Temperature dependence of the relative rate constants of the reactions of alkanes with oh radicals in aqueous solution

Full-scale comparison of UV/H2O2 and UV/Cl2 advanced oxidation: The degradation of micropollutant surrogates and the formation of disinfection byproducts

The photolysis of chlorine by UV light leads to the formation of the hydroxyl radicals (OH) as well as reactive chlorine species (RCS) that can be effective as advanced oxidation processes (AOPs) for water treatment. Much of the research to date has been done at laboratory- or bench-scale. This study reports results from a model that demonstrates that the relative effectiveness of the UV/Cl₂ AOP compared to the more traditional UV/H₂O₂ AOP is a function of optical path length. As such, the relative effectiveness of the two treatment options evaluated at small scale may not reflect the relative performance at full-scale, making results previously obtained at small-scale potentially less scalable. This study therefore compares the performance of UV/Cl₂ to UV/H₂O₂ at a full-scale water treatment plant, using sucralose and caffeine as spiked surrogates for contaminants that are reactive solely to OH radicals, and to both OH and RCS, respectively. pH was varied between 6.5 and 8.0. The results demonstrated that when using a medium pressure UV lamp, UV/Cl₂ might lead to approximately twice the production of OH radicals as UV/H₂O₂ at pH 6.5 when using the same molar oxidant concentration, but adding chlorine to the UV reactor at pH 8.0 had a negligible impact on OH radical concentration in comparison to UV alone. The study also confirmed previous small-scale results that RCS can be a major contributor to UV/Cl₂ treatment for compounds such as caffeine that are susceptible to RCS, with UV/Cl₂ effective at both pH 6.5 and 8.0 for such compounds. Disinfection byproducts were monitored, with adsorbable organohalide (AOX) formation increasing by approximately 10 μg-Cl/L due to chlorine photolysis, but only at pH 6.5 and not at pH 8.0. This implies that UV/Cl₂ might increase AOX mostly due to reaction between OH and organic precursors to make them more reactive with chlorine, and not due to RCS. The formation of specific DBPs of current or emerging regulatory interest was minimal under all conditions, except for chlorate. Chlorate yields were in the order of 6-18% of the photolysed chlorine.

Modeling the pH and temperature dependence of aqueousphase hydroxyl radical reaction rate constants of organic micropollutants using QSPR approach

Designing of advanced oxidation process (AOP) requires knowledge of the aqueous phase hydroxyl radical (^●OH) reactions rate constants (k _OH), which are strictly dependent upon the pH and temperature of the medium. In this study, pH- and temperature-dependent quantitative structure-property relationship (QSPR) models based on the decision tree boost (DTB) approach were developed for the prediction of k _OH of diverse organic contaminants following the OECD guidelines. Experimental datasets (n = 958) pertaining to the k _OH values of aqueous phase reactions at different pH (n = 470; 1.4 × 10⁶ to 3.8 × 10¹⁰ M^-1 s^-1) and temperature (n = 171; 1.0 × 10⁷ to 2.6 × 10¹⁰ M^-1 s^-1) were considered and molecular descriptors of the compounds were derived. The Sanderson scale electronegativity, topological polar surface area, number of double bonds, and halogen atoms in the molecule, in addition to the pH and temperature, were found to be the relevant predictors. The models were validated and their external predictivity was evaluated in terms of most stringent criteria parameters derived on the test data. High values of the coefficient of determination (R ²) and small root mean squared error (RMSE) in respective training (> 0.972, ≤ 0.12) and test (≥ 0.936, ≤ 0.16) sets indicated high generalization and predictivity of the developed QSPR model. Other statistical parameters derived from the training and test data also supported the robustness of the models and their suitability for screening new chemicals within the defined chemical space. The developed QSPR models provide a valuable tool for predicting the ^●OH reaction rate constants of emerging new water contaminants for their susceptibility to AOPs.