Environmental Applications of Mass Spectrometry

Stephen R. Heller

U.S. Environmental Protection Agency,

MIDSD, PM-218,

Washington, D. C. 20460

1. Introduction

Qualitative and quantitative procedures to analyze organic pollutants in all media--air, water, solid waste--have received considerable attention in the past few years. Within the United States most of this attention has been a direct or indirect result of the formation and mission of the United States Environmental Protection Agency (EPA), established in 1971.

The enormous number of chemicals, their degradation products, and metabolites found in the environment is staggering. Probably over 100,000 different chemicals could be identified in air and water if the money, manpower, and technical facilities were available. How many of these are indeed potentially harmful, slightly toxic, or extremely toxic is unknown, and will remain unknown for a long time to come, if not forever. With the passage of the Toxic Substances Control Act, the United States will, for the first time, develop a public inventory of all chemicals (excluding drugs and chemicals covered by other legislation) manufactured, imported into, or exported from the United States. Even with such a list of chemicals, however, development of specific analytical techniques for each is virtually impossible. Hence the only practical solution to identifying pollutants will be to use more general, yet sensitive, procedures based on such properties as differences in solubility, chromatographic behavior, and spectral characteristics. Many of the procedures in the area of wet chemistry are either slow, expensive, or lack the needed sensitivity. Hence the clear reason for the EPA expending considerable efforts and assets is toward finding and developing techniques which are fast, inexpensive, and sensitive. High on this list of methods is GC-MS. Other methods such as Fourier transform-gas chromatography-infrared (FT-GC-IR) and Fourier transform-nuclear magnetic resonance (FT-NMR) are now being developed as complementary tools in pollutant analysis.

GC-MS has many advantages in pollutant identification and analysis. During the 1960s the National Institutes of Health (NIH), National Science Foundation (NSF),and National Aeronautics and Space Administration (NASA) expended considerable sums of money in grants and contracts to improve GC-MS as an analytical technique. By adding a computer system (either totally dedicated or part dedicated and part centralized) the productivity of GC-MS can be made quite high. While a computer certainly does not reduce the need for highly skilled and trained manpower, it does provide great leverage for increasing a mass spectrometrist's productivity. The EPA, with a limited staff, has been able to analyze hundreds of thousands of samples and make many unambiguous identifications of specific organic pollutants found in environmental samples. Identification of pollutants in the micro- to nanogram level has become a simple routine experiment in most EPA laboratories. GC-MS has improved sensitivity by factors of 100-1,000,000, and productivity by a factor of 100, and has reduced identification time 10- to 100-fold.

The EPA has made a major commitment to GC-MS over the past 5 years by equipping its laboratories throughout the country with over two dozen GC-MS instruments having dedicated data systems and interfaced to a central host computer for standard qualitative identifications. Over 3 million dollars have been spent on instrumentation alone and about 0.5 million dollars on qualitative identifications. Figure I shows a typical EPA GC-MS system. Most of the GC-MS instruments in the EPA are Finnigan quadrupoles with DEC PDP-8 minicomputer data systems. There are also a few Varian, Hewlett-Packard, and LKB GC-MS instruments interfaced with Varian, Hewlett-Packard, and INCOS data systems.

The many needs for firm qualitative organic identifications include:

(i) the causes of taste or odor in drinking water,

(ii) the distribution of toxic compounds in surface or wastewater, (iii) the accumulation of persistent compounds in wildlife tissue, (iv) the cause of fish kills,

(v) the effectiveness of treatment facilities in removing classes or specific types of compounds

(vi) the specific sources and degradation mechanisms of organic pollutants, and

(vii) the enforcement of effluent standards for toxic organic compounds.

Several examples are described in this chapter.

FIG. 1. Configuration of a typical GC-M~computer system used by the EPA.

2. Drinking Water Analysis

The first example of GC-MS in the EPA is a detailed description of the Agency's analytical quality assurance (AQA) procedures applied to a study of qualitative analysis for trace organics of drinking water samples taken from five U. S. cities. The concentration, isolation, and identification procedures used by the EPA in this work are liquid-liquid extraction (GC-MS). However, some of the AQA techniques that are described also have applicability in other methods of trace organic analysis including: the entrainment of volatiles in an inert gas stream followed by trapping and GC-MS, and carbon or resin adsorption, extraction, and GC-MS (see also Chapter 5).

The data used to illustrate the AQA procedures were obtained from drinking water samples taken during January and February 1975 in Miami, Seattle, Philadelphia, Cincinnati, and Ottumwa, Iowa. The results of these analyses are a part of a larger survey of drinking water supplies that was conducted by several laboratories during early 1975. Some EPA facilities applied different methodologies of isolation and concentration of the organic contaminants, but GC-MS was always used for identification of individual pollutants. The different methodologies are effective with different classes of pollutants but there is some overlap between classes, serving as an excellent verification of certain results.

The overall philosophy of this survey was to analyze for all organic compounds present in the samples. Within this context, the emphasis of the survey was qualitative, i.e., the identification of individual organic compounds in the water. Precise measurement of concentration was not a goal of the survey.

2.1. Experimental Procedure

Mass spectra were measured with a Finnigan 1015 quadrupole mass spectrometer. The inlet system was a Varian Series 1400 gas chromatograph that was interfaced to the spectrometer by an all-glass jet-type enrichment device and an all-glass transfer line. Control of the quadrupole rod mass-set voltages, data acquisition, data reduction, and data output was accomplished with a Systems Industries data system that employed a Digital Equipment Corporation PDP-8E minicomputer and a 1.6-millionword Diablo disk drive. Data were displayed on a Tektronix 4010 cathode ray tube (CRT) display unit or a Houston plotter.

The GC column used in this study was a 2 m x 2-mm-i.d. coiled glass tube containing 1.5% OV-17 and 1.95% QF-I on Supelcoport (80-100 mesh). The initial column temperature of 60° C was held for 1.5 min. then the temperature was programmed at 8° C min~' to a final temperature of 220° C, which was held for 15 min. Conditions that were held constant throughout the analyses were as follows: helium carrier gas flow rate, about 30 ml min^-1; GC injection port, 190°C; interface and transfer line,

210°C; spectrometer manifold, 100° C; pressure in the MS, 10 Torr;

electron energy, 70 eV; filament current, 500 mA; electron multiplier, 3000

V; mass range scanned from 33-450 emu at an integration time of 8 msec

amu^-1; and sensitivity, 10 AV^-1.

The method used applied to all organic compounds present that are extracted partially or completely into the methylene chloride-diethyl ether solvent. All compounds originally present in water at a concentration of approximately 10 ng liter^-1 (0.01 ppb) or greater that elute from the GC column without decomposition within 35 min were observed. Very volatile compounds, e.g., chloroform and vinyl chloride, were not observed as they were either lost during extract concentration or masked during solvent elusion from the GC. Compounds that were observed include the following:

aliphatic hydrocarbons (C₁₀ and larger), aromatic hydrocarbons (benzene derivatives, biphenyls, alkyl benzenes, polynuclears, etc.), pesticides (chlorinated, organophosphorus, some carbamates), phenols (all types), PCBs, plasticizers (phthalates, adipates, and sebacates), and various other types of compounds including sulfur compounds, amines, alcohols, aldehydes, ketones, and some carboxylic acids.

2.2. Interpretation of Results

Sampling information and results of the water analyses are given in Table 1. Table 2 is a summary of the application of AQA techniques to the analyses reported in Table 1.

Most of the concentration values in Table I are estimates that were based on conservative extraction efficiencies and average response factors. These estimates are probably accurate to within a factor of 10. In a few cases authentic samples were available and extraction efficiencies and response factors were determined. This permitted better estimates of concentration, and these results are probably accurate to better than +-50%. In no case was a precise concentration measurement attempted by development of a calibration curve with several standards and careful measurement of integrated instrument signals: high-precision measurements were beyond the scope of this survey.

The AQA that applies to qualitative organic trace analysis may be conveniently divided into four categories:

(i) reagent and glassware control,

(ii) instrumentation control,

(iii) supporting experiments, and

(iv) data evaluation.

TABLE 1. Results of Analysis Using Liquid-Liquid Extraction and GC-MS

TABLE 2. Analytical Quality Assurance in the Identification of Organics

2.2.1. Reagent and Glassware Control

This is required to minimize the introduction of contamination from the materials used in the liquid-liquid extraction procedure. Effective glassware cleaning procedures have been developed. High-quality commercial reagents and solvents are available, but quality is still somewhat variable and unpredictable. In solvents that are used for extractions, impurities are amplified by about a factor of 2000 during extract concentration. Clearly, if background contaminants that are introduced from reagents or solvents seriously obscure compounds in the sample, purification of these materials is required.

2.2.2. Instrumentation Control

This is required to ensure that the total operating instrumentation system is calibrated and in proper working order. If a computerized GC-MS system is used to collect data, the computer data system must be included in the performance evaluation. The recommended instrumentation control procedure employs a standard reference compound and a set of reference criteria to evaluate the performance of the overall system. This evaluation should be performed each day the GC-MS system is used to acquire data from samples or reagent blanks. The records from the performance evaluations should be maintained with the sample and reagent blank records as permanent documentation supporting the validity of the data.

The reagent blank is a supporting experiment required for all samples. This is true even when contamination from glassware and reagents is well controlled. The reagent blank result is the documentation that proves that good control was exercised, and it defines precisely the level of background that was beyond control.

The reagent blank evaluation may be a straightforward comparison of corresponding peaks and mass spectra in the reagent blank and sample. A more rigorous procedure is required to make objective judgments in situations that are not obvious. An effective technique for comparing blanks and samples employs selective ion monitoring (SIM). The SIM profile provides an apparent increase in sensitivity by subtracting from the total ion current all the ion abundance data contributed by background, unresolved components, and other irrelevant ions. The SIM profile generator is a standard data reduction program on all modern computerized GC-MS systems (see Chapter 4). A fast graphics display device is required to facilitate reviewing a large number of SIM plots.

It is emphasized that it is not necessary to have even a tentative identification of a compound to apply this technique to reagent blank evaluation. To conduct an SIM comparison, the mass spectra of all GC peaks in the sample are examined. One or several ions that are prominent in a spectrum from each peak are selected, and the sample and reagent blank SIM profiles are generated on the CRT. Comparison of these permits, in most cases, straightforward judgments concerning the presence of compounds in the sample and the reagent blank.

If a corresponding peak is observed in the reagent blank and its concentration, as judged from the peak height, is approximately the same as or exceeds the sample concentration, the decision is clear and the compound must not be reported. A far more difficult judgment must be made when the concentration of a component in the sample exceeds its concentration in the reagent blank. The material in the sample could, of course, be a true sample component. Alternatively, it has been observed empirically that compounds in the blank sometimes merely appear to be at lower concentration than the same compounds in the corresponding sample. In view of the uncertainties, any compound that is observed in the sample should not be reported if it is part of an overall pattern of peaks that is repeated in the blank, although at a lower apparent concentration.

2.2.3. Supporting Experiments

Chemical ionization, field ionization, and high-resolution mass measurements are GC-MS techniques capable of generating very strong evidence in support of identifications. However, the production of this evidence is restricted because only a relatively few laboratories have developed capabilities with these techniques. High-resolution mass measurements are further limited by sample size, since some sacrifice in sensitivity is required to achieve sufficient resolution.

After a tentative identification is made, either by interpretation or empirical spectrum matching, several other types of supporting experiments become possible. The retention data from the GC-MS of a pure compound (standard) may be compared with analogous data from the sample component. Similarly, the mass spectra of the standard and sample component, obtained under identical conditions, may be compared. The standard may be dissolved in water at an appropriate concentration, extracted, and measured. Its recovery in the same fraction that the suspected component appeared in, and the observation of the same mass spectrum as the sample component, is strong confirmation of the correctness of the identification.

2.2.4. Data Evaluation

The evaluation of the data must weigh the available evidence in terms of its reliability and determine the cost and benefits to be gained by gathering additional information.

Clearly the most convincing evidence for an identification is obtained by examining pure standards that correspond to suspected sample components. However, the existence of this evidence is constrained by the availability of the pure standard and the additional cost and time required to examine it. Because it is not usually possible to predict which compounds will be found, some standards will not be available immediately. There are many very practical limitations imposed on the development and maintenance of a large library of pure authentic standards. Many compounds are obtainable from chemical supply houses, but procurement time is variable and may extend to weeks or months. Some compounds are not available from any supplier, frequently because they are metabolites or by-products of industrial processes rather than manufactured products. This same limitation of standard availability also precludes careful concentration measurements in many cases.

Because of the problem of standard availability, it is worthwhile to determine whether conditions could exist that would lead to reliable identifications without standards. One criterion for a reliable identification that might be used is a quantitative measure of the goodness of match between an experimental mass spectrum and a spectrum from the printed literature or a computer-readable data base. The Biemann similarity index (Sl), calculated on a scale from option KB of the MSSS (see Chapter 9) has been used. Experience with this Sl indicates that, in general, a value greater than about 0.4 corresponds to the existence of a reasonable match between two mass spectra.

A reasonable match often does imply an identification, but sometimes it does not; positional isomers and members of homologous series of compounds often give very similar mass spectra.

Another problem with identifications based on empirical spectrum matching is that differences in ion abundance measurements are sometimes observed when the mass spectrum of a compound is measured on two different spectrometers (see p. 21). Most of these differences are probably caused by nonuniform calibration procedures or a failure to use an ion abundance calibration procedure. Also, it is well known that different types of inlet systems often have effects on relative abundance measurements. With a GC or batch inlet system that is operated in the 100-250°C temperature range, temperature-dependent fragmentations are promoted with frequent reductions in the abundances of molecular and other higher mass ions. With a well-designed direct inlet system, these temperature effects may be largely precluded. As a result of these factors, it is quite common for two spectra of the same compound, measured with different inlet systems or spectrometers, to give a rather low Sl. A low SI may also be caused by unresolved or partly resolved components which generate mass spectra containing extraneous ion abundance values.

It is concluded that the SI must be used with caution. A relatively high SI (>0.7) may be regarded as an indication of a reasonable match, but only as suggestive of the probability of an identification. A relatively low SI (<0.4) cannot be regarded as complete rejection.

2.3. Analytical Quality Assurance

These AQA concepts were applied to the analyses reported in Table 1. Table 2 summarizes the results of the tests. Bromoform, nicotine, dibromochloromethane, isophorone, trimethyl isocyanurate, benzoic acid, phenylacetic acid were not found by SIM in the corresponding reagent blanks and each gave spectra that were good matches by inspection with spectra in the MSSS data base. In each spectrum the molecular ion was observed and the M + 1 isotope accuracy or halogen isotope abundance distribution pattern was with the expected experimental error. In addition, each compound was extracted in the expected fraction, the more volatile components had the shorter retention times, and all the fragment ions in the mass spectra were reasonable and consistent with the assigned structure. On the basis of this evidence, these seven identifications were considered firm without recourse to authentic standards. Standards of two of the compounds were readily available, and these were used to supply additional supporting evidence.

Hexachloroethane gave a very good spectrum match by inspection and an expected short retention time; also, it was extracted in the appropriate fraction. The molecular ion was not observed, but ions were observed with halogen isotope distribution patterns that corresponded to the C₂Cl₅, C₂Cl₄, C₂Cl₃, C₂Cl₂, and CCI₃ ions. Therefore a consistent set of fragment ions was observed and these account for all the atoms of the proposed structure. The only other reasonable possibility for this peak was pentachloroethane, but the recorded spectrum of this compound in the MSSS data base did not exhibit a C₂HCl₅ molecular ion.

The compound di-n-octyl adipate was tentatively identified by the empirical matching procedure. However, no molecular ion was observed and the complexity of the fragmentation pattern precluded a rapid determination of its consistency with the proposed structure. This is a clear example of a spectrum that contains inadequate information to permit an accurate identification without a pure reference standard. The compound was found in the acid fraction. This aroused suspicion about its identity since dioctyl adipate might be expected to appear in the neutral fraction.

A sample of octyl decyl adipate containing di-n-decyl and di-n-octyl impurities was available in the laboratory. This was added to laboratory tap water and extracted according to the method. All the adipates were found in the acid fraction, as was the compound found in the Miami water sample. The retention time and mass spectrum of authentic dioctyl adipate was the same as that of the compound in the Miami water. This evidence strongly supports the identification of the authentic contaminant as di-noctyl adipate. Its origin may be from vinyl plastic garden hose and similar materials that are in widespread use.

The compound 1,2-bis(2-chloroethoxy)ethane (C₆H₁₂O₂Cl₂) gave a spectrum that was in excellent agreement with the spectrum in the data base. Again, no molecular ion was observed and a reference standard was not available. However, the fragment ions at m/e 63 and 65 (C₂H₄Cl), 93 and 95 (C₃H₆OCI), and 107 and 109 (C₄ H₈OCl) account for all the atoms in the compound and are consistent with the assigned structure. Two additional ions at m/e 137 and 139 correspond to the loss of a CH₂Cl group from the molecular ion. The overall evidence strongly supports the identification.

Seven other compounds were detected, but no identities are reported because inadequate evidence was available to permit reliable characterizations. Three of these appeared to be the same compound, and the available information about them is an excellent example of the application of the AQA concepts. Peaks were found at the same retention time near the detection limit of 10 ppt in the neutral fractions from Miami, Cincinnati, and Philadelphia. The three mass spectra were essentially the same except for variations in the abundance of the common background ion at m/e 43 C₃H₂) and several other weak ions. This spectrum is a good match of the spectrum of chloropicrin. Since the molecular ion was not observed, however, interpretation of the match must be made with caution. The ions at m/e117, 119, and 121 clearly indicate the presence of a CCl₃ group, and this is supported by the CCl₂ ions at mle 82, 84, and 86 and the CCl ions at m/e 47 and 49. There is no ion that clearly points to an NO₂ group, and the spectrum therefore fails to account for all the atoms of the proposed structure. Under these circumstances an authentic standard was required in order to obtain additional information. Pure chloropicrin was shown to elute much earlier than the compounds in the three neutral fractions. Therefore, although this compound contains a CCl₃ group, it remains unidentified at this time. There are weak ions at m/e 103 and 145 in all three spectra; these suggest the saturated oxygenated hydrocarbon ions C₅H₁₁O₂ and C₈H₁₇O₂. This compound appears similar to the 1,2-bis(2-chloroethoxy)ethane found in the Philadelphia neutral fraction; it has a longer chain and more chlorine atoms, and may be an intermediate in the formation of the ubiquitous chloroform. A chemical ionization mass spectrum may provide a valuable insight into the identity of this compound.

3.Study of Landfill Leachate

The second example is a study of chemical elements and volatile organic compounds in a landfill leachate.

To determine a practical treatment for water containing pollutants leached from an abandoned landfill, Delaware's Department of Natural Resources requested analyses of several water samples.

In a residential and light-industrial area of Newcastle County, a resident complained about a persistent, unpleasant odor in his drinking water. Although the water was supplied by a private company, various governmental agencies became involved when the obnoxious odors were traced to contaminants leached from an abandoned landfill near the commercial wells.

For about 13 years, Newcastle County had used an abandoned sandpit as a receptacle for municipal and industrial garbage. In 1968 the landfill was closed after an area 5 km long and varying from 400 to 800 m in width was filled with refuse estimated to be 10-15 m deep. Within 1.5 km of the outer edge of the landfill is the Artesian Water Company's well field, from which 11-18 million liters of water are pumped daily.

Newcastle County hired a consulting firm to determine the pollution source and to propose a remedy to prevent further ground water contamination. The consulting engineers concluded that landfill leachate had polluted the aquifer. To prevent further contamination of the well field, the consulting firm proposed drilling recovery and blocking wells. Blocking wells would be located to remove water that would normally flow into the landfill area and become contaminated. Recovery wells would be drilled in or near the landfill area to remove the leachate-containing water which could then be treated and returned to the aquifer. Only treated water would then reach the private well field. To monitor aquifer pollution and to devise an effective treatment, state and county officials needed knowledge of the chemical composition of the leachate. Therefore Delaware's Department of Natural Resources requested through the EPA's Region III office in Philadelphia, Pennsylvania, that the Athens, Georgia Research Laboratory identify organic and inorganic pollutants in four water samples: water from a well inside the landed, water from two recovery wells between the landfill and the well field, and finished water from the Artesian Well Company (Fig. 2).

FIG. 2. Map showing landfill area and sampling sites for the leachate analysis.

Volatile organic components were identified and measured by GC and GC-MS. Each sample was extracted by a procedure designed to separate it into neutral, acidic and basic fractions. Preliminary examination by GC showed which fractions contained significant amounts of organic components, and mass spectral data were acquired for these fractions. Preliminary identifications of several compounds were obtained by computer matching of unknown mass spectra with standard mass spectra. When standard samples were available, these identifications were confirmed by comparing mass spectra obtained under the same conditions. Further confirmation was obtained by comparing GC retention times of standards and unknowns. Quantitative data were calculated from GC peak area measurements.

The relative contamination in each well was shown by comparison of the total amount of organic materials indicated by peak areas from the gas chromatograms. These data (Table 3) showed that the landfill well contained approximately 100 times more volatile organic matter than the recovery wells.

Thirty compounds were positively identified (using the MSSS) and quantitated in the landfill well sample (Table 4). Major components were short-chain acids and industrial chemicals. The most concentrated volatile organic component was 2,3-dibromo-1-propanol (23.8 mg liter-'). Several compounds (various alcohols, hydrocarbons, and ethers) that were tentatively identified could not be positively identified, because no standards were available. One of these was 1-chloro-2,3-dibromopropane, a derivative of the major organic contaminant of the well.

Several compounds (caprolactam and nine short-chain acids) were found in both recovery well #3 and landfill well water (Table 4). Although the major component of the landfill well, 2,3-dibromo-1-propanol, was not positively identified in water from recovery well #3, gas-chromatographic evidence suggested that a trace amount of this compound was present.

Recovery well #29 was less contaminated than recovery well #3, but several compounds were identified: triethyl phosphate, mono- and dichlorobenzene, and eight short-chain acids (Table 4). Seven of the acids were also found in well #3.

The Artesian Well Company water extract did not contain volatile organic contaminants in quantities that could be detected by GC or GC-MS, and no organic compounds were identified. The neutral-fraction chromatogram showed only a few ill-defined humps with no sharp peaks; the acidic fraction chromatogram had no peaks. Compounds present in this finished water at concentrations of 0.001 mg liter-' should have been detected, because the finished water extract represented a larger sample volume than the well water extracts.

Analysis by spark source mass spectrometry (SSMS) analysis produced quantitative data for the 21 elements detected in these four samples and supported the volatile organic component analyses. The landfill well sample was the most contaminated; well #29 was less contaminated than well #3. Several elements were present in considerably higher concentrations in the landfill well water than in other water samples, but the most

significant differences were observed for concentrations of bromine and barium. The high concentration of bromine in the landfill well supported the identification of 2,3-dibromo-l-propanol as the major organic contaminant. Comparison of SSMS data from all four samples indicated that magnesium, iron, manganese, cobalt, and boron would be other useful elements to trace the movement of contaminants from the landfill toward the well field.

TABLE 3. Volatile Organic Material in Water - Samples from Wells Shown in Fig. 2.

TABLE 4. Volatile Organic Compounds Identified in Water Samples from Wells Shown in Fig. 2

Analytical data were reported to the Delaware Department of Natural Resources. A series of recovery wells has been completed. Water from these wells is presently discharged into small creeks in the area, but the county is constructing aeration tanks that will permit effluent discharge into a tidal area beyond the freshwater zone.

4. A Study of the Houston Ship Channel

The last example of the use of GC-MS in EPA work is a study of organic pollutants associated with power plant cooling water in the Houston Ship Channel.

The Houston Ship Channel, which receives many industrial discharges, is the source of cooling water for a large power generating plant. Cooling water flows through a canal to the oil-fired power generating plant and is discharged into a nearby bay adjacent to important shrimp-producing estuaries (Fig. 3). Present discharges may be detrimental to receiving water quality, and even larger volumes of cooling water will be required for planned power plant expansion. The EPA needed data to evaluate biologic and hydrologic studies prepared by power plant officials and undertook the identification of organic contaminants by GC-MS and the comparison of samples by gas chromatographic fingerprinting to qualitatively establish relative degrees of pollution.

Samples were collected from nine states (Table 5) during a four day period, stored in 18-liter plastic containers on ice until received at a mobile laboratory, and kept frozen until extracted. A blank sample (10 liters of distilled water) was also stored frozen in an 18-liter plastic container for six days and extracted and analyzed by the same procedure used for the samples. Each sample was acidified and extracted with chloroform to obtain neutral and acidic materials; the water layer from this extraction was made basic and extracted again with chloroform to obtain basic materials. Each extract (3.2 liters total) was concentrated to about 3 ml, stored in a vial, and shipped on dry ice to the laboratory. A second extraction procedure was used to separate acidic and neutral organics. To facilitate GC analyses, acidic materials were converted to methyl esters of ethers with diazomethane. The volume of each extract was reduced to 50 Ill, and a 2-,ul aliquot was injected into the gas chromatograph to be separated on a 50-ft Carbowax 20M-TPA SCOT column. For GC-MS analyses sample volumes were reduced as necessary for sensitivity requirements.

TABLE 5. Collection Sites for Samples Indicated in Fig. 3

Few organic compounds were specifically identified. Comparison of mass spectra and GC retention times showed, however, that several compounds were present in the samples that were not present in the blank. Mass spectra of compounds unique to sample fractions were compared with mass spectra in data collections that contained spectra of only 17,000 compounds. The blank fractions contained several organic compounds. Some of these compounds identified from their mass spectra are plasticizers (phthalate and adipate esters) that were probably introduced during laboratory procedures. Others are due to solvent impurities and artifacts produced during methylation of the acid fractions.

In the neutral fraction of the cooling system influent (sample #8), triethyl phosphate and benzothiazole were identified; they were not found in neutral fractions of either the blank or the bay sample (#17) collected 800 m from the discharge point. Comparison of sample and standard GC peak heights indicated the concentration of each was approximately , MICROg liter^-1. Azulene and 1- and 2-methylnaphthalene were identified in the bay sample neutral fraction. No spectral matches were found for other neutral water pollutants. Several acyclic aliphatics were probably alkanes or oxygenated alkanes but were not specifically identified. The neutral fraction of a bay water sample collected 1.6 km south of the cooling water canal discharge point (# 18) contained triethyl phosphate (a compound also identified in the influent sample), two dichlorobiphenyl isomers, and two ethyl esters of long-chain saturated acids. Exact structures of the latter four compounds were not determined.

Although water pollutants in acidic fractions of the influent and bay water sample #17 were not specifically identified, the chromatograms show that the bay sample (#17) contained fewer organics in lower concentrations than the cooling system influent (#8).

The basic fraction of the influent (sample #8) contained few organic compounds not present in the blank; bay sample #17 contained more organic compounds than the influent sample. The basic pollutants were not identified.

Comparison of flame ionization gas chromatograms of neutral fraction of samples #1, #6, #7, #8, #18, and #23 indicated the relative organic content of waters from different areas (collection sites in Fig. 3).

This organic pollutant information was reported to the EPA Region VI Enforcement Division for inclusion with other analytical data (such as dissolved oxygen, total organic carbon, metals, total residue, total and Kjeldahl nitrogen, sulfates, salinity, pH, temperature, chlorides, chlorinated hydrocarbons, and various biological parameters), which were obtained from other EPA laboratories.

A report was prepared to support litigation. However, in January 1973 the issue was settled out of court when power plant officials agreed to monitor chemical and biological parameters of discharged cooling water and Trinity Bay water.

5. Summary

GC-MS plays a large and growing role in the EPA's analytical abilities to monitor the environment. While most of the Agency's work has been in the area of water studies, air and solid waste groups are also now beginning to use this very powerful technique. Vital to the use of GC-MS in the Mass Spectral Search System (MSSS) (Chapter 9), which was and still is a system in which EPA provides substantially for its development and use.

6. Exercises

1. Why is there a need to use solvents of extremely high purity in trace analyses of environmental samples?

2. Some solvents are deliberately adulterated. Investigate this practice.

3. Phthalate ester plasticizers are ubiquitous contaminants. Where might they be found in the laboratory?

4. A seawater sample is shown by GC with a flame ionization detector lo contain a series of n-alkanes, presumably derived from petroleum. During GC-MS, an additional component is detected, coeluting with n-octadecane. The major ions in the spectrum of this compound are at m'/e 32, 64, 96, 128, 160. 192, 224, and 256. What is it?

5. What precautions should you take before believing a computer ''identification'' of a compound during GC-MS?

7. Suggested Reading

A. L. ALFORD, Environmental Applications of Mass Spectrometry, Biiomed. Mass. Spectrosr . 2, 229 (1975).

A. L. ALFORD, EPA Research Report No. 660/4-75-004, June 1975.

J. W. EICHELBERGER and W. M. MIDDLLTON, EPA Research Report No. 600/4-75-007, September 1975.

A. L. ALFORD, EPA Research Report No. 600/2-73-103, September 1973.