Table of Contents Author Guidelines Submit a Manuscript
Journal of Chemistry
Volume 2013 (2013), Article ID 517631, 10 pages
Research Article

Linear and Nonlinear Regression Methods for Equilibrium Modelling of p-Nitrophenol Biosorption by Rhizopus oryzae: Comparison of Error Analysis Criteria

1Department of Chemical Engineering, University of Chemical Technology and Metallurgy, 8 Kliment Ohridski, 1756 Sofia, Bulgaria
2Chemistry Unit, Department of Pharmacology, Animal Physiology and Physiological Chemistry, Faculty of Veterinary Medicine, Trakia University, Students Campus, 6000 Stara Zagora, Bulgaria

Received 13 June 2012; Accepted 9 August 2012

Academic Editor: Javier Hernandez-Borges

Copyright © 2013 Zvezdelina Lyubenova Yaneva et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The study assessed the applicability of Rhizopus oryzae dead fungi as a biosorbent medium for p-nitrophenol (p-NP) removal from aqueous phase. The extent of biosorption was measured through five equilibrium sorption isotherms represented by the Langmuir, Freundlich, Redlich-Peterson, multilayer and Fritz-Schlunder models. Linear and nonlinear regression methods were compared to determine the best-fitting equilibrium model to the experimental data. A detailed error analysis was undertaken to investigate the effect of applying seven error criteria for the determination of the single-component isotherm parameters. According to the comparison of the error functions and to the estimation of the corrected Akaike information criterion ( ), the Freundlich equation was ranked as the first and the Fritz-Schlunder as the second best-fitting models describing the experimental data. The present investigations proved the high efficiency (94%) of Rhizopus Oryzae as an alternative adsorbent for p-NP removal from aqueous phase and revealed the mechanism of the separation process.