4.7 Article

Quantitative structure -activity relationship models for predicting singlet oxygen reaction rate constants of dissociating organic compounds

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 735, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2020.139498

Keywords

Reaction rate constants; Singlet oxygen (O-1(2)); Quantitative structure-activity relationship; Dissociating organic compounds; Multiple linear regression (MLR)

Funding

  1. National Natural Science Foundation of China [21976027, 51808252, 21607022]
  2. Jilin Scientific and Technological Development Program [20190103145JH, 20180520078JH]
  3. Fundamental Research Funds for the Central Universities [2412019FZ019]
  4. Brook Byers Institute for Sustainable Systems at the Georgia Institute of Technology
  5. Hightower Chair at the Georgia Institute of Technology
  6. Georgia Research Alliance at the Georgia Institute of Technology

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As singlet oxygen (O-1(2)) is ubiquitous in the environment, O-1(2)-involved oxidation may play an important role in the transformation and fate of organic pollutants. Accordingly, the reaction rate constants (k(1O2)) of organic compounds with O-1(2) are important to determine the environmental fate and persistence assessment of organic pollutants. However, currently there are limited k(1O2) data available, especially for organic chemicals with different charged (deprotonated/protonated) forms. Herein three quantitative structure-activity relationship (QSAR) models (one comprehensive model and two models for neutral and deprotonated molecules) were created for predicting aqueous k(1O2) values for diversely dissociating molecules. The models include larger datasets (180 chemicals) and have wider applicability domain than previous ones. Molecular structural characteristics (only half-wave potential is present in both models) determining the O-1(2) reaction rate of neutral and deprotonated molecules vary greatly. The comparison results of predicting k(1O2) values of organic compounds at certain pH conditions show that the combination of the QSAR models for neutral and deprotonated molecules has advantages over the comprehensive QSAR model. This work is the first study to predict k(1O2) for a wide variety of neutral and deprotonated molecules and provides an important tool for assessing the fate of organic pollutants in aquatic environments.

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