物种敏感度分布法(SSD)在农药水质基准推导中的应用  

Application of Species Sensitivity Distribution( SSD) to Derivation of Water Quality Criteria for Pesticides

作　　者：梁霞[1,2] 周军英[2] 李建宏[1] 王香兰[2] 宋宁慧[2] 单正军[2] 

机构地区：[1]南京师范大学生命科学学院,江苏南京210023 [2]环境保护部南京环境科学研究所,江苏南京210042

出　　处：《生态与农村环境学报》2015年第3期398-405,共8页Journal of Ecology and Rural Environment

基　　金：环保公益性行业科研专项(201009033)

摘　　要：水质基准推导方法在水质基准制定中起着至关重要的作用,物种敏感度分布法是目前国际上常用的基准推导方法,但利用此方法推导水质基准时,可选用的模型很多,但并不是所有的模型都能很好地拟合农药毒性数据集。为了筛选得到拟合优度较好的模型,选取4种典型农药,对采用不同模型拟合物种敏感度分布曲线的结果进行比较研究。结果显示,sigmoid、Gaussian、Gompertz和exponential growth 4种模型对于农药数据集,无论是在曲线走势、HC5值的合理性还是拟合优度方面的拟合效果都优于其他几种模型。因此,在应用物种敏感度分布法推导农药水质基准时,可以首选上述4种模型进行拟合,然后再从中选出最优模型来确定基准值,从而保证基准值推导的科学性。研究结果可为农药水质基准制定时推导方法的选择提供科学参考。Deriving methods play an important role in water quality criteria derivation. Species sensitivity distributions（SSD） is a common method used to derive water quality criteria in the world. A number of models are available to derivewater quality criteria, but not all the models could well fit the toxicity data sets of pesticides. In order to select some mod.els that fit with high goodness, 4 typical pesticides were selected in the study to compare the models in goodness of fit. Re.sults show that sigmoid, Gaussian,Gompertz and exponential growth were better than the other models in fitting curve tend.ency, rationality of HC5 and goodness of fit. Therefore it is suggested that when utilizing SSD to derive criteria for pesti.cides, sigmoid, Gaussian, Gompertz and exponential growth should be used to get fitting curves first, and then the mostoptimal model should be chosen to determine benchmark values for the water quality criteria, so as to ensure scientificity ofthe derivation of the water quality criteria. The findings can serve as scientific references for selection of derivation methodsfor formulation of water quality criteria for pesticides.

关 键 词：物种敏感度分布法 农药 水质基准 推导方法 

分 类 号：X592[环境科学与工程—环境工程]