Predicting reaction rate constants of ozone with ionic/non-ionic compounds in water

Abstract

Ozonation is a significant technology for the mitigation of pollutants in water. The second-order reaction rate constant (k_O3) of ozone (O₃) with compounds is essential for measuring their reactivity toward O₃ and understanding their fate during ozonation. However, there is a huge gap between the number of existing chemicals and the available experimental k_O3 values. Moreover, the reactivity of ionizable compounds with different ionization forms toward O₃ may differ greatly. In this study, two quantitative structure activity relationship (QSAR) models for non-ionic and ionic species, are respectively established with partial least squares (PLS) and support vector machine (SVM) methods based on the large datasets (324 non-ionic states and 188 ionic states). These models exhibit good fitting ability (non-ionic model: R²_tr > 0.760; ionic model: R²_tr > 0.780), robustness (Q²_CUM > 0.700), predictive performance (non-ionic model: R²_ext > 0.760; ionic model: R²_ext > 0.810) and wide applicability domain. The molecular parameters in two models are revealed to be significantly different, which may be attributed to the significant difference in molecular structures in two datasets and different reactivities of uncharged and charged states toward O₃. Additionally, the overall k_O3 for compounds at certain pH can be estimated by combining the two single QSAR models. These models and methods can become the effective tools for predicting the conversion rate of pollutants by O₃ in the urban sewage and drinking water treatment.