Environ. Scl. Technol. 19Q2,26, 2240-2251
Spatial and Temporal Variance of Hydrocarbon Pollution Data in a Coastal River- Influenced Sedimentary System Joan 0. Grimalt"
Department of Environmental Chemistry (CID-CSIC), Jordi Glrona, 18, 08034-Barcelona, Catalonia, Spain Lourdes Canton and Begoiia Alonso
Department of Applied Chemistry, College of Chemistry, University of the Basque Country, P.O. Box 1072, 20080-Donostla, Basque Country, Spain The statistical significance of the coastal pollution mapping studies based on the sedimentary composition of aliphatic, chlorinated, and aromatic hydrocarbons has been evaluated from the replicate sampling (four research vessel cruises) and analysis of six coastline perpendicular transects, each situated in front of a river mouth. The analysis of variance has shown that this type of sediment network affords the recognition of the main coastal pollution discharge sites at the l % confidence level, but it is not useful for tracing their area of influence. In addition, qualitative and quantitative changes in polychlorinated biphenyl composition (also significant at the 1% confidence level) have shown that the concentrations of coastal sedimentary hydrocarbons are not in steady state. All hydrocarbons studied are lognormally distributed, which parallels the grain-size composition of the sedimentary matrices and is consistent with a close association between these hydrophobic compounds and water-suspended particles. Introduction The land-to-sea transfer of organic pollutants is a major topic in environmental marine chemistry that still has many fundamental aspects to be elucidated (1). The study of coastal and open sea sediments has often provided important clues for a better understanding of budget, transport routes, and biogeochemical cycles (2-4). The sediments afford an integrated picture of the hydrophobic pollutants arriving at the water column (5),and their trace organic composition is more constant than in other environmental compartments such as air and water, or even organisms. Many of the conclusions resulting from these studies are based on theoretical models (6, 7),laboratory experiments (8), or observations in well-controlled aquatic environments such as some lakes (9). However, the trace organic composition of the marine sediments depends on numerous physical (10,10,chemical (12), and biological (13) processes that are particularly important in the river-marine exchange systems of coastal areas. These processes tend to modify the sedimentary composition in different ways, generally increasing the dispersion of concentrations of the organic pollutants. Their combined effects are difficult to model and should be evaluated in the context of the spatial and temporal distributions of the organic pollutants selected for study. In principle, any realistic interpretation of these distributions should avoid predetermined assumptions and find statistical probability functions corresponding to the concentrations of the compounds in the area of study. The experimental errors associated with sampling, handling, and analysis should also be considered. These goals require the study of the random variation by replicate research vessel (R/V) cruise collection and repeated measurement of the trace organic pollutant concentrations in the sedi2240 Envlron. Sci. Technol., Vol. 26, No. 11, 1992
ment network (14). Unfortunately, this approach has not been undertaken to date, probably due to the high cost and manpower requirements involved. The work presented here encompasses a variance and probability distribution study on the sedimentary composition of aliphatic, chlorinated, and aromatic hydrocarbons in a coastal environment from Biscay Bay (Guipuzcoan Coast, Basque Country, Spain). This coastal section receives the discharges of six rivers, Deba, Urola, Urumea, Oyarzun, Oria, and Bidasoa (see Figure l), that drain a heavily industrialized and urbanized area. The sedimentary hydrocarbon composition in the open sea sediments results from the combined effect of the contributions from these rivers and the waves, tides, and currents in the open marine system. The study has encompassed the repeated R/V sampling (four cruises in July 1986, November 1986, February 1987, and May 1987) of six coastline perpendicular transects, each located in front of the discharge sites of one of the rivers. This sampling and analytical scheme has afforded the evaluation of the hydrocarbon pollution data in terms of the statistical confidence levels corresponding to sedimentary concentration steadiness and river-related spatial distribution trends. Experimental Section Materials. Pestipur-grade n-hexane and methanol were purchased from SDS (Peypin, France). Resi-analyzedgrade dichloromethane was from Baker (Phillipsburg, NJ). Analytical reagent-grade acetone was from Carlo Erba (Milan, Italy). Analytical reagent-grade hydrochloric acid (25%), neutral silica gel (Kieselgel40,70-230 mesh), alumina (aluminum oxide 90% active, 70-230 mesh), and copper were from Merck (Darmstadt, F.R.G.). Potassium hydroxide was purchased from Fluka Chemie (Buchs, Switzerland). Soxhlet thimbles were from Schleicher and Schuell (Kassel, F.R.G.). The potassium hydroxide was cleaned by sonication in dichloromethane. The silica gel, the alumina, and the Soxhlet thimbles were extracted with dichloromethanemethanol (2:1, v/v) in a Soxhlet apparatus for 24 h. After solvent evaporation, the silica and the alumina were heated for 12 h at 120 and 350 "C, respectively. A total of 5 % (w/w) Milli-Q-grade water was then added to the chromatographic adsorbents for deactivation. Copper was activated with two rinses of 10% (w/w) hydrochloric acid (5 min each) and prepared for sample desulfurization by a series of successive rinses using Milli-Q-grade water, acetone, and n-hexane (two rinses with each). All organic solvents were distilled on a 1-m packed column (Rashig) equivalent to 12 theoretical plates, with a reflux ratio of 12:l. The purity of the solvents was checked by concentrating, under vacuum, 100 mE of solvent to 10 p L for gas chromatographic (GC) analysis. Blank requirements were as follows: splitless injection of
0013-936X/92/0926-2240$03.00/0
0 1992 American Chemical Society
I Flgure 1. Map of the Guipuzcoan Coast showing the sltes sampled In each river transect.
2.5 pL should result in chromatograms with no unresolved GC envelope and with very few peaks, representing up to 1ng in terms of their flame ionization detector response. This threshold, under the above dilution factor, is equivalent to 0.08 ng/g when referred to 30 g of sediment. Sampling Extraction and Fractionation. Surface sediments were taken by gravity coring from the R / V Elorrio and stored at -20 OC in the dark. The upper 3 cm was cut prior to analysis and Soxhlet extracted with 150 mL of (2:l) dichloromethane-methanol for 36 h. The extract was vacuum evaporated to 2 mL and hydrolyzed overnight with 35 mL of 6% KOH-MeOH. The neutral fraction was recovered with n-hexane (3 X 30 mL) and desulfurized with activated copper. The volume of this fraction was again vacuum evaporated to 0.5 mL and fractionated by column chromatography according to previously established methods (15). A column filled with 8 g of both 5% water-deactivated alumina (70-230 mesh, Merck) (top) and silica (70-230 mesh, Merck) (bottom) was used. The followingfractions were collected (Numbers and letters in bold-face type throughout the paper refer to the compounds listed in Table 111.): (I) 20 mL of n-hexane (aliphatic hydrocarbons, 1-25 and a-d), (11)20 mL of 10% dichloromethane in n-hexane (chlorinated biphenyls, 26-75 and e-m), and (111) 40 mL of 20% dichloromethane in n-hexane [polycyclic aromatic hydrocarbons (PAHs), 76-1 023.
Instrumental Analysis. The samples were analyzed by gas chromatography with two instruments, a PerkinElmer Model 8310 and a Hewlett-Packard Model 5890A, equipped with flame ionization (FID)and electron capture detection (ECD), respectively. These instruments were also provided with split/splitless injection. In both cases, the separation was carried out on a 30 m X 0.32 mm i.d. SPB-6 (film thickness, 0.25 pm) fused-silica capillary column (Supelco, Bellefonte, PA). Injections were made in the splitless mode (split valve closed for 48 s; hot needle technique) with the column held at 60 OC and then heated to 300 OC at 6 OC/min. The carrier gas was hydrogen (0.5 m/s linear velocity). The injector and detector were maintained at 300 and 330 OC, respectively. Nitrogen was used as make-up gas (30 mL/min). Selected samples were analyzed by gas chromatography coupled to mass spectrometry (GC-MS) using a Hew-
lett-Packard Model 5995 instrument coupled with an HP-300 data system. Mass spectrometer temperatures were as follows: transfer line, 300 "C;ion source, 200 "C; analyzer, 230 "C. Data were acquired in the electron impact mode (70 eV), scanning from 50 to 650 mass units at 1 s/decade. Helium was the carrier gas, and the other chromatographic conditions were the same as described above. Alternatively, some samples were analyzed by GC-MS using a Hewlett-Packard Model 5998A instrument coupled with an HP-300 data system. Negative ions were recorded in the chemical ionization mode (reagent gas, methane, 1.5 Torr). Mass spectrometer temperatures were as follows: transfer line, 300 "C; ion source, 150 OC; analyzer, 130 OC. Scan mode and chromatographic conditions were the same as described for the previous GC-MS analyses. Identification and Quantitation. Compound identification was performed by GC-MS and coinjection with authentic standards. Quantitation was performed with the following external standard mixtures: fraction I, n-tetradecane, n-docosane, n-dotriacontane, and n-hexatriacontane; fraction 11,polychlorinated biphenyl (PCB) congeners 28,52, 101, 138, 153, and 180; fraction 111, phenanthrene, anthracene, fluoranthene, benz[a]anthraceae, benzo[a]pyrene, perylene, indeno[ 1,2,3-cd]pyrene, benzo[ghi]perylene, dibenz[a,h]anthracene, and coronene. In all cases, the peaks of the sample chromatograms were quantitated by reference to the response factor of the standard compound eluting at the closest retention time. Negative ion chemical ionization mass spectrometry (GCMS-NICI) was used to confirm the identity of the PCB congeners, and their areas were modified according to previously determined ECD response factors (26). This method was validated by analysis of a BCR-CEC certified reference sewage sludge (17). The unresolved complex mixtures (UCM) of the aliphatic and aromatic fractions were integrated with a digital planimeter connected to a Hewlett-Packard 86 microprocessor and quantitated according to the average response factors of the components present in the corresponding external standard. This method was validated in a previous intercalibration study (18).Samples and standards were repeatedly injected until less than 3-5% dispersion in the area measurements was obtained. The samples of the latter cruises were quantiEnvlron. Scl. Technol., Vol. 26, No. 11, 1992 2241
Table I. General Characteristics of the Rivers Considered in This Study main channel catchment av flow (km) area (km2) (m3/s)
river Deba Urola Oria
53.9 55.0 65.9
531 343 861
13.4 8.5 26.3
Urumea
39.5
266
11.1
Oyarzun
15.4
74
3.1
Bidasoa
66.5
830
24.7
main anthropogenic inputs metal industry low inputs urban, paper mill industry urban, paper and electrochemical industries paper mill industry; harbor activity urban
tated together with some sediments collected in July 1986 which were used as cross-calibration standards. Software. All the calculations presented in this study were performed using laboratory-made Fortran 77 routines dedicated to the handling and calculation of large-dimension data sets. The programs were run in an H P 900/835 minicomputer with HP-UNIX as the operating system.
Results and Discussion Area of Study and Sampling Sites. Table I lists the main hydrological features of the rivers considered in this study. A short summary of the major anthropogenic sources is also given. In general terms, these rivers constitute moderate-to-small water flows which, with the exception of the Urola River, receive a high pollution load. Kraft paper mill effluents represent a major source of organic materials for the Oria, Urumea, and Oyarzun rivers (19). These inputs are particularly important in the Oyarzun River, which also receives a significant portion of the industrial effluents generated in the Urumea basin. Metal discharges make up the other major group of industrial contributions (20,21). These are very important
in the Deba River and, to a smaller degree, in the Oria and Urola rivers. The Urumea River also receives significant loads of mercury and phenols (21)from chemical industries situated on the river shores. Urban contributions are important in the Bidasoa, Oyarzun, Urumea, and Oria rivers. Harbor activities are significant in the Bidasoa, Oyarzun, and Oria rivers. The sampling sites were located along transects situated in front of the mouths of these six rivers (Figure 1). The sediments corresponding to the Oria and Bidasoa transects were situated at water depth levels of 10, 20, and 50 m. This sampling spacing was not adequate in the case of the Urumea and Oyarzun rivers because of the steep inclination of the continental slope. Therefore, the collection sites in the Urumea River were at lo-, 30-, and 50-mwater depths, and only two water depth levels, 25 and 50 m, were sampled in Oyarzun transect. The samples corresponding to the Deba and Urola transects were collected at shallower water depth scales of 10, 25, and 40 m and 7,10, and 15 m, respectively, because in these two cases river influence was expected to be small in the 50-m water depth sediments. Sediment Lithology. The average particle size composition of the marine sediments considered for study is shown in Table 11. The Urola, Oria, and Oyarzun transects exhibit a continuous particle distribution gradient from less to more fine materials as the water depth increases, that is, as the fluvial inertia and the wave energy diminishes (22). The Bidasoa and Urumea transects show the opposite trend, with a coarser grain-size lithology in the sediments located at water depths of 50 m. These two rivers have a meandering course near the mouth which enhances the sedimentation of a significant proportion of the finer grain-size materials near the coast. Finally, the deepest sediments of the Deba River outflow contain a significant amount of shell residues, which again corresponds to an increase in coarser materials. As currently observed (23-25),the grain-size composition of these Sediments is log-normally distributed.
Table 11. Average Particle Size of the Marine Sediments Collected in the Guipuzcoan Coast depth (m)
2-1 mm
1-0.5 mm 4.0 (2.5) 3.0 (2.5) 54 (3.1)
size fractions, % 0.25-0.125 mm 0.5-0.25 mm
Deba River 22 (8.5) 21 (14) 23 (6.8)
10
1.2" (0.77)*
20 40
1.5 (0.73) 1.8 (0.83)
2.3 (1.6) 1.3 (0.23) 21 (3.0)
7
0.99 (1.2)
1.1 (0.39)
10
1.2 (1.0)
15
2.1 (0.73)
1.6 (0.70) 1.5 (0.59)
Urola River 6.8 (0.33) 40 (1.5) 2.6 (0.54) 20 (1.9) 7.5 (2.0) 41 (1.9)
10
20 50
0.45 (0.37) 0.64 (0.33) 0.40 (0.28)
0.46 (0.33) 0.65 (0.53) 0.37 (0.08)
Oria River 0.38 (0.34) 5.2 (5.9) 0.84 (0.51) 0.39 (0.38) 61-29 (0.38) 0.38 (0.53)
10
1.0 (0.42)
30 50
4.1 (0.72) 19 (18)
25 50
6.8 (4.3) 1.6 (0.53)
5.9 (2.9) 0.87 (0.47)
10
1.0 (0.88) 2.0 (1.2)
0.71 (0.63) 3.8 (3.3) 16 (6.0)
20 50 a
>2 mm
25 (38)
1.7 (0.38) 19 (6.6) 29 (17)
Mean. *Standard Deviation.
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Urumea River 3.9 (1.2) 23 (3.8) 51 (9.0) 20 (3.1) 30 (11) 20 (23) Oyarzun River 37 (7.5) 1.6 (0.72) 9.0 (3.2)
0.125-0.063 mm
