化学
降级(电信)
生物污染
污水
结垢
矿化(土壤科学)
膜污染
流出物
过氧化氢
污水处理
环境化学
膜
环境科学
有机化学
环境工程
生物化学
电信
计算机科学
氮气
作者
Thiago Lopes da Silva,Camila Stéfanne Dias Costa,Meuris Gurgel Carlos da Silva,Melissa Gurgel Adeodato Vieira
标识
DOI:10.1016/j.jclepro.2022.131226
摘要
Non-steroidal anti-inflammatory drugs (NSAIDs) are a class of drugs widely used due to their analgesic and anti-inflammatory effect. Because of their incomplete metabolization in humans and animals, these species are excreted in urine and faeces and reach the sewage network and, due to the recalcitrance of these compounds in conventional treatments, their presence has been detected in water bodies all over the world. Although these concentrations are not controlled by legislation related to water quality, the presence of these substances is a concern because they are persistent and biologically active for long periods. Efforts are directed towards the development of treatment processes that enable the NSAIDs degradation and, in this scenario, the advanced oxidation processes (AOP) are shown as an alternative for degradation and mineralization of persistent organic compounds. This review presents information related to the properties of anti-inflammatory drugs found in water and effluents, the most recent results on the concentration of these compounds in different aquatic environments, the main characteristics of AOP and the results recently achieved in oxidation processes aimed at degradation of NSAIDs. It is worth mentioning that combined and/or hybrid methods composed by membrane filtration reactors and AOPs consist a recent and promising approach of self-cleaning/self-antifouling characteristics that enable enhanced degradation efficiency, lower reagent consumption and costs, and improve membrane flux as fouling is reduced. Besides the most common homogeneous and heterogeneous AOP processes and their trends (e.g., methods based on ozone, Fenton reactions, and UV irradiation), hybrid methods encompassing integrated membrane filtration-AOPs reactors are also reported and critically analyzed. Concluding remarks, future perspectives and challenges were given and discussed.
科研通智能强力驱动
Strongly Powered by AbleSci AI