ELECTROCOAGULATION-BASED REMOVAL OF ARSENIC FROM COBALT ORE PROCESSING EFFLUENTS: AN RESPONSE SURFACE METHOD RSM OPTIMIZATION STUDY

This study investigates the removal of arsenic from leaching solutions obtained during the processing of Dashkesan cobalt ore using the electrocoagulation method. Electrocoagulation (EC) is a promising technology for the effective removal of arsenic from industrial wastewater. The influence of various process parameters (initial concentration of AsO43⁻ ions, initial and latest pH of the solution, electrolysis time, current density, amount of supporting electrolyte (NaCl), presence of other ions etc.) on the efficiency of arsenate ion removal were studied. During electrocoagulation, hydrolysis of iron ions passing the solution results in the formation of an amorphous precipitate – Fe(OH)3 coagulant. Experiments were conducted at different current and voltage values, pH levels, and time intervals. In the initial stages (U = 5.4 V, I = 0.125 A), the Fe(OH)2 and Fe(OH)3 precipitates were formed after the dissolution and hydrolysis of iron at the anode zone, which were adsorbed AsO4³⁻ ions. The optimal operating time was 20 minutes, with a current density of 10 mA/cm2 and pH = 7–8. As a result of electrocoagulation, the concentration of arsenic in the solution decreased from 0.05 g/l to 0.01 mg/l. In addition, Response Surface Methodology (RSM) was applied to statistically model and optimize the electrocoagulation process. A quadratic model was developed to describe the effects of key parameters (initial arsenic concentration, electrolysis time, and pH) and their interactions on arsenic removal efficiency. Analysis of variance (ANOVA) confirmed the significance of the model (F = 4.42, p = 0.029), with initial arsenic concentration identified as the most influential factor (p = 0.001). The RSM-based optimization predicted maximum arsenic removal efficiency of 96–99.5%, which was in excellent agreement with experimental results, confirming the adequacy of the model for process optimization and scale-up.