| dc.description.abstract | One of the main causes of industrial pollution is the discharge of effluents containing heavy metals. Heavy metals can have serious effects on human and animal health. Beside the health effects, heavy metals are non-renewable resources. Therefore, effective recovery of heavy metals is as important as their removal from waste streams.
Due to the discharge of large amounts of metal-contaminated wastewater, industries bearing heavy metals, such as Cd, Cr, Cu, Ni, As, Pb and Zn, are the most hazardous among the chemical-intensive industries. Because of their high solubility in the aquatic environments, heavy metals can be absorbed by living organisms. Once they enter the food chain, large concentrations of heavy metals may accumulate in the human body. Sorption is a proven technology for the removal of heavy metal ions from synthetic and real industrial effluents. Several researchers investigated numerous sorbent types and proposed sorbents including activated carbon, bacteria, fungi, algae and industrial wastes.
Since the modelling of sorption isotherm data is important for predicting and comparing sorption performance, commonly the potential of sorbents are described by sorption isotherms. Sorption isotherm is the plot of sorption uptake (Q) and the final equilibrium solute concentration (Cf) and in literature two, three and even four-parameter isotherm models are available for modelling adsorption data. In this study; experimental data obtained from batch equilibrium tests have been analyzed by two parameter (Freundlich, Langmuir, Temkin), three-parameter (Redlich–Peterson, Sips, Toth) isotherm models by nonlinear regression analysis. The characteristic parameters for each isotherms and related correlation coefficients are determined by using MATLAB Version 7.10 (Release 2010a)Curve Fitting Tool Box. | es_ES |
