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Removal of toluene vapors using a fungal biofilter under intermittent loading
Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
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Process Safety and Environmental Protection journal homepage: www.elsevier.com/locate/psep
Removal of toluene vapors using a fungal biofilter under intermittent loading Seyed Morteza Zamir, Rouein Halladj ∗ , Bahram Nasernejad Faculty of Chemical Engineering, Amirkabir University of Technology, PO Box 15875-4413, Tehran, Iran
a b s t r a c t To investigate the performance of a compost biofilter treating toluene vapor during intermittent loading, a biofiltration system was set up. This system was inoculated with a special type of white-rot fungus, Phanerochaete chrysosporium. The system was loaded 10 h per day on 0.096, 0.024, 0.06 m3 /h of air flow rates, and 173.1 and 52.6 mg m−3 of pollutant concentration while there was no aeration to the system during the remaining 14 h of the day. Maximum removal efficiency and elimination capacity obtained were about 92% and 1913.7 mg m−3 h−1 , respectively. The fungal biofilter showed its robustness to the alterations in inlet toluene concentration and gas flow rate. The kinetic of biological reaction was studied by application of Monod type equation. The kinetic constants Km and rm are evaluated as 3.495 g m−3 and 50 g m−3 h−1 , respectively. The results confirmed that the fungal system could effectively remove toluene in such a harsh condition without adding excess nutrient solution and during intermittent loading. © 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Key words: Biofilter; Toluene; Phanerochaete chrysosporium; Compost; Intermittent loading
1.
Introduction
There are various industrial processes from which an air stream polluted by volatile organic compounds (VOCs) is produced. Among these industries, refinery and petrochemical units, coating facilities, adhesives, pulp and paper and printing industries are the main sources of these pollutants. Additionally, increasing environmental problems as well as the ever more stringent national and international regulations have led to the development and optimization of processes aimed at reducing pollution of water, air and soil (Devinny et al., 1999). Heretofore, industrial waste gases have been treated by physicochemical methods such as absorption, condensation and incineration. However, in the past few decades biological treatment methods have also demonstrated competitive capabilities. Biofiltration is known as one of the most applicable technologies in biological treatment methods. The process involves passing of contaminated streams through a porous media on which microorganisms have been immobilized in the biofilter. The microorganisms are capable of biodegrad-
∗
ing the contaminants. Degradation mechanisms are different depending on various microorganisms. However, an oxidation process takes place subsequently, and alongside the microbial growth, CO2 is produced. Generally, biofiltration has proven to be an applicable method for gas treatment since it is considered to be an economical technology compared with other techniques and the contaminant removal efficiency (RE) is very high and also the minimum CO2 is produced in this technology (Kennes and Thalasso, 1998). In recent years, fungi inoculation has been increasingly applied in biofilters (Aizpuru et al., 2005; Delhomenie et al., 2001; Garcia-Pena et al., 2001). Although the ability of some types of fungi in wastewater treatment has been identified so far, applying them in gas phase treatment is still considered to be a new subject. Fungi show significant preferences comparing to bacteria since they are more resistant to environmental changes such as temperature, pH and humidity. For instance, the water activity, which is defined as the amount of required water that is free in a given environment, is 0.6 for fungi where it is more than 0.9 for bacteria (Kennes and Veiga, 2004). Additionally, the presence of hypha in fungi facilitates the absorbance of hydrophobes from air streams by
Corresponding author. Tel.: +98 2164543168; fax: +98 2166405847. E-mail address: [email protected] (R. Halladj). Received 14 November 2009; Received in revised form 25 September 2010; Accepted 2 October 2010 0957-5820/$ – see front matter © 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.psep.2010.10.001
Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
Nomenclature Cg Cgi Cgo EC h Km P Q r rmax RE t Vf
toluene concentration (mg m−3 or g m−3 ) inlet toluene concentration (mg m−3 or g m−3 ) outlet toluene concentration (mg m−3 or g m−3 ) elimination capacity (mg m−3 h−1 ) bed height (m) Monod saturation constant (g m−3 ) pressure drop (mm H2 O) volumetric air flow rate (m3 h−1 ) biodegradation reaction rate (g m−3 h−1 ) maximum biodegradation rate (g m−3 h−1 ) removal efficiency (%) residence time (min) bed volume (m3 )
increasing the area of transport (Qi et al., 2002; Yaomin et al., 2006). Not only the application of fungi improves the phase partition of hydrophobic compounds between air and cellular system but also the capability of adaptation to the biofilters operational conditions is a substantial advantage (VergaraFernandez, 2006). In many industries the contaminated air stream is not released continuously and the concentration of contaminants in air stream can possibly be very low at the beginning of the day, then it can reach the maximum by midday and eventually decreases again at the end of the day. Furthermore, aeration in definite hours during a full-day (e.g. 8 h work days) or during the days of facility re-tooling can cause concentration pulses in the biofilter and decreases the efficiency of removing pollutants. Therefore fungi are more applicable and suitable for such operations. Although there have been sufficient investigations about the performance of biofilters under short term or weekend shutdown (Cox and Deshusses, 2002; Park and Kinney, 2001; Rene et al., 2005; Wani et al., 2000) few researchers have evaluated the effect of daily discontinuous aeration on the performance of biofilters and consequently there is insufficient data available about the operation of biofilters in such tough conditions (Moe and Qi, 2004). Toluene is one of the most common air pollutants in different chemical industries. This aromatic substance has a low vapor pressure and is widely used as a solvent or as a reactant in some reactions to produce other chemicals. Thus, a
9
lot of researchers have studied the treating of toluene from air stream (De Visscher and Li, 2008; Kwon and Cho, 2009; Maestre et al., 2007; Vergara-Fernandez et al., 2007; Zand et al., 2007). In this research, a biofilter filled with sterilized compost and lava as support particles is inoculated with the whiterot fungi, P. chrysosporium. The selected fungus has been previously used in the treatment of wastewaters complex compounds and has shown reasonable results (Ahmadi et al., 2006). There have also been some researches about removing aromatic compounds belonging to the BTEX group from air by using P. chrysosporium (Oh et al., 1998). Yadav and Reddy (1993) showed that the oxidation of these chemicals generally occurs during the primary metabolism and the ligninolytic enzymes are not involved in this reaction. Toluene was selected as the volatile organic compound. The aim of this research was to study the performance of this fungal biofilter for removal of toluene from air stream in discontinuous aeration conditions.
2.
Materials and methods
2.1.
Microorganism
The fungus, P. chrysosporium ATCC24725, was obtained from the microbial collection of Iran Research Organization for Science and Technology. It was subcultured on a 2%YMG agar media (4 g yeast extract/10 g malt extract/6 g glucose in 1 L of distilled water) and incubated at 25 ◦ C for 5 days and then was stored at 4 ◦ C. Preparing for the inoculation, small amount of the fungus grown on agar was transferred to 150 ml 2% YMG media into a 500 ml Erlenmeyer. Then it was cultured in a shaker incubator (Kuhner) for 4 days at 27 ◦ C and 150 rpm. Afterwards, the formed pellets were separated from culture medium and transferred to a mixer and were mixed for 30 s to form tiny and symmetric pellets.
2.2.
Experimental set up
The biofiltration set up established for the experiments, is shown in Fig. 1. A column made of Plexiglas was used for biofiltration experiments in this study. The column had an inner diameter of 9.9 cm; a total height of 75 cm and an effective volume of 4 L (empty basis) and consisted of three stages. A mixture of powdered compost supplied from Tehran compost factory and lava (with the wet weight ratio of 2/1) acted as packing material. The lava rubbles were semispherical with
Fig. 1 – Schematic of the biofilter set up. A, compressed air; B, three-way; C, rotameter; D, pollutant chamber; E, humidifier; F, biofilter column; G, exhaust air; H, drain.
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Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
Table 1 – Chemical composition of raw compost* . Raw compost Water (%) Total N (%) Available P (% P2 O5 ) Available K (% K2 O) Available Mg (% MgO) Organic content (%) pH ∗
20 0.6 0.7 0.3–0.9 0.3–0.9 25 6.8
Table 2 – Time schedule of experimental periods and main operational conditions. Phase Period (day)
Air flow rate (m3 /h)
Inlet toluene (mg/m3 )
Resident time (min)
I II III IV
0.096 0.024 0.06 0.06
173.1 173.1 173.1 52.6
1.1 4.4 1.7 1.7
0–25 26–40 41–50 51–60
The aeration was implemented 10 h a day for all phases.
Data obtained from Tehran Compost Factory.
EC = the mean diameter of 25 mm. The packing materials were sterilized in autoclave (15 psi, 30 min) and in oven (150 ◦ C, 2 h). Table 1 shows the chemical composition of raw powdered compost. In advance of the tests, the porosity of packing was measured by Delhomenie et al. (2003) method which calculated to be 0.45, approximately. The packing material divided to nine same-weight parts before filling the reactor. Each part was mixed with the prepared fungal suspension and then placed at column. Through this inoculation method, the fungal population was equally distributed in bed. The gas flow rate was adjusted by two low capacity rotameters and the stream passed a humidification column to maintain the vital moisture for microbial growth. Another air stream crossed a toluene stock vessel and was then combined with the moist air stream to generate feed air which finally entered the biofilter column from the bottom. Each section of the column has separate outlets providing the possibility to take samples from gas at three points across the column. The experiments were carried out at the room temperature changed between 22 and 25 ◦ C during the time of the tests.
2.3.
Analytical method
Gas samples were collected from ports located at the biofilter inlet (port A) and outlet (port D) using a 1-ml Hamilton gas tight syringe. After achieving steady-state condition in the operation of the system, sampling from ports B and C was done. All samplings were carried out at the end of loading time due to some researchers demonstrated that biofilter performance gradually increased during the course of each loading period (Moe and Qi, 2004). Toluene concentrations were then measured using a gas chromatograph (Younglin ACME 6000 series) equipped with a flame ionization detector (FID). Helium was used as the carrier gas and the temperatures of oven, injector and detector were 120, 150 and 250 ◦ C, respectively. To study the possibility of clogging during the experiments, the bed pressure drop was measured by a manometer with 1 mm H2 O precision.
2.4. Biofilter performance under different operating conditions The performance of a biofiltration system is identified on the concepts of removal efficiency and elimination capacity. These two key parameters are defined as follows: RE =
CGi − CGo × 100 CGi
(1)
(CGi − CGo ) × Q Vf
(2)
where CGi , CGo , Q and Vf are the inlet and outlet pollutant concentrations (mg m−3 ), volumetric flow rate of air (m3 h−1 ) and bed volume (m3 ), respectively. As summarized in Table 2, the system was operated under four operating conditions. The operating conditions, gas flow rate and toluene concentration, were altered in each phase in order to investigate the influence of each parameter on the performance of the fungal biofilter. The loading to the biofilter was accomplished for 10 h a day for all phases of experiments to provide the intermittent loading. The system was completely turned off during the next 14 h and no feed was done in this period.
3.
Results and discussion
3.1.
Biofilter performance
One of the most important effective factors in the efficiency of a reactor is the residence time of the reaction components. Since biofilters are considered as biological reactors, this parameter is also of great importance in biofilters. Residence time alterations result from the changes in the flow rate of the gas entering the column. Fig. 2 shows the outlet concentration of toluene in the air stream and the removal efficiency of the biofilter during the time of the experiments. In the first three phases of experiment, the pollutant concentration was adjusted to 173.1 mg m−3 . Besides, the gas flow rate was set to 0.096 m3 h−1 , 0.024 m3 h−1 and also 0.06 m3 h−1 . Now that the gas-biofilm contact time was low in the start-up phase, the time of achieving steady-state condition was reached to 25 days. It is obvious that the increase in the gas residence time in the biofilter would significantly cause greater decrease in the amount of toluene in the outlet gas stream and greater improvement in the RE during phase II, as many scientists have observed (Maestre et al., 2007; Vergara-Fernandez et al., 2007; Zand et al., 2007). It is also clear that at the flow rate of 0.024 m3 h−1 , the system would become stable in less than 10 days. When the air flow rate increased again up to 0.06 m3 h−1 , the outlet concentrations increased consequently. However, these concentrations are lower than what they are during the phase I of Fig. 2. This happened because the residence time is still more than what it was when the biofilter started to work. Furthermore, microorganisms have completely adapted to the contaminated air. There are some irregularities in the toluene outlet concentration during the last days of each period of operation. Feeding biofilter in 10 h periods and shutting it down until the starting of the next period, is probably the most relevant reason for showing this behavior. Especially, these irregularities
Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
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Fig. 2 – Variation in toluene outlet concentration () and removal efficiency () during experimental period. were seen when the system seemed to be close to its steady state condition. It is, moreover, clear that 10–90% of toluene has been removed under different conditions. But in the steady state conditions, the RE reached 45%, 87% and 60%, respectively. According to Fig. 2, at the points in which there is an increase in the outlet concentration, RE has decreased. The highest RE was achieved when the residence time increased up to 4.4 min. In this case, the microorganisms clearly had sufficient time to absorb and oxidize the pollutant. At the first day of the experiments in phase IV, the toluene concentration was set at 52.6 mg m−3 . A comparison between phase III and IV demonstrated that in the lower concentration of pollutant, steady-state was achieved in 4 days and RE increased continuously. In fact, when the pollutant loading decreased, the microbial population consumed toluene more rapidly in comparison with the time they had been adapted to a 173.1 mg m−3 of inlet concentration. Fig. 3 indicates the effect of hexane inlet load on the elimination capacity of the bioreactor. In general, the maximum EC obtained at various phases of the experiments was reduced by increasing the inlet load. The variations of EC of the biofil-
Fig. 3 – Effect of inlet load on the distribution of toluene elimination capacity.
ter are shown in Fig. 3. A comparison between Figs. 2 and 3 exhibits the independency of the two key concepts described above. For example, RE reached its maximum level between the days 25 and 40. In contrast, EC declined dramatically which was due to a very low flow rate of air. Some irregularities are observed in Fig. 3 and similarly in Fig. 2. In addition to the reasons that have been mentioned above, it is possible that some pores in bed have been clogged, that is the biofilm has grown and blocked these pores. Therefore, the gas had to change its direction toward other pores with lower microbial population. A pore network model proves that this explanation is correct (results not shown here). Thus, RE declined during a limited time and then it became steady again. When the air flow rate decreased to 0.024 m3 h−1 , EC decreased to 983 mg m−3 h−1 in the phase II of the Fig. 3. On the contrary, RE reached 90%. In the final period of experiments, where the inlet contaminant concentration decreased to 52.6 mg m−3 in a constant gas flow rate, EC diminished, consequently. In this phase, the difference between inlet and outlet concentration was not high enough to increase the EC.
3.2.
Pressure drop through the bed
A partial or complete clogging of the bed can occur in biofilters. The complete clogging not only can increase the pressure drop along the bed drastically, but also can cause an increase in operational costs. However, the partial blocking may not be very important generally, it can cause the channeling of the bed in some cases (Devinny et al., 1999; Kennes and Thalasso, 1998; Delhomenie et al., 2003). In this case, gas passes through the channels of the bed without a sufficient gas-biofilm contact time and the elimination of the pollutant would not happen practically. Fig. 4 shows the alteration of pressure drop during the time of experiments in different operating conditions. In all phases of the tests, the pressure drop increased during the time in view of the fact that microorganisms were growing in the pores. In phase I, according to Darcy equation, the pressure drop had the highest amount among all phases where the flow rate was at its maximum. Oppositely, the pressure drop declined in phase II, as the flow rate decreased to 0.024 m3 h−1 . Generally, the maximum pressure drop was observed in the last day of phase I (6 mm H2 O) after 60-day
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Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
Fig. 4 – Alteration in pressure drop during the time of experiment in each phase. operation time. This observation indicated the proper performance of the bed hydraulically in compare to Delhomenie et al. (2003) who observed pressure drops between 1 cm H2 O/m of bed and 2.7 cm H2 O/m of bed in a compost biofilter with different nitrogen compound concentration as nutrient. Table 3 shows the variation of pressure drop in each section of the filter column. These results were obtained after reaching steady state in the outlet concentration. It is obvious that the maximum pressure drop, more than 50% of the total pressure drop, was seen in the first stage for all flow rates. The compaction of compost as a result of absorbing the major part of the total moisture existing in the inlet air and microbial growth are the main reasons of this behavior. Nevertheless, this pressure drop was quite low considering the total P.
3.3.
Profile of toluene concentration along the bed
Sampling from three ports along the column makes one possible to estimate how much toluene is eliminated in each centimeter of the bed height. Fig. 5 shows the variations of dimensionless toluene concentration along the bed height in the different experiments. As the steep of Fig. 5 shows, about 50% of the total pollutant conversion has occurred through the first stage owing to the fact that the gas entered the biofilter with a higher load of contaminant which was available for fungal population. The pollutant concentration diminished gradually in stages 2 and 3 in the column as other researchers have depicted (Rene et al., 2005; VergaraFernandez et al., 2007). Moreover, when the inlet flow rate decreased to 0.06 and 0.024 m3 h−1 , the proportion of toluene removing through the first stage increased, as microorganisms had more time to absorb and transfer carbon or energy source to the biofilm. In addition, as the toluene partial pressure in air decreased through the height of reactor, the diffusion of toluene into the biofilm reduced consequently according to the well known equations for determining the gas–liquid
Fig. 5 – Profile of toluene concentration along the bed for phase I (--), phase II (. . .. . .), phase III (--) and phase IV (. . .. . .) of experiments. diffusion coefficients. Also, in phase IV when toluene concentration decreased to 52.6 mg m−3 in a constant flow rate, the elimination in stage 1 was higher than in phase III. Because the consumption of toluene by biofilm was not affected by decreasing the mass concentration, as RE did not change significantly in Fig. 2, the intensity of diminishing pollutant in first stage increased in Fig. 5.
3.4.
The kinetic of the biodegradation can be investigated either microkinetically or macrokinetically. However, the microkinetic method cannot be extended to the gas phase systems. Because the phase of degradation is not similar to the phase of biodegradation in shake flask. Hence, in this research, macrokinetic study was applied to determine the Monod constants. The same method of macrokinetic determination was used by the Krailas et al. (2004) and Mathur et al. (2006). The kinetics of the system can be expressed by a Monod relationship assuming that oxygen limitation was ignorable in the system and the kinetic controlled the reaction. At steady-state condition of microbial growth, the growth and death rate of microorganisms were balanced. The kinetic constants were determined using the plug flow model (Mathur et al., 2006): ∂Cg ∂Cg = −Ug +r ∂t ∂h
Phase
Pressure drop (mm H2 O) Bed height = 17cm
I II III IV
3 2 3 3
Bed height = 34 cm 5 3 4 4
Bed height = 51 cm 6 4 5 5
(3)
where Cg is toluene concentration (g m−3 ), Ug is the superficial velocity (m h−1 ), t is the time interval, h is the distance from the bed (m), and r is the overall reaction rate and it is defined by Eq. (4): r=
Table 3 – Amount of pressure drop in each section of the bed in different phases of experiments.
Kinetic study
rmax Cg Km + Cg
(4)
where rmax is the maximum biodegradation rate (g m−3 h−1 ) and Km is the saturation constant (g m−3 ) in the gas phase. At steady state, the accumulation term ∂Cg /∂t equals to zero. Eq. (3) was integrated under the following boundary conditions: Cg = Cgi at h = 0
(5)
Cg = Cgo at h = L
(6)
Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
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References
Fig. 6 – Macrokinetic determination of Monod constants.
where Cgi and Cgo are inlet and outlet toluene concentration (g m−3 ) and L is the biofilter length (m). Eq. (7) was obtained by solving Eqs. (3) and (4): Km 1 1 V/Q = + Cgi − Cgo rmax CLn rmax
(7)
where Cln is the logarithmic mean concentration [(Cgi − Cgo )/ ln(Cgi /Cgo )], V is the biofilter volume (m3 ), and Q is the volumetric flow rate (m3 h−1 ), rmax and Km for the gas phase can be obtained by plotting [(V/Q)/(Cgi − Cgo )] against (1/Cln ) with correlation coefficient of 0.9922 which showed that Monod equation could properly express the biodegrading kinetic. From Fig. 6, the rmax and Km were calculated as 50 g m−3 h−1 and 3.495 g m−3 , respectively. It showed that there was no inhibition effect of toluene on the fungal population under the studied concentrations. Also, Km was reported around 7.45 g m−3 (Mathur et al., 2006) for mono-chlorobenzene removal. As the elimination capacities obtained here is significantly lower than calculated rmax , it seems that the control of the reaction by kinetic is a proper assumption. Therefore, that the system can operate under higher loads of pollutant in this condition properly.
4.
Conclusion
The main findings in this research can be concluded as follows:
(1) The compost biofilter inoculated with P. chrysosporium could effectively remove toluene vapor (between 50% and 92%) under intermittent loading. (2) The effect of residence time was more significant than changing the inlet concentration on the biofiltration of toluene due to low load of pollutant in this research. (3) Under the experimental condition, the Monod type equation could properly fit the data and express the kinetic of toluene biofiltration.
Acknowledgement The authors gratefully acknowledge National Iranian Oil Refining and Distribution Company (NIORDC) for their financial support.
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Contents lists available at ScienceDirect
Process Safety and Environmental Protection journal homepage: www.elsevier.com/locate/psep
Removal of toluene vapors using a fungal biofilter under intermittent loading Seyed Morteza Zamir, Rouein Halladj ∗ , Bahram Nasernejad Faculty of Chemical Engineering, Amirkabir University of Technology, PO Box 15875-4413, Tehran, Iran
a b s t r a c t To investigate the performance of a compost biofilter treating toluene vapor during intermittent loading, a biofiltration system was set up. This system was inoculated with a special type of white-rot fungus, Phanerochaete chrysosporium. The system was loaded 10 h per day on 0.096, 0.024, 0.06 m3 /h of air flow rates, and 173.1 and 52.6 mg m−3 of pollutant concentration while there was no aeration to the system during the remaining 14 h of the day. Maximum removal efficiency and elimination capacity obtained were about 92% and 1913.7 mg m−3 h−1 , respectively. The fungal biofilter showed its robustness to the alterations in inlet toluene concentration and gas flow rate. The kinetic of biological reaction was studied by application of Monod type equation. The kinetic constants Km and rm are evaluated as 3.495 g m−3 and 50 g m−3 h−1 , respectively. The results confirmed that the fungal system could effectively remove toluene in such a harsh condition without adding excess nutrient solution and during intermittent loading. © 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Key words: Biofilter; Toluene; Phanerochaete chrysosporium; Compost; Intermittent loading
1.
Introduction
There are various industrial processes from which an air stream polluted by volatile organic compounds (VOCs) is produced. Among these industries, refinery and petrochemical units, coating facilities, adhesives, pulp and paper and printing industries are the main sources of these pollutants. Additionally, increasing environmental problems as well as the ever more stringent national and international regulations have led to the development and optimization of processes aimed at reducing pollution of water, air and soil (Devinny et al., 1999). Heretofore, industrial waste gases have been treated by physicochemical methods such as absorption, condensation and incineration. However, in the past few decades biological treatment methods have also demonstrated competitive capabilities. Biofiltration is known as one of the most applicable technologies in biological treatment methods. The process involves passing of contaminated streams through a porous media on which microorganisms have been immobilized in the biofilter. The microorganisms are capable of biodegrad-
∗
ing the contaminants. Degradation mechanisms are different depending on various microorganisms. However, an oxidation process takes place subsequently, and alongside the microbial growth, CO2 is produced. Generally, biofiltration has proven to be an applicable method for gas treatment since it is considered to be an economical technology compared with other techniques and the contaminant removal efficiency (RE) is very high and also the minimum CO2 is produced in this technology (Kennes and Thalasso, 1998). In recent years, fungi inoculation has been increasingly applied in biofilters (Aizpuru et al., 2005; Delhomenie et al., 2001; Garcia-Pena et al., 2001). Although the ability of some types of fungi in wastewater treatment has been identified so far, applying them in gas phase treatment is still considered to be a new subject. Fungi show significant preferences comparing to bacteria since they are more resistant to environmental changes such as temperature, pH and humidity. For instance, the water activity, which is defined as the amount of required water that is free in a given environment, is 0.6 for fungi where it is more than 0.9 for bacteria (Kennes and Veiga, 2004). Additionally, the presence of hypha in fungi facilitates the absorbance of hydrophobes from air streams by
Corresponding author. Tel.: +98 2164543168; fax: +98 2166405847. E-mail address: [email protected] (R. Halladj). Received 14 November 2009; Received in revised form 25 September 2010; Accepted 2 October 2010 0957-5820/$ – see front matter © 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.psep.2010.10.001
Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
Nomenclature Cg Cgi Cgo EC h Km P Q r rmax RE t Vf
toluene concentration (mg m−3 or g m−3 ) inlet toluene concentration (mg m−3 or g m−3 ) outlet toluene concentration (mg m−3 or g m−3 ) elimination capacity (mg m−3 h−1 ) bed height (m) Monod saturation constant (g m−3 ) pressure drop (mm H2 O) volumetric air flow rate (m3 h−1 ) biodegradation reaction rate (g m−3 h−1 ) maximum biodegradation rate (g m−3 h−1 ) removal efficiency (%) residence time (min) bed volume (m3 )
increasing the area of transport (Qi et al., 2002; Yaomin et al., 2006). Not only the application of fungi improves the phase partition of hydrophobic compounds between air and cellular system but also the capability of adaptation to the biofilters operational conditions is a substantial advantage (VergaraFernandez, 2006). In many industries the contaminated air stream is not released continuously and the concentration of contaminants in air stream can possibly be very low at the beginning of the day, then it can reach the maximum by midday and eventually decreases again at the end of the day. Furthermore, aeration in definite hours during a full-day (e.g. 8 h work days) or during the days of facility re-tooling can cause concentration pulses in the biofilter and decreases the efficiency of removing pollutants. Therefore fungi are more applicable and suitable for such operations. Although there have been sufficient investigations about the performance of biofilters under short term or weekend shutdown (Cox and Deshusses, 2002; Park and Kinney, 2001; Rene et al., 2005; Wani et al., 2000) few researchers have evaluated the effect of daily discontinuous aeration on the performance of biofilters and consequently there is insufficient data available about the operation of biofilters in such tough conditions (Moe and Qi, 2004). Toluene is one of the most common air pollutants in different chemical industries. This aromatic substance has a low vapor pressure and is widely used as a solvent or as a reactant in some reactions to produce other chemicals. Thus, a
9
lot of researchers have studied the treating of toluene from air stream (De Visscher and Li, 2008; Kwon and Cho, 2009; Maestre et al., 2007; Vergara-Fernandez et al., 2007; Zand et al., 2007). In this research, a biofilter filled with sterilized compost and lava as support particles is inoculated with the whiterot fungi, P. chrysosporium. The selected fungus has been previously used in the treatment of wastewaters complex compounds and has shown reasonable results (Ahmadi et al., 2006). There have also been some researches about removing aromatic compounds belonging to the BTEX group from air by using P. chrysosporium (Oh et al., 1998). Yadav and Reddy (1993) showed that the oxidation of these chemicals generally occurs during the primary metabolism and the ligninolytic enzymes are not involved in this reaction. Toluene was selected as the volatile organic compound. The aim of this research was to study the performance of this fungal biofilter for removal of toluene from air stream in discontinuous aeration conditions.
2.
Materials and methods
2.1.
Microorganism
The fungus, P. chrysosporium ATCC24725, was obtained from the microbial collection of Iran Research Organization for Science and Technology. It was subcultured on a 2%YMG agar media (4 g yeast extract/10 g malt extract/6 g glucose in 1 L of distilled water) and incubated at 25 ◦ C for 5 days and then was stored at 4 ◦ C. Preparing for the inoculation, small amount of the fungus grown on agar was transferred to 150 ml 2% YMG media into a 500 ml Erlenmeyer. Then it was cultured in a shaker incubator (Kuhner) for 4 days at 27 ◦ C and 150 rpm. Afterwards, the formed pellets were separated from culture medium and transferred to a mixer and were mixed for 30 s to form tiny and symmetric pellets.
2.2.
Experimental set up
The biofiltration set up established for the experiments, is shown in Fig. 1. A column made of Plexiglas was used for biofiltration experiments in this study. The column had an inner diameter of 9.9 cm; a total height of 75 cm and an effective volume of 4 L (empty basis) and consisted of three stages. A mixture of powdered compost supplied from Tehran compost factory and lava (with the wet weight ratio of 2/1) acted as packing material. The lava rubbles were semispherical with
Fig. 1 – Schematic of the biofilter set up. A, compressed air; B, three-way; C, rotameter; D, pollutant chamber; E, humidifier; F, biofilter column; G, exhaust air; H, drain.
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Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
Table 1 – Chemical composition of raw compost* . Raw compost Water (%) Total N (%) Available P (% P2 O5 ) Available K (% K2 O) Available Mg (% MgO) Organic content (%) pH ∗
20 0.6 0.7 0.3–0.9 0.3–0.9 25 6.8
Table 2 – Time schedule of experimental periods and main operational conditions. Phase Period (day)
Air flow rate (m3 /h)
Inlet toluene (mg/m3 )
Resident time (min)
I II III IV
0.096 0.024 0.06 0.06
173.1 173.1 173.1 52.6
1.1 4.4 1.7 1.7
0–25 26–40 41–50 51–60
The aeration was implemented 10 h a day for all phases.
Data obtained from Tehran Compost Factory.
EC = the mean diameter of 25 mm. The packing materials were sterilized in autoclave (15 psi, 30 min) and in oven (150 ◦ C, 2 h). Table 1 shows the chemical composition of raw powdered compost. In advance of the tests, the porosity of packing was measured by Delhomenie et al. (2003) method which calculated to be 0.45, approximately. The packing material divided to nine same-weight parts before filling the reactor. Each part was mixed with the prepared fungal suspension and then placed at column. Through this inoculation method, the fungal population was equally distributed in bed. The gas flow rate was adjusted by two low capacity rotameters and the stream passed a humidification column to maintain the vital moisture for microbial growth. Another air stream crossed a toluene stock vessel and was then combined with the moist air stream to generate feed air which finally entered the biofilter column from the bottom. Each section of the column has separate outlets providing the possibility to take samples from gas at three points across the column. The experiments were carried out at the room temperature changed between 22 and 25 ◦ C during the time of the tests.
2.3.
Analytical method
Gas samples were collected from ports located at the biofilter inlet (port A) and outlet (port D) using a 1-ml Hamilton gas tight syringe. After achieving steady-state condition in the operation of the system, sampling from ports B and C was done. All samplings were carried out at the end of loading time due to some researchers demonstrated that biofilter performance gradually increased during the course of each loading period (Moe and Qi, 2004). Toluene concentrations were then measured using a gas chromatograph (Younglin ACME 6000 series) equipped with a flame ionization detector (FID). Helium was used as the carrier gas and the temperatures of oven, injector and detector were 120, 150 and 250 ◦ C, respectively. To study the possibility of clogging during the experiments, the bed pressure drop was measured by a manometer with 1 mm H2 O precision.
2.4. Biofilter performance under different operating conditions The performance of a biofiltration system is identified on the concepts of removal efficiency and elimination capacity. These two key parameters are defined as follows: RE =
CGi − CGo × 100 CGi
(1)
(CGi − CGo ) × Q Vf
(2)
where CGi , CGo , Q and Vf are the inlet and outlet pollutant concentrations (mg m−3 ), volumetric flow rate of air (m3 h−1 ) and bed volume (m3 ), respectively. As summarized in Table 2, the system was operated under four operating conditions. The operating conditions, gas flow rate and toluene concentration, were altered in each phase in order to investigate the influence of each parameter on the performance of the fungal biofilter. The loading to the biofilter was accomplished for 10 h a day for all phases of experiments to provide the intermittent loading. The system was completely turned off during the next 14 h and no feed was done in this period.
3.
Results and discussion
3.1.
Biofilter performance
One of the most important effective factors in the efficiency of a reactor is the residence time of the reaction components. Since biofilters are considered as biological reactors, this parameter is also of great importance in biofilters. Residence time alterations result from the changes in the flow rate of the gas entering the column. Fig. 2 shows the outlet concentration of toluene in the air stream and the removal efficiency of the biofilter during the time of the experiments. In the first three phases of experiment, the pollutant concentration was adjusted to 173.1 mg m−3 . Besides, the gas flow rate was set to 0.096 m3 h−1 , 0.024 m3 h−1 and also 0.06 m3 h−1 . Now that the gas-biofilm contact time was low in the start-up phase, the time of achieving steady-state condition was reached to 25 days. It is obvious that the increase in the gas residence time in the biofilter would significantly cause greater decrease in the amount of toluene in the outlet gas stream and greater improvement in the RE during phase II, as many scientists have observed (Maestre et al., 2007; Vergara-Fernandez et al., 2007; Zand et al., 2007). It is also clear that at the flow rate of 0.024 m3 h−1 , the system would become stable in less than 10 days. When the air flow rate increased again up to 0.06 m3 h−1 , the outlet concentrations increased consequently. However, these concentrations are lower than what they are during the phase I of Fig. 2. This happened because the residence time is still more than what it was when the biofilter started to work. Furthermore, microorganisms have completely adapted to the contaminated air. There are some irregularities in the toluene outlet concentration during the last days of each period of operation. Feeding biofilter in 10 h periods and shutting it down until the starting of the next period, is probably the most relevant reason for showing this behavior. Especially, these irregularities
Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
11
Fig. 2 – Variation in toluene outlet concentration () and removal efficiency () during experimental period. were seen when the system seemed to be close to its steady state condition. It is, moreover, clear that 10–90% of toluene has been removed under different conditions. But in the steady state conditions, the RE reached 45%, 87% and 60%, respectively. According to Fig. 2, at the points in which there is an increase in the outlet concentration, RE has decreased. The highest RE was achieved when the residence time increased up to 4.4 min. In this case, the microorganisms clearly had sufficient time to absorb and oxidize the pollutant. At the first day of the experiments in phase IV, the toluene concentration was set at 52.6 mg m−3 . A comparison between phase III and IV demonstrated that in the lower concentration of pollutant, steady-state was achieved in 4 days and RE increased continuously. In fact, when the pollutant loading decreased, the microbial population consumed toluene more rapidly in comparison with the time they had been adapted to a 173.1 mg m−3 of inlet concentration. Fig. 3 indicates the effect of hexane inlet load on the elimination capacity of the bioreactor. In general, the maximum EC obtained at various phases of the experiments was reduced by increasing the inlet load. The variations of EC of the biofil-
Fig. 3 – Effect of inlet load on the distribution of toluene elimination capacity.
ter are shown in Fig. 3. A comparison between Figs. 2 and 3 exhibits the independency of the two key concepts described above. For example, RE reached its maximum level between the days 25 and 40. In contrast, EC declined dramatically which was due to a very low flow rate of air. Some irregularities are observed in Fig. 3 and similarly in Fig. 2. In addition to the reasons that have been mentioned above, it is possible that some pores in bed have been clogged, that is the biofilm has grown and blocked these pores. Therefore, the gas had to change its direction toward other pores with lower microbial population. A pore network model proves that this explanation is correct (results not shown here). Thus, RE declined during a limited time and then it became steady again. When the air flow rate decreased to 0.024 m3 h−1 , EC decreased to 983 mg m−3 h−1 in the phase II of the Fig. 3. On the contrary, RE reached 90%. In the final period of experiments, where the inlet contaminant concentration decreased to 52.6 mg m−3 in a constant gas flow rate, EC diminished, consequently. In this phase, the difference between inlet and outlet concentration was not high enough to increase the EC.
3.2.
Pressure drop through the bed
A partial or complete clogging of the bed can occur in biofilters. The complete clogging not only can increase the pressure drop along the bed drastically, but also can cause an increase in operational costs. However, the partial blocking may not be very important generally, it can cause the channeling of the bed in some cases (Devinny et al., 1999; Kennes and Thalasso, 1998; Delhomenie et al., 2003). In this case, gas passes through the channels of the bed without a sufficient gas-biofilm contact time and the elimination of the pollutant would not happen practically. Fig. 4 shows the alteration of pressure drop during the time of experiments in different operating conditions. In all phases of the tests, the pressure drop increased during the time in view of the fact that microorganisms were growing in the pores. In phase I, according to Darcy equation, the pressure drop had the highest amount among all phases where the flow rate was at its maximum. Oppositely, the pressure drop declined in phase II, as the flow rate decreased to 0.024 m3 h−1 . Generally, the maximum pressure drop was observed in the last day of phase I (6 mm H2 O) after 60-day
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Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
Fig. 4 – Alteration in pressure drop during the time of experiment in each phase. operation time. This observation indicated the proper performance of the bed hydraulically in compare to Delhomenie et al. (2003) who observed pressure drops between 1 cm H2 O/m of bed and 2.7 cm H2 O/m of bed in a compost biofilter with different nitrogen compound concentration as nutrient. Table 3 shows the variation of pressure drop in each section of the filter column. These results were obtained after reaching steady state in the outlet concentration. It is obvious that the maximum pressure drop, more than 50% of the total pressure drop, was seen in the first stage for all flow rates. The compaction of compost as a result of absorbing the major part of the total moisture existing in the inlet air and microbial growth are the main reasons of this behavior. Nevertheless, this pressure drop was quite low considering the total P.
3.3.
Profile of toluene concentration along the bed
Sampling from three ports along the column makes one possible to estimate how much toluene is eliminated in each centimeter of the bed height. Fig. 5 shows the variations of dimensionless toluene concentration along the bed height in the different experiments. As the steep of Fig. 5 shows, about 50% of the total pollutant conversion has occurred through the first stage owing to the fact that the gas entered the biofilter with a higher load of contaminant which was available for fungal population. The pollutant concentration diminished gradually in stages 2 and 3 in the column as other researchers have depicted (Rene et al., 2005; VergaraFernandez et al., 2007). Moreover, when the inlet flow rate decreased to 0.06 and 0.024 m3 h−1 , the proportion of toluene removing through the first stage increased, as microorganisms had more time to absorb and transfer carbon or energy source to the biofilm. In addition, as the toluene partial pressure in air decreased through the height of reactor, the diffusion of toluene into the biofilm reduced consequently according to the well known equations for determining the gas–liquid
Fig. 5 – Profile of toluene concentration along the bed for phase I (--), phase II (. . .. . .), phase III (--) and phase IV (. . .. . .) of experiments. diffusion coefficients. Also, in phase IV when toluene concentration decreased to 52.6 mg m−3 in a constant flow rate, the elimination in stage 1 was higher than in phase III. Because the consumption of toluene by biofilm was not affected by decreasing the mass concentration, as RE did not change significantly in Fig. 2, the intensity of diminishing pollutant in first stage increased in Fig. 5.
3.4.
The kinetic of the biodegradation can be investigated either microkinetically or macrokinetically. However, the microkinetic method cannot be extended to the gas phase systems. Because the phase of degradation is not similar to the phase of biodegradation in shake flask. Hence, in this research, macrokinetic study was applied to determine the Monod constants. The same method of macrokinetic determination was used by the Krailas et al. (2004) and Mathur et al. (2006). The kinetics of the system can be expressed by a Monod relationship assuming that oxygen limitation was ignorable in the system and the kinetic controlled the reaction. At steady-state condition of microbial growth, the growth and death rate of microorganisms were balanced. The kinetic constants were determined using the plug flow model (Mathur et al., 2006): ∂Cg ∂Cg = −Ug +r ∂t ∂h
Phase
Pressure drop (mm H2 O) Bed height = 17cm
I II III IV
3 2 3 3
Bed height = 34 cm 5 3 4 4
Bed height = 51 cm 6 4 5 5
(3)
where Cg is toluene concentration (g m−3 ), Ug is the superficial velocity (m h−1 ), t is the time interval, h is the distance from the bed (m), and r is the overall reaction rate and it is defined by Eq. (4): r=
Table 3 – Amount of pressure drop in each section of the bed in different phases of experiments.
Kinetic study
rmax Cg Km + Cg
(4)
where rmax is the maximum biodegradation rate (g m−3 h−1 ) and Km is the saturation constant (g m−3 ) in the gas phase. At steady state, the accumulation term ∂Cg /∂t equals to zero. Eq. (3) was integrated under the following boundary conditions: Cg = Cgi at h = 0
(5)
Cg = Cgo at h = L
(6)
Process Safety and Environmental Protection 8 9 ( 2 0 1 1 ) 8–14
13
References
Fig. 6 – Macrokinetic determination of Monod constants.
where Cgi and Cgo are inlet and outlet toluene concentration (g m−3 ) and L is the biofilter length (m). Eq. (7) was obtained by solving Eqs. (3) and (4): Km 1 1 V/Q = + Cgi − Cgo rmax CLn rmax
(7)
where Cln is the logarithmic mean concentration [(Cgi − Cgo )/ ln(Cgi /Cgo )], V is the biofilter volume (m3 ), and Q is the volumetric flow rate (m3 h−1 ), rmax and Km for the gas phase can be obtained by plotting [(V/Q)/(Cgi − Cgo )] against (1/Cln ) with correlation coefficient of 0.9922 which showed that Monod equation could properly express the biodegrading kinetic. From Fig. 6, the rmax and Km were calculated as 50 g m−3 h−1 and 3.495 g m−3 , respectively. It showed that there was no inhibition effect of toluene on the fungal population under the studied concentrations. Also, Km was reported around 7.45 g m−3 (Mathur et al., 2006) for mono-chlorobenzene removal. As the elimination capacities obtained here is significantly lower than calculated rmax , it seems that the control of the reaction by kinetic is a proper assumption. Therefore, that the system can operate under higher loads of pollutant in this condition properly.
4.
Conclusion
The main findings in this research can be concluded as follows:
(1) The compost biofilter inoculated with P. chrysosporium could effectively remove toluene vapor (between 50% and 92%) under intermittent loading. (2) The effect of residence time was more significant than changing the inlet concentration on the biofiltration of toluene due to low load of pollutant in this research. (3) Under the experimental condition, the Monod type equation could properly fit the data and express the kinetic of toluene biofiltration.
Acknowledgement The authors gratefully acknowledge National Iranian Oil Refining and Distribution Company (NIORDC) for their financial support.
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