The environmental risk of heterogeneous oxidation is unneglectable: Time-resolved assessments beyond typical...

The safety of advanced oxidation processes is paramount, surpassing treatment efficiency concerns. However, current research is limited to the qualitative toxicity investigations of targeted contaminants by-products, while the detoxification effects of heterogeneous advanced oxidation processes are largely unknown. Here we propose an environmental risk assessment that distinguishes between preferred oxidation pathways of the detoxification effects, thereby selecting the most suitable treatment system for each contaminant. Through environmental risk analyses based on the by-product quantification, >40 % of previously overlooked toxicity has been rediscovered, significantly improving the accuracy of contaminant detoxification evaluation. The by-products contributed risk mostly reached the maximum after 30 min of reaction, evenly distributed on aquatic indicators but largely originated from on radical oxidation pathways. Density functional theory is applied to determine the generation probability of isomers, and deep neural network regression modelling accelerated derivation on structural transformation of toxic molecules. Furthermore, an evaluation system is established using risk quotients and cluster analysis classification modelling, enabling the quantitative cross-comparison in oxidation systems. This approach enhances the understanding of the safety and efficiency within oxidation processes, introducing various new methods supporting quantitative environmental risk assessment of emerging contaminant degradation in complicated heterogeneous oxidation processes. SYNOPSIS: The environmental risks in advanced oxidation processes are quantified by deep learning and theoretical chemistry-assisted assessments.