Free chlorine removal from industrial wastewater using activated carbon filtration requires accurate modeling and optimal control to balance treatment efficiency and adsorbent consumption. In this study, a combined experimental–machine learning–optimization framework was developed to predict and optimize residual chlorine concentration in a pilot-scale activated carbon filtration unit. A total of 200 experimental runs were collected using a pilot activated carbon filtration system by varying flow rate, initial chlorine concentration, pressure, pH, temperature, and carbon dose. Two ensemble learning models, Random Forest (RF) and Gradient Boosting (GB), were trained and validated using five-fold cross-validation. Both models exhibited high predictive accuracy, with GB outperforming RF on the full dataset (R² = 0.9995, Root Mean Square Error (RMSE) = 0.0355 mg·L⁻¹, Mean Absolute Error (MAE) = 0.0276 mg·L⁻¹) and on the independent test set (R² = 0.9417). Feature importance and partial dependence analyses revealed that the initial chlorine concentration and activated carbon dose were the dominant controlling variables, while increasing flow rate led to higher residual chlorine levels. A multi-objective optimization strategy based on Pareto dominance was implemented using the trained GB model as a surrogate to simultaneously minimize residual chlorine and carbon consumption. The optimal compromise solution corresponded to an activated carbon dose of approximately 51.5 kg and a residual chlorine concentration of 0.156 mg·L⁻¹ at a flow rate of 43.1 m³·h⁻¹. The proposed framework demonstrates a reliable and cost-effective approach for predictive control and sustainable optimization of dechlorination processes in industrial wastewater treatment.

The aim of this work is to study the radical copolymerization of acrylonitrile with 1-chloro-3-piperidin-2-propylacrylate and to study the structure and properties of the synthesized copolymers. Ammonium persulfate was used as the radical initiator. Water and dimethylformamide were used as solvents. Under these conditions the process proceeds heterogeneously in water, and homogeneously with high speed in dimethylformamide. The synthesis rate of the 1-chloro-3-piperidino-2-propylacrylate and acrylonitrile copolymers increases with increasing temperature in the studied solvents. Experimental studies have shown that copolymerization does not proceed in the absence of the initiator and this indicates a radical nature of the reaction. The structure of synthesized compounds was confirmed by IR spectral analyses. The participation of multiple bonds of both monomers during copolymerization was determined. The composition of copolymers has been determined which indicates that the copolymer formed at early stages is enriched with 1-chloro-3-piperidino-2- propylacrylate units. The values of the monomers relative activities were calculated by Feinemann-Ross method. The found values of copolymerization constants are r1=0.28, r2=0.62 and the constant value of the copolymerization product is less than unity proving both types of formed polymer radicals react much faster with foreign monomer than with their own.