Setting water quality criteria in China: approaches for developing species sensitivity distributions for metals and metalloids

Both nonparametric and parametric approaches were used to construct SSDs for use in ecological risk assessments. Based on toxicity to representative aquatic species and typical water contaminants of metals and metalloids in China, nonparametric methods based on the bootstrap were statistically super...

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Published inReviews of environmental contamination and toxicology Vol. 230; p. 35
Main Authors Liu, Yuedan, Wu, Fengchang, Mu, Yunsong, Feng, Chenglian, Fang, Yixiang, Chen, Lulu, Giesy, John P
Format Journal Article
LanguageEnglish
Published United States 01.01.2014
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Abstract Both nonparametric and parametric approaches were used to construct SSDs for use in ecological risk assessments. Based on toxicity to representative aquatic species and typical water contaminants of metals and metalloids in China, nonparametric methods based on the bootstrap were statistically superior to the parametric curve-fitting approaches. Knowing what the SSDs for each targeted species are might help in selecting efficient indicator species to use for water quality monitoring. The species evaluated herein showed sensitivity variations to different chemical treatments that were used in constructing the SSDs. For example, D. magna was more sensitive than most species to most chemical treatments, whereas D. rerio was sensitive to Hg and Pb but was tolerant to Zn. HC5 values, derived for the pollutants in this study for protecting Chinese species, differed from those published by the USEPA. Such differences may result from differences in geographical conditions and biota between China and the United States. Thus, the degree of protection desired for aquatic organisms should be formulated to fit local conditions. For approach selection, we recommend all approaches be considered and the most suitable approaches chosen. The selection should be based on the practical information needs of the researcher (viz., species composition, species sensitivity, and geological characteristics of aquatic habitats), since risk assessments usually are focused on certain substances, species, or monitoring sites. We used Tai Lake as a typical freshwater lake in China to assess the risk of metals and metalloids to the aquatic species. We calculated hazard quotients for the metals and metalloids that were found in the water of this lake. Results indicated the decreasing ecological risk of these contaminants in the following order: Hg <As<Ni<Zn<Cu<Cd<Pb<Cr. From the methodological perspective, six SSD approaches used delivered different WQC values and affected the risk assessment results of the metals and metalloids to aquatic species. Based on the MEC and HC5 derived from SSDs by nonparametric and parametric approaches together, the risk levels of metals and metalloids were characterized from their hazard quotients as being high risk (Cr, Pb, Cd, and Cu), medium risk (Zn and Ni), or low risk (As and Hg).
AbstractList Both nonparametric and parametric approaches were used to construct SSDs for use in ecological risk assessments. Based on toxicity to representative aquatic species and typical water contaminants of metals and metalloids in China, nonparametric methods based on the bootstrap were statistically superior to the parametric curve-fitting approaches. Knowing what the SSDs for each targeted species are might help in selecting efficient indicator species to use for water quality monitoring. The species evaluated herein showed sensitivity variations to different chemical treatments that were used in constructing the SSDs. For example, D. magna was more sensitive than most species to most chemical treatments, whereas D. rerio was sensitive to Hg and Pb but was tolerant to Zn. HC5 values, derived for the pollutants in this study for protecting Chinese species, differed from those published by the USEPA. Such differences may result from differences in geographical conditions and biota between China and the United States. Thus, the degree of protection desired for aquatic organisms should be formulated to fit local conditions. For approach selection, we recommend all approaches be considered and the most suitable approaches chosen. The selection should be based on the practical information needs of the researcher (viz., species composition, species sensitivity, and geological characteristics of aquatic habitats), since risk assessments usually are focused on certain substances, species, or monitoring sites. We used Tai Lake as a typical freshwater lake in China to assess the risk of metals and metalloids to the aquatic species. We calculated hazard quotients for the metals and metalloids that were found in the water of this lake. Results indicated the decreasing ecological risk of these contaminants in the following order: Hg <As<Ni<Zn<Cu<Cd<Pb<Cr. From the methodological perspective, six SSD approaches used delivered different WQC values and affected the risk assessment results of the metals and metalloids to aquatic species. Based on the MEC and HC5 derived from SSDs by nonparametric and parametric approaches together, the risk levels of metals and metalloids were characterized from their hazard quotients as being high risk (Cr, Pb, Cd, and Cu), medium risk (Zn and Ni), or low risk (As and Hg).
Author Fang, Yixiang
Liu, Yuedan
Chen, Lulu
Mu, Yunsong
Feng, Chenglian
Giesy, John P
Wu, Fengchang
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Snippet Both nonparametric and parametric approaches were used to construct SSDs for use in ecological risk assessments. Based on toxicity to representative aquatic...
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StartPage 35
SubjectTerms Animals
Aquatic Organisms - drug effects
China
Ecosystem
Environmental Exposure
Environmental Monitoring - methods
Lakes - analysis
Metalloids - toxicity
Metals - toxicity
Models, Biological
Models, Statistical
Plants - drug effects
Risk Assessment - methods
Water Pollutants, Chemical - toxicity
Water Quality - standards
Title Setting water quality criteria in China: approaches for developing species sensitivity distributions for metals and metalloids
URI https://www.ncbi.nlm.nih.gov/pubmed/24609517
Volume 230
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