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Critical Review of UV-Advanced Reduction Processes for the Treatment of Chemical Contaminants in Water

[Image: see text] UV-advanced reduction processes (UV-ARP) are an advanced water treatment technology characterized by the reductive transformation of chemical contaminants. Contaminant abatement in UV-ARP is most often accomplished through reaction with hydrated electrons (e(aq)(–)) produced from U...

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Detalles Bibliográficos
Autores principales: Fennell, Benjamin D., Mezyk, Stephen P., McKay, Garrett
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10114900/
https://www.ncbi.nlm.nih.gov/pubmed/37102145
http://dx.doi.org/10.1021/acsenvironau.1c00042
Descripción
Sumario:[Image: see text] UV-advanced reduction processes (UV-ARP) are an advanced water treatment technology characterized by the reductive transformation of chemical contaminants. Contaminant abatement in UV-ARP is most often accomplished through reaction with hydrated electrons (e(aq)(–)) produced from UV photolysis of chemical sensitizers (e.g., sulfite). In this Review, we evaluate the photochemical kinetics, substrate scope, and optimization of UV-ARP. We find that quantities typically reported in photochemical studies of natural and engineered systems are under-reported in the UV-ARP literature, especially the formation rates, scavenging capacities, and concentrations of key reactive species like e(aq)(–). The absence of these quantities has made it difficult to fully evaluate the impact of operating conditions and the role of water matrix components on the efficiencies of UV-ARP. The UV-ARP substrate scope is weighted heavily toward contaminant classes that are resistant to degradation by advanced oxidation processes, like oxyanions and per- and polyfluoroalkyl substances. Some studies have sought to optimize the UV-ARP treatment of these contaminants; however, a thorough evaluation of the impact of water matrix components like dissolved organic matter on these optimization strategies is needed. Overall, the data compilation, analysis, and research recommendations provided in this Review will assist the UV-ARP research community in future efforts toward optimizing UV-ARP systems, modeling the e(aq)(–)-based chemical transformation kinetics, and developing new UV-ARP systems.