Use of response surface methodology in the optimization of coagulation-flocculation of wastewaters employing biopolymers

The aim of this work was to optimize the coagulation-flocculation (CF) process applied to municipal wastewaters (WW). Optimization of CF was performed to minimize chemical oxygen demand (COD), turbidity, sludge produced, and some metals in sludge. A Box-Behnken design was used to evaluate the effects and interactions of three factors such as type of biopolymer (guar, mesquite seed gum and Opuntia mucilage), dose of biopolymer (25, 50 and 75 mg/L) and initial organic load of wastewaters WW (725, 1,425 and 1,325 mg COD/L). Regarding the statistical analysis, Results were assessed with various descriptive statistics such as p value, lack of fit (F-test), coefficient of R² determination and adequate precision (AP) values. p values <0.05 demonstrates that the model for those response variables were significant at the 95% confidence level. The PLOF values > 0.05 show that the F-statistics was insignificant implying significant model correlation between the variables and process responses. Regarding the fit of the model, the obtained R² values were up to 0.98 for sludge produced, 0.94 for COD removal, 0.91 for Cd, 0.90 for turbidity removal, and 0.75 for sludge density. It is noteworthy that response surface methodology (RSM) also allowed optimizing de CF process. Employing this methodology it is feasible to determine COD, turbidity, and salts removals, as well as the amount and quality of the produced sludges under hypothetical conditions within predetermined parameter ranges, without the need of carrying out experimental runs.