S3MIVOLATIItE ORGANIC COMPOUNDS IN THE OEWERAL U. S. POPULATION: " ATS FY86 RESULTS VOLUME I This work was supported by the U. S. Environmental Protection Agency under EPA contract numbers 68 02 4294, 68 D8 0115, 68 DO 0126, 68 D2 0139, 68 02 4252, 68 02 4293, and 68 D9 0174 Prepared for Khoan Dinh, Work Assignment Manager Technical Programs Branch Chemical Management Division Office of Pollution Prevention and Toxics U. S. Environmental Protection Agency Washington, DC 20460 July 1994 The material in this document has been subject to Agency technical and policy review and approved for publication as an EPA report. The views expressed by individual authors, however, are their own and do not necessarily reflect those of the U. S. Environmental Protection Agency. Mention of trade names, products, or seryices does not convey, and should not be interpreted as conveying, official EPA approval, endorsement, or recommendation. PREFACE The determination of the levels of semivolatile organic compounds in the general population of the United States described in this report was achieved through cooperative efforts of many EPA and contract support staff. EPA staff participating in the program included principal investigators from the Technical Programs Branch ( TPB) of the Chemical Management Division ( 0) of the Office of Pollution Prevention and Toxics ( OPPT). Contract support to OPPT was provided by:

0 Battelle under EPA Contract Nos. 68 02 4294,68 D8 0115, 68 DO 0126, and 68 02 0139.

Midwest Research Institute ( MRI) under EPA Contract No. 68 02 4252.

0 Westat, Inc., under EPA Contract Nos. 68 02 4293and 68 D9 0174.

The roles and responsibilities of each of these organizations and key individuals participating in this effort are presented below.

Battelle Battelle was responsible for developing the FY86 hTS specimen collection program, creating and maintaining the data bases on the Patient Summary Reports, designing the specimen compositing plan and the statistical methodology for data analysis, conducting the statistical analysis to develop estimates of semivolatile. re. sidua1levels in the general U. S. population based on demographic factors, and producing this final report. Key individuals included: Dr. Robert Lordo, Dr. John Orban, Mr. Ying Liang Chou, Ms. Pamela Hartford, and Ms. Tamara Collins.

Midwest Research Institute ( MRIL MRI was responsible for the coordination of the collection of the FY86 " ATS specimens, preparation of the " ATS composites and quality control ( QC) samples, conducting the HRGC/ MS analysis of the composites, reporting the results, and contributing to this final report. Key individuals included: Dr. John Stanley, Dr. Stan Spurlin, Mr. Jack Balsinger, Ms. Hope Green, and Ms. Patti Alm.

iii Westat. Inc.

Westat was responsible for creating and maintainingthe data bases fur the Analysis Reports, developing and executing statistical procedures for identifying outliers in the reported concentrations, and writing the final report on the results of the outlier analysis. Key individuals included: Mr. John Rogers and Ms. Helen Powell.

EPA/ OPPT EPA/ QPPT was responsible for oversight in the development of the study plan, managing and coordinating the conduct of the overall study, and reviewing, editing and finalization of this report. Key individuals included: Dr. moan Dinh, Ms. Janet Remmers, and Mr. John Schwemberger as Work Assignment Managers and Dr. Joseph Breen, Ms. Edith Sterrett, Mr. Gary Grindstaff, and Mr. Philip Robinson as Project Officers.

iv TABLE OF CONTENTS Volume I Pase gxgcuTIvEsuMMARY ................... . 0' xvii 1.0 INTRODUCTION ................... .. . 1 1 1.1 Background ................. .. . 1 1 1.2 Objectives ................. .. . 1 3 1.. 3 Report Organization .............. .. . 1 3 2.0 NHATS FY86 SAMPLg DSSIGN ............. .. . 2 1 2.1 Sampling Design ............... . . I . 2 1 2.1.1 The " ATS Stratification Scheme . . .. . 2 3 2.1.2 MSA Selection ............ .. . 2 3 2.1.3 Specimen Collection Quotas ...... .. . 2 6 2.2 Sample Collection Procedures ........ .. . 2 9 2.3 Specimen Collection Summary ......... .. 2 11 3.0 NEATS FY86 COMPOSITE DESIGN ........... .. . 3 1 3.1 Design Goals and Compositing Criteria .... .. . 3 1 3.2 Laboratory Compositing Procedures ...... .. . 3 4 3.3 Summary of FY86 " HATS Composite SampXes ... .. . 3 6 4.0 CHEMISTRY ..................... .. . 4 1 4.1 Analytical Procedures ............. .* . 4 1 4.1.1 Sample Preparation .......... ..  4 1 <IP_ADDRESS> Extraction ......... *. . 4 3 <IP_ADDRESS> Lipid Determination ..... .. . 4 3 <IP_ADDRESS> Extract Concentration .... .. . 4 3 4.1.2 Cleanup Procedure .......... .. . 4 4 <IP_ADDRESS> Gel Permeation Chromatography .. . 4 4 <IP_ADDRESS> GPC Eluent Concentration . . .. . 4 5 <IP_ADDRESS> Florisil Column Cleanup ... .. . 4 5 4.1.3 Analysis Procedures ......... .. . 4 7 V .. TABLE OF CONTENTS . ( cont.)

Volume I ( coat.)

4.1.4 Quantitation/ Data Reduction ........

<IP_ADDRESS> Qualitative Identification ... <IP_ADDRESS> Quantitation .......... <IP_ADDRESS> Recovery of Surrogate Standards . Qr1.4.4 Data Qualifiers ......... <IP_ADDRESS> Estimating the Method Limit of Detection ............

4.2 QA/ QC for Chemical Analysis ...........

4.2.1 Demonstrating Achievement of Instrument performance Requirements .......... 4.2.2 Calibration . forQuantitative Semivolatile Analysis ..........

<IP_ADDRESS> Initial Calibration ....... <IP_ADDRESS> Routine Calibrations ......

4.2.3 Spiking Solution Preparation .......

<IP_ADDRESS> Native Standard Spiking Solution Paue . 4 8 . 4 8 4 14 4 15 4.15.

4 16 4 17 4 17'

4 19 4 19 4 25 4 25 ............. 4 25 <IP_ADDRESS> Surrogate Standard Spiking Solution ............ <IP_ADDRESS> Internal Standard Spiking Solution ............ <IP_ADDRESS> Performance Audit Solutions ...

4.2.4 QC Samples ................

<IP_ADDRESS> Method Blanks .......... <IP_ADDRESS> Control Samples ......... <IP_ADDRESS> Spiked Control Samples .....

4.3 Overall Data Quality .............. 4 25 4 28 4 28 4 28 4 28 4 30 4 30 4 31 5.0 DATAISSUES ...................... 5 1 5.1 Determining Native Compounds to Enclude in Statistical Analysis .............. 5 2 5.1.1 Detection Status of the Semivolatiles ... 5 3 5.1.2 Data Reporting Unique to Dieldrin and p. p. DDE .......... 5 8 vi . *

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a . . . . . . . . .

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. Pase . 5 9 5 10 5 11 5 14 5 19 5 22 5 22 5 30 5 30 5 30 5. 30 5 36 5 36 5 36 5 45 5 48 . .  6 1 . . 6 2 . . . 6 7 . . . 6 7 . . . 6 7 . . 6 10 . . 6 12 . . . 7 1 . . . 7 2 TABLE OF CONTENTS ( coat.)

Volume I tcont.)

Page 7.2 Population Estimates from Statistical Modelling. . . . . . . . . . . . . . . . . . . . . 7 8 7.3 Hypothesis Testing . . . . . . . . . . . . . . . 7 27 7.4 Outlier Detection . . . . . . . . . . . . . . . . 7 29 7.5 Model Validation . . . . . . . . . . . . . . . 7 32 8.0 COMPARISON WITH RESmjTS FROM PREVIOUS SURVEYS INTHENHATSPROGRAM.. . .. . . . . . .8 1 8.1 Cornparison of Design and Analytical Procedures . . . . . . . . . . . . . . . . . . . 8 2'

8.1.1 Comparison of Study Designs . . . . . . . . 8 2 8.1.2 Comparison of Analytical Procedures . . . . 8 6 8.2 LODs and Percent Detection Summaries . . . . . . 8 10 8.3 Descriptive Statistics on Measured Concentrations . . . . . . . . . . . . . . . . . 8 15 8.3.1 Scatterplots of the Sample Concentrations . . . . . . . . . . . . 8 16 8.3.2 Unweighted National Averages . . . . . . . 8 17 8.3.3 Weighted National Averages . . : . . . . . 8 18 8.4 Statistical Comparison of National Concentration Estimates . . . . . e . . 8 26 8.4.1 Semivolatile Compounds Included in Statistical Comparison . . . . . . . . . . 8 27 8.4.2 Fitting the Additive Model . . . . . . . . 8 28 <IP_ADDRESS> National Estimates . . . . . . . 8 29 <IP_ADDRESS> Marginal Estimates . . . . . . . 8 31

<IP_ADDRESS> Likelihood Ratio Tests :. . . . 8 34 . <IP_ADDRESS> Conclusions . . . . . . . . . . . 8 34 9.0 REFERENCES . . . . . . . . . . . . . . . . . . . 9 1 Volume I1 Appendix A: Listing of " ATS FY86 Composite Data %

viii TABLE OF CONTENTS ( cont.)

Volume I1 ( cont.)

Listing of NHATS FY86 QC Data For Compounds Detected in At Least 50% of Composites ( plus octachlorobiphenyl)

Plots of Observed VS. Spiked Concentrations for Spiked Semivolatile Compounds Detected in At Least 50% of Composites ( plus Octachlorobiphenyl) .

Plots of Observed Concentration vs. Batch ID for Unspiked Semivolatile Compounds Detected in At Least 50% of Composites Summary of QC Data for the FY86 " ATS Spiked Semivolatile Compounds Not on the Target List for Statistical Analysis Characterizing the Distribution of " HATS FY86 Semivolatile Compound Goncentrations ( inng/ g, Unadjusted for Surrogate Recoveries) Based on All 50 Composite Samples Estimates of Average Concentrations with 95% Confidence Intervals As Determined by the Additive Model, for Selected Subpopulations in the FY86 " HATS Concentrations ( ng/ g) from the FY82, FY84, and FY86 " ATS, Plotted in Chronological Order with Age Group as the Plotting Symbol Surrogate Adjusted Concentrations ( ng/ g) from the FY82, FY84, and FY86 " ATS, Plotted in Chronological Order with Age Group as the Plotting Symbol Arithmetic Averages ( and Standard Errors) of Extractable Lipid Concentrations ( ng/ g) for Compounds Analyzed in the FY86 " HATS and Also Analyzed in the FY82 and/ or FY84 " ATS Comparisons of Predicted Average Concentrations ( ng/ g) by Selected Subpopulations for Selected Semivolatiles over the FY82, FY84, and FY86 NHATS Plots of Estimates Average Concentrations ( ng/ g) by Census Region and by Age Group, Plus and Minus Two Standard Errors, Based on the Additive Model for the FY82, FY84, and FY86 " ATS I LIST OF TABLES Volume I Pase Table ES 1 Semivolatile Compounds Detected in At Least 44% of the FY86 NHATS Composite Samples ..... xx Table kS 2 Estimates of National Average Concentrations for Selected Semivolatiles, with 95% Confidence Intervals, from the FY86 MIATS ... xxii Table ES 3 Estimates of National Average Concentrations for Selected Semivolatiles, with 95% Confidence Intervals, from the FY82, FY84, and FY86 NHATS ............. xxvi Table 2 1 Demographic Categories in Which Subquotas Were Established for Collecting Adipose Tissue Specimens ............ 2 2 Table 2 2 Sampling Strata Definitions for the " HATS .... 2 4 Table 2 3 Sample MSAs Selected for the FY86 NHATS ..... 2 7 Table 2 4 FY86 Age and Sex Subquotas, and the Race Subquota, far Each NHATS Collection Site Within Each Stratum .............. 2 10 Table 2 5 FY86 NHATS Specimen Collection Summary .... 2 13 Table 2 6 FY86 NHATS Speciment Collection Summary by Demographic Subpopulation ......... 2 14 Table 3 1 Distribution of FY86 " ATS Composite Samples by Census Division and Age Group ........ 3 7 Table 3 2 Demographic Makeup of FY86 NHATS Composite Samples ................ 3 8 Table 4 1 Recommended HRGC/ MS Operating Procedures .... 4 8 Table 4 2 Characteristic Masses and Intensities for the Qualitative Identification of the Semivolatile Target Analytes, Chromatographic Conditions, and Estimated Limit of Detection ........ 4 9 Table 4 3 DFTTP Key Masses and Abundance Criteria .... 4 18 Table 4 4 Calibration Solutions for the 6% Florisil Fraction ................ 4 20 X   LIST OF TABLES ( cont.)

Volume I ( cont.)

Pase ___ 4 5 Calibration Solutions for the 50% d Florisil Fraction ............... 4 23 ble 4 6 Calibration Solutions for PCB Analysis .... 4 24  le 4 7 Proposed QC Spiking Solutions .......... 4 26 hle 4 8 Spike Levels for Surrogate and Internal Standards ..... ..... . . 4 29 # e 4 9 Quality Control Samples Included in the FY86 " ATS Analytical Procedure ........ 4 30 sle 4 10 Data Quality Objectives for the FY86 NHATS,

h> Along With Actual Performance ......... 4 32 > le 5 1 Percent of " ATS FY86 Composite Samples in Each Detection Level Cat. egory .. .. 5 4 & le 5 2 Matching NHATS FY86 Native Compounds with Surrogate Compounds . .. ... .. 5 1' 2 & le 5 3 Estimates of R and A for Surrogate .. 2:' Compounds .................... 5 15 . e ..& ! able 5 4 Spiked Target. Compounds for the FY86 NHATS, $:. .  withSpiking Levels .............. 5 21 ' 1 .

le 5 5 Summary of ( Surrogate Adjusted) QC Data for the FY86 " HATS Spiked T'argetCompounds 5 23 ...%: Table5 6 Percent Recoveries for Spiked Target Compounds, as Determined ' fromTwo '\ I.;. 1.,*..' .... Calculation Methods ......... ..  5 29 C. ,'$* kz&& > I $ t~,$?.. #,

% i. i.',. X.. , Table 5 7 Means and Standard Errors of Surrogate z?.$. .: :

Adjusted Concentrations ( ns f Unspiked Target Compounds for QC Samples ( by Batch and Overall) ................. 5 31 able 5 8 Batch Analysis Results on Method Blanks and Control Samples for Compounds Detected in At Least 50% of Composites, Where the Compound Was Detected in the Method Blank ... 5 32

xi j. i , . '. , ..> I I, . I LIST OF TABLES ( cont.)

Pase Table 5 9 Regression Models Used to Analyze NHATS FY86 QC Data for Spiked Compounds ........ 5 34 Table 5 10 Estimated Batch Recoveries and Average Recovery for Spiked Compounds with Percent Detected At Least 50% ( Adjusted Data) ..... 5 37 Table 5 11 Tests for Significant Differences in Batch Slopes Among Selected Batches for Spiked Target Compounds .......... 5 39 Table 5 12 Predicted Concentrations and Coefficients of Variation at Each Spike Level for Spiked Target Compounds Analyzed by the Batch Slopes Model .............. 5 40 Table 5 13 Estimated Batch Background Levels and Average Background Level for the Two Methods of Reporting p, p DDE Concentrations, as Estimated by the Batch Intercepts Model .... 5 44 Table 5 14 Results of Statistical Analysis of QC Data on Unspiked Target Compounds ......... 5 46 Table 5 15 Predicted Concentrations and Coefficients of Variation for Unspiked Target Compounds at the Control Level ............. 5 47 Table 6 1 " ATS Analysis Factors and Categories ...... 6 3 Table 7 1 Descriptive Statistics of NHATS FY86 Semivolatile Compound Concentrations Based on All 50 Composite Samples ........ 7 3 Table 7 2 Estimates of Average Concentrations for Selected Semivolatiles, with Standard Errors and Approximate 95% Confidence Intervals, According to Census Region from " ATS FY86 Composite Samples ............... 7 10 Table 7 3 Estimates of Average Concentrations for Selected Semivolatiles, with Standard Errors and Approximate 95% Confidence Intervals, According to Age Group from NHATS FY86 Composite Samples ............... 7 14 xii BEST COPY AVAILABLE LIST OF TABLES ( cont.)

Volume I 4cont. L Pase ' 4 Estimates of Average Concentrations for Selected Semivolatiles, with Standard Errors and Approximate 95% Confidence Intervals, According to Race Group from " ATS FY86 Composite Samples ............. 7 17 I 5 Estimates of Average Concentrations for Selected Semivolatiles, with Standard Errors and Approximate 95% Confidence Intervals, According to Sex Group from " ATS FY86Composite Samples ............. 7 20  6 Estimates of Average Concentrations for and Approximate 95% Confidence Intervals, for the Nation from NHATS FY86Composite Samples ............. 7 23  7 Chlorobiphenyl Distribution Across the Five Target PCB Homologs in the FY86 " ATS ........ ; ....... 7 26  8 Significance Levels from Hypothesis Tests for Differences Between Demographic Groups for " ATS FY86 Semivolatiles ....... 7 28  9 Measured Concentrations with High Influence on Determining the Additive Model Fit ... 7 34 Selected Semivolatiles, with Standard Errors  10 R Squared Correlation Between Observed Concentrations and Concentrations Predicted by the Additive Model for NHATS FY86 Semivolatiles ............... 7 36  1 Number of Specimens and Composites Within the FY82, FY84, and FY86 " ATS According to MSA .................. . 8 3  2 Total Number of Specimens Included in Composite Samples Analyzed in the FY82, FY84, and FY86 " ATS, by Subpopulation and Across the Entire Study .......... . 8 4  3 Total Number of Composite Samples Analyzed in the FY82, FY84, and FY86 " ATS, by Subpopulation and Across the Entire Study . 8 5 xiii LIST OF TABLES ( cont.)

Table 8 4 Table .8 5 Table 8 6 \

Table 8 7 Table 8 8 Table 8 9 Table 8 10 Table 8 11 Appendix A: Volume I tcont. 1 Semivolatile Compounds Quantitated Using the Same Internal Quantitation Standards ( IQS) in NHATS FY84 and FY86 .........

Semivolatile Compounds Quantitated Using Different Internal Quantitation Standards ( IQS) in NHATS FY84 and FY86 .........

Average Lipid Adjusted Limit of Detection ( LOD, ng/ g) and Percent of Composites with Detected Concentrations, for Compounds Analyzed in the M86 NHATS and Also Analyzed in the FY82 and/ or FY84 mTS ............

Weighted National Averages of Unadjusted Concentrations ( ng/ g) and Standard Errors for Compounds Analyzed in the FY86 " ATS and Also Analyzed in the FY82 and/ or FY84 NHATS . .

Weighted National Averages of Surrogate Adjusted Concentrations ( ng/ g) and Standard Errors for Compounds Analyzed in the FY86 NHATS and Also Analyzed in the FY82 and/ or FY84 NKATS ............

Comparisons of Predicted National Average Concentrations ( ng/ g) for Selected Semivolatiles over the FY82, FY84, and FY86 NHATS ..................

Chlorobiphenyl Distribution Across the Five PCB Homologs Considered for Statistical Analysis in the FY86 NHATS ..........

Significance Levels from Hypothesis Tests for Differences Between Demographic Groups for Selected Semivolatiles in the FY82, FY84, and FY86 NHATS .............

Volume I1 Listing of NHATS FY86 Composite Data Pase . 8 8 . 8 9 8 11 8 20 8 23 8 30 8 32 8 35 xiv . .....    LIST OF TABLES ( cont.)

Volume I1 ( cent.)

Listing of " ATS FY86 QC Data For Compounds Detected in At Least 50% of Composites ( plus Octachlorobiphenyl1 Summary of QC Data for the FY86 NHATS Spiked Semivolatile Compounds Not on the Target List for Statistical Analysis Characterizing the Distribution of NHATS FY86 Semivolatile Compound Concentrations ( in ng/ g, Unadjusted for Surrogate Recoveries) Based on All 50 Composite Samples Arithmetic Averages ( and Standard Errors) of Extractable Lipid Concentrations ( ng/ g) for Compounds Analyzed in the FY86 NHATS and Also Analyzed in the FY82 and/ or FY84 NHATS Comparisons of Predicted Average Concentrations ( ng/ g) by Selected Subpopulations for Selected Semivolatiles over the FY82, FY84, and FY86 " ATS LIST OF FIGURES Volume I Pase Flot Scheme for Analysis of S mi rolatile Compounds in the FY86 NHATS . . . . . . . . . .4 2 Volume 11 Plots of Observed vs. Spiked Concentrations for Spiked Semivolatile Compounds Detected in At Least 50% of Composites ( plus Octachlorobiphenyl). Plots of Observed Concentration vs. Batch ID for Unspiked Semivolatile Compounds Detected in At Least 50% of Composites Estimates of Average Concentrations with 95% Confidence Intervals As Determined by the Additive Model, for Selected Subpopulations in the FY86 NHATS . .. . . .. ... I, I LIST OF FIGURES ( cat.)

Volume I1 ( cont.)

Appendix G Concentrations ( ng/ g) from the FY82, FY84, and EY86 " ATS, Plotted in Chronological Order with Age Group as the Plotting Symbol Appendix H Surrogate Adjusted Concentrations ( ng/ g) N82, FY84, and FY86 " ATS, Plotted in Chronological Order with Age Group as t Symbol Appendix K Plots of Estimates Average Concentratio Census Region and by Age Group, Plus and Min3. s' Two Standard Errors, Based on the Additive the FY82, FY84, and FY86 " ATS mi . .__. . _ I_

. . I RdMARY National Human Monitoring Program ( NHMP), operated bited States Environmental Protection Agency's Office of * I [ on prevention and Toxics ( USEPA/ OPPT), is a national monitor the human body burden of selected chemicals. $& A & nal Human Adipose Tissue Survey ( NHATS), one component p, was performed annually to collect and analyze a & de sample of adipose tissue specimens from autopsied : a and surgical patients. The purpose of the NHATS was to kfy and quantify the prevalence and levels of selected : ais in human adipose tissue. The analysis results were o establish an exposure based chemicals list, to estimate Lne body burden levels for selected chemicals, and to ! F terize trends in these levels within predefined demographic . The " ATS was intended to fulfill the human and ronmental monitoring mandates of the Toxic Substances Control KC.

fandthe Federal Insecticide,' Fungicide, and Rodenticide Act, $

The EPA/ OPPT earmarked the FY86 NHATS tissue repository r the analysis of semivolatile compounds using HRGC/ MS methods. & NHATS study design was similar to those used in the FY82 i FY84 " HATS, where HRGC/ MS analyses of semivolatile compounds F ? re also performed. This report presents the objectives, ethodology, and results of the FY86 " HATS, and a comparison of SUlts with the FY82 and FY84 " ATS.

The specific objectives of the FY86 NHATS analysis were L~' X*' CF.. W Determine the extent to which semivolatile organic: ir'

,.... >, .+ 2'. . ..? compounds are present in human adipose tissue samples, I.. i..? i xvii Estimate the average concentrations of semivolatiles in the adipose tissue of humans in the U. S. population and in its various subpopulations,

Determine if any key demographic factors ( geographic region, age, race, and sex) are associat'ed with the average'concentrations of semivolatiles in human adipose tissue, and Compare the estimated average concentration levels of semivolatiles in the FY86 NHATS with estimates from the FY82 and FY84 NHATS, when similar techniques were used to estimate the same semivolatiles.

APPROACH One hundred and eleven ( 111) qualitative and quantitative semivolatile organic compounds were targeted in the chemical analysis of human adipose tissue samples in the FY86 NHATS. For compounds with sufficient detection percentages, measured concentration data were statistically analyzed to estimate average concentration levels in the U. S. population and to determine if any of four demographic factors of interest ( geographic region, age, race, and sex) were associated with the average concentration levels. Statistical analysis was also used to compare average concentration. levelsfound in the FY82, FY84, and FY86 NHATS for selected compounds. The analytical samples in the FY82, FY84, and FY86 NHATS were composites of individual patient specimens. Compositing criteria were established to achieve the study objectives of estimating and comparing average concentrations in selected subpopulations, while reducing the number of samples to analyze. The criteria specified that composites should only be created using specimens from donors in the same age group and from the same U. S. Census division. This ensured makimum precision for estimating differences in body burden levels among populations from different geographic regions and age groups. A total of 50 composite samples were analyzed in the FY86 NHATS. These samples were prepared from 671 individual xviii i I, i 1 lected from selected metropolitan statistical areas 48 conterminous United States.

mivolatiles targeted for analysis, 23 were ds ad their detection percentages among the FY86 e samples are listed in Table ES 1. For rposes, this table also includes the detection or these compounds among the FY82 and FY84 " ATS les. Seventeen ( 17) of the compounds in Table ES 1for statistical analysis of measured concentration. s entration estimates for the five PCB homologs Table ES 1 ( tetra, penta, hexa, hepta, and octal were consolidated to characterize overall PCB he following additional PCB parameters were tal concentration of PCBs ( sum of the estimated mologs. However, since each omitted homolog was a1 average concentrations in human adipose tissue for

  i Table 135 1. Sedvolatile Compounds Detected in at Least 44% of the FY86 NIZATS Composite Samples P Compound .

P'P DDE PtP DDT Heptachlor epoxide Beta BHC Trans nonachlor Oxychlordane Dieldrin(') CAS Number Pesticides 72 55 9 50 29 3 1024 57 3 319 85 7 39765 80 5 26880 48 8 60 57 1 Chlorobenzenes Hexachlorobenzene 118 74 1 1,4 Dichlorobenzene _ 106 46 7 PAH8 Naphthalene 91 20 3 PCBS Hexachlorobiphenyl . . 26601 64 9 Pentachlorobiphenyl 25429 29 2 Heptachlorobiphenyl 28655 71 2 . I Detection Percentage 4 FY82 FY84 FY86 100% 96% 100% 68% 89% 96% 708 80% 94% 93% 89% 92% 57% 96% 92% 83% 78% 33% 39% 62%

719% 83% 98% 86%

42% 24% 84%

75% 98% 94% 73% 85% 88% 52% 84% 86% Tetrachlorobiphenyl 26914 33 0 55% 41% 66% Octachlorobiphenyl 31472 83 0 41% 18% 44%

Phthalate Esters Bis ( 2 ethylhexyl) phtha1ate( 2) 177 81 7 0% 78% Di n butyl phtha1atet2) 84 74 2 50% 100% ' 76% Butyl benzyl phthalate( 2? 85 68 7 74% 62% 72% 96% 80%

72%

xxi Table ES 2. Estimates of National Averag Selected Semivolatiles, With ce Intervals, frum the PY86 aTS PIP DDT PIP DDE Beta BHC Heptachlor epoxide Oxychlordane Trans nonachlor Dieldrin l14 DichlorobenZene Hexachlorobenzene Naphthalene Tetrachlorobiphenyl Pentachlorobiphenyl Hexachlorobiphenyl Heptachlorobiphenyl Octachlorobiphenyl Total PCBs(') Estimated Pesticides 177. 2340. 157. 57.6 114. 130. 47.0 Chlorobenzene6 90.9 51.3 20.7 PCBa 56.4 135. 314. 125. 42.7 672.

Level of Chlorination(*) 58.3%

Other ( Qualitative)

1 Nonene 124. Hexyl acetate 123. ( 137, 217.) ( 179? 3, 2880.) ( 137, 207.) ( 43 2, 66.1) ( 33 4, 129.) ( 43.6, 161.) ( 3 Of 63.1)

( 6Q. 2, 122.) ( 43 3, 59.3)

( 15 9, 25.4)

( 46.9, 65.9) ( 104, 165.) ( 276., 351.) ( 80.7, 169.) ( 19 3, 66.1)

( 603 742.) ( 51.2, 65.4)

( 20.6, 227.) ( 79.5, 166.) over t. he at lea. st in xxiii the 17 compounds included in the statistical analysis. Approximate 95% confidence intervals are included in this table for each national average. Relative standard errors of these estimates ranged from 5.9% for hexachlorobiphenyl to 27.1% for octachlorobiphenyl.

Acre Group Effect8 The effect of age group on average concentration for the 17 compounds in Table ES 2 was statistically significant for six of the seven pesticides ( all except dieldrin), five PCB homologs, and hexachlorobenzene. In each case, the average concentration increased with the age of the donor. Among the PCB homologs, the average concentration for the 45+ age group was from 188% ( pentachlorobiphenyl) to 706% ( heptachlorobiphenyl) above the average for the 0 14 age group ( an increase from 75.6 to 218 ng/ g for pentachlorobiphenyl, and from 26.9 to 217 ng/ g for heptachlorobiphenyl). Similar percent increases were observed with the pesticides. For example, average concentration of p, p DDT was 73 ng/ g for the 0 14age group and 252 ng/ g for the 45+

age group  a 245% increase.

Geocrraphic Effects Statistically significant differences in average concentration for the 17 compounds in Table ES 2 were observed between census regions for p, p DDT, p, p DDE, heptachlor epoxide, hexachlorobenzene, naphthalene, and three of the five PCB homologs. Average concentration of p, p DDT and the PCBs were highest in the northeast. Heptachlor epoxide was highest in the south, and hexachlorobenzene was highest in the west. Similar I such patterns were observed in the FY82 and FY84 NKATS.

; I Race and Sex Grourm The differences in estimated average concentrations between race groups ( whitevs. nonwhite) and between sex groups xxiv ( male vs. female) were not statistically significant for any of the 17 modeled compounds.

Y OF THE COMPARISON WITH FY82 AND  84 " ATS RESULTS Fifty four ( 54) of the 111 semivolatiles analyzed in the 86 " ATS were also analyzed in either one or both of the FY82 or FY84 " ATS. Of these 54 compounds, twelve were detected in at least 50% of the samples in each of the FY82, EY84, and FY86 surveys. Statistical comparison of average concentration across surveys was performed on ten of these twelve compounds ( butyl benzyl phthalate and di n butylphthalate were excluded from statistical analysis based on FY86 QC data analysis findings). The estimated national average concentrations within each survey for these ten compounds, along with approximate 95% confidence intervals, are listed in Table ES 3. Statistical analysis results are also included in Table ES 3 to identify those compounds whose results for FY82 and FY84 differ significantly from FY86. For the four PCB homologs considered in the statistical comparison, the FY86 average concentration was from 48% to 259%

higher than the FY82 average concentration. The differences in these averages for tetra, penta, and hexa chlorobiphenyl were statistically significant between these two surveys. The observed differences in average concentration for PCB homologs. between FY84 and FY86 were less apparent; the only statistically significant difference was a 58% increase from FY84 to FY86 in average concentration for hexachlorobiphenyl. Total PCBs in FY82 and FY84 differed significantly from FY86 results, due to the larger national average noted in FY86.

Fewer incidents of significant differences between surveys were apparent among the five pesticides. For p, p DDT and Plp DDE, differences of 43% and 101%, respectively, between the FY84 and FY86 average concentrations were statistically sigqificant. Both differences were increases over the FY84 average. Meanwhile, the only pesticide with a significant xxv _. Table ES 3. Estimates of National Average Concentrations for Selected Semivolatiles, With 95% Confidence Intervals, from the FY82, FY84, and FY86 " ATS Compound Beta BHC Trans nonachlor Heptachlor epoxide Hexach1orobenzen. e Tetrachlorobiphenyl Pentachlorobiphenyl Hexachlorobiphenyl : i, Estimated , 95% Avg. Conc. Confidence " ATS ( ng/ g) Interval Pesticides FY82 189. ( 125., 253.) FY84' 123: ( 102., 145.) FY86 177. ( 137., 217.)

FY82 1840. , ( 1130., 2550.) FY84 1150. ( 968., ' 1330.) FY86 2340. ( 1790.~ 2880.1 FY82 291. ( 183., 400.) FY84 199. ( 150., 248.) FY86 157. ( 107., 207.)

FY82 109. [ 53.0, 165.) FY84 105.. I 94.4, 115.) FY86 130. ( 99.6, 161.)

FY82 59.4 ( 32.2, 86.5) FY84 68.3 ( 53.9, 82.6) FY86 57.6 ( 49.2, 66.11 Chlorobenzenes FY82 118. { 1.0, 256.) FY84 42.9 ( 31.9, 53.9) FY86 51.3 ( 43.3, 59.3)

PCBs FY82 15.7 ( 12.8, 18.6) FY84 FY86 48.8 56.4 ( 36.8, 60.8) ( 46.9, 65.9)

FY82 78.3 ( 62.3, 94.4) FY84 FY86 115. 135. ( 92.8, 137.) ( 104., 165.)

FY82 FY84 FY86 176. 198. 314. ( 119., 233.) ( 177., 220.) ( 276., 351.) Diff. From FY86 12.1  53.4"

 498.  1190.*

135.* 42.3  21.3  25.8 1.73 10.6 66.9  8.38  40.7"  7.60  56.2"  19.8  137.*  115.* Estimated 95% Diff. Avg. Conc. Confidence From Compound " ATS ( ng/ g) Interval ' FY86 PCBs ( cost.)

Heptachlorobiphenyl FY82 84.6 ( 50.1, 119.)  40.5 . FY84  129. ( 107., 149.) 3.51 FY86 125: ( 80.7, 169.)

Total PCBs(') FY82 407. ( 337. , 476.)  266.* FY84 508. ( 469. , 547.) ' 164.* FY86 672. ( 603. , 742.)

Chlorination Level@) M82 59.3% ( 47.7, 71.0). 1.0 FY84 58.1% ( 53.1, 63.1)  0.2 FY86 58.3% ( 51.2, 65.4)

* Significantly different from zero at the 0.05 level. (' 1 Sum of concentrations for tetra to octa chlorobiphenyl. ( 2) Overall chlorination level for Pas, defined in Section <IP_ADDRESS>.

xxvii I,

difference in average concentration between the Fy82 and FY86 NHATS was beta BHC; this difference was a 46% decrease from the FY82 estimate. When interpreting the observed differences in the average concentration levels between the FY86   ATS and both the FY82 and FY84 NHATS, it is important to consider differences in analytical approach. For example, differences in the internalquantitation standards used, the recovery levels observed, the analytical laboratories, and improvements made in the analytical method over time all may contribute substantially to observed differences between surveys. Additional surveys under the current analytical approach ( HRGC/ MS on composite samples) covering a longer time period are needed to more accurately characterize and interpret trends in average concentration levels of semivolatiles. As has been done in the past, the designs and analysis methods for these surveys should be established to meet the objective of comparing results across surveys, while minimizing any nuisance effects contributing to the comparisons. 1.0. INTRODUCTION 1.1. BACKGROUND The National Human Adipose Tissue Survey ( NHATS) has been the main operative program of EPA's National Human Monitoring Program ( NHMP). The " HATS program has collected and analyzed human adipose tissue samples on an annual basis to monitor human exposure to potentially toxic compounds. The " MP/ NHATS was established by the'U. S. Public Health Service in 1967 and transferred to the EPA in 1970. Since 1981, the EPA Office of Pollution Prevention and Toxics ( EPA/ OPPT) has been responsible for the " MP/" ATS. The NwlTS intended to fulfill the human and environmental monitoring mandates of the Toxic Substances Control Act and the Federal Insecticide, Fungicide, and Rodenticide Act, as amended. Adipose tissue specimens were collected annually for the " ATS by cooperating pathologists and medical examiners during routine post mortem examinations or elective surgeries, These cooperators were selected from a statistical sample of Metropolitan Statistical Areas ( MSAs) within the 48 conterminous United States. Target quotas specifying the number of specimens within each donor age, race, and sex classification were established for each collection center. Sampling plans were designed for each annual survey to produce statistically unbiased and precise estimates of the levels and prevalence of compounds in the U. S. population and in various demographic subpopulations. In the 1970s and early 1980s, the " HATS program characterized the prevalence and levels of 19 organochlorine pesticides and polychlorobiphenyls ( PCBS) in individual human adipose tissue specimens, using packed column gas chromatography/ electron capture detection ( PGC/ ECD) methods. Recognizing the need to extend the capabilities of the " ATS program, the EPA/ OPPT initiated a series of programs in 1984 to expand the utility of the tissue repository. In order to expand the list of target compounds monitored by " ATS a change to high resolution 1 1 c :;

ij i gas chromatography/ mass spectrometry ( HRGC/ MS) methods was made. Individual specimens were composited prior to HRGC/ MS analysis to optimize the amount of data which could be generated. Analysis on composite samples rather than individual patient samples necessitated a modified statistical analysis approach to obtain national and subpopulation estimates at an individual level. The first study in the " ATS program which utilized the expanded capabilities of the HRGC/ MS methodology was the " Broad Scan Analysis Study" ( Mack and Panebianco, 1986). The FY82 NHATS specimen repository was selected for this study. The target chemicals considered in this broad scan study included 30 semivolatile compounds, 17 volatile organic compounds, and 11 polychlorinated dibenzo para dioxins ( PCDDs) and polychlorinated dibenzo furans ( PCDFs). The broad scan study demonstrated that 13 of these semivolatile compounds, 11 of the volatile compounds, and nine of the dioxins and furans were detected in at least half of the composite samples. Estimated average levels for some semivolatiles increased significantly with age, while the South and Northeast census regions tended to have higher levels than the West and North Central regions. The FY84 " ATS specimen repository was used in conducting a comparability study between the PGC/ ECD and HRGC/ MS analytical methods ( Westat, 1990). Paired composite samples were analyzed using both methods. A total of 58 semivolatile compounds were analyzed by HRGC/ MS, of which 14 were detected in at least 50% of the samples. The results of the comparability study indicated that the PGC/ ECD method was generally more #

sensitive than the HRGC/ MS method in measuring concentrations for a variety of lipophilic compounds, with the opposite holding true for PCBs. Method comparability issues have yet to be resolved for many of the target semivolatile compounds. The goal of the study performed on the N  ATS FY86 specimen repository was to estimate baseline body burden levels of semivolatile organic compounds, and to characterize trends in these levels within predefined demographic groups ( census region,

1 2 c " ba3Q. t region, age, race, and sex classification) are concentration levels of semivolatiles the NHATS   ... .' I/ I I age group, sex, and race). HRGC/ MS methods were employed so that ~ y86results could be compared to FY82 and FY84 results. A total of 111 semivolatile compounds were analyzed in the FY86 " ATS.

This report presents the results of the FY86 " ATS analysis on semivolatiles, along with the comparison to results from the FY82 and FY84 " ATS.

1.2. OBJECTIVES The specific objectives of the FY86 " ATS and analysis rn Determine the extent to which semivolatile organic compounds are present in human adipose tissue samples,

rn Estimate the average concentrations of semivolatiles in the adipose tissue of humans in the U. S. population and in its various subpopulations,

rn Determine if any key demographic factors ( geographic 4 ~

 J.=. J ==

associated with the average concentrations of semivolatiles in human adipose tissue, and Compare the prevalence and estimated average in tiie FY86 NHATS with that from the FY82 and FY84 " ATS, where similar sampling and analytical techniques were used.

he results of this study will contribute to EPA's knowledge base n the prevalence and concentration levels of semivolatiles in an adipose tissue samples. Statistical analysis will etermine the extent to which concentrations of these compounds e changing over a six year time frame in the 1980s, relative to alytical effects and trends.

REPORT ORGANIZATION Volume I of this report presents the methods, results, Conclusions of the statistical analysis conducted on the FY86 S adipose tissue sample data. While discussions on sample n, composite design, and chemistry methods are also included 1 3 in this report, these subjects are more fully addressed in other references ( see Chapter 9).

Battelle developed the sample design and composite design for the FY86 NHATS. The sample and composite designs are highlighted in Chapters 2 and 3, respectively. Chapter 4 discusses the chemistry procedures that Midwest Research Institute ( MRI) used to analyze the FY86 composite and QC samples. Included in this chapter are discussions of overall data quality, analytical procedures, and QA/ QC procedures. FY86 data issues and other pre statistical analysis results are presented in Chapter 5. Detection status of the 111 semivolatile compounds are presented, along with data issues found to be unique to the FY86 analysis approach. For example, methods were developed in this effort to adjust measured concentrations for surrogate recoveries in order to more accurately estimate actual sample concentrations. The results of statistical analysis on QC sample data are presented in Chapter 5; these results characterize measurement error, recoveries, background levels, and the presence of batch effects. Chapter 6 contains a discussion of the statistical methodologies used by Batteile in estimating average concentration levels ana. associatedstandard errors for target compounds. The results of applying these statistical methodologies to the FY96 " ATS data are presented in Chapter 7. Finally, Chapter 8 presents the results of comparing FY86 " ATS results with those from the FY82 and FY84 " ATS for the same compounds. Supporting information on individual sample, data, including data listings and plots, data summary statistics, QC data plots, and graphical display of the estimated average concentrations with associated levels of uncertainty, is included as appendices. These appendices constitute Volume I1 of this document.

1 4 2.0 NHATS FY86 SAMPLE DESIGN The human adipose tissue specimens in the FY86 " ATS repository were collected from October, 1985, through September, 1986. The method in which these specimens were supplied to the ~. J" ATSprogram follows the " HATS Sampling Design. In each year of the NHATS program, cooperators ( hospital pathologists or medical examiners) collected approximately 700 1200 adipose tissue specimens. Although the NHATS target population is the general, noninstitutionalized U. S. population, the sampling population was limited to cadavers and surgical patients due to the invasive nature of the process required to collect the adipose specimens from living persons. Section 2.1 discusses the " ATS Sampling Design and its multistage characteristics. Methods used to collect specimens are discussed in Section 2.2. Finally, a summary of the types of specimens collected in the M86 " ATS is presented in Section . I SAMPLING DESIGN The NHATS program used a multistaged sampling design to tain adipose tissue specimens from autopsied cadavers and rgical patients throughout the United States. The NHATS c mpling Design consisted of three components:

The 48 conterminous states were stratified into distinct geographical areas.

A sample of Metropolitan Statistical Areas ( MSAs) was selected within the strata. The probability of selecting an MSA was proportional to its population percentage within the stratum.

One or more cooperators were chosen from each MSA and asked to supply a specified quota of tissue specimens to the NHATS. To maintain similarity in the sampling designs across fiscal years, the same MSAs and cooperators were retained from year to year to the extent possible.

2 1 As part of the third component of the " ATS Sampling Design, the manner in which cooperators selected the donors and tissue specimens was nonprobabilistic, but followed a specific set of criteria. Quotas and subquotas for the number of specimens supplied to the " ATS were assigned to each cooperator. The subquotas determined the desired number of specimens coming from particular combinations of donor age group, race, and sex. Demographic categories in which subquotas were defined are presented in Table 2 1. The subquotas were proportional to the 1980 U. S. Census population counts for each sampling stratum.

Table 2 1. Demographic Categories in Which Subquotas Were Established for Collecting Adipose Tissue Specimens Age group 0 14years 15 44years 45+ years Race group Caucasian Non Caucasian Sex group Female Male I Because the survey required some divergence from strict probabilistic sampling, the validity of the statistical estimates derived from the data depended on several assumptions:

m The concentrations of toxic substances in the adipose tissue of cadavers and surgical patients are assumed to be comparable to those in the general population.

W The levels of toxic substances in urban residents are approximately the same as in rural residents, and thus the selection of only urban hospitals and medical examiners ( i. e., those located in MSAs) does not introduce any significant bias into the estimates of average concentration levels.

2 2 rn No systematic bias is introduced by the fact that the cooperators are not randomly selected and that the donors and specimens are nonprobabilistically sampled according to pre specified quotas.

Further discussion of the three components of the NHATS Sampling Design follow.

Prior to 1985, the sampling strata from which MSAs were randomly selected were the nine U. S. Census divisions. But in 9 1985, EPA wanted the ability to obtain estimates of average \+

$ concentration levels in each of the ten EPA regions. Thus, beginning with the FY85 NHATS, the sampling strata were redefined as seventeen geographic areas of the country, resulting from the & &';$?:;; ,..,~ li.. Lt.. ll >$@ F: i ntmvaert ion of t. he nine census' divisions and the ten EPA regions. Selecting the sample under this new stratification scheme made it possible to make comparisons with previous " ATS results and also obtain estimates for the EPA regions. The states, census divisions, and EPA regions that define the seventeen strata are shown in Table 2 2.

Although the FY86 NHATS sampling design specified that specimens be collected across the seventeen strata, it was not possible to create composites so that all specimens within a composite came from the same stratum. However, the Composite Design assured that each composite contained specimens orisinatinq from the same census division and age group. This ii was done to ensure that the FY86 and FY82 analysis results Could be compared. Chapter 3 discusses the Composite Design in greater P . detail.

9:. isampling . f plan. Cooperators were recruited from each selected MSA '; f ;,. h & provide tissue samples for the NHATS. :

2 3 Table 2 2. Sampling Strata Definitions for the " ATS Texas 10 West North 7 Iowa Central Missouri Nebraska Kansas 11 West North a North Dakota Central South Dakota Table 2 2. ( cont.)

12 Mountain 8 Montana Wyoming Colorado Utah 13 Mountain 9 Arizona Nevada 14 Pacific 9 California 15 Mountain 10 Idaho 16 Pacific 10 Washington Oregon 17 Mountain 6 New Mexico 2 5 . Once the seventeen sampling strata were identified for the FY85 " ATS, a sample of MSAs was selected using a controlled selection technique, known as the Keyfitz technique ( Kish and Scott, 1971). This sample differed from those'MSAsselected prior to the FY85 " HATS. However, the Keyfitz technique maximized the probability of retaining previously selected MSAS, thus allowing to continue employing existing cooperators ( Mack, et. al., 1984). The MSA sample selected in FY85 served as the base " ATS sample for FY86 through FY91.

The FY86 " HATS sampling design contained 46 MSAs, of which two ( St. Louis and Moline) were each split into two primary sampling units to reflect areas of the MSA falling into different sampling strata. All but one of the MSAs selected for the FY85 " HATS were used in the FY86 NHATS; the omitted MSA ( Medford OR) was replaced ( Eugene OR) because satisfactory cooperators could not be found. The sample MSAs for the FY86 NHATS are listed by stratum in Table 2 3. Four MSAs ( LosAngeles, Chicago, Detroit, and New York) were listed as double collection sites because their populations were much larger than other MSAs within their strata. Strata 13, 15, and 17 had no MSAs selected due to their small population sizes.

2 1 3 SDecimen Collection Quotas Pre assigned quotas determined the numbers of specimens selected within each sample MSA. In addition, demographic subquotas were assigned to each MSA to ensure that the specimens collected were representative of the strata with respect to the three demographic factors in Table 2 1 ( age group, race group, and sex group). The subquota assigned to each MSA was determined proportionally represented, but the subquota did not specify that . Table2 3. Sample MSAa Selected for the FY86 " ATS 1 New England 2 Middle Atlantic 3 Middle Atlantic 4 South Atlantic 5 South Atlantic 6 East South Central 7 East North Central 8 West North Central 9 West South Central 10 West North Central, 1 Springfield, MA Boston, MA 2 Albany, NY New York, Id) Binghamton/ Elmira, NY Newark, NJ 3 3 4 4 5 5 6 Philadelphia, PA Pittsburgh, PA Erie, PA Washington, DC Norfolk, VA Tampa, FL Greenville, SC Orlando, FL West Palm Beach/ Boca Raton, FL Miami, FL Atlanta, GA Memphis, TN( 2) Birmingham, AL Lexington, KY Dayton, OH Detroit, MI(') Columbus, OH Cleveland, OH Akron, OH Chicago, IL(') Madison, WI Moline, ILt2)

Rochester, MN El Paso, TX Lubbock, TX Houston, TX San Antonio, TX Dallas, TX Omaha, NE St. Louis. MO(~) Table 2 3. ( cont.)

11 West North Central 12 Mountain 14 Pacific 16 Pacific 8 8 9 10 I I I * " * h (*) Indicates a double collection site. A double collection site is an MSA whose population relative to its stratum is so large that its proper representation in the sample requires it to be selected twice.

Indicates a split MSA. A split MSA is one which covers more than one stratum. Only the portion of the stratum in which the MSA is listed is represented in the sample.

@) Indicates a replacement MSA. A replacement MSA is an MSA that was not selected in the FY8S probability sample, but was chosen to replace an FY8S sample MSA for which a satisfactory cooperator could not be found. Sioux Falls, SD Salt Lake City, UT Denver, CO San Francisco, CA Sacramento, CA LOS Angeles, a(') Portland, OR Spokane, WA Eugene, OR( 3) Yakima, WA 2 8 represented within each combination of age group and sex, The subquotas only specified the total nut& er of Caucasian and non Caucasian specimens to be collected from each MSA. The subquotas for the seventeen sampling strata for the FY86 sample design are presented in Table 2 4. Each MSA had a quota of twenty seven specimens, except for the four MSAs that were designated as double collection MSAs. In those MSAs, the quotas and subquotas were doubled. Cooperators within an MSA were assigned quotas and subquotas appropriate to that. MSA. The total number of samples specified for the FY86 NHATS was 1404. This was based on the quota of twenty seven specimens for each of the forty eight MSAs, plus twenty seven additional specimens for each of th. e four MSAs designated as double collection MSAs.

2.2 SAMPLE COLLECTION PROCEDURES NHATS specimens were adipose tissue samples excised by pathologists and medical examiners during therapeutic or elective surgery or during postmortem examinations. If the specimen was Collected postmortem, the tissue was obtained from an unembalmed cadaver which had been dead for less than twenty four hours and had been kept under refrigeration during that time. The death should have been caused by sudden traumatic injury, such as cardiac arrest, car accident, or gunshot wound. The following groups were excluded from specimen collection:

institutionalized individuals;

persons known to be occupationally exposed to toxic chemicals;

persons who died of pesticide poisoning; and persons suffering from cachexia.

2 9 Table 2 4. FY86 Age and Sex Subquotaa, and the Race Subquota, for Each NHATS Collection Site Within Each Stratum New England 1 2 3 3 6645 Middle Atlantic 2 5 33 6645 I Middle ' Atlantic I 3 3 3 3 6645 I South Atlantic 3 6 3 3 6744 South Atlantic 4 6 3 3 6645 East South Central East North Central West North Central West South Central West North Central West North Central Mountain Mountain Pacific Mountain Pacific Mountain 4 5 3 3 6645 5 4 3 3 6645 5 1 3 3 6645 3 6 6 4 4 I I 7 2 3 3 6 6 4 5 ' 8 2 3 3 6 6 4 5 a 2 3 3 9 4 3 3 6 6 4 5 9 7 3 3 6 7 4 4 10 1 4 4 6 6 3 4 10 2 3 3 7 7 3 4 6 7 4 3 For each stratum, the six subquotas across age and sex groups add to 27, the total quota for each selected MSA from the stratum. The non Caucasian I.

subquota represents the number of specimens out of 27 corresponding to non Caucasian donors.

2 10 These guidelines were stipulated so that the levels of substances detected in the specimens were a result of environmental exposure. ..

Instructions for the cooperators stipulated that at least five grams of tissue be obtained from each donor. In addition, the cooperators were to avoid contamination through contact with disinfectants, paraffins, plastics, preservatives, and solvents. Cooperators placed the collected specimens in glass jars with Teflon@ lids and stored them at  loo to  200 C. The jars were packed on dry ice for overnight shipment to mI, the contractor responsible for tissue storage. MRI received the specimens and checked them for adequacy of shipping conditions and level of conformance with cooperator quota. MRI determined an approximate specimen weight and transferred the specimens to storage at  2OO C. Upon examining the patient summary reports, MRI forwarded the reports to Battelle for processing.

2.3 SPECIMEN COLLECTION SUMMARY In the FY86 NHATS, cooperators provided 739 specimens in 31 of the sample MSAs. In preliminary review of the specimens, 671 were collected in accordance with the quotas and subquotas. These specimens were labeled " Design1# specimens. The remaining specimens were labeled lfSurplusff specimens, as their collection as considered beyond the quotas and subquotas requested. The process of labeling specimens as Design or Surplus dlowed established guidelines ( Orban,. et. al., 1988). However, PA added a stipulation that the collection dates of Surplus Pecimens be uniformly distributed throughout the fiscal year.

SO, it was necessary to modify Surplus specimen assignment from e preliminary review, as one composite contained mostly low ight specimens. Surplus specimens were relabeled as Design cimens and added to this composite in order for the composite achieve sufficient tissue mass. Meanwhile, the same number of n specimens from another amply representedcomposite within ame census division were relabeled Surplus specimens and 2 11 Or.! g>@ q  4 1 removed from the composite. Thus the total number of Surplus specimens collected in FY86 did not change following this adjustment. The maximum nueer ofspecimens from a MSA remained I at the original quota of twenty seven ( or fifty four from a double collection MSA)

Table 2 5 is a summary of the collection effort for the FY86 " ATS, detailed by census division. In FY86, EPA chose not to make estimates for EPA regions. Instead, EPA maintained . similarity to the FY82 geographic classifications in order to compare FY86 results to FY82 results. All 671 Design specimens were placed into one of fifty composites, on which laboratory analysis was performed. Table 2 6 shows the number of quota specimens, collected specimens, and Design specimens in each of the four demographic subpopulations ( census region, age group, sex, and race) which act as analysis factors in the linear model. Because the number of samples in the chemical analysis was not large enough to obtain reliable estimates for all nine census divisions, Battelle combined the divisions into four census regions for the FY82; FY84, and FY86 model analyses.

2 12 i,

c E" 4 0 aJ a 0 3 # al 0 0 a  48 0 0 4 m 3"

~

2 13 Table 2 6. FY86 NHATS Specimen Collection Summary by Demographic Subpopulation Census Region Age Group Sex Group Race Group Northeast North Central 270 405 124 265 123 248 Sijuth 459 255 205 West 270 95 95 Total 1404 739 671 0 14 years 15 44 years 45+ years 317 642 445 115 248 376 108 221 342 Total 1404 739 671 Male 681 354 315 Female 723 385 356 Total 1404 739 671 White 1179 564 529 Nonwhite 225 175 142 ~~

k I Total 1 1404 I 739 I 671 ,

3.0 NHATS FY86 COMPOSITE DESIGN Battelle assigned the 671 Design specimens ' inthe Fy86 " ATS tissue repository to composite samples using specific composite design criteria ( Orban, et. al. 1988). The necessity for cornpositing samples prior to chemical analysis was to ensure that at least twenty grams of tissue were available per sample to meet the limit of detection goals for the target compounds. The Composite Design resulted in constructing 50 composite samples.

3.1 DESIGN GOALS COMPOSXTING CRITERIA listed I I I The five goals of the FY86 " ATS Composite Design, in order of importance, were to:

maintain similarity to the FY82 Composite Design,

maintain equal weighing of specimens within the composite samples,

specify additional numbers of pure sex composite samples than in FY82,

control the MSA effect, and provide the best range of race group percentages across the composite samples.

Because of the constraints imposed by the sampling and compositing protocols and the frequency of collection nonresponse, it was not always possible to meet all the design goals. Each of the above goals required a different mix of individual specimens within the composite samples. Thus, attempts were made to achieve all goals across the design to the extent possible. The five goals are discussed in detail below.

.. I Similaritv to the FY82 Composite Desisn EPA imposed this criterion to ensure that the results of FY86 data analysis could be compared with FY82 results, where Ompositing was performed and the same semivolatile compounds ere analyzed. The design criterion imposed by this objective is 3 1 that eaeh composite sample had to be constructed from individual specimens collected from exactly one census division and exactly one age group category. Thus there were 27 distinct categories within which composite samples were formed. Once the FY86 Composite Design was established, it was desired to compare results of data analysis on the FY86 samples with the results obtained from the HRGC/ MS analysis on FY84 composite samples. The FY84 Composite Design closely paralleled the FY82 Composite Design, allowing the FY86 results to be compared with the FY84 results as well as the FY82 results. Of primary importanae, the FY84 design stipulated that all specimens found in a given composite originate from the same age group and census division.

2. Euual weiuhincr of mecimens within the comnosite samDles This criterion is primarily for ease of interpretation. In attempting to make inferences on individual specimen concentrations, it is far easier to interpret the observed composite sample concentrations as the arithmetic average of the individual specimen concentrations. Therefore, this design goal specified that each individual specimen within a composite sample contribute an equal amount of tissue to the composite sample. This specification allows the lipid adjustedconcentration of the composite sample to be interpreted as approximately the arithmetic average of the lipid adjustedindividual specimen concentrations, with equality occurring whenever all specimens in the composite sample have the same percentage of lipid material. In the FY86 analysis, specimens were not labeled as Surplus as a result of specimen weight, nor was specimen weight used to determine whether the specimen would be included in a composite sample. The specimen weights were evaluated only after composites were defined based on the other design criteria. Composites with insufficient tissue mass  or chemical analysis were modified if practical alternatives were available. This 3 2 policy resulted in combining two initial composites and modifying an additional two composites. To ensure that equal weighing of specimens within the composite samples was maintained throughout the analysis, instructions for evaluating individual specimen weights were based on the ratio of the maximum weight to the minimum weight of all specimens within the composite sample. Any low weight specimens causing this ratio to exceed 3.0 was recommended for removal from the composite.

3. Construct more Dure sex comDosite samnles than in FF82 Pure sex composites ( composites containing specimens originating from either all male patients or all female patients) were constructed when sufficient numbers of specimens were available within a particular census division/ age group category and more than one composite sample was allocated to this category by the design. Pure sex composites were needed to achieve more precise estimates of sex effects in the population. This design strategy was in contrast to the FY82 Composite Design, which provided for more balanced sex composite samples ( samples with nearly half male and half female specimens). Including more pure sex composites in the FY86 design intended to reduce the standard errors for the sex group estimates from that observed for the FY82 analysis ( Draper and Smith, 1981, pp. 52 55).

4. Control the MSA effect Controlling the number of MSAs contributing specimens to composite samples was intended to reduce the effect of the MSA on the estimated average concentrations. This was done because MSAs are regarded as being major sources of differences in observed Concentrations across the nation due to their varied exposure Scenarios ( Panebianco, 1986). To avoid confounding the MSA L effect with any of the geographic or demographic effects, the , Composite Design stipulated:

CY P ( 3 05 I, " h I I 4a. to keep the number of MSAs represented in each composite sample consistent across the. design ( targeted at 2 3 MSAS), and 4b. to maintain approximately the same number of pure sex composite samples within a group of MSAs.

Criterion 4a helped to ensure a constant variance of measured concentrations across the sample whenever the composite sample concentrations are averages over an equal number of MSAs. Criterion 4b was intended to prevent confounding a large MSA effect with the sex effect,

5. Control the race urouD nercentaaes across the cornnosite samnles The benefits for constructing pure race group composite samples paralleled the benefits for constructing pure sex composite samples. However, achieving this design goal was dependent'on the number of non Caucasian specimens collected in the twenty seven census division/ age group categories and the number of composite samples in the design. At least one pure Caucasian composite sample and at least one pure non Caucasian composite sample were constructed in four different census division/ age group categories.

3.2 LABORATORY COMPOSITING PROCEDURES In the FY86 " ATS Composite Design, specimens from nine census divisions and three age groups were segregated into 50 composites. Battelle provided MRI with composite sample data sheets that identified the specific individual specimens to be included in each composite ( Appendix A of Orban, et. al., 1988).

A composite consisted of from three to twenty four specimens, The composite sample data sheets provided sufficient information ( EPA ID number, package number, sample weight, hospital code, etc.) such that the individual specimens could be cross checked with the study design. The data sheets were used as work sheets to record actual laboratory compositing procedures.

3.

.. Initially, the samples were grouped into composites, and any samples of insufficient weight (< 1.0 g) or potentially I contaminated samples were reported by MRI to the EPA Work Assignment Manager ( WAM). Such samples were omitted from the analysis The weights of composites included in laboratory analysis ranged from 1.884g to 22.514g, with three composites below the target weight of 20s. The composite with the lowest weight consisted of only three samples from the 0 14year age category. The other two composites below the target weight had insufficient samples. The composite samples were placed on dry ice during the compositing procedure. An electronic four place balance was used to weigh the samples, and the calibration of the balance was checked with a Class P set of weights ( laboratory grade, tolerance 1/ 25,000) before any weighing was begun and once during the sample weighings. To weigh the samples, a clean culture tube was labeled with the composite number. This tube was placed on the balance, and the weight was tared. A sample was removed from the composite bag, the jar opened, and a portion of the frozen adipose removed with a clean stainless steel spatula. The adipose was placed in the culture tube and the weight recorded to three decimal places on the compositing sheets. Additional adipose was added if necessary. A goal of 210% of the desired weight was attempted where possible. The weights of the individual specimens were recorded on the composite data sheets. The weight of the culture, beaker, and adipose tissue was rezeroed, and the next sample in the composite was weighed.

A new spatula was used between each sample. This procedure was repeated for each sample in the composite. When the composite was completed, it was capped and stored in a sample freezer at  loo C. All data on the actual compositing procedures ( amount . dde Id, remaining composite) weight, date inventoried, and total weight recorded on the data sheets provided by 3 5 Q* i"<": 3 02; 2 If t. he spec. were Battelfe. MRI submitted all data sheets in a separate report documenting the compositing activity ( MRI, 1988a).

^"

3.3 SUMMARY OF FY86 & HATS COMPOSXTB SAMPLES The FY86 " ATS Composite Design resulted in const 50 composite samples using 671 individual specimens collected from 31 MSAs. Composite samples were formed from specimens . collected exclusively from the same census division/ age group category. The numbers of composites within each of these categories are given in Table 3 1. Unlike the exclusivity by census division and age group, the composite samples had specimen percentages within sex and race groups which iraried across the design depending on the availability of specimens within specific demographic subpopulations. Table 3 2 shows the demographic makeup of the FY86 NHATS composite samples. The 50 composite samples were randomlyassigned to five laboratory batches of ten samples each. Within each batch, the ten comDosite samples and three lipid based QC samples were  placed in random order for chemical analysis.

3 6 Table 3 1. Distribution of FY86 NHATS Composite Samples by Census Division and Age Group Mountain 1 1 2 4 ,. Pacific 1 1 4 6 Total 10 16 I 24 50 ,._...., . . _.. ,_

3 7 ml o. Cn0 ..... dDmmam a3dDPa3lea300 dO. OOO .... ..... * moo eo000 em0 eo 0 rl rlrl a E: rd rl bl d w 3 mP* mPmorn OwaNlOmOm ........ rlrlorlrlrlrlrl ~ rn000000 ........ waoooooo dIn0 000 rl i lrlrl OOOdDOOOrn OOOd ........ .... ooomooorn OOOd 0 o* 0 m mo d( drl rl rl 3 8 ~ omoooooooo ........... a3omoooooooo woa3a30 0 000 d rl d ddd womoo* odow .......... 0 0 No~ oowoNoo mom omo* d dd * aOmoo ..... dP000 CnPQ\ OO dd moo00 ..... a30000 mo 0 dd A c, k Od za ' 2; k c, c, rnd g8 3 9 Ln  f 0000 .... om00 NO ri  4 PIrnaOOOC t ...... ( 6 WmmOOO at wQ) Q\ o 0 % rid A 8 U 3 2 k OOrnOOOO U ...... c PrnOOOO Ccm0 Pi 0 0 A ma  0 + * n 0 .*

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U N .* 0 2 A B rlcvmm ri rcilmmmm 1 . 4.0 CHgMISTRY The 50 composite samples in the FY86 " ATS were prepared by MRI in the analysis laboratory for determination of semivolatile compounds using high resolution gas chromatography/ mass spectrometry ( MGC/ MS). The performance of the analysis effort was demonstrated through recoveries of surrogate compounds and internal quantitation standards ( IQS), as well as through analysis on 20 QC samples ( method blanks, control tissue samples, and spiked control tissue samples). Section 4.1 discusses the various steps in the analytical procedure, including how results are quantified. Section 4.2 presents the QA/ QC methods that were implemented. The presentation of the results for analysis of QC samples is primarily relegated to Chapter 5. Section 4.3 presents data quality objectives established for the laboratory analytical method and the extent to which these objectives were met.

4.1. ANALYTICAL PROCEDURES The analytical procedures performed in the FY86 NHATS included the extraction and cleanup of the composite tissue samples using Gel Permeation Chromatography ( GPC) and Florisil column fractionation, the analysis by HRGC/ MS, and the quantitation of results. A flow diagram of these activities is found in Figure 4 1. Each of these procedures is described in detail below.

4.1.1. Sanmle Prevaration The preparation of the cornposited adipose tissue Specimens for determination of semivolatiles required a multistep Procedure. The stages of this procedure include quantitative extraction and cleanup through several chromatographic columns. These stages are described below.

4 1 II Human Adipose Tissue, 20 g .. .

I 1 Add Stable Isotope Labeled Surrogate 1 Compounds ~

Ii Extraction = Tissuemizer 1 Bulk Lipid Removal Gel Permeation Chromatography 1 Florisil Fractionation 200 mL 6% ethyl ether / hexane 300 mL 50% ethyl ether / hexane HRGC/ MS ( Scanning) 0.01 = 0.1 pg/ g ( PCBs, OCl Pesticides, etc.)

I Quantitation / Data Transfer I I 1 ..

I Figure 4 1. Flow Scheme for Analysis of Semivolatile Com~ pounds in the FY86 " ATS 4 2 <IP_ADDRESS>. Extraction. After the compositing stage ( Chapter 3),

the adipose composites were stored at  100~ in 50 m~ culture tubes sealed with aluminum foil. To begin the sample extraction procedure, the samples were allowed to come to room temperature and then fortified with 200 pL of the surrogate spiking solution, Spiked control QC samples were fortified with 50 pL and 200 pL of the native compound spiking solution for the low and high dose samples, respectively. Ten milliliters of methylene chloride was added and the sample homogenized for 1 min with a Tekmar Tissuemizer. The mixture was allowed to separate, and the methylene chloride was decanted through a funnel of 5 to 10 g of sodium sulfate into a 200 mL volumetric flask. The funnel was rinsed with 10 mL of methylene chloride into the volumetric flask. The homogenization was repeated two times with fresh 10mL portions of methylene chloride. The culture tube was rinsed with additional methylene chloride and the remaining contents of the tube transferred to the funnel. Finally, the funnel was rinsed with additional methylene chloride until the volumetric flask was brought up to volume ( 200mL).

4.1.1 2. Lipid Determination. At this point the flask was stoppered, inverted several times to mix the extract, and 1 mL was removed with a disposable pipet and placed into a preweighed ( mea, suredto 0.0001 g) 1 dram glass vial. The methylene chloride in the vial was reduced under nitrogen until an oily residue remained. The weight of the lipid was obtained by difference, and the percent lipid for the composite was calculated and recorded.

<IP_ADDRESS> Extract Concentration, The remaining portion of the extract ( 99 mL) was quantitatively transferred, with a 30 to 40mL rinse, to a 500 mL Kuderna Danish evaporator equipped with a 20 mL receiver, One or two clean boiling chips and a three ball Snyder column were added to the flask. The Snyder column was >

prewet with 1 mL of methylene chloride and the volume reduced to 15 to 25 mL over a steam bath. The apparatus was removed from the steam bath and allowed to cool. The flask and joint were rinsed with 5 mL of methylene chloride into the receiver. The extract was then quantitatively transferred to a 40 mL sample vial with a TFE lined screw cap, adjusting the volume to approximately 40 mL with methylene chloride.

4.1,2. Cleanup Procedure <IP_ADDRESS>. Gel Permeation Chromatography. GPC columns were packed with 60 g of Bio Beads SX 3 that had been allowed to swell overnight in methylene ch1oride: cyclohexane ( 50: SO). The beads were allowed to settle to form a uniform packing. Solvent, methylene ch1oride: cyclohexane ( 50: 50), was pumped through the column at a flow rate oz 5 mL/ min. After air had been displaced from the column, the pressure was adjusted to 5 to 15 psi. The GPC column was then calibrated using a solution of approximately 1 mg/ mL butyl benzyl phthalate, 1 mg/ mL 4 nitrophenol and 390 mg/ mL extracted bulk human lipid in methylene chloride. The calibration resulted in a GPC program that . provided 135 mL ( 27minutes) of eluent with lipid directed to a discard fraction, followed by a' 225mL ( 45 minute) collection period. This was the chromatographic pattern established from the elution of the butyl benzyl phthalate through the elution of 4 nitrophenol. An additional wash time of 50 mL ( 10 minutes) was included to prevent sample carryover. Prior to loading the GPC,' thesample collection tubes and injector port were rinsed with acetone, methylene chloride, toluene, and hexane. Syringes, beakers, and filters were washed with soap and water, rinsed with water, deionized water, acetone, methylene chloride, toluene, and hexane. All extracts were drawn through a Millipore stainless steel Swinney filter with a 0.5 pm type FH membrane. Sample loops were rinsed with 5 mL of methylene ch1oride: cyclohexane ( 50: 50) and loaded with 2 mL of the sample extracted followed by 3 mL of solvent. One loop between each composite was used as an eluent blank. The cleaned extracts were collected in clean 4 L amber solvent bottles.

4.1,2.2. GPC Eluent Concentration. The cleaned extracts from the combined GPC effluent was concentrated, using 500 or 1000 a Kuderna Danish ( K I)) evaporators, to approximately 10 mL. The Snyder column was prewet with methylene chloride and a new boiling chip added with addition of eluent. When all the eluent . wasconcentrated to 5 to 10 mL, the apparatus was allowed to cool. If the extract remained highly colored or viscous, the sample was quantitatively loaded onto the GPC and reprocessed in three to four loops. Then the extract was reconcentrated and transferred to Florisil as follows. If the sample extract appeared clean, SO mL of hexane was added. The Snyder column was replaced and prewet with 1 mL of hexane. The volume was reduced to 10 mL and the flask and lower joint rinsed with 1 to 2 mL of hexane into the concentrator tube. The extract was then concentrated to approximately 1 mL under a gentle stream of purified nitrogen.

<IP_ADDRESS>, Flotieil Column Cleanup, A 25 x 300 mm chromatographic column with solvent reservoir and TFE stopcock was prepared by packing the bottom with a small wad of silanized glass wool and rinsing with 20 mL of hexane. A 100 mL aliquot of hexane was added to the column. The precleaned Florisil was allowed to COOL in a desiccator, and 12.5 grams were transferred to the column. When the Florisil had settled, sufficient anhydrous sodium sulfate was added to achieve a one half inch layer on top of the Florisil. The hexane was drained just to the top of the anhydrous sodium sulfate layer. The extract was transferred to the top of the column. The extract receptacle was rinsed with three successive 2 to 3 mL aliquots of hexane, adding the rinses to the column. A 500 mL K D flask and receiver were placed under the column, and the sample was drained onto the column until the 4 5 anhydrous sodium sulfate was nearly exposed. The column was eluted with 200 mL of 6% ethyl ether in hexane ( v/ v) ( Fraction 1) at a rate of about 5 mL/ min. The X D flask and receiver were replaced with another IC D flask and receiver. The column was eluted with 300 mb of 50% ethyl ether in hexane { v/ v> ( Fraction 2)

The fractions were concentrated to approximately 10 mL using hexane to prewet the Snyder column. The flask and lower joint were rinsed with 1 to 2 mL of hexane. The receiver was then placed under a gentle stream of purified nitrogen and the volume reduced to less than 1 mL. If either fraction remained highly colored, viscous, or turbid, it was rediluted in methylene chloride and loaded again on the GPC. If the sample appeared clean, the sample was transferred to a clean precalibrated reactivial, The receiver was rinsed with three 1 mL aliquots of hexane, adding the rinse to the reactivial. The volume was reduced to less than 0.5 mL, the vials sealed, and the samples refrigerated. All 6% fractions were reduced to 200 pL under a gentle stream of purified nitrogen. The 6% fractions were fortified with 200 pl of an internal quantitation standard ( IQS) solution and the volume returned to 200 pL under a gentle stream of purified nitrogen. The IQS solution included naphthalene dg, anthracene dlo, and benzo[ a] anthracene d12. An aliquot of each sample was transferred to an autosampler vial and submitted for HRGC/ MS analysis. The 50% fractions were further reduced under a gentle stream of purified nitrogen. The 50% fractions were further reduced under a gentle stream of purified nitrogen. A white precipitate formed in some samples. The volume was reduced to 200, 400, or 600 pL, depending upon the volume of precipitate.

An aliquot of the IQS solution equal to the sample volume was c added, and then the samples were concentrated to the same volume 4 6 ... . 1 they each had prior to addition of the IQS solution. sample. wassubmitted for HRGC/ MS analysis. An aliquot of 4.1.3. Analysis Procedures The quality assurance program plan for the FY84 and  86 NHATS analysis of composite samples ( Stanley et. al., 1986)

describes in detail the analytical methodology for the HRGC/ MS analysis of semivolatiles in the FY86 NHATS. Additional information related to the method can also be found in USEPA ( 1986)

surveys are discussed in Chapter 8.

relevant to the FY86 approach are included below. Specific differences in the methods between these three Sections of these reports At the beginning of each day that analyses were per formed, the analyst verified that the instrument was properly calibrated through analysis of decafluorotripheylphosphine ( DFTTP, see Section 4.2.1). The analyst documented whether the DFTTP criteria were satisfied. Prior to beginning analysis, a hexane blank was injected to document system cleanliness. If any evidence of system contamination was found, then another hexane blank was analyzed. Two microliters ( determinedto nearest 0.1 pL) of the spiked sample extract were injected into the HRGC/ MS system using a splitless injection technique. The syringe was carefully cleaned between injections by the following procedure to prevent carryover of contaminants:

I Rinse the syringe 10 times with hexane;

I Fill the syringe with toluene and sonicate syringe and plunger in toluene for 5 min and repeat at least twice;

I Rinse the syringe 10 times with hex\ ane.

After applying this procedure, the syringe was ready for use. Instrument performance was monitored by examining and If these areas recording the peak areas for the three IQS. decreased to less than 50% of the calibration standard, then sample analyses were stopped until the problem was found and corrected. The recommended HRGC/ MS operating conditions for the semivolatile organic compounds are listed in Table 4 1:

Table 4 1. Reconmended FiRGC/ MS Operating Conditions Column temperature column Injector temperature HRGC/ MS interface Carrier gas Injector technique Electron energy Mass range 6OoC ( 2 min) then 10 ° C/ min to 310 ° ( 10 min) 25OOC 3OOOC Helium at 30 cm/ sec 2 pL, splitless with a 45 second delay, a split flow of 30 mL/ min, and a septum purge of 5 mL/ min 70 eV ( nominal) 40 550amu 4.1.4. QuantitatiodData Reduction In this subsection, the. procedures for the data reduc tion are outlined for the. analysisof data from the HRGC/ MS method for semivolatile compounds. The data for each sample were interpreted with computer assisted quantitation routines. A mass spectral library and quantitation list of the target analytes based on relative retention times and the primary characteristic ion were used to search each data file.

<IP_ADDRESS>. Qualitative Identification. The quantitation routine identified positive responses based on the primary or secondary characteristic ion for each of the analytes. Table 4 2provides a list of these analytes ( native compounds, surrogates, and IQS),

along with the primary and secondary quantitation ions used for compound characterization. _. _ I 4 Q) al 8 0 cdk tE 9 9 4 3

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n 0 0 li V 0 d ln 4 12 I m a, W m 2 0 4 U m . d k a, U u E 4 9 w 0 3 i 3 9  $! . d U Id rl a, k a,

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rl 9  s The following criteria based on Table 4 2 must have been met in order to make a. qualitative identification:

8 The characteristic masses of each parameter of interest must maximize in the game scan or within one scan of each other.

rn The retention time must fall within kt10 seconds of the retention time of the authentic compound.

rn The relative peak heights of the three characteristic masses in the EICPs must fall within f30% of the relative intensities of these masses in a reference mass spectrum. The reference mass spectrum can be obtained from a standard analyzed in the GC/ MS system or from a reference library.

rn The response for each of the Characteristic ions must be at least 2,5 times the background signal to noiseratio.

<IP_ADDRESS>. Quantitation. Data were quantitated on the internal standard method. IQS were paired with each analyte for quantita tion purposes; these pairings are displayed in Table 4 2.

Relative response factors ( RRFs) for native   quantitativet1 semivolatile compounds were calculated from the data obtained during the analysis of calibration solutions using the following formula:

RRF = Asm c* s AIS csm ( 4 1)

where Am = The area of the primary quantitation ion for the analyte in question, AIS = The area of the primary quantitation ion for the labeled IQS paired with the given analyte, Cm = Concentration ( ng/ pL) of the analyte, and CIS = Concentration ( ng/ pL) of the IQS.

Once the RRF values were obtained, the lipid adjusted concentration of a semivolatile analyte within an adipose tissue sample ( Cmpl,) was calculated as follows:

4 14 where RRF was determined from the calibration, = The area of the primary quantitation ion for the analyte in question within the sample, As = The area of the primary quantitation ion for the labeled IQS paired with the analyte, = The amount ( total ng) of the labeled IQS added to the sample prior to extraction, WAT = Weight ( 9) of the odginal adipose tissue sample, and LC = Percent extractable lipid from the sample.

<IP_ADDRESS>. Recovery of Surrogate Standards. Recoveries of the labelled surrogate standards measured in the final extract were calculated using the following formula:

Ass QIS 100% % Recovery = AIS * Qss MFSS ( 4 3)

where & and Qs are defined above, ASS = Area of the primary quantitation ion determined for the surrogate standard, Qss = Amount ( ng) of the surrogate standard added to the sample prior to extraction, RRF for the surrogate standard relative to its IQS, as determined from the initial calibration. and RRFSS =

<IP_ADDRESS>. Data Qualifiers. Quantitative data were classified to indicate the intensity of the signal response. For quantitative compounds, the qualifiers were defined as follows:

a Not Detected ( ND) : S/ N ratio less, than 2.5. Trace { TR): S/ N ratio at 2.5 or above, but less than 10I) Positive Quantifiable ( PQ): S/ N ratio at 10 or above.

The semivolatile compounds described as llqualitativeanalytes'l in the FY86 NHATS were not quantitated beyond a one significant figure estimate. A " positive detect" ( PD) was reported for analytes that met ' thequalitative criteria.

<IP_ADDRESS>. Estimating the Method Limit of Detection. A method limit of detection ( LOD) was estimated for a given sample in the following situations for a specific analyte:

I no response was noted for the analyte; a response was noted but the ion ratios were incorrect; I a response was noted but was below the calibration range; or I the reported response was quantitated as a trace value.

If no response was noted, the LOD was reported as the lower end of the established calibration range. The LOD value was reported as total ng/ injection such that the LOD could be extrapolated for each individual sample. For samples for which a response at the compound's retention time was noted but the qualitative criteria for ion ratios were outside an acceptable range, the estimated LOD was calculated as the response of the interference, and the concentration value was regarded as not detected ( ND). If a response was noted at the correct retention time and met the qualitative criteria of ion ratio agreement for identification, but the calculated response was below the calibration curve, then the value was identified as not detected. If a response was qualified as a trace value, then the f analyst also provided an estimated LOD. This was accomplished by using the observed signal to noiseratio on either side of the response or the lower calibration limit, whichever was higher. 4.2. QA/ ClC FOR CHEMICAL ANALYSIS 4.2.1. Demonstratinu Achievement of Instrument Performance Reauirements Achievement of the instrument performance requirements were demonstrated in the following stages:

( 1) MGC Column Performance A 30 m HRGC column, DB 5, film thickness = 0.2 pm, was used for analysis of all samples and standards for the 6% fraction extracts, and a 30 m DB 1301, film thickness = 0.2 pm, was used for all 50% fraction extracts. The column performance was initially demonstrated using a Grob hydrocarbon mixture. The retention times should be within * 30% of the values supplied by the manufacturer with the column when chromatographed under similar conditions. If during the course of the analysis it became necessary to install a new column, this column was verified in a similar manner.

( 2) Tunina and Mass Calibration. The mass spectrometer was tuned at least daily to yield optimum sensitivity using decafluorotripheylphosphine ( DFTTP). The criteria that must be met axe listed in Table 4 3. Corrective actions were implemented whenever the resolving power did not meet the requirement. Examples of these corrective actions are recalibrating the mass Spectrometer, changing the GC column, or maintenance of the instrument. Corrective actions were determined by consultation between the analyst, the work assignment leaderts), and the mass spectrometry facility staff.

( 3) RRF Check and Instrument Sensitivitv Check. As part of the initial and routine instrument performance checks, a single calibration standard Mas analyzed and RRF values of the respective analytes were compared to specific internal standards. The initial and routine calibration criteria require that the 4 17 Table 4 3. DFTTP Key Masses and Abundance Criteria(')

51 68 69 I 70 127 8% 82% of mass 198 ~ 2% of mass 69 11% 91% of mass 198 ~ 2% of mass 69 32% 59% of mass 198 198 base peak, 100% abundance 199 275 441 442 I h II 443 I EPA Method 1625 Revision B: Dilution GC/ MS, January 1985.

.,.. ... Sj f f 4% 9% of mass 198 11% 30% of mass 198 44% 110% of mass 443 30% 86% of mass 198 14% 24% of mass 442 Semivolatile Organic Compounds by Isotope f 1 precision of the RRF measurements are * 30% for the target analytes. Sensitivity of the MS was documented through the responses noted for the first calibration standard of each analysis day. The method requires that a low level standard be analyzed to document sufficient instrumental response to support instrumental detection limits. Routine checks on the instrumental sensitivity were achieved by monitoring the response for the IQS from injection to injection and documenting the responses in the MS log book. If the response for the IQS was noted to drop by greater than 50% of the response noted in the previous calibration standard, the analyst verified instrumental performance through the analysis of an additional calibration standard. The qualitative analytes in the FY86 " ATS were identified by relative retention times and characteristic mass peaks. These met the same qualitative identification factors as the quantitative targets but were not quantitated beyond a onesignificant figureestimate. The RRFs for the compounds were not a required factor in the initial calibration and daily performance checks. A '! positive detect" ( PD) was reported for analytes that met the qualitative criteria in Section 4.1.4.

4.2.2. Calibration for Quantitative Semivolatile Analysis <IP_ADDRESS>. Initial Calibration. Initial calibration was required before any samples were analyzed, or when any routine calibration did not meet the required criteria for the consistency of RRFs (~ 30% for quantitative targets and internal standards). An initial calibration was conducted by performing the following steps:

( 1) Tuning and calibrating the instrument with PFK and DFTTP.

4 19 Table 4 4. Calibration Solutions for the 6% Flotieil Fraction Lindane ( T BHC) 100 so 10 5 1 Mirex 100 so 10 5 1 Chlordane 100 50 10 5 1 Oxychlordane 100 50 10 5 1 Aldrin 100 50 10 5 1 CU BHC 100 50 10 5 1 I A BHC 100 50 10 5 1 @ BHC 100 50 10 5 1 Heptachlor epoxide Heptachlor 100 100 50 so 10 10 I 5 5 1 1 P, P' DDT 100 50 10 5 1 0, p'  DDT 100 so 10 5 1 p, p' DDE 100 50 10 5 1 0, p'  DDE 100 50 10 5 L 0, p'  DDD 100 50 10 5 1 p, p'  DDD t Nonachlor . 100 50 10 5 1 1,3 Dichlorobenzene 100 50 10 5 1 1,4 Dichlorobenzene 100 50 10 5 1 lI2 Dichlorobenzene 100 50 10 5 1 1,2,4 Trichlorobenzene 100 50 1 10 5 1 l12,3 Trichlorobenzene 100 50 10 5 1 1,3,5 Trichlorobenzene 100 50 10 5 1 1,2,3,4 Tetrachlorobenzene 100 __ 50 10 5 2 1,2,3,5 Tetrachlorobenzene 100 50 10 5 1 1,2,4,5 Tetrachlorobenzene 100 50 10 5 l.

Pentachlorobenzene 100 I 50 10 5 1 Hexachlorobenzene 100 50 10 5 1 Naphthalene 100 50 10 5 1 Phenanthrene 100 50 10 5 1 4 20 Tabla 4 4. ( Coat.)

Fluoranthene . 100 50 10 I 5 1 Chrysene 100 50 10 5 1 Benzotalpyrene 100 50 IO 5 1 Acenaphthylene 100 50 10 5 1 Acenaphthene 100 50 10 5 1 Fluorene 100 50 10 5 1 Biphenyl I 100 50 10 5 1 1,2 Dibromo 3 chloropropane I 100 1 50 I 10 I 5 1 10 5 100 10 Octachlorostyrene 50 10 5 1 Tetrabromobiphenyl. 100 50 10 5 1 o Cymene 100 50 10 5 1 m Cymene 100 50 10 5 1 100 50 10 5 Pyrene 100 50 10 5 1 ~

Hexachlorobutadiene ( HCBD) 100 50 1 Hexachlorocyclopentadiene 50 5 1 100 p Cymene 1 4 21 Analyzing the five concentration calibration solutions for the 6% fracton eluates listed in Table 4 4. The low concentration solution, CS5, was used to demonstrate the lower limit of detection provided by the available instrument.

Computing the RRFs for each analyte in the concentration calibration solution using the criteria for positive identification of semivolatile analytes and the computational methods given in Section 4.1.4.

Computing the means and their respective relative standard deviations ( RSD, expressed as a percentage) for the RRFs for each analyte in the standard. The RSD was calculated as the standard deviation to all measurements of a particular RRF value divided by the average RRF value and multiplied by 100%. These samples were identified in the individual batch reports.

Repeating the above process for the 50% Florisil fraction eluates ( Table 4 5) and PCB calibration solution ( Table' 4 6) .

The above fractionation was based on the previous broad scan analysis of adipose tissue. In the case of pant itative : a analytes not previously determined, comparisons to similar Bcompounds have been made for the purpose of determining in which t :;

Florisil fraction the analyte was most likely to appear. To declare an acceptable initial calibration, the RSD $ .3 for the response factors for the analysis of analytes across the : F $  4calibration'rangemust have been less than * 30%. If this 3 r criterion held, then the RRF was assumed to be nonvariant and the .$

average RRF could. beused for calculating a RSD value. Alter' natively, the results were used to p1ot. acalibration curve of response ratios, A3/ AiS versus RRF.

An acceptable initial calibration also required the traces for all ions used for quantitation to present a signal to noise ( S/ N) ratio of at least 2.5. This included analytes and isotopically labeled standards. Isotopic ratios must have been within + 30% of the theoretical ' values.

4 22 Table 4 5. Calibration Solutions for the 50% Florisil Fraction Dimethyl phthalate 100 50 I 10 I 5 1 Dibutyl phthalate 100 50 10 5 1 Butylbenzyl phthalate 100 so 10 5 1 Di n octylphthalate 100 50 10 5 1 Diethyl phthalate 100 so 10 5 1 Di n butylphthalate 100 so 10 S 1 I I Tributyl phthalate 100 50 10 5 1 Diethylhexylphthalate ( DEHP) 100 so 10 S 1 Tributylphosphate so0 250 SO 25 5 Triphenylphosphate 200 100 20 10 2 Tris( 2 chloroethy1) phosphate 500 250 50 25 5 Tributoxyethylphosphate 200 100 20 10 2 1 Tritolylphosphate 200 100 20 10 2 Tris( dichloropropyl) phosphate 500 250 so 2s 5 Dieldrin 500 250 50 25 5 Endrin so0 250 50 25 5 Endrin ketone 500 250 50 2s 5 Tris( 2,3 dibromopropyl) phosphate 500 250 so 2s 5 2 Phenylphenol 100 50 10 5 1 Trichloro o terphenyl 200 100 20 10 2 Tetrachloro o terphenyl 200 100 20 10 2 4 Chloro o terphenyl 200 100 20 10 2 Pentachlorodiphenyl ether 200 100 20 10 2 2 Methoxy 3 methylpyrazine 200 100 20 10 2 Ethyl hydrocinnamate 200 100 20 10 2 4 23 Table 4 6. Caf; ibration Solutione for PCB Analysis Monochlorobiphenyl 100 50 10 5 1 Dichlorobiphenyl 100 50 10 5 1 Trichlorobiphenyl' 100 50 10 5 1 11 I I 1 Nonachlorobiphenyl 100 I 20 2 I I I I I Decachlorobiphenyl 500 I 250 50 25 5 4 24 <IP_ADDRESS>. Routine Calibrationq. Routine calibrations were performed at the beginning of every day before actual sample analyses were performed and as the last injection of every day. Routine calibrations involved the following steps:

( 1) Injecting 2 pL of the concentration calibration solutipns CS3 for the 6% fraction as the initial calibration check on each analysis day and as the final check on each analysis day.

( 2) Computing the RRFs for each analyte in the concentration calibration solution using the criteria for positive identification of semivolatiles given in Section 4.1.4.

To declare an acceptable routine calibration, the measured RRF for all analytes must have been within * 30% of the mean values established by initial calibration of the calibration concentraton solutions. Also, isotopic ratios must have been within & 30% of the theoretical value for each analyte and isotopically labeled standard.

4.2.3. Snikinu Solution Prenaration <IP_ADDRESS>. Native Standard Spiking Solution. A native standard spiking solution was prepared in dichloromethane from the individual stock standards. This solution was used for preparing laboratory spikes of adipose tissue. For example, if the anticipated spike level is 0.10 pg/ g in a 20 g sample, the target analyte should be added to the spiking solution to achieve a final concentration of 10 pg/ mL. The specific PCB isomers used for preparing calibration solutions were also included in the target spiking solution. The spiking solution and proposed levels are listed in Table 4 7.

<IP_ADDRESS>. Surrogate Standard Spiking Solution. A mixed surrogate standard spike solution was prepared in dichloromethane from the individual stock  standards. The surrogate standard spike Table .4 7. Proposed QC Spiking Solutione E, E'  DDE E, E'  DDT Dieldrin Heptachlor epoxide  t Nonachlor Mirex y Chlordane Hexachlorobenzene 1,2,4,5 Tetrachlorobenzene 1,4 Dichlorobenzene 1,2,4 Trichlorobenzene Diethyl phthalate Butylbenzyl phthalate Triphenyl phosphate Tris( dichloroethyl1phosphate Benzo[ a] pyrene Phenanthrene Chrysene Hexachloro 1,3 butadiene  R Limonene 2 Phenyl phenol Coumarin  o Cymene 2 Indanone DL Isoborneol Ethyl hydrocinnamate Octamethylcyclotetrasiloxane Monochlorobiphenyl Dichlorobiphenyl Trichlorobiphenyl 29.5 200 I 50 28.4 200 50 21.9 200 50 14.3 200 50 21.9 21.7 200 200 I 50 50 22.3 200 50 19.5 200 I 50 28.8 200 50 124 200 1 50 20.7 200 50 23.0 200 50 22.6 200 50 19.2 200 50 372 200 50 24.1 200 50 23.6 200 50 5.07 200 50 19.6 200 50 23.4 200 50 20.7 200 50 25.2 200 50 28.0 200 50 17.3 200 50 26.7 200 50 32'. 7 200 50 21.1 200 50 25.3 200 50 27.9 200 50 24.6 200 so 4 26 ( y(">:*] 3 Table 4 7. ( coat.) .

Tetrachlorobiphenyl I 56.2 200 50 Pentachlorobiphenyl 65.0 200 50

Hexachlorobiphenyl 52.6 200 50 Heptachlorobiphenyl 130 200 50 Octachlorobiphenyl 137 200 50 Nonachlorobiphenyl 154 200 50 Decachlorobiphenyl 96.1 200 50 (' 1 Final spike level is based on ng of analyte/ g of adipose ( 20 g sample). The actual reported value would be based on ng of analyte/ g of extractable lipid.

( 3 From EPA Method 680 list except for the nonachlorbiphenyl which is not included in Method 680.

4 27 ,,. I .........., solution were prepared to deliver the surrogates at the amounts specified in Table 4 8 in a 200 pL volume. This requires that the stock solution contain the surrogates at concentrations ranging from 10 to 50 gg/ mL.

<IP_ADDRESS>. Internal Standard Spiking Solution. The internal standard spiking stock solution concentrations are also listed in Table 4 8 for each of the deuterated internal standards.

<IP_ADDRESS>. Performance Audit Solutions. Included among the samples in at least two sample batches was a solution provided by the quality control coordinator containing known amounts of specific target analytes representing each major compound class to be determined. The accuracy of measurements for performance evaluation samples was in the range of 70 130%.

1< 4.2.4. pC Samples 3G Samples included for QC purposes within each batch of 4 i composite samples are summarized in Table 4 9. The order of 4 preparation and analysis with respect to the FY86 " HATS composi 1 ites was specified in the sample design. This section discusses ! each of these QC sample types. Discussion of the findings and conclusions from QC sample analyses are presented in Section 5.3.

<IP_ADDRESS>. Method Blanks. One method blank was generated within each batch of samples. A method blank was generated by performing all steps detailed in the analytical procedure using all reagents, standards, equipment, apparatus, glassware, and solvents that Lwereused for a sample analysis, but not adding any adipose tissue. The method blank contained the same amounts of labeled surrogate standards that were added to samples before bulk lipid cleanup. Protocol dictated that if the levels detected in the method blank were greater than 10% of the levels seen in the 4 28 Table 4 8. Spike Levels for Surrogate and Internal Standards(')

Surrogate Compounds l82,4 Trichlorobenzene dg I 3.428 Chrysene dlz 2.808 UC6 i82# 4,5 Tetrachlorobenzene I 2.470 13C6 Hexachlor~ benZene 1.932 ' k6 4  Chlorobiphenyl 2.222 l3Cl2 3,3 ,4 4' Tetrachlorobiphenyl I 4.016 ' 3c1z 28 2 8 38 3 ,58 5 ,6,6  0ctachlorobiphenyl 6.852 ' 3C12 Decachlorobiphenyl 12.20 Diethyl phthalate 3,4,5,6 d) 2.252 Di n butyl phthalate 3,4,5 6 40) 1.800 Lindane 1.672 Heptachlor I3C I1 2.030 Internal Standards Naphthalene 4 II 1.901 Anthracene dlo 1.910 Benzofa] anthracene d, II 2* 102 Refer to EPA Method 1625, Revision 3 SemivolatileOrganic Compounds by Isotope Dilution GC/ MS, Federal Register 1984, 49 ( 2091, pp. 184 197.

Concentration calculated for a solution of 200 pL final volume.

O) Were not reported in most samples.

4 29 .. . __ _ i_ "..:, :.. Table 4 9. Quality Control Samples Included in the FY86 " ATs Analytical Procedure Method blank One per batch Spiked control adipose Two per batch ( two tissue sample different spike levels)

Unspiked control One per batch adipose tissue sample Assess laboratory background contribution.

Evaluate method performance ( accuracy and precision)

Evaluate method performance ( accuracy and nrecision)

7 g 8 i tissue samples, then the solvents, reagents, spiking solutions, apparatus, and glassware were checked to locate and eliminate the source of contamination before any further samples were extracted and analyzed.

<IP_ADDRESS>. Control Samples. Control samples were prepared from a bulk sample of approximately 2 kg of human adipose tissue. This material was prepared by blending the tissue with methylene chloride, drying the extract by eluting through anhydrous sodium sulfate, and removing the methylene chloride using rotoevaporation at elevated temperatures ( SOOC). The evaporation process was extended to ensure all traces of the extraction solvent have been removed. The resulting oi, lymatrix ( lipid) was subdivided into 20 g aliquots which were analyzed with each sample batch.

<IP_ADDRESS>. Spiked Control Samples. Spiked lipid samples were prepared by using a portion of the homogenized lipid. Sufficient spiked lipid matrix was prepared to provide a minimum of two spiked samples per sample batch: one sample spiked at a low concentration and one at a high concentration. Method performance was addressed in this study by calculating recoveries for each spiked sample as follows:

4 30 Recovery(%) = conc. ( spikedsample)  conc. ( controlsample) * Spike level ( 4 4) This method to calculating percent recovery leads to a test of ruggedness of che method with respect to detecting finite differences in concentration. Note that an equally accepted approach to calculating percent recovery is given by the formula conc. ( spiked sample) Recovery (% ) = conc. ( control sample) + spike level * 100% ( 4 5)

Formula ( 4 5) can lead to larger percentages than formula ( 4 4)

applied in this study. This fact should be considered when interpreting observed recovery percentages in this study. Analytical results of the QC samples are statistically summarized in Chapter 5. This chapter also presents conclusions and issues resulting from the QC sample analysis.

I 4.3 OVERALL DATA QUALITY At the outset of the analysis effort for the FY86 NHATS, specific data quality objectives were defined for the quantita tive and qualitative analyses of the target semivolatile com pounds. Data quality objectives were established for calibration criteria ( relative response factors [ RRFs]) for each analyte and internal standard, internal standard respdnse area, and method performance based on the recoveries of labeled surrogate com pounds and native compounds spiked into a spiked internal QC sample. The data generated with respect to these criteria are presented within this report. Further details were provided in the original data reports. Table 4 10 summarizes the performance achieved versus the specific criteria and data quality objectives for the analysis of the FY86 NKATS composites.

4 31 Table 4 10. Data Quality ObjectLves for the FY86 " ATS, Along With Actual Performance RRF calibration Labeled surrogate stan dards Spiked internal QC Sam ples Internal standard re sponse areas / f30t all quantitative analykes 40% 160%

50% 150%

505. 150% of initial daily calibration stan dard 4 32 > 90% of all RRF factors within DDQs.

> 84% for all labeled surrogate spikes; 12% of the deviation due to 50% fraction surrogates.

70% of all measurements within criteria; 22% of all deviations due to 50% fraction compounds.

> 90% of all measurements within criteria.  5.0 DATA ISSUES The NfIATS FY86 sampling effort resulted in a total of 50 composites of adipose tissue specimens for chemical analysis ( see Chapter 3). In the analytic laboratory, these 50 composites were partitioned into five groups, or batches, of ten composites each. Each batch also included the following four laboratory QC samples:

8 One method blank I Three samples prepared from a homogeneous bulk lipid extract; two of these samples spiked at differing levels by selected native compounds.

Thus, the " ATS FY86 chemical analysis was performed on five batches each containing fourteen analytical samples, for a total of 70 analytical samples. Samples within a batch were chemically analyzed as a group under similar laboratory conditions. Prior to chemical analysis, all non blank analytical samples were spiked with a set of twelve surrogate compounds. These labelled compounds do not exist in the natural environment and were selected to represent the native compounds of interest. Analysis of surrogate recovery data was performed to evaluate method performance and overall recovery levels. This chapter addresses a series of preliminary data issues which include a summary of the composite data and statistical analysis on the QC data. The information gathered from this preliminary data investigation was essential for the statistical analysis and interpretation of sample results. The objectives of the preliminary data analysis included the following:

Identify those compounds having a sufficiently large percentage of composite samples with detected results. Results for these compounds will likely reflect more accurate estimates of average concentration levels and variability.

... I,

. .. .__ I..._. 4...__... ,., " . ~

. i *".. .~ t. , ., ,, I _*

I Identify the extent that systematic errors in measured concentrations are present over time by considering surrogate recovery data. If necessary, adjust the measured concentrations for these errors.

I Characterize method performance through analysis of QC sample data, identifying sources of variability and the extent of batch effects in the ( adjusted) measured concentrations.

Each of these efforts is documented in separate subsections which follow.

5.1 DETERMINING NATIVE COMPOUNDS TO INCLUDE IN STATISTICAL ANALYSIS A total of 111 semivolatile compounds were considered in. theFY86 " ATS. These compounds fall into several chemical classes:

I I I I I I 8 I I I m Pesticides ( 19 compounds) Chlorobenzenes ( 11compounds) Phthalate esters ( 5 compounds) Phosphate triesters ( 5 compounds) PAHs ( 9 compounds) PCBs ( 10 compounds) Other quantitative compounds ( 19 compounds) Qualitative pesticides ( 9 compounds) Qualitative chlorinated aromatics ( 9 compounds) Qualitative PAHs ( 4 compounds) Other qualitative compounds ( 11 compounds)

Section 5.1.1 identifies the compounds analyzed within each chemical class and the detection percentages for each compound as observed within the " HATS FY86 composite samples. Statistical analysis was performed only on compounds with sufficiently high detection percentages. Section 5.1.2 discusses unique data reporting for two pesticides which have been historically prevalent in the " HATS program.

5 2 I  5.1 1 Detection Status of the Semivolatiles When reporting a measured concentration for a given semivolatile compound in a laboratory sample, the NHATS FY86 analytical method determined whether the compound was successfully detected in the sample. For quantitative compounds, the method classified each result into one of three possible data qualifier categories, indicating the intensity of the signal response:

m Not detected  Result is less than 2.5 times the signal to noiseratio.

Trace Result is between 2.5 and 10 times the aignal to noise ratio.

m Positive uuantifiable  Result is greater than 10 times the signal to noiseratio.

If a result was categorized as trace or positive quantifiable, the compound was considered detected in the sample. For qualitative compounds, only detected and not detected results wdre reported. Estimated method detection limits were reported when not detected or trace results occurred for a sample. When a compound was not detected in a sample, it was assumed that the sample's true compound concentration was at some level below the detection limit. For the statistical analysis, one half of the detection limit was used as the estimated concentration level for not detected samples. Table 5 1 reports the percentage of FY86 composite samples occurring in each of the data qualifier categories for the 111 semivolatile compounds. The percent of composite samples with detected results are also reported. Of the 111 compounds, 23 were detected in at least 50% of the 50 composite samples, and one compound nearly met the 50%

threshold ( octachlorobiphenyl, detected in 44% of the samples). These 24 compounds are identified as target compounds for 5 3 .. . . . . . . . . . I Table 5 1. Percent of " ATS FX86 Composite Samples in Each Detection Level Category Compound Number and Name CAS t t. Not t t Pos. Number Detected Detected Trace Quant.

* 1 2 * 3 * 3 4 5 6 * 7 8 9 10 11 * 12 * 13 * 14 15 16 60 * 60 61 62 17 * 18 19 20 21 22 23 24 25 26 * 27 * 41 42 43 44 45 46 47 48 49 P, P DDT 0, P DDT P, P DDE { M/ Z= 288) P, P DDE ( M/ Z= 316) 0, P DDE 0, P DDD ALPHA BHC BETA BHC DELTA BHC GAMMA BHC( LINDANE) ALDRIN HEPTACHLOR HEPTACHLOR EPOXIDE OXYCHLORDANE TRANS NONACHLOR GAMMA CHLORDANE MIREX DIELDRIN DIELDRIN ( CORRECTED) EXDRIN ENDRIN KETONE PESTICIDES 50 29 3 789 02 6 72 55 9 72 55 9 3424 82 6 53 19 0 319 84 6 319 85 7 319 86 8 ' 58 89 9 309 00 2 76 44 8 1024 57 3 26880 48 8 39765 80 5 57 74 9 2385 85 5 60 57 1 60 57 1 7221 93 4 CHLOROBENZENES 541 73 1 106 46 7 95 50 1 87 61 6 120 82 1 108 70 3 96 4 0 96 0 100 0 0 100 0 0 100 100 0 0 100 0 100 0 0 . 0 100 0 0 0 100 0 0 92 8 2 90 0 100 0 0 4 96 0 4 0 100 0 0 0 100 0 0 94 6 0 94 78 22 2 76 92 8 0 92 0 100 0 0 32 68 2 30 12 88 0 12 62 38 22 40 0 100 0 0 2 98 2 0 0 100 0 0 86 14 0 86 0 100 0 0 0 100 0 0 0 100 0 0 0 100 0 0 0 100 0 0 0 100 0 0 0 100 0 0 0 100 0 0 98 2 4 94 84 16 8 76 0 100 0 0 0 100 0 0 0 100 0 0 8 92 8 0 2 98 2 0 0 100 0 0 4 96 0 4 0 100 0 0 1,2,3,4 TE CHLOROBENZENE 634 66 2 1,2,3,5 TETRACHLOROBENZENE 634 90 2 182,4,5 TETRACHLOROBENZENE 95 44 3 PENTACHLOROBENZENE 608 93 5 HEXACHLOROBENZENE 118 74 1 PAHS NAPHTHALENE 91 20 3 ACENAPHTHALENE 208 96 8 ACENAPHTHENE 83 32 9 FLUORENE 86 73 7 PHENANTHRENE 85 01 8 FLUORANTHENE 206 44 0 PYRENE 129 00 0 CHRYSENE 218 01 9 BEN20 ( A) PYRENE 50 32 8 5 4 T8ble 5 1. ( coat.)

Compound Number CAS % % Not % t POS. and Name Number Detected Detected Trace Quant.

50 MO  CHLOROBIPl3RNYL 2732 1818 0 100 0 0 51 DICWtOROBIPHENYL 25512 42 9 0 100 0 0 52   RICHLOROBIP  YL 25323 68 6 30 70 2 28 * 53 TETRACHLOROBIPfIENYL 26914 33 0 66 34 0 66 * 54 PENTACHLOROBIPHENYL 25429 29 2 88 12 0 88 * 55   LOROBfP IENYL 26601 64 9 94 6 0 94 * 56 EII~ PTACHLOROBIPHENYL 28655 71 2 86 14 0 86 * 57 OCTAcfILoROBIPHENYt 31472 83 0 44 56 0 44 58 NONAUiLOROBIPHENYL 53742 07 7 26 74 0 26 59 DECACHWROBIPHENYL 2051 24 3 28 72 0 28 PHTWUJLTE ESTERS 63 DIMETRYL PIITHALATE 131 11 3 0 100 0 0 64 DIETHYL PIiTHALATE 84 66 2 10 90 2 8 * 65 DI N BUTYL PHTHALATE 84 74 2 76 24 6 70 * 66 BUTYLBENZYL PHTHALATE 85 68 7 72 28 4 68 * 67 BIS ( 2 ETIIYLHEXYL) PHTHALATE 177 81 7 78 22 0 78 PIIOBPEULTE TRIESTERS 68 TRXBUTYL PHOSPHATE 126 73 8 0 100 0 0 69 TRIS ( 2 CHLOROETHYL) 115 96 8PHOSPHATE 0 100 0 0 70 TRIS ( 2,3 DIBROMOPROPYL) 126 72 7PHOSPHATE 0 100 0 0 71 TRIPHENYL PHOSPHATE 115 86 6 4 96 0 4 72 TRITOLYL PHOSPHATE 1330 78 5 2 98 2 0 OTHER 28 BIPHENYL 92 52 4 0 100 0 0 29 1,2 DIBROMO 3 CKIX) RO 96 12 8 0 100 0 0PROPANE 30 HEXACHLORO BUTADIENE 87 68 3 0 100 0 0 31 HEXACHLORO CYCLOPENTADIm 77 47 4 0 100 0 0 32 2,2  , 4  , S TETRABROMO 0 100 0 BIPHENYL 527 84 4 80 20 76 * 33 0 CYMENE * 34 D LIMONENE 5898 27 5 96 4 94 35 D, L ISOBORNEOL 124 76 5 0 100 0 36 1 INDANOrn a3 33 0 0 100 0 37 2 1NDA  E 615 13 4 0  100 0 38 BUTYLATED HYDROXYTOL~ 128 37 0 18 82 14 39 COUMARIN 91 64 5 0 100 0 * 40 OCTAMETHYL CYCLOTETRASILOXANB 556 67 2 72 28 4 68 73 ETHYL HYDROCIN  4L~ 2021 28 5 2 . 98 2 0 74 2 METHOXY 3 MEnCm; P tRAZINE 2847 30 5 0 100 0 0 5 5 Table 5 1. ( cont.)

CAS % t Not k PQS. and Name Compound Number Number Detected Detected Trace Quant. I  i 4 dTHER ( coat.)

75 2,2', 4,4', 5 PENTACHLORO DIBHENYL ETHER 0 100 0 0 76 4 CHLORO P TERPHENYL 0 100 0 0 77 TRICHLORO P TERPHENYL 0 * 100 0 0 78 2 PHENYL PHENOL 90 43 7 24 76 2 22 PESTICIDES ( QUALITATIVE) 9)

85 ISOPHORONE 86 DICHLOROVOS 98 CHLORPYRIFOS 99 ISOPROPALIN 100 BUTACHLOR 101 NITROFEN 102 PERTHANE  106 DICOFOL 107 P. P'  METHOXYCHLOR 78 59 1 16 84 62 73 7 2 98 2921 88 2 28 72 33820 53 0 10 90 23184 66 9 12 88 1836 75 5 8 92 72 56 0 0 100 115 32 2 6 94 72 43 5 0 100 CHLORINATgD AROMATICS ( QUALITATIVE)( a)

88 2,4,6 TRICHLOROANISOLE 89 2,4,6 TRICHLOROPHENOL 90 2,4,5 TRIcHLOROPHENOL 91 2,3,6 TRICHLOROANISOLE 92 2,3,6 TRICfaOROPHENOL 95 PENTACHLOROANISOLE 96 PENTACHLORONITROBENZENE 97 2,3,4 TRICHLOROANISOLE 110 OCTACHLORONAPHTHALENE 105 BENZO '( A) ANTHRACENE 108 BENZO ( B) FLUORANmENE 109 BENZO ( K) FLUORANTHENE: 111 DIBENZO ( A, H) ANTHRACENE 87 40 1 100 88 06 2 100 95 95 4 100 50375 10 5 100 933 75 5 100 98 82 68 8 100 54135 80 7 96 2234 13 1 98 56 55 3 26 74 10 90 207 08 9 4 96 53 70 3 0 100 OTHER ( QUALITATIVE)( a)

* 79 1 NO" E 124 11 8 50 50 80 CUMENE 98 82 8 34 66 * 81 lt214 TRIMETHYLBENZENE 95 63 6 62 38 * 82 HEXYL ACETATE 142 92 7 82 18 83 1,3 DIETHYLBENZENE 141 93 5 8 92 84 1,4 DIETHYLBENZENE 105 05 5 0 100 87 QUINOLINE 91 22 S 8 92 93 DIBENZOFURAN 132 64 9 0 100 94 CHLORDANE 2 98

Compound Number CAS % 0 Not 0 0 POS, and Name Number Detected Detected Trace Quat.

OTHER ( QUALITATIVE) ( cont. 1 103 CHLOROBENZYLATE 510 15 6 0 100

104 BIS ( 2 ET  EXYL) ADIPATE 103 23 1 10 90 L Detected in at least 44% of the FY86 composite samples.

( a) Qualitative compounds were only monitored for detection versus non detection.

5 7 statistical ahalysis and are noted with asterisks in Table 5 1, Statistical analysis of QC and composite data was restricted to these target compounds. For the other 87 compounds, each having no more than a 34% detection rate, results were summarized through descriptive statistics only.

5.1.2 Data ReDortincr Uniuue to Dieldrin and P, D DDE For two pesticides analyzed in the " ATS FY86 program, two sets of measured concentrations were obtained from different protocols. The two sets of results for these compounds, dieldrin and p, p DDE, were each treated as two distinct entities in data analysis. The procedures unique to these compounds to obtain measured concentrations are discussed in this subsection. According to Table 5 1, dieldrin had only a 12% detection rate among the FY86 composite samples. In Batches 1,

3, 4, and 5, the reported concentration levels for 29 samples ( including 4 QC samples) were below the lowest calibration standard. According to the QAPP for laboratory analysis ( MRI, 1988b), if the calculated laboratory response was below the range of calibration standards while satisfying criteria for retention time and ion ratio agreement,. thevalue was to be identified as a " not detected" result. While this approach was followed for the initial set of reported dieldrin results, the HRGC/ MS results indicated that dieldrin was indeed present in some samples whose measured concentrations were below the calibration standards. Thus the data'qualifier classification of dieldrin data was redetermined to reflect the signal to noiseratio that would have been applied if the data were above the lowest calibration standard. The quantifiable concentrations for these samples were recalculated using the signal to noiseratio to define the detection limit. This second classification of the dieldrin data resulted in a 62% detection rate among the composite samples, classifying dieldrin as a target compound for statistical analysis. Thus statistical analysis for dieldrin was performed only on the recalculated results.

5 8 ce? T') Q 37 Historically, the compound p, p DDEhas been detected in a majority of " ATS samples. However, in the FY86 analysis, the primary quantitation ion used to calculate the p, p DDE concentrations ( m/ z= 288) was saturated at the mass spectrometry detector. It is expected that using an ion for quantitation at or near saturation would result in an underestimate of the true concentration. To help remedy this situation, a secondset of p, p DDE concentrations was calculated based on a lower response ion ( m/ z= 316). The modified p, p DDEdata were obtained based on recalculated calibration curve&. Unless interferences were present under the lower response ion, most of the modified data were higher than the original data based on the primary quantitation ion. Although the modified p, p DDEdata values are likely more accurate estimates of the true sample concentrations, most of these values were higher than the highest calibration standard. This caveat should accompany any conclusions made on the reported p, p DDE data from the FY86 NHATS.

ADJUSTING CONCEPJTRATION DATA FOR SURROGATE RECO RIES 5.2 Measured compound concentrations in MIATS composite samples are generally contaminated by systematic and random errors. A potential source of systematic error in the NHATS FY86 data has been identified by the recoveries of surrogate compounds spiked into the composite samples. These recoveries were much This type of higher in  86 compared with previous surveys. systematic error can lead to the conclusion that measured concentrations for a compound are increasing over time, when in fact the true concentration has remained constant during the period. Statistical methods for characterizing trend in compound concentrations should focus on how the true concentration changes over time rather than how the average measured concentration changes. Dinh ( 1991) has developed a statistical technique to estimate true concentration levels in tkie " ATS. This technique used the recoveries of surrogate 5 9 @. K? i: p 0QE3 I I /.

compounds to adjust the measured concentration data of native compounds. The result is a more accurate representation of the true concentration of native compounds over time. The " ATS statistical analyses summarized in this report, including trends analyses, were conducted on FY82, FY84, and FY86 data that were first adjusted by applying this technique. A discussion of this technique follows.

5.2.1 Data Adiustment Method The statistical technique developed by Dinh ( 1991) for adjusting native compound concentrations was based on fitting a systematic errors in variablesmodel to the NHATS data ( see Sections <IP_ADDRESS> and <IP_ADDRESS>). This model predicted the measupd concentration as a linear function of the unknown true concentration. In turn, the expected value of the unknown true concentration given the measured concentration was estimated from the model fit. This latter result was considered an " adjustmentgg to the measured concentration and provided a more accurate estimate of the unknown actual concentration. To estimate the expected value of an unknown true concentration in a composite sample, it was necessary to obtain accurate characterizations of recoveries and true concentrations for the native compounds. This information was best represented by analysis results on surrogate compounds. As part of the daily QC procedure, several surrogate compounds were injected at known concentrations into each " ATS composite sample. Surrogate compounds do not naturally exist in composite samples; thus the actual concentration of a surrogate compound in a sample is known to equal to the amount spiked into the sample. As a result, the recovery levels for surrogate compounds provided information on overall method performance and accuracy. While recovery data were available for native compounds as well as surrogate compounds, only recoveries for surrogate compounds were used to adjust the measured concentrations of native compounds. Native compound recoveries were excluded for the following reasons:

native compound recoveries can be affected by contamination and interferences of unknown magnitude,

m native compound recoveries were available only for the 15 spiked QC samples, while surrogate recoveries were available for all NHATS samples.

Each surrogate compound spiked into an " ATS composite sample represented a class of one or more native compounds of interest. The surrogate compounds and the native compounds represented by each surrogate are listed in Table 5 2. When possible, a native compound was linked directly to its surrogate counterpart, such as lindane and chrysene. However, most native compounds did not have a direct surrogate counterpart included in the spiking. These compounds were associated with an average result across multiple surrogates in the relevant chemical group. The methods used to adjust the measured concentrations of composite and QCsamples are now discussed.

<IP_ADDRESS> Composite Data Adjustment. In this procedure, the measured concentration of a compound is assumed to be linearly related to the actual compound concentration in a composite sample. Let C be the number of " ATS composite samples analyzed, let Yibe a measured concentration of a compound in the i& " ATS composite sample ( ill,..., C), and let gi be the compound's >

unknown true concentration in the sample. Then x ri 1 Yi = Rpi + ei , ( 5 1)

where R is the unknown recovery of the compound by the analytical method, and eiis random error having mean zero. Assume that pi and ei are normally distributed and are uncorrelated across the Composites. Then the expectation of pi given Yi is given by 5 11 Table 5 2. Matching NHATS FY86 Native Compounds with Surrogate Compounds Chrvsene d,, I ~~ Tr~ chl~ obenz I ene

dq11 13C6  1,2,4,5 Tetrachlorobenzene 1 1 13C6  Hexachlorobenzene Mean of above three surrosates 13C6  4 Chlorobiphenyl 13c12 3,3', 4,4' Tetrachlorobiphenyl 2,2', 3,3', 5,5', 6,6' Octachlorobiphenyl 13CI2 Decachlorobiphenyl Mean of above four surrogates Mean of tetra and octa chlorobiphenyl surrogates t 13C  Heptachlor Lindane d6 '

Mean of above two surrogates I 41 49 20 22 23 25 27 17 19, 26 50 53 57 59 51, 52, 58 54 56 12 9 1 8, 10 11, 13 16, 60 62, 85 86. 98 102, 106 107 Mean of all ten surrogates above 28 40, 63 84, 97 97, 103 105, 108 111 5 12 11 where Thus the true concentration pi in the i* composite sample ( i= l,..., C) is estimated by substituting estimates of the unknown parameters A, R, and E( Yi) in equation ( 5 2). The arithmetic mean of the observed Yiacross the 50  composite samples, denoted by Y, serves as an estimate for E( Yi)

in equation ( 5 2). Estimates for A and R were obtained by fitting the regression model in ( 5 1) to measured concentrations of surrogate compounds. Let pi be the concentration at which a surrogate compound is spiked into composite sample i, and let Yi be the resulting measured concentration of the surrogate compound in the sample. Because pi represents a true concentration, the linear regression model in ( 5 1) was fit 20 the composite sample data to obtain a least squaresestimate ( R) of the recovery R for the surrogate compound. The " r squared" value from the regression ( the regression sum ofA squares divided by the total sum of squares) is the estimate ( A) for the adjustment coefficient A. Substituting these parameter estimates in equation ( 5 2) leads to an estimate of the actual concentration in the composite sample:

pi = [ ( l A) Y++ AYi] / 8 ( 5 3)

Thus for a given composite sample, Formula ( 5 3) represents an adjustment to the measured concentration for a given semivolatile compound.

5 13 Table 5 3 lists the estimates of R and A for all compounds in the FY82, FY84, and FY86 NfiATS for semivolatiles. For FY86, these estimates are base'd on only those composite samples with a wet weight of at least ten grams. This table shows the relatively high recoveries in FY86 for most surrogate A compounds ( valuesof R greater than one) compared with the other fiscal years. Meanwhile, the estimated recoveries were similar for FY82 and FY84. Among the three fiscal years in Table 5 3, spiked and measured concentrations for surrogate compound data were only available for the FY84 and FY86 NiiATS. Thus only for the FY84 and FY86 NHATS could the parameters R and A could be estimated by fitting the linear regression model in equation ( 5 1). In contrast, only recovery data were available for surrogate compounds in the FY82 " ATS. As a result, an estimate of R for a given surrogate compound in the FY82 NHATS was calculated'by averaging the observed sample recoveries. Because an estimate of A could not be determined from the available FY82 surrogate data, the corresponding estimates of A from the FY84 data were applied to FY82.

<IP_ADDRESS> QC Data Adjustment. A slight modification to the approach in <IP_ADDRESS> was needed to adjust the measured concentration of a native compound in an analytical sample when a portion of the concentration in the sample was known. This situation occurred when the sample was spiked with a known amount of the compound. For example, ten of the FY86 NHATS QC samples were spiked with 36 native compounds prior to analysis. The known portion of the concentration must be considered when estimating the entire actual compound concentration in the sample. Suppose that the i* QC sample was spiked with a native compound at a known concentration Si. Let the unknown concentration of the native compound in this sample be pi before f 5 14 1 Table 5 3. Estimates of R and A for Surrogate Compounds Trichloro benzene Tetrachloro benzene Hexachloro benzene Other Chloro benzenes(@

Chrysene and other PAH compounds Monochloro biphenyl Tetrachloro biphenyl Penta, ._. .:..,\ Hexa, and Heptachlor0biphenvlm Octachloro biDhenvl , Pesticide group( 4)

Chlorobenzene group 1 0.5089 0.8697 0.2915 0.8697 0.6203 0.9100 0.4374 0.9301 0.4400 0.9301 0.7666 0.9290 0.5788 0.9716 0.5658 0.9716 0.9940 0.9413 0.5089 0.9514 0.4325 0.9514 0.7586 0.9315 ..

PA8 group 7 0.5858 0.9805 0.6500 0.9805 . 1.0088 0.9743 PCBa group 0.6223

' 0.6798 0.9552 0.6452 0.9552 0.5089 0.9696 0.6455 0.9696 1.2018 0.9154 0.4968 0.9662 0.6456 0.9662 I 0 8975 5 15 Table 5 3. ( cant.)

Diethyl 0.5764 0.9032 0.6313 0.9032 1.0369 phthlate II Di n butyl 0.5764 0.7850 0.4472 0.7850 phthalate I1.0369 0.9340 I Butyl benzyl 0.5764 0.6145 0.4059 phthalate N Other 0.5764 0.8235 0.4948 0.8235 1.0369 0.9340 phthalates w F Other 0.5764 0.9558 0.6637 0.9558 1.0369 0.9340 compounds L Notes for Table 5 3 Grouping of compounds without direct surrogate counterparts for FY86 is documented in Table 5 2.

 ) Estimates of A for FY82 are taken from FY84 estimates.

 ) Composite samples having ten or more grams wet weight were used in determining estimates for R and A.

( 4) Surrogates for pesticides were not analyzed in  82 or FY84. Estimates for these two years are based on the linear regression in ( 5 1) where Yi and pi are substituted by the average of the spiked and found concentrations across all surrogates.

(  The estimates of R and A for FY86 are obtained by the linear regression in ( 511 where Yi and pi are substituted by the average of the found and spiked concentrations, respectively, of surrogate heptachlor and lindane.

5 16 Table 5 3. ( Coat.)

The estimates of R and A are obtained by the linear regression in ( 5 1) where yi and /+ are substituted by the average of the found and spiked concentrations, respectively, of surrogate tri, tetra, and hexa chlorobenzene.

0 The estiwtes of R and A are obtained by the linear regression in ( 5 1) where yi and pi are substituted by the average of the found and spiked concentrations, respectively, of surrogate tetra and octa chlorobiphenyl.

The estimates of R and A are obtained by the linear regression in ( 5 1) where Yiand pi are substituted by the average of the found and spiked concentrations, respectively, of surrogate mono, tetra, octa, and decachlorobiphenyl

0 Surrogates corresponding to phthalates were not analyzed in FY82. Surrogate phthalate data in FY86 were not analyzed due to the prevalence of missing values. Estimates of R and A for phthalates in FY82 and FY86 are based on the linear regression in ( 5 1) where Yi and pi are substituted by the average of the spiked and found concentrations across all surrogates.

( lo) Estimates of R and A for all compounds not represented on other rows of this table are based on the linear regression in ( 5 1) where Yiand pi are substituted by the average of the spiked and found concentrations across all surrogates.