Prediction of Second-Order Rate Constants of Sulfate Radical with Aromatic Contaminants Using Quantitative Structure-Activity Relationship Model

Han Ding,Jiangyong Hu

doi:10.3390/w14050766

Abstract

Predicting the second-order rate constants between aromatic contaminants and a sulfate radical (kSO4•−) is vital for the screening of pollutants resistant to sulfate radical-based advanced oxidation processes. In this study, a quantitative structure-activity relationship (QSAR) model was developed to predict the values for aromatic contaminants. The relationship between logkSO4•− and three molecular descriptors (electron density, steric energy, and ratio between oxygen atoms and carbon atoms) was built through multiple linear regression. The goodness-of-fit, robustness, and predictive ability of the model were characterized statistically with indicators showing that the model was reliable and applicable. Electron density was found to be the most influential descriptor that contributed the most to logkSO4•−. All data points fell within the applicability domain, and no outliers existed in the training set. The comparison with other models indicates that the QSAR model performs well in elucidating the mechanism of the reaction between aromatic compounds and sulfate radicals.

Highlights

Sulfate radical-based advanced oxidation processes (SR-AOPs) are considered as a promising technology for the treatment of wastewater with recalcitrant organic contaminants [1]
It was assumed in this study that the highest electron density the carbon atom of the benzene ring was positively correlated with log kSO− ; i.e., a higher electron density would lead to a faster reaction rate, which is consistent with the result of the model, as the coefficient of E is positive
The stepwise multiple linear regression (MLR) was used to exclude insignificant descriptors, and the final model was composed of E, S, and oxygen atoms and carbon atoms (O/C)

Summary

Introduction

Sulfate radical-based advanced oxidation processes (SR-AOPs) are considered as a promising technology for the treatment of wastewater with recalcitrant organic contaminants [1].

Methods

Discussion

Conclusion