Optimizing coagulation-flocculation processes with aluminium coagulation using response surface methods

A data-based multivariate method such as response surface methods and desirability function is considered advantageous for analysing coagulation treatment optimization. Thus, this study investigated the optimization of coagulation-flocculation using response surface methodology. The parameters investigated were pH, alum dose and alkalinity. The optimum coagulation conditions for the individual responses: turbidity, colour, residual aluminium and phenanthrene were pH 7.0, alum dose 80.0 mg/L and alkalinity 80.0 mg/L; pH, 6.5, alum dose 70.0 mg/L and alkalinity 90.0 mg/L; pH, 7.0, alum dose 63.2 mg/L and alkalinity 80.0 mg/L and pH 6.2, alum dose 80.0 mg/L and alkalinity of 80.0 mg/L, respectively. The model equation derived from the optimization study was adequate for predicting the response values. The quadratic model was significant (p < 0.0001), and it had a high correlation (R2, 0.746-0.975) and an insignificant (LOF, p > 0.05) lack of fit.

Automated summary

This study optimized the coagulation-flocculation treatment using response surface methodology. The results showed that specific pH, alum dose, and alkalinity conditions led to the best treatment performance. The derived model equation was able to accurately predict the response values.