Analysis and Optimization of Coagulation Efficiency for Brackish Water Reverse Osmosis Brine Based on Ensemble Approach

Abstract

Reuse of wastewater through brackish water reverse osmosis presents a major challenge due to the generation of brine, which contains organic and inorganic compounds to be removed. This study focuses on analyzing and optimizing coagulation conditions for brackish reverse osmosis brine treatment by evaluating pollutant removal efficiencies under various scenarios and leveraging advanced modeling techniques. Jar tests were performed using polyaluminum chloride and ferric chloride, evaluating the removal of total organic carbon, turbidity, UV524, and phosphorus. Models were developed using response surface methodology, support vector machines, and random forest. Although the same data sets were used, the characteristics of these models were found to be different: Response surface methodology delivered high-fidelity, smooth response surfaces (R2 > 0.92), support vector machine pinpointed sharp threshold regions, and random forest defined robust operating plateaus. By overlaying model-specific optimum contours, the consensus regions were identified for reliable removal across total organic carbon, turbidity, and phosphate. This ensemble strategy enhanced predictive reliability and provided a comprehensive decision-support tool for multi-objective optimization. The findings underscore the potential of ensemble-based modeling to improve the design and control of brackish reverse osmosis brine treatment processes, offering a data-driven pathway for addressing one of the most critical bottlenecks in wastewater reuse systems.