Continuous fixed-bed column study and adsorption modeling: removal of cadmium (II) and lead (II) ions in aqueous solution by dead calcareous skeletons

The sorption of Cd(II) and Pb(II) ions was conducted in a continuous fixed-bed column by using dead calcareous skeletons (CS). The column performances were evaluated by varying the adsorbent bed height, influent flow rate and metals initial concentration. The breakthrough curve for the bed height in...

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Bibliographic Details
Main Authors: Lim, Ai Phing, Aris, Ahmad Zaharin
Format: Article
Published: Elsevier 2014
Online Access:http://psasir.upm.edu.my/id/eprint/36901/
http://www.sciencedirect.com/science/article/pii/S1369703X14000898
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Summary:The sorption of Cd(II) and Pb(II) ions was conducted in a continuous fixed-bed column by using dead calcareous skeletons (CS). The column performances were evaluated by varying the adsorbent bed height, influent flow rate and metals initial concentration. The breakthrough curve for the bed height indicated that a longer bed column prolonged the life span of the column with a maximum capacity of 26.447 and 38.460 mg/g for the Cd(II) and Pb(II) column, respectively. The increased flow rate and initial concentration caused the column exhaustion time to occur earlier. The experimental column data were also expressed in column adsorption models, namely, the Thomas, Yoon–Nelson and Adam–Bohart models. The Thomas model fitted well with the Cd(II) data with the correlated curve (r2 > 0.9). The Yoon–Nelson model was selected to predict the 50% breakthrough time achieved by the column system and provided the estimated breakthrough time for the columns that were not exhausted during the operation. The Adam–Bohart model was applicable for the initial part of adsorption with the saturation concentration data at the equilibrium. The saturation index of aragonite and calcite depicted that dissolution of calcium occurred in the aqueous solution. The experimental and theoretical data were correlated with a significant relationship trend (p < 0.01), which showed that the trend of experimental data fit well with the modeling trend. The trends of both the experimental and theoretical data were strongly and significantly correlated due to involving the column parameters and the components of CS.