Study of seasonal variations and risk assessment of selected metals in sediments from Mangla Lake, Pakistan

Journal of Geochemical Exploration 125 (2013) 144–152

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Study of seasonal variations and risk assessment of selected metals in sediments from Mangla Lake, Pakistan Muhammad Saleem, Javed Iqbal, Munir H. Shah ⁎ Department of Chemistry, Quaid-i-Azam University, Islamabad 45320, Pakistan

a r t i c l e

i n f o

Article history: Received 4 December 2012 Accepted 12 December 2012 Available online 21 December 2012 Keywords: Sediment Metal Risk assessment Sediment quality guidelines Multivariate analysis

a b s t r a c t Composite sediment samples were collected from Mangla Lake, Pakistan, in order to determine the seasonal variations in the concentrations of selected metals (Ca, Cd, Cr, Cu, Fe, Mg, Mn, Pb and Zn) and to evaluate the associated risk assessment. Average metal levels in acid-extract of the sediments revealed similar decreasing trend during summer and winter: Ca>Fe>Mg>Mn>Zn>Cr>Pb>Cu>Cd. Generally, elevated metal levels were observed during winter. Metal pollution index was evaluated using enrichment factor (EF) and geoaccumulation index (Igeo), which showed significantly higher contamination by Cd and Pb. Association with adverse biological effects to aquatic biota was also assessed using the classification of the sediments and sediment quality guidelines. Pb exceeded the threshold effect level (TEL) and Cd even exceeded the probable effect levels (PEL) during the both seasons, whereas, Cu and Cr exceeded the TEL levels during winter and Zn exceeded the limits during summer. However, potential acute toxicity and PELq assessment for the sediments demonstrated that the risk for the benthic biota was insignificant. Multivariate principal component analysis and cluster analysis evidenced considerable anthropogenic contribution of the metals in sediments during both seasons. The sediments were also extracted with a weak electrolyte solution (0.1 M Ca(NO3)2) to predict the bioavailability of the metals which revealed that Cd and Pb were the most bioavailable, while Fe and Mn were the least bioavailable. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Sediments show great capacity to accumulate and integrate the metals even from low concentrations in the overlying water column. Accumulation of the metals in sediments is dependent on the properties of the adsorbed chemicals and the prevailing physicochemical conditions (ElNemr et al., 2007; Tam and Wong, 2000). Although all the pollutants adsorbed on the sediments are not bioavailable, certain mechanisms such as, direct consumption from the benthic fauna, sediment resuspension, desorption, redox reactions or biodegradation of the sorptive substance may induce the release of pollutants back to the water column (Hakanson, 1980; Soares et al., 1999; Wright and Mason, 1999). Hence, sediments may act as potential sinks or sources of various contaminants in the aquatic ecosystems under different environmental conditions (Adams et al., 1992; Christophoridis and Fytianos, 2006). Metal contamination of surface sediments could directly affect the water quality, resulting in potential consequences to the food chain and ultimately to the human health. Therefore, along with total metal concentrations, estimation of the biologically available fractions is important, which helps to assess the potential for mobilization of the metals at contaminated sites and their availability to other organisms

⁎ Corresponding author. Tel.: +92 51 90642137; fax: +92 51 90642241. E-mail addresses: [email protected], [email protected] (M.H. Shah). 0375-6742/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.gexplo.2012.12.006

(An and Kampbell, 2003; Rodrigues et al., 2010). Many chemical extraction procedures have been proposed to estimate the levels of metals in soils or sediments, which may be directly or indirectly available to organisms. Generally, weak acids/electrolytes are employed to extract the bioavailable metal content in soils/sediments (An and Kampbell, 2003). The distribution of metals within the aquatic environments is governed by complex processes of material exchange affected by various anthropogenic activities or natural processes including atmospheric inputs, soil erosion, biological activities, water drainage and discharge of urban and industrial wastewaters (Ip et al., 2007; Leivouri, 1998). Major sources of the metals in the environment are discharge of metal containing waste, industrial effluents, smelting and metallurgical processes, landfill leachates, agrochemicals and secondary precipitation of airborne particulate matter (Bandl, 1995). Some of the metals are of critical ecological significance due to their toxicity, resistance to degradation and their consequent tendency to bioaccumulate (Diagomanolin et al., 2004). In most of the cases, trace metals exert their toxicity by competing with essential minerals for active enzyme or membrane protein sites and by reacting with biologically active groups, interfering with the photosynthetic processes and affecting the composition of a plankton community (Rai et al., 1981; Walsh, 1978). Major objectives of the present study were to examine the seasonal distribution and covariations of the selected metals (Ca, Cd, Cr, Cu, Fe, Mg, Mn, Pb and Zn); to predict the bioavailability of the metals; and to find out the potential sources of these metals in the surface

M. Saleem et al. / Journal of Geochemical Exploration 125 (2013) 144–152

sediments collected from Mangla Lake, Pakistan. The study was also intended to evaluate the level of anthropogenic contamination and enrichment of the metals utilizing various indices and to assess the ecological risk assessment associated with the measured metal levels. The plausible association between the contamination of the sediments and the adverse biological effects to aquatic biota based on the sediment quality guidelines would also be investigated. It is anticipated that the study would provide a baseline data regarding the distribution, accumulation and contamination of the selected metals in the sediments and would help to reduce the contamination by identifying the major pollution sources. It would also helpful to design the pollution abatement strategy to control the inflow of pollutants into the water reservoir.

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2. Materials and methods 2.1. Study area Mangla Lake, Pakistan, is the 12th largest Lake in the world and the map (Fig. 1) showing its location is taken from Pakistan Digital Databank (Khan et al., in press). It was built across the Jhelum River in Mirpur district of Azad Jammu and Kashmir, Pakistan. The main structures of the Lake include 4 embankment lakes, 2 spillways, 5 power-cum-irrigation tunnels, a 1000 MW power station, upper Jhelum canal and a canal to Jhelum River. The main Lake is 3140 m long and 138 m high (above core trench) with a reservoir of 253 km2. The present gross storage capacity has declined to 4.75 million acre feet (5.86 km3)

Fig. 1. Location of the study area.

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from the actual design of 5.88 million acre feet (7.25 km3) due to sedimentation. Average sediment deposition rate in recent years ranged from 46.08 to 32.05 million cubic meters per year (Butt et al., 2011). The Lake was designed primarily to increase the amount of water that could be used for irrigation from the flow of the Jhelum River and its tributaries, which irrigate many thousand acres land. The possible sources of metal contamination are untreated urban/domestic wastes, industrial effluents, agricultural run off and geological weathering. So far, no detailed study related to the metal contamination of the lake sediments has been reported. 2.2. Sample collection and preservation Sampling of surface sediments was carried out during summer and winter 2011 from the Mangla Lake. A total of 180 composite surface sediment samples (1–10 cm top layer) were collected during both seasons (90 in each season) in pre-cleaned Ziploc polythene bags using a snapper (Φ 5 cm). The above water from the samples was removed manually and the samples were kept in airtight plastic ice-cold containers. Each composite sample was composed of 5–10 sub-samples collected from an area of 50–100 m 2. Composite sampling is generally preferred for the assessment of inorganic contaminants in the sediments with the potential advantages of improved coverage of the area without increasing sample number, more information about average contaminant concentration, ability to detect hot spots, more representative estimates of mean concentrations, accurate exposure point concentrations and reduced sampling cost (Carson, 2001; Correll, 2001; USEPA, 1991). Although composite sampling methodology may result in partial loss of spatial variability but considering the size of Mangla reservoir it was considered more appropriate to cover the maximum part of the lake in order to assess the overall pollution stress. Broadly, the samples were collected from three parts of the lake shown as ‘A’, ‘B’ and ‘C’ in the location map (Fig. 1) and 30 samples were collected from each part during each season. The sediment samples were oven dried, grounded, homogenized and sealed in clean polythene bags and then stored in a refrigerator until further processing (Sakai et al., 1986). 2.3. Sample preparation and analysis Sediment samples were processed to assess the acid-extractable and Ca(NO3)2 extractable concentrations of the selected metals. To evaluate the bioavailable metal contents, a single-step extraction procedure, using 0.1 M Ca(NO3)2 was applied to the sediment samples at room temperature (An and Kampbell, 2003). An aliquot of 5 g of the samples was added to 50 mL of 0.1 M Ca(NO3)2 and the extraction was performed in pre-cleaned glass vessels by shaking, using an autoshaker at 240 vibrations per minute for 16 h. A blank was also processed with the same amount of 0.1 M Ca(NO3)2 without sediment sample. Three replicate extractions were performed for each sample. The final extract was separated from the solid residue through filtration using a fine (0.45 μm pore) filter paper (An and Kampbell, 2003; Radojevic and Bashkin, 1999; Rodrigues et al., 2010). To estimate the acid-extractable metal content, 1–2 g dried sediment sample was digested in a microwave system using a freshly prepared acid mixture: 9 mL HNO3 and 3 mL HCl (USEPA, 2007). A blank was also prepared with the same amount of acids without sediment sample. The digested samples were then filtered through the fine filters and made up to 50 mL with deionized water and stored at 4 °C. Selected metals (Ca, Cd, Cr, Cu, Fe, Mg, Mn, Pb and Zn) in the acid-extract and Ca(NO3)2- extract of the sediment samples were analyzed using flame atomic absorption spectrophotometer (Shimadzu AA-670, Japan) under optimum analytical conditions. Calibration line method was used for quantification of the metals and the samples were appropriately diluted whenever required (Radojevic and Bashkin, 1999). Standard reference material (SRM-2709) was also analyzed to ensure the reliability of the

metal analysis on the instrument (Table 1). Analytical grade chemicals were used throughout the study. Deionized water was used to prepare all the reagents and calibration standards. The working standards of the metals were prepared from standard stock solution of 1000 mg/L by successive dilutions. All the measurements were made in triplicate. Some of the sediment samples were also analyzed at an independent laboratory for cross comparison and a maximum of ±2% difference was observed in the two results. 2.4. Statistical analysis Statistical methods can be used to assess the complex ecotoxicological processes by showing the relationship and interdependency among the variables and their relative weights (Bartolomeo et al., 2004; Iqbal and Shah, 2011). STATISTICA software was used for statistical analyses of the metal data (StatSoft, 1999). Basic statistical parameters such as, minimum, maximum, mean, standard error (SE) and skewness were computed along with correlation analysis, while multivariate statistics in terms of principal component analysis (PCA) and cluster analysis (CA) were also carried out. The PCA was performed using varimax normalized rotation on the data set and the CA was applied to the standardized matrix of samples, using Ward's method and the results are reported in the form of dendrogram. PCA is mainly used for data reduction and it aims at finding a few components that explain the major variations within the data. Each component is a weighted and linear combination of the original variables. CA organizes a set of variables into two or more mutually exclusive unknown groups/clusters based on combination of internal variables. The purpose of CA is to discover a system of organizing variables where each groups/cluster share properties in common. Thus, it is cognitively easier to predict mutual properties based on overall group membership (Shah et al., 2012; Zhou et al., 2008). 2.5. Estimation of pollutant indicators Anthropogenic contribution of the selected metals in the sediment samples can be estimated from the metal enrichment relative to the widely accepted background/pre-industrial levels. Different approaches to determine the metal enrichment have been reported using different rationales (Abrahim and Parker, 2008; Grant and Middleton, 1990; Loska et al., 1997). The central notion is to produce a numerical result comparing the estimated metal contents with a background level, such as the average continental crust abundances. Enrichment factor (EF) estimates the anthropogenic impact on sediments, using a normalization element in order to alleviate the variations produced by heterogeneous sediments. The reference element is selected so as to have minimum variability of occurrence or is present in such large concentrations in the studied environment, that neither small concentration variations nor other synergistic or antagonistic effects towards the examined elements are significant (Abrahim and Parker, 2008). Since the sediments from the

Table 1 Certified vs. measured concentrations of selected metals (mg/kg) in standard reference material (SRM-2709). Metal

Certified

Measured ± SDa

Ca Cd Cr Cu Fe Mg Mn Pb Zn

18900 0.38 130 34.6 35000 15100 538 18.9 106

18700 ± 300 0.35 ± 0.04 140 ± 12 35.6 ± 1.8 34800 ± 450 14900 ± 280 552 ± 13 19.7 ± 1.7 109 ± 4.5

a

For triplicate analysis.

M. Saleem et al. / Journal of Geochemical Exploration 125 (2013) 144–152

½X=Fesample

ð1Þ

½X=Fecrust

where, [X/Fe]sample and [X/Fe]crust refer, respectively, to the ratios of mean concentrations (mg/kg, dry weight) of the target metal and Fe in the examined sediments and continental earth crust (Lide, 2005). EF values were interpreted as; EF b 1 — no enrichment, EF 1 to 3 — minor enrichment, EF 3 to 5 — moderate enrichment, EF 5 to 10 — moderately severe enrichment, EF 10 to 25 — severe enrichment, EF 25 to 50 — very severe enrichment and EF > 50 — extremely severe enrichment (Abrahim and Parker, 2008; Grant and Middleton, 1990; Loska et al., 1997). The index of geoaccumulation (Igeo) enables the assessment of contamination by comparing the current and pre-industrial concentrations of the metals in earth crust (Iqbal and Shah, 2011; Loska et al., 2004). It is calculated using the following mathematical formula:  Igeo ¼ log2

Cn 1:5Bn

 ð2Þ

where Cn is the measured concentration of the metal in the sediment samples and Bn is the geochemical background value in earth crust (Lide, 2005). The factor 1.5 is introduced to minimize the effect of possible variations in the background values which may be attributed to lithogenic variations. Igeo values were interpreted as; Igeo ≤0 — practically uncontaminated, 0b Igeo b 1 — uncontaminated to moderately contaminated, 1b Igeo b 2 — moderately contaminated, 2b Igeo b 3 — moderately to heavily contaminated, 3b Igeo b 4 — heavily contaminated, 4b Igeo b 5 — heavily to extremely contaminated and 5 > Igeo — extremely contaminated (Iqbal and Shah, 2011; Loska et al., 2004). Sediment quality guidelines (SQGs) are useful to screen sediment contamination by comparing sediment contaminant concentration with the corresponding quality guidelines (Caeiro et al., 2005), which evaluate the degree to which the sediments associated chemical status might adversely affect aquatic organisms and are designed to assist the interpretation of sediment quality (Wenning et al., 2005). SQGs, including sediment quality criteria, sediment quality objectives and sediment quality standards, have been developed by various federal and provincial agencies in North America and are used in numerous applications, including designing monitoring programs, interpreting historical data, evaluating the need for detailed sediment quality assessments, assessing the quality of prospective dredged materials, conducting remedial investigations and ecological risk assessments, and developing sediment quality remediation objectives (Caeiro et al., 2005; Long and MacDonald, 1998; Long et al., 1995; Pekey et al., 2004; Smith et al., 1996). Two types of SQGs developed for freshwater ecosystems (MacDonald et al., 2000) were applied in the present study to assess the ecotoxicology of the metal concentrations in the sediments: (a) the threshold effect level (TEL) and (b) probable effect level (PEL) values. Low range value (TEL) is the concentration below which adverse effects upon sediment dwelling fauna would be infrequently/rarely expected. In contrast, the PEL represents chemical concentration above which adverse effects are likely/frequently to occur. Furthermore, toxic units were also used to normalize the toxicity of the various metals to allow comparison of their relative effects, defined as the ratio of the determined concentration to PEL value (Pedersen et al., 1998). Potential acute toxicity of pollutants (∑TUs) was calculated as the numeric sum of the toxic units (TUs). 3. Results and discussion The statistical evaluation of physicochemical parameters of the sediments during present study revealed that the sediments were

100000

Summer

A

B

C

10000

Metal Level (mg/kg)

EF ¼

slightly acidic showing mean pH values of 6.6 during both summer and winter. Generally, pH in bioleaching process of contaminated sediments depends upon the buffering capacity of the sediments depending on which metals may be released from the sediments (Bartoli et al., 2012; Chen and Lin, 2001). Average values of electrical conductivity (EC) were almost comparable during summer (10.7 mS/cm) and winter (10.3 mS/cm). A similar pattern was shown by total alkalinity (TA); average levels were 0.11 mg CaCO3/g during summer and 0.10 mg CaCO3/g during winter. Mean levels of total dissolved solids (TDS) during summer (5.3 g/L) were slightly higher than winter (5.1 g/L), which may be attributed to the climatic variations as the average temperature observed during summer (27.7 °C) was relatively higher than winter (15.6 °C). Overall, no statistically significant seasonal variability among the physicochemical parameters was noted in the sediments. Metal data in the sediments were evaluated for spatial variations during summer and winter as shown in Fig. 2. An examination of the data revealed that no significant spatial variability was observed in the metal levels from three parts of the lake designated as ‘A’, ‘B’ and ‘C’ in both seasons. Hence, more or less similar metal levels were observed in the entire reservoir which may partially be attributed to the composite sampling methodology and homogenous mixing of the pollutants in lake. Therefore, variability in the metal levels were most likely due to seasonal variations rather than spatial. The statistical distribution of selected metals in acid-extract of the sediments during summer and winter is shown in Table 2. On the average basis, the selected metals followed similar decreasing trend during both seasons: Ca> Fe > Mg >Mn> Zn >Cr>Pb> Cu > Cd. An average concentration of Ca during summer (44500 mg/kg) was moderately higher compared to its mean level during winter (41500 mg/kg). It exhibited relatively larger dispersion during summer than winter. The sediments were severely enriched (EF >10) with respect to Ca during the both seasons (Fig. 3a). Generally metals showing EF > 5 are considered as predominantly contributed by anthropogenic sources.

1000 100 10 1 0.1 Ca

Cd

Cr

Cu

Fe

Mg

Mn

Pb

Zn

100000 Winter

A

B

C

10000

Metal Level (mg/kg)

Lake are rich in Fe content, it was selected as normalization factor. The EF is calculated using the following equation (Loska et al., 1997):

147

1000 100 10 1 0.1 Ca

Cd

Cr

Cu

Fe

Mg

Mn

Pb

Zn

Fig. 2. Spatial variations of selected metal levels in the sediments during summer and winter.

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Table 2 Statistical summary of selected metals distribution (mg/kg) in acid-extract and Ca(NO3)2-extract of the sediments during summer and winter.

Acid extract

Summer (n = 90)

Winter(n = 90)

Ca(NO3)2-extract

Summer(n = 90)

Winter (n = 90)

Min Max Mean SE Skew Min Max Mean SE Skew Min Max Mean SE Skew Min Max Mean SE Skew

Ca

Cd

Cr

Cu

Fe

Mg

Mn

Pb

Zn

8540 69800 44500 3030 −0.34 29600 63800 41500 1530 0.65 65.7 161 99.4 5.66 0.82 55.7 154 104 4.59 0.01

0.05 3.62 1.33 0.18 0.63 0.35 4.08 1.52 0.17 0.99 0.01 0.18 0.09 0.01 0.01 0.01 0.24 0.13 0.01 −0.05

12.6 35.2 21.3 1.16 0.30 27.9 52.7 42.0 1.38 −0.39 0.02 0.49 0.24 0.03 0.09 0.04 1.06 0.41 0.05 0.76

4.84 26.6 13.4 1.03 0.70 11.0 36.9 23.3 1.20 0.59 0.02 0.16 0.10 0.01 0.11 0.03 0.31 0.15 0.01 0.34

3720 4180 3870 22.0 1.03 3590 3910 3800 11.8 −0.83 0.16 1.67 0.80 0.08 0.50 0.61 3.65 1.71 0.12 0.59

2160 3870 3180 107 −0.48 2830 3900 3680 37.9 −2.84 3.81 23.8 10.8 0.84 1.11 7.79 17.0 11.9 0.41 0.47

32.6 493 324 17.0 −1.24 365 1080 612 26.1 1.37 0.01 1.06 0.13 0.04 4.27 0.15 4.00 1.21 0.20 1.12

2.51 49.9 17.2 2.45 1.14 8.12 46.4 30.6 2.31 −0.52 0.17 1.58 0.90 0.06 −0.08 0.01 1.70 0.66 0.09 0.75

2.02 150 37.4 5.38 2.98 23.6 87.4 50.1 2.89 0.68 0.01 0.20 0.09 0.01 0.46 0.01 0.22 0.10 0.01 0.50

Cadmium is relatively mobile metal and its concentration is somewhat low as a contaminant in the environment where it is contributed by both natural and anthropogenic sources. Cd concentration ranged from 0.05 to 3.62 mg/kg and from 0.35 to 4.08 mg/kg with average levels of 1.33 and 1.52 mg/kg during summer and winter, respectively. Slightly higher Cd levels during winter may be attributed to the variations in water capacity of the Lake; during winter water input to the reservoir is generally limited which resulted in the precipitation/enrichment of the pollutants in the sediments; thereby increasing its concentration. Relatively large dispersion of Cd during summer and winter indicated consistently varying concentration of the metal in the Lake, mostly attributed to the anthropogenic activities. Extremely severe enrichment of Cd in the sediments during both seasons was observed (Fig. 3a). The geoaccumulation index also revealed moderately to heavily contamination of sediments by Cd (Fig. 3b). Consequently, Cd emerged as a major pollutant in the sediments, indicating severe risk to the aquatic environment. The concentration of Cd in most of the samples (>73%) was observed to be higher than TEL values, whereas only few samples (4% during summer and 7% during winter) exceeded PEL values (Table 3). Average concentration of Cr in acid-extract of the sediments was observed to be significantly higher (pb 0.001) during winter (42.0 mg/kg) compared with the summer (21.3 mg/kg). As explained earlier, such noteworthy disparities in the metal levels may be attributed to the variations in seasonal inflow of the water in the Lake. In comparison with TEL values, concentration of Cr in all sediments was observed to be lower during summer, while 70% samples exceed the TEL values during winter (Table 3). Cr exhibited relatively narrow dispersion in acid-extract of the sediments. The EF showed minor enrichment during summer and moderate enrichment of the metal during winter (Fig. 3a). Copper is a micronutrient for aquatic life in freshwaters and sediments, but it becomes toxic at higher level. The average values of Cu were 13.4 mg/kg and 23.3 mg/kg in acid-extract of the sediments during summer and winter, respectively. As was noted in the previous cases, Cu contents were found to be enriched in the sediments during winter (pb 0.01). The observed concentrations of Cu were lower than TEL and PEL levels during the both seasons (Table 3). Geoaccumulation index values of Cu manifested practically uncontamination during both seasons (Fig. 3b); however, EF showed minor enrichment during summer and moderate enrichment during winter (Fig. 3a). Iron is one of the abundant metals in earth crust and its mean concentrations in acid-extract of the sediments were 3870 mg/kg and 3800 mg/kg during summer and winter, respectively. Relatively narrow dispersion was noted in acid-extract of the sediments during the both seasons. Thus no significant seasonal variations were observed for Fe

in the sediments. Moreover, Igeo demonstrated that the sediments were practically uncontaminated with respect to Fe contents during both seasons (Fig. 3b). Almost comparable levels of Mg were observed in the acid-extract of the sediments during both seasons; mean concentration of Mg was 3180 mg/kg during summer and 3680 mg/kg during winter. It showed moderately narrow dispersion in the sediments, thus, Mg contents in the sediments were not appreciably affected by the anthropogenic activities, as also manifested by Igeo and EF values, showing uncontamination and minor enrichment, respectively (Fig. 3a and b). Average concentrations of Mn were found to be 324 mg/kg and 612 mg/kg in acid-extract of the sediments during summer and winter, respectively. Like most of the cases discussed previously, Mn was found to be enriched in the sediments during winter (pb 0.001). The comparative distribution of Mn revealed narrow distribution in acid-extract of the sediments. Geoaccumulation index exhibited uncontamination of sediments during the both seasons (Fig. 3b), while, EF showed moderate to severe enrichment in acid-extract of the sediments (Fig. 3a). Lead is a toxic metal and its low concentrations might pose a threat to life in an aquatic environment in comparison with other metals. The mean level of Pb was 17.2 mg/kg and 30.6 mg/kg in acid-extract of the sediments during summer and winter, respectively. On the average basis, Pb contents during winter were significantly higher (p b 0.05) than summer. The measured levels of Pb in most of the sediment samples (88%) were found to be lower than TEL and PEL levels during summer; however, about 53% samples exceeded the TEL values during winter (Table 3). Additionally, Pb manifested relatively broad dispersion during both seasons which may be attributed to anthropogenic intrusions. EF revealed severe enrichment of Pb in sediments during summer and very severe enrichment during winter (Fig. 3a), while geoaccumulation index indicated moderate contamination of the sediments by Pb (Fig. 3b). Zinc is a micronutrient in aquatic organisms in freshwaters and sediments, but it becomes toxic at higher concentrations. Its mean levels were 37.4 mg/kg and 50.1 mg/kg in acid-extract of the sediments during summer and winter, respectively. The measured levels of Zn were found to be lower than TEL and PEL values in both seasons (Table 3). Geoaccumulation index indicated practically uncontamination of Zn in sediments (Fig. 3b), while EF revealed moderately severe enrichment and severe enrichment during summer and winter, respectively (Fig. 3a). Correlation study can provide interesting information on the sources and pathways of the pollutants. The correlation study for the selected metals in acid-extract of sediments during summer exhibited significantly strong relationships between Mg–Cu (r =0.81), Fe–Cu (r = 0.77),

M. Saleem et al. / Journal of Geochemical Exploration 125 (2013) 144–152

Enrichment Factor (EF)

1000

a) 150 129

Summer

Winter

100 32 18

16 15 9.6

10

6.1

5.8 3.3

3.0

7.8

11

5.0 2.0

2.3

1

0.1 Ca

Cd

Cr

Cu

Mg

Mn

Pb

Zn

Geoaccumulation Index (Igeo)

6

b) 2.6

Winter

2.8

2 0.5

0 -0.3

-0.5 -0.6

-1.1 -1.5

-1.2

-2

-2.0

-1.9 -2.8

-2.1

-2.7 -3.2 -3.5

-4 -4.4 -4.5

-6

Ca(NO3)2-extract / Acid-extract (%)

Summer

4

Ca

Cd

Cr

Cu

Fe

Mg

Mn

Pb

Zn

100

c) 10

Summer

6.51

Winter

8.33 5.24 2.14 1.12 0.98

1

0.72 0.64 0.34 0.32

0.25 0.22

0.24

0.20

0.20

0.1 0.04

0.04

0.02

0.01 Ca

Cd

Cr

Cu

Fe

Mg

Mn

Pb

Zn

Fig. 3. Seasonal variations in (a) enrichment factors (EF), (b) geoaccumulation indices (Igeo) and (c) bioavailability of selected metals in the sediments during summer and winter.

Zn–Cu (r = 0.76), Fe–Cr (r = 0.74), Fe–Zn (r = 0.68), Mn–Fe (r =0.65), Mg–Fe (r=0.54), Mn–Cu (r=0.51), Cu–Cr (r=0.50), Mg–Zn (r=0.49) and Mn–Cr (r=0.46). It indicated strong associations of these metals in the sediments where they might share common sources. Among the selected metals, Cu, Fe and Zn revealed strong relationships with other metals which may be an indicator of their multi-source contribution in the sediments. However, Cd exhibited inverse correlation with Zn while Pb showed negative relationships with Mn, Zn, Mg, Cu, Fe and Cr. These negative correlations indicated probable diverse and anthropogenic sources of Cd and Pb in the sediments compared with other metals. In case of acid-extract during winter, significantly strong correlations were observed between Zn–Cu (r=0.96), Fe–Cu (r=0.79), Zn–Fe (r=0.79), Mg–Fe (r=0.77), Mg–Cu (r=0.71), Mg–Zn (r=0.67), Mn–Fe (r= 0.58) and Mn–Zn (r=0.53), thus indicating strong interrelationships among these metals in the sediments. The correlation study hence

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showed mutual variations of the metal levels in the sediments during both seasons. On comparative basis, major associations among the metals remained the same during both seasons. The complex nature of the data will further be elaborated with the help of multivariate methods to find out the possible associations of the selected metals in the acid-extract of the sediments during summer and winter. Multivariate PCA and CA were employed in order to understand the complex nature of the relationships among the metals in acid-extract of the sediments. The PC loadings extracted by varimax normalized rotation of the data-set of selected metals in acid-extract of the sediments during summer and winter are shown in Table 4, whereas, the corresponding CA of selected metals based on Ward's method applied on the correlation matrix of the metals are shown in the form of dendrogram in Fig. 4. In case of acid-extract of the sediments during summer, three principal components (PCs) were obtained with eigen values greater than 1, together explaining about 73% variance of the data. First PC exhibited elevated loadings of Fe, Cu, Mg, Mn, Zn and Cr which also constituted a strong cluster, mostly contributed by the lithogenic activities. PC 2 indicated the highest loadings for Ca along with significant contributions of Cr and Zn, while, third PC revealed higher contributions of Cd and Pb. CA showed a shared cluster of Ca, Pb and Cd. These metals were believed to be associated with the anthropogenic activities, particularly industrial and agricultural activities (Demlie and Wohnlich, 2006; Gowd and Govil, 2007). Four PCs were obtained in case of acid-extract of the sediments during winter with eigen values greater than 1, together explaining more than 84% variance of the data (Table 4). First PC exhibited maximum loadings of Zn, Cu, Fe and Mg, which also constituted a strong cluster, attributed to the lithogenic sources. PC 2 indicated significant loadings in favor of Pb and Mn, while PC 3 and 4 revealed higher contributions of Cr and Ca-Cd, respectively. The related CA demonstrated shared clusters of Pb–Cr and Mn–Cd–Ca, indicating anthropogenic contamination of the sediments predominantly contributed by the industrial and agricultural activities. Overall, relatively higher anthropogenic contribution of the pollutants was observed during winter compared with the summer. Possible sources of Cd could be nonpoint sources such as application of phosphate fertilizers as well point sources like pigment and metal works (Demlie and Wohnlich, 2006; Sayadi and Sayyed, 2011). Environmental levels of Cd are greatly enhanced by the existing industrial operations as it is commonly used as a pigment in paint, plastics, ceramics and glass manufacture (Gowd and Govil, 2007). Pb has long been recognized as an industrial hazard (Krishna and Govil, 2007) and the elevated concentrations of Pb may be attributed to fertilizer and paint industries. Lead is released from smelting, motor-vehicle exhaust fumes and from corrosion of lead pipe work (Gowd and Govil, 2007). Pb is used in batteries, ammunition, solder, piping, pigments, insecticide and alloys. High concentration of Cr could be from tanneries, pharmaceuticals, pigments, metal works or a combination of all (Kumar et al., 2008). In the current study, Cd, Cr, Ca, Mn and Pb may be contributed by industrial effluents, domestic wastes, atmospheric deposition and agricultural activities. The Ca(NO3)2-extractable concentrations of the metals are described in Table 2, where Cd concentration was the highest, followed by Pb, Cr, Cu, Mg, Ca, Zn, Mn and Fe the least. The order of the extractable metal levels was not the same as the order of the acid-extractable fractions of the metals. There was no direct relationship between both extractable fractions. The Ca(NO3)2-extractable metal recoveries were within approximately 9% of the acid-extractable metal concentrations, as shown in Table 2 and Fig. 3c. Cadmium indicated the greatest extraction efficiency and Fe the least. Since metal bioavailability is related to metal solubility, extractable metal concentrations may correspond to the bioavailable metal concentrations. The results demonstrated that Cd and Pb were the most available metals; Cr, Cu and Zn were moderately extracted; and Fe and Mn were the least. Nonetheless, overall extraction efficiencies of Cd, Ca, Fe and Mn were found to be greater during winter, whereas the remaining metals exhibited more extraction efficiencies during summer.

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Table 3 Description of sediments classification and sediments quality guidelines (SQGs) in acid-extract of the sediments during summer and winter.

Sediments classification

non-polluted moderately polluted heavily polluted TEL PEL non-polluted moderately polluted heavily polluted bTEL ≥TEL and b PEL >PEL non-polluted moderately polluted heavily polluted bTEL ≥TEL and b PEL >PEL

Sediments quality guidelines (SQGs) Percentage of samples

Summer

Winter

Cd

Cr

Cu

Fe

Mn

Pb

Zn

– – >6 0.596 3.53 97 3 – 23 73 4 97 3 – 20 73 7

b25 25-75 >75 37.3 90 83 17 – 100 – –

b25 25-50 >50 35.7 197 97 3 – 100 – – 70 30 – 97 3

b17000 17000-25000 >25000 – – 100 – – – – – 100

b300 300-500 >500 – – 30 70 – – – –

b40 40-60 >60 35 91.3 93 7 – 88 12 – 73 27 – 47 53 –

b90 90-200 >200 123 315 97 3 – 96 4 – 100 – – 100 – –

100 – 30 70

17 83 – – –

– – – –

where, units of metal levels are mg/kg, TEL-threshold effect level; and PEL-probable effect level.

Table 4 Principal component loadings of selected metals in acid-extract of the sediments during summer and winter. Summer PC 1

Winter PC 2

PC 3

PC 1

PC 2

PC 3

PC 4

Eigen Value 4.07 1.31 1.19 3.92 1.55 1.11 1.01 % Total Variance 45.2 14.5 13.2 43.6 17.2 12.3 11.2 % Cumulative Variance 45.2 59.7 72.9 43.6 60.8 73.1 84.3 Ca −0.07 0.94 −0.03 0.07 −0.03 0.14 0.92 Cd −0.05 0.09 0.94 −0.21 0.50 0.25 0.62 Cr 0.68 0.42 −0.11 0.13 0.10 0.93 0.06 Cu 0.90 −0.03 0.23 0.95 −0.05 0.04 0.02 Fe 0.88 0.24 0.10 0.90 0.13 0.13 0.14 Mg 0.76 −0.20 −0.07 0.78 −0.19 0.22 0.35 Mn 0.73 −0.28 0.04 0.55 0.63 −0.15 0.18 Pb −0.04 0.20 0.60 −0.26 0.82 0.29 −0.03 Zn 0.70 0.41 0.31 0.95 0.04 −0.08 0.01

summer; whereas, the sediments were observed to be moderately contaminated with Cd, Cr, Cu and Pb and severely polluted with Mn during winter (Table 3). Consequently, more pollution was found in the sediments during winter than summer. In an attempt to give each sediment with a unique factor explaining its overall toxicity related to metals, PEL quotients (PELq's) were calculated as the average of each of the ratios between the concentration measured for a metal and corresponding PEL value (De Vallejuelo et al., 2010; Long and MacDonald, 1998). PELq factors facilitate decision maker's work in sediment quality assessment, and are frequently used in these kinds of studies (Leorri et al., 2008). They can be used to portray

a) Summer (Ward`s method)

Linkage Distance (Pearson r)

2.5

2.0

1.5

1.0

0.5

0.0

Zn

Mg

Cu

Mn

Fe

Cr

Cd

Pb

Ca

Cd

Ca

b) Winter (Ward`s method)

2.0

Linkage Distance (Pearson r)

The sediment quality guidelines are most widely used to assess the ecotoxicology of sediments. This approach is based on the relation between measured concentrations of metals and observed biological effects, such as mortality, growth or reproduction of living organisms. TEL refers to the concentration below which adverse biological effects are expected to occur rarely, and PEL indicates the concentration above which adverse effects are expected to occur frequently. Details on how these criteria have been determined can be found elsewhere (Long and Morgan, 1990). The sediment quality guidelines for the selected metals and a classification of the samples based on these guidelines are shown in Table 3. The data from the SQG guidelines during summer suggested that Cr and Cu were found to be associated with adverse biological effects rarely; Pb and Zn were found to be associated with adverse effects occasionally; and Cd was considered to be associated with frequent adverse biological effects. In comparison, the winter data revealed that Zn was only observed to be associated with adverse effects rarely; Pb, Cr and Cu were supposed to be associated with adverse effects occasionally; and Cd was revealed to be associated with adverse biological effects frequently. Overall, Cd, Pb and Zn were considered to be associated with adverse effects during summer; while, Cd, Cr, Cu and Pb were observed to be associated with the adverse biological effects during winter. Nevertheless, more adverse effects were observed during winter than summer. Furthermore, potential acute toxicity of contaminants in sediment samples can be estimated as the sum of toxic units (∑TU). The calculated mean levels of potential acute toxicity were 0.99 and 1.51, during summer and winter, respectively. Thus more potential toxicity was observed during winter than summer. Based on the SQG of USEPA (Baudo et al., 1990), the sediments were moderately polluted with Cd, Cr, Cu, Mn, Pb and Zn during

1.5

1.0

0.5

0.0

Mg

Fe

Zn

Cu

Pb

Cr

Mn

Fig. 4. Cluster analysis of selected metals in the sediments during summer and winter.

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the sediment as non-toxic (PELq b 0.1), slightly toxic (0.1b PELqb 0.5), moderately toxic (0.5b PELqb 1.5) and highly toxic (PELq> 1.5). In the present study, all the sediments were found to be slightly toxic during summer and winter. However, the mean values of PELq during summer and winter were observed to be 0.2 and 0.3, respectively, indicating that the sediments were more toxic during summer than winter. 4. Conclusions The statistical distribution of selected metals in the sediments samples was mostly random and associated with larger dispersion during both seasons. However, significantly higher levels of Cr, Cu, Mn, Pb and Zn were observed during winter compared with the summer. No significant spatial variations in the metal levels were observed in the sediments. Cd and Pb were the most Ca(NO3)2 extractable metals, while Fe and Mn were found to be the least. The correlation study revealed diverse mutual variations of selected metals in acid-extract of the sediments. Among the selected metals, Cd, Pb, Ca and Zn were severely enriched; Cr, Cu and Mn were moderately enriched; and Mg revealed no enrichments in the sediments during the both seasons. Geoaccumulation index revealed moderate contamination of Cd and Pb during both seasons. The sediments were classified as moderately polluted with respect to Mn, Cr, Cu, Pb and Cd during summer; while, Cr, Cu and Cd were moderate pollutants and Mn was heavily pollutant during winter. The source apportionment carried out by PCA and CA evidenced prevailing anthropogenic contributions of some selected metals in the sediments. Association with adverse effects to aquatic organisms was determined, using the classification and quality guidelines of the sediments (SQGs). Cd and Pb were found to be associated with frequent adverse biological effects and occasional effects during both seasons; Cr and Cu were assumed to be related with occasional adverse biological effects during winter; and Zn was associated with occasional adverse biological effects during summer. However, potential acute toxicity and PELq assessment for the sediments demonstrated that the risk for the benthic biota was insignificant. Acknowledgements The research fellowship awarded by Quaid-i-Azam University, Islamabad to carry out this project is thankfully acknowledged. We are also grateful to the administration of Mangla Lake, Pakistan for their cooperation and help during the sampling campaign. References Abrahim, G.M.S., Parker, R.J., 2008. Assessment of heavy metal enrichment factors and the degree of contamination in marine sediments from Tamaki Estuary, Auckland, New Zealand. Estuarine, Coastal and Shelf Science 136, 227–238. Adams, W.J., Kimerle, R.A., Barnett, J.W., 1992. Sediment quality and aquatic life assessment. Environmental Science and Technology 26, 1865–1875. An, Y.J., Kampbell, D.H., 2003. Total, dissolved, and bioavailable metals at Lake Texoma marinas. Environmental Pollution 122, 253–259. Bandl, H.B., 1995. Heavy metals in the environment: origin interaction and remediation. Elsevier, London. Bartoli, G., Papa, S., Sagnella, E., Fioretto, A., 2012. Heavy metal content in sediments along the Calore river: relationships with physical-chemical characteristics. Journal of Environmental Management 95, S9–S14. Bartolomeo, A.D., Poletti, L., Sanchini, G., Sebastiani, B., Morozzi, G., 2004. Relationship among parameters of lake polluted sediments evaluated by multivariate statistical analysis. Chemosphere 55, 1323–1329. Baudo, R., Giesy, J.P., Muntao, M., 1990. Freshwater sediment quality criteria: toxicity bioassessment in sediment: chemistry and toxicity of in place pollutants. Lewis Publishers, Ann Arbor, MI. Butt, M.J., Mahmood, R., Waqas, A., 2011. Sediments deposition due to soil erosion in the watershed region of Mangla Dam. Environmental Monitoring and Assessment 181, 419–429. Caeiro, S., Costa, M.N., Ramos, T.B., Fernandes, F., Silveira, N., 2005. Assessing heavy metal contamination in Sado Estuary sediment: an index analysis approach. Ecological Indicators 5, 151–169. Carson Jr., J.H., 2001. Analysis of composite sampling data using the principle of maximum entropy. Environmental and Ecological Statistics 8, 201–211.

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