Refined kinetic analyses of micropollutant degradation by UV-AOPs incorporating dynamic oxidant decay

Experimental data regression and model analyses of micropollutant (MP) degradation kinetics in ultraviolet-based advanced oxidation processes (UV-AOPs) typically assume a constant fluence-based pseudo-first-order rate constant (k'). However, oxidant decay continuously disrupts steady-state concentrations of reactive radicals and repeatedly establishes new equilibria, making k' vary over time-an error source that has not been rigorously assessed. Here, we evaluated these errors and developed refined kinetic analysis methods. Second-order polynomial regression analysis was proposed to quantify both initial and real-time k' values, demonstrating superior accuracy to conventional linear regression analysis, particularly for fast-decaying oxidants (e.g., free chlorine), UV-resistant MPs, and complex water matrices. Furthermore, we established a refined steady-state approximation (rSSA) model incorporating dynamic oxidant decay, which demonstrated enhanced prediction accuracy than the conventional steady-state approximation model. For instance, in a secondary sedimentation effluent at a photon fluence of 1.47 × 10⁻² einstein m^-2, the relative error of model-predicted primidone removal by UV/free chlorine reduced from 98.3% to 12.6%. Additionally, relative deviation framework identified scenarios that violate the constant k' assumption, providing guidance for the selection of kinetic analysis methods. These advancements provide a robust foundation for rigorous experimental design and kinetic interpretation, offering potential value for more rational and energy-efficient operation of UV-AOPs.