Ecotoxicology and Environmental Safety 110 (2014) 49–55

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Evaluation of ecological risk of metal contamination in river Gomti, India: A biomonitoring approach Sanjay Kumar Gupta a,n, Mayuri Chabukdhara b, Praveen Kumar a, Jaswant Singh c, Faizal Bux a a

Institute for Water and Wastewater Technology, Durban University of Technology, South Africa North Eastern Space Applications Centre, Umiam, Meghalaya, India c Dr. R. M. L. Avadh University Faizabad, India b

art ic l e i nf o

a b s t r a c t

Article history: Received 1 March 2014 Received in revised form 5 August 2014 Accepted 6 August 2014

The aim of this study was to evaluate the extent of heavy metal pollution in river Gomti and associated ecological risk. River water, sediments and locally abundant mollusk (Viviparus (V.) bengalensis) were sampled from six different sites and analyzed for seven metals: Cadmium (Cd), Chromium (Cr), Copper (Cu), Manganese (Mn), Nickel (Ni), Lead (Pb) and Zinc (Zn). Mean metal concentrations (mg/l) in river water were 0.024 for Cd, 0.063 for Cr, 0.022 for Cr, 0.029 for Mn, 0.044 for Ni, 0.018 for Pb and 0.067 for Zn. In river sediments, the concentrations (mg/kg dry wt) were 5.0 for Cd, 16.2 for Cr, 23.2 for Cr, 203.2 for Mn, 23.9 for Ni, 46.2 for Pb and 76.3 for Zn, while in V. bengalensis mean metal concentrations (mg/kg, dry wt) were 0.57 for Cd, 12.0 for Cr, 30.7 for Cu, 29.9 for Mn, 8.8 for Ni, 3.6 for Pb and 48.3 for Zn. Results indicated elevated concentrations of Cu, Zn and Mn in V. bengalensis as compared to other non-essential elements. Potential ecological risk (RI) in sediments showed high to very high metal contamination. Cluster analysis indicated that Pb, Zn, Cd and Ni in sediments may have anthropogenic sources. The findings thus suggest heavy metal contamination of river water and sediments have reached alarming levels, which is well corroborated by elevated level of metal accumulation in V. bengalensis. & 2014 Elsevier Inc. All rights reserved.

Keywords: Heavy metal Gomti Viviparus bengalensis Ecological risk Biomonitoring

1. Introduction Heavy metal contamination of aquatic ecosystems has become a serious environmental concern throughout the world (Boran and Altinok, 2010; Chaharlang et al., 2012; Shariati et al., 2011). Rapid urbanization and industrialization often contribute to the discharge of heavy-metal containing industrial or municipal effluent into neighboring water bodies, particularly rivers and streams (Chabukdhara et al., 2012; Fleit and Lakatos, 2003; Gaur et al., 2005; Kumar, 1989; Modak et al., 1990; Singh et al., 2005c; Suthar et al., 2009). Once released into riverine systems, heavy metals may simultaneously prevail in the water column and be adsorbed into the river sediment which serves as an ecological sink (Kesavan et al., 2010; Sajwan et al., 2008). The adsorption of metals within the sediment causes it to act as a non-point source heavy metal reservoir, resulting in an incremental leaching of the retained metals back into the water column as a function of factors

n Correspondence to: Institute for Water and Wastewater Technology, Durban University of Technology, S 10 Level 1, Steve Biko Campus, PO Box 1334, Durban 4001, South Africa. Fax: þ27 31 3732777. E-mail addresses: [email protected], [email protected] (S.K. Gupta).

http://dx.doi.org/10.1016/j.ecoenv.2014.08.008 0147-6513/& 2014 Elsevier Inc. All rights reserved.

such as pH, temperature, salinity, etc., even after the point source has been removed (Forstner, 1981). Metals present in the aquatic ecosystem get rapidly integrated into the food web, compounding the deleterious effects to the aquatic biota, as well as people relying on them (Alyahya et al., 2011; Chaharlang et al., 2012; Gupta and Singh, 2011; Quiniou et al., 2007; Roméo et al., 2005; Romeo et al., 2000; Sidoumou et al., 2006). A functional assessment of the pollution status prevailing in and around an aquatic ecosystem requires measurement of chemical contaminants in the water column and sediment (Picado et al., 2007). A complete biomonitoring and ecological risk assessment requires addition of suitable biological indicators, which are integral to accurately ascertain even the minute variations within the complex milieu of an aquatic biosphere (Lam and Gray, 2003). Various indicator organisms such as oligochaetes, daphnids, chironomid, etc. are being used for the heavy metals pollution in aquatic ecosystems (Protano et al., 2014; Romano Spica et al., 2014; Serpa et al., 2014; Vlachopoulou et al., 2014). The potential ecological risk index (RI) is one of the several tools that have been developed over the years for assessment of contamination of aquatic environments (Hakanson, 1980; Protano et al., 2014). RI is the sum of risk factors for all heavy metals in sediments and it represents the sensitivity of the biological community to the toxic substance, thereby illustrating the potential ecological risk caused by the overall

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heavy metal contamination (Hakanson, 1980). Since, RI can assess the effect of multiple pollutants in an ecosystem at the same time thus has been the most widely used method (Protano et al., 2014; Sheykhi and Moore, 2013; Zhang et al., 2012). Bivalves and gastropod mollusks possess adaptive ability to accumulate a wide range of organic and inorganic contaminants well in excess, without suffering mortality, even with continuous exposure to the contaminated matrix (Andral et al., 2011; Goldberg, 1975; Goldberg and Bertine, 2000). Various species of mollusks have been studied for the assessment of chemical contamination of costal waster and sediments as these traits have proven them to be exceptional biomonitoring tools for aquatic systems with potentially toxic organic and inorganic contaminants (Gupta and Singh, 2011; Kucuksezgin et al., 2013; Livingstone, 1985; Quiniou et al., 2007; Romeo et al., 2000; Simkiss et al., 1982). Further, the sedentary nature of this species eliminates the intrinsic data elucidation bias of other organisms due to intricate migratory aspects and life cycles, thus making it ideal for heavy metal biomonitoring (Short and Sharp, 1989; Walsh et al., 1994). The magnitude of metal accumulation in mollusks reflects the degree of contamination in its biota (Farkas et al., 2003; Kucuksezgin et al., 2001, 2013; Salanki et al., 2003). The literature on Viviparus bengalensis as a bioindicator species is scanty. Only few reports are available on the toxicity assessment of metals to this species (Elder and Collins, 1991; Gupta et al., 1981a, 1981b). None of these studies were conducted in-situ, therefore V. bengalensis was chosen for the study. River Gomti is one of the major tributaries of river Ganges, which sustains the lives of people inhabiting Northern India. It receives untreated domestic wastewater from urban sewers, industrial effluents from industrial and agricultural run-off from its vast catchments area (25,800 km2). Thus monitoring of such tributaries assumes great significance. Despite few studies on the water and sediment contamination of the Gomti river (Gaur et al., 2005; Lohani et al., 2008; Singh et al., 2007a, 2005a, 1997, 2007c), investigations on the ecological impact assessment of heavy metals biomagnification are limited, specifically with regard to the Gomti's flora and fauna. Therefore, to assess the degree of metal contamination in the river Gomti and its potential ecological risk, present study was designed to assess the occurrence and distribution of selected metals in water, sediments and a locally abundant species of gastropod mollusk V. bengalensis.

2. Materials and methods 2.1. Study area The river Gomti, originates near Madho-Tanda Minkot (200 m above sea level, north latitude 281, 340 and east longitude 801, 070 ) which lies 50 km south of the Himalayan foothills covers a total distance of 730 km with a catchment region of about 25,800 km2. The river is a primary sourse of water for the city of Lucknow, state capital of Uttar Pradesh, India, and is a repository of the domestic sewage from the city's 26 sewers. As per current census of India (2011), the city had population of 2,815,601; an increase of 25.36 percent compared to census 2001. Such rapid population growth is attributed to rapid urbanization of the region, which houses a number of industries such as distillery, textile, pulp and paper, rubber and plastics, agrobased, sugar mills, chemical, etc. Some other pollution contributing activities in the river catchment area include but not limited to washerman lines and crematoriums. The river is characterized by sluggish flow throughout the year, except during the monsoon season.

2.2. Sampling method and preservation Samples of water, sediments and V. bengalensis were collected from six different sites (Fig. 1) all along the route of river Gomti in Lucknow. The sites were: Gaughat (S1), Mohan Meikin (S2), Martyr's Memorial (S3), Nishatganj Bridge (S4), Piparaghat (S5) and Malhaur (S6). The sites were selected due to commonality of both the prevalence of target gastropod population and the source of contamination within the immediate vicinity. Gaughat (S1) was upstream and excluded

from human activities, S2, S3, S4 and S5 were frequently subjected to anthropogenic activities while S6 was downstream of the river Gomti. The sampling was performed in summer of 2012. Water and sediment samples were collected in triplicate from three subsites, i.e. cis, trans and middle of each site. Water samples were collected in sterile polyethylene bottles (2 L) following standard methods (APHA, 1998). Prior to sampling, all bottles were soaked in ten percent nitric acid (HNO3) followed by rinsing with ultrapure water. The samples were acidified to pHo2 using concentrated HNO3 at sampling site. Sediment samples (approx. 2 kg) from each subsite of all six sites were collected (54 samples) in separate polyethylene bags using a grab sampler. Twenty individual V. bengalensis specimens were randomly handpicked from 0.5–1 m depths of the cis and trans subsites of each sampling site. Collected mollusk samples were subsequently positioned in filtered river water to permit extraction of the particulate matter existing within the mantle cavity and digestive tract before being transported to the laboratory in clean, labeled polyethylene bags in ice containers. All samples were stored in airtight ice-cold containers and transported to the laboratory within 6–8 h of sampling. The water and sediment samples were stored at 4 1C until further processing and analysis. The mollusk samples were methodically cleaned, in the laboratory, with a nylon brush under running tap water and any epiphytes or remaining debris was cautiously removed (Nakhlé et al., 2006). The soft tissue was carefully extracted with a stainless steel spatula from the shells and stored at  20 1C until further analysis (Karouna-Renier and Sparling, 2001). 2.3. Heavy metal analysis The metals analysis of water samples was carried out by acid digestion following standard methods (APHA, 1998). In brief, 100 ml water samples were digested with concentrated HNO3 (20 ml) at 100 1C up to dryness. The digest was cooled to room temperature, diluted and filtered through Whatman no. 42 filter paper. The filtrate was made-up to 20 ml with 0.01 N nitric acid. The sediment samples were oven dried (80 1C, 24 h), powdered with a pestle and mortar and sieved (230 mesh) in order to separate large materials and pebbles from the sediments. The soft tissues of the mollusk were defrosted and dried to a stable mass at 65 1C. Samples were then powdered to a uniform particle size (o250 mm) using a PVC pestle and mortar. The processed sediment and mollusk samples (1 g) were acid digested with a digestion mixture (4:1) of concentrated nitric and perchloric acid (Conti and Cecchetti, 2003; Moon et al., 1994; Yang et al., 2009). The digestion was carried out to dryness and the respective digests were made-up to 20 ml with 0.01 N nitric acid. The metals concentrations of each digest were analyzed using atomic absorption spectrometry (Varian AA240 Zeeman). The results of sediments and mollusks samples are presented on a dry-weight (d.w.) basis. 2.4. Reagents and chemicals All the chemicals and reagents used throughout the study were of analytical grade (E-Merck, India). The reagents and calibration standards were prepared using ultra-pure Mili-Q water (TKA Milli-Q Ultra-Pure Water System, Germany). The metal standards were prepared from certified stock solution of 1000 mg/l (E-Merck, Germany) by successive dilution with ultrapure water. The analytical methodologies were guaranteed through the use of standard operating procedures, calibration with standards, analysis of reagent blanks, matrix spikes, recovery of known additions and analysis of replicates. All analyses were carried out in triplicate, and the results were expressed as the mean. Whole procedure blank tests were performed on ultra-pure water, in order to assess the absence of any contamination occurring from reagents and materials. 2.5. Data analysis The data were analyzed using a statistical package SPSSs (Window Version 17.0). Normality of data was checked using Shapiroe–Wilk's normality test (p 40.01). In sediments, except for Mn, all metals showed normal distribution while in mollusks none of the metal showed normal distribution. Therefore, to analyze significant differences among sampling stations for different metal levels in sediments,one-way ANOVA was applied and Tukey's t-test was also performed to identify the homogeneous type of the data sets. For mollusks, difference among the metals concentrations was revealed in the six sites using Kruskal–Wallis test. Spearman's rank correlation coefficient was used to measure the relationship between metals in mollusks and sediments. The data was considered significant at pr 0.05. Cluster analysis was perfomed to identify groups or clusters of similar variables or sites, on the basis of similarities within a class and dissimilarities between different classes, using Ward's method. The distance measure used in cluster analysis was the squared Euclidean distance. The potential ecological risk index (RI) was assessed using (Hakanson, 1980) method: Ei r ¼ Ti rCi f ðCi f ¼ C i =C n Þ RI ¼ ∑Ei r

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Fig. 1. The location map of the sampling sites.

where Eir is the potential ecological risk index of an individual metal, Cif is the contamination factor (a ratio between concentration of the metal in samples and reference value for the metal), and Tir is the toxic factor of an individual metal provided by (Hakanson, 1980). Tir values adopted are 5 (Pb and Cu), 1 (Zn), 30 (Cd), 2 (Cr) and 6 (Ni) (Gan et al., 2000). The regional reference values for metals were not available so values from the crust material were applied (Turekian and Wedepohl, 1961), which are (mg/kg) 0.3 for Cd, 45 for Cu, 90 for Cr, 95 for Zn, 20 for Pb and 68 for Ni. The adjustment of factor standards was made according to Liu et al. (2009) and the metal pollution categories based on RI were considered as low (RI r110), moderate (110o RIr 220), high (220 oRI r 440), and very high contamination (RI4440).

3. Result and discussion 3.1. Metal levels in water, sediments and V. bengalensis The concentration of different heavy metals (mg/l, Table S1, Supplementary materials) in water was Cd (0.013–0.055), Cr (0.045–0.332), Cu (0.014–0.042), Mn (0.012–0.063), Ni (0.03– 0.069), Pb (0.013–0.026) and Zn (0.056–0.074). In sediments, the concentration ranged (mg/kg dry wt, Table 2): Cd (2.077–8.505),

Cr (10.107–22.928), Cu (5.202–33.277), Mn (119.187–294.251), Ni (7.866–39.944), Pb (7.083–88.952) and Zn (54.334–100.456). The heavy metal analysis of water and sediment samples from different sites showed high to very high levels at S2–S6 with Mohan Meakins (S2) to be the most contaminated (Table S1). This can be due to hydrology of Gomti which is characterized by low flow especially in summer seasons. The higher deposition of heavy metals in river sediments could also be attributed to alkaline pH, fine particle size and high surface area of silt and clay (Konhauser et al., 1997; Gaur et al., 2005; Gibbs, 1977; Solomons and Forstner, 1984; Dean et al., 1972). The Zn, Cu and Mn were found to be the most abundant metals in all the sites, the reason being the adjacent sewer outfall which feeds into the river water column. The high metal concentration, due to urban and industrial runoff at various sites of river Gomti across Lucknow city has also been previously reported (Gaur et al., 2005; Lohani et al., 2008; Singh et al., 2007b, 2004, 1997, 2005b). Results indicated the level of all the metals to be very low in water and sediments at Gaughat (S1), which is attributed to low burden of urban and industrial discharges at this site, thereby confirming the predicted low level

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of heavy metal contamination. The difference in concentration of metals was statistically significant (po0.001) in the sediments of different sampling sites (Table 1). The lowest concentration was seen at S6 while it was highest at S2. The concentration of Cd and Cr was minimum at S1 whereas it was least at S6 for Cu, Ni, Pb and Zn. The midstream sites (S2, S3, S4 and S5) showed an overall high metal concentrations which could be due to the influence of active anthropogenic activities in the adjacent areas which include a number of sewerage systems and a beverage industry discharging domestic and industrial effluent into the river. Mean metal concentrations in V. bengalensis at different sites are shown in Table 2. The difference among sampling sites for level of metals was statistically significant (Kruskal–Wallis test): Cd (p o0.05), Cr (po 0.01), Cu (p o0.01), Mn (p o0.01), Ni (p r0.01), Pb (po 0.05) and Zn (p o0.01). Cd and Zn showed highest accumulation (mg/kg dry wt) at S2 whereas Cr, Mn, Ni and Pb showed maximum and minimum accumulation at S3 and S1, respectively. The study indicated higher concentrations of Cu and Zn in V. bengalensis as compared to other non-essential elements. The higher concentration of Cu and Zn may be attributed to the presence of blood amphocytes in membrane bound vesicles that can trap Cu and Zn in the mollusk (George et al., 1984; Thomson et al., 1985). Statistical summary of metal concentrations in water, sediments and V. bengalensis is shown in Table 2. In river water, Cr showed the maximum concentration while sediment sample showed higher levels of Mn and Zn. The concentrations of heavy metals in mollusk were much higher than those evaluated in the river water. The study also reflected the inherent ability of V. bengalensis to survive, without suffering mortality, in the environment continuously exposed to heavy metals contamination. 3.2. Ecological risk due to metal contamination in sediments The overall ecological risk index (RI), as shown in Table 3, indicated high (S1-234.4; S6-275.4) to very high pollution (S2, S3, S4 and S5; RI range 496–894) at different sites. Such high contamination leads to higher bioaccumulation of metal in V.

bengalensis and hence poses a high risk to other aquatic fauna too. Based on the RI value, metal contamination in sediments for the different sampling sites can be ranked in the following order S2 4S3 4S4 4S5 4 S64 S1. The unavailability of updated reference metal levels for any selected ecosystems or geographical region could lead to an overestimation or underestimation of the actual pollution load in the sediments and thus the ecological risk index (Protano et al., 2014). Therefore, for accurate estimation of ecological risk of trace metals, regular updates for reference level after certain period of time is required even at the regional levels in each country specially in geological regions with sensitive ecological habitats. 3.3. Correlation analysis and cluster analysis Table 4 presents the correlation coefficients relating to heavy metals in the sediment and V. bengalensis. Metal–metal pairs in sediments showed significant correlation in Cd–Cr (r¼1.00, po0.01), Cd–Cu (r¼0.89, po0.05), Cd–Ni (r¼ 0.83, po0.05), Cr–Cu (r¼0.89, po0.05), Cr–Ni (r¼ 0.83, po0.05), Cu–Ni (r¼0.89, po0.05), Cu–Zn (r¼0.94, po0.01), Mn–Ni (r¼0.89, po0.05), Mn–Pb (r¼1.00, po0.01), Mn–Zn (r¼ 0.83, po0.05), Ni–Pb (r¼0.94, po0.01), Ni– Zn (r¼0.94, po0.01) and Pb–Zn (r¼ 0.83, po0.05). A high correlation among metal pairs in sediments indicates a common origin due Table 3 Ecological risk factor (Eir) and the potential ecological risk index (RI) of heavy metals in surface sediments of the Gomti River. Eir

Site

S1 S2 S3 S4 S5 S6

RI

Cd

Cr

Cu

Ni

Pb

Zn

208 851 701 496 478 251

0.22 0.51 0.45 0.38 0.34 0.26

1.54 4.42 3.58 3.7 1.67 0.58

12.69 15.13 11.06 17.85 11.28 19.97

10.98 22.24 18.77 10.49 5.04 1.77

0.94 1.12 1.13 1.26 0.33 1.85

234.4 894 736 529.7 496.7 275.4

Table 1 Heavy metal concentrations in sediment at different sampling sites. Sites S1 S2 S3 S4 S5 S6 n

a

(n ¼3) (n ¼3) (n ¼3) (n ¼3) (n ¼3) (n ¼3)

Cd (mg/kg dry wt) n

a

2.08 7 0.85a 8.517 1.99c 7.017 0.49bc 4.96 7 0.78ab 4.78 7 1.43ab 2.517 1.27a

Cr (mg/kg dry wt)

Cu (mg/kg dry wt)

Ni (mg/kg dry wt)

Pb (mg/kg dry wt)

Zn (mg/kg dry wt)

10.117 1.36a 22.93 7 1.85c 20.22 7 1.45bc 16.88 7 1.51abc 15.17 1.88abc 11.89 7 1.36ab

13.88 7 2.15ab 39.777 2.24c 32.2 7 4.48c 33.287 2.49c 15.047 3.92b 5.2 7 1.92a

22.277 3.82b 39.94 72.15c 33.347 4.33c 23.19 73.04b 16.89 7 2.81b 7.87 7 2.02a

43.9 7 4.27c 88.95 7 3.45e 75.1 73.53d 41.977 3.19c 20.17 72.95b 7.08 7 1.38a

66.27 3.76b 100.46 7 4.66d 83.36 7 4.51c 91.577 2.28cd 61.9 74.76ab 54.53 7 6.85a

n¼3 Refers to triplicate composite (cis, trans and middle) samples from each site. Mean value followed by different letters is statistically different (ANOVA; Tukey's t-test, p o 0.001).

Table 2 Metal contents in soft tissues of Viviparus bengalensis collected from six different sampling sites. Site

Cd (mg/kg dry wt)

Cr (mg/kg dry wt)

Cu (mg/kg dry wt)

Mn (mg/kg dry wt)

Ni (mg/kg dry wt)

Pb (mg/kg dry wt)

Zn (mg/kg dry wt)

S1 S2 S3 S4 S5 S6 Kruskal–Wallis test

0.52 7 0.06 1.23 7 0.26 0.477 0.05 0.36 7 0.09 0.42 7 0.04 0.45 7 0.03 p o 0.05

9.97 70.44 12.99 7 0.19 15.477 0.46 10.56 7 0.06 12.46 7 0.44 10.26 7 0.13 p o 0.01

28.02 7 0.64 44.32 7 1.22 41.157 0.33 27.577 0.38 14.217 0.13 28.63 7 0.47 p o 0.01

28.79 7 0.97 35.66 7 0.53 36.137 0.32 32.63 7 0.40 17.36 7 0.27 28.977 0.90 p o0.01

7.247 0.43 10.62 70.19 10.80 70.20 7.79 7 0.23 8.687 0.19 7.63 7 0.24 p r0.01

2.52 7 0.38 4.517 0.14 4.54 7 0.32 4.38 7 0.20 b 2.82 7 0.08 2.677 0.26 p o 0.05

41.277 1.15 69.95 7 1.42 59.08 7 0.78 40.96 7 0.83 36.52 7 0.36 42.317 0.29 p o 0.01

V. bengalensis were handpicked from cis and trans subsite of each sampling site and each aliquot consisted of 20 specimens.

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Table 4 Spearman's correlation coefficients (r) among the heavy metal concentrations in (a) sediments and (b) the molluscs.

Cd S Cr S Cu S Mn S Ni S Pb S Zn S Cd M Cr M Cu M Mn M Ni M Pb M Zn M

Cd S

Cr S

Cu S

Mn S

Ni S

Pb S

Zn S

Cd M

Cr M

Cu M

Mn M

Ni M

Pb M

Zn M

1

1.00nn 1

0.89n 0.89n 1

0.66 0.57 0.71 1

0.83n 0.83n 0.89n 0.94nn 1

0.66 0.66 0.71 1.00nn 0.94nn 1

0.77 0.77 0.94nn 0.83n 0.94nn 0.83n 1

 0.26  0.26  0.26 0.37 0.08 0.37  0.03 1

 0.94nn  0.94nn  0.94nn  0.83n  0.94nn  0.83n 0.89n 0.14 1

 0.48  0.48  0.54 0.09  0.14 0.08  0.26 0.77 0.43 1

 0.60  0.60  0.60  0.37  0.43  0.37  0.37 0.31 0.66 0.77 1

 0.94nn  0.94nn  0.94nn  0.83nn  0.94nn  0.83nn  0.89n 0.14 1.00nn 0.43 0.66 1

 0.89nn  0.89nn  0.83n  0.77  0.83n  0.77  0.71 0.08 0.94nn 0.48 0.83n 0.94nn 1

 0.49  0.49  0.54 0.08  0.14 0.08  0.26 0.77 0.43 1.00 0.77 0.43 0.49 1

S – sediments. M – molluscs (V. bengalensis). nn n

Correlation is significant at the 0.01 level (2-tailed). Correlation is significant at the 0.05 level (2-tailed).

Fig. 2. Dendrogram using Ward's method showing the relationship among (a) metals and (b) sampling stations.

to the nature of their interactions. Correlation analysis for sediments and V. bengalensis showed no linear relationship between same metal pairs in sediments and V. bengalensis. This indicates that the accumulation of metals could be influenced by several other factors. The differing relationship may also be affected by different physiological and environmental functions of the organism and sampling sites. The relationships between the metals were also assessed by means of cluster analyses using Ward's method (linkage between groups), using the Euclidian distance as a similarity measure and these were subsequently synthesized into dendogram plots (Fig. 2a). The results showed close associations between Pb and Zn, Cd and Ni in sediments. These metals may have come from an anthropogenic source. Previous studies have also demonstrated major source of pollution in river Gomti to be of anthropogenic origins (Gaur et al., 2005; Singh et al., 2004, 2005a, 2005c). Mn was isolated from other metals and may have natural as well as anthropogenic origins. Cu was also isolated and its concentration was lower than other metals so it may have come from a

natural source. Cluster analysis performed on the sampling sites enabled the identification of site groups (Fig. 2b). S2, S3 and S4 were closely associated showing relatively higher concentrations of metals; the sites are influenced by rapid urbanization and industrialization. Similar observations were also made by Gaur et al. (2005) and Singh et al. (2005c). S1 (upstream site) was isolated from other sites and less polluted. S5 and S6 in downstream are closely associated and showed higher metal levels than S1.

4. Conclusion The study revealed high heavy metal contamination in water and sediment of river Gomti which was higher at midstream sites. The sediment was found to be preferred repository of heavy metals. The mollusk V. bengalensis showed high heavy metal bioaccumulation and ability to persist in contaminated environment without suffering mortality. Potential ecological risk index (RI) indicated high to

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very high metal contamination that may pose risk to the aquatic biota in the long term due to bioaccumulation. The highest risk was found to be associated with Cd contamination. The study thus indicated towards high metal contamination and need of immediate remedial measures to be taken by the concerned regulating authorities for the abatement of pollution in river Gomti for its protection and restoration.

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