Heavy metal contamination along the China coastline: A comprehensive study using Artificial Mussels and native mussels

Heavy metal contamination along the China coastline: A comprehensive study using Artificial Mussels and native mussels

Journal of Environmental Management 180 (2016) 238e246 Contents lists available at ScienceDirect Journal of Environmental Management journal homepag...

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Journal of Environmental Management 180 (2016) 238e246

Contents lists available at ScienceDirect

Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman

Research article

Heavy metal contamination along the China coastline: A comprehensive study using Artificial Mussels and native mussels Natalie Degger a, Jill M.Y. Chiu b, c, *, Beverly H.K. Po b, a, Anna C.K. Tse a, Gene J. Zheng b, Dong-Mei Zhao d, Di Xu e, Yu-Shan Cheng f, Xin-Hong Wang g, Wen-Hua Liu h, T.C. Lau i, c, Rudolf S.S. Wu j, c, ** a

School of Biological Sciences, The University of Hong Kong, Hong Kong, China Department of Biology, Hong Kong Baptist University, Hong Kong, China State Key Laboratory in Marine Pollution, Hong Kong, China d National Marine Environmental Monitoring Center, State Oceanic Administration, Liaoning, China e College of Marine Life Science, Ocean University of China, Qingdao, China f City University of Hong Kong Shenzhen Research Institute, Shenzhen, China g State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China h Marine Biology Institute, Shantou University, Shantou, China i Department of Biology and Chemistry, City University of Hong Kong, Hong Kong, China j Department of Science and Environmental Studies, Hong Kong Education University, Hong Kong, China b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 28 January 2016 Received in revised form 29 April 2016 Accepted 4 May 2016

A comprehensive study was carried out to assess metal contamination in five cities spanning from temperate to tropical environment along the coastal line of China with different hydrographical conditions. At each of the five cities, Artificial Mussels (AM) were deployed together with a native species of mussel at a control site and a polluted site. High levels of Cr, Cu and Hg were found in Qingdao, high level of Cd, Hg and Pb was found in Shanghai, and high level of Zn was found in Dalian. Furthermore, level of Cu contamination in all the five cities was consistently much higher than those reported in similar studies in other countries (e.g., Australia, Portugal, Scotland, Iceland, Korea, South Africa and Bangladesh). Levels of individual metal species in the AM showed a highly significant correlation with that in the native mussels (except for Zn in Mytilus edulis and Cd in Perna viridis), while no significant difference can be found between the regression relationships of metal in the AM and each of the two native mussel species. The results demonstrated that AM can provide a reliable time-integrated estimate of metal concentration in contrasting environments over large biogeographic areas and different hydrographic conditions, and overcome the shortcomings of monitoring metals in water, sediment and the use of biomonitors. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Heavy metal China coastline Live mussels Artificial Mussels Aquatic system health

1. Introduction Traditional monitoring of heavy metals in the aquatic environment involves determining metal concentrations in water or sediment, but both methods present their own problems and

* Corresponding author. Department of Biology, Hong Kong Baptist University, Hong Kong, China. ** Corresponding author. Department of Science and Environmental Studies, Hong Kong Education University, Hong Kong, China. E-mail addresses: [email protected] (J.M.Y. Chiu), [email protected] (R.S.S. Wu). http://dx.doi.org/10.1016/j.jenvman.2016.05.008 0301-4797/© 2016 Elsevier Ltd. All rights reserved.

limitations. The concentration of metals in water is typically low with large temporal fluctuations. Frequent sampling is therefore required to provide a representative estimate, while chemical analysis of a large number of samples may not be cost effective (Philips and Rainbow, 1993; Rainbow, 1995). Metal concentrations in sediment provides a time-integrated estimate of metal levels, but are significantly affected by particle size, organic content and redox conditions, which cannot be standardized (Philips and Rainbow, 1993). Due to their remarkable ability to concentrate metals from the ambient environment, biomonitors (especially mussels and barnacles), have been commonly employed to monitor and compare temporal and spatial changes of heavy metals in

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aquatic environments since the 1970’s (Kennish, 1997; Rodriguez and Thebault, 2007), and this is exemplified by the global “mussel watch” program (Goldberg, 1975; Goldberg et al., 1978; Kimbrough et al., 2008). However, metal accumulation in biomonitors is not only species specific, but also significantly affected by physical and biological factors as well as pollution levels (Leung et al., 2001, 2002; Philips and Rainbow, 1993; Wu et al., 2005). This presents great difficulties in comparing biomonitors under different hydrographic conditions and seasons. Moreover, the limited natural distributions of species often prevent making comparison over large geographic areas. To overcome the above limitations in metal monitoring, a passive sampling device known as the Artificial Mussel (AM), was developed (Wu et al., 2007). Results of laboratory studies demonstrated that the AM can uptake and release Cd, Cr, Cu, Pb, Zn and Hg in a concentration-dependent manner, including the bioavailable fraction. Field studies further showed the AM is field robust, and can provide a time-integrated estimate of metal concentrations in the environment, exhibiting a metal profile similar to that of the green-lipped mussel (Perna viridis) at the control site and the polluted site (Wu et al., 2007). Leung et al. (2008) deployed the AM alongside the blue mussel (Mytilus edulis) in Scotland and Iceland, and demonstrated that AMs can provide good indication on the dissolved metal (Cd, Cr, Cu, Hg, Pb, Zn) fractions in the marine environment. Degger et al. (2011) studied the metal accumulation profile of AMs deployed alongside with the brown mussel (Perna perna) in three distinct geographical regimes in South Africa, identifying pollution hot spots and demonstrating the effectiveness and robustness of the AM in metal monitoring over large biogeographical area. Likewise, a field study in Portugal (Gonzalez-Rey et al., 2011) also demonstrated that the AM had similar metal profiles to the Mediterranean mussel (Mytilus galloprovincialis), and concluded that the AMs can be used successfully to monitor metals under different hydrographical regimes. Kibria et al. (2012) employed AMs for monitoring heavy metal in water catchment areas of Australia and identified input and hotspots of metals for risk assessment. Ra et al. (2014) showed significant correlations between accumulation of Cd, Cu and Pb in AMs and mussel (Mytilus edulis) at all study sites in Korea, and concluded that AM provides a better time integrated estimates for dissolved metal concentration. The above studies showed that the AMs can serve as a reliable and robust tool to monitor metals and assess risk in both the marine and freshwater environments. China has one of the longest coast lines (14,500 km) in the world, stretching from Guangxi in the south (18 150 N) to Liaoning (53 300 ) in the north. The rapid industrialisation and urbanisation of China in the last three decades saw an increased load of wastes from the industry and mining tailings to its coastal environments (Pan and Wang, 2012). A number of “hot spots” with high levels of contamination have been identified along the coast of China, including Liaodong Bay, Xiamen Bay, Pearl River Delta and the Yangtze River catchment (Li et al., 2012). In this study, five cities spanning from temperate to tropic environment along the China coast and with different hydrographic conditions, were selected, and at each of the five cities, AM were deployed together with a native species of mussel at a control site and a polluted site. The objectives were to: (a) provide a systematic account and comparison on the levels of metal contaminations along the China coast; and (b) test and compare the performance of AMs with native mussels under contrasting hydrographical conditions and different pollution levels. 2. Materials and methods Five cities along the coastline of China, spanning from temperate

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to tropical (from north to south: Dalian, Qingdao, Shanghai, Shantou and Shenzhen), were selected for the present study (Fig. 1). Dalian has a population of 6 million people and the coastal area has become increasingly threatened by pollution generated from industry, shipyards, fuel, aquaculture and domestic waste, and heavily contaminated by Zn, Pb and Hg (Mao et al., 2009; Zhao et al., 2012). Qingdao is situated in Jiaozhou Bay, a semi-enclosed coastal water body on the east coast of China. Petroleum contamination, untreated industrial and municipal water discharges and run-off form the major anthropogenic sources of heavy metals entering the Bay (Wang et al., 2007), and increased levels of metals such as Cu, Pb and Cr have been found (Wang et al., 2006). With 24 million people, Shanghai is the largest city in China and also one of the largest cities in the world. Numerous industrial enterprises and over 10,000 factories proliferated in the city in the last two decades, making coastal pollution an imminent problem (Cao et al., 2008; Wang et al., 2009), and high levels of Cd, Cr, Ni and Pb have been reported in marine sediments (Yuan et al., 2004; Zhang et al., 2009). A recent study conducted by Qiao et al. (2013) in Shantou Bay revealed elevated concentrations of heavy metals in marine sediment, which have been largely attributed to agricultural practices along the Rongjiang River basin, the introduction of industrial and municipal discharges from the Meixi River from Shantou City. Shenzhen is amongst the fastest developing city in the world in the last 20 years, where industrial and land reclamation occur in an enormous scale and contributed to high heavy metal levels (Pb, Cu and Zn) in Shenzhen Bay (Chen and Jiao, 2008; Huang et al., 2007) resulting in adverse effects on the marine environment (Huang et al., 2007). 2.1. Artificial Mussels and mussels deployment and collection Within each of the above five cities, a reference site remote from pollution sources and urban activities, and a site receiving moderate to heavy pollution loading, were selected for this study (Table 1). At each of these ten sites, 60 AMs secured in a plastic cage were deployed at 0.5e1.0 m below chart datum. Concurrently, over 100 native mussels (i.e. the blue mussel Mytilus edulis for Dalian, Qingdao and Shanghai; and the green-lipped mussel Perna viridis for Shantou and Shenzhen) were collected from a clean site at the respective city. M. edulis (umbo length: 3.5e6 cm) and P. viridis (umbo length: 5.5e8 cm) were acclimated in clean seawater for a month and deployed in a nylon bag alongside the AMs in June 2011. Six AMs and eight native mussels were randomly collected from each site 30 days after deployment for metal analysis. Another six AMs were further collected from each site 90 days after deployment for metal analysis, to provide information on temporal variations of metal concentration. 2.2. Metal analysis All metal analyses were conducted following the protocol described in Wu et al. (2007). Briefly, the contents of each individual AM were emptied into a sintered glass filter followed by eluting two times with 12.5 mL 6 M HNO3 (analytical grade). The elutriant was made up to a known volume with deionized double distilled water and the concentrations of Cd, Cr, Cu, Hg, Pb and Zn were determined, using a Perkin Elmer Optima 2100 DV ICP-AES (Plasma flow: 15 L/min; auxiliary flow: 0.3 L/min; nebulizer flow: 0.8 L/min; RF flow: 1300 W, pump rate: 1.0 mL/min). Metal standard solution (1000 mg/mL in 2% nitric acid) from”High Purity Standards” was used as calibration standards for construction of calibration curves.

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Fig. 1. The five cities along the coastline of China selected for the present study. Map has been adapted from d-maps.

Soft tissue of native mussels were dissected with a plastic knife, rinsed with deionized double distilled water, dried and weighed before acid digestion in a block digestor (Techne DG-1), using 30% hydrogen peroxide and 70% nitric acid (1:1 v/v). Metal concentrations in the soft tissue of the digested samples were determined using ICP-AES as described above. Dried oyster tissue (National Institute of Standards and Technology, US Standard Reference Material 1566a) was used as certified reference material, and the recovery rate was >99%. Concentration of metals in the AM was expressed in terms of mg/ g of Chelex, and concentration of metals in mussels was expressed as mg/g dry tissue weight. 2.3. Statistical analysis All data were first tested for normality and homogeneity of variance using Kolmogrov-Smirnov and Levene’s tests (Zar, 1996). For the AMs, differences in metal concentrations between month 1 and month 3, and also between sites at month 1 and month 3, were tested by a student t-test. Mann-Whitney test was performed on nonparametric data. Correlation between metal levels in the AM and native mussels was analysed using Pearson’s correlation test. All statistical analyses were conducted using the Graph-Pad Prism 5 for Mac OS X (GraphPadSoftware, San Diego, CA), and significant level was set at p < 0.05. Regression relationship between level of metals in the AM and the two species of native mussels were tested by covariance analysis. 3. Results 3.1. Spatial and temporal variations of metal concentration at each city 3.1.1. Dalian (Fig. 2) Except for Hg, levels of all metals in the polluted site (LB) were significantly higher than those at the reference site (HRB). Levels of Cr and Zn were consistently higher in LB in both months, while significant monthly variations in Cd, Cu and Pb were found.

No significant temporal differences could be observed at the reference site (HRB), indicating consistent levels of all the six metals throughout the 3 months study. At the polluted site (LB), significant decrease in Cr associated with an increase in Cu were evident from month 1 to month 3, while no significant change was observable for the other metals. 3.1.2. Qingdao (Fig. 3) Being a heavy industrial area, SFD was expected to be much more contaminated than the reference site (HB). At month 1, Cd and Pb contamination was significantly higher in SFD than that in HB, but such a discrepancy was not observable in month 3. Level of Cr and Cu at SFD were consistently higher than those found in HB in both months. In HB, significant increases in Cr and Cu were found from month 1 to month 3, but no significant change was found for the remaining four metals. In SFD, significant increase in Cu and decrease in Pb were observed from month 1 to month 3, while no temporal changes were observable for the remaining four metals. 3.1.3. Shanghai (Fig. 4) Located at the downstream of the Huangpu River, GHG is heavily polluted by industrial (petrochemical, metallurgy, textiles and paper) and domestic waste discharged from the catchment and Shanghai city (Cao et al., 2008; Zhang, 2007). Significant spatial differences between the control and polluted sites were clearly evident for all six metals. Levels of Cr, Cu and Pb were higher in GHG than in SJ in both months, and levels of Cd and Hg were also higher in GHG than in SJ in month 1. Except Cu and Zn, no significant temporal changes were found in the other four metals in SJ, while significant temporal variations of all six metals were observed from month 1 to month 3 in the polluted site (GHG). Interestingly, three metals (Cd, Hg and Pb) showed a significant decrease while the other three (Cr, Cu and Zn) showed an increase, indicating a change in metal input. 3.1.4. Shantou (Fig. 5) North Harbour (NH) is an industrial site with high level of metal

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Table 1 The ten study sites (and their abbreviations) of the five cities along the Chinese coast selected for the present study. City Dalian

Site (abbreviation), latitude and longitude coordinates

Heishi Reef Bay (HRB) 38 520 29.341200 N, 121 350 46.503600 E Lingshui Bridge (LB) 38 530 9.942000 N, 121 350 38.313600 E Qingdao Huiquan Bay (HB) 36 30 4.449600 N, 120 200 24.270000 E Sifang District (SFD) 36 120 15.454800 N, 120 210 28.231200 E Shanghai Sanhang Ju (SJ) 31 470 44.250000 N, 121 40 36.800400 E Gaoqiao Hua Gong (GHG) 31 190 45.048000 N, 121 330 25.912800 E Shantou Nan’ao County (NC) 23 260 34.317600 N, 117 10 57.788400 E North Harbour (NH) 23 270 15.710400 N, 116 520 22.447200 E Shenzhen Shekou Ferry Port (SFP) 22 280 35.328000 N, 113 540 55.144800 E Xixiang Wharf (XW) 22 330 10.404000 N, 113 510 2.275200 E

Site description

Native mussel species deployed

Reference site, remote from any anthropogenic activities

Mytilus edulis

Near municipal area and heavily polluted by sewage discharges

M. edulis

Reference site, swimming beach with good water quality

M. edulis

Heavy industrial area

M. edulis

Reference site with strong current and far from any anthropogenic activities

M. edulis

Industrial area with chemical pollution

M. edulis

Reference site and remote from anthropogenic activities

Perna viridis

Industrial site with domestic sewage discharge and heavy marine traffic P. viridis

Ferry port, relatively remote from industrial and municipal activities

P. viridis

Highly urbanized area with heavy marine traffic

P. viridis

Fig. 2. Concentration of the six metals in AM in Dalian. Data expressed in mean ± SEM mg/g Chelex. Asterisk (*) denotes significant difference (p < 0.05) between month 3 and month 1 at that site, and “#” denotes significant difference (p < 0.05) between the two sites. HRB, Heishi Reef Bay; LB, Lingshui Bridge.

contamination. As expected, concentrations of Cr, Cu, Pb and Zn in NH were higher than those at the reference site (NC). Surprisingly, level of Hg at NC was significantly higher than that at NH.

None of the metals showed significant difference between months in NC, while in NH, levels of Cd, Cu and Zn in AM were significantly higher in month 3 than in month 1.

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3.1.5. Shenzhen (Fig. 6) Being an urban area with marine traffic, Xixiang Wharf (XW) is expected to be more polluted than the reference site (Shekou Ferry Port, SFP). Due to the large temporal variation, the spatial pattern is different between month 1 and month 3. At month 1, levels of Cd, Cu, Hg and Zn were significantly higher in the polluted site XW. However, the data in month 3 showed the opposite. Levels of Cu and Hg were found to be significantly higher in SFP than in XW. Metal concentrations in SFP showed large temporal variations. Significant decreases were found in Cd and Zn whereas significant increases were found in Cu and Hg from month 1 to month 3. Level of Cd, Cu, Hg and Zn in XW all showed a significant decrease. No significant change was observed for other metals.

3.2. Summary of spatial and temporal variation of metal concentration of the 5 cities 3.2.1. Spatial variations With only a few exceptions, levels of the six metals in AMs deployed at the polluted sites were significantly higher than their respective control site at all the five cities. The difference is particularly pronounced in Dalian and Qingdao, where temporal variations were relatively small. However, exceptions were found in Shanghai (for Zn), Shantou (for Hg) and Shenzhen (for Cu and Hg) in one of the months.

3.2.2. Temporal variations No significant temporal changes were found in the reference sites in Dalian and Shantou, and temporal variations of metal levels in Dalian, Qingdao and Shantou were relatively small. In contrast, significant temporal variations for most of the metals were observed in the polluted site of Shanghai and Shenzhen, with a 10fold change between month 1 and month 3 in some cases.

3.3. Correlation of metal accumulation by Artificial Mussels and native mussels and difference in regression of AM vs M. edulis and AM vs P. viridis Correlations of metal accumulation by AM and the two native mussels are shown in Fig. 7. Except for Hg and Zn, strong, significant correlations were found between all the other five metals in M. edulis and AM (r2 ranged from 0.9732 to 0.9995, p < 0.001). Except for Cd, strong, significant correlations were found between all the other four metals in P. viridis and AM (r2 ranged from 0.8467 to 0.9803, p < 0.01 to 0.001). Correlation coefficient of Hg was not calculated for P. viridis since Hg in most samples was below detection limit (i.e. < 0.02 mg/g). Covariance analysis further showed no significant difference in the regression relationships between all the six metal in AM vs M. edulis and AM vs P. viridis (Cd: F ¼ 0.05, p ¼ 0.83; Cr: F ¼ 1.17, p ¼ 0.31; Cu: F ¼ 4.65, p ¼ 0.06; Pb: F ¼ 4.29, p ¼ 0.07; Zn: F ¼ 0.65, p ¼ 0.32).

4. Discussion 4.1. Comparison of metal concentrations of the 5 polluted sites Levels of metals at the polluted sites of Qingdao (i.e. Sifang District) and Shanghai (i.e. Gaoqiao Hua Gong) were clearly much higher than polluted sites of the other cities in China. Specifically, levels of Cr, Cu and Hg in Qingdao were highest among the five cities along the China coast. In contrast, level of Zn at Qingdao was the lowest amongst the five cities. Levels of Cd, Hg and Pb in Shanghai were the highest of the five cities. Dalian, Shantou and Shenzhen are generally less polluted than Qingdao and Shanghai, although the highest level of Zn was found in Dalian. With the exception of Cd, the spatial trend of metal levels in month 3 is generally similar to that in month 1 in all the five cities.

Fig. 3. Concentration of the six metals in AM in Qingdao. Data expressed in mean ± SEM mg/g Chelex. Asterisk (*) denotes significant difference (p < 0.05) between month 3 and month 1 at that site and “#” denotes significant difference (p < 0.05) between the two sites. HB, Huiquan Bay; SFD, Sifang District.

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Fig. 4. Concentration of the six metals in AM in Shanghai. Data expressed in mean ± SEM mg/g Chelex. Asterisk (*) denotes significant difference (p < 0.05) between month 3 and month 1 at that site and “#” denotes significant difference (p < 0.05) between the two sites. SJ, Sanhang Ju; GHG, Gaoqiao Hua Gong.

Fig. 5. Concentration of the six metals in AM in Shantou. Data expressed in mean ± SEM mg/g Chelex. Asterisk (*) denotes significant difference (p < 0.05) between month 3 and month 1 at that site and “#” denotes significant difference (p < 0.05) between the two sites. NC, Nan’ao County; NH, North Harbour.

4.2. Comparison of the five polluted sites in China with other countries Metal concentrations in AM after 1 month deployment along China coast were compared with AM deployed for the same period in Australia (Kibria et al., 2012), Hong Kong (Wu et al., 2007), Portugal (Gonzalez-Rey et al., 2011), Scotland, Iceland (Leung et al.,

2008), Korea (Ra et al., 2014), South Africa (Degger et al., 2011) and Bangladesh (Kibria et al., 2016). The results showed that level of Cd contamination was generally higher in Hong Kong, Portugal, Scotland, Iceland (>1 mg/g) than that in China (0.033e0.618 mg/g), while levels of Cd in Australia and South Africa were among the lowest (0.01e0.013 and 0e0.031 mg/g respectively). Level of Cr in Qingdao (233 mg/g) was remarkably

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Fig. 6. Concentration of the six metals in AM in Shenzhen. Data expressed in mean ± SEM mg/g Chelex. Asterisk (*) denotes significant difference (p < 0.05) between month 3 and month 1 at that site and “#” denotes significant difference (p < 0.05) between the two sites. SFP, Shekou Ferry Port; XW, Xixiang Wharf.

Fig. 7. Correlation of concentrations of the six metals in Artificial Mussels and the two native mussels, M. edulis and P. viridis. For Hg, correlation coefficient was not calculated since Hg in most native mussel samples was below detection limit (i.e. < 0.02 mg/g) (n ¼ 2).

higher than all the other countries, followed by Shanghai (23.26 mg/ g). Level of Cu contamination in China (20.9e207 mg/g) was generally much higher than other countries, with an exceptionally high level of Cu found in Qingdao (207 mg/g). Compared with similar studies in other countries, level of Hg were relatively low in the five cities in China (0.012e0.131 mg/g), noting that Hg level in Bangladesh was far much higher (11.8e18.2 mg/g). Levels of Pb contamination at Shanghai and Qingdao (30.48 and 22.41 mg/g

respectively) were also much higher than those found in most countries. Highest level of Zn was found in Dalian (106.6 mg/g), followed by Australia and Iceland (21.5e90.8 and 28e80 mg/g respectively). Overall, the comparison revealed that Qingdao probably suffered from the most serious metal contamination amongst all cities and countries, with the highest level of Cr and Cu, and a relatively high level of Hg and Pb, metal contamination.

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4.3. Correlation analysis of metal uptake by Artificial Mussels and native mussels Highly significant correlations were found in metal concentrations in AMs and native mussels for all the metals (p < 0.01) (Fig. 7). Among the metals, Cr showed the strongest correlation (r2 ¼ 0.9994), followed by Cu (r2 ¼ 0.9954), Pb (r2 ¼ 0.9616), Hg (r2 ¼ 0.9523), Cd (r2 ¼ 0.8587), with Zn (r2 ¼ 0.5508) being the least strongly correlated. When the two species of native mussels were separately analysed, significant correlations of all metals were found for both species except Zn in M. edulis and Cd in P. viridis. The results show that: (a) metal accumulation is different in different species of biomonitor; and (b) similar to biomonitors, concentrations of metals in AM provide a reliable time-integrated estimate for spatial and temporal variations of metals in the aquatic environment. The overall results of this study clearly demonstrated that all of the metal species in AMs correlated well with those in native mussels, regardless of the differences in species and hydrographic/ pollution conditions between sites and cities. Indeed, similar results were noted in previous studies in Hong Kong, South Africa, Scotland, Iceland, Portugal, Korea and Australia (Degger et al., 2011; Gonzalez-Rey et al., 2011; Kibria et al., 2012; Leung et al., 2008; Ra et al., 2014; Wu et al., 2007). Notably, AM only takes up dissolved phase metals while mussels take up both the dissolved and particulate phases (from food), which may account for the difference observed. Nevertheless, from an environmental monitoring point of view, it does not mean in any way that AM is inferior to mussels, since even different species of mussels/biomonitors take up different fractions of metals (both dissolved form and food) in the environment. As such, there is no standard (model) biomonitor species that can be considered representative. It should be noted that the primary objective of environmental monitoring is to detect spatial changes (to identify source of input and hot spots) and temporal changes (to detect environmental deterioration or improvement). The AM does not only fully meet with these requirements, but also a smaller sample size is required compared with the use of biomonitors they are much less affected by environmental factors. In summary, high levels of metals were identified in Qingdao, Shanghai and Dalian, and level of Cu in all the five cities was consistently much higher than those reported in other countries. Dalian, Qingdao and Shantou are important fisheries ground and mariculture sites in China. Despite sites with high metal levels revealed in the present study are not for seafood harvest and aquaculture, the high levels of Cr, Cu, Pb and Zn found in these cities, the likelihood of heavy metal contamination of fisheries produces in these cities through bioaccumulation warrant further investigation. Good correlations were found between metal levels in the AM with those in both species of native mussels. The overall results confirmed that AM can provide a reliable time-integrated estimate of metal concentration over large biogeographic areas with contrasting hydrographic conditions, and overcome the shortcomings of monitoring metals in water, sediment and the use of biomonitors. Acknowledgement The work described in this paper was supported by an Areas of Excellence grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (AoE/P-04/04). References Cao, T., An, L., Wang, M., Lou, Y., Yu, Y., Wu, J., Zhu, Z., Qing, Y., Glime, J., 2008. Spatial

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