Applying biotic ligand models and Bayesian techniques: Ecological risk assessment of copper and nickel in Tokyo rivers

Integrated Environmental Assessment and Management

Volumn 9, Issue 1, 2013, Pages 63-69

  Hayashi, Takehiko I ^a  

^a NATIONAL INSTITUTE FOR ENVIRONMENTAL STUDIES   (Japan)

Author keywords

Bayesian statistics; Biotic ligand model; Ecological risk assessment; Environmental standard; Heavy metal

Indexed keywords

COPPER; LIGAND; NICKEL;

ARTICLE; BAYES THEOREM; BIOTA; CHEMISTRY; ECOTOXICOLOGY; ENVIRONMENTAL EXPOSURE; JAPAN; METABOLISM; METHODOLOGY; RISK ASSESSMENT; RIVER; STATISTICAL MODEL; WATER POLLUTANT;

BAYES THEOREM; BIOTA; COPPER; ECOTOXICOLOGY; ENVIRONMENTAL EXPOSURE; LIGANDS; MODELS, STATISTICAL; NICKEL; RISK ASSESSMENT; RIVERS; TOKYO; WATER POLLUTANTS, CHEMICAL;

MLCS; MLOWN;

EID: 84878405112     PISSN: 15513793     EISSN: None     Source Type: Journal    
DOI: 10.1002/ieam.1326     Document Type: Article

References (16)

1. Campbell PGC. 1995. Interactions between trace metals and organisms: critique of the free-ion activity model.: In: Tessier A, Turner D, editors. Metal speciation and bioavailability in aquatic systems. Chichester (UK): Wiley. p. 45-102.
2. Central Environmental Council Environmental Water Group. 2003. Setting of environmental quality standards for the conservation of aquatic organisms. Tokyo, Japan: Environmental Agency.
3. Central Environmental Council Environmental Water Group. 2009. 19th report 6. Tokyo, Japan: Environmental Agency.
4. Di Toro DM, Allen HE, Bergman HL, Meyer JS, Paquin PR, Santore RC. 2001. Biotic ligand model of the acute toxicity of metals. 1. Technical basis. Environ Toxicol Chem 20:2383-2396.
5. Edogawa River Office. Temporal change in water quality in monitoring sites [Internet]. [cited 2011 August 4]. Available from: http://www.ktr.mlit.go.jp/ktr_content/content/000015349.pdf
6. [EU] European Union. 2008. European Union risk assessment report. Voluntary risk assessment of Cu, copper II sulphate pentahydrate, copper(I)oxide, copper(II)oxide, dicopper chloride trihydroxide. Available from: http://echa.europa.eu/copper-voluntary-risk-assessment-reports/
7. [EU] European Union. 2009. European Union risk assessment report. Nickel and nickel compounds. Available from: http://esis.jrc.ec.europa.eu/doc/risk_assessment/REPORT/nickelreport311.pdf
8. Gelman A. 2004. Bayesian data analysis. Boca Raton (FL): Chapman & Hall/CRC. p. 696.
9. Hayashi TI, Kashiwagi N. 2011. A Bayesian approach to probabilistic ecological risk assessment: risk comparison of nine toxic substances in Tokyo surface waters. Environ Sci Pollut Res 18:365-375.
10. Kamo M, Hayashi TI. 2011. Biotic ligand model: historical overview and perspectives. Jpn J Environ Toxicol 14:25-38. Japanese.
11. Lunn DJ, Thomas A, Best N, Spigelhalter D. 2000.WinBUGS-A Bayesian modeling framework: Concepts, structure, and extensibility. Stat Comput 10:325-337.
12. Nagai T. 2011. Metal speciation and bioavailability in natural aquatic environment. Jpn J Environ Toxicol 14:13-23. Japanese.
13. Niyogi S, Wood CM. 2004. Biotic ligand model, a flexible tool for developing sitespecific water quality guidelines for metals. Environ Sci Technol 38:6177-6192.
14. Posthuma L, Suter GW, Traas TP. 2002. Species sensitivity distributions in ecotoxicology. Boca Raton (FL): Lewis Publishers. p. 616.
15. R Development Core Team. 2007. R: Language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
16. van Sprang PA, Verdonck FAM, van Assche F, Regoli L, De Schamphelaere KAC. 2009. Environmental risk assessment of zinc in European freshwaters: A critical appraisal. Sci Total Environ 407:5373-5391.