Geochemical speciation and risk assessment of heavy metals in the river estuarine sediments—A case study: Mahanadi basin, India

Journal of Hazardous Materials 186 (2011) 1837–1846

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Geochemical speciation and risk assessment of heavy metals in the river estuarine sediments—A case study: Mahanadi basin, India Sanjay Kumar Sundaray a,d,∗ , Binod Bihari Nayak b , Saulwood Lin a , Dinabandhu Bhatta c a

Institute of Oceanography, National Taiwan University, Taipei 10617, Taiwan Institute of Minerals and Materials Technology, Bhubaneswar 751013, Orissa, India Department of Chemistry, Utkal University, Bhubaneswar 751004, Orissa, India d Department of Chemistry, S.C.S. (Autonomous) College, Puri 752 001, Orissa, India b c

a r t i c l e

i n f o

Article history: Received 7 September 2010 Received in revised form 15 December 2010 Accepted 16 December 2010 Available online 23 December 2010 Keywords: Sequential extraction Heavy metals Risk assessment code (RAC) Sediment quality guidelines (SQGs) Factor and cluster analyses

a b s t r a c t Sequential extraction technique was used to study the mobility and dynamics of operationally determined chemical forms of heavy metals in the sediments and their ecological risk on the biotic species. The results reveal that high environmental risk of Cd, Ni, Co and Pb, are due to their higher availability in the exchangeable fraction. Substantial amount of Cd, Co, Mn, Cu, Zn, Ni and Pb, is observed as carbonate bound, which may result due to their special affinity towards carbonate and their co-precipitation with its minerals. Colloids of Fe–Mn oxides act as efficient scavengers for the heavy metals like Zn, Pb, Cu, Cr, Co, and Ni. Toxic metals like Ni, Pb and Cd are of concern, which occasionally may be associated with adverse biological effects based on the comparison with sediment quality guidelines (SQGs). The risk assessment code (RAC) suggests that the highest mobility of Cd poses a higher environmental risk and also threat to the aquatic biota. Factor analysis reveals that the enrichment of heavy metals in bioavailable fraction is mostly contributed from anthropogenic sources. These contributing sources are highlighted by cluster analysis. © 2010 Elsevier B.V. All rights reserved.

1. Introduction In sediments, heavy metals are present in a number of chemical forms, and generally exhibit different physical and chemical behaviors in terms of chemical interaction, mobility, biological availability and potential toxicity [1–3]. It is necessary to identify and quantify the mode of occurrence in which a metal is present in sediment to gain a more precise understanding of the potential and actual impacts of elevated level of metals in sediments and to evaluate processes of downstream transport, deposition and release under changing environmental conditions [2]. Most of the studies deal with the contamination of sediments by heavy metals using only the total metal content as a criterion to assess its potential effect as contaminant. Measurement of the total concentration of metals provides inadequate information to assess the bioavailability or toxicity of metals. An evaluation of total metal levels following a strong acid digestion of the sediment may be useful as a global index of contamination, but it provides little indication of their bioavailability, mobility and reactivity in sediments [4,5]. The metal speciation into different fractions is the most reliable cri-

∗ Corresponding author at: Institute of Oceanography, National Taiwan University, Taipei 10617, Taiwan. Tel.: +886 223636040x110; mobile: +886 910304342. E-mail address: [email protected] (S.K. Sundaray). 0304-3894/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.jhazmat.2010.12.081

teria to quantify the potential effect of contamination of sediments by heavy metals. The toxicity of metals depends especially on their chemical forms rather than their total elemental contents [3]. Sequential extractions can be useful to have an operational classification of metals in different geochemical fractions. Metals in river sediments can be bound to various compartments; adsorbed on clay surfaces or iron and manganese oxyhydroxides; present in lattice of secondary minerals like carbonates, sulphates or oxides; occluded in amorphous materials such as iron and manganese oxyhydroxide; complexed with organic matter or present in lattice of primary minerals such as silicates [6–9]. Sequential extraction techniques would provide the history of metal input, digenetic transformation within the sediments and the reactivity of heavy metal species of both natural and anthropogenic origin. This is recognized as a useful methodology for gaining information on the manner of occurrence, bioavailability, mobilization and transport of metals despite poor selectivity [10,11]. The Mahanadi river, a major source of water carries a pollution load from industrial and agricultural areas of Orissa, India [12,13]. Number of researchers have worked on the role of different urban and industrial effluents upon the water quality of Mahanadi river and estuarine systems [12–22]. In this study, sequential extraction technique was used to interpret the dynamics, mobility and risk assessment of heavy metals in sediment samples collected from Mahanadi river basin, India.

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Fig. 1. Map showing station locations.

The objectives of the present work were (i) to assess the dynamics and mobility of heavy metals in different geochemical fractions in the sediments, (ii) to identify the bioavailability and ecological risk of these metals and (iii) to define the contributing sources of heavy metals in river estuarine sediment samples with the aid of sediment quality guidelines (SQGs), risk assessment code (RAC) and multivariate statistical analyses such as factor analysis and cluster analysis.

recent deltaic alluvium of the river with littoral deposits. The basin lithology consists of granite suite (34% of the basin area), khondalite suite (7%), charnockite suite (15%), limestone, shale of lower gondwana (17%), sandstone, shale of upper gondwana (22%) and coastal alluvium (5%). A part of the richest mineral belt of the subcontinent consisting of Fe ore, coal, lime-stone, dolomite, bauxite, Pb and Cu deposits fall within the basin [15]. 2.3. Anthropogenic setup of the basin

2. Study area description 2.1. Geographical setting The Mahanadi river system is the third largest in the peninsula of India and the largest river of Orissa state. The basin (80◦ 30 –86◦ 50 E and 19◦ 20 –23◦ 35 N) extends over an area approximately 141,600 km2 , has a total length of 851 km and an annual runoff of 50 × 109 m3 with a peak discharge of 44,740 m3 s−1 . The basin is characterized by a tropical climate with average annual rainfall of 142 cm with 90% occurring during the south westmonsoon [12,15]. The river begins in the Baster hills of Madhya Pradesh, flows over different geological formations of Eastern Ghats and adjacent areas and joins the Bay of Bengal after divided into different branches in the deltaic area. The main branches of River Mahanadi meet Bay of Bengal at Paradip and Nuagarh (Devi estuary) (Fig. 1). The tidal estuarine part of the river covers a length of 40 km. Based on physical characteristics, the estuary has been characterized as a partially mixed coastal plain estuary. 2.2. Geology of the basin The basin geology is characterized by the pre-cambrians of Eastern Ghatts consisting of rock types as khondalites, charnockites, leptynites, granites, gneisses, etc., the limestones sandstones and shales of the Gondwanas, and the costal tracts constituted by the

Cuttack (population about 0.5 million), Sambalpur (population about 0.2 million) and port city Paradip (population about 0.15 million) are the three major urban settlements on the banks of the river (Fig. 1). The river serves as a major source of domestic water supply of the Cuttack, Sambalpur cities and indirectly to Paradip city through Taladanda canal. Subsequently the river receives back the untreated domestic waste water from Sambalpur, Bauda, Cuttack, Choudwar, Jagatpur and Paradip cities of Orissa state and effluents from some industrials (fertilizer, paper, textile distilleries and others) directly during its coarse [19]. It also receives large amount of agricultural runoff along its coarse. Human influences are pronounced at Sambalpur, Cuttack and Paradip, where the proliferation of industries and sewer discharges is prominent. 3. Materials and methods 3.1. Sampling collection and analytical methods Under the sediment quality monitoring programme of the Mahanadi river basin, samples from 31 locations of Mahanadi river estuarine system starting from Hirakud reservoir to the estuary points i.e. at Paradip and Nuagarh (Fig. 1) were using a portable type Peterson’s grab sampler. Each sample was obtained by mixing sediments randomly collected (3 times) at each sampling point. Samples were brought to the laboratory packed in polyethylene air

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Fig. 2. Flow charts for speciation scheme of sediments.

tight bags. All the samples were carried to laboratory and preserved in a refrigerator at 3–4 ◦ C. Before characterization and speciation, samples were air-dried and homogenized. A portion of the sample was taken for textural analysis (sand, silt and clay percentages). The estimation of organic matter in sediments was determined by Walkley and B1ack method [23]. The amount of CaCO3 (including other carbonates) in the bulk sediment samples was estimated by the rapid titration method of Hutchinson and Melclennan [23]. In the present study, heavy metals (Fe, Mn, Zn, Cu, Co, Cr, Ni, Pb and Cd) were sequentially extracted from <88 ␮m (−200 ASTM) fraction of sediments following the five step method proposed by Tessier et al. [6] into operationally defined as exchangeable (F1), carbonate (F2), Fe–Mn hydroxide (reducible) (F3), organic (F4) and residual (F5). These fractions may be considered to decrease in lability from exchangeable to residual. The <88 ␮m fraction contains fine sand, silt and clay which are highly responsible for retaining heavy metals into aquatic sediments [24,25]. The different fractions and reagents used in the sequential experiment are shown in flow diagram (Fig. 2). In recent years this five-step extraction method [6] is a widely used one [2,9,24–29]. After each successive extraction, samples were centrifuged at 4000 rpm for 20 min to separate the extract from sediments. The concentrations of Fe, Mn, Zn, Cu, Co, Cr, Ni, Pb and Cd in each of the leachates were determined by AAS (Perkin Elmer AAS 3110) in flame mode. The precision and accuracy of the methods were

systematically and routinely checked analyzing USGS reference sample no. GXR (soil), where it has been found the precision (coefficient of variation of five replicate analysis) were 3% for Cu, Cr and Fe and 4% for Pb, Cd, Co, Ni, Mn and Zn. 4. Results and discussion 4.1. Speciation of heavy metals The minimum, maximum, average value and standard deviation of heavy metals distributions (␮g/gm) in various geochemical fractions are presented in Table 1. The heavy metals associated with different fractions in Mahanadi river-estuarine sediments follow the order: Fe: Residual > Reducible > Organic > Exchangeable > Carbonate Mn: Residual > Reducible > Carbonate > Exchangeable > Organic Zn: Residual > Reducible > Carbonate > Organic > Exchangeable Cr: Residual > Reducible > Organic > Carbonate > Exchangeable Cu: Residual > Organic > Reducible > Carbonate > Exchangeable Co: Residual > Reducible > Organic > Carbonate > Exchangeable Ni: Residual > Reducible > Organic > Carbonate > Exchangeable Pb: Residual > Reducible > Organic > Carbonate > Exchangeable Cd: Residual > Carbonate > Exchangeable > Reducible > Organic

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Table 1 Heavy metal distributions (%) in various operationally defined geochemical fractions in the Mahanadi river basin. F1 Fe (%) Min. Max. Average Stand. dev. Zn (%) Min. Max. Average Stand. dev. Cu (%) Min. Max. Average Stand. dev. Ni (%) Min. Max. Average Stand. dev. Cd (%) Min. Max. Average Stand. dev. Mn (%) Min. Max. Average Stand. dev. Cr (%) Min. Max. Average Stand. dev. Co (%) Min. Max. Average Stand. dev. Pb (%) Min. Max. Average Stand. dev.

0.010 0.830 0.159 0.247

F2 0.010 0.052 0.026 0.009

F3

F4

F5

4.68 19.28 8.59 4.47

0.30 11.30 2.29 2.70

73.37 94.55 88.93 6.59

0.76 4.62 1.86 1.06

10.43 15.42 12.70 1.22

10.35 38.85 22.22 6.37

2.24 18.56 7.00 5.04

28.32 72.86 56.21 11.21

0.77 6.78 2.35 1.66

4.87 15.52 8.38 3.01

7.78 23.18 14.99 4.39

7.53 34.85 15.14 6.94

25.63 76.06 59.13 13.89

0.34 13.85 5.00 3.23

5.40 13.68 8.30 1.94

8.21 23.98 13.83 4.20

4.35 23.08 8.78 4.72

31.36 78.10 64.10 12.09

9.07 28.15 13.98 5.17

11.26 21.64 17.33 2.85

5.95 19.60 10.86 3.68

1.53 11.83 3.93 2.80

22.74 64.80 53.90 11.35

1.32 16.83 4.63 3.65

5.16 18.42 10.38 4.03

8.20 38.47 22.04 7.72

1.42 11.75 3.60 2.67

23.77 79.49 59.36 15.62

0.35 5.78 1.73 1.32

0.76 3.88 2.37 0.99

7.57 24.07 13.75 4.31

1.83 16.20 5.39 3.70

58.92 86.08 76.76 7.72

1.33 15.82 4.51 3.43

2.28 18.50 6.99 4.34

8.20 32.47 13.67 4.85

4.67 19.45 8.95 4.22

27.61 82.25 65.89 15.17

0.86 5.83 2.31 1.43

1.07 8.25 3.24 1.87

11.45 29.05 19.14 4.80

4.96 23.68 8.77 4.63

41.86 80.21 66.54 11.25

F1, exchangeable bound; F2, carbonate bound; F3, reducible bound; F4, organic bound; F5, residual bound.

Results of the sequential extraction suggest that the residual fraction dominated the Fe (73.4–94.5%), Cr (58.9–86.1%) and Pb (41.9–80.2%) distribution in the Mahanadi river estuarine sediments. The exchangeable and carbonate fractions of Fe are totally geo-chemically insignificant (<1% of total). Geochemical speciation data of sedimentary heavy metals suggest that high concentration of Cd, Mn, Ni and Co in the exchangeable fraction has an adverse impact on aquatic biota. The metals like Mn, Cd, Co, Cu, Zn, Ni, and Pb represent an appreciable portion in carbonate phase, as these metals have special affinity towards carbonate and may coprecipitate with its minerals [24]. The lower degree of association of Cr (0.8–3.9%) in carbonate fraction in the Mahanadi river estuarine sediments may arise due to the inability of Cr3+ to form a precipitate or complex with carbonates. Carbonate bound Mn exhibits the second highest among non-lithogenic fraction. Higher content of Mn in carbonate bound is most likely due to their similarity in ionic radii to that of calcium, which allows them to substitute Ca in carbonate phase [24,25,30]. Among the non-lithogenic fractions the Fe–Mn oxy-hydroxide is the main scavenger for all metals (except Cu and Cd). This attributes to the adsorption, flocculation and co precipitation of heavy metals with the colloids of Fe and Mn oxy-hydroxide [25,26,31–33]. Further, organic bound Pb, Co, Cr, Ni and Fe seem to be the second dominant fraction among the non lithogeneous.

The lower percentage of Fe and Mn in organic fraction probably results from the competition between Fe–Mn-organic complex and hydrous Fe–Mn oxide forms [24]. In polluted sites [12], Cu is mostly locked up in non-lithogeneous fraction [24]. Copper can be retained by sediment through exchange and specific adsorption but precipitation may also be an important mechanism of retention in polluted sediments [34]. For Cu, organic matter is the major scavenger among the non-lithogeneous in the Mahanadi river estuarine sediment. This is significantly reflected from the distribution of organic matter in the polluted sites of the river estuarine sediments (Table 2). Even though copper is generally adsorbed to a greater extent than other metals with the exception of lead, the high affinity of Cu2+ ions for soluble organic ligands may greatly increase their mobility in sediments [35]. The metal can easily complex with organic matters because of the easy formation of high stability constants of organic-Cu compounds [36]. The fractionation profile for cadmium is totally different from other metals, which indicates that it is mostly bound to first three fractions i.e. exchangeable (9.07–28.15%), carbonate (11.26–21.64%) and reducible (5.95–19.60%) fractions in the non residual phase. These results are similar to other works carried out previously in aquatic sediments [37–40]. The major fraction of cadmium in carbonate form indicates that at a slight lowering of pH,

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Table 2 Concentration of heavy metals in bioavailable and nonbioavailable fractions (␮g/gm), organic matter and pH in each sampling site of Mahanadi river basin. St. No.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Min. Max. Mean

Fe

Mn

Bio*

Nbio*

Bio*

34 20 38 83 479 163 24 16 17 11 17 23 45 14 226 462 37 24 15 43 26 41 633 360 784 23 576 31 43 26 23 11 784 141

55,160 46,066 66,221 68,162 89,098 74,555 40,989 43,361 45,966 36,172 42,596 44,073 57,558 42,335 66,580 90,390 55,465 46,435 47,883 79,711 58,283 60,940 83,437 55,927 91,198 41,710 85,449 52,616 78,991 61,847 51,836 36,172 91,198 60,033

133 79 98 223 329 159 74 92 86 77 56 91 103 69 157 271 142 132 116 307 188 244 418 312 571 89 298 94 226 179 219 56 571 182

Zn

Nbio* 884 790 853 991 1025 998 805 826 885 873 812 827 1018 902 1019 1162 919 1005 977 1370 933 975 1107 796 1160 835 1226 823 1125 783 794 783 1370 951

Cr

Cu

Bio*

Nbio*

Bio*

18 15 13 21 30 24 11 9 16 13 13 14 20 12 21 34 18 14 17 28 27 25 36 25 39 15 34 10 16 18 21 9 39 20

111 112 79 122 168 132 75 59 91 105 81 86 110 79 111 161 107 87 99 141 150 128 188 169 197 99 176 59 83 105 147 59 197 117

1.8 71 1.7 52 2.0 54 3.9 63 6.0 76 4.3 59 1.8 53 2.5 54 1.7 52 2.7 59 1.6 56 1.8 54 3.2 71 2.6 56 4.8 72 6.5 84 2.2 62 1.8 64 1.4 61 2.2 73 1.5 67 3.1 91 5.1 93 3.9 92 10.3 136 2.0 53 7.8 92 2.0 56 1.5 61 1.6 66 1.4 72 1.4 52 10.3 136 3.1 69

Nbio*

Co

Ni

Pb

Cd

Bio*

Nbio*

Bio*

Nbio*

Bio*

Nbio*

Bio*

Nbio*

Bio*

Nbio*

2.5 3.4 2.3 3.5 8.1 5.0 2.1 1.9 2.5 2.8 2.0 2.8 3.5 2.0 5.0 8.5 2.8 3.1 3.5 3.4 3.8 3.2 7.6 5.7 10.3 1.5 9.9 2.3 4.2 2.4 4.0 1.5 10.3 4.0

36 39 29 29 32 32 28 30 30 28 23 31 30 30 32 35 30 29 27 42 35 35 37 31 44 17 36 28 34 30 40 17 44 32

1.4 1.9 2.4 5.2 10.7 5.5 2.4 3.5 2.6 3.6 2.1 2.1 3.9 1.8 5.6 9.5 2.9 2.8 3.7 7.4 5.4 6.4 18.7 10.1 22.0 2.1 8.1 4.9 8.3 4.4 6.0 1.4 22.0 5.7

32 37 36 47 59 43 34 39 37 51 35 39 54 36 48 52 41 37 39 53 33 38 44 36 42 29 44 36 49 28 29 28 59 41

5.1 4.2 4.9 8.2 11.4 9.3 4.3 4.6 3.8 5.3 3.9 2.7 5.4 2.8 9.1 15.5 5.3 3.7 5.8 10.1 5.8 6.4 19.6 16.9 27.5 3.8 15.7 4.1 7.7 6.1 7.3 2.7 27.5 8.0

54 51 44 57 64 57 40 34 38 43 39 36 35 31 46 65 43 32 44 72 38 40 70 52 80 32 68 35 54 38 40 31 80 47

5.9 3.0 3.0 8.8 13.2 8.9 3.7 3.8 3.4 3.2 2.4 3.3 3.2 3.1 10.9 19.7 5.0 3.5 5.2 7.0 6.3 7.2 17.2 9.4 25.7 3.6 27.4 3.8 6.8 9.7 8.9 2.4 27.4 7.9

119 102 102 112 118 114 105 114 110 104 115 109 116 104 143 149 109 120 113 135 131 138 144 139 171 104 187 110 123 111 128 102 187 123

1.1 1.1 1.0 1.7 2.1 1.8 0.8 0.7 1.2 1.4 0.8 0.8 0.9 0.9 1.8 2.1 1.2 1.5 1.1 1.1 1.0 1.1 2.6 2.1 3.1 1.2 2.4 1.0 1.2 1.0 1.0 0.7 3.1 1.4

2.8 3.0 2.5 3.6 3.2 2.7 1.9 1.5 2.6 3.0 2.0 2.3 2.2 2.6 3.4 3.2 2.5 2.4 2.4 3.1 3.1 3.2 3.2 3.2 3.3 3.3 3.5 2.8 3.6 3.3 3.7 1.5 3.7 2.9

pH

OM mg/g

7.57 7.74 7.39 7.50 7.15 7.56 7.52 7.49 7.45 7.55 7.42 7.46 7.93 8.01 7.94 8.07 7.90 7.58 7.60 7.79 7.87 8.09 6.81 7.46 4.55 7.38 7.31 7.40 7.63 7.81 8.05 4.55 8.09 7.52

1.65 0.69 0.75 1.28 1.79 1.15 0.95 0.72 0.98 1.12 1.03 1.25 1.58 0.95 1.76 2.13 1.46 1.32 1.42 1.96 1.88 1.74 4.16 3.12 5.76 1.48 2.96 1.44 1.22 1.68 1.74 0.69 5.76 1.71

Bio*, bioavalable fraction; Nbio*, nonbioavailable fraction.

an appreciable percentage of cadmium would have been remobilized and becoming readily available [37]. Further, the similarity of ˚ and Cd (0.97 A) ˚ should favour the the ionic radius of Ca (0.99 A) co-precipitation of Cd carbonates and its incorporation into the calcite lattice to give solid solutions of Cd␣ Ca1−␣ CO3 [41–43]. The high percentage of Cd in the non-residual phase indicates the bioavailability of this element to the aquatic organisms in the studied river. There are several sources of Cd in the aquatic systems which include runoff containing phosphate fertilizer from agricultural areas nearby the river. This phosphate fertilizer, which is applied to the agricultural farms most probably contains Cd [44]. Presence of Cd could also be as a result of road traffic, which has been described as an important source of Cd emission [45]. It is recognized that sequential extraction technique enables prediction of possible metal impact on biota in aquatic ecosystems. The fractions introduced by human activity include the exchangeable and bound to carbonate which are considered to be weakly bound. These may equilibrate with aqueous phase thus becoming more rapidly bioavailable and cause environmental toxicity [46–49]. The metal fraction bound to Fe–Mn oxides and the organic matter can be mobilized when environmental conditions become increasingly reducing or oxidizing [49]. The metal present in the inert fraction, being of detrital and lattice origin or primary mineral phases, can be regarded as a measure of contribution by natural sources [47]. The potential level of bioavailability, based on the sum of chemical fractions 1 (exchangeable) and 2 (carbonate-bound) [46–52], and non-bioavailability fractions (␮g/gm) of heavy metals in each sediment samples of Mahanadi river estuarine systems are presented in Table 2. The bioavailable fraction represents the fraction

that when the right pH and redox conditions are favourable, the metal will be soluble and can be taken up by aquatic plants or ingested by animals causing environmental toxicity. The proportion of the mean metal concentration to the bioavailable metals follows the order: Mn > Fe > Zn. Ni ≥ Pb > Co > Cu > Cr > Cd. While the percentage of the bioavailable metals follows the order: Cd > Mn ≥ Zn > Ni > Co ≥ Cu > Pb > Cr > Fe. Generally, Fe and Mn are most abundant metals in the sediment and hence their content in bioavailable fraction is relatively high. Although, Cd contributes least to the bioavailable content, a greater percentage (21–49%) is found in the bioavailable form. This suggests that Cd is highly mobile and is under high environmental risk. The concentration in the bioavailable fraction is a serious environmental concern. The variability in the total metal contents and fraction of bioavailable and nonbioavailable of all these metals in all 31 sites (Table 3) may be attributed partly to the weathering and transport properties of minerals, anthropogenic inputs and other components of the sediments. However, the contribution from anthropogenic activities is the most significant and clearly visible in the river estuarine systems. 4.2. Assessment of risk by the presence of heavy metals 4.2.1. By sediment quality guidelines (SQGs) It is important to determine whether the concentrations of heavy metals in sediments found pose a threat to aquatic life, and which is assessed by three sets of sediment quality guidelines such as TEL (threshold effects level) and PEL (probable effects level), LEL (lowest effect level) and SEL (severe effect level), ERL (effects range low) and ERM (effects range medium) [53–56]. These three sets of

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Table 3 Level of bioavailable and nonbioavailable fractions (%) and total metal contents in each sampling site of Mahanadi river basin. St. No.

Bioavailable metal (%)

Non-bioavailable metal (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

9.0 8.2 9.2 12.5 16.7 13.6 8.9 10.1 9.4 9.5 8.3 8.3 10.2 8.0 13.1 16.6 10.5 10.7 10.5 11.1 11.1 11.8 19.3 17.1 22.0 9.1 17.0 9.6 11.5 11.3 11.7

91.0 91.8 90.8 87.5 83.3 86.4 91.1 89.9 90.6 90.5 91.7 91.7 89.8 92.0 86.9 83.4 89.5 89.3 89.5 88.9 88.9 88.2 80.7 82.9 78.0 90.9 83.0 90.4 88.5 88.7 88.3

Total metal (␮g/gm) 56,672 47,381 67,588 69,945 91,536 76,374 42,254 44,652 47,346 37,558 43,857 45,398 59,183 43,685 68,497 92,931 56,994 47,997 49,413 82,010 59,937 62,726 86,281 57,990 94,525 43,024 88,260 53,919 80,838 63,260 53,381

numerical SQGs were directly applied (without normalization) to assess possible risk arises from the heavy metal contamination in sediments of the study area. The classification of SQGs along with its effects and comparison results are presented in Tables 4 and 5 respectively. It is interpreted that TEL as the concentrations, bellow which adverse biological effects rarely occur. Hence, it is considered to provide a high level of protection for aquatic organisms. Similarly, PEL as the concentrations, above which adverse biological effects frequently occur. Hence, it is considered to provide a lower level of protection for aquatic organisms. With respect to this SQGs, a site is determined as contaminated if at least 10% sample values exceed TEL. When compared to the TEL–PEL SQGs, the concentrations of Cd, Cu, Cr, Ni and Pb are above TEL with 100% of samples. In case of copper and chromium, 100% of samples fall in the range between TEL and PEL. While 80.7%, 80.6% and 48.6% samples exceed PEL for the metals Ni, Pb and Cd respectively. When compared to the LEL–SEL SQGs, among the metals, Cd, Cr, Ni and Pb concentration are exceeding LEL in 100% of samples. Ni and Pb concentrations exceed SEL in 45.2% and 80.6% samples respectively. Similarly when com-

pared with ERL–ERM SQGs, most of the metals are within ERL and ERM. However, Ni concentration exceeds ERM in 41.9% samples. Although there is a small difference between the results obtained with three used SQGs, the above results lead to the conclusion that toxic metals like Cd, Ni and Pb are of concern in the present study area and that may occasionally be associated with adverse biological effects. 4.2.2. By risk assessment code (RAC) It is evident from the data that the metals in the sediments are bound to different fractions with different strengths, the value can, therefore, give a clear indication of sediment reactivity, which in turn assess the risk connected with the presence of heavy metals in an aquatic environment. To assess this, a risk assessment code (RAC) is utilized [2,37,52]. RAC assesses the availability of metals in sediments by applying a scale to the percentage of metals in the exchangeable and carbonate fractions. This is important because the fractions introduced by anthropogenic activities are typified by the adsorptive, exchangeable and bound to carbonate fractions, which are weakly bonded metals that could equilibrate with the aqueous phase and thus become more rapidly bioavailable [3]. According to RAC guideline, for any metal, sediment which can release in exchangeable and carbonate fractions, less than 1% of the total metal will be considered safe for the environment and sediments with 11–30% carbonate and exchangeable fractions will be at medium risk to the environment. On the contrary, sediment releasing in the above fractions more than 50% of the total metal has considered being highly dangerous, which can be easily enter the food chain. The classification of risk has been categorized in terms of risk assessment code (RAC) and is tabulated in Table 6. The present study (Fig. 3) reveals that the concentrations of Cd are posing a high risk (31–50%) (Table 6) to the environment at Sambalpur down (St. No. 5), Chipilima (St. No. 6), Tulasipur (St. No. 15), Shikharpur (St. No. 16), Oswal down (St. No. 23), Mahanadi estuary (St. No. 24), Atharbanki creek (St. No. 25) and Kathajodi down (St. No. 27). Besides the above sites, Cd is bounded either in exchangeable or in carbonate fraction (about 11–30%) in the entire river estuarine sediments, which reflects that cadmium comes under the medium risk category (Table 6) and can easily enter the food chain. Because of the toxicity and availability of cadmium, it can poses serious threat to the ecosystem. Zn and Mn though fall in medium risk category in most of the sites, these two are less toxic and essential elements also. Fe besides having less environmental risk is present mostly in residual form, from which it cannot be easily leached out and comes under the no risk category (<1%). However rest of the trace metals such as Cr, Cu, Co, Ni and Pb in the sediments come under medium category in the above stations. 4.3. Multivariate statistical analyses To assess the dynamics of heavy metals and identify the contributing sources of bioavailable heavy metals in river estuarine sediments, multivariate statistical analyses such as factor and

Table 4 Classification of sediment quality guidelines (SQGs) and its effects. Sediment quality guidelines TEL and PEL guidelines

LEL and SEL guidelines

ERL and ERM guidelines

Effect PEL SEL ERM

Not associated with adverse biological effects May occasionally be associated with adverse biological effects Frequently associated with adverse biological effects Dredged sediments may have no contamination The impact is moderate Severely impacted Minimal effects range Effects would occasionally occur Effects would frequently occur

References [53,54]

[55]

[56]

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Table 5 Comparison between sediment quality guidelines (SQGs) and heavy metals concentration (␮g/g) in the present study with percentage of samples in each guideline. Fe* Sediment quality guidelines TEL PEL LEL SEL ERL ERM Measured values in this study Range Average Compared with TEL and PEL % of samples PEL Compared with LEL and SEL % of samples SEL Compared with ERL and ERM % of samples ERM

Mn

Zn

Cu

Cr

Ni

Pb

Cd

18.7 108 16 110 34 270

52.3 160 26 110 81 370

15.9 42.8 16 50 20.9 51.6

30.2 112 31 110 46.7 218

0.68 4.21 0.6 9 1.2 9.6

68–236 137

18–55 36

53–147 72

34–107 55

105–215 131

2.2–6.4 4.2

48.4 51.6 0

0 100 0

0 100 0

0 19.3 80.7

0 18.4 80.6

0 51.6 48.4

38.7 61.3 0

3.2 96.8 0

0 100 0

0 54.8 45.2

0 18.4 80.6

0 100 0

64.5 35.5 0

41.9 58.1 0

0 100 0

0 58.1 41.9

0 100 0

0 100 0

Metal concentration (mg/g, except Fe*) – – 124 – – 271 2 460 120 4 1100 270 – – 150 – – 410 3.6–9.2 868–1731 6 1133 % of samples in each guideline

0 3.2 96.8

0 51.6 48.4

Fe*, concentration in %.

cluster analyses were carried out using SPSS 10.0 statistical software. 4.3.1. Factor analysis A factor analysis (FA) was carried out in an attempt to further clarify the dynamics and contribution of bioavailable fraction of metals in the sediments. The R-mode varimax factor analysis was performed on the metal concentration in bioavailable and nonbioavailable fraction along with organic matter (OM), CaCO3 and textural parameters of the sediments for 31 cases. FA with varimax rotation of standardized component loadings was conducted for extracting and deriving factors, respectively, and those principal components (PCs) with eigen value greater than 1 were retained [12,57,58]. The factor analysis of the present data set further sorted by the contribution of less significant variables (<0.5 factor score). The results of sorted rotated factor loading scores along with eigen values, percentage of variances are shown in Table 7. There

Table 6 Risk assessment code (RAC) [52]. Category

Risk

Metal in carbonate and exchangeable fractions (%)

1 2 3 4 5

No risk Low risk Medium risk High risk Very high risk

<1 1–10 11–30 31–50 >50

are four factors or PCs, explaining 86.03% of the total variance, which is sufficient to give a good idea of data structure. The factor 1 represents 69.11% of total variance and found to have more number of significant variables than the others, where organic matter plays a major role for distributing all metals. Organic matter, bioavailable fraction of all the nine heavy metals and Cr, Pb, Zn, Ni and Cd in the total, Cr, Pb and Zn in nonbioavailable fraction

Fig. 3. Risk assessment code (RAC) of heavy metals in the sediments collected from 31 different sites of Mahanadi river basin.

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Table 7 R-mode varimax rotated factor analysis data for bioavailable and nonbioavailable fractions of heavy metals in the sediments of Mahanadi river basin. Variable

F1

Fe (1)* OM Ni(1) Cr(1) Cr(T)*** Cd(1) Pb(1) Cr(2)** Cu(1) Pb(T) Co(1) Pb(2) Mn(1) Zn(1) Zn(T) Zn(2) Ni(T) Cd(T) Clay Cu(2) Cu(T) CaCO3 Cd(2) Co(2) Co(T) Mn(2) Fe(2) Fe(T) Mn(T) Ni(2) Sand Silt Eigen value % of variance Cum. %

0.905 0.871 0.866 0.866 0.858 0.848 0.847 0.840 0.811 0.797 0.783 0.756 0.739 0.707 0.707 0.704 0.679 0.675

0.518 0.570

F2

F4

0.529 0.530 0.528 0.747 0.713 0.636 0.627 0.621 0.910 0.824 0.782 0.638 0.636 0.633 0.590

0.515 0.522 0.547 0.571

22.12 69.11 69.11 Anthropogenic factor

F3

2.15 6.73 75.84 Clay factor

1.80 5.63 81.47 Fe–Mn oxy-hydroxide or lithogeneous factor

0.918 −0.864 1.46 4.55 86.03 Textural factor

(1)*, Bioavailable fraction. (2)**, Nonbioavailable fraction. (T)***, Total i.e. sum of bioavailable and nonbioavailable fraction.

are strongly loaded (>0.6) in this factor. In this factor Cu, Fe, Mn in total, Fe, Ni in nonbioavailable fraction and CaCO3 are moderately loaded. Organic matter in the sediment is the major reservoir for these metals. Organic matters not only solubilise the metal species by complexing the metal ions but also take out the metal ions from the solution [59]. Municipal sewage/industrial effluent discharged from three major townships namely Sambalpur, Cuttack and Paradip, and two fertilizer industries namely Oswal fertilizer plants, Paradip phosphate limited (PPL) are accounted as the main source of organic matter for this river estuarine system [12]. This association of bioavailable fraction of metals with organic matter reveals that these fraction of metals are contributed by the above townships/industries. Further the association of metals such as Cr, Pb, Zn, Ni and Cd in total with their bioavailable fraction reveals that major portion these above metals are contributed from anthropogenic factor. Considering the above observations, factor 1 may be termed as “Anthropogenic Factor”. Factor 2 is accounting for 6.73% of the total variance and characterized by loadings of clay and CaCO3 with Zn, Cu, Cd in nonbioavailable fraction and Zn, Cu in total. Textural parameters also play an important role for fixation of the above heavy metals. The significant loading of clay content with heavy metals demonstrates that the deposition of fine grained materials is the most important physical control on the abundance and distribution of these metals in nonbioavailable fraction [60,61]. Therefore, this factor may be termed as “Clay Factor” Factor 3 shows a variance of about 5.63%, where Fe, Mn oxyhydroxide play a major role for controlling the dynamics of metals

such Fe, Mn, Co and Ni in nonbioavailable and total fractions. Fe and Mn oxides/hydroxides singly or in combination seem to play important role in scavenging heavy metals [6]. The present study reveals that all the heavy metals are scavenged by Fe, Mn oxyhydroxide colloids but in different degrees. Further the association of nonbioavailable fraction of metals with total metals, reveals that major portion these above metals (except Ni) are contributed from lithogenic source. Therefore, this factor may be termed as “Fe–Mn hydroxide or Lithogeneous Factor”. Note that Fe, Mn, Ni in total and Fe, Ni in nonbioavailable fraction are loaded both factor 3 and factor 1. Metals such as Zn, Cu in total and Zn in nonbioavailable fraction that express moderately to high loadings with both factor 2 and factor 1, are related to more than one controlling factors. Factor 4, is strongly loaded with the textural parameters like sand and silt, which are inversely related to each other. This factor contributes 4.55% of the total variance and may be termed as “Textural Factor”. 4.3.2. Cluster analysis Cluster analysis (CA) allows the grouping of sampling sites on the basis of the similarities of heavy metals in bioavailable fraction. Hierarchical agglomerative CA was performed on the normalized data set by means of Ward’s method, using Euclidean distances as a measure of similarity. This method was selected because it possesses a small space distorting effect, uses more information on cluster contents than other methods and has been proven to be an extremely powerful grouping mechanism [12,62].

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as these metals have special affinity towards carbonate and may co-precipitate with its minerals. The present study suggests that colloids of Fe–Mn oxides act as efficient scavengers for metals like Zn, Pb, Cu, Cr, Co and Ni. While organic matter and CaCO3 have been found to be more effective scavenger for Cu and Cd respectively. Cadmium is mostly bound to first three fractions in the non residual phase, which indicates the bioavailability of this metal to the aquatic organisms in the studied river. This suggests that Cd is highly mobile and is under high environmental concern. SQGs reveal that toxic metals like Cd, Ni and Pb are of concern in the present study area and which may occasionally be associated with adverse biological effects. Risk assessment code (RAC) suggests that concentration of Cd is posing a high risk to the environment at some polluted stations [12] in the study area. Because of the toxicity and availability of cadmium, it can pose serious threat to the ecosystem. While metals such as Cr, Cu, Co, Ni and Pb in the sediments come under medium category in the above polluted stations. Factor analysis demonstrates the dynamics and contribution of bioavailable fraction of metals in the sediments by suggesting four different factors such as “Anthropogenic Factor”, “Clay Factor”, “Fe–Mn hydroxide or Lithogeneous Factor” and “Textural Factor”. Factor analysis reveals that the enrichment of heavy metals in bioavailable fraction are mostly contributed from anthropogenic sources such as municipal sewages/industrial effluents discharged from three major townships and two fertilizer industries. Further this study suggests that major portion of Cr, Pb, Zn, Ni and Cd are contributed from anthropogenic factor. Cluster analysis clearly distinguishes the contributing sites which are responsible for the enrichment of bioavailable fraction of metals and associated with environmental risk. Fig. 4. Dendrogram showing relationship among heavy metals (bioavailable) contributing sites.

This analysis for metal concentrations in bioavailable fraction is rendered as dendrogram (Fig. 4), where all 31 sampling sites of the river estuarine system are clustered into five different groups depending upon the enrichment of metals in bioavailable fraction. The sites in groups have similar characteristics features and anthropogenic/natural background source types. The first and second groups are characterized as anthropogenic contributing sites. Group I is related with the station (St. No. 23) affected by industrial effluents from Oswal plants and station (St. No. 25) affected by industrial effluents from PPL along with municipal sewage from Paradip township, which are categorized as group of most contaminated stations. Group-II (St. Nos. 5, 16, 27, 24) is related with the stations affected by the sewage from Cuttack, Sambalpur and Paradip townships. Group-III (St. No. 6 and 15) is related with moderately contaminated sites, where as group-IV is associated with estuarine characteristics (St. Nos. 21, 30, 22, 29, 31 and 20) and moderately contaminated (St. No. 4) stations. Group V is related with less or non contaminated sites. The above results reveal that there is a medium to high environmental risk in the above sites of the river estuarine systems present in group I and II. This indicates that these sites are the contributing sources for the bioavailable fraction of metals in the present study. 5. Conclusion Geochemical speciation data of sedimentary heavy metals suggest that high environmental risk of Cd, Ni, Co and Pb, is due to their higher availability in the exchangeable fraction, which poses an adverse impact on aquatic biota. The metals like Cd, Co, Mn, Cu, Zn, Ni and Pb represent an appreciable portion in carbonate phase,

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