Jan Arvee V. Andallo, Lance A. Cruz, John Andrew B. Gapan, Jaime Gabriel M. Hernandez, and Allen Clifford Orbase, BS Chemical Engineering students, successfully defended their thesis proposal entitled "Chitosan/Poly(vinylamine)/Calamansi Peel Hydrochar Composite Beads for the Simultaneous Removal of Manganese (II) and Arsenic (III) in Water" last April 23, 2023, in partial fulfillment of their Chemical Engineering Methods of Research.
The vulnerability of aquatic ecosystems to heavy metal pollution has been identified as a rising pollution concern. Due to biomagnifications over time, metals that are deposited in aquatic environments may accumulate in the food chain and cause ecological damage, endangering human health and a sustainable food supply. Urban lakes like Laguna de Bay are more vulnerable to anthropogenic sources of heavy metal contamination. Human and animal health are known to be negatively impacted by heavy metals like arsenic (As), cadmium (Cd), chromium (Cr), lead (Pb), mercury (Hg), manganese (Mn), and nickel (Ni).
Among all available methods for wastewater treatment, adsorption is a straightforward, sustainable, cost-effective, and environmentally friendly method. However, further research and development, optimization, and practical implementation of the integrated process is required for a broad variety of applications.
This study will focus on the removal of Manganese and Arsenic contents in simulated water using composite beads made from low-cost, eco-friendly, readily accessible chitosan, polyvinylamine, and calamansi peels. The beads will be synthesized using the extrusion-coagulation method. Additionally, the study aims to investigate the effect of adsorption parameters on the removal of manganese (II) and arsenic (III) in the simulated water. The adsorption process will be carried out in a batch system. To investigate the surface interaction behavior of the adsorption reaction, the widely used isotherm models will be used. The adsorption kinetics will also be investigated using various kinetic models.
Their research project will be conducted from 2023 to 2024.