Author(s): Chang JS, Huang JC, Chang JS, Huang JC
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Abstract Fixed-bed columns packed with calcium alginate (CA)-immobilized biomass of Pseudomonas aeruginosa PU21 were utilized to remove lead (Pb), copper (Cu), and cadmium (Cd) from the contaminated water. In the absence of competing metals, saturation capacity of CA-immobilized cells in batch operations was 1.60, 2.42, and 1.06 mmol/g, for Pb, Cu, and Cd, respectively. The Langmuir constants (K) obtained from the Langmuir isotherm were 157.6, 4.2, and 3.7 mM-1 for Pb, Cu, and Cd, respectively. Results from single-metal biosorption with 10-cm immobilized-cell columns show that, for an influent metal concentration of 193 microM, the total capacities for Pb, Cu, and Cd, respectively, were 5.12, 4.03, and 3.48 mmol, which is nearly 25-30\% higher than those obtained from columns containing only cell-free CA matrix. With the influent containing ternary mixtures of Pb, Cu, and Cd, columns with immobilized cells exhibited predominant selectivity to Pb, whereas in the cell-free columns, the dominance of Pb adsorption reduced, along with an appreciable increase in the adsorption of Cu. The metal-laden columns were regenerated by elution with HCl solution (pH 2.0). The metal recovery ratios were 80:1, 60:1, and 27:1 for Cu, Cd, and Pb, respectively. Moreover, with a pH gradient elution, the column-trapped metals can be optimally recovered at distinct pH values. Continuous biosorption of Pb, Cu, and Cu with four columns in series was also conducted. Results from the multibed operation demonstrate that Pb ions strongly inhibited the adsorption of Cu and Cd, which only occurred initially, and subsequently, an essential portion of the adsorbed Cu and Cd ions was replaced by Pb ions due to the ion exchange effect. However, since Pb ions were rapidly removed from the bulk at the onset of metal loading, Pb adsorption in columns 2-4 was negligible for the first 10-30 h, leading to an elevation in the breakthrough time (tb) and the capacity for Cu and Cd in columns 2-4. A back-propagation neural network model was shown to be able to predict the breakthrough curves of the three metals in the multicolumn processes with a ternary-metal feed.
This article was published in Biotechnol Prog
and referenced in Journal of Microbial & Biochemical Technology