Elsevier

Marine Pollution Bulletin

Volume 137, December 2018, Pages 555-565
Marine Pollution Bulletin

Bioaccumulation of trace metals in aquatic food web. A case study, Liaodong Bay, NE China

https://doi.org/10.1016/j.marpolbul.2018.11.002Get rights and content

Highlights

  • Ecological exposure to As, Cd, Cu, Ni, Pb, Zn was assessed for Liaodong Bay.

  • MERLIN-Expo was applied to model metal bioaccumulation in aquatic species.

  • As, Cd, Cu, Ni, Pb and Zn accumulate mostly in invertebrates.

  • Good agreement between simulated and observed data was noted.

  • Sensitivity of modelled results were analysed using the Morris and EFAST techniques.

Abstract

The recently developed modelling tool MERLIN-Expo was applied to support the exposure assessment of an aquatic food web to trace metals in a coastal environment. The exposure scenario, built on the data from Daliao River estuary in the Liaodong Bay (Bohai Sea, China), affected by long-term and large-scale industrial activities as well as rapid urbanization in Liao River watershed, represents an interesting case-study for ecological exposure modelling due to the availability of local data on metal concentrations in water and sediment. The bioaccumulation of selected trace metals in aquatic organisms was modelled and compared with field data from local aquatic organisms. Both model results and experimental data demonstrated that As, Cd, Cu, Ni, Pb and Zn, out of examined metals, were accumulated most abundantly by invertebrates and less by higher trophic level species. The body parts of the sampled animals with the highest measured concentration of metals were predominantly muscles, intestine and liver and fish skin in the case of Cr.

The Morris and extended Fourier Analysis (EFAST) were used to account for variability in selected parameters of the bioaccumulation model. Food assimilation efficiency and slopes and intercepts of two sub-models for calculating metal specific BCFs (BCFmetal-exposure concentration) and fish weight (Weightfish-Lengthfish) were identified as the most influential parameters on ecological exposure to selected metals.

Introduction

It is well known that trace metals including metals and metalloids are released from both natural and anthropogenic sources and pose potential risks to ecosystem and human health due to their accumulation in food webs. Human sources of pollutants including metals are numerous as a consequence of rapid urbanization and industrialization over the last century. The coastal and estuarine ecosystems in China are now facing increasing metal pollution stress because metals released along with municipal and industrial wastes may enter the sea by river transportation, and ultimately accumulate in the coastal areas, introducing long-term accumulative effects (Pan and Wang, 2012). North-eastern China coastal regions, such as Bohai Sea, are considered to be the most affected by metal contamination (Gao and Chen, 2012). More importantly, metals can be taken up by marine organisms, entering the food chain and be potentially transferred to the upper trophic levels, which can eventually lead to adverse effects on humans due to the consumption of contaminated seafood (Szefer, 2013). Currently, there is a very serious concern for seafood safety originating from accumulation of metals and organic pollutants (Liu et al., 2015; Hu et al., 2016; Rodríguez-Hernández et al., 2016; Tong et al., 2017) as well as from threats that just recently have been gaining proper attention such as plastics and microplastics (Oksman, 2016, EFSA Panel on Contaminants in the Food Chain (CONTAM), 2016; Peng et al., 2017), which require deepening the understanding about contaminants bioaccumulation in food chains (Koelmans, 2015). The transfer of contaminants from abiotic environment to a specific food product is of importance regarding the quality and safety of food and has been recognised by international regulatory bodies, such as the European Commission (EC) of European Union (EU) which has set up safety maximum levels for several contaminants in certain foodstuffs including fish and seafood (EC No 1881/2006). However, currently in the EU the available limits are established only for few metals; maximum Cd concentration levels in muscle meat of fishes varies between species from 0.1 mg/kg fw in sea bream, grey mullet or sardines to 0.3 mg/kg fw for anchovy and swordfish, 0.5 mg/kg fw for crustaceans and 1.0 mg/kg fw for bivalve mollusks and cephalopods. Similarly, maximum concentration levels for Pb are set to 0.3 mg/kg fw for fish, 0.5 mg/kg fw for crustaceans (both pertaining to muscles), and 1.5 mg/kg fw for bivalve molluscs. Hg maximum level was fixed at 0.5 mg/kg fw for fishery products and muscle meat of fish and 1.0 mg/kg fw for number of fish species including mullet, swordfish and tuna (EC No 1881/2006)). Similarly, China also promulgated the National Food Safety Standard (National food safety standards in food contaminants. The State Standard of the People's Republic of China, GB 2762-2017), and the Maximum Limit Concentrations (MLC) that are 0.5 mg/kg fw for Pb in fish and crustaceans, and 1.5 mg/kg fw in bivalve molluscs; for Cd, MLC is set at 0.1, 0.5 and 2.0 mg/kg fw for fish, crustaceans and bivalves respectively, while MLC for As and Hg in aquatic animals and their products is set at 0.5 mg/kg fw and 1.0 mg/kg fw in fish and their products, and for Cr there is a 2.0 mg/kg fw limit in aquatic animals and their products.

Aquaculture global production rose to 73.8 million tonnes in 2014, a third of which comprised molluscs, crustaceans and other non-fish animals, with China remaining the leading nation for aquaculture (FAO, 2016). Asian countries alone account for some 91% of the global production of molluscs and 70% of global aquaculture production (Li et al., 2011). The domestic demand for seafood in China has increased dramatically from an annual consumption of 7 kg per person in 1985 to about 25 kg in 2005 and 37.9 kg in 2013 (Fabinyi, 2016; FAO, 2016). China currently consumes 37% of global production of seafood and aquatic products, reaching seafood consumption per capita 44 kg – estimated to increase to 50 kg by 2026 (OECD/FAO, 2017; Harkell, 2018).

Food products safety can benefit greatly from the application of predictive models for the evaluation of exposure and bioaccumulation to trace metals and the identification of risks based on aquatic ecosystem health condition.

The prediction of metal transfer along aquatic food webs depends significantly on understanding how organisms accumulate metals from their environment. It is important to recognise that aquatic organisms are exposed to trace metals from both soluble and dietary source which need to be factored in (Thomann et al., 1995; Diepens et al., 2015. Biokinetic models can provide critical information for our understanding of the key processes controlling metal bioaccumulation, thus explaining vast differences in metal body burdens found among different animal species (Luoma and Presser, 2000). Additionally, mechanistic models permit to incorporate variability in biokinetic parameters, thus allowing to find likely explanation of the different patterns of bioaccumulation seen in different species under various environmental conditions. Despite the number of existing food web bioaccumulation models (e.g., ECOFATE (Gobas et al., 1998), AQUAWEB v1.1 (Arnot and Gobas, 2004), BASS v 2.2 (Barber, 2008)), they are mostly designed for modelling exposures to nonpolar organic contaminants offering little support for addressing spatial and temporal variabilities in estimating exposures. On the other hand, the MERLIN-Expo exposure modelling tool (Ciffroy et al., 2016) was developed for a broad range of environmental pollutants including trace metals (Tanaka et al., 2011), allowing the user to adapt the model to specific requirements of localised exposure scenario (Fierens et al., 2016). For these reasons, it was selected as the main application in this study.

The main objective of the present study was to model concentration of trace metals in aquatic species occurring in Liaodong bay (Bohai Sea, China). The modelling exercise consisted of the calculation of metal concentration levels specific to invertebrate and fish organisms from measured water/sediment metal contamination data, and the comparison of model results with measured metal concentrations in aquatic species from Liaodong bay food web. Additionally, the application of sensitivity analysis aided in identifying the most critical parameters from the model that ultimately influenced the overall metal concentrations in organisms.

Section snippets

Description of study area and monitoring campaign

The Daliao River estuary is located in southern Liaoning Province, NE China (121°33′-122°36′E, 40°26′-41°27′N) (Fig. 1) and has representative characteristics of many estuaries in China with high pollution pressure. The Daliao River flows through many important large- or medium-sized industrial cities, combining with the Hun River and the Taizi River, and ultimately flows into the Liaodong Bay, Bohai Sea. The Daliao River watershed includes some of the traditional industrial hot spots of China

Metals in water column and sediment

Measured concentrations of examined trace metals in sediments and in water are reported in Table S4. Eight metals show higher concentration in sediments than in water, the highest difference was detected for Pb and Cr. Only Zn shows inverse sediment-water relationship. Concentrations of metals in sediments were compared with recent literature concentration data collected for the Liadong Bay and the Bohai Bay (Table S5). Although sediment concentration values are characterised by significant

Conclusions

Concerns over high metal concentrations in the aquatic environment stem primarily from the risk these contaminants can pose for living organisms, including, at the top of the food chain, people who might consume contaminated seafood.

We have demonstrated how the recently developed tool MERLIN-Expo can be used to simulate site specific exposure for aquatic organisms to several trace metals. The application of the model was tailored to the exposure scenario in Liaodong Bay using as inputs

Acknowledgements

This work was financially supported by the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 269233—GLOCOM (Global Partners in Contaminated Land Management) and by the Chinese Ministry of Science and Technology (No. 2012CB525005).

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