Chloroform aerobic cometabolic biodegradation in a continuous‐flow reactor: Model calibration by means of the gauss‐newton method. (17th February 2019)

• Record Type: Journal Article
• Authors: Frascari, Dario; Pinelli, Davide; Ciavarelli, Roberta; Nocentini, Massimo; Zama, Fabiana
• Is Part Of: Canadian journal of chemical engineering. Volume 97:Number 6(2019)
• Page Start: 1771
• Page End: 1784
• Publication Date: 2019-02-17
• Subjects: bioremediation -- aerobic cometabolism -- chlorinated solvents -- Gauss‐Newton method -- model calibration; Chemical engineering -- Periodicals; Technology -- Periodicals; 660.05
• DOI: 10.1002/cjce.23449
• Languages: English
• ISSNs: 0008-4034

Abstract

Abstract: Chlorinated solvents are toxic and poorly biodegradable pollutants frequently found in contaminated aquifers. Experimental data of chloroform (CF) aerobic cometabolic biodegradation in a sand column with butane as growth substrate were simulated with a system of non‐stationary second‐order partial differential equations with non‐linear kinetic terms. A MATLAB optimization code based on the Gauss‐Newton method and coupled with the Comsol Multiphysics finite elements solver was developed to calibrate the model. For each experimental phase, the best‐fit quality was evaluated by an innovative multi‐variable model adequacy test. The proposed code solved systems of up to 5 partial differential equations and optimized up to 6 unknown parameters, leading to statistically acceptable best‐fits. The optimization of the butane/oxygen pulsed feed led to an 82 % CF biodegradation and to a 0.27 gCF /gbutane transformation yield. When the substrate/pollutant ratio was minimized, the standard model of aerobic cometabolism initially tested required additional terms aimed at taking into account the depletion of reducing energy, in order to attain a statistically acceptable best‐fit. This is the first work in which a model of aerobic cometabolism taking into account reducing energy availability was applied to a continuous‐flow process. The proposed optimization code can be used for model calibration in a wide range of physical problems described by non‐stationary, non‐linear partial differential equations, a task that no commercial software can perform. The developed code is made available in the Supplementary Material.