heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts

MPB-07480; No of Pages 10 Marine Pollution Bulletin xxx (2016) xxx–xxx

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Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts Golam Kibria a,⁎, Md Maruf Hossain b, Debbrota Mallick b, T.C. Lau c, Rudolf Wu d a

School of Applied Sciences, RMIT University, Melbourne, Australia Institute of Marine Sciences & Fisheries, University of Chittagong, Bangladesh Department of Biology & Chemistry, City University of Hong Kong, Hong Kong d Department of Science and Environmental Studies, Hong Kong Institute of Education, Tai Po, Hong Kong b c

a r t i c l e

i n f o

Article history: Received 30 December 2015 Received in revised form 3 February 2016 Accepted 4 February 2016 Available online xxxx Keywords: Trace/heavy metals Artificial mussel Pollution Bangladesh Bay of Bengal Environmental and public health risk

a b s t r a c t Using artificial mussels (AMs), this study reports and compares time-integrated level of eleven trace metals (Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, U, Zn) in Karnafuli River estuary and coastal area of the Bay of Bengal, Bangladesh. Through this study, “hot spots” of metal pollution were identified. The results may demonstrate that the Karnafuli Estuary, and adjacent coastal area of Chittagong, Bangladesh are highly polluted by high risk metals (cadmium, chromium, copper, mercury, nickel, lead, uranium). Agricultural, domestic and industrial wastes directly discharged into the waterways have been identified as the main causes of metal pollution in Chittagong, Bangladesh. The high level of metal pollution identified may impact on local water quality, and seafood catch, livelihoods of people and public health resulting from seafood consumption. There is a need for regular monitoring to ascertain that local water quality with respect to metal levels are within acceptable levels to safeguards both environmental health and public health. © 2016 Elsevier Ltd. All rights reserved.

Many rivers, estuaries and coastal areas of Bangladesh are heavily contaminated with agricultural, domestic, industrial effluents (e.g. from farming, sewage, landfills, paper mills, dyeing industries, textile mills, oil refineries, tanneries, fertiliser factories, ship breaking yards (Hossain, 2010). Previous studies have revealed that fertilisers, farm manures, fungicides, effluents from sewage and pulp and paper mills, waste incineration, refineries, urban and storm water run-off, agricultural run-off, acid mine drainage, iron and steel production, land fill, and the petroleum industry are the principal sources of metal pollution in the aquatic environment (Marcotullio, 2007; Kibria et al., 2010a). A number of pollution studies in coastal and marine waters were carried out in Bangladesh including metals in ship-breaking areas (Islam and Hossain, 1986; DNV, 2001; Siddiquee, 2004; Hossain and Islam, 2006; Metai and Hossain, 2007; Hoq et al., 2011; Hossain, 2010; Hossain and Rahman, 2010; Shameem, 2012), oil and grease, heavy metals and nutrient (Shab Uddin, 2010); PCBs (Hossain, 2002); oil (Khan, 1994), and pesticide (Khan and Talukder, 1993). Mahmood et al. (1994) and Hossain (2004) reported accumulation of mercury in marine shrimp (Penaeus monodon, Penaeus indicus, Metapenaeus monoceros) and marine fish (Tenualosa ilisha, Coilia dussumerii, Johnius belangerii and Pampus chinensis). Khan and Talukder (1993) and Islam et al. (2006) assessed the effects of pesticide (DDT) on mudskipper, Apocryptes bato. According

⁎ Corresponding author. E-mail address: [email protected] (G. Kibria).

to Rahman (2010), the construction of flood control and irrigation projects (dams on rivers) in Bangladesh have caused significant impacts on recruitment of anadromous hilsa, T. ilisha — the most important commercial fish of Bangladesh. In general, pollution from domestic, industrial, agrochemicals and oil are major threats to water quality of marine and coastal area of Bangladesh (UNEP, 1986). Contamination of aquatic systems with metals through discharges from mining, industrial and agricultural activities may render water unsuitable for aquatic biodiversity or supporting marine aquaculture. Metal pollution may affect ecosystem biodiversity, eliminate sensitive native species or reduce species abundance through reproductive impairment and increased incidence of diseases (Wu et al., 2007; Kibria et al., 2012). Invertebrates and fish can biomagnify metals to million times higher than the ambient environment, thereby posing risks to human seafood consumption (Luoma and Rainbow, 2008; Kibria et al., 2010a; Kibria et al., 2013). Consumption of water or seafood (fish, shrimp, and oysters) contaminated with high levels of heavy metals (e.g., mercury, lead, and cadmium) can lead to cancer or damage to the central nervous system and kidney (WHO, 1996). The typically high temporal and spatial variabilities of metals in the aquatic environment make it necessary to take water samples frequently in order to provide a statistical valid estimate and the efforts and analytical cost required often form a major obstacle for comprehensive metal pollution studies over large areas, especially in Bangladesh. The ‘Artificial mussel’ (AM) technology developed recently has been shown to provide a cost effective tool for heavy metal monitoring

http://dx.doi.org/10.1016/j.marpolbul.2016.02.021 0025-326X/© 2016 Elsevier Ltd. All rights reserved.

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

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G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

Table 1 Description of trace metal monitoring sites in estuary and coastal area of the Bay of Bengal, Bangladesh during 2013. Name of the sampling sites

Sources of pollution

GPS

Salinity variations

Site 1. Near the Madunaghat Bridge, Halda Location: Halda River (Fig. 1) Site 2. Near Kalurghat Bridge, Kalurghat Location: Karnafuli River Estuary, less impacted site (Fig. 1) Site 3. Mouth of the Chaktai Canal, Chaktai Location: Karnafuli River Estuary (Fig. 1)

Agricultural farming (rice); paper mills (Asian paper mill), dyeing industries; textile mills upstream

N 22° 25.9966̕ E 91° 52.344̕

Fresh water

Kalurghat industrial area is situated about 4 km downstream; Karnafuli Paper Mill (Kaptai) is situated upstream of this site One of the main discharge points of domestic, city and industrial wastes of Chittagong (tanneries, textile, steel industries; fish & shrimp processing plants) One of the main discharge points of domestic and industrial wastes (dyeing, tanneries, textile, and steel industries, 150–160 small engineering workshops; fish & shrimp processing plants) Oil refineries, cement clinkers, export processing zone, various other industries are situated upstream of this site, lighter ship docking place Oil refiners, fertiliser factories, dry dock, metal industries

N 22° 23.845 E 91⁰ 53.218̕ N 22° 19.645̕ E 91° 50.814̕

Estuarine

Site 4. Sadarghat Location: Karnafuli River Estuary (Fig. 1) Site 5. Near 15 no jetty Location: Karnafuli River Estuary (Fig. 1) Site 6. Mouth of the Karnafuli River Estuary Patenga, Coastline Location: Karnafuli river estuary (Fig. 1) Site 7. Khejurtolighat Location: Chittagong Coastline, Uttarkattoli (Fig. 1) Site 8. Salimpur Location: Chittagong Coastline, Fauzdarhat (Fig. 1)

One of the main discharge points of domestic and industrial wastes (dyeing, textile, tanneries) Ship-breaking area with several industries.

in freshwater, estuarine and marine environments, and is also able to provide a time-integrated estimate for comparison over large geographic areas (see Wu et al., 2007; Leung et al., 2008; Degger et al., 2011; Gonzalez-Rey et al., 2011; Kibria et al., 2010b; Kibria et al., 2012; Claassens et al., 2016). For the first time, this study used AM technology to assess threats and risks posed by trace metals to various beneficial water uses including water quality, biodiversity and

Estuarine

N 22° 19.425̕ E 91° 49.878̕

Estuarine

N 22° 14.486̕ E 91° 49.272̕

Estuarine

N 22° 13.630̕ E 91° 48.094̕ N 22° 21.451̕ E 91° 44.994̕ N 22° 23.873̕ E 91° 44.605̕

Coastal Coastal Coastal

human health in Bangladesh. The objectives of the current study were to: • Use “artificial mussels” (AMs) for determining the temporal and spatial variation of eleven metals (Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Zn, and U) in the estuary and coastal area of Chittagong, Bangladesh.

Fig. 1. Location of trace metal monitoring/sampling sites in the Karnafuli river estuary and adjacent coastal area of Bay of Bengal, Bangladesh (St-1: near Madunaghat bridge, Halda (H); St2: near Kalurghat bridge, Kalurghat (K); St-3: mouth of the Chaktai canal, Chaktai (CH); St-4: Sadarghat (S); St-5: near 15 no jetty (15no); St-6: mouth of the Karnafuli Estuary, Patenga (P); St-7: Khejurtolighat (KH), Uttarkattoli; St-8: near shipbreaking, Salimpur (SA).

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

Fig. 2. ‘Artificial mussel’ device used in trace/heavy metals monitoring in Bangladesh (Kibria et al., 2012).

• Identify ‘hot spots’ of metal pollution in the estuary and adjacent coastal area of Chittagong, Bangladesh. • To assess the ecological and public health risks of metal contamination.

Eight sampling sites were selected for monitoring of trace metals, covering the estuary (the Karnafuli River estuary) and coastal area of Chittagong, Bay of Bengal, Bangladesh (Fig. 1 and Table 1). These sites were chosen based on a preliminary survey to identify and locate low, medium and highly impacted sites (known to be polluted from agricultural, domestic, and industrial effluents including farming, sewage, landfills, paper mills, dyeing industries, textile mills, oil refineries, fertiliser factories, ship breaking yards; see Table 1). Chittagong is the second largest city, industrial centre and the main sea port of Bangladesh. About 144 industrial units discharge untreated solid wastes and liquid effluents containing, persistent organic and inorganic substances, toxic metallic compounds into the Karnafuli River estuary and surrounding coastal water bodies (BoBLME, 2011). The artificial mussel (AM) (an innovative continuous pollution monitoring passive sampling device; Fig. 2) was used to sample and monitor trace/heavy metals in waterways of Bangladesh following Wu et al. (2007); Kibria et al. (2012). The merits of using AM compared to bio-monitors and spot/grab sampling for trace metals/heavy metals are given in Kibria et al., 2010a, 2010b. Field deployment of AM include placing of AM (three replicate AMs per site) in a plastic basket (with 10 mm opening for exchange of water) and retrieval at the end of four week interval. The experiments/research ran for six months (six deployment; June–December 2013). Different

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deployment procedures were undertaken based on location of each monitoring site, suitability of deployment and requirements for maintenance of stringent occupational health safety during field deployment and retrieval of AMs. For example, deployment procedures differed between narrow tidal rivers/estuaries and open coastal sites in Bangladesh as illustrated in Fig. 3a to c. Each batch of AMs deployed in estuary and coastal water of the Bay of Bengal was retrieved at the end of a four week (28 day) interval. After retrieval, the following procedures were followed: the fouling organisms attached on the surface of AMs were washed down and AMs were briefly rinsed with the site water. Each AM was then wrapped within a wet sponge/cotton pad with identification tags included inside each resealable bag before shipment to the Chemistry Laboratory, City University Hong Kong, for analysis (Kibria et al., 2012). The AM samples were analysed following methods described in Wu et al. (2007); Kibria et al. (2012). Water quality comprising temperature, pH, salinity, conductivity, TDS, hardness and dissolved oxygen, was measured during retrieval of AMs at each site (see Table 2). The average rainfall data also collected shows that monitoring (June 2013–December 2013) was carried out during monsoon/wet seasons (June–August), and autumn and late autumn seasons (September–December) (Fig. 4). Highest rainfall in 2013 was recorded during June, July, August and September with a peak in July (598 mm). Rainfall gradually increased from April to July and gradually decreased from July to December. Statistical analysis was performed using IBM SPSS version 19, MINITAB version 14 and Microsoft Excel 2007. Analysis of variance (ANOVA) with post-hoc least significant difference (LSD) test (one way ANOVA) performed at the level of 95% level of significance to detect spatial and temporal variations. Ranking and homogeneity of different sampling sites was determined using the Waller–Duncan homogeneity test. Principal component analysis (PCA) was performed to determine association as well as the differences in the concentration between different zones. The number of significant principal component (PC) was selected on the basis of varimax rotation with Kaiser normalisation with eigenvalue greater than one. The AM deployed in estuary and coastal area of the Bay of Bengal, Bangladesh (Table 1) accumulated all the eleven targeted metals including cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), uranium (U), and Zinc (Zn). Out of these eleven metals, seven metals (Cd, Co, Cr, Cu, Ni, Pb, Zn) were frequently detected at all the sites, both spatially (Fig. 5) and temporally (Fig. 6). The order of accumulation of metals (mean of all sites and all seasons) in the AMs was as follows:

FeNMnNZnNCuNHgNNiNPbNCdNCrNCoNU

Fig. 3. a — AM deployment by floating bamboo poles: AM deployed in a narrow river/estuary (site 1) in Bangladesh by using bamboo poles (as a float) and anchoring from the shore of the river and hanging down the basket at a desired point from the floating bamboo pole and operating from the shore. The deployed AM basket was always kept 1 m below the depth of low tide level. b — AM deployment by stacked bamboo poles: AM deployed in a wide tidal river/estuary in Bangladesh (sites 2, 3, 4, 5) by fixing strong bamboo poles/wooden logs into sediments at a desired location or attaching to a fishers operated behundi net (set bag net). The deployed AM basket was always kept 1 m below the depth of low tide level. c — AM deployment by using buoys: AM deployed in coastal sites in Bangladesh (sites 6, 7, 8) by anchoring onto floating buoys and passing a strong nylon rope in between. The deployed AM basket was always kept 1 m below the depth of low tide level.

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

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G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

Fig. 3 (continued).

Spatial (Fig. 5) and temporal (Fig. 6) variations in Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni Pb, Zn, U concentrations were found. Cd was detected in all the sampling sites with highest concentrations detected at two sites: site: 07 Khejurtolighat and site 08: Salimpur (Fig. 5). During July–August, highest Cd concentrations were detected, which were significantly higher than August–September, September–October, October–November, November–December sampling periods (Fig. 6). Co was detected in all the sampling sites with highest concentrations detected at one site: site: 04 Sadarghat (Fig. 5). During June–July, significantly highest Co concentrations were detected which were significantly higher during July–August, August–September sampling periods (Fig. 6). Cr was detected in all the sampling sites with highest concentrations detected at one site: site 7 Khejurtolighat (Fig. 5). During August–September, highest Cr concentrations were detected which were not significantly different from other sampling periods (Fig. 6). Cu was detected in all the sampling sites with highest concentrations detected at one site: site: 04 Sadarghat (Fig. 5). During July–August, highest Cu concentrations detected which were not significantly different from other sampling periods (Fig. 6). Fe was detected in all the sampling sites with highest concentrations detected at two sites: site 3 Chakti and site 4 Sadarghat (Fig. 5). During August–September, highest Fe concentrations detected which were not significantly different from other sampling periods (Fig. 6). Hg was detected in all the sampling sites except site 2 (where it was below the detection limits) with highest concentrations detected at two sites: site7 Khejurtolighat and site 1 Halda (Fig. 5). During November–December, highest concentrations of Hg were detected which were significantly higher compared to June–July, July–August, August–September sampling periods (Fig. 6). Mn was detected in all the sampling sites with highest concentrations detected at two sites: site4 Sadarghat and site 3 Chakti (Fig. 5). During June–July highest concentrations of Mn were detected which were not significantly different from the rest of the sampling periods (Fig. 6). Ni was detected in all the sampling sites with highest concentrations detected at site 1 Halda (Fig. 5). During June–July period lower concentrations of Ni were detected which were significantly different from the rest of the sampling periods (Fig. 6). Pb was detected in all the sampling sites with highest concentrations detected at site7 Khejurtolighat followed by site 1 Halda (Fig. 5). During November–December period highest concentrations of Pb were detected which were not significantly different from August–September, September–October, October–November periods but were significantly higher from July–August period (Fig. 6). U was not detected in all the sampling sites, with highest concentrations detected at two sites: site6 Patenga and site 8: Salimpur (Fig. 5). At sites 3 and 4 the concentrations detected were below the detection limits. U was only detected during June–July period but was below the detection limits in other sampling periods (Fig. 6). Zn was detected in all the sampling sites with highest concentrations detected at site7 Khejurtolighat (Fig. 5). During October–November period highest concentrations of Zn were detected which were significantly higher than June–July period (Fig. 6).

A number of ‘metal pollution hotspots’ have been identified (Table 3) based on the following facts: a. sites where metal concentrations were significantly higher (statistically significant) and b. sites where elevated concentrations of metals were detected compared to other sites. Based on metal pollution monitoring in Bangladesh and detection of highly toxic, bio-accumulative, endocrine disrupting or carcinogenic metals, we categorised monitoring sites into most hazardous, medium hazardous and least hazardous, as listed below: • Most hazardous sites (sites where highly toxic, bio-accumulative, endocrine disrupting and carcinogenic metals were detected at elevated concentrations): Site 1 Halda (Hgt,b,e, Pbt,b,e,c, Nit,c); Site 7 Khejurtolighat (Cdt,b,e,c, Crc, Hgt,b,e, Zne,t), Site 4 Sadarghat (Co, Cut, Fe, Mn), Site 8 Salimpur (Cdt,b,e,c, U), and Site 6 Patenga (U) (note: superscripts t = toxic metals; b = bio-accumulative metals; e = endocrine disrupting metals; c = carcinogenic metals) • Moderately hazardous sites (pollution “hot spots” where comparatively less toxic metals were detected at elevated concentrations but no carcinogenic or endocrine disrupting metals were detected): Site 3 Chaktai (Fe, Mn) • Least hazardous sites (sites where elevated metals were not detected): Site 4 15 no jetty and Site 02- Kalurghat

Principal component analysis (PCA) was performed to establish factors that contribute towards the metal pollution composition, concentration and metal pollution sources and distribution. The number of significant principal components (PCs) was selected on the basis of varimax rotation with Kaiser normalisation with eigenvalues greater than 1. Eigenvalues for the first function (PC-1) indicated 41.73% of the total variance is highly loaded by Cd, Co, Hg, Ni, Pb (Table 4) and originated from untreated industrial and domestic wastes; eigenvalues for the second function (PC-2) indicated 21.52% of the total variance loaded by Cr, Cu, Zn (Table 4) and originated from industrial and agricultural sources and eigenvalues for the third function (PC-3) indicated 19.55% of the total variance loaded by Fe and Mn (Table 4) and originated from industrial waste water, coastal activities and natural sources. For the first time, this study used ‘artificial mussels’ (AMs) to identify and unravel metal pollution in estuary and coastal waters of the Bay of Bengal, Bangladesh. The study detected eleven metals, some of which are hazardous (toxic, bio-accumulative, endocrine disrupting and carcinogenic) (see above). AM has been successfully used in Hong Kong, UK, South Africa, Portugal, Australia, for pollution monitoring or risk assessment or identifying ‘hot spots’ (see Table 5). Results of these studies demonstrated that AM can serve as a reliable and cost effective tool for monitoring trace metal pollution in fresh, brackish, and marine waters. Metals accumulated in the AMs provide an indication of the levels of labile-metal species (the most toxic and dissolved fractions that are bioavailable to aquatic organisms) in the water over the deployment period (Wu et al., 2007; Kibria et al., 2012). In order to convert AM

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

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Fig. 3 (continued).

Fig 4. Average rainfall in Chittagong during 2013 (www.weather-and-climate.com).

chelex resin concentrations into time weighted average water concentrations for the period of AM deployment, calibration (or uptake) factors for each metal are required for comparison with the water quality

guideline values for beneficial water uses. These are not currently available (Kibria et al., 2012). The research study conducted using AM technology generated some new knowledge and information for Bangladesh including the following: (a) successfully deployed and retrieved AM devices as a standard and cost-effective metal pollution monitoring tool in waterways of Bangladesh (river, estuary and coastal area) (Fig. 3a–c; (b) detected eleven metals: Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, U, Zn (Figs. 5, 6; Table 3), some of which are known to be highly toxic to biota such as fish, shrimps/prawn, amphibians and mammals (Cd, Cu, Hg, Ni, Pb, U, Zn) (Kibria et al., 2010a); bio-accumulative (Cd, Hg, Pb) (Kibria et al., 2010a); endocrine disrupting (Cd, Hg, Pb, Zn) (Kibria et al., 2010a); and carcinogenic (Cd, Cr, Ni, Pb) (IARC, 2006; Kibria et al., 2010a); (c) documented spatial and temporal variations in metal concentrations during the period of investigation (June–December 2013 including

Fig. 5. Spatial patterns of metal uptake (mean ± se) in AMs from eight sampling sites in Bangladesh (mean of six months): Site 1: Halda; Site 2: Kalurghat; Site 3: Chaktai; Site 4: Sadarghat; Site 5: 15 no jetty; Site 6: Patenga; Site 7: Khejurtolighat; Site 8: Salimpur. Bars with the common/same letter are statistically indifferent (1-way ANOVA and LSD test). Post-hoc test was not performed for U because at least one group has fewer than two cases. LSD performed in 95% of confidence level; BDL = below the detection limit. Explanation: ab: Bars denoted by ab are significantly indifferent from both bars denoted by a and b; a: Bars denoted by a are significantly different from b but significantly indifferent from ab; b: Bars denoted by b are significantly different from a but significantly indifferent from ab.

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

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G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

Fig. 6. Temporal patterns of metal uptake (mean ± se) in AMs during six sampling periods in Bangladesh. Bars with the same letter are significantly indifferent and bars with different letters are significantly different (1-way ANOVA and LSD test). Post-hoc test was not performed for U because at least one group has fewer than two cases. BDL = below the detection limit. LSD performed in 95% of confidence level; Explanation: ab: Bars denoted by ab are significantly indifferent from both bars denoted by a and b; a: Bars denoted by a are significantly different from b but significantly indifferent from ab; b: Bars denoted by b are significantly different from a but significantly indifferent from ab.

Table 2 Site specific average water quality data of eight sampling sites in Chittagong, Bangladesh during 2013 sampling periods. Water quality data were collected during retrieval of AMs. Sampling sites

Water temp. (°C)

Water pH

Salinity (ppt)

Conductivity (m/s)

TDS (g/L)

Hardness (mg/L)

Dissolved oxygen (mg/L)

Site 1 Halda Site 2 Kalurghat Site 3 Chaktai Site 4 Sadarghat Site 5 15 no jetty Site 6 Patenga Site 7 Khejurtolighat Site 8 Salimpur

28.6 28.0 28.4 28.7 29.4 29.6 29.4 29.2

7.7 7.5 6.9 7.0 7.22 7.3 7.1 7.2

0.3 0.4 0.74 1.32 5.96 6.4 11.49 11.71

0.77 0.77 1.59 3.39 10.00 10.70 18.33 18.18

0.50 0.34 1.02 1.56 6.70 7.00 12.47 12.33

99.16 71.25 73 186.7 435 615.75 701.8 657.5

6.64 6.4 0.12 2.6 5.9 5.01 3.5 4.99

rainy/monsoon (June–August), autumn (August–October), and late Autumn (October–December) (Figs. 5, 6); (d) identified metal pollution “hot spots” in waterways of Bangladesh (Table 3); (e) categorised

pollution monitoring sites into most, moderately and least hazardous sites; and (f) identified possible metal pollution composition, and sources in the studied areas (Tables 1, 4).

Table 3 Metal pollution ‘hot spots’ identified in river, estuary and coastal area of Bay of Bengal, Bangladesh (Chittagong), during 2013. Pollution

‘Hot spots’ with description of pollution discharges from the site

Cd Co Cr Cu Fe

• • • • • • • • • • • • • • • •

Hg Mn Ni Pb U Zn

Site 7 Khejurtolighat (receive effluents from dyeing, textile, tanneries), Site 8- Salimpur (receive effluents from ship breaking activities). Site 4 Sadarghat (receive effluents from domestic and industrial wastes including dyeing, tanneries, textile and steel industries) Site 7 Khejurtolighat (receive effluents from dyeing, textile, tanneries). Site 4 Sadarghat (receive effluents from domestic and industrial wastes including dyeing, tanneries, textile and steel industries). Site 3 Chaktai (receive effluents from domestic, city and industries including tanneries, textile, steel industries; fish & shrimp processing plants). Site 4 Sadarghat (receive effluents from domestic and industrial wastes including dyeing, tanneries, textile and steel industries). Site 7 Khejurtolighat (receive effluents from dyeing, textile, tanneries). Site 1 Halda- (Agricultural farming, paper mills, dyeing industries, textile mills). Site 4 Sadarghat (receive effluents from domestic and industrial wastes including dyeing, tanneries, textile and steel industries). Site 3 Chaktai (receive effluents from domestic, city and industries including tanneries, textile, steel industries; fish & shrimp processing plants). Site 1 Halda- (Agricultural farming, paper mills, dyeing industries, textile mills). Site 7 Khejurtolighat (receive effluents from dyeing, textile, tanneries). Site 1 Halda- (Agricultural farming, paper mills, dyeing industries, textile mills). Site 8 Salimpur (receive effluents from ship breaking activities). Site 6 Patenga (receive effluents from oil refineries, fertiliser factories, dry dock, metal industries Site 7 Khejurtolighat (receive effluents from dyeing, textile, tanneries).

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx Table 4 Principle component (PC) analysis showing contribution of statistically dominant variables measured from river, estuary and coastal area of the Bay of Bengal, Bangladesh (Chittagong) during 2013. Variable

PC-1

PC-2

PC-3

Cd (cadmium) Cr (chromium) Co (cobalt) Cu (copper) Fe (iron) Hg (mercury) Mn (manganese) Ni (nickel) Pb (lead) Zn (zinc) Eigenvalue % of total variance Cumulative

0.889 −0.270 0.825 −0.288 −0.080 0.846 −0.001 0.776 0.886 0.195 4.173 41.728 41.728

−0.143 0.853 −0.109 0.894 −0.018 −0.237 −0.025 0.167 −0.123 0.795 2.152 21.522 63.251

0.048 −0.165 0.055 0.237 0.979 −0.295 0.985 0.131 −0.299 −0.063 1.955 19.553 82.803

Extraction method: principal component analysis; rotation method: varimax with Kaiser normalisation and rotation converged in 5 iterations. Data shown in bold font are the main contribution elements to the component.

Human activities such as mining and industries, and sewage discharges, electronic wastes and agriculture run-off are common anthropogenic sources contributing to the elevated levels of trace metals in aquatic environment (Kibria et al., 2010a). The detection of hazardous metals (Cd, Co, Cr, Cu, Hg, Fe, Mn, Ni, Pb, U, and Zn) and identification of metal pollution “hot spots” may indicate that water quality in the Karnafuli river estuary and adjacent coastal area of the Bay of Bengal, Bangladesh may have been impaired. It may indicate that metal pollution could be a threat to beneficial water uses including seafood, fish farming/aquaculture, aquatic biodiversity and livelihoods of people associated with estuarine and coastal ecosystems. Cd, Cr, Cu, Hg, Zn are toxic to fish and can damage vital organs (gills, kidney, brain) of fish (Cardeilhac and Whitaker, 1988; ANZECC and ARMCANZ, 2000; Hossain and Islam, 2006; Kibria et al., 2010a). In addition, Cd, Hg and Pb can bioaccumulate in mussels, oysters, shrimps, lobsters and fish and can be transferred to humans via the food chain pathway such as from consumption of metal-contaminated seafood (ANZECC and ARMCANZ, 2000; Kibria et al., 2010a). Furthermore, Cd, Pb, Ni are carcinogenic to humans (NHMRC and NRMCC, 2011). It is expected that uptake and toxicity of common pollutants (metals) in aquatic organisms (e.g. marine organisms such as fish, invertebrates) may be enhanced with increasing temperatures/global warming (Kibria et al., 2013). At higher

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temperatures, the metabolism of aquatic organisms is increased and oxygen concentration is reduced in water and therefore, the rate of water inflow into the animal can increase to extract more oxygen, which can increase the entrance of dissolved chemical pollutant(s) into the body (Kennedy and Walsh, 1997; Marques et al., 2010; Anawar, 2013). Temperature related increases in the uptake, bioaccumulation and toxicity of metals (arsenic, copper, cobalt, cadmium and lead) have been reported in several marine organisms, including crustaceans, echinoderms and molluscs (Hutchins et al., 1996; Khan et al., 2006; Wang et al., 2005; Mubiana and Blust, 2007; Kibria et al., 2013). This study showed that AM can provide time integrated estimates for the 11 trace metals in river, estuarine and marine environments and serve as an effective tool for monitoring of trace/heavy metal pollution in Bangladesh. Amongst these Cd, Co, Cu, Hg, Pb, U are known to be highly toxic, bio-accumulative, endocrine disrupting and carcinogenic and “hot spots” of these metals have been identified in waterways of Bangladesh and may pose a risk to environmental water quality, aquatic biodiversity, seafood security, and human health. The results may demonstrate that the Karnafuli River-estuary and adjacent coastal area of the Bay of Bengal, Bangladesh are highly polluted by hazardous metals. Agricultural and untreated domestic, industrial and city wastes directly discharged into the waterways have been identified as the main causes of metal pollution in Bangladesh. The identified pollution “hot spots” possess significant ecological values since these waterways support commercial fisheries, recreational activities, natural breeding and nursing grounds of native fish, prawn/shrimp and other ecosystem goods and services including rural livelihoods. As a consequence of metal pollution, the growth, survival and reproduction of aquatic species may be impaired (e.g. fish, prawn, shrimp and amphibians), sensitive native species may be eliminated or reduced, food contamination/food poisoning (e.g. seafood, crops, vegetables) may be enhanced (due to bioaccumulation and bio-magnification of some toxic metals), seafood may be rejected (due to higher contamination with mercury, cadmium and lead) and human health may be at risk to diseases (e.g. cancer or kidney failure or metal poisoning diseases due to elevated exposure of metals via food and water). Livelihoods of people associated with fishing, aquaculture, and seafood export business may be affected due to pollution, deterioration of water quality and contamination of food with metals. There is a possibility that aquatic organisms such as fish would move away from the highly polluted estuaries and coasts of the Bay of Bengal, Bangladesh to a suitable environment (maybe outside Bangladesh territory) thus would impact on

Table 5 AM device used in various countries for pollution monitoring. Authors

Country

Environment

Metals detected

Main findings related to pollution monitoring by AM

Wu et al. (2007)

Hong Kong

Marine

Cd, Cr, Cu, Pb, Zn

Leung et al. (2008)

Scotland, UK

Marine

Cd, Cr, Cu, Pb, Zn

Degger et al. (2011)

South Africa

Marine

Cd, Cr, Cu, Pb, Zn

Gonzalez-Rey et al. (2011) Kibria et al. (2012)

Portugal

Marine

Cd, Cr, Cu, Pb, Zn

AMs provided a time-integrated estimate on spatial and temporal patterns of metal concentrations; AMs were able to accumulate the labile fractions of metals. AMs were successfully used in monitoring metal levels in marine environments; AMs accumulated dissolved fractions of metals. AMs were successfully used in monitoring metal levels in marine environments; AMs provided relevant and complementary information on dissolved metal concentrations. AMs were found to be a useful tool for environmental quality assessment.

Australia

Freshwater creeks, rivers, irrigation channels and drains

Cd, Cu, Hg, Pb, Zn

Claassens et al. (2016) Present study

South Africa

Freshwater

Bangladesh

River, estuary and coastal area

Successfully deployed and retrieved AMs in rivers, creeks, channels and drains; AMs facilitated a time-integrated monitoring of metal pollution; AMs helped in assessing climate variability (dry vs wet years) impacts on pollution loading and identifying pollution ‘hot spots’. As, Cd, Cr, Co, Cu, Pb, Successfully deployed and retrieved AMs in freshwater; AM identified metal Mn, Ni, Se, U, V, Zn pollution ‘hot spots’ in mining areas. Cd, Co, Cr, Cu, Fe, Hg, Successfully deployed and retrieved AMs in river, estuary and coastal areas; AMs Mn, Ni, Pb, U, Zn provided a time-integrated estimate on spatial and temporal patterns of metal pollution concentrations; AMs helped to identify metal polluting ‘hot spots’; AMs facilitated categorising sites into most, moderately and least hazardous pollution sites; AMs facilitated assessing possible risks of metal pollution to various sectors including seafood, fish farming/aquaculture, aquatic life/species, livelihoods of people and human health.

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

8

Metals

1

2

3

4

5

6

7

8

Irrigation

Livestock drinking

Recycled water

Aquaculture (freshwater & marine)

Sediment

Aquatic life/aquatic ecosystems protection (freshwater & marine) (95% or 99% species protection)

Human health (drinking water)

Human health (seafood)

Cd

0.01–0.05 mg/L

(0.01 mg/L

0.002 mg/L

0.002 mg/L

2.0 mg/kg for abalone, scallops, oyster

Co

0.2–1.0 mg/L

1 mg/L

NA

(b0.2–1.8 μg/L (freshwater); (b0.5–5 μg/L (marine) NA

Cr

0.1–1 mg/L

1 mg/L

0.05 mg/L

Cu

0.2–5 mg/L

Fe Hg

0.2–10 mg/ 0.002 mg/L

0.4 mg/L for sheep, 1 mg/L for cattle, 5 mg/L for pigs and poultry NA 0.002 mg/L

Mn

0.2–10 mg/L

Ni Pb

1.5–10 mg/kg dw

0.2 μg/L

NA

1.4 μg/L (freshwater); 0.005 μg/L (marine) (Nagpal, 2004) 0.01 μg/L (freshwater; 0.14 μg/L (marine) (99% protection) 1.4 μg/L (freshwater); 1.3 μg/L (marine) (95% protection)

NA

NA

0.05 mg/L

No limit

2 mg/L

5 mg/kg (molluscs), 10 mg/kg (crustacean), 0.5 mg/kg (fish)

NA 0.06 μg/L (Freshwater); 0.1 μg/L (marine) (99% protection) 1200 μg/L (freshwater-99% protection): marine (NA) 8 μg/L (freshwater); 7 μg/L (marine) (99% protection) 3.4 μg/L (freshwater); 4.4 μg/L (marine) (95% protection)

b0.3 mg/L 0.001 mg/L

0.5 mg/L

NA 0.5 mg/kg (abalone, crab, prawn, scallops, oysters); 1.0 mg/kg (tuna, sword fish, snapper) NA

0.02 mg/L

NA

2 mg/L

b20 μg/L (freshwater); b20 μg/L (marine) b5 μg/L (freshwater & marine)

65–270 mg/kg dw

NA 0.001 mg/L

b10 μg/L (freshwater & marine) 1 μg/L (freshwater); 1 μg/L (marine)

NA 0.15–1 mg/kg dw

NA

NA

NA

0.2–2 mg/L

1 mg/L

0.02 mg/L

2–5 mg/L

0.1 mg/L

NA

b10 μg/L (freshwater); b10 μg/L (marine) b100 μg/L (freshwater); b100 μg/L (marine) 1-7 μg/L (freshwater & marine)

Zn

2–5 mg/L

0.1 mg/L

U

0.01–0.1 mg/L

0.2 mg/L

3 mg/L

b5 μg/L (freshwater); b5 μg/L (marine) NA

80–370 mg/kg dw

21–52 mg/kg dw 50–200 mg/kg dw

0.01 mg/L

2 mg/kg (abalone, scallops, oysters; 0.5 mg/kg (eel, snapper, swordfish, tuna, whiting, mackerel, blue grenadier) 5 mg/kg for fish; 25 mg/kg for crustacean; 130 mg/kg for oysters NA

200–410 mg/kg dw

2.4 μg/L (freshwater; 7.0 μg/L (marine)

0.1 mg/L

NA

15 μg/L (short term exposure); 33 μg/L long term exposure) (freshwater); marine (NA) (CEQG, 2011).

0.017 mg/L

G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

Please cite this article as: Kibria, G., et al., Trace/heavy metal pollution monitoring in estuary and coastal area of Bay of Bengal, Bangladesh and implicated impacts, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.02.021

Table 6 Water, sediments and food quality guidelines threshold values for trace/heavy metals for beneficial water uses. [1, 2, 4, 5, 6 = based on ANZECC and ARMCANZ, 2000; 3 = based on NWQMS, 2007; 7 = based on NHMRC and NRMMC, 2011; 8 = based on Food Standards Australia, 2001; NRS, 2012] dw = dry weight; NA = not available.

G. Kibria et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

local seafood catch. There is a need for a regular monitoring to ascertain that local water quality with respect to metal levels are within the recommended guideline threshold values (Table 6) to safeguard human and environmental health or protection of aquatic biodiversity and ecosystems.

Acknowledgements The work described in the paper was partly supported by a grant from the University Grants Committee of the Hong Kong Special Administrative Region, China (AoE/P-04/04 (AM supply and analysis, shipment of AM to and from Hong Kong). The rest of the field components including (deployment/retrieval, field and other incidental costs, etc) were supported by the Food and Agriculture Organisation of the United nations (FAO)/ Bay of Bengal Large Marine Ecosystems (BoBLME) Project supported project (FAOBGDLOA-0312014-031). We sincerely acknowledge the personal and professional efforts of Prof. T. C. Lau and Post-Doc Researcher Dr. Ruwei Wang at City University of Hong Kong whose painstaking analysis of all the AM samples made it possible to produce this paper. Special acknowledgement to Dr. Chris O'Brien, Regional Coordinator, Dr. Rudolf Hermes and Mr. C. L. Andreasson of BoBLME for their support and valuable inputs throughout the program. We are grateful to anonymous reviewers whose valuable comments helped to improve the paper.

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