Geochemical fractionation and risk assessment of trace elements in sediments from tide-dominated Hooghly (Ganges) River Estuary, India

Journal Pre-proof Geochemical fractionation and risk assessment of trace elements in sediments from tide-dominated Hooghly (Ganges) river Estuary, India

Priyanka Mondal, Marco Schintu, Barbara Marras, Alexandre Bettoschi, Alessandro Marrucci, Santosh Kumar Sarkar, Ranju Chowdhury, Muthuswamy Ponniah Jonathan, Jayanta Kumar Biswas PII:

S0009-2541(19)30502-9

DOI:

https://doi.org/10.1016/j.chemgeo.2019.119373

Reference:

CHEMGE 119373

To appear in:

Chemical Geology

Received date:

27 August 2019

Revised date:

5 November 2019

Accepted date:

6 November 2019

Please cite this article as: P. Mondal, M. Schintu, B. Marras, et al., Geochemical fractionation and risk assessment of trace elements in sediments from tide-dominated Hooghly (Ganges) river Estuary, India, Chemical Geology (2019), https://doi.org/10.1016/ j.chemgeo.2019.119373

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© 2019 Published by Elsevier.

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Geochemical fractionation and risk assessment of trace elements in sediments from tide-dominated Hooghly (Ganges) River Estuary, India Priyanka Mondala, Marco Schintub, Barbara Marrasb, Alexandre Bettoschib, Alessandro Marruccib, Santosh Kumar Sarkara,*, Ranju Chowdhurya, Muthuswamy Ponniah Jonathanc, Jayanta Kumar Biswas d

a

Department of Marine Science, University of Calcutta, 35 Ballygunge Circular Road,

Calcutta 700019, India

Centro Interdisciplinario de Investigaciones y Estudios sobre Medio Ambiente y Desarrollo

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c

Dipartimento di Scienze Mediche e Sanità Pubblica- Università di Cagliari, Cagliari, Italy

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b

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(CIIEMAD), Instituto Politécnico Nacional (IPN), Calle 30 de Junio de 1520, Barrio la Laguna Ticoman, Del. Gustavo A. Madero, C.P.07340, Ciudad de México, México. Department of Ecological Studies, International Centre for Ecological Engineering ,

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d

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University of Kalyani, Kalyani, Nadia 741235, India *Corresponding author. Address: Department of Marine Science, University of Calcutta, 35,

4849.

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Ballygunge Circular Road, Calcutta 700019, India. Tel: 09831242492; Fax: +91-33-2461

Abstract

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E-mail address: [email protected] (S.K. Sarkar)

The geochemical fractionation and potential mobilization of cadmium, chromium, copper, nickel and lead were studied in surficial sediments (top 0-10 cm; <63μm grain-size) of the Hooghly (Ganges) River Estuary, eastern part of India, using a sequential extraction procedure. The risk assessment was evaluated at three specific levels; i.e., enrichment level (enrichment factor, geo-accumulation index), the availability level (elements bound to different fractions, risk assessment code, Individual and Global contamination factors) and biological toxicity level (Potential ecological risk index; sediment quality guidelines). Different geochemical phases indicated heterogeneities in TE distribution patterns

as

follows: (i) Cd was dominant in the exchangeable phase and significant proportion of Pb was bounded to the reducible fractions; (ii) the potential mobile fraction (ΣF1−F3) in the sediments was higher for Cd and Pb (> 46%), reflecting their adverse impact on benthic

Journal Pre-proof organisms as they are weakly bound to the sediment and can migrate to water; (iii) a minor fraction of Cu (<10%) was found in the oxidizable fraction suggesting less environmental risk to the aquatic biota and (iv) the dominance of the Ni, Cr and Cu in the residual fraction supports the assumption of their geogenic origin. Both Cd and Cu posed medium to high ecological risk values based on risk assessment code (RAC). Global Contamination Factor (GCF) values allowed to identify the "pollution hotspots" in the study area.

Keywords:

trace

elements;

geochemical

fractionation;

bioavailability;

mobility;

Introduction

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environmental risk; Hooghly River Estuary

Rapid urbanization and industrialization result in the increase of trace element (TE)

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concentrations, especially in developing countries including India, and their subsequent

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release into the estuaries where sediments serve as the ultimate sink (Gadkar et al., 2019; Jung et al., 2019).The complex estuarine hydrodynamics play a very important role in the

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deposition, re-suspension and transportation of the TEs in the sediments (Pourabadehei and Mulligan, 2016; Wang et al., 2016), where they persist for long period and become

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bioavailable to living organisms due to their potential to bioaccumulate and biomagnify through food chain (Bryan & Langston, 1992; Zhou et al., 2008; Bakshi et al., 2018). For

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better understanding the risk associated with TEs, contamination indices such as Geoaccumulation Index (Igeo), Enrichment Factor (EF), Potential Ecological Risk Index (RI) and Sediment Quality Guidelines (SQGs) are considered. In general, TEs in sediments can exist in different chemical forms, namely, the acidsoluble/ exchangeable fraction (F1), Reducible fraction (F2), oxidisable fraction (F3), and residual fraction (F4) (Tessier et al., 1979; Rauret et al., 1999; Zhang et al., 2017). Quantification of total TE concentrations in estuarine sediments does not reflect their contamination status (Sundaray et al., 2011) since bioavailability; toxicity and mobility of each element greatly differ depending on their mineralogical and chemical form (Baeyens et al., 2003; Nicolau et al., 2006; Nouri et al., 2011). Furthermore, knowledge about geochemical fractions and speciation of TEs in sediments is required to understand their mobilization processes as well as to identify the geochemically reactive pools, which act as a better indication of their potential risk (Li et al., 2016; Matong et al., 2016; Rinklebe et al., 2016). The progress of sediment formation influence the geochemical distribution of TEs in

Journal Pre-proof sediments as sediments are dynamic systems and their genesis depends on the climate along with the position in the landscape (Rinklebe and Shaheen, 2017). The risk posed by TE pollution does not depend only on the total TE content but on their chemical speciation (Zhu et al., 2012). To assess the ecological risk of TEs in sediments considering these aspects, Individual Contamination Factor (ICF), Global Contamination Factor (GCF) and Risk Assessment Code (RAC) were evaluated. The Hooghly River, a major source of water for the people living in the plains of West Bengal, India, receives industrial and urban pollutants from point sources and large amount of

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pesticides, fertilizers and other organic pollutants from non-point sources throughout its course. Rapid urbanization and industrialization of the catchment area are responsible for

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increased concentration of trace elements, petroleum hydrocarbons and high molecular weight organic contaminants in the estuarine sediments. Several studies have been conducted

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on TE contamination in sediments along the Hooghly River Estuary (Antizar-Ladislao et al.,

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2015; Sarkar et al., 2017; Mondal et al., 2018a, 2018b), but record on geochemical fractionation is very limited (Massalo et al.,2012). The complex dynamic coastal zone of

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HRE, an important biodiversity hotspot, is getting seriously affected mainly due to intensive human activities (e.g., industrialization, urbanization, agricultural development, reclamation

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processes etc.,), and climate change. The contamination from potentially toxic inorganic elements is getting increased steadily, which are accumulated in benthic and pelagic

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organisms at an alarming rate (Alam et al., 2010; Fattorini et al., 2013; Watts et al., 2013; Chatterjee et al., 2014). Among the Indian estuaries, Hooghly is unique in being the largest, and as the mainstay of inland capture fisheries production of the country. Most significantly, it acts as the potential breeding and nursery ground of finfish and shellfish, supports a diverse flora and fauna including rare, vulnerable and endangered species and extends enormous ecosystem services. Considering the above consequences, the present work has been undertaken with the following objectives : (1) to investigate the concentrations and spatioseasonal distribution of TEs (As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, V and Zn) in sediments and geochemical fractionation of Cd, Cr, Cu, Ni and Pb in surface sediments; (2) to assess the mobility and availability of TEs in different geochemical fractions in the sediments and (3) to determine the contamination and ecological risks associated with TEs by using pollution indices such as, Igeo, EF, RAC, ICF and GCF.

2.

Description of the study area

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2.1. Geographical and geological setting

Ganges, the largest river of India, originates from the Gangotri glacier (at altitude of 4206 m) in the mountain range of Himalayas (Chakraborty et al., 2014). It drains through the states of Uttarakhand, Uttar Pradesh, Bihar and West Bengal covering a distance of ~2525 km before debouching into the Bay of Bengal. The Ganges basin with 1949 cities and towns and population over 500 million, has highest population density (712 persons per square kilometre) in India (2011 census). After flowing over 2000 km, it bifurcates near Rajmahal

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(Bihar, India) — the eastern course being Padma channel (Bangladesh) and the western course, the Bhagirathi–Hooghly channels (West Bengal, India). The Hooghly River Estuary

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(HRE) (21°31′N–23°30′N and 87°45′E–88°45′E), the major distributary of Ganges, extends

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over an area of approximately 6X104 km2 and is ~295 km long. The river is tidal ~240 km upstream from the sea (Bay of Bengal) and is subjected to semidiurnal tides. The annual tidal

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range at Gangasagar, close to the confluence of Hooghly and Bay of Bengal, varies from 5.37 m to 0.71 m (mean values) while at Kolkata (former Calcutta), located 110 km north of

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Gangasagar, it ranges from 5.11 m to 1.26 m (mean values)

in spring and neap tide

respectively. Based on physical characteristics, the estuary has been characterized as a

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positive, mixohaline, well-mixed estuary (Mondal et al., 2018a). The wet south-west monsoon brings 70-80% of annual rainfall between July and September with an annual

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average rainfall of ~1700 mm (Rakshit et al., 2014).The depth of the estuary varies along the channel from 21 m at Diamond Harbour to ~8 m at the mouth of the estuary (CIFRI, 2012). The width of the river at the mouth of the estuary is ~25,000 m. The total annual sediment load of Hooghly River at Calcutta was calculated as 411 X106 t (328 X106 t sediment load + 83 X106 t chemical load) (Abbas and Subramanian, 1984) and the sediment accumulation rate is ~3.0 – 4.8 mm year-1 (Banerjee et al., 2012). The total erosion rate (549 t/km2/yr) of the basin at Calcutta is almost three times that of Amazon and over three times that of the world average (150 t/km2/yr) (Subramanian et al., 1987).

2.2.

Anthropogenic set up

Kolkata (population ~ 4.5 million), Howrah (population ~ 4.8 million) and port city Haldia (population ~ 0.2 million) are the major urban settlements on either banks of Hooghly river. Though the river serves as a major source of water supply to the region, it subsequently

Journal Pre-proof receives huge load of untreated/semi-treated domestic and municipal sewage from the urban settlements as well as runoffs from nearby agricultural lands. Effluents from industries such as, brick kilns, paper and pulp, jute and cotton textiles, tanneries, paints, coal-based thermal power plant, distillery, etc. (as shown in Supplementary Fig. 1) are discharged into the river directly or indirectly contributing substantial inorganic and organic pollutants. According to the reports of National Mission for Clean Ganga (NMCG), the river receives 87 million L/day wastewater from 22 grossly polluting industries out of which chemical industry discharges 70% of total wastewater generated, followed by pulp & paper industry which is 20% (https://nmcg.nic.in/pdf/pollution%20assessment.pdf). Human induced stresses such as sand

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mining from river bed, riverine transport, immersion of idols (containing synthetic paints),

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and use of antifouling paints in country boats as well as frequent dredging activities also

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aggravate the pollution problem.

Materials and methods

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3.1. Sampling sites, collection and pre-treatment of samples

Eight sampling sites, namely, Tribeni (S1), Barrackpore (S2), Babughat (S3), Budge Budge (S4), Nurpur (S5), Diamond Harbour (S6), Lot 8 (S7) and Gangasagar (S8) (as shown in

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Supplementary Fig. 1), have been selected along the ~175 km long tidal stretch of HRE. The sampling site Gangasagar is situated at the confluence of R. Hooghly and Bay of Bengal

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while Tribeni is located in the upstream region experiencing negligible tidal influence. Due to diversity of pollutant sources and high population density of the region, tidal mixing and salinity gradients, the river stretch considered here provides an iconic fluvial system for comparing the impact of anthropogenic stresses and other environmental matrices. The surface sediment samples (top 0-10 cm) were collected in triplicate using plastic spatula from the intertidal regions during ebb tide during covering three seasons: premonsoon, monsoon and post-monsoon. The research samples were kept in acid–rinsed polyethylene bags with no head space and temporarily stored in a cooler box with ice packs at 4°C to prevent changes in chemical composition among different phases. The sediments were stored at -20°C until further analyses. These were oven-dried at 40°C to constant weight and ground gently with an agate mortar and pestle. A portion of the dried sample was sieved through a 63µm nylon mesh for homogenization, and stored in sealed plastic bags. A fraction of fresh unsieved sample was separated for determining the sediment characteristics.

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3.2. Physico-chemical analysis of sediments

Physicochemical parameters such as air and sediment temperature were taken immediately in the field by a Celsius thermometer (0–110°C, mercury) and the pH of the samples was determined with the help of an ORP meter (model no. HI 98160) using combination glass electrode manufactured by Hanna instrument (India) Pvt. The methodology related to analyses of the sediment physico-chemical variables (such as organic carbon (Corg) content; carbonate content, grain size analyses and textural parameters)

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has been described in detailed by previous workers (Sarkar et al., 2017; Mondal et al., 2018a).

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The content of moisture was analysed following SAA (1977).

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3.3. Total trace element (TE) determination

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Aliquots of ~ 0.2 g of sediments were placed in Teflon vessels with 3 mL of HCl and 9 mL of HNO3 (Merck Suprapur, trace metal grade). After each addition, the samples were left

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to rest for 15–20 min. The vessels were then heated in an Ethos D microwave oven (Milestone, US) for the following cycle: 2 min at 250 W, 1 min at 0 W, 5 min at 250 W, 4

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min at 400 W, 4 min at 600 W and, finally, 5 min at 300 W (EPA 3051A-2007). After cooling, the samples were filtered through an ashless Whatman 41 filter, diluted to 100 mL

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with Milli-Q water and analysed. Blanks were prepared using the same procedure without sediment. The TE determinations were performed by graphite furnace atomic absorption spectrometry (GF-AAS) using the model Varian GTA120-AA240Z with the Zeeman Effect and background correction (As, Cd, Cr, Cu, Ni, Pb, and V) or a flame AAS for Fe, Mn, and Zn (Varian AA240F). Total Hg was measured using a Direct Mercury Analyzer (DMA-80, Milestone, US). 3.4. Sequential extractions of selected trace elements Sequential extraction of five toxic TEs (Cd, Cr, Cu, Ni and Pb) was performed on aliquots of dried sediments following three-stage procedure (Rauret et al., 1999; Schintu et al., 2016): 1) Acid-soluble /exchangeable fraction (F1); 2) Easily reducible fraction, bound oxides Fe/Mn (F2); 3) Oxidisable fraction, bound organic matter and sulphides (F3) and 4) Residual fraction (F4) as shown in Supplementary Table 1. 3.5. Quality Assurance/Quality Control (QA/QC)

Journal Pre-proof All the materials used for the experiments were carefully cleaned by soaking in dilute HNO3 (1:10) and rinsed with deionized water Milli-Q water (Millipore). The accuracy and precision of the analyses were checked by analysing 7 replicate samples of the reference material IAEA 158 “Trace metals and methylmercury in marine sediments” (Campbell et al., 2008) and 7 replicate samples of the reference material SETOC-721 (Wageningen University, The Netherlands). The accuracies were within 15% of the certified values for arsenic and better than 10% for the residual elements. The precision, expressed as RSD, was always better than 7% for the measured TEs. Element concentrations for Cd, Cr, Cu, Ni, and Pb in BCR sequential extraction were tested using the reference material, BCR-701-Lake sediment.

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The concentrations obtained for each element demonstrated recoveries greater than 85%,

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which can be considered satisfactory for such type of analyses (Pueyo et al., 2001). The sum of the TE concentrations (3 steps plus the residue) in the individual fraction of each sample

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agreed within 20% with the total digestion.

Determination of bioavailable and non-bioavailable fractions

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3.6.

Element bioavailability factor was deduced from the formula proposed by Fatoki and

Evaluation of sediment contamination and risk assessment

3.7.1.

Geo-accumulation Index (Igeo)

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3.7.

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(F3+F4)/ (F1+F2+F3+F4).

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Awofolu (2003): (F1+F2) / (F1+F2+F3+F4) and the non-bioavailable fractions to be

The geo-accumulation index (Igeo) is defined by the following equation: Igeo = log2 [Cn/1.5* Bn]

where, Cn = concentration of the examined element ‘n’ in the surface sediments; Bn = geochemical background concentration of element ‘n’. Factor 1.5 is the background matrix correction factor due to lithogenic effects. According to the different Igeo values, the TE pollution levels can be interpreted as follows: Igeo ≤ 0, uncontaminated (Class 0); 0 < Igeo ≤ 1, uncontaminated to moderately contaminated (Class 1); 1< Igeo ≤ 2, moderately contaminated (Class 2); 2< Igeo ≤ 3, moderately to heavily contaminated (Class 3); 3 < Igeo ≤ 4, heavily contaminated (Class 4); 4< Igeo ≤ 5, heavily to extremely contaminated (Class 5); Igeo ≥ 5, extremely contaminated (Class 6) (Müller 1981).

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3.7.2.

Enrichment Factor (EF)

Enrichment factor is a useful tool to discriminate among anthropogenic and natural inputs of TEs and to reflect the state of contamination in the environment (Zhao et al., 2015). To reduce the impact of the particle grain size effects on TE pollution, data on element accumulation should be normalized by a reference element (Wang et al., 2015). In this study, Fe has been selected as reference element to distinguish between natural and anthropogenic sources. Therefore, according to Garcıa-Pereira et al., 2015, the enrichment factor (EF) with

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respect to Fe can be computed as:

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EF = (Element/Fe) Sample/ (Element/Fe) Background

Generally, an EF value of ~1 suggests that a given TE may entirely originate from natural

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weathering processes or crustal materials (Zhang and Liu, 2002). It might be noted that minor positive deviation of EF value from unity may not originate from anthropogenic activities. An

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EF value of >1.5 suggests that a significant portion of element is being contributed from

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anthropogenic sources and not due to natural geogenic sources (Feng et al., 2004).

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3.7.3. Sediment Quality Guidelines (SQGs)

Sediment quality guidelines (SQGs) are important tools for assessing contamination of estuarine sediments (Long et al., 1995). Two sets of sediment quality guidelines such as effects range-low (ERL) and effects range-medium (ERM) or threshold effects level (TEL) and probable effects level (PEL) are proposed to determine whether the TEs in sediments pose a threat to aquatic ecosystem (Long et al., 1998; MacDonald et al., 2000). In this study, we have used both sets of SQGs to assess the potential adverse biological effects. Based on SQGs proposed by Long and Morgan (1990) and Long et al. (1995), adverse effects of TE concentrations in sediments can be classified into three ranges: observed scarcely (< ERL value), observed occasionally (greater than ERL value but less than ERM value), and observed frequently (> ERM value). The threshold effects level (TEL) were interpreted to present chemical concentrations below which adverse biological effects rarely occur, and the probable effects level (PEL) were intended to present chemical concentrations above which adverse biological effects frequently occur (Macdonald et al., 2000).

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3.7.4. Potential Ecological Risk Index (RI)

Potential Ecological Risk Index (RI) was introduced to assess the ecological risk degree of TEs in sediments. The value of RI, which is widely used, can be calculated using the following equations (Hakanson 1980): Cif = CiD/CiR

(eq. 1) (eq. 2)

RI = ΣEir

(eq. 3)

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Eir = Tir×Cif

where, RI = sum of potential risk of individual TE; Eir = potential risk of individual TE; Tir =

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toxic-response factor for a given TE; Cif = contamination coefficient; CiD = TE concentration

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in sediments; CiR = average background shale value. Hakanson (1980) defined five categories of Eir (Eir<40, Low risk; 40 ≤ Eir< 80, Moderate risk; 80 ≤ Eir<160, Considerable risk; 160 ≤

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Eir<320, High risk; Eir ≥ 320, Very high risk) and four categories of RI (RI < 150, Low risk;

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150 ≤ RI < 300, Moderate risk; 300 ≤ RI < 600, Considerable risk; RI ≥ 600, Very high risk).

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3.7.5. Individual Contamination Factors (ICF) and Global Contamination Factor (GCF)

The individual contamination factors (ICF) for the different sediment samples were

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obtained by dividing the sum of the non-residual fractions (F1 + F2 + F3) by the residual fraction (F4) of each sample, while Global Contamination Factor (GCF) for each sampling site was calculated by summing the ICF of all the TEs obtained for the sediment samples (Ikem et al., 2003). The applicability of GCF is important as it reflects the overall potential risks posed by the toxic elements to the environment and biota (Yao et al., 2006). Both ICF and GCF classifications were interpreted as suggested by Zhao et al. (2012): ICF < 0 & GCF < 6 - indicates low, 1 < ICF < 3 & 6 < GCF < 12– moderate, 3 < ICF < 6 & 12 < GC < 24 – considerable whereas ICF > 6 & GCF > 24 presents high contamination.

3.7.6. Risk Assessment Code (RAC)

The RAC, proposed by Perin et al. (1985), was used to evaluate the bioavailability and mobility of TEs in sediments.

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𝑅𝐴𝐶 =

𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛𝑠 𝑜𝑓 𝑇𝐸 𝑖𝑛 𝐹1 𝐹1 + 𝐹2 + 𝐹3 + 𝐹4

The RAC indices can be divided into following five classes: Class I, no risk, RAC < 1; Class II, low risk, 1 < RAC < 10; Class III, medium risk, 11 < RAC < 30; Class IV, high risk, 31 < RAC< 50; and Class V, very high risk, RAC > 50.

4.

Results

4.1.

Sediment physico-chemical properties

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The annual mean values of sediment quality parameters clearly exhibited an almost

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homogenous pattern of distribution throughout the study period as evidenced in Fig. 1. pH values exhibited small range of variations (7.09 at Babughat (S3) to 7.86 at Barrackpore (S2)

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during monsoon), with an alkaline nature suitable for better productivity. Values of Corg were considerably low with the following seasonal trend: Pre-monsoon (0.47 ± 0.28%) > post-

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monsoon (0.40± 0.39%) > monsoon (0.24 ± 0.05%). Moisture content varied from 26.5 to

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40.0% of the sediment weight (mean: 32.5%) while CaCO3 exhibited moderate variations (9.02 to 15.4 % of the dry sediment weight; mean: 11.3 %).

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Three typical sediment textural patterns (clayey, clayey loam and sandy clay loam) have been identified with the predominance of clay particles (<4 µm) at 87.5% of the sampling

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sites. The mean grain size composition of HRE sediments revealed the dominance of clay particles (56.4%) followed by silt (27.6%) and sand (16.0 %). The maximum clay content was recorded at Babughat (S3) during post-monsoon (78.2%) while clayey loam texture was exclusively recorded at Budge Budge (S4) during post-monsoon season. The silt content varied from 14.3% at Babughat (S3) during post-monsoon to 35.0% at Nurpur (S5) during pre and post-monsoon while the maximum (53.0%) and minimum (4.7%) content of sand was recorded at Lot 8 (S7) and Nurpur (S5) respectively during pre-monsoon season. 4.2. Assessment of total trace elements The descriptive statistics of the TEs in the sediment samples are shown in Table 1. On the basis of average annual concentrations (mg kg-1), total TE in sediments decreased in the following manner: Fe >Mn> Zn > V> Cr > Ni > Cu >Pb> As > Cd> Hg. The maximum concentrations (in mg kg-1) for As (5.7), Cu (24.6), Hg (0.03), Ni (28.6) and V (46.8) were encountered at Barrackpore (S2) and for Fe (29,560) and Mn (641) at Gangasagar (S8) during

Journal Pre-proof monsoon season. An overall low concentration of majority of the TEs (Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, V and Zn) was recorded during monsoon season without showing any specific spatial trend of distribution. Comparing the average shale value, proposed by Turekian and Wedepohl (1961), TE concentration showed lower value except Cd. The maximum concentrations for Cd during the 3 seasons (pre-monsoon: 0.54 mg kg-1); monsoon: 0.49 mg kg-1; post-monsoon: 0.65 mg kg-1) were recorded at Babughat (S3), exceeding the background value of 0.30 mg kg-1.

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4.3. Trace element fractionation The present study has considered geochemical fractionation of 5 selected TEs (Cd, Cr,

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Cu, Ni and Pb) to evaluate the strength of association between TEs and sediments (Wang et

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al., 2015; Najamuddin et al., 2016). The selected TEs (Cd, Cr, Cu, Pb and Ni) are highly toxic when taken up by living organisms. The percentage of TE extracted in each fraction covering

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three seasons, as depicted in Fig. 2, was calculated from the ratio between the concentration of the element in each fraction, and the sum of concentrations in all fractions. The

sequence:

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geochemical fractions of each TE showed anomalous characteristics with the following

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Cd: acid-soluble > residual > reducible >oxidisable Cr: residual >oxidisable> reducible > acid-soluble

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Cu: residual > reducible > acid-soluble >oxidisable Ni: residual >oxidisable> reducible > acid-soluble Pb: reducible > residual >oxidisable> acid-soluble Cadmium was strongly associated with the acid-soluble/exchangeable fractions (F1) for all the sediment samples ranging from 32.1% at Gangasagar (S8) to 92.9% at Babughat (S3) during monsoon and pre-monsoon respectively. Reducible fraction, comprising 63.5% of the total element content, was the most dominant geochemical phase for Pb, followed by residual (26.4 ± 6.3), oxidisable (7.2 ± 1.0 %) and the acid-soluble (3.0 ± 1%) fraction. Lead concentration in the reducible fraction showed the following seasonal variations: 6.7 mg kg-1 at Nurpur (S5) to 8.8 mg kg-1 at Babughat (S3) during pre-monsoon; 2.8 mg kg-1 at Budge Budge (S4) to 6.5 mg kg-1 at Gangasagar (S8) during monsoon and 4.8 mg kg-1 at Nurpur (S5) to 7.9 mg kg-1 at Diamond Harbour (S6) during post-monsoon.

Journal Pre-proof The residual fraction for Cr, Cu and Ni ranged from 18.0 - 29.3 mg kg-1, 5.0 – 16.4 mg kg-1 and 13.2 – 28.1 mg kg-1 respectively, with the minimum concentrations being observed at sampling sites located upstream of the estuary (Tribeni (S1) to Budge Budge (S4)). The average percentage association of the residual fraction of TEs are present in the following decreasing order: Ni (85.7 ± 2.9%) > Cr (85.1 ± 3.5%) > Cu (50.4 ± 11.6 %) while very minor fractions of the same were present in the oxidisable phase: Cr (7.5 ± 1.2 %) > Ni (6.9 ± 0.7 %) > Cu (4.5 ± 2.3%). Among the non-residual fractions, Cu was mainly associated with Fe and Mn oxides (F2) followed by acid-soluble (F1) and oxidisable fraction (F3)

Bioavailability and mobility of trace elements

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4.4.

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(concentration (mg kg-1) in F2 (5.5±2.1) > F1 (2.5 ± 1.0) > F3 (0.8±0.45)).

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The bioavailable fractions for TE ranged from 46 - 99 % for Cd, 2-12% for Cr, 8-64% for Cu, 4-15% for Ni and 56 -76% for Pb (Fig.3). The annual average percentage of Cd showed high

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bioavailability dominance of 85%, closely followed by Pb (66%). Both Cr and Ni, exhibited low bioavailability sharing 93% in the non- bioavailable fraction. About 45% of the total Cu

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concentration is associated with the bioavailable fraction, while 55% of it is bound to the non-

4.5.

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bioavailable fraction.

Assessment of sediment contamination

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4.5.1. Geo-accumulation Index (Igeo)

Based on the classification of Müller (1981), the Igeo values of the TEs (except Cd) for all sampling sites were found to be below zero (Igeo ≤ 0), indicating that the sediments were practically unpolluted (Table 2). The Igeo value for Cd varied from -4.8 at Gangasagar (S8) during monsoon to 0.53 at Babughat(S3) during post-monsoon. Cadmium exhibited class I level of contamination (0≤ Igeo ≤ 1) at Babughat (S3) for all three seasons whereas exclusively at Budge Budge (S4) during post-monsoon. The average Igeo values for the TEs were in the following descending order: Mn (-1.4) >Pb (-1.5) > Fe (-1.6) > Zn (-1.6) > Cr (-2.1) > Cd (2.2) >As (-2.3) > Ni (-2.4) > V (-2.5) > Hg (-7.0).

4.5.2. Enrichment Factor (EF)

Journal Pre-proof In the present study, the average EF values of As (0.60), Cd (1.2), Cr (0.72), Cu (0.74), Hg (0.02), Mn (1.2), Ni (0.58), Pb (1.1), V (0.57) and Zn (1.0) were below 1.5 (EF <1.5) indicating their natural or lithogenic origin (Table 2). However, the EF of Cd at sampling site Babughat(S3) and Budge Budge (S4) was found to be greater than 1.5 (EF > 1.5) implying the acquisition of anthropogenic inputs, reaching the highest value at Babughat(S3) (EFCd = 4.8) during post-monsoon. Due to high EF values recorded for both Cd and Pb, the site Babughat (S3) needs special attention, mainly affected by severe human- induced stresses. The EF values further corroborate the results of Igeo indicating the surface sediments along

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HRE have anthropogenic inputs of Cd.

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4.6. Biological risk assessment

Sediment Quality Guidelines (SQGs)

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4.6.1.1.

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4.6.1. Risk based on total TE concentrations

The concentrations of As, Cd, Cr, Cu, Hg, Pb and Zn at all sampling sites were lower than ERL value (20.9 mg kg-1) at

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their corresponding ERL values (Table 3). However, the concentration of Ni has exceeded the Tribeni(S1), Barrackpore(S2), Gangasagar(S8), Diamond

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Harbour (S6; during pre-monsoon) and Lot 8 (S7; during post-monsoon), suggesting adverse biological effects in sediments. Nickel, being an essential element for all organisms, becomes

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toxic at high concentrations. A long term exposure of Ni to marine organisms can modify their morphology and behaviour (Alam and Manghan, 1992) and disrupt the storage and/or mobilization of essential metabolic substrates such as proteins, glucose (Scott and Sloman, 2004; Khan et al., 2014).

Concentration of Cu has exceeded the prescribed TEL value (18.7 mg kg-1) at Tribeni (S1) and Barrackpore (S2) over the seasons and also at Lot 8 (S7) exclusively during postmonsoon. Meanwhile, Ni concentrations were between TEL and PEL guidelines at 87.5%, 50% and 75% of the sites during pre-monsoon, monsoon and post-monsoon season respectively. These results indicate that adverse effect on sediment-dwelling organisms would be observed occasionally. Campana et al. (2012) investigated the sublethal effects of Cu to the benthic crustaceans (amphipod and harpacticoid copepods) and found that reproduction was strongly affected by the sediment properties and toxicity related to sediment-bound Cu. The rest of the TEs such as As, Cd, Cr, Hg, Pb and Zn had concentrations below their respective TEL values suggesting that they have rarely noxious impact on biota. The results

Journal Pre-proof demonstrated that Cu and especially Ni should be studied carefully emphasizing on the potential ecological risks they might pose to the environment (Table 3).

4.6.1.2.

Potential Ecological Risk Index (RI)

Potential Ecological Risk Index (RI) was calculated considering 8 TEs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) as the biological toxicity factor (Tir) for Fe, Mn and V were not available. The Eir values for all the TEs, except Cd, at 100% of the sampling sites were below 40 (Eir < 40), indicating that these elements pose low potential ecological risk to the benthic and

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aquatic organisms. Cadmium exhibited moderate ecological risk (Eir = 48.5 - 65.1) at two

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sampling sites (Babughat (S3) during pre and post-monsoon and Budge Budge (S4) during post-monsoon season) (Table 3).

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RI values ranged from 12.71 at Lot 8 (S7) to 75.0 at Babughat (S3) with a mean value of

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25.7 ± 6.2 (Fig. 4), indicating low ecological risk (RI < 150) at all the sampling sites.

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4.6.2. Risk based on trace element fractionation

4.6.2.1. Individual Contamination Factors (ICF) and Global Contamination Factor (GCF)

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The TEs with high ICF reveal low retention time and are released into the environment easily and therefore possess high risk to aquatic life (Saleem et al., 2015). The

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ICF value for Cd at majority of the sites ranged from 9.1 – 119.5 indicating high contamination (excepting Lot 8 (S7) and Gangasagar (S8)) (Fig.5). In contrast, low contaminations (ICF < 1) were recorded for Cr and Ni at 100% sampling sites followed by Cu at 45.8% of the sampling sites (as shown in Table 3), indicating low mobility and high stability of these TEs in the environment. In contrast, Pb exhibited moderate to considerable contamination at all the study sites. The results of ICF revealed that Cd followed by Pb and Cu have the lowest retention time in sediments and consequently the highest ability to be released into the overlying water whereas Cr and Ni manifested the highest retention time. The GCF, calculated by summing the ICF for five TEs, varied from 123.7 at Babughat (S3) during post-monsoon to 4.1 at Gangasagar (S8) during monsoon season (mean value 31.3) indicating that the sediments were highly contaminated (Fig. 5). The results revealed that the amalgamated effect of Cd, Cr, Cu, Ni and Pb might cause potential hazards to the aquatic ecosystem.

Journal Pre-proof 4.6.2.2. Risk Assessment Code (RAC)

The RAC (%) results in sediments exhibited no risk for Cr (except at Tribeni (S1) during pre-monsoon and monsoon season and at Babughat (S3) during post-monsoon) and low risk for Ni and Pb (except at S8 during monsoon) (Table 4). Medium risk was indicated by Cu at 83.3% of the sampling sites while the remaining 16.7% posed low risk to the benthic organisms. Cadmium manifested very high risk (RAC = 32.1 – 92.9%) at all the sampling sites and are of great concern. A significant remedial measure should be taken to prevent the

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highly mobile Cd from entering the food chain and pose threat to the estuarine environment.

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5.1. Physico-chemical characteristics of sediment

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5. Discussion

In the estuarine environment, Corg might originate both from

allochthonous and

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autochthonous sources (Noronha-D'Mello and Nayak, 2016; Neyestani et al., 2016).The prevalent low Corg content corroborates previous findings from this estuarine environment

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(Antizar-Ladislao et al., 2015; Sarkar et al., 2017; Mondal et al., 2018 a, b) which might be ascribed to the constant tidal and flushing activities. Calcium carbonate (CaCO3) is mainly

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biogenic in origin (e.g., shell fragments) in the estuarine sediments.

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The sediment textural pattern is influenced by set factors such as morphology of the river channel, source, corrosion, abrasion, sorting and depositional features of the sediment (Kumar and Ramanathan, 2015). Finer particles have greater affinity for binding TEs due to greater surface area and thus act as an important sink of contaminants (Cundy and Croudace 1995; Spencer et al., 2003). The textural pattern at Lot 8 (S7) and Gangasagar (S8) displayed sandy clay loam during the pre-monsoon season indicating the dominance of sand particles. These two high energy zone sites, where huge influx of seawater from Bay of Bengal prevents the sedimentation of fine-grained particles (Nair et al., 1993; Ayyamperumal et al., 2006; Rodríguez-Espinosa et al., 2018). Due to flocculation and faster settling of suspended particles, sampling sites situated in the upstream of the river exhibited the dominance of finegrained fraction as they belong to low energy zone. 5.2. Concentration and spatial distribution of trace elements

Journal Pre-proof Coefficients of variations (CV) were used to estimate the variability of analysed TEs between different sampling sites and seasons. Maximum variation was observed for Cd (CV111.9%) reflecting its heterogeneous distribution pattern while the other TEs exhibited an overall homogeneous spatial variations as revealed from CV values: As (25.2%); Cr (14.5%); Cu (21.3%); Fe (16.1 %); Hg (24.0 %); Mn (15.7%); Ni (23.3%); Pb (16.6%); V(18.9 %); and Zn (22.1%). Among the TEs, Fe was found to be the most abundant element in all sediment samples as because it is one of the most common elements in the earth's crust fundamentally originating from natural sources. Similar observation was also reported by Venkatramanan et al. (2013) from Thirumalairajan river estuary, India and Chaharlang et al.

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(2016) from Shadegan wildlife refuge, Iran. The enrichment of the two lithogenic elements

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(Fe and Mn) at Gangasagar (S8) is mainly controlled by the supply of riverine input and occurrence of mangrove vegetation, corroborating the findings of Kasilingam et al., (2016).

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The inconsistent pattern of assortment of TE concentration along the HRE might be attributed to various physico-chemical factors which control the rate of adsorption-desorption of

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elements, tidal currents as well as the various anthropogenic activities (as previously stated in section 2.2). This is important to note that a number of tributaries from upstream to

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downstream of Hooghly estuary, namely Damodar, Rupnarayan and Haldi, play critically important roles in sediment deposition and geomorphological processes. These physical

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features along with tidal action and strong currents play significant role in transportation of sediment load and TE dynamics in the estuary. Furthermore, ion-exchange processes

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involving coupled adsorption and desorption also play a dominant role in generating TEs in the HRE (Samanta and Dalai, 2018). 5.3. Geochemical fractionation of trace elements The annual average percentage of the Cd in acid-soluble fraction was as high as 77.3 ± 14.4%, while only 7.7% and 5.7% comprised the reducible and oxidisable fractions respectively. The existing alkaline nature of the sediment plays a significant role for Cd abundance in F1 fraction which facilitates the replacement of Mg2+ or Ca2+ by this element in the crystal lattice of carbonate mineral due to the similar ionic radius of Ca (0.99Ǻ) and Cd (0.97Ǻ)(Yang et al. 2017). In addition, it might also favour the co-precipitation of this element with carbonates and its incorporation into the calcite lattice to give solid solutions of CdαCa1-αCO3 (Iwegbue et al., 2009; Sundaray et al., 2011; Ma et al., 2016). It is noteworthy to infer that enrichment of Cd (60-95% of the total concentration) in acid-leachable fraction from similar environmental set-up was reported by Mondal et al. (2018b). However,

Journal Pre-proof dominance of Cd in both exchangeable/acid-soluble as well as reducible fraction was reported by Wang et al. (2019). The dominance of Pb in the reducible fraction might be ascribed to the following reasons: (i) both natural organic matter and Fe-Mn oxides seemed to play an important role in controlling the adsorption of this element to sediment surface (Yuan et al., 2004; Fadiran et al., 2014). Lead species are strongly sorbed to Fe-Mn oxides, which were reported to be more important than association with clays and organic materials (Fergusson, 1990; Soliman et al., 2018) and (ii) both Fe and Mn oxides exist as nodule concretions and are excellent scavengers

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for Pb but are thermodynamically unstable under anoxic conditions. However, it is worth to refer that any change in the anoxic conditions of sediment will influence the release or

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retention of this element in the reducible phase (Charlatchka and Cambier, 2000; Fernandes and Nayak, 2016). Lead is mainly derived from industry and municipal discharges, massive

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use of lead-based paint in domestic and commercial purpose, use of acid-lead batteries by

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local people, use of pesticides containing Pb and automobile exhaust. Significant non-point sources of Pb in the aquatic environment are from urban run-off and atmospheric depositions

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(ATSDR 2007).

The chemically stable and environmentally immobile residual fraction indicate the

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portion of elements associated with the alumina-silicate minerals (Yang et al., 2014) and are not easily released into the aquatic environment (Solomon et al., 2016). This inert phase was

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dominated by Cr, Cu and Ni which might originate from natural weathering of the catchment area as recorded by Nasnodkar and Nayak (2019) from the Vaghotan estuary, west coast of India. The dominant proportion of Ni in residual phase corroborates the results of the previous studies by Qiao et al. (2013) from Shantou Bay, China; Saleem et al. (2015) from Mangla Lake, Pakistan; Lee et al. (2017) from Hoedong reservoir, Korea. The low degree of association of Cr with the non-residual fraction (average 15.0%) in sediments of HRE might be due to the inability of Cr3+ to form a precipitate or complex with Fe/Mn oxide-hydroxide and carbonates (Sundaray et al., 2011; Soliman et al., 2018). The association of Cu with organic matter might be due to the fact that Cu is preferably fixed with particulate organic matter (POM) in the river sediments which is also the main ligand accessible to Cu for complexation among TEs (Zhang et al., 2017). It has been further reported by Palleiro et al. (2016) that organic matters (together with non-crystalline Al and Fe hydrous oxides) are considered to be one of the most active sediment components which have the ability to retain Cu.

Journal Pre-proof However, Cu exclusively showed season-specific association at the site Lot 8 (S7), such as Fe and Mn oxides (F2) during post-monsoon and organic matter and sulfides (F3) during pre-monsoon (Fig. 3). An overall close similarity of the dominant geochemical phases for Cd, Cr, Cu, Ni and Pb is observed to the previous findings by Massolo et al.,(2012) from the Hooghly River and Sundarban Mangrove Wetland. These are as follows: (i) acid-soluble phase – Cd (> 60%), (ii) Reducible phase – Pb (55.7%); (iii) Residual phase – Cr (88.991%), Ni (~56%) and Cu (~40%). This trend of homogeneity endorses similar sediment type having same input source, relating to physico-chemical conditions of the estuary either during an ensuing diagenetic change or at the time of sedimentation.

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The study also revealed that percentage of TEs in the mobile fractions was lower

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during the wet monsoon season compared to dry pre and post-monsoon season which might be attributed to the increase in water mass flow which affected TE intake from anthropogenic

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sources. Furthermore, due to strong tidal actions prevailing during monsoon, the TEs were desorbed from the surface of the particles and tend to be present in the water column rather

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than be deposited in the sediment.

fractionation

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5.4. Assessment of bioavailability and mobility of trace elements in relation to geochemical

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The highest percentage bioavailability for Cd (99%) and Pb (76%) was recorded at Babughat (S3), during post-monsoon and pre-monsoon respectively. Being located at the

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vicinity of the metropolitan twin cities (Kolkata and Howrah), this sampling site receives huge amount of untreated/semi-treated industrial, municipal and sewage effluents, electronic waste as well as deposition of air pollutants from road traffic which are the potential sources of Cd and Pb in the sediment. The elevated levels of Cd and Pb in the bioavailable fractions might be introduced by anthropogenic intrusions and are considered to poses serious environmental hazards. Thompson et al. (2007) noted that Cd was linked to lysosomal damage and mortality of the benthic organisms. Again, Bourgoin et al. (1991) investigated the factors influencing Pb bioavailability to the bivalve mollusc Mytilus edulis and reported significant correlations occurred between Pb concentration in tissues

and

sediment bioavailable fractions. The presence of such toxic TEs in the environment ensures potential danger to the water making it unsafe for use. The impact of an element in an environment is determined by its ease of availability: the higher the level of bioavailability, the higher the impact on its target system (toxicity effect) (Fatoki and Awofolu, 2003; Okoro et al., 2017). Previous studies by Najamuddin et al. (2016) and Rodrigues and Formoso

Journal Pre-proof (2006) have documented that labile fractions associated with sediments mainly originate from anthropogenic activities, whereas the non-labile fractions commonly originate from natural processes.

6. Conclusions

The results displayed valuable insights into the geochemical mode of element retention, such as: Cd was predominately associated with the acid-soluble fraction (F1); Pb with reducible fraction (F2) while Cr, Cu, and Ni were primarily present in the residual fraction

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(F4). Cadmium was noted as the major contributor to sediment toxicity owing to its high

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bioavailable percentage and thus poses potential environmental risk during complex estuarine processes. Both Igeo and EF values for Cu, Zn, Cr, and Ni distinctly showed that these TEs

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were mostly derived from natural crustal contributions, whereas the values for Cd and Pb indicated anthropogenic inputs. According to RAC, Cd and Cu were associated with very

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high and medium risk levels respectively and can easily enter the food chain and poses serious threats for aquatic as well as benthic organisms. The authors recommend an in-depth

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investigation in HRE sediments, especially focusing on Cd and Pb in the labile fraction and adopting adequate control measures in compliance with national and international regulations

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on the protection of marine water systems. The study can help decision makers with a perceptive view of the current contamination status of this stressed estuarine environment,

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and support the coastal management and environmental protection strategies.

Acknowledgements

The research work was financially supported by the Department of Science and Technology

(DST),

New

Delhi,

India

[sanction

no.:

DST/INSPIRE

Fellowship/2014/IF140943] in a research project titled “Distribution and possible sources of trace metals in sediments along the Hugli Estuary and Sundarban Mangrove Wetland, India and their ecotoxicological significance”. The first author Priyanka Mondal is grateful to the DST for awarding her a research fellowship under “Innovation in Science Pursuit for Inspired Research (INSPIRE)" programme. The authors extend their sincere thanks and gratitude to the anonymous reviewers who have given their valuable comments and suggestions for the upgradation of the manuscript.

Journal Pre-proof Declarations of interest: none.

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Fig. 1.

Physicochemical characteristics of sediment at the different sampling sites.

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Fig. 2.

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Total concentration and percentage distribution of trace elements in four geochemical fractions at 8 sampling sites covering three seasons.

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Fig. 3.

The non-bioavailability and bioavailability percentage of trace elements in the sediment.

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Fig. 4.

Trend of Potential Ecological Risk Index (RI) at different sampling sites (RI < 150 = low risk).

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Fig.5.

The individual (ICF) and global contamination factor (GCF) in HRE (GCF < 6; low risk, 6 < GCF < 12; moderate risk, 12 < GCF < 24; considerable risk, GCF > 24; high risk).

Journal Pre-proof Table 1 Values of maximum, minimum, average, standard deviation (SD) and median (in mg kg -1) for total concentration of trace elements in the intertidal surface sediments along Hooghly River Estuary (HRE). Maximum

Minimum

Average

SD

Median

As

5.67

2.10

4.00

1.01

4.07

Cd

0.65

0.02

0.16

0.18

0.10

Cr

37.4

20.6

31.8

4.60

33.0

Cu

24.6

10.3

16.7

3.55

16.2

Fe

29560

15501

23322

3745

22979

Hg

0.02

0.01

0.02

0.00

0.02

Mn

641

311

482

76

477

Ni

28.6

13.1

19.8

4.62

19.2

Pb

12.9

6.02

10.7

1.79

11.3

V

48.1

24.2

36.3

6.86

35.3

Zn

64.5

23.8

46.9

10.4

45.1

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Trace elements

Table 2

Enrichment Factors and Geo-accumulation index value for trace elements in sediments along the Hooghly River Estuary. Enrichment Factor (EF) Trace Elements

As Cd Cr Cu Fe

Geo-accum

EF Range

Sediment Quality

Igeo Class

Igeo Range

0.60-0.75

No enrichment

Class 0

-3.21 to -1.78

0.09-4.81

No enrichment to moderate enrichment

Class1

-4.77 to 0.53

0.63-0.82

No enrichment

Class 0

-2.71 to -1.85

0.61-0.99

No enrichment

Class 0

-2.72 to -1.45

-

-

Class 0

-2.19 to -1.26

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Mn Ni Pb V Zn

0.02-0.04

No enrichment

Class 0

-7.80 to -6.40

0.97-1.30

No enrichment to minor enrichment

Class 0

-2.03 to -0.99

0.49-0.70

No enrichment

Class 0

-2.97 to -1.83

0.93-1.52

No enrichment to minor enrichment

Class 0

-2.32 to -1.21

0.49-0.70

No enrichment

Class 0

-3.01 to -2.02

0.76-1.31

No enrichment to minor enrichment

Class 0

-2.58 to -1.14

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Table 3


ii

> ERL and < ERM

iii

> ERM

b

Comparison with TEL and PEL

i

TEL and < PEL

iii

> PEL The grade of ecological risk

i

low risk

Cu

100

100

100

100

-

100

-

0

0

0

0

-

0

-

0

0

0

0

-

0

-

ii

moderate risk

iii

considerable risk

iv

high risk

v

very high risk

d

Individual Contamination Factor (ICF)

Fe

Hg

Mn

% of samples in each guidel

% of samples in each guidel

100

100

100

70.8

-

100

-

0

0

0

29.2

-

0

-

0

0

0

0

-

0

-

(Eir)

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Cr

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Comparison with ERL and ERM

i

na

a

ii

Cd

As

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Categories

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Percentage of trace elements in each category associated with biological risks.

% of samples in each grad 100

87.5

100

100

-

100

-

0

12.5

0

0

-

0

-

0

0

0

0

-

0

-

0

0

0

0

-

0

-

0

0

0

0

-

0

-

% of samples in each grad

i

low contamination

-

0

100

45.8

-

-

-

ii

moderate contamination

-

8.3

0

54.2

-

-

-

iii

considerable contamination

-

12.5

0

0

-

-

-

iv

high contamination

-

79.2

0

0

-

-

-

Journal Pre-proof Table 4 Comparison of risk assessment code values (RAC, %) at different sampling sites.

Cd

Cr

Cu

Ni

Pb

Tribeni (S1)

VH

N

M

L

L

Barrackpore (S2)

VH

N

M

L

L

Babughat (S3)

VH

N

M

L

L

Budge Budge (S4)

VH

N

M

L

L

Nurpur (S5)

VH

N

M

L

L

Diamond Harbour (S6)

VH

N

L

L

L

Lot 8 (S7)

VH

N

M

L

L

Gangasagar (S8)

VH

N

L

L

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Sampling Sites

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VH: very high; H: high; M-medium; L: low; and N: no risk.

Journal Pre-proof Declaration of interests

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5