Process Optimization for Arsenic Adsorption onto Natural Zeolite Incorporating Metal Oxides by Response Surface Methodology

Abstract

Arsenic (As) adsorption onto metal oxide-precipitated clinoptilolite was investigated by using response surface methodology (RSM). Box-Behnken experimental design combined with RSM was used to examine and to optimize major process parameters. The quadratic statistical model was defined by three independent variables namely, pH (3-7), temperature (25-65 degrees C), and initial arsenate (As(V)) concentration (0.5-9.5 mg L-1) while adsorption capacities of modified zeolites were designated as dependent variables. The iron oxide-precipitated zeolite (ZNa-Fe) was found to be more effective adsorbent when compared with aluminum oxide-modified one (ZNa-Al). The maximum As(V) adsorption capacities for ZNa-Fe and ZNa-Al were observed at pH 3.0 and pH 4.96, respectively. In the chosen range, higher adsorption capacities were achieved with increasing temperature, indicating the endothermic behavior of process for both samples. Initial As(V) concentration had a marked favorable effect on the amount of As(V) adsorbed onto adsorbents in the selected field. The constructed polynomial model was found significant, as was evident from the model F values (FZNa-Fe=414.95 and FZNa-Al=167.17). The coefficients of determination values of second-order polynomial regression models were found as 0.9981 and 0.9953 for ZNa-Fe and ZNa-Al, respectively, indicating the accuracy and general availability of the model.