PREDICTION OF BY-PRODUCT FORMATION DURING CHLORINE DIOXIDE DISINFECTION: FROM STATISTICAL TO HYBRID MODELS
DOI:
https://doi.org/10.20535/2218-930012026359443Keywords:
drinking water treatment, chlorine dioxide disinfection, chlorite formation, disinfection byproducts, adaptive dosing, response surface methodology, hybrid modelsAbstract
Safe drinking water supply remains one of the most critical humanitarian challenges facing Ukraine amid ongoing armed conflict. Destruction of water infrastructure, combined with deteriorating source water quality has created an urgent need for adaptive, scientifically grounded disinfection management tools. Chlorine dioxide offers significant advantages over conventional chlorination, including efficacy across a wide pH range, biofilm disruption capacity and absence of carcinogenic trihalomethanes. However, chlorine dioxide disinfection generates specific oxidation byproducts (primarily chlorites and chlorates) whose combined concentration is strictly limited under national and European regulations, creating a fundamental technological paradox between guaranteed pathogen inactivation and byproduct minimization. Presented study develops an integrated computer modelling framework for chlorine dioxide disinfection byproduct prediction and control. A hybrid model architecture was proposed as the foundation for an adaptive SCADA-integrated dosing system capable of real-time chlorine dioxide adjustment based on continuous water quality sensor inputs. A five-factor central composite rotatable design (pH, temperature, chlorine dioxide dose, contact time, total organic carbon) was implemented to build second-order polynomial response surface models for two target responses: the fraction of consumed chlorine dioxide as a measure of disinfection efficiency and chlorite concentration in treated water. Analysis of regression equations revealed the pH as the dominant factor controlling chlorite formation, with the free term of the chlorite formation model approaching the regulatory limit at average operating conditions, confirming that passive parameter maintenance cannot guarantee regulatory compliance. Multi-criteria optimization using the Harrington desirability function identified the optimal operating regime: pH 6.0, temperature 25 °C, chlorine dioxide dose 6.0 mg/dm3, contact time 18.2 hours, TOC ≤ 10 mg/dm3. A Pareto frontier analysis structured the full set of optimal trade-off solutions into three operational modes, providing water utilities with a flexible decision-making tool adaptable to current epidemiological priorities. Monte Carlo stochastic simulation quantified seasonal risk differentiation, demonstrating that pH reduction is a more effective control lever than dose reduction for maintaining chlorite compliance under summer source water conditions.
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