Modelling and optimization of the use of green graphene oxide in the removal of lead (II) ions from wastewater using RSM-CCD :

Abstract

Background: The discharge of wastewater containing heavy metals into streams, lakes, ground water and rivers is increasing rapidly. Lead is one of the most toxic heavy metals, which is generated by a number of industries. Among the various removal technologies of heavy metals from wastewater, adsorption has gained great importance as a purification and separation technique in industrial scales. Methods: Green Graphene oxide (GGO) was synthesized by modified Hummer’s method. Its application as an excellent adsorbent for lead (II) removal was also demonstrated using response surface methodology (RSM) using Central composite design (CCD). The effects of five independent variables; adsorbent dose, initial lead ion concentration, and temperature and contact time on the lead (II) removal efficiency were investigated and the process was optimized using RSM. Using central composite design (CCD), 52 experiments were carried out and the process response was modeled using a quadratic equation as function of the variables. Results: The optimum values of the variables were found to be 1.2879g/l, 147.2727ppm, 59.6465 minutes, 34.54550C and 6.5253 for adsorbent dosage, lead (II) initial concentration, contact time, temperature and pH, respectively. Using RSM-CCD approach, a quadratic regression model was generated to demonstrate the relationship between removal efficiency (RE) and factors of Adsorbent dose (A), initial ion concentration (B), contact time (C), temperature (D)and pH (E). Conclusions: The significance of each of the model term was evaluated using the probability of error value (P values) and R-sq. P-values less than 0.050 showed that the terms were significant. The model was adequate with 0.8066 R-sq. and 0.000 P-value. Recommendations: The synthesized GO desires characterization with respect to functional groups, structure and morphology. Adsorption isotherms and kinetics studies need to be further conducted to understand the adsorption mechanism. Use of other optimization techniques like artificial intelligence and Taguchi methods need to be compared with RSM-CCD. The possibility of using blended sugarcane bagasse and rice straw to enhance efficiency should be investigated. Keywords: Green Graphene oxide, Adsorption, Lead (II) ions, Modelling, Optimization, Response Surface Methodology and Central composite design