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      A Review of the Dynamic Mathematical Modeling of Heavy Metal Removal with the Biosorption Process

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      Processes
      MDPI AG

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          Abstract

          Biosorption has great potential in removing toxic effluents from wastewater, especially heavy metal ions such as cobalt, lead, copper, mercury, cadmium, nickel and other ions. Mathematically modeling of biosorption process is essential for the economical and robust design of equipment employing the bioadsorption process. However, biosorption is a complex physicochemical process involving various transport and equilibrium processes, such as absorption, adsorption, ion exchange and surface and interfacial phenomena. The biosorption process becomes even more complex in cases of multicomponent systems and needs an extensive parametric analysis to develop a mathematical model in order to quantify metal ion recovery and the performance of the process. The biosorption process involves various process parameters, such as concentration, contact time, pH, charge, porosity, pore size, available sites, velocity and coefficients, related to activity, diffusion and dispersion. In this review paper, we describe the fundamental physical and chemical processes involved in the biosorption of heavy metals on various types of commonly employed biosorbents. The most common steady state and dynamic mathematical models to describe biosorption in batch and fixed-bed columns are summarized. Mathematical modeling of dynamic process models results in highly coupled partial differential equations. Approximate methods to study the sensitivity analysis of important parameters are suggested.

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          Pseudo-second order model for sorption processes

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            Insights into the modeling of adsorption isotherm systems

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              Modelling and Interpretation of Adsorption Isotherms

              The need to design low-cost adsorbents for the detoxification of industrial effluents has been a growing concern for most environmental researchers. So modelling of experimental data from adsorption processes is a very important means of predicting the mechanisms of various adsorption systems. Therefore, this paper presents an overall review of the applications of adsorption isotherms, the use of linear regression analysis, nonlinear regression analysis, and error functions for optimum adsorption data analysis.
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                Author and article information

                Contributors
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                Journal
                PROCCO
                Processes
                Processes
                MDPI AG
                2227-9717
                June 2022
                June 08 2022
                : 10
                : 6
                : 1154
                Article
                10.3390/pr10061154
                28bf7183-f267-4de4-9f5e-b2994daf3b9e
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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