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Not for commercial use, personal use only Marine Pollution Bulletin xxx (xxxx) xxx–xxx

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Contamination and ecological risk assessment of trace elements in sediments of the rivers of Sundarban mangrove forest, Bangladesh M.A. Islama,⁎, A. Al-mamunb, F. Hossainc, S.B. Quraishid, K. Nahera, R. Khana, S. Dasa, U. Tamima, S.M. Hossaina, F. Nahidb a

Institute of Nuclear Science & Technology, Atomic Energy Research Establishment, Ganakbari, Ashulia, Dhaka 1349, Bangladesh Physics Discipline, Khulna University, Khulna 9208, Bangladesh c Department of Physics, Jessore University of Science & Technology, Jessore 7408, Bangladesh d Chemistry Division, Atomic Energy Centre Dhaka, 4 Kazi Nazrul Islam Avenue, Dhaka, Bangladesh b

A R T I C L E I N F O

A B S T R A C T

Keywords: Trace element Neutron activation analysis Atomic absorption spectrometry Ecological risk Multivariate statistical analysis Sundarban mangrove forest

In this study, total concentrations of 16 trace elements (Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Hg, Pb, Th and U) in sediments of the rivers of the Sundarban mangrove forest, after the catastrophic oil spill accident in the Sela river of Sundarban, were determined. The overall mean concentrations of V, Cr, Fe and Cd in surface sediments of the Sundarban are remarkably higher than available literature data of those elements. Trace element contamination assessment, using different environmental contamination indices, reveals that As, Sb, Th and U are low to moderately contaminated while Cd is moderately to severely contaminated in the sediments of this area. The multivariate statistical analyses were applied to reveal the origin and behavior of the elements during their transport in the mangrove ecosystem. High Cr, Ni, Cu and As concentrations suggest the risk of potentially adverse biological effects in the ecosystem.

1. Introduction Trace element contamination in aquatic environments has been intensively studied in recent years due to its toxicity, abundance, and persistence in the environment. Trace element, especially heavy metal, residues can accumulate in aquatic flora and fauna, which may enter into the human food chain and result in health problems (Chabukdhara and Nema, 2012; Ma et al., 2016; Wu et al., 2017). The main reason for element contamination is the increasing complex mixtures of chemicals discharged to the coastal zone from non-point sources. Sediments usually provide useful information on environmental and geochemical pollution status (Larsen and Jensen, 1989; Uluturhan et al., 2011; Tamim et al., 2016) because they are the main sink for various pollutants, including elements discharged into the environment (Dassenakis et al., 1997; N.F. Tam and Wong, 2000; N.F.Y. Tam and Wong, 2000). Recognizing the pollution characteristics of trace elements in river sediments and targeting their potential sources is of key importance for proposing effective strategies to protect watershed ecosystems. Various indices have been developed to assess the contamination and environmental risk of trace elements in surface sediments based on their total content, speciation, bioavailability and toxicity (Yang et al., 2009; Yu et al., 2011). To evaluate the combined risk of several trace elements in

⁎

sediments, the pollution load index (PLI) and potential ecological risk index (RI) have also been developed (Yang et al., 2009; Huang et al., 2013). Mangroves are diverse ecosystems that are found in sheltered estuaries and along river banks and lagoons in the tropics and subtropics. Mangroves act as a fragile link between marine and fresh water ecosystems, pollution sinks, and source of nutrient flux into the marine ecosystem (Maiti and Chowdhury, 2013). In the recent decade, mangrove ecosystem has been increasingly threatened due to the adverse effects of anthropogenic activities such as urbanization, industrialization and aquaculture (Vane et al., 2009; Ahmed et al., 2011; Chaudhuri et al., 2014). Trace element contamination and cycling poses a serious threat to the mangrove ecosystem (Wang et al., 2013; Costa-Boddeker et al., 2017). Adsorption of excessive trace element from sediments to mangrove plants may lead to contamination of the food chain (Ahmed et al., 2011; Álvaro et al., 2015). The measurement of trace element concentrations and characterization of their distribution in the mangrove ecosystem leads to better understanding of the mechanisms controlling the dispersal, accumulation and fate of the elements in the mangrove settings. The Sundarban mangrove forest, covering about 10,200 km2 area, 60% of which is in Bangladesh and the rest in India. The progressive

Corresponding author. E-mail addresses: [email protected], [email protected] (M.A. Islam).

http://dx.doi.org/10.1016/j.marpolbul.2017.07.059 Received 13 February 2017; Received in revised form 23 July 2017; Accepted 25 July 2017 0025-326X/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Islam, M.A., Marine Pollution Bulletin (2017), http://dx.doi.org/10.1016/j.marpolbul.2017.07.059

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size and homogeneous mixture using a mortar and pestle and sieved through 0.25 mm aperture to remove organic materials, stones and lumps. The homogenous powdered samples were stored in labeled glass bottles until elemental analyses.

industrial and agricultural development in Bangladesh and India, and the associated increase of toxic trace element level in the Sundarban mangrove (Ahmed et al., 2011; Silva Filho et al., 2011) demand rigorous control over their concentration and bio-magnification processes in biota. Several studies have been conducted on element pollution in the Indian part of the Sundarban mangroves, (Silva Filho et al., 2011; Banerjee et al., 2012; Bhattacharya et al., 2015; Akhand et al., 2016 etc.) but very few studies have been conducted on the Bangladesh part of Sundarban (Ahmed et al., 2011; Borrell et al., 2016; Kumar et al., 2016). However, these studies are mostly about accumulation of trace elements in aquatic organism of Bangladesh part of Sundarban. In the last few years, several oil, fertilizer and coal fly ash carrying cargo accidents occurred at the Sela and Poshur rivers inside the Sundarban of Bangladesh. Among these incidents, a catastrophic oil carrying cargo accident on December 9, 2014, spilled 350,000 l of fuel oil into the Sela river inside the Sundarban (Phillips, 2014). Since the Sela and Poshur rivers are connected to the small creeks inside the Sundarban, there are concerns over the ecological catastrophe that occurred in the Sundarban due to these accidents. In this study, contamination and ecological risk assessments of trace elements in Sundarban mangrove ecosystem of Bangladesh are conducted using various sediment quality indices and statistical approaches.

2.3. Sample analysis 2.3.1. Instrumental neutron activation analysis (INAA) For trace element determination by INAA, about 50 mg of each dried powder sample was weighed in polyethylene bag and heat sealed. Two certified reference materials (CRMs) from International Atomic Energy Agency (IAEA): Soil-7 and IAEA-SL-1 (Lake Sediment), and one standard reference material: NIST-1633b (Coal Fly Ash), along with the sediment samples, were analyzed in this study. Relative standardization method of INAA was applied for element determination. IAEA-Soil-7 was used as the standard, while IAEA-SL-1 and NIST-1633b were used as the control samples. The samples and standards were irradiated using pneumatic transfer (rabbit) system at the 3 MW TRIGA Mark–II research reactor of Bangladesh Atomic Energy Commission. Short-term and long-term types of irradiation were performed targeting radioactive nuclei with short and long-half-lives. Short irradiation of each sample/standard was performed separately at a thermal neutron flux of 1.77 × 1012 cm− 2·s− 1 for 1 min at 250 kW, whereas long irradiation was performed simultaneously with all the samples and standards at a thermal neutron flux of 1.70 × 1013 cm− 2·s− 1 for 7 min at 2.4 MW. For the calculation of trace element concentrations, the considered product radionuclides with their half-lives and gamma-ray energies are given in Table 1. In the case of long irradiation, neutron flux gradient within the sample stack was determined by irradiating three IRMM530RA Al–0.1% Au (0.1 mm foil) monitor foils placing them at the bottom, middle and top of the sample stack. After irradiation, the activities of irradiated samples and standards were measured using a high resolution HPGe detector (resolution at FWHM is 1.88 keV at 1332.5 keV of 60Co) coupled with a digital gamma spectrometry system. For long irradiated samples, first counting was performed for 1 h after a decay time of 2 days for the elements As and Sb, while the second counting was performed for 2 h after a decay time of 4–5 days for U. Third counting was performed for 3 h after a decay time of 4 weeks for the elements Cr, Fe, Co, Zn and Th. Samples and standards irradiated for a short time, first counting was performed for 300 s after a decay time of about 300 s for the elements Al and V, and second counting for 600 s after a decay time of 2 h for Mn. To determine element concentration, by considering more than one gamma-ray, the average concentration obtained by the concerned gamma-rays is reported. For correcting the 28Si(n,p)28Al and 31P(n,α)28Al interferences in determining the Al concentration using 28Al radionuclide, high purity Si (SiO2) and P (KH2PO4) chemical reagents (from Spex, USA) were prepared and irradiated with the samples. The specific activity of Si due to 28Si(n,p)28Al reaction was used to subtract the interfering activities where Si concentrations of the studied sediment samples and standards were determined by atomic absorption spectrometry (AAS) (Bernas, 1968). The Al concentration correction, due to 28Si(n,p)28Al reaction was yielded 2–4% for the samples. The P interference, due to 31 P(n,α)28Al reaction in Al determination, was calculated in the same way as stated above for IAEA-SL-1 and NIST-1633b which yielded no significant concentration corrections (< 0.01%) for Al. The P contents of the reference materials were used from their certified values for the correction. Since sediment samples contain around same level of P, as in IAEA-SL-1, therefore, no correction was applied for P interference in Al determination by INAA of the sediment samples.

2. Materials and methods 2.1. Study area Sundarban is the largest mangrove forest in the world and a significant part of it is declared as UNESCO world heritage site (FAO/ UNDP, 1998). The Sundarban mangrove forest (88°00′–89°55′E and 21°30′–22°30′N) is located in the estuary of the river Ganges in southwest Bangladesh and in the south-eastern region of the State of West Bengal in India. The forest meets the Bay of Bengal in the south. Sundarban is home to several threatened plant and animal species (including the Royal Bengal Tiger). The forest covers an area of 10,000 km2, of which 7000 km2 (70%) is land, and the remaining 3000 km2 is under water in the form of rivers, canals and creeks. Most creeks and canals flow into the large rivers, which are interconnected. This delta plain is a tide-influenced depositional system where the tropical south-west monsoon controls the freshwater discharge in the area (Goodbred et al., 2003). Mongla sea port, the second largest sea port of Bangladesh, is situated at the confluence of the Poshur river and the Mongla river. The Port is very close to the Sundarban mangrove forest. The port has trade links with almost all major ports of the world. All ships and cargo boats are carrying goods to the ports through the rivers of the Sundarban. Sundarban mangrove ecosystem is degrading day by day due to different anthropogenic activities like port activities, industrial effluents, ship breaking, fishing, tourism, agriculture, aquaculture etc. (Hussain and Acharya, 1994). 2.2. Sample collection and preparation The superficial sediment (0–5 cm) samples were collected from fifteen sampling points in December 2015, one year after the catastrophic oil spill accident in Sundarban. Three replicate samples were collected from each point and mixed into a composite sample. Geographical locations of the sampling points are presented in Fig. 1. Sampling points started from the freshwater zone near Mongla port (S-1) to saline water zone (S-15). The river bed sediments were collected using an acrylic pipe sampler during low tides. The upper 5 cm of each sample was taken using an acid-washed plastic spatula. All samples were immediately packed in acid-rinsed polyethylene plastic bags and stored at low temperature (4 °C) before sample preparation at the laboratory. The samples were dried in an electric oven at 45 °C for 72 h to gain constant weight. The dried samples were then ground into a small grain

2.3.2. Atomic absorption spectrometry (AAS) All chemical reagents were of analytical grade or of Suprapure quality (E. Merck, Germany). Double deionized water (Milli-Q System, Millipore) was used for the preparation of all solutions. The element 2

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Fig. 1. Map showing the study area and sampling sites of the Sundarban.

by cold vapor atomic absorption spectrometry (CVAAS) (Analytik jena nova AA350). Replicate samples/standards, spike samples and method blanks were used to monitor the performance of the instrument and quality of the data. To ensure quality of the analytical data, comparisons of trace element analyses results in this study to the certified values of the reference materials and the detection limits under the present experimental set-up are given in Table 2. In this study, concentrations of Ni, Cu, Cd, Hg and Pb in method blanks were 0.034, 0.0, 0.022, 0.0016 and 0.14 mg kg− 1, respectively. The spike recoveries were from 85 to 99%.

Table 1 Radionuclides with their half-lives and gamma-ray energies for INAA determination of the elements (NNDC, 2017). Elements a

Al Va Cr Mna Fe Co Zn As Sb Th U a

Radionuclide 28

Al V Cr 56 Mn 59 Fe 60 Co 65 Zn 76 As 122 Sb 233 Pa 239 Np 52

51

Half-life

Gamma-ray energy (keV)

2.24 min 3.74 min 27.7 d 2.58 h 44.5 d 5.27 y 243.9 d 26.2 h 2.72 d 27.0 d 2.36 d

1779.0 1434.1 320.1 846.8, 1810.7 1099.0, 1291.6 1173.0, 1332.5 1115.5 559.1 564.2 311.9 277.6

2.4. Assessment of element pollution 2.4.1. Enrichment factor (EF) Enrichment factor (EF) is an estimate of the anthropogenic impact on the sediments (Abrahim and Parker, 2008). The EF can be calculated by using the following equation:

Elements are determined by short irradiation of INAA.

standard solutions used for calibration were prepared by diluting stock solutions of 1000 mg/l of each element. For trace element content determinations, 1 g sediment subsamples and same standards (IAEA-SL-1 and NIST-1633b) used in INAA were digested in Teflon vessels with 7 ml HNO3 (65%) in a microwave accelerator reaction system (MARS 5, CEM, USA) following standard procedure (USEPA, Method 3051A, 2007). After microwave digestion, the sample solutions were filtered and adjusted to a suitable volume with double deionized water. The sediment extracts were analyzed for Cu and Ni by a flame atomic absorption spectrometry (FAAS), and Pb and Cd were measured using a graphite furnace atomic absorption spectrometry (GFAAS) (Varian AA Duo 240 FS and Varian 280Z). Mercury (Hg) in extracts was determined

EF =

(Metal Al)Sample (Metal Al)Background

In this study, Al concentration was used as proxy for mineralogical and grain size changes in sediments (Schropp et al., 1990; Daskalakis and O'Connor, 1995; Tam and Yao, 1998) as it allows for discrimination between natural versus enriched elements concentrations especially in the mangrove sediments. In this study, the background levels (i.e., the average contents of elements in the Earth's crust) given by Rudnick and Gao, 2014, were employed for each of the elements investigated. Moreover, since pristine areas of Sundarban mangroves lie in the inaccessible Tiger Reserve, there is no local background data available for 3

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Table 2 Comparison of results of the element analyses in this study to the certified values of those elements in the reference materials and detection limits of the elements under the present experimental set-up. Elements

Al V Cr Mn Fe Co Ni Cu Zn As Cd Sb Hg Pb Th U a

Unit

Technique

% mg kg− 1 mg kg− 1 mg kg− 1 % mg kg− 1 mg kg− 1 mg kg− 1 mg kg− 1 mg kg− 1 mg kg− 1 mg kg− 1 μg/kg mg kg− 1 mg kg− 1 mg kg− 1

INAA INAA INAA INAA INAA INAA AAS AAS INAA INAA AAS INAA AAS AAS INAA INAA

IAEA-CRM-SL-1

NIST-SRM-1633b

Detection limit

This study (n = 3)a

Certified value

This study (n = 3)a

Certified value

9.39 ± 0.60 163 ± 3 103 ± 6 3330 ± 38 6.81 ± 0.48 19.5 ± 2.0 40.4 ± 4.0 27.6 ± 2.51 221 ± 20 28.3 ± 2.6 0.29 ± 0.03 1.42 ± 0.10 142 ± 16 35.5 ± 4.1 14.2 ± 0.4 4.22 ± 0.09

8.90 170 (155–185) 104 (95–113) 3460 (3300–3620) 6.74 (6.57–6.91) 19.8 (18.3–21.3) 44.9 (36.9–53.9) 30 (24–36) 223 (213–233) 27.6 (24.7–30.5) 0.26 (0.21–0.31) 1.31 (1.19–1.43) 130 (80–180) 37.7 (30.3–45.1) 14 (13–15) 4.02 (3.69–4.35)

14.4 ± 1.1 297 ± 15 190 ± 8 129 ± 11 7.97 ± 0.26 51.0 ± 2.8 113 ± 7 105 ± 5 218 ± 10 130 ± 7 0.75 ± 0.08 5.83 ± 0.65 148 ± 2 61.2 ± 4.8 26.3 ± 1.5 9.14 ± 0.32

15.05 ± 0.27 295.7 ± 3.6 198.2 ± 4.7 131.8 ± 1.7 7.78 ± 0.23 50 120.6 ± 1.8 112.8 ± 2.6 210 136.2 ± 2.6 0.784 ± 0.006 6 143.1 ± 1.8 68.2 ± 1.1 25.7 ± 1.3 8.79 ± 0.36

0.0049 5.6 17.7 4.3 0.097 0.86 0.8 0.6 16 0.63 0.20 0.39 10 1.5 0.85 1.2

Values are mean values and uncertainties are standard deviation (1σ) for n = 3.

this system. Previous studies conducted in this system have also used upper continental crust (UCC)/shale values instead of pristine background values (Chatterjee et al., 2009; Kumar et al., 2016). The EF values close to unity indicate crustal origin and EF < 1.0 suggests a possible mobilization or depletion of elements (Zsefer et al., 1996). The EF > 1.0 indicates that the element is of anthropogenic origin. According to EF classification, the values 1.5–3.0, 3.0–5.0, 5.0–10 and > 10 are the evidence of minor, moderate, severe and very severe contamination of the elements in the sediments, respectively (Brich and Olmos, 2008).

The consensus-based SQGs were developed from the published freshwater sediment-quality guidelines that have been derived from a variety of approaches (MacDonald et al., 2000). These synthesized guidelines consist of a threshold effect level (TEL) below which adverse effects are not expected to occur and a probable effect level (PEL) above which adverse effects are expected to occur more often than not. The effect range low (ERL) represents the chemical concentration below which adverse effects would be rarely observed, but above the effects range median (ERM) concentration, adverse effects would frequently occur (Long and Morgan, 1991).

2.4.2. Pollution load index (PLI) To assess the sediment quality, an integrated approach of pollution load index (PLI) of the elements is calculated. The PLI is defined as the n'th root of the multiplications of the contamination factor (CF) of elements (Tomlinson et al., 1980) by the following equation:

2.4.5. Mean ERM Quotient (M-ERM-Q) To determine the possible biological effects of combined toxicant groups, Long et al., 2000 proposed the M-ERM-Q method. The M-ERMQ is obtained by calculating mean quotients for a large range of contaminants (Gao and Chen, 2012) using the following equation

1

n

PLI = (CF1 × CF2 × CF3 × ………×CFn ) n M‐ERM‐Q =

where, CF is the ratio between the content of each element to the background values of sediments. The PLI gives an assessment of the overall toxicity status of the sample and also it is a result of the contribution of the studied elements. PLI = 1 indicates the presence of only baseline levels of pollutants while values above one would indicate progressive deterioration of the site (Mohiuddin et al., 2011).

n i=1

n

2.4.6. Statistical analysis Correlation matrix and principal component analysis (PCA) were performed using Statistica 8.0 for Windows (StatSoft Inc. STATISTICA, 2008) in order to evaluate associations among the investigated variables in the samples. PCA was performed on the original data set (without any weighting or standardization) following the standard procedures outlined by Davis (1986). After the application of PCA, a varimax-normalized rotation is applied to minimize the variances of the factor loadings across the variables for each factor.

n

∑ Er i = ∑ Tr i

Ci ERMi

where Ci is the concentration of element i, ERMi is the ERM values for the element i and n is the number of element. According to the classification of M-ERM-Q: M-ERM-Q < 0.1 represents 9% probability of toxicity, 0.11 ≤ M-ERM-Q < 0.5 represents 21% probability of toxicity, 0.51 ≤ M-ERM-Q < 1.5 represents 49% probability of toxicity and M-ERM-Q > 1.5 represents 76% probability of toxicity (Long et al., 2000).

2.4.3. Potential ecological risk assessment Potential ecological risk index (RI) is also introduced to assess the degree of contamination of the trace elements in sediments. The equations for calculating the RI were proposed by Hakanson (1980) are as follows.

RI =

∑i = 1

× CF i

i=1

where, Eri is the potential ecological risk factor of an individual element, Tri is the biological toxic factor of an individual element and CFi is the single element contamination factor. RI is the comprehensive potential ecological risk index. The sensitivity of the biological community to the toxic substance, as well as the potential ecological risk caused by the overall contamination, is illustrated by the RI.

3. Results and discussion 3.1. Spatial variation of trace elements

2.4.4. Sediment quality guidelines (SQG) The consensus-based SQGs are used to assess possible risk arises from the trace element contamination in sediments of the study area.

The total concentrations of 16 environmentally important major and trace elements in surface sediments of the rivers of the Sundarban 4

7.46 8.50 8.05 7.05 8.28 8.02 7.05 6.53 7.17 7.44 5.58 7.38 7.36 6.97 7.61 8.50 5.58 7.36 0.73 9.9 8.15 8.0

Zn

58.1 88.8 77.8 68.7 46.8 64.8 83.6 46.2 77.2 60.7 58.9 72.9 68.0 65.8 76.9 88.8 46.2 67.7 12.3 18.2 67 95

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 Max Min Mean SD RSD,% UCCb Shalec

Sample

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 Max Min Mean SD RSD,% UCCb Shalec

5

5.5 8.2 7.5 6.6 5.9 6.3 8.0 5.8 7.2 5.6 5.8 7.0 6.6 6.3 7.4

0.24 0.27 0.25 0.22 0.26 0.25 0.22 0.21 0.23 0.24 0.18 0.23 0.23 0.22 0.24

6.80 9.04 7.48 7.15 7.42 5.80 3.40 6.30 6.86 7.90 4.73 6.70 7.40 6.30 8.20 9.04 3.40 6.76 1.39 20.5 4.8 13

As ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.30 0.52 0.42 0.41 0.42 0.32 0.19 0.28 0.31 0.35 0.23 0.35 0.41 0.37 0.45

84.1 ± 4.0 120 ± 4 104 ± 4 87.1 ± 4.1 96.4 ± 4.0 89.4 ± 3.8 84.8 ± 4.0 74.6 ± 3.2 77.1 ± 4.0 86.1 ± 4.1 55.6 ± 2.4 83.0 ± 3.6 90.7 ± 3.8 80.8 ± 3.5 90.6 ± 3.8 120 55.6 86.9 14.1 16.2 97 130

V

0.45 0.40 0.82 0.47 0.45 0.42 0.50 0.47 0.42 0.40 0.35 0.42 0.40 0.47 0.42 0.82 0.35 0.46 0.11 23.2 0.09 0.3

Cda

68.0 82.1 82.4 78.0 64.0 68.1 64.9 57.8 73.1 56.1 43.0 70.6 64.4 58.1 75.1 82.4 43.0 67.0 10.6 15.8 92 90

Cr

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.02 0.01 0.01 0.02 0.03 0.03 0.01 0.02 0.03 0.05 0.01 0.01 0.01 0.02 0.04

4.0 4.8 4.8 5.0 4.3 4.5 4.3 4.1 4.5 3.5 2.9 4.6 4.3 3.9 5.0

35 27 24 34 35 31 32 24 22 28 21 31 39 35 39

0.620 ± 0.060 1.24 ± 0.09 0.952 ± 0.086 0.718 ± 0.071 0.702 ± 0.070 0.576 ± 0.055 0.624 ± 0.054 0.964 ± 0.079 0.627 ± 0.060 1.07 ± 0.09 0.511 ± 0.051 0.354 ± 0.046 0.955 ± 0.086 0.728 ± 0.073 0.781 ± 0.078 1.24 0.354 0.762 0.235 30.8 0.4 1.5

Sb

723 ± 510 ± 505 ± 708 ± 737 ± 668 ± 689 ± 500 ± 439 ± 587 ± 422 ± 656 ± 830 ± 723 ± 818 ± 830 422 634 132 20.8 775 850

Mn ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.18 0.19 0.19 0.18 0.18 0.16 0.18 0.15 0.14 0.15 0.12 0.15 0.16 0.13 0.16

34.25 42.50 46.40 29.75 28.75 21.50 26.25 25.50 45.25 22.00 25.25 26.25 23.25 24.25 33.00 46.4 21.5 30.3 8.3 27.5 50 400

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.03 0.17 0.09 0.30 0.12 0.06 0.24 0.08 0.18 0.02 0.43 0.11 0.14 0.05 0.03

Hg (μg/kg)a

4.11 4.90 4.62 4.00 3.97 3.59 3.91 3.56 3.49 3.65 2.83 3.63 3.95 3.19 3.80 4.90 2.83 3.81 0.51 13.4 3.92 4.72

Fe (%) ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.9 0.9 0.8 0.9 0.8 0.8 0.8 0.9 0.8 0.8 0.56 0.8 0.8 0.7 0.9

15.0 ± 0.8 19.8 ± 0.2 23.6 ± 0.5 16.5 ± 0.2 15.3 ± 0.5 14.0 ± 0.2 17.5 ± 0.7 13.3 ± 0.1 16.5 ± 0.5 13.8 ± 0.4 9.8 ± 0.3 16.8 ± 0.2 15.5 ± 0.6 14.3 ± 0.4 15.8 ± 0.6 23.6 9.75 15.8 3.11 19.7 17 20

Pba

15.2 15.0 14.6 15.1 14.7 14.7 14.8 13.2 13.3 14.6 8.91 13.3 13.8 11.9 15.3 15.3 8.91 13.9 1.67 12.0 17.3 19

Co

21.7 22.2 21.9 26.7 20.8 21.6 23.3 19.7 27.2 19.0 25.6 19.6 21.7 19.0 17.5 27.2 17.5 21.8 2.85 13.1 10.5 12

Th

28.4 38.1 33.7 28.6 28.1 25.5 30.5 24.1 32.0 26.2 18.2 30.9 29.2 27.4 28.6 38.1 18.2 28.6 4.49 15.7 47 68

Nia

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

1.0 1.1 1.0 1.1 0.9 1.0 1.1 0.9 1.2 0.8 1.1 0.9 1.0 0.9 0.8

0.3 0.5 0.7 0.1 0.2 0.2 0.3 0.1 0.2 0.6 0.3 0.4 1.0 0.7 0.7

4.22 7.88 6.02 5.21 4.28 4.17 4.08 4.77 6.75 5.06 5.60 3.65 6.84 6.64 5.16 7.88 3.65 5.36 1.24 23.2 2.7 3.7

U

0.02 0.12 0.06 0.21 0.09 0.06 0.22 0.06 0.10 0.02 0.22 0.09 0.13 0.04 0.02

0.36 0.79 0.63 0.67 0.47 0.42 0.40 0.39 0.54 0.41 0.45 0.43 0.79 0.67 0.66

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

21.28 30.25 27.76 21.38 22.58 19.55 24.03 20.55 25.18 21.40 13.18 23.33 21.20 20.85 22.50 30.3 13.2 22.3 3.83 17.1 28 45

Cua

Individual uncertainties with concentrations measured by AAS are due to standard deviation (n = 3) whereas for concentrations measured by INAA are due to total uncertainties estimated in INAA for single measurement. a Measured by AAS; Except for Ni, Cu, Cd, Hg and Pb, all other elements were measured by INAA. b UCC: Upper continental crust (Rudnick and Gao, 2014). c Shale (Turekian and Wedepohl, 1961).

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

Al (%)

Sample

Table 3 Element abundances (mg kg− 1, otherwise specified) in the surface sediments of the rivers of the Sundarban.

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are > 1.5 indicate non-crustal contributions and/or non-natural weathering processes (e.g., anthropogenic influences) (Sutherland et al., 2000; Zhang and Liu, 2002; Zhang and Shan, 2008). In this study, EF ranges of the studied elements are as follows: V, 0.84–1.18; Cr, 0.67–0.98; Mn, 0.63–1.19; Fe, 0.93–1.20; Co, 0.75–1.01; Ni, 0.55–0.78; Cu, 0.69–1.04; Zn, 0.69–1.44; As, 0.82–1.83; Cd, 4.26–9.22; Sb, 0.98–3.01; Hg, 0.44–1.03; Pb, 0.84–1.41; Th, 1.79–3.56 and U, 1.49–3.03. The mean EF values for all studied elements (except As, Cd, Sb, Th and U) are < 1.5 in the sediments of the rivers, which suggests that most of the studied elements are not a major concern. The average EF values of As (1.56 ± 0.26), Sb (2.11 ± 0.59), Cd (5.67 ± 1.19), Th (2.34 ± 0.48) and U (2.21 ± 0.54) suggest anthropogenic impact on the element levels in the rivers. The EF values of As, Sb, Th and U indicate minor contamination while Cd indicates moderate to severe contamination in the sediments of the study area. The contamination factor (CF) values estimated in the sampling sites are low for Al, V, Cr, Mn, Co, Ni, Cu, Hg and Pb; moderate for As, Sb, Th and U; between low and moderate for Fe and Zn; Considerable for Cd at most of the sampling sites. The calculated PLI values due to 16 elements in surface sediments, along with the range of previous literature data of the Bangladeshi Sundarban (Kumar et al., 2016), are shown in Fig. 2. PLI values in all sites except S11 (PLI = 0.82) are > 1, ranging from 1.00 to 1.37 with average PLI = 1.10. The highest PLI values are observed in the sampling sites S2 (PLI = 1.37). According to the classification adopted by Tomlinson et al. (1980), surface sediments at all sampling sites of the Sundarban indicate deterioration in the sediment quality (PLI > 1) while S11 fall under no pollution category. For the studied area of this mangrove system, the previous literature data of PLI ranges from 0.92–1.14 with average 1.02 (Kumar et al., 2016). The sampling of that study was conducted before the several accidents occurred at the Poshur and Sela rivers including oil and coal carrying cargo accidents. Therefore, PLI values also indicate the progressive deterioration of the sediment quality due to the cargo accidents and other anthropogenic activities. Based on the different pollution indices (EF and CF), the Sundarban mangrove sediments are minor to moderately contaminated by As, Sb, Th, and U while moderately to severely contaminated by Cd.

mangrove forest are tabulated in Table 3. Aluminum, V, Cr, Mn, Fe, Co, Zn, As, Sb, Th and U were determined by INAA whereas Ni, Cu, Cd, Hg and Pb were determined by AAS. Descriptive statistics of the elemental concentrations, as well as the literature data for the UCC, (Rudnick and Gao, 2014) and Shale values (Turekian and Wedepohl, 1961) for the respective elements are also given in Table 3. Among the sampling points, most of the elements content do not vary over a long range (RSD: 9.9–19.7%), whereas some element (Mn, As, Cd, Sb, Hg and U) contents vary over a wide range (RSD: 20.5–30.8%, Table 3). This spatial variation of the trace elements can be attributed to variations in anthropogenic stresses, geo-chemical process, tidal settings and point/ non-point sources in the area (Jonathan et al., 2010). Moreover, recent oil spillage and fertilizer and coal fly ash carrying cargo accidents, occurring at the Sela and Poshur rivers inside the Sundarban, may also cause the spatial variation of the element contents. When compared with UCC and Shale values, it is observed that mean concentrations of As, Cd, Sb, Th and U show elevated values with respect to UCC, while Cd, Th and U show elevated values with respect to Shale values (Table 3).The concentration of As varied from 3.40 ± 0.19 (S7) to 9.04 ± 0.52 mg kg− 1 (S2), with a mean concentration of 6.76 ± 1.39 mg kg− 1. The concentration of Cd varied from 0.350 ± 0.007 (S11) to 0.820 ± 0.003 (S3) mg kg− 1, with a mean concentration of 0.460 ± 0.107 mg kg− 1. Overall Cd concentration values found in this study are 4 to 8 times higher than the UCC value. Elevated levels of Cd concentration have also been recorded in the Indian part of Sundarban (Akhand et al., 2016) and other mangrove forests (Li et al., 2006; Ranjan et al., 2008). The concentration of Sb varied from 0.354 ± 0.046 (S12) to 1.24 ± 0.09 (S2) mg kg− 1, with a mean concentration of 0.762 ± 0.235 mg kg− 1. Among the sampling points, relatively higher concentrations of trace elements (except Mn and Th) were found in S2 and S3 stations. Station S11 shows the overall lowest concentrations of the studied trace elements. The stations S2 and S3 are located near the Mongla port and at the confluence of the Poshur and Mongla river. The overall homogenous spatial distribution of trace elements in the surface sediments (except S-2 and S-3) can be attributed to the presence of non-point sources in the area. The areas of the sampling points S-2 and S-3 suggest occurrence of point sources in the area nearby the Mongla port (like presence of jetties and increased marine activities). Several oil, petroleum and cement industries are located near the Mongla port city. The untreated effluents from these industries may also cause higher concentrations of the trace elements in S2 and S3 points. The concentrations of studied trace elements are compared with those of other mangrove sediments all over the world (Table 4). The comparison of average concentrations of trace elements recorded herein with those available data reported in sediments from different regions of the world shows that the overall concentrations of V, Cr, Fe and Cd in surface sediments of the Sundarban are remarkably high while other elements had values comparable to many mangrove ecosystems all over the world (Table 4). Vanadium is a key element in crude oil. Higher concentrations of V recorded in this study may be due to an oil spillage accident that occurred at the Sela river of the studied area in December 2014. Higher values of Fe compared to mangroves all over the world may be attributed to the possibility of Fe precipitation as iron sulphide, which is a common phenomenon in mangrove sediments (Nobi et al., 2010) and input from anthropogenic sources (e.g., shipbreaking and port activities). The relatively high content of Cd observed in this study is due to anthropogenic sources including chemical fertilizers and pesticides used in agricultural and shrimp aquaculture activities (Ghrefat et al., 2011) near the study area.

3.3. Ecological risk assessment To assess the ecological risks of the studied trace elements, in this study different ecological risk assessment methods are used. The potential ecological risk factor (Eri) estimated with individual elements along with comprehensive potential ecological risk index (RI) are given in Table 5. Toxic response factor (Tri), SQGs as well as Mean-ERMQuitent values are also given in Table 5. Since Hakanson, 1980 did not provide the toxic response factor of Mn and Sb; in this study, their values calculated by other researchers (Xu et al., 2008; Zhao et al., 2012) based on the principles established by Hakanson are used for Eri calculation. The potential ecological risk factor (Eri) values found with all considered elements are < 40, and they posed a ‘low potential ecological risk’ for all sampling points, except for Cd (Table 5). For Cd, Eri ranged between 80 and 160 for all sampling points (considerable) except S3 and S7, where the risk was considered to be ‘high’ (Eri > 160) (Zhao et al., 2012). For all considered elements, comprehensive RI estimation was found to be ‘moderate’ (150 ≤ RI ≤ 300) at all sampling points except S3, where it is considerable (300 ≤ RI ≤ 600) at that point (Table 5). These results indicate that the area near the confluence of the Poshur river and Mongla river represents the highest ecological risk, which is most probably due to the presence of higher element levels in this area from different anthropogenic activities like ship breakings and naval transportation activities (pigments, anti-corrosive element coating etc.), agricultural and shrimp aquaculture run off (Siegel, 2002; Antizar-Ladislao et al., 2015). As shown in Table 5, the Mean ERM Quotients varied from 0.106 to 0.201. According to M-ERM-Q criteria (Long et al., 2000), the obtained values

3.2. Trace element contamination assessment The enrichment factors (EFs) of trace elements have been commonly used to assess human-made contamination. In general, EF values of 0.5–1.5 reflect regional rock compositions, whereas EF values that 6

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Table 4 Comparison of element concentrations (mg kg− 1, otherwise specified) in surface sediment in the various mangrove sediments around the world. Location

This study Sundarban (BD)a Sundarban (BD)b India Sundarbanc Sundarband Godavarie Muthupetf Senegalg Panamah Colombiai Australia Port Jacksonj Queenslandk Brisbanel Brazil Clean mangrovem Rio Casqueirom Hong Kong Clean mangroven Mai Poo Spain (Cadiz)p

V

Cr

Mn

Fe (%)

Co

Ni

Cu

Zn

As

Cd

Hg (μg/ kg)

Pb

56–120 (86.9) – 32.9

43–82 (67.0) 38.7 15.7

422–830 (634) 554 437

2.8–4.9 (3.81) 3.43 17.4

8.9–15.2 (13.9) 14.4 31.3

18–38 (28.6) 167 76.1

13–30 (22.3) 31.7 10.5

46–89 (67.7) 58.6 73.6

3.4–9.0 (6.76) 14.0 4.6

0.35–0.82 (0.460) 0.07 0.55

21–46 (30.8) – 6.4

10–24 (19.7) 17.9 19.3

– – – – 14.3 66.0 –

28.3 50.3 2.2 141 28.8 9.2 13.2

647 – 1059 701 21.0 171 623

0.294 – 0.45 3.25 0.32 0.17 1.56

6.67 – 28.8 – 0.9 – –

34.5 43.8 25.7 62.0 2.5 93.1 32.5

38.31 32.5 47.8 32.0 3.5 4.1 23.3

34.4 – – 89.0 5.4 15.8 91.0

3.82 9.88 – – – – 0.059

0.21 0.118 10.9 0.24 0.033 7.0 1.92

70 – – – 13.0 – 2.4

15.8 18.3 55.8 11.2 2.4 33.2 12.6

– 2–65 48.5

– 2–24 42.0

– 4–397 –

– 0.22–3.3 –

– ≤ 11 –

– ≤9 30.8

61 ≤13 23.1

243 15–118 98.3

– ≤17 6.9

– ≤ 0.4 0.4

– – –

100 ≤14 58.7

– –

– –

– –

0.246 0.253

– –

– –

3.82 15.4

24.2 59.9

– –

0.60 1.63

– –

– –

– – –

18.4 33.0 69.0

185 – 534

2.45 0.176 0.760

– – –

24.9 70.8 30.0

28.3 67.1 31

74.0 222 117

– – 9.0

0.455 1.2 0.30

– – 900

43.8 135 61

a

Kumar et al., 2016. Awal et al., 2009. c Chowdhury et al., 2015. d Antizar-Ladislao et al., 2015. e Ray et al., 2006. f Janaki-Raman et al., 2007. g Bodin et al., 2013. h Guzmán and Jiménez, 1992. i Perdomo et al., 1999. j MacFarlane et al., 2003. k Preda and Cox, 2002. l Mackey and Hodgkinson, 1995. m Harris and Santos, 2000. n N.F. Tam and Wong, 2000; N.F.Y Tam and Wong, 2000. o Ong Che, 1999. p Izquierdo et al., 1997. (For this study, mean values (n = 15) are within parenthesis). b

0.11 (S11) to 0.50 (S2) indicate that the combination of the studied elements has a 21% probability of being toxic. At S2 and S3, near the Mongla port area, the M-ERM-Q values are found to be 0.201 and 0.192, respectively which are higher than the other sampling points. Different SQGs are used to assess the potential biological effects of trace elements in the Sundarban mangrove sediments. With reference to TEL and PEL SQGs, any site is considered contaminated if 10% of the values exceed TEL. Therefore, in the Sundarban mangrove sediments Cr, Ni, Cu and As have > 10% of the values above TEL. For Cr, 93%; Ni, 100%; Cu, 93% and As, 40% of the samples have values between TEL and PEL; while no element concentration shows above PEL (Table 5). When compared with ERL and ERM SQGs, only Cr (13%), Ni (93%) and As (6.7%) fall between ERL-ERM values. The apparent effect threshold (AET) values for V, Cr, Mn, Ni, Cu, Zn, As, Cd, Sb, Hg and Pb are 57.0, 62.0, 260, 110, 390, 410, 35.0, 3.0, 9.3, 0.41 and 400 mg kg− 1, respectively (NOAA, 2012). According to AET SQGs, only V (93%), Cr (73%), Mn (100%) and Co (93%) fall above AET, thus posing a threat for potential adverse biological impacts. The results of sediment classification based on SQGs suggest that Zn, Hg and Pb are not expected to cause adverse biological effects on biota of the Sundarban because the values obtained are below TEL and ERL (Table 5). However, the surface sediments at most of the studied stations can be classified as presenting a threat to marine organisms due to the high concentrations of V, Cr, Mn, Co, Ni and Cu.

Fig. 2. Pollution load index values for surface sediments of the Sundarban. (Lit. data from Kumar et al., 2016).

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Table 5 Classification of sediments based on different ecological risk indices and the proposed SQGs. Sample

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 Tri

Eri Cr

Mn

Ni

Cu

Zn

As

Cd

Sb

Hg

Pb

1.48 1.79 1.79 1.70 1.39 1.48 1.41 1.26 1.59 1.22 0.94 1.53 1.40 1.26 1.63 2.0

0.93 0.66 0.65 0.91 0.95 0.86 0.89 0.65 0.57 0.76 0.54 0.85 1.07 0.93 1.06 1.0

3.02 4.05 3.59 3.04 2.99 2.71 3.24 2.57 3.40 2.79 1.93 3.29 3.10 2.91 3.05 5.0

3.80 5.40 4.96 3.82 4.03 3.49 4.29 3.67 4.50 3.82 2.35 4.17 3.79 3.72 4.02 5.0

0.87 1.33 1.16 1.03 0.70 0.97 1.25 0.69 1.15 0.91 0.88 1.09 1.01 0.98 1.15 1.0

14.2 18.8 15.6 14.9 15.4 12.1 7.1 13.1 14.3 16.5 9.8 14.0 15.4 13.1 17.1 10

150 133 273 158 150 142 167 158 142 133 117 142 133 158 142 30

15.5 31.0 23.8 18.0 17.6 14.4 15.6 24.1 15.7 26.9 12.8 8.8 23.9 18.2 19.5 10

27.4 34.0 37.1 23.8 23.0 17.2 21.0 20.4 36.2 17.6 20.2 21.0 18.6 19.4 26.4 40

4.41 5.81 6.94 4.85 4.49 4.12 5.15 3.90 4.85 4.04 2.87 4.93 4.56 4.19 4.63 5.0

RI

M-ERM-Q

222 236 369 230 221 199 227 229 224 208 169 201 206 223 220

0.152 0.201 0.192 0.160 0.147 0.141 0.160 0.131 0.173 0.142 0.106 0.163 0.154 0.145 0.164

SQGs (mg kg− 1)

Cr

Mn

Ni

Cu

Zn

As

Cd

Sb

Hg

Pb

References

TEL PEL ERL ERM

52.3 160 81 370

– – – –

15.9 42.8 20.9 51.6

18.7 108 34 270

124 271 150 410

7.24 41.6 8.2 70

0.68 4.21 1.2 9.6

– – – –

0.130 0.700 0.15 0.71

30.24 112 46.7 218

CCME, 1999 CCME, 1999 NOAA, 2012 NOAA, 2012

Percentage of the samples based on SQGs < TEL 7 – TEL-PEL 93 – < ERL 87 – ERL-ERM 13 –

0 100 7 93

7 93 100 0

100 0 100 0

60 40 93 7

93 7 100 0

– – – –

100 0 100 0

100 0 100 0

Tri = Toxic Response factor; TEL = Threshold Effects Level; PEL = Probable Effects Level; ERL = Effect Range Low; ERM = Effect Range Medium.

3.4. Statistical analysis to elucidate pollution sources and transport behavior of the elements

different processes like biological effects and external inputs operating in the sediments (Ray et al., 2006).

3.4.1. Correlation analysis In order to establish relationships among elements and their behavior during transport in the mangrove environment, a correlation matrix was calculated for trace elements in the sediments which is given in Table 6. According to the values of Pearson correlation coefficients, most of the studied elements show significant correlations with Fe and Al, except Mn, Th and U. The significant positive correlations between Al and other elements indicate that aluminosilicate minerals are the main geochemical carriers of these elements in the Sundarban (Rubio et al., 2000). Strong positive correlations between Fe and V, Cr, Co, Ni, Cu and Pb (Table 6) indicate that the V, Cr, Co, Ni, Cu and Pb distributions were controlled by the same factors, such as Fe oxy-hydroxides and clay minerals, and also they have a similar origin. Poor correlations of some elements with either Al and/or Fe are due to association of those elements with organic detritus (e.g., Hanson et al., 1993; Daskalakis and O'Connor, 1995). In Table 6, a majority of elements show very poor or negative correlation with Mn, which indicates that the presence of Mn oxyhydroxides have an insignificant influence on accumulation of the studied trace elements (Datta and Subramanian, 1998) or Mn-oxide may be only a minor host phase for these elements in the sediments of the Sundarban. Similar poor associations of Mn with other trace elements in sediments were also noticed in Indian coastal sediment (Alagarsamy, 2006). Significant positive correlation between Cd and Pb (r = 0.73, P < 0.01) points to their geochemical similarities (chalcophilic behavior) and also their common anthropogenic sources. Ship breaking, pigments and anti-corrosive element coating activities may be potential causes for the elements (Siegel, 2002; Kibria et al., 2016). The lack of significant correlations between Th and U with the other elements indicates their different geochemical behaviors or

3.4.2. Principal component analysis (PCA) For principal component analysis in this study, all principal factors with eigenvalues > 1.0 are taken into account. The first four factors (PCs) are able to account for 84.34% of the variance of all variables. The calculated factor loadings, together with cumulative percentage and percentages of variance explained by each factor, are listed in Table 7. PC1 shows the highest loadings for Al, V, Cr, Fe, Co, Ni, Cu, Zn and Pb and it explains 51.7% of the variance. These elements are controlled by the geological background (Boruvka et al., 2005 and Sajn et al., 2011). Considering the PCA results, PC1 is supposed to reflect the contribution of natural geological sources, which is also confirmed by the low EF values and correlation analysis as discussed in the previous sections. PC2 shows high loading of Mn, Th and U, and it explains 15.4% of the total variance. The U has also high loading in PC3, indicating quasi-independent behavior of this element within the group. A strong positive loading for As and Sb is observed in PC3. Meanwhile, high values of EF and CF are observed for As and Sb, which implies that these elements are originated from anthropogenic sources. Enrichment of As and Sb in the sediments suggests the effect of discharge of agricultural and acquacultural wastes (chemical fertilizer, pesticides and insecticides used in agricultural field and shrimp aquaculture farms) throughout the Poshur and Mongla rivers. PC4 shows highest loading for Cd. In this study, highest values of EF and CF are observed for this toxic trace element. The Cd contamination of Sundarban mangrove sediments has also been reported by other studies (Awal et al., 2009; Akhand et al., 2016). Therefore, PC4 indicates other anthropogenic sources differ from PC3.

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Table 6 Pearson correlation matrix for element data of the sediment samples.

Al V Cr Mn Fe Co Ni Cu Zn As Cd Sb Hg Pb Th U

Al

V

Cr

Mn

Fe

Co

Ni

Cu

Zn

As

Cd

Sb

Hg

Pb

Th

U

1.00 0.91 0.71 0.29 0.77 0.77 0.73 0.74 0.30 0.61 0.28 0.37 0.38 0.65 − 0.30 0.09

1.00 0.77 0.21 0.91 0.73 0.83 0.83 0.46 0.64 0.34 0.60 0.46 0.77 − 0.23 0.32

1.00 0.13 0.80 0.73 0.85 0.82 0.63 0.53 0.46 0.24 0.69 0.85 0.09 0.21

1.00 0.10 0.45 0.05 −0.06 −0.05 0.11 −0.13 −0.12 −0.41 −0.02 −0.43 −0.27

1.00 0.74 0.82 0.83 0.45 0.55 0.46 0.57 0.59 0.83 −0.04 0.24

1.00 0.62 0.63 0.26 0.45 0.26 0.34 0.26 0.57 − 0.21 − 0.17

1.00 0.97 0.71 0.50 0.36 0.38 0.68 0.88 0.01 0.39

1.00 0.64 0.50 0.45 0.48 0.71 0.89 −0.06 0.35

1.00 0.11 0.20 0.14 0.51 0.65 0.20 0.42

1.00 0.03 0.61 0.42 0.37 − 0.30 0.44

1.00 0.17 0.48 0.73 − 0.03 0.02

1.00 0.25 0.34 − 0.23 0.60

1.00 0.71 0.33 0.47

1.00 0.03 0.26

1.00 0.23

1.00

Bold correlations are significant at P < 0.01.

TEL and ERL values indicating that there may be some ecotoxicological risk to organisms living in sediments of the Sundarban. The multivariate statistical analysis (Pearson's correlation analysis and principal component analysis) revealed the origin and behavior of the elements during their transport in the mangrove ecosystem. The data from this study will also be helpful to quantify levels of trace element pollution, as well as to manage future ecological risks of the sensitive Sundarban mangrove ecosystem.

Table 7 Varimax rotated factor loading matrix of 16 elements (variables) for Sundarban sediment samples. Element

PC1

PC2

PC3

PC4

Al V Cr Mn Fe Co Ni Cu Zn As Cd Sb Hg Pb Th U Eigen value % variance explained % cumulative variance

0.762 0.807 0.934 0.235 0.815 0.753 0.923 0.865 0.733 0.398 0.366 0.193 0.609 0.861 0.071 0.173 8.27 51.7 51.7

− 0.400 − 0.234 0.031 − 0.714 − 0.116 − 0.501 0.114 0.083 0.432 − 0.203 0.029 − 0.057 0.512 0.109 0.763 0.561 2.47 15.4 67.1

0.300 0.459 0.086 −0.191 0.349 0.068 0.247 0.319 −0.018 0.744 −0.044 0.883 0.236 0.124 −0.283 0.702 1.70 10.6 77.7

0.074 0.095 0.126 − 0.403 0.253 0.055 0.059 0.221 − 0.172 − 0.068 0.861 0.145 0.348 0.436 − 0.080 − 0.171 1.06 6.60 84.3

Acknowledgements The authors thank personnel of the Center for Research Reactor (CRR) of Bangladesh Atomic Energy Commission for sample irradiation to perform INAA. The authors are grateful to I.B. Elius and S. Mahmud for their kind help during manuscript preparation. The technical personnel of RNPD, INST and Analytical Chemistry Laboratory, Chemistry Division of Atomic Energy Center, Dhaka are gratefully acknowledged for their kind help during sample preparation and analysis for this study. Anonymous reviewer and associate editor of MPB are gratefully acknowledged for their constructive comments on the manuscript. References Abrahim, G.M.S., Parker, R.J., 2008. Assessment of trace element enrichment factors and the degree of contamination in marine sediments from Tamaki Estuary, Auckland, New Zealand. Environ. Monit. Assess. 136, 227–238. Ahmed, K., Yousuf, M., Haque, R., Mondol, P., 2011. Trace element concentrations in some macrobenthic fauna of the Sundarbans mangrove forest, south west coast of Bangladesh. Environ. Monit. Assess. 177, 505–514. Akhand, A., Chanda, A., Das, S., Sanyal, P., Hazra, S., 2016. High cadmium contamination at the gateway to Sundarban ecosystem driven by Kolkata metropolitan sewage in India. Curr. Sci. 110, 386–391. Alagarsamy, R., 2006. Distribution and seasonal variation of trace elements in surface sediments of the Mandovi estuary, west coast of India. Estuar. Coast. Shelf Sci. 67, 333–339. Álvaro, N.V., Neto, A.I., Couto, R.P., Azevedo, J.M.N., Rodrigues, A.S., 2015. Crabs tell the difference-relating trace element content with land use and landscape attributes. Chemosphere 144, 1377–1383. Antizar-Ladislao, B., Mondal, P., Mitra, S., Sarkar, S.K., 2015. Assessment of trace element contamination level and toxicity in sediments from coastal regions of West Bengal, eastern part of India. Mar. Pollut. Bull. 101, 886–894. Awal, M.A., Hale, W.H.G., Stern, B., 2009. Trace element concentrations in mangrove sediments in the Sundarbans, Bangladesh. Mar. Pollut. Bull. 58, 1922–1952. Banerjee, K., Senthilkumar, B., Purvaja, R., Ramesh, R., 2012. Sedimentation and trace element distribution in selected locations of Sundarban mangroves and Hooghly estuary, northeast coast of India. Environ. Geochem. Health 34, 27–42. Bernas, B., 1968. A new method for decomposition and comprehensive analysis of silicates by atomic absorption spectrometry. Anal. Chem. 40, 1682–1686. Bhattacharya, B.D., Nayak, D.C., Sarkar, S.K., Biswas, S.N., Rakshit, D., Ahmed, M.K., 2015. Distribution of dissolved trace elements in coastal regions of Indian Sundarban mangrove wetland: a multivariate approach. J. Clean. Prod. 96, 233–243. Bodin, N., N'Gom-Kâ, R., Kâ, S., Thiaw, O.T., Tito de Morais, L., Le-Loch, F., Rozuel-

4. Conclusions In this study, the degree of trace element distribution and contamination in surface sediments of the rivers of the mangrove forest Sundarban was examined. The total concentrations of 16 environmentally important major and trace elements (Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Hg, Pb, Th and U) were determined by INAA and AAS. The overall concentrations of V, Cr, Fe and Cd in sediments of the Sundarban are remarkably higher than those available literature data reported from different mangrove sediments of the world. Trace element contamination assessment using different environmental contamination indices (EF and CF) reveals that sediments are low to moderately contaminated by As, Sb, Th and U while moderate to severely contaminated by Cd. The pollution load index (PLI) also indicates the progressive deterioration of the sediment quality of the Sundarban due to different anthropogenic activities. The possible sources for the deterioration of the sediment quality can be attributed to the different chemical carrying cargo accidents, port activities, ship breaking, agricultural and aquacultural run-off of that area. The estimated potential ecological risks based on potential ecological risk factors and different SQGs were considerable to high ecological risk at the study area for Cd, while Cr, Ni, Cu and As concentrations exceeded the 9

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