Modeling and Optimization of Arsenic (III) Removal from Aqueous Solutions by GFO Using Response Surface Methodology

Authors

  • A. Nadali Department of Environmental Health Engineering, School of Public Health, Hamadan University of Medical Science, Hamadan, Iran
  • F. S. Tabatabaei Research Center for Environmental Pollutants, Qom University of Medical Sciences, Qom, Iran.
  • H. Heidari Research Center for Environmental Pollutants, Qom University of Medical Sciences, Qom, Iran.
  • H. Izanloo Research Center for Environmental Pollutants, Qom University of Medical Sciences, Qom, Iran.
  • M. Asadi-Ghalhari Research Center for Environmental Pollutants, Qom University of Medical Sciences, Qom, Iran.
  • M. Zamanzadeh Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  • N. Vaezi Research Center for Environmental Pollutants, Qom University of Medical Sciences, Qom, Iran.
  • R. Aali Research Center for Environmental Pollutants, Qom University of Medical Sciences, Qom, Iran.
Abstract:

Arsenic is a highly toxic element for human beings, which is generally found in groundwater. Dissolved Arsenic in water can be seen as As+3 and As+5 states. The adsorption process is one of the available methods to remove Arsenic from aqueous solutions. Thus, this papers aims at removing Arsenic (III) from aqueous solutions through adsorption on iron oxide granules. The relation among four independent variables, namely the initial concentration of Arsenic (III), pH, adsorbent dose, and contact time have been investigated through Response Surface Methodology. Design-Expert software and Central Composite Design method have been used to design and analyze the experiments and results. Also, SEM and FTIR analysis have been conducted to characterize the absorbent morphology. The optimum initial concentration of Arsenic (III), pH, contact time, and adsorbent dosage are 30ppm, 5, 49.99min, and 8g/l, respectively. Under these optimum conditions, the Arsenic (III) removal efficiency is 67%. The predicted 2FI model shows the highest Arsenic removal coefficient (R2=0.887).

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Journal title

volume 6  issue 3

pages  543- 553

publication date 2020-07-01

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