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Oxidation of Aquatic Organic Contaminants Induced by Excited Triplet States
Open accessAbstract
The developments of the last fifteen years in the field of triplet-induced degradation of aquatic organic contaminants are reviewed. There is increasing evidence that the elusive excited triplet states of colored dissolved natural organic matter (CDOM) initiate the oxidative degradation of various contaminants. To date, phenols, phenylurea herbicides, and sulfonamide antibiotics have been shown to be affected by such an oxidation. The parallel study of aqueous oxidation of target contaminants induced by excited triplet states of aromatic ketones, taken as model systems, has been useful in understanding the action of triplet CDOM and in developing predictive tools to assess aquatic oxidation rates of such contaminants.
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Citations
Cited by
Wenk, J., von Gunten, U., & Canonica, S. (2011) · Environmental Science & Technology · doi:10.1021/es102212t · Cited by 507
Self-citationLiu, Y., He, X., Duan, X., Fu, Y., Fatta-Kassinos, D., & Dionysiou, D. D. (2016) · Water Research · doi:10.1016/j.watres.2016.03.011 · Cited by 317
De la Cruz, N., Esquius, L., Grandjean, D., Magnet, A., Tungler, A., de Alencastro, L. F., & Pulgarín, C. (2013) · Water Research · doi:10.1016/j.watres.2013.07.005 · Cited by 272
Metadata
- Authors
- Canonica, S.
- Venue
- CHIMIA
- Publisher
- Swiss Chemical Society
- Published
- 2007-10-24
- Volume
- 61
- Issue
- 10
- Pages
- 641
- ISSN
- 0009-4293 (ISSN-L)
- 2673-2424
- OpenAlex
- W1989370127
- Cited by
- 171
- References
- 0
- FWCI
- 4.79
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Canonica, S. (2007). Oxidation of Aquatic Organic Contaminants Induced by Excited Triplet States. CHIMIA. https://doi.org/10.2533/chimia.2007.641
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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.