Accepted Manuscript

Assessment of heavy metal pollution, distribution and source apportionment in the

sediment from Feni River estuary, Bangladesh

Md. Saiful Islam, M. Belal Hossain, Abdul Matin, Md. Shafiqul Islam Sarker

PII: S0045-6535(18)30491-0
DOI: 10.1016/j.chemosphere.2018.03.077
Reference: CHEM 21021

To appear in: ECSN

Received Date: 2 July 2017

Revised Date: 17 February 2018
Accepted Date: 11 March 2018

Please cite this article as: Islam, M.S., Hossain, M.B., Matin, A., Islam Sarker, M.S., Assessment of
heavy metal pollution, distribution and source apportionment in the sediment from Feni River estuary,
Bangladesh, Chemosphere (2018), doi: 10.1016/j.chemosphere.2018.03.077.

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1 Assessment of heavy metal pollution, distribution and source

2 apportionment in the sediment from Feni River estuary, Bangladesh

3 Md. Saiful Islama, M Belal Hossaina,*, Abdul Matina, Md. Shafiqul Islam Sarkerb

4 a: Department of Fisheries and Marine Science, Noakhali Science and Technology

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5 University, Noakhali-3814, Bangladesh.

b: Forensic Science Laboratory, Rapid Action Battalions Headquarters, Dhaka-1229,

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7 Bangladesh.

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8 *Corresponding author’s email: mbhnstu@gmail.com

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10 Note: First two authors contributed equally.

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22 Assessment of heavy metal pollution, distribution and source

23 apportionment in the sediment from Feni River estuary, Bangladesh

24 ABSTRACT

25 Heavy metal pollution in sediment resources may pose serious threat to ecosystem and

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26 human health through food web. In this study, surface sediment samples of 10 stations along

the Feni River estuary were analyzed to profile the accumulation, sources and pollution levels

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28 of heavy metals. The results revealed that the average contents (µg g-1) of eight selected

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29 heavy metals followed the order of Mn (37.85) > Cr (35.28) > Ni (33.27) > Co (31.02) > Pb

30 (6.47) > Ag (1.09) > As (0.85) > Hg (0.71), and the concentrations varied spatially and

31
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seasonally with relatively higher levels at upward stations and during the rainy season.
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32 According to sediment quality guidelines (SQGs), the sediment samples were heavily

contaminated with Ag and Hg, and moderately with Co. Threshold effect concentration
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34 (TEC) and probable effect concentration (PEC) values indicated that the concentration of
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35 only Ni and Cr were likely to occasionally exhibit adverse effects on the ecosystem.
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36 Enrichment factor (EF), geo-accumulation index (Igeo) and contamination factor (CF)

37 analyses revealed that Ag, Co and Hg were at moderate to high pollution levels and the rests
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38 (As, Cr, Ni, Pb and Mn) were at no to low pollution levels. Potential ecological risk index

39 (PERI) also showed that Ag, Co and Hg were the most potential ecological risk factor being
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determined in this studied area. Correlation matrix combined with multivariate principal
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41 component analysis and cluster analysis suggest that Ag, Co, Ni and Hg originated from

42 anthropogenic sources (agrochemicals, silver nanoparticles anti-microbial agent, silver

43 plating), whereas As, Cr, Pb and Mn primarily originated from natural geological

44 background.
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45 Keywords: Heavy metals, Estuarine sediments, Multivariate analysis, Potential ecological

46 risk assessments, Feni River estuary.

47 1. Introduction

48 Heavy metal pollution is considered to be a serious threat to any aquatic ecosystems

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49 because of its toxicity, persistent nature, omnipresent, and ability to non-biodegradability and

50 be bio-accumulated into the food chain (Duman et al., 2007). Heavy metals enter the aquatic

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51 ecosystems through point sources such as industrial, municipal and domestic waste water

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52 effluents as well as diffuse sources which include surface runoff, erosion, and atmospheric

53 deposition (Akcay et al., 2003; Demirak et al., 2006; Armstrong-Altrin et al., 2015; Ramos-

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54 Vázquez et al., 2017). These metals that are introduced into the aquatic environment are
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55 ultimately incorporated into aquatic sediments (Zhang et al., 2017). Thus, sediments are one

56 of the possible media in monitoring the health of aquatic ecosystems (Baran et al., 2002).
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57 Sediments serve as the largest pool of metals in any aquatic environments (Zhang et
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58 al., 2017), and more than 90% of the heavy metal load in the aquatic ecosystems has been
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59 found to be related to suspended particulate matter and sediments (Zheng et al., 2008; Amin

60 et al., 2009). Metals in suspended particulates settle down and lay up in sediments
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61 (Kucuksezgin et al., 2008), while the dissolved metals adsorb onto fine particles which may

62 carry them to bottom sediments (Singh et al., 2005) and persist in the sediment for a long
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63 time. Their distribution are influenced by the mineralogical and chemical composition of
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64 suspended material, anthropogenic influences, deposition, sorption, enrichment in organism

65 (Jain et al., 2007), and various physico-chemical characteristics (Singh et al., 2005).

66 Sediments are ecologically important components of the aquatic habitat and play a

67 significant role in maintaining the trophic status of any water body (Zhang et al., 2017; Singh

68 et al., 2005) and provides a site for biogeochemical cycling and the foundation of the food
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69 web (Burton et al., 2001). Therefore, sediments provide an essential link between chemical

70 and biological processes and are an integral component for functioning of ecological

71 integrity. In addition, sediments act as a sink of organic as well as inorganic pollutants and

72 provide a history of anthropogenic pollutant input (Bermejo et al., 2003; Shuhaimi, 2008) and

73 ecological changes (Shomar et al., 2005).

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74 The contamination of sediments with heavy metals leads to serious environmental

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75 (Loizidouet al., 1992) and worldwide problems (Yoon et al., 2006; Fernandes et al., 2008;

76 Kucuksezgin et al., 2008). Therefore, sediment has widely been studied for anthropogenic

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77 impacts on the aquatic environments (Sayadi et al., 2010). Various studies have reported the

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78 distribution and contamination of heavy metals and quantification of pollution load in
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79 sediments of different rivers and estuaries such as the Yangtze River estuary, China (Wang et

80 al. 2015a), the River Gomti, India (Singh et al., 2005), the Luanhe River estuary, China (Liu
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81 et al. 2016)), and the Karnaphuli River estuary, Bangladesh (Ali et al., 2016). However,

82 estuarine sediment contamination by heavy metals has meagerly been investigated in

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83 Bangladesh in general and no information is available for the Feni River estuary and its
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84 associated tributaries. Nationally, the Feni River estuary plays a very significant role in
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85 providing a huge amount of fish supplies to the local and national markets as well as

86 livelihood to the local inhabitants. The estuary has been subjected to heavy metal pollution
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87 due to a rapid increase in population and unplanned human settlements in its catchment area,
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88 agricultural activities, fish farming, fishing, industrial and medical waste discharge,

89 recreational activities, washing activities, poultry waste discharge, dumping of solid waste

90 and direct and/or indirect discharge of untreated domestic effluents. Therefore, the present

91 study aimed to (1) determine the spatial and seasonal distributional trends of heavy metals in

92 the sediments of Feni River estuary, (2) assess ecosystem risk of heavy metals following

93 sediment quality guidelines viz., threshold effect level/probable effect level (TEL/PEL), (3)
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94 quantify the extent of metal pollution using enrichment factor (EF), geo-accumulation indices

95 (Igeo) and potential ecological risk index (PERI), and (4) identify the natural and/or

96 anthropogenic sources of these metals using correlation matrix and multivariate statistical

97 techniques.

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98 2. Materials and Methods

99 2.1. Study area

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100 Located in the central coast of Bangladesh, Feni River estuary (also known as Little

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101 Feni River estuary; Latitude 22° 46'44" N and Longitude 91°22'42" E) originates in the

102 South Tripura district (India) and flows a distance of 116 km through different cities and

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municipalities in India and Bangladesh, and finally empties into the Bay of Bengal. The
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104 estuary is heavily used for irrigation, fishing, agriculture, aquaculture, washing, livestock

105 farming, recreation, dumping domestic waste, sewage disposal and water based transport.
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106 Rainfall in this area is mostly seasonal, with a rainy season between June and November and
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107 a dry period between December and May. An average annual rainfall is 3,302 mm and annual
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108 temperature varies from a maximum of 34.3 °C to a minimum of 14.4 °C (Miah et al., 2015).

109 The salinity of the estuary ranged from 4.20 -7.50 ppt with a mean value of 5.78 ±1.32 ppt.
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110 Due to the heavy rainfall and annual flooding, the region is composed of fertile alluvial plains

111 resulting from the underlying forces of the Feni river. Therefore, most of the catchment areas
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112 are suitable for temporary or permanent crops such as rice, wheat, beans, vegetables, red
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113 pepper, potato, tomato, bananas and sugarcane. However, to increase the production of these

114 crops, indiscriminate and long-term repeated application of fertilizers and metal-containing

115 pesticides, herbicides and fungicides have been gradually accumulated to potentially harmful

116 levels in the soils.

117 2.2. Sediment sampling

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118 In total, sixty samples of surface sediments (0–5 cm) from 10 stations (S1 to S10) in

119 the Feni River estuary (Fig. 1) were collected using an Ekman dredge during the wet (June

120 2016) and dry (January 2017) seasons. Samples that showed no evidence of surface

121 disturbance were retained. Triplicate samples were collected at each station in each season.

122 All samples were stored in a cooler at 4 °C, and then were frozen at −20 °C after being

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123 transferred to the laboratory immediately for further analysis (Lasorsa and Casas, 1996).

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124 Before analysis, the sediments were defrosted at room temperature, dried at 50 °C to constant

125 weight (~24 h) (Hyun et al., 2007), and ground in an agate mortar (Zhao et al., 2016). The

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126 fraction smaller than 63 µm was used for analyses in this study due to strong association of

127 metals with fine-grained sediments (Tam and Wong, 2000). Global Positioning System

(GPS) was used to locate the sites.

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128

129 2.3. Determination of metals

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130 For the measurement of total metal concentrations, acid digests of each sediment
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131 sample were prepared using USEPA method 3051. Each sediment sample measuring 0.5 g
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132 was digested in 10 ml of ultrapure HNO3 using Micro Wave Digestion System (WX-6000,

133 Preekem, Shangai), and then filtered and diluted. Total metal concentrations of Ag, Co, Ni,
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134 Hg, Cr, Pb, As and Mn were determined in triplicate using Inductively Coupled Plasma-Mass

135 Spectrometry (ICP-MS) (SPECTRO MS, SPECTRO GmbH, Germany) at Forensic Science
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136 Laboratory, Rapid Action Battalions Headquarters, Dhaka, Bangladesh. All the reagents used
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137 were of super quality and of analytical grade. All solutions were prepared using ultrapure

138 water (Ultra Clear TM TWF UV UF Type IP23, EVOQUA Water Technologies, Germany).

139 All acid proof plastic and Teflon apparatus were soaked in HNO3 (10%) for at least 24 h and

140 rinsed repeatedly with ultrapure water. Analytical blanks and standard reference material

141 were run in the same way as the samples, and heavy metal concentrations were determined

142 using standard solutions prepared in the same acid matrix. Certified reference material (CRM
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143 320) supplied by Merck KGaA (Germany) was used (N=3) to ensure the validation of data

144 and the accuracy and precision of analytical method. Analytical results of the selected metals

145 indicated a good agreement between the reference and analytical values of the reference

146 materials. Percentages of recoveries were between 95% and 105% for the all metals. The

147 results also showed that there was no contamination during analysis, and the relative standard

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148 deviation (RSD) of all replicate samples was <= 10%. The limit of detection (LOD) of the

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149 metals varied (As = Ag = Ni = Pb = Mn = 0.001, Cu = Co = 0.0007, Hg = 0.0005, Cr = 0.003

150 and Zn = 0.002 ppm).

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151 2.4. Assessment of sediment pollution

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152 2.4.1. Enrichment factor (EF)
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153 Normalized enrichment factor is applied (Salati and Moore, 2010) to differentiate

154 metal source originating from anthropogenic and natural means (Sayadi et al., 2010). This
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155 involves normalization of the sediment with respect to reference elements such as Al, and Fe
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156 (Amin et al., 2009; Karbassi et al., 2008), Mn, Ti and Sc (Salati and Moore, 2010), and Li
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157 and Cs (Pereira et al., 2007). Normalized EF of metals in Feni River estuary sediments from

158 each site was calculated using Eq. (1). Manganese (Mn) was used as a reference element to
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159 calculate anthropogenic metal enrichments as described by Loska et al. (1997). World

160 average concentration of metals reported for the shale by Turekian and Wedepohl (1961) was
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161 used as background values for heavy metals.

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( ⁄ ) 
162 EF = ……. (1)
( ⁄ )  

163 where (Cn/CMn) is the ratio of concentration of the element of concern (Cn) to that of Mn

164 (CMn) in the sediment sample (µg g-1 dry weight) and (Cn/CMn) is the same ratio in an

165 unpolluted reference sample.

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166 Five contamination categories are recognized on the basis of the enrichment factor: 2 <EF < 5

167 states deficiency to moderate enrichment, EF = 5–10 moderately severe enrichment, EF =

168 10–25 severe enrichment, EF= 25-50 very severe enrichment and EF >50 extremely high

169 enrichment (Birch and Olmos, 2008).

2.4.2. Geo-accumulation index (Igeo)

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170

171 Geo-accumulation index (Igeo) was developed by Müller (1979) and had widely been

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172 used in trace metal studies of sediments and soils (Amin et al., 2009). To quantify the degree

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173 of heavy metal pollution in Feni River sediments, Igeo was calculated according to Muller

174 (1979) and is given in Eq. (2).

175 I = log  (C ⁄1.5B ) ……. (2)

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176 where Cn is the concentration of the examined metal in the sediment, Bn is the geochemical
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177 background value of a given metal in the shale (Turekian and Wedepohl, 1961) and the factor

178 1.5 is used to account the possible variations in the background values.
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179 The geo-accumulation index consists of seven grades or classes: Class 0 (practically

180 uncontaminated): Igeo< 0; Class 1 (uncontaminated to moderately contaminated): 0 <Igeo< 1;

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181 Class 2 (moderately contaminated): 1 <Igeo< 2; Class 3 (moderately to heavily contaminated):

182 2 <Igeo< 3; Class 4 (heavily contaminated): 3 <Igeo< 4; Class 5 (heavily to extremely

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183 contaminated): 4 <Igeo< 5; Class 6 (extremely contaminated): 5 <Igeo. The elemental

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184 concentrations in Class 6 may be hundredfold greater than the geochemical background value

185 (Bhuiyan et al., 2010).

186 2.4.3. Contamination Factor (CF)

187 The level of contamination of sediment by metal is expressed in terms of a

188 contamination factor (CF) calculated as:

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189 CF = ……… (3)
  

190 where Cn Sample is the concentration of a given metal in river sediment, and Bn is the

191 geochemical background value of a given metal in the shale (Turekian and Wedepohl, 1961).

192 CF values were interpreted as follows: low contamination at CF < 1; moderate contamination

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193 at 1 ≤ CF < 3; considerable contamination at 3 ≤ CF < 6; and very high contamination at CF

>6, according to Hakanson, 1980.

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194

195 2.4.4. Potential ecological risk index (PERI)

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196 The PERI was used to assess the comprehensive potential ecological risk of heavy metals in

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197 sediment and was initially introduced by Hakanson (1980). The potential ecological risk
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198 factor of a given metal (E ) is defined as


E = T ×  $
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199 …………. (4)

%

Equation (3) was used to calculate the risk index (RI) of sampling sites as follows:
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200


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201 RI = ' T ×  $ ……… (5)
() %
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202 where Ci is the concentration of metal i in sediment, C0 is the concentration of the same

203 element in background sediment, T is the biological toxicity factor of an individual element,
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204 which was determined for Cu = Pb = Ni= 5, Zn = 1, As = 10, Cr = 2 and Cd = 30 (Suresh et

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205 al., 2011), E is the potential ecological risk factor of a single metal, and RI is the

206 comprehensive potential ecological risk index of the metals. The PERI of heavy metals was

207 categorized according to five levels, as shown in Table S1.

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209 2.5. Statistical analysis

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210 Statistical methods can be used to assess the complex ecotoxicological processes by showing

211 the relationship and interdependency among the variables and their relative weights

212 (Bartolomeo et al., 2004). Correlation and principal components analyses, the most common

213 multivariate statistical methods, were used to check for significant relationships among heavy

214 metals in the sediment samples. The various statistical methods were performed with a 95%

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215 confidence interval (significance p < 0.05). Factor analysis based on principal component

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216 analysis (PCA) was used to ascertain sources of contamination (natural and anthropogenic).

217 Cluster analysis was used to identify spatial variability among the sites. Euclidean distance

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218 was used as dissimilarity matrix, whereas Ward's method was used as a linkage method. All

219 the statistical analyses were done using free statistical software, PAST (Hammer et al., 2001).

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220 3. Results and discussion

221 3.1. Seasonal and spatial variation in the surface sediment of the study area
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222 Concentrations of heavy metals in the study area are summarized in Table 1. The
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223 mean concentrations (µg g-1) of the selected metals followed similar decreasing trend during
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224 both seasons: Mn (37.85) > Cr (35.28) > Ni (33.27) > Co (31.02) > Pb (6.47) > Ag (1.09) >

225 As (0.85) > Hg (0.71). Co, Cr, Ni and Pb were significantly different between seasons (p ≤
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226 0.01) and greater at sampling sites viz., S3, S4, S5, S6 and S7 located in close vicinity of

227 agricultural land, urban, semi-urban and tourist areas with anthropogenic activities (Table 1).
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228 In wet season concentrations of all metals were higher than dry season in sediment sample
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229 (Fig. 2). However, lower concentrations of metals in dry season could be attributed to the

230 decreased dilution of runoff and unpolluted water. Sometimes, the variations in metal

231 concentrations may also be influenced by changes in lithological inputs, hydrological effects,

232 geological features, cultural influences and type of vegetation cover (Jain et al., 2007).
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233 During wet season the concentrations of Ag were higher in all the sites which ranged from

234 0.09 µg/g to 2.07 µg g-1. The highest concentration of Ag was recorded in the site S3 (2.07

235 µg/g) in sediment samples. On the average basis of both seasons, the higher concentrations of

236 Mn, Cr, Ni, Co, Pb, Ag, As and Hg at the sampling sites S1, S3, S5, S6 and S7 may be

237 attributed to several anthropogenic activities (Fig. 2 and Table 1). For example, the site S6

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238 and S7 were located in highly agricultural land with semi-urbanized area, and the estuary at

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239 this site directly receives untreated domestic sewage, agricultural runoff, urban runoff, and

240 wastes from construction of residential and commercial areas.

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241 The heavy metal concentrations in sediment of the Feni river estuary were compared with

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242 other selected estuaries (Table 2). The mean concentrations of Cr, As and Pb were higher in
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243 this estuary than the values reported by Ali et al. (2016) in the Karnaphuli River estuary. The

244 mean concentrations of Cr, Pb and As in the Yangtze River estuary were found higher but Ni
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245 was lower as recorded by Wang et al. (2015a) than present measured concentrations. The

246 mean concentrations of Cr and Pb were found to be higher but Ni was lower in the Ganges
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247 estuary (Subramanian et al., 1988) and Luanhe River estuary (Liu et al., 2016) than in this
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248 study.
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249 3.2. Sediment quality guidelines (SQGs)

250 Sediment quality guidelines (SQGs) are useful to screen sediment contamination by
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251 comparing sediment contaminant concentration with the corresponding quality guidelines
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252 (Caeiro et al., 2005), which evaluate the degree to which the sediments associated chemical

253 status might adversely affect aquatic organisms and are designed to assist the interpretation of

254 sediment quality (Wenning et al., 2005). Threshold effect level (TEL) refers to the

255 concentration below which adverse biological effects are expected to occur rarely, and

256 Probable effect level (PEL) indicates the concentration above which adverse effects are
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257 expected to occur frequently (Long and Morgan, 1990). Table 1 furnishes the heavy metal

258 concentrations in sediment from the Feni River, as well as the average shale values and

259 sediment quality guidelines (SQGs) used in this study. When comparing the average values

260 of heavy metals with the average shale values, the results indicated that Ag, Co and Hg were

261 higher than the average shale value in the wet and dry seasons. This indicates that the

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262 anthropogenic activities had a direct effect on the concentration of these metals in sediment

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263 (Chai et al., 2014). The concentration of heavy metals in the sediment samples were

264 contrasted with the consensus-based threshold effect concentration (TEC) and probable effect

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265 concentration (PEC) values (Table 1). The results show that Ni and Cr were between TEC

266 and PEC for 70% and 20% indicating that the concentration of Ni and Cr were likely to

267
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occasionally exhibit adverse effects on the ecosystem.
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268 3.3 Pollution level of heavy metals
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269 3.3.1. Enrichment factor (EF)

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270 A comparison of metal concentration in sediments with background reference values

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271 is generally used to assess metal enrichment (Tuna et al., 2007). Mean EF values of Ag, As,

272 Co, Cr, Ni, Pb and Hg were greater in the wet season, and followed the order: Ag > Co >
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273 Hg> Ni > Cr >Pb> As (Fig. S1). Lower values of metal EF in dry season can be related to

274 decrease in the anthropogenic activities. Total EF values followed the order of S9 > S10 >
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275 S3 > S8 > S6 > S7 > S4 > S5 > S2 > S1. The EF values of Ag ranged from 53.90 (S1) to
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276 841.22 (S9) which corresponded to extremely severe enrichment. Severe enrichment with Ag

277 may be attributed to urban hospital and clinic waste, some upstream silver plating industries,

278 runoff from agricultural land and rive bank erosion. Co and Ni are commonly used in

279 household products such as stainless steel, alloys, batteries, and car bearings and thus, there is

280 plenty chance of increased input of Co and Ni from urban areas (Barałkiewicz and Siepak,
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281 1999). An increased amount of Ni may also be connected to silty sedimentary rock in the

282 upstream. Some anthropogenic sources e.g., fossil fuel burning and coal burning in brick-

283 fields, and natural sources may contribute to enrichment of Hg in the study area.

284 3.3.2. Geo-accumulation index (Igeo)

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285 Igeo values have been used to explain sediment quality (Karbassi et al., 2008). The Igeo

286 of sampling sites during the wet and dry seasons are displayed in Fig. S2. Among the metals

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287 Ag showed the highest accumulation in wet season. Igeo values of Ag ranged from 1.17 (site

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288 S9) to 4.30 (site S3) which corresponded to class 2 of moderately polluted and class 5 of

289 strongly to extremely polluted sediment samples.

290
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The Index of geo-accumulation (Igeo) shows that Feni river estuary is not polluted with As,
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291 Cr, Mn and Pb (Igeo< 0), unpolluted to moderately polluted with Co and Hg (Igeo< 1), and

292 moderately to highly polluted with Ag (Igeo> 2). The average highest Igeo value showed Ag
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293 (2.93) which corresponded to class 4 and indicated Feni river estuary was highly polluted by
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294 Ag.
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295 3.3.3. Contamination factor (CF) and potential ecological risk index (PERI)
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296 The highest CF values for all metals studied were found at site-S3, which receives a huge

297 amount of agricultural discharge (Fig. 3). Total contamination factors followed the order of
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298 site S3 > S6 > S9 > S7 > S10 > S8 > S4 > S2 > S1. The average CF value for Ag was 15.6
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299 (Fig. 3) which revealed that Feni River estuary was very highly polluted with Ag.

300 The results of the potential ecological risk index (PERI) for only four heavy metals (Ni, Pb,

301 Cr and As) in the surface sediment of the Feni River estuary are depicted in Fig. S3. The

302 biological toxicity factors (Tri) for the rest metals (Ag, Co, Mn and Hg) were not available to

303 calculate PER value. From the PERI calculation, heavy metal pollution by a single element

304 was obtained, and the degree of pollution from the four heavy metals decreased in the
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305 following sequence: Ni >Pb> Cr > As. In comparison with the other elements, the PERI for

306 Ni was higher than other metals. However, the Eir values of Ni indicated pollution in the

307 sediment samples of Feni River estuary. The increased amount of Ni might be originated

308 from local household products e.g., stainless steel, batteries.

3.4. Pollution source identification based on Pearson Correlation, CA and PCA

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309

310 Correlations among heavy metals may reflect the origin and migration of these elements

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311 (Suresh et al., 2011). If no correlation exists among the elements, then the metals are not

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312 controlled by a single factor (Kukrer et al., 2014). The concentration of Ag was not

313 significantly correlated with any of the heavy metals except for a negative correlation with Pb

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314 (Table 3). However, positive correlations (p < 0.01) were found between several element
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315 pairs: As-Pb (0.84), Co-Cr (0.90), Co-Mn (0.98), Co-Ni (0.90), Cr-Mn (0.98), Cr-Ni (0.98)

316 Cr-Hg (0.95) Mn-Ni (0.98), Mn-Hg (0.92) and Ni-Hg (0.93). Three element pairs exhibited a
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317 significantly positive correlation of p < 0.05.

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318 One group of elements comprised of As, Cr, Mn, Pb and Hg. The concentrations of these five
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319 metals were slightly lower or close to the average shale values. In addition, the results of EF,

320 Igeo, CF and PERI assessment indicated that the contents of these five metals presented a low
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321 or zero potential ecological risk. These findings suggested that this group of elements might

322 originate from natural sources, such as river bank erosion, weathering and atmospheric
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323 precipitation (Wu et al., 2014; Wang et al., 2015b).

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324 A second group, including Ag, Ni and Co, could be ascribed to an anthropogenic factor. The

325 mean concentrations of these metals were higher than their average shale values. The element

326 of Ag, Ni and Co had similar spatial distribution trends, with higher concentrations appearing

327 in landward sites: S3, S4, S5, S6, S7 and S9 . Various human activities e.g., using fertilizer,

328 metal-containing pesticides, fungicides, herbicides in agriculture and aquaculture, waste

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329 disposal, dredging in and around the Feni River estuary, may greatly contribute to the

330 concentration of Ag, Ni and Co. Domestic and commercial use of stainless steel, alloyes,

331 batteries may contribute to the increase of Co and Ni. Recent increasing use of silver-

332 nanoparticle antibacterial and antifungal agent in wound care products, medical devices,

333 cosmetics and textiles may also be associated with high concentration of Ag in the study area

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334 (Landsdown, 2010). Metallic silver may be inert; however, biologically active Ag+ binds

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335 strongly to metallothionein, albumins, and macroglobulins of human body which can cause

336 skin allergy, Argyria and argyrosis disease (Lansdown, 2015).

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337 Cluster analysis (CA) was used to group the similar sampling sites (spatial variability) and to

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338 identify specific areas of contamination (Simeonov et al., 2000). Spatial CA rendered a
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339 dendrogram (Fig. S4) where all ten sampling sites on the river were grouped into two

340 statistically significant clusters/groups at (Dlink/Dmax) × 100 < 15. Group 1 consisted of
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341 three sites (S8, S9 & S10) with lowest metal concentrations in sediment samples and group 2

342 consisted of seven sites (S5, S6, S7, S3, S4, S2 & S1) with highest metal concentrations
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343 which were surrounded by semi urban and agricultural areas. Group 1 corresponded to
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344 weakly contaminated sites and group 2 corresponded to highly contaminated sites. Group 2
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345 sites were situated upstream of the catchment areas, and sediments at these sites were

346 polluted with anthropogenic activities such as waste-water discharges from urban areas,
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347 dumping of solid waste, raw sewage, automobile washing and auto-workshops near these
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348 sites.

349 PCA leads to a reduction of the initial dimension of the data set to two principle components

350 (PCs) which explain 91.89% of the data variation (Fig. 4). A total of two significant PCs

351 were extracted with eigenvalues > 1. PC1 was heavily loaded with As, Cr, Mn, Pb and Hg

352 which explained 68.95% of the total variance and exhibited an eigenvalue of 5.52. PC2

353 explained 22.94% of total variance and was strongly correlated with Ag (0.52) and Co (0.41).
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354 A positive correlation existed between Ag and Co; hence, Ag and Co may exist from a

355 common origin (Wang et al., 2015a). High concentrations of Ag and Co are possibly caused

356 by anthropogenic inputs from flooding of agricultural lands, medical waste, domestic waste,

357 upstream silver plating industries, and atmospheric deposition, which were widespread

358 throughout the catchment area of the estuary.

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359 Conclusions

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360 The results of the current study provide information on the characteristics of pollution from

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361 heavy metals of the Feni River estuary for the first time. The results showed that the degree

362 of pollution from eight selected heavy metals followed the decreasing order of Mn > Cr > Ni

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363 > Co > Pb > Ag > As > Hg. The concentrations of heavy metal were greater in the wet season
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364 than in the dry season which can be associated with heavy rainfall during monsoon and the

365 subsequent flooding of agricultural lands causing dissolution of heavy metals. The mean
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366 concentrations of Ag and Co were higher than the average world values. Calculations of EF,
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367 Igeo and CF demonstrated that Ag, Co and Hg were at moderate to high pollution levels and
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368 As, Cr, Ni, Pb and Mn were at no to low pollution levels. Potential ecological risk index

369 (PERI) also revealed that Ag, Co and Hg were the most potential ecological risk factors.
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370 Major possible sources of Ag can be medical waste and upstream silver plating industries.

371 Household uses of stainless steel, batteries, alloys, and burning fossil fuel can be connected to
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372 enhanced accumulation of Co and Hg. Therefore, Ag, Co and Hg were the most important
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373 factors affecting the ecological environment of the Feni River estuary. The results of the PCA

374 analysis suggest that Ag, Co and Ni mainly originated from anthropogenic sources (due to

375 excessive use of fertilizers, agrochemicals, metal-containing pesticides, silver-nanoparticle

376 antimicrobial agent, upstream silver plating industries) and As, Cr, Mn, Pb and Hg mainly

377 originated from natural sources (geological rock). The generated information can be a basis

378 for effectively targeting policies to protect the sediment of Feni river from long-term
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379 accumulation of heavy metals and for ensuring land and water based food quality, and

380 protecting human health. Important strategies should be implemented to reduce or ban the use

381 of agrochemicals, pesticides, inclusion of wastewater treatment and safe disposal of silver

382 containing medical devices.

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383 Conflict of interest

384 The authors declare that there is no conflict of interest.

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385 Acknowledgements

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386 The authors are deeply thankful to the laboratory in Forensic Analysis Department, Rab HQ,

Bangladesh for providing all necessary research facilities. They are also delighted to express

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387

their gratitude and sincere thanks to editor and four anonymous reviewers for their useful
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388

389 comments and suggestions to improve the quality of article.

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390
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391 References
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FIGURE LEGENDS:

Fig. 1. Sampling sites in the Feni River estuary.

Fig. 2. Seasonal (a) and spatial (b) variations of metal concentrations in the sediments during
wet and dry season. Error bars indicate standard error of Mean.

Fig. 3. Contamination factor (CF) selected metals in sediment of Feni River. (Dot line of the

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horizontal axis indicates the level of contamination degree).

Fig 4. PCA plot showing the loading of two components influencing variation of heavy

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metals in the sediments from Feni River estuary.

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Fig. 1. Sampling sites in the Feni River estuary.

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45
Metals concentrations (µg/g) 40 a Wet season
35 Dry season
30
25
20
15
10
5

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0
Ag As Co Cr Mn Ni Pb Hg
Metals

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b
Metals concentrations (µg/g)

50 Ag As Co Cr Mn Ni Pb Hg

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40
30
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20
10
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0
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10
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Sampling sites
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Fig. 2. Seasonal (a) and spatial (b) variations of metal concentrations in the sediments during
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wet and dry season. Error bars indicate standard error of Mean.
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18
Wet season Dry season
16
14
12
10 Very high
CF value

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8 pollution
6 Considerable
4 pollution

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2 Moderate pollution
0 Low pollution

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Ag As Co Cr Mn Ni Pb Hg
Metals

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Fig. 3. Contamination factor (CF) selected metals in sediment of Feni River. (Dot line of the
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horizontal axis indicates the level of contamination degree).
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16

12

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Pb
PC2 (22.94 % variation)

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0 AsCr
Ni
HgMn
Ag

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-4

-8
Co

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-12
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-16

-20
-64 -48 -32 -16 0 16 32 48 64
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PC1 (68.95 % variation)

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Fig 4. PCA plot showing the loading of two components influencing variation of heavy
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metals in the sediments from Feni river estuary.

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Table 1

Metal concentrations (µg/g) in sediments of the Feni river estuary during wet and dry season
(n=30 for each season).

Ag As Co Cr Mn Ni Pb Hg

Mean 1.17 0.93 32.30 36.82 39.55 35.02 7.09 0.79

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(wet
season)

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Range 0.09- 0.13- 14.48- 17.77- 23.46- 13.54- 0.67- 0.87-
(wet 2.07 2.79 45.84 46.09 48.73 45.71 17.03 1.57

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season)

Mean 1.01 0.78 29.75 33.74 36.15 31.52 5.86 0.63

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(dry
season)
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Range 0.26- 0.13- 11.11- 13.91- 17.92- 8.56- 0.36- 0.09-
(dry 1.86 2.27 42.84 41.74 46.01 41.86 14.04 1.04
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season)

Aver. 1.09 0.85 31.02 35.28 37.85 33.27 6.47 0.71

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(Feni
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river
estuary)
Aver. 0.07 13.00 19.00 90.00 850.00 68.00 20.00 0.40
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(Shalea)

TECb NA 9.79 N.A. 43.40 NA 22.7. 35.80 NA

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PECb NA 33.00 N.A. 111.00 NA 48.60 128.00 NA

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a
Turekian and Wedepohl(1961). b MacDonald et al. (2000).
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Table 2

Heavy metal concentrations (µg/g) in sediment samples from the Feni river estuary and other
selected estuary from the references.

Mean concentrations (µg/g) of heavy metal

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Estuary Cr As Mn Pb Ni Ag Hg Co References

Feni river 35.28 0.85 37.85 6.47 33.27 1.09 0.71 31.02 This study

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estuary
(Bangladesh)

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Karnaphuli 11.56- 37.23- NA 21.98- NA NA NA NA Ali et al.
river estuary 35.48 160.32 73.42 (2016)

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(Bangladesh)
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Ganges 21- NA 254- 12- 8-57 NA NA NA Subramanian
estuary 100 800 115 et al. (1988)
(India)
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Luanhe River 9.6- 3.4- NA 22.6- 3.5- NA NA NA Liu et al.

estuary 35.6 13.5 43.7 35.8 (2016)
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(China)
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The Yangtze 79.1 9.1 NA 23.8 31.9 NA NA NA Wang et al.

River estuary (2015a)
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(China)

Yellow River 44.09 NA NA 43.05 Na NA NA NA Sun et al.

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Estuary (2015)
(China)
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Gironde 78.4 18.4 NA 46.8 NA NA NA NA Larrose et al.

estuary (2010)
(France)
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Table 3

Pearson correlation analysis of heavy metals in the Feni river estuary.

Ag As Co Cr Mn Ni Pb Hg

Ag

As -0.63

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Co -0.05 0.02

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Cr -0.35 0.39 0.90**

Mn -0.22 0.28 0.93** 0.98**

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Ni -0.28 0.40 0.90** 0.98** 0.98**

Pb -0.64* 0.84** 0.29 0.67* 0.59 0.64

Hg -0.31 0.53 0.78*

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0.95** 0.92** 0.93** 0.76*
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*Significant at p < 0.05 levels. ** Significant at p < 0.01 levels.
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HIGHLIGHTS

• EF, Igeo, CF and PERI were used to profile pollution levels of heavy metals in sediments of the
Feni River estuary.

• Ag, Co, Hg and Ni enrichment was more in sediments.

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• Ag and Co were above average shale values; however, Ni exceeded the TEC values.

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• Ag, Co and Ni threats to aquatic ecosystem should not be ignored.

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