EPA-R2-73-234
July 1973 Environmental Protection Technology Series
Organic Pollutant Identification
Utilizing Mass Spectrometry
National Environmental Research Center
Office of Research and Development
U.S. Environmental Protection Agency
Corvallis, Oregon 97330
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and
Monitoring, Environmental Protection Agency, have
been grouped into five series. These five broad
categories were established to facilitate further
development and application of environmental
technology. Elimination of traditional grouping
was consciously planned to foster technology
transfer and a maximum interface in related
fields. The five series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
This report has been assigned to the ENVIRONMENTAL
PROTECTION TECHNOLOGY series. This series
describes research performed to develop and
demonstrate instrumentation, eguipment and
methodology to repair or prevent environmental
degradation from point and non-point sources of
pollution. This work provides the new or improved
technology required for the control and treatment
of pollution sources to meet environmental quality
standards.
For tale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C, 20402 • Price 85 cents
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EPA-R2-73-234 V
July 1973
ORGANIC POLLUTANT IDENTIFICATION
UTILIZING MASS SPECTROMETRY
by
John M. McGuire
Ann L. Alford
Mike H. Carter
Southeast Environmental Research Laboratory
College Station Road
Athens, Georgia 30601
Project #16ADN 25
Program Element flB1027
NATIONAL ENVIRONMENTAL RESEARCH CENTER
OFFICE OF RESEARCH AND MONITORING
U. S. ENVIRONMENTAL PROTECTION AGENCY
CORVALLIS, OREGON 97330
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EPA Review Notice
This report has been reviewed by the Environmental
Protection Agency and approved for publication.
Mention of trade names or commercial products does not
constitute endorsement or recommendation for use.
ii
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Abstract
A system has been developed for the rapid identification
of volatile organic water pollutants. It involves gas
chromatography/mass spectrometry with computerized
matching of mass spectra. Application of this system
to the analysis of waste effluents revealed a signifi-
cant number of pollutants that were not previously
known to be present.
iii
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CONTENTS
Section Page
I Conclusions 1
II Introduction 3
III GC/MS/Computer/Matching System 7
IV Specific Pollutant Identifications ... 15
V Acknowledgments 29
VI References 31
VII Glossary 33
VIII Appendix 35
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FIGURES
Paqe
1. Schematic outline of Finnigan GC/MS/computer
system 8
2. Comparison of parathion mass spectra from
magnetic and quadrupole spectrometers .... 12
3. Flame ionization chromatogram of water
extract 16
4. Reconstructed gas chromatogram of pesticide
manufacturing plant effluent 17
5. Reconstructed gas chromatogram of plant
effluent containing polychlorinated
biphenyls 19
6. Limited mass reconstructed gas chromatogram of
plant effluent containing polychlorinated
biphenyls 21
7. Reconstructed gas chromatogram of synthetic
pesticide mixture 22
8. Mass spectrum of p^'-DDT from synthetic
pesticide mixture 23
9. Reconstructed gas chromatogram of coal gasifi-
cation plant extract 24
10. Computerized spectra matching program dialogue
for a component of coal gasification plant
extract 26
11. Reconstructed gas chromatogram of synthetic
rubber plant effluent 28
VI
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TABLES
Paqe
1. Comparison of Compounds Reported by Dis-
charger and Compounds Identified by EPA
in Industrial Discharge 4
2. Steps in GC/MS/Computer Analysis 10
3. Compounds Identified in Pesticide Plant
Effluent 18
4. Identification of Trace Components in
Synthetic Pesticide Mixture 20
5. Compounds Tentatively Identified in Waste
Effluent of Coal Gasification Pilot Plant . . 25
VII
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SECTION I
CONCLUSIONS
1. Combined gas chromatography and mass spectrometry
is a powerful tool for identification of organic
pollutants in the environment.
2. Utility and speed of this technique are enhanced
when the mass spectrometer is computer controlled.
3. Computerized matching of pollutant mass spectra
with spectra in the EPA/Battelle data base provides
rapid identifications with minimal operator decisions,
4. The 11,000-spectra data base is not sufficiently
comprehensive to identify all unknown pollutants.
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SECTION II
INTRODUCTION
Setting and enforcing water quality criteria, deter-
mining the fate and effects of water pollutants, and
developing optimum control measures require the
capability for identifying specific organic pollutants.
Table 1 dramatically illustrates the need to determine
the composition of industrial wastes by chemical
analysis. The compounds in the left column are those
suspected by the discharger to be in his effluent based
on his knowledge of products, raw materials and
processes. The right column, based on chemical analysis
of the effluent, contains over twice as many compounds.
The identification technique must be highly specific
since thousands of compounds must be considered.
Because some organic compounds are toxic to aquatic
organisms at concentrations below 10 ug/&, the technique
must also be sensitive.
Gas-liquid chromatography (GC) has adequate sensitivity
and reproducibility to provide excellent quantitation
for volatile organics when the identity of the chemical
is known. However, pollutant identifications obtained
by comparison of relative retention times are subject
to interferences and are questionable for the unknown
mixtures found in natural waters. GC, however, may be
used as a preliminary separation technique. The
effluent may then be introduced into a different type
of instrument for qualitative identification.
High resolution mass spectrometry provides the elemental
composition of unknowns but present instruments are
neither sensitive enough nor fast enough to monitor GC
peaks. Infrared spectroscopy and nuclear magnetic
resonance spectrometry provide specific identification
but have low sensitivities.
Workers at the Southeast Environmental Research
Laboratory showed the feasibility of using gas chroma-
tography interfaced with low resolution mass spectro-
metry for unknown identification (1-4). They used an
Hitachi RMU-7 mass spectrometer tuned for maximum
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Table 1
Comparison of Compounds Reported by Discharger and
Compounds Identified by EPA
in Industrial Discharge
Products and Raw
Materials Reported
Compounds Identified
Propylene
Ethylene
Butadiene
Butane
Octane
Ethylene glycol
Ethylene oxide
Polyglycols
Ammonia
Raw gas
Ethane
Refinery gases
Refinery €2 stream
Refinery C3 stream
Propane
Hydroformer gas
Platformer gas
*Identification
m-xylene*
p_-xylene*
1,5-cyclooctadiene
o-xylene*
Tsopropylbenzene (cumene)
styrene*
o_-ethyltoluene
o-methylstyrene*
diacetone alcohol
indan*
2-butoxyethanol
3-methylstyrene
indene*
dimethylfuran isomer
n-pentadecane
1-methylindene*
3-methy1indene
acetophenone
n-hexadecane
a-terpineol
naphthalene*
a-methylbenzyl alcohol
2-methylnaphthalene*
benzyl alcohol
1-methylnaphthalene*
ethylnaphthalene isomer
phenol*
2,6-dimethylnaphthalene*
methyl ethyl naphthalene isomer
cresol isomer
acenaphthene
acenaphthalene
raethylbiphenyl isomer
fluorene
phthalate diester (undetermined)
3,3-diphenylpropanol
phthalate diester (undetermined)
confirmed'with a standard.
was
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sensitivity, together with manual chart reading and
data reduction. Many hours of applied effort are
required to gather data, read charts, correct back-
grounds, construct a data presentation for interpre-
tation, and interpret the data. Because of this, manual
GC/MS is too slow for effective identification of
water pollutants.
Most time-limiting factors in manual GC/MS can be
accomplished by a computer. To evaluate the feasibility
of this approach, a computerized system was obtained in
1971. A mini-computer in this system controls the
operation of a quadrupole mass spectrometer and
associated output devices. At the same time, a project
was started to develop a computerized program for
interpretation of the resulting mass spectra.
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SECTION III
GC/MS/COMPUTER/MATCHING SYSTEM
Computerized GC/MS produces many mass spectra from a
single environmental sample (5). Interpretation of
these spectra is time-consuming. To make the technique
usable by all enforcement laboratories, an EPA research
grant was made to Battelle Memorial Institute to
develop a computerized spectra matching program and a
reference library of organic pollutant spectra. The
program (6) being developed is a very useful tool,
providing identification of an unknown spectrum within
one minute.
This GC/MS/computer/spectra-matching system has been
selected by the Contaminants Characterization Program
as the best current means for rapid identification of
organic contaminants in water.
instrumentation
The GC/MS/computer system now used at the Southeast
Environmental Research Laboratory for semi-automatic
pollutant identification is outlined in Figure 1.
The GC is a modified Varian 1400 chromatograph with a
temperature controlled oven that can be programmed
from 50° to 500° C. It has no independent detector
and serves only as a specialized inlet to the mass
spectrometer.
The all-glass, single-stage Gohlke jet separator
enriches organic samples by utilizing differences in
diffusion rates of sample and carrier gases in a
turbulent jet.
The Finnigan 1015 mass spectrometer is a quadrupole
instrument with three mass ranges extending to m/e
750. It is capable of unit resolution throughout the
range (e.g., 1/20 at mass 20 and 1/625 at mass 625).
Therefore, instrument sensitivity at low mass is much
higher than in a magnetic instrument. At a scan speed
of 120 amu/sec, sensitivity is adequate to give
-------
Schematic Outline of Finnigan
GO/MS/ Computer System
00
Varian 1400 jg,^
Chromatograph ^^y
Digital Equip.^
DEC Tapes
#
Diablo x
Disk
Gohlke ^^,
' Separator^^
' D n D O / n. -*^
rDr o/e
"^ Computer
X^ \|/ N
Reduced
Data
Finni gan 1015
Mass Spectrometer
i i
System
Industrie4?
1 nterface '*>>N>>v.
ADC&DAC
CDC 6400
<|^B D i rect
x Probe
1 nlet
^ L i cu id
Inlet
^ Plotter
Reconstructed
Interpretat i on
List of
Best Matches
\
Scsc'tra
Manua I
I n tcrpreta t i en
Boundaries of Heated Zones
Sample Path
-Data Path
ManuaI
VaIidat ion
of Results
FIGURE 1. Outline of Finnigan GC/MS/Computer System
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identifiable spectra for 20 ng of material introduced
into the GC inlet.
The liquid inlet is used for introduction of calibration
compounds, the direct probe for solid materials.
The System Industries interface, the analog-to-digital
converter, and the digital-to-analog converter permit
the Digital Equipment Corporation (DEC) computer to
control the mass spectrometer during calibration and
data acquisition; to accept data from the mass spectro-
meter; and to control the Houston plotter during data
reduction.
The DEC PDP8/e computer, which is the heart of the data
system, has a 4096 word core and an ASR33 teletype-
writer. Programs, raw data, and reduced data are
stored on either the two DECtape units or the Diablo
disc. Output of the reduced data is achieved under
computer control via the plotter, the teletypewriter,,
or a coupling device. The coupling device connects
the PDP8 to the central CDC 6400 computer and permits
semi-automatic spectrum identification by the matching
program.
Using this system, data reduction times are much less
than for the manual reduction methods formerly used.
Only 30 minutes of applied operator time is required
to create the instruction string needed to output
reduced data for a 20-peak chromatogram. Data reduc-
tion time ranges from slightly more than one hour for
the disc system to more than two hours for the tape
system. Manual data reduction would require approxi-
mately 12 hours. The GC/MS/computer analytical
procedure outlined in Table 2 works well; however, two
obvious improvements are needed. The first is faster
data output utilizing a cathode ray tube, and the
second is a modification to permit time-shared use of
the PDP8 for simultaneous acquisition and processing
of data. With these modifications, overall data
reduction time could be reduced by half.
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Table 2
Steps in GC/MS/Computer Analysis
1. Formation of amu reference calibration file
2. Data acquisition
3. Plot of reconstructed gas chromatogram
4. Manual selection of GC peak and background
spectra
5. Creation of background corrected spectra
files
6. Output of spectra to central computer for
data interpretation by spectra matching
program
7. Manual inspection of match results
Matching Prc
Matching schemes of varying complexity have been
described in the literature. All rely on a set of
representative reference spectra. In the case of the
most complex deductive programs, such as the DENDRAL
proaram (6-8) developed-at Stanford, the data base need
not be extensive, but must be comprehensive. In the
case of comparative systems (9, 10) the data base must
include a spectrum of the unknown compound.
to the reference spectrum for each match, and easy
access to a central spectra library. The algorithm or
a matching program described in the literature UJJ
was selected as the basis for the EPA ^tchxng program^
The rapid program developed jointly by Batte11^ *"V
Southeast Environmental Research Laboratory centered
around this algorithm and a CDC 6400 time-shared
computer (12).
10
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The EPA/Battelle matching program, taking advantage of
the high information redundancy of mass spectra, is
based on the two most intense peaks in every 14 mass
units. There are four main steps in the matching
process:
• screening based on molecular weight range,
• screening based on the most intense peak of
the unknown spectrum,
0 pre-searching based on the spectrum family, and
• ordering of best matches based on peak-by-peak
comparison of the unknown spectrum with those
reference spectra passing the pre-search.
To reduce operator time and eliminate human errors and
prejudices in selecting, formatting, and transmitting
data, PDF8 utility routines transfer input spectra
data directly from the user's remote PDP8 to the central
CDC 6400. These programs have been evaluated and
improved during the past year.
A match against the present data base of 11,000 spectra
(10,600 general organic spectra from the Aldermaston
collection and 400 pollutant spectra from the Southeast
Environmental Research Laboratory and Battelle,)
requires approximately 45 seconds.
The "similarity index" (S.I.) gives the user an imme-
diate indication of the quality of the matches. The
"best hit" will be the first identification; the S.I.
will show whether it is a poor match (<0.2 if the data
base does not contain any closely related compounds),
one of several fair matches (0.2-0.35 if the correct
compound is not in the data base but related ones are),
or a good match (>0.35 if the S.I. of the second best
hit is significantly lower.)
Compared with magnetic deflection spectrometers, qua-
drupole instruments exhibit a bias toward low mass.
This is demonstrated in Figure 2, which compares both
types of spectra for the pesticide, parathion.
Since the Aldermaston data base is comprised primarily
of spectra obtained on magnetic deflection mass
11
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PARATHION
•-
•
•
-
f v se GO TO BO an KB no 120 i» iw ise ico ITB I*! iar zw zio ao zao ?w zse zee no ZBP so » 310 aeo 330 j« t.
•-
SKTTfUl rtfOK 1S5
-
1
-
I8
ML.
R_
•
uliM
JiJI
l*«
FIGURE 2. Comparison of parathion spectrum from a) magnetic
instrument and b) quadrupole instrument
-------
spectrometers, a major concern in the development of
the matching system was whether suitable matches
could be obtained between quadrupole and magnetic
deflection spectra. Experience with the system has
shown that the program provides excellent matches.
In one study made at the Southeast Environmental
Research Laboratory, 50% of the unknowns present in
the effluent of a Kraft paper mill were found correctly
as the best hit, 8% as the second best hit, and 2% as
the third best hit (13). The success of the system
should improve since reference spectra are added
continually.
13
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SECTION IV
SPECIFIC POLLUTANT IDENTIFICATIONS
Examples are presented to illustrate the use of GC/MS
for specific identifications of environmental pollutants
Manual GC/MS
One project of the Southeast Environmental Research
Laboratory involves the identification of pollutants
from the textile industry. As part of this research,
A. W. Garrison (14) utilized manual GC/MS methods to
identify two pollutants and track them from their
source in a carpet yarn mill to the water intake of a
town six miles away. The flame ionization chroraatogram
of an extract of water from the receiving creek showed
one major peak and many small ones. Only the two peaks
labeled in Figure 3 were identified. From its mass
spectrum, the major peak was identified as p_-nonyl-
phenolr a degradation product of a surfactant used in
the fibre dying process. The second peak was identi-
fied by flame ionization chromatography as dieldrin, a
moth-proofing compound known to be used in the plant.
Mass spectrometry confirmed the identification.
Computerized GC/MS
The effluent of a pesticide manufacturing plant was
monitored by GC. It contained low concentrations of
several chlorine-containing pesticides and much higher
concentrations of other chlorinated organics with
relative retention times different from those of known
pesticides.
The sample was analyzed by low resolution GC/MS operated
under computer control. The reconstructed gas chromato-
gram (RGC) shows 31 peaks (Figure 4). Fourteen of these
(Table 3) were identified generically as chlorinated
hydrocarbons of which 13 were identified specifically.
The 13 spectra (Appendix I) were included in the EPA/
Battelle reference file.
15
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Gas Chromatogram of Organic Extract of Creek Water
a
fa
10
12
14
18
20
Min.
FIGURE 3. Flame ionization chromatogram of water extract
-------
PESTICIDE MRNUFHCTIRIN6 PUNT EFFLUENT
3 10 20 10 10 GO « 70
so loo 110 iv no 110 ISB \ms
FIGURE 4. Reconstructed gas chromatogram of pesticide manufacturing plant effluent
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Table 3
Compounds Identified in Pesticide Plant Effluent
trichlorocyclopentene isomer
hexachlorobutadiene
hexachlorocyclopentadiene
hexachloronorbornadiene isomer
octachlorocyclopentene
heptachloronorbornene isoraers (2)
chlordene
heptachlor
1 , 2-epoxy-4,5,6,7,8,8a-hexachloro-et-
dicyclopentadiene (hexachlor epoxide)
chlordane
nonachlor
endrin
isomer of endrin (not specifically identified)
Electron capture gas chromatography of an extract of
the effluent from another plant indicated the presence
of polychlorinated biphenyls (PCB's) at concentrations
of less than 1 yg/A. An initial run on the low-
resolution mass spectrometer gave the RGC shown in
Figure 5. The major peaks below spectrum 15 were
readily identified as chlorobenzenes and monochloro-
biphenyls. On the basis of their mass spectra, peaks
with longer retention times were judged to be due to
chlorinated biphenyls; however, high background in
this run prevented us from obtaining an RGC comparable
to the chromatogram obtained with the electron capture
detector, which is relatively more responsive to the
chlorine-containing peaks. A limited mass reconstructed
gas chromatogram, (LMRGC) covering the major PCB molecular
ion peaks, would have permitted the comparison, but the
presence of background ions interfered with some major
PCB peaks.
To circumvent this interference, blank scans were made
at highest instrument sensitivity to determine all
significant background ions. In a second data
acquisition run, all significant peaks noted in
the blank were ignored by the computer. A
limited mass reconstructed gas chromatogram,
obtained from these data for the hexachlorobiphenyl
18
-------
INDUSTRIE- PLPNT
VO
FIGURE 5. Reconstructed gas chromatogram of plant effluent
containing polychlorinated biphenyls
-------
region (Figure 6), was comparable to the electron
capture detector chromatogram. Based on this compari-
son and the chromatographic data, the suspected
material was identified as Aroclor 1260.
Computerized GC/MS and Spectra Matching
To check the practicality of computerized spectra
matching as a means of identifying trace contaminants
in the environment, a synthetic mixture of four pesti-
cides was prepared. Atrazine, sevin, parathion, and
p,p'-DDT were dissolved in an organic solvent at
concentrations equivalent to those that would have
resulted from extraction of a water sample containing
them at concentrations of 1 vig/A. The RGC (Figure 7)
of this mixture showed a high background. The DDT
spectrum (Figure 8) was typical of the spectral quality
of the run. As shown by the S.I.'s in Table 4, good
matches were obtained by the EPA/Battelle computerized
spectra matching program.
Table 4
Identification of Trace Components in Synthetic
Pesticide Mixture
Component Best Match
Atrazine Atrazine
Sevin Sevin
Parathion Parathion
p,p'-DDT p,p'-DDT
Second Best
Match S.I.
None
Sevin 0.501
Parathion 0.220
£,p_'-DDT 0.287
In a study of the effluent of an experimental coal
gasification plant, organic components were extracted
with methylene chloride. The RGC of the extract
(Figure 9) contained seven distinct peaks.
20
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INDUSriRIflL PLflNT
CLIMITED MRSSD
SPEETHLMNLlflER
100 310 120 130 110 ISO 1€0 170 180 130 205 230
FIGURE 6. Limited mass reconstructed gas chromatogram of plant effluent
containing polychlorinated biphenyls
-------
SYIWCTIC PESTICIDE MIXTURE
to £
atrozine
p,p - DDT
SPECTflLtl
FIGURE 7. Reconstructed gas chromatogram of synthetic pesticide mixture
-------
SYNTHETIC PESTICIDE MIXTURE
P.P'-OOT
OJ
g
1
-
f-
b&U
So
P *"
•
2D 30
M/
)l|i,i U ,,
'•M 50
C
GO
-
lu
111 ..ii Id
80 90 100 110 1ZO 130
|
"'I""''1
110
I I
ll,,....,...!,..).!,,.., , .,
ISO IGO 170 ISO 190
•
II
210 ZZO Z30 ?W 2SO 2BO 270 288 290 308 3I8 320 330 3^0 3SO 360 370
FIGURE 8. Mass spectrum of p,p'-DDT from synthetic pesticide mixture
-------
•-
I*
10 20 30 10
SPECTHLfl NLMBER
SO 60 70 90 90 100 110 120 130 110 ISO 160 170 ISO ISO 200
FIGURE 9. Reconstructed gas chroroatogram of coal gasification plant extract
-------
In a computerized matching of the spectra for those
compounds, the best matches were with C6, C7/ and Cg
hydroxyl-containing materials. High S.I.'s were
indicated for the first six peaks, but a low one for
the last GC peak. Subsequent visual inspection of
the mass spectrum for this GC peak indicated that the
last peak arose from two compounds with the same
retention time.
The identifications are given in Table 5. When
different materials were selected by the matching
program as the best and second best matches, relative
GC retention times favored the best match over the
second best. In a continuation of the computer dialogue,
given in Figure 10, for RGC peak 3, thirteen cresol
spectra were matched with S.I.'s greater than 0.645.
The first non-cresol match was 3-tolyl-N-methyl
carbamate with an S.I. of 0.574.
Table 5
Compounds Tentatively Identified in Waste
Effluent of Coal Gasification Pilot Plant
RGC
Peak
1
2
3
4
6
7
Best Match
Phenol
o- Cresol
m-Cresol
2,5-Dimethyl-
phenol
3,4-Dimethyl-
phenol
2,4-Dimethyl-
phenol
a-Naphthol
0.700
0.653
0.245
Second Best
Match
Phenol
m-Cresol
o-Cresol
2,6-Dimethyl- 0.804
phenol
3,4-Dimethyl- 0.692
phenol
3,4-Dimethyl- 0.637
phenol
1,2-dihydroxy- 0.232
1,2-dihydro-
naphthalene
25
-------
S, E, 0R P?S
I.D.? '0AL GASIFICATION PLANT EFFLUENT
PAPEK l'At?E?Y
FN--P73 ; S' -1 :
CHPFI-1 (1ST i£XT) :
37,3;38,8; 3 9 ,2 9 ; 4 0 , 4 ;41,2;43,2;50,12^51,20;52,10;61;
53f18;54,6;55,4;61,2;62,4;63,9;64,2;65,4;66,2;56;:
74,2;77,41;78,9;79,38;80,13;81,2;89,4;90,12;91,6;61;
106,3;107,100;108,91;109,6;33;:
END
PARMTRS? M100-500
111 HITS
M-CRES0L 108 C7.H8.0 AST 0181
FILE KEY= 186
SI=0.857
1-HYDR0XY-3-METHYLBENZENE (3-METHYLPHEN0L—M-CKES0L)
108 C7.H8.J? TRC 0068
FILE KEY= 6392
SI=0.845
1-HYDR0XY-2-METHYLBENZENE (2-METHYLPHEN0L—O-CRES0L)
108 C7.H8.j2f TRC 0067
FILE KEY= 6391
SI=0.834
1-HYDR0XY-4-METHYLBENZENE (4-METHYLPHEN0L—P-CRES0L)
108 C7.H8.0T TRC 0069
FILE KEY= 6393
SI=0.815
M-CRES0L 108 C7.H8.0T AST 0459
FILE KEY= 462
81=0.805
Figure 10.
Computerized spectra matching program
dialogue for a component of coal gasi-
fication plant extract
26
-------
The present matching program depends on the presence in
the reference library of the correct compound to
identify an unknown. If the correct compound is not in
the library, but closely related ones are, these
materials will be identified as the most likely ones.
At this point, inspection of matches and spectra
frequently suggests the correct answers. In any case,
identities should be confirmed by use of standards.
Analysis of the waste effluent of a synthetic rubber
producer resulted in the RGC shown in Figure 11. This
chrcmatogram shows four major peaks; however, satis-
factory identifications by spectra matching were
obtained for only two compounds. The second peak was
found to be bis(2-chloroethoxy)methane (S.I.=0.63) and
the fourth major peak was 1,2-bis(2-chloroethoxy)ethane
(S.I.=0.676). Visual inspection of the spectra for the
first and third GC j>eaks indicated that the compounds
contained sulfur; however, no matches were obtained
for compounds having molecular weights compatible
with the molecular ion peaks of the spectra. We
concluded that the first and third peaks were due to
sulfur-containing compounds not included in the
library.
27
-------
-
oo
SYNNCTIC RUBBER COfffW
e
•-•
R_
8.
*-<
5
sfL
R.
R_
10 ze » 10
SPECTHUH NLfCEP
.
SO GO 70 80 90
100 110 120 130 110 ISO 160 170 190 190 200 210 220 ZM 210 SO
FIGURE 11. Reconstructed gas chromatogram of synthetic rubber plant effluent
-------
SECTION V
ACKNOWLEDGMENTS
The authors acknowledge the data contributed by Dr.
Lawrence H. Keith and Dr. Arthur W. Garrison of the
Contaminants Characterization Program. Samples were
provided by Mr. Donald Brown of EPA Region IV Chemical
Services Branch, Dr. Warren Reynolds of EPA Region VI
Chemical Services Branch, and Mr. A. G. Sharkey, Jr.
of the U. S. Bureau of Mines, Pittsburgh, Pennsylvania.
29
-------
SECTION VI
REFERENCES
1. L. H. Keith, A. W. Garrison, M. M. Walker, A. L.
Alford, and A. D. Thruston, Jr., "The Role of
Nuclear Magnetic Resonance Spectroscopy and Mass
Spectrometry in Water Pollution Analysis," presen-
ted at the 158th National Meeting of the American
Chemical Society, Division of Water, Air and Waste
Chemistry, New York, N. Y., September, 1969.
2. A. W. Garrison, L. H. Keith, and M. M. Walker, "The
Use of Mass Spectrometry in the Identification of
Organic Contaminants in Water from the Kraft Paper
Mill Industry," presented at the 18th Annual Con-
ference on Mass Spectrometry and Allied Topics,
San Francisco, California, June, 1970.
3. L. H. Keith, "Chemical Characterization of Indus-
trial Effluents," presented at the 163rd National
Meeting of the American Chemical Society, Division
of Water, Air and Waste Chemistry, Boston,
Massachusetts, April, 1972.
4. A. W. Garrison, L. H. Keith and A. L. Alford,
Advances in Chemistry Series, No. Ill, 27 (1972).
5. L. H. Keith and J. M. McGuire, "Computer-Controlled
Mass Spectral Characterizations of Industrial
Organic Pollutants," presented at the 164th
National Meeting of the American Chemical Society,
Division of Water, Air and Waste Chemistry, New
York, N. Y., August, 1972.
6. B. G. Buchanan and G.. L. Sutherland, Memo No. 62,
Stanford Artificial Intelligence Report, July,
1967.
7. A. M. Duffield, A. V. Robertson, C. Djerassi, B". G.
Buchanan, G. L. Sutherland, E. A. Feigenbaum, and
J. Lederburg, J. Amer. Chem. Soc. , 9_1, 2977 (1969).
8. J. Lederburg, G. L. Sutherland, B. G. Buchanan,
E. A. Feigenbaum, A. V. Robertson, A. M. Duffield,
and C. Djerassi, J. Amer. Chem. Soc., 91, 2973
(1969).
31
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9. B. S. Finkle, D. M. Taylor, E. J. Bonelli, J.
Chromat. Sci., 10, 312 (1972).
10. S. R. Heller, Anal. Chem., 44, 1951 (1972).
11. H. S. Hertz, R. A. Kites, and K. Biemann, Anal.
Chem., £3, 681 (1971).
12. J. R. Hoyland and M. B. Neher, Battelle Columbus
Lab. Annual Report to Environmental Protection
Agency, Project #16020 HGD, March, 1973.
13. L. H. Keith, Southeast Environmental Research Lab,
Athens, Georgia, personal coiranunication, 1973.
14. A. W. Garrison and D. W. Hill, Amer. Dyestuff
Reporter, February, 1972.
32
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SECTION VII
GLOSSARY
GC—gas chromatography, a separation technique based
on the partition of materials between gas and
liquid phases.
GC/MS—a union of GC and MS in which the chromatograph
effluent passes directly into a mass spectrometer
inlet.
LMRGC—limited mass reconstructed gas chromatogram, a
computer output that shows the relative currents
resulting from positive ions of particular mass-to-
charge ratio reaching the mass spectrometer detec-
tor as a function of scan number.
MS—mass spectrometry, an identification technique
based on the fragmentation of ionized materials.
RGC—reconstructed gas chromatogram, a computer output
that shows the relative currents resulting from all
positive ions reaching the mass spectrometer
detector as a function of scan number. This plot
usually resembles the chromatogram obtained in GC.
S.I.—Similarity Index, a numerical indication, ranging
from zero to one, of how well an unknown spectrum
matches a reference spectrum.
33
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SECTION VIII
APPENDIX
Mass spectra of 13 compounds identified in pesticide
manufacturing plant effluent.
35
-------
TRIOLORXYCLOPENTQt
u»
Rj
•
20 38 W SB 60 70
MX E
ili.ililli.UJ,
90 IOB 110 J2D J30 J1O ISO ISO I70 ISO 19B 200 210 Z2B 330 2KJ 290 268 770 280 Z30 30D 310 3ZO
Mass spectrum of trichlorocyclopentene isomer
-------
Ul
bfi.
3D 10
ns E
SB 60 70 90 30 100 110 130 130 I« ISO 160 170 180 ISO 200 210 ZZO Z30 310 2SO 260 370 288 298 350 310 320 33B
Mass spectrum of hexachlorobutadiene
-------
JCXROLOROCYCLOPENfTflDIEhE
LJ
at
20 3D K3 SO GO 70 SO 30 100 110 138 130 110 ISO 1GB 170 180 190 200 210 220 230 210 ZSO 268278280230300 310335338310
HS E
Mass spectrum of hexachlorocyclopentadiene
-------
^EXROLOflONORBOfWFCIENE
8
S_
v
to
RJ
•
lU
B
X 10
fix E
SO SO 70
I im|iiii|.Hfii | ,
100 110 120 130 I
"I I"" I I .
ISO 160 170 180 130 350
aw
aee an
ao
aw
Mass spectrum of hexachloronorbornadiene isomer
-------
XTFCH.ORXYCLOPENTENE
3D
n/ E
SB 68 70 80
"I""1*1"!'"1'""! | |.t..|...1lilT»T-|ii"|iiii|il-i| | r..,....|.,..,....,.ii.,.,i.,..,Tln).i..hM| |,i,,,,,,i|i.,,,ii..| , r.,.,,.r,)ilil|l.l»,.T ,„
30 ISO 118 120 130 110 ISO 160 170 ISO 19O 200 210 22B Z3B ZK5 ZSD 260 Z1t> 3BB 298 380 310 32B 330
Mass spectrum of octachlorocyclopentene
-------
HEFTflCH-CRONOflBOflNENE
5,
8.
8-
hB.
R.
2_
-"•T"""T* f" pm.iifHBiipi ,...,.,.,-...
ZB 30 *J SO 60 70 80 90 100 1IO 120 130 110 ISO 160 170 IfO I90 £00 210
HX E
230 Z« 2SO
Mass spectrum of heptachloronorbornene Isomer
-------
N>
IB 100 ITB ISO 130 JOB ZJ8 ZZD 233 210 2SB
2BO Z90 300 310 320
370
Mass spectrum of heptachloronorbornene
-------
CH.OROENE
CO
B.
3J 30 KJ a> 01 -m
30 IOB MO I2B 130 l« ISO IGO 170
130 ZOO 210 22B 230 MO 290 2BD 270 2H 230 300 310 380 39 310 ;
Mass spectrum of chlordene
-------
2B 30
fl/ E
SB SO 70 90
_ "T i "•'i""'""i r i""
90 105 HO 120 130 HO ISO ISO 17O 180 190 ZOB ZIO ZD 230 Z«3 ZSO 260 Z70
•T 1* i r i""l'"N i i f i r-
aa030O3l03a3330>K53S03EO?7O3Pr39r
Mass spectrum of heptachlor
-------
hEXRCH_OR EPOXIDE
Ln
,!i
L JlLj
lllilL.ilh... illli, i. J,i,i. l,l.,h . ...
...1.1
iL ullii,
20301033607081530 100 110 120 130 140 ISO 160 170 180 130 200 210 220 230 210 250 260 270 280 Z30 300 310 320 330 310 350 3)
n/ c
Mass spectrum of hexachlor epoxide
-------
aw IK ae «B «ie •§ «p
Mass spectrum of chlordane
-------
NQNR04-GR
flXE
3EB
3TO 380 33B KB
«e *w
Mass spectrum of nonachlor
-------
OCRIN
_ ' I ' r^^^T^"'^w1*™lT*^ fntjIttifinfM
SB (J> IB 80 30 IBB I IB 128 3D 1«
Hx E
in >• 'a,
o
»
•1 1 1 1
360 J7C 300 390
Mass spectrum of endrin
-------
SELECTED WATER
RESOURCES ABSTRACTS
INPUT TRANSACTION FORM
I. Rep
3. Accession No,
w
4. Title
ORGANIC POLLUTANT IDENTIFICATION UTILIZING MASS
SPECTROMETRY
S,
ff.
7. Author(s)
McGuire, J.M. , Alford, A.L., Carter, M.H.
Perfonaia? Organization
Report NO' •
10. Project tfo-
9. Organization U.S. Environmental Protection Agency
National Environmental Research Center
Southeast Environmental Research Lab.
Athens, Georgia
11. Contract/Grant No.
t3. Type e.' Repof sttd
Period Covered
15. Supplementary Notes
Environmental Protection Agency report number EPA-R2-73-234,
July 1973.
16. Abstract
A system has been developed for the rapid identification of
volatile organic water pollutants. It involves computer controlled
gas chromatography/mass spectrometry with computerized matching of
mass spectra. Application of this system to the analysis of waste
effluents revealed a significant number of pollutants that were not
previously known to be present.
s *Pollutant Identification, *Organic Compounds, *Mass
Spectrometry, *Gas Chromatography, *Computers, *Date Processing,
*Organic Pesticides, Phenols
nb. identifies *GC/MS, *Computer Controlled, *Computer Matching, Coal
Gasification Effluent, Synthetic Rubber Effluent, Pesticide
Manufacturing Effluent
}7c. COWRR Field & Group Q5A
JS. Availability
19. S
(Report)
20. SscufJiy C/ass.
21. K* of
Pages
22. Pwc*
Send To;
WATER RESOURCES SCIENTIFIC INFORMATION CENTER
U.S. DEPARTMENT OF THE INTERIOR
WASHINGTON, O. C. 2O24O
John M. McGuire
Institution
Southeast Environmental Res. Lab,
WRSfC r<32 (REV JUNE 13711
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