污染物
环境科学
鉴定(生物学)
水生环境
风险分析(工程)
风险评估
水生生态系统
生化工程
环境监测
环境风险评价
环境资源管理
计算机科学
生态学
环境工程
生物
业务
工程类
计算机安全
作者
Yanjun Du,Xiong Xu,Quanzhen Liu,Lu Bai,Kexin Hang,Donghong Wang
标识
DOI:10.1016/j.scitotenv.2021.150691
摘要
Thousands of organic pollutants are intentionally and unintentionally discharged into water bodies, adversely affecting the ecological environment and human health. Screening for organic pollutants that pose a potential risk in aquatic environments is essential for risk management. This review evaluates the processes, methods, and technologies used to screen such pollutants in the aquatic environment and discuss their advantages and disadvantages, in addition to the challenges and knowledge gaps in this field. Combining non-target screening, target screening, and suspect screening is often effective for compiling a list of potential risk compounds and enables the quantitative analysis of these compounds. Sample preparation technologies and pollutant detection technologies considerably affect the results of pollutant screening. The limited amount of chemical and toxicological information contained in databases hinders the screening of organic pollutants with potential risk. Machine learning, high-throughput methods, and other technologies will increase the accuracy and convenience of screening for high-risk pollutants. This review provides an important reference for screening these compounds in aquatic environments and can be used in future pollutant screening and risk management.
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