A comparison of statistical methods for deriving freshwater quality criteria for the protection of aquatic organisms

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• 作者：Liqun Xing (1)
  Hongling Liu (1)
  Xiaowei Zhang (1)
  Markus Hecker (2)
  John P. Giesy (3) (4)
  Hongxia Yu (1)
  
• 关键词：Species sensitivity distribution (SSD) ; Hazardous concentration for 5?% of species (HC5) ; Water quality criteria ; Statistical methods
• 刊名：Environmental Science and Pollution Research
• 出版年：2014
• 出版时间：January 2014
• 年：2014
• 卷：21
• 期：1
• 页码：159-167
• 全文大小：511 KB
• 作者单位：Liqun Xing (1)
  Hongling Liu (1)
  Xiaowei Zhang (1)
  Markus Hecker (2)
  John P. Giesy (3) (4)
  Hongxia Yu (1)
  
  1. State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210046, China
  2. School of Environment and Sustainability and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
  3. Department of Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
  4. Department of Biology and Chemistry and State Key Laboratory for Marine Pollution, City University of Hong Kong, Kowloon, Hong Kong, SAR, China
  
• ISSN：1614-7499

文摘

Species sensitivity distributions (SSDs) are increasingly used in both ecological risk assessment and derivation of water quality criteria. However, there has been debate about the choice of an appropriate approach for derivation of water quality criteria based on SSDs because the various methods can generate different values. The objective of this study was to compare the differences among various methods. Data sets of acute toxicities of 12 substances to aquatic organisms, representing a range of classes with different modes of action, were studied. Nine typical statistical approaches, including parametric and nonparametric methods, were used to construct SSDs for 12 chemicals. Water quality criteria, expressed as hazardous concentration for 5?% of species (HC5), were derived by use of several approaches. All approaches produced comparable results, and the data generated by the different approaches were significantly correlated. Variability among estimates of HC5 of all inclusive species decreased with increasing sample size, and variability was similar among the statistical methods applied. Of the statistical methods selected, the bootstrap method represented the best-fitting model for all chemicals, while log-triangle and Weibull were the best models among the parametric methods evaluated. The bootstrap method was the primary choice to derive water quality criteria when data points are sufficient (more than 20). If the available data are few, all other methods should be constructed, and that which best describes the distribution of the data was selected.