Recent advances and emerging trends in CFD applications for disinfection in water and wastewater treatment: A decade in retrospect

Computational fluid dynamics (CFD) is widely used to analyze and optimize water and wastewater disinfection. This targeted structured review synthesizes approximately 110 peer-reviewed studies published during 2014–2025, with selected earlier studies retained for historical context. Applications spanning UV and UV-LED reactors, chlorination, ozonation, peracetic acid (PAA), advanced oxidation processes (AOPs), and emerging systems are evaluated using a decision-oriented right-fidelity framework that links the engineering quantity of interest to model fidelity, validation evidence, dominant uncertainty, and application readiness. Major advances include multiphysics coupling of hydrodynamics with radiation, reactive transport, and gas–liquid mass transfer; higher-fidelity turbulence treatment; uncertainty-aware validation; and CFD-trained surrogate models. Direct CFD–AI evidence is currently concentrated in surrogate and optimization studies, whereas physics-informed neural networks and digital-twin applications remain emerging or prospective for disinfection. Across technologies, the dominant uncertainty is process specific: optical and dose-response assumptions for UV, matrix-dependent kinetics for chlorine and PAA, and multiphase mass-transfer closures for ozone. The review provides practitioner guidance on model selection, minimum validation requirements, current reliability limits, and evidence needed for routine design, regulatory assessment, and operational decision support.