Chen Bo-Yu, Zheng Si-Rui, Niu Xi-Cheng, Zhao Jin-Song
Key Laboratory of Subtropical Agriculture and Environment, Ministry of Agriculture, College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China.
Huan Jing Ke Xue. 2011 Apr;32(4):1101-7.
The increasing pollution of organophosphorus pesticides (OP) in water have been of concerns. Taking the widely used triazophos as the object, a species sensitivity distribution (SSD) model was developed using a log-logistic distribution based on the median effective concentrations (EC50) of triazophos to aquatic species at various trophic levels, and then the model was tested and evaluated using probability plots and good-of-fit tests. The results showed that the SSD for aquatic biota exposed to triazophos was well fitted by a log-logistic distribution, which was totally determined by the two parameters, alpha = -0.4788 and beta = 0.7546, with standard error 0.2381 and 0.1078 respectively. Based on the SSD model, the hazardous concentration for 5% of the species (HC5) and the criteria maximum concentration (CMC) of triazophos were 1.992 x 10(-3) mg/L and 9.96 x 10(-4) mg/L, respectively. Through comparing the HC5 and CMC with the safe concentration for single-species, it could be found that environmental quality criteria derived from the SSD model was more strict, and closed to the real ecological environment. In addition, according to the reported data, the potentially affected fraction (PAF) of species exposed to triazophos in the Laizhou Bay (Bohai Sea, China) area was 0.36% predicted by the SSD model, and the corresponding risk might not be significant.
水体中有机磷农药（OP）污染日益严重，引发了人们的关注。以广泛使用的三唑磷为研究对象，基于三唑磷对不同营养级水生物种的半数有效浓度（EC50），利用对数逻辑斯蒂分布建立了物种敏感度分布（SSD）模型，然后通过概率图和拟合优度检验对该模型进行了测试和评估。结果表明，暴露于三唑磷的水生生物群落的SSD与对数逻辑斯蒂分布拟合良好，该分布完全由两个参数确定，α = -0.4788，β = 0.7546，标准误差分别为0.2381和0.1078。基于SSD模型，三唑磷的5%物种危害浓度（HC5）和标准最大浓度（CMC）分别为1.992×10⁻³mg/L和9.96×10⁻⁴mg/L。通过将HC5和CMC与单物种安全浓度进行比较发现，SSD模型推导的环境质量标准更为严格，且更接近实际生态环境。此外，根据报告数据，SSD模型预测中国渤海莱州湾地区暴露于三唑磷的物种潜在受影响比例（PAF）为0.36%，相应风险可能不显著。
