Spatial analysis of 4,5-dichloro-2-n-octyl-4-isothiazolin-3-one (Sea-Nine 211) concentrations and probabilistic risk to marine organisms in Hiroshima Bay, Japan.
作者： Kazuhiko Mochida , Takeshi Hano , Toshimitsu Onduka , Hideki Ichihashi , Haruna Amano
DOI: 10.1016/J.ENVPOL.2015.05.012
关键词:
摘要: We analyzed the spatial distribution of an antifouling biocide, 4,5-dichloro-2-n-octyl-4-isothiazolin-3-one (Sea-Nine 211) in surface water and sediments Hiroshima Bay, Japan to determine extent contamination by this biocide. A quantitative estimate environmental concentration (ECD) species sensitivity distributions (SSDs) for marine organisms were derived using a Bayesian statistical model carry out probabilistic ecological risk analysis, such as calculation expected potentially affected fraction (EPAF). The analysis supported notion that Sea-Nine 211 is used mainly treatment ship hulls Japan. calculated EPAF suggests approximately up maximum 0.45% are influenced toxicity Bay. In addition, estimation with conventional quotient method indicated was cause concern
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Joanna S. Jaworska, Theo P. Traas, Tom Aldenberg, Normal Species Sensitivity Distributions and Probabilistic Ecological Risk Assessment CRC Press. pp. 73- 126 ,(2001) , 10.1201/9781420032314-9
WD Shade, SS Hurt, AH Jacobson, KH Reinert, Ecological Risk Assessment of a Novel Marine Antifoulant ASTM International. ,(1993) , 10.1520/STP13169S
Toshimitsu Onduka, Akira Kakuno, Haruna Amano, Kazuhiko Mochida, Kazunori Fujii, Toxicity of 4,5-dichloro-2-n-octyl-3 2H -isothiazolone Sea-Nine 211 to two marine teleostean fishes Japanese journal of environmental toxicology. ,vol. 13, pp. 105- 116 ,(2010) , 10.11403/JSET.13.105
David J. Lunn, Andrew Thomas, Nicky Best, David Spiegelhalter, WinBUGS – A Bayesian modelling framework: Concepts, structure, and extensibility Statistics and Computing. ,vol. 10, pp. 325- 337 ,(2000) , 10.1023/A:1008929526011
Roger S Bivand, Edzer J Pebesma, Virgilio Gómez-Rubio, Edzer Jan Pebesma, None, Applied spatial data analysis with R Springer. ,(2013) , 10.1007/978-1-4614-7618-4
Aaron M. Ellison, An Introduction to Bayesian Inference for Ecological Research and Environmental Decision‐Making Ecological Applications. ,vol. 6, pp. 1036- 1046 ,(1996) , 10.2307/2269588
Tom Aldenberg, Joanna S. Jaworska, Uncertainty of the Hazardous Concentration and Fraction Affected for Normal Species Sensitivity Distributions Ecotoxicology and Environmental Safety. ,vol. 46, pp. 1- 18 ,(2000) , 10.1006/EESA.1999.1869
Takehiko I. Hayashi, Nobuhisa Kashiwagi, A Bayesian approach to probabilistic ecological risk assessment: risk comparison of nine toxic substances in Tokyo surface waters Environmental Science and Pollution Research. ,vol. 18, pp. 365- 375 ,(2011) , 10.1007/S11356-010-0380-5
Kazuhiko Mochida, Haruna Amano, Katsutoshi Ito, Mana Ito, Toshimitsu Onduka, Hideki Ichihashi, Akira Kakuno, Hiroya Harino, Kazunori Fujii, Species sensitivity distribution approach to primary risk analysis of the metal pyrithione photodegradation product, 2,2'-dipyridyldisulfide in the Inland Sea and induction of notochord undulation in fish embryos. Aquatic Toxicology. ,vol. 118, pp. 152- 163 ,(2012) , 10.1016/J.AQUATOX.2012.04.002
S.A.L.M. Kooijman, A safety factor for LC50 values allowing for differences in sensitivity among species Water Research. ,vol. 21, pp. 269- 276 ,(1987) , 10.1016/0043-1354(87)90205-3