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Methyl Tertiary-Butyl Ether Adsorption by Bioactivated Carbon From Aqueous Solution: Kinetics, Isotherm and Artificial Neural Network Modeling Publisher



Fatehizadeh A1, 2 ; Zare MR3 ; Van Ginkel SW4 ; Taheri E1, 2 ; Amin MM1, 2 ; Rafiei N1, 2 ; Mahdavi M5, 6
Authors
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Authors Affiliations
  1. 1. Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. Environment Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
  3. 3. Department of Environmental Health Engineering, School of Health, Larestan University of Medical Sciences, Larestan, Iran
  4. 4. School of Civil and Environmental Engineering, Georgia Institute of Technology, 200 Boddy Dodd Way, Atlanta, 30332, GA, United States
  5. 5. Social Determinates of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran
  6. 6. Student Research Committee of Saveh University of Medical Sciences, Saveh, Iran

Source: Desalination and Water Treatment Published:2019


Abstract

The present study evaluated fabrication of bioactivated carbon (BAC) from waste activated sludge (WAS) for methyl tert-butyl ether (MTBE) removal from aqueous solution. BACs were prepared using KOH, H3PO4, and ZnCl2 as chemical activation reagents, followed by thermal activation. Batch experiments with different BAC types and dosages, solution pH, initial MTBE concentrations, and contact times were conducted to investigate the BAC effectiveness. The obtained data were analyzed using the kinetics and isotherm model and also with artificial neural network (ANN). The result of Fourier transform infrared (FTIR) spectra of WAS and BAC was depicted that the C-H and C-C were major surface functional groups. The ZnCl2 activated carbon had the highest adsorption capacity for MTBE adsorption, followed by H3PO4 and KOH activated carbons. The results showed that the highest MTBE removal was observed at solution pH equal to 4 and approximately 30% of MTBE could be adsorbed with 30 min contact time. It was also found that MTBE adsorption followed the R-P isotherm and pseudo-second order (type 1) kinetic models. During ANN modeling, the optimum neurons number for Levenberg-Marquardt training algorithm was determined equal to 5 with highest R2 value and lowest mean square error were found to be 0.99 and 5.7 × 10-4, respectively. © 2019 Desalination Publications. All rights reserved.
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