a discussion on organic pollutants in the sea: their origin, distribution, degradation and ultimate...

The Recognition of Organic Pollutants in Aquatic SedimentsAuthor(s): G. Eglinton, B. R. T. Simoneit and J. A. ZoroSource: Proceedings of the Royal Society of London. Series B, Biological Sciences, Vol. 189, No.1096, A Discussion on Organic Pollutants In the Sea: Their Origin, Distribution, Degradationand Ultimate Fate (May 20, 1975), pp. 415-442Published by: The Royal SocietyStable URL: http://www.jstor.org/stable/76994 .

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Proc. R. Soc. Lond. B. 189, 415-442 (1975)

Printed in Great Britain

The recognition of organic pollutants in aquatic sediments

BY G. EGLINTON, B. R. T. SIMONEITt AND J. A. ZORO

The Organic Geochemistry Unit, School of Chemistry, The University of Bristol, Bristol

Aquatic sediments contain small amounts of organic matter which have been contributed from the land by water and wind erosion, from the water column, and from the sediment itself by biological activity. These fluxes include variable loads of pollutants and their degradation products. Base-line studies of the organic components of contemporary surface sediments and of layers from cores are urgently needed so that the pollutants can be distinguished from the natural compounds. Such analyses require precise analytical procedures capable of identifying pollutants and natural compounds, both expected and unexpected. Computerized gas chromatography-mass spectrometry provides this capability and the option of further processing the stored data long after acquisition. The ways in which computers can be used to process mass spectral data are discussed and some applications are described. The use of one advanced computerized gas chromatography-mass spectroscopy system for the analysis of an estuarine sediment is described in detail. The presence of phthalate esters, polynuclear aromatic hydrocarbons and partially degraded crude oil, as well as certain natural lipids, is demonstrated.

INTRODUCTION

Aquatic sediments receive small amounts of organic matter which have been contributed from a variety of natural and anthropogenic sources. These twin fluxes are subject to the same environmental processes and laws. The chemistry of

aquatic sediments is therefore best treated as a single problem rather than as two

separate tasks - the 'natural' chemistry and the pollutant chemistry. Sediments can be regarded as communal sinks and, to some extent, banks for natural products and for pollutants. Very little is known of the fate of organic compounds contributed to sediments but microorganisms must play a large part in effecting changes in the organic matter. They will consume and degrade some of it, contri- bute their own biomass and also control the chemical state of the sediment to a

large extent. Hence, understanding of the fate of pollutants in the marine environment is dependent on knowledge of the chemistry and microbiology of the sediments.

One of the most interesting problems concerns the recognition of compounds t Permanent address: Space Sciences Laboratory, University of California, Berkeley,

California 94720, U.S.A. [ 415 ]



G. Eglinton and others (Discussion Meeting) which are uniquely pollutants - compounds which have zero natural abundance - as exemplified by 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (DDT) and DDT

derivatives, polychlorinated biphenyl (PCB) and other organochlorines. Much more common are those compounds which occur naturally in addition to being contributed by man's activities. Thus, certain alkanes, cycloalkanes, and aromatic

hydrocarbons may enter the environment naturally by the way of oil seeps and erosion of sedimentary deposits, by contemporary biosynthesis or as the result of industrial processes. The same compound can have multiple origins. For example, a fluorocarbon or chlorocarbon may originate as a pollutant; certain feldspars are known to contain low molecular mass fluorocarbons, presumably formed hydro- thermally (Kranz I969). Again, the presence of volatile, medium molecular mass,

non-polar, bromine-containing compounds in marine organisms has been demonstrated (Lunde I973a, b). These compounds concentrate in the lipids and are

probably synthesized in one or more stages of the marine food chains. Aromatic

hydrocarbons, such as perylene, are believed to be formed naturally, one obvious source being the smoke from forest fires.

To some extent the origin(s) can be inferred from the structure of a compound and its relative proportions in the mixture where it is encountered. Further information can come from its geographical distribution and its depth distribution in the sediment, data which are both time and space dependent. Organic com-

pounds can be contributed to marine sediments allochthonously by aeolian trans-

port and by water via rivers, deltas and estuaries, and autochthonously through in situ formation by phytoplankton and the ensuing food chain. The sediments

provide a record of the different fluxes. Organic carbon budgets have been presented for several marine situations, including the sea off California and the Black Sea

(see, for example, Deuser 197I).

MARINE SEDIMENTS AS A HISTORICAL RECORD OF POLLUTION

Aquatic sediments deposited steadily over the past few thousand years hold the record of man's activities in the form of the varying amounts of the mineral,

biological and organic inputs. Thus, careful and intensive studies of sediment cores are essential if we are to answer the questions 'Which are pollutants?' and 'What are the natural levels for compounds contributed both naturally and anthropo-

genically?' Where layers are varied and undisturbed and show sequential dates, the variations in input of an element or substance may be traced back quite

readily. Indeed, a good example of a parallel type of measurement is provided by the content of lead in the dust trapped in ice cores taken from the Greenland Ice

Cap and Antarctica. The advent of the industrial age is clearly measured by a

rapid rise in the lead content of the seasonal ice/snow varves (Murozumi, Chow &

Patterson 1969). An elegant demonstration of the value of layered cores for the determination of

416



Recognition of organic pollutants in aquatic sediments

the input of organic pollutants has been provided recently by the work of Hom, Risebrough, Soutar & Young (I974). Their analyses of dated marine sediments from the Santa Barbara Basin of the Southern California Bight have shown that deposition of PCB began about 1945 and that DDE first appeared in the sediments deposited about 1952. Concentrations of both show a progressive increase until 1967. The sediments are laminated and the anoxic bottom water and sediment exclude burrowing organisms. The accuracy of the overall time framework

(approx. 4 mm/year), derived by counting the seasonal varves, was confirmed by the correspondence of rainfall and sedimentation patterns (Soutar & Isaacs 1974) and by 210Pb and 228Th/232Th radiometric age measurements (Koide, Soutar & Goldberg 1972; Koide, Bruland & Goldberg 1973; Krishnaswami, Amin, Lal & Soutar 1974). The estimated deposition rates in 1967 of DDE and PCB were 1.9 x 10-4 g m-2 year-l and 1.2 x 10-4 g m-2 year-l, respectively.

The above type of study should be applied to a wide variety of compounds and to sites from many sea and ocean bed locations so that base-line levels can be determined. Such data, furthermore, hold a wealth of information on the climatic and environmental history of the earth's surface. To some extent, cores from the

Deep Sea Drilling Project (D.S.D.P.) will assist in this, but unfortunately the

upper portion of each core is lost. Changes due to the various anthropogenic factors

already outlined cannot be seen in these cores as the youngest sediments analysed are already too old.

There are other problems in reading the record contained in sediment sequences for the natural and anthropogenic fluxes. They include the disturbance of the sediment by bioturbation, recycling by bottom feeders and slumping as a result of water and sediment movement. Another difficulty is that of migration and diffusion processes in the sediment which have been encountered recently in some studies (e.g. Erlenkeuser, Suess & Willkomm 1974). Finally, the actual deposition in the past may have been substantially affected as to rate and nature by climatic variations (Bryson 1974). Anthropogenic effects include agricultural activities, such as the burning of forests, which lead to changes in the actual fluxes of organic matter. Some disentangling of the various factors should result from careful comparison of sediment layers of the same age but taken from different regions of the ocean floors. The analytical data should be inter-related with differing alloch- thonous and autochthonous contributions represented by wind- and water-borne particulate matter and by biological production in situ. The wind-borne component is known to be related to climate and changes in agricultural practices and is a major factor controlling the distribution of some pollutants.

The first observations of aeolian dust fallout onto ships in the Atlantic were reviewed by Darwin (1846). More recent studies of fallout and of marine sediments with aeolian components have been reported. The most widely studied area is west of the Cape Verde Islands, where the heaviest loads have been reported (Parkin, Phillips & Sullivan I970; Chester & Johnson 1971; Chester et al. 1972). The mineralogy and particle size distributions of these dusts have been studied by

417



418 G. Eglinton and others (Discussion Meeting)

the various investigators to trace the terrigenous sources. These results have been reviewed by Chester (I972). A sample suite from a larger survey of the Atlantic and Indian Oceans, China Sea and Sea of Japan was also analysed for carbonate and total carbon (Aston, Chester, Johnson & Padgham I973). The total carbon values extended to 47 % and carbonate to about 2 %. The nature of this non- carbonate carbon is not known, but such samples are under organic analysis in this

laboratory.

TABLE 1. A COMPARISON OF SOME TECHNIQUES AVAILABLE FOR THE

ANALYSIS OF ORGANIC POLLUTANTS

certainty of

sensitivity identification techniquet (the more * the better) comments'

f.i.d.-g.c. ** * poor for complex mixtures

e.c.d.-g.c. *** * restricted mainly to halogenated compounds

g.c.-m.s. ** ** poor for complex mixtures

c.-g.c.-m.s. ** *** can analyse all g.c.-m.s. data and resolve complex mixtures

m.i.m.-g.c.-m.s. (*** ** requires prior knowledge of

compounds to be detected

c.-g.c.-h.r.m.s. ** **** expensive; not widely available

t f.i.d., flame ionization detection; e.c.d., electron capture detection; m.i.m., multiple ion

monitoring; h.r.m.s., high resolution mass spectrometry.

THE ANALYSIS OF LIPIDS IN MARINE SEDIMENTS

The methods in common use and those which show considerable potential are

listed in table 1. In analysing sediments for pollutants, the first problem that arises

is that of efficient extraction. Pollutants are commonly assumed to be extracted

by organic solvents but some of the organic matter contributed to sediments may be converted into insoluble complexes, such as humates. Chemical degradation

procedures (e.g. oxidation and hydrolysis) may be necessary to release bound

pollutants but little information is available on this point. A second problem con-

cerns the actual sites of absorption and adsorption: Thus, pollutants may be held

within the clay minerals, thereby necessitating demineralization or lattice swelling for efficient extraction. Thirdly, the original pollutants may no longer be present in the sediment since they may have been converted into metabolic and other

degradation products. The analytical methods employed should be capable of

detecting and determining unusual and unexpected compounds, such as novel

natural products and compounds other than the original pollutants. One technique

awaiting exploitation is that of radiolabelled incubation as used in the study of the

short term fate of compounds in lake sediments (Eglinton 1973). Obviously, this is

more difficult to carry out in marine situations.




In any analytical problem, the method selected predetermines to some extent the results obtained. Thus, in general, it is customary to detect and quantify an

organic compound by means of a deliberate search, using a technique known to concentrate it into a particular fraction. It is much more difficult to analyse for

compounds of unknown structure and of unknown abundance. Techniques such as

computerized gas chromatography-mass spectrometry (c.-g.c.-m.s.), both low and

high resolution, are particularly valuable here and they are almost independent of

prior knowledge of the likely composition of a sample. The equipment required is, of course, more expensive and less generally available than that needed for routine

monitoring procedures, such as gas chromatography (g.c.) alone. The examination of complex mixtures is simplified by computer processing of the g.c.-m.s. data since less elaborate sample prefractionation is required. The latter part of this

paper reviews the nature and capabilities of the c.-g.c.-m.s. and explores the use of this technique in the recognition of pollutants in sediments.

Organic compounds in Recent marine sediments

The key to an understanding of the nature and distribution of organic com-

pounds in the Recent sediments lies in the determination of base-line ranges of values for natural abundances.

For organic compounds which are uniquely pollutants (e.g. DDT) these values will of course be zero. For the more numerous organic compounds which occur

naturally but have greatly increased in concentration in the environment due to man's activities (e.g. polynuclear aromatic hydrocarbons), the base-line abundances are not zero. Thus, detailed knowledge of the chemical identity and amounts of

organic compounds naturally present in marine sediments is essential before searches for unknown pollutants can be of much value. In addition, specific separation schemes will be needed in order to concentrate, isolate and quantify low levels of pollutants.

Various groups of organic compounds and particulate organic matter found in marine sediments can be traced back to an inferred terrigenous source (table 2). These substances are admixed with the autochthonous marine organic matter. They are brought to the marine environment by aeolian, river and ice-rafting transport processes.

The bulk mineralogy and organic carbon content of oceanic sediments is quite varied. For example, large areas of the Pacific Ocean floor consist of carbonate sediments (average organic C, approx. 0.1 %), the Atlantic Ocean has clayey and shaley sediments (average organic C, 0.3-12 %), the Bengal Basin has deltaic sands and silts (organic C, 0-0.3 %), and the Mediterranean Sea has clays and evaporites with some gyttja (organic C, 3 %) (Simoneit & Burlingame 1972, 1974, and Initial Reports of the D.S.D.P.).

Some natural inputs and mineral conveyors of potential pollutants have been described. Clays are excellent adsorbants for organic matter. Fatty acids were found to be strongly associated with clay particulates in sea water (Meyers &

419

26 Vol. I89. B.



TABLE 2. DEEP SEA SEDIMENTS: POSSIBLE MARKERS FOR TERRIGENOUS MATERIALS

class

CH3(CH2)nCH3

CEI3(CH2)nCO2H triterpanes diterpenoid acids

triterpenoid acids

polycyclic aromatics carbon particles

example

C247-C34

C28s-C33

dehydroabietic acid

bishomohopanoic acid

perylene

fulvic and humic acids

cutins pollen

lignins coal, kerogen

hydroxy acids

phenolic aldehydes

inferred source

higher plants

higher plants ferns, bacteria conifers

probably bacteria

forest fires, etc.

probably proteinaceous and carbohydrate matter

higher plants higher plants

higher plants ancient sedimentary rocks

location

ubiquitous

ubiquitous Atlantic Pacific

(N. American coast) Atlantic and

Gulf f of Mexico

Pacific (N. American coast)

Atlantic Atlantic

Pacific (N. American coast)

references

Simoneit & Burlingame (I972, I974) Aizenshtat et al. (1973) as above Simoneit & Burlingame (i974) Simoneit & Burlingame (1972)

Simoneit (1974a, b) Simoneit & Burlingame (I974) Van Dorsselaer et al. (i974) Aizenshtat ( 973) Simoneit & Burlingame (I974) Aizenshtat et al. (I973) Rashid & King (I969, 1970, 1971) Nissenbaum & Kaplan (I972) Caldicott (I973) Musich (1973)

Gardner & Menzel (I974)

t32

a

Cb or

P-

0 tf

O

P. 0c




Quinn I971, I973). Carbonates also interact with organic matter by sorption during crystal accretion (Suess I970, I973). In the case of Recent sediments this

sorption layer consists of nitrogen-rich protein-like material (Suess 1973). Dissolved organic matter (e.g. fulvic acid) has been shown to have a solubilization effect on normal and isoprenoid hydrocarbons (Boehm & Quinn 1973). Intermolecular association of fulvate and humate matter probably results in micelles which can incorporate the saturated hydrocarbons, but not aromatics.

Some localized pollution problems are caused by erosion of soils, petroleum seeps, and dumping of wastes. The erosion and weathering of soil from agricultural land is a major contributor of pollutants to the marine sediments (Robinson 1973). Large amounts of soil humate matter are suspended along with soil minerals and carried to the sea via the drainage systems. Fulvic acids were found to form stable complexes with lyophobic compounds, as for example, fatty acids and phthalate esters (Ogner & Schnitzer I970). Thus, suspended humate matter and dissolved fulvates may play a significant role as sinks for pollutants such as phthalates. Natural petroleum seeps, both littoral and off shore, have been contaminating beaches and oceans for millions of years (Landes I973). The best known example today is the Santa Barbara Channel, where the daily natural seepage is 8-11 m3.

The long term dumping of various high nutrient wastes (e.g. sewage sludge) into the New York Bight has resulted in large increases of the lead, copper and organic carbon concentrations (Gross I972). The highest levels of total organic carbon are observed in the sediments at the dumping sites and down the Hudson Canyon on the continental shelf and slope.

The organic matter of Recent marine sediments is a complex mixture of water- soluble compounds, solvent-soluble lipids and insoluble humate and kerogen materials. Before the 1960s, analyses of the solvent-soluble organic matter of such sediments were sparse and consisted mainly of carbon and hydrocarbon analyses (e.g. Trask I939). Various compound classes and series have been identified in Recent marine sediments: hydrocarbons (Stevens, Bray & Evans 1965), fatty acids (Kvenvolden 1962; Parker I967), carotenoids (Fox, Updegraff & Novelli I944; Vallentyne 1957, 1960), sugars (Prashnowsky, Degens, Emery & Pimenta 1961), isoprenoid acids (Blumer & Cooper 1967), sterols (Attaway & Parker 1970), amino acids (Wehmiller & Hare 1971), polynuclear aromatic hydrocarbons (Orr & Grady I967; Aizenshtat 1973), and porphyrins and chlorins (Baker & Hodgson I968; Baker 1971; Baker & Smith 1973).

More detailed surveys of marine sediments have appeared (e.g. Rittenberg et al. 1963; Welte & Ebhardt I968; Peake, Baker & Hodgson 1972; Presley, Kolodny, Nissenbaum & Kaplan 1972; Simoneit & Burlingame 1972, I974; Aizenshtat, Baedecker & Kaplan I973; Simoneit 1974a). These detailed surveys discuss the mineralogy, palaeontology and organic matter content of the various marine sediments. The extensive drilling programme of the D.S.D.P. has covered the major world oceans (Initial Reports of the D.S.D.P.) and some preliminary data on the nature of the organic matter (both solvent-soluble and insoluble) in these

421



G. Eglinton and others (Discussion Meeting) sediments have appeared (Simoneit & Burlingame 1972, I974; Aizenshtat et al. 1973; Baker & Smith I973; Hoering I973; Simoneit, Scott & Burlingame 1973a).

Computer handling of g.c.-m.s. data

Gas chromatography is a powerful tool for the separation of volatile components of a mixture and mass spectrometry provides rapid and, in many cases, un- ambiguous identifications. G.c.-m.s. combinations have been used for the analysis of mixtures of organic compounds since the early 1960s. Since then the method has become widely used in diverse applications and has been thoroughly reviewed (Brooks & Middleditch 1973; McFadden 1973). A review of mass spectrometry by Burlingame, Cox & Derrick (I974) includes discussions of recent advances in

g.c.-m.s. and c.g.c.-m.s. The method has assumed major importance in environmental chemistry, organic geochemistry and in biomedicine. Until recently it was normal practice for the chemist to acquire his mass spectral data as analogue records on photosensitive paper. Acquisition was followed by a long sequence of manual operations including counting, ion intensity digitization, background subtraction and normalization. Now, however, several manufacturers produce complete systems consisting of a g.c.-m.s. linked to a laboratory computer. These

systems remove the time-consuming drudgery and permit the acquisition and processing of large quantities of data. A very advanced small computer system has been described by Smith, Olsen, Walls & Burlingame (I97I) for the acquisition, processing and display of low, medium and high resolution mass spectral data from both single and double focusing mass spectrometers in real-time. This group now has a large computer system for the simultaneous handling in real-time of data from several mass spectrometers (Burlingame, Olsen & McPherron 1973).

Modern computerized g.c.-m.s. systems are very flexible in the ways that they can be used for the analysis of mixtures. However, there are two basic situations: first, complex mixtures (i.e. crude extracts) and, secondly, mixtures simplified by careful chemical prefractionation. The g.c. traces for complex mixtures will show numerous poorly resolved peaks, but the computer may be used to extract much valuable information from the total raw m.s. data. Good spectra may be obtained

by the subtraction of neighbouring spectra and the spectra so produced identified

by further computerprocessing ormanualinterpretation. Simplified mixtures should

give good g.c. peak separation, thereby allowing automatic background subtraction

programs to generate clean mass spectra for most components. The computer may be used to perform classification, interpretation and file search processes directly on the acquired data. In both situations the following approaches can be employed:

(i) Specific compound classes may be recognized in the spectra collected from a

complex mixture by using mass fragmentogram displays for individual ions.

(ii) The mass spectrometer may be used as a highly specific and highly sensitive detector by means of single or multiple ion monitoring (m.i.m.). Levels of detection

approach those obtained with the electron capture detector in gas chromatography.

422




(iii) Direct computer comparison of collections of data from an unpolluted sediment and from a similar, though polluted, sediment will pick out components present in one but not in the other. The mass spectra of these components can then be processed further to identify them as pollutants or as natural sediment components produced in unusually large amounts as an indirect consequence of pollution. This method is of obvious utility in studies of sediment layers and for the comparison of sediments close to, and far removed from sources of pollution.

High resolution mass spectrometry (h.r.m.s.) is a useful ancillary technique. An example of such a system consists of an A.E.I. MS-902 high resolution mass spectrometer linked to a Sigma 7 computer system under Logos control (Burlingame I970; Burlingame, Smith, Merren & Olsen I970). The use of computer systems allows absolute compositional data to be obtained for all the significant fragment ions of the compound or compound mixture under analysis. This asset makes the on-line h.r.m.s. method useful for special problems in environmental chemistry. This system has been routinely used for general survey analyses of extract mixtures from D.S.D.P. core samples (Simoneit & Burlingame I972, 1974; Simoneit 1974b). Trace impurities in commercial Aroclor preparations were separated from the PCBs and identified as polychlorinated dibenzofurans by h.r.m.s. (Bowes et al. I973, I974). The specificity of composition assignments makes the h.r.m.s.

technique, with both direct inlet probe and g.c. coupling, extremely useful for the analysis of uncharacterized pollutants.

Computers have been used for mass spectral data processing for several years, and the subject has been reviewed (Ward I97I, I973). In principle, there are few

ways in which low resolution mass spectra may be identified by the use of computers. Many studies have used the conventional data processing method of file searching whereby the spectrum of an unknown compound is compared with spectra of known compounds held in file. This process may be carried out as follows: complete spectra may be compared, but this is expensive in terms of computer time; simplified spectra, consisting of ions chosen by intensities and other restrictions may be used; the files of standard spectra may be subdivided by the application of mass spectrometric or chemical parameters, and so on. The file search method has been reviewed by Ridley (1972).

It has been widely considered worth while to centralize mass spectral data into large 'banks' which would then be readily available to all mass spectrometrists. The Mass Spectrometry Data Centre at Aldermaston (Reading, RG7 4PR, Berk- shire, U.K.) is internationally recognized as being the central agency for collection and dissemination of mass spectral information and data. The Centre currently maintains a collection of about 14000 complete mass spectra and an eight peak index of 31000 spectra. Both are available on magnetic tape. The Centre has recently taken over the management of a system by which spectrometrists can search large files of spectra via normal telephone lines from four continents. This system has been described by Heller (I972) and Heller, Fales & Milne (I973). By the end of 1975 the data base for this search system is expected to consist of about

423



G. Eglinton and others (Discussion Meeting) 40000 spectra, some of which will have been contributed by the U.S. Environ- mental Protection Agency. Such a service may be useful for identification of

particular unknown compounds but cannot be used to process the hundreds of

spectra which may be generated each day by a computerized g.c.-m.s. system in routine use. Large central systems of any kind tend to suffer from a lack of flexi-

bility and to be liable to periodic failures as a result of administrative problems, breakdowns and industrial disputes. Even if the large central system works well, there will inevitably be time delays in using the system. For applications in biomedicine, forensic science and some aspects of environmental science (such as water quality control) such delays may be unacceptable.

Several problems confront the chemist who wishes to purchase and manipulate such data banks in his own institution. Mass spectra are not precisely reproducible, even on the same machine under standard conditions, and these differences are much greater if different instruments are used and different conditions apply. Thus, for computerized file searching using such a data bank the constraints required to select matching spectra must be chosen with some care. To hold 31000 reduced

spectra and to search through them in real-time requires considerable computer facilities. Selection of the spectra relevant to the particular field of the chemist in order to restrict the file search process to relevant spectra is an obvious, if tedious, procedure.

An alternative approach illustrated in this paper is the use of files of spectra built up in the user's laboratory. The standard spectra are produced on the instrument used for obtaining the spectra of the unknowns. Operating conditions, background subtraction and other variables are under local control which permits finer definition of matching parameters. Spectra can be sorted and filed in the most useful way as they are acquired. The data base is limited to compounds of interest to the particular laboratory. This approach is ideally suited to the needs of a

specialist laboratory equipped with a laboratory computer. Methods using the

principle of restricted specialist files have been described by Markey, Urban &

Keyser (I973), Robertson & Merritt (I973), and Abramson (I973). If the laboratory computer is linked to a large computing facility then searching large files of data

(e.g. M.S.D.C.) is also convenient, and the research worker has the best of both worlds. However, the simple file searching technique will give little useful information unless the spectrum of the unknown itself or a closely related compound is

present in the files. This disadvantage has led to the development of alternative methods of computer-aided mass spectral interpretation.

The most impressive programs (Dendral and Intsum) have been developed at

Stanford, California (Duffield et al. 1969; Smith et al. 1973). These programs depend on an inference method using known fragmentation mechanisms and utilize data in addition to the low resolution mass spectra. The method is, in principle, of

general applicability, but a large computer is required, and the programs, which are large and complex, are unsuitable for routine processing of g.c.-m.s. data.

Another approach is to provide the analyst with an indication of the chemical

424




class of the compound rather than a full identification. Successful methods include the 'ion series' method of Smith (i972) and a statistical binary classification (e.g. Felty & Jurs I973). The latter, and other 'pattern recognition' methods depend for successful operation on large training sets of data and do not utilize the

empirical knowledge of spectrometrists. A method particularly suited to the needs of specialist laboratories equipped

with small computers (and experienced analysts) has been devised by Gray &

Gronneberg (I975), and is described and illustrated in this paper. This method requires no knowledge of computers on the part of the spectrometrist and the interpretative output may be obtained simultaneously with continued data acquisition.

C.-g.c.-m.s. analysis of organic pollutants in the environment

Perhaps surprisingly, not much literature has yet appeared on c.g.c.-m.s. identifications of organic pollutants in the environment and even less has appeared on such identifications in marine situations. A few examples are given here to indicate the scope of the method.

Simoneit, Smith, Eglinton & Burlingame (I973b) performed c.-g.c.-m.s. on the total organic extract from San Francisco Bay water and, using the mass fragmentogram technique, identified four phthalate esters present in significant amounts. Similar methods have led to the identification of aromatic hydrocarbons (believed to be due to automobile exhausts) and dioctyl and dibutyl phthalate esters in the total organic extract of water from the Charles River, Boston (Hites & Biemann

1972; Hites I973). A typical hump, believed to be due to fuel oil pollution, was also observed. Quantification of the aromatic compounds was obtained by high pres- sure liquid chromatography. Aromatic hydrocarbons and phthalate esters have also been identified (by g.c.-m.s.) in a Japanese river (Ishiwatari & Hanya 1974). A g.c.-m.s. combination together with a computer system to process the g.c. data has been used to identify 70 polycyclic aromatic hydrocarbons which were extracted from urban airborne particulates (Lao, Thomas, Oja & Dubois 1973). G.c.-m.s. has been used to identify PCBs extracted from human adipose tissue (Biros, Walker & Medbury I970) and from bald eagles (Bagley, Reichel & Cromartie

I970). Undoubtedly, the organization which has most experience in the detection of

pollutants by c.-g.c.-m.s. is the U.S. Environmental Protection Agency (McGuire, Alford & Carter 1973; Webb, Garrison, Keith & McGuire 1973). In 1969-71 a careful study of the c.-g.c.-m.s. method for pollutant identification was carried out by this organization and their first commercial g.c.-m.s. system with a small dedicated computer was purchased in 1971. The E.P.A. has conclusively demonstrated the value of c.-g.c.-m.s. A file search based on the method of Hertz, Hites & Biemann (197I) is principally used for identification of pollutants. Workers in the E.P.A. have used quadrupole mass spectrometer m.i.m. techniques for the detection of PCB residues in the sediment from an Ohio Lake (Eichelberger, Harris & Budde I974).

425




The c.-g.c.-m.s. method is also in use in biomedicine, as in the rapid evaluation of large numbers of g.c.-m.s. analyses of steroids in blood, urine and tissues

(Reimendal & Sjovall I973). A c.-g.c.-m.s. data system for the identification of 133

drugs of abuse has been described (Finkle & Taylor 1972). Identifications are performed by the file search method. This is a good example of the great value of

specialist files of standard spectra to suit a particular specialized application.

b/) bn ._

aq

C)

0

o C)

0Q 0

C) '^: ^3

FIGuRE 1. Flow chart for the processing capabilities of the c.-g.c.-m.s. system at Bristol

University. Real-time processing screens a normalized, background-subtracted spectrum on the v.d.u. immediately after each scan. Simultaneous print-out of results from the

operation of the classification and interpretation programs is optional but is only worth while with good quality spectra. All spectra are stored on disk from which they may be recalled for delayed processing. Fragmentograms, v.d.u. display of individual spectra and the real-time print-outs are used as a guide in the selection of spectra for editing by spectrum subtraction, plotting, listing and automatic classification or identification by the interpretation or file search programs. Finally, identified and otherwise useful

spectra can be transferred to permanent search files.




A c.g.c.-m.s. system with real-time processing A Varian MAT CH-7 mass spectrometer linked to a Varian 1200 gas chromato-

graph via a single-stage Watson-Biemann separator has been used in the Organic Geochemistry Unit, University of Bristol, since 1969. In 1973 a data system was added. The central item is a PDP 8/e computer with 16k memory. The mass

spectrometer is linked to the computer via a Carrick interface which records the time and intensity of ion peaks from the mass spectrometer and passes this digital information to the computer at the end of each scan. The computer performs a

variety of data manipulation processes and stores information on DEC tapes and on a cartridge disk (Gray I974; Sanderson, Philp, Eglinton & Zoro I974). The PDP 8/e is scheduled to be a remote terminal for the University I.C.L. 4-75 com-

puter; in this way, tasks which require a large computer may be carried out, large quantities of information may be stored on compatible tapes and data may be

exchanged with other mass spectrometry groups at home and abroad. Output from the PDP 8/e is presented to the user in a variety of ways via the peripheral devices. These include a teletype, a video display unit (v.d.u.), a matrix printer and a digital plotter.

The sequence of events in the computer-aided analysis of the data from a

g.c.-m.s. run is illustrated in figure 1.

Real-time processing The mass spectrometer is operated in the continuous cyclic scanning mode.

During each scan the new spectrum is stored in the interface core memory. This leaves the computer free to perform data processing operations on the previous scan during the magnet flyback period and during the subsequent scan. Transfer of the data derived by each scan from the interface to the computer core memory is achieved in milliseconds. Thus, in normal operation with a 3.5 s scan and a 3.5 s

flyback time, 7 s are available to the computer for interscan processing. This is

ample time for counting, normalizing to base peak, automatic background subtraction, display on the v.d.u. and storing the modified mass spectrum on disk. With assembler code programs these processes are accomplished in about a second and several seconds remain available. This spare time may be utilized by classification and interpretive programs (also written in assembler code) which give inter-scan summary information on the printer. The non-real-time versions of these

programs are described below.

Delayed processing The first stage in the deiayed processing of data from g.c.-m.s. runs is frequently

the plotting of the computer-reconstructed total ion current (t.i.c.) trace and the

plotting of mass fragmentograms. In this method the intensity of selected ions is

plotted against scan number. A plot of the intensity of a particular ion against scan number may draw attention to one or more peaks in the mixture. The

427



G. Eglinton and others (Discussion Meeting)

appropriate spectra may then be analysed more closely. Another major program permits the user to display collected spectra on the v.d.u. screen and perform functions such as subtraction of one spectrum from another, renormalization of a

spectrum to a specified ion, scaling up of specified parts of a spectrum, etc. Selected

spectra may be rapidly transferred to smaller files on disk or tape. The files of selected spectra may then be plotted as bar diagrams or printed as a digital matrix for leisured perusal and interpretation by the chemist.

Three computer methods of mass spectral data analysis are in use in the Organic Geochemistry Unit. Two of these (classification and interpretation) may be performed in real-time or may be performed later during delayed processing.

The classification method is based on ion series as described by Smith (I972) and used by Smith & Eglinton (I972). The printed output consists of file name, spectrum number, mismatch scores, parent ions for suggested classes, and a word

description of the classes of compounds to which the unknown may belong. The interpreter method (Gray & Gronneberg 1975) uses a data table previously

built up by the chemist during an interactive session at the v.d.u. This table consists of a hierarchical tree of decisions based on absolute or relative intensities of ions of specified masses for particular compound types. Thus, the empirical knowledge of a spectrometrist with specialist knowledge of the spectra of certain classes of compounds is built into the system. This method is very flexible and the

spectrometrist can decide to what level the interpretation proceeds, depending on the particular application. Thus, for a set of spectra of compounds of known chemical class the method can produce precise identification of each component. For a mixture of completely unknown compounds, a classification according to chemical class may be obtained andthe classified spectra subsequentlyreprocessedby a restricted file search method or by a further interpretation using the same method but using definitions within each class to give complete identifications. The printed output from the Interpret program consists of the file name and spectrum number, proposed molecular mass, one or more identifications with scores and, optionally, an indication of the route taken through the hierarchical tree in order to arrive at the identification. The sum of ion currents in the unknown spectrum and the sum of ion currents and the number of ions accounted for in each result are also given.

The file search method (Gr6nneberg, Gray & Eglinton 1975) uses files of the

spectra of standard compounds. These search files consist of spectra reduced to ten

significant ions and a key ion. The complete spectra of the unknown components are compared with the file of reduced standard spectra. The printed output consists of file name, spectrum number, scores and reference numbers of matching standard spectra. As specialized files of standard mass spectra are built up file

searching will become the final definitive stage in the identification of components which have been previously encountered. Identification of unusual or unexpected components such as novel pollutants will be performed by the classification and

interpreter methods with confirmation of the identification by a spectrometrist before the spectrum is included in the standard files.

428




ANALYSIS OF AN ESTUARINE SEDIMENT

The c.-g.c.-m.s. system currently under development at Bristol has already been extensively employed in the analysis of organic compounds extracted from a

variety of Recent aquatic sediments (e.g. by Eglinton, Maxwell & Philp I974).

g.c. g.c. g.c. c-g.c.-m.s. c-g- -g.c.-m.s.

e.c.d.-g.c. FIGURE 2. Flow chart for the extraction, fractionation and analysis of the solvent-soluble

components of a sample of mud from the River Usk. Quantities are in parts/106 (dry mass) and are estimated by mass, except for the polynuclear aromatic hydrocarbons (PNA) and phthalates, which were estimated by f.i.d.-g.c.

The sample chosen here as the basis of a pollutant-orientated study is an estuarine tidal mud from an industrial region. It is from the mouth of the Usk River where it enters the Severn Estuary at Newport (O.S. ref. 320 855) and was taken at 12 noon (ebb tide) on 22 May 1974. A surface scrape sample (approx. 2 cm depth)

429




was removed from the mud slope about 5 m from the edge of the shore vegetation. The mud consisted of fine-grained clay, grey-brown in colour and extensively burrowed by estuarine worms (Nereis diversicolor) (Boyden & Little i973).

The sample workup procedure is outlined in figure 2. The organic carbon content of the dried sediment was 4.65 % and its carbonate content was 4.70 % (Bush

| .A. - - total extract

0

o_ -4

fraction 1

iZ*QL" \\/a IT?/ ^^V^fraction 2

.i -,-330i0O"C fraction 3 I .....' -"'

0 20 40 60

time/min

FIGotRE 3. Gas chromatograms for the lipid fractions (figure 2) obtained from the Usk river mud. The g.e. conditions used were as follows: 1.5 mmi x3m stainless steel column, packed with 3 % Dexsil on Gaschrom Q (100-200 mesh), programmed from 120 to 310 ?C at 8 ?C0min, and using N2 at a flow rate of 10 ml/min.

i970). Most of the water was removed from the sediment by centrifugation (6000 rev/min, 10 min). The sample was then extracted by three successive aliquots of Dole & Meinertz (1960) mixture (heptane: isopropanol, 1: 4) using ultrasonication for 10 min each, followed by re-centrifugation. Excess water was added to each extract, the resulting heptane layers were combined and evaporated under reduced pres- sure, yielding a dark brown oil. The concentrated extract was then subjected to thin layer chromatography (t.l.c.) using silica gel G plates and 15 % diethyl ether




in hexane as developing solvent. The bands in the following Rf ranges were eluted: fraction 1, 0.55-1.0 (hydrocarbons); fraction 2, 0.25-0.55 (esters and aromatics) and fraction 3, 0.0-0.25 (alcohols). Analogous t.l.c. analyses of standard com-

pounds and mixtures (e.g. polynuclear aromatic hydrocarbons, phthalates and

PCBs) demonstrated their respective Rf regions. All these eluted fractions were

(a)

r^ , , ....... ,, , ; ,', ........., ,... ..

o 50 100

(b)

(c) I

......... ! .........i ........., ........, ,...,! ,, ..,..,,.,i ...., ,,.,,, .,.~'""hli',,,"l ,,, ..,....1 ........., ........., ..........

0 50 100

scan number

FIGURE 4. C.-g.c.-m.s. analysis of fraction 2. Detection of phthalates. (a) Computer generated total ion chromatogram for portion of c.-g.c.-m.s. run. (cf. figure 3, fraction 2: the response of the f.i.d. to particular components is not the same as that of the t.i.c. monitor.) (b) Mass fragmentogram for mle = 279. (c) Mass fragmentogram for m/e = 149 (characteristic of phthalates).

subjected to g.c. analysis on a Perkin-Elmer model F-11 instrument. The gas chromatograms (figure 3) indicated that all three fractions were complex mixtures, the areas of the individual peaks very approximately summed matching the area of the original extract trace. All three chromatograms display background envelopes of unresolved peaks, the major complexity being in fraction 1.

Each fraction was then analysed by c.-g.c.-m.s. using the system described in the previous section. The mass spectra were recorded at 70 eV ionization energy and 300 ,uA filament emission. The procedures followed (figure 1) are best illustrated by an account of the c.-g.c.-m.s. analysis of fraction 2.

431




The data were acquired with real-time display on the v.d.u. and spectra with

significant intense ions were noted manually by scan number. Automatic back-

ground subtraction was not employed because of the height and variability of the

envelope, which also precluded the real-time operation of the classifier and inter-

preter programs. The next step was to transfer the completed run (140 scans) to

tape for delayed processing at leisure. A total ion chromatogram was plotted (figure 4a) to serve as a general guide to the location of g.c. peaks in relation to scan numbers. Individual scans were then recalled to the v.d.u. and those located wherein major ions appeared and disappeared over a few scans, corresponding to the passage of a distinctive compound through the g.c.-m.s. Exact m/e values could then be read from an expanded spectrum. Homologous series became evident when regularly spaced scans showed a particular fragment ion or ions: for example, m/e = 149, which is a characteristically intense ion of phthalates, when plotted as a mass fragmentogram (figure 4c) clearly indicates the presence of a series of these

compounds. Other mass fragmentograms were similarly informative (e.g. figure 4b). With these mass fragmentograms as a guide, scans giving maximum signal for a selected component were chosen (e.g. figure 5b) and edited by subtracting neighbouring spectra to reduce the signal from the unresolved envelope (figure 5a). The resulting spectra (e.g. figure 5c) were generally of good quality and were

easily recognized by comparison with filed spectra of standards. Furthermore, most of these edited spectra were processed satisfactorily by the classifier, inter-

preter, and file search programs (table 3). The recognition of some components, for example, the phthalates and polynuclear aromatics, was followed up by co-

injection of standard samples, with consequential enhancement of the appropriate peaks. Quantification was similarly effected. Finally, the exercise was followed

through (figure 1) by adding selected spectra from the data tapes to the search files.

Fraction 1

The g.c. trace of fraction 1 (hydrocarbons) consists of a hump, maximizing at the approximate retention time of n-docosane (cf. figure 3b). C.-g.c.-m.s. analysis of this crude fraction indicated an unresolved background envelope consisting mainly of a complex mixture of alicyclic hydrocarbons. The n-alkanes are in low abundance and the carbon preference index (c.p.i.) (Cooper & Bray 1963) for

n-Cll to n-C20 is 1.02, a typical value for petroleum. The isoprenoids, phytane (Ph) and pristane (Pr), are present in the following ratios: Pr/Ph = 1.1, n-C,7/Pr = 1.2 and n-Cl8/Ph = 1.1. These ratios and the other data above are indicative of a

partially weathered and/or microbially degraded petroleum. Blumer et al. (1970) and Blumer, Ehrhardt & Jones (i973) have made detailed studies of the evaporation, dissolution and degradation of several oils and they observed similar ratios

for the partially altered petroleums.

432



TABLE 3. MAJOR COMPONENTS OF FRACTION 2 FROM THE USK RIVER SEDIMENT

compound (assigned) phenanthrene and anthracene di-n-butyl phthalate dipentyl phthalate methyl phenanthrene and methyl

anthracene fluoranthene acephenanthrylene or

aceanthrylene pyrene di-(2-ethylhexyl) phthalate chrysene di-n-nonyl phthalate methyl chrysene benzopyrene (probably 1,2-) benzopyrene (probably 3,4-) methyl benzopyrene

c.-g.c.-m.s. molecular scan no.

composition mass (cf. figure 4a)

C141T0lo C16H2204

C17XH2404 C15H12

C16H10

C1611Ho

C16Ho10

C24H3804 C186H12

C26H4204 Cl9H14 C20H12

020H12

C21H14

C,xHx4

178 278 292 192

202 202

202 390 228 418 242 252 252 266

7-11 10 20 20

classifier (c) and interpreter (i) resultst

10 DB 3 RING PNA P+178(i) PHTHALATE (c) UNCLASSIFIED (C)

10 DB 3 RING SUBS PNA P+192(i)

38 12 DB 4 RING PNA P+202 (i) 44 12 DB 4 RING PNA P+202(i)

53 72 76 80 87

107 115 122

UNCLASSIFIED (i) PHTHALATE MwV 390(c) 13 DB 4 RING PNA P+228(i)

PHTHALATE (c) 13 DB 4 RING SUBS PNA P+242(i) 15 DB 5 RING PNA P+252(i) 15 DB 5 RING PNA P+252(i) 15 DB 5 RING SUBS PNA P+266(i)

confirmationt

g.c, m.s. g.c., m.s. m.s.

g.c., m.s.

g.c., m.s. g.c., m.s. g.c., m.s. g.c., m.s. m.s.

approx. . conc. c.

(parts/106) 6

9 c 8 0 6 3

30 e 18

0.5 30 25 14

6 24

3 c~ Co-

t Computer analysis of edited spectra: DB, double bonds; PNA, polynuclear aromatic. I g.c., coinjection of standard; m.s., comparison with standard mass spectrum (after background deletion).




Fraction 2

Fraction 2 (esters and aromatics) (cf. figure 3c) also exhibits a minor hump in the g.c. trace. The c.-g.c.-m.s. analysis indicates a series of phthalate esters, polynuclear aromatic hydrocarbons and other alicyclic lipid material. The total ion

chromatogram and two mass fragmentograms are shown in figure 4 and the results

0

0 OC,H2n +1

OC,IH2,n+i

0

1

0

0-H

2 CH 03, 149 2 C8H503, rnJA= 149

0

OH2

OC8H17

3 0, e=279 3 C16H2304, m7e=279

0 00 0

4 5

C16Hlo, mol. mass=202 6 7

C20H12, mol. mass =252

are summarized in table 3. The compounds 1, n = 4, 5, 8 and 9 were present (cf. table 3). The m/e = 149 ion (structure 2) is the base peak in the mass spectra of these compounds and is shown in the mass fragmentogram of figure 4c. The single peak (figure 4b) in the mass fragmentogram of m/e = 279 (structure 3) represents the loss of C8HI6 from the molecular ion of the n = 8 compound. The spectrum editing process by subtraction of a neighbouring scan is illustrated in figure 5.

The other major compounds present in the fraction were polynuclear aromatic

hydrocarbons, characterized by intense molecular ions and doubly charged molecular ions. The following series were identified: CnH2n_8i, n = 14; CnH2n_22, n = 16; CnH2_124, n = 18, 19; and CnHg2n2s, n = 20, 21. Coinjection of standard

compounds and correlation of retention data with literature values (Lao et al.

00rC

434




1973) permitted structural assignments for some of these compounds. The unresolved doublet peak at scans 7-11 (cf. figure 4a) is a mixture of phenanthrene and anthracene. The peak maximizing at scan 38 is fluoranthene (structure 4) and scan 44 is either acephenanthrylene or aceanthrylene but not pyrene. Scan 53 is a weak spectrum of pyrene (structure 5) and scans 107 and 115 are probably spectra

(a)

I <")tt' * T

(C)

100 200 300 400

scan number

FIGURE 5. C.-g.c.-m.s. analyses of fraction 2. Spectrum edit by scan subtraction. (a) Scan 69. Base peak m/e = 55, intensity 562 units. (b) Scan 71. Base peak m/e = 149, intensity 406 units. (c) Scan 71-scan 69. Base peak mle = 149, intensity 366 units. This spectrum closely matches that of di(2-ethylhexyl)phthalate.

of 1,2-benzopyrene and 3,4-benzopyrene (structures 6 and 7, respectively). By co-injection it was demonstrated that these scans do not correspond to perylene. The elution order (Lao et al. I973) for these isomers is 6 before 7. The remaining aromatic compounds (cf. table 3) were identified from their mass spectra only.

Fatty acid esters and dicarboxylic acid esters were also present as minor components. Mass chromatograms of m/e = 74 [(CH602)', the diagnostic ion of methyl esters of n-fatty acids] and m/e = 102 [(C5H,00O2), the corresponding ion of isopropyl esters] indicated minor amounts of myristic, palmitic and stearic acid esters. The isopropyl esters are probably artefacts generated during sample extraction with isopropanol. Similar esterifications catalysed by clays in sediments with the extraction solvents methanol, ethanol and acetone have been noted (Arpino & Ourisson 197I; Simoneit & Burlingame 1973, 1974; Simoneit et al.

435

27 Vol. I89. B.




1973a). The diagnostic ion for dicarboxylic acid esters is m/e = 98 but a mass

fragmentogram indicated only trace components. Polychlorinated biphenyls (PCBs) were specifically sought in this fraction by

two techniques; mass fragmentography and e.c.d.-g.c. but were not detectable by either technique at a level of 1 part/106 (dry mass) of sediment. Peaks were observed by e.c.d.-g.c. analysis of this crude extract but were not comparable with the traces obtained for Aroclor 1242 and 1254 standards.

Fraction 3

Fraction 3 consists mainly of two classes of compound, namely the homologous series of normal fatty alcohols and certain sterols, both identified by c.-g.c.-m.s. after derivatization to give their TMSi ethers. The straight chain alcohols, CnH2n+20, range from n = 16-30, with the even carbon number homologues predominant (c.p.i. = 14.1). The mass spectra of the fatty alcohol TMSi ethers are

quite simple, exhibiting a prominent ion due to the loss of CH+ from the molecular ion.

The sterols are CnH2-_80, for n = 27-29 and CnH2_60O, for n = 29. The mass

spectra fit the fragmentation patterns of cholesterol-TMSi ether (25/106), 5,?-

stigmastanol-TMSi ether (7/106), and sitosterol-TMSi ether (8/106). These identifi-

cations, while reasonably secure, would be more satisfactory if obtained by capillary g.c.-m.s. and supported by additional spectral data from other tech-

niques. The apparent absence of 5/,-cholestanol, which has been suggested as an indicator of domestic sewage input (Matthews & Smith 1968) is surprising.

Summary of Usk sediment analysis Table 4 summarizes the findings from this brief analytical study designed to

scan the extractable organic compounds in the medium molecular mass (C10-C40)

range. Free acids were not examined as few significant pollutants come into this

category. The sampling site is exposed to effluent from ships and from industrial and

urban areas and the c.-g.c.-m.s. findings indicate some of the results of these inputs.

They also suggest that the crude oil component has been weathered. The quantities of hydrocarbon in this Usk sediment are unusually high but the 'weathered

pattern' of the relative amounts of the various hydrocarbon types is like those

being encountered from coastal sediments worldwide. For example, surficial sedi-

ments from Narragansett Bay, Rhode Island, were found to contain a similarly

complex mixture (hump) of hydrocarbons (Farrington & Quinn 1973). A petroleum source for these hydrocarbons was inferred and then confirmed by Zafiriou (i973) using 14C analysis. Microbes preferentially metabolize normal alkanes and then

isoprenoids and lower-ring naphthenes (Miget, Oppenheimer, Kator & LaRock

I970; Zobell 1970; Atlas & Bartha I972a; Bailey, Jobson & Rogers I973). The

microbial degradation of the hydrocarbons depends strongly on the substrate; nutrients are more important than water abundance or temperature history for

436



Recognition of organic pollutants in aquatic sediments 437

this process (Atlas & Bartha 1972b; Floodgate 1972; Blumer et al. I973; Hughes, this volume, p. 375). In another study, the weathering of two stranded crude oils was followed over a one year period (Blumer et al. 1973). At both locations a

major portion of the oil persisted, modified by evaporation and by partial microbial degradation. Similar data over a longer study period are available for the Falmouth (U.S.A.) oil spill (Blumer et al. 1970; Blumer & Sass I972).

TABLE 4. SUMMARY OF C.-G.C.-M.S. FINDINGS FOR TIE USK RIVER SEDIMENT

amounts compound groups (parts/106) comments

n-alkanes isoprenoids 230 degraded crude oil, no obvious alicyclics (hump) higher plant input triterpanes phthalate esters 60 industrial pollution polynuclear aromatic hydrocarbons 140 characteristic of petroleum and

air particulates fatty alcohols 58 contemporary biological activity sterols 42 biological activity stanols J reducing conditions in sediment

The polynuclear aromatic hydrocarbons reported here are also unusually abun- dant and probably derive mainly from high aromatic crude oils but these com-

pounds are also major components of soots and urban airborne particulates (Smith I972; Lao et al. I973; Simoneit, Smith, Eglinton & Burlingame I974).

The main point to be made from the above analyses, however, is that very limited fractionation followed by c.-g.c.-m.s. has afforded much valuable information concerning the organic content and particularly the organic pollutant content of the sediment. Of prime importance is the capability of a computerized system to record and store all the data from a g.c.-m.s. run. As a universal rather than a selective detector, the data it provides are then available for re-examination for

specific purposes such as, in the present instance, the detection and confirmation of the presence of polynuclear aromatic hydrocarbons.

CONCLUSIONS

There is a need to increase the scope and precision of the recognition of organic pollutants in the marine environment. Really detailed analysis of a relatively small number of environmental samples is likely to extend greatly our knowledge of the range of natural and pollutant organic compounds. Such. information should serve to guide and complement the more routine and narrow-range survey analyses for pollutants. Different types of sediment (lagoonal, continental shelf, oceanic, etc.) require examination for free and bound organic compounds.

Highly specific techniques suited to the detection of certain types of pollutant 27-2




such as the chlorinated hydrocarbons require the backing of methods for positive identification. But more vital still is a non-specific, broad-range capability for the sensitive analysis of complex mixtures of organic compounds, both expected and

unexpected, pollutant and natural. The c.-g.c.-m.s. system is just this. Commercial versions are becoming cheaper, easier to operate and more versatile. Furthermore, c.-g.c.-m.s. has great scope for further development in each segment of the basic

system. Modern high resolution g.c. utilizes glass capillary columns and all-glass injection systems. Injection systems which avoid the passage of solvent through the column are available. Mass spectrometers with high pumping capacity are able to accept high carrier gas flows direct from capillary columns without a separation step with its attendant losses. Fast scanning mass spectrometers can cope with the

very sharp peaks which result from high resolution g.c. Storage facilities (disk or

tape) are available for collecting the data from successive capillary g.c.-m.s. runs, each of several hundred scans.

M.i.m.-g.c.-m.s. is capable of routinely monitoring samples for very small amounts of pollutant organic compounds, thus extending the job currently done

by e.c.d.-g.c. for halogenated compounds. H.r.m.s. and chemical ionization m.s. will find application for particular identification problems. Libraries of mass

spectra and interpretation and search programs will proliferate and expand. Each

c.-g.c.-m.s. laboratory should build up its own specialized files, using its own instrument with operating parameters under local control. These valuable, specialized, ordered search files can be augmented with data from centralized collections (e.g. M.S.D.C.) as necessary.

As to the g.c.-m.s. analyses themselves, simple and limited fractionation of crude extracts is desirable because contamination, losses and handling times are reduced. Extraction, fractionation, derivatization and g.c. columns and liquid phases should be optimized and standardized for g.c.-m.s. purposes. Retention time and m.s. data collected by different research groups would then be comparable and interchangeable. The use of computers permits analysis of complex fractions, long-term storage of complete sets of g.c.-m.s. data and future comparisons of

compound distribution patterns and/or identifications to other related samples. Data for sediment lipids from type locations or environments should be retained as special pattern files.

Computer methods also need to be standardized. Mass spectra and reduced

spectral data should be stored in standard format and programs for the recognition of spectra should be written in such a way that they can be readily exchanged with other groups. Exchange of interpretation data (such as the hierarchical trees used in the interpretation program described in this paper) will ensure the dissemination of specialized skills developed in individual laboratories. Plans are already in hand for such exchanges between the Bristol group and certain other groups with common interests in the U.S.A.

438




We thank the Natural Environment Research Council (Research Grant

GR3/1257), the Nuffield Foundation, the British Library, the University of Bristol, the National Aeronautics and Space Administration (N.A.S.A. Grant

NGL-05-003-003) and the Oceanography Section of the National Science Founda- tion (NSF Grant GA-24214) for financial support.

We also thank Mr M. D. Hunter, Welsh National Water Development Authority, Usk River Division, Newport, for advice on sampling sites.

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1881-1898. Arpino, P. & Ourisson, G. I97I Analyt. Chem. 43, 1656-1657. Aston, S. R., Chester, R., Johnson, L. R. & Padgham, R. C. 1973 Mar. Geol. 14, 15-28. Atlas, R. M. & Bartha, R. 1972a Biotech. Bioengn. 14, 297-308. Atlas, R. M. & Bartha, R. 1972b Biotech. Bioengn. 14, 309-318. Attaway, D. & Parker, P. L. I970 Science, N.Y. 169, 674-676. Bagley, G. E., Reichel, W. L. & Cromartie, E. 1970 J. Ass. Offic. analyt. Chem. 53, 251-261. Bailey, N. J. L., Jobson, A. M. & Rogers, M. A. I973 Chem. Geol. 11, 203-221. Baker, B. L. & Hodgson, G. W. I968 Chem. Geol. 3, 119-133. Baker, E. W. I971 Chem. Geol. 7, 45-49. Baker, E. W. & Smith, G. D. 1973 In Init. Repts. of DSDP (eds. B. C. Heezen & I. G.

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vol. 2, pp. 302-335. London: The Chemical Society. Bryson, R. A. 1974 Science, N.Y. 184, 753-759. Burlingame, A. L. 970 Recent developments in mass spectroscopy (eds. K. Ogata & T. Haya-

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