Background heavy metal levels in estuarine ...

The Scienceof the Total Environment 172(199.5)175-188

ELSEVIER

Background heavy metal levels in estuarine sediments and organisms in Galicia (northwest Spain) as determined by modal analysis Emilio Carral” , Xoh Area de Ecoloxia,

Fact. de Bioloxfa,

Puente, Rub&n Villares, Alejo Carballeira Unv. de Santiago

de Compostela,

15706 Santiago

de Compostela,

Spain

Received 8 August 1994;accepted26 January 1995

Abstract We investigated metal (Al, Fe, Mn, Co, Cr, Cu, Ni, Zn and Pb) concentrations in surface sediments (107 samples) and intertidal organisms (424 samples of macroalgae, phanerogams, molluscs and polychaetes) from 44 estuarine areas in Galicia (northwest Spain). Three acid extraction procedures (HCI, HNO, and HNO, + HF) were used. Following analysis of the effect of sediment particle size distribution on metal contents, Al content was selected as a normalization element. For most species and most metals, there was only minor contamination of the organism samples by particulate matter, confirming the efficiency of the washing and depuration procedures used and thus obviating the need to correct for such contamination on the basis of Fe contents. Background metal levels in the sediments and organisms were estimated by modal analysis. To the best of our knowledge, this is the first time that this method has been used for this purpose. Keywords: Estuarine sediments; Modal analysis; Intertidal distribution

1. Introduction

Metals occur naturally in the environment and are widely distributed, as free ions or forming part of complexes or compounds (Fiirstner and Wittman, 1981; Wedepohl, 1991). In much of the

* Corresponding author.

organisms; Acid extraction procedures; Particle size

developed world, however, industrial activity has led to environmental metal concentrations which - with the exception of Fe and Hg - are lOO-lOOO-fold higher than in the Earth’s crust (Wedepohl, 1991). Locally, living organisms may be exposed (via feeding, gas exchange or simple contact) to very much higher levels. Clearly an accurate evaluation of the degree of metal contamination at a given location requires an estima-

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tion of natural (background) levels in the physical environment and in the biota (Bryan et al., 198.5; Carpenter et al., 1991; Wedepohl, 1991). In the present study, we have investigated metal levels in intertidal sediments and organisms (macroalgae, phanerogams, bivalve molluscs and polychaetes) in the estuaries of Galicia (northwest Spain). Estuaries are particularly suitable sites for the evaluation of littoral contamination, for a number of reasons. Throughout history, estuaries have tended to be favoured sites for human settlement and associated industrial activity, and have characteristically received heavy contaminant inputs. Estuarine sediments show a strong tendency to accumulate contaminants, especially heavy metals, and analysis of these sediments thus constitutes a rapid means of obtaining timeintegrated information concerning a range of limnological variables (Larsen and Jensen, 1989; Ev-

Fig. 1. Estuarine

sampling

eraarts and Fisher, 1992). In addition, estuaries often constitute wetland sites of international ecological importance; in Galicia, for example, five Rias are included under the RAh4SAR convention, estuaries are also economically very important for shellfish production. 2. Materials

and methods

2.1. Study area and sedimentsampling

Sediments and organisms were sampled from a total of 44 estuarine sites in Galicia (northwest Spain; Fig. 1). A total of 107 top-l-cm intertidal sediment samples were collected in the summer of 1990. Samples were obtained with a plastic spatula, transported to the laboratory at 4°C and frozen until analysis (Robbe, 1981). The number of samples were determined using Hikanson criteria for lakes, i.e. using the area

sites in Galicia

(NW Spain).

E. Carral

et al. / The Science of the Total Environment

and coastline extension of the studied system (Hakanson, 1984). Because the complexity of estuaries is greater than lakes, especially as regards variability in metal content, in a previous study of the Ria of Ribadeo (Carballeira et al., 1991) and that of Bros and Cowell (1987) standard error/sample number relationships were used to established the representative number of samples. Minimum sample number is reached when the error standard is small (curve becomes plane). For the Ribadeo estuary, the results indicated that double the number of samples were required (8 samples instead 4). A minimum number of four

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samples were obtained by Hakanson method (Fig. 2). Pb, Cu, Mn and Cr present the maximum and minimum coefficient of variation (%) for sediment metal concentration, respectively. The homogeneity of the sediment samples (terrestrial versus marine contribution) was also controlled: first, the selection of the sample stations was always in the inner part of the estuary where the deposition processes predominate, and where the finest sediment particles are the major component; second, by examining the C/N relation distribution - 94% of the samples belong to a population with a C/N = 11 + 5. Only 6%

Pb (c.v.=33%)

Cu (c.v.=26%)

Mn (c.v.=ll%)

Cr (c.v.=lO%)

16 Standard

Error

Sample

number

Fig. 2. Minimum sample number calculated by standard error/sample number ratio application (Bras and Cowell, 1987). The number of samples are selected when the curve becomes plane. Vertical lines indicate the sample number estimated by Hakanson method. C.V.%, maximun and minimun values for metal concentrations (Pb, Cu, Mn and Cr respectively) in intertidal sediments of Ria of Ribadeo (HF + HNO, extraction).

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belong to a sub-population characterized by C/N = 2 f 0.5, indicating an oceanic influence (Gomez-Parra et al., 1984; Matson and Brison, 1990) (Fig. 3). The sub-populations were determined by modal analysis (Section 3). Previous studies confirm a terrestrial origin of the sediment in the inner part of the Rias, using gibbsite as an indicator of continental sediment (Macias and Calvo, 1988). 2.2. Physico-chemical characteristics of sediments

When comparing metal contents in different sediment samples, one of the chief problems is that their contents may be affected by various sediment characteristics, notably redox conditions and particle size (Shimmield and Pedersen, 1990; Jackson et al., 1993). Factors of this type also have a major influence on the availability of metals to epibenthic organisms, most of which feed in, or on the surface layer of the sediment (Thomson et al., 1980). Accurate on-site determination of pH in the surface layer of the sediment is extremely difficult. We therefore determined pH in the laboratory as described by Guitiin and Carballas (1976); Schalscha et al. (1981) has reported that the pH in water of dried sediment samples is only slightly lower than the pH determined in the field. The coefficient of variation in pH for the 107 sediment samples indicates considerable homogeneity in this parameter (Table 1). Eh is even more

C/N

Frequency

0 I

2 population

1

11 population

Atomic

ratio

2

Fig. 3. Modal analysis results for C/N ratio in sediments. A major sub-population is characterized by C/N = 11.

Table 1 Mean, range and coefficient of variation (CV) of pH in the 107 sediment samples PH Mean

Range

cv (%o)

7.8

6.1-8.8

6.7

difficult to determine in the field than pH; in situ measurement, i.e. insertion into an undisturbed sediment layer to a depth of 1 cm in order to obtain a stable measurement value, is very difficult. From the characteristics of the Galicia estuary system (large tidal range and reworked sediment surface for shellfish production), in all cases, we can assume an oxic surface sediment layer, yellow-brown (pale brown) colour. Intertidal sediments are also characterized by a non-calcareous composition in the inner part of the Galicia estuaries (2-5% carbonates, Rodriguez et al., 1987), and the watershed lithology comprises granitic-schists, predominantly granitic. In the future the possible influence of watershed lithology on heavy metal background levels will be evaluated. 2.3. Sediment analysis

The < 63-pm fraction was obtained by wet sieving through a nylon mesh, using water from the sampling site (previously filtered through a 0.45pm filter) in order to minimize the loss of metals by desorption (Robbe, 1981). Three extraction procedures were used: (a) with HCl, (b) with HNO, and (c) with HNO, and HF. Parallel extractions proved more efficient than sequential extractions (Roger, 1986; Young et al., 1992). Extraction with HCl provides an estimate of the amount of labile metal (and some derived from minerals which disolve), i.e. metal weakly bound to the sediment and thus more readily available to the biota (Luoma and Bryan, 1981; Tessier and Campbell, 1984). Twenty ml of 1 N HCI (Merck Suprapur) was added to 2 ml (equivalent to 0.5 g dry wt.) of sieved sediment, and the mixture was maintained at room temperature with mechanical shaking for 2 h (Bryan et al., 1985;

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Louzidou et al., 1992). The extract was centrifuged and the metal contents were determined in the supernatant by atomic absorption spectrophotometry (AAS; Perkin-Elmer 2100). The dry weight of 2 m 1 o f sieved wet sediment was determined from two aliquots following correction for the salt content of the water used in sieving. Extraction with HNO, (for some metals), or with a mixture of HNO, and HF, provides an estimate of the total metal content in the sample. The more complex HNO, + HF procedure is necessary in order to ensure complete solution of Al (important since Al content is used as a standardization factor in the subsequent analysis). This mixture has also been shown to be effective in breaking down organic matter and siliceous material (Agemian and Chau, 1975; Thomson et al., 1980). Prior to extraction, the sample was finely ground in an agate mortar (until total disgregation) to ensure maximum contact with the extractant, as recommended by Nadkarni (1984). Ten ml of HNO, (Merck Suprapur), or 15 ml of a 2:l mixture of HNO, and HCl (both Merck Suprapur), was then added to 0.5 g of oven-dried ground sediment in a 120-ml Teflon bomb, and the mixture was heated in a 700-W microwave oven (Thomson M450S). In the case of the HNO, + HF extraction, the mixture was then treated with boric acid (Bernas, 1968), which contributes to signal stabilization in AAS (Hsu and Locke, 1983) and permits the use of glassware without a risk of contamination. The extract (HNO, or HNO, + HF) was then centrifuged, and the supernatant stored in plastic containers until analysis by AAS as for the HCI extraction (Agemian and Chau, 1975). The efficiencies of the two extraction processes (HNO, and HNO, + HF) were investigated by parallel analysis of a certified reference material (marine sediment MESS-l) of similar characteristics to the sediment studied. 2.4. Sampling of organisms

With the aim of investigating metal levels in the sediment, available in solution and in particle-associated form, the following species (all re-

ported to be suitable as indicators of metals) were selected. Plants: Fucus ceranoides, Fucus spiralis, Ascophyllum nodosum, Ulva sp., Enteromorpha sp. and Zostera noltii. Animals: Cerastodemza edub, Scrobicularia plana, Mytilus galloprovincialis, Nereis diversicolor (Phillips, 1980; Bryan et al., 1985; Lyngby and Brix, 1987; Barreiro,

1991).

Samples (25-30 individuals of each species present) were collected from the 107 sampling sites in the summer of 1990 during the period of maximum mussel growth prior to autumn spawning (September-October) (Andreu, 1989; Aguirre, 1989). To minimize variability due to differences in age or life-cycle stage, care was taken to ensure that the individuals sampled were of a similar size and from similar vertical positions in the intertidal zone. Samples were washed immediately with water from the site and transported to the laboratory at 4°C. Before analysis, plant samples were washed exhaustively with distilled water, taking care not to damage tissues, in order to remove any adhering sediment and epiphytes. Old and damaged tissues were discarded. Macroalgal apices (distal 1 cm) and thalli were analysed separately, since metal concentrations in macroalgae have been reported to vary with tissue age (Bryan and Hummerstone, 1973; Soderlund et al., 1988; Barreiro, 1991). All animals underwent depuration for 5-7 days in filtered seawater (27%~) from the sampling sites (molluscs) or in milled HNO,washed sand under seawater (polychaetes) in a closed-circuit tank with an activated charcoal filter. For analysis, soft-tissue (molluscs), wholeorganism (Zostera, polychaetes) or apex or thallus (macroalgae) samples were homogenized (Polytron PT 10-35, 750 W, 50 Hz) and the homogenate was dried at 50°C and stored in plastic bags until extraction. For extraction, 0.5 g of oven-dried sample was digested with 10 ml of 65% HNO, in a microwave oven, and analysis was by AAS as described above for the sediments. The efficiency of the extraction of each metal (previously reported to be high; Barreiro, 1991)

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was confirmed by parallel analysis of certified reference material (Rynchostegium riparioides BCR6 and Mytilus edulis CRMl).

172 (1995) 175-188

dence on particle size. The correlation coefficients are low and can be attributed to; (a) the fact that only the < 63-pm fraction has been studied for metal concentration and (b) the fact that the samples were taken from both clean and contaminated areas (Voutsinou-Taliadouri and Varnavas, 1987). When particle size effect is corrected by normalisation metal content/Al content (metal/Al), there are no significant correlations with proportions by weight in the < 20-pm or < 2-pm fractions (Table 31, indicating that, for our data, Al content is suitable for use as a standardization factor. Other authors (e.g. Loring, 1990) have recommended the use of Li content for standardization on the grounds that: (a) Li content is often more closely correlated with that of other metals than Al content, and (b) the relationships between Al and other metals may be obscured by the presence of feldspars, which have high Al contents and low contents of other metals (Luoma, 1990; Loring, 1991). However, Buckley and Cranston (1990) found no significant correlation between feldspar content and either Al or Li contents in sediments (r = - 0.16 and -0.58, respectively). In addition, the feldspar content of Galician sediments very rarely exceed 30% (Macias, 1986), which is much less than the 60% reported as being potentially problematic by Loring (1991).

2.5. Data analysis

Background levels in the sediments and organisms were estimated by modal analysis (as contained in the program NORMSEP; Tomlinson, 19711, which allows identification of discrete Gaussian sub-populations within a data set, centred around a modal value (Section 3). 3. Results and discussion The influence of particle size on metal contents in sediment can be partially corrected for by analysing the same particle size class for all samples. However, between-sample variation in particle size distribution within the selected class may still have significant effects on metal contents; a number of authors (Akerman, 1980; Luoma, 1990) consider it necessary to use a standardization factor (for example, Al or Cs content) to correct for these effects. In the < 63-pm fraction of our sediment samples, some metal contents (Al, Co, Ni and Cr> are significantly correlated with the proportion by weight in both the < 20-pm fraction and the < 2-pm fraction (Table 2), indicating a depen-

Table 2 Spearman rank correlations between metal contents (HNO, + HF extraction) in the < 63-pm fraction of the sediments, and the percentage of that content contained in the < 20+m or < Z-wm fraction of the same sample Al

Fe

Mn

co

Pb

Ni

Zn

CU

Cr

Al Fe Mn co Pb Ni Zn CU Cr

1

NS 1

NS 0.74 1

0.55 0.57 0.49 1

0.59 NS - 0.25* 0.21* 1

0.19% 0.54 0.52 0.70 NS 1

0.50 0.23* NS 0.29 0.71 NS 1

0.42 0.35 NS 0.38 0.66 0.31 0.85 1

NS 0.66 0.46 0.37 - 0.27 0.66 NS 0.22* 1

< 20