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Quantitative structure-activity relationships for oxidation reactions of organic chemicals in water

Even in the absence of microbiological mediation, oxidation is one of the most important chemical processes contributing to the degradation of organic contaminants in the aquatic environment. The oxidants that are responsible for these reactions include hydroxyl radical, carbonate radical, organic o...

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Bibliographic Details
Published in:Environmental toxicology and chemistry 2003-08, Vol.22 (8), p.1743-1754
Main Authors: Canonica, Silvio, Tratnyek, Paul G.
Format: Article
Language:English
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Summary:Even in the absence of microbiological mediation, oxidation is one of the most important chemical processes contributing to the degradation of organic contaminants in the aquatic environment. The oxidants that are responsible for these reactions include hydroxyl radical, carbonate radical, organic oxyl and peroxyl radicals, peroxides, excited triplet states of organic chromophores, singlet molecular oxygen, ozone, chlorine dioxide, permanganate, and chromate. Some of these oxidants contribute to natural attenuation of organic contaminants, but many are of greater interest because of their role in engineered remediation technologies. Kinetic studies of these processes have lead to numerous quantitative structure‐activity relationships (QSARs). Many of these QSARs are simple empirical correlations to common convenient descriptor variables like Hammett constants (σ), half‐wave oxidation potentials (E1/2), energies of the highest occupied molecular orbital (EHOMO) or rate constants for other oxidation reactions. However, several environmentally relevant, aqueous‐phase oxidation reactions have been described with QSARs based on theoretical models for electron transfer that were developed by Marcus‐Hush and Rehm‐Weller. This review summarizes many of the reported QSARs for aquatic oxidations of organic compounds with emphasis on the interrelation between traditional empirical models and the potential for future development of QSARs based on theoretical models.
ISSN:0730-7268
1552-8618
DOI:10.1897/01-237