Theoretical modeling and performance optimization for the treatment of ferric- and manganese-contaminated groundwater by flow-electrode capacitive deionization

Abstract

Coastal regions face increasing threats from rising sea levels, exacerbating groundwater contamination by salinity and heavy metal pollutants. This study presents a novel integration of theoretical modeling and experimental validation to optimize flow-electrode capacitive deionization (FCDI) for the removal of iron (Fe³⁺) and manganese (Mn²⁺) from groundwater. Unlike previous studies focusing solely on empirical approaches, this study develops and validates a comprehensive theoretical framework that accurately predicts specific energy consumption (SEC) and key energy loss mechanisms in FCDI. The model aligns closely with experimental results, confirming its reliability for system optimization. The first application of an optimized FCDI system tailored to Jakarta’s groundwater conditions was demonstrated through parameter optimization, achieving high removal efficiencies of up to 94 % for Fe³⁺ and Mn²⁺. Optimal operational conditions—17 wt% flow-electrode mass loading, a flow-electrode flow rate of 45 mL/min, and a feed flow rate of 5 mL/min—were determined to minimize SEC (0.171–0.398 kWh/gion), positioning FCDI as an energy-efficient alternative to conventional groundwater treatment technologies. This study not only advances the practical application of FCDI for dual contamination challenges in brackish and fresh groundwater but also establishes a generalizable modeling approach for optimizing FCDI performance across diverse water matrices. The findings provide a critical step toward scalable and sustainable electrochemical water treatment solutions for coastal regions facing similar contamination challenges.