CFD Modeling of Immobilized Phenol Biodegradation in Three-Phase

4514

Ind. Eng. Chem. Res. 2009, 48, 4514–4529

GENERAL RESEARCH CFD Modeling of Immobilized Phenol Biodegradation in Three-Phase Airlift Loop Reactor Xiaoqiang Jia,†,‡ Jianping Wen,*,†,‡ Xue Wang,† Wei Feng,† and Yan Jiang† Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin UniVersity, Tianjin 300072, P. R. China, and Key Laboratory of Systems Bioengineering (Tianjin UniVersity), Ministry of Education, Tianjin 300072, P. R. China

A 3D transient CFD model was developed to simulate the dynamic behaviors of batch phenol biodegradation by immobilized Candida tropicalis in a gas-liquid-solid three-phase airlift loop reactor (ALR), coupling of three-phase fluid flow, species interphase mass transfer, and intrinsic bioreaction, with the bubble size distribution (BSD) determined by the multiple size group (MUSIG) model. Simulation of the time courses of the volume-averaged species mass concentrations in the riser and downcomer of the ALR was performed, whereas the phenol and oxygen concentrations in the liquid phase were validated by corresponding experiments. Source-term comparisons between species interphase mass transfer and bioreaction were done to distinguish the rate-limiting step in the process. Moreover, local transient phenol biodegradation characteristics such as oxygen concentration profiles in the gas, liquid, and solid phases; phenol concentration profiles in the liquid and solid phases; and cell concentration profiles in the solid phase were all predicted reasonably well. Furthermore, the performances of the ALR and a bubble column reactor (BCR) were compared, and the advantage of the former reactor was confirmed. Introduction Phenol is a common pollutant in industrial wastewaters such as those generated by oil refineries, petrochemical plants, coking plants, brown-coal distilling plants, wood processing plants, and phenolic-resin manufacturers.1 Increased accumulation of phenol in the ecosystem can cause deleterious effects; thus, it is obligatory to treat this waste before it can be safely discharged into water.2 Biological treatment is a feasible approach compared to physicochemical methods for removing phenol from wastewater because of its low cost and avoidance of secondary pollution, especially at relatively lower phenol concentrations.3 Reactions with immobilized microorganisms have drawn much attention, as they offer several advantages over processes with suspended biomass, such as protecting cells from toxic substances, preventing suspended particles from appearing the effluent, and allowing easy separation from the reaction mixture and subsequent reuse.4,5 Polyvalent salts of alginate are preferable among types of solid matrixes because of their low cost and mild conditions even while maintaining a high concentration of cells in the reactor.6-9 Recently, the airlift loop reactor (ALR) has been extensively used in fermentations and wastewater treatment processes because of its advantages in terms of simple construction and operation, low investment and operating costs, very fine gas dispersion, definitely directed circulation flow, high mixing and mass-transfer performance, and relatively low power requirements.10 Numerous investigations have indicated the very good performance of ALRs in phenol biodegradation, in both gas-liquid (G-L) two-phase systems and gas-liquid-solid * To whom correspondence should be addressed. Tel.: 86-2227890492. E-mail: [email protected]. † School of Chemical Engineering and Technology. ‡ Key Laboratory of Systems Bioengineering.

(G-L-S) three-phase systems.11-14 However, the understanding of these very complex systems, involving coupling of multiphase fluid flow, species interphase mass transfer, and intrinsic bioreaction, is rather limited, which significantly prevents better optimization and scaling-up of ALR processes.15 In the past decade, the computational fluid dynamic (CFD) method has been employed as a useful tool for understanding the complicated multiphase hydrodynamics of ALRs, to a large extent replacing time-consuming and expensive experiments.16-23 The current focus is on the modeling of multiphase bioreaction processes, such as phenol biodegradation. However, most reports in the literature to date have been limited to the modeling of G-L two-phase hydrodynamics, and only Feng et al. have developed a three-dimensional (3D) transient CFD model for simulating the local dynamic behaviors of phenol biodegradation in G-L two-phase ALRs using free cells.24 Reports of CFD modeling on G-L-S three-phase fluid flows in ALRs are rather limited,25 not to mention phenol biodegradation in such systems. The objective of this work was to develop a 3D transient CFD model for simulating the immobilized batch phenol biodegradation in a three-phase ALR, including coupling of three-phase fluid flow, species interphase mass transfer, and intrinsic bioreaction. Model simulations of changes in the volume-averaged phenol and oxygen concentrations in the liquid phase of the riser and downcomer were validated by corresponding experimental measurements. The rate-limiting step was distinguished through source-term comparisons. Local transient phenol biodegradation behaviors of the ALR such as hydrodynamic characteristics and species mass concentration distributions were predicted by the developed model as well. Theory Model Assumptions. In this work, a 3D transient CFD model was developed to simulate the dynamic behaviors of batch

10.1021/ie800816d CCC: $40.75  2009 American Chemical Society Published on Web 03/25/2009

Ind. Eng. Chem. Res., Vol. 48, No. 9, 2009 4515

phenol biodegradation by immobilized Candida tropicalis in a G-L-S three-phase ALR, based on a previously developed three-phase ALR hydrodynamic CFD model.26 Several assumptions were made for this model development as follows: (1) In the immobilized batch phenol biodegradation process, solid particles are suspended in the liquid phase. Oxygen is transferred from the gas phase into the liquid phase, and both phenol and oxygen are transferred from the liquid phase into the solid phase, where they are consumed by microbial cells. (2) The solid particles are assumed to be spherical with the same radius and to remain constant during the biodegradation process, and the cells are assumed to be uniformly distributed within the solid particles.27 (3) Substrate degradation and cell growth within the solid particles are both limited by the phenol and oxygen concentrations, with all other nutrients present in excess. (4) The influence of free cells in the liquid phase on phenol biodegradation is negligible because of their very small amount.27 The Eulerian approach was employed to describe the flow behavior of each phase. The liquid phase composed of the mineral salt medium, phenol, and oxygen was considered to be the continuous phase; the gas phase was composed of nitrogen and oxygen; the solid phase was composed of alginate gel; and phenol, oxygen, and cells were considered to be the dispersed phases. The turbulence CFD model simulating the local transient hydrodynamics and the multiple size group (MUSIG) model describing the bubble size distribution (BSD) were presented in detail previously26 and thus are not repeated here. Species Transport Equations. The description of the species transport equations is as follows: ∂ (F R x ) + ∇·(FgRgxo,gug) ) ∂t g g o,g

[(

∇· Rg FgDo,g + ∂ (F R x ) + ∇·(FlRlxo,lul) ) ∂t l l o,l

[(

∇· Rl FlDo,l +

) ]

µT,g (∇xo,g) - Γo,gl ScT,g

) ]

µT,l (∇xo,l) + Γo,gl - Γo,ls ScT,l

∂ (F R x ) + ∇·(FlRlxp,lul) ) ∂t l l p,l

[(

∇· Rl FlDp,l

) ]

µT,l + (∇xp,l) - Γp,ls ScT,l

∂ (F R x ) + ∇·(FsRsxo,sus) ) ∂t s s o,s µT,s (∇xo,s) - So,s + Γo,ls ∇· Rs FsDo,s + ScT,s

[(

) ]

∂ (F R x ) + ∇·(FsRsxp,sus) ) ∂t s s p,s µT,s ∇· Rs FsDp,s + (∇xp,s) - Sp,s + Γp,ls ScT,s

[(

) ]

∂ (F R x ) + ∇·(FsRsxx,sus) ) ∂t s s x,s

[(

∇· Rs FsDx,s

) ]

µT,s + (∇xx,s) + Sx,s ScT,s

(1)

(2)

(3)

constraint component in the liquid phase, and alginate gel is considered to be the constraint component in the solid phase. The mass fractions of the above three constraint components in corresponding phases were determined by the species balance equations as recommended by the CFX software. xo,g + xn,g ) 1

(7)

xo,l + xp,l + xm,l ) 1

(8)

xo,s + xp,s + xx,s + xa,s ) 1

(9)

The gas- and liquid-phase oxygen kinematic diffusivities were Do,g ) 2 × 10-5 m2 · s-1 and Do,l ) 2.54 × 10-9 m2 · s-1, and the liquid-phase phenol kinematic diffusivity was Dp,l ) 8.69 × 10-10 m2 · s-1.28 The solid-phase oxygen and phenol kinematic diffusivities were calculated using the random-pore model when cells were present.27

[ [

Do,s ) Do,l (1-2.6) × 10-3 Dp,s ) Dp,l (1-2.6) × 10-3

( (

Fsxx,s -3

kg·m

Fsxx,s -3

kg·m

(5)

(6)

Nitrogen is considered to be the constraint component in the gas phase, the mineral salt medium is considered to be the

2

(10) 2

(11)

Note that, in the above two equations, the cell concentration in the solid phase is in the dimensionless state. The solid-phase cell kinematic diffusivity (Dx,s) is considered to be 0. Haldane’s equation has been shown to be suitable for simulating the intrinsic cell growth kinetics of Candida tropicalis when phenol is the sole carbon source and exhibits inhibition under high concentration.29 As this study was carried out in an immobilized cell system, the effect of the oxygen limitation has to be taken into account to better simulate the cell growth behavior within the alginate gel beads, which is expressed by the Monod equation.30 As fresh cells in the late exponential phase were used in this study and the reaction time was rather short, cell death/decay kinetics was not considered. Therefore, the reaction source term can be written as Sx,s ) Rsµx(Fsxx,s) ) Rs

µmax(Fsxp,s)

× Ks + (Fsxp,s) + (Fsxp,s)2 /Ki (Fsxo,s) (F x ) Ko + (Fsxo,s) s x,s

Sp,s ) Rs[Aµx(Fsxx,s) + B(Fsxx,s)] ) ASx,s + RsB(Fsxx,s) So,s ) Sx,s /Yx/o

(4)

)] )]

(12) (13) (14)

The intrinsic bioreaction kinetic parameters were obtained from a previous study as µmax ) 1.33 × 10-4 s-1, Ks ) 1.17 × 10-2 kg · m-3, Ki ) 2.08 × 10-1 kg · m-3, A ) 8.23 × 10-1, and B ) 7.69 × 10-5 s-1 29 and from the literature as Ko ) 2.6 × 10-4 kg · m-3 and Yx/o ) 4.65 × 10-1.30 The species interphase mass-transfer source term was calculated as Γo,gl ) Ko,glag[(Flx*o,l) - (Flxo,l)]

(15)

Γo,ls ) Ko,lsas[(Fsx*o,s) - (Fsxo,s)]

(16)

Γp,ls ) Kp,lsas[(Fsx*p,s) - (Fsxp,s)]

(17)

The gas-liquid oxygen mass-transfer coefficient (Ko,gl) was calculated as31

4516 Ind. Eng. Chem. Res., Vol. 48, No. 9, 2009

Ko,gl )

( )

εFl 2 √Do,l µ √π l

0.25

(18)

The liquid-solid oxygen mass-transfer coefficient (Ko,ls) and the liquid-solid phenol mass-transfer coefficient (Kp,ls) were calculated from the following correlations:32

{ {

( )[

Ko,ls )

Do,l µl 2 + 0.695 ds FlDo,l

Kp,ls )

Dp,l µl 2 + 0.695 ds FlDp,l

1/3

( )[ 1/3

Ug,supgds4 (µl /Fl)3 Ug,supgds4 (µl /Fl)3

]} ]} 0.2

(19)

0.2

(20)

It should be pointed out that possible deviations might arise in the above calculations from using a correlation for conventional three-phase fluidized beds, as the solid distribution in our work was considered to be nonuniform and the solid loading was relatively low. However, work done by Livingston and Chase30 showed that the values of the phenol and oxygen liquid-solid mass-transfer coefficients in an airlift loop reactor obtained from this generally applicable correlation were in good agreement with their experiments, and the good simulation results of our work also validated the applicability of this classical correlation.-11 The liquid-phase saturated oxygen mass fraction at the specified gas-phase oxygen mass fraction (x*o,l), the solid-phase saturated oxygen mass fraction at the specified liquid-phase oxygen mass fraction (x*o,s), and the solid-phase saturated phenol mass fraction at the specified liquid-phase phenol mass fraction (x*p,s) were all calculated through the mass-fraction equilibrium ratios of oxygen and phenol between the gas-liquid interphase and the liquid-solid interphase. The gas-bubble specific area was calculated as ag ) 6Rg/dg, and the solid-bead specific area was calculated as as ) 6Rs/ds. The phase density (F), molecular viscosity (µ), volume fraction (R), velocity vector (u), turbulence viscosity (µT), liquidphase turbulence eddy dissipation (ε), and Sauter mean bubble diameter (dg) were all obtained from the hydrodynamic CFD model coupled with the MUSIG model presented previously.26 The species transport due to interphase mass transfer and bioreaction was sufficiently small compared with the main body of each phase that its effect on the continuity equations and momentum equations could be neglected.33 Initial and Boundary Conditions. Transient calculations started from the assumption that each phase velocity was 0 m/s, the gas volume fraction was 0, and the solid particles were uniformly distributed in the reactor. The initial phenol concentrations in the liquid phase were Cp,0 ) 0.1, 0.15, and 0.2 kg · m-3; the initial phenol concentration in the solid phase was 0 kg · m-3; the initial cell concentration in the solid phase was 9 kg · m-3; the initial oxygen volume fraction in the gas phase was 0.21; the initial oxygen concentration in the liquid and solid phases was 7.56 × 10-3 kg · m-3 (saturated oxygen concentration at 30 °C and normal pressure); and the solid loadings were Rs,0 ) 1%, 2%, and 3% (volume fraction). The values of the superficial gas velocity were Ug,sup ) 0.01, 0.015, and 0.02 m/s, and the inlet gas velocities were determined according to the area of the distributor plate with a gas holdup of unity, and the size fraction of the third bubble group with a diameter of 4.5 mm was set to be unity for the inlet conditions used.26 The boundary conditions for the walls were defined as no-slip for the continuous phase and free-slip for the dispersed phases. At the top of the computational domain, proper outlet

conditions were defined so that only gas could leave the domain through the inner area and only liquid could leave the domain through the periphery, whereas the solid was kept within the reactor.34 Numerical Solution. To numerically solve the partial differential equations, a “high-resolution” discretization of the equations was carried out using a finite-volume scheme with a coupled multigrid solver as implemented in the commercial CFD code CFX. Unstructured hexahedral grids of 10 × 10 × 15 mm, 9 × 10 × 15 mm, 9 × 9 × 15 mm, 5 × 10 × 15 mm, 5 × 9 × 15 mm, and 5 × 5 × 15 mm were implemented with a total number of 29 160 cells within the 0.2 × 0.2 × 0.6 m computation domain.26 To save computing costs, a time-step strategy was employed:35 100 steps at 0.001 s, 100 steps at 0.002 s, 100 steps at 0.005 s, 100 steps at 0.01 s, 100 steps at 0.02 s, 100 steps at 0.05 s, and a time step length of 0.1 s for the rest of the time. A typical solver run over 600 s of computed time required about 800 h on an Intel Pentium D 3.0 GHz processor. Convergence was good at the criterion of 1 × 10-4 for all of the variables calculated. Experiments Microorganism and Culture Conditions. A pure culture of the yeast Candida tropicalis stored in our laboratory was used in this study; it was isolated with the ability to utilize phenol as the sole carbon source and could tolerate very high phenol concentrations up to 2 kg · m-3. Liquid cultures were grown in a mineral salt medium containing 0.5 kg · m-3 phenol at 30 °C in a rotary shaker at 200 rpm. The liquid mineral salt medium contained 0.4 kg · m-3 K2HPO4, 0.2 kg · m-3 KH2PO4, 0.1 kg · m-3 NaCl, 0.1 kg · m-3 MgSO4, 0.01 kg · m-3 MnSO4 · H2O, 0.01 kg · m-3 Fe2(SO4)3 · H2O, 0.01 kg · m-3 Na2MoO4 · 2H2O, and 0.4 kg · m-3 (NH4)2SO4 (pH 6.0). Phenol was filter-sterilized through membranes (pore size of 2 × 10-7 m) and added to the medium before inoculation.29 The cell concentration in the liquid mineral salt medium was monitored spectrophotometrically, and the cell concentration on a dry-weight basis was measured by filtering the cell suspension with a filter and drying the filter paper to a constant weight for 24 h at 105 °C. A linear relationship between the dry cell weight and the optical density (OD) was obtained as: cell concentration (kg · m-3) ) 0.35 × OD - 6.92 × 10-4.15 Immobilization Procedure. Preparation of immobilized alginate gel beads containing cells followed a similar procedure of a previous study.26 Sodium alginate [2% (w/v)] was used for the immobilization of the cells of Candida tropicalis. Inoculum of the cell suspension in the late exponential phase (OD ) 1.3, cell concentration ) 0.45 kg · m-3) was centrifuged and then added to the sterilized sodium alginate at room temperature to give a cell concentration of 9 kg · m-3. Then, the alginate/cell mixture was agitated uniformly and aseptically extruded through a needle into a stirred solution of sterile 0.1 M calcium chloride. The height of the needle and the rate of stirring of the calcium chloride solution were adjusted carefully so that uniform spherical alginate gel beads were obtained with an average diameter of 3.5 × 10-3 m. The beads were left to harden in the calcium chloride solution for 2 h for complete replacement of sodium ions by calcium ions. The apparent density was evaluated by placing a number of alginate gel beads in a 50 mL glass cylinder, and a value of 1048 kg · m-3 was obtained. Batch Phenol Biodegradation in Three-Phase ALR. The experimental apparatus is similar to that used by Feng et al.24 The Plexiglas rectangle column had a cross-sectional area of 0.2 × 0.2 m and a height of 1.0 m, and the rectangular draft


Figure 1. Time courses of riser and downcomer volume-averaged Rg, dg, and uw at different values of Ug,sup ) 0.01, 0.015, and 0.02 m/s and at fixed Cp,0 ) 150 mg/L and Rs,0 ) 0.02.

Figure 2. Time courses of riser and downcomer volume-averaged Co,g, Co,l, and Co,s at different values of Ug,sup ) 0.01, 0.015, and 0.02 m/s and at fixed Cp,0 ) 150 mg/L and Rs,0 ) 0.02.


Figure 3. Time courses of riser and downcomer volume-averaged Cp,l, Cp,s, and Cx,s at different values of Ug,sup ) 0.01, 0.015, 0.02 m/s and at fixed Cp,0 ) 150 mg/L and Rs,0 ) 0.02.

Figure 4. Time courses of riser and downcomer volume-averaged Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s at different values of Ug,sup ) 0.01, 0.015, and 0.02 m/s and at fixed Cp,0 ) 150 mg/L and Rs,0 ) 0.02.


Figure 5. Time courses of riser and downcomer volume-averaged Co,g, Co,l, and Co,s at different values of Cp,0 ) 100, 150, and 200 mg/L and at fixed Ug,sup ) 0.015 m/s and Rs,0 ) 0.02.

Figure 6. Time courses of riser and downcomer volume-averaged Cp,l, Cp,s, and Cx,s at different values of Cp,0 ) 100, 150, and 200 mg/L and at fixed Ug,sup ) 0.015 m/s and Rs,0 ) 0.02.


Figure 7. Time courses of riser and downcomer volume-averaged Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s at different values of Cp,0 ) 100, 150, and 200 mg/L and at fixed Ug,sup ) 0.015 m/s and Rs,0 ) 0.02.

Figure 8. Time courses of riser and downcomer volume-averaged Rg, dg, and uw at different values of Rs,0 ) 0.01, 0.02, and 0.03 and at fixed Ug,sup ) 0.015 m/s and Cp,0 ) 150 mg/L.


Figure 9. Time courses of riser and downcomer volume-averaged Co,g, Co,l, and Co,s at different values of Rs,0 ) 0.01, 0.02, and 0.03 and at fixed Ug,sup ) 0.015 m/s and Cp,0 ) 150 mg/L.

Figure 10. Time courses of riser and downcomer volume-averaged Cp,l, Cp,s, and Cx,s at different values of Rs,0 ) 0.01, 0.02, and 0.03 and at fixed Ug,sup ) 0.015 m/s and Cp,0 ) 150 mg/L.


Figure 11. Time courses of riser and downcomer volume-averaged Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s at different values of Rs,0 ) 0.01, 0.02, and 0.03 and at fixed Ug,sup ) 0.015 m/s and Cp,0 ) 150 mg/L.

tube that was coaxially fixed 0.045 m above the bottom had a size of 0.14 × 0.14 × 0.45 m. The square glass distributor, centrally located at the bottom of the column, was 0.05 m in width and contained 169 holes with a diameter of 0.001 m. Liquid mineral salt medium was the liquid phase with a static height of 0.6 m; its physical properties were taken as the same as those of pure water according to the correlations proposed by Escobedo et al., as the mineral salts and the liquid-phase phenol and oxygen concentrations were sufficiently low.36 Air composed of nitrogen (79% in volume fraction) and oxygen (21% in volume fraction) was the gas phase with superficial gas velocities of 0.01, 0.015, and 0.02 m/s; it was filtered by an air filter column and measured by a rotor flowmeter and then introduced into the column through a gas diffuser. At the outlet of the column, a filter was also used to protect the ALR from being polluted. Alginate gel beads containing cells were the solid phase with bead loadings of 1%, 2%, and 3%. The ALR was sterilized with 3% hydrogen peroxide solution and washed with deionized water and sterilized mineral salt medium several times; then, batch phenol biodegradation by immobilized Candida tropicalis in the three-phase ALR was performed under the initial pH of 6.0 and a temperature of 30 °C maintained by circulating thermostatted water in a water jacket, at different initial phenol concentrations of 0.1, 0.15, and 0.2 kg · m-3. Samples were taken periodically in the riser and downcomer of the ALR for the measurement of phenol and oxygen concentrations in the liquid phase at a series of locations along the column; microscope observation did not find any contamination of the system during the whole process. Measurement of the phenol concentration was done by the HPLC method presented previously.29 Measurement of the oxygen concentration was performed with an absolute oxygen electrode (Mettler Toledo 6050, Greifensee, Switzerland). Each measurement was

repeated three times, and the data shown in the corresponding figures are the average results. Results and Discussion Model Simulation of Time Courses of VolumeAveraged Process Variables. The developed CFD model was used to simulate the time courses of the riser and downcomer volume-averaged dynamic behaviors of immobilized batch phenol biodegradation in the three-phase ALR, including the hydrodynamic characteristics and species mass concentrations, as shown in Figures 1 below, under different operating conditions, such as superficial gas velocity, initial phenol concentration, and solid loading. Changes in the xygen and phenol concentrations in the liquid phase were experimentally measured and used to validate the corresponding model simulation results as shown in Figures 2, 3, 5, 6, 9, and 10. In all of these figures, the agreement is satisfactory. For comparisons of the liquidphase phenol concentration, the correlation coefficients (R2) were larger than 0.992 in all cases. For comparisons of the liquidphase oxygen concentration, the correlation coefficients (R2) were larger than 0.871 in all cases. The relatively low correlation coefficients for comparisons of the oxygen concentration compared to those for comparisons of the phenol concentration might be due to the relatively low sensitivity of the DO electrode measurement compared to the HPLC method. Figures 1-4 show the time courses of the riser and downcomer volume-averaged hydrodynamic characteristics such as the gas holdup (Rg), Sauter mean bubble diameter (dg), and axial liquid velocity (uw); species mass concentrations such as the gas-phase oxygen concentration (Co,g), liquid-phase oxygen (Co,l) and phenol (Cp,l) concentrations, and solid-phase oxygen (Co,s), phenol (Cp,s), and cell (Cx,s) concentrations; and species transport


Figure 12. Local transient profiles of dynamic behaviors of Rg, dg, uw, Rs, Co,g, Co,l, Co,s, Cp,l, Cp,s, Cx,s, Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s at Ug,sup ) 0.015 m/s, Cp,0 ) 150 mg/L, and Rs,0 ) 0.02 for t ) 20, 120, 220, 320, 420, and 520 s.

comparisons such as the difference between the gas-liquid oxygen mass-transfer source term and the liquid-solid oxygen mass-transfer source term (Γo,gl - Γo,ls), the difference between the liquid-solid oxygen mass-transfer source term and the solidphase oxygen reaction source term (Γo,ls - So,s), and the difference between the liquid-solid phenol mass-transfer source term and the solid-phase phenol reaction source term (Γp,ls Sp,s), at different values of superficial gas velocity (Ug,sup ) 0.01, 0.015, and 0.02 m/s) and fixed initial phenol concentration (Cp,0 ) 150 mg/L) and solid loading (Rs,0 ) 0.02) in the riser and downcomer of the ALR. It is clearly shown in Figure 1 that Rg increases with increasing Ug,sup, but uw does not change very much in either the riser or the downcomer. Rg in the riser is much higher than that in the downcomer, and the direction of uw in the downcomer

is reversed with respect to that in the riser, with a slightly lower absolute value. It is interesting to see that dg in the riser decreases with increasing Ug,sup. In the downcomer, dg at Ug,sup ) 0.01 and 0.015 m/s shows no obvious change, but dg has a markedly higher value at Ug,sup ) 0.02 m/s. Generally speaking, at low Ug,sup, the riser and downcomer have almost the same value of dg, whereas at high Ug,sup, the downcomer has a higher value of dg, which can be attributed to the more obvious bubble breakup effect in the riser and the more obvious bubble coalescence effect in the downcomer. Generally speaking, the hydrodynamic performance of the ALR has a very regular pattern. In immobilized batch phenol biodegradation processes, Co,g, Co,l, and Co,s are normally higher at larger Ug,sup, as shown in Figure 2, corresponding to higher bioreaction rates and thus lower Cp,l and Cp,s and higher Cx,s, as shown in Figure 3.


Figure 13. Local transient profiles of species mass concentrations Co,g, Co,l, Co,s, Cp,l, Cp,s, and Cx,s at Ug,sup ) 0.015 m/s, Cp,0 ) 150 mg/L, and Rs,0 ) 0.02 for t ) 120 s.

Experimental measurements of Cp,l support the idea that an increase in the superficial gas velocity might promote the bioreaction. Co,g in the riser is obviously higher that that in the downcomer; Co,l in the riser is slightly higher than that in the downcomer. In contrast, Co,s in the riser and downcomer are almost the same, as can be seen in Figure 2. The case is also the same for Cp,l, Cp,s, and Cx,s, which do not exhibit much difference between the riser and downcomer, as shown in Figure 3. This means that, although the riser and downcomer of the ALR have very different hydrodynamic performances, they do not exhibit much difference in bioreaction performance because of the fast liquid recirculation, which is also a distinct advantage of the ALR in terms of reducing the “dead region”. Γo,gl - Γo,ls and Γo,ls - So,s are both less than zero along the whole time course, whereas Γp,ls - Sp,s is greater than zero only at the very beginning and is less than zero for the rest of the time, as shown in Figure 4, which indicates that species interphase mass transfer is the rate-limiting step in most cases. Γo,gl - Γo,ls decreases with increasing Ug,sup, whereas Γo,ls - So,s and Γp,ls - Sp,s show little difference at varied Ug,sup. Γo,gl - Γo,ls in the riser is much smaller than that in the downcomer, whereas Γo,ls - So,s and Γp,ls - Sp,s do not show much difference in the riser and downcomer. Figures 5-7 show the time courses of the riser and downcomer volume-averaged Co,g, Co,l, and Co,s; Cp,l, and Cp,s, Cx,s; and Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s, respectively, at different values of Cp,0 ) 100, 150, and 200 mg/L and at fixed Ug,sup ) 0.015 m/s and Rs,0 ) 0.02. As it is assumed in this study that the change in phenol concentration does not affect the liquid-phase physical properties, the system hydrodynamics must not be affected either. It can be seen in Figure 5 that the change in Cp,0 has little effect on the oxygen concentrations in the gas and liquid phases. Higher Cp,0 requires longer times for complete phenol biodegradation, corresponding to higher Cp,l and Cp,s values at any time during the process, as shown in Figure 6, which results in higher Co,s values at the beginning of the process for lower consumption rates because of the phenol inhibition effect, as well as lower Co,s values at the end of the process for higher consumption rates because of the carbon

shortage effect, as shown in Figure 5. The three Cp,0 values are all above 50 mg/L, the value at which the maximum specific cell growth rate occurs,29 so they experience a similar trend as can be seen in Figure 6. At the very beginning of the process, phenol is transferred into the solid phase rapidly, resulting in fast decreases in Cp,l and Cp,s and a fast increase in Cx,s. In this period, the specific cell growth rate (µx) increases first when Cp,s is below 50 mg/L and then decreases when Cp,s is above 50 mg/L, whereas the mass-transfer rate decreases because of a decrease in the liquid-solid phenol concentration difference. When the mass-transfer rate equals the bioreaction rate, Cp,s reaches its maximum value (higher than 50 mg/L). After that, phenol is transferred into the solid phase less quickly, resulting in a slow decrease in Cp,l and Cp,s and a slow increase in Cx,s. The growth rates of cells at higher Cp,0 values in the first part do not exhibit much difference but are higher than those in the second part, resulting in higher Cx,s values at the end, as shown in Figure 6, further indicating that interphase mass transfer is the rate-limiting step and plays a more important role than bioreaction. Γo,gl - Γo,ls and Γo,ls - So,s do not change much at different values of Cp,0, whereas Γp,ls - Sp,s is larger at the beginning of the process, as shown in Figure 7, as a result of the larger difference in phenol concentrations between the liquid and solid phases and the lower bioreaction rate because of the phenol inhibition effect at higher Cp,0, which is smaller during the rest of the process as a result of the higher bioreaction rate when phenol exhibits a carbon shortage effect. Figures 8-11 show the time courses of the riser and downcomer volume-averaged values of Rg, dg, and uw; Co,g, Co,l, and Co,s; Cp,l, Cp,s, and Cx,s; and Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s, respectively, at different values of Rs,0 ) 0.01, 0.02, and 0.03 and at fixed Ug,sup ) 0.015 m/s and Cp,0 ) 150 mg/L. A change in the solid loading does not bring significant fluctuations to the hydrodynamic characteristics such as Rg, dg, and uw, as shown in Figure 8, which might be due to the small amount of solid particles added and the similar density to the water. Generally speaking, an increase in Rs,0 results in an increase in the solid-bead specific area and the liquid-solid mass transfer and bioreaction, bringing decreases in Co,g, Co,l, and Co,s in the first half of the process. In the second half of the process, biodegradation ends more rapidly at higher Rs,0, which brings quicker recovery of the oxygen concentration in both the liquid and solid phases, as shown in Figure 9. It is expected that an increase in Rg can bring an obvious decrease in the phenol concentration. However, as interphase mass transfer is the rate-limiting step and the range of phenol concentrations is much larger than the range of oxygen concentrations, the change in Cp,l and Cp,s is comparatively mild in Figure 10. It should be noticed that the experiments capture some more obvious effects of solid loading on Cp,l, which indicates that there might be further refinement of the CFD model developed in this study, especially the interphase mass-transfer model. Higher Rg means a larger quantity of cells and a lower final Cx,s at the given value of Cp,0, as shown in Figure 10. It can be found in Figure 11 that Γo,gl - Γo,ls is not as sensitive to changes in Rg. Γo,ls - So,s is smaller at higher Rg. In the beginning of the process, Γp,ls Sp,s increases with increasing Rg when it is greater than zero; in the subsequent time, Γp,ls - Sp,s decreases with increasing Rg when it is less than zero. Model Simulation of Local Transient Process Variables. This developed 3D transient CFD model is well applied to simulate the riser and downcomer volume-averaged dynamic behaviors of the immobilized batch phenol biodegradation processes in the three-phase ALR as described above, and


Figure 14. Riser and downcomer volume-averaged BSD at Ug,sup ) 0.015 m/s, Cp,0 ) 150 mg/L, and Rs,0 ) 0.02 for t ) 20, 120, 220, 320, 420, and 520 s.

the local distribution of the dynamic behaviors within the reactor is also what we care much about, which can help us better understand the performance of the three-phase bioreaction. Figure 12 is the model simulated local transient profiles of the hydrodynamic characteristics such as Rg, dg, u, Rs; specie mass concentrations such as Co,g, Co,l, Co,s, Cp,l, Cp,s, Cx,s; sourceterm differences such as Γo,gl - Γo,ls, Γo,ls - So,s, Γp,ls - Sp,s at the vertical section of the ALR from left to right, at t ) 20, 120, 220, 320, 420, 520 s from up to down, respectively, under Ug,sup ) 0.015 m/s, Cp,0 ) 150 mg/L, Rs,0 ) 0.02. It can be seen from these charts that the gas bubble plume moves wiggly in a pseudoperiodical way in the inner tube, with higher Rg in the riser compare with that in the downcomer. In the downcomer and near the inner wall of the tube, bubbles are taken downward by the circumfluence of the liquid as a result of the density difference between the top and bottom of the reactor. dg is larger above the gas distributor in the riser and entrance of the downcomer as a result of bubble accumulation. Solid particles distribute nonuniformly in the reactor, with obvious accumulation in the corners. The distribution of Co,g, Co,l, Co,s, Cp,l, Cp,s, Cx,s at anywhere within the reactor and the concentration changes with time can be visually exhibited by the model prediction. Co,g changes not much as a whole through the process and has a lower value in the downcomer compared with that in the riser, especially in the corners of the bottom. Co,l experiences a slight decrease and makes an almost uniformly distribution in the riser as well as in the downcomer. Co,s decreases obviously as the phenol biodegradation proceeds and rises up at the end when the bioreaction ceases; the fluctuation of the distribution of Co,s within the ALR is not so obvious either. The cases of phenol degradation and cell growth are shown as expected and the local distributions of Cp,s and Cx,s are almost uniform in the specified ranges. The local transient profiles of the source-term differences such as Γo,gl - Γo,ls, Γo,ls - So,s and Γp,ls - Sp,s are also simulated, corresponding to the hydrodynamic and bioreaction characteristics at that very moment.

In Figure 12, species mass concentration ranges are relatively wide for better comparisons at different time. However, the local distribution fluctuations might be ignored at certain locations where the differences are not so big. Figure 13 is the model prediction of the local transient oxygen, phenol and cell concentration profiles in each phase at t ) 120 s. The ranges of Co,g, Co,l, Co,s, Cp,l, Cp,s, Cx,s are 280-300 mg/L, 5.5-6.5 mg/L, 0-1.0 mg/L, 55-65 mg/L, 54-56 mg/L, 9.105-9.110 g/L in Figure 13, which are much smaller compared with 260-300 mg/L, 0-8 mg/L, 0-8 mg/L, 0-150 mg/L, 0-150 mg/L, 9.0-9.2 g/L in Figure 12. It can be seen from Figure 13 that the distribution of Co,g is the most heterogeneous one with higher values in the riser, and lower values in the downcomer as well as in the bottom of the reactor. It is clear that the distribution of Co,g is very dependent on that of Rg. The distribution of Co,l is not so uniform in the ALR, with a much more obvious fluctuation in the downcomer. The case of the distribution of Co,s is that: it has higher values near the walls of the column as well as the inner tube and also in the corners of the bottom, where the bioreaction rates are lower. In Figure 12, it can hardly see any difference in the distribution of Cp,l, which exhibits a clear heterogeneous distribution in Figure 13 within a much smaller range however. The distribution of Cp,s follows a similar trend with Cp,l. The distribution of Cx,s is almost uniform in the main body and has lower values near the walls of the outer column as well as the inner tube and also in the corners of the bottom, where some solid beads stay. From the above two figures, it can be concluded that this developed CFD model can also be well applied to capture the local transient distributions of the dynamic behaviors of immobilized phenol biodegradation in a three-phase ALR, including the hydrodynamic characteristics and species mass concentration profiles, which are very important to understand and optimize the performance of the process. It should be pointed out that, although the distributions of the liquid-phase oxygen and phenol concentrations exhibit


Figure 15. Local transient profiles of BSD at Ug,sup ) 0.015 m/s, Cp,0 ) 150 mg/L, and Rs,0 ) 0.02 for t ) 20, 120, 220, 320, 420, and 520 s.

heterogeneous phenomena as shown in Figure 13 to some extent, the validation of the riser and downcomer volume-averaged

model-simulated results by experimental measurements mentioned in the Experiments section is convincing, as the fluctua-


Figure 16. Comparison of reactor volume-averaged dynamic behaviors between immobilized phenol biodegradation performance in ALR and BCR at Ug,sup ) 0.02 m/s, Cp,0 ) 150 mg/L, and Rs,0 ) 0.02. (a) Rg, dg, uw, Co,g, Co,l, and Co,s. (b) Cp,l, Cp,s, Cx,s, Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s.


tions of the concentrations are all within 8.3% (6.0 ( 0.5 and 60 ( 5 mg/L), and the experimental results are the average values of measurements at a series of locations along the column in the riser and downcomer of the reactor. Model Simulation of BSD. Prediction of the BSDs in the riser and downcomer of the three-phase ALR has been done previously.26 In this study, the riser and downcomer volumeaveraged size fraction of each bubble group and the local transient profiles of the bubble group size fraction distribution were also simulated by the developed model for the three-phase bioreaction process, as shown in Figures 14 and 15, for Ug,sup ) 0.015 m/s, Cp,0 ) 150 mg/L, and Rs,0 ) 0.02. Figure 14 shows the volume-averaged BSDs in the riser and downcomer at t ) 20, 120, 220, 320, 420, and 520 s. Small bubbles form a larger proportion of all bubbles in the riser compared to that in the downcomer, and the third bubble group has the largest volumeaveraged size fraction of about 0.4 in the riser and about 0.2 in the downcomer. Obviously, larger bubbles form a larger proportion in the downcomer than in the riser as a consequence of continuous gas accumulation by liquid circulation there. Figure 15 shows the model prediction of the local transient profiles of the BSDs of groups 1-10 in the ALR at t ) 20, 120, 220, 320, 420, and 520 s. It is clear that small bubbles (groups 1-5) prevail throughout the whole reactor and the third group makes up the largest size fraction of all bubble groups. Comparison between ALR and Bubble Column Reactor (BCR) Immobilized Phenol Biodegradation. To better validate the advantages of the ALR, the CFD model developed in this study was also used to simulate the immobilized phenol biodegradation process in a three-phase bubble column reactor (BCR), which has geometric dimensions similar to those of the ALR used in this work only without the inner tube. The performance of the BCR was compared with that of the ALR as shown in Figure 16, in terms of the reactor volumeaveraged values of Rg, dg, uw, Co,g, Co,l, Co,s, Cp,l, Cp,s, Cx,s, Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s, under the same operating conditions of Ug,sup ) 0.02 m/s, Cp,0 ) 150 mg/L, and Rs,0 ) 0.02. From Figure 16a, it can be seen that the ALR has higher values of Rg and dg but a lower value of uw under the same operating conditions. Co,g in the ALR is lower than that in the BCR, but Co,l and Co,s are somewhat higher in the ALR. Correspondingly, it can be seen in Figure 16b that the ALR has lower values of Cp,l and Cp,s, as well as a lower Cx,s. The source-term differences Γo,gl - Γo,ls, Γo,ls - So,s, and Γp,ls - Sp,s are all less than zero most of the time for the process in the ALR as well as in the BCR, with a slight difference between the two reactor types. It can be concluded that the ALR exhibits better performance in phenol biodegradation because of its wellregulated flow pattern compared to that in the BCR. Concluding Remarks A 3D transient CFD model was developed for simulating the dynamic behaviors of batch phenol biodegradation by immobilized Candida tropicals in a three-phase ALR, coupling of three-phase fluid flow, species interphase mass transfer, and intrinsic bioreaction, with the MUSIG model employed to determine the BSD in the reactor. First, time courses of the riser and downcomer volumeaveraged hydrodynamic characteristics, species mass concentrations, and species source-term differences in the ALR were simulated using the developed model. Performance differences between the two main regions of the ALR were compared and discussed. Model simulation results of the volume-averaged oxygen and phenol concentration changes in the liquid phase

were well validated by corresponding experimental measurements. The results revealed that species interphase mass transfer is the rate-limiting step of the biodegradation process most of the time through the species transport source-term comparisons. Then, local transient profiles of the dynamic behaviors of phenol biodegradation in the three-phase ALR were predicted reasonably well by the developed model. Detailed analysis of the model simulations revealed that the species mass concentration distributions are controlled by the dynamic changing of the three-phase hydrodynamics and the source-term differences. Moreover, volume-averaged and local transient BSDs in the riser and downcomer were also predicted by the model, which demonstrated that small bubbles make up a larger fraction among all gas bubble groups, which is favorable to species interphase mass transfer and, therefore, to the bioreaction. Finally, immobilized phenol biodegradation performance between the ALR and the BCR was compared, which confirmed that the ALR behaves better because of its well-regulated flow pattern. Generally speaking, this developed 3D transient CFD model can be well applied to capture the dynamic behaviors of immobilized phenol biodegradation in the three-phase ALR, which will be helpful in optimizing the design and construction of such reactors and the operation of the biodegradation process, as well as facilitating scale-up strategies. Acknowledgment The authors acknowledge the financial support provided by the National 973 Project of China (2007CB714302), Research FundfortheDoctoralProgramofHigherEducation(20060056010), International Science and Technology Cooperation Program (2007DFA90530), Natural Science Foundation of Tianjin (07JCZDJC01500), Key Project of Chinese Ministry of Education, Program for Changjiang Scholars and Innovative Research Team in University, and Program of Introducing Talents of Discipline to Universities (B06006). Nomenclature A ) growth-associated constant for phenol consumption a ) specific area, m-1 B ) non-growth-associated constant for phenol consumption, s-1 C ) concentration, kg · m-3 D ) kinematic diffusivity, m2 · s-1 d ) diameter, m g ) gravitational acceleration, m · s-2 K ) mass-transfer coefficient, m · s-1 Ki ) phenol inhibition constant, kg · m-3 Ko ) oxygen half-saturation constant, kg · m-3 Ks ) phenol half-saturation constant, kg · m-3 S ) reaction source term, kg · m-3 · s-1 ScT ) turbulence Schmidt number, default value is 0.9,33 dimensionless t ) time, s Ug,sup ) superficial gas velocity, m · s-1 u ) velocity vector, m · s-1 x ) mass fraction Yx/o ) cell growth yield based on oxygen Greek Letters R ) volume fraction ε ) turbulence eddy dissipation, m2 · s-3 Γ ) interphase mass-transfer source term, kg · m-3 · s-1 µ ) specific cell growth rate, s-1, in eqs 12 and 13 µ ) molecular viscosity, Pa · s, in eqs 18-20

Ind. Eng. Chem. Res., Vol. 48, No. 9, 2009 4529 -1

µmax ) kinetic constant, s µT ) turbulence-induced viscosity, Pa · s F ) density, kg · m-3 Superscripts * ) saturated state - ) dimensionless state Subscripts 0 ) initial state a ) alginate gel g ) gas phase l ) liquid phase m ) mineral salt medium n ) nitrogen o ) oxygen p ) phenol s ) solid phase sup ) superficial x ) cell

Literature Cited (1) Aleksieva, Z.; Ivanova, D.; Godjevargova, T.; Atanasov, B. Degradation of Some Phenol Derivatives by Trichosporon cutaneum R57. Process Biochem. 2002, 37, 1215. (2) Bandhyopadhyay, K.; Das, D.; Bhattacharyya, P.; Maiti, B. R. Reaction Engineering Studies on Biodegradation of Phenol by Pseudomonas putida MTCC 1194 Immobilized on Calcium Alginate. Biochem. Eng. J. 2001, 8, 179. (3) Alva, V. A.; Peyton, B. M. Phenol and Catechol Biodegradation by the Haloalkaliphile Halomonas campisalis: Influence of pH and Salinity. EnViron. Sci. Technol. 2003, 37, 4397. (4) Ozaki, H.; Liu, Z.; Terashima, Y. Utilization of Microorganisms Immobilized with Magnetic Particles for Sewage and Wastewater Treatment. Water Sci. Technol. 1991, 23, 1125. (5) Torres, L. G.; Sańchez-de-la-Vega, A.; Beltrań, N. A.; Jimeńez, B. E. Production and Characterization of a Ca-alginate Biocatalyst for Removal of Phenol and Chlorophenols from Wastewaters. Process Biochem. 1998, 33, 625. (6) Bandhyopadhyay, K.; Das, D.; Maiti, B. R. Solid Matrix Characterization of Immobilized Pseudomonas Putida MTCC 1194 Used for Phenol Degradation. Appl. Microbiol. Biotechnol. 1999, 51, 891. (7) Juarez-Ramirez, C.; Ruiz-Ordaz, N.; Cristiani-Urbina, E.; GalindezMayer, J. Degradation Kinetics of Phenol by Immobilized Cells of Candida tropicalis in Fluidized Bed Reactor. World J. Microb. Biot. 2001, 17, 697. (8) Mordocco, A.; Kuek, C.; Jenkins, R. Continuous Degradation of Phenol at Low Concentration Using Immobilized Pseudomonas putida. Enzyme Microb. Technol. 1999, 25, 530. (9) Pai, S. L.; Hsu, Y. L.; Chong, N. M.; Sheu, C. S.; Chen, C. H. Continuous Degradation of Phenol by Rhodococcus sp. Immobilized on Granular Activated Carbon and in Calcium Alginate. Bioresour. Technol. 1995, 51, 37. (10) Wen, J. P.; Jia, X. Q.; Cheng, X. R.; Yang, P. Characteristics of Three-Phase Internal Loop Airlift Bioreactors with Complete Gas Recirculation for Non-Newtonian Fluids. Bioprocess Biosyst. Eng. 2005, 27, 193. (11) Viggiani, A.; Olivieri, G.; Siani, L.; Di Donato, A.; Marzocchella, A.; Salatino, P.; Barbieri, P.; Galli, E. An Airlift Biofilm Reactor for the Biodegradation of Phenol by Pseudomonas stutzeri OX1. J. Biotechnol. 2006, 123, 464. (12) Ryan, D. R.; Leukes, W. D.; Burton, S. G. Fungal Bioremediation of Phenolic Wastewaters in an Airlift Reactor. Biotechnol. Prog. 2005, 21, 1068. (13) Zhang, Y.; Quan, X.; Rittmann, B. E.; Wang, J.; Shi, H.; Qian, Y.; Yu, J. IAL-CHS (Internal Airlift Loop-Ceramic Honeycomb Supports) Reactor Used for Biodegradation of 2,4-Dichlorophenol and Phenol. Water Sci. Technol. 2004, 49, 247. (14) Quan, X. C.; Shi, H. C.; Zhang, Y. M.; Wang, J. L.; Qian, Y. Biodegradation of 2,4-Dichlorophenol and Phenol in an Airlift Inner-loop Bioreactor Immobilized with Achromobacter sp. Sep. Purif. Technol. 2004, 34, 97.

(15) Jia, X. Q.; Wen, J. P.; Jiang, Y.; Liu, X. L.; Feng, W. Modeling of Batch Phenol Biodegradation in Internal Loop Airlift Bioreactor with Gas Recirculation by Candida tropicalis. Chem. Eng. Sci. 2006, 61, 3463. (16) Bagatin, R.; Andrigo, P.; Protto, L.; Meastri, F.; Di Muzio, F.; Masi, M.; Carraa, P. Fluid Dynamics of Gas-Liquid Airlift Reactors through CFD Packages. In PVP Computational Technologies for Fluid/Thermal/Structural/ Chemical Systems with Industrial Applications; ASME: New York, 1999; Vol. 397-1, pp 293-303. (17) Glover, G. M. C.; Blazeˇj, M.; Generalis, S. C.; Markosˇ, J. ThreeDimensional Gas-Liquid Simulation of an Airlift Bubble Column Reactor. Chem. Pap. 2003, 57, 387. (18) Oey, R. S.; Mudde, R. F.; Van Den Akker, H. E. A. Numerical Simulations of an Oscillating Internal-Loop Airlift Reactor. Can. J. Chem. Eng. 2003, 81, 684. (19) van Baten, J. M.; Ellenberger, J.; Krishna, R. Hydrodynamics of Internal Air-lift Reactors: Experiments versus CFD Simulations. Chem. Eng. Process. 2003, 42, 733. (20) van Baten, J. M.; Ellenberger, J.; Krishna, R. Using CFD to Describe the Hydrodynamics of Internal Air-lift Reactors. Can. J. Chem. Eng. 2003, 81, 660. (21) Mudde, R. F.; Van Den Akker, H. E. A. 2D and 3D Simulations of an Internal Airlift Loop Reactor on the Basis of a Two-Fluid Model. Chem. Eng. Sci. 2001, 56, 6351. (22) van Baten, J. M.; Krishna, R. Comparison of Hydrodynamics and Mass Transfer in Airlift and Bubble Column Reactors Using CFD. Chem. Eng. Technol. 2003, 26, 1074. (23) Blazeˇj, M.; Glover, G. M. C.; Generalis, S. C.; Markosˇ, J. GasLiquid Simulation of an Airlift Bubble Column Reactor. Chem. Eng. Process. 2004, 43, 137. (24) Feng, W.; Wen, J. P.; Liu, C. Y.; Yuan, Q.; Jia, X. Q.; Sun, Y. Modeling of Local Dynamic Behavior of Phenol Degradation in an Internal Loop Airlift Bioreactor by Yeast Candida tropicalis. Biotechnol. Bioeng. 2007, 97, 251. (25) Oey, R. S.; Mudde, R. F.; Portela, L. M.; Van Den Akker, H. E. A. Simulation of a Slurry Airlift Using a Two-Fluid Model. Chem. Eng. Sci. 2001, 56, 673. (26) Jia, X. Q.; Wen, J. P.; Feng, W.; Yuan, Q. Local Hydrodynamics Modeling of a Gas-Liquid-Solid Three-Phase Airlift Loop Reactor. Ind. Eng. Chem. Res. 2007, 46, 5210. (27) Banerjee, I.; Modak, J. M.; Bandopadhyay, K.; Das, D.; Maiti, B. R. Mathematical Model for Evaluation of Mass Transfer Limitations in Phenol Biodegradation by Immobilized Pseudomonas putida. J. Biotechnol. 2001, 87, 211. (28) Washburn, E. W., Ed. International Critical Tables of Numerical Data, Physics, Chemistry and Technology; McGraw-Hill: New York, 1926. (29) Jiang, Y.; Wen, J. P.; Li, H. M.; Yang, S. L.; Hu, Z. D. The Biodegradation of Phenol at High Initial Concentration by the Yeast Candida tropicalis. Biochem. Eng. J. 2005, 24, 243. (30) Livingston, A. G.; Chase, H. A. Modeling Phenol Degradation in a Fluidized-Bed Bioreactor. AIChE J. 1989, 35, 1980. (31) Dhanasekharan, K. M.; Sanyal, J.; Jain, A.; Haidari, A. A Generalized Approach to Model Oxygen Transfer in Bioreactors Using Population Balances and Computational Fluid Dynamics. Chem. Eng. Sci. 2005, 60, 213. (32) Arters, D. C.; Fan, L. S. Solid-Liquid Mass Transfer in a GasLiquid-Solid Fluidized Bed. Chem. Eng. Sci. 1986, 41, 107. (33) ANSYS CFX-SolVer, Release 10.0: Theory; ANSYS Canada Ltd.: Waterloo, Canada, 2005. (34) Padial, N. T.; VanderHeyden, W. B.; Rauenzahn, R. M.; Yarbro, S. L. Three-Dimensional Simulation of a Three-Phase Draft-Tube Bubble Column. Chem. Eng. Sci. 2000, 55, 3261. (35) Feng, W.; Wen, J. P.; Fan, J. H.; Yuan, Q.; Jia, X. Q.; Sun, Y. Local Hydrodynamics of Gas-Liquid-Nanoparticles Three-Phase Fluidization. Chem. Eng. Sci. 2005, 60, 6887. (36) Escobedo, J. ; Ali Mansoori, G. Asphaltene and Other HeavyOrganic Particle Deposition during Transfer and Production Operations. In Proceedings of the 1995 SPE Annual Technical Conference and Exhibition, Production Operations and Engineering/General; Society of Petroleum Engineers (SPE): Richardson, TX, 1995; p 343.

ReceiVed for reView May 24, 2008 ReVised manuscript receiVed February 19, 2009 Accepted February 25, 2009 IE800816D

CFD Modeling of Immobilized Phenol Biodegradation in Three-Phase

Recommend Documents