Sediment quality in a metal-contaminated tropical bay assessed with a multiple lines of evidence approach

• Autor(a) principal: Rodrigues, Sarah K.
• Data de Publicação: 2017
• Outros Autores: Abessa, Denis M. S. [UNESP], Rodrigues, Ana Paula de C., Soares-Gomes, Abilio, Freitas, Carolina B., Santelli, Ricardo E., Freire, Aline S., Machado, Wilson
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.envpol.2017.05.045; http://hdl.handle.net/11449/162967
• topic: Metal bioavailability; Equilibrium-partitioning model; Metal toxicity tests; Macrobenthos; Sepetiba Bay

A sediment quality assessment was performed near to the main industrial source of metal contamination in Sepetiba Bay, Brazil, which represents one of the worst cases of trace metal contamination reported for coastal areas. Acute and chronic toxicity tests, benthic fauna community analysis and metal bioavailability evaluations were applied to identify risks to the benthic community. Significant amphipod mortality was observed close to the major pollution source and lower copepod fertility was observed for all stations. Equilibrium-partitioning and biotic-ligand models to predict pore water metal toxicity, which were based on acid-volatile sulfide (AVS) and organic carbon fraction (f(oc)) normalization approaches, suggested that metals are not likely to be available in sediment pore water. However, Cd, Pb and Zn concentrations were mainly (>50%) weakly bound to sediments, suggesting high potential bioavailability. Linking the chemical results with ecotoxicological responses, we observed that sediment feeding organisms presented acute and chronic toxicities that were positively correlated to the metal concentrations in the sediments. Additionally, benthic fauna composition was dominated by tolerant species, revealing a trophic structure response to environmental contamination. These results reinforce the necessity of a multiple lines of evidence approach to establish sediment quality and to support environmental management decisions that are based on observed effects and potential extrapolation scenarios into, the future. (C) 2017 Elsevier Ltd. All rights reserved.