A model for treating isopropyl alcohol and acetone mixtures in a trickle-bed air biofilter

Process Biochemistry 39 (2004) 1849–1858

A model for treating isopropyl alcohol and acetone mixtures in a trickle-bed air biofilter Chungsying Lu∗ , Kwotsair Chang, Shihchieh Hsu Department of Environmental Engineering, National Chung Hsing University, Taichung 402, Taiwan Received 9 May 2003; accepted 3 September 2003

Abstract A mathematical model that incorporates mass transfer process and biofilm reactions is presented to predict the performance of a trickle-bed air biofilter (TBAB) for treating isopropyl alcohol (IPA) and acetone (ACE) mixtures. The model consists of a set of mass balance equations for IPA, ACE and oxygen in the bulk gas phase and within the biofilm. The effluent gas phase IPA and ACE concentrations predicted by the present model were in good agreement with the measured data available in a previous study. The important parameters were evaluated by sensitivity analysis to determine their respective effects on model performance. Four parameters were identified that strongly influenced model performance: surface area of the biofilm per unit volume of packing material (AS ), empty-bed residence time (EBRT), maximum specific growth rate of microorganism (µm ), and microbial yield coefficient (Y). Practical applications of the model to derive the performance equation of TBAB for treating different inlet IPA and ACE concentrations were also demonstrated. © 2003 Elsevier Ltd. All rights reserved. Keywords: Modeling; Biofiltration; Trickle-bed air biofilter; Isopropyl alcohol; Acetone; Sensitivity analysis; Performance equation

1. Introduction The trickle-bed air biofilter (TBAB) is a relatively new technology which has been proven very efficient for treating many kinds of volatile organic compounds (VOCs) from waste gases by a number of researchers [1–4]. The process involves mass transfer of VOCs from the gas phase to the biofilm, and subsequent bio-oxidation within the biofilm. Therefore, a thorough understanding of the factors that influence the rates of mass transfer process and biofilm reaction is necessary before practical application of a TBAB in the field can be extensively realized. These considerations result in efforts to develop a valid model for predicting the TBAB performance. Effective modeling can lead to the development of a trustworthy performance equation that decreases the time and cost of experimentation at the pilot scale. This paper presents a mathematical model that incorporates mass transfer process and biofilm reactions to predict the performance of TBAB for treating isopropyl alcohol (IPA) and acetone (ACE) mixtures. They are com-

monly emitted from the manufacture of semi-conductor and opto-electron that are the major industries in Taiwan. The model performance is evaluated by the measured data available in a previous study [4]. Effects of the important parameters on the model performance are determined in the sensitivity analysis and practical application of the model to derive the performance equation of TBAB is also demonstrated.

2. Theory Consider the case of a VOC-containing air stream moving through a column filled with coal particles that are covered with a steady-state biofilm. VOCs are transported to the air/biofilm interface, where they are absorbed into the biofilm and employed as carbon and/or energy sources by the microorganisms. The physical concept of this process is shown schematically in Fig. 1. 2.1. Basic assumptions

∗

Corresponding author. Tel.: +886-4-2285-2483; fax: +886-4-2286-2587. E-mail address: [email protected] (C. Lu). 0032-9592/$ – see front matter © 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.procbio.2003.09.019

The following major assumptions are made in developing a mathematical model for IPA and ACE removal by a TBAB:

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C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

d 2 SO 2 dSO + XV f(XV )DO 2 = −f(XV )DO r dr dr

Fig. 1. Schematic diagram of trickle-bed air biofilter for treating mixed IPA and ACE vapor.

1. The system is in a pseudo-steady-state operating condition. 2. The gas flow is in the axial direction alone and the flow velocity remains constant. 3. Since the biofilm thickness is very small compared to the inner radius of coal particle, the convective transport within the biofilm is neglected. 4. There is no boundary layer at the air/biofilm interface and the concentration of compound within the biofilm is a function of the concentration of that compound in the gas phase in contact with the biofilm [5]. 5. Every species of microorganisms exists uniformly in the whole steady-state biofilm, that is, the sum of all microorganisms is regarded as one kind of biomass within the biofilm. 6. The metabolic reactions only occur within the biofilm. 7. The mass diffusivity (D), biofilm density (XV ) and biofilm thickness (δ) are constant through the TBAB. 8. In the gas phase, there are no concentration variations in the radial direction of the biofilter column and the axial diffusion of each compound can be neglected as compared to axial convection. 2.2. Model development On the basis of above assumptions, the governing equations that describe the transport of IPA, ACE and oxygen within the biofilm are expressed as f(XV )DI

d 2 SI 2 dSI XV = −f(XV )DI µI + r dr YI dr 2

XV d 2 SA 2 dSA + µA f(XV )DA 2 = −f(XV )DA r dr YA dr

(1)

 µI µA + YOI YOA (3)

where subscripts I, A and O represent IPA, ACE and oxygen; f(XV ) the correction factor for the mass diffusivity within the biofilm; D the mass diffusivity in water; S the liquid phase concentration; r the radial direction; XV the biofilm density; µ the specific growth rate of microorganism; and Y the microbial yield coefficients. The terms on the left hand side and the first terms on the right hand side of Eqs. (1)–(3) account for the molecular diffusion of IPA, ACE and oxygen in the radial direction. The terms on the right hand side (RHS) of Eqs. (1) and (2) consider the utilization of IPA and ACE by the microorganisms, while the second term on the RHS of Eq. (3) accounts for the consumption of oxygen during the removal of IPA and ACE. The specific growth rate of microorganism is described by a dual Haldane-type dependence on the IPA, ACE and oxygen, and is given by the following expression µmI SI SO µI = (4) 2 K KSI + SI + SI /KiI + KIA SA OI + SO µA =

SO µmA SA 2 K KSA + SA + SA /KiA + KAI SI OA + SO

(5)

where µm is the maximum specific growth rate of microorganism; KS the half-saturation constant; KO the oxygen half-saturation constant; Ki the inhibition constant; KIA and KAI are the cross-inhibition constants for IPA and ACE expressing interaction with ACE and IPA, respectively. The corresponding boundary conditions are CI CA CO (6) , SA = at r = R + δ, SI = , SO = mI mA mO dSI dSA dSO = = =0 (7) dr dr dr where R is the radius of coal particle; δ the biofilm thickness; C the gas phase concentration; and m the thermodynamic distribution coefficient of a compound between the air and water. The governing equations for IPA, ACE and oxygen in the air stream are 
dCI dSI ug = AS f(XV )DI (8) dh dr r=R+δ 
dCA dSA ug = AS f(XV )DA (9) dh dr r=R+δ
 dCO dSO ug = AS f(XV )DO (10) dh dr r=R+δ at r = R,

with initial conditions at h = 0,

(2)




CI = CIi ,

CA = CAi ,

CO = COi

(11)

where ug is the superficial gas velocity; h the position along the TBAB; AS the surface area of bioflim per unit volume

C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

of packing material; and Ci the gas phase influent concentration.

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Table 1 Values of parameters used in the model verification Parameter

Unit

Values

References

where is the ratio of VOC concentration at the exit to that at the entrance of TBAB; ∆ = f(XV )DAS HKS m/ug δCi [6]; H the height of TBAB packed with media; and α, β the coefficients of Eq. (12), which can be determined either from the experimental data or from the theoretical predictions.

AS COi DA DI DO mA mI mO f(XV ) KSA KSI KAI KIA KiA KiI KO H R XV YA

cm−1

3 2.75 × 10−5 1.15 × 10−5 1.11 × 10−5 2.41 × 10−5 0.0016 0.000347 34.4 0.070–0.26 9.48 × 10−5 3.54 × 10−4 2.58 × 10−3 4.37 × 10−3 5.44 × 10−4 1.86 × 10−3 2.67 × 10−7 85 1 0.07–0.28 0.40

This [5] [14] [14] [12] [8] [8] [5] [13] [9] [9] This This [9] [9] [5] This This This [9]

2.4. Numerical analysis

YI

2.3. Performance equation From a design or operational perspective, the aim would be reach a relatively high VOC removal efficiency and minimize the cost. Therefore, the performance equation is necessary for selecting a best design and operating condition. A correlation equation to predict the performance of TBAB for VOCs removal can be expressed by the following exponential relationship Ce∗ = α exp(−β∆)

(12)

Ce∗

Eqs. (1)–(3) along with the boundary conditions constitute a set of coupled boundary value problems (BVPs) that describe the simultaneous mass transfer and metabolic reactions of IPA, ACE and oxygen within the biofilm. The numerical evaluation of these BVPs was performed using the IMSL [7] subroutine, DBVPFD, for the solution of nonlinear multipoint and moving boundary value problems. Eqs. (8)–(10) along with the initial conditions form a system of ordinary differential equations (ODEs) that describes the simultaneous transport of IPA, ACE and oxygen in the air stream. These ODEs are solved by a stiff ordinary differential equation solver, DIVPAG [7]. The procedure for solving these equations is provided below. The concentration profiles and mass fluxes of IPA, ACE and oxygen within the biofilm region are obtained by solving Eqs. (1)–(3) at the inlet conditions (h = 0) where the values of inlet gas phase concentrations are known. Using the mass fluxes at the air/biofilm interface, the mass balance Eqs. (8)–(10) are then solved to obtain the gas phase concentrations at a position h from the inlet. At this position the concentration profiles and mass fluxes within the biofilm are solved again and the procedure is repeated up to the point where a h increment leads to the exit position from the TBAB (h = H). The employed spatial step size (h) is 0.1 cm.

3. Results and discussion 3.1. Parameters estimation Formulation of the present model required that the kinetic parameters and physical constants in the mass balance

YOA YOI µmI µmA δ

g/cm3 cm2 /s cm2 /s cm2 /s – – – – g/cm3 g/cm3 – – g/cm3 g/cm3 g/cm3 cm cm g/cm3 g dry biomass produced/g ACE consumed g dry biomass produced/g IPA consumed g dry biomass produced/g O2 consumed g dry biomass produced/g O2 consumed s−1 s−1 cm

work

work work

work work work

0.29

[9]

0.24

[9]

0.14

[9]

5.15 × 10−5 1.11 × 10−4 0.008–0.025

[9] [9] This work

equations be defined. Most parameters used in this work are taken from the experimental conditions and results or from the typical values in the literature and are listed in Table 1. An estimation of important parameters is provided below. 3.1.1. Distribution coefficients The values of mI and mA (1 atm, 20 ± 2 ◦ C) for the IPA/water and ACE/water system were adopted from the literature [8] and equalled 3.47 × 10−4 and 1.60 × 10−3 , respectively. The mO value (1 atm, 25 ◦ C) for the oxygen/water system is equal to 34.4 [5]. These literature values were employed in the present study. 3.1.2. Yield coefficients Lin [9] has conducted a series of shake-flask experiments on single VOC removal by suspended VOC-utilizing consortium. The average YI and YA values of 0.288 and 0.400 g dry biomass produced/g VOC consumed, respectively, were obtained in his study and employed in the model. The yield coefficients of biomass on oxygen, YIO and YAO must be evaluated from the theoretical approach. Since (NH4 )2 SO4 was used as the primary nitrogen source in the nutrient feed and a typical cellular composition can be represented as CH1.8 O0.5 N0.2 [10], the stoichiometry for IPA and ACE

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C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

oxidation and cell synthesis is C3 H8 O + 3.76O2 + 0.07(NH4 )2 SO4 → 0.70CH1.8 O0.5 N0.2 + 2.30CO2 + 3.58H2 O + 0.07H2 SO4

(13)

C3 H0 O + 3.02O2 + 0.09(NH4 )2 SO4 → 0.93CH1.8 O0.5 N0.2 + 2.07CO2 + 2.44H2 O + 0.09H2 SO4

(14)

According to above equations, the YOI and YOA values were estimated as 0.14 and 0.24 g dry biomass produced/g O2 consumed, respectively. 3.1.3. Biological kinetic constants The results of shake-flask experiments conducted by Lin [9] were also employed to determine the biological kinetic

constants for single VOC removal. The µmI and µmA were estimated as 5.15×105 and 1.11×104 s−1 ; KSI and KSA were estimated as 3.54 × 10−4 and 9.48 × 10−5 g/cm3 and KiI and KiA were estimated as 1.86 × 10−3 and 5.44 × l0−4 g/cm3 . Chang [11] has also conducted a series of shake-flask experiments on the removal of IPA and ACE mixtures by suspended VOC-utilizing consortiums. Results of the specific growth rate of the microorganism (µI and µA ) by the batch cultivation for different initial IPA and ACE concentrations (SI and SA ) are shown as solid triangle (䉱) in Fig. 2a and b. Oxygen limitation was assumed unimportant since the liquid volume was small and mixing in the flask was quite fast. That is, the SO value is much greater than the KO value. Therefore, the removal of IPA and ACE can be described by a single Haldane-type expression. Value of KIA in Eq. (4) is determined by taking the inverse of Haldane equation, multiplying SI in both sides and substituting SI , µI , µmI , KSI , KiI and SA for linear regression. The results are shown as a

-1

Specific growth rate (hr )

0.12

0.09

0.06

Measured 0.03

0.00 0.0E+00

Simulated

5.0E-04

1.0E-03

1.5E-03

2.0E-03

2.5E-03

3.0E-03

3

(a)

Initial IPA concentration (g/cm ) 0.30

-1

Specific growth rate (hr )

0.24

0.18

0.12

Measured Simulated

0.06

0.00 0.0E+00 (b)

2.0E-04

4.0E-04

6.0E-04

3

Initial ACE concentration (g/cm )

Fig. 2. Relationship between specific growth rates of microorganism and initial VOC concentrations: (a) IPA and (b) ACE.

C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

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150 IPA

ACE

Concentration (ppmv)

120

90

60

30

0 0.0

0.2

0.4

0.6

0.8

1.0

h/H Fig. 3. Comparisons of the predicted and measured gas phase IPA and ACE concentrations against the incremental biofilter length at EBRT of 60 s.

solid line (—) in Fig. 2a. Value of KAI in Eq. (5) is determined using an analogous approach and is shown as a solid line (—) in Fig. 2b. High correlation coefficients of 0.9888 and 0.8796 were obtained for data of Fig. 2a and b. The KAI and KIA were estimated as 2.58 × 10−3 and 4.37 × 10−4 respectively. The KOI and KOA were adopted from the literature as 2.67 × 10−7 g/cm3 [5]. 3.1.4. Mass diffusivities The mass diffusivity of oxygen in water at 25 ◦ C was taken from the literature [12]. The IPA and ACE mass diffusivity in water at 25 ◦ C was estimated by using the Wilke–Chang equation [14]. The correction factor for the mass diffusivity within the biofilm, f(XV ), is a function of biofilm density and

can be estimated from the empirical equation of Fan et al. [13]. 3.2. Model verification The performance of the present model was evaluated by comparing its numerical solutions with the measured data of runs 2, 6, 7 in a previous study [4]. The TBABs were operated at EBRTs of 60, 30 and 20 s with influent air containing 150 ppmv IPA and 150 ppmv ACE. Figs. 3–5 show comparisons of the measured and predicted gas phase IPA and ACE concentrations against the incremental biofilter length. Symbols represent the measured data while lines depict the predicted results. It was seen that good agreement between

150

IPA ACE

Concentration (ppmv)

120

90

60

30

0 0.0

0.2

0.4

0.6

0.8

1.0

h/H Fig. 4. Comparisons of the predicted and measured gas phase IPA and ACE concentrations against the incremental biofilter length at EBRT of 30 s.

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C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

Fig. 5. Comparisons of the predicted and measured gas phase IPA and ACE concentrations against the incremental biofilter length at EBRT of 20 s.

1.0

As = 1 cm-1 As = 3 cm-1 As = 5 cm-1

0.8

C/C i

0.6

0.4

0.2

0.0

0.0

0.2

0.4

(a)

0.6

0.8

1.0

h/H

1.0

As = 1 cm-1 As = 3 cm-1 As = 5 cm-1

0.8

C/C i

0.6

0.4

0.2

0.0 0.0 (b)

0.2

0.4

0.6

0.8

1.0

h/H

Fig. 6. Effects of varying biofilm surface area per unit volume of packing material (AS ) on the dimensionless concentration profile: (a) IPA and (b) ACE.

C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

the measured data and the predicted results is obtained in the middle part and the effluent of TBAB. The differences in the removal efficiencies of IPA and ACE were generally on the order of below 3%. The present model appears efficient to predict the TBAB performance for removal of IPA and ACE mixtures. 3.3. Sensitivity study Having established the accuracy and consistency of the present model, a sensitivity analysis of important parameters on the performance of TBAB were conducted. The parameters described in the prediction of run 2 (EBRT = 60 s, CIi = 3.73 × 107 g/cm3 , CAi = 3.56 × 10−7 g/cm3 , COi = 2.75 × 10−4 g/cm3 , AS = 3 cm−1 , µmI = 5.15 × 10−5 s−1 , µmA = 1.11 × 10−4 s−1 KSI = 3.54 × 10−4 g/cm3 , KSA = 9.48 × 10−5 g/cm3 , YI = 0.288 g dry biomass produced/g IPA consumed, YA = 0.400 g dry biomass produced/g ACE

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consumed) are used as the base case. Trials are conducted for these parameters at above or below the base case by certain factors, keeping all other variables constant. Effects of altering AS from 1 to 5 cm−1 on the performance of TBAB are shown in Fig. 6. Note that the dimensionless IPA and ACE concentration profiles are sensitive to the change of AS . An increase of AS provides a lower IPA and ACE concentration profile due to an increase in the surface area of biofilm available for the mass transfer of IPA and ACE from gas phase to the air/biofilm interface. The removal efficiencies of IPA and ACE increased from 78 to 100% and from 56 to 100%, respectively, with an increase of AS from 1 to 5 cm−1 . A sensitivity analysis of EBRT from 30 to 90 s was carried out and the results are shown in Fig. 7. The dimensionless IPA and ACE concentration profiles are very sensitive to the change of EBRT. A longer EBRT results in a lower IPA and ACE concentration profile due to an increase in the time

1.0 EBRT = 90 s EBRT = 60 s EBRT = 30 s

0.8

C/C i

0.6

0.4

0.2

0.0 0.0

0.2

0.4

(a)

0.6

0.8

1.0

h/H

1.0 EBRT = 90 s EBRT = 60 s EBRT = 30 s

0.8

C/C i

0.6

0.4

0.2

0.0 0.0 (b)

0.2

0.4

0.6

0.8

1.0

h/H

Fig. 7. Effects of varying empty-bed residence time (EBRT) on the dimensionless concentration profile: (a) IPA and (b) ACE.

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1.0

µ mI = 1.5 × 10-5 s-1 µ mI = 5.5 × 10-5 s-1 µ mI = 9.5 × 10-5 s-1

0.8

C/C i

0.6

0.4

0.2

0.0 0.0

0.2

0.4

(a)

0.6

0.8

1.0

h/H 1.0

µ mA = 6.0 × 10-5 s-1 µ mA = 1.0 × 10-4 s-1 µ mA = 5.0 × 10-4 s-1

0.8

C/C i

0.6

0.4

0.2

0.0 0.0

0.2

0.4

(b)

0.6

0.8

1.0

h/H

Fig. 8. Effects of varying maximum specific growth rate (µm ) on the dimensionless concentration profile: (a) IPA and (b) ACE.

to consume IPA and ACE vapors by the microorganisms. The removal efficiencies of IPA and ACE increased from 92 to 100% and 71 to 100%, respectively, with an increase of EBRT from 30 to 90 s. Impacts of changing maximum specific growth rate (µm ) on the performance of TBAB are shown in Fig. 8. The removal efficiencies of IPA and ACE are higher for a higher µm value. This was because more microorganisms were yielded for a higher µm value, thus consumed IPA and ACE vapors at a faster rate. The removal efficiencies of IPA and ACE increased from 87 to 100% and 77 to 100%, respectively, with an increase of µmI and µMA values from 1.5 × 10−5 to 9.5 × 10−5 s−1 and 6.0 × 105 to 5.0 × 104 s−1 , respectively. Effects of varying YI and YA from 0.1 to 0.9 on the dimensionless IPA and ACE concentration profiles are shown in Fig. 9. As can be seen, a higher Y value results in a higher IPA and ACE concentration profile, indicat-

ing that the consumption of IPA and ACE vapors is less efficient under a higher Y value. The removal efficiencies of IPA and ACE increased from 87 to 100% and 77 to 100%, respectively, with a decrease of Y value from 0.9 to 0.1. Investigations on altering COi from 2.0 × 10−4 to 3.5 × 10−4 g/cm3 , KI and KA from 1.0×10−4 to 7.0×10−4 g/cm3 and 6.0 × 10−5 to 3.0 × 10−4 g/cm3 , KiI and KiA from 2.0 × 10−4 to 2.0×10−2 g/cm3 and 5.0×10−5 to 5.0×10−3 g/cm3 , respectively, were also conducted. Negligible differences in the dimensionless IPA and ACE concentration profiles are observed indicating that these parameters are not critical in TBAB process for the range tested herein. 3.4. Practical application Eq. (12) was employed to obtain the performance equation of TBAB for removal of IPA and ACE mixtures. The per-

C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

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1.0

YI = 0.1 YI = 0.3 YI = 0.9

0.8

C/C i

0.6

0.4

0.2

0.0

0.0

0.2

0.4

0.6

0.8

1.0

h/H

(a)

1.0

YA = 0.1 YA = 0.4 YA = 0.9

0.8

C/C i

0.6

0.4

0.2

0.0

0.0

0.2

0.4

(b)

0.6

0.8

1.0

h/H

Fig. 9. Effects of varying microbial yield coefficient (Y) on the dimensionless concentration profile: (a) IPA and (b) ACE.

formance equation contains a range of AS from 1 to 5 cm−1 , EBRT from 30 to 90 s, CIi from 1.86 × 10−7 to 7.46 × 10−7 g/cm3 and CAi from l.78 × 107 to 7.11 × 10−7 g/cm3 and can be expressed as

operating EBRT was selected from the longer EBRT and must be ≥43 s.

∗ CIe = (58.53 ± 2.0131) exp(−115.27 ± 2.017∆I )

(15)

4. Conclusions

∗ CAe = (85.37 ± 4.0226) exp(−81.25 ± 4.125∆A )

(16)

Practical application of Eq. (15) and (16) is demonstrated as follows. If 90% IPA removal is desired, ∆I must be ≥21.45 for CIi of 3.73 × 10−7 g/cm3 . If 90% ACE removal is desired, ∆A must be ≥51.53 for CAi of 3.56 × 10−7 g/cm3 (determined by substituting Ce∗ = 0.1 in Eqs. (15) and (16), and calculating ∆). From a design perspective, if the TBAB was operated at 60 s, the best AS was selected from the higher value between ∆I and ∆A and must be ≥3.65 cm−1 . From an operational perspective, if the AS was designed as 5 cm−1 , then the optimum

A mathematic model was developed and validated by comparing its predictions with the measured gas phase IPA and ACE concentrations. The impacts of important parameters were determined by a sensitivity analysis. Surface area of biofilm per unit volume of packing material (AS ), empty-bed residence time (EBRT) and microbial yield coefficient (Y) are identified to strongly influence the model performance. Practical applications of the present model to derive performance equation of TBAB using a typical range of AS , EBRT, CIi and CAi were demonstrated. The performance equation was then applied to obtain a best design and oper-

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C. Lu et al. / Process Biochemistry 39 (2004) 1849–1858

ating condition. Using a similar approach to what presented in this study, the performance equations for removing other VOCs by TBAB can also be derived.

i O

influent condition oxygen

Acknowledgements Notation AS C Ce∗ D f H h KS KAI KIA Ki KO m R r S ug XV Y YO Greek µ µm δ ∆ α, β

biofilm surface area per unit volume of packing material gas phase concentration ratio of the concentration at the exit to that at the entrance of TBAB mass diffusivity in liquids correction factor for the mass diffusivity within the biofilm height of TBAB packed with media position along TBAB column substrate half-saturation constant cross-inhibition constant for isopropyl alcohol expressing interaction with acetone cross-inhibition constant for acetone expressing interaction with isopropyl alcohol inhibition coefficient oxygen half-saturation constant thermodynamic distribution coefficient radius of coal particle radial distance from the center of coal particle liquid phase concentration superficial air velocity biofilm density yield of biomass on substrate yield of biomass on oxygen Letters specific growth rate maximum specific growth rate biofilm thickness dimensionless parameter for calculating the VOC removal efficiency in the TBAB (∆ = f (XV )DAS HKS m/ug δCi ) coefficients of the performance equation

Subscripts A acetone e effluent condition I isopropyl alcohol

Support from the National Science Council, Taiwan (NSC 90-2211-E-005-016) is gratefully acknowledged.

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