Kinetic modeling of heavy metal adsorption systems

Abstract

Adsorption is a simple and effective technology to remove and recover heavy metal from wastewater to mitigate detrimental impacts on the environment and human health. Wastewater and acid leachate in metal recovery processes typically contain mixtures of different metals in appreciable amounts, which can affect the separation process. Multicomponent adsorption studies are therefore vital to enhance our understanding of the effect of multiple components on the capacities and selectivity of the adsorbent. While a number of multicomponent equilibrium isotherms have been developed to describe the competitive effect in multicomponent systems, many rely on extended versions of single isotherms to predict on binary data. However, the predictions often fall short of expectations due to differences in affinity of metals towards the adsorption sites. Additional parameters are needed to account for this competition to develop better fitted models, which Freundlich based models modified by Al-duri and Sheindorf–Rebuhn–Sheintuch with an additional activity coefficient are found to describe the multicomponent experimental data better. Equilibrium isotherms can provide us with information on adsorption capacities and selectivity, in order to understand the uptake rate of the metals and subsequently the residence time, it is necessary to carry out multicomponent batch kinetic study. We have found very few works on multicomponent batch kinetic adsorption studies, let alone a good kinetic model to correlate these data. In this work, we have developed a multicomponent kinetic model to describe the competitive adsorption system in a chelating ion exchange resin and chitosan. Single component equilibrium isotherm and batch kinetic studies on CuSO₄, NiSO₄ and ZnSO₄ are first carried out, followed by binary component equilibrium isotherm and batch kinetic studies of Cu-NiSO₄, Cu-ZnSO₄ and Ni-ZnSO₄ in the ratio of 1:1. Modeling is carried out at each stage using different equations and the best fitting model is determined by the minimum SSE value. A selectivity coefficient is used to correlate the competition between two metals throughout the adsorption processes in the newly developed binary kinetic model. Outcomes from this study will help to close gaps in determining multicomponent heavy metal adsorption kinetics which past studies have rarely investigated so far.

Date of Award	2017
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology