Predicting the reaction rate constants of micropollutants with hydroxyl radicals in water using QSPR modeling.

Abstract:

:Quantitative structure-property relationship (QSPR) models which predict hydroxyl radical rate constants (kOH) for a wide range of emerging micropollutants are a cost effective approach to assess the susceptibility of these contaminants to advanced oxidation processes (AOPs). A QSPR model for the prediction of kOH of emerging micropollutants from their physico-chemical properties was developed with special attention to model validation, applicability domain and mechanistic interpretation. In this study, 118 emerging micropollutants including those experimentally determined by the author and data collected from the literature, were randomly divided into the training set (n=89) and validation set (n=29). 951 DRAGON molecular descriptors were calculated for model development. The QSPR model was calibrated by applying forward multiple linear regression to the training set. As a result, 7 DRAGON descriptors were found to be important in predicting the kOH values which related to the electronegativity, polarizability, and double bonds, etc. of the compounds. With outliers identified and removed, the final model fits the training set very well and shows good robustness and internal predictivity. The model was then externally validated with the validation set showing good predictive power. The applicability domain of the model was also assessed using the Williams plot approach. Overall, the developed QSPR model provides a valuable tool for an initial assessment of the susceptibility of micropollutants to AOPs.

journal_name

Chemosphere

journal_title

Chemosphere

authors

Jin X,Peldszus S,Huck PM

doi

10.1016/j.chemosphere.2015.05.034

subject

Has Abstract

pub_date

2015-11-01 00:00:00

pages

1-9

eissn

0045-6535

issn

1879-1298

pii

S0045-6535(15)00497-X

journal_volume

138

pub_type

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