Decision optimization for sustainable water disinfection: Computational modelling of DBP risk, efficacy, and energy trade-offs

Disinfection is essential in water and wastewater treatment to eliminate pathogenic microorganisms and safeguard public health. However, many methods generate disinfectant byproducts (DBPs) that threaten human health and aquatic ecosystems. This review evaluates conventional technologies such as chlorination, chloramination, and ozonation alongside emerging options including ultraviolet irradiation, solar disinfection, advanced oxidation processes (AOPs), and electrochemical techniques. Each is assessed for microbial inactivation efficiency, DBP formation, operational feasibility, and environmental sustainability. Focus is placed on toxic DBPs, including trihalomethanes, haloacetic acids, and nitrosamines, recognized for carcinogenic and endocrine-disrupting effects. In addition, the impact on inorganic contaminants such as nitrate, arsenic, and heavy metals is discussed. Energy demand, chemical usage, and carbon emissions are also compared. While advanced and hybrid systems show promise in reducing DBPs and enhancing performance, they face challenges in cost, scalability, and regulatory acceptance. Sustainable disinfection requires integrated strategies balancing microbial safety, environmental protection, and resource efficiency. Future priorities include context-specific solutions, regulatory refinement, and innovation in low-impact, energy-efficient technologies for safe, sustainable water treatment. The review also highlights emerging applications of artificial intelligence, predictive modelling, and decision support systems (DSS) to optimize disinfection efficiency, minimize DBP formation, and enable smart, sustainable water treatment.