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李彦莹,李雪花,杨先海,陈广超,等. 有机污染物生物降解性预测模型[J]. 生态毒理学报, 2012, 7(5): 549-555
有机污染物生物降解性预测模型
Predicting Models for Biodegradability of Organic Pollutants
投稿时间:2012-06-29  修订日期:2012-09-29
DOI:
中文关键词:  有机污染物  初级生物降解性  最终生物降解性  预测模型  功能树
英文关键词:organic pollutants  primary biodegradability  ultimate biodegradability  prediction model  functional tree
基金项目:国家863计划重点项目(2010AA065105)和工业生态与环境工程教育部重点实验室开放课题
作者单位
李彦莹 大连理工大学环境学院工业生态与环境工程教育部重点实验室大连 116024 
李雪花 大连理工大学环境学院工业生态与环境工程教育部重点实验室大连 116024 
杨先海 大连理工大学环境学院工业生态与环境工程教育部重点实验室大连 116024 
陈广超 大连理工大学环境学院工业生态与环境工程教育部重点实验室大连 116024 
陈景文 大连理工大学环境学院工业生态与环境工程教育部重点实验室大连 116024 
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中文摘要:
      生物降解性是评估污染物环境持久性的重要依据,也是化学品是否获准生产及进入市场的评价指标。采用17位生物降解领域专家评估的生物降解等级数据,通过功能树(FT)算法建立了包含15个分子结构参数的初级生物降解和最终生物降解预测模型。外部验证结果表明,模型具有较好的预测准确性,初级生物降解性加权准确度(weighted accuracy,WA):训练集WA=84.1%,验证集WA=78.9%;最终生物降解性WA:训练集WA=91.0%;验证集WA=83.6%。预测正确性对化合物的杠杆值作图,表征了生物降解性模型的应用域。
              
AuthorAffiliation
Li YanyingLiaoning Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
Li XuehuaLiaoning Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
Yang XianhaiLiaoning Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
Chen GuangchaoLiaoning Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
Chen JingwenLiaoning Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
英文摘要:
      Biodegradability is significant for the evaluation of environmental persistence of pollutants, which has become a criterion of evaluation on a chemical allowing to be manufactured and market. The primary biodegradation and ultimate biodegradation models which contained 15 molecular structure descriptors were developed employing 17 biodegradation experts evaluating rating data and functional tree algorithm. The external validation results indicated that the models have a good predictive ability. The weighted accuracy (WA) of primary biodegradation is 84.1% and 78.9% for training set and validation set, respectively. WA for ultimate biodegradation is 91.0% and 83.6% for training set and validation set, respectively. Moreover, the applicability domain of the biodegradation models were characterized by the plots of prediction accuracy versus leverage values of chemicals.
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