Adsorption Using Lime-Iron Sludge–Encapsulated Calcium Alginate Beads for Phosphate Recovery with ANN- and RSM-Optimized Encapsulation

Abstract

Excessive discharge of phosphates in municipal and industrial effluents into water bodies continues to amplify the rate and extent of eutrophication that is impairing aquatic ecosystems throughout the world. Consequently, research into technologies to combat the problem of eutrophication continues unabated. This study aimed to develop a protocol to encapsulate dewatered lime-iron sludge in calcium alginate beads and assess and optimize its phosphate adsorption performance. Response surface methodology (RSM) and artificial neural network (ANN) were used to optimize the encapsulation process through parameter variation. RSM was superior in capturing the nonlinear behavior of the process. Numerical optimization in RSM revealed that maximum adsorption could be obtained from beads prepared using 0.25 g sodium alginate and 0.5 g lime-iron sludge in 25 mL of distilled water to produce a homogeneous mixture and added dropwise into a solution of 0.31 g CaCl2 in 25 mL of distilled water. The accuracy of the RSM prediction was subsequently validated by laboratory experiments that revealed a residual error of 2.9% and thus highlights the applicability of the model. Batch experiments were conducted and modeled to expound the mechanisms of adsorption. Kinetic data were best simulated using the pseudo-second order model while equilibrium data followed the Langmuir isotherm at room temperature and the Sips isotherm at higher temperatures. Physisorption, hydrogen bonding, dipole interaction, and ligand exchange were the dominant attachment mechanisms while film and intraparticle diffusion were the pertinent transport mechanisms. The beads exhibited a maximum monolayer adsorption capacity of 8.3 mg/g that compared well to other phosphate-targeting adsorbents reported in the literature.