Journal
CHEMOSPHERE
Volume 138, Issue -, Pages 1-9Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2015.05.034
Keywords
Molecular descriptors; Hydroxyl radical; Reaction rate constant; Micropollutants; Applicability domain
Categories
Funding
- Ontario Ministry of Research and Innovations (MRI)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
Ask authors/readers for more resources
Quantitative structure-property relationship (QSPR) models which predict hydroxyl radical rate constants (k(oH)) 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 k(oH) 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 k(oH) 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. (C) 2015 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available