Process optimization studies of Congo red dye adsorption onto cashew nut shell using response surface methodology

Background: High cost of commercially available activated carbon increases the treatment cost. Hence, no-cost or low-cost, alternate adsorbents are the current thirst in this area of research. The limitations of conventional methods of experimentation can mislead the optimum operating conditions. The present investigation mainly deals with utilization of the low-cost, agricultural waste adsorbent, cashew nut shell, and the determination of the optimum conditions for Congo red dye removal from an aqueous solution using response surface central composite design methodology. Results: The adsorbent, cashew nut shell, can remove the Congo red dye completely from the aqueous solution. The parameters pH, adsorbent dose, initial dye concentration, time, and temperature considered for this investigation play an important role in the adsorption studies of Congo red dye removal. The optimum values of pH, adsorbent dose, initial dye concentration, time, and temperature were found to be 3.2, 24.76 g/L, 20 mg/L, 67 min, and 30°C for complete removal of Congo red dye, respectively. The experimental values were in good agreement with predicted values. Conclusions: Adsorption of Congo red dye from an aqueous solution with a low-cost adsorbent prepared from an agricultural waste was studied to determine the potential use of this adsorbent for complete removal of the dye. Batch studies were performed to address the influence of various parameters such as pH, adsorbent dose, initial dye concentration, time, and temperature. Response surface central composite design methodology was used to find the interaction among the variables and to determine the optimum conditions towards the adsorption of dye from the aqueous solution. The optimum values of pH, adsorbent dose, initial dye concentration, time, and temperature were found to be 3.2, 24.76 g/L, 20 mg/L, 67 min, and 30°C for complete removal of Congo red dye, respectively. The experimental values were in good agreement with predicted values.