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Weighted species sensitivity distribution method to derive site-specific quality criteria for copper in Tai Lake, China

  • Rui Shi
  • , Chunhui Yang
  • , Runhua Su
  • , Jiarui Jin
  • , Yi Chen
  • , Hongling Liu
  • , John P. Giesy
  • , Hongxia Yu

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Tai Lake (Ch: Taihu), which is the largest lake in Jiangsu province, China, has been affected by human activities. As part of a concerted effort to improve water quality to protect the integrity of the Tai Lake ecosystem, a water quality criterion (WQC) was developed for copper (Cu) II. The acute WQC was based on 440 values for acute toxicity of Cu to 24 species from 6 phyla, 16 families, and 20 genera. In addition, 255 values for chronic toxicity of Cu to 10 species from 5 phyla, 8 families, and 9 genera were used to derive chronic WQC. Instead of using a traditional approach based species sensitivity distributions (SSD), a weighted species sensitivity distribution (WSSD) approach was used to calculate the cumulative probability based on endemic species to Tai Lake. Acute and chronic WQC developed by use of the WSSD were 5.3 and 3.7 μg Cu/L, respectively. While the WQC values were comparable to those of other countries, there were slight differences due to variability in species composition of different regions. The site-specific criteria indicated that the current standard set for surface water by the Chinese government might not be protective of aquatic organisms in Tai Lake.
    Original languageEnglish
    Pages (from-to)12968-12978
    JournalEnvironmental Science and Pollution Research
    Volume21
    Issue number22
    DOIs
    Publication statusPublished - 2014

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 6 - Clean Water and Sanitation
      SDG 6 Clean Water and Sanitation

    Research Keywords

    • Asia
    • Model
    • Probabilistic
    • Statistics
    • Weighted species sensitivity distributions

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