Recovery of sulphate from industrial wastewater in the form of strontium sulphate and optimisation using hybrid metaheuristic approach: RSM-GA and RSM-PSO

Large quantities of inorganic salts from process effluent are inevitable and a threat to the environment. Sulphates were the major anions (initial concentration = 70 g/L) in pigment industry effluent. Strontium ions could recover the sulphate by precipitation as SrSO₄, a commercially useful precipitate. The stoichiometric ratio of precipitant, mixing, and temperature were optimised by response surface methodology (RSM) and the precipitant ratio had the maximum influence (Sensitivity 99.62%). The model created by RSM showed notable performance (predicted R² = 0.9987). Further enhancement of optimisation was done by coupling RSM with a genetic algorithm (GA) and particle swarm optimisation (PSO). Both of them were able to determine the global optima efficiently when their hyper-parameters were optimised. In GA, the crossover ratio was higher than the mutation ratio. PSO converged close to 20 iterations, exhibiting better exploration and exploitation capacity. The optimised values of stoichiometric ratio (1.35), temperature (30.7°C), and mixing speed (230 rpm) were validated experimentally, which gave 99.95% sulphate utilisation. The precipitation reaction followed first-order kinetics (R² = 0.9908) and was majorly dependent on precipitant concentration. Preliminary cost estimation with Aspen showed that chemical precipitation could be an employable option for utilising high levels of sulphate from wastewater.