5
8.4
5.5
18.S
25.7
Number of
Chlorines*
4
4
4
4-] 25%
5J 75%
5
- 5
5
5n 70%
5-130%
5^ 30%
5-1 70%
5
6
6
6
6
7
Zata ootamea from Weoa tnd AfcCiM.*
| Attention time relative to o.g'-OOE-* 100. Measured from first aooearanee of solvent.
'• 3elawe standard deviation of sia tnerrses fas percentages of trie meen of Vie resuost.
• from GC/MS data. Peats containing mixtures of isomers of afferent cnlorine
.lumberrare araeteted.
13
-------
9. Composition of Aroclor /2501
ART*
70
34
So-
117
125
146
ISO
174
203
r232
\-24A
230
332
372
A£3
S28
Total
Mean
Weight
Percent
2.7
4.7
3.8
3.3
12.3
14.1
4.9
12.4
9.3
9.8
11.0
4.2
4.0
.5
r.s
98. S
Relative
Std. Oe*.*
S-.3
1.6
3.5
ft 7
3.3
3.S
2.2
2.7
4.0
3.4
2.4
5.0
8.6
2S.3
10.2
Numper of
Chlorines*
S
S
5\ 60%
6
5-j 75%
6-1 £5%
5
ff-|5O%
71 50%
6
fin 1O%
7-1 9O%
6"\ 10%*
7-*9Q%
7
7
a
a
a
' Oaia detained from Weto and
1 Detention time relative to p.a'-OOE—IOO. Measured fromfirst appearance of solvent.
Overlapping peats tfiet are auamnated as one seak are bracketed.
3 Relative standard deviation of sot tnafyses las percentages af the mean of the resuici.
' from GC/MS data. Peaks containing mixtures of isomers of different chlorine
numbers are oracJtetedL
*C3mposnion determined at the center of peak 104.
* Composition determined at the center of pea* 232.
21
1
i
i
i
i
i
i
t
j
i
1
i
i
i
21
It
'•
t
i
i
16
1
*1
1 1
/ =111
1*U JVU
i
i
i
i
i
y
i
Column: 3% OV-I
Detector
s/eevon Capture
Column Temperature:
'SO°C
28
•
A
M J^
vV-x_
Column: 354 OV-r
Detector: Electron Capture
Column Temperature: 15Q9C.
0 4 3
Time. mm.
figure J. GascnromatogramotAro-
etor 1221.
4
Time. nun.
Figure 2. G*s chromatpgram o1 Aroctor 1232.
14
-------
37
Column: 3% OV-1
Oeteszor r/eetron Ctoture
Column Temoereture: 77O°C
J2
Time, min.
figure 3. Ges efiromnogrtm o( Aroelof 1242.
Column: 3KQV*1
Detector? Elesxron Csature.
Column Temperature: 7 70"C
0 4 g 12
Time. mm.
figure 4. G*s ehrometogrtm ofAroclor 1248.
20
;s
-------
Co/umiK 3% OV-f
Dotoaon llowon Cioturt.
Column rtmgtroturoi 170*C
>2t
233
t 13 It
Tlmo. min.
<3tt thfomotogrtm ofArotlor I2H.
20
Ca/u/nrv 3% QV-l
OfiMtw: tltttrtn Ctttur*
Column Ttmovnurv 170*C
S2I
0 * t 12 It 20 24 21 32 3t 40 44 4t S2 51 10
Tlmo. m//t
flguro 8. Oof ttiromotognm of Aroolor 1290.
16
-------
[
Calumni 3% QV-t
Of Motor: Hill 700*4
-f VM/mtft f» J20*C
1
li
04 i 12 If 20 24
Tttfltt /Flrl9«
ffyun 7. G*iiftrom»t*ffr»/n«fPQiloeitarm/gtur*
21 32
17
-------
Appendix 7-J
Method 680: Determination of Pesticides
and PCBs in Water and Soil/Sediment by
Gas Chromatography/Mass Spectrometry
7-J-l
-------
Method 680. Determination of Pesticides and PCBs
in Water and Soil/Sediment
by Gas Chrcmatography/Mass Spectrometry
November 1985
Ann Alford-Stevens
Thomas A. Bellar
Janes W. Eichelberger
William L. Budde
Physical and Chemical Methods Branch
Environmental Monitoring and Support Laboratory
Office of Research and Development
D. S. Environmental Protection Agency
Cincinnati, Ohio 45268
-------
INDEX
Section
Number Subject
1 Scope and Application
2 Summary of Method
3 Definitions
"4 Interferences
5 Safety
6 Apparatus and Equipment
7 Reagents and Consumable Materials
8 Sample Collection, Preservation and Handling
9 Calibration
10 Quality Control
11 Procedures
12 Calculations
13 Automated Identification and Measurement
14 Method Perforamnce
15 References
Tables
1 Re ermine nded GC Operating Conditions
2 PCB Congeners Used as Calibration Standards
3 Scheme for Preparation of PCB Stock Solution
4 Composition and Approximate Concentrations of Calibration Solutions
for Pull-Range Data Acquisition
5a Composition and Approximate Concentrations of Calibration Solutions
for SIM Data Acquisition for PCB Determinations
5b Composition and Approximate Concentrations of Calibration Solutions
for SIM Data Acquisition for Pesticide Determinations
6 Criteria for DFTPP Spectrum
7,i Ions for Selected Ion Monitoring to Determine PCBs by Acquiring
Data for Four Sets of OS Ions Each
7b Ions for Selected Ion Monitoring to Determine PCBs by Acquiring
Data for Five Sets of <2Q Ions Each
7c Five Ion Sets of <2Q Ions Each for Selected Ion Monitoring of PCBs
8 Retention Time Data For PCB Isomer Groups and Calibration Congeners
9 Ions for Selected Ion Monitoring Data Acquisition for Pesticide
Analytes, Internal Standards and Surrogate Compounds
10 Ion Sets for Selected Ion Monitoring of Pesticide Analytes,
Internal Standards, and Surrogate Compounds
11 Known Relative Abundances of Ions in PCB Molecular Ion Clusters
12 Quantitation, Confirmation, and Interference Check Ions for
PCB Analytes, Internal Standards, and Surrogate Compounds
13 Correction for Interference of PCB Containing Two Additional Chlorines
14 Correction for Interference of PCB Containing One Additional Chlorine
15 Accuracy and Precision of Automated Measurements of PCBs and Pesticides
in Fortified Water Extracts
Figures
1
2
Total ion current profile of PCB calibration congeners and
pesticide Analytes
Diagram indicating approximate relative retention times of PCB
isomer groups and retention time congeners.
-------
1. SCOPE AND APPLICATION
1.1. This method provides procedures for mass spectrometric determination
of polychlorinated biphenyls (PCBs) and the listed pesticides in water,
soil, or sediment. This method is applicable to samples containing PCBs
as single congeners or as complex mixtures, such as commercial Aroclors.
PCBs are identified and measured as isomer groups (i.e., by level of
chlorination). The existence of 209 possible PCB congeners makes
impractical the listing of the Chemical Abstracts Service Registry
Number (CASKN) for each potential method analyte. Because PCBs are
identified and measured as isomer groups, the non-specific CASKN for
each level of chlorination is used to describe method analytes.
Analyte(s) Formula
Aldrin
BHCs
alpha isomer
beta isomer
delta isomer
gamma isomer(lindane) CgHgClg
Chlordane (technical)
alpha-chlordane C^gHgClg
gamma-chlordane C •) gHgClg
trans-nonachlor CfnHsClg
4,4*rDDD C14H10C14
4,4'-DDE
4,4'-DDT
Dicldrin C12HgCl6O
Endosulfan I
Endosulfan II
Endosulfan sulfate ,
Endrin
Endrin aldehyde C12HgCl60
Endrin ketone
Heptachlor
Heptachlor epoxide
Hethoxychlor
PCBs
Monochlorobiphenyls
Dichlorobiphenyls
Trichlorobiphenyls
Tetrachlorobiphenyls
Pentachlorobiphehyls C^HsCls
Hexachlorobiphenyls C^2R4Clg
HeptachlorobiphenyIs C^ 2H3Cl7
Octachlorobiphenyls C-) 2H2Clg
Nonachlorobiphenyls Ci2RCl9
Decachlorobiphenyl C^2C1^Q
C10H5C17
C10H5Cl70
C16H1SC1302
C12HgCl
C12H8C12
C12H7C13
CASHN
309-00-2
319-84-6
319-85-7
319-86-8
58-89-9
57-74-9
5103-71-9
5103-74-2
39765-80-5
72-54-8
72-55-9
50-29-3
60-57-1
959-98-8
33213-65-9
1031-07-8
72-20-8
7421-93-4
53494-70-5
76-44-8
1024-57-3
72-43-5
27323-18-8
25512-42-9
25323-68-6
26914-33-0
25429-29-2
26601-64-9
28655-71-2
31472-83-0
53742-07-7
2051-24-3
-------
-2-
1.2 Detection limits vary among method analytes and with sample matrix, sample
preparation procedures, condition of the GC/MS system, type of data
acquisition, and individual samples. The calculated method detection
limit (HDD for each pesticide in fortified reagent water extracts analyzed
with full-range data acquisition is presented in Sect. 14. Analysis of
calibration solutions indicated that the calculated MDLs do not accurately
reflect instrumental detection limits. The following guidance is based on
numerous analyses of calibration solutions with one instrument over a period
of approximately six months. Pesticide analytes other than endosulfans
I and II can be identified and accurately measured when the injected
aliquot contains 2 ng of each analyte; the endosulfans require about 4 ng
each. With selected-ion-monitoring (SIM) data acquisition, pesticide
analyte detection limits are lowered by at least a factor of five. Detection
limits for individual PCB congeners increase with increasing number of
chlorine atoms, with the detection limit for decachlorobiphenyl being
about 5-10 times higher than that of a monochlorobiphenyl. A monochloro-
biphenyl can be identified and accurately measured when the injected
extract aliquot contains 1 ng and full-range data are acquired. The
detection limit for total PCBs will depend on the number of individual
PCB congeners present. SIM data acquisition procedures reduce the detection
limit for PCBs by at least a factor of three.
2. SUMMARY OF METHOD
A 1-L water sample is placed in a separatory funnel and extracted with methylene
chloride. Appropriate extraction procedures for soil/sediment samples will be
added when results are obtained from ongoing experiments. The extract is dried
and exchanged to hexane during concentration to a final volume of 1 mL or less.
Sample extract components are separated with capillary column gas chronatography
(GC) and identified and measured with low resolution, electron ionization mass
spectrometry (MS). An interfaced data system (DS) to control data acquisition
and to store, retrieve, and manipulate mass spectral data is essential. Either
full-range or selected-ion-monitoring (SIM) data are acquired, depending on the
concentration range of concern. If full-range data are acquired, all method
analytes can be identified and measured with one GC/MS analysis. If all pesti-
cides and PCBs must be determined and if SIM data are necessary to meet required
detection limits, two GC/MS analyses are necessary, one to detect and measure
pesticides and one to detect and measure PCBs.
Two surrogate compounds are added to each sample before sample preparation;
these compounds are 13C12-4f4'-DDT and 13C6-gamma-BHC. Two internal standards,
chrysene-d-j2 And phenanthrene-d-j g, are added to each sample extract before GC/MS
analysis and are used to calibrate MS response. Bach concentration measurement
is based on an integrated ion abundance of one characteristic ion* All pesticides
are identified as individual compounds, and a concentration is calculated by
relating the MS response of each compound to the MS response of the internal
standard with GC retention tlaa nearer that of the pesticide analyte. The
extent of sample contamination with technical chlordane is indicated by identi-
fication and measurement of the two most persistent components, gamma-chlordane
and nonachlor. (Alpha-chlordane and heptachlor, other major components of
technical chlordane, may also be present and will be detected and measured
with this method.)
PCBs are identified and measured as isomer groups (i.e., by level of chlorination)
A concentration is measured for each PCB isomer group; total PCB concentration
in each sample extract is obtained by summing isomer group concentrations.
-------
-3-
Nine selected PCB congeners are used as calibration standards, and one internal
standard, chrysene-d12/ is used to calibrate MS response to PCBs, unless sample
conditions require the use of the second internal standard, phenanthrene-dig.
3. DEFINITIONS
3.1 CONCENTRATION CALIBRATION SOLUTION (CAL) — A solution of method analytes
used to calibrate the mass spectrometer response.
3.2 CONGENER NUMBER — Throughout this method, individual PCBs are described
with the number assigned by Ballschmiter and Zell (2). (This number is
also used to describe PCB congeners in catalogs produced by Ultra Scientific,
Hope, RI.)
3.3 INTERNAL STANDARD •— A pure compound added to a sample extract in known
amounts and used to calibrate concentration measurements of other compounds
that are sample components. The internal standard must be a compound
that is not a sample component.
3.4 LABORATORY DUPLICATES (LD1 and LD2) —Two sample aliquots taken in the
analytical laboratory are analyzed with identical procedures. Analysis
of laboratory duplicates indicates precision associated with laboratory
procedures but not with sample collection, preservation or storage procedures.
3.5 LABORATORY PERFORMANCE CHECK SOLUTION (LPC) — A solution of method analytes,
surrogate compounds, and internal standards used to evaluate the performance
of the GC/MS/DS with respect to a defined set of method criteria.
3.6 LABORATORY REAGENT BLANK (LRB) — An aliquot of reagent water or neutral
solid reference material that is treated as a sample. It is exposed to
all glassware and apparatus, and all method solvents, reagents, internal
standards, and surrogate compounds are used. The extract is concentrated
to the final volume used for samples and is analyzed the same as a sample
extract.
3.7 LABORATORY SPIKE DUPLICATE SAMPLE — One aliquot (LSD) of a sample is
analyzed before fortification with any method analytes. In the laboratory,
a known quantity of method analytes (LSA) is added to two independent
aliquots of the same sample/ and final analyte concentrations (LF1 and
LF2) are measured with the same analytical procedures used to measure LSD.
3.8. LABORATORY SURROGATE SPIKE
/
3.8.1 Measured Value (LSD ~ Surrogate compound concentration measured
with the same procedures used to measure sample components.
3.8.2 Theoretical Value (LS2) — The concentration of surrogate compound
added to a sample aliquot before extraction. This value is determined
from standard gravimetric and volumetric techniques used during
sample fortification.
3.9 METHOD DETECTION LIMIT (MDL) — A statistically determined value (1)
indicating the "»!«•<«»"» concentration of an analyte that can be identified
and measured in a sample matrix with 99% confidence that the analyte
concentration is greater than zero. This value varies with the precision
of the replicate measurements used for the calculation.
-------
3.10 PERFORMANCE EVALUATION SAMPLE — A sample containing known concentrations
of method analytes that has been analyzed by multiple laboratories to
determine statistically the accuracy and precision that can be expected
when a method is performed by a competent analyst. AnAlyte concentrations
are unknown to the analyst.
3.11 QUALITY CONTROL (QC) CHECK SAMPLE — A sample containing known concentra-
tions of analytes that ia analyzed by a laboratory to demonstrate that it
can obtain acceptable identifications and measurements with procedures to
be used to analyze environmental samples containing the same or similar
analytes. Analyte concentrations are known by the analyst. Preparation
of the QC check sample by a laboratory other than the laboratory performing
the analysis is highly desirable.
3.12 SURROGATE COMPOUND -- A compound not expected to be found in the sample
is added to a sample aliquot before extraction and is measured with the
same procedures used to measure sample components. Associated with the
surrogate compound are two values, laboratory surrogate spike- measured
value (LSD and laboratory surrogate spike - theoretical value (LS2).
The purpose of a surrogate compound is to monitor method performance
with each sample.
4. INTERFERENCES
4.1 Interferences may be caused by contaminants in solvents, reagents, glassware,
and other sample processing equipment. Laboratory reagent blanks (LRBs)
are analyzed routinely to demonstrate that these materials are free of
interferences under the analytical conditions used for samples.
4.2 To minimize interferences, glassware (including sample bottles) should
be meticulously cleaned* As soon as possible after use, rinse glassware
with the last solvent used. Then wash with detergent in hot water and
rinse with tap water followed by distilled water. Drain dry and heat in a
muffle furnace at 450*C for a few hours. After cooling, store glassware
inverted or covered with aluminum foil. Before using, rinse each piece
with an appropriate solvent. Volumetric glassware should not be heated
in a muffle furnace.
4.3 For both pesticides and PCBs, interference can be caused by the presence
of much greater quantities of other sample components that overload the
capillary column; additional sample extract preparation procedures must
then be used to eliminate interferences. Capillary column GC retention
times and the compound-specific characteristics of mass spectra eliminate
many interferences that formerly were of concern with pesticide/PCB
determinations with electron capture detection. The approach and identi-
fication criteria used in this method for PCBs eliminate interference by
most chlorinated compounds other than other PCBs. With the isomer group
approach, coeluting PCBs that contain the same number of chlorines are
identified and measured together. Therefore, coeluting PCBs are a problem
only if they contain a different number of chlorine atoms. This interference
problem is obviated by rigorous application of the identification criteria
described in this method.
4.4 For SIM identification and measurement of pesticides, other chlorinated
sample components that produce the same quantitation and confirmation
ions may interfere, but only if retention times are nearly equivalent.
-------
-5-
5. SAFETY
5.1 The toxicity or carcinogenicity of each chemical used in this method
has not been precisely defined. Therefore, each should be treated as a
potential health hazard, and exposure should be reduced to the lowest
feasible level. Each laboratory is responsible for safely disposing
materials and for maintaining awareness of OSHA regulations regarding
safe handling of the chemicals used in this method. A reference file of
material data handling sheets should be made available to all personnel
involved in analyses. Additional information on laboratory safety is
available (3-5).
5.2 The following method analytes have been classified as known or suspected
human or mammalian carcinogens: BHCs, 4,4'-DDD, 4,4'-DDT, and PCBs.
Primary standards of these compounds should be prepared in a hood. A
toxic gas respirator should be worn when the analyst handles solutions
containing high concentrations of these compounds.
6. APPARATUS AND EQUIPMENT
6.1 SAMPLING EQUIPMENT
6.1.1 Water Sample Bottles — Meticulously cleaned (Sect. 4.2) 1-L or
1-qt amber glass fitted with a Teflon-lined screw cap. (Bottles in
which high purity solvents were received can be used as sample
bottles without additional cleaning if they have been handled
carefully to avoid contamination during and after use of original
contents*)
6.1.2 Soil/Sediment Sample Bottles — Appropriate containers will be
specified when appropriate extraction procedures are determined.
6.2 GLASSWARE
6*2.1 Separatery Funnel — 2-L with Teflon stopcock.
6.2.2 Drying Column — glass column approximately 400 mm long X 19 mm ID
with coarse frit filter disc.
6.2.3 Chromatography Column — glass column approximately 400 mm long
X 19 mm ID with coarse frit filter disc and Teflon stopcock.
6.2.4 Concentrator Tube — 10-mL graduated Kuderna-Danish design
with ground-glass stopper.
6.2.5 Evaporative Flask — 500-mL Kuderna-Danish design that is
attached to concentrator tube with springs.
6.2*6 Snyder Column — three-ball macro Kuderna-Danish design.
6.2.7 Vials — 10- to 15-mL amber glass with Teflon-lined screw caps.
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6.3 COMPUTERIZED GC/MS SYSTEM
6.3.1 The GC must be capable of temperature programming and be equipped
with all required accessories, such as syringes, gases, and a capillary
column. The GC injection port must be designed for capillary columns.
Manual splitless injections were used to acquire data used as the basis
for quality control requirements. An automatic injector, however, is
desirable, because it should provide more precise retention times and
areas. On-column injection with an uncoated precolumn is encouraged,
because high mass descrimination and analyte degradation problems
are minimized with this technique. With some GCs, however, the
irreproducibility of the low initial column temperature required for
on-column injections will cause irreproducible retention times (RTs)
and relative retention times (RRTs). That can result in an inability
to distinguish between two closely-eluting pesticide isomers and may
cause ion sets to be changed at inappropriate times during SIM data
acquistion. Splitting injections are not recommended.
6.3.2 Either full range or SIM mass spectral data are obtained with electron
ionization at a nominal electron energy of 70 eV. To ensure sufficient
precision of mass spectral data, the required MS scan rate must
allow acquisition of at least five full-range mass spectra or five
data points for each monitored ion while a sample component elutes
from the GC. The MS must produce a mass spectrum meeting all criteria
for <20 ng of decafluorotriphenylphosphine (DFTPP) introduced through
the GC inlet.
6.3.3 An interfaced data system (DS) is required to acquire, store, reduce,
and output mass spectral data. The OS must be capable of searching
a data file for specific ions and plotting ion abundances versus time
or spectrum number to produce selected ion current profiles (SICPs)
and extracted ion current profiles (EICPs). Also required is the
capability to obtain chromatographic peak areas between specified
times or spectrum numbers in SICPs or EICPs. Total data acquisition
time per cycle should be >Q.S a and must not exceed 1.5 s«
6.3.4 SIM Option — For SIM data acquisition, the DS must be equipped with
software capable of acquiring data for multiple groups of ions,
and the DS must allow automated and rapid changes of the set of ions
being monitored. To acquire all PCB data needed for implementation
of two currently-available automated interpretation procedures, the
SIM program moat be capable of acquiring data for four groups (or
mass ranges) each consisting of £35 ions or for five groups of £20
ions each. The times spent monitoring ions during sample analyses
oast be the sane as the times used when calibration solutions were
analyzed*
6.4 GC COLUMN — A 30 m X 0.32 am ID fused silica capillary column coated with
a 0.25 urn or thicker film crosslinked phenyl methyl silicons (such as
Durabond-5 (DB-5), J and W Scientific, Rancho Cordova, CA) or polydiphenyl
vinyl dimethyl siloxane (such as SB-54, Alltech Associates, Deerfield, ID
is required. Operating conditions known to produce acceptable results with
these columns are shown in Table 1; separation of pesticide analytes and PCB
calibration congeners with a DB-5 column and those operating conditions is
shown in Figure 1. Retention times have been reported (6) for all 209 PCB
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congeners with an SE-54 column, which provides the same retention order for
PCBs and essentially the same separation capabilities as a DB-5 column.
6.5 MISCELLANEOUS EQUIPMENT
6.5.1 Volumetric flasks - 2-mL, 5-mL, 10-mL, 25-mL, and 50-mL with
ground glass stoppers.
6.5.2 Microsyringes - various standard sizes.
6.5.3 Boiling Chips — approximately 10/40 mesh. Heat at 400»C for
30 min or extract with methylene chloride in a Soxhlet apparatus.
6.5.4 Water Bath — heated, with concentric ring cover, capable of tempera-
ture control within * 2°C.
6.5.5 Analytical Balance — capable of accurately weighing to 0.0001 g.
7. REAGENTS AND CONSUMABLE MATERIALS
7.1 SOLVENTS — High purity, distilled-in-glass hexane and methylene chloride.
For precise injections with splitless injectors and capillary columns, all
samples and standards should be contained in the same solvent. Effects of
minor variations in solvent composition (i.e., small percentage of another
solvent remaining in hexane extracts) are minimized with the use of internal
standards. (External standard calibration is not acceptable.)
7.2 SODIUM SULFATE — ACS, granular, anhydrous. Purify by heating at 400°C
for 4 h in a shallow tray.
7.3 SODIUM THIOSULFATE — ACS, granular.
7.4 TETRABUTYLAMMONIUM SULFITE REAGENT —• Dissove 3.39 g of tetrabutyl-
ammonium hydrogen sulfate in 100 mL distilled water. To remove impurities
extract solution three times with 20-mL portions of hexane. Discard the
hexane extracts, and add 25 g sodium sulfite to the water solution. Store
the resulting solution in an amber bottle with a Teflon-lined screw cap.
The solution can be stored at room temperature for at least one month.
7.5. MS PERFORMANCE CHECK SOLUTION — Prepare a 10 ng/uL solution of decafluoro-
triphenylphoaphine (DFTPP) in an appropriate solvent.
7.6 INTERNAL STANDARDS — Chrysene-d^ *nd phenanthrene-d-jg are used as internal
standards. They are added to each sample extract just before analysis and are
contained in all calibration/performance check solutions.
7.7 SURROGATE COMPOUNDS — 13C12-4^'-DDT and 13C6-ganma-BHC are added to every
sample before extraction and are included in every calibration/performance
check solution.
7.8 PCS CONCENTRATION CALIBRATION CONGENERS — The nine individual PCS congeners
listed in Table 2 are used as concentration calibration compounds for PCS
determinations. One isomer at each level of chlorination is used as the
concentration calibration standard for all other isomers at that level of
chlorination, except that decachlorobiphenyl (C110) is used for both C19
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and Cl-jQ isomer groups. The basis for selection of these calibration
congeners has been reported (7).
7.9 PCB RETENTION TIME CONGENERS FOR SIM DATA ACQUISITION OPTION ~ Knowledge
of the retention tines of certain congeners is necessary to determine
when to acquire data with each ion set. Two concentration calibration
congeners also serve as retention time congeners; the first eluting
Cl-j-PCB indicates the time when data acquisition must have been initiated
for ion set #1, and the C110-PCB indicates when all PCBs have eluted.
Two or three additional PCB congeners are used to establish times to
initiate data acquisition with other ion sets (Sect. 9.4).
7.10 PESTICIDE SOLUTIONS
7.10.1 Pesticide Stock Solutions — Prepare from pure standard materials.
Weigh approximately 25.0 mg (with accuracy of 0.1 mg) of each
surrogate compound and each pure pesticide analyte, except
Endosulfan I and Endosulfan II. For those two pesticides/ prepare
a stock solution twice as concentrated as that prepared for other
pesticide analytas. Dissolve each compound in hexane and dilute to
volume in a 10-mL (5-mL for the two Endosulfans) volumetric flask.
(Concentration of each component • 2.5 mg/mL, except Endosulfans,
which should be 5 mg/mL.} Smaller or larger volumes of stock solution
may be used if desired. If compound purity is certified at £96%,
the weight can be used without correction to calculate the concen-
tration of the stock standard solution. Commercially prepared
stock standards in hexane can be used at any concentration if they
are traceable to USEPA-supplied standards.
7.10.2 Pesticide Primary Dilution Solutions — A convenient approach to
solution preparation is to prepare two pesticide primary dilution
solutions that are twice the concentration of th* highest concentration
calibration solution required. These solutions can then be diluted
as necessary to prepare all needed calibration solutions. One solution
contains endrin aldehyde and one does not, because the medium level
calibration solution does not contain endrin aldehyde. Place 1 mL
of each pesticide analyte/surrogate compound stock solution in a
25-mL volumetric flask. (Total volume for all 22 pesticide analytes
and 2 surrogate compounds » 24 mL.) Make to volume with hexane and
mix well. (Concentration of endosulfan sufate, endosulfan I and
endosulfan II -200 ng/uL; concentration of each other component -
100 ng/uL.)
7.11 PCB SOLUTIONS
7.11.1 Stock Solutions of PCB Calibration Congeners — Prepare a stock
solution of each of the nine PCB concentration calibration congeners
at a concentration of 1 ug/uL in hexane. (If SIM data are to be
acquired, prepare a 1 ug/uL stock solution of each of the three
retention time congeners also.) Place each solution in a clean
glass vial with a Teflon-lined screw cap and store at 4*C if solutions
are not to be used right away. Solutions are stable indefinitely
if solvent evaporation is prevented.
CAUTION: Each time a vial containing small volumes of solutions is
warmed to room temperature and opened, a small volume of solvent in
the vial headspace evaporates, significantly affecting concentration.
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Solutions should be stored with the smallest possible volume of
headspace, and opening vials should be minimized.
7.11.2 PCB Primary Dilution Standard — Take aliquots -of the stock
solutions of the nine PCB concentration calibration congeners and
mix together in the proportions of one part of each solution of the
Cl<| (f1), C12 (#5), and C13 (#29) congeners, two parts of each solution
of the C14 (#50), C15 (#87), and C16 (#154) congeners, three parts
of each solution of the 017 (#188) and Clg (#200) congeners, and five
parts of the C110 (#209) congener solution. (Note: The retention
time congeners described in Sect. 7.9 are not included in the PCB
primary dilution standard because they are not needed for full-range
data acquisition.) This will provide a primary dilution standard
solution of the composition shown in Table 3. Calculate the concen-
tration in ug/uL; use three significant figures. Place each solution
in a clean glass vial with a Teflon-lined screw cap and store at
4°C. Mark the meniscus on the vial wall to monitor solution volume
during storage; solutions are stable indefinitely if solvent evapo-
ration is prevented.
7.12 INTERNAL STANDARD (IS) SOLUTIONS — Two solutions are needed to prepare
concentration calibration solutions (CALs).
7.12.1 IS solution #1 (for full-range CALS) — Weigh 7.5 mg + 0.1 mg
each of phenanthrene-d10 and chrysene-d^; dissolve in hexane and
dilute to 10 mL in a volumetric flask. (Concentration of each
IS'- 750 ng/uL)
7.12.2 IS solution #2 (for SIM CALS) — Take 1 mL of IS solution #1 and
dilute to 10 mL in a volumetric flask. (Concentration of each
IS - 75 ng/uL)
7.13 CALS FOR FULL-RANGE DATA ACQUISITION — Five hexane solutions are required.
The solutions contain constant concentrations of the ISs (chrysene-d12
and phenanthrene-d^) and varying concentrations of individual pesticide
analytes, the nine PCB calibration compounds, and the two surrogate compounds
( C12~4»4'-DDT and Cg-gamma-BHC)* (Composition and approximate concen-
trations are given in Table 4.) Four solutions (high and low concentrations)
contain both ISs, both surrogate compounds, the nine PCB concentration
calibration congeners, and each of the single-compound pesticide analytes.
The fifth solution, the medium level concentration solution, contains all
the above compounds except endrin aldehyde, which is not present for reasons
described in Sect* 8. The lowest concentration solution contains each
individual pesticide analyte and each PCB calibration congener at a concen-
tration near but greater than its anticipated detection limit. (Because
MS response to PCBs decreases with increasing level of chlorinatlon, PCB
congener concentrations in CALs increase with level of ehlorination.)
Components of the highest concentration solution (High CAL) are present at
a concentration that allow injections of 2-uL aliquots without MS saturation
or GC column overloading.
7.13.1 The Full-Range High CAL can be prepared by mixing equal portions
of the PCB primary dilution solution and the pesticide primary
dilution solution that contains endrin aldehyde and then adding an
appropriate volume of IS solution #1. For example, 1 mL of each
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prinary dilution solution and 20 uL of IS solution #1 provide the
appropriate concentration for High CAL.
7.13.2 Other full-range GALS are prepared by diluting the primary dilution
standard solutions and adding the appropriate amount of IS solution
f1. CAUTION: The pesticide primary dilution standard that does
not contain endrin aldehyde must be used for the medium level
full-range CAL.
7.14 CALS FOR SIM DATA ACQUISITION OPTION — Two sets of solutions are needed,
one set of five solutions for determinations of pesticide analytes, and
one set of five solutions for PCS determinations. Appropriate concen-
trations of SIM CALs are given in Tables 5a and 5b. Solutions are
prepared by diluting appropriate primary dilution standards and adding
an appropriate volume of IS solution #2.
CAUTION: The Pesticide SIM Medium CAL does not contain endrin aldehyde;
the PCS SIM CALS must include the three PCS retention time congeners.
that are used to establish conditions for SIM data acquisition.
7.15 Prepare a solution of surrogate compounds in a water miscible solvent
to provide a concentration in the sample/blank extract that is near
the concentration anticipated for analytes when an aliquot of X20 uL is
added to the sample before extraction.
7.15 Calculate the concentration (two significant figures if OOO and three
significant figures if MOO ng/uL) of each component in each solution.
Note: Concentrations presented in tables are only approximate.
7.16 LABORATORY PERFORMANCE CHECK SOLUTION - For both full-range data acquisition,
and the SIM data acquisition option, the Medium CAL is used as the laboratory
performance check solution (LPC) to verify response factors and to demonstrate
adequate GC resolution and MS performance.
8. SAMPLE COLLECTION, PRESERVATION AND STORAGE
8.1 HATER SAMPLES
8.1.1 Samples must be collected in clean (Sect. 4.2) glass containers.
Note: When samples are anticipated to contain low concentrations
of method analytes, a sample larger than 1-L may be needed. An
effective sample collection procedure to minimize losses of hydro-
phobic analytes is to add a portion of extracting solvent to each
•ample container when the sample is collected. When a 1-gal sample
is collected, an appropriate solvent volume is approximately 100 mL.
(The entire sample must be used as one sample aliquot, and blank
sample/solvent volumes must be adjusted also.)
8.1.2 Samples must be iced or refrigerated at 4*C from time of collection
until extraction. If samples will not be extracted within 72 h after
collection, use either sodium hydroxide or sulfuric acid to adjust
sample pH to within a range of 5 to 9. Record the volume of acid
or base used. If aldrin is to be determined, add sodium thiosulfate
when residual chlorine is present. Field test kits are available
for measurement of residual chlorine*
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8.1.3 Samples should be extracted within 7 days after collection and analyzed
within 40 days after extraction.
8.2 SOIL/SEDIMENT SAMPLES — Appropriate procedures will be specified when
results are obtained from ongoing experiments.
9. CALIBRATION
Demonstration and documentation of acceptable initial calibration is required
before any samples are analyzed and is required intermittently throughout
sample analyses as dictated by results of continuing calibration checks.
After initial calibration is successfully performed, a continuing calibration
check is required at the beginning and end of each 12-h period during which
analyses are performed. The Medium CALs for pesticide determinations do not
include endrin aldehyde. This allows the Medium CAL to be used for continuing
calibration checks, including a check to ensure that endrin decomposition is
£10%. During initial calibration a separate Medium CAL containing endrin
aldehyde and the internal standard is analyzed to determine the response factor
for endrin aldehyde. Thereafter, if endrin aldehyde is a component of any
sample and endrin decomposition is not a problem, the response factor for
endrin aldehyde is verified by analyzing a calibration solution containing it.
9.1 DATA ACQUISITION OPTIONS — Either full-range or SIM data acquisition may
be used.
9.1.1 Full-range data acquisition is recommended if sample extract
components are anticipated to be at sufficiently high concentrations.
9.1.2 SIM data acquisition will provide an increase in sensitivity by
at least a factor of five for pesticide determinations and by at
least a factor of three for PCB determinations.
9.2. INITIAL CALIBRATION
9.2.1 Calibrate and tune the MS with standards and procedures prescribed
by the manufacturer with any necessary modifications to meet USEPA
requirements.
9.2.2 Inject a 1- uL or 2-uL aliquot of the 10 ng/uL DFTPP solution and
acquire a mass spectrum that includes data for m/z 45-450. If the
spectrum does not meet all criteria (Table 6), the MS must be
hardware tuned to meet all criteria before proceeding with calibration.
9.2.3 Pull-Range Calibration — Inject a 1- or 2-uL aliquot of the Medium
CAL and acquire data from m/z 45 to 510. Acquire >5 spectra during
elution of each GC peak. Total cycle time should be >0.5 s and £1.5 s.
Note: Either a 1- or 2-uL aliquot should be used consistently for
CALs and sample/blank extracts.
9.2.4 SIM Calibration — Acquire at least five data points for each ion
during elation of each GC peak. Total cycle time should be £0.5 s
and £1*5 s.
CAOTION: When acquiring SIM data, GC operating conditions must be
carefully reproduced for each analysis to provide reproducible
retention times; if not, ions will not be monitored at the appropriate
times.
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9.2.4.1 SIM Calibration for PCB determinations
9.2.4.1.1 TWO options for SIM data acquisition are provided.
Data can be acquired with four sets of £six mass
ranges (<3S ions each as shown in Table~*7a) or
with the five ion sets (£20 ions each) shown in
Tables 7b and 7c. ""
9.2.4.1.2 The time (scan number) for initiation of data acquisition
with each ion set must be carefully determined from
the retention times (scan numbers) of the retention
time congeners. Approximate relative retention times
of calibration congeners and approximate relative
retention time windows for PCB isomer groups are
shown in Table 8. (Also see Figures 1 and 2.)
9.2.4.1.3 SIM data acquisition with four ion sets. Begin data
acquisition with Ion Set #1 before elution of PCB
congener f1, the first elating Cl-j-PCB. Stop
acquisition with Ion Set #1 and begin acquisition
with Ion Set f2 just (approximately 10 s) before
elution of PCB congener #104, the first eluting
C15-PCB. Stop acquisition with Ion Set #2 and begin
acquisition with Ion Set #3 just (approximately 10 s)
after elution of PCB congener #77, the last eluting
C14-PCB. Stop acquisition with Ion Set #3 and begin
acquisition With Ion Set #4 just (approximately 10 s)
after elution of 13C12-4,4'-DDT.
9.2.4.1.4 SIM data acquisition with five ion sets. Acquire
data with the four Ion Sets described in Sect.
9.2.4.1.3 and add a fifth Ion Set beginning data
acquisition with that set just (approximately 10 s)
before elution of PCB congener #208, the first
eluting Clg-PCB.
9.2.4.2 SIM Calibration for Pesticide Determinations — Three sets of
<15 ions each are used (Tables 9-10). Begin data acquisition
with Ion Set #1 before elution of alpha-BHC, the first eluting
pesticide analyte. Begin data acquisition with Ion Set #2 after
elution of aldrin and before elution of heptachlor epoxide.
Stop acquisition with Ion Set #2 and begin acquisition with Ion
Set #3 after elution of endosulfan II and before 4,4'-DDD.
9.2.5 Performance Criteria
9.2.5.1 Pull-Range Data from Analysis of Medium CAL
9.2.5.1.1 GC performance — baseline separation of beta-BHC
and gamma-BBC; baseline separation of endrin ketone
and chrysene-d12; height of C11-PCB peak £80% beta-BHC
peak height; height of chrysene-d12 peak 760% of the
peak height of methoxychlor, which may partially coelute
with the Clg-PCB congener.
9.2.5.1.2 MS sensitivity ~ Signal/noise ratio of X5 for
m/z 499 of PCB congener #209, Cl^g
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9.2.5.1.3 MS calibration — Abundance of >40% and £60% of
m/z 502 relative to m/z 498 for PCS congener #209.
9.2.5.1.4 Lack of degradation of endrin. Examine an extracted
ion current profile (EICP) for m/z 67 in the retention
time window between 4,4'-DDE and endosulfan sulfate;
confirm that the abundance of m/z 67 at the retention
time of endrin aldehyde is <10% of the abundance of
m/z 67 produced by endrin.
9.2.5.1.5 Lack of degradation of 13C12-4,4'-DDT. Examine EICPs
for m/z 258 and m/z 247 in the retention time window
that includes 4,4'-DDD/ 4,4'-DDE and 4,4'-DDT; m/z
258 would be produced by 13C12-4,4'DDE, and m/z 247 by
1 C12-4,4'-DDD. Confirm that the total abundance of
both ions is <5% of m/z 247 produced by 13C12-4,4'-DDT.
9.2.5.2 SIM PCB Data
9.2.5.2.1 GC separation — Baseline separation of PCB congener
#87 from congeners #154 and #77, which may coelute.
9.2.5.2.2 MS sensitivity — Signal/noise ratio of >5 for m/z
499 of PCB congener #209, C110-PCB, and for m/z 241
of chrysene-d-j*2.
9.2.5.2.3 MS calibration — Abundance of >70% and <95% of m/z
500 relative to m/z 498 for congener #209, C110-PCB.
9.2.5.3 SIM Pesticide Data
9.2.5.3.1 GC separation — Baseline separation of endrin
fcetone and chrysene-d12' baseline separation of
beta-BBC and gamma-BBC; baseline separation of endrin
ketone and chrysene-d-j2; height of chrysene-d12 peak
260% of methoxychlor peak height.
9.2.5.3.2 MS sensitivity — Signal/noise ratio of >5 for m/z
241 of chrysene-d<]2.
9.2.5.3.3 MS calibration — Abundance of m/z 241 relative
to that of m/z 240 produced by chrysene-d-j 2 is >15%
and <25%.
9.2.5.3.4 Lack of degradation of endrin. Examine an SICP for
m/z 67 in the retention time window between 4,4'-DDE
and endosulfan sulfate; confirm that the abundance
of m/z 67 at the retention time of endrin aldehyde
is <10% that of m/z 67 produced by endrin.
9.2.5.3.5 Lack of degradation of 13C12-4,4'-DDT. Examine SICPs
for m/z 258 and m/z 247 in the retention time window
that includes 4,4'-ODD, 4.4'-DDE, and 4,4'-DDT; m/z
258 would be produced by C12-4,4'-DDE, and m/z 247
by 13C12-4,4'-DDD. Confirm that the total abundance
of both ions is <5% of m/z 247 produced by 13C15-4,4'-DDT.
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9.2.6 Replicate Analyses of CALs — If all performance criteria are met,
analyze one 1- or 2-uL aliquot of each of the other four CALs.
9.2.7 Response Factor Calculation
9.2.7.1 Calculate five response factors (RFs) for each pesticide
analyte, PCB calibration congener/ and surrogate compound
relative to both ISs (See Sect. 12.3.2), phenanthrene-d10 and
chrysene-d -) 2 :
RF - AX Qi /
where Ax = integrated ion abundance of quantitation
ion for a pesticide, a PCB calibration
congener or a surrogate compound,
A^g » integrated ion abundance of m/z 240, the
quantitation ion when chrysene-d^ is used
as the internal standard or m/z 188, the
quantitation ion when phenanthrene-d10
is used as the internal standard,
Q^g * injected quantity of chrysene-d12 or
phenanthr ene-d-j g ,
Qx * injected quantity of pesticide analyte, PCB
calibration congener or surrogate compound.
RF is a unitless number, units used to express quantities
must be equivalent. Mote: The C12-PCB calibration congener
may not be resolved from alpha-BHC. If not, alpha-BHC will
contribute to the ion abundance measured for Cl2~PCB. To
correct for this contribution, subtract 6.7% of the ion
abundance of m/z 219 measured for alpha-BHC from the ion
abundance measured for m/z 222 for C
9.2.8 Response Factor Reproducibility — For each pesticide analyte, PCB
calibration congener and surrogate compound, calculate the mean RF
from analyses of each of the five CALS. When the RSD exceeds 20%,
analyze additional aliquots of appropriate CALS to obtain an acceptable
RSD of RFs over the entire concentration range, or take action to
improve GC/MS performance.
9.2.9 SIM Analyte Retention Time Reproducibility
9.2.9.1 PCB determinations - Absolute retention times of PCB congeners
#77 and #104 should not vary by more than +10 s from one
analysis to the next. (Retention »<"• reproducibility is
not as critical for congeners #1 and #209 as for #77 and
#104, which are used to determine when ion sets are changed.)
9.2.9.2 Pesticide determinations — Absolute retention times of
gamma-chlordane, endosulfan I, and endosulfan II should not
vary by more than +10 s from one analysis to the next.
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9.2.10 Record a spectrum of each CAL component.
9.3. CONTINUING CALIBRATION CHECK
9.3.1 With the following procedures, verify initial calibration at the
beginning and end of each 12-h period during which analyses are to
be performed.
9.3.2 Calibrate and tune the MS with standards and procedures prescribed
by the manufacturer.
9.3.3 Analyze a 1-uL or 2-uL aliquot of the DFTPP solution and ensure
acceptable MS calibration and performance (Table 6).
9.3.4 Inject a 1-uL or 2-uL aliquot of the Medium CAL and analyze with the
same conditions used during Initial Calibration.
9.3.5 Demonstrate acceptable performance for criteria described in Sect.
9.2.5.
9.3.6 Determine that neither the area measured for m/z 240 for chrysene-d-^
nor that for m/z 188 for. phenanthrene-dfQ has decreased by more than 30%
from the area measured in the most recent previous analysis of a
calibration solution or by more than 50% from the mean area measured
during initial calibration.
9.3.7 Response Factor Reproducibility,— For an acceptable Continuing Cali-
bration Check, the measured RF for each analyte/surrogate compound
must be within +20% of the mean value calculated (Sect. 9.2.7)
during Initial Calibration. If not, remedial action must be taken;
recalibration may be necessary.
9.3.8 SIM Analyte Retention Time Reproducibility — Demonstrate and
document acceptable (Sect. 9.2.9) reproducibility of absolute retention
times of appropriate pesticide analytes and PCS retention time congeners.
9.3.9 Remedial actions must be taken if criteria are not met; possible
remedies are:
9.3.9.1 Check and adjust GC and/or MS operating conditions.
9.3.9.2 Clean or replace injector liner.
9.3.9.3 Flush column with solvent according to manufacturers
instructions.
9.3.9.4 Break off a short portion (approximately 0.33 m) of the
column; check column performance by analysis of performance
check solution.
9.3.9.5 Replace GC column; performance of all initial calibration
procedures then required.
9.3.9.6 Adjust MS for greater or lesser resolution.
9.3.9.7 Calibrate MS mass scale.
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9.3.9.8 Prepare and analyze new concentration calibration/
performance check solution.
9.3.9.9 Prepare new concentration calibration curve(s).
10. QUALITY CONTROL
10.1 LABORATORY REAGENT BLANK (LRB) — Perform all steps in the analytical
procedure (Section 11) using all reagents, standards, surrogate compounds,
equipment, apparatus, glassware, and solvents that would be used for a
sample analysis? but omit an aliquot of sample (water or soil/sediment).
For water samples, substitute 1 L of reagent water. If available,
substitute EPA-provided reagent blank solid material for an aliquot of
soil/sediment.
10.1.1 An LRB must contain the same amount of surrogate compounds and
internal standards that is added to each sample. This amount
will vary with sample type and with the type of data acquisition
(full-range or SIM).
10.1.2 Analyze an LRB before any samples are extracted and analyzed.
10.1.3 Before a new batch of solvents or reagents is used for sample
extraction or for column chromatographic procedures, analyze
an LRB. In addition, analyze a laboratory solvent blank (LSB),
which is the same as an LRB except that no surrogate compounds or
internal standards are added; this demonstrates that reagents
contain no impurities producing an ion current above the level of
background noise for quantitation ions for those compounds.
10.1.4 Analyze an LRB along with each batch of £20 samples.
10.1.5 An acceptable LRB contains no method analyte at a concentration
greater than one half of its HDL and contains no additional compounds
with elution characteristics and mass spectral features that would
interfere with identification and measurement of a method analyte
at its NDL. If the LRB that was extracted along with a batch of
samples is contaminated, the entire batch of samples must be
reextracted and reanalyzed.
10.1.6 Corrective action for unacceptable LRB — Check solvents, reagents,
apparatus and glassware to locate and eliminate the source of
contamination before any samples are extracted and analyzed.
Purify or discard contaminated reagents and solvents.
10.2 CALIBRATION — Included among initial and continuing calibration procedures
are numerous quality control checks to ensure that valid data are acquired
(See Sect. 9). Continuing calibration checks are accomplished with results
from analysis of one solution, the medium level calibration solution for
the appropriate type of data acquisition, either full-range or SIM.
10.2.1 If some criteria are not met for a Continuing Calibration Check
after a 12-h period during which samples were analyzed, those
samples must be reanalyzed. Those criteria are: GC performance
(Sect. 9.2.5), MS calibration as indicated by DFTPP spectrum, and
MS sensitivity as indicated by area of internal standards.
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-17-
10.2.2 When other criteria in Sect. 9.2 are not met, results for affected
analytes must be labeled as suspect to alert the data user of the
observed problem. Included among those criteria are: response
factor check for each analyte or PCB calibration congener/ degra-
dation of DDT and endrin, and retention time reproducibility for
SIM data acquisition.
10.3 INITIAL DEMONSTRATION OF LABORATORY CAPABILITY FOR HATER ANALYSES
(Insufficient information is currently available for demonstration for
soil/ sediment analyses.)
10.3.1 Until appropriate Quality Control Check Samples are available/
each laboratory should prepare one or more solutions containing
each method analyte at a concentration corresponding to that antici-
pated in samples. Until accuracy and precision limits have been
established for PCB isomer groups in appropriate samples, a solution
containing an Aroclor mixture may be used; compare total measured
PCB concentration to the total Aroclor concentration. Report
Aroclor concentration and measured concentrations of PCB isomer
groups and total measured PCB concentration.
10.3.2 Add an appropriate volume of a solution of method analytes
to each of four 1-L aliquots of reagent water. Extract and
analyze according to procedures in Sect. 11.
10.3.2 For each analyte, calculate measured concentrations, relative
standard deviation of" the four measurements, and method bias
(Sect. 12.6).
10.4 LABORATORY PERFORMANCE CHECK SOLUTION — In this method, the medium level
concentration calibration solution also serves the purpose of a laboratory
performance check solution.
10.5 LABORATORY SURROGATE SPIKE
10.5.1 Measure the concentration of both surrogate compounds in
every sample and blank.
10.5.2 Urtil performance based acceptance limits have been established for
surrogate compounds, the following guidelines are provided:
measured bias with LRB - -30% to +10%; measured bias with
water or soil/sediment extract =» -50% to +25%.
10.6 QUALITY CONTROL CHECK SAMPLE — Not yet available; anticipate need for
analysis of one for each batch of £20 samples. If full-range data are
acquired, both pesticide and PCB analytes can be determined with one
analysis. If SIM data are acquired, one extraction and two GC/MS analyses
will be needed to determine both PCBs and pesticides.
10.7 LABORATORY SPIKZD DUPLICATE SAMPLE — Select one sample from each batch of
<20 samples of similar type and fortify (spike) two aliquots of that sample
with a solution containing appropriate concentrations of pesticide analytes
and at least one Aroclor mixture. After addition of surrogate compounds,
extract and analyze (Sect. 11) these two fortified aliquots along with
an additional unfortified sample aliquot. Relative difference (RD) of
duplicate results for surrogate compound concentrations should be <40%.
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-18-
(RD - [C, - C2 / 0.5 (C., + C2)l 100 ) Calculate bias (Sect. 12.6) for
each analyte and surrogate compound. Insufficient data are currently
available to provide guidance for acceptable bias and RD of measured
analyte concentrations.
10.8 PERFORMANCE EVALUATION SAMPLE — Not yet available; to be analyzed
periodically when available.
11. PROCEDURES
11.1 SAMPLE EXTRACTION
11.1.1 Water Samples
11.1.1.1 Mark the water meniscus on the side of the sample bottle
for later determination of sample volume. Pour entire
sample into a 2-L separatery funnel. (If a sample larger
than 1-L or 1-qt is extracted, the funnel size and solvent
volume for samples and blanks must be adjusted also.)
11.1.1.2 Add an appropriate volume of surrogate compound solution.
11.1.1.2 Add 60 mL of methylene chloride to the sample bottle,
seal, and shake 30 s to rinse the inner surface. Transfer
the solvent to the separatory funnel and extract the
sample by shaking the funnel for 2 min with periodic
venting to release excess pressure. Wait at least 10 min
to allow the organic layer to separate from the water
phase. If the emulsion interface between layers is more
than one-third the volume of the solvent layer, use
mechanical techniques (such as stirring, filtration
of emulsion through glass wool, or centrifugation) to
complete phase separation. Collect the methylene chloride
extract in a 250-mL Erlenmeyer flask. Add a second 60-mL
volume of methylene chloride to the sample bottle and
repeat the extraction procedure a second time, combining
the extracts in the Erlenmeyer flask. Perform a third
extraction in the same manner.
11.1.1.3 Assemble a Kurderna-Danish (K-D) concentrator by attaching
a 10-mL concentrator tube to a 500-mL evaporative flask.
11.1.1.4 Pour the combined extract into a solvent-rinsed drying
column containing about 10 cm of anhydrous sodium sulfate.
Rinse the Erlenmeyer flask with a 20 to 30 mL portion of
methylene chloride, and add the rinse to the drying column.
Collect the combined extract in the K-D concentrator.
11.1.1.5 Add one or two clean boiling chips to the evaporative
flask and attach a three-ball Snyder column. Prewet
the Snyder column by adding about 1 mL of methylene
chloride to the top. Place the K-D apparatus on a hot
water bath (60-65*C) so that the concentrator tube is
partially immersed in the hot water, and the entire
lower rounded surface of the flask is bathed with hot
vapor. Adjust the vertical position of the apparatus
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and the water temperature as required to complete the
concentration In 15-20 min. At the proper rate of
distillation the balls of the column will actively chatter
but the chambers will not flood with condensed solvent.
When the apparent volume of liquid reaches 1 mL, remove
the K-D apparatus from the water bath and allow it to
drain and cool for at least 10 min.
11.1.1.6 Momentarily remove the Snyder column, add 50 mL of hexane
and a new boiling chip, and reattach the Snyder column.
Increase the temperature of the hot water bath to about
80 *C. Concentrate the extract to approximately 10 mL
as in Sect. 11.1.1.5, except use hexane to prewet the
column. Elapsed time of concentration should be 5-10
min.
11.1.1.7 Remove the Snyder column and rinse the flask and its
lower joint into the concentrator tube with 1-2 mL of
hexane. A 5-mL syringe is recommended for this operation.
Stopper the concentrator tube and store refrigerated if
further processing will not be performed within a few
hours* If the extract will be stored longer than two
days/ transfer it to a Teflon-sealed screw-cap vial.
11.1.1.8 Determine the original sample volume by refilling the
sample bottle to the mark and transferring the liquid
to a 1000-mL graduated cylinder. Record the sample
volume to the nearest 5 mL.
11.1.2 Soil/Sediment Samples — Appropriate extraction procedures to be
specified when results of ongoing experiments are obtained.
11.2 Sulfur Removal — Elemental sulfur can be removed by the procedure described
below. (Sulfur is not expected to be a problem in water sample extracts but
sulfur removal is recommended for soil/sediment sample extracts.)
11*2.1 Transfer the extract to a 50-mL clear glass bottle or vial with a
Teflon-lined screw cap. Rinse the extract container wtih 1*0 mL of
hexane, adding the rinse to the 50-mL bottle*
11.2.2 Add 1 mL of Tetrabutylammonium-sulfite reagent and 1 mL 2-propanol,
cap the bottle, and shake for at least 1 min. If the sample is
colorless or if the initial color is unchanged, and if clear crystals
(precipitated sodium sulfite) are observed, sufficient sodium
sulfite is present. If the precipitated sodium sulfite disappears,
add more crystalline sodium sulfite in approximately 100-mg portions
until a solid residue remains after repeated shaking.
11.2.3 Add 5 mL of distilled water and shake for at least 1 min. Allow
the sample to stand for 5-10 min and remove the hexane layer (top)
for analysis. Dry the extract by passing it through a 10-cm
column containing hexane-washed sodium sulfate. Rinse the sodium
sulfate with about 30 mL of hexane and add this hexane to the
extract. Concentrate the extract to approximately 10 mL with a
K-D apparatus. Store in a refrigerator if GC/NS analysis is not to
be performed within a few hours.
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11.3 GC/MS ANALYSIS
11.3.1 Remove the sample extract or blank from storage and allow it to warm
to ambient laboratory temperature if necessary. With a stream of
dry, filtered nitrogen, reduce the extract/blank volume to the
appropriate volume, depending on anticipated analyte concentrations.
Add an appropriate volume of the appropriate internal standard stock
solution.
11.3.1.1 Internal standard concentration for full-range
data acquisition - 7.5 ng/uL of extract.
11.3.1.2 Internal standard concentration for SIM data
acquisition - 0.75 ng/uL of extract.
11.3.2 Inject a 1-uL or 2-uL aliquot of the blank/sample extract into the GC
operated under conditions used to produce acceptable results during
calibration.
11.3.3 Acquire mass spectral data with either full-range data acquisition
conditions or SIM conditions, as appropriate. Use the same data
acquisition tinfi and MS operating conditions previously used to
determine response factors.
11.3.4 Examine data for saturated ions in mass spectra of target compounds,
if saturation -occurred, dilute and reanalyze the extract after the
quantity of the internal standards is adjusted appropriately.
11.3.5 For each internal standard, determine that the area measured in the
sample extract has not decreased by >30% from the area measured
during the most recent previous analysis of a calibration solution
or by >50% from the mean area measured during initial calibration.
If either criterion is not met, remedial action must be taken to
improve sensitivity, and the sample extract must be reanalyzed.
11.4 IDENTIFICATION PROCEDURES
11.4.1 Using the ions shown in Tables 7a-7c for PCBs or Table 9 for
pesticides, examine ion current profiles (ICPs) to locate internal
standards, surrogate compounds, pesticide analytes, and PCBs for each
isomer group. Use the RKT data in Table 9 as guidelines for location
of pesticide analytes and the RRT window data in Table 8 as guidelines
for location of PCS isomers. (A reverse search software routine
can be used to locate compounds of concern.)
11.4.2 Full-Range Data
11.4.2.1 Examine each pesticide and PCS candidate spectrum after
background correction routines have been applied. Compare
the candidate spectrum with the appropriate standard spectrum
measured during calibration. Verify the absence of any ions
with mass greater than the highest mass possible for the
compound of concern. (Ions in PCS M* ion clusters are shown
in Table 12.)
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-21-
11.4.2.2 Obtain integrated abundance areas for quantitation and
confirmation ions.
11.4.3 SIM Data — Obtain appropriate selected ion current profiles (SICPs)
for IS quantitation and confirmation ions/ for each ion monitored
to detect pesticides and the surrogate compounds (Table 9), and for
the quantitation and confirmation ions for each PCS isomer group.
11.4.4 PCB Analytes
11.4.4.1 For all PCB candidates, confirm the presence of an (M-70)+
ion cluster by examining ICPs or spectra for at least one of
the most intense ions in the appropriate ion cluster.
11.4.4.2 For Clj-Cly isomer groups, examine ICPs or spectra for intense
(M+70)* ions that would indicate a coeluting PCB containing two
additional chlorines. (GC retention time data show that
this is not a potential problem for other PCB isomer groups;
see Figure 2.) If this interference occurs, a correction can
be made. Obtain and record the area for the appropriate ion
(Table 12) for the candidate PCB isomer group. Use the
information in Table 13 to correct the measured abundance of
M*. For example, if a C17-PCB and a Clg-PCB candidate coelute,
the C17-PCB will contribute to the ion measured for m/z 326 and
m/z 324, the quantitation and confirmation ions, respectively,
for a C15-PCB. Obtain and record the area for m/z 322 (the
lowest mass ion in the (M+-70)* ion cluster of a Clg-PCB
fragment produced by a C17-PCB). To determine the m/z 326 and
m/z 324 areas produced by the Cls PCB, calculate the CIj-PCB
contribution to each and subtract it from the measured area.
In this example, 164% of the area measured for m/z 322 should
be subtracted from the area measured for m/z 324, and 108% of
the m/z 322 area should be subtracted from the area measured
for m/z 326 (Table 13).
11.4.4.3 For Cl2~Clg-PCB candidates, examine ICPs or spectra for
intense (M+35)"*" ions that would indicate a coeluting PCB
containing one additional chlorine. This coelution causes
interferences because of the natural abundance of 1^C.
(This interference will be small and can be neglected except
when measuring the area of a small amount of a PCB coeluting
with a large amount of another PCB containing one more
chlorine.) To correct for this interference/ obtain and
record the area for the appropriate ion (Table 14) from
the (M-1)"1" ion cluster/ and subtract 13.5% of the area
measured for the (M-1)* ion from the measured area of the
quantitation ion. For example, for Cls-PCB candidates/
obtain and record the area for m/z 325; subtract 13.5% of
that area from the measured area of m/z 326.
11.4.5 All Analytes — Use ICP data to calculate the ratio of the measured
peak areas of the quantitation ion and confirmation ion(s), and
compare to the acceptable ratio (Table 9 for pesticides and Table 12
for PCBs). If acceptable ratios are not obtained/ a coeluting or
partially coeluting compound may be interfering. Examination of data
from several scans may provide information that will allow application
of additional background corrections to improve the ion ratio.
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-22-
11.5. IDENTIFICATION CRITERIA
11.5.1 Internal Standards
11.5.1.1 Chrysene-d12 — the abundance of m/z 241 relative to m/z
240 oust be £.15% and £25%, and these ions must maximize
simultaneously. The area measured for m/z 240 must be
within 30% of the area measured during the most recent
calibration.
11.5.1.2 Phenanthrene-d-i 0 — the abundance of m/z 189 relative to m/z
188 must be £10% and <22%, and these ions must maximize
simultaneously. The area measured for m/z 188 must be
within 30% of the area measured during the most recent
acceptable calibration.
11.5.1.3 Retention time must be within ±10 s of that observed
during the most recent acceptable calibration.
11.5.2 Pull-Range Data for Pesticide Analytes and Surrogate Compounds
11.5.2.1 Retention time of the sample component must be within Jt s
of the time observed for that same compound when a calibration
solution was analyzed. Calculate the value of £ with the
equation, t * (RT)V^/ where RT » observed retention time
(in seconds) of the compound during the last previous acceptable
calibration.
11.5.2.2 All ions with relative abundance >10% in the mass spectrum
must be present in the mass spectrum of the candidate sample
component; a molecular ion with relative abundance >2% in
the standard spectrum must be present in the candidate
spectrum.
11.5.2.3 The ion that was the most abundant (base peak) in the standard
spectrum must also be the base peak in the candidate spectrum.
11.5.2.4 For all ions with relative abundance >20% in the standard
spectrum, the relative abundance in the candidate spectrum
must not vary by more than ±15% in percentage units (i.e.,
if 50% in standard, must be~>35% and £65%).
11.5.2.5 Ions with relative abundance >10% in the candidate spectrum
but not present in the standard spectrum must be considered
and accounted for by the analyst. When data processing
software is used to obtain candidate spectra, both processed
and unprocessed spectra must be evaluated.
11.5.3 SIM Data for Pesticide Analytes and Surrogate Compounds
11.5.3.1 Absolute retention time of each surrogate compound and
pesticide candidate must be within 10 s of that measured
during the last previous acceptable calibration.
11.5.3.2 All ions monitored for each compound (Table 9) must be
present and must maximize simultaneously.
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-23-
11.5.3.3 In a spectrum averaged across a GC peak and with background
correction, if necessary, the most abundant ion must correlate
with Table 9 data.
11.5.3.4 Observed relative abundances of the monitored ions must
meet the following criteria:
Aldrin — m/z 263 - >20% and m/z 265 = >13%
BHC (each isomer) — m/z 183 - 70-95% of m/z 181
13C6-gamma-BHC -- m/z 189 - 75-90% of m/z 187
Chlordane (alpha and gamma) — m/z 375 = 75-99%
4,4'-DDE -- m/z 248 « 45-85%
4.4'-ODD and 4,4'-DDT — m/z 237 =« 45-85%
13C12-4,4'-DDT — m/z 249 = 45-85%
Dieldrin — m/z 263 = >3% and m/z 108 = >8%
Endosulfan I and II — m/z 339 = >30% and m/z 341 = >20%
Endosulfan sulfate — m/z 274 = 60-95%
Endrin — m/z 263 =» _>50%
'Endrin aldehyde — m/z 345 = £10%
Endrin ketone — m/z 317 - £30%
Heptachlor — m/z 272 * >3oT and m/z 274 =» >20%
Heptachlor epoxide — m/z 353 » >60%
Methoxycnlor — m/z 228 » 3-30%
Nonachlor — m/z 407 = 65-95%
11.5.4 Full-Range and SIM Data for PCBs
11.5.4.1 Absolute retention times of surrogate compounds must be
within ±10 s of that measured during the last previous
continuing calibration check.
11.5.4.2 Quantitation and confirmation ions for each PCB isomer group
must maximize within ±1 scan of each other.
11.5.4.3 The integrated ion current for each quantitation and confir-
mation ion must be at least three times background noise and
must not have saturated the detector.
11.5.4.4 For each PCB isomer group candidate, the ratio of the quanti-
tation ion area to the confirmation ion area must be within
limits shown in Table 12; at least one ion in the (M-70)+
ion cluster must be present.
12. CALCULATIONS
12.1 From appropriate ICPs of quantitation ions, obtain and record the spectrum
number of the chromatographic peak apex and the area of the entire
chromatographic peak.
12.2 For PCBs, sum the areas for all isomers identified at each level of
chlorination (e.g., sum all quantitation ion areas for C^-PCBs).
12.3 Calculate the concentration of each surrogate compound, pesticide
candidate, and PCB isomer group using the formula;
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cx - (Ax * Qi»>/
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-25-
12.5 Report calculated values to two significant figures.
12.6 When samples of known composition or fortified samples are analyzed,
calculate the percent method bias using the equation:
B » 100 (Cs - Ct)/ Ct
where Cs « measured concentration (in micrograms per kilogram
or micrograms per liter),
Cfc » theoretical concentration (i.e., the
quantity added to the sample aliquot/weight or volume
of sample aliquot).
Mote: The bias value retains a positive or negative sign.
13. AUTOMATED IDENTIFICATION AND MEASUREMENT
Special software can be used for automated identification and measurement of
PCBs (8) and pesticides. Unprocessed GC/MS data are handled without human
interaction with the software operating on the dedicated computer. A concen-
tration for each pesticide and each PCB isomer group is calculated automatically.
Contact EMSL-Cincinnati for further information.
14. METHOD PERFORMANCE
To obtain single laboratory accuracy and precision data for method analytes,
replicate 1-L aliquots of reagent water and river water fortified with known
amounts of analytes were extracted and analyzed. Automated procedures were used
to identify and measure method analytes in 2-uL aliquots of 1-mL extracts.
Because a sufficient quantity of individual PCB congeners was not available,
Aroclor mixtures were used to fortify water samples. This is not desirable,
because individual PCBs in Arodors vary in concentration. As Aroclor concen-
trations decrease in a sample extract, an increasing number of components
will fall below the detection limit and will not be identified and measured.
In addition, insufficient data are available about Aroclor composition to assess
accuracy of isomer group measurements or to assess MDLs for PCBs when Aroclors
are used to fortify samples.
14.1 Medium Level Reagent Water Extracts — Five aliquots of reagent water
fortified with each individual pesticide at a concentration of 10 ug/L and
Aroclors 1221, 1242, 1254, and 1268 at concentrations of 5 ug/L, 50 ug/L,
50'ug/L and 25 ug/L, respectively, were extracted and analyzed. Method
bias for individual pesticides ranged from -10% to +18% with a mean method
bias of +2% for all 21'pesticides (Table 15). For individual pesticides,
RSDs of measured concentration ranged from 0.61% for endrin ketone to
9.8% for endrin aldehyde. No true values are known for concentrations of
PCB isomer groups in Aroclors, but the mean measured total PCB concentration
was 110 ug/L (RSD 2.9%), which indicated a method bias of -15%. For
individual isomer groups, RSDs of mean measured concentrations ranged
from 3.9% to 16%.
14.2 Low Level Reagent Water Extract — Reagent water was fortified with each
pesticide at a concentration of 3 ug/L and a total PCB concentration of
27 ug/L (Aroclors 1221, 1 ug/L; 1242, 10 ug/L; 1254, 10 ug/L; and 1268,
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6 ug/L). When seven replicate extracts were analyzed, method bias for
individual pesticides ranged from -17% to +20% with a mean method bias of
-2% (Table 15). An MDL was calculated for each pesticide using the equation
relating the standard deviation of the seven replicate measurement and
Student's t: value for a one-tailed test at the 99% confidence level with n-1
degrees of freedom (1). With this calculation, MDL is defined as the
minimum concentration that can be measured and reported with 99% confidence
that the value is above zero. The excellent precision achieved with these
measurements resulted in unrealistically low MDLs ranging front 0.2 to 0.8
ug/L for pesticide analytes (Table 15). A PCS MDL is an individual congener
characteristic and cannot be determined with samples fortified with Aroclor
mixtures. Estimates of MDLs for individual components of PCB isomer groups
were obtained by proportioning the total quantity measured for each isomer
group among individual measured isomers. The estimated MDL values for
individual PCBs also were unrealistically low (0.01-0.1 ug/L) because of
the excellent precision of measurements. A more realistic statement of
detection limits for pesticides and PCBs can be found in Sect. 1.2.
14.3 River Water Extracts — Five aliquots of river water fortified with
each pesticide at a concentration of 5 ug/L and total PCB concentration
of 70 ug/L (Arodors 1221, 2 ug/L; 1242, 30 ug/L; 1254, 30 ug/L; and
1268, 8 ug/L) were extracted and analyzed. Method bias for individual
pesticides ranged from -30% to +8% with a mean of -8% (Table 15). The
excellent precision of measured pesticide PCB isomer group concentrations
was indicated by RSDs ranging from 1.6% to 7.5%. The mean measured total
PCB concentration of 51 ug/L (RSD 2.5%) indicated a method bias of -27%.
15. REFERENCES
1. Glaser, J. A., D. L. Foerst, G. D. McKee, S. A. Quave, and W. L. Budde,
"Trace Analyses for Wastewaters", Environ. Sci. Technol. 15, 1426, 1981.
2. Ballschmiter, K. and M. Zell, Freseniua Z. Anal. Chem., 302, 20, 1980.
3. "Carcinogens — Working with Carcinogens"/ Department of Health Service,
Center for Disease Control, National Institute for Occupational Safety
and Health, Publication No. 77-206, August 1977.
4. "OSHA Safety and Health Standards, General Industry", 29 CFR 1910,
Occupational Safety and Health Administration, OSHA 2206, Revised
January 1976.
5. "Safety in Academic Chemistry Laboratories", American Chemical Society
Publication, Committee on Chemical Safety, 3rd Edition, 1979.
6. Mullin, M. D., C. Pocnini, S. McCrindle, M. Romxes, S. H. Safe, and
L. M. Safe, "High Resolution PCB Analysis: Synthesis and Chromatographic
Properties of All 209 PCB Congeners", Environ. Sci. Technol. 18, 466, 1984.
7. Gebhart, J. E., Hayes, T. L., Alford-Stevens, A. L., and W. L. Budde,
•Mass Spectrometric Determination of Polychlorinated Biphenyls as
Isomer Groups", Anal. Chem. 57, 2458, 1985.
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8. Slivon, L. E., J. E. Gebhart, T. L. Hayes/ A. L. Alford-Stevens,
W. L. Budde, "Automated Procedures for Mass Spectrometric Determi-
nation of Polychlorinated Biphenyls as Isomer Groups", Anal. Chen.
57, 2464, 1985.
9. Rote, J. W. and W. J. Morris, "Use of Isdtopic Abundance Ratios in
Identification of Polychlorinated Biphenyls by Mass Spectrometry",
J. Assoc. Offie. Anal. Chen. 56(1), 188, 1973.
Table 1. Recommended GC Operating Conditions
Column Type:
Film Thickness:
Column Dimensions:
Helium Linear Velocity:
Temperature Program for Splitless Injection:
o Pull-range data acquisition for PCBs
and pesticides
(Analysis time - approx. 50 min)
SE-54 or DB-5
0.25 urn
30 m X 0.32 mm
28-29 cm/sec
at 250 »C
o SIM data acquisition for PCBs
(Analysis M""» * approx. 25 min)
o SIM data acquisition for pesticides
(Analysis time * approx. 30 min)
Inject at 80«C and hold 1 min;
increase at 30•/min to 160*C and
hold 1 min; increase at 3°/min to
310»C.
or
Inject at 80»C and hold 1 min; heat
rapidly to 160*C and hold 1 min;
increase at 3»/min to 310»C.
Inject at 45*C and hold 1 min; increase
at 20«/min to 150«C and hold 1 min;
increase at 10Vain to 310*C.
Inject at 80*C and hold 1 min; increase
at 30«/min to 160»C and hold 1 min;
increase at 3»/min to 250«C; hold
past elution time of methoxychlor.
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Table 2. PCS Congeners Used as Calibration Standards
Congener Chlorine
PCB Isomer Group Number* Substitution
Concentration Calibration Standard
Monochlorobiphenyl 1 2
Dichlorobiphenyl 5 2,3
Trichlorobipheny1 29 2,4,5
Tetrachlorobiphenyl 50 2,2',4,6
Pentachlorobiphenyl 87 2,2',3,4,5'
Hexachlorobiphenyl 154 2,2',4,4',5,6'
Hcptachlorobiphenyl 188 2,2',3,4',5,6,6'
Octachlorobiphenyl 200 2,2',3,3',4,5',6,6'
Nonachlorobiphenylk - —
Decachlorobiphenyl 209 2,2',3,3',4,4',5,5',6,6'
Retention Time Calibration Standards
Tetrachlorobiphenyl 77 3,3',4,4'
Pentachlorobiphenyl 104 2,2f,4,6,6'
Nonachlorobiphenyl 208 2,2',3,3',4,5,5',6,7'
a Numbered according to the system of Ballschmiter and Zell (2).
b Decachlorobiphenyl is used as the calibration congener for both nona-
and decacblorobiphenyl isomer groups*
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Table 3. Scheme for Preparation of PCB Primary Dilution Standard
PCB
Cong.
#1
#5
#29
#50
#87
#154
#188
#200
#209
Isorner
Group
0-1
C12
C13
C14
C15
cie
C17
C18
0-10
Stock Sol.
Cone.
mg/nL
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
Proportion
for Primary
Oil. Sol.
1 part
1 part
1 part
2 parts
2 parts
2 parts
3 parts
3 parts
5 parts
Primary Oil.
Std. Cone.
ng/uL
50
50
50
100
100
100
150
150
250
Total 20 parts
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Table 4. Composition and Approximate Concentrations of Calibration Solutions
for Full-Range Data Acquisition
Analyte/Int. Std./
Surrogate Compound
CM, 1
Concentration (ng/uL)
CAL 2 CAL 3 CAL 4 CAL 5
PCB Cal. Congeners
Cl, (#1)
C12 (#5)
C13 (#29)
C14 (#50)
C15 (#87)
C16 (#154)
C17 (#188)
C18 (#200)
C110 (#209)
Pesticides
Aldrin
BBC, each isaner
Chlordane, each isomer
4/4'-ODD
4,4'-DDE
4,4'-DDT
Dieldrin
Endosulfan I
Endosulfan II
Endosulfan sulfate
Endrin
Endrin aldehyde
Endrin Ice tone
Beptachlor
Heptachlor epoxide
Methoxychlor
Nonachlor, each isomer
Internal Standards
Chrysene-di2
Phenanthrene-d-j g
Surrogate Compounds
13Cg-gasnna BHC
13C12-4,4'-DOT
0.5
0.5
0.5
1
1
1
1.5
1.5
2.5
2.5
2.5
2.5
5
5
5
7.5
7,5
12.5
5
5
5
10
10
10
15
15
25
10
10
10
20
20
20
30
30
50
25
25
25
50
50
50
75
75
125
1
1
1
1
1
1
1
2
2
2
1
1
1
1
1
1
1
5
5
5
5
5
5
5
10
10
10
s
5
5
5
5
5
5
10
10
10
10
10
10
10
20
20
20
10
—
10
10
10
10
10
20
20
20
20
20
20
20
40
40
40
20
20
20
20
20
20
20
50
50
50
50
50
50
50
100
100
100
50
50
50
50
50
50
50
7.5
7.5
7.5
7.5
5
5
7.5
7.5
10
10
7.5
7.5
20
20
7.5
7.5
50
50
-------
-31-
Table 5a. Composition and Approximate Concentrations of Calibration Solutions
for SIM Data Acquisition for PCB Determinations
Concentration (ng/uL)
Compound
Cal. Congeners
Cl! (#1)
C12 (#5)
C13 (#29)
C14 (#50)
C15 (#87)
Cls (#154)
C17 (#188)
Clg (#200)
C110 (#209)
RT Congeners
C14 (#77)
Cls (#104)
Clg (#208)
CAL 1
0.1
0.1
0.1
0.2
0.2
0.2
0.3
0.3
0.5
0.2
0.2
0.4
CAL 2
0.5
0.5
0.5
1.0
1
1
1.5
1.5
2.5
1
1
2
CAL 3
1
1
1
2
2
2
3
3
5
2
2
4
CAL 4
2
2
2
4
4
4
6
6
10
4
4
8
CAL 5
5
5
5
10
10
10
15
15
25
10
10
20
Internal Standards
Phenanthr ene-d
^ g
0.75 0.75 0.75 0.75 0.75
0.75 0.75 0.75 0.75 0.75
Surrogate Compounds
13
C12-4,4'-DDT
0.2
0.2
2
2
4
4
10
10
-------
-32-
Table 5b. Composition and Approximate Concentrations of Calibration Solutions
for SIM Data Acquisition for Pesticide Determinations
Concentration (nq/uL)
Analyte/Internal Std/
Surrogate Compound
Pesticide Analytes
Aldrin
BBC, each isomer
Chlordane, each isomer
4, 4 '-ODD
4, 4 '-DDE
4 ,4 '-DDT
Dieldrin
Endosulf an I
Endosulf an II
Endosulf an sulf ate
Endrin
Endrin aldehyde
Endrin ketone
Heptachlor
Heptachlor epoxide
Methoxychlor
Nonachlor, each isomer
Internal Standards
Chrysene-df 2
Phenanthrene-d-j g
Surrogate Compounds
1 3C6-gamma-BHC
13C-,-4,4'-DDT
CAL 1
0.2
0.2
0.2
0.2
0.2
0.2
0.2
•
0.4
0.4
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.75
0.75
0.2
0.2
CAL 2
1
1
1
1
1
1
1
2
2
1
1
1
1
1
1
1
1
0.75
0.75
1
1
CAL 3
2
2
2
2
2
2
2
4
4
2
2
-
2
2
2
2
2
0.75
0.75
2
2
CAL 4
5
5
5
5
5
5
5
10
10
5
5
5
5
5
5
5
5
0.75
0.75
5
5
CAL 5
10
10
10
10
10
10
10
20
20
10
10
10
10
10
10
10
10
0.75
0.75
10
10
-------
-33-
Table 6. Criteria for DFTPP Spectrum
m/z Relative Abundance
127 40-60%
197 <1%
198 100% (Base Peak)
199 5-9%
275 10-30%
365 >1%
441 • Present and 40%
443 17-23% of m/z 442
-------
-34-
Table 7a. Ions for Selected Ion Monitoring to Determine PCBs by Acquiring
Data for Four Sets of <35 Ions Each
PCS Isomer Group/
Int . Std. /Sur r .Cmpd.
Monochlorobiphenyls
Di chlor obipheny Is
Trichlorobiphenyls
Tetrachlor obipheny Is
Pentachlorobiphenyls
Hexachlorobiphenyls
Heptachlorobiphenyls
Octachlorobiphenyls
Nonach lorobipheny Is
Decachlorobiphenyl
Chrysene-d^ 2
Phenanthrene-d1 g
1 ^Cg-gamma-BHC
13C12-4,4'-DOT
Nominal
Hoi. Wt.
188
222
256
290
324
358
392
426
460
494
240
188
294
364
Mass or Range
to be Monitored
152; 186-190
220-224
254-260
288-294
322-328
356-362
390-396
424-430
460-466
496-500
240-241
188-189
187,189
247| 249 '
No. of
Ions
6
5
7
7
7
7
7
7
7
5
2
2
2
2
Ion Sets
#1 #2 #3 #4
6
5
7 7 1a
7 7 1b
7 7
6C 7 7
6* 7
7
7
5
2
2e
2f
2
Total t ions
25 27 24 35
"Monitor m/z 254 to confirm presence of (M-70)* for Cl5-PCBs.
Monitor m/z 288 to confirm presence of (M-70)* for Clg-PCBs.
cBegin range at m/z 357 in Ion Set t2.
dBegin range at m/z 391 in Ion Set #3.
eM/z 188 and 189 included among ions used to detect and measure monochlorobiphenyIs.
fM/z 187 and 189 included among ions used to detect and measure monochlorobiphenyIs.
-------
-35-
Table 7b. Ions for Selected Ion Monitoring to Determine PCBs by Acquiring Data for Five Sets, of <20 Ions Each
Ion
Set
1
2
3
4
5
I some r Group/
IS/Surrogate
Cl
cjj
Cl*
13C6-garama-BHC
Phenanthrene-djQ
C13
C14
C15
C16
d5
cie
C17
13C12-4,4'-DDT
ci6
C17
Clg
Chrysene-dj2
Cle
Clg
ciio
Quant.
Ion
188
222
256
292
187
188
256
292
326
360
326
360
394
247
360
394
430
240
430
464
498
Confirm.
Ions
190
224
258
290,294
189
189
258
290,294
324,328
358,362
324,328
358,362
392,396
249
358,362
392,396,398
428,432
241
426,428,432
460,462,466
494,496,500
M-70
Ions
152,153b
152,153,186,188°
186,188
220,222
186,188
220,222
254,256,258
288,290,292
254,256
288,290
322,324,326
"
288,290
322,324
356,358,360
—
356,358,360
390,392,394
424,426,428,430
M+70
Ions
256,258
290,292,294
-
_
-
"
324,326,328
360,362
-
—
392,394,396,398
-
-
"
426,428,430,432
-
—
^
494,496,498,500
-
^
M+35
Ions
222,224
256,258
290,292,294
_
-
"
290,292,294
324,326,328
360,362
—
360,362
392,394,396,398
-
"
392,394,396
428,430,432
—
"
462,464,466
496,498,500
—
Ion Measured8
for Correction
221
255
— _
-
"
254 255
288 289
323
— -
322 323
357
-
^ ^
356 357
391
- -
*• —
425
- -
«• «•
a See Tables 12-13.
b
c
Cl«-PCBs lose HCl.
Some Cl2-PCBs lose C12 and some lose HCl.
-------
-36-
Table 7c. Ions for Selected Ion Monitoring to Determine PCBs by Acquiring
Data for Five Ion Sets of <20 Ions
Ion Set
No. 1*
'152
153
186
187
188
189
190
220
221
222
224
255
256
258
290
292
294
Ion Set
No. 2b
186
188
220
222
254
255
256
258
288
289
290
292
294
323
324
326
328
358
360
362
Ion Set
No. 3C
247
249
254
256
288
290
322
323
324
326
328
357
358
360
362
392
394
396
398
Ion Set
No. 4d
240
241
288
290
322
324
326
356
357
358
360
362
391
392
394
396
398
428
430
432
Ion Set
No. 5e
356
358
360
390
392
394
424
425
426
428
430
432
462
464
466
496
498
499
500
502
17 ions
20 ions
19 ions
20 ions
20 ions
a Ions to identify and measure Cl-j-Cl.-PCBs, phenanthrene-d1Q, and
Cg-gamma-BHC.
Ions to identify and measure Clj-Clg-PCBs.
0 Ions to identify and measure Cl5-Cl7-PCBs and 13C12-4,4'-DDT.
d Ions to identify and measure Clg-Clg-PCBs and chrysene-d12*
c Ions to identify and measure C
-------
-37-
Table 8* Retention Time Data for PCS Isomer Groups and Calibration Congeners
Isomer Group
Monochlorobiphenyls
Dichl orobipheny Is
Trichlorobiphenyls
Te tr achlorobipheny Is
Pentachlorobiphenyls
Hexachlorobiphenyls
Hept achlorobipheny Is
Octachlorobiphenyls
Nonachlorobiphenyls
Decachlorobiphenyl
Approximate
RRT Range*
0.30-0.35
0.38-0.50
0.46-0.64
0.55-0.82
0.64-0.92
0.75-1.1
0.88-1.2
0.99-1.21
1.16-1.28
1.3
Cal. Cong.
Number
1
5
29
50
87
154
188
200
-
209
Cal . Cong
RRTa
0.30
0.43
0.54
0.56
0.80
0.82
0.88
1.03
-
1.3
a Retention time relative to chrysene-d^ with a 30 m X 0.31 mm ID SE-54 fused
silica capillary column and the following GC conditions: splitless injection
at 80*C; hold for 1 min; heat rapidly to 160°C and hold 1 min; increase at
3°C/min to 310«C.
-------
-38-
Table 9. Ions for Selected Ion Monitoring Data Acquisition for Pesticide Analytes,
Internal Standards and Surrogate Compounds (Ordered by Retention Tine)
Gamna-BHC
13
Ion Analyte/Internal Std/ Approx. Quant*
Set Surrogate Compound (MW) RRT Ion
Alpha-BHC (288) 0.43 219
Beta-BBC (288) 0.47 219
(288) 0.48 219
Cg-gaoraa-BHC (294) 0.48 225
Phenanthrene-d-j Q (188) 0.49 188
Delta-BHC (288) 0.51 219
Heptachlor (370) 0.58 272
Aldrin (362) 0.64 263
Heptachlor epoxide(386) 0.70 353
Ganma-chlordane (406) 0.74 373
Endosulfan I (404) 0.76 195
Alpha-chlordane (406) 0.76 373
Trans-nonachlor (440) 0.77 409
Dieldrin (378) 0.80 79
4,4'-DDE (316) 0.81 246
Endrin (378) 0.83 81
Endosulfan II (404) 0.85 195
4,4'-DDD (318) 0.87 235
Endrin aldehyde (378) ' 0.88 67
Endoeulfan sulfate(420) 0.92 272
4,4'-DOT (352) 0.93 235
13C12-4,4'-DDT (364) 0.93 247
Endrin ketone (378) 0.99 67
Chrysene-d12 (240) 1.00 240
Methoxychlor (344) 1.03 227
Ions (Approximate
Relative Abundance)
181 (100), 183 (90), 219 (70)
181 (100), 183 (90), 219 (70)
181 (100), 183 (90), 219 (75)
187 (100), 189 (90) 225 (80), 227 (40)
188 (100), 189 (15)
181 (100), 183 (90), 219 (70)
100 (100), 272 (60), 274 (40)
66 (100), 263 (40), 265 (25)
81 (100)., 353 (80), 355 (65)
373 (100), 375 (95)
195 (100), 339 (50), 341 (35)
373 (100), 375 (95)
409 (100), 407 (85)
79 (100), 263 (10), 108 (15)
246 (100), 248 (65)
81 (100), 263 (75)
195 (100), 339 (50), 341 (35)
235 (100), 237 (65), 165 (65)
67 (100), 345 (30)
272 (100), 274 (80), 387 (50)
235 (100), 237 (65), 165 (65)
247 (100), 249 (65)
67 (100), 317 (50)
240 (100), 241 (20)
227 (100), 228 (15)
-------
-39-
Table 10. Ion Seta for Selected Ion Monitoring of Pesticide Analytes, Internal
Standards and Surrogate Compounds (Ordered by Retention Time)
Ion Set
No. 1
66
100
181
183
187
188
189
219
225
227
263
265
272
274
Monitored
Compounds
Alpha-arc
Beta-BHC
Delta-BBC
Gamma— BBC
Cg— gamma— BBC
Phenanthrene-d^ g
Heptaehlor
Aldrin
Ion Set
No. 2
79
81
108
195
246
248
263
339
341
353
355
373
375
407
409
Monitored
Compounds
Heptaehlor
epoid.de
Alpha-chlor dane
Gamma-chlordane
Endosulf an I
Trans-nonachlor
Dieldrin
4, 4 '-ODE
Endrin
Endosulf an II
Ion Set
No. 3
67
165
227
228
235
237
240
241
247
249
272
274
317
345
387
Monitored
Compounds
4, 4 '-ODD
Endrin aldehyde
Endosulfan sulfate
4/4'-DDT
13C12-4,4'-DDT
Endrin ketone
Chrysene-df 2
Methoxychlor
14 ions f 8 "' •"! M mTQ^n
15 ions, 9 compounds
15 ions 8 compounds
-------
-40-
Table 11. Known Relative Abundances of Ions in PCS Molecular Ion Clusters*
m/z
Relative
Intensity
Monochlorobiphenyls
188 100
"189 13.5
190 33.4
192 4.41
Dichlorobiphenyls
222 100
223 13.5
224 66.0
225 8.82
226 1*1.2
227 1.44
Trichlorobiphenyls
256 100
257 13.5
258 98.6
259 13.2
260 32.7
261 4.31
262 3.73
263 0.47
Tetrachlorobiphenyla
290 76.2
291 10.3
292 100
293 13.4
294 49.4
295 6.57
296 11.0
297 1.43
298 0.95
Pentachlorobipheny Is
324 61.0
325 8.26
326 100
327 13.5
328 65.7
329 8.78
330 21.7
331 2.86
332 3.62
333 0.47
334 0.25
m/z
Relative
Intensity
Hexachlorobiphenyls
358 50.9
359 6.89
360 100
361 13.5
362 82.0
363 11.0
364 36.0
365 4.77
366 8.92
367 1.17
368 1.20
369 0.15
Heptachlorobiphenyls
392 43.7
393 5.91
394 100
395 13.5
396 98.3
397 13.2
398 53.8
399 7.16
400 17.7
401 2.34
402 3.52
403 0.46
404' 0.40
Octachlorobiphenyls
426 33.4
427 4.51
428 87.3
429 11.8
430 100
431 13.4
432 65.6
433 8.76
434 26.9
435 3.57
436 7.10
437 0.93
438 1.18
439 0.15
440 0.11
m/z
Relative
Intensity
Nonachlorobiphenyls
460 26.0
461 3.51
462 76.4
463 10.3
464 100
465 13.4
466 76.4
467 10.2
468 37.6
469 5.00
470 12.4
471 1.63
472 2.72
473 0.35
474 0.39
Decachlorobiphenyl
494 20.8
495 2.81
496 68.0
497 9.17
498 100
499 13.4
500 87.3
501 11.7
502 50.0
503 6.67
504 19.7
505 2.61
506 5.40
507 0.71
508 1.02
509 0.13
"Source: Rote and Morris (9)
-------
-41-
Table 12. Quantitation, Confirmation, and Interference Check Ions for PCBs,
Internal Standards/ and Surrogate Compounds
Analyte/
M-70 Interference
Horn. Quant. Confirm. Expected Accept. Confirm. Cheek Ions
Internal Std.
PCS Isomer Group
<*1
C12
C13
ci4
cis
Cl6
C17
<=18
Clg
"10
Internal standards
Chrysene-d
-------
-42-
Table 13. Correction for Interference of PCS Containing Two Additional Chlorines
Candidate
Ion Measured
Quant. Confirm, to Determine
% of Meas. Ion Area to
be Subtracted from
Isomer Group
Trichlorobipheny Is
Tetrachlorobiphenyls
Pentachlorobiphenyls
Hexachlorobiphenyls
Heptachlorobiphenyls
Ion
256
292
326
360
394
Ion
258
290
324
362
396
Interf erence
254
288
322
356
390
Quant
Ion Area
99%
65%
108%
161%
225%
Confirm.
Ion Area
33%
131%
164%
71%
123%
Table 14. Correction for Interference of PCB Containing One Additional Chlorine
Candidate
Isomer Group
Dichlorobiphenyls
Trichlorobipheny Is
Tetrachlorobiphenyls
Pentachlorobiphenyls
Hexachlorobiphenyls
Heptachlorobipheny la
Octachlorobiphenyls
Quant.
Ion
222
256
292
326
360
394
430
to Determine
Interference
221
255
289
323
357
391
425
to be Subtracted
from Quant. Ion Area
13.5%
13.5%
17.4%
22.0%
26.5%
30.9%
40.0%
-------
-43-
Table 15. Accuracy and Precision of Automated Measurements of PCBs and Pesticides in Fortified Water Extracts
Medium Level Reagent Water*
Low Level Reagent Water*1
Ohio River Water*
Analyte
(Meas. Ion)
True Mean Meas*
Cone. Cone., ug/L Bias
ug/L (RSD, %) %
True Mean Meas.
Cone. Cone., ug/L Bias MDL
ug/L (RSD, %) % ug/L
True Mean Meas.
Cone. Cone., ug/L Bias
ug/L (RSD, %) %
Aldrln (263)
BHC, alpha (219)
BHC, beta (219)
BHC, gamma (219)
BHC, delta (219)
Chlordane, alpha (373)
Chlordane, gamma (373)
4,4'-ODD (235)
4,4'-DDE (246)
4,4'-DDT (235)
Dieldrln (79)
Bndosulfan I (195)
Bndosulfan II (195)
Endosulfan sulf. (272)
Endrin (81)
Endrln aldehyde (67)
Bndrin ketone (67)
Heptaohlor (272)
Heptaehlor epox. (353)
Methoxychlor (227)
Nonachlor, trans (409)
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
9.6
9.8
10.5
10.2
9.9
9.6
9.6
10.4
9.8
10.9
10.6
9.6
10.2
10.6
11.8
9.0
11.5
10.6
10.0
11.4
9.5
(3.6)
(4.3)
(3.6)
(4.7)
(4.2)
(3.9)
(4.6)
(3.0)
(3.2)
(3.0)
(3.2)
(5.8)
(4.5)
(2.3)
(2.8)
(9.8)
(0.61)
(5.1)
(2.5)
(1.6)
(4.6)
-4
-2
+5
+2
-1
-4
-4
+4
-2
+9
46
-4
+2
+6
+18
-10
+ 15
+6
0
+ 14
-5
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2.5
2.8
3.0
2.9
2.9
2.9
2.7
2.9
2.8
2.9
2.9
3.1
3.3
3.2
3.6
2.8
3.2
2.6
3.0
3.1
2.8
(7.2)
(5.0)
(2.5)
(5.3)
(4.8)
(4.0)
(4.8)
(3.8)
(5.4)
(4.5)
(7.6)
(4.8)
(6.3)
(4.4)
(7.0)
(8.4)
(1.9)
(5.3)
(5.9)
(2.3)
(2.4)
-17
-7
0
-3
-3
-3
-10
-3
-7
-3
-3
+3
+ 10
+7
+20
-7
+7
-13
0
+3
-7
0.6
0.4
0.2
0.5
0.4
0.4
0.4
0.4
0.5
0.4
0.7
0.5
0.7
0.4
0.8
0.7
0.2
0.4
0.6
0.2
0.2
5 4
5 4
5 !
5 4
5
5
5
5
5
5
5
5
5 I
5 x
5 !
5 4
5 *
'5 *
5 I
5 4
5 '
1.7 (3.0)
1.7 (1.6)
>.1 (2.5)
1.8 (3.0)
.8 (2.4)
.6 (4.2)
.4 (3.5)
.8 (2.5)
.5 (4.5)
.7 (3.9)
.5 (4.3)
..4 (5.0)
1.5 (4.1)
1.8 (1.7)
>.4 (7.5)
1.4 (4.8)
1.7 (3.0)
1.9 (3.5)
1.8 (3.9)
1.8 (3.8)
1.4 (4.3)
-6
-6
+2
-4
-4
-8
-12
-4
-10
-6
-10
-12
-30
-4
+8
-12
-6
-2
-4
-4
-12
All pesticides
10
10.2 (7.1) +2
2.9 (8.6) -2
4.6 (7.7)
-8
-------
-44-
Table 15. (Cont.) Accuracy and Precision of Automated Measurements of PCBs and Pesticides in '
Fortified Water Extracts
Medium Level Reagent Water*
Low Level Reagent Water**
Ohio River Water*
Analyte
(Meas. Ion)
PCBs
C11
C12
C13
C14
cis
C16
C17
Cla
C19
ciio
(188)
(222)
(256)
(292)
(326)
(360)
(394)
(428)
(466)
(500)
True Mean Meas. Mean
Cone. Cor.o. , ug/L Bias
ug/L (ROD,
130 110
3
6
17
21
28
9
1
7
12
2
.6
.5
.2
.7
.8
.8
.3
.1
.6
.0
%)
(2.
(9.
(5.
(5.
(4.
(3.
(5.
(4.
(3.
(5.
%
9) -15
9) -
7) -
3) -
1) -
6) -
7) -
3) -
5) -
3) -
(16.0) -
True Mean
Cone . Cone .
Meas. Mean
, ug/L Bias
ug/L (R6D, %) %
27 21
0
1
• 3
4
5
1
1
2
0
.2
.7
.2
.1
.1
.6
.6
-
.6
.7
.6
(2.8) -21
(15)
(10)
(10)
(3.8)
(2.8)
(3.1)
- -
(2.7)
(4.6)
(12)
Method True Mean Meas. Mean
Detect. Cone. Cone., ug/L Bias
Limit ug/L (R8D, %) %
0 70 51
1
3
10
11
15
4
0
1
3
0
.3 (2
.83 (4
.42 (3
.1 (3
.0 (4
.4 (3
.86 (6
.5) -27
.8)
.9)
.0)
.5)
.6)
.4)
.335(4.8)
.56 (4
.00 (1
.442 (
.3)
.8)
1.8)
Surrogate Compounds
13C6-gamma-BHC (187) -
13C|2-4,4»-DDT (247) -
3.0 (3.4)
0.3
5
5
4.9
4.4
(1.4) -2
(7.0) -12
* Results of analysis of five replicate extracts of 1-L aliquots of fortified water.
b Results of analysis of seven replicate extracts of 1-L aliquota of fortified water.
0 PCB method detection limits cannot be determined because Aroclor mixtures were used to fortify samples.
-------
iee.e-i
RIC
5"
1. Clj-PCB
2. alpha-BHC +
C12-PCB
3. beta-BHC
4 . gamma-BHC
5. phenanthrene-djQ
6. delta-BHC
7. C13-PCB
X
/
I
^
^-*— _
e. ci4-pcB
9. heptachlor
10. aldrln
tj
11. heptachlor epoxlde. ltf
12. gamma chlordane
13. endoaulfan I
14. alpha chlordane
15* trana-nonachlor
3
<
i
7
10
4
1
II
' '3 it.
If
16. C15-PCB 23
17. DDE 24
18. C16-PCB 25
19. endrln 26
20. endoaulfan II 27
21. PDD 28
22. Bndrln aldehyde 29
+ C17-PCB
if
1
N
M
0
12.
*£
xf
ruJlif1-1
sS
I
_]
a
.
7
^
BB
endoaulfan aulfate
DDT
endrln ketone
chryaene-d^2
Clg-PCB
methoxychlor
C110-PCB
Figure 1. Total Ion Current profile of PCB Calibration Congeners and Pesticide Analytea.
-------
ci2
Cl,
Cl
3
Cl
Cl,
Cl
10
C19
C18
C15
I
a\
13
C12-4,4»-DOT
Chrysene-dj2
0.3 0.4 0.5 0.6 0.7 0.8 0.9- 1.0 1.1 1.2 1.3
Relative Retention Time
Figure 2. Diagram indicating approximate relative retention times (DB-5 GC column; chrysene-d^ Internal standard)
of PCB laomer groups and retention time marker compounds (for PCB SIM data acquiatlon option).
-------
50272-101
REPORT DOCUMENTATION
PAGE
1. REPORT NO.
EPA 560/5-90-008B
3. Recipient's Accession No.
4. Tltte and Subtitle
PCB, Lead, and Cadmium Levels in Shredder Waste Materials: A Pilot Study
5. Report Date
April 1991
7. Author(s)
Westat Inc., Midwest Research Institute (MRI), Battelle Columbus Division (BCL)
8. Performing Organization RepL No.
9. Performing Organization Name and Address
Westat, Inc.
1650 Research Blvd.
Rockville, MD 20850
10. Project/Task/Work Unit No.
11. Contract (C) or Grant (G) No.
(O 68-02-4293 (Westat)
(6) 68-02-4252 (MRI)
68-02-4294 (BCL)
12. Sponsoring Organization Name and Address
U.S. Environmental Protection Agency
Offices of Toxic Substances and Solid Waste
Washington, DC 20460
13. Type of Report & Period Covered
Technical Report
14.
15. Supplementary Notes
16. Abstract (Limit: 200 words)
Comprehensive Technical Report on Pilot Study;
The US EPA conducted a pilot study to investigate the presence of polychlorinated biphenyls (PCBs) and other
hazardous substances in waste products produced at metal salvage and recycling facilities. Field sampling, sample
preparation, and laboratory methods were developed. For the purposes of the pilot study, input materials were
segregated by type to allow separate shredding of three distinct material categories: automobiles only, white goods
(appliances) only, and mixed input. PCBs were found in all sampled materials at all pilot study sites: however, 98% of
the PCBs were associated with the waste product (which is known as fluff due to its fibrous appearance). Leachability
was determined and appeared to be lower than that found in most soil matrices. The fluff was analyzed for lead and
cadmium; those contaminants were found in most samples. The Extraction Procedures Toxicity test (EPTOX) was run
for lead and cadmium. The pilot study data do not dearly point to any particular input material as the source of PCBs,
lead, or cadmium. Highest PCB levels were found in mixed input materials, which included construction materials,
demolitions waste, and at some sites, appliances and/or automobile components. White goods fluff and automobile fluff
had similar levels of PCBs.
17. Document Analysis & Descriptors
Environmental contaminants
b. ktentlflers/Open-Ended Terms
Fluff, PCB, cadmium, lead, shredder
c. COSATI Reid/Group
18. Availability Statement
Available to public from NTIS, Springfield, VA
19. Security Class (This Report)
Unclassified
20. Security Class (This Page)
Unclassified
21. No.
522
22. Price
(SeeANSI-Z39.18)
See Instructions on Reverse
OPTIONAL FORM 272 (4-77)
(Formerly NT1S-35)
Department of Commerce
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