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Multiple Roles of Dissolved Organic Matter in Advanced Oxidation Processes
Abstract
Advanced oxidation processes (AOPs) can degrade a wide range of trace organic contaminants (TrOCs) to improve the quality of potable water or discharged wastewater effluents. Their effectiveness is impacted, however, by the dissolved organic matter (DOM) that is ubiquitous in all water sources. During the application of an AOP, DOM can scavenge radicals and/or block light penetration, therefore impacting their effectiveness toward contaminant transformation. The multiple ways in which different types or sources of DOM can impact oxidative water purification processes are critically reviewed. DOM can inhibit the degradation of TrOCs, but it can also enhance the formation and reactivity of useful radicals for contaminants elimination and alter the transformation pathways of contaminants. An in-depth analysis highlights the inhibitory effect of DOM on the degradation efficiency of TrOCs based on DOM's structure and optical properties and its reactivity toward oxidants as well as the synergistic contribution of DOM to the transformation of TrOCs from the analysis of DOM's redox properties and DOM's transient intermediates. AOPs can alter DOM structure properties as well as and influence types, mechanisms, and extent of oxidation byproducts formation. Research needs are proposed to advance practical understanding of how DOM can be exploited to improve oxidative water purification.
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Metadata
- Authors
- Yang, X., Rosario-Ortiz, F. L., Lei, Y., Pan, Y., Lei, X., & Westerhoff, P.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2022-07-07
- Volume
- 56
- Issue
- 16
- Pages
- 11111-11131
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W4284705168
- Cited by
- 459
- References
- 255
- FWCI
- 24.16
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.