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A model to predict long-term performance of vapor-phase bioreactors: a cellular automaton approach
1Department of Civil Engineering, University of Texas at Austin, 78712, USA.
Abstract:
A novel numerical model was constructed to predict performance of vapor-phase bioreactors (VPBs) operated over extended periods. This model incorporates two unique features to simulate changes in pollutant removal efficiency and biomass accumulation: (1) total biomass is divided into two microbial components, active and inactive biomass, and (2) biomass growth and biofilm thickness changes are simulated by means of a cellular automaton (CA) approach. The CA approach, a differential-discrete algorithm, numerically allows the excess quantity of biomass in each numerical element to move toward the biofilm surface as biomass accumulates. One set of experimental bioreactor data was used to estimate unknown model parameters. A 90-day simulation using the estimated parameters agreed with pollutant removal and biomass accumulation profiles determined experimentally. Four additional model simulations using the same estimated model parameters were generally consistent with experimental data collected from a series of toluene-degrading VPBs operated over a range of conditions. Model predictions imply that the decline in bioreactor performance observed over extended operation was caused by a decline in the active biomass fraction and a decrease in the biofilm specific surface area. This CA model provides insight into biomass accumulation during complex bioreactor operation and improves our capability to predict long-term VPB performance.
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