Arsenic removal from solution using nano-magnetic compound: optimization modeling by response surface method.

Abstract

This study was aimed to investigate the effectiveness of compounds containing iron and manganese to reduce the mobility of arsenic and its effective adsorption and optimize the arsenic adsorption process by CCD. In this study, MnFe2O4 nanoparticles (MFO-n) were synthesized using the co-precipitation method to remove arsenic and reduce its toxicity in solution. Several tests including Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), X-ray fluorescence (XRF), and Brunauer-Emmett-Teller (BET) tests were used to characterize the synthesized MFO-n. To model and optimize the As adsorption process using the response surface methodology, four independent variables affecting the efficiency of arsenic adsorption were investigated. These variables including pH (3 to 11), concentration of arsenic in solution (1000 to 4000µg/L), concentration of nanoparticles (1 to 5g/L), and time (15 to 195min) were investigated. The central composite design (CCD) approach was used to design the experiments and optimize the model parameters. The variance analysis indicated that the prediction of As adsorption from solution by the synthesized nanoadsorbent using the CCD model was well performed (p < 0.0001) with high accuracy (R2 = 0.97). The results further indicated that the optimum quantity of pH, concentration of nanoparticles, time, and initial concentration of As are 5, 2g/L, 60min, and 3250µg/L, respectively. The highest As elimination from the solution was estimated to be 94.77%. Our results further indicated that MFO-n had high efficiency in eliminating both toxic arsenic species from the solution.