Improved prediction of sediment toxicity using a combination of sediment and overlying water contaminant exposures.

Benthic invertebrates Chronic toxicity prediction Field-based assessments Multiple linear regression Risk assessment Sediment quality

Journal

Environmental pollution (Barking, Essex : 1987)
ISSN: 1873-6424
Titre abrégé: Environ Pollut
Pays: England
ID NLM: 8804476

Informations de publication

Date de publication:
Nov 2020
Historique:
received: 01 05 2020
revised: 21 06 2020
accepted: 04 07 2020
pubmed: 16 7 2020
medline: 17 9 2020
entrez: 16 7 2020
Statut: ppublish

Résumé

The choice of sediment quality assessment methodologies can strongly influence assessment outcomes and management decisions for contaminated sites. While in situ (field) methods may potentially provide greater realism, high costs and/or complex logistics often prevent their use and assessment must rely on laboratory-based methods. In this study, we utilised static-renewal and flow-through ecotoxicology tests in parallel on sediments with a wide range of properties and varying types and concentrations of contaminants. The prediction of chronic effects to amphipod reproduction was explored using multiple linear regression (MLR). The study confirmed the considerable over-estimation of the risk of toxicity of contaminated sediments in field locations when assessments rely on the results of laboratory-based static and static-renewal tests. Improved prediction of toxicity risks was achieved using a combination of contaminant exposure measures from sediment and overlying water. Existing sediment and water quality guideline values (GVs) were effective for predicting risks posed by sediments containing mixtures of common metal and organic contaminants. For 17 sediments with paired data sets from static-renewal and flow-through tests, the best prediction of toxicity to reproduction was achieved using a 2-parameter MLR that included hazard quotients for sediment contaminants and toxic units for dissolved metals (r

Identifiants

pubmed: 32668359
pii: S0269-7491(20)33334-0
doi: 10.1016/j.envpol.2020.115187
pii:
doi:

Substances chimiques

Metals 0
Water Pollutants, Chemical 0
Water 059QF0KO0R

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

115187

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest 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.

Auteurs

Yanfeng Zhang (Y)

Centre for Environmental Contaminants Research, CSIRO Land and Water, Lucas Heights, NSW, 2234, Australia; Tianjin Key Laboratory of Remediation & Pollution Control for Urban Ecological Environment, Key Laboratory of Pollution Processes and Environmental Criteria of Ministry of Education, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.

David A Spadaro (DA)

Centre for Environmental Contaminants Research, CSIRO Land and Water, Lucas Heights, NSW, 2234, Australia.

Josh J King (JJ)

Centre for Environmental Contaminants Research, CSIRO Land and Water, Lucas Heights, NSW, 2234, Australia.

Stuart L Simpson (SL)

Centre for Environmental Contaminants Research, CSIRO Land and Water, Lucas Heights, NSW, 2234, Australia; Hong Kong Branch of the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China. Electronic address: Stuart.Simpson@csiro.au.

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Classifications MeSH