Adsorptive removal of arsenic by novel iron/olivine composite: Insights into preparation and adsorption process by response surface methodology and artificial neural network. (1st March 2018)

• Record Type: Journal Article
• Authors: Ghosal, Partha S.; Kattil, Krishna V.; Yadav, Manoj K.; Gupta, Ashok K.
• Is Part Of: Journal of environmental management. Volume 209(2018)
• Page Start: 176
• Page End: 187
• Publication Date: 2018-03-01
• Subjects: Arsenic removal -- 32 factorial design -- Response surface method -- Iron impregnated olivine -- Artificial neural network -- Isotherm and kinetic model; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2017.12.040
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Olivine, a low-cost natural material, impregnated with iron is introduced in the adsorptive removal of arsenic. A wet impregnation method and subsequent calcination were employed for the preparation of iron/olivine composite. The major preparation process parameter, viz., iron loading and calcination temperature were optimized through the response surface methodology coupled with a factorial design. A significant variation of adsorption capacity of arsenic (measured as total arsenic), i.e., 63.15 to 310.85 mg/kg for arsenite [As(III) T ] and 76.46 to 329.72 mg/kg for arsenate [As(V) T ] was observed, which exhibited the significant effect of the preparation process parameters on the adsorption potential. The iron loading delineated the optima at central points, whereas a monotonous decreasing trend of adsorption capacity for both the As(III) T and As(V) T was observed with the increasing calcination temperature. The variation of adsorption capacity with the increased iron loading is more at lower calcination temperature showing the interactive effect between the factors. The adsorbent prepared at the optimized condition of iron loading and calcination temperature, i.e., 10% and 200 °C, effectively removed the As(III) T and As(V) T by more than 96 and 99%, respectively. The material characterization of the adsorbent showed the formation of the iron compound in the olivine and increase in specific surface area to the tune of 10 multifold compared to the base material, which is conducive to the enhancement of the adsorption capacity. An artificial neural network was applied for the multivariate optimization of the adsorption process from the experimental data of the univariate optimization study and the optimized model showed low values of error functions and high R 2 values of more than 0.99 for As(III) T and As(V) T . The adsorption isotherm and kinetics followed Langmuir model and pseudo second order model, respectively demonstrating the chemisorption in this study. Graphical abstract: Image 1 Highlights: Olivine is introduced first time for adsorptive removal of pollutant. Impregnation of iron and calcination enhance the adsorption potential of olivine. Iron/olivine composite was effectively used for arsenic removal. Response surface methodology was used to optimize preparation process parameters. Artificial neural network was used to model adsorption process.