Title of article :
A New Temperature Effect Model to Predict Benzoic Acid Isotherm Curves onto Activated Carbon
Author/Authors :
-، - نويسنده Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563 Tehran, I.R. IRAN Ghorbanian, Sohrab Ali , -، - نويسنده Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563 Tehran, I.R. IRAN Abolghasemi, Hossein , -، - نويسنده Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563 Tehran, I.R. IRAN Mousavian, Mohammad Ali , -، - نويسنده Faculty of Chemistry, Amirkabir University of Technology, Tehran, I.R. IRAN Ghanadi, Mohammad
Issue Information :
فصلنامه با شماره پیاپی 44 سال 2007
Pages :
9
From page :
49
To page :
57
Abstract :
-
Abstract :
The recovery and removal of the most organic acids in liquid solutions is usually treated with fixed-bed adsorption processes. Among many adsorbents, Granular Activated Carbon (GAC) is used to remove organic pollutants such as Benzoic Acid (BA) from wastewaters conventionally. In this research, adsorption isotherm curves of BA onto GAC at varying temperatures 25-60 °C are developed and the amounts of BA concentration in feed fluid and on the adsorbent are obtained. The results show that Radke and Prausnitz (Ra-Pr) model among five applicable isotherm models has best fitting with experimental data. In this paper, for the first time, a new model for temperature effect on isotherm curve of BA is investigated. This model could predict isotherm curves in accordance to the isotherm curve in reference temperature with absolute relative error (ARE) less than 1.2%. Thus Temperature Effect Term (T.E.T) model is able to predict isotherm curves only by using experimental data in one temperature successfully. Furthermore T.E.T and Ra-Pr models jointly, could predict the every isotherm curve only with experimental data in three equilibrium points in one temperature with low error. In this case, the average A.R.E% in comparison with experimental data is less than 1.4%.  
Journal title :
Iranian Journal of Chemistry and Chemical Engineering (IJCCE)
Serial Year :
2007
Journal title :
Iranian Journal of Chemistry and Chemical Engineering (IJCCE)
Record number :
2151859
Link To Document :
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