Agent-Based model to predict the fate of the degradation of organic compounds in the aqueous-phase UV/H2O2 advanced oxidation process

Abstract

Advanced oxidation processes (AOPs) are promising water treatment technologies used to destroy trace organic compounds. Yet, the inability to predict the degradation fate of trace organic compounds due to their diverse chemical structures and potential for transformation byproducts greatly limits AOP effectiveness. Current prediction methods are time consuming and discontinuous because they rely on conventional kinetic models that often require solving ‘stiff’ ordinary differential equations numerically. In this study, we present a novel approach to AOP degradation prediction that uses an agent-based model to represent the chemical entities of individual molecular species and to simulate the movement and reactions of these entities over time in a defined space. Predicted time-dependent concentration profiles of a parent test compound, acetone, and its transformation products in UV/H2O2 AOP are shown to be consistent with our experimental observations.