Double inhibition model for degradation of phenol byPseudomonas putida Q5

Sánchez, José Francisco Fernandez; Kamp, B.; Onysko, Kira A.; Budman, Hector; Robinson, Campbell W.

doi:10.1002/(sici)1097-0290(19981205)60:5<560::aid-bit6>3.0.co;2-l

Cited by 10 publications

References 13 publications

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Biodegradation of phenol in the presence of heavy metals

Nakamura

Sawada

2000

J. Chem. Technol. Biotechnol.

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A microbial growth model was presented for estimating the dynamic behavior of cell growth and substrate consumption in the biodegradation of phenol containing a heavy metal, such as zinc or copper ions. The application of the model for experiments in a batch culture and a continuous culture was examined. The values calculated according to the model corresponded satisfactorily with experimental data, such as the optical density of cells and the concentration of phenol. Using the model, the stability of steady states in a continuous culture was analytically evaluated based on the eigenvalues. The steady states were separated into three categories: (i) a stable steady state where phenol was consumed, (ii) an unstable steady state where phenol was consumed, and (iii) a washout state where phenol was not consumed. The number, kind, and stability of steady states varied signi®cantly with operational conditions such as dilution rate, feed concentration of phenol, and feed concentration of heavy metal ions. The operational conditions required to obtain the stable steady state where phenol was consumed are shown graphically.

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Biodegradation of phenol in the presence of heavy metals

Nakamura

Sawada

2000

J. Chem. Technol. Biotechnol.

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Lag phase model for transient growth of pseudomonas putida on phenol

2001

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oluble, toxic organic chemicals often contaminate industrial wastewater effluents and create difficulties within treatment facilities S to which they are discharged. Many large industrial facilities use dedicated bioremediation ponds to continuously degrade their toxic wastewaters before they leave the plant site. Unfortunately, due to process upsets, maintenance shut-downs or just the inherent nature of the operation, the effluent wastewater rarely remains at steady-state due to changes in any number of process variables including flowrate, pollutant concentrations, temperature, etc.Phenol is a model toxic compound that has been used by many investigators to represent the behaviour of toxic wastewater treatment systems. It has been successfully bioremediated in many research and industrial applications and the kinetic behaviour of microbial degradation of phenol is well-known (Hill and Robinson, 1975). However, the most commonly applied substrate inhibition model, Haldane kinetics (Haldane, 1930), does not represent transient phenol bioremediation data with much accuracy (Allsop et al., 1993).More complex growth models have shown significant improvements in predicting transient phenol biokinetics. One approach assumes the production of an intermediate compound in the biodegradation process. Even then, delay functions are often employed to accurately predict transient experimental data (Li and Humphrey, 1989 Before microbial cells can commence active metabolism of a substrate, they have to adjust to their surrounding environment (Bailey and Ollis, 1986). This period involves the translation of new genetic information resulting in a shift in the concentrations of ribonuclease and protein molecules inside the cells (Pamment et al., 1978). This lag phase can take several hours and can be triggered by a sudden change in the environment surrounding the cells such as temperature, type of substrate or even concentration of substrate. One approach to modelling this lag phase is to assume pure time delay, that is no change in biomass activity, substrate and product concentrations. However, some models predict changes in these variables, such as the time dependentThe successful design of large-scale bioreactors requires the ability to predict both steady-state and dynamic operating conditions. At the same time, mathematical models should not be too complex in order to reduce experimental work required to determine kinetic parameters. A simple model which predicts the behaviour of batch and transient continuous culture operations is presented and experimentally verified. The model is based on two regions of metabolic activity: the lag phase and the active phase. Pseudomonas putida growing on phenol as a substrate in a well-mixed bioreactor was tested in three modes of operation: batch, continuous start-up and continuous step-change. The model is demonstrated to predict all the qualitative aspects of the dynamic phases of growth and is quantitatively accurate.

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Improved modelling of the unsteady‐state behaviour of an immobilized‐cell, fluidized‐bed bioreactor for phenol biodegradation

2002

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istorically, the focus in water pollution abatement has been on the removal of suspended solids, nutrients and biochemical H oxygen demand. However, there is increasing interest in studying the removal of toxic and persistent compounds. Despite the xenobiotic nature of these compounds, many are at least partially degradable by microorganisms, particularly if the microorganisms have been acclimated to a given wastewater.The most common biological wastewater treatment method is the activated sludge process, which consists of a mixed culture of freely suspended microorganisms that use pollutants both as a carbon source and for energy. In this process, there are limitations on the maximum permissible biomass concentration to allow for floc formation and settling under quiescent conditions, and on the dilution rate (reactor feed rate per unit liquid volume) to avoid washout of the biomass. Additionally, the activated sludge process is generally sensitive to fluctuations in flow, concentration or temperature, arising from either periodic variations in the feed conditions or by shock loads due to spills, malfunctions, etc.(Christiansen and Spraker, 1982).Biofilm processes, in which the microorganisms are attached to a support material, have certain advantages over conventional suspension cell systems such as the activated sludge process as follows: 1) more resistance to process fluctuations (Holladay et al., 1978); 2 ) better protection against toxic or inhibitory compounds (Stevens, 1988); 3) tolerance to higher dilution rates without washout of the biomass (Tang et al., 1987); and 4) biomass concentrations 5 to 10 times higher than in free suspension system are obtained, allowing for higher degradation rates and smaller reactors (Stathis, 1980). Advantages 1 through 3 arise from the diffusional resistance to the flux of substrate into the biofilm. Wanner and Cujer (1986) presented an early model of changes in biofilm thickness, which also could be used to predict the dynamics and spatial distribution of several microbial species present in a biofilm. Their model was not intended to provide a precise numerical description of heterotrophic-autotrophic competition in biofilms, but rather to illustrate the ease by which the model could be solved on a computer.Biofilm systems may occur in a number of configurations, including trickling filters, submerged filters, rotating disks and fluidized beds. Advantages of immobilized-cell fluidized-bed reactors (ICFBRs) are: a significantly larger surface for biofilm formation as compared to other loo, ON N2L 3 G l . CanadaThe dynamic response of an immobilized-cell, fluidized-bed reactor (ICFBR) to step changes in phenol loading was investigated at 10°C for a pure culture of Pseudomonas putida Q5, a psychrotrophic bacterium. A novel dynamic model was developed and tested to simulate the response of all four key process variables: the bulk phenol concentration, the suspended biomass concentration, the concentration profile of the substrate in the biofilm and the biofilm thickness. A...

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Double inhibition model for degradation of phenol byPseudomonas putida Q5

Cited by 10 publications

References 13 publications

Biodegradation of phenol in the presence of heavy metals

Biodegradation of phenol in the presence of heavy metals

Lag phase model for transient growth of pseudomonas putida on phenol

Improved modelling of the unsteady‐state behaviour of an immobilized‐cell, fluidized‐bed bioreactor for phenol biodegradation

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