Volume 16, Number 2 (7-2017)                   TB 2017, 16(2): 88-97 | Back to browse issues page


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Danaee S, Fazaelipoor M H, Salmani M H. Using of Moisture Term in the Dynamic Modeling in Treatment Process of Hexane-Contaminated Air. TB. 2017; 16 (2) :88-97
URL: http://tbj.ssu.ac.ir/article-1-2331-en.html

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Abstract:   (193 Views)

Introduction: Biofiltration of volatile organic compounds is a biological method in which air containing contaminant is passed through a packed bed and the pollutant is transferred from gas phase to biofilm where it is degraded by microorganisms. Degrading microbial activity is strongly influenced by moisture content of bed so that it is considered as the most important factor for controlling optimum performance of biofiltration. A solutions for reduction of the bed drying problems is use of water super absorbents which are able to store and maintain water.

Methods: For the first time, a two-dimensional dynamic model of biofiltration of hexane contaminated air is presented in which terms of moisture content and axial dispersion are considered in mass transfer equations. Effects of water super absorbent including continuous increase in porosity of the bed and specific surface area were entered into the equations. The equations were discretized by Finite Volume Method for solving numerically. Then, to determine the accuracy of model predictions, biofiltration experiments were done in flow rate of 0.7 l/min and inlet concentration of 2 g/m3.

Results: The model could present a pattern of decline in moisture content of the bed after moistening stop. Experimental data of increasing of pollutant outlet concentration because of bed moisture reduction were well predicted by the model (standard error = 0.45%) and an estimation of end point was presented.

Conclusion: The results indicated that consideration of moisture content term under unsteady state conditions can develop the model performance and describe biofiltration process with all its complexities.

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Type of Study: Applicable | Subject: Special
Received: 2016/11/7 | Accepted: 2016/12/21 | Published: 2017/07/17

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