공기중의 톨루엔을 제거하는 바이오필터의 거동에 관한연구:

II. 동적 모사 및 실험적 검증

홍성도, 한희동, 최호석, 김인호, 이현재*

충남대학교 공과대학 화학공학과, (주)한탈*

Behavior of biofilters for the removal of toluene from air:

II. Dynamic simulation and experimental confirm

Sung-Do Hong, Hee-Dong Han, Ho-Suk Choi, In-Ho Kim, Hyun-Jae Lee*

Department of Chemical Engineering, Chungnam National University,

Hantal, Inc., Taejon, Korea*

Introduction

Biofiltration is an air pollution technology in which microorganisms immobilized on organic/inorganic packing materials at an off-gas containing biodegradable volatile organic or inorganic compounds and is often a highly efficiency and low-cost alternative. Recently, in Europe and Japan, it is the most commonly employed odor control technique.

Biofiltration is very complex hybrid technology, which involve adsorption, absorption and biochemical reaction. Recently, numerous efforts have been made the process model. In early 1980s, Jennings et al.1 and Ottengraf2 first suggested biofilm models with assumptions of basic mass balance principles, simple kinetics, and a plug flow air stream. These models answered the value of overall order of reaction occurring in biofilms. Shareefdeen et al.3-5 proposed both steady-state and transient models in which the biodegradation was assumed to be first order with respect to both oxygen and the organic pollutant. The idea of their study was that some pollutants were adsorbed on the bare surface of support media while others were absorbed on the biofilm partially covering on the support media. Hodge and Devinny6 used an axially dispersed plug-flow model for gas phase and a linear driving force(LDF) model to approximate the interface mass transfer kinetics. In this study, they regarded the biofilm and the support media as a unified phase represented by a single, average concentration and assumed the pollutant degradation to be first order with respect to its average concentration in the unified phase.

Although many efforts were made to accurately describe the biofiltration, either only simulation or only experiment did not allow us to fully understand the process. Thus, we tried to use both tools to understand the biofiltration. In this study, we first solved a steady state problem of the biofilter process based upon Shareefdeen et al.'s model6. To match simulation results with experimental results, we introduced a correction function for the reaction kinetics and determined some unknown parameters including specific surface area of the support media and biofilm thickness. Through the dynamic simulation, we also examined the performance of a biofilter under given conditions and the relationship between operating parameters such as the inlet concentration of toluene and the flow rate of contaminated air.

Theory

The assumptions made in deriving the model are the same as Shareefdeen et al.'s6. The governing equations are as follows.

(Ⅰ) Mass balance in the biofilms are:

(1)

(2)

(Ⅱ) Mass balances in the gas phase are:

(3)

(4)

(Ⅲ) Mass balance in the solid phase(particles) is

(5)

For the biodegradation of pollutant j, the following interactive model was used

(6)

For the adsorption of pollutant j on solid media, the Freundlich isotherm was used

(7)

The transient model constitutes a set of partial differential equations in three dimensions(time, biolayer, and bed height). To simply solve the problem, a quasi-steady-state approximation was made for the biolayer, and the use of effectiveness factors was introduced by following the approach of Tong and Fan7.

(8)

(9)

Experimental materials and methods

Figure 1 shows the schematic diagram of a biofilter system, which we used in the experiments. The main part of the unit was an acrylic column of 10.6cm diameter and 160cm height, equipped with a sampling port at each stage. The height of the biofilter bed was 120cm, leading to a value of bed volume equal to 10.59x10-3 m3. The packing material consisted of a mixture of peat and calstone(5:3 volume ratio before mixing). The microorganism used in the experiments was Pseudomonas.Putida type A and the strain of Pseudomonas.Putida is provided by Dr. Khoo, Korea Microbial Technology, Inc.  The culture medium used contained per liter: glucose, 1.1g; NH4Cl 0.1g; MgSO4 7H2O 0.05g; FeSO47H2O 0.005g; MnSO4H2O 0.005g ; CaCl2 0.00375g; Yeast extract 1g; 0.1M phosphate buffer solution 18ml. The microorganism cultured with the above medium in a shaking flask was well mixed with the packing materials and then packed to the column. The air stream was divided into two streams. The main one was passed through a water vessel for humidification. The second stream was passed through a closed toluene vessel. And then two streams were mixed before they entered the biofilter bed. The flow rates of two streams were controlled by two flow meters, respectively. The concentration of toluene was measured by a portable GAS-TEC(Flame Ionization Monitor Type 47674, Telegan Gas Monitoring Ltd., West Sussex, England) detector. The temperature of the biofilter bed was kept from 25℃ to 30℃ for maintaining high microbial activity. To avoid the pressure drop in the biofilter bed due to compaction, whole column was divided by 4 stages.

Results and discussion

Figure 1. Schematic diagram of               data experimental apparatus

The process was modeled with general mass balance equation, which take into account reaction, mass transfer, and adsorption of the pollutant onto the packing material. We used IMSL library(DIVPRK for gas phase and BVPFD for biofilm) included in Digital Visual Fortran(Digital Equipment Corporation, Maynard, Massachusetts) to obtain numerical solutions of both steady-state and transient models. We first obtained the steady state solutions at the air flow rate of 10 L/min and the toluene concentrations of 100, 200, 300 ppm, respectively. After that, we fit the simulation results with experimental data. As a result, we had to introduce the following deactivating factor as a function of inlet toluene concentration since the deactivation observed with increasing the toluene concentration in the experiment.

(10)

where CTI is in g/m3. From the careful examination of the model equations, we found that possible parameters affecting the performance of our biofilter are As*, , Xv. When we measured the number of microbes in the packing materials, it was gradually reduced with the average value of 108c.f.u./g-packing material.

For the transient simulation, we used the following expression of an effectiveness factor as a function of inlet toluene concentration.

or	(11)

The effectiveness factor actually depends on the concentration of toluene as shown in the inset of Figure 2 although its dependence is too small. In this calculation, however, we assumed that the effectiveness factor did not depend on the local concentration of toluene but it only depended on the inlet concentration of toluene. The correction factor introduced at the steady state simulation reflected to the transient simulation with the form of the corrected effectiveness factor. The DSS020 subroutine8 was used to convert the partial differential equations into the ordinary differential equation. The value of inlet toluene concentration for the dynamic simulation was chosen as an average of experimental values in each step. As shown in Figure 3, the dynamic simulation shows good agreements with experimental data. Since the space time of our experimental system is about 1 min, the dynamic response from the step change of inlet toluene concentration is very fast. The inset of Figure 3 shows the response.

Figure 2. Effect of inlet toluene   Figure 3. Comparison of experimental          concentration on the effectiveness factor     data with the dynamic simulation results

Conclusions

We successfully solved dynamic problem of the biofilter process by simply introducing an effectiveness factor, which was obtained from the fitting of steady-state simulation results with experimental data.  The dynamic solution shows good agreement with experimental results obtained at three different step inputs. Thus, the simulation predicted well a response for the unusual increase of toluene concentration in the biofilter. The dependence of the biofilter performance on various parameters such as As*, , Xv,.and □were also studied in this work.

Reference

1. Jennings, P.A., Snoeyink, V. L., and Chian, E.S.K., Biotechnol.

Bioeng.,18,1249.(1976)

2. Ottengraf, S.P.P., Biotechnol. Bioengng.,19, 1411,(1977).

3. Shareefdeen, Z.;Baltzis, B.C.; Oh, Y.S.; Bartha, R. Biotech. Bioeng.,41,              512.(1993).

4. Shareefdeen, Z. and Baltzis, B.C., Chem. Eng. Sci.,49, 4347,(1994).

5. Shareefdeen, Z.;Baltzis, B.C., Galindo, E.,   Ramirez, O.T., Eds.; Kluwer            Academic Publishers.: Dordrecht, The Netherlands,(1994)

6. Hodge , D.S., Devinny, J. S., J. Environ. Eng. Div. (Am. Soc. Civ. Eng.), 121       (1), 21,(1995).

7. Tong, C.C., Fan, L.-S., Biotechnol. Bioengng, 31, 24(1988)

8. Silebi, C.A., Schiesser, W.E., Dynamic Modeling of Tansport Process Systems,        Academic Press, Inc., New York, (1992)