Abstract
This study investigates the operational performance and optimization of a real greywater treatment system utilizing aluminum (Al)-based electrocoagulation (EC). The EC process was systematically evaluated and optimized through Response Surface Methodology (RSM) using the Box-Behnken Design (BBD), focusing on three critical parameters: pH, current density, and electrolysis time. Greywater samples collected from domestic sources were characterized by key physicochemical parameters including pH, COD, TSS, turbidity-ty, and electrical conductivity. The electrochemical treatment was conducted using a batch reactor equipped with Al electrodes in a monopolar configuration. Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), X-ray Diffraction (XRD), and Fourier-Transform Infrared Spectroscopy (FTIR) were employed to characterize both the electrodes and the generated sludge. Results revealed a maximum COD removal efficiency of 86.34% under optimized conditions, with current density being the most influential factor, followed by its significant interaction with pH. The developed quadratic model exhibited high predictive accuracy (R(2) = 0.96) and revealed significant nonlinear and interaction effects among the parameters. Sludge characterization confirmed the presence of amorphous aluminum hydroxide and oxyhydroxide phases, indicating effective coagulant generation and pollutant capture. The treated greywater met physicochemical criteria for non-potable reuse, such as agricultural irrigation, supporting resource recovery objectives. These findings demonstrate that EC is a low-waste, chemically efficient, and scalable process for decentralized wastewater treatment, aligning with the goals of sustainable chemical engineering.