AI Summary & Key Takeaways
AI InsightANOVA results showed that the responses of model have high coefficient values (R2 > 0.80), and hence the second order regression model can be explained with these experimental data.
📌 3 Key Takeaways
Abstract
In this study, coagulation processes using FeCl36H2O and Al2(SO4)318H2O as coagulants were employed and designed for chemical oxygen demand (COD) and total suspended solids (TSS) removal from food industry wastewater via response surface methodology (RSM). RSM was used for the optimization of coagulation processes and evaluation of the effects and interactions between process variables (pH, coagulant dosage and reaction time). ANOVA was used to analyze the experimental data obtained in the study and secondary regression models were developed by using Statgraphics Centurion XVI.I software. The optimum conditions were pH 9, dosage 1500 mg/L and time 25 min for maximum COD removal efficiency for FeCl36H2O and pH 9, dosage 1493 mg/L and time 25 min for Al2(SO4)318H2O. Under optimum conditions, COD and TSS removal efficiencies were 46.4% and 96.7% for FeCl36H2O and 31.2% and 96.2% for Al2(SO4)318H2O, respectively. ANOVA results showed that the responses of model have high coefficient values (R2 > 0.80), and hence the second order regression model can be explained with these experimental data. The proposed model fits very well with the experimental data with R2 of 0.9677 for COD and 0.9543 for TSS removal for FeCl36H2O and 0.9456 for COD and 0.9260 for TSS removal for Al2(SO4)318H2O, respectively. Model results showed that the RSM for coagulation processes using both coagulants is a powerful tool for optimizing the experimental conditions. Moreover, it can be concluded that both coagulation processes may be an effective alternative pre-treatment process for food industry wastewater.