Author(s)

MUHAMMAD USAMA SALIM GANDAPUR, MUHAMMAD RAZA UL MUSTAFA, HIFSA KHURSHID, MOHAMED HASNAIN ISA

Abstract

Increasing concerns over industrial wastewater contamination, particularly related to oil and grease pollutants, necessitate the development of sustainable treatment solutions. This study investigates the application of the response surface methodology (RSM) for designing experiments for the removal of oil and grease in wastewater. Optimizing the set of runs through RSM modelling can reduce the number of experiments, which ultimately helps to save time and reduce the cost of experiments. Three parameters (i.e., contact time, dosage and pH) were selected for the design of experiments. A total of 17 experimental runs were obtained using RSM with parametric ranges of contact time 25 to 125 min, pH of 3 to 9 and dosage of 0.15 g/L to 0.45 g/L. Batch tests were performed to obtain adsorption capacity and these data were used in RSM to obtain optimum values of the parameters. The batch experimental results demonstrated that the adsorption capacities range between 24.44 to 109.33 mg/g. The developed RSM predictive model produced adjusted R² = 0.946 and predicted R² = 0.926, which reflects significant and good agreement. Optimal conditions were identified as pH 6, contact time of 44 mins and oil palm leaves activated carbon dosage of 0.15 g/L, achieving a maximum adsorption capacity of 110.661 mg/g. The findings reflected the successful application of RSM to obtain appropriate parameters for the optimum removal of oil and grease from wastewater.

Keywords

activated carbon, adsorption, response surface methodology, optimization, oil palm leaves