<p>Co-occurring presence of arsenic and fluoride is a major contaminator of groundwater in several parts of the world. Nevertheless, there is limited research on combined removal of arsenic and fluoride in packed-bed column&#xa0;adsorption studies. This article examines the removal of As(V) and F<sup>−</sup> in a packed-bed column using both single and binary adsorption modes. The effects of experimental parameters like the influent concentration (5, 50, and 100&#xa0;mg/L), flowrate (3.1 and 7&#xa0;mL/min), and bedheights (2.5, 5, and 10&#xa0;cm), on the effluent concentration, were evaluated. It was found that adsorption rate kinetics play an important role in the initial period of packed-bed adsorption, and then at later time, the equilibrium adsorption predominates. Fluoride adsorption was faster compared to As(V) adsorption as suggested by the kinetic adsorption rate constants. The simultaneous adsorption results revealed a consistent decrease in F<sup>−</sup> adsorption in the presence of competing As(V) ions, showing antagonistic competitive behavior. In competitive adsorption, as the flowrate increased, the selectivity factor of As(V) declined, and F<sup>−</sup> increased comparatively. Analytical column adsorption models were employed for simulating the experiments in packed bed. The Thomas, Yoon–Nelson (YN), and Bed-Depth Service Time (BDST)&#xa0;column model fitting were analyzed using the four statistical error metrics: MAPE, NAPE, RMSE, and Chi-square. The predictions of the Thomas model were slightly better, with <i>R</i><sup>2</sup> values between 0.92 and 0.96 for As(V) and 0.92–0.99 for F<sup>−</sup>, while the R<sup>2</sup> of the Yoon&#xa0;Nelson model ranged between 0.92 and 0.96 for As(V) and 0.85–0.97 for F<sup>−</sup>, and BDST model showed the average <i>R</i><sup>2</sup> of 0.98 for As(V) and F<sup>−</sup>. Further the BDST model was used to predict the column adsorption design parameters at different concentrations. Column&#xa0;regeneration studies showed that adsorption capacity reduced significantly after regeneration, suggesting strong chemisorption.</p>

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Competitive adsorption of arsenic(V) and fluoride in packed-bed column: experimental and modeling studies

  • Amrutha Acharya,
  • L. N. Disha,
  • Yajya Puri,
  • Srinivas M. Kini,
  • Gautham Jeppu,
  • Chikmagalur Raju Girish

摘要

Co-occurring presence of arsenic and fluoride is a major contaminator of groundwater in several parts of the world. Nevertheless, there is limited research on combined removal of arsenic and fluoride in packed-bed column adsorption studies. This article examines the removal of As(V) and F in a packed-bed column using both single and binary adsorption modes. The effects of experimental parameters like the influent concentration (5, 50, and 100 mg/L), flowrate (3.1 and 7 mL/min), and bedheights (2.5, 5, and 10 cm), on the effluent concentration, were evaluated. It was found that adsorption rate kinetics play an important role in the initial period of packed-bed adsorption, and then at later time, the equilibrium adsorption predominates. Fluoride adsorption was faster compared to As(V) adsorption as suggested by the kinetic adsorption rate constants. The simultaneous adsorption results revealed a consistent decrease in F adsorption in the presence of competing As(V) ions, showing antagonistic competitive behavior. In competitive adsorption, as the flowrate increased, the selectivity factor of As(V) declined, and F increased comparatively. Analytical column adsorption models were employed for simulating the experiments in packed bed. The Thomas, Yoon–Nelson (YN), and Bed-Depth Service Time (BDST) column model fitting were analyzed using the four statistical error metrics: MAPE, NAPE, RMSE, and Chi-square. The predictions of the Thomas model were slightly better, with R2 values between 0.92 and 0.96 for As(V) and 0.92–0.99 for F, while the R2 of the Yoon Nelson model ranged between 0.92 and 0.96 for As(V) and 0.85–0.97 for F, and BDST model showed the average R2 of 0.98 for As(V) and F. Further the BDST model was used to predict the column adsorption design parameters at different concentrations. Column regeneration studies showed that adsorption capacity reduced significantly after regeneration, suggesting strong chemisorption.