Assessment of heavy metals in sediments from a ... - Springer Link

Environ Monit Assess (2011) 172:407–417 DOI 10.1007/s10661-010-1343-5

Assessment of heavy metals in sediments from a typical catchment of the Yangtze River, China Ying Wang · Zhifeng Yang · Zhenyao Shen · Zhenwu Tang · Junfeng Niu · Fan Gao

Received: 11 March 2009 / Accepted: 18 January 2010 / Published online: 6 February 2010 © Springer Science+Business Media B.V. 2010

Abstract An intensive investigation was conducted to study the accumulation, speciation, and distribution of various heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in sediments from the Yangtze River catchment of Wuhan, China. The potential ecological risks posed by these heavy metals also were estimated. The median concentrations of most heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) were higher than the background values of soils in Wuhan and were beyond the threshold effect level (TEL), implying heavy metal contamination of the sediments. Carbonatebound Cd and exchangeable Cd, both of which had high bioavailability, were 40.2% and 30.5% of the total for Cd, respectively, demonstrating that Cd poses a high ecological risk in the sediments. The coefficients of the relationship among Pb, Hg, and Cu were greater than 0.797 using correlation analysis, indicating the highly positive correlation among these three elements. Besides,

total organic carbon content played an important role in determining the behaviors of heavy metals in sediments. Principal component analysis was used to study the distribution and potential origin of heavy metals. The result suggested three principal components controlling their variability in sediments, which accounted for 36.72% (factor 1: Hg, Cu, and Pb), 28.69% (factor 2: Cr, Zn, and Ni), and 19.45% (factor 3: As and Cd) of the total variance. Overall, 75% of the studied sediment samples afforded relatively low potential ecological risk despite the fact that generally higher concentrations of heavy metals relative to TEL were detected in the sediments. Keywords Heavy metal · Contamination · Potential ecological risk assessment · Sediments · Yangtze River

Introduction

Y. Wang · Z. F. Yang (B) · Z. Y. Shen · Z. W. Tang · J. F. Niu · F. Gao State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, People’s Republic of China e-mail: [email protected] Y. Wang e-mail: [email protected]

Heavy metals are serious pollutants because of their toxicity, persistence, and nondegradability in the environment (Olivares-Rieumont et al. 2005; Brunner et al. 2008; Idris et al. 2007; Morin et al. 2008). Over the past century, heavy metals have been discharged into the world’s rivers and estuaries as a result of rapid industrialization (Chen et al. 2004) and have accumulated in sediments. Contaminated sediments, in turn, can act as sources

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of heavy metals, imparting them into the water and debasing water quality (Zhong et al. 2006; Atkinson et al. 2007). To assess the ecological risks of heavy metals, a geochemical sediment survey is required to illustrate the distribution, sources, and enrichments of heavy metals in sediments. To date, many researchers have conducted extensive surveys of heavy metal contamination in sediments (Meybeck et al. 2007; Osán et al. 2007). The results demonstrated that accumulation of heavy metals has occurred in sediments of different regions. For example, Feng et al. (2004) reported that heavy metal contamination existed in the Yangtze River intertidal zone and that the intensity of accumulation increased significantly with time. Farkas et al. (2007) investigated the spatial and temporal trends of heavy metal loads in the surface sediments of the River Po in Italy, which has been polluted by Cd, Pb, and Zn. Although the quantification of heavy metal concentrations conducted in these studies can provide a general estimation of the overall intensity of heavy metal contamination in sediments, such data cannot provide useful information about the chemical nature or potential mobility and bioavailability of a particular element. Thus, the analysis of heavy metal speciation, which offers a more objective assessment of an element’s actual environment impact, is critically important (Relic’ et al. 2005; Cuong and Obbard 2006). The assessment of the potential ecological risk of heavy metal contamination was proposed as a diagnostic tool for water pollution control purposes as a result of the increasing content of heavy metals in sediments and their subsequent release into the water, which could threaten ecological health. Presently, the method of measuring the potential ecological risk index (Hakanson 1980) is attracting more attention and has been widely used. Compared with other methods, such as the geoaccumulation index, the pollution load index, and the excess after regression analysis (Ray et al. 2006; Farkas et al. 2007), the potential ecological risk index benefits from the inclusion of a toxicresponse factor for a given substance; thus, this method can be used to evaluate the combined pollution risk of multiple types of heavy metals to the ecological system.

Environ Monit Assess (2011) 172:407–417

The Yangtze River—the largest river in China and the third largest in the world—flows 6,300 km from the Qinghai–Tibet Plateau to the East China Sea. Wuhan, which is located in the middle reach of the Yangtze River, is the industrial and economical center of the Hubei Province in central China. The Yangtze River catchment of Wuhan is the direct source of drinking water for this region and areas downstream. However, severe environmental pollution, especially heavy metal accumulation, in Wuhan has occurred as a byproduct of a thriving and prosperous economy during the past two decades. Surveys of heavy metal contamination in this area rarely have been conducted, so implementing such studies has become extremely important. This study focused on determining the accumulation, distribution, and speciation of heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in sediments from the Yangtze River catchment of Wuhan. Principal component analysis (PCA) and correlation analysis (CA) were used as the statistical tools to analyze the data. The potential ecological risk to the aquatic system of heavy metals in sediments also was assessed. The results obtained here could provide benchmark levels to test outcomes of future remediation efforts and could be used in the exploration of strategies to protect human health and the ecosystem.

Materials and methods Sample collection The Yangtze River catchment of Wuhan, containing many lakes and tributaries, is located in the middle reaches of the Yangtze River. In resent years, industry activities, such as chemical, electric plating, and refining industries, in this area have developed quickly. That not only makes the area present a thriving and prosperous economy but also causes severe environmental pollution. In this work, a survey of the mainstream of the Yangtze River and its eight main tributaries as well as seven representative lakes was conducted in the Yangtze River catchment of Wuhan. Thirteen surface sediment samples were collected in July 2005, and another 23 were collected in December


2005. Figure 1 shows details about the sampling sites. These sampling sites were determined using a global positioning system. The sediments were collected with a Van Veen grab (Eijkelkamp, the Netherlands). The top approximately 2 cm of sediment in each grab were removed and placed in a pre-cleaned aluminum box using a stainless steel spoon. The samples from each core were freezedried and then sieved through a 2-mm nylon sieve to remove coarse debris. The sediments then were ground with a mortar and pestle until all the particles passed through a 200-screen mesh. All the freeze-dried sediment samples were stored at −20◦ C until analysis. Analytical methods Metal concentrations of the samples were measured at the Institute of Geophysical and Geochemical Exploration, Chinese Academy of

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Geological Sciences, which is certificated by the China National Accreditation Board for Laboratories. The results met the accuracy demanded by the China State Bureau of Technical Supervision. The methods of metal extraction and analysis are established by the institute. A brief description of the methods is provided here. About 0.25 g of sediments were subjected to a digestion solution (5.0-mL HNO3 + 10-mL HF + 2.0-mL HClO4 ) and heated to evaporation. After cooling, the residue was digested again in the same way and then mixed with 8 mL of aqua regia. Via heating, the mixture was concentrated to 2 or 3 mL. The digested residue was brought up to a volume of 25 mL with deionized water for analysis of Cr, Cu, Ni, and Zn concentrations and mixed with 2% nitric acid for analysis of Cd and Pb using an inductively coupled plasma mass spectrometer (Thermo). The concentrations of As and Hg were analyzed by atomic fluorescence spectrometry.

Fig. 1 Map of sediment sampling sites in the mainstream of the Yangtze River (Y), the branches of the Yangtze River (B), and the representative lakes (L) in the Yangtze River catchment of Wuhan

42.00 3.50 160.00 197.00 0.49 43.00 91.00 315.00 et al. (2005) a Ni

PEL TEL

7.20 0.60 42.00 36.00 0.17 16.00 35.00 123.00 15.00 0.20 90.00 35.00 0.15 40.00 35.00 100.00 0.32 0.83 0.43 0.89 1.52 0.23 0.48 1.02 1.08 1.31 2.23 4.58 3.16 −0.58 1.91 2.33 4.97 0.81 46.74 53.16 0.40 9.72 23.77 236.02 15.44 0.98 108.00 60.03 0.26 41.86 49.19 230.39 15.20 0.65 95.00 48.50 0.14 44.00 42.50 144.50

Wuhan soilsa CV Skew SD Mean Median

29.89 3.36 296.16 343.40 1.93 56.63 141.92 1,142.10

Table 1 shows the concentration range, median, mean, SD, skew, and CV of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in the sediments from the Yangtze River catchment of Wuhan, as well as background values of soils in Wuhan, the threshold effect level (TEL), and the probable effect level (PEL). Most of the median values of studied heavy metals were greater than the TEL but lower than the PEL (As, Cd, Cr, Cu, Pb, and Zn). The median concentration of Cd was as high as 3.25 times the

As Cd Cr Cu Hg Ni Pb Zn

Distribution and speciation of heavy metals

Minimum

Results and discussion

Maximum

Descriptive data analysis was performed, including calculation of maximum, minimum, median, mean, SD, skew, and coefficient of variation (CV). PCA and CA, the most commonly used multivariate statistical methods, also were conducted using SPSS 13.0.

Heavy metals

Descriptive and multivariate analyses

Table 1 Concentrations of heavy metals in sediments from the Yangtze River catchment of Wuhan (μg·g−1 )

The speciation of the heavy metals in the sediments was assumed to consist of six operationally defined solid-phase fractions, which were obtained by selective sequential dissolution. The protocol employed in this study was based on the procedures developed by Han and Banin (1996, 1997). Particle size analysis was performed using a SALD-3001 particle analyzer [0.269–2,000 μm, relative standard deviation (RSD) < 3%; Shimadzu, Japan]. Total organic carbon (TOC) content of the sediments was determined using a Liqui TOC analyzer (Elementar, Germany). The detection limits were 1 μg/g for As and Cu, 0.02 μg/g for Cd, 5 μg/g for Cr, 2 μg/g for Ni, Pb, and Zn, and 0.002 μg/g for Hg. Quality control was assured by the analysis of duplicate samples, a reagent blank, procedural blanks, and standard reference materials. Blanks were below the detection limit, and the measurement of standards was generally better than ±5%. Repeat measurements produced values within ±10%. Analytical precision, expressed as RSD generally was better than 14%.


7.95 0.15 56.74 21.10 0.04 19.59 20.41 49.30

410


411

Partitioning of patters of heavy metals

background value of soils in Wuhan. The concentrations of As, Cr, and Ni in all the samples, Cu in 77.8% of the samples, Pb in 75% of the samples, Zn in 61.1% of the samples, Cd in 58.3% of the samples, and Hg in 36.1% of the samples exceeded the TEL. Compared with the contents of heavy metals in sediments from other major rivers in eastern China (Chen et al. 2000), the concentrations found in this study were relatively high. This finding suggests that heavy metal contamination has occurred in this region and that further investigations of speciation, sources, and ecological risk assessment of heavy metals are needed. The ecological risk of heavy metals in sediments is clearly associated with both the total content and their speciation. According to many researchers (Fernandes 1997; Li et al. 2007), the speciation of heavy metals in sediments mainly exists in six fractions, which were bound to different sediment compositions. Figure 2 displays the partitioning of the heavy metal species into exchangeable (EXC), carbonate bound (CARB), easily reducible oxides bound, organic matter bound, residual oxides bound, and residual fractions in the sediments. The EXC and CARB fractions are generally believed to have the greatest tendency toward remobilization from the sediment phase to the more bioavailable pore water phase, and consequently, they pose the most easily induced ecological risk (Fernandes 1997; Li et al. 2007).

100 80 60 40 20 0

As EXC

Cd CARB

Cr

Cu Ni Pb Heavy metals ERO

OM

Zn RO

Hg RES-R

Fig. 2 Partitioning of patterns of heavy metals in sediments from the Yangtze River catchment of Wuhan

The EXC-Cd and CARB-Cd fractions accounted for 30.5% and 40.2% of the total concentration for Cd, respectively, indicating the relatively higher ecological risk of Cd in the sediments. Although EXC-Pb and CARB-Pb, which represented 3.10% and 8.12% of the total, respectively, were not very high, much attention should be paid to Pb because of its role in environmental endocrine disruption. For Zn and Cu, EXC fractions were both lower than 1%; the CARB fractions, however, were 19.38% and 7.41%, respectively, and these could be released into water as the environmental condition changed (e.g., pH value change). As, Hg, Ni, and Cr partitioned predominately into the residual fraction, suggesting that these elements have relatively lower bioavailability. Correlation analysis Table 2 summarizes the results of the Pearson correlation analyses among the heavy metals, TOC, pH, clay, and silt contents from the sediments. Pb, Hg, and Cu were significantly positively correlated (r ≥ 0.797), and Zn, Ni, and Cr formed another positively correlated group (r > 0.5). Cd also was positively correlated with Pb, Ni, and Cu, indicating that Cd concentration may also be influenced by mining and smelting activities apart from its natural source. The correlation coefficients between As and other elements were low (r ≤ 0.384), implying that As may be influenced by other different factors. The reason is being investigated. It is generally acknowledged that pH plays an important role in governing concentrations of soluble metals (Atkinson et al. 2007), but no significant correlations between all elements and pH were observed in the sediments in this study. The range of the PH values in these samples is between 6.25 and 8.21, wherein the pH values of most sites (26 samples) is between 7.00 and 8.00. This result indicated no apparent difference in pH values for these samples. Therefore, the influence of pH values on concentrations of soluble metals is not obvious. Significant correlations between TOC and most heavy metals in the sediments suggest that TOC influenced metal binding, which may be due to strong adsorption, ion exchange, and the

Principal component analysis

1.000 1.000 0.777** −0.735**

1.000 −0.621**

chelate effect of humus on heavy metals. Clay and silt contents correlated positively with Cr, Pb, and Ni (0.421 ≤ r ≤ 0.609), implying that higher clay and silt content might enhance the adsorptions of these metals (Fukue et al. 2006).

1.000 0.671** 0.715** 0.421* 0.577** −0.266

1.000 0.616** 0.373 0.409* −0.292

1.000 0.448* 0.445* −0.376

PCA is a powerful tool for pattern recognition, classification, modeling, and other aspects of data evaluation (Csomos et al. 2002; Pardo et al. 2008), and it is one of the simplest and oldest methods for common factor analysis. These factors or axes are orthogonal linear combinations of the measurement variables and can be useful when examining or comparing the characteristics of heavy metals. When the first two axes of the ordination function are plotted, data from an experimental system with similar characteristics lie close together, whereas those with dissimilar characteristics are plotted far apart (Van Wijngaarden et al. 1995). Heavy metal data in this study were analyzed using PCA. To make the results more easily interpretable, PCA with varimax normalized rotation also was applied; this process can maximize the variances of the factor loadings across variables for each factor. Table 3 shows the component matrix and their eigenvalues. The 3D plot of the PCA loadings (Fig. 3a) illustrates that three factors accounted for 84.86% of the total variance. Factor

Table 3 Rotated component matrix (Varimax with Kaiser normalization) for heavy metal levels in sediments from the Yangtze River catchment of Wuhan Variables

* p < 0.05 ** p < 0.01 a TOC, microgram per gram b Clay, particle size < 4 μm c Silt, particle size was 4–62.5 μm

1.000 0.335 0.797** 0.690** 0.662** 0.162 0.263 −0.202 1.000 0.876** 0.461* 0.889** 0.549** 0.615** 0.181 0.339 −0.150 As Cd Cr Cu Hg Ni Pb Zn TOCa Clayb (%) Siltc (%) pH

1.000 0.296 0.199 0.120 −0.099 0.384 0.293 0.059 0.289 0.324 0.334 −0.050

1.000 0.175 0.400* 0.381 0.439* 0.550** 0.257 0.296 0.130 0.241 0.228

1.000 0.333 0.402* 0.673** 0.568** 0.750** 0.450* 0.488* 0.541** −0.347

1.000 0.674** 0.530** 0.398 0.609** 0.581** −0.131

Zn Pb Ni Hg Cu Cr Cd As

Table 2 Pearson’s correlation matrix for the metal concentrations and selected sediment parameters (n = 36)

TOCa

Clayb (%)

pH


Siltc (%)

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Hg Cu Pb Cr Zn Ni As Cd Eigenvalue % of variance Cumulative %

Component 1

2

3

0.914 0.906 0.795 0.144 0.483 0.267 −0.091 0.560 2.937 36.72 36.72

0.301 0.227 0.447 0.938 0.778 0.667 0.146 −0.051 2.295 28.69 65.41

−0.139 0.105 0.322 0.118 −0.063 0.516 0.871 0.615 1.556 19.45 84.86

PCA loadings > 0.60 are shown in bold


413

Fig. 3 The result of PCA: a Plot of PCA for heavy metal variables and b PCA ordination biplot of the 36 sampling sites and heavy metals

1 was dominated by Hg, Cu, and Pb (36.72% of the total variance). Moreover, the significantly positive correlation (Table 2) observed among these three metals suggested that these elements had almost the same source. According to distribution characteristics, high concentrations of Hg,

Cu, and Pb were observed at sites characterized by serious pollution with industrial and municipal wastewater (e.g., sites B9, B14, B15, and L7). For example, site B9 lies in the Fuhe River, where chemical, petrochemical, fertilizer, textile, iron manufacturing, and electrical machinery

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industries are located and where the population is large. At this site, large quantities of untreated industrial and municipal wastewater are discharged without treatment, which resulted in class 5 of water quality in the Fuhe River. The B14 sample lies beside the Wuhan Iron & Steel (Group) Corporation, and wastewater from smelting and chemical industries debases the water quality in this area. The B15 sample was collected from a small tributary that passes through a small industrial zone located southwest of Wuhan City. Finally, the L7 sample is located in the Longyanghu Lake, which is home to industries such as the Hanyang steel company and the Hanyang arms factory. These facts suggest that the Hg, Cu, and Pb contents that compose PC1 were related to the discharge of industrial and municipal wastewaters. Factor 2 was dominated by Cr, Zn, and Ni, which accounted for 28.69% of the total variance. Cr loading (0.938) was obviously higher than that of the other elements, which may imply a quasiindependent behavior of Cr within the group. Factor 3 was dominated by As and Cd and accounted for 19.45% of the total variance. In Fig. 3b, As and Cd were separated by a larger distance in the PCA loading plot, indicating that the two elements were poorly correlated. PCA and CA results were in agreement, as the elements of the three factors were grouped in well-defined areas in the tri-dimensional plot of the three first principal components (Fig. 3a). The grouping of the sites can be explained by the fact that levels of heavy metals in sediments depend on historical input intensity and physicochemical properties of heavy metals and on some environmental factors, which may vary among regions. The biplot in Fig. 3b shows the PCA results of the sampling sites and heavy metal component loadings. The use of a PCA biplot could be of practical significance in the qualification of pollution sources. In Fig. 3b, all the variables are separated by PCA as clearly as expected and the vectors (lines) are relatively long, indicating again that the first two factors accounted for most of the variance of all of the quantified variables. The concentration distributions of heavy metals for the 36 sampling sites also are clearly presented in Fig. 3b.


Most of the studied sites coordinated near the origin (Fig. 3b), which represented the mean concentration of all the sampling sites (Van Wijngaarden et al. 1995); this clustering showed that the concentrations of heavy metals in most sites were close to the mean values of heavy metals in the sediments. However, the heavily polluted sites can be recognized easily among all of the sampling sites. Sites L7 (1,933 μg/g) and B14 (1,430 μg/g) were dominated by Hg, which originated mainly from fuel and coal combustion (L7) and the smelting of iron and steel (B14; Muniz et al. 2004); these results suggested recent local excessive Hg input by the Hanyang industrial zone. Sites B9 (1,142 μg/g), B14 (685 μg/g), and B15 (499 μg/g) were dominated by Zn, which may be because many factories that manufacture galvanized products exist around these sampling sites. A large amount of industrial wastewater was discharged into the river at these sites, which led to higher Zn accumulation in the sediments. Ecological risk assessment With the aim of achieving a broader assessment of heavy metal pollution in the sediments of the Yangtze River catchment of Wuhan in terms of ecological risks, Hakanson (1980) developed the following quantitative approach. The potential ecological risk factor of a given contaminant (Ei ) is defined as Ei = Ti ×

Ci , C0

(1)

where Ti is the toxic-response factor for a given substance (i.e., Hg = 40, Cd = 30, As = 10, Pb = Cu = Ni = 5; Cr = 2; Zn = 1), Ci represents the metal content in the sediments, and C0 is the regional background value of heavy metals in the sediments. In the current study, the heavy metal contents of soils in Wuhan (Table 1) were used as the regional background values. The sum of the individual potential risks factors (Ei )—that is the potential ecological risk index (RI)—is the potential risk for a region. RI can be expressed as: RI =

n i=1

Ei .

(2)


According to Hakanson (1980), the following Ei and RI values give an indication of ecological risk: Ei < 40; RI < 150 = low potential ecological risk 40 ≤ Ei < 80; 150 ≤ RI < 300 = moderate potential ecological risk 80 ≤ Ei < 160; 300 ≤ RI < 600 = considerable potential ecological risk 160 ≤ Ei < 320; RI ≥ 600 = very high potential ecological risk Ei ≥ 320 = dangerous Figure 4 shows the potential ecological risk factors (Ei ) of different heavy metals in the surface sediments analyzed in this study. The Ei mean values of As, Cr, Cu, Ni, Pb, and Zn were all lower than 10, indicating that these metals posed low ecological risk for the water in the Yangtze River catchment of Wuhan. In contrast, Cd had the highest Ei mean value (147.08), and it exhibited considerable ecological risk. The mean Ei value for Hg was 69.70, suggesting that it posed moderate ecological risk in most sampling sites (55.6% of all samples). However, in some sites, such as L7, B14, B15, B9, and B4, Hg posed a higher ecological risk; that is, Hg pollution occurred mainly in tributaries of the Yangtze River catchment of Wuhan. Overall, Cd and Hg posed a higher individual ecological risk than the other

Fig. 4 Potential ecological risk factors (Ei ; the maximum, mean, and minimum values) of different heavy metals in surface sediments from the Yangtze River catchment of Wuhan

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studied metals; thus, both of these metals are of greatest concern in terms of ecological hazards in the Yangtze River catchment of Wuhan. The potential ecological risk indices (RI) were calculated to assess pollution by multiple metals in sediments in the Yangtze River catchment of Wuhan. RI values for most sampling sites (75% of the sediment samples) were lower than 300, suggesting that most areas had low and moderate ecological risk from heavy metals; however, 13.9% of the sediment samples had RI values ranging from 300 to 600, indicating high ecological risk. RI values of sediment samples from sites L7, B14, B15, and Y6 were higher than 600; these areas (11.1% of sediment samples) were exposed to rather high ecological risk from heavy metals. The highest RI value was observed at Longyang Lake (L7), which is located in the Hanyang industrial zone; this result was consistent with the analytical result from PCA. Thus, increased industrial discharge was thought to be responsible for the highest ecological risk from pollution by multiple metals.

Conclusions The concentration and speciation analysis of various heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in sediments from the Yangtze River catchment of Wuhan in China was investigated. Most of the median concentrations of heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) in the sediments were higher than the background values of soils in Wuhan and the TEL. Thus, heavy metal contamination has occurred in this region. The speciation analysis suggested that Cd exhibited the greatest carbonate bound and exchangeable fractions and consequently posed the highest ecological risk. A significantly positive correlation among Pb, Hg, and Cu was observed, and Zn, Ni, and Cr formed another group. TOC significantly influenced the concentrations of metals in sediments. PCA performed on the eight heavy metals identified three principal components controlling their variability in sediments, which accounted for 36.72% (factor 1: Hg, Cu, and Pb), 28.69% (factor 2: Cr, Zn, and Ni), and 19.45% (factor 3: As and Cd) of

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the total variance. Calculation of RI for As, Cr, Cu, Ni, Pb, and Zn (lower than 10) revealed that these elements posed low individual ecological risks at most sampling sites; Cd and Hg presented a higher risks that were 147.08 and 69.70, respectively. In terms of the multiple metal pollution effect, 75% of all the samples were exposed to low and moderate potential ecological risk of heavy metals, although generally higher concentrations of heavy metals relative to TEL were detected in the sediments. Acknowledgements The research was supported by the National Basic Research Program of the People’s Republic of China (973 Project, 2003CB415204) and the National Natural Science Fund of China (No. 50708007).

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