Interpretations of Contaminant Sources to San Pedro Shelf Sediments

Chapter 16

Downloaded by UNIV OF MICHIGAN ANN ARBOR on October 2, 2017 | http://pubs.acs.org Publication Date: July 1, 1997 | doi: 10.1021/bk-1997-0671.ch016

Interpretations of Contaminant Sources to San Pedro Shelf Sediments Using Molecular Markers and Principal Component Analysis 1

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Charles R.Phillips ,M. IndiraVenkatesan ,and Robert Bowen 1

Science Applications International Corporation, 10260 Campus Point Drive, San Diego, CA 92121 Institute of Geophysics and Planetary Physics, University of California, Los Angeles, CA 90024 Science Applications International Corporation, 165 Dean Knauss Drive, Narragansett, RI 02882 2

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The relative contributions of wastewater discharges and river runoff to measured contaminant concentrations in marine sediments on the San Pedro Shelf, California, were evaluated using molecular markers, principal component analysis (PCA) and soft independent modeling of class analogies (SIMCA). Distributions of sewage markers, linear alkylbenzenes (LABs) and coprostanol+epicoprostanol, were clearly influenced by the wastewater discharges. However, no corresponding patterns in concentra tions of chlorinated pesticides, polychlorinated biphenyls (PCBs), or polycyclic aromatic hydrocarbons (PAHs) were evident, with the exception of correlations between concentrations of parent plus alkyl-substituted naphthalenes and both summed LABs and coprostanol+ epicoprostanol. PCA results indicated three station groupings: (1) a wastewater discharge footprint that was associated with distributions of LABs, coprostanol, and naphthalenes; (2) nearshore stations potentially influenced by riverine inputs of petroleum hydrocarbons; and (3) a deep slope and canyon region possibly affected by regional contaminant and natural seep inputs and historical pesticide and hydrocarbon residues. SIMCA analyses did not indicate strong correspondences between chemical signatures for the sewage and river runoff end-members and those for the shelf and slope sediments. The absence of a better fit may be attributable to changes in abundances of sediment contaminants due to weathering or diagenesis, variability in hydrocarbon composition among end-member samples, and the greater relative importance of other, as yet unknown, contaminant sources. The southern San Pedro Shelf is adjacent to a highly urbanized area of Orange County in southern California that receives contaminant inputs from multiple sources, including 242

© 1997 American Chemical Society

Eganhouse; Molecular Markers in Environmental Geochemistry ACS Symposium Series; American Chemical Society: Washington, DC, 1997.

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Interpretations of Contaminant Sources

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approximately 10 L/day of treated wastewatersfromthe County Sanitation Districts of Orange County (CSDOC) ocean outfall. CSDOC routinely monitors the effects of their wastewater discharge. However, evaluations of source contributions have been difficult because the contaminant characteristics for many potential sources are similar, and the analytical methods used previously to analyze wastewaters and sediments are not particularly sensitive. Nevertheless, an understanding of the relative contributions of these sources to sediment contamination is important for wastewater management decisions. Molecular markers have previously been used to distinguish sewage-derived materials in marine sediments (1-6). Applications of molecular markers as tags are based on their enrichment in sewage compared to other source inputs, their strong affinity for particles (analogous to other anthropogenic contaminants), and their resistance to biological degradation (7). Multiple suites of markers have also been used to distinguish different contaminant input sources (8-10). Similarly, multivariate techniques for data analyses, including PCA, have been applied to evaluate spatial patterns in sediment metals (11, 12), petroleum hydrocarbons (e.g., 13 and references therein), and organic pollutants (e.g., 14, 15). PCA is a particularly effective tool for assessing spatial relationships in com positional patternsfromlarge and complex data sets. The objective of this study was to evaluate the relative contributions of wastewater discharges to concentrations of anthropogenic contaminants in sediments on the southern San Pedro Shelf. Organochlorine, saturated, and aromatic hydrocarbon concentrations, along with several molecular markers, including LABs, fecal sterols, and selected triterpanes and steranes, were quantified in wastewaters, grease particles (globules) from the outfall, and sediments from the Santa Ana River and Newport Bay (within the immediate drainage basin), as well as offshore sediments, using appropriately sensitive analytical methods. The molecular marker and contaminant data were analyzed using PCA and SIMCA as a descriptive and quantitative approach to improve our ability to resolve the multiple contaminant input sources to the southern San Pedro shelf. Study Area The study area is the southern portion of the San Pedro shelf, south of Los Angeles and Long Beach, and bounded by the Newport and San Gabriel submarine canyons that cross the shelf to the east and west of the CSDOC outfall (Figure 1). The narrow shelf consists primarily of soft substrate comprising relict sediments with sedimentary materials from storm runoff, coastal erosion, and aeolian sources (16, 17). Sediment grain size generally decreases with increasing water depth, grading from medium sands inshore tofinesands and clays at the upper slope (18). Sediment transport on the shelf is influenced by wavegenerated currents, primarily during winter storms (19). Nontidal currents in the bottom layers are northwesterly during most of the year. The CSDOC outfall terminates 8 kmfromshore with a multi-port diffuser at a depth of 60 m. Continuous discharge of treated wastewaters results in a suspended solids mass emission of 42,300 kg/day. Dischargesfromthe Santa Ana River are seasonally variable, but average 72 x 10 L/day, and represent average emissions of 200,000 kg/day of suspended solids and 5 g/day each of total DDTs and PCBs (20). Newport Bay is a small coastal embayment that receives urban, agricultural, and industrial wastes. Sediments 6


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within the bay historically have contained elevated concentrations of chlorinated pesticides, organotins, and metals (21). We are not aware of any information regarding export rates to the ocean of bay sediments or associated contaminants. Additional potential sources of contaminants to the region include discharges from commercial vessels, oil and gas production operations at offshore platforms, dredged material disposal operations at a site in Newport Canyon, historical dumping of DDT at sites within San Pedro Channel, and atmospheric deposition (21, 22).


Methods and Materials Sample Collection. Surficial sediments were collected from 27 locations on the San Pedro Shelf, including the San Gabriel and Newport submarine canyons, in depths from 20-500 m (Figure 1). Sediments were collected using a 0.1 m , Kynar-coated, Van-Veen grab sampler that was rinsed with filtered seawater, methanol, and hexane between successive grabs. Samples were removedfromthe surface 2 cm of undisturbed grabs using a Teflon-coated scoop with 2 cm-high sides that provided a guide for achieving a consistent sample thickness. Recent sediments were also collected at three locations within Newport Bay, using the Van-Veen grab, and at three locations near the mouth of the Santa Ana River using a hand-held scoop. Samples for determinations of organic contaminants and markers (approximately 500 g) were placed in pre-cleaned glass jars with Teflon-lined lids and frozen. Separate samples (approximately 10-20 g) taken for CHN (carbon, hydrogen, nitrogen) determinations were placed in precleaned 40 mL glass vials. Globules were obtainedfromsediment grab (Van Veen) samples collected near the terminus of the outfall diffuser in January 1995 following periods of high flow associated with stormwater runoff. Samples of the final wastewater effluent represented three 24hour composites collected over a nine-day period (October 1/2,4/5, 8/9, 1994). 2

Sample Analyses. Sediment, effluent, and globule samples were extracted, extracts were fractionated, and finalfractionswere purified according to procedures described previously by Venkatesan (23-25). Instrumentation used for identification and quantitation of target compounds are identified below. Detailed descriptions are provided elsewhere (ref 24, 25: sterols; ref. 23, 24: n-alkanes, terpanes, steranes, PAHs, PCBs, and chlorinated pesticides; ref 26: LABs). Saturated Fraction. Normal (C -C ) and branched alkanes were quantitated by gas chromatography (GC) with a flame ionization detector. Triterpanes (13 compounds) and steranes (16 compounds) were quantitated by gas chromatography/mass spectrometry (GC/MS) using extracted ion current profiles (m/z 191 and 217/218/245, respectively). Linear alkylbenzenes (Cj i-C .20 compounds) were quantitated by GC/MSfromextracted ion current profiles (26). Compound concentrations were corrected for losses during workup based on recoveries of a spiked LAB calibration standard solution. 12

36

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Aromatic Hydrocarbon Fraction. Aromatic hydrocarbonfractionswere analyzed by GC/MS in full scan mode, and the extracted ion current profiles were used for identifica tion and quantitation of PAHs (43 compounds). Samplefractionswere initially screened


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by comparison with a standard PAH mixture containing all of the target compounds. Ratios of response factors for the parent and alkylated homologs of naphthalene in the standard were used to extrapolate response factors for alkylated homologs of other PAHs. Final concentrations were corrected for matrix spike compound recoveries. Chlorinated pesticides (16 compounds including DDTs, hexachlorobenzene, aldrin, dieldrin, endrin, mirex, heptachlor, heptachlor epoxide, alpha-chlordane, trans-nonachlor, arid lindane) and PCBs (19 congeners) were quantitated on a dual column (DB-5 and DB-1701 connected with an effluent Y splitter) GC with an electron capture detector. Polar Fraction. Sterols (10 compounds including coprostanol, epicoprostanol, coprostanone, cholesterol, cholestanol, brassicasterol, campesterol, stigmasterol, Psitosterol, and dinosterol) were derivatized to silylethers, quantitated by GC, and confirmed by GC/MS. Carbon and Nitrogen Analyses. Separate sediment samples were analyzed for total carbon and nitrogen using a CHN analyzer. Organic carbon was determined by acidifying sample aliquots, to remove inorganic carbon, and reanalyzing the sample. Quality Assurance Summary. Procedure blanks, matrix spikes, and reference materials (where available) were analyzed with each batch of samples. Target analytes were not detected in procedure blanks, with the exceptions of concentrations near the respective limits of quantitation of a single PCB congener and 2,4-DDE in one or two blanks. Measured concentrations of 15 PCB congeners in a reference material (National Institute of Standards and Technology, SRM #1941) were within 86-161% of certified values, and coefficients of variation (n=4) werefrom6-30%. Concentrations of four of six chlorinated pesticides in SRM #1941 were 72-119% of the certified values. Higher values for two other pesticides, dieldrin and heptachlor epoxide, were likely due to matrix interferences. Coefficients of variation for replicate measurements (n=4) of individual pesticides in the SRM ranged from 6-34%. Concentrations of 18 PAHs in SRM #1941 were within 58-129% of certified values, and coefficients of variation (n=4) were 5-56%, although concentrations of all but four compounds were within 80-110% of certified values and coefficients of variation for all but five compounds were < 20%. Measured carbon concentrations in SRM #1572 were 99-100% of the certified values. No certified reference materials are available for sterols, LABs, terpanes, or steranes. Analytical accuracy of sterol determinations was evaluated from matrix spike recoveries. Mean recoveries of individual sterols ranged from 72-99%, with coefficients of variation for replicate measurements (n=4) < 10%. Matrix spike recovery was not assessed for terpanes and sterenes because no highly concentrated standard spike solution was available. Data Analysis. Principal component and SIMCA analysis of the compound concentration data for source and sediment samples was performed using SIRIUS software (Pattern Recognition Systems, A/P Breton, Norway). Multiple PCA runs were performed using different subsets (classes) of compounds. Variables used for the two PCA classes described here are defined in Table I. The original data set contained a total of 181 analytes. Initial analyses of these data showed that a large number of compounds (e.g.,



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steranes and triterpanes) had little variability among sediment stations and/or covaried within their compound class. Because these would provide little additional information above that found in the class, they were removedfromthe working data set. Other selected compounds were summed into composite variables as shown in Table I. While the preselection of compounds used for this PCA could have a significant effect, care was taken in the selection of compounds and cojnpound classes to avoid biasing the results. Concentrations of compounds, and compound classes, within the group of sediment samples, effluents and globule samples varied over a large range. Because the PCA technique is a least squares method, samples with higher concentrations will significantly influence the results. To prevent this, each sample was normalized using a technique called mid-range normalization. This method has the advantage of eliminating spurious correlations due to the effects of closure (27). Analyte concentration data were logtransformed and then standardized to unit variance by subtracting the mean and dividing by the standard deviation (28, 29). This allows each of the variables to contribute evenly in the PCA (30). Additional composite variables for petroleum hydrocarbons, sterols, and LABs were evaluated as source and degradation indicators. These included summed C - C nalkanes (£Alk), ratios of odd to even n-alkanes within the C - C range (odd:even), and summed C - C alkanes (lower molecular weight alkanes), as described by Steinhauer and Boehm (57) and Tissot and Welte (32). Also, ratios of external (6-C + 5-C ) to internal (4-C + 3-C + 2-C ) phenyldodecane isomers (I/E) were evaluated as an indicator of LAB degradation (33). 1 0

15

12

3 6

34

19

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12

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Table I. Variables Used for PCA Analyses, Classes 0 and SS Alkanes: n-Ci , n-C , n-C , n-C , n-C ; pristane (pris); phytane (phyt). 2

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18

31

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PAHs: summed (C -C ) naphthalenes (Naph); summed (C -C ) fluorenes (Fluo); summed (C -C ) phenanthrene/anthracene (Phen); summed (C -C ) dibenzothiophenes (DBT); sum of fluoranthene, pyrene, benzo(a)anthracene, chrysene, benzo(b+k) fluoranthenes, benzo(a)pyrene, benzo(e)pyrene, and perylene (PAH45); sum of 43 PAHs, including alkylated homologs (Tpah). 0

0

4

0

4

3

0

3

LABs: total C - L A B s (LABI 1); total C -LABs (LAB 12); total C -LABs (LAB 13); total C -LABs (LAB 14); total LABs (TotLAB). n

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13

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PCBs: sum of 19 PCB congeners (totPCB); sum of PCB congeners # 77, 105, 118, and 126 (coplPCB). Pesticides: sum of 2,4'- and 4,4'- isomers of DDT, DDD, and DDE (totDDT); sum of 16 pesticides, including DDTs (totpest); hexachlorobenzene (HCB);achlordane (alpha-ch). Sterols: coprostanol (Coprnol); epicoprostanol (Epicopr); coprostanone (Coprone); dinosterol (Dinoster).


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Following PCA, a SIMCA analysis was performed to partition the relative contributions from source classes to the chemical signatures of individual stations. SIMCA is a technique of classification by means of disjoint cross-validated principal component models (34). Sediment samples were assigned to one of three classes based upon their geographical associations and results of the preliminary PCA: class SR consisted of river/bay stations 128-133 and all other stations were grouped as class SO. Effluent samples were assigned to class EF. These classes were standardized, and a PCA was performed on each. The method of cross validation was employed to indicate a stopping point in the accumulation of components. The class of sediment samples, SO, was fit to each of these 'source classes', SR and EF, and a measure of the class membership was obtained for the fit of each sample in class SO to each of the two source classes. Results and Discussion Chemical Composition of Source Materials: Effluent and Globules. Concentrations of LABs and fecal sterols in CSDOC effluent and globules (Table II) were comparable to Table II. Concentrations of Organic Contaminants and Sewage Markers in Source Materials: Effluent, Globules, and Santa Ana River and Newport Bay Sediments. Effluent concentrations normalized to average suspended solids concentrations are shown in parentheses.

Effluent (ug/L; n = 3)

£DDT

£PCB

£AIk

0.017 ± 0.004

0.079 ± 0.009

25 ± 4 . 6

(1.4 - 1.8)

(Effluent, ug/g) (0.25 - 0.48)

£

£LAB

Cop+ Ecop

2.0 ± 0 . 1

8.2 ± 1.8

270 ± 28

(400 - 610)

(40 - 45)

(150-230)

(4800 6200)

P

A

H

Globules (ug/g, n = 3)

0.53 ± 0.26

10 ± 3 . 7

860 ± 240

870 ± 230

29 ± 9.6

990 ± 330

Newport Bay (ug/g; n = 3)

0.040 ± 0.036

0.022 ± 0.012

2.4 ± 1.4

1.8 ± 0.89

0.018 ± 0.012

0.56 ± 0.43.

Santa Ana R. (ug/g; n=3)

0.006± 0.002

0.010± 0.002

5.0 ± 5 . 8

1.7=4= 1.8

0.010± 0.007

0.17± 0.15

those reported previously in other Southern California wastewater and sludge matrices (7, 6, 7, 35). £LABs in effluent, normalized to average effluent solids concentrations (47 mg/L) and expressed on a dry weight basis (mean: 175 pg/g; range: 150-230 pg/g), were severalfold higher than those in globules (mean: 28.9 pg/g; range: 15.5-37.6 pg/g). Coprostanol concentrations (227-295 //g/L) represented 50-53% of the total sterols (i.e.,


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summed concentration of 10 compounds), whereas epicoprostanol was not detected in the effluent. Coprostanol+epicoprostanol (638-1435 Mg/g) were 59-63% of the total sterol concentration in globules. The relative abundances of individual saturated and aromatic hydrocarbons in the wastewater effluent and globules were generally similar and characteristic of petroleumderived materials, as indicated by: (1) homologous series of normal alkanes with low odd:even-carbon ratios (-1.2) and high proportions (34-37%) of the n-C - n-C to £Alk; (2) parent plus C through C -substituted naphthalenes comprised a large proportion (68-74%) of the ]TPAH concentration; and (3) abundances of alkylated homologs typically exceeded those of the parent PAH compounds (Figure 2). Similar hydrocarbon compositions were reported for effluents from the Los Angeles County Sanitation Districts (35, 36) and San Diego (Point Loma) Treatment Plant (57). Concentrations of individual and summed chlorinated hydrocarbons in the effluent were low (

Interpretations of Contaminant Sources to San Pedro Shelf Sediments

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