A mathematical model consisting of mass balance equations and accounting for reaction, mass transfer and axial dispersion is presented to describe the steady-state degradation of phenol in a biofilter. The reliability of model simulations was tested using experimental data from a laboratory-scale biofilter bed column, packed with a mixture of peat and glass beads and inoculated with a pure strain of Pseudomonas putida. Comparison of model estimates with experimental concentration profiles of the pollutant along the biofilter height proves that the model is appropriate to interpret the experimental results and simulate the process. The model can therefore be used as a design tool to predict the effect of varying operating conditions (e.g. inlet pollutant concentration, gas velocity) on reactor performance (e.g. degradation capacity and efficiency). Sensitivity analysis of the model shows that parameters such as dispersion coefficient and maximum specific growth rate have to be accurately estimated for the correct prediction of reactor performance. (C) 2004 Elsevier B.V. All rights reserved.
Mathematical modelling and simulation of phenol degradation in biofilters
NICOLELLA, CRISTIANO
2004-01-01
Abstract
A mathematical model consisting of mass balance equations and accounting for reaction, mass transfer and axial dispersion is presented to describe the steady-state degradation of phenol in a biofilter. The reliability of model simulations was tested using experimental data from a laboratory-scale biofilter bed column, packed with a mixture of peat and glass beads and inoculated with a pure strain of Pseudomonas putida. Comparison of model estimates with experimental concentration profiles of the pollutant along the biofilter height proves that the model is appropriate to interpret the experimental results and simulate the process. The model can therefore be used as a design tool to predict the effect of varying operating conditions (e.g. inlet pollutant concentration, gas velocity) on reactor performance (e.g. degradation capacity and efficiency). Sensitivity analysis of the model shows that parameters such as dispersion coefficient and maximum specific growth rate have to be accurately estimated for the correct prediction of reactor performance. (C) 2004 Elsevier B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
