Optimization of Nanocellulose Filter Paper from Forest Resources (Shorea Roxburghii) for Water Purification in Textile Wastewater using RSM
Keywords:Turbidity Removal, CCD, RSM, Coefficient of determination, Lack-of-fit
In this study, results of parametric effects and optimization of turbidity removal from textile wastewater using response surface methodology (RSM) based on a statistically designed experimentation via the Central composite design (CCD) are reported. A five-level, three-factor CCD was employed using initial turbidity (X1), pH (X2) and initial temperature (X3) as process variables. The RSM model predicted an optimal turbidity removal efficiency of 98.88% at conditions of X1 (75 NTU), X2 (5.5 pH) and X3 (40℃). The model was by checking the coefficient of determination, R2 (0.80) and proved to have strong effect size. The lack of fit for the model with high probability (P = 0.956) and low F-value (F = 0.19) supported the efficiency of model to predict turbidity removal percentage. X3 have a negative coefficient value which indicates the directly proportional relationship with the turbidity removal. Other two terms (X1X2) and (X1X3) shown negative coefficient as well which demonstrate the relationship between these three variables. Confirmation of experimental results was found to be close to the prediction derived from the models. This demonstrates the benefits of the approach based on the RSM in achieving good predictions while minimizing the number of required experiments.