Du Yanjun, Xu Xiong, Liu Quanzhen, Bai Lu, Hang Kexin, Wang Donghong
Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 100085 Beijing, China; University of Chinese Academy of Sciences, 100049 Beijing, China; National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, 100021 Beijing, China.
Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 100085 Beijing, China.
Sci Total Environ. 2022 Feb 1;806(Pt 3):150691. doi: 10.1016/j.scitotenv.2021.150691. Epub 2021 Oct 1.
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.
数以千计的有机污染物被有意无意地排放到水体中，对生态环境和人类健康产生不利影响。筛选出在水生环境中构成潜在风险的有机污染物对于风险管理至关重要。本综述评估了用于在水生环境中筛选此类污染物的过程、方法和技术，并讨论了它们的优缺点，以及该领域的挑战和知识空白。结合非靶向筛选、靶向筛选和可疑物筛选通常对于编制潜在风险化合物清单很有效，并且能够对这些化合物进行定量分析。样品制备技术和污染物检测技术对污染物筛选结果有很大影响。数据库中包含的化学和毒理学信息有限，阻碍了对具有潜在风险的有机污染物的筛选。机器学习、高通量方法和其他技术将提高筛选高风险污染物的准确性和便利性。本综述为在水生环境中筛选这些化合物提供了重要参考，可用于未来的污染物筛选和风险管理。
