Abstract

The abatement of organic micropollutants during oxidation processes has become an emerging issue for various urban water systems such as drinking water, wastewater, and water reuse. Reaction kinetics and mechanisms play an important role in terms of efficiency of these processes and the formation of transformation products, which are controlled by functional groups in the micropollutants and the applied oxidants. So far, the kinetic and mechanistic information on the underlying reactions was obtained by experimental studies; additionally, predictive quantitative structure activity relationships (QSARs) were applied to determine reaction kinetics for the oxidation of emerging compounds. Since this experimental approach is very laborious and there are tens of thousands potential contaminants, alternative strategies need to be developed to predict the fate of micropollutants during oxidative water treatment. Due to significant developments in quantum chemical (QC) computations in recent years and increased computational capacity, QC based methods have become an alternative or a supplement to the current experimental approach.

This Account provides a critical assessment of the current state-of-the-art of QC-based methods for the assessment of oxidation of micropollutants. Starting from a given input structure, QC computations need to locate energetic minima on the potential energy surface (PES). Then, useful thermodynamic and kinetic information can be estimated by different approaches: Experimentally determined reaction mechanisms can be validated by identification of transition structures on the PES, which can be obtained for addition reactions, heavy atom transfer (Cl,+ Br', 0-) and H atom transfer (simultaneous proton and electron transfer) reactions.

However, transition structures in the PES cannot be obtained for e--transfer reactions. Second-order rate constants k for the reactions of micropollutants with chemical oxidants can be obtained by ab initio calculations or by QSARs with various QC descriptors. It has been demonstrated that second-order rate constants from ab initio calculations are within factors 3-750 of the measured values, whereas QSAR-based methods can achieve factors 2-4 compared to the experimental data. The orbital eigenvalue of the highest occupied molecular orbital (EHomo) is the most commonly used descriptor for QSAR-based computations of k-values.

In combination with results from experimental studies, QC computations can also be applied to investigate reaction mechanisms for verification/understanding of oxidative mechanisms, calculation of branching ratios or regioselectivity, evaluation of the experimental product distribution and assessment of substitution effects. Furthermore, other important physical-chemical constants such as unknown equilibria for species, which are not measurable due to low concentrations, or plc values of reactive transient species can be estimated. With further development of QC-based methods, it will become possible to implement kinetic and mechanistic information from such computations in in silico models to predict oxidative transformation of micropollutants. Such predictions can then be complemented by tailored experimental studies to confirm/falsify the computations.

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