Statistical evaluation of models for the removal of heavy metals in adsorption columns using bio-waste materials

Abstract

Agro-based waste constitutes a significant amount of waste in major urban and rural communities and is therefore part of any municipal waste management strategy. The feasibility of the use of agro-based waste as adsorbents for heavy metals has been studied by a number of researchers. However, there is no comprehensive study dealing with the selection of models for design. The key variables in the process are; the heavy metals concentration, the mass of bio-sorbent and the flow rate of the influent waste water. Several models that were not originally derived for the adsorption of heavy metals are used to predict the breakthrough curves. In this study a statistical analysis of the performance of two of the widely used models (Yoon- Nelson and Thomas) was carried out in order to propose a suitable model for use in design, while pointing out the limitations. The study further investigates the use of mean empirical parameters and fitting the coefficients as a function of process parameters in an attempt to generalize the models for easy application. Both models perform equally well with the model coefficients adjusted with changes in the flow parameters. The use of average values of the parameters to generalize the models shows that the Yoon-Nelson model is incapable of predicting the performance with changes in the flow parameters. Based on available data and the results of the present analysis, the Thomas model is recommended for the design of adsorption columns for heavy metals.