Abstract
•Novel Semifluidized bed operation for divalent heavy metal removal.•The adsorbent synthesised and used is very low cost and lightweight.•Operating variables are optimized for maximum efficiency obtained.•A mass transfer based dynamic model developed solved and validated.•Dispersion coefficients for both the sections have been estimated.
In this investigation, an attempt has been made to evaluate the performance of a novel Semifluidized bed adsorption column for the removal of divalent heavy metal ions from synthetic wastewater. Low cost low density adsorbent has been synthesized from Sugarcane bagasse based biochar and Na-Alginate. The biochar has specific surface area of 391.42 m2/g and it’s composite has 200.14 m2/g respectively. Major operating parameters for the system were adsorbent bed height, initial solute concentration and feed flow rate. The optimum condition of the process for maximum percentage removal of metal ions was analysed by Response Surface Methodology technique. The satisfactory values of correlation coefficients ensure the suitability of the model from process optimization. The optimum conditions for Zn2+, Cu2+ and Ni2+ were of same values having initial adsorbent bed height 12.97 cm, initial solute concentration 14.05 mg/L and feed flow rate of 2.81 LPM(Liter Per Minute) and maximum percentage removal were found to be 87.56 %, 88.89 % and 84.31 % respectively. A real-time dynamic mass transfer model based on solid-liquid mass balance has also been developed and validated with all the experimental data. Solid-liquid interphase mass transfer coefficient along with the axial dispersion coefficient for individually packed and a fluidized section of bed was also estimated from the developed model. The axial dispersion coefficient was calculated as 5.1 ± 0.3 × 10−11 m2/s for packed section and 4.8 ± 0.3 × 10-6 m2/s for fluidized section. Mass transfer coefficient for Zn2+, Cu2+ and Ni2+ were 1.11–1.21 × 10-4 m/s, 1.31−1.371 × 10-4 m/s 1.09−1.18 × 10-4 m/s under specific bed operating conditions.