Statistical optimisation by combination of response surface methodology and desirability function for removal of azo dye from aqueous solution

Abstract

Traditional one by one factor analysis has some drawbacks related to time, cost, feasibility and optimisation. To overcome of these process parameters, response surface methodology (RSM) with Central Composite Design (CCD) was used in this study to evaluate the effects of main factors and their interaction for congo red (CR) removal and to derive the model optimisation by composition of all parameters in order to reduce excessive experiments. The ‘profiling and desirability function’ was also employed for the specific values of controlled parameters for optimisation and highest desirability. The use of analysis of variance (ANOVA) and ‘t’ test showed that the interactions of all studied parameters (pH, dose and concentration) on congo red (CR) dye for adsorbent (used tea leaves) have significant impact of removal %. The lack of fit test (LOF) and residual analysis were also performed for adequacy of the model. Applying desirability function, the optimal conditions of pH, adsorbent dose and initial concentration were found to be 4.32, 0.47 g, and 92.05 mg L⁻¹ corresponding to 93.46% removal for used tea leaves. Batch equilibration method was followed for the removal of CR dye for adsorbent. Langmuir adsorption isotherm was conformed well to removal data for used tea leaves.

Keywords:

• response surface methodology
• desirability function
• congo red
• used tea leaves