4.7 Article

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

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 835, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2022.155501

关键词

Ionic; non-ionic compounds; Ozonation; Reaction rate constant; Quantitativestructure-activity relationship; Partial least squares (PLS)

资金

  1. National Natural Science Foundation of China [21976027, 21976026, 42130705, 41877364, 21607022]
  2. Fundamental Research Funds for the Central Universities [2412019FZ019]
  3. Jilin Province Science and Technology Develop-ment Projects [20180520078JH, 20200301012RQ]

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In this study, two quantitative structure-activity relationship models were developed for non-ionic and ionic species to predict their reaction rate constants with ozone. These models showed good predictive performance and applicability and can be used to estimate the conversion rate of pollutants by ozone in urban sewage and drinking water treatment.
Ozonation isa significant technology for the mitigation of pollutants in water. The second-order reaction rate constant (k(O3)) of ozone (O-3) 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 experi-mental k(O3) values. Moreover, the reactivity of ionizable compounds with different ionization forms toward O-3 may dif-fer 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: R-tr(2) > 0.760; ionic model: R-tr(2) > 0.780), robustness (Q(CUM)(2)> 0.700), predictive performance (non-ionic model: R- ex t(2)> 0.760; ionic model: R-ex t(2)> 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 molec-ular structures in two datasets and different reactivities of uncharged and charged states toward O-3. Additionally, the overall kO3 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 O-3 in the urban sewage and drinking water treatment.

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