&EPA
            United States
            Environmental Protection
            Agency
                Office of
                Toxic Substances'
                Washington DC 20460
, EPA-560/5-87-002A
 May, 1987
            Toxic Substances-
CHARACTERIZATION OF HRGC/MS
UNIDENTIFIED PEAKS FROM THE ANALYSIS OF
HUMAN ADIPOSE TISSUE
VOLUME I - TECHNICAL
                                                   Printed on Recycled Paper

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CHARACTERIZATION OF HRGC/MS UNIDENTIFIED PEAKS FROM THE
           ANALYSIS OF HUMAN ADIPOSE TISSUE

             VOLUME I:  TECHNICAL APPROACH
                          by

                     Jon D. Onstot
                   Randall E. Ayling
                    John S. Stanley
                     FINAL REPORT

              EPA Contract No. 68-02-4252
                Work Assignment No. 23
               MRI Project No. 8823-A01

                     June 30, 1987
                      Prepared  for:

            National Human Monitoring  Program
              Field Studies  Branch  (TS-798)
              Exposure Evaluation Division
        Office of  Pesticides and Toxic Substances
          U.S.  Environmental  Protection Agency
                  401 M  Street, S.W.
                  Washington, DC  20460

    Attn:   Ms.  Janet Remmers, Work  Assignment Manager
           Dr.  Joseph  J.  Breen, Program Manager

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                                 DISCLAIMER


This document has been reviewed and approved for publication by the Office of
Toxic Substances, Office of Pesticides and Toxic Substances, U.S. Environmental
Protection Agency.   The use  of trade names or  commercial  products  does not
constitute Agency endorsement or recommendation for use.

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                                   PREFACE


          This report describes Midwest Research Institute's approach to
characterize unidentified chromatographic peaks in HRGC/MS data collected
from the analysis of human adipose tissue for general volatile and semi vola-
tile organic compounds.  This report is provided as two separate volumes.
Volume I describes the technical approach and presents a summary of the
results based on frequency of observation by age group and census_region.
Volume II is an appendix to Volume I and contains additional details on
frequency of occurrence for both identified and unidentified peaks based on
census region, census division, and age.  This report focuses on the approach
to identifying compounds from the HRGC/MS spectra.  The frequency of detection
of specific compounds is presented.  The HRGC/MS data were collected for_46
samples prepared as composites from individual specimens of the U.S. Environ-
mental Protection Agency's fiscal year 1982 (FY82) National Human Adipose
Tissue Survey (NHATS) repository.  The sample collection, compositing, and
the analysis of the composites for specific volatile and semivolatile  organic
compounds are described in detail  in separate reports (Stanley 1986b,  Stanley
1986c).

          This  approach to the  characterization  of HRGC/MS  unidentified  peaks
was developed and  conducted  for the  EPA's  Office of Toxic  Substances,  Field
Studies  Branch  (EPA Contract No.  68-02-4252,  Work Assignment 23,  Ms.  Janet
Remmers,  Work Assignment  Manager,  .and  Dr.  Joseph Breen,  Project Officer.
This  report was prepared  by  Mr.  Jon  Onstot with  assistance from Mr.  Randall E.
Ay!ing and  Dr.  John S.  Stanley,  MRI  Work Assignment Leader.
                                              MIDWEST RESEARCH INSTITUTE
                                              Paul C.  Constant
                                              Program Manager
 Approved:
 Jack Balsinger
 Qua-Hsj:y/Assurance Coordinator
    in E. Going, Director
   lemical Sciences Department
                                       m

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                              TABLE OF CONTENTS

                                                                         Page

List of Figures	     v]
List of Tables	    V11
Executive Summary 	 	     1X
I.         Introduction
               A.  Broad Scan Analysis Strategy ...... .....      1
               B.  Work Assignment Objectives ............      2
               C.  Significance ...................      2
               D.  Organization of this Report.  ... ........      3

II.       Recommendations ......................      3

               A.  Refinements to the Identification Method .....      3
               B.  Compound Confirmation ...............      4
               C.  Additional Investigation of Remaining Unknown
                     Peaks ......... . ............      4
               D.  Further Investigations  . „ ............      6
III.      Experimental Procedure
               A.  Description of  Identification Method  .......      6
               B.  Description of  ACORN  ...............      7
               C.  Library Search  Criteria ..............      9
               D.  Retention Time  Test.  ...  ............      9
               E.  Manual Review of ACORN Results  ..........      10
               F.  Application of  the  Identification  Method  to  FY82
                      NHATS Data Set .................      13

 IV.        Results  .... ............  :  .........      18

 V.         Discussion .....................  ....      49

               A.  Limitations of  the  Peak  Identification Method.  .  .      49
               B.  Limitations of  the  FY82  Data ...........      50

 VI.        References .........................      57

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                               LIST OF FIGURES

Figure                              Title                                Page

   1       Flowchart of ACORN peak identification program 	  ;.       8

   2       Library search results of unknown peak with multiple
             candidate compound .identifications	      11

   3       Example of an ACORN summary report 	  '.      12

   4       Example of the manual review of RRT values using a       :
             "master RIC"	•      14

   5       Reconstructed ion chromatogram (RIC) of volatile compos-
             ites from the 0-14, 15-44, and 45+ age groups from the
             South Atlantic (SA) census division	      15

   6       Reconstructed ion chromatogram (RIC) of 6% Florisil
             semi volatile composites for the 0-14, 15-44, and 45+
             age groups from the New England (NE) census division .  .      16

   7       Reconstructed ion chromatogram (RIC) of 15/50% Florisil
             semivolatile composites for the 0-14, 15-144, and 45+
             age groups from the West North Central (WN) census
             division	      17

   8       Example of degradation of mass spectral quality as a
             result of instrument saturation	      51
                                                          „•

   9       Library search results of an unknown peak with inadequate
             fragmentation for reliable identification	      53

  10       RIC chromatogram with hydrocarbon "hump" 	      55

  11       Mass spectrum of a representative scan from the
             hydrocarbon "hump"	      56

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                               LIST OF TABLES

Table                               Title                                Page

  1        Compounds Tentatively Identified in the Volatile Organic
             Analysis Data Set vs.  Frequency/Age Group	    19

  2        Compounds Tentatively Identified in the 6% Florisil Semi-
             volatile Organic Analysis Data Set vs. Frequency/Age
             Group	•    21

  3        Compounds Tentatively Identified in the 15/50% Florisil
             Semi volatile Organic Analysis Data Set vs.  Frequency/Age
             Group	    23

  4        Compounds Tentatively Identified in the Volatile Organic
             Analysis Data Set vs.  Frequency/Census Region	    25

  5        Compounds Tentatively Identified in the 6% Florisil Semi-
             volatile Organic Analysis Data Set vs. Frequency/Census
             Region	    27

  6        Compounds Tentatively Identified in the 15/50% Florisil
             Semivolatile Organic Analysis Data Set vs.  Frequency/
             Census  Region	    29

  7        Unidentified Peaks in the Volatile Organic Analysis Data
             Set vs. Frequency/Census Region  	    31

  8        Unidentified Peaks in the 6%  Florisil Semivolatile
             Organic Analysis Data Set vs. Frequency/Census Region  .  .    34

  9        Unidentified Peaks in the 15/50% Florisil Semivolatile
             Organic Analysis Data Set vs. Frequency/Census Region  .  .    40

  10        NHATS FY82 Composite Peak Inventory - Volatile Organic
             Analysis Data Set	     46

  11        NHATS FY82 Composite Peak Inventory - 6% Florisil
             Semivolatile Organic Analysis Data Set 	     47

  12        NHATS FY82 Composite Peak Inventory - 15/50% Florisil
             Semivolatile Organic Analysis Data Set 	     48

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                              EXECUTIVE SUMMARY


          The National Human Adipose Tissue Survey (NHATS) provides the EPA
Office of Toxic Substances with a unique mechanism for establishing exposure
of the general U.S. population to toxic compounds.  This monitoring program
has been used primarily for establishing exposure trends for organochlorine
pesticides and PCBs.  The adipose specimens collected in fiscal year 1982
(FY82) were analyzed as composites for general volatile and semi volatile or-
ganic compounds as part of an effort to expand the use and capabilities of
the NHATS program.  This effort was undertaken as a means to detect poten-
tially toxic compounds that might be entering the environment.

          The FY82 samples were composited into 46 samples and were analyzed
by high resolution gas chromatography/mass spectrometry (HRGC/MS).  Quantita-
tive data were reported for a specific list of volatile and semi volatile or-
ganic compounds.  The response to these compounds is a fraction of the total
HRGC/MS response for each of the composites.  Many of the peaks in the HRGC/MS
chromatograms remain unidentified.  As part of the effort to document human
exposure to toxic chemicals, it is necessary to identify as many of these re-
sponses as possible.

          A method for the automatic identification of unknown HRGC/MS peaks
was developed and applied to the volatile and semi volatile datafiles.  The
files were analyzed in three groups:  volatiles,  and semivolatiles from two
fractions collected from Florisil cleanup (6% diethyl ether/hexane, and 15/50%
diethyl ether/hexane).

          The method consisted of the following steps:  automatic  identifica-
tion of unknown spectra via comparisons to reference mass spectra, transfer
of the results to a microcomputer for additional  processing, compilation of
the transferred data  into a spreadsheet program,  and generation of compound
identification tables from the spreadsheet.  A computer program, called ACORN,
was written to perform the automatic identification step.

          Application of this method to the three sets of data  resulted in
the identification  of 121 compounds in the volatile samples, 81 compounds in
.the 6% Florisil semivolatiles, and 96 compounds in the 15/50% Florisil semi-
volatiles.  These  compounds are in addition to the compounds identified and
quantitated in the  target cbmpound search previously reported  (Stanley 1986a,
Stanley 1986b, Stanley 1986c).  Identified compounds were grouped  into 18
chemical classes  for  the volatiles, 22 classes for the 6% Florisil semivola-
tiles, and 21 classes for the 15/50% Florisil semivolatiles.  Compound classes
included saturated  and unsaturated hydrocarbons,  aldehydes,  ketones,  steroids,
heterocyclic  compounds, drugs, aliphatic and  phthalate esters,  phenols, halo-
carbons, and  methyl-substituted organosiloxanes.

          An  additional 99  spectra remained unidentified  in  the volatile  sam-
ples, and 258 and 343 spectra in  the 6% and 15/50% Florisil  semivolatiles,
respectively.

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I.   INTRODUCTION

          The National Human Adipose Tissue Survey (NHATS) is the main opera-
tive program of the National Human Monitoring Program (NHMP).  The NHMP was
first established by the U.S.  Public Health Service in 1967 and was subse-
quently transferred to the U.S.  Environmental Protection Agency in 1970.
During 1979 the program was transferred within EPA to the Exposure Evaluation
Division (EED) of the Office of Toxic Substances (OTS).

          NHATS is an annual program to collect a nationwide sample of adipose
tissue specimens and to chemically analyze them for the presence of toxic com-
pounds.   The objective of the NHATS program is to detect the level and pre-
valences of the compounds in the general population.   The NHATS data are
used to address part of OTS's mandate under the Toxic Substances Control  Act
(TSCA) to assess chemical risk to the U.S. population.  The specimens are
collected from autopsied cadavers and surgical patients according to a statis-
tical survey design (Lucas, Pierson, Myers, Handy 1981).  The survey design
ensures that specified geographical regions and demographic categories are
appropriately represented to permit valid and precise estimates of baseline
levels, time trends, and comparisons across subpopulations.  Historically,
organochlorine pesticides and PCB residues have been selected for evaluation.

     A.   Broad Scan Analysis Strategy

          EPA/OTS has recognized the need to provide a more comprehensive
assessment of the toxic substances that accumulate in adipose tissue.  An
aggressive strategy to assess TSCA-related substances that persist in the
adipose tissue of the general U.S. population has been developed by EED.   The
NHATS specimens collected during fiscal year 1982 (FY82) were selected for a
broad scan analysis of volatile and semivolatile organic TSCA-related chemi-
cals (Mack, Stanley 1984).

          The initiative to achieve a more comprehensive assessment necessi-
tated either the development of new methods or the modification of the exist-
ing analytical procedures, specifically high resolution gas chromatography/
mass spectrometry (HRGC/MS).  Data on organochlorine pesticides and PCBs re-
ported for the NHATS specimens up to the FY82 collection are based on packed
column gas chromatography/electron capture detector (PGC/ECD) analysis.

          Under a previous work assignment program for EPA/OTS, Midwest
Research Institute (MRI) conducted the analysis of human adipose tissue as
composites for a specific list of organic compounds (Stanley 1986a, Stanley
1986b, Stanley 1986c, Stanley 1986d).  Forty-six composites from the NHATS
FY82 collection period were analyzed for volatile and semivolatile organic
compounds by HRGC/MS.  Although the broad scan analysis approach for a spe-
cific list of compounds provided EPA/OTS with an expanded  list of potentially
toxic compounds in adipose tissue, a number of peaks observed in the HRGC/MS
reconstructed ion chromatograms (RIC) were not identified.

          Preliminary procedures were developed to automatically characterize
the unidentified peaks, and a pilot study of 10 samples was conducted to test
the procedures.  Results of this pilot study proved encouraging enough to
launch the study of the entire volatile and semivolatile sample set.

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     B.   Work Assignment Objectives

          The work assignment had three major objectives:   (1) automatically
characterize HRGC/MS chromatographic peaks (i.e., identify compounds by name)
via comparison of unknown spectra to NBS mass spectral  library reference
spectra; (2) compile a comprehensive database of mass spectra observed in the
NHATS composite samples; and (3) determine the frequency with which each com-
pound or unidentified mass spectrum was observed in the sample set.

     C.   Significance
of
          At the present time, the NHATS program is limited to the screening
   a predetermined list of toxic substances.   The philosophy of using a rela-
tively small list of target compounds is common in programs requiring GC/MS
analysis of large numbers of samples.  The advantages of this technique are
numerous.  Acquisition of full scan HRGC/MS data for target compound analysis
is standardized and does not usually require extensive setup time.  Operating
conditions for target compound analysis may be optimized for a particular
sample type and anticipated concentration range, resulting in good sensitivity
for most compounds.  The post-acquisition target analyte identification and
quantisation step is relatively fast, usually requiring less than 30 s per
compound.  Finally, both acquisition and quantitation may be easily automated.

          However, a major drawback to the target compound approach is that
nontarget HRGC/MS peaks do not enter into the analysis process.  As a result,
the overall significance of a sample or population of samples may be incor-
rectly interpreted.  The situation is unfortunate because the mass spectral
information necessary for unknown compound identification is available from
datafiles acquired for target compound analysis.

          The reason why this information is not typically used for unknown
peak identification is straightforward:  the technology to automatically
process mass spectral information on this scale has not kept pace with the
technology to acquire it.  As a result, acquisition may take minutes, while
a complete post-acquisition analysis of unknown constituents might require
hours, days, or even months, depending on the amount of information contained
in the data.  Thus, target compound analysis may be regarded merely as a sim-
plification of the larger, more difficult goal of complete characterization
of real samples.

          This report describes a method for the automatic identification of
HRGC/MS chromatographic peaks in the data from the volatile and semi volatile
organic analysis of composite adipose tissue samples.  The method consists
of the following steps:  automatic identification of unknown spectra via com-
parisons to reference mass spectra; transfer of the results to a microcomputer
for additional processing; compilation of the tranferred data  into a spread-
sheet program; and generation of compound identification tables from the
spreadsheet.  A computer program, called ACORN, was written to perform the
automatic peak identification step.

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          Application of the method to the three sets of data resulted in the
identification of 121 compounds in the volatile samples, 81 compounds in the
6% Florisil semivolatiles, and 96 compounds in the 15/50% Florisil semivola-
tiles.  An additional 99 spectra remained unidentified in the volatile sam-
ples, and 258 and 343 spectra in the 6% and 15/50% Florisil semivolatiles,
respectively.

     D.   Organization of this Report

          Following this introductory section, Section II presents recommenda-
tions for pursuing future activities in characterizing unidentified HRGC/MS
peaks and developing a mass spectral database for adipose tissue.   Section III
is the experimental section and presents a description of the identification
method and criteria incorporated in the computer-controlled search to charac-
terize the HRGC/MS data.  The results from the application of this automated
search program are presented in Section IV.  Section V discusses the technical
difficulties that were encountered using this approach to characterize the
volatile and semi volatile HRGC/MS data.  Pertinent references are cited in
Section VI.  Supplementary tables and a listing of ACORN, the peak identifi-
cation computer program, are provided in Volume II (Appendices).


II.  RECOMMENDATIONS

          Recommendations for further activities in the area of unidentified
peaks may be divided into three major areas:   refinement of the identification
procedure; confirmation of compounds identified in this study; and further
investigation of the remaining unidentified peaks.

     A.   Refinements to the Identification Method

          A number of refinements could be made to the identification proce-
dure to improve reliability and execution speed.  Reliability could be im-
proved by more fully utilizing the available retention time information.  For
example, the work in this study relied on a single reference compound for the
calculation of the relative retention times (RRTs) of the unknown peaks.
However, procedures could be developed to include retention information for
surrogate compounds, target compounds known to be present in samples, or com-
monly observed background peaks.  This could even be extended to include the
unidentified peaks themselves.  For example,  analysis of a file might begin
with the unknown peak closest to the internal standard.  If the unknown peak
could be positively identified from the reference library, it could then be
used as the reference for the unknown peak adjacent to it, and so on until
all peaks in the file are analyzed.  Differences in retention time between
unknown and reference are minimized using this scheme, thus improving the
accuracy of the retention time test.

          A major limitation of the Incos-based liorary search routine is that
no attempt is made to judge the quality of the unknown spectrum.  The Incos
data system makes the assumption that spectra submitted to the library rou-
tines are of high quality.  Unfortunately, this assumption may not be valid
for spectra submitted in an automatic procedure.  Thus, this requires signif-
icant interaction through manual review of the data.  It would be useful if a


                                      .3

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                                                                             I

 test could be performed on the unknown spectrum which would provide a quanti-~
 tative  measure of its  quality, such as the percentage of masses  rising above
 the surrounding signal-to-noise level, whether any masses might  belong to
 coeluting peaks or background, or whether a molecular ion is present.   A
 weighted quality index might then be assigned which could be used  to assess
 the validity of subsequent library searches during automatic processing.

           Other possible refinements to the identification procedure might
 include translation of the ACORN program code to FORTRAN instead of using the
 macro or "procedural"  language of the Incos data system  and addition of more
 information to the ACORN summary report,  such as RRT and mass  spectrum quality
 index values (described above) for each peak.   Programs  could  also  be  written
 to  automatically perform a number of bookkeeping activities on the  seed li-
 brary that are presently done by an operator at a video  terminal.   Finally,
 the transfer of data from the Incos to the microcomputer could be  streamlined
 with additional  programming.   These refinements would require  an additional
 level of effort which  would probably not be recovered through  increased effi-
 ciency  on a small  peak identification project.   For large scale  peak identifi-
 cation  projects,  however,  the resulting efficiency would justify the additional
 expense.

      B.   Compound Confirmation

           It is  strongly recommended that some type of confirmatory  work be
 performed for compounds which were tentatively identified in this  study.  A
 significant number of  identified compounds could not be  traced to  a  specific
 isomer.   In other cases,  peaks could not be assigned to  specific compounds
 within  certain chemical  classes  due to the similarity of mass  spectra  within
 the class.   Examples of such  classes were the homologous series  of  hydro-
 carbons,  phthalates, isomers  of  chlorinated compounds, steroids, etc.   Am-
 biguities  might  be resolved by analysis  of standard mixtures using  HRGC/MS
 parameters  identical to those used in the original  target compound  analysis.

      C.   Additional  Investigation  of Remaining Unknown Peaks

           Many of  the  HRGC/MS chromatographic peaks  analyzed in  this study
 remain  unidentified  for two main reasons.   First,  many of the  unidentifiable
 spectra were  unsuitable  for interpretation purposes  even after computerized
 enhancement was  employed.   This  was  the major cause  of peaks not being
 identified  in  this  study.   Secondly,  the  finite  nature of the  NBS library
 prevented  some  spectra from being  identified  in  those cases when the cor-
 responding  compound  simply  was not  represented  in  the library.  Despite these
 difficulties,  additional  identifications  may  be  possible  through analysis of
 samples using  optimized  HRGC/MS  acquisition parameters,  additional  mass spec-
 tral  interpretation  programs,  or high  resolution mass spectrometry.

          1.  Optimization  of  HRGC/MS Acquisition  Parameters

          Improving  the quality  of the unknown spectra could be accomplished
by the reanalysis of a subset  of the samples  using operating conditions more
suitable for unknown peak identification.  For instance,  using a slow GC pro-
gram rate O 2°C/min) would help separate peaks that coeluted in the original

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 analyses,  thereby  improving  the  quality  of  the  mass  spectra.   Longer  GC
 columns  could  be used,  and  in  the  case of the volatile  samples  a wide bore
 "Megabore"  capillary  column  might  improve separation as well  as reduce over-
 loading.   A mass scanning range  more  appropriate  to  mass  spectral  interpreta-
 tion  of  unknowns could  be used for the semivolatiles.   Finally, samples  could
.be  analyzed at various  detection sensitivity settings in  order  to  compensate
 for differences in  unknown compound concentration levels.   The  improved  spec-
 tra could  then be  resubmitted  to the  ACORN  program.   It is  believed that a
 significant number  of unknown  spectra could be  identified from  this procedure
 alone.

           2.   Other Mass Spectral  Interpretation  Programs and Databases

           It is suspected that several peaks in this  study  were not identi-
 fied  because the corresponding reference spectrum was not present  in  the NBS
 library.   In such cases, the use of a different mass  spectral library might
 prove successful.   One  example of  a commercially  available  library is  the
 Wiley Registry of Mass  Spectra,  containing  approximately  120,000 reference
 spectra  on  a single compact disk (CD) for use with an IBM-PC.   A similar al-
 ternative  is to submit  unidentified spectra of off-site mass  spectral  inter-
 pretation  services,*such as the  Self-Training Interpretive  Retrieves!  System
 (STIRS)  and  Probability Based  Matching (PBM) programs available from  Cornell
 University  (Kwok, Ventkatarughaver, McLafferty 1973; McLafferty, Hertel,
 Villwock 1974; Martinsen, Song 1985).   A disadvantage to  both of these
 approaches  is  that  a  significant effort would be  required to  convert  the
 large number of remaining unknown  spectra to a format compatible with  the
 other data  systems.

          3.   High  Resolution  GC/High Resolution  MS

          Additional  information could be gained  by  reanalysis of  a subset of
the samples  using high resolution  GC/high resolution MS (HRGC/HRMS).    HRMS
provides accurate mass information  for ions observed in mass  spectra.   Mass
assignments with an accuracy of  approximately 5 millimass units (mmu)  are
achievable for broad  scan capillary GC analysis in high resolution mode.   Ac-
curate mass  values  are primarily used to calculate possible elemental   formulas
for the molecular and fragmentation ions.   This information could  be  used both
to confirm the NBS-derived compound assignments and to provide additional in-
formation concerning  unidentified  peaks.

          4.  Chemical lom'zation

          Additional  information could also be gained from reanalysis  using
chemical  ionization GC/MS.   This technique  typically produces a stronger
signal in^the molecular ion than electron impact  ionization (El).   Thus,
chemical  ionization could provide  confirmation for a number of compounds
which have similar El spectra,  but different molecular weights.   An example
is the class of straight-chain hydrocarbons, which exhibit nearly  identical
spectra in the low mass  range and which do  not usually produce molecular ions
in El.

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          5.  Additional Manual Interpretation

          Most of the manual work performed in this study involved reviewing
the results of the automatic peak identification procedure.   However, addi-
tional interpretation could be manually performed on the remaining unidenti-
fied peaks.  Manual interpretation could potentially provide information not
readily available from a spectral matching approach, such as compound class,
functional groups and molecular weight.

     D.  Further Investigations

          The results of this study should be examined for significance to
further efforts involving the screening of adipose tissue.   This would in-
clude determining the source, concentration, exposure and level of toxicity'
of the identified compounds.


III.   EXPERIMENTAL PROCEDURE

          This section describes the steps involved in the peak identification
procedure and their application to the FY82 data.  A brief overview of the
identification method is provided, followed by a discussion of ACORN, the com-
puter program written to automatically perform the identification step.  Var-
ious aspects of the computer program as they related to the identification
process are discussed.  Finally, the application of the identification ,method
to the FY82 data is described.

     A.  Description of Identification Method

          A general method for the identification was devised which consisted
of three major steps.  The first step involved the selection of peaks to be
analyzed.  This was accomplished through a combination of manual peak selec-
tion and use of the automatic peak selection routine provided in the CHRO pro-
gram of the Incos data system.  A first-pass peak selection was performed
using CHRO.  The results of the selection were then manually reviewed.  Manual
review of the automatic peak selection procedure was necessary because the
program occasionally had difficulty determining the correct apex of peaks lo-
cated on the shoulder of others peaks.  The program also failed to properly
select very broad peaks.

          The second step was the identification procedure itself.;  A computer
program, ACORN, was written which performed the identification procedure auto-
matically.  The program was designed to operate on a single file at a time,
allowing an opportunity for a manual review of the results before proceeding
to the next file.
                                      6

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          The.third step of the method involved the transfer of the results
of the identification program to a microcomputer for further data processing.
It was necessary to perform this additional data processing on another com-
puter because the Incos data system did not have the software necessary to
perform the desired tasks.   An Apple Macintosh with a 20-megabyte Winchester
hard disk drive was used for both the transfer step and the additional data
processing.  The transfer was relatively straightforward since the Macintosh
also functioned as the display terminal for the Incos data system via terminal
emulation software.  Since all the transferable information was in text for-
mat, the transfer process simply involved instructing the Incos to display
the information on the Macintosh screen while in terminal emulation mode, and
then instructing the Macintosh to "capture" or store the displayed data to
its own disk.   The transferred text was then reformatted so that it could be
loaded into a spreadsheet program.

          The final step of the method, compilation into the spreadsheet pro-
gram and generation of data tables, was relatively straightforward.  Microsoft
EXCEL for the Macintosh was the spreadsheet program chosen for this study.
Three main spreadsheets were produced from the FY82 data, each spreadsheet
consisting of compound information from one of the three types of analysis.
Each spreadsheet was arranged as a two-dimensional array of samples vs.  com-
pounds identified in the samples.  Once the main spreadsheets were compiled,
summary tables were generated which listed such information as compound name,
CAS registry number, compound formula, relative retention time (RRT), as well
as frequency of occurrence within certain age groups and geographical regions.

     B.   Description of ACORN

          The most essential element of the method was the computer program
which automatically performed the compound identifications.   The program,
called ACORN,  was written using a combination of FORTRAN and the "procedural"
or macro language of the Finnigan/Incos data system.   ACORN was designed to
perform a "two-tiered" forward library search on each HRGC peak in a datafile,
as shown in the program flowchart in Figure 1.   Under this scheme, each spec-
trum in a datafile was first compared against a special  mass spectral library
of dynamic length, hereafter referred to as the "seed" library.   The library
search produced a list of possible candidates based on comparison of two sim-
ilarity index values,  FIT and PURITY, to preset threshold values.   Candidate
spectra with similarity index values above the threshold were further screened
using an RRT test.

          If a suitable match could not be found in the  seed library, a second
library search was conducted using the standard NBS library as the reference
library.   Since no RRT data are provided in the NBS library, selection of the
best reference candidate was determined solely by comparing FIT and PURITY
values to preset threshold  values.   If a suitable match  was  found in the NBS
library,  the NBS spectrum was appended to the seed library.   If a match could
not be found in either the  seed or the NBS library, the  unknown spectrum it-
self was appended to the seed library and assigned the name  "Unidentified
Peak."  Since spectra  were  added to the seed library only on the precondition
that they had not previously been observed in the data set,  the seed library
served as a comprehensive database of unique spectra observed in a given data
set.

-------
                                x—\
                                 BEGIN
                       Get the ncxl unknown peak for
                               procassing
                      Search the seed library for beat
                         match. Include similarity
                       Ihrsanold tsat and rsui. tsac
             YES
                        Search NBS library for best
                                 match
                        Append unknown spactrum to
                           seed library with name
                            "Unidentified Peak'
                        Update summary report with
                          results of identification
                                procadura
                                                        Append NBS spectrum with best
                                                           match to the saad librar1/'
Figure  1.   Flowchart  of  ACORN  peak  identification program.

                                       8

-------
     C.  Library Search Criteria

          As stated previously, a two-tiered library searching scheme was ap-
plied in ACORN.  This approach was used for the following reasons.  First, it
provided the basis for the design of the automatic compilation of the "seed"
library.  Second, ACORN execution time was reduced.  The seed libraries com-
piled from the data in this report contained 249, 432, and 537 entries for
the volatile, 6% and 15/50% Florisil semivolatile samples, respectively.   The
version of the NBS library used in this study-contained 42,222 reference spec-
tra (Heller, Milne 1983).   Since the time required to perform a library search
is roughly proportional to the number of spectra in the reference library, a
typical search using any of the seed libraries required only a fraction of
the time necessary to perform the same search against the iNBS library.  And
third, the two-1ibrary-approach provided a simple means of implementing the
RRT test.

          Both the seed and NBS library searches were performed using the
standard Incos library search program, called LIBR.  When a library search of
an unknown spectrum is performed, LIBR calculates two values for each refer-
ence spectrum which relate to its similarity to the unknown spectrum.  These
values, called FIT and PURITY, range from 0 to 1000.  A value of 0 for either
FIT or PURITY indicates no similarity, while a value of 1000 indicates max-
imum similarity.  FIT and PURITY values may be negatively affected by such
conditions as the presence of background contamination or coeluting peaks.

          The ACORN program tested minimum FIT and PURITY values to determine
whether an unknown spectrum was found in the seed or NBS libraries.  Threshold
limits were determined by evaluating the result of using various values when
applied to library searches of a set of test spectra.  It was found that
searches of the seed library could be performed reliably using PURITY and FIT
values of 300 and 800 for the volatile samples, and 600 and 800 for the semi-
volatile samples.  NBS library searches required PURITY and FIT values of 800
and 900 for both volatiles and semivolatiles.

          Threshold values were relatively relaxed in the seed library search
because the additional RRT test tended to reduce the number of false positive
identifications.  The NBS search, with no RRT test, required more stringent
threshold values in order to assure a high degree of confidence in compound
identification.  Volatile samples required different threshold values than
the semivolatiles primarily because of differences in operating conditions.
A discussion of these differences is presented in Section V.

     0.  Retention Time Test

          A major limitation of the standard Incos library search routine was
that it often provided more than one acceptable candidate from the available
choices.  This situation often arose for isomers of a single compound, such
as the various PCBs, or for a family of structurally related compounds whose
spectra were dominated by fragmentation ions characteristic for the common
molecular skeleton.  Examples of this type were the various straight-chain
hydrocarbon series, fatty acid esters, and phthalates.  In such cases, the
library search routine was unable to reliably select a match from the various

-------
candidate spectra because each of them was equally valid from a spectral
point of view.  An example of multiple candidate reference spectra is shown
in Figure 2.  In this example, the results of an NBS library search conducted
on an unknown peak are displayed.  The first section of the results output
shows various information about the sample itself, followed by a table of the
three best candidate spectra from the NBS library and their FIT and PURITY
values.   Following the table, a graphic comparison of the unknown spectrum
and the three candidates is given.  As can be seen from the FIT and PURITY
values and the graphic comparisons, all three candidates are very similar to
the unknown spectrum, and further selection using the available data is im-
possible.

          In order to differentiate the numerous observed compounds with sim-
ilar spectra, an RRT test was employed to take advantage of the fact that com-
pounds with similar mass spectra had unique retention times.  The test was
performed immediately after the seed library search, utilizing information
provided by the search.  This test compared the unknown GC peak's RRT to the
RRT values of each of the candidate spectra.  A final candidate was chosen
from entries passing the previous tests by selecting the entry with the RRT
closest to the unknown.  A match was considered successful if the final
candidate passed the library similarity test, had the closest RRT to the un-
known of all candidates passing the library test, and whose predicted reten-
tlon time (calculated as RRTcandidate * RT  t  n   standard fell within a
window ± 15 s from the unknown.

     E.   Manual Review of ACORN Results

          Upon completion of each sample analysis using ACORN, a summary re-
port was produced which listed information about the search results of each
analyzed peak.  An example of an ACORN summary report is shown in Figure 3.
In this example, 40 unknown peaks were analyzed, as indicated in the Peak No.
column.   FIT and PURITY values for best match in the library in which each
peak was found are also given.  For those peaks which were found in the NBS
library, the corresponding NBS library entry number is provided.  The column
titled "CURRENT ENTRY" shows either the seed library entry number which was
the best match to the unknown spectrum or the seed entry number to which an
NBS or unknown spectrum was appended.

          The results of the program were then manually reviewed.  The first
step of the review consisted of checking the ACORN summary report to verify
that the program had operated properly.  Next, each mass spectrum appended to
the seed library was checked to ensure that it was indeed a newly observed
spectrum.  This was accomplished by manually examining the MBS search results,
such as shown in Figure 2, for each appended spectrum.  As can be seen in the
figure, this output provides a ranking of the three best candidate reference
spectra in addition to the unknown spectrum.  The ACORN program always se-
lected the first ranked candidate spectrum for addition to the seed library.
However, if it was determined from manual review that other candidate spectra
were equally valid choices, the name of the compound was changed to reflect
the uncertainty of the selection. ' For example, the name of the compound asso-
ciated with the spectrum shown in Figure 2 was changed to "Cs substituted
naphthalene."  Finally, the RRT, PURITY, and FIT values.were checked for all
                                      10

-------
Library S«arch
                                                                   "
   ~  »«"«*Tta in LIBRARYNB s.arch.d  for maximum PURITY
   99  «iatch.d at l.ast  6 of the 16 largest p«.iks in  th.  unknown
Rank  In.
               Nam«
Rank  Formula
1     C13. H24
2     C13. H24
3     C13. H24
M. Ht 3. Pk    Puritq    Fit
 204   161       362    964
 204   161       331    970
 204   161       336    947
                                                     RFit
                                                      873
                                                      339
                                                      342
    1231
           UBWSY SEWffl
                 11:12:39
             l£: 7381 3'>Mi
           caos.t -iTseew rae; im ces-san
           snetcst  S3    3ftSc iVZi ISl
                                    3    SIC;   33*3.
 3 PK 1S1
 iWMC  [
 QS.H24
   ,11S1  •
 C13.H24
 HUT1®
 3 PK ISl
 &H<  3
 nn1 at
                               149
                                           :sa-
 Figure  2.   Library  search results  of  unknown peak  with  multiple
                  candidate  compound  identifications.
                                       11

-------
   ACDRN LIBRARY SEARCH RESULTS
                                                 FILENAME: 79O1D2335
PEAK
NO.

1
2
3
4
3
6
7
3
9
10
11
12
13
14
15
16
17
19
19
20
21
22
23
24
25
26
27
2B
29
30
31
32
33
34
3S
36
37
33
39
4O
SCAN
NO.

234
261
305
334
348
337
36O
363
373
330
334
399
417
428
441
461
476
436
490
525
634
3O7
345
396
922
943
994
1043
1069
1090
1104
1171
1232
1263
1303
1314
1323
1438
1465
1308
PEAKS
/SCAN

7
9
14
1 O
* w
1?
IS
15
17
26
6
10
10
7
3
4
9
12
10
10
17
15
30
9
26
9
7
9
26
10
3
33
39
32
23
27
79
54
59
IS
19
BEST

FIT
906
933
393
397
993
962
954
333
973
947
729
990
79O
993
996
995
993
946
366
817
1000
993
906
947
676
9O3
702
89O
731
533
953
971
937
772
700
872
913
930
655
323
BEST

PURITY
622
79O
563
391
934
959
9--50
370
942
947
345
307
377
794
913
372
779
62O
617
364
aoo
736
9O6
907
449
594
545
316
743
323
36O
926
345
310
491
346
633
773
537
37O
SE3T
NBS
ENTRY
5352
6202
9533







21473
3692
31109
193O
1391
4155

11863
13161
7014


*-313

10926
3425
*-327
*-291
31223
30302
24633


*-270
*-27O


*-263
*-252
3056O
LIBRARY
CHOICE

NBS
NBS
UNKN
SEED
SEED
SEED
SEED
SEED
SEED
SEED
- UNKN
NBS
UNKN
NBS
NBS
NBS
SEED
NBS
UNKN
UNKN
SEED
SEED
NBS
SEED
UNKN
UNKN
UNKN
UNKN
UNKN
UNKN
NBS '
SEED
SEED
UNKN
UNKN
SEED
SEED
NBS
UNKN
UNKN
                                                                CURRENT
                                                                ENTRY
                                                                  636
                                                                  637
                                                                  6S3
                                                                  121
                                                                  121
                                                                  123
                                                                  123
                                                                  12-
                                                                  125
                                                                  126
                                                                  639
                                                                  69O
                                                                  691
                                                                  692
                                                                  693
                                                                  694
                                                                  694
                                                                  695
                                                                  696
                                                                  697
                                                                    14
                                                                     1
                                                                  693
                                                                  166
                                                                  699
                                                                  700
                                                                  7O1
                                                                  702
                                                                  703
                                                                  704
                                                                  70S
                                                                  175
                                                                  176
                                                                  706
                                                                  707
                                                                  130
                                                                  131
                                                                  703
                                                                  709
                                                                  710
Figure 3.  Example  of  an  ACORN summary report.  The columns titled  "Best Fit
  and "Best Purity"  refer to results of the seed search  if the  peak was
  identified from the  seed library or to results of the  NBS search  if it was
  not identified from  the seed library.  The column titled "Library Choice
  indicates the final  choice of ACORN for the unknown peak.
                                       12

-------
entries which were identified from the seed library.  Entries with library
PURITY and FIT values near the threshold limits were checked by visually
comparing the search results to the actual .spectrum from the sample.

          RRT values were checked by superimposing a hardcopy of the sample's
reconstructed ion current (RIG) profile over a "master RIC" which was marked
with the precise RRT of every seed library entry.  The superimposition of
RICs proved to be a very useful and reliable technique.   It was a simple
matter to line up commonly occurring major peaks and then compare each sample
peak with its corresponding seed entry peak on the master RIC.  In most cases,
the sample peak was exactly superimposed on its corresponding reference peak.
Examples of a "test RIC" and a "master RIC" are shown in Figure 4.   The RRT
test within ACORN itself precluded the possibility of more than minor differ-
ences between sample and reference RRT.  However, the program occasionally
erred if two or more compounds with identical or very similar spectra were
located within a retention window which was narrower than the window of the
RRT test (± 15 s) in ACORN.   Manual comparison to the, master RIC as described
above was usually effective in resolving these difficult cases.  It was possi-
ble for an experienced operator to manually review a datafile containing 60
to 80 peaks in about an hour.

     F.   Application of the Identification Method to FY82 NHATS Data Set

          The data set utilized for this study consisted of composited human
adipose tissue specimens prepared from the NHATS repository which were orig-
inally analyzed as part of a broad scan study.   The composite samples were
originally analyzed by HRGC/MS for volatiles and semivolatile target com-
pounds during the period from April 1984 to July 1984 (Stanley 1986b,
Stanley 1986c).

          The composites consisted of 46 volatiles, 44 semivolatiles from the
6% Florisil cleanup fraction,  and 46 semivolatiles from the 15/50% Florisil
cleanup fraction.  Within each of these categories, there were 12,  17, and 17
samples in the 0-14, 15-44,  and 45+ age groups for the volatile and 15/50%
Florisil semivolatile datafiles, and 12, 15, and 17 samples in the 0-14, 15-44,
and 45+ age groups for the 6% Florisil semivolatile datafile.

          Each data set was treated separately throughout the peak identifi-
cation procedure.  Separate seed libraries were maintained for each group of
samples.  The volatile data set was analyzed entirely before proceeding to
the semivolatile samples.   Semivolatile samples were analyzed in order of age
group; i.e., the 0-14 yr samples for both 6% and 15/50% samples were analyzed
prior to the 15-44 yr samples, and the 45+ samples were analyzed last.  It
has been observed that the number of extractable components in adipose tissue
is dependent upon the age of the individual from which the sample was taken.
The analysis sequence described above was used so that analysis could proceed
from samples with relatively few unknown peaks to samples with large numbers
of unknown peaks.  Examples of the differences between samples from various
age groups from the volatile,  6%, and 15/50% Florisil  semivolatile composites
are shown in Figures 5 through 7, respectively.
                                      13

-------
189.8-1
             RIC                                        DATA;  7281D19R1
             04/19/84 10111:80         CALI: CALD1SR1 *3,CALD13R1 »3
             SAMPLE: 7301-8-03S 62 l-MO-SUO-8-14 1UL 1NJ (2UG D-10 AOOEO)
             CONDS.J -1708EMU 70EU IMA DB5-30M 60-2H-310-10/ 45SEC.SPLT.
             RAHGEl G   1,1789  LABEL: N 8. 4.0  BASE: U 20,  3
»814,7981019R3
         SCANS
730 TO 938
 RIC.
                                                                             1.112
                                                                                           109312.
                                                                                           251904.
                                                                            980
                                                                            19:38
                         SCAM
                         TIME
       Figure 4.   Example of the manual  review of  RRT values using a "Master RIC."
          In this  example, the  upper RIC  is the master and  the lower RIC  is:being
          reviewed.   If  a peak  is observed in  the test RIC  which  is not on the
          master RIC, its location and  seed entry number are recorded on  the
          master in case it is  observed in the future.
                                                  14

-------
               I   *
,  -,l  'V , v
xjV V«,
                                      tn
                                      i  i
                                                           2-SA-VO-O-U
                                                          2-SA-VO-
                                                   IBS
                                                    I
                                   CM
                                   11* «d
                                  44
                                              'ji
                                              i!!
                                                         2-SA-VO-45+
Figure 5.   Reconstructed ion  chromatogram (RIC)  of volatile composites
            from the 0-14, 15-44,  and 45+ age groups from the
                  South Atlantic  (SA) census division.
                                     15

-------
        tie.
                                                      l-NE-SVO-0-1*


1
! ;
111

:a
i,i
a
«44
z* i
. l i I i

I
i
.
!33 I
, .fltf


i


k


act
!
i.-.


i :»
II. :»,;!« 1 :*>
T


u
1

t
\
a

1
"* 1 -»
,ii 1 i




i
• 1C
,l\| L
r
J/


at



li



'


m


i \







Nl :5«1 'TH :*I7
         te.
                aw    ilia
                                                      l-NE-SVO-15-44
                                                 a«<   ri«

                                                     9«n.
                                                      T-NE-SVO-45+
Figure 6.   Reconstructed  ion chromatogram (RIC) of 6%  Florisil
semivolatile composites for the 0-14,  15-44, and 45+ age groups
           from the New  England (NE) census division.
                                 16

-------
                   «a   i»*
                                                            l-WN-SVO-0-14
                                               ptf
                 . U...AL
                                               133  ,
                                                           l-WN-SVO-15-li
                                                I*1
                                                     •"I
                                                   !!?i
                                                      M
            «tc.
                   _.
                                      ir»
                                      I-
                                                          T-WN-SVO-45+
                                              i a ,V
                                              i :jli/
,/l
                  «
-------
IV.   RESULTS

          Application of the peak identification procedure to the FY82 compos-
ites as described above resulted in the following tables of results.   Twelve
tables (Tables 1 through 12) are provided in this report which list_all NBS_
identified compounds from the three composite data sets as well  as information
regarding peaks still unidentified.  An additional six tables (Tables A-l to
A-6) are provided in Appendix A (Volume II) to this report which include more
detailed information regarding the incidence of occurrence of peaks in the
three data sets.

          Tables 1 through 3 present the compounds identified via comparison
to NBS reference spectra for the volatile, 6% Florisil semivolatile, and
15/50% Florisil semivoiatile samples,  respectively.  Each table consists of
the following  information in columnar  form.  The  first column shows an index
number, which  is simply a sequential numbering of the compounds listed in the
table.  The index number is not related to any other numbering order in pre-
vious reports.  The  Compound Class column  indicates the chemical class to
which a compound belongs.  Chemical class  designations were  determined by
manual inspection of the compound  names.   The Compound Name,  Formula,  and
CAS No. columns are  derived from the NBS  library  resident on  the Incos data
system.  In most cases, the names  are  unaltered from the name in the NBS li-
brary.  In some cases,  however, the peak  identification procedure was  unable
to accurately  specify  a positional  isomer, and  the positional portion  of the
NBS name was either  removed or placed  in  parentheses.   For compounds with
positional designations in parentheses, the  corresponding CAS number refers
to the given isomer.   The remaining columns  show  the  frequency of  occurrence
of the listed  compounds within the three  tested age groups:   0-14,  15-44, and
45+ yr.

          Tables 4  through  6  show  the  same information  as Tables  1 through  3,
with  the exception  that frequency  of occurrence data  are  arranged  according
to census region  [North Central  (NC);  Northeast (NE),  South  (S),  and West (W)].
Information  regarding  age groups  is  not given.   The three  tables  represent
data  for the  volatile, 6%,  and  15/50%  Florisil  fractions,  respectively.

          Tables  7  through  9  show the  frequency of occurrence data for peaks
which ACORN  was unable to  identify from the  NBS library.   As with the  previous
sets  of  tables, Tables 7  through  9 represent data compiled from the volatile,
6%,  and  15/50% Florisil fractions, respectively.   The list of entries  is
sorted by  descending frequency of occurrence.   Occurrence data are also listed
 for each census region.

           Tables 10 through 12 represent the degree to which the unknown peaks
 in the FY82 data were identified,  and thus may be considered "peak inventories"
 for the analyzed data.  The tables list the number of peaks selected for analy-
 sis for each of the composites in this study, the number of peaks identified
 by ACORN from comparison to the NBS library, the number of peaks which remain
 unidentified,  and the number of compounds identified and quantitated in the
 target compound search previously reported (Stanley 1986b, Stanley 1986c).
 Thfs information provides a general guide for the amount of work which re-
 mains to be done for complete characterization of the composite samples.
                                       18

-------
Table 1.   Compounds Tentatively Identified in the Volatile Organic Analysis
                     Data Set vs.  Frequency/Age Group
Index
IS.
1
2
3
4
. 5
* 6
7
8
9
" 10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
33
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
* 56
57
58
59
•i. 60
61
62
63
64
Ccmpounddass Compound Name (a)
Internal Standard Bromochloropropane - Internal Standard
Carbon Dioxide Carbon dioxide
Alkane 2-Methyl-butane
Unidentified C5.H10 [Cyclopentane]
C3 Substituted cyclopropane [Propyi-cyclopropana]
C3 Substituted cyclopropane [Propyl-cyclopropane]
2,3-Dimethyl-hexane
1 ,2-Diethyl-cyclobutane
Alkane 2 C10(Decane]
C10 Alkane [2-Methyl-nonane]
2,2,3,3-Tetramethyl-hexane
Sat alkane > C1 1 [2-Methy Wecane]
Alkyl substituted hexane (Pentyl-cydohexanel
2,2-OimethyWecane
G13 Alkane [3,3-Oimethyl-undecanej
Alkane [6-Ethyl-2-methy!-decana|
Alkane [2,6,7-Trimethyl-decanej
Alkane 2 C11 [5-(1-Methylpropyl)-nonane]
C13 Alkane (2,2,7-Trimethy Wecane]
3,3,8-Trimethyl-decane
Alkane [6-Methyl-tridecane]
Alkene C5 Alkane [1 -Pentene]
1-Hexene
Unidentified C6.H12 [1-Hexene]
3-MethyM ,4-heptadiene
1,6-Octadiene
1 ,3,6-Octatriene
Unidentified C8.H12 [3-Ethylidene-1-methyl-cyclopentene]
1-Nonene
3-Ethyl-2-methyl-1 ,3-hexadiene
C10 Ringed alkene [1.7.7-Trimetnyl-bicyclo[2.2.1]hept-2-ene]
1 -Methyl-4-(1 -methylethenyl)-cydohexene
7-{1-Methylethylidene)-bicyc!o[4.1.0] heptane
C11 Alkene [1-Undecene]
C11 Alkene [1-Ethenyl-2-hexenyl-cydopropane]
Isomer of Undecen-3-yne [5-Undec-3-yne]
Isomer of Undecen-3-yne [5-Undec-3-yne]
Arene C2 Alkyl benzene [1,2-Dimethyl-benzene]
C2 Alkyl benzene [1 ,2-Dimethyl-benzene]
C3 Alkyl benzene [1,2,4-Trimethyl-benzen9]
C3 Alkyl benzene [1 -Methylethyl-benzene]
Propyl-benzene
C3 Alkyl benzene [1-Methyl-2-ethyl benzene]
Isomer of tetramethyl benzene [1,2,3,4-Tetramethyl-benzene]
1-Methyl-3-(1-methylethyl-) benzene
Naphthalene
1-Ethylprapyl-benzene
Aliphatic Alcohol 3-Methyl-1 -butanol
1-Hexand
Isomer of ethyl hexanol [3-Methyl-1 -hexanoi]
2-Ethyl-1-Hexanol
Isomer of odanol [1 -Octanol]
Isomer ofoctanol f1-0ctanoi]
Unidentified C13.H28.0 [1-Tridecanol]
Unsaturated Alcohol Isomer of Octen-ol [3-Octen-2-oi]
Isomer of Octen-ol [3-Ocien-2-oi]
Aliphatic Aldehyde Unidentified C5.H10.0 [Pentanal]
Unidentifed C6.H12.0 [Hexanal]
C7 Aldehyde [Heptanal]
Nonanal
Decanal
Unsaturated Aldehyde 2-Methyl-propenal
Isomer of Hexenal [2-Hexenal]
Isomer of Hexenal [2-Hexenal]
C7 Unsat aldehyde [2-Heptenal]
Corrpctmd
Formula (b)
-
C.02
C5.H12
C5.H10
C6.H12
C6.H12
C3.H18
C3.H16
C10.H22
C10.H22
C10.H22
C11.H24
C11.H22
C1iH26
C13.H28
C13.H28
C13.H28
C13.H28
C13.H28
C13.H28
C14.H30
CS.H10
cam 2
C6.H12
C8.H14
CS.H14
C8.H12
C8.H12
C9.H18
C9.H16
C10.H16
C10.H16
C10.H16
C11.H22
C11.H8
C11.H18
C11.H18
C8.H10
C8.H10
C9.H12
C9.H12
C9.H1 2
C9.H1 2
C10.H14
C10.H14
C10.H8
C11.H16
C5.H12.0
C6.H14.0
C7.H16.0
C3.H18.0
cam 8.0
C3.H1 8.0
C13.H28.0
cam 6.0
cam 6.0
C5.H10.0
C6.H1ZO
C7.H14.0
C9.H18.0
C10.H20.0
C4.H6.0
03.H10.0
O3.H10.0
C7.H1ZO
Compound
CAS No. (G)

124-38-9
78-78-4
287-92-3
2415-72-7
2415-72-7
584-94-1
61141-83-1
124-18-5
871-83-0
13475-81-5
6975-98-0
4292-92-6
1 7302-37-3
17312-65-1
62108-21-8
62108-25-2
62185-54-0
62237-99-4
62338-16-3
13287-21-3
109-67-1
592-41-6
592-41-6
1603-01-6
3710-41-6
22038-69-3
62338-00-5
124-11-8
61142-36-7
464-17-5
5989-54-8
53282-47-6
821-95^
22822-99-7
74744-31-3
74744-31-3
95-47-6
95-47-6
95-63-6
98-82-8
103-65-1
611-14-3
488-23-3
535-77<3
91-20-3
1196-58-3
• 123-51-3
111-27-3
13231-81-7
104-76-7
111-87-5
111-37-5
112-70-9
57648-55-2
57648-55-2
110-62-3
66-25-1
111-71-7
124-19-6
112-31-2
78-55-3
6728-26-3
6728-26-3
1 8829-55-5
Number of Occurrences
In All In Each Age Group
Sarrctes 0-14 15-44 45+
46
45
18
7
13
22
31
3
18
9
10
6
1
13
1
3
21
1
10
1
4
4
15
24
4
4
10
1
8
44
44
1
1
8
2
17
31 •
41
16
2
1
8
3
1
2
1
1
29
1
3
7
12
29
1
2
15
46
45
46
46
43
1
21
32
46
12
12
6
3
2
3
6
2
4
2
1
1
0
4
0
2
3
0
2
0
1
1
7
6
0
3
3
0
2
12
10
1
0
3
0
4
8
9
2
0
0
0
0
0
0
0
0
7
0
1
1
4
9
0
0
3
12
12
12
12
11
1
5
10
12
17
17
6
3
7
8
14
1
4
3
2
5
0
4
0
3
7
0
4
0
1
0
5
9
0
1
1
0
4
17
17
0
0
5
0
4
12
• 16
7
1
1
5
2
1
1
1
1
12
1
1
4
4
11
0
1
5
17
17
17
17
17
0
7
12
17
17
16
6
1
4
11
11
0
3
4
7
0
1
5
1
3
11
1
4
1
2
3
3
9
4
0
6
1
2
15
17
0
1
0
2
9
11
16
7
1
0
3
1
0
1
0
0
10
0
1
2
4
9
1
1
7
17
16
17
17
15
0
9
10
17
                                    19

-------
                                                          Table  1  (concluded)
ndax
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
30
3t
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
t17
118
119
120
121
Compound Class











Aliphatic Ketona




Unsaturatad Ketone



Aliphatic Ether
Aliphatic Ester





















,


Unsalurated Ester
Haiocarbon




Phenol
Haiorocyc'a
Suifida

Organo-SBicon
Compound Name (a)
C7 Unsat aldehyde [2-HeptenaJ]
2,4-Heptadienal
2,4-Nonadienal
Isomerof decenal [2-DecsnaJ]
Isomerof decenal [2-Decenai]
UnsaL aldehyde [2-Decsnal]
Unsat. aldehyde [2-Decsnai]
Unsat aldehyde [2-Oecenal]
Diene aldehyde [2,4-Decaaienai]
Diena aldehyde [2,4-Decadienaij
Diene aldehyde [2,4-Dodecadienal]
C7 Ketone (2-Heptanone]
4-Heptanone
Unidentified C7.H12.0 [2.2.3-Trimetriyl-cyciobutanone]
C8 Ketone [3-Octanonej
Sat. ketone [2-Oecanone]
Isomer of Octen-one (3-Oc:en-2-onej
08 Ketona [3-Oc:en-1-one]
3,5-Octadien-2-one
C9 UnsaL ketone [3-Nonen-2-one]
Olmeihoxy methane
Propanoic acid, ethyl ester
05 Methyl ester [Butanoic acid, methyl ester]
Propanoic add, propyl ester
Pentanoic add, methyl ester
07 Methyl ester [Hexanoic add, methyl ester]
3-Methyl butanoic add, ethyl ester
Propanoic add, butyl ester
2-Methyl propanoic acid, 1-methylethyl ester
Acetic acid, pentyl ester
2-Methyl butanoic acid, ethyl estar
08 Ethyl ester [Hexanoic add, ethyl ester]
Acetic add, hexyl ester
08 Ester [3-Methyl butanoic acid, propyl ester]
08 Ester [Butanoic acid, 1-Methylpropyl ester]
08 Ester [Butanoic acid, 1-Methylpropyl ester]
Octanoic add, methyl ester
Hexanoic add, 1-methy!ethyl ester
Butanoic acid, pentyl ester
Hexanoic acid, 2-methylpropyl ester
Octanoic add, ethyl ester
010 Ester [2-Methyl-propanoic acid, hexyl ester]
011 Ester [Hexanoic add, pentyl ester]
011 Ester [4-Methyl pentanoic add, pentyl ester]
011 Ester [Hexanoic acid, 2-Methylbutyl ester]
Isomer of octanoic add [3-Methyl-butyl ester]
3-Octen-1-ol, acetate
05 Bromoalkana [1-Bromopentane]
3-Bromo-Pentane
Brominated alkane 5 07 [1-Bromo-heptane]
Dichlorobutar.a [1,4-dichlorobutane]
2-8romo-2-chloro-1 ,1 .trifluoro-ethane
tsomer of einyl-ohenol [4-Elhyl-onenol]
Unidentified C9.H14.0 [2-Pentyi-iuranl
Dimethyl disuifide
Dimethyl trisulfia'e
Decamethyl-cydopentasiloxane
Corrpound
Formula (b)
C7.H1ZO
C7.H10.0
C9.H14.0
C10.H18.0
C10.H18.0
C10.H18.0
C10.H18.0
C10.H18.0
C10.H16.0
C10.H16.0
C12.H20.0
C7.H14.0
C7.H14.0
C7.H12.0
C3.H16.0
C10.H20.0
C3.H14.0
C8.H14.0
C8.H1ZO
C9.H16.0
C3.H8.02
C5.H10.02
C5.H10.02
C6.H12.02
C6.H12.02
C7.H14.02
C7.H14.02
C7.H14.02
C7.H14.02
C7.H14.02
C7.H14.02
C8.H16.02
C8.H16.02
C8.H16.02
C8.H16.02
C8.H16.02
C9.H18.02
C9.H18.02
C9.H18.02
C10.H20.02
C10.H20.02
C10.H20.02
C11.H22.02
C11.H22.02
C11.H22.02
C13.H26.02
C10.H18.02
CS.H11.BR
C5.H11.BR
C7.H15.BR
C4.H8.CL2
C2.H.CL8R.F3
C3.H10.0
C3.H14.0
CZH6.S2
C2.H6.S3
C10.H30.05.SI5
Ccrrpcund
CAS No. fcl
57266-86-1
4313-03-5
6750-03-4
3913-81-3
3913-81-3
3913-81-3
3913-81-3
3913-81-3
25152-84-5
25152-84-5
21662-16-8
11043-0
123-19-3
1449-49-6
106-58-3
393-54-9
1669-44-9
1669-44-9
30086-02-3
14309-57-0
109-87-5
105-37-3
623-42-7
106-36-5
624-24-8
106-70-7
108-64-5
590-01-2
617-50-5
628-63-7
7452-79-1
123-66-0
142-92-7
557-00-6
819-97-6
819-97-6
111-11-5
2311-46-8
540-18-1
105-79-3
106-32-1
2349-07-7
540-07-8
25415-71-8
2601-13-0
2035-99-6
69668-83-3
110-53-2
1809-10-5
629-04-9
110-56-5
151-67-7
123-07-9
3777-69-3
824-92-0
3658-80-8
541-02-6
In All
Sarrdes
23
32
29
1
25
28
29
45
1
15
26
36
35
7
1
1
3
37
8
25
1
29
3
7
1
42
16
2
4
3
5
12
16
7
1
4
27
1
17
1
36
12
24
6
4
24
1
3
3
2
2
16
8
29
27
2
28
In Each Age Group
0-14 15-44 45+
8
6 '
10
1
5
9
9
12
. 1
• 6
' 6
9
10
1
0
1
0
11
3
10
0
4
1
0
0
11
4
0
0
1
0
4
5
1
0
0
11
0
6
0
10
3
8
1
1
7
1
2
1
1
0
3
4
11
4
0
4
6
11
11 .
0
10
11
12
17
0
4
10
• 13
12
5
0
0
5
13
3
6
0
' 12
0
3
0
17
5
0
3
1
2
2
5
3
1
3
9
1
9
0
14
3
9
2
3
9
0
0
1
1
1
7
0
9
12
0
11
9
15
8
0
10
8
8
16
0
5
10
14
13
1
1
0
4
13
2
9
1
13
2
4
1
14
7-
2
1
1
3
6
6
3
0
1
7
0
2
1
12
6
7
3
0
8
0
1
1
0
1
3
2
9
11
2
13
(a)  Tentative compound identification is based on search vs. the NBS mass spectral library. Confirmation has not been achieved by comparing
     retention with an authentic standard. In cases where more than one reference compound successfully matched the unknown spectrum,
     a general descriptive name is reported and the best ranked NBS name is provided in brackets.

(b)  ki cases where both a general name and an NBS name is reported, the formula corresponds to the NBS name and may not be applicable to the general name.

(c)  In cases where both a general name and an NBS name is reported, the CAS no. corresponds to the NBS name.
                                                                   20

-------
Table 2.   Compounds Tentatively Identified in the 5% Florisil Semivolatile Organic
                     Analysis Data Set vs. Frequency/Age Group
Index
I.S.
1
2
3
4
5
6
7
3
9
10
^ 11

12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
• 59
60
61
62
63
64
Ccmcound Class
Internal Standard
Alkane


Saturated Ketone
Saturated Ester


Sulfide

Dipeptide
Alkene





Unsaturated Aldehyde

Unsaturated Amine
Unsaturated Ketone
Arene


















Aromatic Aldehyde

Aromatic Ketone

Phenol


Aromatic Ester
Aromatic Ether

Aromatic Amine
Aromatic Oxime
Thiocyanic Ester
Heterocyclic Compound







Steroid




Corroound (a)
D10-Anthracene ,•; .p
2,6,10,14-Tetramethyl-hexadecane
2,6,10,1 4-Tetramethyl-nonadecane
Alkane SC18 [2,6,10,14,19-Pentamethyl eicosane]
1 ,2,4-Cyclopentatrione
12-Methyl-tridecanoic add, methyl ester
Nonanedioic add, bis(l-methylpropyl) ester
9-Octadecenoic acid, ethyl ester
Methyl 2-methyl-1 -(methylthio)butyl disuifide
Dimethyl trisulfide
Glydne, anhydride
C5 Substituted naphthalene
[Octahydro-tetramethyl-1H-cyclopropan(A]naphthalene]
Hexahya'ro-4,7-dimethyl-1-(1-methylethyl)-naphthalene...
5-Elhyiidene-1 -methyl-cycioheptene
C30 Unsat hydrocarbon [Hexamethyl-tetracosahexaenej
Ylangene
2-8utyl-2-octenal
Unidentified C9.H8.0 [Cycloociatetraene-1-carboxaldehyce]
N,N-Dimethyl-3-octen-2-amine
6, 1 0-Dimethyl-5,9-undecadien-2-one
C4 Alkyl benzene [1-Ethyl-2,3-dimethyl benzene]
2-Ethyl-1 ,3-dimethyl-benzene
C4 Alkyl benzene [4-Ethyl-1 ,2-dimethyl-benzene]
C4 Alkyl benzene [Diethyl benzene]
C4 Alkyl benzene [Methyl(1-methylethyl)-benzene]
Cydohexyl-benzene
C3 Alkyi benzene [1,3,5-Trimethyl-benzene]
C4 Alkyl benzene [1-Ethyl-2,3-dimethyl benzene]
C5 Alkyl benzene [1-Ethyl-4-(1-methylethyl)-benzene]
C3 Alkyl benzene [1-Elhyl-3-methyl-benzene]
C3 Alkyl benzene [l-Ethyl-2-methyl-benzene]
C3 Alkyl benzene [1 ,3,5-Trimethyl-benzene
C3 Alkyi benzene [1 ,3,5-Trimethyl-benzene
C4 Alkyl benzene (1-Elhyl-2,4-dimethyl-benzenej
2-Methyl-naphthalene
Unidentified C10.H12 [2,3-Dihydro-1-methyl-1H-lndene]
Unid. C15.H24 [Hexahydro-tetramethyl-benzocydoheptene]
UnsaL C4alkyl benzene [4-Ethenyl-1,2-dimethyl-benzene]
2-Propenyl-benzene
Benzaldenyde
4-Pentyl-benzaldehyde
Unidentified C9.H8.0 [2,3-Dihydro-1H-lnden-1-one]
1-Phenyl-ethanone
2,6-Bis(1,1-dimethylethyl)-4-methyl-phenol
[1,1'-Biphenyl]-2-ol
2,2'-Methylenebis[6-(1 , 1 -dimethylethyl)-4-methyl-phenol
Benzenepropanoic add, ethyl ester
1,1'-0xybis-benzene
1 -Methoxy-4-(1 -propenylj-benzene
C2 Alkyl benzenamine [3,5-Oimethyl-benzenamine]
4-Methyl benzaldehyde, oxime
Thiocyanic add, phenyl ester
2,3,5-Trimethyl-1 H-oyrrole
Unidentified C3.H7.N f1H-lndoie]
Unidentified C8.H7.N [Indolizine]
2-(Methylthio)-benzothiazoie
5-(2-Propenyl)-1 ,3-8enzodioxoie
1 ,4-Dioxaspiro(4.6]undec-7-ene
2,4-Dihydro-2,5-dimethyl-3H-pyrazol-3-one
5,5-Diethyl-2,4-imidazolidinedione
(5.Alpha)-cholest-3-ene
(3.Beta.)- Cholest-5-en-3-ol acetate
Cholest-5-en-3-ol- (3. beta.)-, propanoate
Cholest-5-en-3-one
Cholest-5-ene
Formula (b)

C20.H42
C23.H48
C25.H52
C5.H4.O3
C15.H30.02
C17.H32.04
C20.H38.02
C7.H16.S3
C2.H6.S3
C4.H8.03.N2
C15.H24

C1S.H24
C10.H16
C30.H50
C15.H24
C12.H22.0
C9.H8.0
C10.H21.N
C13.H22.0
C10.H14
C10.H14
C10.H14
C10.H14
C10.H14
C1ZH16
C9.H12
C10.H14
C11.H16
C9.H12
C9.H12
C9.H12
C9.H12
C10.H14
C11.H10
C10.H12
C15.H24
C10.H12
C9.H10
C7.HaO
C1ZH16.0
C9.H8.0
caHao
C15.H24.0
C12.H10.0
C23.H3Z02
C11.H14.02
C1ZH10.0
C10.H12.0
C8.H11.N
C3.H9.0.N
C7.H5.N.S
C7.H11.N
C8.H7.N
C3.H7.N
C8.H7.N.S2
C10.H10.02
C9.H14.02
CS.H8.0.N2
C7.H12.02.N2
C27.H46
C29.H48.02
C30.H50.02
C27.H44.0
C27.H46
AS Number (cl

638-36-8
55124-80-6
52268-60-5
15849-14-6
5129-58-8
57983-36-5
111-62-6
69078-83-7
3658-80-8
4202-74-8
1 7334-55-3

183-76-1
15402-94-5
H1-02-4
14912-44-3
13019-16-4
30844-12-3
55956-31-5
3796-70-1
933-98-2
2870-04-4
934-80-5
25340-17-4
25155-15-1 '
827-52-1
108-67-8
933-98-2
4218-48-8
620-14-4
611-14-3
108-67-8
108-67-8
874-41-9
91-57-6
767-58-8
1461-03-6
27831-13-6
300-57-2
100-52-7
6853-57-2
83-33-0
98-86-2
1 28-37-0
90-43-7
119-47-1
2021-28-5
101-84-8
104-46-1
108-69-0
3717-15-5
5285-87-0
2199-41-9
120-72-9
274-40-3
615-22-5
94-59-7
7140-60-5
2749-59-9
5455-34-5
28338-69-4
604-35-3
633-31-8
601-54-7
570-74-1
InAfl
Sarrdea
44
24
8
4
1
4
1
29
6
1
3
6

^
34
1
2
4
1
1
.1
1
10
6
6
7
3
3
1
1
6
8
3
5
10
1
1
1
5
3
11
1
3
2
8
2.
2
3
33
1
7
39
3
11
4
3
1
1
1
3
1
9
1
1
3
10
In each Age Grcxo
0-14 15-44 45 + '
12
6
0
0
1
2
0
9
1
0
3
1

0
3
0
0
2
0
0
0
0
2
0
1
1
1
2
0
0
1
2
1
1
1
0
0
0
1
1
11
0
0
0
0
0
0
0
4
1
0
10
0
3
0
0
0
0
0
3
0
0
0
1
0
2
15
5
4
0
0
1
0
9
0
0
0
0

0
10
1
0
0
0
1
1
0
3
1
2
2
1
0
0
0
1
0
0
1
2
0
1
0
1
0
0
1
3
1
3
0
0
2
13
0
0
13
1
0
1
1
0
0
0
0
• 0
2
1
0
2
4
17
13
4
4
0
1
1
11
5
1
0
5

1
16
0
2
2
1
0
0
1
5
5
3
4
1
1
1
1
4
6
2
3
7
1
0
1
3
2
0
0
0
1
5
2
2
1
16
0
7
16
2
3
3
2
1
1
1
0
1
7
0
0
1
4
!n Blanks
3
0
0
0
0
0
0
0
0
0
0
0

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0-
0
0
0
                                      21

-------
Table 2 (concluded") • |

Wot
SS
66
67
68
69
70
71
72
73
74
75
76
77
78
79
ao
31

CcmxcndCasj Comooundfa)
(5.Alpha.)-cholest-7-en-3-one
Cholesta-3,5-dien-7-one
(3.Beta.)-cholesta-4,6-dien-3-ol benzoate
Cholesterol
Isomerof cholestenol [5-cho!esten-3-ol propionate]
Pregnans, (S.alpha.)-
(3.Beta.)-26,27-dinorergost-5-en-3-ol benzoate
Chlorinated Hydrocarbon 1,1-Dichtaro-l-prooene
(4-Ch!oropnenyl)phenyl-methanone
2-Chloro-6-methyl-benzonitriie
Dichlorobenzene [1,3-dichloro-benzene]
lindane
ODD
Organo-Silicon Isomer of decamethyl-cydopentasiloxane
Ocamethyl-cyciotetrasiloxane
isomer of decameihyl-cyciopentasiioxane
Phihajao Diheotyl onthalate

Formula (b)
C27.H44.0
C27.H42.0
C34.H48.02
C27.H46.0
C30.H50.02
C21.H36
C33.H48.02
C3.H4.CL2
C13.H9.0.CL
C8.H6.N.CL
C8.H4.CI2
C6.H6.CL6
C14.H10.CL4
C10.H30.05.Si5
C3.H24.04.SI4
C10.H30.05.SI5
C22.H34.04

AS Number (c)
15459-85-5
567-72-6
25485-34-1
57-88-5
633-31-8
641-85-
58003-48-8
563-58-6
134-85-0
6575-09-3
541-73-1
58-89-9
72-54-8
541-02-6
556-67-2
541-02-6
3648-21-3
In All
Sarrdes
1
1
3
3
40
4
1
1
1
1
13
6
12
28
21
1
1
In each Age Group |
0-14
0
0
0
0 •
9
1
0
0
0
1
3
2
4
4
7
0
0
15-44
1
1
2
1
15
0
1
1
1
0
1
0
3
7
3
0
0
45 +
0
0
1
2
, 16
3
0-
0
.0 ':
0.
9.
4
5
17
11
1
1
In Blanks I
• o
0
0
0
0
0
0
0
0
0
0
0
o •'-•
0
"
0
0
(a)   Tentative compound identification is based on search vs. the NBS mass spectral library. Confirmation has not been achieved by comparing
     retention with an authentic standard. In cases where more than one reference compound successfully matched the unknown spectrum,
     a genera) descriptive name is reported and the best ranked NBS name is provided in brackets.

(b)  hi cases where both a genera) name and an NBS name is report^, the formula corresponds to the NBS name and may not be applicable to the general name.

(c)   In cases Where both a general name and an NBS name is reported, the CAS no. corresponds to the NBS name.
                                                                          22

-------
Table 3.   Compounds Tentatively Identified in the 15/50% Florisil Semivolatile Organic
                       Analysis Data Set vs.  Freauency/Age Group
Index
IS.
1
2
3
4
5
6
7
3
' 9
10
11
12
13
U
15
16
17
18
19
20
21
22
23
24
25
26
27
23
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
CofrncundCass
Internal Standard
Altone
Saturated Ester



Saturated Polyfunctional

Alkene
Unsaturated Aldehyde

Unsaturated Ketona



Unsaturated Polyfuntional



Alkyne
Arena




Aromatic Aldehyde


Aromatic Ketone
Aromatic Amide
Aromatic Carboxylate



Phthalic Acid Derivative




Phenol


Aromatic Polyfunctional



Drug






Heterocydic Compound










Conrcoundfa) . ..:
D10-Anthracene - Internal Standard
Unidentified C10.H20 [Diethyl cyclohexane]
1,7,7-Trimethyl-bicyclo[2.2.1]heptan-2-ol, exo propanoate-
Dodecanoic acid, ethyl ester
Hexanedioic acid,mono(2-ethylhexyl) ester
Alkyl ester [15-Methyl-heptadecanoate]
Ethylhydrazone croDionaidehyde
9-Oxo-nonanoic acid, eihyl ester
1-Methyl-3-{1-methylettienyl)-cyclohexene
. Trimethyl-3-cydohexene-l -carboxaldehyde
2-Butyl-2-octenal
3-Metnyl-3-8uten-2-one, dimer
2,4,6-Cycloheptatnane-1 -one
5-Undecen-4-one
3-Eihyl-2-methyl-4-heptene-3-one
Substituted cyciopentenone (Butyl-methoxy-cyciooenten-1-onej
Substituted cyciopentenone [Butyl-methoxy-cyc!opemen-1-one]
Substituted cyciopentenone [Butyl-methoxy-cyc!openten-1-onej
2-Methoxy-2-octen-4-one
5,5-Dimethyl-3-heptyne
C3-Alkyl benzene [1,3,5-trimethyl-benzene]
C3 Alkyl benzene [1,2,4-Trimethyl-benzene]
C3-Alkyl benzene [1,2,4-trimethyi-benzene]
C3 Alkyl benzene [1-Ethyl-3-methyl-benzene]
Unidentified C11.H10 [1-Ethylidene-indene]
Benzaldehyde
Unidentified C10.H10.0 [.Alpha.-ethylidene-benzeneacetaldehyde]
Unidentified C10.H10.0 [.Alpha.-ethylidene-benzeneacetaldehyde]
1-Phenyl-ethanone
N-Methyl-1 -naphthalenecarboxamida
Benzenepropanoic acid, .beta.,.beta.-dimethyl-
2-{acatylamino)-benzoic adid.methyl ester
Benzenepropanoic acid, ethyl ester
Benzenepropanoic acid
Butyl decyl phthalate
Isomer of diheptyl phthalate
Isomer of diheptyl phthalate
Butyl phthalate, ester with butyl glycolate
Unidentified phthalate
Methyl phenol [2-Methyl-phenol]
(1,1'-Biphenyl]-2-ol
2-Naphthalenol
1 ,3-Dimethoxy-benzene
1-Phenyl-1,2-butanediol
2-Ethoxy-benzaldenyde
Unidentified C7.H5.0.N.S [Thiocyanic acid, 4-hydroxyphenyl ester
Methaquabne
Unidentified barbiturate [5-E!hyl-1,3-dimethyl pyrimidinetrione]
Alkyl substituted pyrimidinetrione [Mephobaroital]
Alkyl substituted pyrimidinetrione [Pentobarbital]
Alkyl substituted pyrimidinetnone [Phenobarbitai]
Alkyl substituted oyrimidinetnone iMetharoital]
Alkyl suosututed pyrimiainetnone {MetnarDitaij
1,7-Naphthyridine
Isomer of dimethyl-piperidine [1,4-Oimethyl-piperidine]
3-Pyridinecarboxaldehyde, oxime
4-Pyridinecarboxaldehyde
Unidentified C8.H7.N [Indolizine]
C2 Alkyl pyrazine [2,6-Oimethyl pyrizine]
2-Methoxy-3-rnethyi-pyrazine
1,2-Benzisothiazole
Unidentified C7.H11.N.S [ 2-MethyU-propyl-thiazole]
Alkyl thazole [4-Ethyl-5-methyl-thiazole]
4-Propyl-thiazole
Number of Occurrences
InAI In each Age Group
Formula(b) CASnumoer(c) Sanples 0-14 15-44 45+ InSanks
C14.D10
C10.H20
C13.H22.02
C14.H28.02
C14.H26.04
C20.H40.02
C5.H1ZN2 .
C11.H20.03
C10.H16
C10.H16.0
C12.H22.0
C5.H8.02
C7.H6.0
C11.H20.0
C10.H18.0
C10.H16.02
C10.H16.02
C10.H16.02
C9.H16.02
C9.H16
C9.H12
C9.H12
C9.H12
C9.H12
C11.H10
C7.H6.0
C10.H10.0
C10.H10.0
C8.H8.0
ciami.o.N
C11.H14.02
C10.H11.03.N
C11.H14.02
C9.H10.02
C22.H34.04
C22.H34.04
C22.H34.04
C18.H24.06

C7.H8.0
C1ZH10.0
C10.H8.0
C8.H10.02
C10.H14.02
C9.H10.02
C7.H5.0.N.S
C16.H14.0.N2
C3.H12.03.N2
C13.H14.03.N2
C11.H18.03.N2
C12.H1Z03.N2
C3.H14.03.N2
C3.H14.03.N2
C3.H6.N2
C7.H15.N
C6.H6.0.N2
C6.H5.0.N
C8.H7.N
C6.H8.N2
C6.H8.0.N2
C7.H5.N.S
C7.H11.N.S
C6.H9.N.S
CS.H9.N.S

1331-43-7
2756-56-1
106-33-2
4337-65-9
57274-46-1
7422-92-6
' 3433-16-7
499-03-6
40702-26-9
13019-1S-4
54789-11-3
539-80-0
56312-55-1
49833-36-7
53690-92-9
53690-92-9
53690-92-9
24985-48-6
23097-98-5
95-63-6
95-63-6
108-67-8
620-14-4
2471-83-2
100-52-7
4411-89-6
4411-89-6
98-86-2
3400-33-7
1010-48-6
2719-60-2
1010-48-6
501-52-0
89-19-0
3648-21-3
3648-21-3
85-70-1

95-48-7
9043-7
135-19-3
151-10-0
22607-13-2
613-69-4
3774-52-5
72-44-6
7391-61-9
115-38-8
76-74-4
50-06-6
50-11-3
30-11-3
253-89-0
695-15-3
51892-18-1
872-85-5
274-40-8
' 108-50-9
2882-21-5
272-16-2
41981-63-9
52414-91-2
41981-60-6
46
2
1
4
1
13
1
2
4
3
28
2
2
3
2
3
4
23
2
1
8
5
1
2
2
8
4
20
4
1
1
2
5
1
11
2
3
6
3
5
18
1
2
2
4
1
4
1
3
19
5
1
3
3
11
10
1
2
3
7
4
3
5
3
12
0
0
0
0
1
1
0
. 1
0
10
2
2
1
1
1
1
6
2
1
4
3
1
0
0
5
2
5
0
0
0
1
1
0
3
1
1
2
0
0
3
0
1
1
2
1
0
0
2
5
3
0
1
0
9
5
1
0
3
3
0
0
3
2
17
0
0
0
0
4
0
0
2
2
9
0
0
0
0
0
0
4
0
0
1
1
0
0
1
1
1
7
2
0
1
0
4
0
4
1
2
1
1
0
6
0
0
0
1
0
4
0
1
8
1
0
1
2
2
4
0
0
0
1
0
0
0
0
17
2
1
4
1
8
0
2
1
1
9
0
0
2
1
2
3
13
0
0
3
1
0
2
1
2
1
3
2
1
0
1
0
1
4
0
0
3
2
5
9
1
1
1
1
0
0
1
0
6
• 1
1
1
i
0
1
0
2
0
3
4
8
2
1
4
3
0
0
1
0
0
0
0
0
0
0
0
0
0
^
i
3
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
4
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
1
0
                                        23

-------
                                                          Table  3  (concluded)
Wex
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
Comxxind Class Compound fa)
1,3-Benzcdioxcle
4,7-Dimeihy!-3(2H)"benzofuranone
Unid. C11.H16.02 [Tetrahydro-trirnethyl-2(4H)-benzofuranone]
5-{Butylimino)-2(5H)-furanone
2H-1-8enzopyran-2-one
1 ,3.5-Trimethyl-l H-pyrazole
Isomer of thienyl-ethanone [1-(3-Thienyl)-ethanone]
1-(4-Hydroxy-3-!hienyl)-ethanone
2,3,4-tnmethyl thiophene
2-Methyl-5-propyl-thiophene
2-t-Butoxy-thiophene
Steroid Isomer of cho!est-en-ol [Cholest-S-en-3-oi.acetatej
Isomer of choiest-an-ol [Choiest-S-en-o-ol.acaiatej
Chotest-5-en-3-ol (S.beia.)-, propanoate
Cholest-5-en-3-one
Cho!est-5-ene
Isomer of cholest-en-ol [4-Methyl-cholest-8(14)-en-3-ol]
Cholesta-3,5-dien-7-one
Cho!esta-4,6-
-------
Table 4.   Compounds Tentatively Identified in the Volatile Organic Analysis
                   Data Set vs. Frequency/Census
Index Compound Cass
I.S. Internal Standard
1 Carbon Dioxide
2 Alkane
3
„ 4
5
6
7
8
"* 9
10
11
12
13
14
15
16
17
18
19
20
21 Alkene
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37 Arena
38
39
40
41
42
43
44
45
46
47 Aliphatic Alcohol
48
49
50
51
52
53
54 Unsaturated Alcohol
' 55
56 Aliphatic Aldehyde
57
58
' 59
60
61 Unsaturated Aldehyde
62
63
64
65
66
67
Compound Name (a)
Bromochloropropane - Internal Standard
Carbon dioxide
2-Methyl-butane
Unidentified C5.H10 [Cyclopentane]
C3 Substituted cyclopropane [Propyl-cyclopropane]
C3 Substituted cyclopropane [Propyi-cyclopropane]
2,3-Dimethyl-hexane
1 ,2-Diethyl-cyclobutane
Alkane SC10[Decane]
C10 Alkane [2-Methyl-nonanej
2,2,3,3-Tetramethyl-hexane
Sat alkane 2 C1 1 te-Methyl-c'ecane]
Alkyl substituted hexane jPentyl-cyciohexanej
2,2-Oimethyl-decane
C13 Alkane i3,3-0imethyl-unaecane)
Alkane [6-Eihyl-2-methyl-cecane]
Alkane [2,6,7-Trimethyl-decane]
Alkane 5 C11 [5-{1-Methylprapyl)-nonane]
C13 Alkane [2,2,7-Trimethyl-decane]
3,3,8-Trimethyl-decane
Alkane [6-Methyl-tridecane]
C5 Alkane [1-Pentene]
1-Hexene
Unidentified C6.H12 [1-Hexene]
3-Methyl-1 ,4-heptadiene
1,6-Octadiene
1,3,6-Octatriene
Unidentified C8.H12 [3-Ethylidene-l-methyl-cyclopentenej
1-Nonene
3-Ethyl-2-methyl-1 ,3-hexadiene
C10 Ringed alkane [1,7,7-Trimethyl-bicyclo[Z2.1]hept-2-ene]
1 -Meihyl-4-(1 -methylethenyl)-cyc!ohexene
7-(1-Methylethylidene)-bicyc!o{4.1 .0] heptane
C11 Alkene [1-Undecene]
C11 Alkene [1-Ethenyl-2-hexenyl-cydopropanej
Isomer of Undecen-3-yne [5-Undec-3-yne]
Isomer of Undecen-3-yne [S-Undec-3-yne]
C2 Alkyl benzene {1 ,2-Dimethyl-benzene]
C2 Alkyl benzene [1 ,2-Dimethyi-benzene]
C3 Alkyl benzene [1 ,2,4-Trimethyl-benzene]
C3 Alkyl benzene [1 -Methylethyl-benzene] .
Propyl-benzene
C3 Alkyl benzene [1 -Methyl-2-ethyl benzene]
Isomer of tetramethyl benzene [1,2,3,4-Tetramethyl-benzene]
1-Methyl-3-(1-methylethyl-) benzene
Naphthalene
1 -Ethylpropyl-benzene
3-MethyM-butanol
1-Hexanol
Isomer of ethyl hexanol [3-Methyl-1-hexanol]
2-Eihyl-1-Hexanol
Isomer of octanol [1 -Octanoi]
Isomer of octanol f1 -Octanol]
Unidentified C13.H28.0 [1-Tridecanoi]
Isomer of Octen-ol [3-Octen-2-ol]
Isomer of Octen-ol [3-Octen-2-ol]
Unidentified C5.H10.0 [Pentanal]
Unidentifed C6.H^O [Hexanal]
C7 Aldehyde [Heptanal]
Nonanal
Decanal
2-Methyl-propenal
Isomer of Hexenal [2-Hexenal]
Isomer of Hexenal [2-Hexenal]
C7 Unsat aldehyde [2-Heptenal]
C7 Unsat aldehyde [2-Heptenal]
2,4-Heptadienal
2,4-Nonadienal
Compound
F:ormula(b)

C.02
C5.H12
C5.H10
C6.H12
C8.H12
C3.H18
CS.H16
C10.H22
C10.H22
C10.H22
C11.H24
C11.H22
C12.H26-
C13.H28
C13.H28
C13.H28
C13.H28
C13.H28
C13.H28
C14.H30
C5.H10
C6.H12
C6.H12
C8.H14
C3.H14
C8.H12
C8.H12
C9.H18
C9.H16
C10.H16
C10.H16
C10.H16
C11.H22
C11.H8
C11.H18
C11.H18
C8.H10
C8.H10
C9.H12
C3.H12
C3.H12
C3.H12
C10.H14
C10.H14
C10.H8
CI1.H16
C5.H12.0
O3.H14.0
C7.H16.0
C3.H18.0
C3.H18.0
cam 8.0
C13.H28.O
C8.H16.0
C8.H16.0
CS.H10.0
C8.H1ZO
C7.H14.0
C9.H18.0
C10.H20.0
C4.H6.0
C8.H10.0
ai.H10.0
C7.H12.0
C7.WZO
C7.H10.0
C9.H14.0
Compound
CAS No. (c)

124-38-9
78-784
287-92-3
2415-72-7
2415-72-7
584-94-1
61141-83-1
124-18-5
871-83-0
13475-81-5
3975-98-0
4292-92-6
1 7302-37-3
17312-65-1
82108-21-8
62108-25-2
62185-54-0
62237-99-4
62338-16-3
13287-21-3
109-67-1
592-41-6
592-41-6
1603-01-6
3710-41-6
22038-69-3
62338-00-5
124-11-8
61142-36-7
464-17-5
5989-54-3
53282-47-6
821-954
22822-99-7
74744-31-3
74744-31-3
95-47-6
95-47-6
95-63-6
98-82-8
103-65-1
611-14-3
488-23-3
535-77-3
91-20-3
1196-58-3
123-51-3
111-27-3
13231-81-7
104-76-7
111-37-5
111-87-5
112-70-9
57648-55-2
57648-55-2
110-62-3
66-25-1
111-71-7
124-19-6
112-31-2
78-85-3
6728-26-3
6728-26-3
18829-55-5
57266-86-1
4313-03-5
6750-03-4
Total Number of Occurrences
Number of h Each Region
Occurrences NC N= 5 W
46
45
18
7
13
22
31
3
16
9
10
8
i
'3
1
3
21
1
10
1
4
4
15
24
4
4
10
1
8
44
44
1
1
8
2
17
31
41
16
2
1
8
3
1
2
1
1
29
1
3
7
12
29
1
2
15
46
45
46
46
43
1
21
32
46
23
32
. 2,9
12
11
4
1
5
S
3
0
7
4
2
2
0
a
i
i
4
1
4
1
3
0
4
7
2
2
4
0
2
10
11
1
0
1
0
6
8
12
8
0
1
2
1
0
2
0
1
11
1
0
3
3
5
1
0
7
12
12
12
12
11
0
3
6
12
7
9
7
9
9
5
1
1
5
7
0
2
3
4
0
0
1
0
3
3
0
0
0
0
0
2
5
0
1
3
0
2
9
8
0
0
0
0
2
7
9
1
0
0
0
0
0
0
0
0
5
0
1
1
*
a
0
0
2
9
9
9
9
9
0
5
9
9
4
8
9
19
19
6
4
7
11
13
3
7
0
3
4
0
5
0
2
13
0
6
0
1
4
5
fl
1
0
1
0
4
19
19
0
0
4
1
6
12
17
7
2
0
6
2
1
0
1
0
10
0
H
2
7
10
0
2
5
19
18
19
19
18
1
10
13
19
8
12
10
6
6
3
1
0
0
3
0
0
2
1
0
1
1
0
2
1
0
0
0
0
0
4
1
1
1
2
1
0
6
6
0
1
3
1
3
4
3
0
0
0
0
0
0
0
0
0
3
0
1
1
•i
5
0
0
1
6
6
6
6
5
0
3
4
6
4
3
3
                                  25

-------
VxfeX CorrpcundChss
68
69
70
71
72
73
74
75
76 Aliphatic Kefona
77
• f
78
79
30
31 Unsaiurated Keiona
32
33
84
85 Aliphatic Ether
86 Aliphatic Ester
87
88
89
90
91
92
93
94
95
96
97
«* f
98
99
100
102
103
104
105
106
107
108
109
110
111 Unsaturatod Ester
112 HaJocaiton
114
115
116
117 Phenol
118 Hotarccyda
<19 Suifida
190
[6w
121 Organo-Siltcon
I au i c; -r ^i-ui
Compound Mams (a)
Isomer of decenal [2-Decenai]
Isomer of decenal [2-Decenai]
UnsaL aldehyde [2-Decenai]
UnsaL aldehyde [2-Oecenaij
UnsaL aldehyde [2-Decenal]
Diene aldehyde [2,4-Oecaaienal]
Oiene aldehyde (2,4-0 ecaflienaij
Diene aldehyde [2,4-Oodecadienal]
07 Ketone [2-Heptanone]
4-Heptanone
Unidentified C7.H12.0 [2,Z3-Trimethyl-cyclobutanone]
08 Ketone [3-Octanonej
SaL ketone [2-Oecanone]
isomer of Oc:en-one [3-Octen-2-one]
03 Ketone [3-Octen-f-one]
3,5-Octadien-2-one
09 UnsaL ketone [3-Nonen-2-one]
Dimethoxy methane
Propanoic acid, ethyl ester
05 Methyl ester [Butanoic add, methyl ester]
Propanoic add, propyl ester
Pontanofcadd, methyl ester
07 Methyl ester [Hexanoic add, methyl ester]
3-Methyl butanoic add, ethyl ester
Propanoic add, butyl ester
2-Methyl prapanoic add, 1-methylethyl ester
Acetic add, pentyl ester
2-Methyl butanoic acid, ethyl ester
08 Ethyl ester [Hexanoic acid, ethyl ester]
Acetic add, hexyl ester
08 Ester [3-Methyl butanoic add, propyl ester]
08 Ester [Bulanoic acid, 1-Methylpropyl ester]
08 Ester [Butanoic acid, 1-Methylpropyl ester]
Octanoic add, methyl ester
Hexanoic add, 1-melhy!ethyl ester
Butanoic acid, pentyl ester
Hexanoic add, 2-methylprapyl ester
Octanoic add, ethyl ester
010 Ester [2-Methyl-propanoic acid, hexyl ester]
011 Ester [Hexanoic add, pentyl ester]
011 Ester [4-Methyl pentanoic acid, pentyl ester]
011 Ester [Hexanoic acid, 2-Methylbutyl ester]
Isomer of octanoic acid [3-Methyl-butyl ester]
3-Octen-1-ol, acetate
05 Bromoalkane [1-Bromopentane]
3-Bromo-Pentane
Brominated alkane 5 07 [1-Bromo-heptane]
Dichlorobutane [1,4-dichlorobutane]
2-8romo-2-chloro-1 ,1 .trifluoro-ethane
Isomer of ethyl-phenol [4-Ethyl-phenol]
Unidentified C3.H14.0 [2-Pentyl-furan]
Dimethyl disulfide
Dimethyl tnsuifide
Decamethyl-cydopentasiioxane
Conpcund
Formula (b)
C10.H18.0
C10.H18.0
C10.H18.0
C10.H18.0
C10.H18.0
C10.H16.0
C10.H16.0
C12.H20.0 •
C7.H14.0
C7.H14.0
C7.H1ZO
cam 6.0
C10.H20.0
C3.H14.0
C3.H14.0
C3.H1ZO
C9.H16.0
C3.H8.02
C5.H10.02
C5.H10.02
C6.H1Z02
C8.H12.02
C7.H14.02
C7.H14.02
C7.H14.02
C7.H14.02
C7.H14.02
C7.H14.02
C8.H16.02
cam 6.02
C8.H16.02
C3.H16.02
cam 6.02
C9.H18.02
C9.H18.02
C9.H18.02
C10.H20.02
C10.H20.02
C10.H20.02
C11.H22.02
C11.H22.02
C11.H22.O2
C13.H26.02
C10.H18.02
C5.H11.BR
C5.H11.BR
C7.H15.BR
C4.H8.CL2
CZH.CLBR.F3
C8.H10.0
C9.H14.0
CZH6.S2
C2.H6.33
C10.H30.05.SI5
Total
Compound Number of
CAS No. (c) OccuiTCJices
3913-81-3
3913-81-3
3913-81-3
3913-81-3
3913-81-3
25152-84-5
25152-84-5
21662-16-8
110-43-0
123-19-3
1449-49-6
106-68-3
693-54-9
1669-44-9
1669-44-9
30086-02-3
14309-57-0
109-87-5
105-37-3
623-42-7
106-36-5
624-24-8
106-70-7
108-64-5
590-01-2
617-50-5
628-63-7
7452-79-1
123-66-0
142-92-7
557-00-6
819-97-6
819-97-6
111-11-5
2311-46-8
540-18-1
105-79-3
106-32-1
2349-07-7
540-07-8
25415-71-8
2601-13-0
2035-99-6
69668-83-3
110-53-2
1809-10-5
629-04-9
110-56-5
151-67-7
123-07-9
3777-69-3
324-92-0
3658-80-8
541-02-6
1
25
28
29
45
1
15
26
36
35
7
1
1
9
37
8
25
1
29
3
7
1
42
16
2
4
3
5
12
16
7
1
4
27
1
17
1
36
12
24
6
4
24
1
3
3
2
2
16
6
29
27
2
28
Number of Occurrences
h Each Region
NO N= S W
0
8
4
6
12
0
' -1
8
, 10
• 12
2
1
1
11
2
5
11
1
. 4
1
10
10
1
2
1
2
3
4
4
1
2
7
0
4
0
12
5
5
3
3
6
1
1
1
1
7
8
11
2
7
0
6
4
7
9
0
4
5
6
8
2

0
2

0
7
4
1
4
0
0
0
8
0
0
0
1
0
3
1
0
0
8
3
0
8
2
7
0
0
4
0
0
0
0
1
4
1
8
1
0
2
1
7
14
12
18
6
Tt
15
11
2

0
6
13
6
9
12
1
2
0
18
5
1
2
1
3
4-
9
3
2
8
7
1
11
4
10
2
1
9
0
1
0
1
4
1
5
9
13
0
14
0
4
6
4
6
4
2
5
4
1

0
0

0
4
2
1
1
0
6
1
0
0
0
0
2
2
0
0
4
3
0
5
1
2
1
0
5
0
1
2
0
3
•J
)
4
2
0
5
(a)  Toniamm compound identification is based on search vs. the NBS mass spectral library. Confirmation has riot been achieved by comparing
     retsnlionwthanauthenlicstandard. In cases where more than one reference compound successfully matched the unknown spectrum,
     a general descriptive name is reported and the best ranked NBS name is provided in brackets.

(b)  In cases where both a general name and an NBS name is reported, the formula corresponds to the NBS name and may not be applicable to the general name.

{c)  In cases where both a general name and an NBS name is reported, the CAS no. corresponds to the NBS name.                               .
                                                                            26

-------
Table 5.   Compounds Tentatively Identified in. the 6% Florisil Semivolatile Organic
                   Analysis Data Set vs. Frequency/Census Region
Index
I.S
1
2
3
-4
5
5
7
.8
9
10
11

12
'.3
14
15
16
17
18
1?
20
> 21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
-52
53
"54
55
56
57
*58
59
60
61
62
Comoound Class
Internal Standard
Alkane


Saturated Ketone
Saturated Ester


Sutfide

Oipeptida
Akene





Unsatuiated Aldehyde

Unsaturated Amine
Unsaturated Ketona
Arena


















Aromatic Aldehyde

Aromatic Ketone

Phenol


Aromatic Esier
Aromatic Ether

Aromatic Amine
Aromatic Oxime
Thiocyanic Ester
Heterocyclic Compound







Steroid


Compound Name (a) J-'
D10- Anthracene
2,6,1 0,14-Tetramethyl-hexadecane
2,6,1 0,1 4-Tetramethyl-nonadecane
Alkane 2 C18 [2,6,10,14,19-Pentamethyl eicosane)
1,2,4-Cyciopentatrione
12-Methyl-tridecanoic acid, methyl ester
Nonanedioic acid. bis(1 -methylpropyl) ester
9-Octadecenoic acid, ethyl ester
Methyl 2-methyM-{methylthio)buiyl disuifide
Dimethyl trisullida
Giycine, anhydride
C5 Substituted naonthaiene
iOctahydro-teirametnyl-IH-cycioorooaniAlnaDmhalenel
Hexahydro-4,7-dimetnyt-1-(1-m8triyiethvi)-naDnthaiene...
5-cthyiidene-1 -methyl-cycioheptene
C30 Unsat. hydrocarbon (Hexametnyl-tatracosanexaene)
Ylangene
2-8utyl-2-octenal
Unidentified C9.H8.0 [Cyclooctatetraene-l-carboxaHehydej
N,N-Dimethyl-3-octen-2-amine
6,10-Oimethyl-5,9-undecadien-2-one
C4 Alky! benzene [1-Ethyl-2,3-dimethyl benzene)
2-Ethyl-1 ,3-dimethyl-benzene
C4 Alkyl benzene [4-Ethyl-1,2-
-------
                                                                 Table  5   (concluded)
hta
63
84
65
66
67
33
39
70
71
72
73
r*
:»s
?6
77
78
79
ao
31
Compound Casa Compound Nama (a)
Chotast-5-an-3-on9
Cho!est-5-ene
(5.A|pna.}-cholest-7-en-3-one
Cholesta-3,5-olan-7-ona
(3.E«ta.)-cho!esta-4,6-d:en-3-ol benzoata
Cholesterol
Esomerolcholestanol [S-chotesten-3-ol propionatej
Pregnane. (5,alpha,)-
(3.Beta.}-26.27-dinorsrgost-5-en-3-ol benzoate
CHonratftd Hydrocarbons 1,1-0icn!ora-1-propena
(4-Ch!orephenyl]phenyl-methanon8
2-Chloro-6-methyl-benzonitnle
Oiehbrcbenzene [1.3-dichlorc-ienzene|
Undana
ODD
OfB3flC-S3con fsomer of decamethyl-cyciopemasitoxane
Cctameihyl-cyclojeirasiloxana
isomar of decamethyl-cyclopentasiloxana
Phthalaw Oiheptyl pnthatata
Compound
Formula (b)
C27.H44.0
C27.H46
C27.H44.0
C27.H42.0
C34.H48.02
C27.H46.0
C30.H50.02
C21.H36
C33.H48.02
C3.H4.CL2
C13.H9.0.CL
C3.H6.N.CL
CS.H4.CI2
Co.H6.CL5
C14.H10.CL4
C10.H30.05.SI5
C8.H24.04.SI4
C10.H30.05.SI5
C22.H34.04
Compound
CAS Number (c)
601-54-7
570-74-1
15459-85-5
567-72-6
25485-34-1
57-88-5
633-31-3
641-85-
58003-48-8
563-53-6
134-85-0
5575-09-3
541-73-1
58-39-9
72-54-8
541-02-6
556-67-2
541-02-6
3648-21-3
Total Number
of Occurrences
Samples Blanks
3
10
1
1
3
3
40
4
1
1
1
1
13
5
12
28
21
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Number of Occurrences
in Each Region
NC NE 3 W
0
4
0
0
0
0
12
0
0
1
0
1
4
2
3
7
3
0
0
0
1
0
0
0
1
9
2
0
0
0
0
2
3
1
5
5
0
0
2
4
1
1
2
1
16
1
1
0
0
0
8
t
3
12
9
0
0
1
1
0
0
1
1
3
1
0
0
1
0
1
0
0
4
4
1
1
(a)  T««»l.V» compound idonuHtaiion is based on search vs. the NBS mass spectral Ibrary. Confirmation has not been achieved by comparing
    raUffiJMl with an auhentic standard. In cases where more than one reference compound successfully matched the unknown spectrum,
    a otntral tfescnplrva nama 'a reported and the best ranked NBS nama is provided in brackets.

0}  En casts vrtvon both a general nama and an NBS name is reported, the formula corresponds to the NBS name and may not be applicable to the general name.

(c)  In easts vrtwra both a General name and an NBS name is reported, the CAS no. corresponds to the NBS name.
                                                                               28

-------
Table 6. Compounds Tentatively Identified in the 15/50% Florisil Semivol
Analysis Data Set vs. Freauencv/Census Reaion
Index
ia
1
2
3
4
5
5
7
8
9
10
11
!2
13
!4
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
33
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57 '
58
59
SO
61
62
63
Com pound Class
Internal Standard
Alkane
Saturated Ester



Saturated Polyfunasonal

Atone
Unsaturated Aldehyde

Unsaturated Ketone



Unsaturated Polyfuraional



Alkyna
Arena




Aromatic Aldehyde


Aromatic Ketone
Aromatic Amide
Aromatic Carboxylata Derivative



Phthalic Acid Derivative




Phenol


Aromatic Polyfunctional



Drug






Heterocydic Compound










Compound Nama (a)
010-Anthracene - Internal Standard
Unidentified C10.H20 [Diethyl cyciohexana]
1,7,7-Trim8thyl-bicyclo[2.2.1]haptan-2-ol, exo propanoate-
Dodecanoic acid, ethyl estar
Hexanedioicacid,mono(2-ethyihexyl) ester
Alkyl ester [15-Methyl-heptadecarioate|
Elhyihydrazona propionakiehyda
9-Oxc-nonanoic acid, athyl ester
1 -MethyK5-(1 -melhylethenyl)-cyclohexene
Trimethyl-3-cyclohexene-l -caAoxaWehyda
2-Sutyl-2-octanal
3-Methyl-3-8ut8n-2-on8, dimer
2,4,6-Cycioheptatnene-t -one
5-Unaecen-4-one
5-cthy(-2-memyl-4-ri8pten8-3-on8
Substituted cyclopentenone [3utyl-metnoxy-cyck3pantan-1-one|
Substituted cydopentenone [Butyl-methoxy-cyciopeman-l-onal
Subsdtuted cyctopantenone [Butyl-methoxy-cyclopenten-1-one|
2-Methoxy-2-octen-4-ona
5,5-Dimathyl-3-h8ptyn8
C3-Alkyl banzene [1 ,3,5-trimethyl-benzenel
C3 Alkyl benzene [1,2,4-Trimethyl-benzenej
C3-Alkyl benzene (1,2.4-trimethyl-benzenej
C3 A8
-------
                                                                           6  (concluded)
hfcx ComcoundCaj
64
65
66
87
68
69
70
?t
n
73
74
75 Strcid
;B
77
78
79
30
31
32
33
34
85
36
87
88
89
90 BaJoQOnaiKJ Hydrocarbon
31
92
93
94
95 Organo-StHcon
96
ComDound Name (a]
1.3-Benzodioxcle
4,7-Dimathyl-3(2H)-benzofuranon9
Unidentified C11.H16.02 [Tetrahydro-tri[T!ethyl-2(4H)-benzoluranone]
5-{8utylimino)-2(5H)4uranone
2H-1-Benzopyran-2-one
1,3,5-TrimethvHH-cyrazole
isonw of Ihtenyt-ethanona (1-(3-Tnienyl)-ethanone|
V{4-Hydroxy-3-thienyl)-«thanone
2,3,4-trimeihyl ihtophane
2-Meihyl-5-propyl-tniophene
2-t-Butoxy-lhiophen9
Isomer of cho!est-en-ol (Cholest-5-an-3-ol,acetate|
isomer of cnolest-en-ol IChoisst-5-en-3-ol,acetai8J
Cho!esi-5-en-3-ol (3.beta.)-, propanoate
Chotest-5-en-3-one
Cholest-S-ena
Isomsr of cholest-en-ol [4-Methykholest-8(14)-en-3-oll
Chc!esta-3,5-dien-7-one
Chotesta-4,6-dien-3-ol (S.Beta.). Banzoate
Cho!8sta-5.7-dien-3-ol, (S.beta.)
Isomer of choiestanol [Cholestanol]
Methyl-cho!estan-3-ol, (3.beta.,5.aipha.,6.b8!a.)-
3-(Aco!oxy)-chol9sian-6-on9. (3.beta,5.alpha.)-
Chotesian9-3,5-diol, (3.beta..5.alpha.)-
Cholestanol
Cholesterol
1-Ch!oro-4-{Methy!sulfonvl)-benzene
Iscmerof ftuoro-methyl-benzene [l-Fkioro-2-methyl-benzenel
Carbonochforidothioic acid, S-methyl ester
1,1-OicMorc-ethene
4-Chloro-2-(p he nylmeihyl) -phenol
1-ButynyUrimethyl si!ane
Trim8thyt({1-m8ihyl-2-propynyl)oxyj-siian9
Compound Compound
Formula (b) 3AS Numbsr (c)
C7.H6.02
C10.H10.02
C11.H16.02
C8.H11.02.N
C9.H6.02
CS.H10.N2
C3.H6.0.S
C6.H6.02.S
C7.H10.S
C8.H12.S
C8.H12.0.S
C29.H48.02
C29.H48.C2
C30.HS0.02
C27..H44.Q
C27.H46
C28.H48.0
C27.H42.0
C34.H48.02
C27.H44.0
C27.H48.0
C28.H50.0
C29.H48.03
C27.H48.02
C27.H48.0
C27.H46.0
C7.H7.02.S.CL
C7.H7.F
C2.H3.0.S.CL
C2.H2.CL2
C13.H11.0.CL
C7.H14.SI
C7.H14.0.SI
274-09-9
20895-45-8
17092-92-1
27396-39-0
91-64-5
1072-91-9
1468-83-3
5556-16-1
1795-04-6
33933-73-2
23290-55-3
504-35-3
604-35-3
504-35-3
501-54-7
570-74-1
52014-96-4
567-72-6
633-31-8
434-16-2
80-97-7
43217-65-8
1256-83-3
3347-60-2
80-97-7
57-88-5
98-57-7
95-52-3
2812-72-8
75-35-4
120-32-1
62108-37-6
1 7869-76-0
Total Number
of Occurrences
Samcles Blanks
2
4
6
3
1
1
7
3
5
4
4
37
25
45
44
30
5
22
45
3
23
15
3
2
4
44
1
10
5
1
4
7
5
0
0
0
0
0
1
0
0
0
0
0
1
0
2
2
0
0
1
2
0
0
0
0
0
0
1
0
1
0
0
0
0
0
Number of Occurrences
intacriRscpon
NC HE S W
1
2
, 3
0
0
0
2
0
4
1
1
: 9
1 7
12
12
10
3
5
12
2
9
5
0
1
1
11
1
3
1
0
0
2
2
1
0
0
3
1
0
2
0
0
0
0
7
3
9
a
4
1
4
9
1
3
3
0
0
0
9
0
3
1
0
3
1
0
0
2
2
0
0
1
2
1
1
3
2
16
9
19
19
14
1
11
19
0
11
6
1
1
2
19
0
3
0
0
1
3
3
0
0
1
0
0
0
1
2
0
0
1
5
1
5
5
2
0
2
5
0
0
1
2
0
1
5
0
1
3
1
0
1
0
(a)  Tentatrva compound idertilicatjon is based on search vs. the NBS mass spectral Ifcrary. Confirmation has not been achieved by comparing
    faiantion with an au*o«ic standard \n cases where more than one reference compound successfully matched the unknown spectrum,
    a csr.oral dascnptivo tuma is reported and the best ranked NBS name is provided in bracken.

(b}  !fl CiSM whars both a cenoral nams and an NBS name is reported, the formula corresponds to the NBS name and may not be applicable to the general name.

(cj  hcaswwrars both a general name and an NBS name is reported, the CAS no. corresponds to the NBS name.
                                                                              30

-------
Table 7.   Unidentified Peaks in the Volatile Organic Analysis Data
                  Set vs. Frequency/Census Region
Index
I.S.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33 .
34
35
36
37
38
39
40
41
42
43
44
45
46
Average
RRT
1.000
.481
3.216
3.114
2.659
4.213
.370
2.398
.405
2.890
4.353
3.862
.286
3.322
3.314
2.771
2.689
1.997
3.384
3.873
2.666
4.390
2.570
3.962
' 4.142
.335
2.369
2.619
3.364
3.812
1.488
2.572
3.177
4.159
2.053
.4.388
4.573
.802
1.744
2.495
2.867
2.906
. 3.308
3.501
4.319
.277
.408
Total
Number of
Occurrences
46
46
46
45
44
43
41
41
34
30
28
24
23
21
18
14
13
12
12
12
11
11
10
9
9
8
8
8
8
8
7
7
7
7
6
6
6
5
5
5
5
5
5
5
5
4
4
North Central
12
12
12
11
12
11
9
11
11
8
4
6
5
10
7
4
5
2
3
1
3
2
2
0 •
4
1
1
2
1
2
1
4
2
1
3
1
3
1
0
2
2
1
4
0
2
2
0
Number of Occurrences
in Each Region
Northeast South
9
9
9
9
9
9
9
8
8
6
9
6
3
4
4
2
1
6
0
2
1
2
1
1
0
1
2
2
4
4
0
0
3
0
2
2
3
4
2
1
2
1
0
0
1
1
0
19
19
19
19
18
17
18
18
12
11
10
12
12
5
6
7
5
3
9
7
6
4
5
7
5
6
4
3
3
1
6
2
2
4
1
3
0
0
1
2
0
2
0
5
2
1
2
West
6
6
6
6
5
6
5
4
3
5
5
0
3
2
1
1
2
1
0
2
1
3
2
1
0
0
1
1
o
1
0
1
o
2
o
o
0
0
2
0
1
1 •
1
0
o
o
2
                                 31

-------
Table 7 (conti
Index
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
Average
RRT
1.719
3.064
3.159
3.513
3.881
3.908
4.317
.381
1.141
2.721
3.482
4.146
.285
.573
2.141
2.892
3.012
3.551
3.564
3.700
3.963
4.113
.313
1.036
1511
1.672
2.028
2.239
2.262
2.271
2.301
2.407
2.671
2.891
2.907
2.988
3.073
3.100
3.175
3.314
3.371
3.453
3.461
3.494
3.650
3.782
3.829
Total
Number of
Occurrences
4
4
4
4
4
4
4
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
'1
1
1
1
1
1
1
1
1
1
1
1
!
1
1
1
North Central
1
0
2
3
2
0
0
2
2
2
1
2
2
1
2
0
1
0
2
1
0
0
1
1
0
1
0
1
0
0
1
1
0
0
0
1
0
0
0
0
0
1
1
1
0
0
1
nued)

Number of Occurrences
in Each Region
Northeast South
0
0
0
1
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0 •
0
1
0
2
2
2
0
1
1
3
1
0
0
1
1
0
0
0
2
0
1
0
1
0
2
0
0
0
0
0
0
1
1
0
0
0
0
0
0
1
1
1
1
1
0
0
0
1
0
0

West
1
2
0
0
1
0
1
0
1
• 1
1
0
0
1
0
0
1
1
0
0
, 1
0
0
0
1
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
32

-------
Table 7 (concluded)

Index

94
95
96
97
98
99

Average
RRT
3.975
3.993
4.192
4.635
4.812
5.004
Total
Number of
Occurrences
1
1
1
1
1
1
Number of Occurrences
In Each Region
North Central
0
0
0
0
0
0
Northeast
0
0
1
1
1
1
South
1
1
0
0
0
0
West
0
0
0
0
0
0
33

-------

Table 8.
Index Average RRT
IS
1
2
3
4
5
6
7
E
g
1C
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
28
27
28
29
30
31
32
33
34
35
36
37
38
3S
40
41
42
43
44
45
46
47
48
49
50
1.000
0.924
1.600
0.759
1.027
1.023
1.117
1.706
1.129
0.879
0.702
0.919
0.990
0.838
0.912
1.481
1.760
0.985
1.059
0.673
0.993
0.982
1.533
1.063
1.199
1.374
0.726
1.741
0.952
1.237
1.629
1.586
0.493
1.002
1.065
0.839
1.070
1.728
0.574
0.665
1.178
1.280
1.297
0.190
0.666
0.310
0.603
1.082
1.131
1.146
0.411
Unidentified Peaks in the 6% Florisil Semivolatile Organi
Analysis Data Set vs. Frequency/Census Region
Total Number of Occurrences in Each
Number of
Occurences North Central Northeast
44
42
42
38
38
35
34
34
32
31
30
30
29
28
26
26
25
24
24
23
23
22
22
21
21
21
19
19
17
17
17
16
15
15
15
14
14
14
13
13
13
13
13
12
12
11
11
11
11
11
10
12
12
12
10
12
9
12
11
12
10
9
9
9
8
6
9
7
7
8
6
5
8
8
6
9
6
7
6
7
6
3
6
3
5
4
3
4
6
2
6
5
5
4
3
5
4
1
3
2
3
3
9
9
7
9
8
6
3
5
1
6
4
7
4
4
5
1
2
5
1
6
6
3
2
4
3
3
3
3
2
1
2
1
5
2
2
3
1
1
0
2
0
1
0
3
4
2
1
0
3
2
1
Region
South
18
18
18
17
13
16
15
16
15
14
13
12
13
13
11
14
14
10
12
8
10
9
11
8
9
11
8
9
6
7
11
9
4
7
8
7
6
6
9
5
7
6
8
4
2
2
8
5
4
3
3
West
5
3
5
2
5
4
4
2
4
1 '
4
2,
3
3
4
2
2
2
3
3
2
2
1
3
0
1
1
1
2
3
1
0
3
1
1
1
3
1
2
0
1
1
1
2
1
3
1
3
2
3
3
C
Number of
Occurences in
Blanks
3
0
2
0
0
0
0
1
0
0
0
0
0
0
0
2
1
0 *
0
0
0
0
1
0
0
1
0
0
0
0
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
34

-------
Table 8 (continued)
Index Average RRT
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
0.780
1.009
1.160
1.219
1.224
0.220
0.670
0.959
1.178
1.197
1.626
1.638
0.360
0.674
0.897
0.932
1.051
1.094
1.427
1.475
1.681
1.773
0.337
0.662
0.880
1.177
1.253
1.681
0.278
0.472
0.736
0.991
1.057
1.069
1.073
1.085
1.195
1.407
0.399
0.661
0.730
0.965
1.068
1.144
1.195
1.222
1.326
1.355
1.389
1.411
1.538
Total
Number of
Occurences
10
10
10
10
9
8
8
8
8
8
8
8
7
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
5
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
4
• 4
4 •
Number of Occurrences in Each
North Central Northeast
2
2
4
4
4
2
0
4
2
0
3
4
2
1
1
2
3
4
1
1
4
2
1
1
1
4
3
1
0
2
2
3
3
2
1
2
0
3
0
3
1
0
2
2
2
1
1
2
2
.2
1
1
0
2
2
2
3
1
1
1
1
1
0
0
4
0
2
1
1
1
5
1
2
0
2
1
0
0
1
3
0
0
0
0
2
2
2
0
0
4
0
0
3
0
1
0
0
1
0
0
0
1
Region
South
5
5
3
3
1
1
6
2
4
5
4
4
4
2
6
3
1
2
4
1
1
3
4
1
2
2
2
4
2
3
3
2
1
1
1
1
3
2
0
1
2
1
1
1
1
2
0
2
2
2
1
West
2
3
1
1
2
2
1
1
1
2
0
0
1
0
0
0
2
0
1
0
1
0
1
2
2
0
1
0
0
0
0
0
1
0
1
0
. 2
0
0
0
1
0
1
0
1
1
2
0
0
0
1
Number of
Occurences in
Blanks
0
0
0
0
o
0
o
0
o
0
o
0
o
0
o
0
o
o
1
o
o
o
o
o
o
o
o
2
o
o
o
o
o
o
o
o
o
o
o
o
o
2
o
o
o
o
o
o
o
o
0
          35

-------
Table 8 (continued)
Index Average RRT
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
14S
144
145
146
147
148
149
150
151
152
0.316
0.608
0.662
0.747
0.754
0.855
0.893
0.918
0.967
1.01S
1.025
1.041
1.045
1.050
1.055
1.076
1.107
1.109
1.186
1.244
1.251
1.414
1.457
1.585
0.325
0.356
0.747
0.754
0.817
0.823
0.855
0.896
0.898
0.905
0.933
0.976
0.982
0.985
1.020
1.038
1.053
1.080
1.105
1.120
1.124
1.143
1.152
1.158
1.179
1.221
1.252
Total
Number of
Occurences
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Number of Occurrences in Each
North Central Northeast
1
1
0
0
3
0
0
1
3
1
0
1
1
0
2
3
0
0
0
0
1
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
2
0
2
1
0
1
0
0
1
2
0
0
0
0
0
1
0
0
2
0
0
0
0
0
2
1
2
0
1
0
0
3
0
1
0
0
1
0
0
0
2
2
0
0
2
0
1
2
2
0
0
0
0
0
0
0
c
1
2
0
0
0
1
1
0
0
Region
South
0
1
2
0
0
1
3
2
0
0
2
0
2
1
1
0
0
3
1
3
2
1
3
3
1
0
0
2
0
0
1
0
0
0
1
2
0
1
0
1
2
1
0
0
1
0
1
1
0
2
2
West
1
1
1
1
0
2
0
0
0
0,
0,
0
0
1
0
0
0
0
1
0
0
1
0
0
0
0
0
0
1
0
1
1
0
0
1
0
0
1
0
0
0'
0
1
0
0
0
1
0
1
0
0
Number of
Occurences in
Blanks
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Q
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
          36

-------
Table 8 (continued)
Index Average RRT
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
, 195
196
197
198
199 '
200
201
202
203
1.336
1.345
1.360
1.382
1.542
1.577
1.589
1.600
1.680
1.727
1.731
0.229
0.255
0.266
0.269
0.279
0.293
0.300
0.329
0.357
0.406
0.406
0.463
0.499
0.539
0.575
0.672
0.676
0.708
0.724
0.732
0.732
0.734
0.742
0.743
0.747
0.749
0.799
0.829
0.830
0.855
0.892
0.911
0.914
0.973
1.011
1.018
1.035
1.051
1.053
1.060
Total
Number of
Occurences
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number of Occurrences in Each
North Central Northeast
2
0
1
1
0
2
0
0
0
1
1
0
0
0
0
0
1
0
1
0
1
1
0
0
0
0
0
0
0
1
1
0
0
0
0
0
1
1
0
1
1
0
0
1
1
1
0
0
0
0
0
0
0
1
0
0
0
1
1
0
1
0
1
1
1
0
0
0
1
0
0
0
0
1
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
1
1
0
0
0
0
0
0
1
0
Region
South
0
2
0
1
2
0
1
0
2
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
1
1
0
0
o
o
1
1
1
d
0
0
0
0
0
0
o
0
0
1
1
1
0
1
West
0
0
o
o
0
0
o
1
o
o
o
o
0
o
1
1
o
0
o
1
o
o
o
o
1
o
o
o
o
o
o
1
o
o
o
o
o
o
o
o
o
o
o
o
0
o
o
o
o
o
0
Number of
Occurences In
Blanks
0
o
o
n
•J
o
o
o
u
o
o
1
t
o
\J
o
o
n
V
0
V
o
u
o
o
o
u
n
u
o
n
\J
o
n
V
o
V
n
V
n
V
n
\j
n
\J
n
\J
n
V

n
V
n
V
n
u
A
\J
n
U
n
U
n
\J
2
Cm
o
n
\J
n
U
n
V
n
U
n
V
0
         37

-------
Table 8 (continued)
Index Average RRT
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
1.064
1.075
1.078
1.084
1.107
1.117
1.117
1.118
1.121
1.122
1.134
1.134
1.138
1.140
1.140
1.152
1.161
1.170
1.189
1.208
1217
1.226
1.262
1.288
1.289
1.304
1.348
1.349
1.349
1.350
1.356
1.375
1.379
1.394
1.407
1.534
1.588
1.590
1.596
1.624
1.634
1.646
1.659
1.676
1.678
1.701
1.709
1.718
1.721
1.731
1.734
Total
Number of
Occurences
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number of Occurrences in Each
North Central Northeast
0
1
0
1
0
0
0
0
0
0
0
0
1
0
0
1
0
1
0
0
1
0
0
1
0
0
0
0
1
1
1
1
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
1
0
0
1
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
1
0
0
1
0
0
1
Region
South
0
0
0
0
1
0
1
1
1
1
0
0
0
1
1
0
0
0
1
0
0
0
1
0
1
0
1
1
0
0
0
0
1
0
1
1
1
0
1
0
1
1 •
1
0
0
1
1
0
1
1
0
West
0
0
1
0
0
0
0
0
0
0 •
1 .
0
0
0
0
0
0
0
0 '
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o ,
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Number of
Occurences in
Blanks
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
• o
           38

-------
Table 8 (concluded)

Index
255
256
257
, 258

Average RRT
1.734
1.740
1.804
1.889
Total
Number of
Occurences
1
1
1
1
Number of Occurrences in Each Region
North Central
0
0
1
0
Northeast
1
0
0
0
South
0
1
0
1
West
0
0
0
0
Number of
Occurences in
Blanks
0
o
o
0
39

-------
Table 9.  Unidentified Peaks in the'15/50% Florisil Semivolatile
      Organic Analysis Data Set vs. Frequency/Census Region
Index
IS.
1
2
3
4
5
6
7
8
9
10
1:
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
33
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
58
57
58
59
60
61
62
63
Averags Total Number
RRT of Occurrences
1.000
1.920
0.419
1.052
1.007
0.452
1.616
0.402
0.633
1.742
0449
1569
2.034
1.692
1.682
1.710
0.437
0.606
1.238
1.657
1.187
1.453
0.839
1.665
0.647
1.128
2.059
1.953
1.440
1.490
1.722
1.430
0.932
1.115
1.223
2.009
0.589
1.147
1.557
1.235
1.178
0.555
0.990
1519
1.629
0.876
0.680
0.912
1.086
1.089
1.556
1.980
1.929
0.982
1.809
1.027
1510
1500
1.950
0.586
0.858
1511
1561
2.014
46
44
42
41
40
38
38
37
35 •
35
34
34
Zt-
33
32
32
29
29
29
28
28
28
27
27
26
26
26
25
25
24
23
22
21
21
21
20
20
20
20
19
18
18
17
17
16
16
15
15
15
15
15
15
14
14
14
13
13
13
13
12
12
12
12
12
Number of Occurrences in Each Region
North Central Northeast South
12
12
11
12
12
11
12
10
9
11
10
10
10
11
10
11
6
7
12
10
9
11
10
10
7
11
9
6
8
8
8
7
7
8
6
6
5
5
6
6
5
2
7
6
5
4
3
6
5
6
5
4
3
6
3
6
5
4
4
4
5
4
5
4
9
9
9
6
5
6
6
7
9
6
6
5
5
4
7
3
7
6
2
6
3
4
3
3
4
0
2
4
3
3
4
3
1
0
3
2
5
0
3
1
3
6
1
2
3
2
2
0
1
2
3
2
1
1
2
0
3
3
2
0
3
3
1
0
19
18
17
18
18
15
17
14
13
16
12
16
14
16
14
16
10
11
13
10
14
11
12
13
12
14
13
13
13
11
9
11
12
11
9
10
5
13
9
11
9
8
9
8
7
8
7
8
6
6
5
8
8
7
8
6
4
5
6
7
4
4
5
6
West
6
5
5
5
5
6
3
6
4
2
6
3
5
2
1
2
6
5
2
2
2
2
2
1
3
1
2
2
1
2
2
1
1
2
3
2
5
2
2
1
1
2
0
1
1
2
3
1
3
1
2
1
2
0
1
1
1
1
1
1
0
'1
1
2
Number of
Occurrences
In Blanks
4
1
3
0
0
3
1
3
0
0
3
1
1
0
0
0
3
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
2
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
1
0
0
0
                                  40

-------
Table 9 (continued)
Index
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
Average
RRT
2.088
0.996
1.027
0.218
0.398
1.475
1.522
1.542
1.980
0.745
0.904
1.105
1.359
0.429
0.673 .
0.897
1.548
1.989
0.226
0.243
0.989
1.149
1551
1.973
£151
2.174
0.301
0.392
0.520
0.672
1.198
1.675
1.889
0.492
0.758
1.175
1.202
1.308
1.472
1531
1.966
2.137
1531
0.374
0.450
0.540
0.547
0.559
0.573
0.762
0.918
1.062
1.070
1.105
1.138
1.175
1.288
1.460
1.716
1.729
0.475
0.507
0.520
0.667
Total Number
of Occurrences
12
11
11
11
11
11
11
11
11
10
10
10
1C
9
9
9
9
9
8
8
8
8
8
8
8
8
7
7
7
7
7
7
7.
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5 .
5
5
5
5
5
5
5
5
5
5
5
4
4
4
4
Number of Occurrences in Each Region
North Central Northeast South
4
2
2
2
3
4
3
3
4
3
3
2
3
5
4
2
3
4
2
2
4
3
4
4
2
2
2
2
0
1
2
2
1
3
3
3
1
1
1
3
1
1
1
.1
1
1
1
1
1
2
3
0
2
1
3
2
0
1
1
2
1
0
0
3
2
3
3
3
2
3
2
2
1
1
1
3
3
1
2
1
2
0
2
2
0
2
0
0
1
1
0
1
6
0
0
0
2
2
1
0
0
2
0
0
2
1
0
1
2
0
1
1
0
0
0
1
0
2
0
3
2
1
1
1
1
1
1
0
5
5
5
4
6
4
4
5
5
6
5
4
4
2
3
5
3
5
2
2
3
3
3
4
4
5
2
3
0
5
5
4
3
0
2
3
4
3
3
3
3
3
3
2
2
4
3
3
3
3
2
3
2
2
2
0
2
2
3
2
1
3
2
1
West
1
1
1
2
0
0
2
1
1
0
1
*1
0
1
0
1
1
o
2
2
1
0
1
o
1
0
3
1
1
1
0
1
1
1
0
0
1
o
2
0
0
1
1
•j
o
o
o
o

c
0
1
1
o
o
o
1
1
o
0
1
o
1
0
Number of
Occurrences
in Blanks
0
1
1
0
0
0
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
V
1
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
0
          41

-------

Index
128
129
130
131
132
133
134
135
135
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191

Average
RRT
0.721
0.832
0.936
1.C61
1.109
1.153
1.173
1277
1.328
1580
1.927
1.979
2.00C
0.319
0.375
0.609
0.307
0.346
0.353
0.487
0.727
0.739
0.790
0.821
0.828
1.083
1.119
1.123
1.195
1.309
1.404
1.448
1.538
1.856
1.953
2.084
aoai
0512
0.572
1.809
1.900
0.237
0561
0.337
0.341
0.342
0.382
0.413
0.435
0.450
0.489
0.496
0.552
0.599
0.614
0.677
0.758
0.791
0.908
0.921
0.957
1.059
1.261
1283

Total Number
of Occurrences
4
4
4
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Table
9 (continued)
Number of Occurrences in Each Region
North Central Northeast South
0
0
1
1
2
0
2
1
0
2
2
1
2
2
1
1
0
1
0
1
0
1
0
0
0
0
1
2
0
0
1
0
1
2
2
2
1
2
0
0
0
1
0
1
0
1
0
0
1
1
0
0
1
0
0
0
1
1
1
0
1
1
1
0
0
0
1
1
1
2
0
1
0
1
0
1
0
0
1
0
0
1
0
0
0
1
2
1
1
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
.0
0
2
0
2
0
0
0
0
0
0
0
0
2
2
2
0
0
0
0
0
0
0
1
4
4
1
2
0
2
2
2
4
0
1
1
2
1
0
2
2
1
0
2
3
0
0
2
2
3
2
1
3
2
1
2
2
1
1
1
2
0
2
2
2
1
0
1
0
1
1
2
0
1
2
2
1
0
0
0
0
1
1 •
2
1
1
1 ,
1
West
0
0
1
0
1
0
0
0
0
1
1
1
0
0
1
0
1
0
3
0
0
1
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
1
0
0
0.
0
0
0
0-
Number of
Occurrences
in Blanks
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.0
0
0
42

-------

Index
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255

Average
RRT
1291
1297
1.353
1.463 ,
1.507
1516
1.525
1.586
1.594
1.673
1.866
1531
2.030
2.102
0.333
0.544
0.199
0.203
0.216
0.221
0.239
0.240
0.241
0.254
0.266
0.268
0.283
0.285
0.293
0.300
0.327
0.344
0.352
0.353
0.358
-•0.359
0.362
0.365
0.370
0.371
0.372
0.394
0.405
0.414
0.419
0.421
0.422
0.455
0.463
0.465
0.504
0.507
0.510
0.516
0.545
0.575
0.584
0.652
0.653
0.678
0.683
0.711
0.744
0.745

Total Number
of Occurrences
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1 .
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Table
9 (continued)
Number of Occurrences in Each Region
North Central Northeast South
0
1
1
1
0
0
1
1
2
2
0
1
1
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
o .
0
0
0
1
0
0
0
0
0
1
1
1
1
0
0
0
1
0
0
0
1
0
0
0
1
1
0
0
0
0
0
0
1
1
0
1
0
0
0
0
0
1
0
1
1
0
0
0
0
0
1
0
0
0
0
1
0
c
1
0
0
0
0
0
1
0
1
0
0
0
2
1
1
0
1
1
0
1
0
0
1
1
1
1
0
1
1
1
0
0
1
1
0
0
1
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
1
1
1
0
1
1
1
0
0
0
0
0
1
1
1
0
1
0
1
0
0
0
1
West
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
o
0
o
0
0
o
o
o
o
o
1
o
1
1
o
•)
o
o
•)
o
o
o
o
o
o
o
o
o
o
1
1
o
o
o
o
1
0
o
o
. o
o
•)
0
Number of
Occurrences
in Blanks
0
0
o
o
0
0
o
0
0
0
o
o
o
o
•\
1
0
0
0
o
o
o
o
n
u
o
o
o
o
o
o
o
Q
o
n •
V
o
o
V
o
o
V
o

o
o


o
o
v
Q
n
u
o
o
o
n
w
o
o
o
g
o
n
V
o
n
V
o
n '
\l
o
0
43

-------

bxJsx
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
319
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319

Average
RRT
0.767
0.771
0.775
0.779
0.786
0.787
0.821
0.915
0.929
0.945
0.960
0.988
1.017
1.018
1.037
1.046
1.061
1.C63
1.070
1.089
1.091
1.112
1.121
1.140
1.174
1.180
1.197
1.204
1.204
1218
1.223
1.226
1.243
1.248
1289
1291
1296
1.309
1511
1.335
1.342
1.346
1.348
1.350
1.363
1.366
1.377
1.384
1.386
1.390
1.403
1.421
1.422
1.427
1.433
1.435
1.457
1.481
1.492
1.495
1.499
1523
1.525
1531

Tola] Number
of Occurrences
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
4
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Table
9 (conti
nued)
Number at Occurrences in Each Region
North Centra! Northeast South
1
0
0
0
0
0
0
0
0
0
0
c
0
c
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
1
1
0
1
0
1 . •
1
1
0
1
0 '
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
,1 .
1
0
1
1
1
1
1
0
1 •
1
1
0
1
1
'1
1
1
1
0
0
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
0
1
1
1
1
1
1 .
1 •
1
1
1
0
0
1
0
0
1 .
0
1
0
0
0
1
0

West
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
. 0
0
0
0
0
0
0
0
0
0
0,
0
0
0
0
0
0
0
0
0
0
0 .
0
0

Number of
Occurrences
in Blanks
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
•0
0
0
0
o-
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
44

-------

Index
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343

Average
RRT
1.545
1.562
1.583
1.584
1.589
1.596
1.602
1.606
1.607
1.671
1.695
1.740
1.761
1.762
1.776
1.839
1.907
1.964
1.973
1.980
1.991
2.053
2.063
2.107

Total Number
of Occurrences
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Table
9 (concluded)
Number of Occurrences in Each Region
North Central Northeast South
1
1
1
1
1
1
1
1
1
0
0
0
0
0
1
1
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
1
1
0
0
1
1
1
0
1
1
1
0
West
0
0
0
0
0
0
0
0
0
o
0
o
o
0
0
0
o
0
o
o
0
o
0
0
Number of
Occurrences
in Blanks
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
o
o
o
0
o
o
0
45

-------
Tab!
We*
1
2
3
&
5
6
7
8
9
1C
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
33
39
40
41
42
43
44
45
46
e 10. NHATS
SarrcteName
1-EN-VO-0-14
1-EN-VO-15-44
1-EN-VO-45+
1-ES-VO-0-14
1-ES-VO-15-44
1-ES-VO-45+
1-MA-VO-0-14
1-MA-VO-15-44
1-MA-VO-45+
1-MO-VO-0-14
1-MO-VO-15-44
1-MO-VO-45,.
1-NE-VO-0-14
1-NE-VO-15-44
1-NE-VO-45+
1-PA-VO-0-14
1-PA-VO-15-44
1-PA-VO-45+
1-SA-VO-0-14
1-SA-VO-15-44
1-SA-VO-45+
1-WN-VO-0-14
1-WN-VO-15-44
1-WN-VO-45+
1-WS-VO-0-14
1-WS-VO-15-44
1-WS-VO-45+
2-EN-VO-0-14
2-EN-VO-15-44
2-EN-VO-45+
2-ES-VO-15-44
2.ES-VO-45+
2-MA-VO-0-14
2-MA-VO-15-44
2-MA-VO-45+
2-SA-VO-0-14
2-SA-VO-15-44
2-SA-VO-45+
2-WN-VO-45+
2-WS-VO-15-44
3-EN-VO-15-44
3-EN-VO-45-1-
3-SA-VO-15-44
3-SA-VO-45+
4-SA-VO-15-44
4-SA-VO-45+
FY82 Comoosite
Number of Peaks
Submitted to
ACORN Program
68
63
62
51
43
49
61
54
60
49
45
50
48
53
54
52
56
68
56
58
44
57
59
70
54
61
60
55
70
68
59
53
56
58
52
58
59
67
45
64
59
68
58
62
53
50
Peak Inventory -
Number of Compounds
Identified by
ACORN Program
48 •
42
45
35
26
35
42
35
40
33
30
32
36
35
34
38
42
47
41
39
30
40
42
46
36
43
40
37
47
49
40
36
38
39
32
39
43
47
31
42
43
46
40
42
38
33
Volatile Organic
Number of Unidentified
Peaks RemaJnhg
20
21
17
16
17
14
19
19
20
16
15
18
12
18
20
14
14
21
15
19
14
17
17
24
18
18
20
18
23
19
19
17
18
19
20
19
16
20
14
22
16
22
18
20
15
17
Analysis Data Set
Number of Compounds
Identified by Target
Corocund Analysis
23
23
22
21
21
21
23
24
23
1 21
24
22
22
23
21
22
24
23
21
23
22
22
£>&
22
Cm£t
24
20
20
21
*
22
£•£,
24
t*T
22
25
£*J
24
23
CtJ
24
&*T
22
22
24
24
22
?d
£*T
23
fcW
23
23
£w
23
21
" *
19
46

-------
Table 11.  NHATS FY82 Composite Peak Inventory - 6% Florisil
           Semivolatile Organic Analysis Data Set
index
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
Number of Peaks
Submitted to
Sample Name ACORN Program
1-EN-SVO-0-14
1-EN-SVO-15-44
1-EN-SVO-45+
1-ES-SVO-0-14
1-ES-SVO-15-44
1-ES-SVO-45+
1-MA-SVO-0-14
1-MA-SVO-15-44
1-MA-SVO-45+
1-MO-SVO-0-14
1-MO-SVO-15-44
1-MO-SVO-45+
1-NE-SVO-0-14
1-NE-SVO-15-44
1-NE-SVO-45+
1-PA-SVO-0-14
1-PA-SVO-45+
1-SA-SVO-0-14
1-SA-SVO-15-44
1-SA-SVO-45+
1-WN-SVO-0-14
1-WN-SVO-15-44
1-WN-SVO-45+
1-WS-SVO-0-14
1-WS-SVO-15-44
1-WS-SVO-45+
2-EN-SVO-0-14
2-EN-SVO-15-44
2-EN-SVO-45+
2-ES-SVO-45+
2-MA-SVO-0-14
2-MA-SVO-15-44
2-MA-SVO-45+
2-SA-SVO-0-14
2-SA-SVO-15-44
2-SA-SVO-45+
2-WN-SVO-45+
2-WS-SVO-15-44
3-EN-SVO-15-44
3-EN-SVO-45+
3-SA-SVO-15-44
3-SA-SVO-45+
4-SA-SVO-1 5-44
4-SA-SVO-45+
50
63
79
55
50
54
50
36
54
37
66
64
45
31
82
48
59
79
79
80
55
36
54
54
43
58
49
45
73
72
46
36
49 ,
59
50
77
72
46
52
70
50
59
49
56
Number of Compounds
Identified by
ACORN Program
16 '
19
21
22
24
26
16
13
26
17
23
23
16
14
28
18
22
34
23
31
14
13
27
14
13
25
14
15
17
22
17
9
16
16
14
24
18
13
12
22
14
27
17
20
Number of Unidentified
Peaks Remainfig
34
44
58
33
26
28
34
23
28
20
43
41
29
17
54
30
37
45
56
49
41
23
27
40
30
33
35
30
56
50
29
27
33
43
36
53
54
33
40
43
36
31
32
36
Number of Compounds
Identified by Target
10
1Q
15
14
26
34
w*t
22
22
28
21
•ti
15
23
10
y^
£O
19
13
20
23
tM
24
24
20
&V
26
CM
37
15
26
fcU
31

?n
£U
33
32
v\
£O
25
CfJ
18
n
1 0
")")
££
23
22
16
1Q
i a
28
33
X
y*
CO
32
                              47

-------
Table 12.  NHATS FY82 Composite Peak Inventory - 15/50% Florisil
            Semi volatile Orqanic Analysis Data Set
Index
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Number of Peaks
Submitted to
SamDfeNams ACORN Proaram
1-EN-SVO-0-14
1-EN-SVO-15-44
1-EN-SVO-45+ •
1-ES-SVO-0-14
1-ES-SVO-15-44
1-ES-SVO-45+
1-MA-SVO-0-14
1-MA-SVO-1544
1-MA-SVO-45+
1-MO-SVO-0-14
1-MO-SVO-15-44
1-MO-SVO-45-S-
1-NE-SVO-O-U
1-NE-SVO-15-44
1-NE-SVO-45+
1-PA-SVO-0-14
1-PA-SVO-15-44
1-PA-SVO-45+
1-SA-SVO-O-H
-SA-SVO-15-44
-SA-SVO-45+
-WN-SVO-0-14
-WN-SVO-15-44
-WN-SVO-45+
1-WS-SVO-0-14
1-WS-SVO-15-44
1-WS-SVO-45+
2-EN-SVO-0-14
2-EN-SVO-15-44
2-EN-SVO-45+
2-ES-SVO-15-44
2-ES-SVO-45+
2-MA-SVO-0-14
2-MA-SVO-15-44
2-MA-SVO-45+
2-SA-SVO-0-14
2-SA-SVO-15-44
2-SA-SVO-45+
2-WN-SVO-45+
2-WS-SVO-15-44
3-EN-SVO-15-44
3-EN-SVO-45+
3-SA-SVO-15-44
3-SA-SVO-45+
4-SA-SVO-15-44
4-SA-SVO-45+
75
67
60
78
68
91
59
33
41
57
75
73
48
24
58
38
38
57
97
68
94
79
60
91
66
68
96
108
73
102
22
52
83
.65
99
88
73
129
78
79
46
80
57
77
' 57
22
Number of Conpounds
Identified by
ACORN Program
21
20
19
14
15
18
20
12
21
20
19'
16
15
11
24
13
13
16
26
20
29
24
12
27
22
16
23
24
15
21
6
9
21
18
28
24
15
30
20
20
15
16
14
18
16
6
Number of Unidentified
Peaks Remaning
54
47
41
64
53
73
39
21
20
37
56
63
33
13
34
25
25
41
71
48
65
55
48
64
44
52
73
84
58
81
16
43
62
47
71
64
58
93
58
59
31
64
43
59
41
16
Number of Compounds
Identified by Target
Corrcound Analysis
2 -
1
2
6
7
1
2
4
3
1
3
4
3
3
3
1
'1
3
2
2
3
4
4
5
6
5
6
6
7
,6
1
1
4
4
4
5
6
6
5
3
1
5
5
2
1
1
                                 48

-------
 Each  of  the  samples  analyzed  is  identified  under Sample  Name.  The  sample
 name  code  includes a number to indicate the  number  of composites analyzed
 within -a specific age group in a  designated  census  division.   For example,
 the code l-EN-VO-14  indicates that this is  the  first composite from the East
 North Central  (EN) census  division representing the 0-14 age group.  The code
 VO designates,  the composite was  analyzed  for volatile organic  compounds.  Each
 of the nine  census divisions  are  represented in the tables  (EN = East North
 Central; ES^=  East South Central; MA = Middle Atlantic;  NE  = New England;
 SA =  South Atlantic;  WN =  West North, Central; WS = West  South  Central; MO =
 Mountain;  and  PA = Pacific).

          Additional  tables detailing the frequency of occurrence of HRGC/MS
 responses  are 'included in  Appendices -A through  F, provided  as  a separate vol-
 ume with this  report.  The information in these tables is identical to that
 provided in  the previously described data tables (1 through 9).  However, in-
 cidence  of occurrence information is provided for the nine  census divisions
 in addition.to four  census regions and three age groups.  The  tables in Ap-
 pendices A through C  are "dot matrix" tables displaying  the incidence of oc-
 currence of  identified compounds  for each of the samples analyzed in this
 study.   Compound names are sorted in the  same order as Tables  1 through 3.
 Sample data  are arranged in a matrix of census  region, census  division, and
 age group.   Each table in  the:appendices  is  devoted to a particular census
 region.  The four census regions which are  represented are  the West, South,
 North Central, and Northeast.

          Tables in  Appendices D through  F are  "dot matrix" tables  displaying
 the incidence of occurrence of unidentified  compounds for each of the samples
 analyzed in  this study.  The tables in these appendices  are organized identi-
 cally to the tables  in Appendices A through  C.


 V.  DISCUSSION

          This section provides a discussion of the limitations of  the identi-
 fication method and  limitations of the FY82  data set.

     A.  Limitations  of the Peak Identification Method

          Discussions of the limitations to  the peak identification method
 may be divided into two categories:   limitations of the  implementation of the
 method and limitations inherent to the method itself.

          The primary concern regarding the  implementation of  the method was
 that it was not fully automated.   A number of critical steps could  have bene-
 fited from additional computer programming.   The manual  review process in
 particular was very time-consuming because all   corrections to  the seed library
.had to be made "by hand," i.e.,  an operator  was required to make manual cor-
 rections to the summary report,  identification  list, and seed  library.   Spread-
 sheet generation also proved to be more .time-consuming than originally antici-
 pated.  However, in spite of these limitations, the actual results  of the
 procedure were not affected.
                                      49

-------
          Inherent limitations of the identification scheme were more subtle.
Certainly the most stringent limitation in this respect was the dependence of
the program on high quality spectra.   Unknown mass spectra with distinctive
fragmentation patterns, acceptable signal strength, and no contamination^from
coeluting peaks were easily identified.  Conversely, spectra with very little
fragmentation, poor or excessive signal strength, or significant contamination
were a constant problem.

          This dependence upon quality mass spectra is not peculiar to this
method.  It is a necessary condition for the interpretation of mass spectra_
in general, whether automatic or manual.  No method of automatic peak identi-
fication can be successful unless analytical conditions are optimzed for the
generation of high quality mass spectra.

          It should be emphasized that a manual review was performed for each
compound tentatively identified in this report.  In cases where identification
to a specific compound isomer could not be conclusively determined, a non-
specific compound or compound class name was reported.  However, the full
name of the best ranked NBS reference  compound was  also retained and reported
in brackets.

     B.  Limitations of the FY82 Data

          In addition  to  the  limitations of the  identification method de-
scribed above, there were limitations  with the FY82 adipose datafiles them-
selves when applied to  the area of unknown peak  identification.  Most of
these  limitations stem  from using GC/MS  operating  parameters which were
optimized for target compound analysis rather  than interpretation  of unknown
mass spectra.  Three GC/MS operating parameters  were  identified which had  an
effect on the performance of  the peak  identification  method:   (1)  sensitivity
setting of  the mass spectrometer; (2)  mass  scanning range  of the mass spec-
trometer; and  (3) temperature program  rate  of  the  HRGC.   Background  contribu-
tion also  had  an  effect on the performance  of  the  peak identification method.
Each of these  parameters  is discussed  below.

           1.   MS  Sensitivity

          The  objective of the broad scan  target compound analysis for  the
FY82 samples  was  to quantitate target  compounds  in the 50 to  100 ppb (ng/g)
range.  This  sensitivity  range  is common in  routine target compound  analysis.
Mass spectrometric'response may  be  considered  to be roughly proportional  to
concentration for a given sample  type  such  as  volatile or semi volatile.   Also,
the  dynamic range of  a mass  spectrometer is  approximately two  orders of magni-
tude  for  quantisation  and slightly  higher for  reliable mass spectral  interpre-
tation of unknown compounds.   Spectra observed at sensitivities outside this
 range  may not be  adequate for identification purposes due to saturation at
the  high  end and  excessive  noise  or signal  dropoff at the low end  of the
 range.  These estimates are  quite general,  with each  compound having its own
HRGC  and  MS performance characteristics.

           Unfortunately,  the  organic matrix in the adipose samples of both
 the  volatile and  semivolatile data  sets was very complex.   At sensitivity
                                       50

-------
                          LIBRARY SEARCH                                 DATA: 7901F19M1  tt 358
                          06/19/84 16:52:80 *  5:58                        CALI: CALF19H1 tt  3
                          SAMPLE: »301-l-PA-UO-8-14,-H.8UG 1.5.  4- 1.6UG DEIJT.STI).
                          COUDS.i -1850EIW 10-7SENS .3MA DB5-30H 30-5H-125-6/ 10:1SPL UES@95 CR6RT
                                                   BASE M/Z:  41
                                                   RIC:  6168570.
1295
SAMPLE

C6.H12.0
1295 i
H HT IBB
I 1294
PUR 88?












r
/•
/


X

HEXf)
r



'
LJ
1 1 . ll . .
HAL
- . • . . . t . . . —

               1295
en
              -1295
            M/Z
                                    SAMPLE MINUS LIBRARY
                                                II
                       i I.
T*~
 58
                                                      £.0
70
80
90
                                                                                               100
                                                              110
           Figure 8.   Example  of degradation of mass spectral  quality  as a result of instrument  saturation.
             The upper spectrum'is taken  from a peak which  saturated the mass  spectrometer.   Tick  marks
             above  the mass histograms  indicate ions which  are saturated.   The lower plot is the NBS
             reference mass spectrum for  the compound.

-------
settings required to keep the target compounds within the desired quantita-
tion range, many unknown peaks had responses well outside the range necessary
for reliable mass spectral interpretation.   Figure 8 illustrates the effects
of acquiring mass spectra at sensitivity settings inappropriate for mass spec-
tral interpretation purposes.  In this example, the results of an NBS library
search of an unknown spectrum are shown.  The mass spectrum at the top of the
page shows the unknown spectrum.   Tick marks above some of the masses indicate
signal saturation.  The spectrum immediately below the unknown spectrum is
the best candidate chosen from the NBS library.  Note that there is a marked
change in the relative intensities of many of the saturated masses. , Although
in this case saturation did not prevent the NBS library search from choosing
the correct candidate, other cases resulted in ACORN incorrectly identifying
the unknown peak.  Manual review of the data after each application of ACORN
corrected these misassignments.

          2.  Scan Range Selection

          The semivolatiles presented an additional problem which was related
to the original MS operating parameters.  The semi volatile samples were ac-
quired using a mass range suitable for the detection of molecular clusters
characteristic of chlorinated benzenes and polybrominated compounds such as
polybrominated biphenyls.  This required setting the mass spectrometer to
scan in the high mass region (100-700 amu).  A Finnigan/MAT 311A magnetic
sector mass spectrometer was chosen for the analysis.  Due to design con-
straints of magnetic mass spectrometers of this type, it was necessary to
begin the mass scan at 100 amu in order to achieve an upper mass limit of
700 amu.  Unfortunately, many compounds have significant mass fragmentation
in the 30 to 100 amu mass range.  Fragmentation  in this low mass region is
often of critical importance in correctly  identifying a compound.  Thus, the
quality of  semivolatile  spectra was often  marginal for reliable mass spectral
interpretation purposes.

          This problem was most acute for  compounds with a molecular weight
between 100 and  150 amu.  In these cases there was often insufficient frag-
mentation to confirm the  comparison with the NBS  library.  The  effect of poor
fragmentation on library  search results is shown  in  Figure 9.   The  format of
this output is identical  to  one shown previously  in  Figure 2.   In  this example,
note that a number of compounds of varying elemental formulas were  selected
from the NBS library as  likely candidates.  However, the graphic comparison
of the unknown to the three  best  candidates indicates that only one major peak
at m/z 108  and three minor peaks  clustered around  the major peak were present
in the unknown spectrum.  It is also  apparent  from the graph that  there  is
insufficient evidence to  assign this  spectrum  to  any of the candidates,  as
indicated by the close  similarity of  the unknown  spectrum  to the three  best
candidate  spectra.

          3.  HRGC Temperature  Program

          The broad scan analysis of  the FY82  composite  samples was  optimized
for the most rapid turnaround  time possible without  sacrificing the quality
of the target compound  quantitation results.   This was accomplished by  using
relatively  fast  GC temperature program  rates  (6°C/min for  volati'les,  10°C/min
                                       52

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                        Utr.rv Btareft             Data: 79O1F13BI • 179    Ba» a/1'  1O8
                        06/13/84 10:30:00 »  3:S3    Call: CALF13R3 t  2     RIC:   229887.
                        Saapla: 79OI-S-O32. 6X. 2-«A-SVO-O-14. 1UL INJ (2UG D-10 ADDED)
                        Condi.: -1630EHV, 7QEV. 1HA. DB3-30H-60-2H-310-10. 43 SEC SPLITLESS

                        42222 spectra in LIBRARYN8 searched for Miami* PURITY
                         438 Batcbet at least 4 of tbe 11 largest peak* In the unknowi
                        Refuction:   Pks/lOO u :      4Oj  Win«o..:  30.  7
                        Pr»—ftaareh:  Entries to pass:  2OOi  Ba«pl« gis:   99 - SSOi  Hor« tnt:  2Si  Ratio factors:   a. 0, I. (

                        Rank In.      Naav
                        1  1776 HYORAZINE. PHENYL-
                        3  1778 1.3-BENZENCOIAnlNE
                        3  6496 PYRIDINlUrl,  l-«1INO-4-«ETHYL-. CHLORIDE
                        4  1891 1H-FYHROLE.  2. 3. S-TRIHETMY1.-
                        S  1779 1.2-1ENZENEDIM1INE
                        a  781S 3-CYCUOPENTENE-l-ACETALDEHYDE. 2.2.3-TRInETHYL-
                        7  1BS4 CYC1.OPENTE^E.  3-ETHYUIDENE-l-rCTHYl.-
                        B  17B2 PYRIMIDINE.  *. J-D1BETHYI.-
                        9  17B6 I-PYRIDINAHINE.
                        Rant
                        1
                        2
                        3
                        4
                        9
C6. HS. N3
C6. Ha. N2
C4. H9. N2 CL
C7. HU.N
C6. HS. N2
CIO. H16. 0
CS.H12
C6. KB. N2
C*. Hfl. MS
H. Ut B. P»   Purltv    Fit  RFlt
 108  1OS     948    967   948
 10a  108     946    964   946
 144   93     938    936   938
 1O»  1O8     937    943   937
 108  108     934    938   924
 1S2  108     922    940   981
 108   93     920    934   9BO
 108  1O8     914    9T2   914
 108  1O8     847    8U4   867
                 1134
              SfWLE
              CS.H8.N2
                         LIBRARY SB5RW                         DBTAl 7«ain3Rl I 179
                         es/ia^4 !9:38iee * 2:53                  WLII cafisa •  2
                         SSWLE: 7581-9-652,C?.2-«»-SUO-«-!4,lUL IHJ (2UG 0-1« OXSB)
                         CCNCS.l -!STK?W,78E«,l«R.CSS-38rr€8-3f-318-19,« SE SPUTUSS
                                                  BASE IVHi 188
                                                  RICl   22988?.
              CS.K9.H2.O.
                                PYRIDIHIUB, l-vmlNO-4-ferHYl.-, OtURIDE
                                 18!
                                             Ill
                                                        UJ
                                                                    129
                                                                               123
                                                                                           138
Figure  9.    Library  search  results  of an  unknown  peak  with  inadequate fragmen-
   tation  for reliable  identification.    The  upper plot in the  lower  figure is
   the mass  spectrum of the unknown peak.   Note that only four masses are
   present in the  unknown spectrum.    Poor  fragmentation  often  results in
   multiple  candidate  spectra,  as  shown  in the  upper portion of  the  figure.
                                                     53

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for semivolatiles) to compress the GC profile as much as possible.  Unfortu-
nately, this caused a number of unknown peaks to overlap and coelute.

          The Incos data system contains enhancement software which attempts
to deconvolute mixed spectra, but its success is dependent on the degree of.
overlap of the various GC peaks.  As the overlap becomes greater and the num-
ber of overlapping compounds increases, the enhancement routine becomes less
successful in deconvoluting spectra.  Peaks with complete or nearly complete
overlap cannot be deconvoluted at all.

          The ACORN procedure always used enhanced spectra when conducting
searches of the seed and NBS libraries.  Despite this precaution, however, a
number of mass spectra were analyzed which upon closer examination were found
to be mixtures of two or more compounds.  There did not appear to be a solu-
tion to this problem using the available data.  Different operating conditions
could be employed to optimize the analysis for unknown compound identification
purposes.  These could include a slower GC temperature program rate, use of a
longer capillary column, or use of a Megabore column for volatile analysis.
Of course, these changes would require reanalysis of at least a limited number
of samples.

          4.   Background Contribution

          A number of samples in the semivolatile fraction exhibited a hump-
shaped RIC profile, shown in Figure 10, which is common for samples of bio-
logical origin.   The hump exhibits a rather uniform spectrum throughout its
entire length, which is shown in Figure 11.   The presence of this hump
throughout a major portion of the RICs interfered with attempts to extract
high quality spectra of peaks located on the humps.   The effect of the hydro-
carbon hump was least acute for samples in the 0-14 age group and progres-
sively influenced data quality in the higher age group samples.  Figure 6,
which was presented earlier in this text,  illustrates the difference in the
intensity of the hydrocarbon hump in proceeding from the 0-14 age group to
the 45+ age group.
                                      54

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iea.a-1
       R1C                               DATA: P381D66R5 »1
       84/66/84  16:45:68                  CALIs CAL086R3 12
       SAMPLE: 7981-8-949 67. l-MA-SUO-8-14  1UL
       COHDS.: -1606EMU 78EU Ittfl 085-38(1-69-2H-318-18/ 45 SEC.
       RANGE:  G    1,1588  LABEL: H  B, 4.8  QUAH: A  0. 1.8 J
                                                       783
                                   SCANS
                               1 TO 1508
                              SP1.ITLESS
                              3  BASE: U 28,
                                427
                        3 3
R1C
           11?
                186
                  1	
                 288
                 5:48
                                                                             625664.
                                                  781
                                      527
                                   488
                                                                      1819
                                                                         1858
                                                                                 1176
                                                              1328
 468
11:28
—I	
  £88
 17:68
—I	
  868
 22:48
1808
28:28
1268
34:68
1408
39:48
SCAN
TIME
                    Figure  10.    RIC  chromatogram  with hydrocarbon "hump.
                                                      55

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TECHNICAL REPORT DATA
(Please read Insir.icrions on the reverse before completing
1. REPORT NO. 2.
FPA-5fin/5-.R7-DQ2A 	
A. TITUS AND SUBTITLE
Characterization of HRGC/MS Unidentified Peaks from
the Analysis of Human Adipose Tissue, Volume I -
Technical Approach
7. AUTHOR(S)
J. D. Onstot, R. E. Ayling, J. S. Stanley
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Midwest Research Institute
425 Volker Boulevard
Kansas City, MO 64110
12. SPONSORING AGENCY NAME ANO ADDRESS
U.S. Environmental Protection Agency
Office of Toxic Substances (TS-798)
Field Studies Branch, 401 M Street, S.W.
Washington. DC ?D460. 	
3. RECIPIENT'S ACCSSSlON»NO.
S. REPORT DATE
June 30. 1987
6. PERFORMING ORGANIZATION CODE
Midwest Research Institute
8. PERFORMING ORGANIZATION REPORT
8823-A(01)
10. PROGRAM ELEMENT NO.
Work Assignment 23
11. CONTRACT/GHAN t NO.
68-02-4252
13. TYPE OF REPORT ANO PERIOD COVE;
Final Report 1/86-1/87
14. SPONSORING AGENCY CODE
EPA/OTS/FSB
15. SUPPLEMENTARY NOTES
The National Human Adipose Tissue Survey (NHATS), administered by EPA/OTS, is an on-
going chemical monitoring network designed to detect levels and prevalences of toxic
substances in the adipose tissue of the general U.S. population.  Adipose specimens
 :ollected in fiscal year 1982 were analyzed as composites for volatile and semi vola-
tile organic compounds via HRGC/MS as part of a previous effort.  The data files were
then processed using a method developed to automatically identify unknown HRGC/MS
peaks.  The method consisted of automatic identification of unknown spectra via com-
parisons to reference mass spectra, transfer of the results of the identification
step to a microcomputer, compilation of the data into a spreadsheet program and gen-
eration of compound identification tables from the spreadsheet.  Application of the
method to the adipose data resulted in the identification of volatile compounds from
18 separate chemical classes and semivolatiles from 29 chemical classes.  Compound
classes included saturated and unsaturated hydrocarbons, aldehydes, ketones, steroids
heterocyclic compounds, drugs, aliphatic and phthalate esters, phenols, halocarbons,
and methyl-substituted organosiloxanes.  Volume I  (EPA-560/5-87-002A) describes the
technical approach.  Volume  II (EPA-560/5-87-002B)  provides supplemental data.
17 
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