New solution for predicting the removal efficiency of organic contaminants by UV/ H2O2: From a case study of 1H-benzotriazole

Abstract

Rapid prediction of the removal efficiency and energy consumption of organic contaminants under various operating conditions is crucial for advanced oxidation processes (AOPs) in industrial application. In this study, 1H-Benzotriazole (BTZ, CAS: 95-14-7) is selected as a model micropollutant, a validated incorporated Computational Fluid Dynamics (CFD) model is employed to comprehensively investigate the impacts of initial concentrations of H2O2, BTZ and dissolved organic carbon (DOC) (i.e., [DOC]0, [BTZ]0 and [DOC]0), as well as the effective UV lamp power P and volumetric flow rate Qv. Generally, the operation performance depends on [DOC]0 and [BTZ]0 in similar trends, but with quantitatively different ways. The increase in [H2O2]0 and P/Qv can promote •OH generation, leading to the elimination of BTZ. It is worth noting that P/Qv is found to be linearly correlated with the removal order of BTZ (ROBTZ) under specific conditions. Based on this finding, the degradation of other potential organic contaminants with a wide range of rate constants by UV/H2O2 is further investigated. A model for predicting energy consumption for target removal rates of organic pollutants is established from massive simulation data for the first time. Additionally, a handy Matlab app is first developed for convenient application in water treatment. This work proposes a new operable solution for fast predicting operation performance and energy consumption for the removal of organic contaminants in industrial applications of advanced oxidation processes.